Revision 0:49cb9a5a60f3, committed 2020-04-15

Comitter:

kone96

Date:

Wed Apr 15 07:09:26 2020 +0000

Commit message:

TensorFlow Lite MNIST example

Changed in this revision

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/mbed-os.lib
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/mbed-os.lib	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,1 @@
+https://os.mbed.com/teams/EL4121-Embedded-System/code/mbed-os/#b74591d5ab33

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/core/public/version.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/core/public/version.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,139 @@
+/* Copyright 2015 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_CORE_PUBLIC_VERSION_H_
+#define TENSORFLOW_CORE_PUBLIC_VERSION_H_
+
+// TensorFlow uses semantic versioning, see http://semver.org/.
+
+// Also update tensorflow/tensorflow.bzl and
+// tensorflow/tools/pip_package/setup.py
+#define TF_MAJOR_VERSION 2
+#define TF_MINOR_VERSION 1
+#define TF_PATCH_VERSION 0
+
+// TF_VERSION_SUFFIX is non-empty for pre-releases (e.g. "-alpha", "-alpha.1",
+// "-beta", "-rc", "-rc.1")
+#define TF_VERSION_SUFFIX ""
+
+#define TF_STR_HELPER(x) #x
+#define TF_STR(x) TF_STR_HELPER(x)
+
+// e.g. "0.5.0" or "0.6.0-alpha".
+#define TF_VERSION_STRING                                            \
+  (TF_STR(TF_MAJOR_VERSION) "." TF_STR(TF_MINOR_VERSION) "." TF_STR( \
+      TF_PATCH_VERSION) TF_VERSION_SUFFIX)
+
+// GraphDef compatibility versions (the versions field in graph.proto).
+//
+// Each graph has producer and min_consumer versions, and each
+// consumer has its own version and a min_producer.  In addition, graphs can
+// mark specific consumer versions as bad (to prevent bugs from executing).
+// A consumer will execute a graph if the consumer's version is at least the
+// graph's min_consumer, the graph's producer version is at least the consumer's
+// min_producer, and the consumer version isn't specifically disallowed by the
+// graph.
+//
+// By default, newly created graphs have producer version TF_GRAPH_DEF_VERSION
+// min_consumer TF_GRAPH_DEF_MIN_CONSUMER, and no other bad consumer versions.
+//
+// Version history:
+//
+// 0. Graphs created before GraphDef versioning
+// 1. First real version (2dec2015)
+// 2. adjust_contrast only takes float, doesn't perform clamping (11dec2015)
+// 3. Remove TileGrad, since it was equivalent to reduce_sum (30dec2015)
+// 4. When support for this version is removed, we can safely make AttrValue
+//    parsing more strict with respect to empty list values (see
+//    111635679, 7jan2016).
+// 5. Graphs are wholly-validated during Session::Create() (7jan2016).
+// 6. TensorFlow is scalar strict within Google (27jan2016).
+// 7. Remove TopK in favor of TopKV2 (5feb2016).
+// 8. Replace RandomCrop from C++ with pure Python (5feb2016).
+// 9. Deprecate batch_norm_with_global_normalization (16feb2016).
+// 10. Deprecate conv3d_backprop_{filter,input} (10jun2016).
+// 11. Deprecate {batch}_self_adjoint_eig (3aug2016).
+// 12. Graph consumers understand the node_def field of FunctionDef (22aug2016).
+// 13. Deprecate multiple batch linear algebra ops (9sep2016).
+// 14. Deprecate batch_matrix_* ops. (10sep2016).
+// 15. Deprecate batch_fft_* ops. (14sep2016).
+// 16. Deprecate tensor_array (v1) ops in favor of v2 (10nov2016).
+// 17. Deprecate inv (11nov2016).
+// 17. Expose reverse_v2 (10nov2016)
+// 18. Add VariableV2 (30nov2016)
+// 19. Deprecated ops created by models moved out of core SkipGram, NegTrain.
+//     (08dec2016)
+// 20. Catch all version 1.0 changes to Python API generation. SplitV is now
+//     used for tf.split, ReverseV2 is now used by tf.reverse, ConcatV2 is
+//     now used by tf.concat. Graphs use flooring
+//     division and mod semantics. TensorArrayV3. (12dec2016)
+//     Also considered the version for when it is required for reduction
+//     ops' indices to be scalar or vector, and not higher rank.
+//     Some earlier graph def versions allowed this.
+// 21. Dropped FunctionDef.Node support, switched to node_def introduced
+//     in version 12. (11jan2017)
+// 22. Placeholder now can specify and enforce scalar and partial
+//     shapes, particularly when restoring a graph from GraphDef
+//     produced at version 22 or later.  (04/10/2016)
+// 23. Remove NonMaxSuppression in favor of NonMaxSuppressionV2.
+// 24. Deprecate lookup ops (v1) ops in favor of v2 (30may2017)
+// 25. Deprecate stack (v1) ops in favor of v2 (2017/6/15).
+// 25. Deprecate RandomPoisson (v1) ops in favor of v2 (2017/10/25).
+// 26. Add a bool 'stripped_default_attrs' to MetaInfoDef indicating
+//     whether default-valued attrs have been stripped from the nodes in the
+//     GraphDef. (7dec2017)
+// 27. Deprecate TensorArray ops v2 in favor of v3 and deprecated io_ops
+//     deprecated in favor of V2 ops. (2018/01/23)
+// 28. Deprecate MatrixExponential op in favor of Python implementation.
+//     (2018/08/21).
+// (2019/02/15). Added `control_ret` field to FunctionDef proto, and
+//     `control_output` field to OpDef proto.
+// 29. Deprecate StatefulStandardNormal op in favor of StatefulStandardNormalV2.
+//     (2019/03/25).
+// (2019/04/17). Added `arg_attr` field to FunctionDefProto.
+// 30. (2019/05/09) First date based GraphDef version. GraphDef
+//     versions advance by 1 each day after this point.
+
+#define TF_GRAPH_DEF_VERSION_MIN_PRODUCER 0
+#define TF_GRAPH_DEF_VERSION_MIN_CONSUMER 0
+#define TF_GRAPH_DEF_VERSION 175  // Updated: 2019/10/1
+
+// Checkpoint compatibility versions (the versions field in SavedSliceMeta).
+//
+// The checkpoint versions have the same semantics as GraphDef versions, but the
+// numbering scheme is separate.  We have no plans to ever deprecate checkpoint
+// versions, but it's good to have this in place in case we ever need to.
+//
+// Version history:
+//
+// 0. Checkpoints saved before checkpoint versioning.
+// 1. First real version (10feb2015).
+#define TF_CHECKPOINT_VERSION_MIN_PRODUCER 0
+#define TF_CHECKPOINT_VERSION_MIN_CONSUMER 0
+#define TF_CHECKPOINT_VERSION 1
+
+/// Version query functions (defined in generated version_info.cc)
+
+// Host compiler version (declared elsewhere to be __VERSION__)
+extern const char* tf_compiler_version();
+// The git commit designator when tensorflow was built
+// If no git repository, this will be "internal".
+extern const char* tf_git_version();
+// Value of the _GLIBCXX_USE_CXX11_ABI flag, or 0 if it's not set.
+extern int tf_cxx11_abi_flag();
+// Returns 1 if build is monolithic, or 0 otherwise.
+extern int tf_monolithic_build();
+
+#endif  // TENSORFLOW_CORE_PUBLIC_VERSION_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/c/builtin_op_data.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/c/builtin_op_data.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,422 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_C_BUILTIN_OP_DATA_H_
+#define TENSORFLOW_LITE_C_BUILTIN_OP_DATA_H_
+
+#include <stdint.h>
+
+#include "tensorflow/lite/c/c_api_internal.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+// TODO(aselle): Consider using "if this then that" for testing.
+
+// Useful placeholder to put in otherwise empty structs to avoid size warnings.
+typedef struct {
+  char dummy;
+} EmptyStructPlaceholder;
+
+// IMPORTANT: All new members of structs must be added at the end to ensure
+// backwards compatibility.
+
+// Possible padding types (for convolutions)
+typedef enum {
+  kTfLitePaddingUnknown = 0,
+  kTfLitePaddingSame,
+  kTfLitePaddingValid,
+} TfLitePadding;
+
+typedef enum {
+  kTfLiteMirrorPaddingUnknown = 0,
+  kTfLiteMirrorPaddingReflect,
+  kTfLiteMirrorPaddingSymmetric,
+} TfLiteMirrorPaddingMode;
+
+// TODO(b/130259536): We should move this out of builtin_op_data.
+typedef struct {
+  int width;
+  int height;
+  int width_offset;
+  int height_offset;
+} TfLitePaddingValues;
+
+typedef struct {
+  TfLiteMirrorPaddingMode mode;
+} TfLiteMirrorPaddingParams;
+
+// Possible fused activation functions.
+// TODO(aselle): rename to TfLiteActivation
+typedef enum {
+  kTfLiteActNone = 0,
+  kTfLiteActRelu,
+  kTfLiteActRelu1,  // min(max(-1, x), 1)
+  kTfLiteActRelu6,  // min(max(0, x), 6)
+  kTfLiteActTanh,
+  kTfLiteActSignBit,
+  kTfLiteActSigmoid,
+} TfLiteFusedActivation;
+
+typedef struct {
+  TfLitePadding padding;
+  int stride_width;
+  int stride_height;
+  int dilation_width_factor;
+  int dilation_height_factor;
+  TfLiteFusedActivation activation;
+} TfLiteConvParams;
+
+typedef struct {
+  TfLitePadding padding;
+  int stride_width;
+  int stride_height;
+  int filter_width;
+  int filter_height;
+  TfLiteFusedActivation activation;
+  struct {
+    TfLitePaddingValues padding;
+  } computed;
+} TfLitePoolParams;
+
+typedef struct {
+  // Parameters for DepthwiseConv version 1 or above.
+  TfLitePadding padding;
+  int stride_width;
+  int stride_height;
+  // `depth_multiplier` is redundant. It's used by CPU kernels in
+  // TensorFlow 2.0 or below, but ignored in versions above.
+  //
+  // The information can be deduced from the shape of input and the shape of
+  // weights. Since the TFLiteConverter toolchain doesn't support partially
+  // specificed shapes, relying on `depth_multiplier` stops us from supporting
+  // graphs with dynamic shape tensors.
+  //
+  // Note: Some of the delegates (e.g. NNAPI, GPU) are still relying on this
+  // field.
+  int depth_multiplier;
+  TfLiteFusedActivation activation;
+  // Parameters for DepthwiseConv version 2 or above.
+  int dilation_width_factor;
+  int dilation_height_factor;
+} TfLiteDepthwiseConvParams;
+
+typedef struct {
+  int rank;
+  TfLiteFusedActivation activation;
+} TfLiteSVDFParams;
+
+typedef struct {
+  TfLiteFusedActivation activation;
+} TfLiteRNNParams;
+
+typedef struct {
+  bool time_major;
+  TfLiteFusedActivation activation;
+} TfLiteSequenceRNNParams;
+
+typedef struct {
+  bool time_major;
+  TfLiteFusedActivation activation;
+  bool merge_outputs;
+} TfLiteBidirectionalSequenceRNNParams;
+
+typedef enum {
+  kTfLiteFullyConnectedWeightsFormatDefault = 0,
+  kTfLiteFullyConnectedWeightsFormatShuffled4x16Int8 = 1,
+} TfLiteFullyConnectedWeightsFormat;
+
+typedef struct {
+  // Parameters for FullyConnected version 1 or above.
+  TfLiteFusedActivation activation;
+
+  // Parameters for FullyConnected version 2 or above.
+  TfLiteFullyConnectedWeightsFormat weights_format;
+
+  // Parameters for FullyConnected version 5 or above.
+  // If set to true, then the number of dimensions in the input and the output
+  // tensors are the same. Furthermore, all but the last dimension of the input
+  // and output shapes will be equal.
+  bool keep_num_dims;
+} TfLiteFullyConnectedParams;
+
+typedef enum {
+  kTfLiteLshProjectionUnknown = 0,
+  kTfLiteLshProjectionSparse = 1,
+  kTfLiteLshProjectionDense = 2,
+} TfLiteLSHProjectionType;
+
+typedef struct {
+  TfLiteLSHProjectionType type;
+} TfLiteLSHProjectionParams;
+
+typedef struct {
+  float beta;
+} TfLiteSoftmaxParams;
+
+typedef struct {
+  int axis;
+  TfLiteFusedActivation activation;
+} TfLiteConcatenationParams;
+
+typedef struct {
+  TfLiteFusedActivation activation;
+} TfLiteAddParams;
+
+typedef struct {
+  EmptyStructPlaceholder placeholder;
+} TfLiteSpaceToBatchNDParams;
+
+typedef struct {
+  EmptyStructPlaceholder placeholder;
+} TfLiteBatchToSpaceNDParams;
+
+typedef struct {
+  TfLiteFusedActivation activation;
+} TfLiteMulParams;
+
+typedef struct {
+  TfLiteFusedActivation activation;
+} TfLiteSubParams;
+
+typedef struct {
+  TfLiteFusedActivation activation;
+} TfLiteDivParams;
+
+typedef struct {
+  TfLiteFusedActivation activation;
+} TfLiteL2NormParams;
+
+typedef struct {
+  int radius;
+  float bias;
+  float alpha;
+  float beta;
+} TfLiteLocalResponseNormParams;
+
+typedef enum {
+  kTfLiteLSTMFullKernel = 0,
+  kTfLiteLSTMBasicKernel
+} TfLiteLSTMKernelType;
+
+typedef struct {
+  // Parameters for LSTM version 1.
+  TfLiteFusedActivation activation;
+  float cell_clip;
+  float proj_clip;
+
+  // Parameters for LSTM version 2.
+  // kTfLiteLSTMBasicKernel is only supported in version 2 or above.
+  TfLiteLSTMKernelType kernel_type;
+} TfLiteLSTMParams;
+
+typedef struct {
+  // Parameters needed for the underlying LSTM.
+  TfLiteFusedActivation activation;
+  float cell_clip;
+  float proj_clip;
+
+  // If set to true then the first dimension is time, otherwise batch.
+  bool time_major;
+} TfLiteUnidirectionalSequenceLSTMParams;
+
+typedef struct {
+  // Parameters supported by version 1:
+  // Parameters inherited for the LSTM kernel.
+  TfLiteFusedActivation activation;
+  float cell_clip;
+  float proj_clip;
+
+  // If true, store the outputs of both directions in the first output.
+  bool merge_outputs;
+
+  // Parameters supported by version 2:
+  // If set to true then the first dimension is time, otherwise batch.
+  bool time_major;
+} TfLiteBidirectionalSequenceLSTMParams;
+
+typedef struct {
+  bool align_corners;
+} TfLiteResizeBilinearParams;
+
+typedef struct {
+  bool align_corners;
+} TfLiteResizeNearestNeighborParams;
+
+typedef struct {
+  EmptyStructPlaceholder placeholder;
+} TfLitePadParams;
+
+typedef struct {
+  EmptyStructPlaceholder placeholder;
+} TfLitePadV2Params;
+
+typedef struct {
+  // TODO(ahentz): We can't have dynamic data in this struct, at least not yet.
+  // For now we will fix the maximum possible number of dimensions.
+  int shape[8];
+  int num_dimensions;
+} TfLiteReshapeParams;
+
+typedef struct {
+  int ngram_size;
+  int max_skip_size;
+  bool include_all_ngrams;
+} TfLiteSkipGramParams;
+
+typedef struct {
+  int block_size;
+} TfLiteSpaceToDepthParams;
+
+typedef struct {
+  int block_size;
+} TfLiteDepthToSpaceParams;
+
+typedef struct {
+  TfLiteType in_data_type;
+  TfLiteType out_data_type;
+} TfLiteCastParams;
+
+typedef enum {
+  kTfLiteCombinerTypeSum = 0,
+  kTfLiteCombinerTypeMean = 1,
+  kTfLiteCombinerTypeSqrtn = 2,
+} TfLiteCombinerType;
+
+typedef struct {
+  TfLiteCombinerType combiner;
+} TfLiteEmbeddingLookupSparseParams;
+
+typedef struct {
+  int axis;
+} TfLiteGatherParams;
+
+typedef struct {
+  EmptyStructPlaceholder placeholder;
+} TfLiteTransposeParams;
+
+typedef struct {
+  bool keep_dims;
+} TfLiteReducerParams;
+
+typedef struct {
+  int num_splits;
+} TfLiteSplitParams;
+
+typedef struct {
+  int num_splits;
+} TfLiteSplitVParams;
+
+typedef struct {
+  // TODO(ahentz): We can't have dynamic data in this struct, at least not yet.
+  // For now we will fix the maximum possible number of dimensions.
+  int squeeze_dims[8];
+  int num_squeeze_dims;
+} TfLiteSqueezeParams;
+
+typedef struct {
+  int begin_mask;
+  int end_mask;
+  int ellipsis_mask;
+  int new_axis_mask;
+  int shrink_axis_mask;
+} TfLiteStridedSliceParams;
+
+typedef struct {
+  TfLiteType output_type;
+} TfLiteArgMaxParams;
+
+typedef struct {
+  TfLiteType output_type;
+} TfLiteArgMinParams;
+
+typedef struct {
+  TfLitePadding padding;
+  int stride_width;
+  int stride_height;
+} TfLiteTransposeConvParams;
+
+typedef struct {
+  bool validate_indices;
+} TfLiteSparseToDenseParams;
+
+typedef struct {
+  TfLiteType out_type;
+} TfLiteShapeParams;
+
+typedef struct {
+  EmptyStructPlaceholder placeholder;
+} TfLiteRankParams;
+
+typedef struct {
+  // Parameters supported by version 1:
+  float min;
+  float max;
+  int num_bits;
+
+  // Parameters supported by version 2:
+  bool narrow_range;
+} TfLiteFakeQuantParams;
+
+typedef struct {
+  int values_count;
+  int axis;
+} TfLitePackParams;
+
+typedef struct {
+  int axis;
+} TfLiteOneHotParams;
+
+typedef struct {
+  int num;
+  int axis;
+} TfLiteUnpackParams;
+
+typedef struct {
+  float alpha;
+} TfLiteLeakyReluParams;
+
+typedef struct {
+  TfLiteType index_out_type;
+} TfLiteUniqueParams;
+
+typedef struct {
+  int seq_dim;
+  int batch_dim;
+} TfLiteReverseSequenceParams;
+
+typedef struct {
+  EmptyStructPlaceholder placeholder;
+} TfLiteMatrixDiagParams;
+
+typedef struct {
+  EmptyStructPlaceholder placeholder;
+} TfLiteMatrixSetDiagParams;
+
+typedef struct {
+  int then_subgraph_index;
+  int else_subgraph_index;
+} TfLiteIfParams;
+
+typedef struct {
+  int cond_subgraph_index;
+  int body_subgraph_index;
+} TfLiteWhileParams;
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+#endif  // TENSORFLOW_LITE_C_BUILTIN_OP_DATA_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/c/c_api_internal.c
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/c/c_api_internal.c	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,185 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#ifndef TF_LITE_STATIC_MEMORY
+#include <stdlib.h>
+#include <string.h>
+#endif  // TF_LITE_STATIC_MEMORY
+
+int TfLiteIntArrayGetSizeInBytes(int size) {
+  static TfLiteIntArray dummy;
+  return sizeof(dummy) + sizeof(dummy.data[0]) * size;
+}
+
+int TfLiteIntArrayEqual(const TfLiteIntArray* a, const TfLiteIntArray* b) {
+  if (a == b) return 1;
+  if (a == NULL || b == NULL) return 0;
+  return TfLiteIntArrayEqualsArray(a, b->size, b->data);
+}
+
+int TfLiteIntArrayEqualsArray(const TfLiteIntArray* a, int b_size,
+                              const int b_data[]) {
+  if (a == NULL) return (b_size == 0);
+  if (a->size != b_size) return 0;
+  int i = 0;
+  for (; i < a->size; i++)
+    if (a->data[i] != b_data[i]) return 0;
+  return 1;
+}
+
+#ifndef TF_LITE_STATIC_MEMORY
+
+TfLiteIntArray* TfLiteIntArrayCreate(int size) {
+  TfLiteIntArray* ret =
+      (TfLiteIntArray*)malloc(TfLiteIntArrayGetSizeInBytes(size));
+  ret->size = size;
+  return ret;
+}
+
+TfLiteIntArray* TfLiteIntArrayCopy(const TfLiteIntArray* src) {
+  if (!src) return NULL;
+  TfLiteIntArray* ret = TfLiteIntArrayCreate(src->size);
+  if (ret) {
+    memcpy(ret->data, src->data, src->size * sizeof(int));
+  }
+  return ret;
+}
+
+void TfLiteIntArrayFree(TfLiteIntArray* a) { free(a); }
+
+#endif  // TF_LITE_STATIC_MEMORY
+
+int TfLiteFloatArrayGetSizeInBytes(int size) {
+  static TfLiteFloatArray dummy;
+  return sizeof(dummy) + sizeof(dummy.data[0]) * size;
+}
+
+#ifndef TF_LITE_STATIC_MEMORY
+
+TfLiteFloatArray* TfLiteFloatArrayCreate(int size) {
+  TfLiteFloatArray* ret =
+      (TfLiteFloatArray*)malloc(TfLiteFloatArrayGetSizeInBytes(size));
+  ret->size = size;
+  return ret;
+}
+
+void TfLiteFloatArrayFree(TfLiteFloatArray* a) { free(a); }
+
+void TfLiteTensorDataFree(TfLiteTensor* t) {
+  if (t->allocation_type == kTfLiteDynamic) {
+    free(t->data.raw);
+  }
+  t->data.raw = NULL;
+}
+
+void TfLiteQuantizationFree(TfLiteQuantization* quantization) {
+  if (quantization->type == kTfLiteAffineQuantization) {
+    TfLiteAffineQuantization* q_params =
+        (TfLiteAffineQuantization*)(quantization->params);
+    if (q_params->scale) {
+      TfLiteFloatArrayFree(q_params->scale);
+      q_params->scale = NULL;
+    }
+    if (q_params->zero_point) {
+      TfLiteIntArrayFree(q_params->zero_point);
+      q_params->zero_point = NULL;
+    }
+    free(q_params);
+  }
+  quantization->params = NULL;
+  quantization->type = kTfLiteNoQuantization;
+}
+
+void TfLiteTensorFree(TfLiteTensor* t) {
+  TfLiteTensorDataFree(t);
+  if (t->dims) TfLiteIntArrayFree(t->dims);
+  t->dims = NULL;
+
+  TfLiteQuantizationFree(&t->quantization);
+}
+
+void TfLiteTensorReset(TfLiteType type, const char* name, TfLiteIntArray* dims,
+                       TfLiteQuantizationParams quantization, char* buffer,
+                       size_t size, TfLiteAllocationType allocation_type,
+                       const void* allocation, bool is_variable,
+                       TfLiteTensor* tensor) {
+  TfLiteTensorFree(tensor);
+  tensor->type = type;
+  tensor->name = name;
+  tensor->dims = dims;
+  tensor->params = quantization;
+  tensor->data.raw = buffer;
+  tensor->bytes = size;
+  tensor->allocation_type = allocation_type;
+  tensor->allocation = allocation;
+  tensor->is_variable = is_variable;
+
+  tensor->quantization.type = kTfLiteNoQuantization;
+  tensor->quantization.params = NULL;
+}
+
+void TfLiteTensorRealloc(size_t num_bytes, TfLiteTensor* tensor) {
+  if (tensor->allocation_type != kTfLiteDynamic) {
+    return;
+  }
+  if (!tensor->data.raw) {
+    tensor->data.raw = malloc(num_bytes);
+  } else if (num_bytes > tensor->bytes) {
+    tensor->data.raw = realloc(tensor->data.raw, num_bytes);
+  }
+  tensor->bytes = num_bytes;
+}
+#endif  // TF_LITE_STATIC_MEMORY
+
+const char* TfLiteTypeGetName(TfLiteType type) {
+  switch (type) {
+    case kTfLiteNoType:
+      return "NOTYPE";
+    case kTfLiteFloat32:
+      return "FLOAT32";
+    case kTfLiteInt16:
+      return "INT16";
+    case kTfLiteInt32:
+      return "INT32";
+    case kTfLiteUInt8:
+      return "UINT8";
+    case kTfLiteInt8:
+      return "INT8";
+    case kTfLiteInt64:
+      return "INT64";
+    case kTfLiteBool:
+      return "BOOL";
+    case kTfLiteComplex64:
+      return "COMPLEX64";
+    case kTfLiteString:
+      return "STRING";
+    case kTfLiteFloat16:
+      return "FLOAT16";
+  }
+  return "Unknown type";
+}
+
+TfLiteDelegate TfLiteDelegateCreate() {
+  TfLiteDelegate d = {
+      .data_ = NULL,
+      .Prepare = NULL,
+      .CopyFromBufferHandle = NULL,
+      .CopyToBufferHandle = NULL,
+      .FreeBufferHandle = NULL,
+      .flags = kTfLiteDelegateFlagsNone,
+  };
+  return d;
+}

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/c/c_api_internal.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/c/c_api_internal.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,625 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+// This file defines a C API for implementing operations in tflite.
+// These operations can be defined using c++ but the interface between
+// the interpreter and the operations are C.
+//
+// Summary of abstractions
+// TF_LITE_ENSURE - Self-sufficient error checking
+// TfLiteStatus - Status reporting
+// TfLiteIntArray - stores tensor shapes (dims),
+// TfLiteContext - allows an op to access the tensors
+// TfLiteTensor - tensor (a multidimensional array)
+// TfLiteNode - a single node or operation
+// TfLiteRegistration - the implementation of a conceptual operation.
+//
+// Some abstractions in this file are created and managed by Interpreter.
+#ifndef TENSORFLOW_LITE_C_C_API_INTERNAL_H_
+#define TENSORFLOW_LITE_C_C_API_INTERNAL_H_
+
+#include <stdbool.h>
+#include <stddef.h>
+#include <stdint.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+
+typedef enum { kTfLiteOk = 0, kTfLiteError = 1 } TfLiteStatus;
+
+// The list of external context types known to TF Lite. This list exists solely
+// to avoid conflicts and to ensure ops can share the external contexts they
+// need. Access to the external contexts is controled by one of the
+// corresponding support files.
+typedef enum {
+  kTfLiteEigenContext = 0,       // include eigen_support.h to use.
+  kTfLiteGemmLowpContext = 1,    // include gemm_support.h to use.
+  kTfLiteEdgeTpuContext = 2,     // Placeholder for Edge TPU support.
+  kTfLiteCpuBackendContext = 3,  // include cpu_backend_support.h to use.
+  kTfLiteMaxExternalContexts = 4
+} TfLiteExternalContextType;
+
+// Forward declare so dependent structs and methods can reference these types
+// prior to the struct definitions.
+struct TfLiteContext;
+struct TfLiteDelegate;
+struct TfLiteRegistration;
+
+// An external context is a collection of information unrelated to the TF Lite
+// framework, but useful to a subset of the ops. TF Lite knows very little
+// about about the actual contexts, but it keeps a list of them, and is able to
+// refresh them if configurations like the number of recommended threads
+// change.
+typedef struct {
+  TfLiteExternalContextType type;
+  TfLiteStatus (*Refresh)(struct TfLiteContext* context);
+} TfLiteExternalContext;
+
+#define kOptionalTensor (-1)
+
+// Fixed size list of integers. Used for dimensions and inputs/outputs tensor
+// indices
+typedef struct {
+  int size;
+// gcc 6.1+ have a bug where flexible members aren't properly handled
+// https://github.com/google/re2/commit/b94b7cd42e9f02673cd748c1ac1d16db4052514c
+#if !defined(__clang__) && defined(__GNUC__) && __GNUC__ == 6 && \
+    __GNUC_MINOR__ >= 1
+  int data[0];
+#else
+  int data[];
+#endif
+} TfLiteIntArray;
+
+// Given the size (number of elements) in a TfLiteIntArray, calculate its size
+// in bytes.
+int TfLiteIntArrayGetSizeInBytes(int size);
+
+// Create a array of a given `size` (uninitialized entries).
+// This returns a pointer, that you must free using TfLiteIntArrayFree().
+TfLiteIntArray* TfLiteIntArrayCreate(int size);
+
+// Check if two intarrays are equal. Returns 1 if they are equal, 0 otherwise.
+int TfLiteIntArrayEqual(const TfLiteIntArray* a, const TfLiteIntArray* b);
+
+// Check if an intarray equals an array. Returns 1 if equals, 0 otherwise.
+int TfLiteIntArrayEqualsArray(const TfLiteIntArray* a, int b_size,
+                              const int b_data[]);
+
+// Create a copy of an array passed as `src`.
+// You are expected to free memory with TfLiteIntArrayFree
+TfLiteIntArray* TfLiteIntArrayCopy(const TfLiteIntArray* src);
+
+// Free memory of array `a`.
+void TfLiteIntArrayFree(TfLiteIntArray* a);
+
+// Fixed size list of floats. Used for per-channel quantization.
+typedef struct {
+  int size;
+// gcc 6.1+ have a bug where flexible members aren't properly handled
+// https://github.com/google/re2/commit/b94b7cd42e9f02673cd748c1ac1d16db4052514c
+#if !defined(__clang__) && defined(__GNUC__) && __GNUC__ == 6 && \
+    __GNUC_MINOR__ >= 1
+  float data[0];
+#else
+  float data[];
+#endif
+} TfLiteFloatArray;
+
+// Given the size (number of elements) in a TfLiteFloatArray, calculate its size
+// in bytes.
+int TfLiteFloatArrayGetSizeInBytes(int size);
+
+// Create a array of a given `size` (uninitialized entries).
+// This returns a pointer, that you must free using TfLiteFloatArrayFree().
+TfLiteFloatArray* TfLiteFloatArrayCreate(int size);
+
+// Free memory of array `a`.
+void TfLiteFloatArrayFree(TfLiteFloatArray* a);
+
+// Since we must not depend on any libraries, define a minimal subset of
+// error macros while avoiding names that have pre-conceived meanings like
+// assert and check.
+
+// Check whether value is true, and if not return kTfLiteError from
+// the current function (and report the error string msg).
+#define TF_LITE_ENSURE_MSG(context, value, msg)            \
+  do {                                                     \
+    if (!(value)) {                                        \
+      (context)->ReportError((context), __FILE__ " " msg); \
+      return kTfLiteError;                                 \
+    }                                                      \
+  } while (0)
+
+// Check whether the value `a` is true, and if not return kTfLiteError from
+// the current function, while also reporting the location of the error.
+#define TF_LITE_ENSURE(context, a)                                          \
+  do {                                                                      \
+    if (!(a)) {                                                             \
+      (context)->ReportError((context), "%s:%d %s was not true.", __FILE__, \
+                             __LINE__, #a);                                 \
+      return kTfLiteError;                                                  \
+    }                                                                       \
+  } while (0)
+
+#define TF_LITE_ENSURE_STATUS(a) \
+  do {                           \
+    if ((a) != kTfLiteOk) {      \
+      return kTfLiteError;       \
+    }                            \
+  } while (0)
+
+// Check whether the value `a == b` is true, and if not return kTfLiteError from
+// the current function, while also reporting the location of the error.
+// `a` and `b` may be evaluated more than once, so no side effects or
+// extremely expensive computations should be done.
+#define TF_LITE_ENSURE_EQ(context, a, b)                                       \
+  do {                                                                         \
+    if ((a) != (b)) {                                                          \
+      (context)->ReportError((context), "%s:%d %s != %s (%d != %d)", __FILE__, \
+                             __LINE__, #a, #b, (a), (b));                      \
+      return kTfLiteError;                                                     \
+    }                                                                          \
+  } while (0)
+
+#define TF_LITE_ENSURE_TYPES_EQ(context, a, b)                                 \
+  do {                                                                         \
+    if ((a) != (b)) {                                                          \
+      (context)->ReportError((context), "%s:%d %s != %s (%s != %s)", __FILE__, \
+                             __LINE__, #a, #b, TfLiteTypeGetName(a),           \
+                             TfLiteTypeGetName(b));                            \
+      return kTfLiteError;                                                     \
+    }                                                                          \
+  } while (0)
+
+#define TF_LITE_ENSURE_OK(context, status) \
+  do {                                     \
+    if ((status) != kTfLiteOk) {           \
+      return kTfLiteError;                 \
+    }                                      \
+  } while (0)
+
+// Single-precision complex data type compatible with the C99 definition.
+typedef struct {
+  float re, im;  // real and imaginary parts, respectively.
+} TfLiteComplex64;
+
+// Half precision data type compatible with the C99 definition.
+typedef struct {
+  uint16_t data;
+} TfLiteFloat16;
+
+// Types supported by tensor
+typedef enum {
+  kTfLiteNoType = 0,
+  kTfLiteFloat32 = 1,
+  kTfLiteInt32 = 2,
+  kTfLiteUInt8 = 3,
+  kTfLiteInt64 = 4,
+  kTfLiteString = 5,
+  kTfLiteBool = 6,
+  kTfLiteInt16 = 7,
+  kTfLiteComplex64 = 8,
+  kTfLiteInt8 = 9,
+  kTfLiteFloat16 = 10,
+} TfLiteType;
+
+// Return the name of a given type, for error reporting purposes.
+const char* TfLiteTypeGetName(TfLiteType type);
+
+// SupportedQuantizationTypes.
+typedef enum {
+  // No quantization.
+  kTfLiteNoQuantization = 0,
+  // Affine quantization (with support for per-channel quantization).
+  // Corresponds to TfLiteAffineQuantization.
+  kTfLiteAffineQuantization = 1,
+} TfLiteQuantizationType;
+
+// Structure specifying the quantization used by the tensor, if-any.
+typedef struct {
+  // The type of quantization held by params.
+  TfLiteQuantizationType type;
+  // Holds a reference to one of the quantization param structures specified
+  // below.
+  void* params;
+} TfLiteQuantization;
+
+// Legacy. Will be deprecated in favor of TfLiteAffineQuantization.
+// If per-layer quantization is specified this field will still be populated in
+// addition to TfLiteAffineQuantization.
+// Parameters for asymmetric quantization. Quantized values can be converted
+// back to float using:
+//     real_value = scale * (quantized_value - zero_point)
+typedef struct {
+  float scale;
+  int32_t zero_point;
+} TfLiteQuantizationParams;
+
+// Parameters for asymmetric quantization across a dimension (i.e per output
+// channel quantization).
+// quantized_dimension specifies which dimension the scales and zero_points
+// correspond to.
+// For a particular value in quantized_dimension, quantized values can be
+// converted back to float using:
+//     real_value = scale * (quantized_value - zero_point)
+typedef struct {
+  TfLiteFloatArray* scale;
+  TfLiteIntArray* zero_point;
+  int32_t quantized_dimension;
+} TfLiteAffineQuantization;
+
+// A union of pointers that points to memory for a given tensor.
+typedef union {
+  int32_t* i32;
+  int64_t* i64;
+  float* f;
+  // Placeholder for 16b float type. Use uint16* in the pointer union for now.
+  TfLiteFloat16* f16;
+  char* raw;
+  const char* raw_const;
+  uint8_t* uint8;
+  bool* b;
+  int16_t* i16;
+  TfLiteComplex64* c64;
+  int8_t* int8;
+} TfLitePtrUnion;
+
+// Memory allocation strategies. kTfLiteMmapRo is for read-only memory-mapped
+// data (or data externally allocated). kTfLiteArenaRw is arena allocated
+// data. kTfLiteDynamic is for tensors that are allocated during evaluation.
+typedef enum {
+  kTfLiteMemNone = 0,
+  kTfLiteMmapRo,
+  kTfLiteArenaRw,
+  kTfLiteArenaRwPersistent,
+  kTfLiteDynamic,
+} TfLiteAllocationType;
+
+// The delegates should use zero or positive integers to represent handles.
+// -1 is reserved from unallocated status.
+typedef int TfLiteBufferHandle;
+enum {
+  kTfLiteNullBufferHandle = -1,
+};
+
+// An tensor in the interpreter system which is a wrapper around a buffer of
+// data including a dimensionality (or NULL if not currently defined).
+typedef struct {
+  // The data type specification for data stored in `data`. This affects
+  // what member of `data` union should be used.
+  TfLiteType type;
+  // A union of data pointers. The appropriate type should be used for a typed
+  // tensor based on `type`.
+  TfLitePtrUnion data;
+  // A pointer to a structure representing the dimensionality interpretation
+  // that the buffer should have. NOTE: the product of elements of `dims`
+  // and the element datatype size should be equal to `bytes` below.
+  TfLiteIntArray* dims;
+  // Quantization information.
+  TfLiteQuantizationParams params;
+  // How memory is mapped
+  //  kTfLiteMmapRo: Memory mapped read only.
+  //  i.e. weights
+  //  kTfLiteArenaRw: Arena allocated read write memory
+  //  (i.e. temporaries, outputs).
+  TfLiteAllocationType allocation_type;
+  // The number of bytes required to store the data of this Tensor. I.e.
+  // (bytes of each element) * dims[0] * ... * dims[n-1].  For example, if
+  // type is kTfLiteFloat32 and dims = {3, 2} then
+  // bytes = sizeof(float) * 3 * 2 = 4 * 3 * 2 = 24.
+  size_t bytes;
+
+  // An opaque pointer to a tflite::MMapAllocation
+  const void* allocation;
+
+  // Null-terminated name of this tensor.
+  const char* name;
+
+  // The delegate which knows how to handle `buffer_handle`.
+  // WARNING: This is an experimental interface that is subject to change.
+  struct TfLiteDelegate* delegate;
+
+  // An integer buffer handle that can be handled by `delegate`.
+  // The value is valid only when delegate is not null.
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteBufferHandle buffer_handle;
+
+  // If the delegate uses its own buffer (e.g. GPU memory), the delegate is
+  // responsible to set data_is_stale to true.
+  // `delegate->CopyFromBufferHandle` can be called to copy the data from
+  // delegate buffer.
+  // WARNING: This is an // experimental interface that is subject to change.
+  bool data_is_stale;
+
+  // True if the tensor is a variable.
+  bool is_variable;
+
+  // Quantization information. Replaces params field above.
+  TfLiteQuantization quantization;
+} TfLiteTensor;
+
+// Free data memory of tensor `t`.
+void TfLiteTensorDataFree(TfLiteTensor* t);
+
+// Free quantization data.
+void TfLiteQuantizationFree(TfLiteQuantization* quantization);
+
+// Free memory of tensor `t`.
+void TfLiteTensorFree(TfLiteTensor* t);
+
+// Set all of a tensor's fields (and free any previously allocated data).
+void TfLiteTensorReset(TfLiteType type, const char* name, TfLiteIntArray* dims,
+                       TfLiteQuantizationParams quantization, char* buffer,
+                       size_t size, TfLiteAllocationType allocation_type,
+                       const void* allocation, bool is_variable,
+                       TfLiteTensor* tensor);
+
+// Resize the allocated data of a (dynamic) tensor. Tensors with allocation
+// types other than kTfLiteDynamic will be ignored.
+void TfLiteTensorRealloc(size_t num_bytes, TfLiteTensor* tensor);
+
+// A structure representing an instance of a node.
+// This structure only exhibits the inputs, outputs and user defined data, not
+// other features like the type.
+typedef struct {
+  // Inputs to this node expressed as indices into the simulator's tensors.
+  TfLiteIntArray* inputs;
+
+  // Outputs to this node expressed as indices into the simulator's tensors.
+  TfLiteIntArray* outputs;
+
+  // intermediate tensors to this node expressed as indices into the simulator's
+  // tensors.
+  TfLiteIntArray* intermediates;
+
+  // Temporary tensors uses during the computations. This usually contains no
+  // tensors, but ops are allowed to change that if they need scratch space of
+  // any sort.
+  TfLiteIntArray* temporaries;
+
+  // Opaque data provided by the node implementer through `Registration.init`.
+  void* user_data;
+
+  // Opaque data provided to the node if the node is a builtin. This is usually
+  // a structure defined in builtin_op_data.h
+  void* builtin_data;
+
+  // Custom initial data. This is the opaque data provided in the flatbuffer.
+  // WARNING: This is an experimental interface that is subject to change.
+  const void* custom_initial_data;
+  int custom_initial_data_size;
+
+  // The pointer to the delegate. This is non-null only when the node is
+  // created by calling `interpreter.ModifyGraphWithDelegate`.
+  // WARNING: This is an experimental interface that is subject to change.
+  struct TfLiteDelegate* delegate;
+} TfLiteNode;
+
+typedef struct TfLiteContext {
+  // Number of tensors in the context.
+  size_t tensors_size;
+
+  // The execution plan contains a list of the node indices in execution
+  // order. execution_plan->size is the current number of nodes. And,
+  // execution_plan->data[0] is the first node that needs to be run.
+  // TfLiteDelegates can traverse the current execution plan by iterating
+  // through each member of this array and using GetNodeAndRegistration() to
+  // access details about a node. i.e.
+  // TfLiteIntArray* execution_plan;
+  // TF_LITE_ENSURE_STATUS(context->GetExecutionPlan(context, &execution_plan));
+  // for (int exec_index = 0; exec_index < execution_plan->size; exec_index++) {
+  //    int node_index = execution_plan->data[exec_index];
+  //    TfLiteNode* node;
+  //    TfLiteRegistration* reg;
+  //    context->GetNodeAndRegistration(context, node_index, &node, &reg);
+  // }
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteStatus (*GetExecutionPlan)(struct TfLiteContext* context,
+                                   TfLiteIntArray** execution_plan);
+
+  // An array of tensors in the interpreter context (of length `tensors_size`)
+  TfLiteTensor* tensors;
+
+  // opaque full context ptr (an opaque c++ data structure)
+  void* impl_;
+
+  // Request memory pointer be resized. Updates dimensions on the tensor.
+  // NOTE: ResizeTensor takes ownership of newSize.
+  TfLiteStatus (*ResizeTensor)(struct TfLiteContext*, TfLiteTensor* tensor,
+                               TfLiteIntArray* new_size);
+  // Request that an error be reported with format string msg.
+  void (*ReportError)(struct TfLiteContext*, const char* msg, ...);
+
+  // Add `tensors_to_add` tensors, preserving pre-existing Tensor entries.  If
+  // non-null, the value pointed to by `first_new_tensor_index` will be set to
+  // the index of the first new tensor.
+  TfLiteStatus (*AddTensors)(struct TfLiteContext*, int tensors_to_add,
+                             int* first_new_tensor_index);
+
+  // Get a Tensor node by node_index.
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteStatus (*GetNodeAndRegistration)(
+      struct TfLiteContext*, int node_index, TfLiteNode** node,
+      struct TfLiteRegistration** registration);
+
+  // Replace ops with one or more stub delegate operations. This function
+  // does not take ownership of `nodes_to_replace`.
+  TfLiteStatus (*ReplaceNodeSubsetsWithDelegateKernels)(
+      struct TfLiteContext*, struct TfLiteRegistration registration,
+      const TfLiteIntArray* nodes_to_replace, struct TfLiteDelegate* delegate);
+
+  // Number of threads that are recommended to subsystems like gemmlowp and
+  // eigen.
+  int recommended_num_threads;
+
+  // Access external contexts by type.
+  // WARNING: This is an experimental interface that is subject to change.
+  TfLiteExternalContext* (*GetExternalContext)(struct TfLiteContext*,
+                                               TfLiteExternalContextType);
+  // Set the value of a external context. Does not take ownership of the
+  // pointer.
+  // WARNING: This is an experimental interface that is subject to change.
+  void (*SetExternalContext)(struct TfLiteContext*, TfLiteExternalContextType,
+                             TfLiteExternalContext*);
+
+  // Flag for allowing float16 precision for FP32 calculation.
+  // default: false.
+  // WARNING: This is an experimental API and subject to change.
+  bool allow_fp32_relax_to_fp16;
+
+  // Pointer to the op-level profiler, if set; nullptr otherwise.
+  void* profiler;
+} TfLiteContext;
+
+typedef struct TfLiteRegistration {
+  // Initializes the op from serialized data.
+  // If a built-in op:
+  //   `buffer` is the op's params data (TfLiteLSTMParams*).
+  //   `length` is zero.
+  // If custom op:
+  //   `buffer` is the op's `custom_options`.
+  //   `length` is the size of the buffer.
+  //
+  // Returns a type-punned (i.e. void*) opaque data (e.g. a primitive pointer
+  // or an instance of a struct).
+  //
+  // The returned pointer will be stored with the node in the `user_data` field,
+  // accessible within prepare and invoke functions below.
+  // NOTE: if the data is already in the desired format, simply implement this
+  // function to return `nullptr` and implement the free function to be a no-op.
+  void* (*init)(TfLiteContext* context, const char* buffer, size_t length);
+
+  // The pointer `buffer` is the data previously returned by an init invocation.
+  void (*free)(TfLiteContext* context, void* buffer);
+
+  // prepare is called when the inputs this node depends on have been resized.
+  // context->ResizeTensor() can be called to request output tensors to be
+  // resized.
+  //
+  // Returns kTfLiteOk on success.
+  TfLiteStatus (*prepare)(TfLiteContext* context, TfLiteNode* node);
+
+  // Execute the node (should read node->inputs and output to node->outputs).
+  // Returns kTfLiteOk on success.
+  TfLiteStatus (*invoke)(TfLiteContext* context, TfLiteNode* node);
+
+  // profiling_string is called during summarization of profiling information
+  // in order to group executions together. Providing a value here will cause a
+  // given op to appear multiple times is the profiling report. This is
+  // particularly useful for custom ops that can perform significantly
+  // different calculations depending on their `user-data`.
+  const char* (*profiling_string)(const TfLiteContext* context,
+                                  const TfLiteNode* node);
+
+  // Builtin codes. If this kernel refers to a builtin this is the code
+  // of the builtin. This is so we can do marshaling to other frameworks like
+  // NN API.
+  // Note: It is the responsibility of the registration binder to set this
+  // properly.
+  int32_t builtin_code;
+
+  // Custom op name. If the op is a builtin, this will be null.
+  // Note: It is the responsibility of the registration binder to set this
+  // properly.
+  // WARNING: This is an experimental interface that is subject to change.
+  const char* custom_name;
+
+  // The version of the op.
+  // Note: It is the responsibility of the registration binder to set this
+  // properly.
+  int version;
+} TfLiteRegistration;
+
+// The flags used in `TfLiteDelegate`. Note that this is a bitmask, so the
+// values should be 1, 2, 4, 8, ...etc.
+typedef enum {
+  kTfLiteDelegateFlagsNone = 0,
+  // The flag is set if the delegate can handle dynamic sized tensors.
+  // For example, the output shape of a `Resize` op with non-constant shape
+  // can only be inferred when the op is invoked.
+  // In this case, the Delegate is responsible for calling
+  // `SetTensorToDynamic` to mark the tensor as a dynamic tensor, and calling
+  // `ResizeTensor` when invoking the op.
+  //
+  // If the delegate isn't capable to handle dynamic tensors, this flag need
+  // to be set to false.
+  kTfLiteDelegateFlagsAllowDynamicTensors = 1
+} TfLiteDelegateFlags;
+
+// WARNING: This is an experimental interface that is subject to change.
+typedef struct TfLiteDelegate {
+  // Data that delegate needs to identify itself. This data is owned by the
+  // delegate. The delegate is owned in the user code, so the delegate is
+  // responsible for doing this when it is destroyed.
+  void* data_;
+
+  // Invoked by ModifyGraphWithDelegate. This prepare is called, giving the
+  // delegate a view of the current graph through TfLiteContext*. It typically
+  // will look at the nodes and call ReplaceNodeSubsetsWithDelegateKernels()
+  // to ask the TensorFlow lite runtime to create macro-nodes to represent
+  // delegated subgraphs of the original graph.
+  TfLiteStatus (*Prepare)(TfLiteContext* context,
+                          struct TfLiteDelegate* delegate);
+
+  // Copy the data from delegate buffer handle into raw memory of the given
+  // 'tensor'. This cannot be null. The delegate is allowed to allocate the raw
+  // bytes as long as it follows the rules for kTfLiteDynamic tensors.
+  TfLiteStatus (*CopyFromBufferHandle)(TfLiteContext* context,
+                                       struct TfLiteDelegate* delegate,
+                                       TfLiteBufferHandle buffer_handle,
+                                       TfLiteTensor* tensor);
+
+  // Copy the data from raw memory of the given 'tensor' to delegate buffer
+  // handle. This can be null if the delegate doesn't use its own buffer.
+  TfLiteStatus (*CopyToBufferHandle)(TfLiteContext* context,
+                                     struct TfLiteDelegate* delegate,
+                                     TfLiteBufferHandle buffer_handle,
+                                     TfLiteTensor* tensor);
+
+  // Free the Delegate Buffer Handle. Note: This only frees the handle, but
+  // this doesn't release the underlying resource (e.g. textures). The
+  // resources are either owned by application layer or the delegate.
+  // This can be null if the delegate doesn't use its own buffer.
+  void (*FreeBufferHandle)(TfLiteContext* context,
+                           struct TfLiteDelegate* delegate,
+                           TfLiteBufferHandle* handle);
+
+  // Bitmask flags. See the comments in `TfLiteDelegateFlags`.
+  int64_t flags;
+} TfLiteDelegate;
+
+// Build a 'null' delegate, with all the fields properly set to their default
+// values.
+TfLiteDelegate TfLiteDelegateCreate();
+
+// WARNING: This is an experimental interface that is subject to change.
+//
+// Currently, TfLiteDelegateParams has to be allocated in a way that it's
+// trivially destructable. It will be stored as `builtin_data` field in
+// `TfLiteNode` of the delegate node.
+//
+// See also the `CreateDelegateParams` function in `interpreter.cc` details.
+typedef struct {
+  TfLiteDelegate* delegate;
+  TfLiteIntArray* nodes_to_replace;
+  TfLiteIntArray* input_tensors;
+  TfLiteIntArray* output_tensors;
+} TfLiteDelegateParams;
+
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+#endif  // TENSORFLOW_LITE_C_C_API_INTERNAL_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/core/api/error_reporter.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/core/api/error_reporter.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,38 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/core/api/error_reporter.h"
+#include <cstdarg>
+
+namespace tflite {
+
+int ErrorReporter::Report(const char* format, ...) {
+  va_list args;
+  va_start(args, format);
+  int code = Report(format, args);
+  va_end(args);
+  return code;
+}
+
+// TODO(aselle): Make the name of ReportError on context the same, so
+// we can use the ensure functions w/o a context and w/ a reporter.
+int ErrorReporter::ReportError(void*, const char* format, ...) {
+  va_list args;
+  va_start(args, format);
+  int code = Report(format, args);
+  va_end(args);
+  return code;
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/core/api/error_reporter.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/core/api/error_reporter.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,45 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_CORE_API_ERROR_REPORTER_H_
+#define TENSORFLOW_LITE_CORE_API_ERROR_REPORTER_H_
+
+#include <cstdarg>
+
+namespace tflite {
+
+/// A functor that reports error to supporting system. Invoked similar to
+/// printf.
+///
+/// Usage:
+///  ErrorReporter foo;
+///  foo.Report("test %d", 5);
+/// or
+///  va_list args;
+///  foo.Report("test %d", args); // where args is va_list
+///
+/// Subclass ErrorReporter to provide another reporting destination.
+/// For example, if you have a GUI program, you might redirect to a buffer
+/// that drives a GUI error log box.
+class ErrorReporter {
+ public:
+  virtual ~ErrorReporter() {}
+  virtual int Report(const char* format, va_list args) = 0;
+  int Report(const char* format, ...);
+  int ReportError(void*, const char* format, ...);
+};
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_CORE_API_ERROR_REPORTER_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/core/api/flatbuffer_conversions.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/core/api/flatbuffer_conversions.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,827 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/core/api/flatbuffer_conversions.h"
+
+#include <cstdlib>
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/schema/schema_generated.h"
+
+namespace tflite {
+
+namespace {
+
+// Utility class for safely allocating POD data. This is useful for avoiding
+// leaks in cases where op params are allocated but fail to propagate to the
+// parsed op data (e.g., when model parameters are invalid).
+class SafeBuiltinDataAllocator {
+ public:
+  class BuiltinDataDeleter {
+   public:
+    explicit BuiltinDataDeleter(BuiltinDataAllocator* allocator)
+        : allocator_(allocator) {}
+
+    void operator()(void* data) { allocator_->Deallocate(data); }
+
+   private:
+    BuiltinDataAllocator* allocator_;
+  };
+
+  template <typename T>
+  using BuiltinDataPtr = std::unique_ptr<T, BuiltinDataDeleter>;
+
+  explicit SafeBuiltinDataAllocator(BuiltinDataAllocator* allocator)
+      : allocator_(allocator) {}
+
+  template <typename T>
+  BuiltinDataPtr<T> Allocate() {
+    return BuiltinDataPtr<T>(allocator_->AllocatePOD<T>(),
+                             BuiltinDataDeleter(allocator_));
+  }
+
+ private:
+  BuiltinDataAllocator* allocator_;
+};
+
+// Copies the contents from the flatbuffer int vector `flatbuffer` into the
+// int array `buffer`. `flat_vector` and `buffer` represent the same
+// configuration operation for a given operation.
+TfLiteStatus FlatBufferIntVectorToArray(
+    int max_size_of_buffer, const flatbuffers::Vector<int32_t>* flat_vector,
+    int* buffer, ErrorReporter* error_reporter, const char* op_name) {
+  if (!flat_vector) {
+    error_reporter->Report("Input array not provided for operation '%s'.\n",
+                           op_name);
+    return kTfLiteError;
+  } else {
+    int num_dimensions = flat_vector->size();
+    if (num_dimensions > max_size_of_buffer / sizeof(int)) {
+      error_reporter->Report(
+          "Found too many dimensions in the input array of operation '%s'.\n",
+          op_name);
+      return kTfLiteError;
+    } else {
+      for (int i = 0; i < num_dimensions; ++i) {
+        buffer[i] = flat_vector->Get(i);
+      }
+    }
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace
+
+TfLiteStatus ConvertTensorType(TensorType tensor_type, TfLiteType* type,
+                               ErrorReporter* error_reporter) {
+  *type = kTfLiteNoType;
+  switch (tensor_type) {
+    case TensorType_FLOAT32:
+      *type = kTfLiteFloat32;
+      break;
+    case TensorType_FLOAT16:
+      *type = kTfLiteFloat16;
+      break;
+    case TensorType_INT16:
+      *type = kTfLiteInt16;
+      break;
+    case TensorType_INT32:
+      *type = kTfLiteInt32;
+      break;
+    case TensorType_UINT8:
+      *type = kTfLiteUInt8;
+      break;
+    case TensorType_INT8:
+      *type = kTfLiteInt8;
+      break;
+    case TensorType_INT64:
+      *type = kTfLiteInt64;
+      break;
+    case TensorType_STRING:
+      *type = kTfLiteString;
+      break;
+    case TensorType_BOOL:
+      *type = kTfLiteBool;
+      break;
+    case TensorType_COMPLEX64:
+      *type = kTfLiteComplex64;
+      break;
+  }
+  if (*type == kTfLiteNoType) {
+    error_reporter->Report("Unsupported data type %d in tensor\n", tensor_type);
+    return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+// Parse the appropriate data out of the op.
+//
+// This handles builtin data explicitly as there are flatbuffer schemas.
+// If it returns kTfLiteOk, it passes the data out with `builtin_data`, which
+// need to be released by calling `free`.`
+// If it returns kTfLiteError, `builtin_data` will be `nullptr`.
+TfLiteStatus ParseOpData(const Operator* op, BuiltinOperator op_type,
+                         ErrorReporter* error_reporter,
+                         BuiltinDataAllocator* allocator, void** builtin_data) {
+  auto parse_padding = [](Padding padding) {
+    switch (padding) {
+      case Padding_SAME:
+        return kTfLitePaddingSame;
+      case Padding_VALID:
+        return kTfLitePaddingValid;
+    }
+    return kTfLitePaddingUnknown;
+  };
+  auto parse_activation = [](ActivationFunctionType activation) {
+    switch (activation) {
+      case ActivationFunctionType_NONE:
+        return kTfLiteActNone;
+      case ActivationFunctionType_RELU:
+        return kTfLiteActRelu;
+      case ActivationFunctionType_RELU_N1_TO_1:
+        return kTfLiteActRelu1;
+      case ActivationFunctionType_RELU6:
+        return kTfLiteActRelu6;
+      case ActivationFunctionType_TANH:
+        return kTfLiteActTanh;
+      case ActivationFunctionType_SIGN_BIT:
+        return kTfLiteActSignBit;
+    }
+    return kTfLiteActNone;
+  };
+  auto parseLSHProjectionType = [](LSHProjectionType type) {
+    switch (type) {
+      case LSHProjectionType_SPARSE:
+        return kTfLiteLshProjectionSparse;
+      case LSHProjectionType_DENSE:
+        return kTfLiteLshProjectionDense;
+      default:
+        return kTfLiteLshProjectionUnknown;
+    }
+  };
+  auto parseCombinerType = [](CombinerType type) {
+    switch (type) {
+      case CombinerType_MEAN:
+        return kTfLiteCombinerTypeMean;
+      case CombinerType_SQRTN:
+        return kTfLiteCombinerTypeSqrtn;
+      case CombinerType_SUM:
+      default:
+        return kTfLiteCombinerTypeSum;
+    }
+  };
+
+  SafeBuiltinDataAllocator safe_allocator(allocator);
+  *builtin_data = nullptr;
+  switch (op_type) {
+    case BuiltinOperator_CONV_2D: {
+      auto params = safe_allocator.Allocate<TfLiteConvParams>();
+      if (auto* conv_params = op->builtin_options_as_Conv2DOptions()) {
+        params->padding = parse_padding(conv_params->padding());
+        params->stride_width = conv_params->stride_w();
+        params->stride_height = conv_params->stride_h();
+        params->activation =
+            parse_activation(conv_params->fused_activation_function());
+
+        params->dilation_width_factor = conv_params->dilation_w_factor();
+        params->dilation_height_factor = conv_params->dilation_h_factor();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_CAST: {
+      auto params = safe_allocator.Allocate<TfLiteCastParams>();
+      if (const auto* schema_params = op->builtin_options_as_CastOptions()) {
+        auto in_status =
+            ConvertTensorType(schema_params->in_data_type(),
+                              &params->in_data_type, error_reporter);
+        auto out_status =
+            ConvertTensorType(schema_params->out_data_type(),
+                              &params->out_data_type, error_reporter);
+        if (in_status != kTfLiteOk || out_status != kTfLiteOk) {
+          return kTfLiteError;
+        }
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_LSH_PROJECTION: {
+      auto params = safe_allocator.Allocate<TfLiteLSHProjectionParams>();
+      if (const auto* lshParams =
+              op->builtin_options_as_LSHProjectionOptions()) {
+        params->type = parseLSHProjectionType(lshParams->type());
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_AVERAGE_POOL_2D:
+    case BuiltinOperator_MAX_POOL_2D:
+    case BuiltinOperator_L2_POOL_2D: {
+      auto params = safe_allocator.Allocate<TfLitePoolParams>();
+      if (const auto* pool_params = op->builtin_options_as_Pool2DOptions()) {
+        params->padding = parse_padding(pool_params->padding());
+        params->stride_width = pool_params->stride_w();
+        params->stride_height = pool_params->stride_h();
+        params->filter_width = pool_params->filter_width();
+        params->filter_height = pool_params->filter_height();
+        params->activation =
+            parse_activation(pool_params->fused_activation_function());
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_DEPTHWISE_CONV_2D: {
+      auto params = safe_allocator.Allocate<TfLiteDepthwiseConvParams>();
+      if (const auto* conv_params =
+              op->builtin_options_as_DepthwiseConv2DOptions()) {
+        params->padding = parse_padding(conv_params->padding());
+        params->stride_width = conv_params->stride_w();
+        params->stride_height = conv_params->stride_h();
+        params->depth_multiplier = conv_params->depth_multiplier();
+        params->activation =
+            parse_activation(conv_params->fused_activation_function());
+
+        params->dilation_width_factor = conv_params->dilation_w_factor();
+        params->dilation_height_factor = conv_params->dilation_h_factor();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_SVDF: {
+      auto params = safe_allocator.Allocate<TfLiteSVDFParams>();
+      if (const auto* svdf_params = op->builtin_options_as_SVDFOptions()) {
+        params->rank = svdf_params->rank();
+        params->activation =
+            parse_activation(svdf_params->fused_activation_function());
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_UNIDIRECTIONAL_SEQUENCE_RNN: {
+      auto params = safe_allocator.Allocate<TfLiteSequenceRNNParams>();
+      if (const auto* sequence_rnn_params =
+              op->builtin_options_as_SequenceRNNOptions()) {
+        params->activation =
+            parse_activation(sequence_rnn_params->fused_activation_function());
+        params->time_major = sequence_rnn_params->time_major();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_BIDIRECTIONAL_SEQUENCE_RNN: {
+      auto params =
+          safe_allocator.Allocate<TfLiteBidirectionalSequenceRNNParams>();
+      if (const auto* bidi_sequence_rnn_params =
+              op->builtin_options_as_BidirectionalSequenceRNNOptions()) {
+        params->activation = parse_activation(
+            bidi_sequence_rnn_params->fused_activation_function());
+        params->time_major = bidi_sequence_rnn_params->time_major();
+        params->merge_outputs = bidi_sequence_rnn_params->merge_outputs();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_RNN: {
+      auto params = safe_allocator.Allocate<TfLiteRNNParams>();
+      if (const auto* rnn_params = op->builtin_options_as_RNNOptions()) {
+        params->activation =
+            parse_activation(rnn_params->fused_activation_function());
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_EMBEDDING_LOOKUP_SPARSE: {
+      auto params =
+          safe_allocator.Allocate<TfLiteEmbeddingLookupSparseParams>();
+      if (const auto* embedding_params =
+              op->builtin_options_as_EmbeddingLookupSparseOptions()) {
+        params->combiner = parseCombinerType(embedding_params->combiner());
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_FULLY_CONNECTED: {
+      auto params = safe_allocator.Allocate<TfLiteFullyConnectedParams>();
+      if (const auto* fully_connected_params =
+              op->builtin_options_as_FullyConnectedOptions()) {
+        params->activation = parse_activation(
+            fully_connected_params->fused_activation_function());
+        params->keep_num_dims = fully_connected_params->keep_num_dims();
+        switch (fully_connected_params->weights_format()) {
+          case FullyConnectedOptionsWeightsFormat_DEFAULT:
+            params->weights_format = kTfLiteFullyConnectedWeightsFormatDefault;
+            break;
+          case FullyConnectedOptionsWeightsFormat_SHUFFLED4x16INT8:
+            params->weights_format =
+                kTfLiteFullyConnectedWeightsFormatShuffled4x16Int8;
+            break;
+          default:
+            error_reporter->Report("Unhandled fully-connected weights format.");
+            return kTfLiteError;
+        }
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_HASHTABLE_LOOKUP:
+      // no-op.
+      break;
+    case BuiltinOperator_SOFTMAX: {
+      auto params = safe_allocator.Allocate<TfLiteSoftmaxParams>();
+      if (const auto* softmax_params =
+              op->builtin_options_as_SoftmaxOptions()) {
+        params->beta = softmax_params->beta();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_CONCATENATION: {
+      auto params = safe_allocator.Allocate<TfLiteConcatenationParams>();
+      if (const auto* concatenation_params =
+              op->builtin_options_as_ConcatenationOptions()) {
+        params->activation =
+            parse_activation(concatenation_params->fused_activation_function());
+        params->axis = concatenation_params->axis();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_MUL: {
+      auto params = safe_allocator.Allocate<TfLiteMulParams>();
+      if (const auto* schema_params = op->builtin_options_as_MulOptions()) {
+        params->activation =
+            parse_activation(schema_params->fused_activation_function());
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_ADD: {
+      auto params = safe_allocator.Allocate<TfLiteAddParams>();
+      if (const auto* schema_params = op->builtin_options_as_AddOptions()) {
+        params->activation =
+            parse_activation(schema_params->fused_activation_function());
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_DIV: {
+      auto params = safe_allocator.Allocate<TfLiteDivParams>();
+      if (const auto* schema_params = op->builtin_options_as_DivOptions()) {
+        params->activation =
+            parse_activation(schema_params->fused_activation_function());
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_SUB: {
+      auto params = safe_allocator.Allocate<TfLiteSubParams>();
+      if (const auto* schema_params = op->builtin_options_as_SubOptions()) {
+        params->activation =
+            parse_activation(schema_params->fused_activation_function());
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_L2_NORMALIZATION: {
+      auto params = safe_allocator.Allocate<TfLiteL2NormParams>();
+      if (const auto* schema_params = op->builtin_options_as_L2NormOptions()) {
+        params->activation =
+            parse_activation(schema_params->fused_activation_function());
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_LOCAL_RESPONSE_NORMALIZATION: {
+      auto params = safe_allocator.Allocate<TfLiteLocalResponseNormParams>();
+      if (const auto* schema_params =
+              op->builtin_options_as_LocalResponseNormalizationOptions()) {
+        params->radius = schema_params->radius();
+        params->bias = schema_params->bias();
+        params->alpha = schema_params->alpha();
+        params->beta = schema_params->beta();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_LSTM: {
+      auto params = safe_allocator.Allocate<TfLiteLSTMParams>();
+      if (const auto* lstm_params = op->builtin_options_as_LSTMOptions()) {
+        params->activation =
+            parse_activation(lstm_params->fused_activation_function());
+        params->cell_clip = lstm_params->cell_clip();
+        params->proj_clip = lstm_params->proj_clip();
+        switch (lstm_params->kernel_type()) {
+          case LSTMKernelType_FULL:
+            params->kernel_type = kTfLiteLSTMFullKernel;
+            break;
+          case LSTMKernelType_BASIC:
+            params->kernel_type = kTfLiteLSTMBasicKernel;
+            break;
+          default:
+            error_reporter->Report("Unhandled LSTM kernel type: %d",
+                                   lstm_params->kernel_type());
+            return kTfLiteError;
+        }
+      } else {
+        error_reporter->Report("No valid LSTM builtin options exist");
+        return kTfLiteError;
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_UNIDIRECTIONAL_SEQUENCE_LSTM: {
+      auto params =
+          safe_allocator.Allocate<TfLiteUnidirectionalSequenceLSTMParams>();
+      if (const auto* seq_lstm_params =
+              op->builtin_options_as_UnidirectionalSequenceLSTMOptions()) {
+        params->activation =
+            parse_activation(seq_lstm_params->fused_activation_function());
+        params->cell_clip = seq_lstm_params->cell_clip();
+        params->proj_clip = seq_lstm_params->proj_clip();
+        params->time_major = seq_lstm_params->time_major();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_BIDIRECTIONAL_SEQUENCE_LSTM: {
+      auto params =
+          safe_allocator.Allocate<TfLiteBidirectionalSequenceLSTMParams>();
+      if (const auto* bidi_lstm_params =
+              op->builtin_options_as_BidirectionalSequenceLSTMOptions()) {
+        params->activation =
+            parse_activation(bidi_lstm_params->fused_activation_function());
+        params->cell_clip = bidi_lstm_params->cell_clip();
+        params->proj_clip = bidi_lstm_params->proj_clip();
+        params->merge_outputs = bidi_lstm_params->merge_outputs();
+        params->time_major = bidi_lstm_params->time_major();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_RESIZE_BILINEAR: {
+      auto params = safe_allocator.Allocate<TfLiteResizeBilinearParams>();
+      if (const auto* schema_params =
+              op->builtin_options_as_ResizeBilinearOptions()) {
+        params->align_corners = schema_params->align_corners();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_RESIZE_NEAREST_NEIGHBOR: {
+      // Large functions confuse MacOS builds with XCode 8 so a lambda is
+      // required to minimize function size. TODO(b/118447267): Simplify
+      // ParseOpData function and reduce its length.
+      [&]() {
+        auto params =
+            safe_allocator.Allocate<TfLiteResizeNearestNeighborParams>();
+        if (const auto* schema_params =
+                op->builtin_options_as_ResizeNearestNeighborOptions()) {
+          params->align_corners = schema_params->align_corners();
+        }
+        *builtin_data = reinterpret_cast<void*>(params.release());
+      }();
+      break;
+    }
+    case BuiltinOperator_RESHAPE: {
+      auto params = safe_allocator.Allocate<TfLiteReshapeParams>();
+      if (const auto* schema_params = op->builtin_options_as_ReshapeOptions()) {
+        auto* new_shape = schema_params->new_shape();
+        TF_LITE_ENSURE_STATUS(FlatBufferIntVectorToArray(
+            sizeof(params->shape), new_shape, params->shape, error_reporter,
+            "reshape"));
+        params->num_dimensions = new_shape->size();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_SKIP_GRAM: {
+      auto params = safe_allocator.Allocate<TfLiteSkipGramParams>();
+      if (const auto* skip_gram_params =
+              op->builtin_options_as_SkipGramOptions()) {
+        params->ngram_size = skip_gram_params->ngram_size();
+        params->max_skip_size = skip_gram_params->max_skip_size();
+        params->include_all_ngrams = skip_gram_params->include_all_ngrams();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_SPACE_TO_DEPTH: {
+      auto params = safe_allocator.Allocate<TfLiteSpaceToDepthParams>();
+      if (const auto* schema_params =
+              op->builtin_options_as_SpaceToDepthOptions()) {
+        params->block_size = schema_params->block_size();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_DEPTH_TO_SPACE: {
+      auto params = safe_allocator.Allocate<TfLiteDepthToSpaceParams>();
+      if (const auto* schema_params =
+              op->builtin_options_as_DepthToSpaceOptions()) {
+        params->block_size = schema_params->block_size();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_GATHER: {
+      auto params = safe_allocator.Allocate<TfLiteGatherParams>();
+      params->axis = 0;
+      if (const auto* gather_params = op->builtin_options_as_GatherOptions()) {
+        params->axis = gather_params->axis();
+      }
+
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_MEAN:
+    case BuiltinOperator_REDUCE_MAX:
+    case BuiltinOperator_REDUCE_MIN:
+    case BuiltinOperator_REDUCE_PROD:
+    case BuiltinOperator_REDUCE_ANY:
+    case BuiltinOperator_SUM: {
+      auto params = safe_allocator.Allocate<TfLiteReducerParams>();
+      if (const auto* schema_params = op->builtin_options_as_ReducerOptions()) {
+        params->keep_dims = schema_params->keep_dims();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_SPLIT: {
+      auto params = safe_allocator.Allocate<TfLiteSplitParams>();
+      if (const auto* schema_params = op->builtin_options_as_SplitOptions()) {
+        params->num_splits = schema_params->num_splits();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_SPLIT_V: {
+      auto params = safe_allocator.Allocate<TfLiteSplitParams>();
+      if (const auto* schema_params = op->builtin_options_as_SplitVOptions()) {
+        params->num_splits = schema_params->num_splits();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_SQUEEZE: {
+      auto params = safe_allocator.Allocate<TfLiteSqueezeParams>();
+      if (const auto* schema_params = op->builtin_options_as_SqueezeOptions()) {
+        const auto& squeeze_dims = schema_params->squeeze_dims();
+        TF_LITE_ENSURE_STATUS(FlatBufferIntVectorToArray(
+            sizeof(params->squeeze_dims), squeeze_dims, params->squeeze_dims,
+            error_reporter, "squeeze"));
+        params->num_squeeze_dims = squeeze_dims->size();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_STRIDED_SLICE: {
+      auto params = safe_allocator.Allocate<TfLiteStridedSliceParams>();
+      if (const auto* schema_params =
+              op->builtin_options_as_StridedSliceOptions()) {
+        params->begin_mask = schema_params->begin_mask();
+        params->end_mask = schema_params->end_mask();
+        params->ellipsis_mask = schema_params->ellipsis_mask();
+        params->new_axis_mask = schema_params->new_axis_mask();
+        params->shrink_axis_mask = schema_params->shrink_axis_mask();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_ARG_MAX: {
+      auto params = safe_allocator.Allocate<TfLiteArgMaxParams>();
+      if (const auto* schema_params = op->builtin_options_as_ArgMaxOptions()) {
+        ConvertTensorType(schema_params->output_type(), &params->output_type,
+                          error_reporter);
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_ARG_MIN: {
+      auto params = safe_allocator.Allocate<TfLiteArgMinParams>();
+      if (const auto* schema_params = op->builtin_options_as_ArgMinOptions()) {
+        ConvertTensorType(schema_params->output_type(), &params->output_type,
+                          error_reporter);
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_TRANSPOSE_CONV: {
+      auto params = safe_allocator.Allocate<TfLiteTransposeConvParams>();
+      if (const auto* transpose_conv_params =
+              op->builtin_options_as_TransposeConvOptions()) {
+        params->padding = parse_padding(transpose_conv_params->padding());
+        params->stride_width = transpose_conv_params->stride_w();
+        params->stride_height = transpose_conv_params->stride_h();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_SPARSE_TO_DENSE: {
+      auto params = safe_allocator.Allocate<TfLiteSparseToDenseParams>();
+      if (const auto* sparse_to_dense_params =
+              op->builtin_options_as_SparseToDenseOptions()) {
+        params->validate_indices = sparse_to_dense_params->validate_indices();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_SHAPE: {
+      auto params = safe_allocator.Allocate<TfLiteShapeParams>();
+      if (const auto* schema_params = op->builtin_options_as_ShapeOptions()) {
+        ConvertTensorType(schema_params->out_type(), &params->out_type,
+                          error_reporter);
+      }
+      *builtin_data = static_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_PACK: {
+      auto params = safe_allocator.Allocate<TfLitePackParams>();
+      if (const auto* pack_params = op->builtin_options_as_PackOptions()) {
+        params->values_count = pack_params->values_count();
+        params->axis = pack_params->axis();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_DELEGATE: {
+      // TODO(ycling): Revisit when supporting saving delegated models.
+      error_reporter->Report("DELEGATE op shouldn't exist in model.");
+      return kTfLiteError;
+    }
+    case BuiltinOperator_FAKE_QUANT: {
+      auto params = safe_allocator.Allocate<TfLiteFakeQuantParams>();
+      if (const auto* schema_params =
+              op->builtin_options_as_FakeQuantOptions()) {
+        params->min = schema_params->min();
+        params->max = schema_params->max();
+        params->num_bits = schema_params->num_bits();
+        params->narrow_range = schema_params->narrow_range();
+      }
+      *builtin_data = static_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_ONE_HOT: {
+      auto params = safe_allocator.Allocate<TfLiteOneHotParams>();
+      if (const auto* schema_params = op->builtin_options_as_OneHotOptions()) {
+        params->axis = schema_params->axis();
+      }
+      *builtin_data = static_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_UNPACK: {
+      auto params = safe_allocator.Allocate<TfLiteUnpackParams>();
+      if (const auto* unpack_params = op->builtin_options_as_UnpackOptions()) {
+        params->num = unpack_params->num();
+        params->axis = unpack_params->axis();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_LEAKY_RELU: {
+      auto params = safe_allocator.Allocate<TfLiteLeakyReluParams>();
+      if (const auto* leaky_relu_params =
+              op->builtin_options_as_LeakyReluOptions()) {
+        params->alpha = leaky_relu_params->alpha();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_MIRROR_PAD: {
+      auto params = safe_allocator.Allocate<TfLiteMirrorPaddingParams>();
+      const auto* mirror_pad_params = op->builtin_options_as_MirrorPadOptions();
+      if (mirror_pad_params != nullptr) {
+        params->mode =
+            mirror_pad_params->mode() == tflite::MirrorPadMode_REFLECT
+                ? TfLiteMirrorPaddingMode::kTfLiteMirrorPaddingReflect
+                : TfLiteMirrorPaddingMode::kTfLiteMirrorPaddingSymmetric;
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_UNIQUE: {
+      auto params = safe_allocator.Allocate<TfLiteUniqueParams>();
+      const auto* unique_params = op->builtin_options_as_UniqueOptions();
+      if (unique_params != nullptr) {
+        params->index_out_type =
+            unique_params->idx_out_type() == tflite::TensorType_INT64
+                ? TfLiteType::kTfLiteInt64
+                : TfLiteType::kTfLiteInt32;
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_REVERSE_SEQUENCE: {
+      auto params = safe_allocator.Allocate<TfLiteReverseSequenceParams>();
+      if (const auto* reverse_seq_params =
+              op->builtin_options_as_ReverseSequenceOptions()) {
+        params->seq_dim = reverse_seq_params->seq_dim();
+        params->batch_dim = reverse_seq_params->batch_dim();
+      }
+      *builtin_data = reinterpret_cast<void*>(params.release());
+      break;
+    }
+    case BuiltinOperator_IF: {
+      TfLiteIfParams* params = allocator->AllocatePOD<TfLiteIfParams>();
+      if (const auto* if_params = op->builtin_options_as_IfOptions()) {
+        params->then_subgraph_index = if_params->then_subgraph_index();
+        params->else_subgraph_index = if_params->else_subgraph_index();
+      }
+      *builtin_data = reinterpret_cast<void*>(params);
+      break;
+    }
+    case BuiltinOperator_WHILE: {
+      TfLiteWhileParams* params = allocator->AllocatePOD<TfLiteWhileParams>();
+      if (const auto* while_params = op->builtin_options_as_WhileOptions()) {
+        params->cond_subgraph_index = while_params->cond_subgraph_index();
+        params->body_subgraph_index = while_params->body_subgraph_index();
+      }
+      *builtin_data = reinterpret_cast<void*>(params);
+      break;
+    }
+    // Below are the ops with no builtin_data structure.
+    case BuiltinOperator_ABS:
+    case BuiltinOperator_BATCH_TO_SPACE_ND:
+    // TODO(aselle): Implement call in BuiltinOptions, but nullptrs are
+    // ok for now, since there is no call implementation either.
+    case BuiltinOperator_CALL:
+    case BuiltinOperator_CONCAT_EMBEDDINGS:
+    case BuiltinOperator_COS:
+    case BuiltinOperator_CUSTOM:
+    case BuiltinOperator_DEQUANTIZE:
+    case BuiltinOperator_ELU:
+    case BuiltinOperator_EMBEDDING_LOOKUP:
+    case BuiltinOperator_EQUAL:
+    case BuiltinOperator_EXP:
+    case BuiltinOperator_EXPAND_DIMS:
+    case BuiltinOperator_CEIL:
+    case BuiltinOperator_FLOOR:
+    case BuiltinOperator_GREATER:
+    case BuiltinOperator_GREATER_EQUAL:
+    case BuiltinOperator_HARD_SWISH:
+    case BuiltinOperator_LESS:
+    case BuiltinOperator_LESS_EQUAL:
+    case BuiltinOperator_LOG:
+    case BuiltinOperator_LOGISTIC:
+    case BuiltinOperator_LOG_SOFTMAX:
+    case BuiltinOperator_MATRIX_DIAG:
+    case BuiltinOperator_MATRIX_SET_DIAG:
+    case BuiltinOperator_MAXIMUM:
+    case BuiltinOperator_MINIMUM:
+    case BuiltinOperator_NEG:
+    case BuiltinOperator_NOT_EQUAL:
+    case BuiltinOperator_PAD:
+    case BuiltinOperator_PADV2:
+    case BuiltinOperator_PRELU:
+    case BuiltinOperator_RELU:
+    case BuiltinOperator_RELU6:
+    case BuiltinOperator_RELU_N1_TO_1:
+    case BuiltinOperator_ROUND:
+    case BuiltinOperator_RSQRT:
+    case BuiltinOperator_SELECT:
+    case BuiltinOperator_SIN:
+    case BuiltinOperator_SLICE:
+    case BuiltinOperator_SPACE_TO_BATCH_ND:
+    case BuiltinOperator_SQRT:
+    case BuiltinOperator_TANH:
+    case BuiltinOperator_TILE:
+    case BuiltinOperator_TOPK_V2:
+    case BuiltinOperator_TRANSPOSE:
+    case BuiltinOperator_POW:
+    case BuiltinOperator_LOGICAL_OR:
+    case BuiltinOperator_LOGICAL_AND:
+    case BuiltinOperator_LOGICAL_NOT:
+    case BuiltinOperator_FLOOR_DIV:
+    case BuiltinOperator_SQUARE:
+    case BuiltinOperator_ZEROS_LIKE:
+    case BuiltinOperator_FILL:
+    case BuiltinOperator_FLOOR_MOD:
+    case BuiltinOperator_RANGE:
+    case BuiltinOperator_SQUARED_DIFFERENCE:
+    case BuiltinOperator_REVERSE_V2:
+    case BuiltinOperator_ADD_N:
+    case BuiltinOperator_GATHER_ND:
+    case BuiltinOperator_WHERE:
+    case BuiltinOperator_RANK:
+    case BuiltinOperator_QUANTIZE:
+    case BuiltinOperator_NON_MAX_SUPPRESSION_V4:
+    case BuiltinOperator_NON_MAX_SUPPRESSION_V5:
+    case BuiltinOperator_SCATTER_ND:
+      break;
+  }
+  return kTfLiteOk;
+}  // NOLINT[readability/fn_size]
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/core/api/flatbuffer_conversions.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/core/api/flatbuffer_conversions.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,68 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_CORE_API_FLATBUFFER_CONVERSIONS_H_
+#define TENSORFLOW_LITE_CORE_API_FLATBUFFER_CONVERSIONS_H_
+
+// These functions transform codes and data structures that are defined in the
+// flatbuffer serialization format into in-memory values that are used by the
+// runtime API and interpreter.
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/core/api/error_reporter.h"
+#include "tensorflow/lite/core/api/op_resolver.h"
+#include "tensorflow/lite/schema/schema_generated.h"
+
+namespace tflite {
+
+// Interface class for builtin data allocations.
+class BuiltinDataAllocator {
+ public:
+  virtual void* Allocate(size_t size) = 0;
+  virtual void Deallocate(void* data) = 0;
+
+  // Allocate a structure, but make sure it is a POD structure that doesn't
+  // require constructors to run. The reason we do this, is that Interpreter's C
+  // extension part will take ownership so destructors  will not be run during
+  // deallocation.
+  template <typename T>
+  T* AllocatePOD() {
+    static_assert(std::is_pod<T>::value, "Builtin data structure must be POD.");
+    return static_cast<T*>(this->Allocate(sizeof(T)));
+  }
+
+  virtual ~BuiltinDataAllocator() {}
+};
+
+// Parse the appropriate data out of the op.
+//
+// This handles builtin data explicitly as there are flatbuffer schemas.
+// If it returns kTfLiteOk, it passes the data out with `builtin_data`. The
+// calling function has to pass in an allocator object, and this allocator
+// will be called to reserve space for the output data. If the calling
+// function's allocator reserves memory on the heap, then it's the calling
+// function's responsibility to free it.
+// If it returns kTfLiteError, `builtin_data` will be `nullptr`.
+TfLiteStatus ParseOpData(const Operator* op, BuiltinOperator op_type,
+                         ErrorReporter* error_reporter,
+                         BuiltinDataAllocator* allocator, void** builtin_data);
+
+// Converts the tensor data type used in the flat buffer to the representation
+// used by the runtime.
+TfLiteStatus ConvertTensorType(TensorType tensor_type, TfLiteType* type,
+                               ErrorReporter* error_reporter);
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_CORE_API_FLATBUFFER_CONVERSIONS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/core/api/op_resolver.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/core/api/op_resolver.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,59 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/core/api/op_resolver.h"
+
+namespace tflite {
+
+TfLiteStatus GetRegistrationFromOpCode(
+    const OperatorCode* opcode, const OpResolver& op_resolver,
+    ErrorReporter* error_reporter, const TfLiteRegistration** registration) {
+  TfLiteStatus status = kTfLiteOk;
+  *registration = nullptr;
+  auto builtin_code = opcode->builtin_code();
+  int version = opcode->version();
+
+  if (builtin_code > BuiltinOperator_MAX ||
+      builtin_code < BuiltinOperator_MIN) {
+    error_reporter->Report(
+        "Op builtin_code out of range: %d. Are you using old TFLite binary "
+        "with newer model?",
+        builtin_code);
+    status = kTfLiteError;
+  } else if (builtin_code != BuiltinOperator_CUSTOM) {
+    *registration = op_resolver.FindOp(builtin_code, version);
+    if (*registration == nullptr) {
+      error_reporter->Report(
+          "Didn't find op for builtin opcode '%s' version '%d'\n",
+          EnumNameBuiltinOperator(builtin_code), version);
+      status = kTfLiteError;
+    }
+  } else if (!opcode->custom_code()) {
+    error_reporter->Report(
+        "Operator with CUSTOM builtin_code has no custom_code.\n");
+    status = kTfLiteError;
+  } else {
+    const char* name = opcode->custom_code()->c_str();
+    *registration = op_resolver.FindOp(name, version);
+    if (*registration == nullptr) {
+      // Do not report error for unresolved custom op, we do the final check
+      // while preparing ops.
+      status = kTfLiteError;
+    }
+  }
+  return status;
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/core/api/op_resolver.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/core/api/op_resolver.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,48 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_CORE_API_OP_RESOLVER_H_
+#define TENSORFLOW_LITE_CORE_API_OP_RESOLVER_H_
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/core/api/error_reporter.h"
+#include "tensorflow/lite/schema/schema_generated.h"
+
+namespace tflite {
+
+/// Abstract interface that returns TfLiteRegistrations given op codes or custom
+/// op names. This is the mechanism that ops being referenced in the flatbuffer
+/// model are mapped to executable function pointers (TfLiteRegistrations).
+class OpResolver {
+ public:
+  /// Finds the op registration for a builtin operator by enum code.
+  virtual const TfLiteRegistration* FindOp(tflite::BuiltinOperator op,
+                                           int version) const = 0;
+  /// Finds the op registration of a custom operator by op name.
+  virtual const TfLiteRegistration* FindOp(const char* op,
+                                           int version) const = 0;
+  virtual ~OpResolver() {}
+};
+
+// Handles the logic for converting between an OperatorCode structure extracted
+// from a flatbuffer and information about a registered operator
+// implementation.
+TfLiteStatus GetRegistrationFromOpCode(const OperatorCode* opcode,
+                                       const OpResolver& op_resolver,
+                                       ErrorReporter* error_reporter,
+                                       const TfLiteRegistration** registration);
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_CORE_API_OP_RESOLVER_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/core/api/tensor_utils.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/core/api/tensor_utils.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,48 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/core/api/tensor_utils.h"
+
+#include <string.h>
+
+namespace tflite {
+
+TfLiteStatus ResetVariableTensor(TfLiteTensor* tensor) {
+  if (!tensor->is_variable) {
+    return kTfLiteOk;
+  }
+  // TODO(b/115961645): Implement - If a variable tensor has a buffer, reset it
+  // to the value of the buffer.
+  int value = 0;
+  if (tensor->type == kTfLiteInt8) {
+    value = tensor->params.zero_point;
+  }
+  // TODO(b/139446230): Provide a platform header to better handle these
+  // specific scenarios.
+#if __ANDROID__ || defined(__x86_64__) || defined(__i386__) || \
+    defined(__i386) || defined(__x86__) || defined(__X86__) || \
+    defined(_X86_) || defined(_M_IX86) || defined(_M_X64)
+  memset(tensor->data.raw, value, tensor->bytes);
+#else
+  char* raw_ptr = tensor->data.raw;
+  for (int i = 0; i < tensor->bytes; ++i) {
+    *raw_ptr = value;
+    raw_ptr++;
+  }
+#endif
+  return kTfLiteOk;
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/core/api/tensor_utils.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/core/api/tensor_utils.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,28 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_CORE_API_TENSOR_UTILS_H_
+#define TENSORFLOW_LITE_CORE_API_TENSOR_UTILS_H_
+
+#include "tensorflow/lite/c/c_api_internal.h"
+
+namespace tflite {
+
+// Resets a variable tensor to the default value.
+TfLiteStatus ResetVariableTensor(TfLiteTensor* tensor);
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_CORE_API_TENSOR_UTILS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/compatibility.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/compatibility.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,32 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_COMPATIBILITY_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_COMPATIBILITY_H_
+
+// C++ will automatically create class-specific delete operators for virtual
+// objects, which by default call the global delete function. For embedded
+// applications we want to avoid this, and won't be calling new/delete on these
+// objects, so we need to override the default implementation with one that does
+// nothing to avoid linking in ::delete().
+// This macro needs to be included in all subclasses of a virtual base class in
+// the private section.
+#ifdef TF_LITE_STATIC_MEMORY
+#define TF_LITE_REMOVE_VIRTUAL_DELETE \
+  void operator delete(void* p) {}
+#else
+#define TF_LITE_REMOVE_VIRTUAL_DELETE
+#endif
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_COMPATIBILITY_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/debug_log.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/debug_log.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,23 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_DEBUG_LOG_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_DEBUG_LOG_H_
+
+// This function should be implemented by each target platform, and provide a
+// way for strings to be output to some text stream. For more information, see
+// tensorflow/lite/experimental/micro/debug_log.cc.
+extern "C" void DebugLog(const char* s);
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_DEBUG_LOG_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/debug_log_numbers.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/debug_log_numbers.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,185 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+// Implements debug logging for numbers by converting them into strings and then
+// calling the main DebugLog(char*) function. These are separated into a
+// different file so that platforms can just implement the string output version
+// of DebugLog() and then get the numerical variations without requiring any
+// more code.
+
+#include "tensorflow/lite/experimental/micro/debug_log_numbers.h"
+
+#include "tensorflow/lite/experimental/micro/debug_log.h"
+
+namespace {
+
+// All input buffers to the number conversion functions must be this long.
+static const int kFastToBufferSize = 48;
+
+// Reverses a zero-terminated string in-place.
+char* ReverseStringInPlace(char* start, char* end) {
+  char* p1 = start;
+  char* p2 = end - 1;
+  while (p1 < p2) {
+    char tmp = *p1;
+    *p1++ = *p2;
+    *p2-- = tmp;
+  }
+  return start;
+}
+
+// Appends a string to a string, in-place. You need to pass in the maximum
+// string length as the second argument.
+char* StrCatStr(char* main, int main_max_length, const char* to_append) {
+  char* current = main;
+  while (*current != 0) {
+    ++current;
+  }
+  char* current_end = main + (main_max_length - 1);
+  while ((*to_append != 0) && (current < current_end)) {
+    *current = *to_append;
+    ++current;
+    ++to_append;
+  }
+  *current = 0;
+  return current;
+}
+
+// Populates the provided buffer with an ASCII representation of the number.
+char* FastUInt32ToBufferLeft(uint32_t i, char* buffer, int base) {
+  char* start = buffer;
+  do {
+    int32_t digit = i % base;
+    char character;
+    if (digit < 10) {
+      character = '0' + digit;
+    } else {
+      character = 'a' + (digit - 10);
+    }
+    *buffer++ = character;
+    i /= base;
+  } while (i > 0);
+  *buffer = 0;
+  ReverseStringInPlace(start, buffer);
+  return buffer;
+}
+
+// Populates the provided buffer with an ASCII representation of the number.
+char* FastInt32ToBufferLeft(int32_t i, char* buffer) {
+  uint32_t u = i;
+  if (i < 0) {
+    *buffer++ = '-';
+    u = -u;
+  }
+  return FastUInt32ToBufferLeft(u, buffer, 10);
+}
+
+// Converts a number to a string and appends it to another.
+char* StrCatInt32(char* main, int main_max_length, int32_t number) {
+  char number_string[kFastToBufferSize];
+  FastInt32ToBufferLeft(number, number_string);
+  return StrCatStr(main, main_max_length, number_string);
+}
+
+// Converts a number to a string and appends it to another.
+char* StrCatUInt32(char* main, int main_max_length, uint32_t number, int base) {
+  char number_string[kFastToBufferSize];
+  FastUInt32ToBufferLeft(number, number_string, base);
+  return StrCatStr(main, main_max_length, number_string);
+}
+
+// Populates the provided buffer with ASCII representation of the float number.
+// Avoids the use of any floating point instructions (since these aren't
+// supported on many microcontrollers) and as a consequence prints values with
+// power-of-two exponents.
+char* FastFloatToBufferLeft(float f, char* buffer) {
+  char* current = buffer;
+  char* current_end = buffer + (kFastToBufferSize - 1);
+  // Access the bit fields of the floating point value to avoid requiring any
+  // float instructions. These constants are derived from IEEE 754.
+  const uint32_t sign_mask = 0x80000000;
+  const uint32_t exponent_mask = 0x7f800000;
+  const int32_t exponent_shift = 23;
+  const int32_t exponent_bias = 127;
+  const uint32_t fraction_mask = 0x007fffff;
+  const uint32_t u = *reinterpret_cast<uint32_t*>(&f);
+  const int32_t exponent =
+      ((u & exponent_mask) >> exponent_shift) - exponent_bias;
+  const uint32_t fraction = (u & fraction_mask);
+  // Expect ~0x2B1B9D3 for fraction.
+  if (u & sign_mask) {
+    *current = '-';
+    current += 1;
+  }
+  *current = 0;
+  // These are special cases for infinities and not-a-numbers.
+  if (exponent == 128) {
+    if (fraction == 0) {
+      current = StrCatStr(current, (current_end - current), "Inf");
+      return current;
+    } else {
+      current = StrCatStr(current, (current_end - current), "NaN");
+      return current;
+    }
+  }
+  // 0x007fffff (8388607) represents 0.99... for the fraction, so to print the
+  // correct decimal digits we need to scale our value before passing it to the
+  // conversion function. This scale should be 10000000/8388608 = 1.1920928955.
+  // We can approximate this using multiply-adds and right-shifts using the
+  // values in this array. The 1. portion of the number string is printed out
+  // in a fixed way before the fraction, below.
+  const int32_t scale_shifts_size = 13;
+  const int8_t scale_shifts[13] = {3,  4,  8,  11, 13, 14, 17,
+                                   18, 19, 20, 21, 22, 23};
+  uint32_t scaled_fraction = fraction;
+  for (int i = 0; i < scale_shifts_size; ++i) {
+    scaled_fraction += (fraction >> scale_shifts[i]);
+  }
+  *current = '1';
+  current += 1;
+  *current = '.';
+  current += 1;
+  *current = 0;
+  current = StrCatUInt32(current, (current_end - current), scaled_fraction, 10);
+  current = StrCatStr(current, (current_end - current), "*2^");
+  current = StrCatInt32(current, (current_end - current), exponent);
+  return current;
+}
+
+}  // namespace
+
+extern "C" void DebugLogInt32(int32_t i) {
+  char number_string[kFastToBufferSize];
+  FastInt32ToBufferLeft(i, number_string);
+  DebugLog(number_string);
+}
+
+extern "C" void DebugLogUInt32(uint32_t i) {
+  char number_string[kFastToBufferSize];
+  FastUInt32ToBufferLeft(i, number_string, 10);
+  DebugLog(number_string);
+}
+
+extern "C" void DebugLogHex(uint32_t i) {
+  char number_string[kFastToBufferSize];
+  FastUInt32ToBufferLeft(i, number_string, 16);
+  DebugLog(number_string);
+}
+
+extern "C" void DebugLogFloat(float i) {
+  char number_string[kFastToBufferSize];
+  FastFloatToBufferLeft(i, number_string);
+  DebugLog(number_string);
+}

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/debug_log_numbers.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/debug_log_numbers.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,28 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_DEBUG_LOG_NUMBERS_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_DEBUG_LOG_NUMBERS_H_
+
+#include <cstdint>
+
+// Output numbers to the debug logging stream.
+extern "C" {
+void DebugLogInt32(int32_t i);
+void DebugLogUInt32(uint32_t i);
+void DebugLogHex(uint32_t i);
+void DebugLogFloat(float i);
+}
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_DEBUG_LOG_NUMBERS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/constants.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/constants.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,17 @@
+#ifndef TENSORFLOW_LITE_CONSTANTS_H_
+#define TENSORFLOW_LITE_CONSTANTS_H_
+
+// This constant represents the range of x values our model was trained on,
+// which is from 0 to (2 * Pi). We approximate Pi to avoid requiring additional
+// libraries.
+const float kXrange = 2.f * 3.14159265359f;
+
+// This constant determines the number of inferences to perform across the range
+// of x values defined above. Since each inference takes time, the higher this
+// number, the more time it will take to run through the entire range. The value
+// of this constant can be tuned so that one full cycle takes a desired amount
+// of time. Since different devices take different amounts of time to perform
+// inference, this value should be defined per-device.
+extern const int kInferencesPerCycle;
+
+#endif  // TENSORFLOW_LITE_CONSTANTS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/disco_f746ng/constants.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/disco_f746ng/constants.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,4 @@
+#include "./constants.h"
+
+// A larger number than the default to make the animation smoother
+const int kInferencesPerCycle = 70;

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/disco_f746ng/output_handler.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/disco_f746ng/output_handler.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,9 @@
+#include "./output_handler.h"
+
+
+void HandleOutput(tflite::ErrorReporter* error_reporter, float x_value,
+                  float y_value) {
+
+  // Log the current X and Y values
+  error_reporter->Report("x_value: %f, y_value: %f\n", x_value, y_value);
+}

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/inputdata.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/inputdata.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,1 @@
+float input_data[784] = {0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.003921569,0.003921569,0.0,0.0,0.0,0.003921569,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.003921569,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.007843138,0.003921569,0.0,1.0,0.9882353,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.011764706,0.9882353,0.99607843,0.99215686,1.0,1.0,0.0,0.007843138,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.99607843,0.99607843,1.0,0.42352942,0.003921569,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.99607843,0.99215686,0.45490196,0.003921569,0.003921569,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.003921569,0.0,0.8156863,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.99607843,1.0,1.0,0.6392157,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.011764706,0.0,1.0,1.0,1.0,0.0,0.0,0.011764706,0.007843138,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.89411765,1.0,1.0,0.60784316,0.0,0.0,0.003921569,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.99607843,1.0,1.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.9882353,0.99607843,0.99607843,1.0,1.0,0.99215686,0.99215686,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.99607843,0.9882353,0.0,0.7921569,1.0,0.99607843,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.9843137,0.41568628,0.007843138,0.26666668,0.99607843,1.0,0.827451,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.42745098,0.003921569,0.2509804,1.0,0.99607843,0.1254902,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.99607843,0.0,0.003921569,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,0.99215686,0.0,0.0,0.9882353,0.99607843,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,0.38431373,0.81960785,0.99607843,0.99607843,0.99607843,0.003921569,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5803922,0.99215686,0.99215686,0.9843137,1.0,1.0,1.0,0.58431375,0.003921569,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.99215686,1.0,0.99607843,1.0,1.0,1.0,0.003921569,0.003921569,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.011764706,0.8745098,0.99607843,0.99607843,0.99215686,1.0,0.0,0.015686275,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.003921569,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0};
\ No newline at end of file

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/main.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/main.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,8 @@
+#include "./main_functions.h"
+
+int main(int argc, char* argv[]) {
+  setup();
+  while (true) {
+    loop();
+  }
+}

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/main_functions.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/main_functions.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,100 @@
+#include "./main_functions.h"
+
+#include "./constants.h"
+#include "./output_handler.h"
+#include "./mnist_model_data.h"
+#include "./../../kernels/all_ops_resolver.h"
+#include "./../../micro_error_reporter.h"
+#include "./../../micro_interpreter.h"
+#include "./../../../../schema/schema_generated.h"
+#include "./../../../../version.h"
+
+#include "./inputdata.h"
+
+// Globals, used for compatibility with Arduino-style sketches.
+namespace {
+tflite::ErrorReporter* error_reporter = nullptr;
+const tflite::Model* model = nullptr;
+tflite::MicroInterpreter* interpreter = nullptr;
+TfLiteTensor* input = nullptr;
+TfLiteTensor* output = nullptr;
+
+// Create an area of memory to use for input, output, and intermediate arrays.
+// Finding the minimum value for your model may require some trial and error.
+constexpr int kTensorArenaSize = 10 * 1024;
+uint8_t tensor_arena[kTensorArenaSize];
+}  // namespace
+
+// The name of this function is important for Arduino compatibility.
+void setup() {
+  // Set up logging. Google style is to avoid globals or statics because of
+  // lifetime uncertainty, but since this has a trivial destructor it's okay.
+  // NOLINTNEXTLINE(runtime-global-variables)
+  static tflite::MicroErrorReporter micro_error_reporter;
+  error_reporter = &micro_error_reporter;
+
+  // Map the model into a usable data structure. This doesn't involve any
+  // copying or parsing, it's a very lightweight operation.
+  model = tflite::GetModel(model_quantized_tflite);
+  if (model->version() != TFLITE_SCHEMA_VERSION) {
+    error_reporter->Report(
+        "Model provided is schema version %d not equal "
+        "to supported version %d.",
+        model->version(), TFLITE_SCHEMA_VERSION);
+    return;
+  }
+
+  // This pulls in all the operation implementations we need.
+  // NOLINTNEXTLINE(runtime-global-variables)
+  static tflite::ops::micro::AllOpsResolver resolver;
+
+  // Build an interpreter to run the model with.
+  static tflite::MicroInterpreter static_interpreter(
+      model, resolver, tensor_arena, kTensorArenaSize, error_reporter);
+  interpreter = &static_interpreter;
+
+  // Allocate memory from the tensor_arena for the model's tensors.
+  TfLiteStatus allocate_status = interpreter->AllocateTensors();
+  if (allocate_status != kTfLiteOk) {
+    error_reporter->Report("AllocateTensors() failed");
+    return;
+  }
+
+  // Obtain pointers to the model's input and output tensors.
+  input = interpreter->input(0);
+  output = interpreter->output(0);
+  
+  
+  printf("HALLO\n");
+  
+}
+
+// The name of this function is important for Arduino compatibility.
+void loop() {
+
+  // Place our calculated x value in the model's input tensor
+  //input->data.f[0] = x_val;
+  for (int i = 0; i < 784; ++i) {
+    input->data.f[i] = input_data[i];
+  }
+
+  // Run inference, and report any error
+  TfLiteStatus invoke_status = interpreter->Invoke();
+  if (invoke_status != kTfLiteOk) {
+    error_reporter->Report("Invoke failed on x_val: \n");
+    return;
+  }
+  
+  float val = 0;
+  int digit = 0;
+  for (int i = 0; i < 10; ++i) {
+        float current = output->data.f[i];
+		if(current > 0.7 && current > val) {
+			val = current;
+			digit = i;
+		}
+  }
+  
+  printf("NUMBER: %d\n", digit);
+  printf("ACC: %f\n", val);
+}

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/main_functions.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/main_functions.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,13 @@
+#ifndef TENSORFLOW_LITE_MAIN_FUNCTIONS_H_
+#define TENSORFLOW_LITE_MAIN_FUNCTIONS_H_
+
+// Initializes all data needed for the example. The name is important, and needs
+// to be setup() for Arduino compatibility.
+void setup();
+
+// Runs one iteration of data gathering and inference. This should be called
+// repeatedly from the application code. The name needs to be loop() for Arduino
+// compatibility.
+void loop();
+
+#endif  // TENSORFLOW_LITE_MAIN_FUNCTIONS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/mnist_model_data.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/mnist_model_data.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,36618 @@
+#include "./mnist_model_data.h"
+
+// We need to keep the data array aligned on some architectures.
+#ifdef __has_attribute
+#define HAVE_ATTRIBUTE(x) __has_attribute(x)
+#else
+#define HAVE_ATTRIBUTE(x) 0
+#endif
+#if HAVE_ATTRIBUTE(aligned) || (defined(__GNUC__) && !defined(__clang__))
+#define DATA_ALIGN_ATTRIBUTE __attribute__((aligned(4)))
+#define DATA_ALIGN_ATTRIBUTE __attribute__((aligned(4)))
+#else
+#define DATA_ALIGN_ATTRIBUTE
+#endif
+
+const unsigned char model_quantized_tflite[] DATA_ALIGN_ATTRIBUTE = {
+    0x1c, 0x00, 0x00, 0x00, 0x54, 0x46, 0x4c, 0x33, 0x00, 0x00, 0x12, 0x00,
+    0x1c, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0c, 0x00, 0x10, 0x00, 0x14, 0x00,
+    0x00, 0x00, 0x18, 0x00, 0x12, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
+    0x34, 0xb3, 0x06, 0x00, 0x10, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00,
+    0x2c, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
+    0xe4, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0xac, 0x00, 0x00, 0x00,
+    0x0f, 0x00, 0x00, 0x00, 0x54, 0x4f, 0x43, 0x4f, 0x20, 0x43, 0x6f, 0x6e,
+    0x76, 0x65, 0x72, 0x74, 0x65, 0x64, 0x2e, 0x00, 0x0d, 0x00, 0x00, 0x00,
+    0x80, 0x00, 0x00, 0x00, 0x78, 0x00, 0x00, 0x00, 0x6c, 0x00, 0x00, 0x00,
+    0x64, 0x00, 0x00, 0x00, 0x58, 0x00, 0x00, 0x00, 0x50, 0x00, 0x00, 0x00,
+    0x48, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, 0x34, 0x00, 0x00, 0x00,
+    0x28, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
+    0x04, 0x00, 0x00, 0x00, 0x12, 0x4e, 0xf9, 0xff, 0x4c, 0x00, 0x00, 0x00,
+    0x1a, 0x4e, 0xf9, 0xff, 0x1c, 0x01, 0x00, 0x00, 0x22, 0x4e, 0xf9, 0xff,
+    0xa0, 0x01, 0x00, 0x00, 0x2a, 0x4e, 0xf9, 0xff, 0xe4, 0x0b, 0x00, 0x00,
+    0x32, 0x4e, 0xf9, 0xff, 0x40, 0x0e, 0x00, 0x00, 0xf8, 0x4d, 0xf9, 0xff,
+    0xfc, 0x4d, 0xf9, 0xff, 0x00, 0x4e, 0xf9, 0xff, 0x46, 0x4e, 0xf9, 0xff,
+    0x58, 0x2f, 0x06, 0x00, 0x0c, 0x4e, 0xf9, 0xff, 0x52, 0x4e, 0xf9, 0xff,
+    0xe4, 0x30, 0x06, 0x00, 0x18, 0x4e, 0xf9, 0xff, 0x1c, 0x4e, 0xf9, 0xff,
+    0x05, 0x00, 0x00, 0x00, 0x31, 0x2e, 0x35, 0x2e, 0x30, 0x00, 0x00, 0x00,
+    0xec, 0x4e, 0xf9, 0xff, 0x08, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x00, 0x00,
+    0x13, 0x00, 0x00, 0x00, 0x6d, 0x69, 0x6e, 0x5f, 0x72, 0x75, 0x6e, 0x74,
+    0x69, 0x6d, 0x65, 0x5f, 0x76, 0x65, 0x72, 0x73, 0x69, 0x6f, 0x6e, 0x00,
+    0x0c, 0x00, 0x14, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0c, 0x00, 0x10, 0x00,
+    0x0c, 0x00, 0x00, 0x00, 0x20, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00,
+    0x08, 0x00, 0x00, 0x00, 0xf8, 0xb0, 0x06, 0x00, 0x01, 0x00, 0x00, 0x00,
+    0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
+    0x0b, 0x00, 0x00, 0x00, 0xe0, 0x2f, 0x06, 0x00, 0x84, 0xb0, 0x06, 0x00,
+    0x40, 0x2e, 0x06, 0x00, 0xf0, 0x2d, 0x06, 0x00, 0x40, 0x0d, 0x00, 0x00,
+    0xf0, 0x0a, 0x00, 0x00, 0xfc, 0x2f, 0x06, 0x00, 0x78, 0x2e, 0x06, 0x00,
+    0x94, 0x2d, 0x06, 0x00, 0x7c, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
+    0xb2, 0x4f, 0xf9, 0xff, 0x10, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x00, 0x00,
+    0x10, 0x00, 0x00, 0x00, 0x34, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
+    0x0a, 0x00, 0x00, 0x00, 0x22, 0x00, 0x00, 0x00, 0x73, 0x65, 0x71, 0x75,
+    0x65, 0x6e, 0x74, 0x69, 0x61, 0x6c, 0x5f, 0x31, 0x34, 0x2f, 0x64, 0x65,
+    0x6e, 0x73, 0x65, 0x5f, 0x31, 0x38, 0x2f, 0x4d, 0x61, 0x74, 0x4d, 0x75,
+    0x6c, 0x5f, 0x62, 0x69, 0x61, 0x73, 0x00, 0x00, 0xf4, 0x4e, 0xf9, 0xff,
+    0x28, 0x00, 0x00, 0x00, 0xfa, 0x8e, 0x1c, 0xbd, 0x43, 0xb1, 0x68, 0x3d,
+    0x0f, 0x02, 0x87, 0xbd, 0x75, 0xe0, 0xe0, 0xbc, 0xeb, 0x26, 0x98, 0xbd,
+    0x42, 0xa3, 0x96, 0x3d, 0x14, 0x79, 0x99, 0xbd, 0xc9, 0x69, 0x2f, 0xbd,
+    0xba, 0x3d, 0x61, 0x3d, 0xde, 0xf0, 0xa2, 0x3d, 0x26, 0x50, 0xf9, 0xff,
+    0x10, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00,
+    0x4c, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00,
+    0x40, 0x00, 0x00, 0x00, 0x36, 0x00, 0x00, 0x00, 0x73, 0x65, 0x71, 0x75,
+    0x65, 0x6e, 0x74, 0x69, 0x61, 0x6c, 0x5f, 0x31, 0x34, 0x2f, 0x64, 0x65,
+    0x6e, 0x73, 0x65, 0x5f, 0x31, 0x38, 0x2f, 0x4d, 0x61, 0x74, 0x4d, 0x75,
+    0x6c, 0x2f, 0x52, 0x65, 0x61, 0x64, 0x56, 0x61, 0x72, 0x69, 0x61, 0x62,
+    0x6c, 0x65, 0x4f, 0x70, 0x2f, 0x74, 0x72, 0x61, 0x6e, 0x73, 0x70, 0x6f,
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+    0x36, 0xcc, 0x3c, 0xbe, 0x7a, 0x93, 0xd1, 0xbc, 0xbf, 0x98, 0x3d, 0x3e,
+    0x73, 0xaf, 0x25, 0x3e, 0x88, 0x78, 0xb1, 0x3d, 0x7d, 0xe8, 0x90, 0xbd,
+    0xd5, 0x53, 0x12, 0xbe, 0xc4, 0xdd, 0xc8, 0xbd, 0xe5, 0x10, 0x60, 0xbd,
+    0x67, 0x6c, 0xa0, 0x3d, 0x35, 0xd7, 0x95, 0xbd, 0xfb, 0xa4, 0x54, 0xbe,
+    0x15, 0xa1, 0x92, 0x3e, 0x6e, 0x1a, 0x73, 0x3e, 0x8a, 0x73, 0xe3, 0x3d,
+    0x2d, 0x11, 0x05, 0xbe, 0x19, 0x21, 0x16, 0x3e, 0xe3, 0x0e, 0x0c, 0x3e,
+    0x2b, 0x7a, 0x56, 0x3e, 0x21, 0x13, 0x5a, 0xbe, 0x23, 0x4d, 0x69, 0xbd,
+    0x0f, 0x55, 0xaf, 0x3d, 0x42, 0x9f, 0xd2, 0x3c, 0x6d, 0x87, 0x28, 0xbd,
+    0x8d, 0x2c, 0x93, 0x3d, 0xdd, 0xc6, 0x26, 0xbe, 0xaa, 0x14, 0x98, 0x3e,
+    0x6c, 0x44, 0xe8, 0x3c, 0xda, 0x9c, 0xb6, 0xbe, 0x0e, 0x5a, 0x80, 0xbe,
+    0x60, 0xfa, 0x32, 0xbc, 0x4f, 0x8c, 0x91, 0xbc, 0xf4, 0x12, 0x0c, 0xbe,
+    0x60, 0xa7, 0xf9, 0xbd, 0x8b, 0x58, 0x79, 0x3e, 0x6f, 0x48, 0x77, 0x3e,
+    0xa6, 0x6a, 0x01, 0x3e, 0x6b, 0x80, 0x7e, 0x3c, 0xee, 0x9e, 0xe9, 0x3d,
+    0xa1, 0x55, 0x0e, 0x3e, 0xe6, 0x7e, 0xc2, 0xbd, 0x55, 0x9f, 0xb3, 0x3d,
+    0xb3, 0x15, 0xa3, 0x3d, 0xf3, 0xa1, 0xb1, 0x3e, 0xe4, 0x36, 0x2f, 0xbe,
+    0x39, 0xee, 0x82, 0xbe, 0x53, 0x8a, 0x1a, 0x3d, 0x98, 0xb1, 0xff, 0xbd,
+    0x2a, 0x51, 0x9c, 0x3c, 0x48, 0xa5, 0x8a, 0x3c, 0x76, 0xab, 0x57, 0xbe,
+    0x42, 0x20, 0x95, 0xbd, 0x8b, 0x73, 0x4e, 0xbc, 0x5b, 0xce, 0x15, 0x3e,
+    0xb8, 0x33, 0x74, 0xbd, 0xba, 0xd7, 0x1f, 0xbb, 0x6f, 0x2c, 0x2c, 0xbe,
+    0xfa, 0x83, 0xda, 0xbd, 0x12, 0x6d, 0x5b, 0x3d, 0x72, 0x93, 0x13, 0x3e,
+    0xd7, 0x23, 0x46, 0x3d, 0x3d, 0x94, 0x92, 0x3c, 0x5c, 0x23, 0x7b, 0x3e,
+    0xc0, 0xcd, 0x8d, 0xbd, 0x39, 0x29, 0xa7, 0x3d, 0x7b, 0x6e, 0xd2, 0x3b,
+    0x4a, 0x66, 0xce, 0xbd, 0xc7, 0xb0, 0xf7, 0xbd, 0x32, 0x9a, 0xab, 0x3d,
+    0x61, 0xa7, 0xaa, 0xbd, 0x75, 0xd0, 0x39, 0x3e, 0x24, 0xb5, 0x82, 0xbb,
+    0x63, 0x35, 0x9e, 0x3d, 0x9f, 0x1e, 0x8c, 0xbd, 0x67, 0x3c, 0x0c, 0x3e,
+    0x6c, 0xcb, 0x05, 0x3e, 0x17, 0xa1, 0xae, 0x3d, 0xc2, 0x96, 0x0e, 0xbd,
+    0xff, 0x95, 0x16, 0xbe, 0x85, 0x56, 0xb3, 0x3d, 0xec, 0xcc, 0x14, 0x3e,
+    0x92, 0x5a, 0xd5, 0x3e, 0x1d, 0x1d, 0xd2, 0xbd, 0x5b, 0x1e, 0x2f, 0x3e,
+    0xc1, 0xe1, 0x28, 0xbe, 0xfe, 0xbb, 0x8b, 0xbc, 0xab, 0x87, 0xc2, 0xbd,
+    0x51, 0x99, 0xca, 0xbd, 0x05, 0x65, 0xb7, 0xbd, 0xc8, 0x33, 0x2c, 0xbd,
+    0x32, 0x3e, 0x24, 0x3d, 0x14, 0x91, 0x28, 0x3d, 0x16, 0x1d, 0xcf, 0x3d,
+    0xd9, 0xc6, 0x7c, 0x3d, 0xb3, 0xc5, 0x08, 0xbe, 0xc4, 0x3e, 0xcd, 0x3a,
+    0x81, 0xf4, 0x8d, 0xbd, 0x29, 0x25, 0x0d, 0xbe, 0x0a, 0x38, 0xb7, 0x3d,
+    0x0b, 0x09, 0x2c, 0xbe, 0x33, 0x84, 0xb9, 0xbc, 0xd7, 0x7d, 0x11, 0xbc,
+    0x8a, 0xc5, 0xbd, 0xbd, 0x1e, 0x8f, 0xf9, 0xbd, 0x56, 0x23, 0x2a, 0xbe,
+    0xc1, 0xcc, 0x8a, 0x3d, 0xd7, 0xd8, 0x97, 0x3d, 0xbd, 0x3c, 0x2b, 0x3e,
+    0x67, 0x28, 0x45, 0xbe, 0x4d, 0x8a, 0xa8, 0x3e, 0xcc, 0xeb, 0x51, 0x3e,
+    0x94, 0x19, 0x10, 0xbe, 0xc9, 0x83, 0x0c, 0x3e, 0x20, 0x6a, 0x4c, 0x3c,
+    0x82, 0xd7, 0x0b, 0x3e, 0x9d, 0xb9, 0xc2, 0xbd, 0xe1, 0xfe, 0xbf, 0x3b,
+    0xf6, 0x3e, 0x06, 0x3e, 0xbc, 0x08, 0x24, 0xbe, 0x41, 0x69, 0xb3, 0xbd,
+    0x91, 0xec, 0x9d, 0x3c, 0xf0, 0xaa, 0xa9, 0x3d, 0xd0, 0x7c, 0xb2, 0xb9,
+    0xd4, 0xde, 0x4a, 0x3e, 0xc6, 0x2a, 0x33, 0xbd, 0x3c, 0xdf, 0x39, 0xbe,
+    0xf0, 0xf4, 0xf6, 0x3d, 0x15, 0xe4, 0x05, 0xbd, 0x75, 0x98, 0x5b, 0xbe,
+    0x7b, 0x38, 0x19, 0x3d, 0x1b, 0x72, 0x28, 0x3e, 0x3d, 0x66, 0x10, 0xbe,
+    0x15, 0xb7, 0xac, 0xbd, 0xcf, 0xcb, 0x32, 0x3d, 0xa7, 0xbb, 0x54, 0xbd,
+    0x9f, 0xf5, 0x6e, 0xbe, 0x69, 0x42, 0x2a, 0xbe, 0x8b, 0xcb, 0x23, 0x3c,
+    0xf2, 0x25, 0x99, 0x3d, 0x11, 0xc4, 0xf0, 0xbd, 0x78, 0x6e, 0xcc, 0xbc,
+    0xb9, 0x6f, 0x81, 0x3e, 0x7c, 0x59, 0x7a, 0xbe, 0x33, 0x3c, 0x8e, 0x3d,
+    0xa4, 0xc4, 0x1f, 0xbd, 0xe9, 0x9d, 0x26, 0xbe, 0x5d, 0x56, 0x11, 0x3e,
+    0xaa, 0x29, 0xc5, 0x3d, 0x3d, 0x61, 0x58, 0x3d, 0x16, 0x35, 0x87, 0x3c,
+    0x87, 0x5d, 0x1b, 0x3c, 0x01, 0x03, 0x24, 0x3e, 0xee, 0x7a, 0x5f, 0xbd,
+    0x58, 0x70, 0x26, 0xbd, 0xaa, 0x66, 0xf6, 0xbc, 0x7a, 0x95, 0x17, 0x3e,
+    0xf8, 0x14, 0x65, 0xbe, 0xb8, 0x32, 0xb1, 0xbd, 0xab, 0x80, 0x15, 0xbe,
+    0x44, 0xde, 0x5b, 0x3c, 0x6d, 0x09, 0x1e, 0x3e, 0xfc, 0x6d, 0x0a, 0xbe,
+    0x76, 0xf5, 0x30, 0xbe, 0x1d, 0x17, 0x2d, 0xbe, 0xca, 0x74, 0x82, 0xbe,
+    0x57, 0x96, 0x1a, 0xbe, 0xa9, 0xa9, 0x83, 0xbe, 0x83, 0xa9, 0x81, 0x3e,
+    0x99, 0xbb, 0x71, 0x3e, 0x79, 0xfa, 0xee, 0xbd, 0xa6, 0xae, 0x08, 0xbd,
+    0xfb, 0xa2, 0x51, 0x3e, 0x8e, 0xfa, 0x77, 0xbd, 0xd9, 0x3c, 0x22, 0x3e,
+    0x1e, 0x52, 0x8d, 0x3d, 0x36, 0xb8, 0x90, 0xbd, 0x9a, 0x6d, 0xad, 0x3e,
+    0xff, 0xee, 0xd4, 0x3d, 0xc3, 0xa8, 0xa9, 0x3d, 0x04, 0x3a, 0xb5, 0x3b,
+    0x9a, 0xd3, 0x81, 0xbe, 0x65, 0x71, 0x55, 0x3d, 0xa2, 0x74, 0x2a, 0x3e,
+    0xb3, 0x34, 0x50, 0xbc, 0xc8, 0x65, 0x86, 0x3d, 0xa8, 0x4e, 0xac, 0xbe,
+    0xcf, 0x04, 0x90, 0x3d, 0x29, 0x9b, 0x45, 0x3e, 0x77, 0x88, 0x00, 0x3e,
+    0x7c, 0x75, 0xea, 0xbd, 0xae, 0xc6, 0xd6, 0xbd, 0xd7, 0x81, 0x51, 0x3e,
+    0xbe, 0x8c, 0xc7, 0x3c, 0xab, 0xc1, 0x2e, 0x3e, 0xfa, 0x87, 0x42, 0x3e,
+    0x1c, 0xe6, 0x00, 0x3d, 0x6e, 0x4c, 0xce, 0x3d, 0xb3, 0x7b, 0x28, 0x3e,
+    0x64, 0xd5, 0x20, 0x3d, 0x97, 0xfd, 0xcc, 0x3d, 0x65, 0x94, 0x18, 0xbe,
+    0x3e, 0x39, 0x09, 0x3e, 0x82, 0xb3, 0xbe, 0x3a, 0xb8, 0x11, 0x95, 0xbe,
+    0x6e, 0xbc, 0x99, 0x3d, 0x8c, 0x68, 0xf6, 0x3b, 0x91, 0x27, 0x96, 0x3d,
+    0x3a, 0xa2, 0x16, 0xbd, 0x4a, 0x8f, 0x3c, 0xbc, 0x0b, 0xab, 0x65, 0xbe,
+    0xe8, 0xed, 0x32, 0x3e, 0x17, 0xa5, 0xae, 0xbd, 0x1c, 0xe4, 0xfd, 0xbd,
+    0x6d, 0xd8, 0x05, 0x3e, 0xd3, 0x56, 0xd1, 0x3d, 0xc1, 0xf7, 0x56, 0xbe,
+    0x95, 0x02, 0x31, 0x3d, 0xe9, 0xa6, 0x8e, 0xbe, 0x33, 0xc4, 0xa8, 0xbd,
+    0xd2, 0x95, 0x8e, 0x3d, 0x07, 0x62, 0x0f, 0x3e, 0xd3, 0x50, 0x91, 0xbc,
+    0xbc, 0x8e, 0x63, 0xbe, 0x70, 0xe6, 0x2f, 0x3e, 0x47, 0xaa, 0x01, 0x3e,
+    0xfd, 0xc0, 0x25, 0x3e, 0x4a, 0xbb, 0x96, 0xbe, 0xdc, 0x87, 0x33, 0xbe,
+    0x79, 0x6c, 0x48, 0x3e, 0x92, 0x94, 0x88, 0xbd, 0x52, 0x23, 0x65, 0x3c,
+    0x83, 0x86, 0x20, 0x3d, 0xcf, 0xc0, 0x31, 0x3e, 0x74, 0x1e, 0xfd, 0xbd,
+    0x70, 0xb5, 0x92, 0xbe, 0x72, 0xf7, 0x34, 0xbe, 0x55, 0xee, 0xa2, 0x3d,
+    0xf2, 0xc6, 0xd1, 0x3d, 0xd8, 0xb1, 0xa9, 0xbe, 0xc0, 0x02, 0x1f, 0xbd,
+    0xd5, 0xf5, 0x09, 0xbd, 0x3c, 0xd3, 0x10, 0x3e, 0xd9, 0xe4, 0x9d, 0x3a,
+    0x04, 0x67, 0x6f, 0x3d, 0xc9, 0x44, 0xec, 0x3b, 0xc8, 0x13, 0x06, 0xbe,
+    0xb1, 0x99, 0xd6, 0xbd, 0x58, 0x4c, 0xa7, 0xbd, 0x8e, 0xcc, 0x05, 0xbe,
+    0xcf, 0xb1, 0xea, 0x3d, 0xa1, 0xfc, 0xce, 0xbc, 0xa4, 0x0e, 0xea, 0xbd,
+    0xaa, 0xca, 0x11, 0x3e, 0xd3, 0x78, 0x07, 0xbc, 0xea, 0x40, 0x81, 0xbd,
+    0xf0, 0xa4, 0x9d, 0x3d, 0x28, 0xdc, 0x21, 0xbe, 0xf0, 0x07, 0x79, 0xbe,
+    0xa4, 0x1c, 0x83, 0xbd, 0xd8, 0x38, 0x4b, 0xbe, 0x14, 0x57, 0xf6, 0x3d,
+    0x09, 0x96, 0x1d, 0xbd, 0x63, 0xfa, 0x54, 0x3d, 0xbd, 0x0b, 0xcf, 0xbd,
+    0x2d, 0x61, 0x30, 0x3d, 0xdb, 0xf9, 0xd1, 0x3d, 0xf4, 0xdc, 0xce, 0xbd,
+    0x2c, 0x38, 0xb6, 0xbe, 0xdb, 0xc1, 0x0d, 0x3e, 0xa1, 0x6a, 0xc1, 0xbd,
+    0xee, 0x7b, 0x99, 0xbc, 0x87, 0x96, 0x13, 0xbe, 0x37, 0x47, 0x07, 0xbe,
+    0x98, 0x24, 0xd1, 0x3d, 0xf6, 0x56, 0x01, 0xbe, 0x17, 0x24, 0x46, 0xbd,
+    0x8f, 0x5c, 0xf9, 0x3d, 0x1b, 0xa6, 0xf9, 0xbd, 0x8f, 0x7f, 0x63, 0x3d,
+    0x62, 0x49, 0x5a, 0xbe, 0xc5, 0x46, 0x95, 0xbc, 0x93, 0xb6, 0x6f, 0xbe,
+    0xa4, 0xb4, 0x02, 0x3e, 0xd7, 0x9c, 0x54, 0xbe, 0x08, 0x2c, 0xa1, 0x3d,
+    0x0c, 0x7e, 0xa2, 0xbe, 0xff, 0x5e, 0xde, 0x3d, 0x1b, 0x67, 0xd4, 0x3d,
+    0x3c, 0x6e, 0xf9, 0xbd, 0x77, 0x68, 0x90, 0xbe, 0x8a, 0xea, 0x49, 0x3e,
+    0x00, 0xc3, 0x12, 0xbd, 0x27, 0xa9, 0x3e, 0x3c, 0x58, 0xff, 0xf4, 0x3b,
+    0x0b, 0x68, 0x52, 0x3c, 0xba, 0xd1, 0x25, 0x3d, 0x1d, 0xff, 0x1b, 0xbe,
+    0xce, 0xb6, 0x41, 0xbe, 0x23, 0x2d, 0x2f, 0xbd, 0xd9, 0x98, 0xa9, 0xbd,
+    0x08, 0x87, 0xc0, 0xbc, 0xe6, 0x98, 0xeb, 0xbd, 0x1a, 0x1d, 0x9b, 0x3d,
+    0x5e, 0xf7, 0xfc, 0x3c, 0x26, 0x73, 0x18, 0xbc, 0x36, 0x86, 0xcd, 0xbd,
+    0x15, 0x12, 0x1f, 0xbe, 0x56, 0xb8, 0xa3, 0xbe, 0x74, 0x63, 0x24, 0x3d,
+    0x42, 0xb8, 0x29, 0xbe, 0x41, 0xca, 0x01, 0x3e, 0xe0, 0x29, 0x4e, 0x3e,
+    0x6b, 0x3f, 0x90, 0xbd, 0x4f, 0x16, 0x07, 0xbc, 0xc6, 0x64, 0x0f, 0xbd,
+    0x1f, 0x78, 0xd3, 0x3d, 0x65, 0xb8, 0x42, 0xbd, 0x6f, 0x7a, 0xac, 0xbd,
+    0xbc, 0x72, 0x61, 0x3e, 0x8f, 0xaa, 0x18, 0x3e, 0x30, 0x7a, 0x92, 0xbd,
+    0x45, 0xf4, 0x5e, 0x3e, 0xf1, 0x98, 0x8d, 0xbe, 0xfe, 0x7b, 0x6d, 0xbd,
+    0x86, 0x27, 0xe6, 0xbd, 0x2d, 0x94, 0xc5, 0x3d, 0xfd, 0xa5, 0xda, 0xbc,
+    0xe3, 0x9c, 0x20, 0xbd, 0x38, 0xf3, 0x3b, 0x3e, 0x29, 0xce, 0x0c, 0x3e,
+    0x00, 0x00, 0x0e, 0x00, 0x14, 0x00, 0x04, 0x00, 0x00, 0x00, 0x08, 0x00,
+    0x0c, 0x00, 0x10, 0x00, 0x0e, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
+    0x01, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x2c, 0x00, 0x00, 0x00,
+    0x02, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x10, 0x03, 0x00, 0x00,
+    0x0e, 0x00, 0x00, 0x00, 0x64, 0x65, 0x6e, 0x73, 0x65, 0x5f, 0x31, 0x36,
+    0x5f, 0x69, 0x6e, 0x70, 0x75, 0x74, 0x00, 0x00, 0x08, 0x00, 0x0c, 0x00,
+    0x04, 0x00, 0x08, 0x00, 0x08, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00,
+    0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x7f, 0x43,
+    0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
+    0xf0, 0x00, 0x00, 0x00, 0x9c, 0x00, 0x00, 0x00, 0x5c, 0x00, 0x00, 0x00,
+    0x18, 0x00, 0x00, 0x00, 0x14, 0x00, 0x1c, 0x00, 0x08, 0x00, 0x0c, 0x00,
+    0x10, 0x00, 0x07, 0x00, 0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x18, 0x00,
+    0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09, 0x01, 0x00, 0x00, 0x00,
+    0x10, 0x00, 0x00, 0x00, 0x14, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00,
+    0x14, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00,
+    0x01, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
+    0x00, 0x00, 0x06, 0x00, 0x08, 0x00, 0x04, 0x00, 0x06, 0x00, 0x00, 0x00,
+    0x00, 0x00, 0x80, 0x3f, 0x88, 0xff, 0xff, 0xff, 0x00, 0x00, 0x00, 0x08,
+    0x10, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00,
+    0x1c, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,
+    0x09, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
+    0x08, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, 0x04, 0x00,
+    0x04, 0x00, 0x00, 0x00, 0xc4, 0xff, 0xff, 0xff, 0x00, 0x00, 0x00, 0x08,
+    0x10, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00,
+    0x1c, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
+    0x06, 0x00, 0x00, 0x00, 0x07, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,
+    0x03, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x82, 0xff, 0xff, 0xff,
+    0x00, 0x00, 0x00, 0x01, 0x14, 0x00, 0x18, 0x00, 0x00, 0x00, 0x08, 0x00,
+    0x0c, 0x00, 0x07, 0x00, 0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x14, 0x00,
+    0x14, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x08, 0x10, 0x00, 0x00, 0x00,
+    0x1c, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00,
+    0x03, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
+    0x05, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00,
+    0x00, 0x00, 0x00, 0x00, 0xd2, 0xff, 0xff, 0xff, 0x00, 0x00, 0x00, 0x01,
+    0x02, 0x00, 0x00, 0x00, 0x10, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
+    0xe6, 0xff, 0xff, 0xff, 0x00, 0x00, 0x00, 0x19, 0xfa, 0xff, 0xff, 0xff,
+    0x00, 0x09, 0x06, 0x00, 0x06, 0x00, 0x05, 0x00, 0x06, 0x00, 0x00, 0x00,
+    0x00, 0x09, 0x06, 0x00, 0x08, 0x00, 0x07, 0x00, 0x06, 0x00, 0x00, 0x00,
+    0x00, 0x00, 0x00, 0x09};
+const int model_quantized_tflite_len = 439180;
+//const int model_input_shape[] = (None, 1);
+//const char model_input_dtype[] = <dtype: 'float32'>;
\ No newline at end of file

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/mnist_model_data.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/mnist_model_data.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,11 @@
+// This is a standard TensorFlow Lite model file that has been converted into a
+// C data array, so it can be easily compiled into a binary for devices that
+// don't have a file system.
+
+#ifndef TENSORFLOW_LITE_MODEL_DATA_H_
+#define TENSORFLOW_LITE_MODEL_DATA_H_
+
+extern const unsigned char model_quantized_tflite[];
+extern const int model_quantized_tflite_len;
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_EXAMPLES_HELLO_WORLD_SINE_MODEL_DATA_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/output_handler.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/examples/mnist/output_handler.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,11 @@
+#ifndef TENSORFLOW_LITE_OUTPUT_HANDLER_H_
+#define TENSORFLOW_LITE_OUTPUT_HANDLER_H_
+
+#include "./../../../../c/c_api_internal.h"
+#include "./../../../../experimental/micro/micro_error_reporter.h"
+
+// Called by the main loop to produce some output based on the x and y values
+void HandleOutput(tflite::ErrorReporter* error_reporter, float x_value,
+                  float y_value);
+
+#endif  // TENSORFLOW_LITE_OUTPUT_HANDLER_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/activation_utils.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/activation_utils.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,55 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_KERNELS_ACTIVATION_UTILS_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_KERNELS_ACTIVATION_UTILS_H_
+
+#include <algorithm>
+#include <cmath>
+#include <cstdlib>
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+
+// Returns the floating point value for a fused activation:
+inline float ActivationValFloat(TfLiteFusedActivation act, float a) {
+  switch (act) {
+    case kTfLiteActNone:
+      return a;
+    case kTfLiteActRelu:
+      return a < 0.f ? 0.f : a;
+    case kTfLiteActRelu1:
+      return a < 0.f ? 0.f : ((a > 1.f) ? 1.f : a);
+    case kTfLiteActRelu6:
+      return a < 0.f ? 0.f : ((a > 6.f) ? 6.f : a);
+    case kTfLiteActTanh:
+      return (expf(a) - expf(-a)) / (expf(a) + expf(-a));
+    case kTfLiteActSignBit:
+      return signbit(a);
+    case kTfLiteActSigmoid:
+      return 1.f / (1.f + expf(-a));
+    default:
+      return a;
+  }
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_KERNELS_ACTIVATION_UTILS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/activations.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/activations.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,178 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/experimental/micro/micro_utils.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace activations {
+
+constexpr int kInputTensor = 0;
+constexpr int kOutputTensor = 0;
+
+template <typename Q>
+inline void ReluQuantized(int32_t lower, const RuntimeShape& input_shape,
+                          const Q* input_data, const RuntimeShape& output_shape,
+                          Q* output_data) {
+  const int flat_size = MatchingFlatSize(input_shape, output_shape);
+  for (int i = 0; i < flat_size; ++i) {
+    const Q val = input_data[i];
+    const Q clamped = val < lower ? lower : val;
+    output_data[i] = clamped;
+  }
+}
+
+inline void ReluFloat(const RuntimeShape& input_shape, const float* input_data,
+                      const RuntimeShape& output_shape, float* output_data) {
+  const int flat_size = MatchingFlatSize(input_shape, output_shape);
+  for (int i = 0; i < flat_size; ++i) {
+    const float val = input_data[i];
+    const float lower = 0.0f;
+    const float clamped = val < lower ? lower : val;
+    output_data[i] = clamped;
+  }
+}
+
+inline void Relu6Float(const RuntimeShape& input_shape, const float* input_data,
+                       const RuntimeShape& output_shape, float* output_data) {
+  const int flat_size = MatchingFlatSize(input_shape, output_shape);
+  for (int i = 0; i < flat_size; ++i) {
+    const float val = input_data[i];
+    const float upper = 6.0f;
+    const float lower = 0.0f;
+    const float clamped = val > upper ? upper : val < lower ? lower : val;
+    output_data[i] = clamped;
+  }
+}
+
+template <typename Q>
+inline void Relu6Quantized(Q lower, Q upper, const RuntimeShape& input_shape,
+                           const Q* input_data,
+                           const RuntimeShape& output_shape, Q* output_data) {
+  const int flat_size = MatchingFlatSize(input_shape, output_shape);
+  for (int i = 0; i < flat_size; ++i) {
+    const Q val = input_data[i];
+    const Q clamped = val > upper ? upper : val < lower ? lower : val;
+    output_data[i] = clamped;
+  }
+}
+
+TfLiteStatus ReluPrepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+TfLiteStatus ReluEval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  switch (input->type) {
+    case kTfLiteFloat32: {
+      ReluFloat(GetTensorShape(input), GetTensorData<float>(input),
+                GetTensorShape(output), GetTensorData<float>(output));
+
+      return kTfLiteOk;
+    }
+    case kTfLiteInt8: {
+      ReluQuantized<int8_t>(input->params.zero_point, GetTensorShape(input),
+                            GetTensorData<int8_t>(input),
+                            GetTensorShape(output),
+                            GetTensorData<int8_t>(output));
+      return kTfLiteOk;
+    }
+    case kTfLiteUInt8: {
+      ReluQuantized<uint8_t>(input->params.zero_point, GetTensorShape(input),
+                             GetTensorData<uint8_t>(input),
+                             GetTensorShape(output),
+                             GetTensorData<uint8_t>(output));
+      return kTfLiteOk;
+    }
+    default: {
+      context->ReportError(context,
+                           "Only float32 is supported currently, got %s",
+                           TfLiteTypeGetName(input->type));
+      return kTfLiteError;
+    }
+  }
+}
+
+TfLiteStatus Relu6Prepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+TfLiteStatus Relu6Eval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  switch (input->type) {
+    case kTfLiteFloat32: {
+      Relu6Float(GetTensorShape(input), GetTensorData<float>(input),
+                 GetTensorShape(output), GetTensorData<float>(output));
+
+      return kTfLiteOk;
+    }
+    case kTfLiteInt8: {
+      const int8_t six = FloatToAsymmetricQuantizedInt8(
+          6.0f, input->params.scale, input->params.zero_point);
+      const int8_t zero = input->params.zero_point;
+      Relu6Quantized<int8_t>(
+          zero, six, GetTensorShape(input), GetTensorData<int8_t>(input),
+          GetTensorShape(output), GetTensorData<int8_t>(output));
+      return kTfLiteOk;
+    }
+    case kTfLiteUInt8: {
+      const uint8_t six = FloatToAsymmetricQuantizedUInt8(
+          6.0f, input->params.scale, input->params.zero_point);
+      const uint8_t zero = input->params.zero_point;
+      Relu6Quantized<uint8_t>(
+          zero, six, GetTensorShape(input), GetTensorData<uint8_t>(input),
+          GetTensorShape(output), GetTensorData<uint8_t>(output));
+      return kTfLiteOk;
+    }
+    default: {
+      context->ReportError(context,
+                           "Only float32 is supported currently, got %s",
+                           TfLiteTypeGetName(input->type));
+      return kTfLiteError;
+    }
+  }
+}
+
+}  // namespace activations
+
+TfLiteRegistration* Register_RELU() {
+  static TfLiteRegistration r = {/*init=*/nullptr,
+                                 /*free=*/nullptr, activations::ReluPrepare,
+                                 activations::ReluEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_RELU6() {
+  static TfLiteRegistration r = {/*init=*/nullptr,
+                                 /*free=*/nullptr, activations::Relu6Prepare,
+                                 activations::Relu6Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/add.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/add.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,212 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/kernels/internal/reference/add.h"
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/reference/integer_ops/add.h"
+#include "tensorflow/lite/kernels/internal/reference/process_broadcast_shapes.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace add {
+
+constexpr int kInputTensor1 = 0;
+constexpr int kInputTensor2 = 1;
+constexpr int kOutputTensor = 0;
+
+struct OpData {
+  bool requires_broadcast;
+
+  // These fields are used in both the general 8-bit -> 8bit quantized path,
+  // and the special 16-bit -> 16bit quantized path
+  int input1_shift;
+  int input2_shift;
+  int32 output_activation_min;
+  int32 output_activation_max;
+
+  // These fields are used only in the general 8-bit -> 8bit quantized path
+  int32 input1_multiplier;
+  int32 input2_multiplier;
+  int32 output_multiplier;
+  int output_shift;
+  int left_shift;
+  int32 input1_offset;
+  int32 input2_offset;
+  int32 output_offset;
+};
+
+void* Init(TfLiteContext* context, const char* buffer, size_t length) {
+  return nullptr;
+}
+
+void Free(TfLiteContext* context, void* buffer) {}
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+TfLiteStatus CalculateOpData(TfLiteContext* context, TfLiteAddParams* params,
+                             const TfLiteTensor* input1,
+                             const TfLiteTensor* input2, TfLiteTensor* output,
+                             OpData* data) {
+  data->requires_broadcast = !HaveSameShapes(input1, input2);
+
+  if (output->type == kTfLiteUInt8 || output->type == kTfLiteInt8) {
+    // 8bit -> 8bit general quantized path, with general rescalings
+    data->input1_offset = -input1->params.zero_point;
+    data->input2_offset = -input2->params.zero_point;
+    data->output_offset = output->params.zero_point;
+    data->left_shift = 20;
+    const double twice_max_input_scale =
+        2 * std::max(input1->params.scale, input2->params.scale);
+    const double real_input1_multiplier =
+        input1->params.scale / twice_max_input_scale;
+    const double real_input2_multiplier =
+        input2->params.scale / twice_max_input_scale;
+    const double real_output_multiplier =
+        twice_max_input_scale /
+        ((1 << data->left_shift) * output->params.scale);
+
+    QuantizeMultiplierSmallerThanOneExp(
+        real_input1_multiplier, &data->input1_multiplier, &data->input1_shift);
+
+    QuantizeMultiplierSmallerThanOneExp(
+        real_input2_multiplier, &data->input2_multiplier, &data->input2_shift);
+
+    QuantizeMultiplierSmallerThanOneExp(
+        real_output_multiplier, &data->output_multiplier, &data->output_shift);
+
+    if (output->type == kTfLiteUInt8) {
+      CalculateActivationRangeUint8(params->activation, output,
+                                    &data->output_activation_min,
+                                    &data->output_activation_max);
+    } else {
+      CalculateActivationRangeInt8(params->activation, output,
+                                   &data->output_activation_min,
+                                   &data->output_activation_max);
+    }
+  }
+
+  return kTfLiteOk;
+}
+
+void EvalAdd(TfLiteContext* context, TfLiteNode* node, TfLiteAddParams* params,
+             const OpData* data, const TfLiteTensor* input1,
+             const TfLiteTensor* input2, TfLiteTensor* output) {
+  float output_activation_min, output_activation_max;
+  CalculateActivationRange(params->activation, &output_activation_min,
+                           &output_activation_max);
+  tflite::ArithmeticParams op_params;
+  SetActivationParams(output_activation_min, output_activation_max, &op_params);
+#define TF_LITE_ADD(opname)                                                   \
+  reference_ops::opname(op_params, GetTensorShape(input1),                    \
+                        GetTensorData<float>(input1), GetTensorShape(input2), \
+                        GetTensorData<float>(input2), GetTensorShape(output), \
+                        GetTensorData<float>(output))
+  if (data->requires_broadcast) {
+    TF_LITE_ADD(BroadcastAdd4DSlow);
+  } else {
+    TF_LITE_ADD(Add);
+  }
+#undef TF_LITE_ADD
+}
+
+TfLiteStatus EvalAddQuantized(TfLiteContext* context, TfLiteNode* node,
+                              TfLiteAddParams* params, const OpData* data,
+                              const TfLiteTensor* input1,
+                              const TfLiteTensor* input2,
+                              TfLiteTensor* output) {
+  if (output->type == kTfLiteUInt8 || output->type == kTfLiteInt8) {
+    tflite::ArithmeticParams op_params;
+    op_params.left_shift = data->left_shift;
+    op_params.input1_offset = data->input1_offset;
+    op_params.input1_multiplier = data->input1_multiplier;
+    op_params.input1_shift = data->input1_shift;
+    op_params.input2_offset = data->input2_offset;
+    op_params.input2_multiplier = data->input2_multiplier;
+    op_params.input2_shift = data->input2_shift;
+    op_params.output_offset = data->output_offset;
+    op_params.output_multiplier = data->output_multiplier;
+    op_params.output_shift = data->output_shift;
+    SetActivationParams(data->output_activation_min,
+                        data->output_activation_max, &op_params);
+    bool need_broadcast = reference_ops::ProcessBroadcastShapes(
+        GetTensorShape(input1), GetTensorShape(input2), &op_params);
+#define TF_LITE_ADD(type, opname, dtype)                             \
+  type::opname(op_params, GetTensorShape(input1),                    \
+               GetTensorData<dtype>(input1), GetTensorShape(input2), \
+               GetTensorData<dtype>(input2), GetTensorShape(output), \
+               GetTensorData<dtype>(output));
+    if (output->type == kTfLiteInt8) {
+      if (need_broadcast) {
+        TF_LITE_ADD(reference_integer_ops, BroadcastAdd4DSlow, int8_t);
+      } else {
+        TF_LITE_ADD(reference_integer_ops, Add, int8_t);
+      }
+    } else {
+      if (need_broadcast) {
+        TF_LITE_ADD(reference_ops, BroadcastAdd4DSlow, uint8_t);
+      } else {
+        TF_LITE_ADD(reference_ops, Add, uint8_t);
+      }
+    }
+#undef TF_LITE_ADD
+  }
+
+  return kTfLiteOk;
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  auto* params = reinterpret_cast<TfLiteAddParams*>(node->builtin_data);
+
+  const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
+  const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  OpData data;
+  TF_LITE_ENSURE_STATUS(
+      CalculateOpData(context, params, input1, input2, output, &data));
+
+  if (output->type == kTfLiteFloat32) {
+    EvalAdd(context, node, params, &data, input1, input2, output);
+  } else if (output->type == kTfLiteUInt8 || output->type == kTfLiteInt8) {
+    TF_LITE_ENSURE_OK(context, EvalAddQuantized(context, node, params, &data,
+                                                input1, input2, output));
+  } else {
+    context->ReportError(context,
+                         "Inputs and outputs not all float|uint8|int8 types.");
+    return kTfLiteError;
+  }
+
+  return kTfLiteOk;
+}
+
+}  // namespace add
+
+TfLiteRegistration* Register_ADD() {
+  static TfLiteRegistration r = {add::Init, add::Free, add::Prepare, add::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/all_ops_resolver.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/all_ops_resolver.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,73 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+    http://www.apache.org/licenses/LICENSE-2.0
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/experimental/micro/kernels/all_ops_resolver.h"
+
+#include "tensorflow/lite/experimental/micro/kernels/micro_ops.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+
+AllOpsResolver::AllOpsResolver() {
+  AddBuiltin(BuiltinOperator_DEPTHWISE_CONV_2D, Register_DEPTHWISE_CONV_2D());
+  AddBuiltin(BuiltinOperator_FULLY_CONNECTED, Register_FULLY_CONNECTED(),
+             /* min_version */ 1,
+             /* max_version */ 4);
+  AddBuiltin(BuiltinOperator_MAX_POOL_2D, Register_MAX_POOL_2D());
+  AddBuiltin(BuiltinOperator_SOFTMAX, Register_SOFTMAX());
+  AddBuiltin(BuiltinOperator_LOGISTIC, Register_LOGISTIC());
+  AddBuiltin(BuiltinOperator_SVDF, Register_SVDF());
+  AddBuiltin(BuiltinOperator_CONV_2D, Register_CONV_2D());
+  AddBuiltin(BuiltinOperator_AVERAGE_POOL_2D, Register_AVERAGE_POOL_2D());
+  AddBuiltin(BuiltinOperator_ABS, Register_ABS());
+  AddBuiltin(BuiltinOperator_SIN, Register_SIN());
+  AddBuiltin(BuiltinOperator_COS, Register_COS());
+  AddBuiltin(BuiltinOperator_LOG, Register_LOG());
+  AddBuiltin(BuiltinOperator_SQRT, Register_SQRT());
+  AddBuiltin(BuiltinOperator_RSQRT, Register_RSQRT());
+  AddBuiltin(BuiltinOperator_SQUARE, Register_SQUARE());
+  AddBuiltin(BuiltinOperator_PRELU, Register_PRELU());
+  AddBuiltin(BuiltinOperator_FLOOR, Register_FLOOR());
+  AddBuiltin(BuiltinOperator_MAXIMUM, Register_MAXIMUM());
+  AddBuiltin(BuiltinOperator_MINIMUM, Register_MINIMUM());
+  AddBuiltin(BuiltinOperator_ARG_MAX, Register_ARG_MAX());
+  AddBuiltin(BuiltinOperator_ARG_MIN, Register_ARG_MIN());
+  AddBuiltin(BuiltinOperator_LOGICAL_OR, Register_LOGICAL_OR());
+  AddBuiltin(BuiltinOperator_LOGICAL_AND, Register_LOGICAL_AND());
+  AddBuiltin(BuiltinOperator_LOGICAL_NOT, Register_LOGICAL_NOT());
+  AddBuiltin(BuiltinOperator_RESHAPE, Register_RESHAPE());
+  AddBuiltin(BuiltinOperator_EQUAL, Register_EQUAL());
+  AddBuiltin(BuiltinOperator_NOT_EQUAL, Register_NOT_EQUAL());
+  AddBuiltin(BuiltinOperator_GREATER, Register_GREATER());
+  AddBuiltin(BuiltinOperator_GREATER_EQUAL, Register_GREATER_EQUAL());
+  AddBuiltin(BuiltinOperator_LESS, Register_LESS());
+  AddBuiltin(BuiltinOperator_LESS_EQUAL, Register_LESS_EQUAL());
+  AddBuiltin(BuiltinOperator_CEIL, Register_CEIL());
+  AddBuiltin(BuiltinOperator_ROUND, Register_ROUND());
+  AddBuiltin(BuiltinOperator_STRIDED_SLICE, Register_STRIDED_SLICE());
+  AddBuiltin(BuiltinOperator_PACK, Register_PACK());
+  AddBuiltin(BuiltinOperator_SPLIT, Register_SPLIT(),
+             /* min_version */ 1,
+             /* max_version */ 3);
+  AddBuiltin(BuiltinOperator_UNPACK, Register_UNPACK());
+  AddBuiltin(BuiltinOperator_NEG, Register_NEG());
+  AddBuiltin(BuiltinOperator_ADD, Register_ADD());
+  AddBuiltin(BuiltinOperator_QUANTIZE, Register_QUANTIZE(), 1, 4);
+  AddBuiltin(BuiltinOperator_DEQUANTIZE, Register_DEQUANTIZE(), 1, 4);
+  AddBuiltin(BuiltinOperator_RELU, Register_RELU());
+  AddBuiltin(BuiltinOperator_RELU6, Register_RELU6());
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/all_ops_resolver.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/all_ops_resolver.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,34 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+    http://www.apache.org/licenses/LICENSE-2.0
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_KERNELS_ALL_OPS_RESOLVER_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_KERNELS_ALL_OPS_RESOLVER_H_
+
+#include "tensorflow/lite/experimental/micro/compatibility.h"
+#include "tensorflow/lite/experimental/micro/micro_mutable_op_resolver.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+
+class AllOpsResolver : public MicroMutableOpResolver {
+ public:
+  AllOpsResolver();
+
+ private:
+  TF_LITE_REMOVE_VIRTUAL_DELETE
+};
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_KERNELS_ALL_OPS_RESOLVER_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/arg_min_max.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/arg_min_max.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,120 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/kernels/internal/reference/arg_min_max.h"
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/experimental/micro/kernels/micro_utils.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace arg_min_max {
+
+constexpr int kInputTensor = 0;
+constexpr int kAxis = 1;
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+template <typename T1, typename T2, typename T3>
+inline void ArgMinMaxHelper(const RuntimeShape& input1_shape,
+                            const T1* input1_data, const T3* input2_data,
+                            const RuntimeShape& output_shape, T2* output_data,
+                            bool is_arg_max) {
+  if (is_arg_max) {
+    reference_ops::ArgMinMax(input1_shape, input1_data, input2_data,
+                             output_shape, output_data, micro::Greater());
+  } else {
+    reference_ops::ArgMinMax(input1_shape, input1_data, input2_data,
+                             output_shape, output_data, micro::Less());
+  }
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node, bool is_arg_max) {
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  const TfLiteTensor* axis = GetInput(context, node, kAxis);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+#define TF_LITE_ARG_MIN_MAX(data_type, axis_type, output_type)            \
+  ArgMinMaxHelper(GetTensorShape(input), GetTensorData<data_type>(input), \
+                  GetTensorData<axis_type>(axis), GetTensorShape(output), \
+                  GetTensorData<output_type>(output), is_arg_max)
+  if (axis->type == kTfLiteInt32) {
+    if (output->type == kTfLiteInt32) {
+      switch (input->type) {
+        case kTfLiteFloat32:
+          TF_LITE_ARG_MIN_MAX(float, int32_t, int32_t);
+          break;
+        case kTfLiteUInt8:
+          TF_LITE_ARG_MIN_MAX(uint8_t, int32_t, int32_t);
+          break;
+        case kTfLiteInt8:
+          TF_LITE_ARG_MIN_MAX(int8_t, int32_t, int32_t);
+          break;
+        default:
+          context->ReportError(context,
+                               "Only float32, uint8 and int8 are "
+                               "supported currently, got %s.",
+                               TfLiteTypeGetName(input->type));
+          return kTfLiteError;
+      }
+    } else {
+      context->ReportError(context,
+                           "Only int32 are supported currently, got %s.",
+                           TfLiteTypeGetName(output->type));
+      return kTfLiteError;
+    }
+  } else {
+    context->ReportError(context, "Only int32 are supported currently, got %s.",
+                         TfLiteTypeGetName(axis->type));
+    return kTfLiteError;
+  }
+
+#undef TF_LITE_ARG_MIN_MAX
+
+  return kTfLiteOk;
+}
+
+TfLiteStatus ArgMinEval(TfLiteContext* context, TfLiteNode* node) {
+  return Eval(context, node, false);
+}
+
+TfLiteStatus ArgMaxEval(TfLiteContext* context, TfLiteNode* node) {
+  return Eval(context, node, true);
+}
+
+}  // namespace arg_min_max
+
+TfLiteRegistration* Register_ARG_MAX() {
+  static TfLiteRegistration r = {nullptr, nullptr, arg_min_max::Prepare,
+                                 arg_min_max::ArgMaxEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_ARG_MIN() {
+  static TfLiteRegistration r = {nullptr, nullptr, arg_min_max::Prepare,
+                                 arg_min_max::ArgMinEval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/ceil.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/ceil.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,64 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/kernels/internal/reference/ceil.h"
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace ceil {
+
+constexpr int kInputTensor = 0;
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, input->type, kTfLiteFloat32);
+  TF_LITE_ENSURE_EQ(context, output->type, input->type);
+  TF_LITE_ENSURE_EQ(context, output->bytes, input->bytes);
+  TF_LITE_ENSURE_EQ(context, output->dims->size, input->dims->size);
+  for (int i = 0; i < output->dims->size; ++i) {
+    TF_LITE_ENSURE_EQ(context, output->dims->data[i], input->dims->data[i]);
+  }
+  return kTfLiteOk;
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  reference_ops::Ceil(GetTensorShape(input), GetTensorData<float>(input),
+                      GetTensorShape(output), GetTensorData<float>(output));
+
+  return kTfLiteOk;
+}
+}  // namespace ceil
+
+TfLiteRegistration* Register_CEIL() {
+  static TfLiteRegistration r = {/*init=*/nullptr,
+                                 /*free=*/nullptr, ceil::Prepare, ceil::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/comparisons.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/comparisons.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,338 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/kernels/internal/reference/comparisons.h"
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace comparisons {
+namespace {
+
+constexpr int kInputTensor1 = 0;
+constexpr int kInputTensor2 = 1;
+constexpr int kOutputTensor = 0;
+
+// TODO(ruic): optimize macros below to using template functions.
+#define TF_LITE_QUANTIZE_COMPARISON(opname)                                    \
+  template <typename input_dtype>                                              \
+  void EvalQuantized##opname(TfLiteContext* context, TfLiteNode* node,         \
+                             const TfLiteTensor* input1,                       \
+                             const TfLiteTensor* input2, TfLiteTensor* output, \
+                             bool requires_broadcast) {                        \
+    if (input1->type == kTfLiteUInt8 || input1->type == kTfLiteInt8) {         \
+      auto input1_offset = -input1->params.zero_point;                         \
+      auto input2_offset = -input2->params.zero_point;                         \
+      const int left_shift = 8;                                                \
+                                                                               \
+      int32 input1_multiplier;                                                 \
+      int input1_shift;                                                        \
+      QuantizeMultiplierSmallerThanOneExp(input1->params.scale,                \
+                                          &input1_multiplier, &input1_shift);  \
+      int32 input2_multiplier;                                                 \
+      int input2_shift;                                                        \
+      QuantizeMultiplierSmallerThanOneExp(input2->params.scale,                \
+                                          &input2_multiplier, &input2_shift);  \
+                                                                               \
+      ComparisonParams op_params;                                              \
+      op_params.left_shift = left_shift;                                       \
+      op_params.input1_offset = input1_offset;                                 \
+      op_params.input1_multiplier = input1_multiplier;                         \
+      op_params.input1_shift = input1_shift;                                   \
+      op_params.input2_offset = input2_offset;                                 \
+      op_params.input2_multiplier = input2_multiplier;                         \
+      op_params.input2_shift = input2_shift;                                   \
+      if (requires_broadcast) {                                                \
+        reference_ops::Broadcast4DSlow##opname##WithScaling(                   \
+            op_params, GetTensorShape(input1),                                 \
+            GetTensorData<input_dtype>(input1), GetTensorShape(input2),        \
+            GetTensorData<input_dtype>(input2), GetTensorShape(output),        \
+            GetTensorData<bool>(output));                                      \
+      } else {                                                                 \
+        reference_ops::opname##WithScaling(                                    \
+            op_params, GetTensorShape(input1),                                 \
+            GetTensorData<input_dtype>(input1), GetTensorShape(input2),        \
+            GetTensorData<input_dtype>(input2), GetTensorShape(output),        \
+            GetTensorData<bool>(output));                                      \
+      }                                                                        \
+    }                                                                          \
+  }
+TF_LITE_QUANTIZE_COMPARISON(Equal);
+TF_LITE_QUANTIZE_COMPARISON(NotEqual);
+TF_LITE_QUANTIZE_COMPARISON(Greater);
+TF_LITE_QUANTIZE_COMPARISON(GreaterEqual);
+TF_LITE_QUANTIZE_COMPARISON(Less);
+TF_LITE_QUANTIZE_COMPARISON(LessEqual);
+#undef TF_LITE_QUANTIZE_COMPARISON
+
+#define TF_LITE_COMPARISON(type, opname, requires_broadcast)                  \
+  {                                                                           \
+    ComparisonParams op_params;                                               \
+    requires_broadcast                                                        \
+        ? reference_ops::Broadcast4DSlow##opname##NoScaling(                  \
+              op_params, GetTensorShape(input1), GetTensorData<type>(input1), \
+              GetTensorShape(input2), GetTensorData<type>(input2),            \
+              GetTensorShape(output), GetTensorData<bool>(output))            \
+        : reference_ops::opname##NoScaling(                                   \
+              op_params, GetTensorShape(input1), GetTensorData<type>(input1), \
+              GetTensorShape(input2), GetTensorData<type>(input2),            \
+              GetTensorShape(output), GetTensorData<bool>(output));           \
+  }
+
+TfLiteStatus EqualEval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
+  const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  bool requires_broadcast = !HaveSameShapes(input1, input2);
+  switch (input1->type) {
+    case kTfLiteBool:
+      TF_LITE_COMPARISON(bool, Equal, requires_broadcast);
+      break;
+    case kTfLiteFloat32:
+      TF_LITE_COMPARISON(float, Equal, requires_broadcast);
+      break;
+    case kTfLiteInt32:
+      TF_LITE_COMPARISON(int32_t, Equal, requires_broadcast);
+      break;
+    case kTfLiteInt64:
+      TF_LITE_COMPARISON(int64_t, Equal, requires_broadcast);
+      break;
+    case kTfLiteUInt8:
+      EvalQuantizedEqual<uint8_t>(context, node, input1, input2, output,
+                                  requires_broadcast);
+      break;
+    case kTfLiteInt8:
+      EvalQuantizedEqual<int8_t>(context, node, input1, input2, output,
+                                 requires_broadcast);
+      break;
+    default:
+      context->ReportError(
+          context, "Does not support type %d, requires bool|float|int|uint8",
+          input1->type);
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+// TODO(renjieliu): Refactor the logic to avoid duplications.
+TfLiteStatus NotEqualEval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
+  const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  bool requires_broadcast = !HaveSameShapes(input1, input2);
+  switch (input1->type) {
+    case kTfLiteBool:
+      TF_LITE_COMPARISON(bool, NotEqual, requires_broadcast);
+      break;
+    case kTfLiteFloat32:
+      TF_LITE_COMPARISON(float, NotEqual, requires_broadcast);
+      break;
+    case kTfLiteInt32:
+      TF_LITE_COMPARISON(int32_t, NotEqual, requires_broadcast);
+      break;
+    case kTfLiteInt64:
+      TF_LITE_COMPARISON(int64_t, NotEqual, requires_broadcast);
+      break;
+    case kTfLiteUInt8:
+      EvalQuantizedNotEqual<uint8_t>(context, node, input1, input2, output,
+                                     requires_broadcast);
+      break;
+    case kTfLiteInt8:
+      EvalQuantizedNotEqual<int8_t>(context, node, input1, input2, output,
+                                    requires_broadcast);
+      break;
+    default:
+      context->ReportError(
+          context, "Does not support type %d, requires bool|float|int|uint8",
+          input1->type);
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+TfLiteStatus GreaterEval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
+  const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  bool requires_broadcast = !HaveSameShapes(input1, input2);
+  switch (input1->type) {
+    case kTfLiteFloat32:
+      TF_LITE_COMPARISON(float, Greater, requires_broadcast);
+      break;
+    case kTfLiteInt32:
+      TF_LITE_COMPARISON(int32_t, Greater, requires_broadcast);
+      break;
+    case kTfLiteInt64:
+      TF_LITE_COMPARISON(int64_t, Greater, requires_broadcast);
+      break;
+    case kTfLiteUInt8:
+      EvalQuantizedGreater<uint8_t>(context, node, input1, input2, output,
+                                    requires_broadcast);
+      break;
+    case kTfLiteInt8:
+      EvalQuantizedGreater<int8_t>(context, node, input1, input2, output,
+                                   requires_broadcast);
+      break;
+    default:
+      context->ReportError(context,
+                           "Does not support type %d, requires float|int|uint8",
+                           input1->type);
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+TfLiteStatus GreaterEqualEval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
+  const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  bool requires_broadcast = !HaveSameShapes(input1, input2);
+  switch (input1->type) {
+    case kTfLiteFloat32:
+      TF_LITE_COMPARISON(float, GreaterEqual, requires_broadcast);
+      break;
+    case kTfLiteInt32:
+      TF_LITE_COMPARISON(int32_t, GreaterEqual, requires_broadcast);
+      break;
+    case kTfLiteInt64:
+      TF_LITE_COMPARISON(int64_t, GreaterEqual, requires_broadcast);
+      break;
+    case kTfLiteUInt8:
+      EvalQuantizedGreaterEqual<uint8_t>(context, node, input1, input2, output,
+                                         requires_broadcast);
+      break;
+    case kTfLiteInt8:
+      EvalQuantizedGreaterEqual<int8_t>(context, node, input1, input2, output,
+                                        requires_broadcast);
+      break;
+    default:
+      context->ReportError(context,
+                           "Does not support type %d, requires float|int|uint8",
+                           input1->type);
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+TfLiteStatus LessEval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
+  const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  bool requires_broadcast = !HaveSameShapes(input1, input2);
+  switch (input1->type) {
+    case kTfLiteFloat32:
+      TF_LITE_COMPARISON(float, Less, requires_broadcast);
+      break;
+    case kTfLiteInt32:
+      TF_LITE_COMPARISON(int32_t, Less, requires_broadcast);
+      break;
+    case kTfLiteInt64:
+      TF_LITE_COMPARISON(int64_t, Less, requires_broadcast);
+      break;
+    case kTfLiteUInt8:
+      EvalQuantizedLess<uint8_t>(context, node, input1, input2, output,
+                                 requires_broadcast);
+      break;
+    case kTfLiteInt8:
+      EvalQuantizedLess<int8_t>(context, node, input1, input2, output,
+                                requires_broadcast);
+      break;
+    default:
+      context->ReportError(context,
+                           "Does not support type %d, requires float|int|uint8",
+                           input1->type);
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+TfLiteStatus LessEqualEval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
+  const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  bool requires_broadcast = !HaveSameShapes(input1, input2);
+  switch (input1->type) {
+    case kTfLiteFloat32:
+      TF_LITE_COMPARISON(float, LessEqual, requires_broadcast);
+      break;
+    case kTfLiteInt32:
+      TF_LITE_COMPARISON(int32_t, LessEqual, requires_broadcast);
+      break;
+    case kTfLiteInt64:
+      TF_LITE_COMPARISON(int64_t, LessEqual, requires_broadcast);
+      break;
+    case kTfLiteUInt8:
+      EvalQuantizedLessEqual<uint8_t>(context, node, input1, input2, output,
+                                      requires_broadcast);
+      break;
+    case kTfLiteInt8:
+      EvalQuantizedLessEqual<int8_t>(context, node, input1, input2, output,
+                                     requires_broadcast);
+      break;
+    default:
+      context->ReportError(context,
+                           "Does not support type %d, requires float|int|uint8",
+                           input1->type);
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace
+}  // namespace comparisons
+
+TfLiteRegistration* Register_EQUAL() {
+  static TfLiteRegistration r = {nullptr, nullptr, nullptr,
+                                 comparisons::EqualEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_NOT_EQUAL() {
+  static TfLiteRegistration r = {nullptr, nullptr, nullptr,
+                                 comparisons::NotEqualEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_GREATER() {
+  static TfLiteRegistration r = {nullptr, nullptr, nullptr,
+                                 comparisons::GreaterEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_GREATER_EQUAL() {
+  static TfLiteRegistration r = {nullptr, nullptr, nullptr,
+                                 comparisons::GreaterEqualEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_LESS() {
+  static TfLiteRegistration r = {nullptr, nullptr, nullptr,
+                                 comparisons::LessEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_LESS_EQUAL() {
+  static TfLiteRegistration r = {nullptr, nullptr, nullptr,
+                                 comparisons::LessEqualEval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/conv.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/conv.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,274 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/kernels/internal/reference/conv.h"
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/reference/integer_ops/conv.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/padding.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace conv {
+
+constexpr int kInputTensor = 0;
+constexpr int kFilterTensor = 1;
+constexpr int kBiasTensor = 2;
+constexpr int kOutputTensor = 0;
+constexpr int kMaxChannels = 256;
+
+// This file has 2 implementation of Conv.
+
+const int kTensorNotAllocated = -1;
+
+struct OpData {
+  TfLitePaddingValues padding;
+  // The scaling factor from input to output (aka the 'real multiplier') can
+  // be represented as a fixed point multiplier plus a left shift.
+  int32_t output_multiplier;
+  int output_shift;
+
+  // Per channel output multiplier and shift.
+  // TODO(b/141139247): Allocate these dynamically when possible.
+  int32_t per_channel_output_multiplier[kMaxChannels];
+  int32_t per_channel_output_shift[kMaxChannels];
+
+  // The range of the fused activation layer. For example for kNone and
+  // uint8_t these would be 0 and 255.
+  int32_t output_activation_min;
+  int32_t output_activation_max;
+};
+
+inline PaddingType RuntimePaddingType(TfLitePadding padding) {
+  switch (padding) {
+    case TfLitePadding::kTfLitePaddingSame:
+      return PaddingType::kSame;
+    case TfLitePadding::kTfLitePaddingValid:
+      return PaddingType::kValid;
+    case TfLitePadding::kTfLitePaddingUnknown:
+    default:
+      return PaddingType::kNone;
+  }
+}
+
+TfLiteStatus CalculateOpData(TfLiteContext* context, TfLiteNode* node,
+                             TfLiteConvParams* params, int width, int height,
+                             int filter_width, int filter_height, int out_width,
+                             int out_height, const TfLiteType data_type,
+                             OpData* data) {
+  bool has_bias = node->inputs->size == 3;
+  // Check number of inputs/outputs
+  TF_LITE_ENSURE(context, has_bias || node->inputs->size == 2);
+  TF_LITE_ENSURE_EQ(context, node->outputs->size, 1);
+
+  // Matching GetWindowedOutputSize in TensorFlow.
+  auto padding = params->padding;
+  data->padding = ComputePaddingHeightWidth(
+      params->stride_height, params->stride_width,
+      params->dilation_height_factor, params->dilation_width_factor, height,
+      width, filter_height, filter_width, padding, &out_height, &out_width);
+
+  // Note that quantized inference requires that all tensors have their
+  // parameters set. This is usually done during quantized training.
+  if (data_type != kTfLiteFloat32) {
+    const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+    const TfLiteTensor* filter = GetInput(context, node, kFilterTensor);
+    const TfLiteTensor* bias =
+        GetOptionalInputTensor(context, node, kBiasTensor);
+    TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+    TF_LITE_ENSURE_STATUS(tflite::PopulateConvolutionQuantizationParams(
+        context, input, filter, bias, output, params->activation,
+        &data->output_multiplier, &data->output_shift,
+        &data->output_activation_min, &data->output_activation_max,
+        data->per_channel_output_multiplier,
+        reinterpret_cast<int*>(data->per_channel_output_shift)));
+  }
+  return kTfLiteOk;
+}
+
+void* Init(TfLiteContext* context, const char* buffer, size_t length) {
+  return nullptr;
+}
+
+void Free(TfLiteContext* context, void* buffer) {}
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+void EvalQuantized(TfLiteContext* context, TfLiteNode* node,
+                   TfLiteConvParams* params, OpData* data,
+                   const TfLiteTensor* input, const TfLiteTensor* filter,
+                   const TfLiteTensor* bias, TfLiteTensor* im2col,
+                   TfLiteTensor* hwcn_weights, TfLiteTensor* output) {
+  const int32_t input_offset = -input->params.zero_point;
+  const int32_t filter_offset = -filter->params.zero_point;
+  const int32_t output_offset = output->params.zero_point;
+
+  ConvParams op_params;
+  op_params.padding_type = RuntimePaddingType(params->padding);
+  op_params.padding_values.width = data->padding.width;
+  op_params.padding_values.height = data->padding.height;
+  op_params.stride_width = params->stride_width;
+  op_params.stride_height = params->stride_height;
+  op_params.dilation_width_factor = params->dilation_width_factor;
+  op_params.dilation_height_factor = params->dilation_height_factor;
+  op_params.input_offset = input_offset;
+  op_params.weights_offset = filter_offset;
+  op_params.output_offset = output_offset;
+  op_params.output_multiplier = data->output_multiplier;
+  op_params.output_shift = -data->output_shift;
+  op_params.quantized_activation_min = data->output_activation_min;
+  op_params.quantized_activation_max = data->output_activation_max;
+  reference_ops::Conv(op_params, GetTensorShape(input),
+                      GetTensorData<uint8_t>(input), GetTensorShape(filter),
+                      GetTensorData<uint8_t>(filter), GetTensorShape(bias),
+                      GetTensorData<int32_t>(bias), GetTensorShape(output),
+                      GetTensorData<uint8_t>(output), GetTensorShape(im2col),
+                      GetTensorData<uint8_t>(im2col), nullptr);
+}
+
+void EvalQuantizedPerChannel(TfLiteContext* context, TfLiteNode* node,
+                             TfLiteConvParams* params, OpData* data,
+                             const TfLiteTensor* input,
+                             const TfLiteTensor* filter,
+                             const TfLiteTensor* bias, TfLiteTensor* output,
+                             TfLiteTensor* im2col) {
+  ConvParams op_params;
+  op_params.input_offset = -input->params.zero_point;
+  op_params.output_offset = output->params.zero_point;
+  op_params.stride_height = params->stride_height;
+  op_params.stride_width = params->stride_width;
+  op_params.dilation_height_factor = params->dilation_height_factor;
+  op_params.dilation_width_factor = params->dilation_width_factor;
+  op_params.padding_values.height = data->padding.height;
+  op_params.padding_values.width = data->padding.width;
+
+  reference_integer_ops::ConvPerChannel(
+      op_params, data->per_channel_output_multiplier,
+      data->per_channel_output_shift, GetTensorShape(input),
+      GetTensorData<int8>(input), GetTensorShape(filter),
+      GetTensorData<int8>(filter), GetTensorShape(bias),
+      GetTensorData<int32>(bias), GetTensorShape(output),
+      GetTensorData<int8>(output));
+}
+
+void EvalFloat(TfLiteContext* context, TfLiteNode* node,
+               TfLiteConvParams* params, OpData* data,
+               const TfLiteTensor* input, const TfLiteTensor* filter,
+               const TfLiteTensor* bias, TfLiteTensor* im2col,
+               TfLiteTensor* hwcn_weights, TfLiteTensor* output) {
+  float output_activation_min, output_activation_max;
+  CalculateActivationRange(params->activation, &output_activation_min,
+                           &output_activation_max);
+
+  ConvParams op_params;
+  op_params.padding_type = RuntimePaddingType(params->padding);
+  op_params.padding_values.width = data->padding.width;
+  op_params.padding_values.height = data->padding.height;
+  op_params.stride_width = params->stride_width;
+  op_params.stride_height = params->stride_height;
+  op_params.dilation_width_factor = params->dilation_width_factor;
+  op_params.dilation_height_factor = params->dilation_height_factor;
+  op_params.float_activation_min = output_activation_min;
+  op_params.float_activation_max = output_activation_max;
+
+  reference_ops::Conv(op_params, GetTensorShape(input),
+                      GetTensorData<float>(input), GetTensorShape(filter),
+                      GetTensorData<float>(filter), GetTensorShape(bias),
+                      GetTensorData<float>(bias), GetTensorShape(output),
+                      GetTensorData<float>(output), GetTensorShape(im2col),
+                      GetTensorData<float>(im2col));
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  auto* params = reinterpret_cast<TfLiteConvParams*>(node->builtin_data);
+
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  const TfLiteTensor* filter = GetInput(context, node, kFilterTensor);
+  const TfLiteTensor* bias = GetOptionalInputTensor(context, node, kBiasTensor);
+
+  int input_width = input->dims->data[2];
+  int input_height = input->dims->data[1];
+  int filter_width = filter->dims->data[2];
+  int filter_height = filter->dims->data[1];
+  int output_width = output->dims->data[2];
+  int output_height = output->dims->data[1];
+
+  OpData data;
+
+  // All per-channel quantized tensors need valid zero point and scale arrays.
+  if (input->type == kTfLiteInt8) {
+    TF_LITE_ENSURE_EQ(context, filter->quantization.type,
+                      kTfLiteAffineQuantization);
+
+    const auto* affine_quantization =
+        reinterpret_cast<TfLiteAffineQuantization*>(
+            filter->quantization.params);
+    TF_LITE_ENSURE(context, affine_quantization);
+    TF_LITE_ENSURE(context, affine_quantization->scale);
+    TF_LITE_ENSURE(context, affine_quantization->zero_point);
+    // Conv is quantized along dimension 0:
+    // https://www.tensorflow.org/lite/performance/quantization_spec
+    TF_LITE_ENSURE_EQ(context, filter->dims->data[0],
+                      affine_quantization->scale->size);
+    TF_LITE_ENSURE_EQ(context, filter->dims->data[0],
+                      affine_quantization->zero_point->size);
+  }
+
+  TF_LITE_ENSURE_STATUS(CalculateOpData(
+      context, node, params, input_width, input_height, filter_width,
+      filter_height, output_width, output_height, input->type, &data));
+
+  switch (input->type) {  // Already know in/out types are same.
+    case kTfLiteFloat32:
+      EvalFloat(context, node, params, &data, input, filter, bias, nullptr,
+                nullptr, output);
+      break;
+    case kTfLiteInt8:
+      EvalQuantizedPerChannel(context, node, params, &data, input, filter, bias,
+                              output, nullptr);
+      break;
+    case kTfLiteUInt8:
+      EvalQuantized(context, node, params, &data, input, filter, bias, nullptr,
+                    nullptr, output);
+      break;
+    default:
+      context->ReportError(context, "Type %s (%d) not supported.",
+                           TfLiteTypeGetName(input->type), input->type);
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace conv
+
+TfLiteRegistration* Register_CONV_2D() {
+  static TfLiteRegistration r = {conv::Init, conv::Free, conv::Prepare,
+                                 conv::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/depthwise_conv.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/depthwise_conv.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,268 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/kernels/internal/reference/integer_ops/depthwise_conv.h"
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/reference/depthwiseconv_float.h"
+#include "tensorflow/lite/kernels/internal/reference/depthwiseconv_uint8.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/padding.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace depthwise_conv {
+namespace {
+
+constexpr int kInputTensor = 0;
+constexpr int kFilterTensor = 1;
+constexpr int kBiasTensor = 2;
+constexpr int kOutputTensor = 0;
+constexpr int kMaxChannels = 64;
+
+struct OpData {
+  TfLitePaddingValues padding;
+  // The scaling factor from input to output (aka the 'real multiplier') can
+  // be represented as a fixed point multiplier plus a left shift.
+  int32_t output_multiplier;
+  int output_shift;
+
+  // Per channel output multiplier and shift.
+  // TODO(b/141139247): Allocate these dynamically when possible.
+  int32_t per_channel_output_multiplier[kMaxChannels];
+  int32_t per_channel_output_shift[kMaxChannels];
+
+  // The range of the fused activation layer. For example for kNone and
+  // uint8_t these would be 0 and 255.
+  int32_t output_activation_min;
+  int32_t output_activation_max;
+};
+
+TfLiteStatus CalculateOpData(TfLiteContext* context, TfLiteNode* node,
+                             TfLiteDepthwiseConvParams* params, int width,
+                             int height, int filter_width, int filter_height,
+                             const TfLiteType data_type, OpData* data) {
+  bool has_bias = node->inputs->size == 3;
+  // Check number of inputs/outputs
+  TF_LITE_ENSURE(context, has_bias || node->inputs->size == 2);
+  TF_LITE_ENSURE_EQ(context, node->outputs->size, 1);
+
+  int unused_output_height, unused_output_width;
+  data->padding = ComputePaddingHeightWidth(
+      params->stride_height, params->stride_width, 1, 1, height, width,
+      filter_height, filter_width, params->padding, &unused_output_height,
+      &unused_output_width);
+
+  // Note that quantized inference requires that all tensors have their
+  // parameters set. This is usually done during quantized training.
+  if (data_type != kTfLiteFloat32) {
+    const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+    const TfLiteTensor* filter = GetInput(context, node, kFilterTensor);
+    const TfLiteTensor* bias =
+        GetOptionalInputTensor(context, node, kBiasTensor);
+    TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+    TF_LITE_ENSURE_STATUS(tflite::PopulateConvolutionQuantizationParams(
+        context, input, filter, bias, output, params->activation,
+        &data->output_multiplier, &data->output_shift,
+        &data->output_activation_min, &data->output_activation_max,
+        data->per_channel_output_multiplier,
+        reinterpret_cast<int*>(data->per_channel_output_shift)));
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace
+
+void* Init(TfLiteContext* context, const char* buffer, size_t length) {
+  return nullptr;
+}
+
+void Free(TfLiteContext* context, void* buffer) {}
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+void EvalFloat(TfLiteContext* context, TfLiteNode* node,
+               TfLiteDepthwiseConvParams* params, OpData* data,
+               const TfLiteTensor* input, const TfLiteTensor* filter,
+               const TfLiteTensor* bias, TfLiteTensor* output) {
+  float output_activation_min, output_activation_max;
+  CalculateActivationRange(params->activation, &output_activation_min,
+                           &output_activation_max);
+
+  tflite::DepthwiseParams op_params;
+  // Padding type is ignored, but still set.
+  op_params.padding_type = PaddingType::kSame;
+  op_params.padding_values.width = data->padding.width;
+  op_params.padding_values.height = data->padding.height;
+  op_params.stride_width = params->stride_width;
+  op_params.stride_height = params->stride_height;
+  op_params.dilation_width_factor = 1;
+  op_params.dilation_height_factor = 1;
+  op_params.depth_multiplier = params->depth_multiplier;
+  op_params.float_activation_min = output_activation_min;
+  op_params.float_activation_max = output_activation_max;
+
+  tflite::reference_ops::DepthwiseConv(
+      op_params, GetTensorShape(input), GetTensorData<float>(input),
+      GetTensorShape(filter), GetTensorData<float>(filter),
+      GetTensorShape(bias), GetTensorData<float>(bias), GetTensorShape(output),
+      GetTensorData<float>(output));
+}
+
+void EvalQuantizedPerChannel(TfLiteContext* context, TfLiteNode* node,
+                             TfLiteDepthwiseConvParams* params, OpData* data,
+                             const TfLiteTensor* input,
+                             const TfLiteTensor* filter,
+                             const TfLiteTensor* bias, TfLiteTensor* output) {
+  DepthwiseParams op_params;
+  op_params.padding_type = PaddingType::kSame;
+  op_params.padding_values.width = data->padding.width;
+  op_params.padding_values.height = data->padding.height;
+  op_params.stride_width = params->stride_width;
+  op_params.stride_height = params->stride_height;
+  op_params.dilation_width_factor = params->dilation_width_factor;
+  op_params.dilation_height_factor = params->dilation_height_factor;
+  op_params.depth_multiplier = params->depth_multiplier;
+  op_params.input_offset = -input->params.zero_point;
+  op_params.weights_offset = 0;
+  op_params.output_offset = output->params.zero_point;
+  // TODO(b/130439627): Use calculated value for clamping.
+  op_params.quantized_activation_min = std::numeric_limits<int8_t>::min();
+  op_params.quantized_activation_max = std::numeric_limits<int8_t>::max();
+
+  reference_integer_ops::DepthwiseConvPerChannel(
+      op_params, data->per_channel_output_multiplier,
+      data->per_channel_output_shift, GetTensorShape(input),
+      GetTensorData<int8>(input), GetTensorShape(filter),
+      GetTensorData<int8>(filter), GetTensorShape(bias),
+      GetTensorData<int32>(bias), GetTensorShape(output),
+      GetTensorData<int8>(output));
+}
+
+void EvalQuantized(TfLiteContext* context, TfLiteNode* node,
+                   TfLiteDepthwiseConvParams* params, OpData* data,
+                   const TfLiteTensor* input, const TfLiteTensor* filter,
+                   const TfLiteTensor* bias, TfLiteTensor* output) {
+  const int32_t input_offset = -input->params.zero_point;
+  const int32_t filter_offset = -filter->params.zero_point;
+  const int32_t output_offset = output->params.zero_point;
+
+  tflite::DepthwiseParams op_params;
+  // Padding type is ignored, but still set.
+  op_params.padding_type = PaddingType::kSame;
+  op_params.padding_values.width = data->padding.width;
+  op_params.padding_values.height = data->padding.height;
+  op_params.stride_width = params->stride_width;
+  op_params.stride_height = params->stride_height;
+  op_params.dilation_width_factor = 1;
+  op_params.dilation_height_factor = 1;
+  op_params.depth_multiplier = params->depth_multiplier;
+  op_params.quantized_activation_min = data->output_activation_min;
+  op_params.quantized_activation_max = data->output_activation_max;
+  op_params.input_offset = input_offset;
+  op_params.weights_offset = filter_offset;
+  op_params.output_offset = output_offset;
+  op_params.output_multiplier = data->output_multiplier;
+  // Legacy ops used mixed left and right shifts. Now all are +ve-means-left.
+  op_params.output_shift = -data->output_shift;
+
+  tflite::reference_ops::DepthwiseConv(
+      op_params, GetTensorShape(input), GetTensorData<uint8_t>(input),
+      GetTensorShape(filter), GetTensorData<uint8_t>(filter),
+      GetTensorShape(bias), GetTensorData<int32_t>(bias),
+      GetTensorShape(output), GetTensorData<uint8_t>(output));
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  auto* params =
+      reinterpret_cast<TfLiteDepthwiseConvParams*>(node->builtin_data);
+
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  const TfLiteTensor* filter = GetInput(context, node, kFilterTensor);
+  const TfLiteTensor* bias =
+      (NumInputs(node) == 3) ? GetInput(context, node, kBiasTensor) : nullptr;
+
+  const TfLiteType data_type = input->type;
+  int width = SizeOfDimension(input, 2);
+  int height = SizeOfDimension(input, 1);
+  int filter_width = SizeOfDimension(filter, 2);
+  int filter_height = SizeOfDimension(filter, 1);
+
+  OpData data;
+
+  // All per-channel quantized tensors need valid zero point and scale arrays.
+  if (input->type == kTfLiteInt8) {
+    TF_LITE_ENSURE_EQ(context, filter->quantization.type,
+                      kTfLiteAffineQuantization);
+
+    const auto* affine_quantization =
+        reinterpret_cast<TfLiteAffineQuantization*>(
+            filter->quantization.params);
+    TF_LITE_ENSURE(context, affine_quantization);
+    TF_LITE_ENSURE(context, affine_quantization->scale);
+    TF_LITE_ENSURE(context, affine_quantization->zero_point);
+    // Depthwise conv is quantized along dimension 3:
+    // https://www.tensorflow.org/lite/performance/quantization_spec
+    TF_LITE_ENSURE_EQ(context, filter->dims->data[3],
+                      affine_quantization->scale->size);
+    TF_LITE_ENSURE_EQ(context, filter->dims->data[3],
+                      affine_quantization->zero_point->size);
+  }
+
+  TF_LITE_ENSURE_STATUS(CalculateOpData(context, node, params, width, height,
+                                        filter_width, filter_height, data_type,
+                                        &data));
+
+  // TODO(aselle): Consider whether float conv and quantized conv should be
+  // separate ops to avoid dispatch overhead here.
+  switch (input->type) {  // Already know in/out types are same.
+    case kTfLiteFloat32:
+      EvalFloat(context, node, params, &data, input, filter, bias, output);
+      break;
+    case kTfLiteInt8:
+      EvalQuantizedPerChannel(context, node, params, &data, input, filter, bias,
+                              output);
+      break;
+    case kTfLiteUInt8:
+      EvalQuantized(context, node, params, &data, input, filter, bias, output);
+      break;
+    default:
+      context->ReportError(context, "Type %s (%d) not supported.",
+                           TfLiteTypeGetName(input->type), input->type);
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace depthwise_conv
+
+TfLiteRegistration* Register_DEPTHWISE_CONV_2D() {
+  static TfLiteRegistration r = {depthwise_conv::Init, depthwise_conv::Free,
+                                 depthwise_conv::Prepare, depthwise_conv::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/dequantize.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/dequantize.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,80 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/kernels/internal/reference/dequantize.h"
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace dequantize {
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+
+  // TODO(b/140515557): Add cached dequant to improve hybrid model performance.
+  TfLiteTensor* input = &context->tensors[node->inputs->data[0]];
+  TfLiteTensor* output = &context->tensors[node->outputs->data[0]];
+
+  TF_LITE_ENSURE(context,
+                 input->type == kTfLiteUInt8 || input->type == kTfLiteInt8);
+  TF_LITE_ENSURE(context, output->type == kTfLiteFloat32);
+
+  return kTfLiteOk;
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  TfLiteTensor* input = &context->tensors[node->inputs->data[0]];
+  TfLiteTensor* output = &context->tensors[node->outputs->data[0]];
+
+  tflite::DequantizationParams op_params;
+  op_params.zero_point = input->params.zero_point;
+  op_params.scale = input->params.scale;
+  switch (input->type) {
+    case kTfLiteUInt8:
+      reference_ops::Dequantize(
+          op_params, GetTensorShape(input), GetTensorData<uint8_t>(input),
+          GetTensorShape(output), GetTensorData<float>(output));
+      break;
+    case kTfLiteInt8:
+      reference_ops::Dequantize(
+          op_params, GetTensorShape(input), GetTensorData<int8_t>(input),
+          GetTensorShape(output), GetTensorData<float>(output));
+      break;
+    default:
+      context->ReportError(context, "Type %s (%d) not supported.",
+                           TfLiteTypeGetName(input->type), input->type);
+      return kTfLiteError;
+  }
+
+  return kTfLiteOk;
+}
+
+}  // namespace dequantize
+
+TfLiteRegistration* Register_DEQUANTIZE() {
+  static TfLiteRegistration r = {nullptr, nullptr, dequantize::Prepare,
+                                 dequantize::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/elementwise.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/elementwise.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,178 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include <cmath>
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace elementwise {
+namespace {
+
+bool IsNumericSupportedType(const TfLiteType type) {
+  return type == kTfLiteFloat32;
+}
+
+bool IsLogicalSupportedType(const TfLiteType type) {
+  return type == kTfLiteBool;
+}
+
+typedef bool (*IsSupportedType)(TfLiteType);
+template <IsSupportedType>
+TfLiteStatus GenericPrepare(TfLiteContext* context, TfLiteNode* node) {
+  TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+  const TfLiteTensor* input = GetInput(context, node, 0);
+  TfLiteTensor* output = GetOutput(context, node, 0);
+  TF_LITE_ENSURE_EQ(context, input->type, output->type);
+  if (!IsSupportedType(input->type)) {
+    context->ReportError(context, "Input data type %s (%d) is not supported.",
+                         TfLiteTypeGetName(input->type), input->type);
+    return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+template <typename T>
+inline TfLiteStatus EvalImpl(TfLiteContext* context, TfLiteNode* node,
+                             T func(T), TfLiteType expected_type) {
+  const TfLiteTensor* input = GetInput(context, node, 0);
+  TfLiteTensor* output = GetOutput(context, node, 0);
+  TF_LITE_ENSURE_EQ(context, input->type, expected_type);
+  const int64_t num_elements = NumElements(input);
+  const T* in_data = GetTensorData<T>(input);
+  T* out_data = GetTensorData<T>(output);
+  for (int64_t i = 0; i < num_elements; ++i) {
+    out_data[i] = func(in_data[i]);
+  }
+  return kTfLiteOk;
+}
+
+inline TfLiteStatus EvalNumeric(TfLiteContext* context, TfLiteNode* node,
+                                float float_func(float)) {
+  return EvalImpl<float>(context, node, float_func, kTfLiteFloat32);
+}
+
+inline TfLiteStatus EvalLogical(TfLiteContext* context, TfLiteNode* node,
+                                bool bool_func(bool)) {
+  return EvalImpl<bool>(context, node, bool_func, kTfLiteBool);
+}
+
+TfLiteStatus AbsEval(TfLiteContext* context, TfLiteNode* node) {
+  return EvalNumeric(context, node, std::abs);
+}
+
+TfLiteStatus SinEval(TfLiteContext* context, TfLiteNode* node) {
+  return EvalNumeric(context, node, std::sin);
+}
+
+TfLiteStatus CosEval(TfLiteContext* context, TfLiteNode* node) {
+  return EvalNumeric(context, node, std::cos);
+}
+
+TfLiteStatus LogEval(TfLiteContext* context, TfLiteNode* node) {
+  return EvalNumeric(context, node, std::log);
+}
+
+TfLiteStatus SqrtEval(TfLiteContext* context, TfLiteNode* node) {
+  return EvalNumeric(context, node, std::sqrt);
+}
+
+TfLiteStatus RsqrtEval(TfLiteContext* context, TfLiteNode* node) {
+  return EvalNumeric(context, node, [](float f) { return 1.f / std::sqrt(f); });
+}
+
+TfLiteStatus SquareEval(TfLiteContext* context, TfLiteNode* node) {
+  return EvalNumeric(context, node, [](float f) { return f * f; });
+}
+
+TfLiteStatus LogicalNotEval(TfLiteContext* context, TfLiteNode* node) {
+  return EvalLogical(context, node, [](bool v) { return !v; });
+}
+
+}  // namespace
+}  // namespace elementwise
+
+TfLiteRegistration* Register_ABS() {
+  static TfLiteRegistration r = {
+      /* init */ nullptr, /* free */ nullptr,
+      elementwise::GenericPrepare<elementwise::IsNumericSupportedType>,
+      elementwise::AbsEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_SIN() {
+  static TfLiteRegistration r = {
+      /* init */ nullptr, /* free */ nullptr,
+      elementwise::GenericPrepare<elementwise::IsNumericSupportedType>,
+      elementwise::SinEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_COS() {
+  static TfLiteRegistration r = {
+      /* init */ nullptr, /* free */ nullptr,
+      elementwise::GenericPrepare<elementwise::IsNumericSupportedType>,
+      elementwise::CosEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_LOG() {
+  static TfLiteRegistration r = {
+      /* init */ nullptr, /* free */ nullptr,
+      elementwise::GenericPrepare<elementwise::IsNumericSupportedType>,
+      elementwise::LogEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_SQRT() {
+  static TfLiteRegistration r = {
+      /* init */ nullptr, /* free */ nullptr,
+      elementwise::GenericPrepare<elementwise::IsNumericSupportedType>,
+      elementwise::SqrtEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_RSQRT() {
+  static TfLiteRegistration r = {
+      /* init */ nullptr, /* free */ nullptr,
+      elementwise::GenericPrepare<elementwise::IsNumericSupportedType>,
+      elementwise::RsqrtEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_SQUARE() {
+  static TfLiteRegistration r = {
+      /* init */ nullptr, /* free */ nullptr,
+      elementwise::GenericPrepare<elementwise::IsNumericSupportedType>,
+      elementwise::SquareEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_LOGICAL_NOT() {
+  static TfLiteRegistration r = {
+      /*init=*/nullptr, /*free=*/nullptr,
+      elementwise::GenericPrepare<elementwise::IsLogicalSupportedType>,
+      elementwise::LogicalNotEval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/floor.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/floor.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,48 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/reference/floor.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace floor {
+
+constexpr int kInputTensor = 0;
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TF_LITE_ENSURE_EQ(context, input->type, kTfLiteFloat32);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  reference_ops::Floor(GetTensorShape(input), GetTensorData<float>(input),
+                       GetTensorShape(output), GetTensorData<float>(output));
+  return kTfLiteOk;
+}
+}  // namespace floor
+
+TfLiteRegistration* Register_FLOOR() {
+  static TfLiteRegistration r = {/*init=*/nullptr,
+                                 /*free=*/nullptr, /*prepare=*/nullptr,
+                                 floor::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/fully_connected.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/fully_connected.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,212 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/kernels/internal/reference/fully_connected.h"
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/reference/integer_ops/fully_connected.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace fully_connected {
+namespace {
+
+struct OpData {
+  // The scaling factor from input to output (aka the 'real multiplier') can
+  // be represented as a fixed point multiplier plus a left shift.
+  int32_t output_multiplier;
+  int output_shift;
+  // The range of the fused activation layer. For example for kNone and
+  // uint8_t these would be 0 and 255.
+  int32_t output_activation_min;
+  int32_t output_activation_max;
+  // The index of the temporary tensor where the quantized inputs are cached.
+  int input_quantized_index;
+};
+
+constexpr int kInputTensor = 0;
+constexpr int kWeightsTensor = 1;
+constexpr int kBiasTensor = 2;
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus CalculateOpData(TfLiteContext* context,
+                             TfLiteFullyConnectedParams* params,
+                             TfLiteType data_type, const TfLiteTensor* input,
+                             const TfLiteTensor* filter,
+                             const TfLiteTensor* bias, TfLiteTensor* output,
+                             OpData* data) {
+  TfLiteStatus status = kTfLiteOk;
+  if (data_type != kTfLiteFloat32) {
+    double real_multiplier = 0.0;
+    TF_LITE_ENSURE_STATUS(GetQuantizedConvolutionMultipler(
+        context, input, filter, bias, output, &real_multiplier));
+    int exponent;
+    QuantizeMultiplier(real_multiplier, &data->output_multiplier, &exponent);
+    data->output_shift = -exponent;
+    TF_LITE_ENSURE_STATUS(CalculateActivationRangeQuantized(
+        context, params->activation, output, &data->output_activation_min,
+        &data->output_activation_max));
+  }
+  return status;
+}
+
+}  // namespace
+
+void* Init(TfLiteContext* context, const char* buffer, size_t length) {
+  return nullptr;
+}
+
+void Free(TfLiteContext* context, void* buffer) {}
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+TfLiteStatus EvalQuantizedInt8(TfLiteContext* context, TfLiteNode* node,
+                               TfLiteFullyConnectedParams* params, OpData* data,
+                               const TfLiteTensor* input,
+                               const TfLiteTensor* filter,
+                               const TfLiteTensor* bias, TfLiteTensor* output) {
+  FullyConnectedParams op_params;
+  op_params.input_offset = -input->params.zero_point;
+  op_params.weights_offset = -filter->params.zero_point;
+  op_params.output_offset = output->params.zero_point;
+  op_params.output_multiplier = data->output_multiplier;
+  // TODO(b/138810107): Figure out whether output shift should be inverted
+  op_params.output_shift = -data->output_shift;
+  op_params.quantized_activation_min = data->output_activation_min;
+  op_params.quantized_activation_max = data->output_activation_max;
+
+  reference_integer_ops::FullyConnected(
+      op_params, GetTensorShape(input), GetTensorData<int8_t>(input),
+      GetTensorShape(filter), GetTensorData<int8_t>(filter),
+      GetTensorShape(bias), GetTensorData<int32_t>(bias),
+      GetTensorShape(output), GetTensorData<int8_t>(output));
+  return kTfLiteOk;
+}
+
+TfLiteStatus EvalQuantized(TfLiteContext* context, TfLiteNode* node,
+                           TfLiteFullyConnectedParams* params, OpData* data,
+                           const TfLiteTensor* input,
+                           const TfLiteTensor* filter, const TfLiteTensor* bias,
+                           TfLiteTensor* output) {
+  const int32_t input_offset = -input->params.zero_point;
+  const int32_t filter_offset = -filter->params.zero_point;
+  const int32_t output_offset = output->params.zero_point;
+
+  tflite::FullyConnectedParams op_params;
+  op_params.input_offset = input_offset;
+  op_params.weights_offset = filter_offset;
+  op_params.output_offset = output_offset;
+  op_params.output_multiplier = data->output_multiplier;
+  // Legacy ops used mixed left and right shifts. Now all are +ve-means-left.
+  op_params.output_shift = -data->output_shift;
+  op_params.quantized_activation_min = data->output_activation_min;
+  op_params.quantized_activation_max = data->output_activation_max;
+
+#define TF_LITE_FULLY_CONNECTED(output_data_type)                      \
+  reference_ops::FullyConnected(                                       \
+      op_params, GetTensorShape(input), GetTensorData<uint8_t>(input), \
+      GetTensorShape(filter), GetTensorData<uint8_t>(filter),          \
+      GetTensorShape(bias), GetTensorData<int32_t>(bias),              \
+      GetTensorShape(output), GetTensorData<output_data_type>(output))
+  switch (output->type) {
+    case kTfLiteUInt8:
+      TF_LITE_FULLY_CONNECTED(uint8_t);
+      break;
+    case kTfLiteInt16:
+      TF_LITE_FULLY_CONNECTED(int16_t);
+      break;
+    default:
+      context->ReportError(
+          context,
+          "Quantized FullyConnected expects output data type uint8 or int16");
+      return kTfLiteError;
+  }
+
+  return kTfLiteOk;
+}
+
+TfLiteStatus EvalFloat(TfLiteContext* context, TfLiteNode* node,
+                       TfLiteFullyConnectedParams* params, OpData* data,
+                       const TfLiteTensor* input, const TfLiteTensor* filter,
+                       const TfLiteTensor* bias, TfLiteTensor* output) {
+  float output_activation_min, output_activation_max;
+  CalculateActivationRange(params->activation, &output_activation_min,
+                           &output_activation_max);
+  tflite::FullyConnectedParams op_params;
+  op_params.float_activation_min = output_activation_min;
+  op_params.float_activation_max = output_activation_max;
+  tflite::reference_ops::FullyConnected(
+      op_params, GetTensorShape(input), GetTensorData<float>(input),
+      GetTensorShape(filter), GetTensorData<float>(filter),
+      GetTensorShape(bias), GetTensorData<float>(bias), GetTensorShape(output),
+      GetTensorData<float>(output));
+  return kTfLiteOk;
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  auto* params =
+      reinterpret_cast<TfLiteFullyConnectedParams*>(node->builtin_data);
+
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  const TfLiteTensor* filter = GetInput(context, node, kWeightsTensor);
+  const TfLiteTensor* bias = GetOptionalInputTensor(context, node, kBiasTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  TfLiteType data_type = input->type;
+  OpData local_data_object;
+  OpData* data = &local_data_object;
+  TF_LITE_ENSURE_STATUS(CalculateOpData(context, params, data_type, input,
+                                        filter, bias, output, data));
+
+  switch (filter->type) {  // Already know in/out types are same.
+    case kTfLiteFloat32:
+      return EvalFloat(context, node, params, data, input, filter, bias,
+                       output);
+    case kTfLiteInt8:
+      return EvalQuantizedInt8(context, node, params, data, input, filter, bias,
+                               output);
+
+    case kTfLiteUInt8:
+      return EvalQuantized(context, node, params, data, input, filter, bias,
+                           output);
+
+    default:
+      context->ReportError(context, "Type %d not currently supported.",
+                           filter->type);
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace fully_connected
+
+TfLiteRegistration* Register_FULLY_CONNECTED() {
+  static TfLiteRegistration r = {fully_connected::Init, fully_connected::Free,
+                                 fully_connected::Prepare,
+                                 fully_connected::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/logical.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/logical.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,87 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/reference/binary_function.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace logical {
+namespace {
+
+// Input/output tensor index.
+constexpr int kInputTensor1 = 0;
+constexpr int kInputTensor2 = 1;
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus LogicalImpl(TfLiteContext* context, TfLiteNode* node,
+                         bool (*func)(bool, bool)) {
+  const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
+  const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  if (HaveSameShapes(input1, input2)) {
+    reference_ops::BinaryFunction<bool, bool, bool>(
+        GetTensorShape(input1), GetTensorData<bool>(input1),
+        GetTensorShape(input2), GetTensorData<bool>(input2),
+        GetTensorShape(output), GetTensorData<bool>(output), func);
+  } else {
+    reference_ops::BroadcastBinaryFunction4DSlow<bool, bool, bool>(
+        GetTensorShape(input1), GetTensorData<bool>(input1),
+        GetTensorShape(input2), GetTensorData<bool>(input2),
+        GetTensorShape(output), GetTensorData<bool>(output), func);
+  }
+
+  return kTfLiteOk;
+}
+
+bool LogicalOr(bool x, bool y) { return x || y; }
+
+TfLiteStatus LogicalOrEval(TfLiteContext* context, TfLiteNode* node) {
+  return LogicalImpl(context, node, LogicalOr);
+}
+
+bool LogicalAnd(bool x, bool y) { return x && y; }
+
+TfLiteStatus LogicalAndEval(TfLiteContext* context, TfLiteNode* node) {
+  return LogicalImpl(context, node, LogicalAnd);
+}
+
+}  // namespace
+}  // namespace logical
+
+TfLiteRegistration* Register_LOGICAL_OR() {
+  // Init, Free, Prepare, Eval are satisfying the Interface required by
+  // TfLiteRegistration.
+  static TfLiteRegistration r = {/* init */ nullptr, /* free */ nullptr,
+                                 /* prepare */ nullptr, logical::LogicalOrEval};
+  return &r;
+}
+
+TfLiteRegistration* Register_LOGICAL_AND() {
+  // Init, Free, Prepare, Eval are satisfying the Interface required by
+  // TfLiteRegistration.
+  static TfLiteRegistration r = {/* init */ nullptr, /* free */ nullptr,
+                                 /* prepare */ nullptr,
+                                 logical::LogicalAndEval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/logistic.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/logistic.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,70 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/kernels/internal/reference/logistic.h"
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace activations {
+
+constexpr int kInputTensor = 0;
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  switch (input->type) {
+    case kTfLiteFloat32: {
+      reference_ops::Logistic(
+          GetTensorShape(input), GetTensorData<float>(input),
+          GetTensorShape(output), GetTensorData<float>(output));
+      return kTfLiteOk;
+    }
+    default: {
+      // TODO(b/141211002): Also support other data types once we have supported
+      // temporary tensors in TFLM.
+      context->ReportError(context,
+                           "Only float32 is supported currently, got %s",
+                           TfLiteTypeGetName(input->type));
+      return kTfLiteError;
+    }
+  }
+}
+
+}  // namespace activations
+
+TfLiteRegistration* Register_LOGISTIC() {
+  static TfLiteRegistration r = {/*init=*/nullptr,
+                                 /*free=*/nullptr, activations::Prepare,
+                                 activations::Eval};
+  return &r;
+}
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/maximum_minimum.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/maximum_minimum.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,141 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/kernels/internal/reference/maximum_minimum.h"
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace maximum_minimum {
+namespace {
+
+// This file has a reference implementation of TFMaximum/TFMinimum.
+enum KernelType {
+  kReference,
+};
+
+constexpr int kInputTensor1 = 0;
+constexpr int kInputTensor2 = 1;
+constexpr int kOutputTensor = 0;
+
+struct OpContext {
+  OpContext(TfLiteContext* context, TfLiteNode* node) {
+    input1 = GetInput(context, node, kInputTensor1);
+    input2 = GetInput(context, node, kInputTensor2);
+    output = GetOutput(context, node, kOutputTensor);
+  }
+  const TfLiteTensor* input1;
+  const TfLiteTensor* input2;
+  TfLiteTensor* output;
+};
+
+struct MaximumOp {
+  template <typename data_type>
+  static data_type op(data_type el1, data_type el2) {
+    return el1 > el2 ? el1 : el2;
+  }
+};
+
+struct MinimumOp {
+  template <typename data_type>
+  static data_type op(data_type el1, data_type el2) {
+    return el1 < el2 ? el1 : el2;
+  }
+};
+
+}  // namespace
+
+template <typename data_type, typename op_type>
+void TFLiteOperation(TfLiteContext* context, TfLiteNode* node,
+                     const OpContext& op_context) {
+  reference_ops::MaximumMinimumBroadcast4DSlow(
+      GetTensorShape(op_context.input1),
+      GetTensorData<data_type>(op_context.input1),
+      GetTensorShape(op_context.input2),
+      GetTensorData<data_type>(op_context.input2),
+      GetTensorShape(op_context.output),
+      GetTensorData<data_type>(op_context.output),
+      op_type::template op<data_type>);
+}
+
+template <KernelType kernel_type, typename OpType>
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  OpContext op_context(context, node);
+
+  if (kernel_type == kReference) {
+    switch (op_context.output->type) {
+      case kTfLiteFloat32:
+        TFLiteOperation<float, OpType>(context, node, op_context);
+        break;
+      case kTfLiteUInt8:
+        TFLiteOperation<uint8_t, OpType>(context, node, op_context);
+        break;
+      case kTfLiteInt8:
+        TFLiteOperation<int8_t, OpType>(context, node, op_context);
+        break;
+      case kTfLiteInt32:
+        TFLiteOperation<int32_t, OpType>(context, node, op_context);
+        break;
+      case kTfLiteInt64:
+        TFLiteOperation<int64_t, OpType>(context, node, op_context);
+        break;
+      default:
+        context->ReportError(
+            context, "Type %s (%d) is not supported by Maximum/Minimum.",
+            TfLiteTypeGetName(op_context.output->type),
+            op_context.output->type);
+        return kTfLiteError;
+    }
+  } else {
+    context->ReportError(context,
+                         "Kernel type not supported by Maximum/Minimum.");
+    return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace maximum_minimum
+
+TfLiteRegistration* Register_MAXIMUM() {
+  static TfLiteRegistration r = {
+      /* init */ nullptr,
+      /* free */ nullptr,
+      /* prepare */ nullptr,
+      maximum_minimum::Eval<maximum_minimum::kReference,
+                            maximum_minimum::MaximumOp>};
+  return &r;
+}
+
+TfLiteRegistration* Register_MINIMUM() {
+  static TfLiteRegistration r = {
+      /* init */ nullptr,
+      /* free */ nullptr,
+      /* prepare */ nullptr,
+      maximum_minimum::Eval<maximum_minimum::kReference,
+                            maximum_minimum::MinimumOp>};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/micro_ops.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/micro_ops.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,80 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_KERNELS_MICRO_OPS_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_KERNELS_MICRO_OPS_H_
+
+#include "tensorflow/lite/c/c_api_internal.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+
+// Forward declaration of all micro op kernel registration methods. These
+// registrations are included with the standard `BuiltinOpResolver`.
+//
+// This header is particularly useful in cases where only a subset of ops are
+// needed. In such cases, the client can selectively add only the registrations
+// their model requires, using a custom `(Micro)MutableOpResolver`. Selective
+// registration in turn allows the linker to strip unused kernels.
+
+TfLiteRegistration* Register_ABS();
+TfLiteRegistration* Register_ADD();
+TfLiteRegistration* Register_ARG_MAX();
+TfLiteRegistration* Register_ARG_MIN();
+TfLiteRegistration* Register_AVERAGE_POOL_2D();
+TfLiteRegistration* Register_CEIL();
+TfLiteRegistration* Register_CONV_2D();
+TfLiteRegistration* Register_COS();
+TfLiteRegistration* Register_DEPTHWISE_CONV_2D();
+TfLiteRegistration* Register_DEQUANTIZE();
+TfLiteRegistration* Register_EQUAL();
+TfLiteRegistration* Register_FLOOR();
+TfLiteRegistration* Register_FULLY_CONNECTED();
+TfLiteRegistration* Register_GREATER();
+TfLiteRegistration* Register_GREATER_EQUAL();
+TfLiteRegistration* Register_LESS();
+TfLiteRegistration* Register_LESS_EQUAL();
+TfLiteRegistration* Register_LOG();
+TfLiteRegistration* Register_LOGICAL_AND();
+TfLiteRegistration* Register_LOGICAL_NOT();
+TfLiteRegistration* Register_LOGICAL_OR();
+TfLiteRegistration* Register_LOGISTIC();
+TfLiteRegistration* Register_MAXIMUM();
+TfLiteRegistration* Register_MAX_POOL_2D();
+TfLiteRegistration* Register_MINIMUM();
+TfLiteRegistration* Register_NEG();
+TfLiteRegistration* Register_NOT_EQUAL();
+TfLiteRegistration* Register_PACK();
+TfLiteRegistration* Register_PRELU();
+TfLiteRegistration* Register_QUANTIZE();
+TfLiteRegistration* Register_RELU();
+TfLiteRegistration* Register_RELU6();
+TfLiteRegistration* Register_RESHAPE();
+TfLiteRegistration* Register_ROUND();
+TfLiteRegistration* Register_RSQRT();
+TfLiteRegistration* Register_SIN();
+TfLiteRegistration* Register_SOFTMAX();
+TfLiteRegistration* Register_SPLIT();
+TfLiteRegistration* Register_SQRT();
+TfLiteRegistration* Register_SQUARE();
+TfLiteRegistration* Register_STRIDED_SLICE();
+TfLiteRegistration* Register_SVDF();
+TfLiteRegistration* Register_UNPACK();
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_KERNELS_MICRO_OPS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/micro_utils.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/micro_utils.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,37 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+    http://www.apache.org/licenses/LICENSE-2.0
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_KERNELS_MICRO_UTILS_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_KERNELS_MICRO_UTILS_H_
+namespace tflite {
+namespace ops {
+namespace micro {
+
+// Same as gtl::Greater but defined here to reduce dependencies and
+// binary size for micro environment.
+struct Greater {
+  template <typename T>
+  bool operator()(const T& x, const T& y) const {
+    return x > y;
+  }
+};
+
+struct Less {
+  template <typename T>
+  bool operator()(const T& x, const T& y) const {
+    return x < y;
+  }
+};
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_KERNELS_MICRO_UTILS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/neg.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/neg.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,58 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/kernels/internal/reference/neg.h"
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace neg {
+
+constexpr int kInputTensor = 0;
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  switch (input->type) {
+    // TODO(wangtz): handle for kTfLiteInt8
+    case kTfLiteFloat32:
+      reference_ops::Negate(GetTensorShape(input), GetTensorData<float>(input),
+                            GetTensorShape(output),
+                            GetTensorData<float>(output));
+      break;
+    default:
+      context->ReportError(
+          context, "Neg only currently supports float32, got %d.", input->type);
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace neg
+
+TfLiteRegistration* Register_NEG() {
+  static TfLiteRegistration r = {/*init=*/nullptr, /*free=*/nullptr,
+                                 /*prepare=*/nullptr, neg::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/pack.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/pack.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,122 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace pack {
+namespace {
+
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+template <typename T>
+TfLiteStatus PackImpl(TfLiteContext* context, TfLiteNode* node,
+                      TfLiteTensor* output, int values_count, int axis) {
+  const int dimensions = output->dims->size;
+  const TfLiteTensor* input0 = &context->tensors[node->inputs->data[0]];
+  const TfLiteIntArray* input_dims = input0->dims;
+  const TfLiteIntArray* output_dims = output->dims;
+
+  if (axis < 0) {
+    axis += dimensions;
+  }
+
+  int outer_size = 1;
+  for (int i = 0; i < axis; ++i) {
+    outer_size *= output_dims->data[i];
+  }
+  int copy_size = 1;
+  for (int i = axis + 1; i < dimensions; ++i) {
+    copy_size *= output_dims->data[i];
+  }
+  int input_size = 1;
+  for (int i = 0; i < input_dims->size; ++i) {
+    input_size *= input_dims->data[i];
+  }
+  TFLITE_DCHECK_EQ(input_size, copy_size * outer_size);
+
+  T* output_data = GetTensorData<T>(output);
+
+  for (int i = 0; i < values_count; ++i) {
+    TfLiteTensor* t = &context->tensors[node->inputs->data[i]];
+    const T* input_data = GetTensorData<T>(t);
+    for (int k = 0; k < outer_size; ++k) {
+      const T* input_ptr = input_data + copy_size * k;
+      int loc = k * values_count * copy_size + i * copy_size;
+      T* output_ptr = output_data + loc;
+      for (int j = 0; j < copy_size; ++j) output_ptr[j] = input_ptr[j];
+    }
+  }
+
+  return kTfLiteOk;
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLitePackParams* data =
+      reinterpret_cast<TfLitePackParams*>(node->builtin_data);
+
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  switch (output->type) {
+    case kTfLiteFloat32: {
+      return PackImpl<float>(context, node, output, data->values_count,
+                             data->axis);
+    }
+    case kTfLiteUInt8: {
+      return PackImpl<uint8_t>(context, node, output, data->values_count,
+                               data->axis);
+    }
+    case kTfLiteInt8: {
+      return PackImpl<int8_t>(context, node, output, data->values_count,
+                              data->axis);
+    }
+    case kTfLiteInt32: {
+      return PackImpl<int32_t>(context, node, output, data->values_count,
+                               data->axis);
+    }
+    case kTfLiteInt64: {
+      return PackImpl<int64_t>(context, node, output, data->values_count,
+                               data->axis);
+    }
+    default: {
+      context->ReportError(context, "Type '%s' is not supported by pack.",
+                           TfLiteTypeGetName(output->type));
+      return kTfLiteError;
+    }
+  }
+
+  return kTfLiteOk;
+}
+
+}  // namespace
+}  // namespace pack
+
+TfLiteRegistration* Register_PACK() {
+  static TfLiteRegistration r = {nullptr, nullptr, pack::Prepare, pack::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/pooling.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/pooling.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,245 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/kernels/internal/reference/pooling.h"
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/kernels/internal/reference/integer_ops/pooling.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/padding.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace pooling {
+
+namespace {
+
+constexpr int kInputTensor = 0;
+constexpr int kOutputTensor = 0;
+
+struct OpData {
+  TfLitePaddingValues padding;
+};
+
+TfLiteStatus CalculateOpData(const TfLiteContext* context,
+                             const TfLitePoolParams* params,
+                             const TfLiteTensor* input,
+                             const TfLiteTensor* output, OpData* data) {
+  // input: batch, height, width, channel
+  int height = SizeOfDimension(input, 1);
+  int width = SizeOfDimension(input, 2);
+
+  int out_height, out_width;
+
+  data->padding = ComputePaddingHeightWidth(
+      params->stride_height, params->stride_width,
+      /*dilation_rate_height=*/1,
+      /*dilation_rate_width=*/1, height, width, params->filter_height,
+      params->filter_width, params->padding, &out_height, &out_width);
+
+  return kTfLiteOk;
+}
+
+void AverageEvalFloat(const TfLiteContext* context, const TfLiteNode* node,
+                      const TfLitePoolParams* params, const OpData* data,
+                      const TfLiteTensor* input, TfLiteTensor* output) {
+  float activation_min, activation_max;
+  CalculateActivationRange(params->activation, &activation_min,
+                           &activation_max);
+
+  PoolParams op_params;
+  op_params.stride_height = params->stride_height;
+  op_params.stride_width = params->stride_width;
+  op_params.filter_height = params->filter_height;
+  op_params.filter_width = params->filter_width;
+  op_params.padding_values.height = data->padding.height;
+  op_params.padding_values.width = data->padding.width;
+  op_params.float_activation_min = activation_min;
+  op_params.float_activation_max = activation_max;
+  reference_ops::AveragePool(
+      op_params, GetTensorShape(input), GetTensorData<float>(input),
+      GetTensorShape(output), GetTensorData<float>(output));
+}
+
+void AverageEvalUint8(const TfLiteContext* context, const TfLiteNode* node,
+                      const TfLitePoolParams* params, const OpData* data,
+                      const TfLiteTensor* input, TfLiteTensor* output) {
+  int32_t activation_min, activation_max;
+  CalculateActivationRangeUint8(params->activation, output, &activation_min,
+                                &activation_max);
+
+  PoolParams op_params;
+  op_params.stride_height = params->stride_height;
+  op_params.stride_width = params->stride_width;
+  op_params.filter_height = params->filter_height;
+  op_params.filter_width = params->filter_width;
+  op_params.padding_values.height = data->padding.height;
+  op_params.padding_values.width = data->padding.width;
+  op_params.quantized_activation_min = activation_min;
+  op_params.quantized_activation_max = activation_max;
+  reference_ops::AveragePool(
+      op_params, GetTensorShape(input), GetTensorData<uint8_t>(input),
+      GetTensorShape(output), GetTensorData<uint8_t>(output));
+}
+
+void AverageEvalInt8(const TfLiteContext* context, const TfLiteNode* node,
+                     const TfLitePoolParams* params, const OpData* data,
+                     const TfLiteTensor* input, TfLiteTensor* output) {
+  int32_t activation_min, activation_max;
+  CalculateActivationRangeInt8(params->activation, output, &activation_min,
+                               &activation_max);
+
+  PoolParams op_params;
+  op_params.stride_height = params->stride_height;
+  op_params.stride_width = params->stride_width;
+  op_params.filter_height = params->filter_height;
+  op_params.filter_width = params->filter_width;
+  op_params.padding_values.height = data->padding.height;
+  op_params.padding_values.width = data->padding.width;
+  op_params.quantized_activation_min = activation_min;
+  op_params.quantized_activation_max = activation_max;
+  reference_integer_ops::AveragePool(
+      op_params, GetTensorShape(input), GetTensorData<int8_t>(input),
+      GetTensorShape(output), GetTensorData<int8_t>(output));
+}
+
+void MaxEvalFloat(TfLiteContext* context, TfLiteNode* node,
+                  TfLitePoolParams* params, OpData* data,
+                  const TfLiteTensor* input, TfLiteTensor* output) {
+  float activation_min, activation_max;
+  CalculateActivationRange(params->activation, &activation_min,
+                           &activation_max);
+
+  tflite::PoolParams op_params;
+  op_params.stride_height = params->stride_height;
+  op_params.stride_width = params->stride_width;
+  op_params.filter_height = params->filter_height;
+  op_params.filter_width = params->filter_width;
+  op_params.padding_values.height = data->padding.height;
+  op_params.padding_values.width = data->padding.width;
+  op_params.float_activation_min = activation_min;
+  op_params.float_activation_max = activation_max;
+  reference_ops::MaxPool(op_params, GetTensorShape(input),
+                         GetTensorData<float>(input), GetTensorShape(output),
+                         GetTensorData<float>(output));
+}
+
+void MaxEvalQuantizedUInt8(TfLiteContext* context, TfLiteNode* node,
+                           TfLitePoolParams* params, OpData* data,
+                           const TfLiteTensor* input, TfLiteTensor* output) {
+  int32_t activation_min, activation_max;
+  CalculateActivationRangeUint8(params->activation, output, &activation_min,
+                                &activation_max);
+
+  tflite::PoolParams op_params;
+  op_params.stride_height = params->stride_height;
+  op_params.stride_width = params->stride_width;
+  op_params.filter_height = params->filter_height;
+  op_params.filter_width = params->filter_width;
+  op_params.padding_values.height = data->padding.height;
+  op_params.padding_values.width = data->padding.width;
+  op_params.quantized_activation_min = activation_min;
+  op_params.quantized_activation_max = activation_max;
+  reference_ops::MaxPool(op_params, GetTensorShape(input),
+                         GetTensorData<uint8_t>(input), GetTensorShape(output),
+                         GetTensorData<uint8_t>(output));
+}
+
+}  // namespace
+
+void* Init(TfLiteContext* context, const char* buffer, size_t length) {
+  return nullptr;
+}
+
+void Free(TfLiteContext* context, void* buffer) {}
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+TfLiteStatus AverageEval(TfLiteContext* context, TfLiteNode* node) {
+  auto* params = reinterpret_cast<TfLitePoolParams*>(node->builtin_data);
+  OpData data;
+
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  TF_LITE_ENSURE_STATUS(CalculateOpData(context, params, input, output, &data));
+
+  // Inputs and outputs share the same type, guarenteed by the converter.
+  switch (input->type) {
+    case kTfLiteFloat32:
+      AverageEvalFloat(context, node, params, &data, input, output);
+      break;
+    case kTfLiteUInt8:
+      AverageEvalUint8(context, node, params, &data, input, output);
+      break;
+    case kTfLiteInt8:
+      AverageEvalInt8(context, node, params, &data, input, output);
+      break;
+    default:
+      context->ReportError(context, "Input type %s is not currently supported",
+                           TfLiteTypeGetName(input->type));
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+TfLiteStatus MaxEval(TfLiteContext* context, TfLiteNode* node) {
+  auto* params = reinterpret_cast<TfLitePoolParams*>(node->builtin_data);
+  OpData data;
+
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  TF_LITE_ENSURE_STATUS(CalculateOpData(context, params, input, output, &data));
+
+  switch (input->type) {
+    case kTfLiteFloat32:
+      MaxEvalFloat(context, node, params, &data, input, output);
+      break;
+    case kTfLiteUInt8:
+      MaxEvalQuantizedUInt8(context, node, params, &data, input, output);
+      break;
+    default:
+      context->ReportError(context, "Type %s not currently supported.",
+                           TfLiteTypeGetName(input->type));
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace pooling
+
+TfLiteRegistration* Register_AVERAGE_POOL_2D() {
+  static TfLiteRegistration r = {
+      pooling::Init,
+      pooling::Free,
+      pooling::Prepare,
+      pooling::AverageEval,
+  };
+  return &r;
+}
+
+TfLiteRegistration* Register_MAX_POOL_2D() {
+  static TfLiteRegistration r = {pooling::Init, pooling::Free, pooling::Prepare,
+                                 pooling::MaxEval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/prelu.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/prelu.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,114 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/kernels/internal/reference/prelu.h"
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace activations {
+
+TfLiteStatus PreluPrepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+inline void BroadcastPrelu4DSlowFloat(
+    const RuntimeShape& unextended_input1_shape, const float* input1_data,
+    const RuntimeShape& unextended_input2_shape, const float* input2_data,
+    const RuntimeShape& unextended_output_shape, float* output_data) {
+  TFLITE_DCHECK_LE(unextended_input1_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_LE(unextended_input2_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_LE(unextended_output_shape.DimensionsCount(), 4);
+  const RuntimeShape output_shape =
+      RuntimeShape::ExtendedShape(4, unextended_output_shape);
+
+  NdArrayDesc<4> desc1;
+  NdArrayDesc<4> desc2;
+  NdArrayDescsForElementwiseBroadcast(unextended_input1_shape,
+                                      unextended_input2_shape, &desc1, &desc2);
+
+  for (int b = 0; b < output_shape.Dims(0); ++b) {
+    for (int y = 0; y < output_shape.Dims(1); ++y) {
+      for (int x = 0; x < output_shape.Dims(2); ++x) {
+        for (int c = 0; c < output_shape.Dims(3); ++c) {
+          auto out_idx = Offset(output_shape, b, y, x, c);
+          auto in1_idx = SubscriptToIndex(desc1, b, y, x, c);
+          auto in2_idx = SubscriptToIndex(desc2, b, y, x, c);
+          auto in1_val = input1_data[in1_idx];
+          auto in2_val = input2_data[in2_idx];
+          output_data[out_idx] = in1_val >= 0.0 ? in1_val : in1_val * in2_val;
+        }
+      }
+    }
+  }
+}
+
+TfLiteStatus PreluEval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, 0);
+  const TfLiteTensor* alpha = GetInput(context, node, 1);
+  TfLiteTensor* output = GetOutput(context, node, 0);
+  int32_t output_multiplier = 0;
+  int output_shift = 0;
+  if (output->type == kTfLiteUInt8 || output->type == kTfLiteInt16) {
+    double real_multiplier =
+        input->params.scale * alpha->params.scale / output->params.scale;
+    QuantizeMultiplierSmallerThanOneExp(real_multiplier, &output_multiplier,
+                                        &output_shift);
+  }
+  switch (input->type) {
+    case kTfLiteFloat32: {
+      BroadcastPrelu4DSlowFloat(
+          GetTensorShape(input), GetTensorData<float>(input),
+          GetTensorShape(alpha), GetTensorData<float>(alpha),
+          GetTensorShape(output), GetTensorData<float>(output));
+      return kTfLiteOk;
+    } break;
+    case kTfLiteUInt8: {
+      PreluParams op_params;
+      op_params.input_offset = -input->params.zero_point;
+      op_params.alpha_offset = -alpha->params.zero_point;
+      op_params.output_offset = output->params.zero_point;
+      op_params.output_multiplier = output_multiplier;
+      op_params.output_shift = output_shift;
+      reference_ops::BroadcastPrelu4DSlow(
+          op_params, GetTensorShape(input), GetTensorData<uint8_t>(input),
+          GetTensorShape(alpha), GetTensorData<uint8_t>(alpha),
+          GetTensorShape(output), GetTensorData<uint8_t>(output));
+      return kTfLiteOk;
+    } break;
+    default:
+      context->ReportError(
+          context, "Only float32 and uint8 are supported currently, got %d.",
+          TfLiteTypeGetName(input->type));
+      return kTfLiteError;
+  }
+}
+
+}  // namespace activations
+
+TfLiteRegistration* Register_PRELU() {
+  static TfLiteRegistration r = {nullptr, nullptr, activations::PreluPrepare,
+                                 activations::PreluEval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/quantize.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/quantize.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,97 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/kernels/internal/reference/quantize.h"
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace quantize {
+
+void* Init(TfLiteContext* context, const char* buffer, size_t length) {
+  return nullptr;
+}
+
+void Free(TfLiteContext* context, void* buffer) {}
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+
+  TfLiteTensor* input = &context->tensors[node->inputs->data[0]];
+  TfLiteTensor* output = &context->tensors[node->outputs->data[0]];
+
+  // TODO(b/128934713): Add support for fixed-point per-channel quantization.
+  // Currently this only support affine per-layer quantization.
+  TF_LITE_ENSURE_EQ(context, output->quantization.type,
+                    kTfLiteAffineQuantization);
+  const auto* affine_quantization =
+      reinterpret_cast<TfLiteAffineQuantization*>(output->quantization.params);
+  TF_LITE_ENSURE(context, affine_quantization);
+  TF_LITE_ENSURE(context, affine_quantization->scale);
+  TF_LITE_ENSURE(context, affine_quantization->scale->size == 1);
+
+  TF_LITE_ENSURE(context, input->type == kTfLiteFloat32);
+  TF_LITE_ENSURE(context,
+                 output->type == kTfLiteUInt8 || output->type == kTfLiteInt8);
+
+  return kTfLiteOk;
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  TfLiteTensor* input = &context->tensors[node->inputs->data[0]];
+  TfLiteTensor* output = &context->tensors[node->outputs->data[0]];
+
+  tflite::QuantizationParams op_params;
+  op_params.zero_point = output->params.zero_point;
+  op_params.scale = output->params.scale;
+  switch (output->type) {
+    case kTfLiteInt8:
+      reference_ops::AffineQuantize(
+          op_params, GetTensorShape(input), GetTensorData<float>(input),
+          GetTensorShape(output), GetTensorData<int8_t>(output));
+      break;
+    case kTfLiteUInt8:
+      reference_ops::AffineQuantize(
+          op_params, GetTensorShape(input), GetTensorData<float>(input),
+          GetTensorShape(output), GetTensorData<uint8_t>(output));
+      break;
+    default:
+      context->ReportError(context, "Output type %s (%d) not supported",
+                           TfLiteTypeGetName(input->type), output->type);
+      return kTfLiteError;
+  }
+
+  return kTfLiteOk;
+}
+
+}  // namespace quantize
+
+// This Op (QUANTIZE) quantizes the input and produces quantized output.
+// AffineQuantize takes scale and zero point and quantizes the float value to
+// quantized output, in int8 or uint8 format.
+TfLiteRegistration* Register_QUANTIZE() {
+  static TfLiteRegistration r = {quantize::Init, quantize::Free,
+                                 quantize::Prepare, quantize::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/reshape.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/reshape.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,99 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace reshape {
+
+constexpr int kInputTensor = 0;
+constexpr int kShapeTensor = 1;
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus ReshapeOutput(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  // Tensorflow's Reshape allows one of the shape components to have the
+  // special -1 value, meaning it will be calculated automatically based on the
+  // input. Here we calculate what that dimension should be so that the number
+  // of output elements in the same as the number of input elements.
+  int num_input_elements = NumElements(input);
+  TfLiteIntArray* output_shape = output->dims;
+
+  if (NumInputs(node) == 1 &&  // Legacy scalar supported with params.
+      output_shape->size == 1 && output_shape->data[0] == 0) {
+    // Legacy tflite models use a shape parameter of [0] to indicate scalars,
+    // so adjust accordingly. TODO(b/111614235): Allow zero-sized buffers during
+    // toco conversion.
+    output_shape->size = 0;
+  }
+
+  int num_output_elements = 1;
+  int stretch_dim = -1;
+  for (int i = 0; i < output_shape->size; ++i) {
+    int value = output_shape->data[i];
+    if (value == -1) {
+      TF_LITE_ENSURE_EQ(context, stretch_dim, -1);
+      stretch_dim = i;
+    } else {
+      num_output_elements *= value;
+    }
+  }
+  if (stretch_dim != -1) {
+    output_shape->data[stretch_dim] = num_input_elements / num_output_elements;
+    num_output_elements *= output_shape->data[stretch_dim];
+  }
+
+  TF_LITE_ENSURE_EQ(context, input->type, output->type);
+  TF_LITE_ENSURE_EQ(context, num_input_elements, num_output_elements);
+  return kTfLiteOk;
+}
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  TF_LITE_ENSURE(context, NumInputs(node) == 1 || NumInputs(node) == 2);
+  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+  return kTfLiteOk;
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  if (ReshapeOutput(context, node) != kTfLiteOk) {
+    return kTfLiteError;
+  }
+
+  for (int i = 0; i < input->bytes; ++i) {
+    output->data.raw[i] = input->data.raw[i];
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace reshape
+
+TfLiteRegistration* Register_RESHAPE() {
+  static TfLiteRegistration r = {nullptr, nullptr, reshape::Prepare,
+                                 reshape::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/round.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/round.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,64 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/kernels/internal/reference/round.h"
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace round {
+
+constexpr int kInputTensor = 0;
+constexpr int kOutputTensor = 0;
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, input->type, kTfLiteFloat32);
+  TF_LITE_ENSURE_EQ(context, output->type, input->type);
+  TF_LITE_ENSURE_EQ(context, output->bytes, input->bytes);
+  TF_LITE_ENSURE_EQ(context, output->dims->size, input->dims->size);
+  for (int i = 0; i < output->dims->size; ++i) {
+    TF_LITE_ENSURE_EQ(context, output->dims->data[i], input->dims->data[i]);
+  }
+  return kTfLiteOk;
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  reference_ops::Round(GetTensorShape(input), GetTensorData<float>(input),
+                       GetTensorShape(output), GetTensorData<float>(output));
+
+  return kTfLiteOk;
+}
+}  // namespace round
+
+TfLiteRegistration* Register_ROUND() {
+  static TfLiteRegistration r = {/*init=*/nullptr,
+                                 /*free=*/nullptr, round::Prepare, round::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/softmax.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/softmax.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,213 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/kernels/internal/reference/softmax.h"
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace activations {
+namespace {
+
+struct OpData {
+  int32_t input_multiplier = 0;
+  int input_left_shift = 0;
+  int32_t input_range_radius = 0;
+  int diff_min = 0;
+};
+
+TfLiteStatus CalculateSoftmaxOpData(TfLiteContext* context,
+                                    const TfLiteTensor* input,
+                                    TfLiteTensor* output,
+                                    const TfLiteSoftmaxParams* params,
+                                    OpData* data) {
+  if (input->type == kTfLiteUInt8) {
+    TF_LITE_ENSURE_EQ(context, output->params.zero_point, 0);
+    TF_LITE_ENSURE(context, output->params.scale == 1.f / 256);
+
+    static const int kScaledDiffIntegerBits = 5;
+
+    tflite::PreprocessSoftmaxScaling(
+        params->beta, input->params.scale, kScaledDiffIntegerBits,
+        &data->input_multiplier, &data->input_left_shift);
+    data->diff_min = -1.0 * tflite::CalculateInputRadius(
+                                kScaledDiffIntegerBits, data->input_left_shift);
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace
+
+void* Init(TfLiteContext* context, const char* buffer, size_t length) {
+  return nullptr;
+}
+
+void Free(TfLiteContext* context, void* buffer) {}
+
+TfLiteStatus SoftmaxPrepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+// Takes a 1D tensor and performs softmax along it.
+void Softmax1DFloat(const TfLiteTensor* input, TfLiteTensor* output,
+                    TfLiteSoftmaxParams* params) {
+  const int input_size = input->dims->data[0];
+  tflite::reference_ops::Softmax(input->data.f, input_size, 1, params->beta,
+                                 output->data.f);
+}
+
+// Takes a 2D tensor and perform softmax along the last dimension.
+void Softmax2DFloat(const TfLiteTensor* input, TfLiteTensor* output,
+                    TfLiteSoftmaxParams* params) {
+  const int batch_size = input->dims->data[0];
+  const int input_size = input->dims->data[1];
+  tflite::reference_ops::Softmax(input->data.f, input_size, batch_size,
+                                 params->beta, output->data.f);
+}
+
+void Softmax1DQuantized(const TfLiteTensor* input, TfLiteTensor* output,
+                        TfLiteSoftmaxParams* params, OpData* data) {
+  // TODO(ahentz): this is arguably a dirty trick. Since the implementation
+  // always traverses the last dimension of a 4D tensor, we will pretend our 1D
+  // tensor is 4D in a special way. We will convert a (Y) shape into a (1,
+  // 1, 1, Y) shape.
+  const int input_size = input->dims->data[0];
+  const int32_t shape_data[4] = {1, 1, 1, input_size};
+  RuntimeShape shape(4, shape_data);
+  SoftmaxParams op_params;
+  op_params.input_multiplier = data->input_multiplier;
+  op_params.input_left_shift = data->input_left_shift;
+  op_params.diff_min = data->diff_min;
+  tflite::reference_ops::Softmax(op_params, shape,
+                                 GetTensorData<uint8_t>(input), shape,
+                                 GetTensorData<uint8_t>(output));
+}
+
+void Softmax2DQuantized(const TfLiteTensor* input, TfLiteTensor* output,
+                        TfLiteSoftmaxParams* params, OpData* data) {
+  // TODO(ahentz): this is arguably a dirty trick. Since the implementation
+  // always traverses the last dimension of a 4D tensor, we will pretend our 2D
+  // tensor is 4D in a special way. We will convert a (X, Y) shape into a (X,
+  // 1, 1, Y) shape.
+  const int batch_size = input->dims->data[0];
+  const int input_size = input->dims->data[1];
+  const int32_t shape_data[4] = {batch_size, 1, 1, input_size};
+  RuntimeShape shape(4, shape_data);
+  SoftmaxParams op_params;
+  op_params.input_multiplier = data->input_multiplier;
+  op_params.input_left_shift = data->input_left_shift;
+  op_params.diff_min = data->diff_min;
+  tflite::reference_ops::Softmax(op_params, shape,
+                                 GetTensorData<uint8_t>(input), shape,
+                                 GetTensorData<uint8_t>(output));
+}
+
+// Takes a 4D tensor and perform softmax along the forth dimension.
+void Softmax4DFloat(const TfLiteTensor* input, TfLiteTensor* output,
+                    TfLiteSoftmaxParams* params) {
+  SoftmaxParams op_params;
+  op_params.beta = params->beta;
+  tflite::reference_ops::Softmax(
+      op_params, GetTensorShape(input), GetTensorData<float>(input),
+      GetTensorShape(output), GetTensorData<float>(output));
+}
+
+void Softmax4DQuantized(const TfLiteTensor* input, TfLiteTensor* output,
+                        TfLiteSoftmaxParams* params, OpData* data) {
+  SoftmaxParams op_params;
+  op_params.input_multiplier = data->input_multiplier;
+  op_params.input_left_shift = data->input_left_shift;
+  op_params.diff_min = data->diff_min;
+  tflite::reference_ops::Softmax(
+      op_params, GetTensorShape(input), GetTensorData<uint8_t>(input),
+      GetTensorShape(output), GetTensorData<uint8_t>(output));
+}
+
+TfLiteStatus SoftmaxEval(TfLiteContext* context, TfLiteNode* node) {
+  auto* params = reinterpret_cast<TfLiteSoftmaxParams*>(node->builtin_data);
+
+  const TfLiteTensor* input = GetInput(context, node, 0);
+  TfLiteTensor* output = GetOutput(context, node, 0);
+
+  OpData local_data_object;
+  OpData* data = &local_data_object;
+  TF_LITE_ENSURE_STATUS(
+      CalculateSoftmaxOpData(context, input, output, params, data));
+
+  // TODO(ahentz): consider an implementation that works for many (all?)
+  // dimensions.
+  switch (input->type) {
+    case kTfLiteFloat32: {
+      if (NumDimensions(input) == 1) {
+        Softmax1DFloat(input, output, params);
+        return kTfLiteOk;
+      }
+      if (NumDimensions(input) == 2) {
+        Softmax2DFloat(input, output, params);
+        return kTfLiteOk;
+      }
+      if (NumDimensions(input) == 4) {
+        Softmax4DFloat(input, output, params);
+        return kTfLiteOk;
+      }
+      context->ReportError(
+          context, "Only 1D, 2D and 4D tensors supported currently, got %dD.",
+          NumDimensions(input));
+      return kTfLiteError;
+    }
+    case kTfLiteUInt8: {
+      if (NumDimensions(input) == 1) {
+        Softmax1DQuantized(input, output, params, data);
+        return kTfLiteOk;
+      }
+      if (NumDimensions(input) == 2) {
+        Softmax2DQuantized(input, output, params, data);
+        return kTfLiteOk;
+      }
+      if (NumDimensions(input) == 4) {
+        Softmax4DQuantized(input, output, params, data);
+        return kTfLiteOk;
+      }
+      context->ReportError(
+          context, "Only 2D and 4D tensors supported currently, got %dD.",
+          NumDimensions(input));
+      return kTfLiteError;
+    }
+    default:
+      context->ReportError(
+          context, "Only float32 and uint8_t supported currently, got %d.",
+          input->type);
+      return kTfLiteError;
+  }
+}
+}  // namespace activations
+
+TfLiteRegistration* Register_SOFTMAX() {
+  static TfLiteRegistration r = {activations::Init, activations::Free,
+                                 activations::SoftmaxPrepare,
+                                 activations::SoftmaxEval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/split.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/split.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,125 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace split {
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+template <typename T>
+TfLiteStatus SplitImpl(TfLiteContext* context, TfLiteNode* node,
+                       const TfLiteTensor* input, int axis_value) {
+  const int output_count = NumOutputs(node);
+  const TfLiteIntArray* input_dims = input->dims;
+  const TfLiteTensor* output0 = &context->tensors[node->outputs->data[0]];
+  const TfLiteIntArray* output_dims = output0->dims;
+
+  const int split_dimensions = input_dims->size;
+  int axis = axis_value < 0 ? axis_value + split_dimensions : axis_value;
+
+  TFLITE_DCHECK_LT(axis, split_dimensions);
+  TFLITE_DCHECK_EQ(output_dims->size, split_dimensions);
+
+  int64_t split_size = output_dims->data[axis] * output_count;
+
+  TFLITE_DCHECK_EQ(split_size, input_dims->data[axis]);
+  int64_t outer_size = 1;
+  for (int i = 0; i < axis; ++i) {
+    outer_size *= input_dims->data[i];
+  }
+
+  int64_t base_inner_size = 1;
+  for (int i = axis + 1; i < split_dimensions; ++i) {
+    base_inner_size *= input_dims->data[i];
+  }
+
+  const T* input_ptr = GetTensorData<T>(input);
+  for (int k = 0; k < outer_size; ++k) {
+    for (int i = 0; i < output_count; ++i) {
+      TfLiteTensor* t = &context->tensors[node->outputs->data[i]];
+      T* output_data = GetTensorData<T>(t);
+      const int copy_size = output_dims->data[axis] * base_inner_size;
+      T* output_ptr = output_data + k * copy_size;
+      for (int j = 0; j < copy_size; ++j) output_ptr[j] = input_ptr[j];
+      input_ptr += copy_size;
+    }
+  }
+
+  return kTfLiteOk;
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  const TfLiteTensor* axis = GetInput(context, node, 0);
+  const TfLiteTensor* input = GetInput(context, node, 1);
+
+  // Dynamic output tensors are needed if axis tensor is not constant.
+  // But Micro doesn't support dynamic memeory allocation, so we only support
+  // constant axis tensor for now.
+  TF_LITE_ENSURE_MSG(context, IsConstantTensor(axis),
+                     "Non constant axis tensor not supported");
+
+  int axis_value = GetTensorData<int32_t>(axis)[0];
+  if (axis_value < 0) {
+    axis_value += NumDimensions(input);
+  }
+
+  TF_LITE_ENSURE(context, axis_value >= 0);
+  TF_LITE_ENSURE(context, axis_value < NumDimensions(input));
+
+  switch (input->type) {
+    case kTfLiteFloat32: {
+      return SplitImpl<float>(context, node, input, axis_value);
+    }
+    case kTfLiteUInt8: {
+      return SplitImpl<uint8_t>(context, node, input, axis_value);
+    }
+    case kTfLiteInt8: {
+      return SplitImpl<int8_t>(context, node, input, axis_value);
+    }
+    case kTfLiteInt16: {
+      return SplitImpl<int16_t>(context, node, input, axis_value);
+    }
+    case kTfLiteInt32: {
+      return SplitImpl<int32_t>(context, node, input, axis_value);
+    }
+    default:
+      context->ReportError(context, "Type %s currently not supported.",
+                           TfLiteTypeGetName(input->type));
+      return kTfLiteError;
+  }
+#undef TF_LITE_SPLIT
+
+  return kTfLiteOk;
+}
+
+}  // namespace split
+
+TfLiteRegistration* Register_SPLIT() {
+  static TfLiteRegistration r = {nullptr, nullptr, split::Prepare, split::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/strided_slice.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/strided_slice.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,180 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/kernels/internal/reference/strided_slice.h"
+
+#include <cmath>
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace strided_slice {
+
+enum KernelType {
+  kReference,
+  // TODO(soroosh): add kGenericOptimized
+};
+
+constexpr int kInputTensor = 0;
+constexpr int kBeginTensor = 1;
+constexpr int kEndTensor = 2;
+constexpr int kStridesTensor = 3;
+constexpr int kOutputTensor = 0;
+
+struct StridedSliceContext {
+  StridedSliceContext(TfLiteContext* context, TfLiteNode* node) {
+    params = reinterpret_cast<TfLiteStridedSliceParams*>(node->builtin_data);
+    input = GetInput(context, node, kInputTensor);
+    begin = GetInput(context, node, kBeginTensor);
+    end = GetInput(context, node, kEndTensor);
+    strides = GetInput(context, node, kStridesTensor);
+    output = GetOutput(context, node, kOutputTensor);
+    dims = NumDimensions(input);
+  }
+  const TfLiteStridedSliceParams* params;
+  const TfLiteTensor* input;
+  const TfLiteTensor* begin;
+  const TfLiteTensor* end;
+  const TfLiteTensor* strides;
+  TfLiteTensor* output;
+  int dims;
+};
+
+// This Op only supports 1-4D cases and since we use the reference 4D
+// implementation, the 1-3D tensors are mapped to 4D.
+const int kMaxDim = 4;
+
+tflite::StridedSliceParams BuildStridedSliceParams(
+    StridedSliceContext* op_context) {
+  tflite::StridedSliceParams op_params;
+  op_params.start_indices_count = op_context->dims;
+  op_params.stop_indices_count = op_context->dims;
+  op_params.strides_count = op_context->dims;
+
+  for (int i = 0; i < op_context->dims; ++i) {
+    op_params.start_indices[i] = GetTensorData<int32_t>(op_context->begin)[i];
+    op_params.stop_indices[i] = GetTensorData<int32_t>(op_context->end)[i];
+    op_params.strides[i] = GetTensorData<int32_t>(op_context->strides)[i];
+  }
+
+  op_params.begin_mask = op_context->params->begin_mask;
+  op_params.ellipsis_mask = 0;
+  op_params.end_mask = op_context->params->end_mask;
+  op_params.new_axis_mask = 0;
+  op_params.shrink_axis_mask = op_context->params->shrink_axis_mask;
+  return op_params;
+}
+
+// Processes the indexing tensors (begin, end and strides) to resize the
+// output tensor. This function is callable from both Prepare() and Eval() as
+// long as the caller ensures the indexing tensors are present.
+TfLiteStatus CheckOutputSize(TfLiteContext* context,
+                             StridedSliceContext* op_context) {
+  using ::tflite::strided_slice::StartForAxis;
+  using ::tflite::strided_slice::StopForAxis;
+  TfLiteIntArray* output_shape = op_context->output->dims;
+  int shape_size = 0;
+  auto op_params = BuildStridedSliceParams(op_context);
+  auto input_shape = GetTensorShape(op_context->input);
+  for (int idx = 0; idx < op_context->dims; ++idx) {
+    int32_t stride = GetTensorData<int32_t>(op_context->strides)[idx];
+    TF_LITE_ENSURE_MSG(context, stride != 0, "stride value has to be non-zero");
+    int32_t begin = StartForAxis(op_params, input_shape, idx);
+    int32_t end = StopForAxis(op_params, input_shape, idx, begin);
+
+    // When shrinking an axis, the end position does not matter (and can be
+    // incorrect when negative indexing is used, see Issue #19260). Always use
+    // begin + 1 to generate a length 1 slice, since begin has
+    // already been adjusted for negative indices by StartForAxis.
+    const bool shrink_axis = op_context->params->shrink_axis_mask & (1 << idx);
+    if (shrink_axis) {
+      end = begin + 1;
+    }
+
+    // This is valid for both positive and negative strides
+    int32_t dim_shape = std::ceil((end - begin) / static_cast<float>(stride));
+    dim_shape = dim_shape < 0 ? 0 : dim_shape;
+    if (!shrink_axis) {
+      TF_LITE_ENSURE_EQ(context, output_shape->data[shape_size], dim_shape);
+      shape_size++;
+    }
+  }
+  TF_LITE_ENSURE_EQ(context, output_shape->size, shape_size);
+  return kTfLiteOk;
+}
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  TF_LITE_ENSURE_EQ(context, NumInputs(node), 4);
+  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+  StridedSliceContext op_context(context, node);
+  TF_LITE_ENSURE_MSG(context, op_context.dims <= kMaxDim,
+                     "input dim should not exceed 4");
+  return CheckOutputSize(context, &op_context);
+}
+
+template <KernelType kernel_type>
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  StridedSliceContext op_context(context, node);
+  auto op_params = BuildStridedSliceParams(&op_context);
+
+#define TF_LITE_STRIDED_SLICE(kernel_type, data_type)                    \
+  kernel_type::StridedSlice(op_params, GetTensorShape(op_context.input), \
+                            GetTensorData<data_type>(op_context.input),  \
+                            GetTensorShape(op_context.output),           \
+                            GetTensorData<data_type>(op_context.output))
+
+  switch (op_context.input->type) {
+    case kTfLiteFloat32:
+      if (kernel_type == kReference) {
+        TF_LITE_STRIDED_SLICE(reference_ops, float);
+      }
+      break;
+    case kTfLiteUInt8:
+      if (kernel_type == kReference) {
+        TF_LITE_STRIDED_SLICE(reference_ops, uint8_t);
+      }
+      break;
+    case kTfLiteInt8:
+      if (kernel_type == kReference) {
+        TF_LITE_STRIDED_SLICE(reference_ops, int8_t);
+      }
+      break;
+    default:
+      context->ReportError(context,
+                           "Type %d is currently not supported "
+                           "by StridedSlice.",
+                           op_context.input->type);
+      return kTfLiteError;
+  }
+#undef TF_LITE_STRIDED_SLICE
+  return kTfLiteOk;
+}
+}  // namespace strided_slice
+
+TfLiteRegistration* Register_STRIDED_SLICE() {
+  static TfLiteRegistration r = {
+      nullptr, nullptr, strided_slice::Prepare,
+      strided_slice::Eval<strided_slice::kReference>};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/svdf.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/svdf.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,503 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include <math.h>
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/experimental/micro/kernels/activation_utils.h"
+#include "tensorflow/lite/experimental/micro/micro_utils.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace svdf {
+namespace {
+
+/**
+ * This version of SVDF is specific to TFLite Micro. It contains the following
+ * differences between the TFLite version:
+ *
+ * 1.) Scratch tensor allocation - scratch tensors must be known ahead of time
+ * for the Micro interpreter.
+ * 2.) Output dimensions - the TFLite version determines output size and runtime
+ * and resizes the output tensor. Micro runtime does not support tensor
+ * resizing.
+ */
+
+// TODO(kreeger): upstream these reference methods into
+// `lite/kernels/reference/svdf.h`
+
+static inline void ApplyTimeWeightsBiasAndActivation(
+    int batch_size, int memory_size, int num_filters, int num_units, int rank,
+    const TfLiteTensor* weights_time, const TfLiteTensor* bias,
+    TfLiteFusedActivation activation, TfLiteTensor* activation_state,
+    TfLiteTensor* scratch, TfLiteTensor* output) {
+  // Compute matmul(activation_state, weights_time).
+  // The rightmost column is used to save temporary output (with the size of
+  // num_filters). This is achieved by starting at
+  // GetTensorData<float>(activation_state), and having the stride equal to
+  // memory_size.
+  for (int b = 0; b < batch_size; ++b) {
+    // Perform batched vector dot product:
+    float* scratch_ptr_batch = GetTensorData<float>(scratch) + b * num_filters;
+    const float* vector1_ptr = GetTensorData<float>(weights_time);
+    const float* vector2_ptr =
+        GetTensorData<float>(activation_state) + b * memory_size * num_filters;
+    for (int i = 0; i < num_filters; ++i) {
+      *scratch_ptr_batch = 0.f;
+      for (int j = 0; j < memory_size; ++j) {
+        *scratch_ptr_batch += *vector1_ptr++ * *vector2_ptr++;
+      }
+      scratch_ptr_batch++;
+    }
+  }
+
+  // Initialize output with bias if provided.
+  if (bias) {
+    // TODO(kreeger): doc me - VectorBatchVectorAssign
+    const float* bias_data = GetTensorData<float>(bias);
+    float* output_data = GetTensorData<float>(output);
+    for (int i = 0; i < batch_size; ++i) {
+      float* output_ptr = output_data + i * num_units;
+      const float* bias_ptr = bias_data;
+      for (int j = 0; j < num_units; ++j) {
+        *output_ptr++ = *bias_ptr++;
+      }
+    }
+  } else {
+    float* output_data = GetTensorData<float>(output);
+    for (int i = 0; i < batch_size * num_units; ++i) {
+      *output_data++ = 0.0f;
+    }
+  }
+
+  // Reduction sum.
+  for (int b = 0; b < batch_size; ++b) {
+    float* output_ptr_batch = GetTensorData<float>(output) + b * num_units;
+    float* scratch_ptr_batch = GetTensorData<float>(scratch) + b * num_filters;
+
+    // Reduction sum vector
+    const float* input_vector_ptr = scratch_ptr_batch;
+    for (int i = 0; i < num_units; ++i) {
+      for (int j = 0; j < rank; j++) {
+        output_ptr_batch[i] += *input_vector_ptr++;
+      }
+    }
+  }
+
+  // Apply activation.
+  for (int b = 0; b < batch_size; ++b) {
+    float* output_ptr_batch = GetTensorData<float>(output) + b * num_units;
+    for (int i = 0; i < num_units; ++i) {
+      *output_ptr_batch = ActivationValFloat(activation, *output_ptr_batch);
+      ++output_ptr_batch;
+    }
+  }
+
+  // Left shift the activation_state to make room for next cycle's activation.
+  // TODO(alanchiao): explore collapsing this into a single loop.
+  for (int b = 0; b < batch_size; ++b) {
+    float* state_ptr_batch =
+        GetTensorData<float>(activation_state) + b * memory_size * num_filters;
+    for (int f = 0; f < num_filters; ++f) {
+      // Shift the vector left:
+      float* batch_ptr = state_ptr_batch;
+      float* batch_start = state_ptr_batch + 1;
+      float* batch_end = state_ptr_batch + memory_size;
+      while (batch_start != batch_end) {
+        *batch_ptr++ = *batch_start++;
+      }
+      state_ptr_batch[memory_size - 1] = 0.0f;
+      state_ptr_batch += memory_size;
+    }
+  }
+}
+
+inline void EvalFloatSVDF(TfLiteContext* context, TfLiteNode* node,
+                          const TfLiteTensor* input,
+                          const TfLiteTensor* weights_feature,
+                          const TfLiteTensor* weights_time,
+                          const TfLiteTensor* bias,
+                          const TfLiteSVDFParams* params, TfLiteTensor* scratch,
+                          TfLiteTensor* activation_state,
+                          TfLiteTensor* output) {
+  const int rank = params->rank;
+  const int batch_size = input->dims->data[0];
+  const int input_size = input->dims->data[1];
+  const int num_filters = weights_feature->dims->data[0];
+  const int num_units = num_filters / rank;
+  const int memory_size = weights_time->dims->data[1];
+
+  // Clear the activation (activation_state's leftmost column).
+  // TODO(ghodrat): Add a test which initialize activation_state with invalid
+  // values in leftmost column and make sure it passes.
+  for (int b = 0; b < batch_size; ++b) {
+    float* state_ptr_batch =
+        GetTensorData<float>(activation_state) + b * memory_size * num_filters;
+    for (int c = 0; c < num_filters; ++c) {
+      float* state_ptr = state_ptr_batch + c * memory_size;
+      state_ptr[memory_size - 1] = 0.0f;
+    }
+  }
+
+  // Compute conv1d(inputs, weights_feature).
+  // The activation_state's rightmost column is used to save current cycle
+  // activation. This is achieved by starting at
+  // GetTensorData<float>(activation_state)[memory_size - 1] and having the
+  // stride equal to memory_size.
+
+  // Perform batched matrix vector multiply accumulate operation:
+  const float* matrix = GetTensorData<float>(weights_feature);
+  const float* vector = GetTensorData<float>(input);
+  float* result = &GetTensorData<float>(activation_state)[memory_size - 1];
+  float* result_in_batch = result;
+  for (int i = 0; i < batch_size; ++i) {
+    const float* matrix_ptr = matrix;
+    for (int j = 0; j < num_filters; ++j) {
+      float dot_prod = 0.0f;
+      const float* vector_in_batch = vector + i * input_size;
+      for (int k = 0; k < input_size; ++k) {
+        dot_prod += *matrix_ptr++ * *vector_in_batch++;
+      }
+      *result_in_batch += dot_prod;
+      result_in_batch += memory_size;
+    }
+  }
+
+  ApplyTimeWeightsBiasAndActivation(
+      batch_size, memory_size, num_filters, num_units, rank, weights_time, bias,
+      params->activation, activation_state, scratch, output);
+}
+
+inline void EvalHybridSVDF(
+    TfLiteContext* context, TfLiteNode* node, const TfLiteTensor* input,
+    const TfLiteTensor* weights_feature, const TfLiteTensor* weights_time,
+    const TfLiteTensor* bias, const TfLiteSVDFParams* params,
+    TfLiteTensor* scratch, TfLiteTensor* scaling_factors,
+    TfLiteTensor* input_quantized, TfLiteTensor* activation_state,
+    TfLiteTensor* output) {
+  const int rank = params->rank;
+  const int batch_size = input->dims->data[0];
+  const int input_size = input->dims->data[1];
+  const int num_filters = weights_feature->dims->data[0];
+  const int num_units = num_filters / rank;
+  const int memory_size = weights_time->dims->data[1];
+
+  // Initialize the pointer to input.
+  const float* input_ptr_batch = GetTensorData<float>(input);
+
+  int8_t* quantized_input_ptr_batch = GetTensorData<int8_t>(input_quantized);
+  const int8_t* weights_feature_ptr = GetTensorData<int8_t>(weights_feature);
+
+  // Initialize the pointer to storage for scaling factors.
+  float* scaling_factors_ptr = GetTensorData<float>(scaling_factors);
+
+  // Initialize the weights scale.
+  const float weights_feature_scale = weights_feature->params.scale;
+
+  // Clear the activation (activation_state's leftmost column).
+  // TODO(ghodrat): Add a test which initialize activation_state with invalid
+  // values in the leftmost column and make sure it passes.
+  // TODO(kreeger): Use a port of tensor_utils when ready (b/140272187).
+  for (int b = 0; b < batch_size; ++b) {
+    float* state_ptr_batch =
+        GetTensorData<float>(activation_state) + b * memory_size * num_filters;
+    for (int c = 0; c < num_filters; ++c) {
+      float* state_ptr = state_ptr_batch + c * memory_size;
+      state_ptr[memory_size - 1] = 0.0;
+    }
+  }
+
+  // Determine if input pointer batch is a zero based vector:
+  bool is_zero_vector = true;
+  for (int i = 0; i < batch_size * input_size && is_zero_vector; ++i) {
+    if (input_ptr_batch[i] != 0.0f) {
+      is_zero_vector = false;
+    }
+  }
+
+  if (!is_zero_vector) {
+    SignedSymmetricPerChannelQuantize(input_ptr_batch, input->dims, 0,
+                                      quantized_input_ptr_batch,
+                                      scaling_factors_ptr);
+
+    // Quantize input from float to int8.
+    for (int b = 0; b < batch_size; ++b) {
+      scaling_factors_ptr[b] *= weights_feature_scale;
+    }
+
+    // Compute conv1d(inputs, weights_feature).
+    // The rightmost column of activation_state is used to save the current
+    // cycle activation. This is achieved by starting at
+    // GetTensorData<float>(activation_state)[memory_size - 1] and having the
+    // stride equal to memory_size. (Matrix batch vector multiply accumulate)
+    float* result = &GetTensorData<float>(activation_state)[memory_size - 1];
+    for (int i = 0; i < batch_size;
+         ++i, quantized_input_ptr_batch += input_size) {
+      const float batch_scaling_factor = scaling_factors_ptr[i];
+
+      // Get the address of the first row:
+      const int8_t* row_ptr = weights_feature_ptr;
+      for (int j = 0; j < num_filters; ++j, result += memory_size) {
+        // Initialize the dot product sum for the row to 0.
+        int32_t dotprod = 0;
+        for (int k = 0; k < input_size; ++k, ++row_ptr) {
+          dotprod += (*row_ptr) * (quantized_input_ptr_batch[k]);
+        }
+        *result += dotprod * batch_scaling_factor;
+      }
+    }
+  }
+
+  // TODO(alanchiao): can optimize hybrid case ~5% by unrolling loop in applying
+  // time weights so that the inner loop multiplies eight elements at a time.
+  ApplyTimeWeightsBiasAndActivation(
+      batch_size, memory_size, num_filters, num_units, rank, weights_time, bias,
+      params->activation, activation_state, scratch, output);
+}
+
+}  // namespace
+
+// Input tensors.
+constexpr int kInputTensor = 0;
+constexpr int kWeightsFeatureTensor = 1;
+constexpr int kWeightsTimeTensor = 2;
+constexpr int kBiasTensor = 3;
+// This is a variable tensor, and will be modified by this op.
+constexpr int kInputActivationStateTensor = 4;
+
+// Output tensor.
+constexpr int kOutputTensor = 0;
+
+void* Init(TfLiteContext* context, const char* buffer, size_t length) {
+  return nullptr;
+}
+
+void Free(TfLiteContext* context, void* buffer) {}
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  const auto* params = reinterpret_cast<TfLiteSVDFParams*>(node->builtin_data);
+
+  // Validate Tensor Inputs (dtype depends on quantization):
+  // [0] = Input, {2, batch_size, input_size}
+  // [1] = Weights Feature, {2, num_filters, input_size}
+  // [2] = Weights Time, {2, num_filters, memory_size}
+  // [3] = Bias (optional), {1, num_units}
+  // [4] = Activation State (variable),
+  //         {2, batch_size, memory_size * num_filters}
+  // TODO(kreeger): Use input tensor as variable until scratch tensor allocation
+  // has been implemented (cl/263032056)
+  // TF_LITE_ENSURE_EQ(context, node->inputs->size, 5);
+  TF_LITE_ENSURE_EQ(context, node->inputs->size, 6);
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  const TfLiteTensor* weights_feature =
+      GetInput(context, node, kWeightsFeatureTensor);
+  const TfLiteTensor* weights_time =
+      GetInput(context, node, kWeightsTimeTensor);
+  const TfLiteTensor* bias = GetOptionalInputTensor(context, node, kBiasTensor);
+  TfLiteTensor* activation_state =
+      &context->tensors[node->inputs->data[kInputActivationStateTensor]];
+
+  // Define input constants based on input tensor definition above:
+  const int rank = params->rank;
+  const int input_size = input->dims->data[1];
+  const int batch_size = input->dims->data[0];
+  const int num_filters = weights_feature->dims->data[0];
+  TF_LITE_ENSURE_EQ(context, num_filters % rank, 0);
+  const int num_units = num_filters / rank;
+  const int memory_size = weights_time->dims->data[1];
+
+  // Validate Input Tensor:
+  TF_LITE_ENSURE_EQ(context, input->type, kTfLiteFloat32);
+  TF_LITE_ENSURE_EQ(context, NumDimensions(input), 2);
+
+  // Validate Weights Feature Input Tensor:
+  TF_LITE_ENSURE_EQ(context, NumDimensions(weights_feature), 2);
+  TF_LITE_ENSURE_EQ(context, weights_feature->dims->data[1], input_size);
+
+  // Validate Weights Time Input Tensor:
+  TF_LITE_ENSURE_EQ(context, NumDimensions(weights_time), 2);
+  TF_LITE_ENSURE_EQ(context, weights_time->dims->data[0], num_filters);
+  TF_LITE_ENSURE_EQ(context, weights_time->dims->data[1], memory_size);
+
+  // Validate Optional Bias Input Tensor:
+  if (bias) {
+    TF_LITE_ENSURE_EQ(context, bias->dims->data[0], num_units);
+    TF_LITE_ENSURE_EQ(context, bias->type, kTfLiteFloat32);
+  }
+
+  // Validate Activation State Input Tensor:
+  TF_LITE_ENSURE_EQ(context, activation_state->type, kTfLiteFloat32);
+  TF_LITE_ENSURE_EQ(context, NumDimensions(activation_state), 2);
+  TF_LITE_ENSURE_EQ(context, activation_state->dims->data[0], batch_size);
+  TF_LITE_ENSURE_EQ(context, activation_state->dims->data[1],
+                    memory_size * num_filters);
+
+  // Validate shared Scratch Tensor (same for full float and hybrid):
+  // [0] = Holds dot-product of time-forward calculations in
+  //       ApplyTimeWeightsBiasAndActivation():
+  //         float, {2, batch_size, num_filters}
+  // TODO(kreeger): Use input tensor as variable until scratch tensor allocation
+  // has been implemented (cl/263032056)
+  // TfLiteTensor* scratch_tensor = GetTemporary(context, node, 0);
+  TfLiteTensor* scratch_tensor = &context->tensors[node->inputs->data[5]];
+
+  TF_LITE_ENSURE_EQ(context, scratch_tensor->type, kTfLiteFloat32);
+  TF_LITE_ENSURE_EQ(context, NumDimensions(scratch_tensor), 2);
+  TF_LITE_ENSURE_EQ(context, scratch_tensor->dims->data[0], batch_size);
+  TF_LITE_ENSURE_EQ(context, scratch_tensor->dims->data[1], num_filters);
+
+  // The weights are of consistent type, so it suffices to check one.
+  const bool is_hybrid_op = IsHybridOp(input, weights_feature);
+  // TODO(kreeger): Handle full quant svdf b/139435798
+  if (is_hybrid_op) {
+    // Validate Input Tensor dtypes:
+    TF_LITE_ENSURE(context, weights_feature->type == kTfLiteUInt8 ||
+                                weights_feature->type == kTfLiteInt8);
+    TF_LITE_ENSURE(context, weights_time->type == kTfLiteUInt8 ||
+                                weights_time->type == kTfLiteInt8);
+
+    // Validate Scratch Tensors:
+    // [0] = (shared - see above for usage)
+    // [1] = Input Quantized, int8_t/uint8_t, {2, batch_size, input_size}
+    // [2] = Scaling Factors, float, {1, batch_size}
+    // [3] = Float Weights Time, float, {2, num_filters, memory_size}
+    TF_LITE_ENSURE_EQ(context, node->temporaries->size, 4);
+    TfLiteTensor* scratch_input_quantized = GetTemporary(context, node, 1);
+    TfLiteTensor* scratch_scaling_factors = GetTemporary(context, node, 2);
+    TfLiteTensor* scratch_float_weights_time = GetTemporary(context, node, 3);
+
+    // Validate Input Quantized Scratch Tensor:
+    TF_LITE_ENSURE(context, scratch_input_quantized->type == kTfLiteUInt8 ||
+                                scratch_input_quantized->type == kTfLiteInt8);
+    TF_LITE_ENSURE_EQ(context, scratch_input_quantized->dims->data[0],
+                      batch_size);
+    TF_LITE_ENSURE_EQ(context, scratch_input_quantized->dims->data[1],
+                      input_size);
+
+    // Validate Scaling Factors Scratch Tensor:
+    TF_LITE_ENSURE_EQ(context, scratch_scaling_factors->type, kTfLiteFloat32);
+    TF_LITE_ENSURE_EQ(context, NumDimensions(scratch_scaling_factors), 1);
+    TF_LITE_ENSURE_EQ(context, scratch_scaling_factors->dims->data[0],
+                      batch_size);
+
+    // Validate Float Weights Time Scratch Tensor:
+    TF_LITE_ENSURE_EQ(context, scratch_float_weights_time->type,
+                      kTfLiteFloat32);
+    TF_LITE_ENSURE_EQ(context, NumDimensions(scratch_float_weights_time), 2);
+    TF_LITE_ENSURE_EQ(context, scratch_float_weights_time->dims->data[0],
+                      num_filters);
+    TF_LITE_ENSURE_EQ(context, scratch_float_weights_time->dims->data[1],
+                      memory_size);
+
+    // TfLite Micro has scratch tensors allocated at the time that Prepare() is
+    // called. Use this time to do a one-time de-quantization copy of
+    // the input values from the Weights Time tensor to the float weights time
+    // scratch tensor.
+    // TODO(kreeger): Consider doing this at model conversion time?
+    SymmetricDequantize(GetTensorData<int8_t>(weights_time),
+                        NumElements(scratch_float_weights_time),
+                        weights_time->params.scale,
+                        GetTensorData<float>(scratch_float_weights_time));
+  } else {
+    // Validate Input Tensor dtypes:
+    TF_LITE_ENSURE_EQ(context, weights_feature->type, kTfLiteFloat32);
+    TF_LITE_ENSURE_EQ(context, weights_time->type, kTfLiteFloat32);
+
+    // Full-float SVDF only uses the one shared scratch tensor (see above for
+    // usage).
+    // TODO(kreeger): Use input tensor as variable until scratch tensor
+    // allocation has been implemented (cl/263032056)
+    // TF_LITE_ENSURE_EQ(context, node->temporaries->size, 1);
+  }
+
+  // Validate Tensor Output:
+  // [0] = float, {2, batch_size, num_units}
+  TF_LITE_ENSURE_EQ(context, node->outputs->size, 1);
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+  TF_LITE_ENSURE_EQ(context, output->type, kTfLiteFloat32);
+  TF_LITE_ENSURE_EQ(context, NumDimensions(output), 2);
+  TF_LITE_ENSURE_EQ(context, output->dims->data[0], batch_size);
+  TF_LITE_ENSURE_EQ(context, output->dims->data[1], num_units);
+
+  return kTfLiteOk;
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  const auto* params = reinterpret_cast<TfLiteSVDFParams*>(node->builtin_data);
+
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+  const TfLiteTensor* weights_feature =
+      GetInput(context, node, kWeightsFeatureTensor);
+  const TfLiteTensor* weights_time =
+      GetInput(context, node, kWeightsTimeTensor);
+  const TfLiteTensor* bias = GetOptionalInputTensor(context, node, kBiasTensor);
+
+  // TODO(kreeger): Use input tensor as variable until scratch tensor allocation
+  // has been implemented (cl/263032056)
+  // TfLiteTensor* scratch = GetTemporary(context, node, /*index=*/0);
+  TfLiteTensor* scratch = &context->tensors[node->inputs->data[5]];
+
+  TfLiteTensor* activation_state =
+      &context->tensors[node->inputs->data[kInputActivationStateTensor]];
+  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
+
+  switch (weights_feature->type) {
+    case kTfLiteFloat32: {
+      EvalFloatSVDF(context, node, input, weights_feature, weights_time, bias,
+                    params, scratch, activation_state, output);
+      return kTfLiteOk;
+      break;
+    }
+
+    case kTfLiteUInt8:
+    case kTfLiteInt8: {
+      TfLiteTensor* scratch_input_quantized = GetTemporary(context, node, 1);
+      TfLiteTensor* scratch_scaling_factors = GetTemporary(context, node, 2);
+      TfLiteTensor* scratch_float_weights_time = GetTemporary(context, node, 3);
+      EvalHybridSVDF(context, node, input, weights_feature,
+                     scratch_float_weights_time, bias, params, scratch,
+                     scratch_scaling_factors, scratch_input_quantized,
+                     activation_state, output);
+      return kTfLiteOk;
+      break;
+    }
+
+    default:
+      // TODO(kreeger): Handle this case for full quant svdf b/139435798
+      context->ReportError(context, "Type %s not currently supported.",
+                           TfLiteTypeGetName(weights_feature->type));
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+}  // namespace svdf
+
+TfLiteRegistration* Register_SVDF() {
+  static TfLiteRegistration r = {svdf::Init, svdf::Free, svdf::Prepare,
+                                 svdf::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/kernels/unpack.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/kernels/unpack.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,116 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+namespace tflite {
+namespace ops {
+namespace micro {
+namespace unpack {
+namespace {
+
+constexpr int kInputTensor = 0;
+
+TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+  return kTfLiteOk;
+}
+
+template <typename T>
+TfLiteStatus UnpackImpl(TfLiteContext* context, TfLiteNode* node,
+                        const TfLiteTensor* input, int output_count, int axis) {
+  const TfLiteTensor* output0 = &context->tensors[node->outputs->data[0]];
+  const TfLiteIntArray* input_dims = input->dims;
+  const TfLiteIntArray* output_dims = output0->dims;
+  const int dimensions = input_dims->size;
+
+  if (axis < 0) {
+    axis += NumDimensions(input);
+  }
+
+  TFLITE_DCHECK_LT(axis, dimensions);
+
+  int outer_size = 1;
+  for (int i = 0; i < axis; ++i) {
+    outer_size *= input_dims->data[i];
+  }
+  int copy_size = 1;
+  for (int i = axis + 1; i < dimensions; ++i) {
+    copy_size *= input_dims->data[i];
+  }
+  int output_size = 1;
+  for (int i = 0; i < output_dims->size; ++i) {
+    output_size *= output_dims->data[i];
+  }
+  TFLITE_DCHECK_EQ(output_size, copy_size * outer_size);
+
+  const T* input_data = GetTensorData<T>(input);
+
+  for (int i = 0; i < output_count; ++i) {
+    TfLiteTensor* t = &context->tensors[node->outputs->data[i]];
+    T* output_data = GetTensorData<T>(t);
+    for (int k = 0; k < outer_size; ++k) {
+      T* output_ptr = output_data + copy_size * k;
+      int loc = k * output_count * copy_size + i * copy_size;
+      const T* input_ptr = input_data + loc;
+      for (int j = 0; j < copy_size; ++j) output_ptr[j] = input_ptr[j];
+    }
+  }
+
+  return kTfLiteOk;
+}
+
+TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+  TfLiteUnpackParams* data =
+      reinterpret_cast<TfLiteUnpackParams*>(node->builtin_data);
+
+  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
+
+  switch (input->type) {
+    case kTfLiteFloat32: {
+      return UnpackImpl<float>(context, node, input, data->num, data->axis);
+    }
+    case kTfLiteInt32: {
+      return UnpackImpl<int32_t>(context, node, input, data->num, data->axis);
+    }
+    case kTfLiteUInt8: {
+      return UnpackImpl<uint8_t>(context, node, input, data->num, data->axis);
+    }
+    case kTfLiteInt8: {
+      return UnpackImpl<int8_t>(context, node, input, data->num, data->axis);
+    }
+    default: {
+      context->ReportError(context, "Type '%s' is not supported by unpack.",
+                           TfLiteTypeGetName(input->type));
+      return kTfLiteError;
+    }
+  }
+
+  return kTfLiteOk;
+}
+}  // namespace
+}  // namespace unpack
+
+TfLiteRegistration* Register_UNPACK() {
+  static TfLiteRegistration r = {nullptr, nullptr, unpack::Prepare,
+                                 unpack::Eval};
+  return &r;
+}
+
+}  // namespace micro
+}  // namespace ops
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/mbed/debug_log.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/mbed/debug_log.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,24 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/experimental/micro/debug_log.h"
+
+#include <mbed.h>
+
+// On mbed platforms, we set up a serial port and write to it for debug logging.
+extern "C" void DebugLog(const char* s) {
+  static Serial pc(USBTX, USBRX);
+  pc.printf("%s", s);
+}

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/memory_helpers.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/memory_helpers.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,95 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/experimental/micro/memory_helpers.h"
+
+#include <cstdint>
+
+#include "tensorflow/lite/core/api/flatbuffer_conversions.h"
+
+namespace tflite {
+
+uint8_t* AlignPointerUp(uint8_t* data, size_t alignment) {
+  std::uintptr_t data_as_uintptr_t = reinterpret_cast<std::uintptr_t>(data);
+  uint8_t* aligned_result = reinterpret_cast<uint8_t*>(
+      ((data_as_uintptr_t + (alignment - 1)) / alignment) * alignment);
+  return aligned_result;
+}
+
+uint8_t* AlignPointerDown(uint8_t* data, size_t alignment) {
+  std::uintptr_t data_as_uintptr_t = reinterpret_cast<std::uintptr_t>(data);
+  uint8_t* aligned_result =
+      reinterpret_cast<uint8_t*>((data_as_uintptr_t / alignment) * alignment);
+  return aligned_result;
+}
+
+size_t AlignSizeUp(size_t size, size_t alignment) {
+  size_t aligned_size = (((size + (alignment - 1)) / alignment) * alignment);
+  return aligned_size;
+}
+
+TfLiteStatus TfLiteTypeSizeOf(TfLiteType type, size_t* size,
+                              ErrorReporter* reporter) {
+  switch (type) {
+    case kTfLiteFloat32:
+      *size = sizeof(float);
+      break;
+    case kTfLiteInt16:
+      *size = sizeof(int16_t);
+      break;
+    case kTfLiteInt32:
+      *size = sizeof(int32_t);
+      break;
+    case kTfLiteUInt8:
+      *size = sizeof(uint8_t);
+      break;
+    case kTfLiteInt8:
+      *size = sizeof(int8_t);
+      break;
+    case kTfLiteInt64:
+      *size = sizeof(int64_t);
+      break;
+    case kTfLiteBool:
+      *size = sizeof(bool);
+      break;
+    case kTfLiteComplex64:
+      *size = sizeof(float) * 2;
+      break;
+    default:
+      reporter->Report("Type %s (%d) not is not supported",
+                       TfLiteTypeGetName(type), type);
+      return kTfLiteError;
+  }
+  return kTfLiteOk;
+}
+
+TfLiteStatus BytesRequiredForTensor(const tflite::Tensor& flatbuffer_tensor,
+                                    size_t* bytes, size_t* type_size,
+                                    ErrorReporter* error_reporter) {
+  int element_count = 1;
+  for (size_t n = 0; n < flatbuffer_tensor.shape()->Length(); ++n) {
+    element_count *= flatbuffer_tensor.shape()->Get(n);
+  }
+
+  TfLiteType tf_lite_type;
+  TF_LITE_ENSURE_STATUS(ConvertTensorType(flatbuffer_tensor.type(),
+                                          &tf_lite_type, error_reporter));
+  TF_LITE_ENSURE_STATUS(
+      TfLiteTypeSizeOf(tf_lite_type, type_size, error_reporter));
+  *bytes = element_count * (*type_size);
+  return kTfLiteOk;
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/memory_helpers.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/memory_helpers.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,44 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MEMORY_HELPERS_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MEMORY_HELPERS_H_
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/core/api/error_reporter.h"
+#include "tensorflow/lite/schema/schema_generated.h"
+
+namespace tflite {
+
+// Returns the next pointer address aligned to the given alignment.
+uint8_t* AlignPointerUp(uint8_t* data, size_t alignment);
+
+// Returns the previous pointer address aligned to the given alignment.
+uint8_t* AlignPointerDown(uint8_t* data, size_t alignment);
+
+// Returns an increased size that's a multiple of alignment.
+size_t AlignSizeUp(size_t size, size_t alignment);
+
+// Returns size in bytes for a given TfLiteType.
+TfLiteStatus TfLiteTypeSizeOf(TfLiteType type, size_t* size,
+                              ErrorReporter* reporter);
+
+// How many bytes are needed to hold a tensor's contents.
+TfLiteStatus BytesRequiredForTensor(const tflite::Tensor& flatbuffer_tensor,
+                                    size_t* bytes, size_t* type_size,
+                                    ErrorReporter* error_reporter);
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MEMORY_HELPERS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/memory_planner/greedy_memory_planner.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/memory_planner/greedy_memory_planner.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,386 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/experimental/micro/memory_planner/greedy_memory_planner.h"
+
+namespace tflite {
+
+// Simple stable in-place sort function. Not time-efficient for large arrays.
+// Would normally be in an anonymous namespace to keep it private, but we want
+// to be able to test it externally.
+void ReverseSortInPlace(int* values, int* ids, int size) {
+  bool any_swapped;
+  do {
+    any_swapped = false;
+    for (int i = 1; i < size; ++i) {
+      if (values[i - 1] < values[i]) {
+        const int value_temp = values[i - 1];
+        values[i - 1] = values[i];
+        values[i] = value_temp;
+        const int id_temp = ids[i - 1];
+        ids[i - 1] = ids[i];
+        ids[i] = id_temp;
+        any_swapped = true;
+      }
+    }
+  } while (any_swapped);
+}
+
+GreedyMemoryPlanner::GreedyMemoryPlanner(unsigned char* scratch_buffer,
+                                         int scratch_buffer_size)
+    : buffer_count_(0), need_to_calculate_offsets_(true) {
+  const int per_buffer_size = sizeof(BufferRequirements) +  // requirements_
+                              sizeof(int) +  // buffer_sizes_sorted_by_size_
+                              sizeof(int) +  // buffer_ids_sorted_by_size_
+                              sizeof(ListEntry) +  // buffers_sorted_by_offset_
+                              sizeof(int);         // buffer_offsets_;
+  // Allocate the arrays we need within the scratch buffer arena.
+  max_buffer_count_ = scratch_buffer_size / per_buffer_size;
+
+  unsigned char* next_free = scratch_buffer;
+  requirements_ = reinterpret_cast<BufferRequirements*>(next_free);
+  next_free += sizeof(BufferRequirements) * max_buffer_count_;
+
+  buffer_sizes_sorted_by_size_ = reinterpret_cast<int*>(next_free);
+  next_free += sizeof(int) * max_buffer_count_;
+
+  buffer_ids_sorted_by_size_ = reinterpret_cast<int*>(next_free);
+  next_free += sizeof(int) * max_buffer_count_;
+
+  buffers_sorted_by_offset_ = reinterpret_cast<ListEntry*>(next_free);
+  next_free += sizeof(ListEntry) * max_buffer_count_;
+
+  buffer_offsets_ = reinterpret_cast<int*>(next_free);
+}
+
+GreedyMemoryPlanner::~GreedyMemoryPlanner() {
+  // We don't own the scratch buffer, so don't deallocate anything.
+}
+
+TfLiteStatus GreedyMemoryPlanner::AddBuffer(
+    tflite::ErrorReporter* error_reporter, int size, int first_time_used,
+    int last_time_used) {
+  if (buffer_count_ >= max_buffer_count_) {
+    error_reporter->Report("Too many buffers (max is %d)", max_buffer_count_);
+    return kTfLiteError;
+  }
+  BufferRequirements* current = &requirements_[buffer_count_];
+  current->size = size;
+  current->first_time_used = first_time_used;
+  current->last_time_used = last_time_used;
+  ++buffer_count_;
+  need_to_calculate_offsets_ = true;
+  return kTfLiteOk;
+}
+
+bool GreedyMemoryPlanner::DoesEntryOverlapInTime(
+    const GreedyMemoryPlanner::ListEntry* entry, const int first_time_used,
+    const int last_time_used) const {
+  const BufferRequirements* entry_requirements =
+      &requirements_[entry->requirements_index];
+  if (entry_requirements->first_time_used > last_time_used) {
+    return false;
+  }
+  if (first_time_used > entry_requirements->last_time_used) {
+    return false;
+  }
+  return true;
+}
+
+GreedyMemoryPlanner::ListEntry*
+GreedyMemoryPlanner::NextSimultaneouslyActiveBuffer(
+    const GreedyMemoryPlanner::ListEntry* start, const int first_time_used,
+    const int last_time_used) {
+  ListEntry* result = nullptr;
+  ListEntry* candidate_next_entry;
+  if (start == nullptr) {
+    candidate_next_entry = &buffers_sorted_by_offset_[0];
+  } else {
+    if (start->next_entry_index == -1) {
+      return nullptr;
+    }
+    candidate_next_entry = &buffers_sorted_by_offset_[start->next_entry_index];
+  }
+  do {
+    if (DoesEntryOverlapInTime(candidate_next_entry, first_time_used,
+                               last_time_used)) {
+      result = candidate_next_entry;
+      break;
+    }
+    if (candidate_next_entry->next_entry_index == -1) {
+      break;
+    }
+    candidate_next_entry =
+        &buffers_sorted_by_offset_[candidate_next_entry->next_entry_index];
+  } while (true);
+  return result;
+}
+
+void GreedyMemoryPlanner::CalculateOffsetsIfNeeded() {
+  if (!need_to_calculate_offsets_ || (buffer_count_ == 0)) {
+    return;
+  }
+  need_to_calculate_offsets_ = false;
+
+  // Start off by ordering the buffers in descending order of size.
+  // This helps find a more compact layout. Intuitively, you can think
+  // about putting the large buffers in place first, and then the
+  // smaller buffers can fit in the gaps, rather than fragmenting the
+  // gaps with small buffers at the beginning.
+  for (int i = 0; i < buffer_count_; ++i) {
+    buffer_sizes_sorted_by_size_[i] = requirements_[i].size;
+    buffer_ids_sorted_by_size_[i] = i;
+    buffer_offsets_[i] = -1;
+  }
+  // This sorting algorithm is naive, and may end up taking a very long time
+  // with hundreds of buffers.
+  ReverseSortInPlace(buffer_sizes_sorted_by_size_, buffer_ids_sorted_by_size_,
+                     buffer_count_);
+
+  // Put the largest buffer at offset zero to start the process.
+  ListEntry* first_entry = &buffers_sorted_by_offset_[0];
+  first_entry->offset = 0;
+  first_entry->requirements_index = buffer_ids_sorted_by_size_[0];
+  first_entry->next_entry_index = -1;
+  next_free_entry_ = 1;
+  buffer_offsets_[buffer_ids_sorted_by_size_[0]] = 0;
+
+  // Work through the rest of the buffers to find a good gap to place each one.
+  for (int i = 1; i < buffer_count_; ++i) {
+    // The id is the order the buffer was originally added by the client.
+    const int buffer_id = buffer_ids_sorted_by_size_[i];
+    // Look at what size and time range the buffer needs to be active.
+    BufferRequirements* wanted_requirements = &requirements_[buffer_id];
+    const int wanted_size = wanted_requirements->size;
+    const int wanted_first_time_used = wanted_requirements->first_time_used;
+    const int wanted_last_time_used = wanted_requirements->last_time_used;
+
+    // Find the first buffer that's active in our time range. All placed
+    // buffers are stored in the order of their starting position in the arena
+    // so that it's easy to find the next buffer in memory, and so the gap.
+    // The candidate_entry variable holds the buffer that we're considering
+    // placing the current buffer after.
+    ListEntry* prior_entry = nullptr;
+    int candidate_offset = 0;
+    // Loop through the offset-ordered list of buffers, looking for gaps.
+    while (true) {
+      // Find out what the next active buffer is.
+      ListEntry* next_entry = NextSimultaneouslyActiveBuffer(
+          prior_entry, wanted_first_time_used, wanted_last_time_used);
+
+      if (prior_entry) {
+        BufferRequirements* candidate_requirements =
+            &requirements_[prior_entry->requirements_index];
+        const int prior_entry_offset =
+            prior_entry->offset + candidate_requirements->size;
+        if (prior_entry_offset > candidate_offset) {
+          candidate_offset = prior_entry_offset;
+        }
+      }
+      if (next_entry == nullptr) {
+        // We're at the end of the list, so we can always append the buffer
+        // here.
+        break;
+      }
+      // Find out how much space there is between us and the next buffer.
+      const int gap = next_entry->offset - candidate_offset;
+      if (gap >= wanted_size) {
+        // This entry has a big enough gap between it and the next, so
+        // use it!
+        break;
+      }
+      // The gap wasn't big enough, so move on to another candidate.
+      prior_entry = next_entry;
+    }
+    // At this point, we've either found a gap (possibly at the end of the
+    // list) and want to place the buffer there, or there are no other active
+    // buffers in this time range and so we can put it at offset zero.
+    // Record the buffer's offset in our plan.
+    buffer_offsets_[buffer_id] = candidate_offset;
+    // Add the newly-placed buffer to our offset-ordered list, so that
+    // subsequent passes can fit in their buffers around it.
+    ListEntry* new_entry = &buffers_sorted_by_offset_[next_free_entry_];
+    new_entry->offset = candidate_offset;
+    new_entry->requirements_index = buffer_id;
+    const int new_entry_index = next_free_entry_;
+    ++next_free_entry_;
+    ListEntry* current_entry = first_entry;
+    // Make sure that we insert the buffer at the correct place in the ordered
+    // list.
+    while (true) {
+      const int next_entry_index = current_entry->next_entry_index;
+      if (next_entry_index == -1) {
+        // We're at the end of the list, so just add the new entry here.
+        current_entry->next_entry_index = new_entry_index;
+        new_entry->next_entry_index = -1;
+        break;
+      }
+      ListEntry* next_entry = &buffers_sorted_by_offset_[next_entry_index];
+      if (next_entry->offset > candidate_offset) {
+        // We're at the right spot to do an insertion and retain the sorting
+        // order, so place the new entry here.
+        new_entry->next_entry_index = current_entry->next_entry_index;
+        current_entry->next_entry_index = new_entry_index;
+        break;
+      }
+      current_entry = next_entry;
+    }
+  }
+}
+
+int GreedyMemoryPlanner::GetMaximumMemorySize() {
+  CalculateOffsetsIfNeeded();
+  if (buffer_count_ == 0) {
+    return 0;
+  }
+  ListEntry* entry = &buffers_sorted_by_offset_[0];
+  int max_size = 0;
+  while (entry) {
+    BufferRequirements* requirements =
+        &requirements_[entry->requirements_index];
+    const int current_size = entry->offset + requirements->size;
+    if (current_size > max_size) {
+      max_size = current_size;
+    }
+    if (entry->next_entry_index == -1) {
+      break;
+    }
+    entry = &buffers_sorted_by_offset_[entry->next_entry_index];
+  }
+  return max_size;
+}
+
+void GreedyMemoryPlanner::PrintMemoryPlan(ErrorReporter* error_reporter) {
+  CalculateOffsetsIfNeeded();
+
+  for (int i = 0; i < buffer_count_; ++i) {
+    error_reporter->Report(
+        "Planner buffer ID: %d, calculated offset: %d, size required: %d, "
+        "first_time_created: %d, "
+        "last_time_used: %d",
+        i, buffer_offsets_[i], requirements_[i].size,
+        requirements_[i].first_time_used, requirements_[i].last_time_used);
+  }
+
+  constexpr int kLineWidth = 80;
+  int max_size = kLineWidth;
+  int max_time = 0;
+  for (int i = 0; i < buffer_count_; ++i) {
+    BufferRequirements* requirements = &requirements_[i];
+    const int offset = buffer_offsets_[i];
+    const int last_time_used = requirements->last_time_used;
+    const int size = offset + requirements->size;
+    if (size > max_size) {
+      max_size = size;
+    }
+    if (last_time_used > max_time) {
+      max_time = last_time_used;
+    }
+  }
+
+  char line[kLineWidth + 1];
+  for (int t = 0; t <= max_time; ++t) {
+    for (int c = 0; c < kLineWidth; ++c) {
+      line[c] = '.';
+    }
+    for (int i = 0; i < buffer_count_; ++i) {
+      BufferRequirements* requirements = &requirements_[i];
+      if ((t < requirements->first_time_used) ||
+          (t > requirements->last_time_used)) {
+        continue;
+      }
+      const int offset = buffer_offsets_[i];
+      if (offset == -1) {
+        continue;
+      }
+      const int size = requirements->size;
+      const int line_start = (offset * kLineWidth) / max_size;
+      const int line_end = ((offset + size) * kLineWidth) / max_size;
+      for (int n = line_start; n < line_end; ++n) {
+        if (line[n] == '.') {
+          char display;
+          if (i < 10) {
+            display = '0' + i;
+          } else if (i < 36) {
+            display = 'a' + (i - 10);
+          } else if (i < 62) {
+            display = 'A' + (i - 36);
+          } else {
+            display = '*';
+          }
+          line[n] = display;
+        } else {
+          line[n] = '!';
+        }
+      }
+    }
+    line[kLineWidth] = 0;
+    error_reporter->Report("%s", line);
+  }
+}
+
+int GreedyMemoryPlanner::GetBufferCount() { return buffer_count_; }
+
+TfLiteStatus GreedyMemoryPlanner::GetOffsetForBuffer(
+    tflite::ErrorReporter* error_reporter, int buffer_index, int* offset) {
+  CalculateOffsetsIfNeeded();
+  if ((buffer_index < 0) || (buffer_index >= buffer_count_)) {
+    error_reporter->Report("buffer index %d is outside range 0 to %d",
+                           buffer_index, buffer_count_);
+    return kTfLiteError;
+  }
+  *offset = buffer_offsets_[buffer_index];
+  return kTfLiteOk;
+}
+
+bool GreedyMemoryPlanner::DoAnyBuffersOverlap(ErrorReporter* error_reporter) {
+  CalculateOffsetsIfNeeded();
+  bool were_overlaps_found = false;
+  for (int i = 0; i < buffer_count_; ++i) {
+    BufferRequirements* a_requirements = &requirements_[i];
+    const int a_start_offset = buffer_offsets_[i];
+    const int a_first_time_used = a_requirements->first_time_used;
+    const int a_last_time_used = a_requirements->last_time_used;
+    const int a_end_offset = a_start_offset + a_requirements->size;
+    for (int j = 0; j < buffer_count_; ++j) {
+      if (i == j) {
+        continue;
+      }
+      BufferRequirements* b_requirements = &requirements_[j];
+      const int b_start_offset = buffer_offsets_[j];
+      const int b_first_time_used = b_requirements->first_time_used;
+      const int b_last_time_used = b_requirements->last_time_used;
+      const int b_end_offset = b_start_offset + b_requirements->size;
+      if ((a_first_time_used > b_last_time_used) ||
+          (b_first_time_used > a_last_time_used)) {
+        // Buffers don't overlap in time.
+        continue;
+      }
+      if ((a_start_offset >= b_end_offset) ||
+          (b_start_offset >= a_end_offset)) {
+        // No overlap in memory.
+        continue;
+      }
+      were_overlaps_found = true;
+      error_reporter->Report(
+          "Overlap: %d (%d=>%d, %d->%d) vs %d (%d=>%d, %d->%d)", i,
+          a_first_time_used, a_last_time_used, a_start_offset, a_end_offset, j,
+          b_first_time_used, b_last_time_used, b_start_offset, b_end_offset);
+    }
+  }
+  return were_overlaps_found;
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/memory_planner/greedy_memory_planner.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/memory_planner/greedy_memory_planner.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,132 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MEMORY_PLANNER_GREEDY_MEMORY_PLANNER_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MEMORY_PLANNER_GREEDY_MEMORY_PLANNER_H_
+
+#include "tensorflow/lite/experimental/micro/memory_planner/memory_planner.h"
+
+namespace tflite {
+
+// A memory planner that uses a greedy algorithm to arrange buffers in memory
+// to minimize the overall arena size needed.
+//
+// The algorithm works like this:
+//  - The client enters the buffer information through AddBuffer().
+//  - When a function like GetOffsetForBuffer() is called, the
+//    CalculateOffsetsIfNeeded() method is invoked.
+//  - If an up to date plan is not already present, one will be calculated.
+//  - The buffers are sorted in descending order of size.
+//  - The largest buffer is placed at offset zero.
+//  - The rest of the buffers are looped through in descending size order.
+//  - The other buffers that need to be in memory at the same time are found.
+//  - The first gap between simultaneously active buffers that the current
+//    buffer fits into will be used.
+//  - If no large-enough gap is found, the current buffer is placed after the
+//    last buffer that's simultaneously active.
+//  - This continues until all buffers are placed, and the offsets stored.
+//
+// This is not guaranteed to produce the best placement, since that's an
+// NP-Complete problem, but in practice it should produce one that's decent.
+class GreedyMemoryPlanner : public MemoryPlanner {
+ public:
+  // You need to pass in an area of memory to be used for planning. This memory
+  // needs to have a lifetime as long as the planner, but isn't owned by this
+  // object, so management should be handled by the client. This is so it can be
+  // stack or globally allocated if necessary on devices without dynamic memory
+  // allocation. How many buffers can be planned for will depend on the size of
+  // this scratch memory, so you should enlarge it if you see an error when
+  // calling AddBuffer(). The memory can be reused once you're done with the
+  // planner, as long as you copy the calculated offsets to another location.
+  // Each buffer requires about 36 bytes of scratch.
+  GreedyMemoryPlanner(unsigned char* scratch_buffer, int scratch_buffer_size);
+  ~GreedyMemoryPlanner() override;
+
+  // Record details of a buffer we want to place.
+  TfLiteStatus AddBuffer(ErrorReporter* error_reporter, int size,
+                         int first_time_used, int last_time_used) override;
+
+  // Returns the high-water mark of used memory. This is the minimum size of a
+  // memory arena you'd need to allocate to hold these buffers.
+  int GetMaximumMemorySize() override;
+
+  // How many buffers have been recorded.
+  int GetBufferCount() override;
+
+  // Where a given buffer should be placed in the memory arena.
+  // This information is stored in the memory arena itself, so once the arena
+  // is used for inference, it will be overwritten.
+  TfLiteStatus GetOffsetForBuffer(ErrorReporter* error_reporter,
+                                  int buffer_index, int* offset) override;
+
+  // Prints an ascii-art diagram of the buffer layout plan.
+  void PrintMemoryPlan(ErrorReporter* error_reporter);
+
+  // Debug method to check whether any buffer allocations are overlapping. This
+  // is an O(N^2) complexity operation, so only use for testing.
+  bool DoAnyBuffersOverlap(ErrorReporter* error_reporter);
+
+  // Used to store a list of buffers ordered by their offset.
+  struct ListEntry {
+    int offset;
+    int requirements_index;
+    int next_entry_index;
+  };
+
+ private:
+  // Whether a buffer is active in a given time range.
+  bool DoesEntryOverlapInTime(const ListEntry* entry, const int first_time_used,
+                              const int last_time_used) const;
+
+  // Walks the list to return the next buffer that is active in a given time
+  // range, or a null pointer if there are none.
+  ListEntry* NextSimultaneouslyActiveBuffer(const ListEntry* start,
+                                            const int first_time_used,
+                                            const int last_time_used);
+
+  // If there isn't an up to date plan, calculate a new one.
+  void CalculateOffsetsIfNeeded();
+
+  // How many buffers we can plan for, based on the arena size we're given in
+  // the constructor.
+  int max_buffer_count_;
+
+  // The number of buffers added so far.
+  int buffer_count_;
+
+  // Records the client-provided information about each buffer.
+  struct BufferRequirements {
+    int size;
+    int first_time_used;
+    int last_time_used;
+  };
+
+  // Working arrays used during the layout algorithm.
+  BufferRequirements* requirements_;
+  int* buffer_sizes_sorted_by_size_;
+  int* buffer_ids_sorted_by_size_;
+  ListEntry* buffers_sorted_by_offset_;
+  int next_free_entry_;
+
+  // Stores the outcome of the plan, the location of each buffer in the arena.
+  int* buffer_offsets_;
+
+  // Whether buffers have been added since the last plan was calculated.
+  bool need_to_calculate_offsets_;
+};
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MEMORY_PLANNER_GREEDY_MEMORY_PLANNER_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/memory_planner/linear_memory_planner.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/memory_planner/linear_memory_planner.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,52 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/experimental/micro/memory_planner/linear_memory_planner.h"
+
+namespace tflite {
+
+LinearMemoryPlanner::LinearMemoryPlanner()
+    : current_buffer_count_(0), next_free_offset_(0) {}
+LinearMemoryPlanner::~LinearMemoryPlanner() {}
+
+TfLiteStatus LinearMemoryPlanner::AddBuffer(
+    tflite::ErrorReporter* error_reporter, int size, int first_time_used,
+    int last_time_used) {
+  if (current_buffer_count_ >= kMaxBufferCount) {
+    error_reporter->Report("Too many buffers (max is %d)", kMaxBufferCount);
+    return kTfLiteError;
+  }
+  buffer_offsets_[current_buffer_count_] = next_free_offset_;
+  next_free_offset_ += size;
+  ++current_buffer_count_;
+  return kTfLiteOk;
+}
+
+int LinearMemoryPlanner::GetMaximumMemorySize() { return next_free_offset_; }
+
+int LinearMemoryPlanner::GetBufferCount() { return current_buffer_count_; }
+
+TfLiteStatus LinearMemoryPlanner::GetOffsetForBuffer(
+    tflite::ErrorReporter* error_reporter, int buffer_index, int* offset) {
+  if ((buffer_index < 0) || (buffer_index >= current_buffer_count_)) {
+    error_reporter->Report("buffer index %d is outside range 0 to %d",
+                           buffer_index, current_buffer_count_);
+    return kTfLiteError;
+  }
+  *offset = buffer_offsets_[buffer_index];
+  return kTfLiteOk;
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/memory_planner/linear_memory_planner.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/memory_planner/linear_memory_planner.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,47 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MEMORY_PLANNER_LINEAR_MEMORY_PLANNER_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MEMORY_PLANNER_LINEAR_MEMORY_PLANNER_H_
+
+#include "tensorflow/lite/experimental/micro/memory_planner/memory_planner.h"
+
+namespace tflite {
+
+// The simplest possible memory planner that just lays out all buffers at
+// increasing offsets without trying to reuse memory.
+class LinearMemoryPlanner : public MemoryPlanner {
+ public:
+  LinearMemoryPlanner();
+  ~LinearMemoryPlanner() override;
+
+  TfLiteStatus AddBuffer(tflite::ErrorReporter* error_reporter, int size,
+                         int first_time_used, int last_time_used) override;
+
+  int GetMaximumMemorySize() override;
+  int GetBufferCount() override;
+  TfLiteStatus GetOffsetForBuffer(tflite::ErrorReporter* error_reporter,
+                                  int buffer_index, int* offset) override;
+
+ private:
+  static constexpr int kMaxBufferCount = 1024;
+  int buffer_offsets_[kMaxBufferCount];
+  int current_buffer_count_;
+  int next_free_offset_;
+};
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MEMORY_PLANNER_LINEAR_MEMORY_PLANNER_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/memory_planner/memory_planner.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/memory_planner/memory_planner.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,71 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MEMORY_PLANNER_MEMORY_PLANNER_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MEMORY_PLANNER_MEMORY_PLANNER_H_
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/core/api/error_reporter.h"
+
+namespace tflite {
+
+// Interface class for planning the layout of memory buffers during the
+// execution of a graph.
+// It's designed to be used by a client that iterates in any order through the
+// buffers it wants to lay out, and then calls the getter functions for
+// information about the calculated layout. For example:
+//
+// SomeMemoryPlanner planner;
+// planner.AddBuffer(reporter, 100, 0, 1);  // Buffer 0
+// planner.AddBuffer(reporter, 50, 2, 3);   // Buffer 1
+// planner.AddBuffer(reporter, 50, 2, 3);   // Buffer 2
+//
+// int offset0;
+// TF_EXPECT_OK(planner.GetOffsetForBuffer(reporter, 0, &offset0));
+// int offset1;
+// TF_EXPECT_OK(planner.GetOffsetForBuffer(reporter, 1, &offset1));
+// int offset2;
+// TF_EXPECT_OK(planner.GetOffsetForBuffer(reporter, 2, &offset2));
+// const int arena_size_needed = planner.GetMaximumMemorySize();
+//
+// The goal is for applications to be able to experiment with different layout
+// strategies without changing their client code, by swapping out classes that
+// implement this interface.=
+class MemoryPlanner {
+ public:
+  MemoryPlanner() {}
+  virtual ~MemoryPlanner() {}
+
+  // Pass information about a buffer's size and lifetime to the layout
+  // algorithm. The order this is called implicitly assigns an index to the
+  // result, so the buffer information that's passed into the N-th call of
+  // this method will be used as the buffer_index argument to
+  // GetOffsetForBuffer().
+  virtual TfLiteStatus AddBuffer(tflite::ErrorReporter* error_reporter,
+                                 int size, int first_time_used,
+                                 int last_time_used) = 0;
+
+  // The largest contguous block of memory that's needed to hold the layout.
+  virtual int GetMaximumMemorySize() = 0;
+  // How many buffers have been added to the planner.
+  virtual int GetBufferCount() = 0;
+  // Calculated layout offset for the N-th buffer added to the planner.
+  virtual TfLiteStatus GetOffsetForBuffer(tflite::ErrorReporter* error_reporter,
+                                          int buffer_index, int* offset) = 0;
+};
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MEMORY_PLANNER_MEMORY_PLANNER_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/micro_allocator.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/micro_allocator.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,501 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/experimental/micro/micro_allocator.h"
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/core/api/flatbuffer_conversions.h"
+#include "tensorflow/lite/core/api/op_resolver.h"
+#include "tensorflow/lite/core/api/tensor_utils.h"
+#include "tensorflow/lite/experimental/micro/compatibility.h"
+#include "tensorflow/lite/experimental/micro/memory_helpers.h"
+#include "tensorflow/lite/experimental/micro/memory_planner/greedy_memory_planner.h"
+#include "tensorflow/lite/experimental/micro/simple_memory_allocator.h"
+
+namespace tflite {
+
+namespace {
+// Used to hold information used during allocation calculations.
+struct TensorInfo {
+  const tflite::Tensor* flatbuffer_tensor;
+  TfLiteTensor* runtime_tensor;
+  int first_created;
+  int last_used;
+  bool needs_allocating;
+};
+
+// We align tensor buffers to 16-byte boundaries, since this is a common
+// requirement for SIMD extensions.
+constexpr int kBufferAlignment = 16;
+// For common data structures that doesn't need SIMD extensions.
+constexpr int kDefaultAlignment = sizeof(int);
+
+class MicroBuiltinDataAllocator : public BuiltinDataAllocator {
+ public:
+  explicit MicroBuiltinDataAllocator(SimpleMemoryAllocator* memory_allocator)
+      : memory_allocator_(memory_allocator) {}
+
+  void* Allocate(size_t size) override {
+    return memory_allocator_->AllocateFromTail(size, kDefaultAlignment);
+  }
+  void Deallocate(void* data) override {
+    // Do not deallocate, builtin data needs to be available for the life time
+    // of the model.
+  }
+
+ private:
+  SimpleMemoryAllocator* memory_allocator_;
+
+  TF_LITE_REMOVE_VIRTUAL_DELETE
+};
+
+}  // namespace
+
+MicroAllocator::MicroAllocator(TfLiteContext* context, const Model* model,
+                               uint8_t* tensor_arena, size_t arena_size,
+                               ErrorReporter* error_reporter)
+    : model_(model),
+      memory_allocator_(tensor_arena, arena_size),
+      error_reporter_(error_reporter),
+      context_(context),
+      arena_(tensor_arena),
+      arena_size_(arena_size) {
+  auto* subgraphs = model->subgraphs();
+  if (subgraphs->size() != 1) {
+    error_reporter->Report("Only 1 subgraph is currently supported.\n");
+    return;
+  }
+  subgraph_ = (*subgraphs)[0];
+  tensors_ = subgraph_->tensors();
+  operators_ = subgraph_->operators();
+
+  context_->tensors_size = tensors_->size();
+  context_->tensors =
+      reinterpret_cast<TfLiteTensor*>(memory_allocator_.AllocateFromTail(
+          sizeof(TfLiteTensor) * context_->tensors_size, kDefaultAlignment));
+
+  // Null all inputs so we can later perform a null check to avoid re-allocating
+  // registered pre-allocated inputs.
+  for (size_t i = 0; i < context_->tensors_size; ++i) {
+    context_->tensors[i].data.raw = nullptr;
+  }
+
+  active_ = true;
+}
+
+TfLiteStatus MicroAllocator::RegisterPreallocatedInput(uint8_t* buffer,
+                                                       size_t input_index) {
+  if (buffer == nullptr || input_index < 0 ||
+      input_index >= subgraph_->inputs()->size()) {
+    error_reporter_->Report("Invalid pre-allocated input %d provided.",
+                            input_index);
+    return kTfLiteError;
+  }
+  const flatbuffers::Vector<flatbuffers::Offset<Buffer>>* buffers =
+      model_->buffers();
+
+  const int tensor_index = subgraph_->inputs()->Get(input_index);
+  const auto* tensor = tensors_->Get(tensor_index);
+  return InitializeRuntimeTensor(*tensor, buffers, error_reporter_,
+                                 &context_->tensors[tensor_index], buffer);
+}
+
+TfLiteStatus MicroAllocator::AllocateNodeAndRegistrations(
+    const OpResolver& op_resolver,
+    NodeAndRegistration** node_and_registrations) {
+  if (!active_) {
+    return kTfLiteError;
+  }
+
+  auto* output =
+      reinterpret_cast<NodeAndRegistration*>(memory_allocator_.AllocateFromTail(
+          sizeof(NodeAndRegistration) * operators_->size(), kDefaultAlignment));
+  if (output == nullptr) {
+    error_reporter_->Report(
+        "Failed to allocate memory for node_and_registrations.");
+    return kTfLiteError;
+  }
+  TfLiteStatus status = kTfLiteOk;
+  auto* opcodes = model_->operator_codes();
+  MicroBuiltinDataAllocator builtin_data_allocator(&memory_allocator_);
+  for (size_t i = 0; i < operators_->size(); ++i) {
+    const auto* op = operators_->Get(i);
+    size_t index = op->opcode_index();
+    if (index < 0 || index >= opcodes->size()) {
+      error_reporter_->Report("Missing registration for opcode_index %d\n",
+                              index);
+      return kTfLiteError;
+    }
+    auto* opcode = (*opcodes)[index];
+    status = GetRegistrationFromOpCode(opcode, op_resolver, error_reporter_,
+                                       &(output[i].registration));
+    if (status != kTfLiteOk) {
+      error_reporter_->Report("Failed to get registration from op code % d\n ",
+                              opcode);
+      return status;
+    }
+    const auto* registration = output[i].registration;
+    if (registration == nullptr) {
+      error_reporter_->Report("Skipping op for opcode_index %d\n", index);
+      return kTfLiteError;
+    }
+    BuiltinOperator op_type =
+        static_cast<BuiltinOperator>(registration->builtin_code);
+
+    if (op_type != BuiltinOperator_CUSTOM && op->custom_options()) {
+      error_reporter_->Report(
+          "Unsupported behavior: found builtin operator %s with custom "
+          "options.\n",
+          EnumNameBuiltinOperator(op_type));
+      return kTfLiteError;
+    }
+
+    const char* custom_data = nullptr;
+    size_t custom_data_size = 0;
+    unsigned char* builtin_data = nullptr;
+    if (op->custom_options()) {
+      custom_data = reinterpret_cast<const char*>(op->custom_options()->data());
+      custom_data_size = op->custom_options()->size();
+    } else {
+      TF_LITE_ENSURE_STATUS(ParseOpData(op, op_type, error_reporter_,
+                                        &builtin_data_allocator,
+                                        (void**)(&builtin_data)));
+    }
+
+    // Disregard const qualifier to workaround with existing API.
+    TfLiteIntArray* inputs_array = const_cast<TfLiteIntArray*>(
+        reinterpret_cast<const TfLiteIntArray*>(op->inputs()));
+    TfLiteIntArray* outputs_array = const_cast<TfLiteIntArray*>(
+        reinterpret_cast<const TfLiteIntArray*>(op->outputs()));
+
+    TfLiteNode* node = &(output[i].node);
+    node->inputs = inputs_array;
+    node->outputs = outputs_array;
+    // This is OK for now as temporary array is not in used.
+    // TODO(wangtz): Support scratch buffers.
+    node->temporaries = nullptr;
+    node->user_data = nullptr;  // Will be filled in after `init`
+    node->builtin_data = reinterpret_cast<void*>(builtin_data);
+    node->custom_initial_data = custom_data;
+    node->custom_initial_data_size = custom_data_size;
+    node->delegate = nullptr;
+  }
+  *node_and_registrations = output;
+  return kTfLiteOk;
+}
+
+TfLiteStatus MicroAllocator::FinishTensorAllocation() {
+  if (!active_) {
+    return kTfLiteError;
+  }
+
+  const size_t tensors_size = tensors_->size();
+
+  const flatbuffers::Vector<flatbuffers::Offset<Buffer>>* buffers =
+      model_->buffers();
+
+  // Initialize runtime tensors.
+  for (size_t i = 0; i < tensors_size; ++i) {
+    auto* runtime_tensor = &context_->tensors[i];
+    auto* flatbuffer_tensor = tensors_->Get(i);
+
+    // Preallocated inputs have already been set up earlier, so skip them.
+    const bool is_preallocated_input = (runtime_tensor->data.raw != nullptr);
+    if (!is_preallocated_input) {
+      TF_LITE_ENSURE_STATUS(InitializeRuntimeTensor(*flatbuffer_tensor, buffers,
+                                                    error_reporter_,
+                                                    runtime_tensor, nullptr));
+    }
+  }
+
+  // tensor_info is only used in this function.
+  auto tmp_allocator = memory_allocator_.CreateChildAllocator();
+  TensorInfo* tensor_info =
+      reinterpret_cast<TensorInfo*>(tmp_allocator.AllocateFromTail(
+          sizeof(TensorInfo) * tensors_size, sizeof(TensorInfo)));
+
+  // Set up the runtime data structures for all tensors.
+  for (size_t i = 0; i < tensors_size; ++i) {
+    TensorInfo* current = &tensor_info[i];
+    current->flatbuffer_tensor = &(*(tensors_->Get(i)));
+    current->runtime_tensor = &context_->tensors[i];
+    const bool is_variable = current->flatbuffer_tensor->is_variable();
+    if (is_variable) {
+      current->first_created = 0;
+      current->last_used = operators_->size();
+    } else {
+      current->first_created = -1;
+      current->last_used = -1;
+    }
+    current->needs_allocating = false;
+  }
+
+  // First go through the inputs and figure out if they need to be allocated.
+  for (size_t i = 0; i < subgraph_->inputs()->size(); ++i) {
+    const int tensor_index = subgraph_->inputs()->Get(i);
+    TensorInfo* current = &tensor_info[tensor_index];
+    // Check for pre-allocated inputs.
+    current->needs_allocating = (current->runtime_tensor->data.raw == nullptr);
+    current->first_created = 0;
+  }
+
+  // Mark all outputs as persistent to the end of the invocation.
+  for (size_t i = 0; i < subgraph_->outputs()->size(); ++i) {
+    const int tensor_index = subgraph_->outputs()->Get(i);
+    TensorInfo* current = &tensor_info[tensor_index];
+    current->last_used = operators_->size() - 1;
+  }
+
+  // Figure out when the first and last use of each tensor is.
+  for (int i = (operators_->size() - 1); i >= 0; --i) {
+    const auto* op = operators_->Get(i);
+    for (size_t n = 0; n < op->inputs()->size(); ++n) {
+      const int tensor_index = op->inputs()->Get(n);
+      TensorInfo* current = &tensor_info[tensor_index];
+      if ((current->last_used == -1) || (current->last_used > i)) {
+        current->last_used = i;
+      }
+    }
+    for (size_t n = 0; n < op->outputs()->size(); ++n) {
+      const int tensor_index = op->outputs()->Get(n);
+      TensorInfo* current = &tensor_info[tensor_index];
+      if ((current->first_created == -1) || (current->first_created < i)) {
+        current->first_created = i;
+      }
+    }
+  }
+
+  // Work out which tensors need to be allocated.
+  for (size_t i = 0; i < tensors_->size(); ++i) {
+    TensorInfo* current = &tensor_info[i];
+    const bool is_read_only =
+        (current->first_created == -1) && (current->last_used != -1);
+    const bool is_preallocated_input =
+        (current->runtime_tensor->data.raw != nullptr);
+    const bool has_partial_lifetime =
+        !is_read_only &&
+        ((current->first_created == -1) || (current->last_used == -1));
+    if (has_partial_lifetime) {
+      error_reporter_->Report(
+          "Logic error in memory planner, tensor %d has an invalid lifetime",
+          i);
+      return kTfLiteError;
+    }
+    if (!is_read_only && !is_preallocated_input) {
+      current->needs_allocating = true;
+    }
+  }
+
+  uint8_t* aligned_arena = AlignPointerUp(arena_, kBufferAlignment);
+  const size_t alignment_loss = (aligned_arena - arena_);
+
+  // Remaining arena size that memory planner can use for calculating offsets.
+  int remaining_arena_size =
+      arena_size_ - (tmp_allocator.GetDataSize() + alignment_loss);
+  GreedyMemoryPlanner planner(aligned_arena, remaining_arena_size);
+
+  // Add the tensors to our allocation plan.
+  for (size_t i = 0; i < tensors_->size(); ++i) {
+    TensorInfo* current = &tensor_info[i];
+    if (current->needs_allocating) {
+      size_t bytes_required;
+      size_t type_size;
+      TF_LITE_ENSURE_STATUS(BytesRequiredForTensor(*current->flatbuffer_tensor,
+                                                   &bytes_required, &type_size,
+                                                   error_reporter_));
+      size_t aligned_bytes_required =
+          AlignSizeUp(bytes_required, kBufferAlignment);
+      TF_LITE_ENSURE_STATUS(
+          planner.AddBuffer(error_reporter_, aligned_bytes_required,
+                            current->first_created, current->last_used));
+    }
+  }
+
+  // Actual size available for placing tensors. This includes memory held by the
+  // tensor info array, which will be released.
+  int actual_available_arena_size =
+      arena_size_ - (memory_allocator_.GetDataSize() + alignment_loss);
+  // Make sure we have enough room.
+  if (planner.GetMaximumMemorySize() > actual_available_arena_size) {
+    error_reporter_->Report(
+        "Arena size is too small for activation buffers. Needed %d but only %d "
+        "was available.",
+        planner.GetMaximumMemorySize(), remaining_arena_size);
+    return kTfLiteError;
+  }
+
+  // Figure out the actual memory addresses for each buffer, based on the plan.
+  int planner_index = 0;
+  for (size_t i = 0; i < tensors_->size(); ++i) {
+    TensorInfo* current = &tensor_info[i];
+    if (current->needs_allocating) {
+      int offset;
+      TF_LITE_ENSURE_STATUS(
+          planner.GetOffsetForBuffer(error_reporter_, planner_index, &offset));
+      current->runtime_tensor->data.uint8 = aligned_arena + offset;
+      ++planner_index;
+    }
+  }
+
+  // Copy default value for variable tensors. Note that this will overwrite
+  // the arena planner data so GetOffsetForBuffer will return wrong
+  // result.
+  for (size_t i = 0; i < tensors_->size(); ++i) {
+    TensorInfo* current = &tensor_info[i];
+    // Set default value for variable tensors:
+    if (current->flatbuffer_tensor->is_variable()) {
+      if (current->runtime_tensor->data.uint8 == nullptr) {
+        error_reporter_->Report("Variable is not allocated");
+        return kTfLiteError;
+      }
+      tflite::ResetVariableTensor(current->runtime_tensor);
+    }
+  }
+
+  active_ = false;
+  return kTfLiteOk;
+}
+
+TfLiteStatus MicroAllocator::InitializeRuntimeTensor(
+    const tflite::Tensor& flatbuffer_tensor,
+    const flatbuffers::Vector<flatbuffers::Offset<Buffer>>* buffers,
+    ErrorReporter* error_reporter, TfLiteTensor* result,
+    uint8_t* preallocated_buffer) {
+  if (!active_) {
+    return kTfLiteError;
+  }
+
+  // Make sure the serialized type is one we know how to deal with, and convert
+  // it from a flatbuffer enum into a constant used by the kernel C API.
+  TF_LITE_ENSURE_STATUS(ConvertTensorType(flatbuffer_tensor.type(),
+                                          &result->type, error_reporter));
+  // Make sure we remember if the serialized tensor is designated as a variable.
+  result->is_variable = flatbuffer_tensor.is_variable();
+
+  // We need to figure out where the actual contents of this tensor are stored
+  // in memory. We'll check to see if there's a serialized buffer (pretty much
+  // the same as a constant op in TensorFlow) associated with this tensor first,
+  // and if there is update the runtime structure to point to its location in
+  // memory.
+  result->data.raw = nullptr;
+  result->bytes = 0;
+  // First see if there's any buffer information in the serialized tensor.
+  if (auto* buffer = (*buffers)[flatbuffer_tensor.buffer()]) {
+    // If we've found a buffer, does it have any data?
+    if (auto* array = buffer->data()) {
+      // If it has any data, is the data size larger than zero?
+      if (size_t array_size = array->size()) {
+        // We've found a buffer with valid data, so update the runtime tensor
+        // data structure to point to it.
+        result->data.raw =
+            const_cast<char*>(reinterpret_cast<const char*>(array->data()));
+        // We set the data from a serialized buffer, so record tha.
+        result->allocation_type = kTfLiteMmapRo;
+      }
+    }
+    // TODO(petewarden): It's not clear in what circumstances we could have a
+    // buffer in the serialized tensor, but it doesn't have any data in it. Is
+    // that a validly-generated file, and if so what does it mean, or is it an
+    // error condition? It would be good to tighten up the specification to make
+    // it less ambiguous.
+  }
+
+  // TODO(petewarden): Some of these paths aren't getting enough testing
+  // coverage, so we should figure out some tests that exercise them.
+  if (!result->data.raw) {
+    // The tensor contents haven't been set from a serialized buffer, so
+    // make a note that they will be allocated from memory. The actual
+    // allocation won't happen until later.
+    result->allocation_type = kTfLiteArenaRw;
+    if (preallocated_buffer != nullptr) {
+      // If the client is supplying memory for the contents of the tensor
+      // themselves, use it.
+      // TODO(petewarden): Should we store the fact this is a client-allocated
+      // buffer?
+      result->data.raw = reinterpret_cast<char*>(preallocated_buffer);
+    }
+  }
+
+  // Figure out what the size in bytes of the buffer is and store it.
+  size_t type_size;
+  TF_LITE_ENSURE_STATUS(BytesRequiredForTensor(
+      flatbuffer_tensor, &result->bytes, &type_size, error_reporter));
+  // Copy the shape of the tensor from the serialized data into the runtime
+  // form. We have to allocate memory for this.
+  result->dims =
+      reinterpret_cast<TfLiteIntArray*>(memory_allocator_.AllocateFromTail(
+          sizeof(int) * (flatbuffer_tensor.shape()->Length() + 1),
+          kDefaultAlignment));
+  result->dims->size = flatbuffer_tensor.shape()->Length();
+  for (size_t n = 0; n < flatbuffer_tensor.shape()->Length(); ++n) {
+    result->dims->data[n] = flatbuffer_tensor.shape()->Get(n);
+  }
+  // Copy the quantization information from the serialized data.
+  const auto* src_quantization = flatbuffer_tensor.quantization();
+  if (src_quantization && src_quantization->scale() &&
+      (src_quantization->scale()->size() > 0) &&
+      src_quantization->zero_point() &&
+      (src_quantization->zero_point()->size() > 0)) {
+    result->params.scale = src_quantization->scale()->Get(0);
+    // This magic handles issues with little-endianness.
+    for (unsigned int b = 0; b < sizeof(int64_t); ++b)
+      *(reinterpret_cast<char*>(&result->params.zero_point) + b) =
+          *(reinterpret_cast<const char*>(
+                src_quantization->zero_point()->Data()) +
+            b);
+    result->params.zero_point =
+        flatbuffers::EndianScalar(result->params.zero_point);
+
+    // Populate per-channel quantization params.
+    int channels = src_quantization->scale()->size();
+    TfLiteAffineQuantization* quantization =
+        reinterpret_cast<TfLiteAffineQuantization*>(
+            memory_allocator_.AllocateFromTail(sizeof(TfLiteAffineQuantization),
+                                               kDefaultAlignment));
+    int* zero_point_array =
+        reinterpret_cast<int*>(memory_allocator_.AllocateFromTail(
+            channels * sizeof(int) + sizeof(int), kDefaultAlignment));
+    int* scale_array =
+        reinterpret_cast<int*>(memory_allocator_.AllocateFromTail(
+            channels * sizeof(float) + sizeof(int), kDefaultAlignment));
+    zero_point_array[0] = channels;
+    scale_array[0] = channels;
+    int* zero_point_data = &zero_point_array[1];
+    float* scale_data = reinterpret_cast<float*>(&scale_array[1]);
+    for (int i = 0; i < channels; i++) {
+      zero_point_data[i] = src_quantization->zero_point()->Get(i);
+      scale_data[i] = src_quantization->scale()->Get(i);
+    }
+    quantization->scale = reinterpret_cast<TfLiteFloatArray*>(scale_array);
+    quantization->zero_point =
+        reinterpret_cast<TfLiteIntArray*>(zero_point_array);
+
+    result->quantization = {kTfLiteAffineQuantization, quantization};
+  }
+  // Copy the name, if there is one.
+  if (flatbuffer_tensor.name()->c_str() != nullptr) {
+    result->name = flatbuffer_tensor.name()->c_str();
+  } else {
+    result->name = "<No name>";
+  }
+  // These aren't used by the micro flavor of TFL, so set them to defaults.
+  result->allocation = nullptr;
+  result->delegate = nullptr;
+  result->buffer_handle = 0;
+  result->data_is_stale = false;
+  return kTfLiteOk;
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/micro_allocator.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/micro_allocator.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,93 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_ALLOCATOR_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_ALLOCATOR_H_
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/core/api/error_reporter.h"
+#include "tensorflow/lite/core/api/flatbuffer_conversions.h"
+#include "tensorflow/lite/experimental/micro/simple_memory_allocator.h"
+#include "tensorflow/lite/schema/schema_generated.h"
+
+namespace tflite {
+
+typedef struct {
+  TfLiteNode node;
+  const TfLiteRegistration* registration;
+} NodeAndRegistration;
+
+// Allocator responsible for allocating memory for all intermediate tensors
+// necessary to invoke a model.
+class MicroAllocator {
+ public:
+  // The lifetime of the model, tensor allocator and error reporter must be at
+  // least as long as that of the allocator object, since the allocator needs
+  // them to be accessible during its entire lifetime.
+  MicroAllocator(TfLiteContext* context, const Model* model,
+                 uint8_t* tensor_arena, size_t arena_size,
+                 ErrorReporter* error_reporter);
+
+  // Specify a particular tensor as pre-allocated.  This means that this tensor
+  // will internally point to the supplied buffer, and no new memory will be
+  // provided.  The buffer must live at least as long as the allocator, since
+  // the buffer will be used every time an op is invoked which uses the
+  // specified tensor.  Most commonly this is useful when a platform-provided
+  // DMA buffer is used as an input, and it is desirable to avoid unnecessarily
+  // allocating a new buffer and copying from the DMA buffer. The user must
+  // ensure the buffer is valid throughout each interpreter run, and is not
+  // prematurely overwritten.
+  TfLiteStatus RegisterPreallocatedInput(uint8_t* buffer, size_t input_index);
+
+  // Sets up all of the data structure members for a runtime tensor based on the
+  // contents of a serialized tensor. This method doesn't allocate any memory,
+  // all allocations happen subsequently in AllocateTensors.
+  TfLiteStatus InitializeRuntimeTensor(
+      const tflite::Tensor& flatbuffer_tensor,
+      const flatbuffers::Vector<flatbuffers::Offset<Buffer>>* buffers,
+      ErrorReporter* error_reporter, TfLiteTensor* result,
+      uint8_t* preallocated_buffer = nullptr);
+
+  // Run through the model and allocate all necessary input, output and
+  // intermediate tensors except for those already provided via calls to
+  // registerPreallocatedInput.
+  // WARNING: doing any allocation after calling is method has the risk of
+  // corruption tensor data so this method is the last method to be called in
+  // this class.
+  TfLiteStatus FinishTensorAllocation();
+
+  // Run through the model to allocate nodes and registrations. We need to keep
+  // them for the entire life time of the model to allow persistent tensors.
+  // This method needs to be called before FinishTensorAllocation method.
+  TfLiteStatus AllocateNodeAndRegistrations(
+      const OpResolver& op_resolver,
+      NodeAndRegistration** node_and_registrations);
+
+ private:
+  const Model* model_;
+  SimpleMemoryAllocator memory_allocator_;
+  ErrorReporter* error_reporter_;
+  TfLiteContext* context_;
+  uint8_t* arena_;
+  size_t arena_size_;
+  // Indicating if the allocator is ready for allocation.
+  bool active_ = false;
+
+  const SubGraph* subgraph_;
+  const flatbuffers::Vector<flatbuffers::Offset<Operator>>* operators_;
+  const flatbuffers::Vector<flatbuffers::Offset<Tensor>>* tensors_;
+};
+
+}  // namespace tflite
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_ALLOCATOR_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/micro_error_reporter.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/micro_error_reporter.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,68 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/experimental/micro/micro_error_reporter.h"
+
+namespace tflite {
+namespace {
+void DebugLogPrintf(const char* format, va_list args) {
+  const int output_cache_size = 64;
+  char output_cache[output_cache_size + 1];
+  int output_cache_index = 0;
+  const char* current = format;
+  while (*current != 0) {
+    if (*current == '%') {
+      const char next = *(current + 1);
+      if ((next == 'd') || (next == 's') || (next == 'f')) {
+        current += 1;
+        if (output_cache_index > 0) {
+          output_cache[output_cache_index] = 0;
+          DebugLog(output_cache);
+          output_cache_index = 0;
+        }
+        if (next == 'd') {
+          DebugLogInt32(va_arg(args, int));
+        } else if (next == 's') {
+          DebugLog(va_arg(args, char*));
+        } else if (next == 'f') {
+          DebugLogFloat(va_arg(args, double));
+        }
+      }
+    } else {
+      output_cache[output_cache_index] = *current;
+      output_cache_index += 1;
+    }
+    if (output_cache_index >= output_cache_size) {
+      output_cache[output_cache_index] = 0;
+      DebugLog(output_cache);
+      output_cache_index = 0;
+    }
+    current += 1;
+  }
+  if (output_cache_index > 0) {
+    output_cache[output_cache_index] = 0;
+    DebugLog(output_cache);
+    output_cache_index = 0;
+  }
+  DebugLog("\r\n");
+}
+}  // namespace
+
+int MicroErrorReporter::Report(const char* format, va_list args) {
+  DebugLogPrintf(format, args);
+  return 0;
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/micro_error_reporter.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/micro_error_reporter.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,36 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_ERROR_REPORTER_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_ERROR_REPORTER_H_
+
+#include "tensorflow/lite/core/api/error_reporter.h"
+#include "tensorflow/lite/experimental/micro/compatibility.h"
+#include "tensorflow/lite/experimental/micro/debug_log.h"
+#include "tensorflow/lite/experimental/micro/debug_log_numbers.h"
+
+namespace tflite {
+
+class MicroErrorReporter : public ErrorReporter {
+ public:
+  ~MicroErrorReporter() {}
+  int Report(const char* format, va_list args) override;
+
+ private:
+  TF_LITE_REMOVE_VIRTUAL_DELETE
+};
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_ERROR_REPORTER_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/micro_interpreter.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/micro_interpreter.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,298 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/micro/micro_interpreter.h"
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/core/api/flatbuffer_conversions.h"
+#include "tensorflow/lite/experimental/micro/compatibility.h"
+
+namespace tflite {
+namespace {
+const int kStackDataAllocatorSize = 128;
+class StackDataAllocator : public BuiltinDataAllocator {
+ public:
+  void* Allocate(size_t size) override {
+    if (size > kStackDataAllocatorSize) {
+      return nullptr;
+    } else {
+      return data_;
+    }
+  }
+  void Deallocate(void* data) override {
+    // Do nothing.
+  }
+
+ private:
+  uint8_t data_[kStackDataAllocatorSize];
+
+  TF_LITE_REMOVE_VIRTUAL_DELETE
+};
+
+const char* OpNameFromRegistration(const TfLiteRegistration* registration) {
+  if (registration->builtin_code == BuiltinOperator_CUSTOM) {
+    return registration->custom_name;
+  } else {
+    return EnumNameBuiltinOperator(BuiltinOperator(registration->builtin_code));
+  }
+}
+
+void ReportOpError(struct TfLiteContext* context, const char* format, ...) {
+  MicroInterpreter* interpreter =
+      static_cast<MicroInterpreter*>(context->impl_);
+  va_list args;
+  va_start(args, format);
+  interpreter->error_reporter()->Report(format, args);
+  va_end(args);
+}
+
+}  // namespace
+
+MicroInterpreter::MicroInterpreter(const Model* model,
+                                   const OpResolver& op_resolver,
+                                   uint8_t* tensor_arena,
+                                   size_t tensor_arena_size,
+                                   ErrorReporter* error_reporter)
+    : model_(model),
+      op_resolver_(op_resolver),
+      error_reporter_(error_reporter),
+      context_(),
+      allocator_(&context_, model_, tensor_arena, tensor_arena_size,
+                 error_reporter_),
+      tensors_allocated_(false) {
+  auto* subgraphs = model->subgraphs();
+  if (subgraphs->size() != 1) {
+    error_reporter->Report("Only 1 subgraph is currently supported.\n");
+    initialization_status_ = kTfLiteError;
+    return;
+  }
+  subgraph_ = (*subgraphs)[0];
+  tensors_ = subgraph_->tensors();
+  operators_ = subgraph_->operators();
+
+  context_.impl_ = static_cast<void*>(this);
+  context_.ReportError = ReportOpError;
+  context_.recommended_num_threads = 1;
+
+  // If the system is big endian then convert weights from the flatbuffer from
+  // little to big endian on startup so that it does not need to be done during
+  // inference.
+  // NOTE: This requires that the flatbuffer is held in memory which can be
+  // modified by this process.
+  if (!FLATBUFFERS_LITTLEENDIAN) {
+    for (int t = 0; t < tensors_size(); ++t) {
+      TfLiteTensor* thisTensor = &context_.tensors[t];
+      if (thisTensor->allocation_type == kTfLiteMmapRo)
+        CorrectTensorEndianness(thisTensor);
+    }
+  }
+
+  initialization_status_ = kTfLiteOk;
+}
+
+void MicroInterpreter::CorrectTensorEndianness(TfLiteTensor* tensorCorr) {
+  int32_t tensorSize = 1;
+  for (int d = 0; d < tensorCorr->dims->size; ++d)
+    tensorSize *= reinterpret_cast<const int32_t*>(tensorCorr->dims->data)[d];
+
+  switch (tensorCorr->type) {
+    case TfLiteType::kTfLiteFloat32:
+      CorrectTensorDataEndianness(tensorCorr->data.f, tensorSize);
+      break;
+    case TfLiteType::kTfLiteFloat16:
+      CorrectTensorDataEndianness(tensorCorr->data.f16, tensorSize);
+      break;
+    case TfLiteType::kTfLiteInt64:
+      CorrectTensorDataEndianness(tensorCorr->data.i64, tensorSize);
+      break;
+    case TfLiteType::kTfLiteInt32:
+      CorrectTensorDataEndianness(tensorCorr->data.i32, tensorSize);
+      break;
+    case TfLiteType::kTfLiteInt16:
+      CorrectTensorDataEndianness(tensorCorr->data.i16, tensorSize);
+      break;
+    case TfLiteType::kTfLiteComplex64:
+      CorrectTensorDataEndianness(tensorCorr->data.c64, tensorSize);
+      break;
+    default:
+      // Do nothing for other data types.
+      break;
+  }
+}
+
+template <class T>
+void MicroInterpreter::CorrectTensorDataEndianness(T* data, int32_t size) {
+  for (int32_t i = 0; i < size; ++i) {
+    data[i] = flatbuffers::EndianScalar(data[i]);
+  }
+}
+
+TfLiteStatus MicroInterpreter::RegisterPreallocatedInput(uint8_t* buffer,
+                                                         size_t input_index) {
+  return allocator_.RegisterPreallocatedInput(buffer, input_index);
+}
+
+TfLiteStatus MicroInterpreter::AllocateTensors() {
+  TF_LITE_ENSURE_OK(&context_, allocator_.AllocateNodeAndRegistrations(
+                                   op_resolver_, &node_and_registrations_));
+  TF_LITE_ENSURE_OK(&context_, allocator_.FinishTensorAllocation());
+
+  tensors_allocated_ = true;
+  return kTfLiteOk;
+}
+
+TfLiteStatus MicroInterpreter::Invoke() {
+  if (initialization_status_ != kTfLiteOk) {
+    error_reporter_->Report("Invoke() called after initialization failed\n");
+    return kTfLiteError;
+  }
+
+  // Ensure tensors are allocated before the interpreter is invoked to avoid
+  // difficult to debug segfaults.
+  if (!tensors_allocated_) {
+    AllocateTensors();
+  }
+
+  // Init method is not yet implemented.
+  for (size_t i = 0; i < operators_->size(); ++i) {
+    auto* node = &(node_and_registrations_[i].node);
+    auto* registration = node_and_registrations_[i].registration;
+    size_t init_data_size;
+    const char* init_data;
+    if (registration->builtin_code == BuiltinOperator_CUSTOM) {
+      init_data = reinterpret_cast<const char*>(node->custom_initial_data);
+      init_data_size = node->custom_initial_data_size;
+    } else {
+      init_data = reinterpret_cast<const char*>(node->builtin_data);
+      init_data_size = 0;
+    }
+    if (registration->init) {
+      node->user_data =
+          registration->init(&context_, init_data, init_data_size);
+    }
+  }
+
+  for (size_t i = 0; i < operators_->size(); ++i) {
+    auto* node = &(node_and_registrations_[i].node);
+    auto* registration = node_and_registrations_[i].registration;
+    if (registration->prepare) {
+      TfLiteStatus prepare_status = registration->prepare(&context_, node);
+      if (prepare_status != kTfLiteOk) {
+        error_reporter_->Report(
+            "Node %s (number %d) failed to prepare with status %d",
+            OpNameFromRegistration(registration), i, prepare_status);
+        return kTfLiteError;
+      }
+    }
+  }
+
+  for (size_t i = 0; i < operators_->size(); ++i) {
+    auto* node = &(node_and_registrations_[i].node);
+    auto* registration = node_and_registrations_[i].registration;
+
+    if (registration->invoke) {
+      TfLiteStatus invoke_status = registration->invoke(&context_, node);
+      if (invoke_status != kTfLiteOk) {
+        error_reporter_->Report(
+            "Node %s (number %d) failed to invoke with status %d",
+            OpNameFromRegistration(registration), i, invoke_status);
+        return kTfLiteError;
+      }
+    }
+  }
+
+  // This is actually a no-op.
+  // TODO(wangtz): Consider removing this code to slightly reduce binary size.
+  for (size_t i = 0; i < operators_->size(); ++i) {
+    auto* node = &(node_and_registrations_[i].node);
+    auto* registration = node_and_registrations_[i].registration;
+    if (registration->free) {
+      registration->free(&context_, node->user_data);
+    }
+  }
+  return kTfLiteOk;
+}
+
+TfLiteTensor* MicroInterpreter::input(size_t index) {
+  const flatbuffers::Vector<int32_t>* inputs = subgraph_->inputs();
+  const size_t length = inputs->size();
+  if ((index < 0) || (index >= length)) {
+    error_reporter_->Report("Input index %d out of range (length is %d)", index,
+                            length);
+    return nullptr;
+  }
+  return &(context_.tensors[inputs->Get(index)]);
+}
+
+TfLiteTensor* MicroInterpreter::output(size_t index) {
+  const flatbuffers::Vector<int32_t>* outputs = subgraph_->outputs();
+  const size_t length = outputs->size();
+  if ((index < 0) || (index >= outputs->size())) {
+    error_reporter_->Report("Output index %d out of range (length is %d)",
+                            index, length);
+    return nullptr;
+  }
+  return &(context_.tensors[outputs->Get(index)]);
+}
+
+TfLiteTensor* MicroInterpreter::tensor(size_t index) {
+  const size_t length = tensors_size();
+  if ((index < 0) || (index >= tensors_size())) {
+    error_reporter_->Report("Tensor index %d out of range (length is %d)",
+                            index, length);
+    return nullptr;
+  }
+  return &context_.tensors[index];
+}
+
+struct pairTfLiteNodeAndRegistration MicroInterpreter::node_and_registration(
+    int node_index) {
+  TfLiteStatus status = kTfLiteOk;
+  struct pairTfLiteNodeAndRegistration tfNodeRegiPair;
+  auto opcodes = model_->operator_codes();
+  {
+    const auto* op = operators_->Get(node_index);
+    size_t index = op->opcode_index();
+    if (index < 0 || index >= opcodes->size()) {
+      error_reporter_->Report("Missing registration for opcode_index %d\n",
+                              index);
+    }
+    auto opcode = (*opcodes)[index];
+    const TfLiteRegistration* registration = nullptr;
+    status = GetRegistrationFromOpCode(opcode, op_resolver_, error_reporter_,
+                                       &registration);
+    if (status != kTfLiteOk) {
+      error_reporter_->Report("Missing registration for opcode_index %d\n",
+                              index);
+    }
+    if (registration == nullptr) {
+      error_reporter_->Report("Skipping op for opcode_index %d\n", index);
+    }
+
+    // Disregard const qualifier to workaround with existing API.
+    TfLiteIntArray* inputs_array = const_cast<TfLiteIntArray*>(
+        reinterpret_cast<const TfLiteIntArray*>(op->inputs()));
+    TfLiteIntArray* outputs_array = const_cast<TfLiteIntArray*>(
+        reinterpret_cast<const TfLiteIntArray*>(op->outputs()));
+
+    TfLiteNode node;
+    node.inputs = inputs_array;
+    node.outputs = outputs_array;
+    tfNodeRegiPair.node = node;
+    tfNodeRegiPair.registration = registration;
+  }
+  return tfNodeRegiPair;
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/micro_interpreter.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/micro_interpreter.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,101 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_INTERPRETER_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_INTERPRETER_H_
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/core/api/error_reporter.h"
+#include "tensorflow/lite/core/api/op_resolver.h"
+#include "tensorflow/lite/experimental/micro/micro_allocator.h"
+#include "tensorflow/lite/experimental/micro/micro_optional_debug_tools.h"
+#include "tensorflow/lite/schema/schema_generated.h"
+
+namespace tflite {
+
+class MicroInterpreter {
+ public:
+  // The lifetime of the model, op resolver, tensor arena, and error reporter
+  // must be at least as long as that of the interpreter object, since the
+  // interpreter may need to access them at any time. This means that you should
+  // usually create them with the same scope as each other, for example having
+  // them all allocated on the stack as local variables through a top-level
+  // function.
+  // The interpreter doesn't do any deallocation of any of the pointed-to
+  // objects, ownership remains with the caller.
+  MicroInterpreter(const Model* model, const OpResolver& op_resolver,
+                   uint8_t* tensor_arena, size_t tensor_arena_size,
+                   ErrorReporter* error_reporter);
+
+  // Specify a particular tensor as pre-allocated.  This means that this tensor
+  // will internally point to the supplied buffer, and no new memory will be
+  // provided.  The buffer must live at least as long as the allocator, since
+  // the buffer will be used every time an op is invoked which uses the
+  // specified tensor.  Most commonly this is useful when a platform-provided
+  // DMA buffer is used as an input, and it is desirable to avoid unnecessarily
+  // allocating a new buffer and copying from the DMA buffer. The user must
+  // ensure the buffer is valid throughout each interpreter run, and is not
+  // prematurely overwritten.
+  TfLiteStatus RegisterPreallocatedInput(uint8_t* buffer, size_t input_index);
+
+  // Run through the model and allocate all necessary input, output and
+  // intermediate tensors except for those already provided via calls to
+  // registerPreallocatedInput.
+  TfLiteStatus AllocateTensors();
+
+  TfLiteStatus Invoke();
+
+  size_t tensors_size() const { return context_.tensors_size; }
+  TfLiteTensor* tensor(size_t tensor_index);
+
+  TfLiteTensor* input(size_t index);
+  size_t inputs_size() const { return subgraph_->inputs()->Length(); }
+  const flatbuffers::Vector<int32_t>* inputs() { return subgraph_->inputs(); }
+
+  TfLiteTensor* output(size_t index);
+  size_t outputs_size() const { return subgraph_->outputs()->Length(); }
+  const flatbuffers::Vector<int32_t>* outputs() { return subgraph_->outputs(); }
+
+  TfLiteStatus initialization_status() const { return initialization_status_; }
+
+  ErrorReporter* error_reporter() { return error_reporter_; }
+
+  size_t operators_size() const { return operators_->size(); }
+  struct pairTfLiteNodeAndRegistration node_and_registration(int node_index);
+
+ private:
+  void CorrectTensorEndianness(TfLiteTensor* tensorCorr);
+
+  template <class T>
+  void CorrectTensorDataEndianness(T* data, int32_t size);
+
+  NodeAndRegistration* node_and_registrations_;
+
+  const Model* model_;
+  const OpResolver& op_resolver_;
+  ErrorReporter* error_reporter_;
+  TfLiteContext context_;
+  MicroAllocator allocator_;
+  bool tensors_allocated_;
+
+  TfLiteStatus initialization_status_;
+  const flatbuffers::Vector<flatbuffers::Offset<Tensor>>* tensors_;
+  const flatbuffers::Vector<flatbuffers::Offset<Operator>>* operators_;
+
+  const SubGraph* subgraph_;
+};
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_INTERPRETER_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/micro_mutable_op_resolver.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/micro_mutable_op_resolver.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,80 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/experimental/micro/micro_mutable_op_resolver.h"
+
+namespace tflite {
+
+const TfLiteRegistration* MicroMutableOpResolver::FindOp(
+    tflite::BuiltinOperator op, int version) const {
+  for (int i = 0; i < registrations_len_; ++i) {
+    const TfLiteRegistration& registration = registrations_[i];
+    if ((registration.builtin_code == op) &&
+        (registration.version == version)) {
+      return &registration;
+    }
+  }
+  return nullptr;
+}
+
+const TfLiteRegistration* MicroMutableOpResolver::FindOp(const char* op,
+                                                         int version) const {
+  for (int i = 0; i < registrations_len_; ++i) {
+    const TfLiteRegistration& registration = registrations_[i];
+    if ((registration.builtin_code == BuiltinOperator_CUSTOM) &&
+        (strcmp(registration.custom_name, op) == 0) &&
+        (registration.version == version)) {
+      return &registration;
+    }
+  }
+  return nullptr;
+}
+
+void MicroMutableOpResolver::AddBuiltin(tflite::BuiltinOperator op,
+                                        TfLiteRegistration* registration,
+                                        int min_version, int max_version) {
+  for (int version = min_version; version <= max_version; ++version) {
+    if (registrations_len_ >= TFLITE_REGISTRATIONS_MAX) {
+      // TODO(petewarden) - Add error reporting hooks so we can report this!
+      return;
+    }
+    TfLiteRegistration* new_registration = &registrations_[registrations_len_];
+    registrations_len_ += 1;
+
+    *new_registration = *registration;
+    new_registration->builtin_code = op;
+    new_registration->version = version;
+  }
+}
+
+void MicroMutableOpResolver::AddCustom(const char* name,
+                                       TfLiteRegistration* registration,
+                                       int min_version, int max_version) {
+  for (int version = min_version; version <= max_version; ++version) {
+    if (registrations_len_ >= TFLITE_REGISTRATIONS_MAX) {
+      // TODO(petewarden) - Add error reporting hooks so we can report this!
+      return;
+    }
+    TfLiteRegistration* new_registration = &registrations_[registrations_len_];
+    registrations_len_ += 1;
+
+    *new_registration = *registration;
+    new_registration->builtin_code = BuiltinOperator_CUSTOM;
+    new_registration->custom_name = name;
+    new_registration->version = version;
+  }
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/micro_mutable_op_resolver.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/micro_mutable_op_resolver.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,46 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_MUTABLE_OP_RESOLVER_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_MUTABLE_OP_RESOLVER_H_
+
+#include "tensorflow/lite/core/api/op_resolver.h"
+#include "tensorflow/lite/experimental/micro/compatibility.h"
+
+#ifndef TFLITE_REGISTRATIONS_MAX
+#define TFLITE_REGISTRATIONS_MAX (128)
+#endif
+
+namespace tflite {
+
+class MicroMutableOpResolver : public OpResolver {
+ public:
+  const TfLiteRegistration* FindOp(tflite::BuiltinOperator op,
+                                   int version) const override;
+  const TfLiteRegistration* FindOp(const char* op, int version) const override;
+  void AddBuiltin(tflite::BuiltinOperator op, TfLiteRegistration* registration,
+                  int min_version = 1, int max_version = 1);
+  void AddCustom(const char* name, TfLiteRegistration* registration,
+                 int min_version = 1, int max_version = 1);
+
+ private:
+  TfLiteRegistration registrations_[TFLITE_REGISTRATIONS_MAX];
+  int registrations_len_ = 0;
+
+  TF_LITE_REMOVE_VIRTUAL_DELETE
+};
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_MUTABLE_OP_RESOLVER_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/micro_optional_debug_tools.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/micro_optional_debug_tools.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,132 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/experimental/micro/micro_optional_debug_tools.h"
+
+#include "tensorflow/lite/schema/schema_generated.h"
+namespace tflite {
+
+std::vector<int> flatbuffersVector2StdVector(
+    const flatbuffers::Vector<int32_t>* fVector) {
+  std::vector<int> stdVector;
+  for (size_t i = 0; i < fVector->size(); i++) {
+    stdVector.push_back(fVector->Get(i));
+  }
+  return stdVector;
+}
+
+void PrintIntVector(const std::vector<int>& v) {
+  for (const auto& it : v) {
+    printf(" %d", it);
+  }
+  printf("\n");
+}
+
+void PrintTfLiteIntVector(const TfLiteIntArray* v) {
+  if (!v) {
+    printf(" (null)\n");
+    return;
+  }
+  for (int k = 0; k < v->size; k++) {
+    printf(" %d", v->data[k]);
+  }
+  printf("\n");
+}
+
+const char* TensorTypeName(TfLiteType type) {
+  switch (type) {
+    case kTfLiteNoType:
+      return "kTfLiteNoType";
+    case kTfLiteFloat32:
+      return "kTfLiteFloat32";
+    case kTfLiteInt32:
+      return "kTfLiteInt32";
+    case kTfLiteUInt8:
+      return "kTfLiteUInt8";
+    case kTfLiteInt8:
+      return "kTfLiteInt8";
+    case kTfLiteInt64:
+      return "kTfLiteInt64";
+    case kTfLiteString:
+      return "kTfLiteString";
+    case kTfLiteBool:
+      return "kTfLiteBool";
+    case kTfLiteInt16:
+      return "kTfLiteInt16";
+    case kTfLiteComplex64:
+      return "kTfLiteComplex64";
+    case kTfLiteFloat16:
+      return "kTfLiteFloat16";
+  }
+  return "(invalid)";
+}
+
+const char* AllocTypeName(TfLiteAllocationType type) {
+  switch (type) {
+    case kTfLiteMemNone:
+      return "kTfLiteMemNone";
+    case kTfLiteMmapRo:
+      return "kTfLiteMmapRo";
+    case kTfLiteDynamic:
+      return "kTfLiteDynamic";
+    case kTfLiteArenaRw:
+      return "kTfLiteArenaRw";
+    case kTfLiteArenaRwPersistent:
+      return "kTfLiteArenaRwPersistent";
+  }
+  return "(invalid)";
+}
+
+// Prints a dump of what tensors and what nodes are in the interpreter.
+void PrintInterpreterState(MicroInterpreter* interpreter) {
+  printf("Interpreter has %zu tensors and %zu nodes\n",
+         interpreter->tensors_size(), interpreter->operators_size());
+  printf("Inputs:");
+  PrintIntVector(flatbuffersVector2StdVector(interpreter->inputs()));
+  printf("Outputs:");
+  PrintIntVector(flatbuffersVector2StdVector(interpreter->outputs()));
+  printf("\n");
+
+  for (size_t tensor_index = 0; tensor_index < interpreter->tensors_size();
+       tensor_index++) {
+    TfLiteTensor* tensor = interpreter->tensor(static_cast<int>(tensor_index));
+    printf("Tensor %3zu %-20s %10s %15s %10zu bytes (%4.1f MB) ", tensor_index,
+           tensor->name, TensorTypeName(tensor->type),
+           AllocTypeName(tensor->allocation_type), tensor->bytes,
+           static_cast<double>(tensor->bytes / (1 << 20)));
+    PrintTfLiteIntVector(tensor->dims);
+  }
+  printf("\n");
+
+  for (size_t node_index = 0; node_index < interpreter->operators_size();
+       node_index++) {
+    struct pairTfLiteNodeAndRegistration node_and_reg =
+        interpreter->node_and_registration(static_cast<int>(node_index));
+    const TfLiteNode& node = node_and_reg.node;
+    const TfLiteRegistration* reg = node_and_reg.registration;
+    if (reg->custom_name != nullptr) {
+      printf("Node %3zu Operator Custom Name %s\n", node_index,
+             reg->custom_name);
+    } else {
+      printf("Node %3zu Operator Builtin Code %3d %s\n", node_index,
+             reg->builtin_code, EnumNamesBuiltinOperator()[reg->builtin_code]);
+    }
+    printf("  Inputs:");
+    PrintTfLiteIntVector(node.inputs);
+    printf("  Outputs:");
+    PrintTfLiteIntVector(node.outputs);
+  }
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/micro_optional_debug_tools.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/micro_optional_debug_tools.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,40 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+// Optional debugging functionality. For small sized binaries, these are not
+// needed.
+#ifndef TENSORFLOW_LITE_MICRO_OPTIONAL_DEBUG_TOOLS_H_
+#define TENSORFLOW_LITE_MICRO_OPTIONAL_DEBUG_TOOLS_H_
+
+#include "tensorflow/lite/experimental/micro/micro_interpreter.h"
+
+namespace tflite {
+// Prints a dump of what tensors and what nodes are in the interpreter.
+class MicroInterpreter;
+void PrintInterpreterState(MicroInterpreter* interpreter);
+
+#ifdef __cplusplus
+extern "C" {
+#endif  // __cplusplus
+struct pairTfLiteNodeAndRegistration {
+  TfLiteNode node;
+  const TfLiteRegistration* registration;
+};
+#ifdef __cplusplus
+}  // extern "C"
+#endif  // __cplusplus
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_MICRO_OPTIONAL_DEBUG_TOOLS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/micro_utils.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/micro_utils.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,195 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/experimental/micro/micro_utils.h"
+
+#include <limits.h>
+#include <math.h>
+#include <stdint.h>
+
+#include "tensorflow/lite/c/c_api_internal.h"
+
+namespace tflite {
+
+namespace {
+
+static const uint8_t kAsymmetricUInt8Min = 0;
+static const uint8_t kAsymmetricUInt8Max = 255;
+static const uint8_t kSymmetricUInt8Min = 1;
+static const uint8_t kSymmetricUInt8Max = 255;
+static const int8_t kAsymmetricInt8Min = -128;
+static const int8_t kAsymmetricInt8Max = 127;
+static const int kSymmetricInt8Scale = kAsymmetricInt8Max;
+
+}  // namespace
+
+int ElementCount(const TfLiteIntArray& dims) {
+  int result = 1;
+  for (int i = 0; i < dims.size; ++i) {
+    result *= dims.data[i];
+  }
+  return result;
+}
+
+// Converts a float value into an unsigned eight-bit quantized value.
+uint8_t FloatToAsymmetricQuantizedUInt8(const float value, const float scale,
+                                        const int zero_point) {
+  int32_t result = round(value / scale) + zero_point;
+  if (result < kAsymmetricUInt8Min) {
+    result = kAsymmetricUInt8Min;
+  }
+  if (result > kAsymmetricUInt8Max) {
+    result = kAsymmetricUInt8Max;
+  }
+  return result;
+}
+
+uint8_t FloatToSymmetricQuantizedUInt8(const float value, const float scale) {
+  int32_t result = round(value / scale);
+  if (result < kSymmetricUInt8Min) {
+    result = kSymmetricUInt8Min;
+  }
+  if (result > kSymmetricUInt8Max) {
+    result = kSymmetricUInt8Max;
+  }
+  return result;
+}
+
+int8_t FloatToAsymmetricQuantizedInt8(const float value, const float scale,
+                                      const int zero_point) {
+  return FloatToAsymmetricQuantizedUInt8(value, scale,
+                                         zero_point - kAsymmetricInt8Min) +
+         kAsymmetricInt8Min;
+}
+
+int8_t FloatToSymmetricQuantizedInt8(const float value, const float scale) {
+  return FloatToSymmetricQuantizedUInt8(value, scale) + kAsymmetricInt8Min;
+}
+
+int32_t FloatToSymmetricQuantizedInt32(const float value, const float scale) {
+  float quantized = round(value / scale);
+  if (quantized > INT_MAX) {
+    quantized = INT_MAX;
+  } else if (quantized < INT_MIN) {
+    quantized = INT_MIN;
+  }
+
+  return static_cast<int>(quantized);
+}
+
+void AsymmetricQuantize(const float* input, int8_t* output, int num_elements,
+                        float scale, int zero_point) {
+  for (int i = 0; i < num_elements; i++) {
+    output[i] = FloatToAsymmetricQuantizedInt8(input[i], scale, zero_point);
+  }
+}
+
+void AsymmetricQuantize(const float* input, uint8_t* output, int num_elements,
+                        float scale, int zero_point) {
+  for (int i = 0; i < num_elements; i++) {
+    output[i] = FloatToAsymmetricQuantizedUInt8(input[i], scale, zero_point);
+  }
+}
+
+void SymmetricQuantize(const float* input, int32_t* output, int num_elements,
+                       float scale) {
+  for (int i = 0; i < num_elements; i++) {
+    output[i] = FloatToSymmetricQuantizedInt32(input[i], scale);
+  }
+}
+
+void SymmetricPerChannelQuantize(const float* input, int32_t* output,
+                                 int num_elements, int num_channels,
+                                 float* scales) {
+  int elements_per_channel = num_elements / num_channels;
+  for (int i = 0; i < num_channels; i++) {
+    for (int j = 0; j < elements_per_channel; j++) {
+      output[i * elements_per_channel + j] = FloatToSymmetricQuantizedInt32(
+          input[i * elements_per_channel + j], scales[i]);
+    }
+  }
+}
+
+void SignedSymmetricPerChannelQuantize(const float* values,
+                                       TfLiteIntArray* dims,
+                                       int quantized_dimension,
+                                       int8_t* quantized_values,
+                                       float* scaling_factors) {
+  int input_size = ElementCount(*dims);
+  int channel_count = dims->data[quantized_dimension];
+  int per_channel_size = input_size / channel_count;
+  for (int channel = 0; channel < channel_count; channel++) {
+    float min = 0;
+    float max = 0;
+    int stride = 1;
+    for (int i = 0; i < quantized_dimension; i++) {
+      stride *= dims->data[i];
+    }
+    int channel_stride = per_channel_size / stride;
+    // Calculate scales for each channel.
+    for (int i = 0; i < per_channel_size; i++) {
+      int idx = channel * channel_stride + i * stride;
+      min = fminf(min, values[idx]);
+      max = fmaxf(max, values[idx]);
+    }
+    scaling_factors[channel] =
+        fmaxf(fabs(min), fabs(max)) / kSymmetricInt8Scale;
+    for (int i = 0; i < per_channel_size; i++) {
+      int idx = channel * channel_stride + i * stride;
+      const int32_t quantized_value =
+          static_cast<int32_t>(roundf(values[idx] / scaling_factors[channel]));
+      // Clamp: just in case some odd numeric offset.
+      quantized_values[idx] = fminf(
+          kSymmetricInt8Scale, fmaxf(-kSymmetricInt8Scale, quantized_value));
+    }
+  }
+}
+
+void SignedSymmetricQuantize(const float* values, TfLiteIntArray* dims,
+                             int8_t* quantized_values, float* scaling_factor) {
+  int input_size = ElementCount(*dims);
+
+  float min = 0;
+  float max = 0;
+  for (int i = 0; i < input_size; i++) {
+    min = fminf(min, values[i]);
+    max = fmaxf(max, values[i]);
+  }
+  *scaling_factor = fmaxf(fabs(min), fabs(max)) / kSymmetricInt8Scale;
+  for (int i = 0; i < input_size; i++) {
+    const int32_t quantized_value =
+        static_cast<int32_t>(roundf(values[i] / *scaling_factor));
+    // Clamp: just in case some odd numeric offset.
+    quantized_values[i] = fminf(kSymmetricInt8Scale,
+                                fmaxf(-kSymmetricInt8Scale, quantized_value));
+  }
+}
+
+void SymmetricQuantize(const float* values, TfLiteIntArray* dims,
+                       uint8_t* quantized_values, float* scaling_factor) {
+  SignedSymmetricQuantize(values, dims,
+                          reinterpret_cast<int8_t*>(quantized_values),
+                          scaling_factor);
+}
+
+void SymmetricDequantize(const int8_t* values, const int size,
+                         const float dequantization_scale,
+                         float* dequantized_values) {
+  for (int i = 0; i < size; ++i) {
+    dequantized_values[i] = values[i] * dequantization_scale;
+  }
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/micro_utils.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/micro_utils.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,86 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_UTILS_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_UTILS_H_
+
+#include <stdint.h>
+
+#include "tensorflow/lite/c/c_api_internal.h"
+
+namespace tflite {
+
+// Returns number of elements in the shape array.
+
+int ElementCount(const TfLiteIntArray& dims);
+
+uint8_t FloatToAsymmetricQuantizedUInt8(const float value, const float scale,
+                                        const int zero_point);
+
+uint8_t FloatToSymmetricQuantizedUInt8(const float value, const float scale);
+
+int8_t FloatToAsymmetricQuantizedInt8(const float value, const float scale,
+                                      const int zero_point);
+
+int8_t FloatToSymmetricQuantizedInt8(const float value, const float scale);
+
+// Converts a float value into a signed thirty-two-bit quantized value.  Note
+// that values close to max int and min int may see significant error due to
+// a lack of floating point granularity for large values.
+int32_t FloatToSymmetricQuantizedInt32(const float value, const float scale);
+
+// Helper methods to quantize arrays of floats to the desired format.
+//
+// There are several key flavors of quantization in TfLite:
+//        asymmetric symmetric  per channel
+// int8  |     X    |    X    |     X      |
+// uint8 |     X    |    X    |            |
+// int32 |          |    X    |     X      |
+//
+// The per-op quantizaiton spec can be found here:
+// https://www.tensorflow.org/lite/performance/quantization_spec
+
+void AsymmetricQuantize(const float* input, int8_t* output, int num_elements,
+                        float scale, int zero_point = 0);
+
+void AsymmetricQuantize(const float* input, uint8_t* output, int num_elements,
+                        float scale, int zero_point = 128);
+
+void SymmetricQuantize(const float* input, int32_t* output, int num_elements,
+                       float scale);
+
+void SymmetricPerChannelQuantize(const float* input, int32_t* output,
+                                 int num_elements, int num_channels,
+                                 float* scales);
+
+void SignedSymmetricPerChannelQuantize(const float* values,
+                                       TfLiteIntArray* dims,
+                                       int quantized_dimension,
+                                       int8_t* quantized_values,
+                                       float* scaling_factor);
+
+void SignedSymmetricQuantize(const float* values, TfLiteIntArray* dims,
+                             int8_t* quantized_values, float* scaling_factor);
+
+void SymmetricQuantize(const float* values, TfLiteIntArray* dims,
+                       uint8_t* quantized_values, float* scaling_factor);
+
+void SymmetricDequantize(const int8_t* values, const int size,
+                         const float dequantization_scale,
+                         float* dequantized_values);
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_MICRO_UTILS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/simple_memory_allocator.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/simple_memory_allocator.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,58 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/experimental/micro/simple_memory_allocator.h"
+
+#include "tensorflow/lite/core/api/flatbuffer_conversions.h"
+#include "tensorflow/lite/experimental/micro/memory_helpers.h"
+
+namespace tflite {
+
+uint8_t* SimpleMemoryAllocator::AllocateFromTail(size_t size,
+                                                 size_t alignment) {
+  if (has_child_allocator_) {
+    // TODO(wangtz): Add error reporting when the parent allocator is locked!
+    return nullptr;
+  }
+  uint8_t* previous_free = (data_ + data_size_max_) - data_size_;
+  uint8_t* current_data = previous_free - size;
+  uint8_t* aligned_result = AlignPointerDown(current_data, alignment);
+  size_t aligned_size = (previous_free - aligned_result);
+  if ((data_size_ + aligned_size) > data_size_max_) {
+    // TODO(petewarden): Add error reporting beyond returning null!
+    return nullptr;
+  }
+  data_size_ += aligned_size;
+  return aligned_result;
+}
+
+SimpleMemoryAllocator SimpleMemoryAllocator::CreateChildAllocator() {
+  // Note that the parameterized constructor initializes data_size_ to 0 which
+  // is not what we expected.
+  SimpleMemoryAllocator child = *this;
+  child.parent_allocator_ = this;
+  // With C++ copy elision, &child should be available after return.
+  has_child_allocator_ = true;
+  return child;
+}
+
+SimpleMemoryAllocator::~SimpleMemoryAllocator() {
+  // Root allocator doesn't have a parent.
+  if (nullptr != parent_allocator_) {
+    parent_allocator_->has_child_allocator_ = false;
+  }
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/simple_memory_allocator.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/simple_memory_allocator.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,63 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_SIMPLE_MEMORY_ALLOCATOR_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_SIMPLE_MEMORY_ALLOCATOR_H_
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/core/api/error_reporter.h"
+#include "tensorflow/lite/schema/schema_generated.h"
+
+namespace tflite {
+
+// TODO(petewarden): This allocator never frees up or reuses  any memory, even
+// though we have enough information about lifetimes of the tensors to do so.
+// This makes it pretty wasteful, so we should use a more intelligent method.
+class SimpleMemoryAllocator {
+ public:
+  SimpleMemoryAllocator(uint8_t* buffer, size_t buffer_size)
+      : data_size_max_(buffer_size), data_(buffer) {}
+
+  // Allocates memory starting at the end of the arena (highest address and
+  // moving downwards, so that tensor buffers can be allocated from the start
+  // in ascending order.
+  uint8_t* AllocateFromTail(size_t size, size_t alignment);
+
+  int GetDataSize() const { return data_size_; }
+
+  // Child allocator is something like a temporary allocator. Memory allocated
+  // by the child allocator will be freed once the child allocator is
+  // deallocated. Child allocator could be cascaded to have for example
+  // grandchild allocator. But at any given time, only the latest child
+  // allocator can be used. All its ancestors will be locked to avoid memory
+  // corruption. Locked means that the allocator can't allocate memory.
+  // WARNING: Parent allocator needs to live longer than the child allocator.
+  SimpleMemoryAllocator CreateChildAllocator();
+
+  // Unlocks parent allocator when the child allocator is deconstructed.
+  ~SimpleMemoryAllocator();
+
+ private:
+  int data_size_ = 0;
+  size_t data_size_max_;
+  uint8_t* data_;
+  SimpleMemoryAllocator* parent_allocator_ = nullptr;
+  // The allocator is locaked if it has a child.
+  bool has_child_allocator_ = false;
+};
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_SIMPLE_MEMORY_ALLOCATOR_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/test_helpers.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/test_helpers.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,401 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/experimental/micro/test_helpers.h"
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/core/api/tensor_utils.h"
+#include "tensorflow/lite/experimental/micro/micro_utils.h"
+
+namespace tflite {
+namespace testing {
+namespace {
+
+class StackAllocator : public flatbuffers::Allocator {
+ public:
+  StackAllocator() : data_(data_backing_), data_size_(0) {}
+
+  uint8_t* allocate(size_t size) override {
+    if ((data_size_ + size) > kStackAllocatorSize) {
+      // TODO(petewarden): Add error reporting beyond returning null!
+      return nullptr;
+    }
+    uint8_t* result = data_;
+    data_ += size;
+    data_size_ += size;
+    return result;
+  }
+
+  void deallocate(uint8_t* p, size_t) override {}
+
+  static StackAllocator& instance() {
+    // Avoid using true dynamic memory allocation to be portable to bare metal.
+    static char inst_memory[sizeof(StackAllocator)];
+    static StackAllocator* inst = new (inst_memory) StackAllocator;
+    return *inst;
+  }
+
+  static constexpr int kStackAllocatorSize = 4096;
+
+ private:
+  uint8_t data_backing_[kStackAllocatorSize];
+  uint8_t* data_;
+  int data_size_;
+};
+
+flatbuffers::FlatBufferBuilder* BuilderInstance() {
+  static char inst_memory[sizeof(flatbuffers::FlatBufferBuilder)];
+  static flatbuffers::FlatBufferBuilder* inst =
+      new (inst_memory) flatbuffers::FlatBufferBuilder(
+          StackAllocator::kStackAllocatorSize, &StackAllocator::instance());
+  return inst;
+}
+
+const Model* BuildMockModel() {
+  using flatbuffers::Offset;
+  flatbuffers::FlatBufferBuilder* builder = BuilderInstance();
+
+  constexpr size_t buffer_data_size = 1;
+  const uint8_t buffer_data[buffer_data_size] = {21};
+  constexpr size_t buffers_size = 2;
+  const Offset<Buffer> buffers[buffers_size] = {
+      CreateBuffer(*builder),
+      CreateBuffer(*builder,
+                   builder->CreateVector(buffer_data, buffer_data_size))};
+  constexpr size_t tensor_shape_size = 1;
+  const int32_t tensor_shape[tensor_shape_size] = {1};
+  constexpr size_t tensors_size = 3;
+  const Offset<Tensor> tensors[tensors_size] = {
+      CreateTensor(*builder,
+                   builder->CreateVector(tensor_shape, tensor_shape_size),
+                   TensorType_INT32, 0,
+                   builder->CreateString("test_input_tensor"), 0, false),
+      CreateTensor(*builder,
+                   builder->CreateVector(tensor_shape, tensor_shape_size),
+                   TensorType_UINT8, 1,
+                   builder->CreateString("test_weight_tensor"), 0, false),
+      CreateTensor(*builder,
+                   builder->CreateVector(tensor_shape, tensor_shape_size),
+                   TensorType_INT32, 0,
+                   builder->CreateString("test_output_tensor"), 0, false),
+  };
+  constexpr size_t inputs_size = 1;
+  const int32_t inputs[inputs_size] = {0};
+  constexpr size_t outputs_size = 1;
+  const int32_t outputs[outputs_size] = {2};
+  constexpr size_t operator_inputs_size = 2;
+  const int32_t operator_inputs[operator_inputs_size] = {0, 1};
+  constexpr size_t operator_outputs_size = 1;
+  const int32_t operator_outputs[operator_outputs_size] = {2};
+  constexpr size_t operators_size = 1;
+  const Offset<Operator> operators[operators_size] = {CreateOperator(
+      *builder, 0, builder->CreateVector(operator_inputs, operator_inputs_size),
+      builder->CreateVector(operator_outputs, operator_outputs_size),
+      BuiltinOptions_NONE)};
+  constexpr size_t subgraphs_size = 1;
+  const Offset<SubGraph> subgraphs[subgraphs_size] = {
+      CreateSubGraph(*builder, builder->CreateVector(tensors, tensors_size),
+                     builder->CreateVector(inputs, inputs_size),
+                     builder->CreateVector(outputs, outputs_size),
+                     builder->CreateVector(operators, operators_size),
+                     builder->CreateString("test_subgraph"))};
+  constexpr size_t operator_codes_size = 1;
+  const Offset<OperatorCode> operator_codes[operator_codes_size] = {
+      CreateOperatorCodeDirect(*builder, BuiltinOperator_CUSTOM, "mock_custom",
+                               0)};
+  const Offset<Model> model_offset = CreateModel(
+      *builder, 0, builder->CreateVector(operator_codes, operator_codes_size),
+      builder->CreateVector(subgraphs, subgraphs_size),
+      builder->CreateString("test_model"),
+      builder->CreateVector(buffers, buffers_size));
+  FinishModelBuffer(*builder, model_offset);
+  void* model_pointer = builder->GetBufferPointer();
+  const Model* model = flatbuffers::GetRoot<Model>(model_pointer);
+  return model;
+}
+
+}  // namespace
+
+const Model* GetMockModel() {
+  static Model* model = nullptr;
+  if (!model) {
+    model = const_cast<Model*>(BuildMockModel());
+  }
+  return model;
+}
+
+const Tensor* Create1dFlatbufferTensor(int size) {
+  using flatbuffers::Offset;
+  flatbuffers::FlatBufferBuilder* builder = BuilderInstance();
+  constexpr size_t tensor_shape_size = 1;
+  const int32_t tensor_shape[tensor_shape_size] = {size};
+  const Offset<Tensor> tensor_offset = CreateTensor(
+      *builder, builder->CreateVector(tensor_shape, tensor_shape_size),
+      TensorType_INT32, 0, builder->CreateString("test_tensor"), 0, false);
+  builder->Finish(tensor_offset);
+  void* tensor_pointer = builder->GetBufferPointer();
+  const Tensor* tensor = flatbuffers::GetRoot<Tensor>(tensor_pointer);
+  return tensor;
+}
+
+const Tensor* CreateMissingQuantizationFlatbufferTensor(int size) {
+  using flatbuffers::Offset;
+  flatbuffers::FlatBufferBuilder* builder = BuilderInstance();
+  const Offset<QuantizationParameters> quant_params =
+      CreateQuantizationParameters(*builder, 0, 0, 0, 0,
+                                   QuantizationDetails_NONE, 0, 0);
+  constexpr size_t tensor_shape_size = 1;
+  const int32_t tensor_shape[tensor_shape_size] = {size};
+  const Offset<Tensor> tensor_offset = CreateTensor(
+      *builder, builder->CreateVector(tensor_shape, tensor_shape_size),
+      TensorType_INT32, 0, builder->CreateString("test_tensor"), quant_params,
+      false);
+  builder->Finish(tensor_offset);
+  void* tensor_pointer = builder->GetBufferPointer();
+  const Tensor* tensor = flatbuffers::GetRoot<Tensor>(tensor_pointer);
+  return tensor;
+}
+
+const flatbuffers::Vector<flatbuffers::Offset<Buffer>>*
+CreateFlatbufferBuffers() {
+  using flatbuffers::Offset;
+  flatbuffers::FlatBufferBuilder* builder = BuilderInstance();
+  constexpr size_t buffers_size = 1;
+  const Offset<Buffer> buffers[buffers_size] = {
+      CreateBuffer(*builder),
+  };
+  const flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<Buffer>>>
+      buffers_offset = builder->CreateVector(buffers, buffers_size);
+  builder->Finish(buffers_offset);
+  void* buffers_pointer = builder->GetBufferPointer();
+  const flatbuffers::Vector<flatbuffers::Offset<Buffer>>* result =
+      flatbuffers::GetRoot<flatbuffers::Vector<flatbuffers::Offset<Buffer>>>(
+          buffers_pointer);
+  return result;
+}
+
+int TestStrcmp(const char* a, const char* b) {
+  if ((a == nullptr) || (b == nullptr)) {
+    return -1;
+  }
+  while ((*a != 0) && (*a == *b)) {
+    a++;
+    b++;
+  }
+  return *reinterpret_cast<const unsigned char*>(a) -
+         *reinterpret_cast<const unsigned char*>(b);
+}
+
+// Wrapper to forward kernel errors to the interpreter's error reporter.
+void ReportOpError(struct TfLiteContext* context, const char* format, ...) {
+  ErrorReporter* error_reporter = static_cast<ErrorReporter*>(context->impl_);
+  va_list args;
+  va_start(args, format);
+  error_reporter->Report(format, args);
+  va_end(args);
+}
+
+// Create a TfLiteIntArray from an array of ints.  The first element in the
+// supplied array must be the size of the array expressed as an int.
+TfLiteIntArray* IntArrayFromInts(const int* int_array) {
+  return const_cast<TfLiteIntArray*>(
+      reinterpret_cast<const TfLiteIntArray*>(int_array));
+}
+
+// Create a TfLiteFloatArray from an array of floats.  The first element in the
+// supplied array must be the size of the array expressed as a float.
+TfLiteFloatArray* FloatArrayFromFloats(const float* floats) {
+  static_assert(sizeof(float) == sizeof(int),
+                "assumes sizeof(float) == sizeof(int) to perform casting");
+  int size = static_cast<int>(floats[0]);
+  *reinterpret_cast<int32_t*>(const_cast<float*>(floats)) = size;
+  return reinterpret_cast<TfLiteFloatArray*>(const_cast<float*>(floats));
+}
+
+TfLiteTensor CreateTensor(TfLiteIntArray* dims, const char* name,
+                          bool is_variable) {
+  TfLiteTensor result;
+  result.dims = dims;
+  result.name = name;
+  result.params = {};
+  result.quantization = {kTfLiteNoQuantization, nullptr};
+  result.is_variable = is_variable;
+  result.allocation_type = kTfLiteMemNone;
+  result.allocation = nullptr;
+  return result;
+}
+
+TfLiteTensor CreateFloatTensor(const float* data, TfLiteIntArray* dims,
+                               const char* name, bool is_variable) {
+  TfLiteTensor result = CreateTensor(dims, name, is_variable);
+  result.type = kTfLiteFloat32;
+  result.data.f = const_cast<float*>(data);
+  result.bytes = ElementCount(*dims) * sizeof(float);
+  return result;
+}
+
+void PopulateFloatTensor(TfLiteTensor* tensor, float* begin, float* end) {
+  float* p = begin;
+  float* v = tensor->data.f;
+  while (p != end) {
+    *v++ = *p++;
+  }
+}
+
+TfLiteTensor CreateBoolTensor(const bool* data, TfLiteIntArray* dims,
+                              const char* name, bool is_variable) {
+  TfLiteTensor result = CreateTensor(dims, name, is_variable);
+  result.type = kTfLiteBool;
+  result.data.b = const_cast<bool*>(data);
+  result.bytes = ElementCount(*dims) * sizeof(bool);
+  return result;
+}
+
+TfLiteTensor CreateInt32Tensor(const int32_t* data, TfLiteIntArray* dims,
+                               const char* name, bool is_variable) {
+  TfLiteTensor result = CreateTensor(dims, name, is_variable);
+  result.type = kTfLiteInt32;
+  result.data.i32 = const_cast<int32_t*>(data);
+  result.bytes = ElementCount(*dims) * sizeof(int32_t);
+  return result;
+}
+
+TfLiteTensor CreateQuantizedTensor(const uint8_t* data, TfLiteIntArray* dims,
+                                   float scale, int zero_point,
+                                   const char* name, bool is_variable) {
+  TfLiteTensor result = CreateTensor(dims, name, is_variable);
+  result.type = kTfLiteUInt8;
+  result.data.uint8 = const_cast<uint8_t*>(data);
+  result.params = {scale, zero_point};
+  result.quantization = {kTfLiteAffineQuantization, nullptr};
+  result.bytes = ElementCount(*dims) * sizeof(uint8_t);
+  return result;
+}
+
+// Create Quantized tensor which contains a quantized version of the supplied
+// buffer.
+TfLiteTensor CreateQuantizedTensor(const float* input, uint8_t* quantized,
+                                   TfLiteIntArray* dims, float scale,
+                                   int zero_point, const char* name,
+                                   bool is_variable) {
+  int input_size = ElementCount(*dims);
+  tflite::AsymmetricQuantize(input, quantized, input_size, scale, zero_point);
+  return CreateQuantizedTensor(quantized, dims, scale, zero_point, name);
+}
+
+TfLiteTensor CreateQuantizedTensor(const int8_t* data, TfLiteIntArray* dims,
+                                   float scale, int zero_point,
+                                   const char* name, bool is_variable) {
+  TfLiteTensor result = CreateTensor(dims, name, is_variable);
+  result.type = kTfLiteInt8;
+  result.data.int8 = const_cast<int8_t*>(data);
+  result.params = {scale, zero_point};
+  result.quantization = {kTfLiteAffineQuantization, nullptr};
+  result.bytes = ElementCount(*dims) * sizeof(int8_t);
+  return result;
+}
+
+TfLiteTensor CreateQuantizedTensor(const float* input, int8_t* quantized,
+                                   TfLiteIntArray* dims, float scale,
+                                   int zero_point, const char* name,
+                                   bool is_variable) {
+  int input_size = ElementCount(*dims);
+  tflite::AsymmetricQuantize(input, quantized, input_size, scale, zero_point);
+  return CreateQuantizedTensor(quantized, dims, scale, zero_point, name);
+}
+
+TfLiteTensor CreateQuantized32Tensor(const int32_t* data, TfLiteIntArray* dims,
+                                     float scale, const char* name,
+                                     bool is_variable) {
+  TfLiteTensor result = CreateTensor(dims, name, is_variable);
+  result.type = kTfLiteInt32;
+  result.data.i32 = const_cast<int32_t*>(data);
+  // Quantized int32 tensors always have a zero point of 0, since the range of
+  // int32 values is large, and because zero point costs extra cycles during
+  // processing.
+  result.params = {scale, 0};
+  result.quantization = {kTfLiteAffineQuantization, nullptr};
+  result.bytes = ElementCount(*dims) * sizeof(int32_t);
+  return result;
+}
+
+TfLiteTensor CreateQuantizedBiasTensor(const float* data, int32_t* quantized,
+                                       TfLiteIntArray* dims, float input_scale,
+                                       float weights_scale, const char* name,
+                                       bool is_variable) {
+  float bias_scale = input_scale * weights_scale;
+  tflite::SymmetricQuantize(data, quantized, ElementCount(*dims), bias_scale);
+  return CreateQuantized32Tensor(quantized, dims, bias_scale, name,
+                                 is_variable);
+}
+
+// Quantizes int32 bias tensor with per-channel weights determined by input
+// scale multiplied by weight scale for each channel.
+TfLiteTensor CreatePerChannelQuantizedBiasTensor(
+    const float* input, int32_t* quantized, TfLiteIntArray* dims,
+    float input_scale, float* weight_scales, float* scales, int* zero_points,
+    TfLiteAffineQuantization* affine_quant, int quantized_dimension,
+    const char* name, bool is_variable) {
+  int input_size = ElementCount(*dims);
+  int num_channels = dims->data[quantized_dimension];
+  // First element is reserved for array length
+  zero_points[0] = num_channels;
+  scales[0] = static_cast<float>(num_channels);
+  float* scales_array = &scales[1];
+  for (int i = 0; i < num_channels; i++) {
+    scales_array[i] = input_scale * weight_scales[i];
+    zero_points[i + 1] = 0;
+  }
+
+  SymmetricPerChannelQuantize(input, quantized, input_size, num_channels,
+                              scales_array);
+
+  affine_quant->scale = FloatArrayFromFloats(scales);
+  affine_quant->zero_point = IntArrayFromInts(zero_points);
+  affine_quant->quantized_dimension = quantized_dimension;
+
+  TfLiteTensor result = CreateTensor(dims, name, is_variable);
+  result.type = kTfLiteInt32;
+  result.data.i32 = const_cast<int32_t*>(quantized);
+  result.quantization = {kTfLiteAffineQuantization, affine_quant};
+  result.bytes = ElementCount(*dims) * sizeof(int32_t);
+  return result;
+}
+
+TfLiteTensor CreateSymmetricPerChannelQuantizedTensor(
+    const float* input, int8_t* quantized, TfLiteIntArray* dims, float* scales,
+    int* zero_points, TfLiteAffineQuantization* affine_quant,
+    int quantized_dimension, const char* name, bool is_variable) {
+  int channel_count = dims->data[quantized_dimension];
+  scales[0] = static_cast<float>(channel_count);
+  zero_points[0] = channel_count;
+
+  SignedSymmetricPerChannelQuantize(input, dims, quantized_dimension, quantized,
+                                    &scales[1]);
+
+  affine_quant->scale = FloatArrayFromFloats(scales);
+  affine_quant->zero_point = IntArrayFromInts(zero_points);
+  affine_quant->quantized_dimension = quantized_dimension;
+
+  TfLiteTensor result = CreateTensor(dims, name, is_variable);
+  result.type = kTfLiteInt8;
+  result.data.int8 = const_cast<int8_t*>(quantized);
+  result.quantization = {kTfLiteAffineQuantization, affine_quant};
+  result.bytes = ElementCount(*dims) * sizeof(int8_t);
+  return result;
+}
+
+}  // namespace testing
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/test_helpers.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/test_helpers.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,108 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_TEST_HELPERS_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_TEST_HELPERS_H_
+
+// Useful functions for writing tests.
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/core/api/error_reporter.h"
+#include "tensorflow/lite/schema/schema_generated.h"
+
+namespace tflite {
+namespace testing {
+
+// Returns an example flatbuffer TensorFlow Lite model.
+const Model* GetMockModel();
+
+// Builds a one-dimensional flatbuffer tensor of the given size.
+const Tensor* Create1dFlatbufferTensor(int size);
+
+// Creates a one-dimensional tensor with no quantization metadata.
+const Tensor* CreateMissingQuantizationFlatbufferTensor(int size);
+
+// Creates a vector of flatbuffer buffers.
+const flatbuffers::Vector<flatbuffers::Offset<Buffer>>*
+CreateFlatbufferBuffers();
+
+// Performs a simple string comparison without requiring standard C library.
+int TestStrcmp(const char* a, const char* b);
+
+// Wrapper to forward kernel errors to the interpreter's error reporter.
+void ReportOpError(struct TfLiteContext* context, const char* format, ...);
+
+void PopulateContext(TfLiteTensor* tensors, int tensors_size,
+                     TfLiteContext* context);
+
+// Create a TfLiteIntArray from an array of ints.  The first element in the
+// supplied array must be the size of the array expressed as an int.
+TfLiteIntArray* IntArrayFromInts(const int* int_array);
+
+// Create a TfLiteFloatArray from an array of floats.  The first element in the
+// supplied array must be the size of the array expressed as a float.
+TfLiteFloatArray* FloatArrayFromFloats(const float* floats);
+
+TfLiteTensor CreateFloatTensor(const float* data, TfLiteIntArray* dims,
+                               const char* name, bool is_variable = false);
+
+void PopulateFloatTensor(TfLiteTensor* tensor, float* begin, float* end);
+
+TfLiteTensor CreateBoolTensor(const bool* data, TfLiteIntArray* dims,
+                              const char* name, bool is_variable = false);
+
+TfLiteTensor CreateInt32Tensor(const int32_t*, TfLiteIntArray* dims,
+                               const char* name, bool is_variable = false);
+
+TfLiteTensor CreateQuantizedTensor(const uint8_t* data, TfLiteIntArray* dims,
+                                   float scale, int zero_point,
+                                   const char* name, bool is_variable = false);
+
+TfLiteTensor CreateQuantizedTensor(const float* input, uint8_t* quantized,
+                                   TfLiteIntArray* dims, float scale,
+                                   int zero_point, const char* name,
+                                   bool is_variable = false);
+
+TfLiteTensor CreateQuantizedTensor(const int8_t* data, TfLiteIntArray* dims,
+                                   float scale, int zero_point,
+                                   const char* name, bool is_variable = false);
+
+TfLiteTensor CreateQuantizedTensor(const float* input, int8_t* quantized,
+                                   TfLiteIntArray* dims, float scale,
+                                   int zero_point, const char* name,
+                                   bool is_variable = false);
+
+TfLiteTensor CreateQuantizedBiasTensor(const float* data, int32_t* quantized,
+                                       TfLiteIntArray* dims, float input_scale,
+                                       float weights_scale, const char* name,
+                                       bool is_variable = false);
+
+// Quantizes int32 bias tensor with per-channel weights determined by input
+// scale multiplied by weight scale for each channel.
+TfLiteTensor CreatePerChannelQuantizedBiasTensor(
+    const float* input, int32_t* quantized, TfLiteIntArray* dims,
+    float input_scale, float* weight_scales, float* scales, int* zero_points,
+    TfLiteAffineQuantization* affine_quant, int quantized_dimension,
+    const char* name, bool is_variable = false);
+
+TfLiteTensor CreateSymmetricPerChannelQuantizedTensor(
+    const float* input, int8_t* quantized, TfLiteIntArray* dims, float* scales,
+    int* zero_points, TfLiteAffineQuantization* affine_quant,
+    int quantized_dimension, const char* name, bool is_variable = false);
+
+}  // namespace testing
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_TEST_HELPERS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/testing/micro_test.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/testing/micro_test.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,210 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+// An ultra-lightweight testing framework designed for use with microcontroller
+// applications. Its only dependency is on TensorFlow Lite's ErrorReporter
+// interface, where log messages are output. This is designed to be usable even
+// when no standard C or C++ libraries are available, and without any dynamic
+// memory allocation or reliance on global constructors.
+//
+// To build a test, you use syntax similar to gunit, but with some extra
+// decoration to create a hidden 'main' function containing each of the tests to
+// be run. Your code should look something like:
+// ----------------------------------------------------------------------------
+// #include "path/to/this/header"
+//
+// TF_LITE_MICRO_TESTS_BEGIN
+//
+// TF_LITE_MICRO_TEST(SomeTest) {
+//   TF_LITE_LOG_EXPECT_EQ(true, true);
+// }
+//
+// TF_LITE_MICRO_TESTS_END
+// ----------------------------------------------------------------------------
+// If you compile this for your platform, you'll get a normal binary that you
+// should be able to run. Executing it will output logging information like this
+// to stderr (or whatever equivalent is available and written to by
+// ErrorReporter):
+// ----------------------------------------------------------------------------
+// Testing SomeTest
+// 1/1 tests passed
+// ~~~ALL TESTS PASSED~~~
+// ----------------------------------------------------------------------------
+// This is designed to be human-readable, so you can just run tests manually,
+// but the string "~~~ALL TESTS PASSED~~~" should only appear if all of the
+// tests do pass. This makes it possible to integrate with automated test
+// systems by scanning the output logs and looking for that magic value.
+//
+// This framework is intended to be a rudimentary alternative to no testing at
+// all on systems that struggle to run more conventional approaches, so use with
+// caution!
+
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_TESTING_MICRO_TEST_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_TESTING_MICRO_TEST_H_
+
+#include "tensorflow/lite/experimental/micro/micro_error_reporter.h"
+
+namespace micro_test {
+extern int tests_passed;
+extern int tests_failed;
+extern bool is_test_complete;
+extern bool did_test_fail;
+extern tflite::ErrorReporter* reporter;
+}  // namespace micro_test
+
+#define TF_LITE_MICRO_TESTS_BEGIN              \
+  namespace micro_test {                       \
+  int tests_passed;                            \
+  int tests_failed;                            \
+  bool is_test_complete;                       \
+  bool did_test_fail;                          \
+  tflite::ErrorReporter* reporter;             \
+  }                                            \
+                                               \
+  int main(int argc, char** argv) {            \
+    micro_test::tests_passed = 0;              \
+    micro_test::tests_failed = 0;              \
+    tflite::MicroErrorReporter error_reporter; \
+    micro_test::reporter = &error_reporter;
+
+#define TF_LITE_MICRO_TESTS_END                                \
+  micro_test::reporter->Report(                                \
+      "%d/%d tests passed", micro_test::tests_passed,          \
+      (micro_test::tests_failed + micro_test::tests_passed));  \
+  if (micro_test::tests_failed == 0) {                         \
+    micro_test::reporter->Report("~~~ALL TESTS PASSED~~~\n");  \
+  } else {                                                     \
+    micro_test::reporter->Report("~~~SOME TESTS FAILED~~~\n"); \
+  }                                                            \
+  }
+
+// TODO(petewarden): I'm going to hell for what I'm doing to this poor for loop.
+#define TF_LITE_MICRO_TEST(name)                                           \
+  micro_test::reporter->Report("Testing %s", #name);                       \
+  for (micro_test::is_test_complete = false,                               \
+      micro_test::did_test_fail = false;                                   \
+       !micro_test::is_test_complete; micro_test::is_test_complete = true, \
+      micro_test::tests_passed += (micro_test::did_test_fail) ? 0 : 1,     \
+      micro_test::tests_failed += (micro_test::did_test_fail) ? 1 : 0)
+
+#define TF_LITE_MICRO_EXPECT(x)                                                \
+  do {                                                                         \
+    if (!(x)) {                                                                \
+      micro_test::reporter->Report(#x " failed at %s:%d", __FILE__, __LINE__); \
+      micro_test::did_test_fail = true;                                        \
+    }                                                                          \
+  } while (false)
+
+#define TF_LITE_MICRO_EXPECT_EQ(x, y)                                          \
+  do {                                                                         \
+    if ((x) != (y)) {                                                          \
+      micro_test::reporter->Report(#x " == " #y " failed at %s:%d (%d vs %d)", \
+                                   __FILE__, __LINE__, (x), (y));              \
+      micro_test::did_test_fail = true;                                        \
+    }                                                                          \
+  } while (false)
+
+#define TF_LITE_MICRO_EXPECT_NE(x, y)                                         \
+  do {                                                                        \
+    if ((x) == (y)) {                                                         \
+      micro_test::reporter->Report(#x " != " #y " failed at %s:%d", __FILE__, \
+                                   __LINE__);                                 \
+      micro_test::did_test_fail = true;                                       \
+    }                                                                         \
+  } while (false)
+
+// TODO(wangtz): Making it more generic once needed.
+#define TF_LITE_MICRO_ARRAY_ELEMENT_EXPECT_NEAR(arr1, idx1, arr2, idx2, \
+                                                epsilon)                \
+  do {                                                                  \
+    auto delta = ((arr1)[(idx1)] > (arr2)[(idx2)])                      \
+                     ? ((arr1)[(idx1)] - (arr2)[(idx2)])                \
+                     : ((arr2)[(idx2)] - (arr1)[(idx1)]);               \
+    if (delta > epsilon) {                                              \
+      micro_test::reporter->Report(                                     \
+          #arr1 "[%d] (%f) near " #arr2 "[%d] (%f) failed at %s:%d",    \
+          static_cast<int>(idx1), static_cast<float>((arr1)[(idx1)]),   \
+          static_cast<int>(idx2), static_cast<float>((arr2)[(idx2)]),   \
+          __FILE__, __LINE__);                                          \
+      micro_test::did_test_fail = true;                                 \
+    }                                                                   \
+  } while (false)
+
+#define TF_LITE_MICRO_EXPECT_NEAR(x, y, epsilon)                              \
+  do {                                                                        \
+    auto delta = ((x) > (y)) ? ((x) - (y)) : ((y) - (x));                     \
+    if (delta > epsilon) {                                                    \
+      micro_test::reporter->Report(                                           \
+          #x " (%f) near " #y " (%f) failed at %s:%d", static_cast<float>(x), \
+          static_cast<float>(y), __FILE__, __LINE__);                         \
+      micro_test::did_test_fail = true;                                       \
+    }                                                                         \
+  } while (false)
+
+#define TF_LITE_MICRO_EXPECT_GT(x, y)                                        \
+  do {                                                                       \
+    if ((x) <= (y)) {                                                        \
+      micro_test::reporter->Report(#x " > " #y " failed at %s:%d", __FILE__, \
+                                   __LINE__);                                \
+      micro_test::did_test_fail = true;                                      \
+    }                                                                        \
+  } while (false)
+
+#define TF_LITE_MICRO_EXPECT_LT(x, y)                                        \
+  do {                                                                       \
+    if ((x) >= (y)) {                                                        \
+      micro_test::reporter->Report(#x " < " #y " failed at %s:%d", __FILE__, \
+                                   __LINE__);                                \
+      micro_test::did_test_fail = true;                                      \
+    }                                                                        \
+  } while (false)
+
+#define TF_LITE_MICRO_EXPECT_GE(x, y)                                         \
+  do {                                                                        \
+    if ((x) < (y)) {                                                          \
+      micro_test::reporter->Report(#x " >= " #y " failed at %s:%d", __FILE__, \
+                                   __LINE__);                                 \
+      micro_test::did_test_fail = true;                                       \
+    }                                                                         \
+  } while (false)
+
+#define TF_LITE_MICRO_EXPECT_LE(x, y)                                         \
+  do {                                                                        \
+    if ((x) > (y)) {                                                          \
+      micro_test::reporter->Report(#x " <= " #y " failed at %s:%d", __FILE__, \
+                                   __LINE__);                                 \
+      micro_test::did_test_fail = true;                                       \
+    }                                                                         \
+  } while (false)
+
+#define TF_LITE_MICRO_EXPECT_TRUE(x)                                   \
+  do {                                                                 \
+    if (!x) {                                                          \
+      micro_test::reporter->Report(#x " was not true failed at %s:%d", \
+                                   __FILE__, __LINE__);                \
+      micro_test::did_test_fail = true;                                \
+    }                                                                  \
+  } while (false)
+
+#define TF_LITE_MICRO_EXPECT_FALSE(x)                                   \
+  do {                                                                  \
+    if (x) {                                                            \
+      micro_test::reporter->Report(#x " was not false failed at %s:%d", \
+                                   __FILE__, __LINE__);                 \
+      micro_test::did_test_fail = true;                                 \
+    }                                                                   \
+  } while (false)
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_TESTING_MICRO_TEST_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/testing/test_utils.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/testing/test_utils.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,273 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_EXPERIMENTAL_MICRO_TESTING_TEST_UTILS_H_
+#define TENSORFLOW_LITE_EXPERIMENTAL_MICRO_TESTING_TEST_UTILS_H_
+
+#include <cmath>
+#include <cstdint>
+#include <initializer_list>
+#include <limits>
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/core/api/tensor_utils.h"
+#include "tensorflow/lite/experimental/micro/micro_utils.h"
+#include "tensorflow/lite/experimental/micro/test_helpers.h"
+#include "tensorflow/lite/experimental/micro/testing/micro_test.h"
+
+namespace tflite {
+namespace testing {
+
+// Note: These methods are deprecated, do not use.  See b/141332970.
+
+// TODO(kreeger): Don't use this anymore in our tests. Optimized compiler
+// settings can play with pointer placement on the stack (b/140130236).
+inline TfLiteIntArray* IntArrayFromInitializer(
+    std::initializer_list<int> int_initializer) {
+  return IntArrayFromInts(int_initializer.begin());
+}
+
+// Derives the quantization range max from scaling factor and zero point.
+template <typename T>
+inline float MaxFromZeroPointScale(const int zero_point, const float scale) {
+  return (std::numeric_limits<T>::max() - zero_point) * scale;
+}
+
+// Derives the quantization range min from scaling factor and zero point.
+template <typename T>
+inline float MinFromZeroPointScale(const int zero_point, const float scale) {
+  return (std::numeric_limits<T>::min() - zero_point) * scale;
+}
+
+// Derives the quantization scaling factor from a min and max range.
+template <typename T>
+inline float ScaleFromMinMax(const float min, const float max) {
+  return (max - min) / ((std::numeric_limits<T>::max() * 1.0) -
+                        std::numeric_limits<T>::min());
+}
+
+// Derives the quantization zero point from a min and max range.
+template <typename T>
+inline int ZeroPointFromMinMax(const float min, const float max) {
+  return static_cast<int>(std::numeric_limits<T>::min()) +
+         static_cast<int>(-min / ScaleFromMinMax<T>(min, max) + 0.5f);
+}
+
+// Converts a float value into an unsigned eight-bit quantized value.
+inline uint8_t F2Q(const float value, const float min, const float max) {
+  int32_t result = ZeroPointFromMinMax<uint8_t>(min, max) +
+                   (value / ScaleFromMinMax<uint8_t>(min, max)) + 0.5f;
+  if (result < std::numeric_limits<uint8_t>::min()) {
+    result = std::numeric_limits<uint8_t>::min();
+  }
+  if (result > std::numeric_limits<uint8_t>::max()) {
+    result = std::numeric_limits<uint8_t>::max();
+  }
+  return result;
+}
+
+// Converts a float value into a signed eight-bit quantized value.
+inline int8_t F2QS(const float value, const float min, const float max) {
+  return F2Q(value, min, max) + std::numeric_limits<int8_t>::min();
+}
+
+// Converts a float value into a signed thirty-two-bit quantized value.  Note
+// that values close to max int and min int may see significant error due to
+// a lack of floating point granularity for large values.
+inline int32_t F2Q32(const float value, const float scale) {
+  double quantized = value / scale;
+  if (quantized > std::numeric_limits<int32_t>::max()) {
+    quantized = std::numeric_limits<int32_t>::max();
+  } else if (quantized < std::numeric_limits<int32_t>::min()) {
+    quantized = std::numeric_limits<int32_t>::min();
+  }
+  return static_cast<int>(quantized);
+}
+
+// TODO(b/141330728): Move this method elsewhere as part clean up.
+inline void PopulateContext(TfLiteTensor* tensors, int tensors_size,
+                            TfLiteContext* context) {
+  context->tensors_size = tensors_size;
+  context->tensors = tensors;
+  context->impl_ = static_cast<void*>(micro_test::reporter);
+  context->GetExecutionPlan = nullptr;
+  context->ResizeTensor = nullptr;
+  context->ReportError = ReportOpError;
+  context->AddTensors = nullptr;
+  context->GetNodeAndRegistration = nullptr;
+  context->ReplaceNodeSubsetsWithDelegateKernels = nullptr;
+  context->recommended_num_threads = 1;
+  context->GetExternalContext = nullptr;
+  context->SetExternalContext = nullptr;
+
+  for (int i = 0; i < tensors_size; ++i) {
+    if (context->tensors[i].is_variable) {
+      ResetVariableTensor(&context->tensors[i]);
+    }
+  }
+}
+inline TfLiteTensor CreateFloatTensor(std::initializer_list<float> data,
+                                      TfLiteIntArray* dims, const char* name,
+                                      bool is_variable = false) {
+  return CreateFloatTensor(data.begin(), dims, name, is_variable);
+}
+
+inline TfLiteTensor CreateBoolTensor(std::initializer_list<bool> data,
+                                     TfLiteIntArray* dims, const char* name,
+                                     bool is_variable = false) {
+  return CreateBoolTensor(data.begin(), dims, name, is_variable);
+}
+
+inline TfLiteTensor CreateQuantizedTensor(const uint8_t* data,
+                                          TfLiteIntArray* dims,
+                                          const char* name, float min,
+                                          float max, bool is_variable = false) {
+  TfLiteTensor result;
+  result.type = kTfLiteUInt8;
+  result.data.uint8 = const_cast<uint8_t*>(data);
+  result.dims = dims;
+  result.params = {ScaleFromMinMax<uint8_t>(min, max),
+                   ZeroPointFromMinMax<uint8_t>(min, max)};
+  result.allocation_type = kTfLiteMemNone;
+  result.bytes = ElementCount(*dims) * sizeof(uint8_t);
+  result.allocation = nullptr;
+  result.name = name;
+  result.is_variable = false;
+  return result;
+}
+
+inline TfLiteTensor CreateQuantizedTensor(std::initializer_list<uint8_t> data,
+                                          TfLiteIntArray* dims,
+                                          const char* name, float min,
+                                          float max, bool is_variable = false) {
+  return CreateQuantizedTensor(data.begin(), dims, name, min, max, is_variable);
+}
+
+inline TfLiteTensor CreateQuantizedTensor(const int8_t* data,
+                                          TfLiteIntArray* dims,
+                                          const char* name, float min,
+                                          float max, bool is_variable = false) {
+  TfLiteTensor result;
+  result.type = kTfLiteInt8;
+  result.data.int8 = const_cast<int8_t*>(data);
+  result.dims = dims;
+  result.params = {ScaleFromMinMax<int8_t>(min, max),
+                   ZeroPointFromMinMax<int8_t>(min, max)};
+  result.allocation_type = kTfLiteMemNone;
+  result.bytes = ElementCount(*dims) * sizeof(int8_t);
+  result.allocation = nullptr;
+  result.name = name;
+  result.is_variable = is_variable;
+  return result;
+}
+
+inline TfLiteTensor CreateQuantizedTensor(std::initializer_list<int8_t> data,
+                                          TfLiteIntArray* dims,
+                                          const char* name, float min,
+                                          float max, bool is_variable = false) {
+  return CreateQuantizedTensor(data.begin(), dims, name, min, max, is_variable);
+}
+
+inline TfLiteTensor CreateQuantizedTensor(float* data, uint8_t* quantized_data,
+                                          TfLiteIntArray* dims,
+                                          const char* name,
+                                          bool is_variable = false) {
+  TfLiteTensor result;
+  SymmetricQuantize(data, dims, quantized_data, &result.params.scale);
+  result.data.uint8 = quantized_data;
+  result.type = kTfLiteUInt8;
+  result.dims = dims;
+  result.params.zero_point = 128;
+  result.allocation_type = kTfLiteMemNone;
+  result.bytes = ElementCount(*dims) * sizeof(uint8_t);
+  result.allocation = nullptr;
+  result.name = name;
+  result.is_variable = is_variable;
+  return result;
+}
+
+inline TfLiteTensor CreateQuantizedTensor(float* data, int8_t* quantized_data,
+                                          TfLiteIntArray* dims,
+                                          const char* name,
+                                          bool is_variable = false) {
+  TfLiteTensor result;
+  SignedSymmetricQuantize(data, dims, quantized_data, &result.params.scale);
+  result.data.int8 = quantized_data;
+  result.type = kTfLiteInt8;
+  result.dims = dims;
+  result.params.zero_point = 0;
+  result.allocation_type = kTfLiteMemNone;
+  result.bytes = ElementCount(*dims) * sizeof(int8_t);
+  result.allocation = nullptr;
+  result.name = name;
+  result.is_variable = is_variable;
+  return result;
+}
+
+inline TfLiteTensor CreateQuantized32Tensor(const int32_t* data,
+                                            TfLiteIntArray* dims,
+                                            const char* name, float scale,
+                                            bool is_variable = false) {
+  TfLiteTensor result;
+  result.type = kTfLiteInt32;
+  result.data.i32 = const_cast<int32_t*>(data);
+  result.dims = dims;
+  // Quantized int32 tensors always have a zero point of 0, since the range of
+  // int32 values is large, and because zero point costs extra cycles during
+  // processing.
+  result.params = {scale, 0};
+  result.allocation_type = kTfLiteMemNone;
+  result.bytes = ElementCount(*dims) * sizeof(int32_t);
+  result.allocation = nullptr;
+  result.name = name;
+  result.is_variable = is_variable;
+  return result;
+}
+
+inline TfLiteTensor CreateQuantized32Tensor(std::initializer_list<int32_t> data,
+                                            TfLiteIntArray* dims,
+                                            const char* name, float scale,
+                                            bool is_variable = false) {
+  return CreateQuantized32Tensor(data.begin(), dims, name, scale, is_variable);
+}
+
+template <typename input_type = int32_t,
+          TfLiteType tensor_input_type = kTfLiteInt32>
+inline TfLiteTensor CreateTensor(const input_type* data, TfLiteIntArray* dims,
+                                 const char* name, bool is_variable = false) {
+  TfLiteTensor result;
+  result.type = tensor_input_type;
+  result.data.raw = reinterpret_cast<char*>(const_cast<input_type*>(data));
+  result.dims = dims;
+  result.allocation_type = kTfLiteMemNone;
+  result.bytes = ElementCount(*dims) * sizeof(input_type);
+  result.allocation = nullptr;
+  result.name = name;
+  result.is_variable = is_variable;
+  return result;
+}
+
+template <typename input_type = int32_t,
+          TfLiteType tensor_input_type = kTfLiteInt32>
+inline TfLiteTensor CreateTensor(std::initializer_list<input_type> data,
+                                 TfLiteIntArray* dims, const char* name,
+                                 bool is_variable = false) {
+  return CreateTensor<input_type, tensor_input_type>(data.begin(), dims, name,
+                                                     is_variable);
+}
+
+}  // namespace testing
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_EXPERIMENTAL_MICRO_TESTING_TEST_UTILS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/CMSIS_ext/arm_cmplx_mag_squared_q10p6.c
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/CMSIS_ext/arm_cmplx_mag_squared_q10p6.c	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,141 @@
+/* This file is a modification of the ARM CMSIS library file arm_cmplx_mag_squared_q15.c
+ * We have retained the original copyright and header information, in
+ * accordance with the Apache 2.0 license terms.
+ */
+
+/* ----------------------------------------------------------------------
+ * Project:      CMSIS DSP Library
+ * Title:        arm_cmplx_mag_squared_q15.c
+ * Description:  Q15 complex magnitude squared
+ *
+ * $Date:        27. January 2017
+ * $Revision:    V.1.5.1
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+/*
+ * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "arm_math.h"
+
+/**
+ * @ingroup groupCmplxMath
+ */
+
+/**
+ * @addtogroup cmplx_mag_squared
+ * @{
+ */
+
+/**
+ * @brief  Q15 complex magnitude squared
+ * @param  *pSrc points to the complex input vector
+ * @param  *pDst points to the real output vector
+ * @param  numSamples number of complex samples in the input vector
+ * @return none.
+ *
+ * <b>Scaling and Overflow Behavior:</b>
+ * \par
+ * The function implements 1.15 by 1.15 multiplications and finally output is converted into 3.13 format.
+ */
+
+void arm_cmplx_mag_squared_q10p6(
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t numSamples)
+{
+  q31_t acc0, acc1;                              /* Accumulators */
+
+#if defined (ARM_MATH_DSP)
+
+  /* Run the below code for Cortex-M4 and Cortex-M3 */
+  uint32_t blkCnt;                               /* loop counter */
+  q31_t in1, in2, in3, in4;
+  q31_t acc2, acc3;
+
+  /*loop Unrolling */
+  blkCnt = numSamples >> 2U;
+
+  /* First part of the processing with loop unrolling.  Compute 4 outputs at a time.
+   ** a second loop below computes the remaining 1 to 3 samples. */
+  while (blkCnt > 0U)
+  {
+    /* C[0] = (A[0] * A[0] + A[1] * A[1]) */
+    in1 = *__SIMD32(pSrc)++;
+    in2 = *__SIMD32(pSrc)++;
+    in3 = *__SIMD32(pSrc)++;
+    in4 = *__SIMD32(pSrc)++;
+
+    acc0 = __SMUAD(in1, in1);
+    acc1 = __SMUAD(in2, in2);
+    acc2 = __SMUAD(in3, in3);
+    acc3 = __SMUAD(in4, in4);
+
+    /* store the result in 3.13 format in the destination buffer. */
+    *pDst++ = (q15_t) (acc0 >> 6);
+    *pDst++ = (q15_t) (acc1 >> 6);
+    *pDst++ = (q15_t) (acc2 >> 6);
+    *pDst++ = (q15_t) (acc3 >> 6);
+
+    /* Decrement the loop counter */
+    blkCnt--;
+  }
+
+  /* If the numSamples is not a multiple of 4, compute any remaining output samples here.
+   ** No loop unrolling is used. */
+  blkCnt = numSamples % 0x4U;
+
+  while (blkCnt > 0U)
+  {
+    /* C[0] = (A[0] * A[0] + A[1] * A[1]) */
+    in1 = *__SIMD32(pSrc)++;
+    acc0 = __SMUAD(in1, in1);
+
+    /* store the result in 3.13 format in the destination buffer. */
+    *pDst++ = (q15_t) (acc0 >> 6);
+
+    /* Decrement the loop counter */
+    blkCnt--;
+  }
+
+#else
+
+  /* Run the below code for Cortex-M0 */
+  q15_t real, imag;                              /* Temporary variables to store real and imaginary values */
+
+  while (numSamples > 0U)
+  {
+    /* out = ((real * real) + (imag * imag)) */
+    real = *pSrc++;
+    imag = *pSrc++;
+    acc0 = (real * real);
+    acc1 = (imag * imag);
+    /* store the result in 3.13 format in the destination buffer. */
+    *pDst++ = (q15_t) (((q63_t) acc0 + acc1) >> 6);
+
+    /* Decrement the loop counter */
+    numSamples--;
+  }
+
+#endif /* #if defined (ARM_MATH_DSP) */
+
+}
+
+/**
+ * @} end of cmplx_mag_squared group
+ */

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/BasicMathFunctions/arm_mult_q15.c
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/BasicMathFunctions/arm_mult_q15.c	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,142 @@
+/* ----------------------------------------------------------------------
+ * Project:      CMSIS DSP Library
+ * Title:        arm_mult_q15.c
+ * Description:  Q15 vector multiplication
+ *
+ * $Date:        27. January 2017
+ * $Revision:    V.1.5.1
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+/*
+ * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "arm_math.h"
+
+/**
+ * @ingroup groupMath
+ */
+
+/**
+ * @addtogroup BasicMult
+ * @{
+ */
+
+
+/**
+ * @brief           Q15 vector multiplication
+ * @param[in]       *pSrcA points to the first input vector
+ * @param[in]       *pSrcB points to the second input vector
+ * @param[out]      *pDst points to the output vector
+ * @param[in]       blockSize number of samples in each vector
+ * @return none.
+ *
+ * <b>Scaling and Overflow Behavior:</b>
+ * \par
+ * The function uses saturating arithmetic.
+ * Results outside of the allowable Q15 range [0x8000 0x7FFF] will be saturated.
+ */
+
+void arm_mult_q15(
+  q15_t * pSrcA,
+  q15_t * pSrcB,
+  q15_t * pDst,
+  uint32_t blockSize)
+{
+  uint32_t blkCnt;                               /* loop counters */
+
+#if defined (ARM_MATH_DSP)
+
+/* Run the below code for Cortex-M4 and Cortex-M3 */
+  q31_t inA1, inA2, inB1, inB2;                  /* temporary input variables */
+  q15_t out1, out2, out3, out4;                  /* temporary output variables */
+  q31_t mul1, mul2, mul3, mul4;                  /* temporary variables */
+
+  /* loop Unrolling */
+  blkCnt = blockSize >> 2U;
+
+  /* First part of the processing with loop unrolling.  Compute 4 outputs at a time.
+   ** a second loop below computes the remaining 1 to 3 samples. */
+  while (blkCnt > 0U)
+  {
+    /* read two samples at a time from sourceA */
+    inA1 = *__SIMD32(pSrcA)++;
+    /* read two samples at a time from sourceB */
+    inB1 = *__SIMD32(pSrcB)++;
+    /* read two samples at a time from sourceA */
+    inA2 = *__SIMD32(pSrcA)++;
+    /* read two samples at a time from sourceB */
+    inB2 = *__SIMD32(pSrcB)++;
+
+    /* multiply mul = sourceA * sourceB */
+    mul1 = (q31_t) ((q15_t) (inA1 >> 16) * (q15_t) (inB1 >> 16));
+    mul2 = (q31_t) ((q15_t) inA1 * (q15_t) inB1);
+    mul3 = (q31_t) ((q15_t) (inA2 >> 16) * (q15_t) (inB2 >> 16));
+    mul4 = (q31_t) ((q15_t) inA2 * (q15_t) inB2);
+
+    /* saturate result to 16 bit */
+    out1 = (q15_t) __SSAT(mul1 >> 15, 16);
+    out2 = (q15_t) __SSAT(mul2 >> 15, 16);
+    out3 = (q15_t) __SSAT(mul3 >> 15, 16);
+    out4 = (q15_t) __SSAT(mul4 >> 15, 16);
+
+    /* store the result */
+#ifndef ARM_MATH_BIG_ENDIAN
+
+    *__SIMD32(pDst)++ = __PKHBT(out2, out1, 16);
+    *__SIMD32(pDst)++ = __PKHBT(out4, out3, 16);
+
+#else
+
+    *__SIMD32(pDst)++ = __PKHBT(out2, out1, 16);
+    *__SIMD32(pDst)++ = __PKHBT(out4, out3, 16);
+
+#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
+
+    /* Decrement the blockSize loop counter */
+    blkCnt--;
+  }
+
+  /* If the blockSize is not a multiple of 4, compute any remaining output samples here.
+   ** No loop unrolling is used. */
+  blkCnt = blockSize % 0x4U;
+
+#else
+
+  /* Run the below code for Cortex-M0 */
+
+  /* Initialize blkCnt with number of samples */
+  blkCnt = blockSize;
+
+#endif /* #if defined (ARM_MATH_DSP) */
+
+
+  while (blkCnt > 0U)
+  {
+    /* C = A * B */
+    /* Multiply the inputs and store the result in the destination buffer */
+    *pDst++ = (q15_t) __SSAT((((q31_t) (*pSrcA++) * (*pSrcB++)) >> 15), 16);
+
+    /* Decrement the blockSize loop counter */
+    blkCnt--;
+  }
+}
+
+/**
+ * @} end of BasicMult group
+ */

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/CommonTables/arm_common_tables.c
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/CommonTables/arm_common_tables.c	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,22176 @@
+/* ----------------------------------------------------------------------
+ * Project:      CMSIS DSP Library
+ * Title:        arm_common_tables.c
+ * Description:  common tables like fft twiddle factors, Bitreverse, reciprocal etc
+ *
+ * $Date:        27. January 2017
+ * $Revision:    V.1.5.1
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+/*
+ * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "arm_math.h"
+#include "arm_common_tables.h"
+
+/**
+ * @ingroup ComplexFFT
+ */
+
+/**
+ * @addtogroup CFFT_CIFFT Complex FFT Tables
+ * @{
+ */
+
+/**
+* \par
+* Pseudo code for Generation of Bit reversal Table is
+* \par
+* <pre>for(l=1;l <= N/4;l++)
+* {
+*   for(i=0;i<logN2;i++)
+*   {
+*     a[i]=l&(1<<i);
+*   }
+*   for(j=0; j<logN2; j++)
+*   {
+*     if (a[j]!=0)
+*     y[l]+=(1<<((logN2-1)-j));
+*   }
+*   y[l] = y[l] >> 1;
+*  } </pre>
+* \par
+* where N = 4096	logN2 = 12
+* \par
+* N is the maximum FFT Size supported
+*/
+
+/*
+* @brief  Table for bit reversal process
+*/
+const uint16_t armBitRevTable[1024] = {
+   0x400, 0x200, 0x600, 0x100, 0x500, 0x300, 0x700, 0x80, 0x480, 0x280,
+   0x680, 0x180, 0x580, 0x380, 0x780, 0x40, 0x440, 0x240, 0x640, 0x140,
+   0x540, 0x340, 0x740, 0xc0, 0x4c0, 0x2c0, 0x6c0, 0x1c0, 0x5c0, 0x3c0,
+   0x7c0, 0x20, 0x420, 0x220, 0x620, 0x120, 0x520, 0x320, 0x720, 0xa0,
+   0x4a0, 0x2a0, 0x6a0, 0x1a0, 0x5a0, 0x3a0, 0x7a0, 0x60, 0x460, 0x260,
+   0x660, 0x160, 0x560, 0x360, 0x760, 0xe0, 0x4e0, 0x2e0, 0x6e0, 0x1e0,
+   0x5e0, 0x3e0, 0x7e0, 0x10, 0x410, 0x210, 0x610, 0x110, 0x510, 0x310,
+   0x710, 0x90, 0x490, 0x290, 0x690, 0x190, 0x590, 0x390, 0x790, 0x50,
+   0x450, 0x250, 0x650, 0x150, 0x550, 0x350, 0x750, 0xd0, 0x4d0, 0x2d0,
+   0x6d0, 0x1d0, 0x5d0, 0x3d0, 0x7d0, 0x30, 0x430, 0x230, 0x630, 0x130,
+   0x530, 0x330, 0x730, 0xb0, 0x4b0, 0x2b0, 0x6b0, 0x1b0, 0x5b0, 0x3b0,
+   0x7b0, 0x70, 0x470, 0x270, 0x670, 0x170, 0x570, 0x370, 0x770, 0xf0,
+   0x4f0, 0x2f0, 0x6f0, 0x1f0, 0x5f0, 0x3f0, 0x7f0, 0x8, 0x408, 0x208,
+   0x608, 0x108, 0x508, 0x308, 0x708, 0x88, 0x488, 0x288, 0x688, 0x188,
+   0x588, 0x388, 0x788, 0x48, 0x448, 0x248, 0x648, 0x148, 0x548, 0x348,
+   0x748, 0xc8, 0x4c8, 0x2c8, 0x6c8, 0x1c8, 0x5c8, 0x3c8, 0x7c8, 0x28,
+   0x428, 0x228, 0x628, 0x128, 0x528, 0x328, 0x728, 0xa8, 0x4a8, 0x2a8,
+   0x6a8, 0x1a8, 0x5a8, 0x3a8, 0x7a8, 0x68, 0x468, 0x268, 0x668, 0x168,
+   0x568, 0x368, 0x768, 0xe8, 0x4e8, 0x2e8, 0x6e8, 0x1e8, 0x5e8, 0x3e8,
+   0x7e8, 0x18, 0x418, 0x218, 0x618, 0x118, 0x518, 0x318, 0x718, 0x98,
+   0x498, 0x298, 0x698, 0x198, 0x598, 0x398, 0x798, 0x58, 0x458, 0x258,
+   0x658, 0x158, 0x558, 0x358, 0x758, 0xd8, 0x4d8, 0x2d8, 0x6d8, 0x1d8,
+   0x5d8, 0x3d8, 0x7d8, 0x38, 0x438, 0x238, 0x638, 0x138, 0x538, 0x338,
+   0x738, 0xb8, 0x4b8, 0x2b8, 0x6b8, 0x1b8, 0x5b8, 0x3b8, 0x7b8, 0x78,
+   0x478, 0x278, 0x678, 0x178, 0x578, 0x378, 0x778, 0xf8, 0x4f8, 0x2f8,
+   0x6f8, 0x1f8, 0x5f8, 0x3f8, 0x7f8, 0x4, 0x404, 0x204, 0x604, 0x104,
+   0x504, 0x304, 0x704, 0x84, 0x484, 0x284, 0x684, 0x184, 0x584, 0x384,
+   0x784, 0x44, 0x444, 0x244, 0x644, 0x144, 0x544, 0x344, 0x744, 0xc4,
+   0x4c4, 0x2c4, 0x6c4, 0x1c4, 0x5c4, 0x3c4, 0x7c4, 0x24, 0x424, 0x224,
+   0x624, 0x124, 0x524, 0x324, 0x724, 0xa4, 0x4a4, 0x2a4, 0x6a4, 0x1a4,
+   0x5a4, 0x3a4, 0x7a4, 0x64, 0x464, 0x264, 0x664, 0x164, 0x564, 0x364,
+   0x764, 0xe4, 0x4e4, 0x2e4, 0x6e4, 0x1e4, 0x5e4, 0x3e4, 0x7e4, 0x14,
+   0x414, 0x214, 0x614, 0x114, 0x514, 0x314, 0x714, 0x94, 0x494, 0x294,
+   0x694, 0x194, 0x594, 0x394, 0x794, 0x54, 0x454, 0x254, 0x654, 0x154,
+   0x554, 0x354, 0x754, 0xd4, 0x4d4, 0x2d4, 0x6d4, 0x1d4, 0x5d4, 0x3d4,
+   0x7d4, 0x34, 0x434, 0x234, 0x634, 0x134, 0x534, 0x334, 0x734, 0xb4,
+   0x4b4, 0x2b4, 0x6b4, 0x1b4, 0x5b4, 0x3b4, 0x7b4, 0x74, 0x474, 0x274,
+   0x674, 0x174, 0x574, 0x374, 0x774, 0xf4, 0x4f4, 0x2f4, 0x6f4, 0x1f4,
+   0x5f4, 0x3f4, 0x7f4, 0xc, 0x40c, 0x20c, 0x60c, 0x10c, 0x50c, 0x30c,
+   0x70c, 0x8c, 0x48c, 0x28c, 0x68c, 0x18c, 0x58c, 0x38c, 0x78c, 0x4c,
+   0x44c, 0x24c, 0x64c, 0x14c, 0x54c, 0x34c, 0x74c, 0xcc, 0x4cc, 0x2cc,
+   0x6cc, 0x1cc, 0x5cc, 0x3cc, 0x7cc, 0x2c, 0x42c, 0x22c, 0x62c, 0x12c,
+   0x52c, 0x32c, 0x72c, 0xac, 0x4ac, 0x2ac, 0x6ac, 0x1ac, 0x5ac, 0x3ac,
+   0x7ac, 0x6c, 0x46c, 0x26c, 0x66c, 0x16c, 0x56c, 0x36c, 0x76c, 0xec,
+   0x4ec, 0x2ec, 0x6ec, 0x1ec, 0x5ec, 0x3ec, 0x7ec, 0x1c, 0x41c, 0x21c,
+   0x61c, 0x11c, 0x51c, 0x31c, 0x71c, 0x9c, 0x49c, 0x29c, 0x69c, 0x19c,
+   0x59c, 0x39c, 0x79c, 0x5c, 0x45c, 0x25c, 0x65c, 0x15c, 0x55c, 0x35c,
+   0x75c, 0xdc, 0x4dc, 0x2dc, 0x6dc, 0x1dc, 0x5dc, 0x3dc, 0x7dc, 0x3c,
+   0x43c, 0x23c, 0x63c, 0x13c, 0x53c, 0x33c, 0x73c, 0xbc, 0x4bc, 0x2bc,
+   0x6bc, 0x1bc, 0x5bc, 0x3bc, 0x7bc, 0x7c, 0x47c, 0x27c, 0x67c, 0x17c,
+   0x57c, 0x37c, 0x77c, 0xfc, 0x4fc, 0x2fc, 0x6fc, 0x1fc, 0x5fc, 0x3fc,
+   0x7fc, 0x2, 0x402, 0x202, 0x602, 0x102, 0x502, 0x302, 0x702, 0x82,
+   0x482, 0x282, 0x682, 0x182, 0x582, 0x382, 0x782, 0x42, 0x442, 0x242,
+   0x642, 0x142, 0x542, 0x342, 0x742, 0xc2, 0x4c2, 0x2c2, 0x6c2, 0x1c2,
+   0x5c2, 0x3c2, 0x7c2, 0x22, 0x422, 0x222, 0x622, 0x122, 0x522, 0x322,
+   0x722, 0xa2, 0x4a2, 0x2a2, 0x6a2, 0x1a2, 0x5a2, 0x3a2, 0x7a2, 0x62,
+   0x462, 0x262, 0x662, 0x162, 0x562, 0x362, 0x762, 0xe2, 0x4e2, 0x2e2,
+   0x6e2, 0x1e2, 0x5e2, 0x3e2, 0x7e2, 0x12, 0x412, 0x212, 0x612, 0x112,
+   0x512, 0x312, 0x712, 0x92, 0x492, 0x292, 0x692, 0x192, 0x592, 0x392,
+   0x792, 0x52, 0x452, 0x252, 0x652, 0x152, 0x552, 0x352, 0x752, 0xd2,
+   0x4d2, 0x2d2, 0x6d2, 0x1d2, 0x5d2, 0x3d2, 0x7d2, 0x32, 0x432, 0x232,
+   0x632, 0x132, 0x532, 0x332, 0x732, 0xb2, 0x4b2, 0x2b2, 0x6b2, 0x1b2,
+   0x5b2, 0x3b2, 0x7b2, 0x72, 0x472, 0x272, 0x672, 0x172, 0x572, 0x372,
+   0x772, 0xf2, 0x4f2, 0x2f2, 0x6f2, 0x1f2, 0x5f2, 0x3f2, 0x7f2, 0xa,
+   0x40a, 0x20a, 0x60a, 0x10a, 0x50a, 0x30a, 0x70a, 0x8a, 0x48a, 0x28a,
+   0x68a, 0x18a, 0x58a, 0x38a, 0x78a, 0x4a, 0x44a, 0x24a, 0x64a, 0x14a,
+   0x54a, 0x34a, 0x74a, 0xca, 0x4ca, 0x2ca, 0x6ca, 0x1ca, 0x5ca, 0x3ca,
+   0x7ca, 0x2a, 0x42a, 0x22a, 0x62a, 0x12a, 0x52a, 0x32a, 0x72a, 0xaa,
+   0x4aa, 0x2aa, 0x6aa, 0x1aa, 0x5aa, 0x3aa, 0x7aa, 0x6a, 0x46a, 0x26a,
+   0x66a, 0x16a, 0x56a, 0x36a, 0x76a, 0xea, 0x4ea, 0x2ea, 0x6ea, 0x1ea,
+   0x5ea, 0x3ea, 0x7ea, 0x1a, 0x41a, 0x21a, 0x61a, 0x11a, 0x51a, 0x31a,
+   0x71a, 0x9a, 0x49a, 0x29a, 0x69a, 0x19a, 0x59a, 0x39a, 0x79a, 0x5a,
+   0x45a, 0x25a, 0x65a, 0x15a, 0x55a, 0x35a, 0x75a, 0xda, 0x4da, 0x2da,
+   0x6da, 0x1da, 0x5da, 0x3da, 0x7da, 0x3a, 0x43a, 0x23a, 0x63a, 0x13a,
+   0x53a, 0x33a, 0x73a, 0xba, 0x4ba, 0x2ba, 0x6ba, 0x1ba, 0x5ba, 0x3ba,
+   0x7ba, 0x7a, 0x47a, 0x27a, 0x67a, 0x17a, 0x57a, 0x37a, 0x77a, 0xfa,
+   0x4fa, 0x2fa, 0x6fa, 0x1fa, 0x5fa, 0x3fa, 0x7fa, 0x6, 0x406, 0x206,
+   0x606, 0x106, 0x506, 0x306, 0x706, 0x86, 0x486, 0x286, 0x686, 0x186,
+   0x586, 0x386, 0x786, 0x46, 0x446, 0x246, 0x646, 0x146, 0x546, 0x346,
+   0x746, 0xc6, 0x4c6, 0x2c6, 0x6c6, 0x1c6, 0x5c6, 0x3c6, 0x7c6, 0x26,
+   0x426, 0x226, 0x626, 0x126, 0x526, 0x326, 0x726, 0xa6, 0x4a6, 0x2a6,
+   0x6a6, 0x1a6, 0x5a6, 0x3a6, 0x7a6, 0x66, 0x466, 0x266, 0x666, 0x166,
+   0x566, 0x366, 0x766, 0xe6, 0x4e6, 0x2e6, 0x6e6, 0x1e6, 0x5e6, 0x3e6,
+   0x7e6, 0x16, 0x416, 0x216, 0x616, 0x116, 0x516, 0x316, 0x716, 0x96,
+   0x496, 0x296, 0x696, 0x196, 0x596, 0x396, 0x796, 0x56, 0x456, 0x256,
+   0x656, 0x156, 0x556, 0x356, 0x756, 0xd6, 0x4d6, 0x2d6, 0x6d6, 0x1d6,
+   0x5d6, 0x3d6, 0x7d6, 0x36, 0x436, 0x236, 0x636, 0x136, 0x536, 0x336,
+   0x736, 0xb6, 0x4b6, 0x2b6, 0x6b6, 0x1b6, 0x5b6, 0x3b6, 0x7b6, 0x76,
+   0x476, 0x276, 0x676, 0x176, 0x576, 0x376, 0x776, 0xf6, 0x4f6, 0x2f6,
+   0x6f6, 0x1f6, 0x5f6, 0x3f6, 0x7f6, 0xe, 0x40e, 0x20e, 0x60e, 0x10e,
+   0x50e, 0x30e, 0x70e, 0x8e, 0x48e, 0x28e, 0x68e, 0x18e, 0x58e, 0x38e,
+   0x78e, 0x4e, 0x44e, 0x24e, 0x64e, 0x14e, 0x54e, 0x34e, 0x74e, 0xce,
+   0x4ce, 0x2ce, 0x6ce, 0x1ce, 0x5ce, 0x3ce, 0x7ce, 0x2e, 0x42e, 0x22e,
+   0x62e, 0x12e, 0x52e, 0x32e, 0x72e, 0xae, 0x4ae, 0x2ae, 0x6ae, 0x1ae,
+   0x5ae, 0x3ae, 0x7ae, 0x6e, 0x46e, 0x26e, 0x66e, 0x16e, 0x56e, 0x36e,
+   0x76e, 0xee, 0x4ee, 0x2ee, 0x6ee, 0x1ee, 0x5ee, 0x3ee, 0x7ee, 0x1e,
+   0x41e, 0x21e, 0x61e, 0x11e, 0x51e, 0x31e, 0x71e, 0x9e, 0x49e, 0x29e,
+   0x69e, 0x19e, 0x59e, 0x39e, 0x79e, 0x5e, 0x45e, 0x25e, 0x65e, 0x15e,
+   0x55e, 0x35e, 0x75e, 0xde, 0x4de, 0x2de, 0x6de, 0x1de, 0x5de, 0x3de,
+   0x7de, 0x3e, 0x43e, 0x23e, 0x63e, 0x13e, 0x53e, 0x33e, 0x73e, 0xbe,
+   0x4be, 0x2be, 0x6be, 0x1be, 0x5be, 0x3be, 0x7be, 0x7e, 0x47e, 0x27e,
+   0x67e, 0x17e, 0x57e, 0x37e, 0x77e, 0xfe, 0x4fe, 0x2fe, 0x6fe, 0x1fe,
+   0x5fe, 0x3fe, 0x7fe, 0x1
+};
+
+
+/*
+* @brief  Floating-point Twiddle factors Table Generation
+*/
+
+/**
+* \par
+* Example code for Floating-point Twiddle factors Generation:
+* \par
+* <pre>for(i = 0; i< N/; i++)
+* {
+*	twiddleCoef[2*i]= cos(i * 2*PI/(float)N);
+*	twiddleCoef[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 16	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are in interleaved fashion
+*
+*/
+const float32_t twiddleCoef_16[32] = {
+    1.000000000f,  0.000000000f,
+    0.923879533f,  0.382683432f,
+    0.707106781f,  0.707106781f,
+    0.382683432f,  0.923879533f,
+    0.000000000f,  1.000000000f,
+   -0.382683432f,  0.923879533f,
+   -0.707106781f,  0.707106781f,
+   -0.923879533f,  0.382683432f,
+   -1.000000000f,  0.000000000f,
+   -0.923879533f, -0.382683432f,
+   -0.707106781f, -0.707106781f,
+   -0.382683432f, -0.923879533f,
+   -0.000000000f, -1.000000000f,
+    0.382683432f, -0.923879533f,
+    0.707106781f, -0.707106781f,
+    0.923879533f, -0.382683432f
+};
+
+/**
+* \par
+* Example code for Floating-point Twiddle factors Generation:
+* \par
+* <pre>for(i = 0; i< N/; i++)
+* {
+*	twiddleCoef[2*i]= cos(i * 2*PI/(float)N);
+*	twiddleCoef[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 32	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are in interleaved fashion
+*
+*/
+const float32_t twiddleCoef_32[64] = {
+    1.000000000f,  0.000000000f,
+    0.980785280f,  0.195090322f,
+    0.923879533f,  0.382683432f,
+    0.831469612f,  0.555570233f,
+    0.707106781f,  0.707106781f,
+    0.555570233f,  0.831469612f,
+    0.382683432f,  0.923879533f,
+    0.195090322f,  0.980785280f,
+    0.000000000f,  1.000000000f,
+   -0.195090322f,  0.980785280f,
+   -0.382683432f,  0.923879533f,
+   -0.555570233f,  0.831469612f,
+   -0.707106781f,  0.707106781f,
+   -0.831469612f,  0.555570233f,
+   -0.923879533f,  0.382683432f,
+   -0.980785280f,  0.195090322f,
+   -1.000000000f,  0.000000000f,
+   -0.980785280f, -0.195090322f,
+   -0.923879533f, -0.382683432f,
+   -0.831469612f, -0.555570233f,
+   -0.707106781f, -0.707106781f,
+   -0.555570233f, -0.831469612f,
+   -0.382683432f, -0.923879533f,
+   -0.195090322f, -0.980785280f,
+   -0.000000000f, -1.000000000f,
+    0.195090322f, -0.980785280f,
+    0.382683432f, -0.923879533f,
+    0.555570233f, -0.831469612f,
+    0.707106781f, -0.707106781f,
+    0.831469612f, -0.555570233f,
+    0.923879533f, -0.382683432f,
+    0.980785280f, -0.195090322f
+};
+
+/**
+* \par
+* Example code for Floating-point Twiddle factors Generation:
+* \par
+* <pre>for(i = 0; i< N/; i++)
+* {
+*	twiddleCoef[2*i]= cos(i * 2*PI/(float)N);
+*	twiddleCoef[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 64	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are in interleaved fashion
+*
+*/
+const float32_t twiddleCoef_64[128] = {
+    1.000000000f,  0.000000000f,
+    0.995184727f,  0.098017140f,
+    0.980785280f,  0.195090322f,
+    0.956940336f,  0.290284677f,
+    0.923879533f,  0.382683432f,
+    0.881921264f,  0.471396737f,
+    0.831469612f,  0.555570233f,
+    0.773010453f,  0.634393284f,
+    0.707106781f,  0.707106781f,
+    0.634393284f,  0.773010453f,
+    0.555570233f,  0.831469612f,
+    0.471396737f,  0.881921264f,
+    0.382683432f,  0.923879533f,
+    0.290284677f,  0.956940336f,
+    0.195090322f,  0.980785280f,
+    0.098017140f,  0.995184727f,
+    0.000000000f,  1.000000000f,
+   -0.098017140f,  0.995184727f,
+   -0.195090322f,  0.980785280f,
+   -0.290284677f,  0.956940336f,
+   -0.382683432f,  0.923879533f,
+   -0.471396737f,  0.881921264f,
+   -0.555570233f,  0.831469612f,
+   -0.634393284f,  0.773010453f,
+   -0.707106781f,  0.707106781f,
+   -0.773010453f,  0.634393284f,
+   -0.831469612f,  0.555570233f,
+   -0.881921264f,  0.471396737f,
+   -0.923879533f,  0.382683432f,
+   -0.956940336f,  0.290284677f,
+   -0.980785280f,  0.195090322f,
+   -0.995184727f,  0.098017140f,
+   -1.000000000f,  0.000000000f,
+   -0.995184727f, -0.098017140f,
+   -0.980785280f, -0.195090322f,
+   -0.956940336f, -0.290284677f,
+   -0.923879533f, -0.382683432f,
+   -0.881921264f, -0.471396737f,
+   -0.831469612f, -0.555570233f,
+   -0.773010453f, -0.634393284f,
+   -0.707106781f, -0.707106781f,
+   -0.634393284f, -0.773010453f,
+   -0.555570233f, -0.831469612f,
+   -0.471396737f, -0.881921264f,
+   -0.382683432f, -0.923879533f,
+   -0.290284677f, -0.956940336f,
+   -0.195090322f, -0.980785280f,
+   -0.098017140f, -0.995184727f,
+   -0.000000000f, -1.000000000f,
+    0.098017140f, -0.995184727f,
+    0.195090322f, -0.980785280f,
+    0.290284677f, -0.956940336f,
+    0.382683432f, -0.923879533f,
+    0.471396737f, -0.881921264f,
+    0.555570233f, -0.831469612f,
+    0.634393284f, -0.773010453f,
+    0.707106781f, -0.707106781f,
+    0.773010453f, -0.634393284f,
+    0.831469612f, -0.555570233f,
+    0.881921264f, -0.471396737f,
+    0.923879533f, -0.382683432f,
+    0.956940336f, -0.290284677f,
+    0.980785280f, -0.195090322f,
+    0.995184727f, -0.098017140f
+};
+
+/**
+* \par
+* Example code for Floating-point Twiddle factors Generation:
+* \par
+* <pre>for(i = 0; i< N/; i++)
+* {
+*	twiddleCoef[2*i]= cos(i * 2*PI/(float)N);
+*	twiddleCoef[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 128	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are in interleaved fashion
+*
+*/
+
+const float32_t twiddleCoef_128[256] = {
+    1.000000000f,  0.000000000f,
+    0.998795456f,  0.049067674f,
+    0.995184727f,  0.098017140f,
+    0.989176510f,  0.146730474f,
+    0.980785280f,  0.195090322f,
+    0.970031253f,  0.242980180f,
+    0.956940336f,  0.290284677f,
+    0.941544065f,  0.336889853f,
+    0.923879533f,  0.382683432f,
+    0.903989293f,  0.427555093f,
+    0.881921264f,  0.471396737f,
+    0.857728610f,  0.514102744f,
+    0.831469612f,  0.555570233f,
+    0.803207531f,  0.595699304f,
+    0.773010453f,  0.634393284f,
+    0.740951125f,  0.671558955f,
+    0.707106781f,  0.707106781f,
+    0.671558955f,  0.740951125f,
+    0.634393284f,  0.773010453f,
+    0.595699304f,  0.803207531f,
+    0.555570233f,  0.831469612f,
+    0.514102744f,  0.857728610f,
+    0.471396737f,  0.881921264f,
+    0.427555093f,  0.903989293f,
+    0.382683432f,  0.923879533f,
+    0.336889853f,  0.941544065f,
+    0.290284677f,  0.956940336f,
+    0.242980180f,  0.970031253f,
+    0.195090322f,  0.980785280f,
+    0.146730474f,  0.989176510f,
+    0.098017140f,  0.995184727f,
+    0.049067674f,  0.998795456f,
+    0.000000000f,  1.000000000f,
+   -0.049067674f,  0.998795456f,
+   -0.098017140f,  0.995184727f,
+   -0.146730474f,  0.989176510f,
+   -0.195090322f,  0.980785280f,
+   -0.242980180f,  0.970031253f,
+   -0.290284677f,  0.956940336f,
+   -0.336889853f,  0.941544065f,
+   -0.382683432f,  0.923879533f,
+   -0.427555093f,  0.903989293f,
+   -0.471396737f,  0.881921264f,
+   -0.514102744f,  0.857728610f,
+   -0.555570233f,  0.831469612f,
+   -0.595699304f,  0.803207531f,
+   -0.634393284f,  0.773010453f,
+   -0.671558955f,  0.740951125f,
+   -0.707106781f,  0.707106781f,
+   -0.740951125f,  0.671558955f,
+   -0.773010453f,  0.634393284f,
+   -0.803207531f,  0.595699304f,
+   -0.831469612f,  0.555570233f,
+   -0.857728610f,  0.514102744f,
+   -0.881921264f,  0.471396737f,
+   -0.903989293f,  0.427555093f,
+   -0.923879533f,  0.382683432f,
+   -0.941544065f,  0.336889853f,
+   -0.956940336f,  0.290284677f,
+   -0.970031253f,  0.242980180f,
+   -0.980785280f,  0.195090322f,
+   -0.989176510f,  0.146730474f,
+   -0.995184727f,  0.098017140f,
+   -0.998795456f,  0.049067674f,
+   -1.000000000f,  0.000000000f,
+   -0.998795456f, -0.049067674f,
+   -0.995184727f, -0.098017140f,
+   -0.989176510f, -0.146730474f,
+   -0.980785280f, -0.195090322f,
+   -0.970031253f, -0.242980180f,
+   -0.956940336f, -0.290284677f,
+   -0.941544065f, -0.336889853f,
+   -0.923879533f, -0.382683432f,
+   -0.903989293f, -0.427555093f,
+   -0.881921264f, -0.471396737f,
+   -0.857728610f, -0.514102744f,
+   -0.831469612f, -0.555570233f,
+   -0.803207531f, -0.595699304f,
+   -0.773010453f, -0.634393284f,
+   -0.740951125f, -0.671558955f,
+   -0.707106781f, -0.707106781f,
+   -0.671558955f, -0.740951125f,
+   -0.634393284f, -0.773010453f,
+   -0.595699304f, -0.803207531f,
+   -0.555570233f, -0.831469612f,
+   -0.514102744f, -0.857728610f,
+   -0.471396737f, -0.881921264f,
+   -0.427555093f, -0.903989293f,
+   -0.382683432f, -0.923879533f,
+   -0.336889853f, -0.941544065f,
+   -0.290284677f, -0.956940336f,
+   -0.242980180f, -0.970031253f,
+   -0.195090322f, -0.980785280f,
+   -0.146730474f, -0.989176510f,
+   -0.098017140f, -0.995184727f,
+   -0.049067674f, -0.998795456f,
+   -0.000000000f, -1.000000000f,
+    0.049067674f, -0.998795456f,
+    0.098017140f, -0.995184727f,
+    0.146730474f, -0.989176510f,
+    0.195090322f, -0.980785280f,
+    0.242980180f, -0.970031253f,
+    0.290284677f, -0.956940336f,
+    0.336889853f, -0.941544065f,
+    0.382683432f, -0.923879533f,
+    0.427555093f, -0.903989293f,
+    0.471396737f, -0.881921264f,
+    0.514102744f, -0.857728610f,
+    0.555570233f, -0.831469612f,
+    0.595699304f, -0.803207531f,
+    0.634393284f, -0.773010453f,
+    0.671558955f, -0.740951125f,
+    0.707106781f, -0.707106781f,
+    0.740951125f, -0.671558955f,
+    0.773010453f, -0.634393284f,
+    0.803207531f, -0.595699304f,
+    0.831469612f, -0.555570233f,
+    0.857728610f, -0.514102744f,
+    0.881921264f, -0.471396737f,
+    0.903989293f, -0.427555093f,
+    0.923879533f, -0.382683432f,
+    0.941544065f, -0.336889853f,
+    0.956940336f, -0.290284677f,
+    0.970031253f, -0.242980180f,
+    0.980785280f, -0.195090322f,
+    0.989176510f, -0.146730474f,
+    0.995184727f, -0.098017140f,
+    0.998795456f, -0.049067674f
+};
+
+/**
+* \par
+* Example code for Floating-point Twiddle factors Generation:
+* \par
+* <pre>for(i = 0; i< N/; i++)
+* {
+*	twiddleCoef[2*i]= cos(i * 2*PI/(float)N);
+*	twiddleCoef[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 256	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are in interleaved fashion
+*
+*/
+const float32_t twiddleCoef_256[512] = {
+    1.000000000f,  0.000000000f,
+    0.999698819f,  0.024541229f,
+    0.998795456f,  0.049067674f,
+    0.997290457f,  0.073564564f,
+    0.995184727f,  0.098017140f,
+    0.992479535f,  0.122410675f,
+    0.989176510f,  0.146730474f,
+    0.985277642f,  0.170961889f,
+    0.980785280f,  0.195090322f,
+    0.975702130f,  0.219101240f,
+    0.970031253f,  0.242980180f,
+    0.963776066f,  0.266712757f,
+    0.956940336f,  0.290284677f,
+    0.949528181f,  0.313681740f,
+    0.941544065f,  0.336889853f,
+    0.932992799f,  0.359895037f,
+    0.923879533f,  0.382683432f,
+    0.914209756f,  0.405241314f,
+    0.903989293f,  0.427555093f,
+    0.893224301f,  0.449611330f,
+    0.881921264f,  0.471396737f,
+    0.870086991f,  0.492898192f,
+    0.857728610f,  0.514102744f,
+    0.844853565f,  0.534997620f,
+    0.831469612f,  0.555570233f,
+    0.817584813f,  0.575808191f,
+    0.803207531f,  0.595699304f,
+    0.788346428f,  0.615231591f,
+    0.773010453f,  0.634393284f,
+    0.757208847f,  0.653172843f,
+    0.740951125f,  0.671558955f,
+    0.724247083f,  0.689540545f,
+    0.707106781f,  0.707106781f,
+    0.689540545f,  0.724247083f,
+    0.671558955f,  0.740951125f,
+    0.653172843f,  0.757208847f,
+    0.634393284f,  0.773010453f,
+    0.615231591f,  0.788346428f,
+    0.595699304f,  0.803207531f,
+    0.575808191f,  0.817584813f,
+    0.555570233f,  0.831469612f,
+    0.534997620f,  0.844853565f,
+    0.514102744f,  0.857728610f,
+    0.492898192f,  0.870086991f,
+    0.471396737f,  0.881921264f,
+    0.449611330f,  0.893224301f,
+    0.427555093f,  0.903989293f,
+    0.405241314f,  0.914209756f,
+    0.382683432f,  0.923879533f,
+    0.359895037f,  0.932992799f,
+    0.336889853f,  0.941544065f,
+    0.313681740f,  0.949528181f,
+    0.290284677f,  0.956940336f,
+    0.266712757f,  0.963776066f,
+    0.242980180f,  0.970031253f,
+    0.219101240f,  0.975702130f,
+    0.195090322f,  0.980785280f,
+    0.170961889f,  0.985277642f,
+    0.146730474f,  0.989176510f,
+    0.122410675f,  0.992479535f,
+    0.098017140f,  0.995184727f,
+    0.073564564f,  0.997290457f,
+    0.049067674f,  0.998795456f,
+    0.024541229f,  0.999698819f,
+    0.000000000f,  1.000000000f,
+   -0.024541229f,  0.999698819f,
+   -0.049067674f,  0.998795456f,
+   -0.073564564f,  0.997290457f,
+   -0.098017140f,  0.995184727f,
+   -0.122410675f,  0.992479535f,
+   -0.146730474f,  0.989176510f,
+   -0.170961889f,  0.985277642f,
+   -0.195090322f,  0.980785280f,
+   -0.219101240f,  0.975702130f,
+   -0.242980180f,  0.970031253f,
+   -0.266712757f,  0.963776066f,
+   -0.290284677f,  0.956940336f,
+   -0.313681740f,  0.949528181f,
+   -0.336889853f,  0.941544065f,
+   -0.359895037f,  0.932992799f,
+   -0.382683432f,  0.923879533f,
+   -0.405241314f,  0.914209756f,
+   -0.427555093f,  0.903989293f,
+   -0.449611330f,  0.893224301f,
+   -0.471396737f,  0.881921264f,
+   -0.492898192f,  0.870086991f,
+   -0.514102744f,  0.857728610f,
+   -0.534997620f,  0.844853565f,
+   -0.555570233f,  0.831469612f,
+   -0.575808191f,  0.817584813f,
+   -0.595699304f,  0.803207531f,
+   -0.615231591f,  0.788346428f,
+   -0.634393284f,  0.773010453f,
+   -0.653172843f,  0.757208847f,
+   -0.671558955f,  0.740951125f,
+   -0.689540545f,  0.724247083f,
+   -0.707106781f,  0.707106781f,
+   -0.724247083f,  0.689540545f,
+   -0.740951125f,  0.671558955f,
+   -0.757208847f,  0.653172843f,
+   -0.773010453f,  0.634393284f,
+   -0.788346428f,  0.615231591f,
+   -0.803207531f,  0.595699304f,
+   -0.817584813f,  0.575808191f,
+   -0.831469612f,  0.555570233f,
+   -0.844853565f,  0.534997620f,
+   -0.857728610f,  0.514102744f,
+   -0.870086991f,  0.492898192f,
+   -0.881921264f,  0.471396737f,
+   -0.893224301f,  0.449611330f,
+   -0.903989293f,  0.427555093f,
+   -0.914209756f,  0.405241314f,
+   -0.923879533f,  0.382683432f,
+   -0.932992799f,  0.359895037f,
+   -0.941544065f,  0.336889853f,
+   -0.949528181f,  0.313681740f,
+   -0.956940336f,  0.290284677f,
+   -0.963776066f,  0.266712757f,
+   -0.970031253f,  0.242980180f,
+   -0.975702130f,  0.219101240f,
+   -0.980785280f,  0.195090322f,
+   -0.985277642f,  0.170961889f,
+   -0.989176510f,  0.146730474f,
+   -0.992479535f,  0.122410675f,
+   -0.995184727f,  0.098017140f,
+   -0.997290457f,  0.073564564f,
+   -0.998795456f,  0.049067674f,
+   -0.999698819f,  0.024541229f,
+   -1.000000000f,  0.000000000f,
+   -0.999698819f, -0.024541229f,
+   -0.998795456f, -0.049067674f,
+   -0.997290457f, -0.073564564f,
+   -0.995184727f, -0.098017140f,
+   -0.992479535f, -0.122410675f,
+   -0.989176510f, -0.146730474f,
+   -0.985277642f, -0.170961889f,
+   -0.980785280f, -0.195090322f,
+   -0.975702130f, -0.219101240f,
+   -0.970031253f, -0.242980180f,
+   -0.963776066f, -0.266712757f,
+   -0.956940336f, -0.290284677f,
+   -0.949528181f, -0.313681740f,
+   -0.941544065f, -0.336889853f,
+   -0.932992799f, -0.359895037f,
+   -0.923879533f, -0.382683432f,
+   -0.914209756f, -0.405241314f,
+   -0.903989293f, -0.427555093f,
+   -0.893224301f, -0.449611330f,
+   -0.881921264f, -0.471396737f,
+   -0.870086991f, -0.492898192f,
+   -0.857728610f, -0.514102744f,
+   -0.844853565f, -0.534997620f,
+   -0.831469612f, -0.555570233f,
+   -0.817584813f, -0.575808191f,
+   -0.803207531f, -0.595699304f,
+   -0.788346428f, -0.615231591f,
+   -0.773010453f, -0.634393284f,
+   -0.757208847f, -0.653172843f,
+   -0.740951125f, -0.671558955f,
+   -0.724247083f, -0.689540545f,
+   -0.707106781f, -0.707106781f,
+   -0.689540545f, -0.724247083f,
+   -0.671558955f, -0.740951125f,
+   -0.653172843f, -0.757208847f,
+   -0.634393284f, -0.773010453f,
+   -0.615231591f, -0.788346428f,
+   -0.595699304f, -0.803207531f,
+   -0.575808191f, -0.817584813f,
+   -0.555570233f, -0.831469612f,
+   -0.534997620f, -0.844853565f,
+   -0.514102744f, -0.857728610f,
+   -0.492898192f, -0.870086991f,
+   -0.471396737f, -0.881921264f,
+   -0.449611330f, -0.893224301f,
+   -0.427555093f, -0.903989293f,
+   -0.405241314f, -0.914209756f,
+   -0.382683432f, -0.923879533f,
+   -0.359895037f, -0.932992799f,
+   -0.336889853f, -0.941544065f,
+   -0.313681740f, -0.949528181f,
+   -0.290284677f, -0.956940336f,
+   -0.266712757f, -0.963776066f,
+   -0.242980180f, -0.970031253f,
+   -0.219101240f, -0.975702130f,
+   -0.195090322f, -0.980785280f,
+   -0.170961889f, -0.985277642f,
+   -0.146730474f, -0.989176510f,
+   -0.122410675f, -0.992479535f,
+   -0.098017140f, -0.995184727f,
+   -0.073564564f, -0.997290457f,
+   -0.049067674f, -0.998795456f,
+   -0.024541229f, -0.999698819f,
+   -0.000000000f, -1.000000000f,
+    0.024541229f, -0.999698819f,
+    0.049067674f, -0.998795456f,
+    0.073564564f, -0.997290457f,
+    0.098017140f, -0.995184727f,
+    0.122410675f, -0.992479535f,
+    0.146730474f, -0.989176510f,
+    0.170961889f, -0.985277642f,
+    0.195090322f, -0.980785280f,
+    0.219101240f, -0.975702130f,
+    0.242980180f, -0.970031253f,
+    0.266712757f, -0.963776066f,
+    0.290284677f, -0.956940336f,
+    0.313681740f, -0.949528181f,
+    0.336889853f, -0.941544065f,
+    0.359895037f, -0.932992799f,
+    0.382683432f, -0.923879533f,
+    0.405241314f, -0.914209756f,
+    0.427555093f, -0.903989293f,
+    0.449611330f, -0.893224301f,
+    0.471396737f, -0.881921264f,
+    0.492898192f, -0.870086991f,
+    0.514102744f, -0.857728610f,
+    0.534997620f, -0.844853565f,
+    0.555570233f, -0.831469612f,
+    0.575808191f, -0.817584813f,
+    0.595699304f, -0.803207531f,
+    0.615231591f, -0.788346428f,
+    0.634393284f, -0.773010453f,
+    0.653172843f, -0.757208847f,
+    0.671558955f, -0.740951125f,
+    0.689540545f, -0.724247083f,
+    0.707106781f, -0.707106781f,
+    0.724247083f, -0.689540545f,
+    0.740951125f, -0.671558955f,
+    0.757208847f, -0.653172843f,
+    0.773010453f, -0.634393284f,
+    0.788346428f, -0.615231591f,
+    0.803207531f, -0.595699304f,
+    0.817584813f, -0.575808191f,
+    0.831469612f, -0.555570233f,
+    0.844853565f, -0.534997620f,
+    0.857728610f, -0.514102744f,
+    0.870086991f, -0.492898192f,
+    0.881921264f, -0.471396737f,
+    0.893224301f, -0.449611330f,
+    0.903989293f, -0.427555093f,
+    0.914209756f, -0.405241314f,
+    0.923879533f, -0.382683432f,
+    0.932992799f, -0.359895037f,
+    0.941544065f, -0.336889853f,
+    0.949528181f, -0.313681740f,
+    0.956940336f, -0.290284677f,
+    0.963776066f, -0.266712757f,
+    0.970031253f, -0.242980180f,
+    0.975702130f, -0.219101240f,
+    0.980785280f, -0.195090322f,
+    0.985277642f, -0.170961889f,
+    0.989176510f, -0.146730474f,
+    0.992479535f, -0.122410675f,
+    0.995184727f, -0.098017140f,
+    0.997290457f, -0.073564564f,
+    0.998795456f, -0.049067674f,
+    0.999698819f, -0.024541229f
+};
+
+/**
+* \par
+* Example code for Floating-point Twiddle factors Generation:
+* \par
+* <pre>for(i = 0; i< N/; i++)
+* {
+*	twiddleCoef[2*i]= cos(i * 2*PI/(float)N);
+*	twiddleCoef[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 512	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are in interleaved fashion
+*
+*/
+const float32_t twiddleCoef_512[1024] = {
+    1.000000000f,  0.000000000f,
+    0.999924702f,  0.012271538f,
+    0.999698819f,  0.024541229f,
+    0.999322385f,  0.036807223f,
+    0.998795456f,  0.049067674f,
+    0.998118113f,  0.061320736f,
+    0.997290457f,  0.073564564f,
+    0.996312612f,  0.085797312f,
+    0.995184727f,  0.098017140f,
+    0.993906970f,  0.110222207f,
+    0.992479535f,  0.122410675f,
+    0.990902635f,  0.134580709f,
+    0.989176510f,  0.146730474f,
+    0.987301418f,  0.158858143f,
+    0.985277642f,  0.170961889f,
+    0.983105487f,  0.183039888f,
+    0.980785280f,  0.195090322f,
+    0.978317371f,  0.207111376f,
+    0.975702130f,  0.219101240f,
+    0.972939952f,  0.231058108f,
+    0.970031253f,  0.242980180f,
+    0.966976471f,  0.254865660f,
+    0.963776066f,  0.266712757f,
+    0.960430519f,  0.278519689f,
+    0.956940336f,  0.290284677f,
+    0.953306040f,  0.302005949f,
+    0.949528181f,  0.313681740f,
+    0.945607325f,  0.325310292f,
+    0.941544065f,  0.336889853f,
+    0.937339012f,  0.348418680f,
+    0.932992799f,  0.359895037f,
+    0.928506080f,  0.371317194f,
+    0.923879533f,  0.382683432f,
+    0.919113852f,  0.393992040f,
+    0.914209756f,  0.405241314f,
+    0.909167983f,  0.416429560f,
+    0.903989293f,  0.427555093f,
+    0.898674466f,  0.438616239f,
+    0.893224301f,  0.449611330f,
+    0.887639620f,  0.460538711f,
+    0.881921264f,  0.471396737f,
+    0.876070094f,  0.482183772f,
+    0.870086991f,  0.492898192f,
+    0.863972856f,  0.503538384f,
+    0.857728610f,  0.514102744f,
+    0.851355193f,  0.524589683f,
+    0.844853565f,  0.534997620f,
+    0.838224706f,  0.545324988f,
+    0.831469612f,  0.555570233f,
+    0.824589303f,  0.565731811f,
+    0.817584813f,  0.575808191f,
+    0.810457198f,  0.585797857f,
+    0.803207531f,  0.595699304f,
+    0.795836905f,  0.605511041f,
+    0.788346428f,  0.615231591f,
+    0.780737229f,  0.624859488f,
+    0.773010453f,  0.634393284f,
+    0.765167266f,  0.643831543f,
+    0.757208847f,  0.653172843f,
+    0.749136395f,  0.662415778f,
+    0.740951125f,  0.671558955f,
+    0.732654272f,  0.680600998f,
+    0.724247083f,  0.689540545f,
+    0.715730825f,  0.698376249f,
+    0.707106781f,  0.707106781f,
+    0.698376249f,  0.715730825f,
+    0.689540545f,  0.724247083f,
+    0.680600998f,  0.732654272f,
+    0.671558955f,  0.740951125f,
+    0.662415778f,  0.749136395f,
+    0.653172843f,  0.757208847f,
+    0.643831543f,  0.765167266f,
+    0.634393284f,  0.773010453f,
+    0.624859488f,  0.780737229f,
+    0.615231591f,  0.788346428f,
+    0.605511041f,  0.795836905f,
+    0.595699304f,  0.803207531f,
+    0.585797857f,  0.810457198f,
+    0.575808191f,  0.817584813f,
+    0.565731811f,  0.824589303f,
+    0.555570233f,  0.831469612f,
+    0.545324988f,  0.838224706f,
+    0.534997620f,  0.844853565f,
+    0.524589683f,  0.851355193f,
+    0.514102744f,  0.857728610f,
+    0.503538384f,  0.863972856f,
+    0.492898192f,  0.870086991f,
+    0.482183772f,  0.876070094f,
+    0.471396737f,  0.881921264f,
+    0.460538711f,  0.887639620f,
+    0.449611330f,  0.893224301f,
+    0.438616239f,  0.898674466f,
+    0.427555093f,  0.903989293f,
+    0.416429560f,  0.909167983f,
+    0.405241314f,  0.914209756f,
+    0.393992040f,  0.919113852f,
+    0.382683432f,  0.923879533f,
+    0.371317194f,  0.928506080f,
+    0.359895037f,  0.932992799f,
+    0.348418680f,  0.937339012f,
+    0.336889853f,  0.941544065f,
+    0.325310292f,  0.945607325f,
+    0.313681740f,  0.949528181f,
+    0.302005949f,  0.953306040f,
+    0.290284677f,  0.956940336f,
+    0.278519689f,  0.960430519f,
+    0.266712757f,  0.963776066f,
+    0.254865660f,  0.966976471f,
+    0.242980180f,  0.970031253f,
+    0.231058108f,  0.972939952f,
+    0.219101240f,  0.975702130f,
+    0.207111376f,  0.978317371f,
+    0.195090322f,  0.980785280f,
+    0.183039888f,  0.983105487f,
+    0.170961889f,  0.985277642f,
+    0.158858143f,  0.987301418f,
+    0.146730474f,  0.989176510f,
+    0.134580709f,  0.990902635f,
+    0.122410675f,  0.992479535f,
+    0.110222207f,  0.993906970f,
+    0.098017140f,  0.995184727f,
+    0.085797312f,  0.996312612f,
+    0.073564564f,  0.997290457f,
+    0.061320736f,  0.998118113f,
+    0.049067674f,  0.998795456f,
+    0.036807223f,  0.999322385f,
+    0.024541229f,  0.999698819f,
+    0.012271538f,  0.999924702f,
+    0.000000000f,  1.000000000f,
+   -0.012271538f,  0.999924702f,
+   -0.024541229f,  0.999698819f,
+   -0.036807223f,  0.999322385f,
+   -0.049067674f,  0.998795456f,
+   -0.061320736f,  0.998118113f,
+   -0.073564564f,  0.997290457f,
+   -0.085797312f,  0.996312612f,
+   -0.098017140f,  0.995184727f,
+   -0.110222207f,  0.993906970f,
+   -0.122410675f,  0.992479535f,
+   -0.134580709f,  0.990902635f,
+   -0.146730474f,  0.989176510f,
+   -0.158858143f,  0.987301418f,
+   -0.170961889f,  0.985277642f,
+   -0.183039888f,  0.983105487f,
+   -0.195090322f,  0.980785280f,
+   -0.207111376f,  0.978317371f,
+   -0.219101240f,  0.975702130f,
+   -0.231058108f,  0.972939952f,
+   -0.242980180f,  0.970031253f,
+   -0.254865660f,  0.966976471f,
+   -0.266712757f,  0.963776066f,
+   -0.278519689f,  0.960430519f,
+   -0.290284677f,  0.956940336f,
+   -0.302005949f,  0.953306040f,
+   -0.313681740f,  0.949528181f,
+   -0.325310292f,  0.945607325f,
+   -0.336889853f,  0.941544065f,
+   -0.348418680f,  0.937339012f,
+   -0.359895037f,  0.932992799f,
+   -0.371317194f,  0.928506080f,
+   -0.382683432f,  0.923879533f,
+   -0.393992040f,  0.919113852f,
+   -0.405241314f,  0.914209756f,
+   -0.416429560f,  0.909167983f,
+   -0.427555093f,  0.903989293f,
+   -0.438616239f,  0.898674466f,
+   -0.449611330f,  0.893224301f,
+   -0.460538711f,  0.887639620f,
+   -0.471396737f,  0.881921264f,
+   -0.482183772f,  0.876070094f,
+   -0.492898192f,  0.870086991f,
+   -0.503538384f,  0.863972856f,
+   -0.514102744f,  0.857728610f,
+   -0.524589683f,  0.851355193f,
+   -0.534997620f,  0.844853565f,
+   -0.545324988f,  0.838224706f,
+   -0.555570233f,  0.831469612f,
+   -0.565731811f,  0.824589303f,
+   -0.575808191f,  0.817584813f,
+   -0.585797857f,  0.810457198f,
+   -0.595699304f,  0.803207531f,
+   -0.605511041f,  0.795836905f,
+   -0.615231591f,  0.788346428f,
+   -0.624859488f,  0.780737229f,
+   -0.634393284f,  0.773010453f,
+   -0.643831543f,  0.765167266f,
+   -0.653172843f,  0.757208847f,
+   -0.662415778f,  0.749136395f,
+   -0.671558955f,  0.740951125f,
+   -0.680600998f,  0.732654272f,
+   -0.689540545f,  0.724247083f,
+   -0.698376249f,  0.715730825f,
+   -0.707106781f,  0.707106781f,
+   -0.715730825f,  0.698376249f,
+   -0.724247083f,  0.689540545f,
+   -0.732654272f,  0.680600998f,
+   -0.740951125f,  0.671558955f,
+   -0.749136395f,  0.662415778f,
+   -0.757208847f,  0.653172843f,
+   -0.765167266f,  0.643831543f,
+   -0.773010453f,  0.634393284f,
+   -0.780737229f,  0.624859488f,
+   -0.788346428f,  0.615231591f,
+   -0.795836905f,  0.605511041f,
+   -0.803207531f,  0.595699304f,
+   -0.810457198f,  0.585797857f,
+   -0.817584813f,  0.575808191f,
+   -0.824589303f,  0.565731811f,
+   -0.831469612f,  0.555570233f,
+   -0.838224706f,  0.545324988f,
+   -0.844853565f,  0.534997620f,
+   -0.851355193f,  0.524589683f,
+   -0.857728610f,  0.514102744f,
+   -0.863972856f,  0.503538384f,
+   -0.870086991f,  0.492898192f,
+   -0.876070094f,  0.482183772f,
+   -0.881921264f,  0.471396737f,
+   -0.887639620f,  0.460538711f,
+   -0.893224301f,  0.449611330f,
+   -0.898674466f,  0.438616239f,
+   -0.903989293f,  0.427555093f,
+   -0.909167983f,  0.416429560f,
+   -0.914209756f,  0.405241314f,
+   -0.919113852f,  0.393992040f,
+   -0.923879533f,  0.382683432f,
+   -0.928506080f,  0.371317194f,
+   -0.932992799f,  0.359895037f,
+   -0.937339012f,  0.348418680f,
+   -0.941544065f,  0.336889853f,
+   -0.945607325f,  0.325310292f,
+   -0.949528181f,  0.313681740f,
+   -0.953306040f,  0.302005949f,
+   -0.956940336f,  0.290284677f,
+   -0.960430519f,  0.278519689f,
+   -0.963776066f,  0.266712757f,
+   -0.966976471f,  0.254865660f,
+   -0.970031253f,  0.242980180f,
+   -0.972939952f,  0.231058108f,
+   -0.975702130f,  0.219101240f,
+   -0.978317371f,  0.207111376f,
+   -0.980785280f,  0.195090322f,
+   -0.983105487f,  0.183039888f,
+   -0.985277642f,  0.170961889f,
+   -0.987301418f,  0.158858143f,
+   -0.989176510f,  0.146730474f,
+   -0.990902635f,  0.134580709f,
+   -0.992479535f,  0.122410675f,
+   -0.993906970f,  0.110222207f,
+   -0.995184727f,  0.098017140f,
+   -0.996312612f,  0.085797312f,
+   -0.997290457f,  0.073564564f,
+   -0.998118113f,  0.061320736f,
+   -0.998795456f,  0.049067674f,
+   -0.999322385f,  0.036807223f,
+   -0.999698819f,  0.024541229f,
+   -0.999924702f,  0.012271538f,
+   -1.000000000f,  0.000000000f,
+   -0.999924702f, -0.012271538f,
+   -0.999698819f, -0.024541229f,
+   -0.999322385f, -0.036807223f,
+   -0.998795456f, -0.049067674f,
+   -0.998118113f, -0.061320736f,
+   -0.997290457f, -0.073564564f,
+   -0.996312612f, -0.085797312f,
+   -0.995184727f, -0.098017140f,
+   -0.993906970f, -0.110222207f,
+   -0.992479535f, -0.122410675f,
+   -0.990902635f, -0.134580709f,
+   -0.989176510f, -0.146730474f,
+   -0.987301418f, -0.158858143f,
+   -0.985277642f, -0.170961889f,
+   -0.983105487f, -0.183039888f,
+   -0.980785280f, -0.195090322f,
+   -0.978317371f, -0.207111376f,
+   -0.975702130f, -0.219101240f,
+   -0.972939952f, -0.231058108f,
+   -0.970031253f, -0.242980180f,
+   -0.966976471f, -0.254865660f,
+   -0.963776066f, -0.266712757f,
+   -0.960430519f, -0.278519689f,
+   -0.956940336f, -0.290284677f,
+   -0.953306040f, -0.302005949f,
+   -0.949528181f, -0.313681740f,
+   -0.945607325f, -0.325310292f,
+   -0.941544065f, -0.336889853f,
+   -0.937339012f, -0.348418680f,
+   -0.932992799f, -0.359895037f,
+   -0.928506080f, -0.371317194f,
+   -0.923879533f, -0.382683432f,
+   -0.919113852f, -0.393992040f,
+   -0.914209756f, -0.405241314f,
+   -0.909167983f, -0.416429560f,
+   -0.903989293f, -0.427555093f,
+   -0.898674466f, -0.438616239f,
+   -0.893224301f, -0.449611330f,
+   -0.887639620f, -0.460538711f,
+   -0.881921264f, -0.471396737f,
+   -0.876070094f, -0.482183772f,
+   -0.870086991f, -0.492898192f,
+   -0.863972856f, -0.503538384f,
+   -0.857728610f, -0.514102744f,
+   -0.851355193f, -0.524589683f,
+   -0.844853565f, -0.534997620f,
+   -0.838224706f, -0.545324988f,
+   -0.831469612f, -0.555570233f,
+   -0.824589303f, -0.565731811f,
+   -0.817584813f, -0.575808191f,
+   -0.810457198f, -0.585797857f,
+   -0.803207531f, -0.595699304f,
+   -0.795836905f, -0.605511041f,
+   -0.788346428f, -0.615231591f,
+   -0.780737229f, -0.624859488f,
+   -0.773010453f, -0.634393284f,
+   -0.765167266f, -0.643831543f,
+   -0.757208847f, -0.653172843f,
+   -0.749136395f, -0.662415778f,
+   -0.740951125f, -0.671558955f,
+   -0.732654272f, -0.680600998f,
+   -0.724247083f, -0.689540545f,
+   -0.715730825f, -0.698376249f,
+   -0.707106781f, -0.707106781f,
+   -0.698376249f, -0.715730825f,
+   -0.689540545f, -0.724247083f,
+   -0.680600998f, -0.732654272f,
+   -0.671558955f, -0.740951125f,
+   -0.662415778f, -0.749136395f,
+   -0.653172843f, -0.757208847f,
+   -0.643831543f, -0.765167266f,
+   -0.634393284f, -0.773010453f,
+   -0.624859488f, -0.780737229f,
+   -0.615231591f, -0.788346428f,
+   -0.605511041f, -0.795836905f,
+   -0.595699304f, -0.803207531f,
+   -0.585797857f, -0.810457198f,
+   -0.575808191f, -0.817584813f,
+   -0.565731811f, -0.824589303f,
+   -0.555570233f, -0.831469612f,
+   -0.545324988f, -0.838224706f,
+   -0.534997620f, -0.844853565f,
+   -0.524589683f, -0.851355193f,
+   -0.514102744f, -0.857728610f,
+   -0.503538384f, -0.863972856f,
+   -0.492898192f, -0.870086991f,
+   -0.482183772f, -0.876070094f,
+   -0.471396737f, -0.881921264f,
+   -0.460538711f, -0.887639620f,
+   -0.449611330f, -0.893224301f,
+   -0.438616239f, -0.898674466f,
+   -0.427555093f, -0.903989293f,
+   -0.416429560f, -0.909167983f,
+   -0.405241314f, -0.914209756f,
+   -0.393992040f, -0.919113852f,
+   -0.382683432f, -0.923879533f,
+   -0.371317194f, -0.928506080f,
+   -0.359895037f, -0.932992799f,
+   -0.348418680f, -0.937339012f,
+   -0.336889853f, -0.941544065f,
+   -0.325310292f, -0.945607325f,
+   -0.313681740f, -0.949528181f,
+   -0.302005949f, -0.953306040f,
+   -0.290284677f, -0.956940336f,
+   -0.278519689f, -0.960430519f,
+   -0.266712757f, -0.963776066f,
+   -0.254865660f, -0.966976471f,
+   -0.242980180f, -0.970031253f,
+   -0.231058108f, -0.972939952f,
+   -0.219101240f, -0.975702130f,
+   -0.207111376f, -0.978317371f,
+   -0.195090322f, -0.980785280f,
+   -0.183039888f, -0.983105487f,
+   -0.170961889f, -0.985277642f,
+   -0.158858143f, -0.987301418f,
+   -0.146730474f, -0.989176510f,
+   -0.134580709f, -0.990902635f,
+   -0.122410675f, -0.992479535f,
+   -0.110222207f, -0.993906970f,
+   -0.098017140f, -0.995184727f,
+   -0.085797312f, -0.996312612f,
+   -0.073564564f, -0.997290457f,
+   -0.061320736f, -0.998118113f,
+   -0.049067674f, -0.998795456f,
+   -0.036807223f, -0.999322385f,
+   -0.024541229f, -0.999698819f,
+   -0.012271538f, -0.999924702f,
+   -0.000000000f, -1.000000000f,
+    0.012271538f, -0.999924702f,
+    0.024541229f, -0.999698819f,
+    0.036807223f, -0.999322385f,
+    0.049067674f, -0.998795456f,
+    0.061320736f, -0.998118113f,
+    0.073564564f, -0.997290457f,
+    0.085797312f, -0.996312612f,
+    0.098017140f, -0.995184727f,
+    0.110222207f, -0.993906970f,
+    0.122410675f, -0.992479535f,
+    0.134580709f, -0.990902635f,
+    0.146730474f, -0.989176510f,
+    0.158858143f, -0.987301418f,
+    0.170961889f, -0.985277642f,
+    0.183039888f, -0.983105487f,
+    0.195090322f, -0.980785280f,
+    0.207111376f, -0.978317371f,
+    0.219101240f, -0.975702130f,
+    0.231058108f, -0.972939952f,
+    0.242980180f, -0.970031253f,
+    0.254865660f, -0.966976471f,
+    0.266712757f, -0.963776066f,
+    0.278519689f, -0.960430519f,
+    0.290284677f, -0.956940336f,
+    0.302005949f, -0.953306040f,
+    0.313681740f, -0.949528181f,
+    0.325310292f, -0.945607325f,
+    0.336889853f, -0.941544065f,
+    0.348418680f, -0.937339012f,
+    0.359895037f, -0.932992799f,
+    0.371317194f, -0.928506080f,
+    0.382683432f, -0.923879533f,
+    0.393992040f, -0.919113852f,
+    0.405241314f, -0.914209756f,
+    0.416429560f, -0.909167983f,
+    0.427555093f, -0.903989293f,
+    0.438616239f, -0.898674466f,
+    0.449611330f, -0.893224301f,
+    0.460538711f, -0.887639620f,
+    0.471396737f, -0.881921264f,
+    0.482183772f, -0.876070094f,
+    0.492898192f, -0.870086991f,
+    0.503538384f, -0.863972856f,
+    0.514102744f, -0.857728610f,
+    0.524589683f, -0.851355193f,
+    0.534997620f, -0.844853565f,
+    0.545324988f, -0.838224706f,
+    0.555570233f, -0.831469612f,
+    0.565731811f, -0.824589303f,
+    0.575808191f, -0.817584813f,
+    0.585797857f, -0.810457198f,
+    0.595699304f, -0.803207531f,
+    0.605511041f, -0.795836905f,
+    0.615231591f, -0.788346428f,
+    0.624859488f, -0.780737229f,
+    0.634393284f, -0.773010453f,
+    0.643831543f, -0.765167266f,
+    0.653172843f, -0.757208847f,
+    0.662415778f, -0.749136395f,
+    0.671558955f, -0.740951125f,
+    0.680600998f, -0.732654272f,
+    0.689540545f, -0.724247083f,
+    0.698376249f, -0.715730825f,
+    0.707106781f, -0.707106781f,
+    0.715730825f, -0.698376249f,
+    0.724247083f, -0.689540545f,
+    0.732654272f, -0.680600998f,
+    0.740951125f, -0.671558955f,
+    0.749136395f, -0.662415778f,
+    0.757208847f, -0.653172843f,
+    0.765167266f, -0.643831543f,
+    0.773010453f, -0.634393284f,
+    0.780737229f, -0.624859488f,
+    0.788346428f, -0.615231591f,
+    0.795836905f, -0.605511041f,
+    0.803207531f, -0.595699304f,
+    0.810457198f, -0.585797857f,
+    0.817584813f, -0.575808191f,
+    0.824589303f, -0.565731811f,
+    0.831469612f, -0.555570233f,
+    0.838224706f, -0.545324988f,
+    0.844853565f, -0.534997620f,
+    0.851355193f, -0.524589683f,
+    0.857728610f, -0.514102744f,
+    0.863972856f, -0.503538384f,
+    0.870086991f, -0.492898192f,
+    0.876070094f, -0.482183772f,
+    0.881921264f, -0.471396737f,
+    0.887639620f, -0.460538711f,
+    0.893224301f, -0.449611330f,
+    0.898674466f, -0.438616239f,
+    0.903989293f, -0.427555093f,
+    0.909167983f, -0.416429560f,
+    0.914209756f, -0.405241314f,
+    0.919113852f, -0.393992040f,
+    0.923879533f, -0.382683432f,
+    0.928506080f, -0.371317194f,
+    0.932992799f, -0.359895037f,
+    0.937339012f, -0.348418680f,
+    0.941544065f, -0.336889853f,
+    0.945607325f, -0.325310292f,
+    0.949528181f, -0.313681740f,
+    0.953306040f, -0.302005949f,
+    0.956940336f, -0.290284677f,
+    0.960430519f, -0.278519689f,
+    0.963776066f, -0.266712757f,
+    0.966976471f, -0.254865660f,
+    0.970031253f, -0.242980180f,
+    0.972939952f, -0.231058108f,
+    0.975702130f, -0.219101240f,
+    0.978317371f, -0.207111376f,
+    0.980785280f, -0.195090322f,
+    0.983105487f, -0.183039888f,
+    0.985277642f, -0.170961889f,
+    0.987301418f, -0.158858143f,
+    0.989176510f, -0.146730474f,
+    0.990902635f, -0.134580709f,
+    0.992479535f, -0.122410675f,
+    0.993906970f, -0.110222207f,
+    0.995184727f, -0.098017140f,
+    0.996312612f, -0.085797312f,
+    0.997290457f, -0.073564564f,
+    0.998118113f, -0.061320736f,
+    0.998795456f, -0.049067674f,
+    0.999322385f, -0.036807223f,
+    0.999698819f, -0.024541229f,
+    0.999924702f, -0.012271538f
+};
+/**
+* \par
+* Example code for Floating-point Twiddle factors Generation:
+* \par
+* <pre>for(i = 0; i< N/; i++)
+* {
+*	twiddleCoef[2*i]= cos(i * 2*PI/(float)N);
+*	twiddleCoef[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 1024	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are in interleaved fashion
+*
+*/
+const float32_t twiddleCoef_1024[2048] = {
+    1.000000000f,  0.000000000f,
+    0.999981175f,  0.006135885f,
+    0.999924702f,  0.012271538f,
+    0.999830582f,  0.018406730f,
+    0.999698819f,  0.024541229f,
+    0.999529418f,  0.030674803f,
+    0.999322385f,  0.036807223f,
+    0.999077728f,  0.042938257f,
+    0.998795456f,  0.049067674f,
+    0.998475581f,  0.055195244f,
+    0.998118113f,  0.061320736f,
+    0.997723067f,  0.067443920f,
+    0.997290457f,  0.073564564f,
+    0.996820299f,  0.079682438f,
+    0.996312612f,  0.085797312f,
+    0.995767414f,  0.091908956f,
+    0.995184727f,  0.098017140f,
+    0.994564571f,  0.104121634f,
+    0.993906970f,  0.110222207f,
+    0.993211949f,  0.116318631f,
+    0.992479535f,  0.122410675f,
+    0.991709754f,  0.128498111f,
+    0.990902635f,  0.134580709f,
+    0.990058210f,  0.140658239f,
+    0.989176510f,  0.146730474f,
+    0.988257568f,  0.152797185f,
+    0.987301418f,  0.158858143f,
+    0.986308097f,  0.164913120f,
+    0.985277642f,  0.170961889f,
+    0.984210092f,  0.177004220f,
+    0.983105487f,  0.183039888f,
+    0.981963869f,  0.189068664f,
+    0.980785280f,  0.195090322f,
+    0.979569766f,  0.201104635f,
+    0.978317371f,  0.207111376f,
+    0.977028143f,  0.213110320f,
+    0.975702130f,  0.219101240f,
+    0.974339383f,  0.225083911f,
+    0.972939952f,  0.231058108f,
+    0.971503891f,  0.237023606f,
+    0.970031253f,  0.242980180f,
+    0.968522094f,  0.248927606f,
+    0.966976471f,  0.254865660f,
+    0.965394442f,  0.260794118f,
+    0.963776066f,  0.266712757f,
+    0.962121404f,  0.272621355f,
+    0.960430519f,  0.278519689f,
+    0.958703475f,  0.284407537f,
+    0.956940336f,  0.290284677f,
+    0.955141168f,  0.296150888f,
+    0.953306040f,  0.302005949f,
+    0.951435021f,  0.307849640f,
+    0.949528181f,  0.313681740f,
+    0.947585591f,  0.319502031f,
+    0.945607325f,  0.325310292f,
+    0.943593458f,  0.331106306f,
+    0.941544065f,  0.336889853f,
+    0.939459224f,  0.342660717f,
+    0.937339012f,  0.348418680f,
+    0.935183510f,  0.354163525f,
+    0.932992799f,  0.359895037f,
+    0.930766961f,  0.365612998f,
+    0.928506080f,  0.371317194f,
+    0.926210242f,  0.377007410f,
+    0.923879533f,  0.382683432f,
+    0.921514039f,  0.388345047f,
+    0.919113852f,  0.393992040f,
+    0.916679060f,  0.399624200f,
+    0.914209756f,  0.405241314f,
+    0.911706032f,  0.410843171f,
+    0.909167983f,  0.416429560f,
+    0.906595705f,  0.422000271f,
+    0.903989293f,  0.427555093f,
+    0.901348847f,  0.433093819f,
+    0.898674466f,  0.438616239f,
+    0.895966250f,  0.444122145f,
+    0.893224301f,  0.449611330f,
+    0.890448723f,  0.455083587f,
+    0.887639620f,  0.460538711f,
+    0.884797098f,  0.465976496f,
+    0.881921264f,  0.471396737f,
+    0.879012226f,  0.476799230f,
+    0.876070094f,  0.482183772f,
+    0.873094978f,  0.487550160f,
+    0.870086991f,  0.492898192f,
+    0.867046246f,  0.498227667f,
+    0.863972856f,  0.503538384f,
+    0.860866939f,  0.508830143f,
+    0.857728610f,  0.514102744f,
+    0.854557988f,  0.519355990f,
+    0.851355193f,  0.524589683f,
+    0.848120345f,  0.529803625f,
+    0.844853565f,  0.534997620f,
+    0.841554977f,  0.540171473f,
+    0.838224706f,  0.545324988f,
+    0.834862875f,  0.550457973f,
+    0.831469612f,  0.555570233f,
+    0.828045045f,  0.560661576f,
+    0.824589303f,  0.565731811f,
+    0.821102515f,  0.570780746f,
+    0.817584813f,  0.575808191f,
+    0.814036330f,  0.580813958f,
+    0.810457198f,  0.585797857f,
+    0.806847554f,  0.590759702f,
+    0.803207531f,  0.595699304f,
+    0.799537269f,  0.600616479f,
+    0.795836905f,  0.605511041f,
+    0.792106577f,  0.610382806f,
+    0.788346428f,  0.615231591f,
+    0.784556597f,  0.620057212f,
+    0.780737229f,  0.624859488f,
+    0.776888466f,  0.629638239f,
+    0.773010453f,  0.634393284f,
+    0.769103338f,  0.639124445f,
+    0.765167266f,  0.643831543f,
+    0.761202385f,  0.648514401f,
+    0.757208847f,  0.653172843f,
+    0.753186799f,  0.657806693f,
+    0.749136395f,  0.662415778f,
+    0.745057785f,  0.666999922f,
+    0.740951125f,  0.671558955f,
+    0.736816569f,  0.676092704f,
+    0.732654272f,  0.680600998f,
+    0.728464390f,  0.685083668f,
+    0.724247083f,  0.689540545f,
+    0.720002508f,  0.693971461f,
+    0.715730825f,  0.698376249f,
+    0.711432196f,  0.702754744f,
+    0.707106781f,  0.707106781f,
+    0.702754744f,  0.711432196f,
+    0.698376249f,  0.715730825f,
+    0.693971461f,  0.720002508f,
+    0.689540545f,  0.724247083f,
+    0.685083668f,  0.728464390f,
+    0.680600998f,  0.732654272f,
+    0.676092704f,  0.736816569f,
+    0.671558955f,  0.740951125f,
+    0.666999922f,  0.745057785f,
+    0.662415778f,  0.749136395f,
+    0.657806693f,  0.753186799f,
+    0.653172843f,  0.757208847f,
+    0.648514401f,  0.761202385f,
+    0.643831543f,  0.765167266f,
+    0.639124445f,  0.769103338f,
+    0.634393284f,  0.773010453f,
+    0.629638239f,  0.776888466f,
+    0.624859488f,  0.780737229f,
+    0.620057212f,  0.784556597f,
+    0.615231591f,  0.788346428f,
+    0.610382806f,  0.792106577f,
+    0.605511041f,  0.795836905f,
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+    0.765167266f, -0.643831543f,
+    0.769103338f, -0.639124445f,
+    0.773010453f, -0.634393284f,
+    0.776888466f, -0.629638239f,
+    0.780737229f, -0.624859488f,
+    0.784556597f, -0.620057212f,
+    0.788346428f, -0.615231591f,
+    0.792106577f, -0.610382806f,
+    0.795836905f, -0.605511041f,
+    0.799537269f, -0.600616479f,
+    0.803207531f, -0.595699304f,
+    0.806847554f, -0.590759702f,
+    0.810457198f, -0.585797857f,
+    0.814036330f, -0.580813958f,
+    0.817584813f, -0.575808191f,
+    0.821102515f, -0.570780746f,
+    0.824589303f, -0.565731811f,
+    0.828045045f, -0.560661576f,
+    0.831469612f, -0.555570233f,
+    0.834862875f, -0.550457973f,
+    0.838224706f, -0.545324988f,
+    0.841554977f, -0.540171473f,
+    0.844853565f, -0.534997620f,
+    0.848120345f, -0.529803625f,
+    0.851355193f, -0.524589683f,
+    0.854557988f, -0.519355990f,
+    0.857728610f, -0.514102744f,
+    0.860866939f, -0.508830143f,
+    0.863972856f, -0.503538384f,
+    0.867046246f, -0.498227667f,
+    0.870086991f, -0.492898192f,
+    0.873094978f, -0.487550160f,
+    0.876070094f, -0.482183772f,
+    0.879012226f, -0.476799230f,
+    0.881921264f, -0.471396737f,
+    0.884797098f, -0.465976496f,
+    0.887639620f, -0.460538711f,
+    0.890448723f, -0.455083587f,
+    0.893224301f, -0.449611330f,
+    0.895966250f, -0.444122145f,
+    0.898674466f, -0.438616239f,
+    0.901348847f, -0.433093819f,
+    0.903989293f, -0.427555093f,
+    0.906595705f, -0.422000271f,
+    0.909167983f, -0.416429560f,
+    0.911706032f, -0.410843171f,
+    0.914209756f, -0.405241314f,
+    0.916679060f, -0.399624200f,
+    0.919113852f, -0.393992040f,
+    0.921514039f, -0.388345047f,
+    0.923879533f, -0.382683432f,
+    0.926210242f, -0.377007410f,
+    0.928506080f, -0.371317194f,
+    0.930766961f, -0.365612998f,
+    0.932992799f, -0.359895037f,
+    0.935183510f, -0.354163525f,
+    0.937339012f, -0.348418680f,
+    0.939459224f, -0.342660717f,
+    0.941544065f, -0.336889853f,
+    0.943593458f, -0.331106306f,
+    0.945607325f, -0.325310292f,
+    0.947585591f, -0.319502031f,
+    0.949528181f, -0.313681740f,
+    0.951435021f, -0.307849640f,
+    0.953306040f, -0.302005949f,
+    0.955141168f, -0.296150888f,
+    0.956940336f, -0.290284677f,
+    0.958703475f, -0.284407537f,
+    0.960430519f, -0.278519689f,
+    0.962121404f, -0.272621355f,
+    0.963776066f, -0.266712757f,
+    0.965394442f, -0.260794118f,
+    0.966976471f, -0.254865660f,
+    0.968522094f, -0.248927606f,
+    0.970031253f, -0.242980180f,
+    0.971503891f, -0.237023606f,
+    0.972939952f, -0.231058108f,
+    0.974339383f, -0.225083911f,
+    0.975702130f, -0.219101240f,
+    0.977028143f, -0.213110320f,
+    0.978317371f, -0.207111376f,
+    0.979569766f, -0.201104635f,
+    0.980785280f, -0.195090322f,
+    0.981963869f, -0.189068664f,
+    0.983105487f, -0.183039888f,
+    0.984210092f, -0.177004220f,
+    0.985277642f, -0.170961889f,
+    0.986308097f, -0.164913120f,
+    0.987301418f, -0.158858143f,
+    0.988257568f, -0.152797185f,
+    0.989176510f, -0.146730474f,
+    0.990058210f, -0.140658239f,
+    0.990902635f, -0.134580709f,
+    0.991709754f, -0.128498111f,
+    0.992479535f, -0.122410675f,
+    0.993211949f, -0.116318631f,
+    0.993906970f, -0.110222207f,
+    0.994564571f, -0.104121634f,
+    0.995184727f, -0.098017140f,
+    0.995767414f, -0.091908956f,
+    0.996312612f, -0.085797312f,
+    0.996820299f, -0.079682438f,
+    0.997290457f, -0.073564564f,
+    0.997723067f, -0.067443920f,
+    0.998118113f, -0.061320736f,
+    0.998475581f, -0.055195244f,
+    0.998795456f, -0.049067674f,
+    0.999077728f, -0.042938257f,
+    0.999322385f, -0.036807223f,
+    0.999529418f, -0.030674803f,
+    0.999698819f, -0.024541229f,
+    0.999830582f, -0.018406730f,
+    0.999924702f, -0.012271538f,
+    0.999981175f, -0.006135885f
+};
+
+/**
+* \par
+* Example code for Floating-point Twiddle factors Generation:
+* \par
+* <pre>for(i = 0; i< N/; i++)
+* {
+*	twiddleCoef[2*i]= cos(i * 2*PI/(float)N);
+*	twiddleCoef[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 2048	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are in interleaved fashion
+*
+*/
+const float32_t twiddleCoef_2048[4096] = {
+    1.000000000f,  0.000000000f,
+    0.999995294f,  0.003067957f,
+    0.999981175f,  0.006135885f,
+    0.999957645f,  0.009203755f,
+    0.999924702f,  0.012271538f,
+    0.999882347f,  0.015339206f,
+    0.999830582f,  0.018406730f,
+    0.999769405f,  0.021474080f,
+    0.999698819f,  0.024541229f,
+    0.999618822f,  0.027608146f,
+    0.999529418f,  0.030674803f,
+    0.999430605f,  0.033741172f,
+    0.999322385f,  0.036807223f,
+    0.999204759f,  0.039872928f,
+    0.999077728f,  0.042938257f,
+    0.998941293f,  0.046003182f,
+    0.998795456f,  0.049067674f,
+    0.998640218f,  0.052131705f,
+    0.998475581f,  0.055195244f,
+    0.998301545f,  0.058258265f,
+    0.998118113f,  0.061320736f,
+    0.997925286f,  0.064382631f,
+    0.997723067f,  0.067443920f,
+    0.997511456f,  0.070504573f,
+    0.997290457f,  0.073564564f,
+    0.997060070f,  0.076623861f,
+    0.996820299f,  0.079682438f,
+    0.996571146f,  0.082740265f,
+    0.996312612f,  0.085797312f,
+    0.996044701f,  0.088853553f,
+    0.995767414f,  0.091908956f,
+    0.995480755f,  0.094963495f,
+    0.995184727f,  0.098017140f,
+    0.994879331f,  0.101069863f,
+    0.994564571f,  0.104121634f,
+    0.994240449f,  0.107172425f,
+    0.993906970f,  0.110222207f,
+    0.993564136f,  0.113270952f,
+    0.993211949f,  0.116318631f,
+    0.992850414f,  0.119365215f,
+    0.992479535f,  0.122410675f,
+    0.992099313f,  0.125454983f,
+    0.991709754f,  0.128498111f,
+    0.991310860f,  0.131540029f,
+    0.990902635f,  0.134580709f,
+    0.990485084f,  0.137620122f,
+    0.990058210f,  0.140658239f,
+    0.989622017f,  0.143695033f,
+    0.989176510f,  0.146730474f,
+    0.988721692f,  0.149764535f,
+    0.988257568f,  0.152797185f,
+    0.987784142f,  0.155828398f,
+    0.987301418f,  0.158858143f,
+    0.986809402f,  0.161886394f,
+    0.986308097f,  0.164913120f,
+    0.985797509f,  0.167938295f,
+    0.985277642f,  0.170961889f,
+    0.984748502f,  0.173983873f,
+    0.984210092f,  0.177004220f,
+    0.983662419f,  0.180022901f,
+    0.983105487f,  0.183039888f,
+    0.982539302f,  0.186055152f,
+    0.981963869f,  0.189068664f,
+    0.981379193f,  0.192080397f,
+    0.980785280f,  0.195090322f,
+    0.980182136f,  0.198098411f,
+    0.979569766f,  0.201104635f,
+    0.978948175f,  0.204108966f,
+    0.978317371f,  0.207111376f,
+    0.977677358f,  0.210111837f,
+    0.977028143f,  0.213110320f,
+    0.976369731f,  0.216106797f,
+    0.975702130f,  0.219101240f,
+    0.975025345f,  0.222093621f,
+    0.974339383f,  0.225083911f,
+    0.973644250f,  0.228072083f,
+    0.972939952f,  0.231058108f,
+    0.972226497f,  0.234041959f,
+    0.971503891f,  0.237023606f,
+    0.970772141f,  0.240003022f,
+    0.970031253f,  0.242980180f,
+    0.969281235f,  0.245955050f,
+    0.968522094f,  0.248927606f,
+    0.967753837f,  0.251897818f,
+    0.966976471f,  0.254865660f,
+    0.966190003f,  0.257831102f,
+    0.965394442f,  0.260794118f,
+    0.964589793f,  0.263754679f,
+    0.963776066f,  0.266712757f,
+    0.962953267f,  0.269668326f,
+    0.962121404f,  0.272621355f,
+    0.961280486f,  0.275571819f,
+    0.960430519f,  0.278519689f,
+    0.959571513f,  0.281464938f,
+    0.958703475f,  0.284407537f,
+    0.957826413f,  0.287347460f,
+    0.956940336f,  0.290284677f,
+    0.956045251f,  0.293219163f,
+    0.955141168f,  0.296150888f,
+    0.954228095f,  0.299079826f,
+    0.953306040f,  0.302005949f,
+    0.952375013f,  0.304929230f,
+    0.951435021f,  0.307849640f,
+    0.950486074f,  0.310767153f,
+    0.949528181f,  0.313681740f,
+    0.948561350f,  0.316593376f,
+    0.947585591f,  0.319502031f,
+    0.946600913f,  0.322407679f,
+    0.945607325f,  0.325310292f,
+    0.944604837f,  0.328209844f,
+    0.943593458f,  0.331106306f,
+    0.942573198f,  0.333999651f,
+    0.941544065f,  0.336889853f,
+    0.940506071f,  0.339776884f,
+    0.939459224f,  0.342660717f,
+    0.938403534f,  0.345541325f,
+    0.937339012f,  0.348418680f,
+    0.936265667f,  0.351292756f,
+    0.935183510f,  0.354163525f,
+    0.934092550f,  0.357030961f,
+    0.932992799f,  0.359895037f,
+    0.931884266f,  0.362755724f,
+    0.930766961f,  0.365612998f,
+    0.929640896f,  0.368466830f,
+    0.928506080f,  0.371317194f,
+    0.927362526f,  0.374164063f,
+    0.926210242f,  0.377007410f,
+    0.925049241f,  0.379847209f,
+    0.923879533f,  0.382683432f,
+    0.922701128f,  0.385516054f,
+    0.921514039f,  0.388345047f,
+    0.920318277f,  0.391170384f,
+    0.919113852f,  0.393992040f,
+    0.917900776f,  0.396809987f,
+    0.916679060f,  0.399624200f,
+    0.915448716f,  0.402434651f,
+    0.914209756f,  0.405241314f,
+    0.912962190f,  0.408044163f,
+    0.911706032f,  0.410843171f,
+    0.910441292f,  0.413638312f,
+    0.909167983f,  0.416429560f,
+    0.907886116f,  0.419216888f,
+    0.906595705f,  0.422000271f,
+    0.905296759f,  0.424779681f,
+    0.903989293f,  0.427555093f,
+    0.902673318f,  0.430326481f,
+    0.901348847f,  0.433093819f,
+    0.900015892f,  0.435857080f,
+    0.898674466f,  0.438616239f,
+    0.897324581f,  0.441371269f,
+    0.895966250f,  0.444122145f,
+    0.894599486f,  0.446868840f,
+    0.893224301f,  0.449611330f,
+    0.891840709f,  0.452349587f,
+    0.890448723f,  0.455083587f,
+    0.889048356f,  0.457813304f,
+    0.887639620f,  0.460538711f,
+    0.886222530f,  0.463259784f,
+    0.884797098f,  0.465976496f,
+    0.883363339f,  0.468688822f,
+    0.881921264f,  0.471396737f,
+    0.880470889f,  0.474100215f,
+    0.879012226f,  0.476799230f,
+    0.877545290f,  0.479493758f,
+    0.876070094f,  0.482183772f,
+    0.874586652f,  0.484869248f,
+    0.873094978f,  0.487550160f,
+    0.871595087f,  0.490226483f,
+    0.870086991f,  0.492898192f,
+    0.868570706f,  0.495565262f,
+    0.867046246f,  0.498227667f,
+    0.865513624f,  0.500885383f,
+    0.863972856f,  0.503538384f,
+    0.862423956f,  0.506186645f,
+    0.860866939f,  0.508830143f,
+    0.859301818f,  0.511468850f,
+    0.857728610f,  0.514102744f,
+    0.856147328f,  0.516731799f,
+    0.854557988f,  0.519355990f,
+    0.852960605f,  0.521975293f,
+    0.851355193f,  0.524589683f,
+    0.849741768f,  0.527199135f,
+    0.848120345f,  0.529803625f,
+    0.846490939f,  0.532403128f,
+    0.844853565f,  0.534997620f,
+    0.843208240f,  0.537587076f,
+    0.841554977f,  0.540171473f,
+    0.839893794f,  0.542750785f,
+    0.838224706f,  0.545324988f,
+    0.836547727f,  0.547894059f,
+    0.834862875f,  0.550457973f,
+    0.833170165f,  0.553016706f,
+    0.831469612f,  0.555570233f,
+    0.829761234f,  0.558118531f,
+    0.828045045f,  0.560661576f,
+    0.826321063f,  0.563199344f,
+    0.824589303f,  0.565731811f,
+    0.822849781f,  0.568258953f,
+    0.821102515f,  0.570780746f,
+    0.819347520f,  0.573297167f,
+    0.817584813f,  0.575808191f,
+    0.815814411f,  0.578313796f,
+    0.814036330f,  0.580813958f,
+    0.812250587f,  0.583308653f,
+    0.810457198f,  0.585797857f,
+    0.808656182f,  0.588281548f,
+    0.806847554f,  0.590759702f,
+    0.805031331f,  0.593232295f,
+    0.803207531f,  0.595699304f,
+    0.801376172f,  0.598160707f,
+    0.799537269f,  0.600616479f,
+    0.797690841f,  0.603066599f,
+    0.795836905f,  0.605511041f,
+    0.793975478f,  0.607949785f,
+    0.792106577f,  0.610382806f,
+    0.790230221f,  0.612810082f,
+    0.788346428f,  0.615231591f,
+    0.786455214f,  0.617647308f,
+    0.784556597f,  0.620057212f,
+    0.782650596f,  0.622461279f,
+    0.780737229f,  0.624859488f,
+    0.778816512f,  0.627251815f,
+    0.776888466f,  0.629638239f,
+    0.774953107f,  0.632018736f,
+    0.773010453f,  0.634393284f,
+    0.771060524f,  0.636761861f,
+    0.769103338f,  0.639124445f,
+    0.767138912f,  0.641481013f,
+    0.765167266f,  0.643831543f,
+    0.763188417f,  0.646176013f,
+    0.761202385f,  0.648514401f,
+    0.759209189f,  0.650846685f,
+    0.757208847f,  0.653172843f,
+    0.755201377f,  0.655492853f,
+    0.753186799f,  0.657806693f,
+    0.751165132f,  0.660114342f,
+    0.749136395f,  0.662415778f,
+    0.747100606f,  0.664710978f,
+    0.745057785f,  0.666999922f,
+    0.743007952f,  0.669282588f,
+    0.740951125f,  0.671558955f,
+    0.738887324f,  0.673829000f,
+    0.736816569f,  0.676092704f,
+    0.734738878f,  0.678350043f,
+    0.732654272f,  0.680600998f,
+    0.730562769f,  0.682845546f,
+    0.728464390f,  0.685083668f,
+    0.726359155f,  0.687315341f,
+    0.724247083f,  0.689540545f,
+    0.722128194f,  0.691759258f,
+    0.720002508f,  0.693971461f,
+    0.717870045f,  0.696177131f,
+    0.715730825f,  0.698376249f,
+    0.713584869f,  0.700568794f,
+    0.711432196f,  0.702754744f,
+    0.709272826f,  0.704934080f,
+    0.707106781f,  0.707106781f,
+    0.704934080f,  0.709272826f,
+    0.702754744f,  0.711432196f,
+    0.700568794f,  0.713584869f,
+    0.698376249f,  0.715730825f,
+    0.696177131f,  0.717870045f,
+    0.693971461f,  0.720002508f,
+    0.691759258f,  0.722128194f,
+    0.689540545f,  0.724247083f,
+    0.687315341f,  0.726359155f,
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+    0.984748502f, -0.173983873f,
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+    0.988257568f, -0.152797185f,
+    0.988721692f, -0.149764535f,
+    0.989176510f, -0.146730474f,
+    0.989622017f, -0.143695033f,
+    0.990058210f, -0.140658239f,
+    0.990485084f, -0.137620122f,
+    0.990902635f, -0.134580709f,
+    0.991310860f, -0.131540029f,
+    0.991709754f, -0.128498111f,
+    0.992099313f, -0.125454983f,
+    0.992479535f, -0.122410675f,
+    0.992850414f, -0.119365215f,
+    0.993211949f, -0.116318631f,
+    0.993564136f, -0.113270952f,
+    0.993906970f, -0.110222207f,
+    0.994240449f, -0.107172425f,
+    0.994564571f, -0.104121634f,
+    0.994879331f, -0.101069863f,
+    0.995184727f, -0.098017140f,
+    0.995480755f, -0.094963495f,
+    0.995767414f, -0.091908956f,
+    0.996044701f, -0.088853553f,
+    0.996312612f, -0.085797312f,
+    0.996571146f, -0.082740265f,
+    0.996820299f, -0.079682438f,
+    0.997060070f, -0.076623861f,
+    0.997290457f, -0.073564564f,
+    0.997511456f, -0.070504573f,
+    0.997723067f, -0.067443920f,
+    0.997925286f, -0.064382631f,
+    0.998118113f, -0.061320736f,
+    0.998301545f, -0.058258265f,
+    0.998475581f, -0.055195244f,
+    0.998640218f, -0.052131705f,
+    0.998795456f, -0.049067674f,
+    0.998941293f, -0.046003182f,
+    0.999077728f, -0.042938257f,
+    0.999204759f, -0.039872928f,
+    0.999322385f, -0.036807223f,
+    0.999430605f, -0.033741172f,
+    0.999529418f, -0.030674803f,
+    0.999618822f, -0.027608146f,
+    0.999698819f, -0.024541229f,
+    0.999769405f, -0.021474080f,
+    0.999830582f, -0.018406730f,
+    0.999882347f, -0.015339206f,
+    0.999924702f, -0.012271538f,
+    0.999957645f, -0.009203755f,
+    0.999981175f, -0.006135885f,
+    0.999995294f, -0.003067957f
+};
+
+/**
+* \par
+* Example code for Floating-point Twiddle factors Generation:
+* \par
+* <pre>for(i = 0; i< N/; i++)
+* {
+*	twiddleCoef[2*i]= cos(i * 2*PI/(float)N);
+*	twiddleCoef[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 4096	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are in interleaved fashion
+*
+*/
+const float32_t twiddleCoef_4096[8192] = {
+    1.000000000f,  0.000000000f,
+    0.999998823f,  0.001533980f,
+    0.999995294f,  0.003067957f,
+    0.999989411f,  0.004601926f,
+    0.999981175f,  0.006135885f,
+    0.999970586f,  0.007669829f,
+    0.999957645f,  0.009203755f,
+    0.999942350f,  0.010737659f,
+    0.999924702f,  0.012271538f,
+    0.999904701f,  0.013805389f,
+    0.999882347f,  0.015339206f,
+    0.999857641f,  0.016872988f,
+    0.999830582f,  0.018406730f,
+    0.999801170f,  0.019940429f,
+    0.999769405f,  0.021474080f,
+    0.999735288f,  0.023007681f,
+    0.999698819f,  0.024541229f,
+    0.999659997f,  0.026074718f,
+    0.999618822f,  0.027608146f,
+    0.999575296f,  0.029141509f,
+    0.999529418f,  0.030674803f,
+    0.999481187f,  0.032208025f,
+    0.999430605f,  0.033741172f,
+    0.999377670f,  0.035274239f,
+    0.999322385f,  0.036807223f,
+    0.999264747f,  0.038340120f,
+    0.999204759f,  0.039872928f,
+    0.999142419f,  0.041405641f,
+    0.999077728f,  0.042938257f,
+    0.999010686f,  0.044470772f,
+    0.998941293f,  0.046003182f,
+    0.998869550f,  0.047535484f,
+    0.998795456f,  0.049067674f,
+    0.998719012f,  0.050599749f,
+    0.998640218f,  0.052131705f,
+    0.998559074f,  0.053663538f,
+    0.998475581f,  0.055195244f,
+    0.998389737f,  0.056726821f,
+    0.998301545f,  0.058258265f,
+    0.998211003f,  0.059789571f,
+    0.998118113f,  0.061320736f,
+    0.998022874f,  0.062851758f,
+    0.997925286f,  0.064382631f,
+    0.997825350f,  0.065913353f,
+    0.997723067f,  0.067443920f,
+    0.997618435f,  0.068974328f,
+    0.997511456f,  0.070504573f,
+    0.997402130f,  0.072034653f,
+    0.997290457f,  0.073564564f,
+    0.997176437f,  0.075094301f,
+    0.997060070f,  0.076623861f,
+    0.996941358f,  0.078153242f,
+    0.996820299f,  0.079682438f,
+    0.996696895f,  0.081211447f,
+    0.996571146f,  0.082740265f,
+    0.996443051f,  0.084268888f,
+    0.996312612f,  0.085797312f,
+    0.996179829f,  0.087325535f,
+    0.996044701f,  0.088853553f,
+    0.995907229f,  0.090381361f,
+    0.995767414f,  0.091908956f,
+    0.995625256f,  0.093436336f,
+    0.995480755f,  0.094963495f,
+    0.995333912f,  0.096490431f,
+    0.995184727f,  0.098017140f,
+    0.995033199f,  0.099543619f,
+    0.994879331f,  0.101069863f,
+    0.994723121f,  0.102595869f,
+    0.994564571f,  0.104121634f,
+    0.994403680f,  0.105647154f,
+    0.994240449f,  0.107172425f,
+    0.994074879f,  0.108697444f,
+    0.993906970f,  0.110222207f,
+    0.993736722f,  0.111746711f,
+    0.993564136f,  0.113270952f,
+    0.993389211f,  0.114794927f,
+    0.993211949f,  0.116318631f,
+    0.993032350f,  0.117842062f,
+    0.992850414f,  0.119365215f,
+    0.992666142f,  0.120888087f,
+    0.992479535f,  0.122410675f,
+    0.992290591f,  0.123932975f,
+    0.992099313f,  0.125454983f,
+    0.991905700f,  0.126976696f,
+    0.991709754f,  0.128498111f,
+    0.991511473f,  0.130019223f,
+    0.991310860f,  0.131540029f,
+    0.991107914f,  0.133060525f,
+    0.990902635f,  0.134580709f,
+    0.990695025f,  0.136100575f,
+    0.990485084f,  0.137620122f,
+    0.990272812f,  0.139139344f,
+    0.990058210f,  0.140658239f,
+    0.989841278f,  0.142176804f,
+    0.989622017f,  0.143695033f,
+    0.989400428f,  0.145212925f,
+    0.989176510f,  0.146730474f,
+    0.988950265f,  0.148247679f,
+    0.988721692f,  0.149764535f,
+    0.988490793f,  0.151281038f,
+    0.988257568f,  0.152797185f,
+    0.988022017f,  0.154312973f,
+    0.987784142f,  0.155828398f,
+    0.987543942f,  0.157343456f,
+    0.987301418f,  0.158858143f,
+    0.987056571f,  0.160372457f,
+    0.986809402f,  0.161886394f,
+    0.986559910f,  0.163399949f,
+    0.986308097f,  0.164913120f,
+    0.986053963f,  0.166425904f,
+    0.985797509f,  0.167938295f,
+    0.985538735f,  0.169450291f,
+    0.985277642f,  0.170961889f,
+    0.985014231f,  0.172473084f,
+    0.984748502f,  0.173983873f,
+    0.984480455f,  0.175494253f,
+    0.984210092f,  0.177004220f,
+    0.983937413f,  0.178513771f,
+    0.983662419f,  0.180022901f,
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+    0.971139158f, -0.238513595f,
+    0.971503891f, -0.237023606f,
+    0.971866337f, -0.235533059f,
+    0.972226497f, -0.234041959f,
+    0.972584369f, -0.232550307f,
+    0.972939952f, -0.231058108f,
+    0.973293246f, -0.229565366f,
+    0.973644250f, -0.228072083f,
+    0.973992962f, -0.226578264f,
+    0.974339383f, -0.225083911f,
+    0.974683511f, -0.223589029f,
+    0.975025345f, -0.222093621f,
+    0.975364885f, -0.220597690f,
+    0.975702130f, -0.219101240f,
+    0.976037079f, -0.217604275f,
+    0.976369731f, -0.216106797f,
+    0.976700086f, -0.214608811f,
+    0.977028143f, -0.213110320f,
+    0.977353900f, -0.211611327f,
+    0.977677358f, -0.210111837f,
+    0.977998515f, -0.208611852f,
+    0.978317371f, -0.207111376f,
+    0.978633924f, -0.205610413f,
+    0.978948175f, -0.204108966f,
+    0.979260123f, -0.202607039f,
+    0.979569766f, -0.201104635f,
+    0.979877104f, -0.199601758f,
+    0.980182136f, -0.198098411f,
+    0.980484862f, -0.196594598f,
+    0.980785280f, -0.195090322f,
+    0.981083391f, -0.193585587f,
+    0.981379193f, -0.192080397f,
+    0.981672686f, -0.190574755f,
+    0.981963869f, -0.189068664f,
+    0.982252741f, -0.187562129f,
+    0.982539302f, -0.186055152f,
+    0.982823551f, -0.184547737f,
+    0.983105487f, -0.183039888f,
+    0.983385110f, -0.181531608f,
+    0.983662419f, -0.180022901f,
+    0.983937413f, -0.178513771f,
+    0.984210092f, -0.177004220f,
+    0.984480455f, -0.175494253f,
+    0.984748502f, -0.173983873f,
+    0.985014231f, -0.172473084f,
+    0.985277642f, -0.170961889f,
+    0.985538735f, -0.169450291f,
+    0.985797509f, -0.167938295f,
+    0.986053963f, -0.166425904f,
+    0.986308097f, -0.164913120f,
+    0.986559910f, -0.163399949f,
+    0.986809402f, -0.161886394f,
+    0.987056571f, -0.160372457f,
+    0.987301418f, -0.158858143f,
+    0.987543942f, -0.157343456f,
+    0.987784142f, -0.155828398f,
+    0.988022017f, -0.154312973f,
+    0.988257568f, -0.152797185f,
+    0.988490793f, -0.151281038f,
+    0.988721692f, -0.149764535f,
+    0.988950265f, -0.148247679f,
+    0.989176510f, -0.146730474f,
+    0.989400428f, -0.145212925f,
+    0.989622017f, -0.143695033f,
+    0.989841278f, -0.142176804f,
+    0.990058210f, -0.140658239f,
+    0.990272812f, -0.139139344f,
+    0.990485084f, -0.137620122f,
+    0.990695025f, -0.136100575f,
+    0.990902635f, -0.134580709f,
+    0.991107914f, -0.133060525f,
+    0.991310860f, -0.131540029f,
+    0.991511473f, -0.130019223f,
+    0.991709754f, -0.128498111f,
+    0.991905700f, -0.126976696f,
+    0.992099313f, -0.125454983f,
+    0.992290591f, -0.123932975f,
+    0.992479535f, -0.122410675f,
+    0.992666142f, -0.120888087f,
+    0.992850414f, -0.119365215f,
+    0.993032350f, -0.117842062f,
+    0.993211949f, -0.116318631f,
+    0.993389211f, -0.114794927f,
+    0.993564136f, -0.113270952f,
+    0.993736722f, -0.111746711f,
+    0.993906970f, -0.110222207f,
+    0.994074879f, -0.108697444f,
+    0.994240449f, -0.107172425f,
+    0.994403680f, -0.105647154f,
+    0.994564571f, -0.104121634f,
+    0.994723121f, -0.102595869f,
+    0.994879331f, -0.101069863f,
+    0.995033199f, -0.099543619f,
+    0.995184727f, -0.098017140f,
+    0.995333912f, -0.096490431f,
+    0.995480755f, -0.094963495f,
+    0.995625256f, -0.093436336f,
+    0.995767414f, -0.091908956f,
+    0.995907229f, -0.090381361f,
+    0.996044701f, -0.088853553f,
+    0.996179829f, -0.087325535f,
+    0.996312612f, -0.085797312f,
+    0.996443051f, -0.084268888f,
+    0.996571146f, -0.082740265f,
+    0.996696895f, -0.081211447f,
+    0.996820299f, -0.079682438f,
+    0.996941358f, -0.078153242f,
+    0.997060070f, -0.076623861f,
+    0.997176437f, -0.075094301f,
+    0.997290457f, -0.073564564f,
+    0.997402130f, -0.072034653f,
+    0.997511456f, -0.070504573f,
+    0.997618435f, -0.068974328f,
+    0.997723067f, -0.067443920f,
+    0.997825350f, -0.065913353f,
+    0.997925286f, -0.064382631f,
+    0.998022874f, -0.062851758f,
+    0.998118113f, -0.061320736f,
+    0.998211003f, -0.059789571f,
+    0.998301545f, -0.058258265f,
+    0.998389737f, -0.056726821f,
+    0.998475581f, -0.055195244f,
+    0.998559074f, -0.053663538f,
+    0.998640218f, -0.052131705f,
+    0.998719012f, -0.050599749f,
+    0.998795456f, -0.049067674f,
+    0.998869550f, -0.047535484f,
+    0.998941293f, -0.046003182f,
+    0.999010686f, -0.044470772f,
+    0.999077728f, -0.042938257f,
+    0.999142419f, -0.041405641f,
+    0.999204759f, -0.039872928f,
+    0.999264747f, -0.038340120f,
+    0.999322385f, -0.036807223f,
+    0.999377670f, -0.035274239f,
+    0.999430605f, -0.033741172f,
+    0.999481187f, -0.032208025f,
+    0.999529418f, -0.030674803f,
+    0.999575296f, -0.029141509f,
+    0.999618822f, -0.027608146f,
+    0.999659997f, -0.026074718f,
+    0.999698819f, -0.024541229f,
+    0.999735288f, -0.023007681f,
+    0.999769405f, -0.021474080f,
+    0.999801170f, -0.019940429f,
+    0.999830582f, -0.018406730f,
+    0.999857641f, -0.016872988f,
+    0.999882347f, -0.015339206f,
+    0.999904701f, -0.013805389f,
+    0.999924702f, -0.012271538f,
+    0.999942350f, -0.010737659f,
+    0.999957645f, -0.009203755f,
+    0.999970586f, -0.007669829f,
+    0.999981175f, -0.006135885f,
+    0.999989411f, -0.004601926f,
+    0.999995294f, -0.003067957f,
+    0.999998823f, -0.001533980f
+};
+
+/*
+* @brief  Q31 Twiddle factors Table
+*/
+
+
+/**
+* \par
+* Example code for Q31 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefQ31[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefQ31[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 16	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to Q31(Fixed point 1.31):
+*	round(twiddleCoefQ31(i) * pow(2, 31))
+*
+*/
+const q31_t twiddleCoef_16_q31[24] = {
+    (q31_t)0x7FFFFFFF, (q31_t)0x00000000,
+    (q31_t)0x7641AF3C, (q31_t)0x30FBC54D,
+    (q31_t)0x5A82799A, (q31_t)0x5A82799A,
+    (q31_t)0x30FBC54D, (q31_t)0x7641AF3C,
+    (q31_t)0x00000000, (q31_t)0x7FFFFFFF,
+    (q31_t)0xCF043AB2, (q31_t)0x7641AF3C,
+    (q31_t)0xA57D8666, (q31_t)0x5A82799A,
+    (q31_t)0x89BE50C3, (q31_t)0x30FBC54D,
+    (q31_t)0x80000000, (q31_t)0x00000000,
+    (q31_t)0x89BE50C3, (q31_t)0xCF043AB2,
+    (q31_t)0xA57D8666, (q31_t)0xA57D8666,
+    (q31_t)0xCF043AB2, (q31_t)0x89BE50C3
+};
+
+/**
+* \par
+* Example code for Q31 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefQ31[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefQ31[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 32	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to Q31(Fixed point 1.31):
+*	round(twiddleCoefQ31(i) * pow(2, 31))
+*
+*/
+const q31_t twiddleCoef_32_q31[48] = {
+    (q31_t)0x7FFFFFFF, (q31_t)0x00000000,
+    (q31_t)0x7D8A5F3F, (q31_t)0x18F8B83C,
+    (q31_t)0x7641AF3C, (q31_t)0x30FBC54D,
+    (q31_t)0x6A6D98A4, (q31_t)0x471CECE6,
+    (q31_t)0x5A82799A, (q31_t)0x5A82799A,
+    (q31_t)0x471CECE6, (q31_t)0x6A6D98A4,
+    (q31_t)0x30FBC54D, (q31_t)0x7641AF3C,
+    (q31_t)0x18F8B83C, (q31_t)0x7D8A5F3F,
+    (q31_t)0x00000000, (q31_t)0x7FFFFFFF,
+    (q31_t)0xE70747C3, (q31_t)0x7D8A5F3F,
+    (q31_t)0xCF043AB2, (q31_t)0x7641AF3C,
+    (q31_t)0xB8E31319, (q31_t)0x6A6D98A4,
+    (q31_t)0xA57D8666, (q31_t)0x5A82799A,
+    (q31_t)0x9592675B, (q31_t)0x471CECE6,
+    (q31_t)0x89BE50C3, (q31_t)0x30FBC54D,
+    (q31_t)0x8275A0C0, (q31_t)0x18F8B83C,
+    (q31_t)0x80000000, (q31_t)0x00000000,
+    (q31_t)0x8275A0C0, (q31_t)0xE70747C3,
+    (q31_t)0x89BE50C3, (q31_t)0xCF043AB2,
+    (q31_t)0x9592675B, (q31_t)0xB8E31319,
+    (q31_t)0xA57D8666, (q31_t)0xA57D8666,
+    (q31_t)0xB8E31319, (q31_t)0x9592675B,
+    (q31_t)0xCF043AB2, (q31_t)0x89BE50C3,
+    (q31_t)0xE70747C3, (q31_t)0x8275A0C0
+};
+
+/**
+* \par
+* Example code for Q31 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefQ31[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefQ31[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 64	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to Q31(Fixed point 1.31):
+*	round(twiddleCoefQ31(i) * pow(2, 31))
+*
+*/
+const q31_t twiddleCoef_64_q31[96] = {
+	(q31_t)0x7FFFFFFF, (q31_t)0x00000000, (q31_t)0x7F62368F,
+	(q31_t)0x0C8BD35E, (q31_t)0x7D8A5F3F, (q31_t)0x18F8B83C,
+	(q31_t)0x7A7D055B, (q31_t)0x25280C5D, (q31_t)0x7641AF3C,
+	(q31_t)0x30FBC54D, (q31_t)0x70E2CBC6, (q31_t)0x3C56BA70,
+	(q31_t)0x6A6D98A4, (q31_t)0x471CECE6, (q31_t)0x62F201AC,
+	(q31_t)0x5133CC94, (q31_t)0x5A82799A, (q31_t)0x5A82799A,
+	(q31_t)0x5133CC94, (q31_t)0x62F201AC, (q31_t)0x471CECE6,
+	(q31_t)0x6A6D98A4, (q31_t)0x3C56BA70, (q31_t)0x70E2CBC6,
+	(q31_t)0x30FBC54D, (q31_t)0x7641AF3C, (q31_t)0x25280C5D,
+	(q31_t)0x7A7D055B, (q31_t)0x18F8B83C, (q31_t)0x7D8A5F3F,
+	(q31_t)0x0C8BD35E, (q31_t)0x7F62368F, (q31_t)0x00000000,
+	(q31_t)0x7FFFFFFF, (q31_t)0xF3742CA1, (q31_t)0x7F62368F,
+	(q31_t)0xE70747C3, (q31_t)0x7D8A5F3F, (q31_t)0xDAD7F3A2,
+	(q31_t)0x7A7D055B, (q31_t)0xCF043AB2, (q31_t)0x7641AF3C,
+	(q31_t)0xC3A9458F, (q31_t)0x70E2CBC6, (q31_t)0xB8E31319,
+	(q31_t)0x6A6D98A4, (q31_t)0xAECC336B, (q31_t)0x62F201AC,
+	(q31_t)0xA57D8666, (q31_t)0x5A82799A, (q31_t)0x9D0DFE53,
+	(q31_t)0x5133CC94, (q31_t)0x9592675B, (q31_t)0x471CECE6,
+	(q31_t)0x8F1D343A, (q31_t)0x3C56BA70, (q31_t)0x89BE50C3,
+	(q31_t)0x30FBC54D, (q31_t)0x8582FAA4, (q31_t)0x25280C5D,
+	(q31_t)0x8275A0C0, (q31_t)0x18F8B83C, (q31_t)0x809DC970,
+	(q31_t)0x0C8BD35E, (q31_t)0x80000000, (q31_t)0x00000000,
+	(q31_t)0x809DC970, (q31_t)0xF3742CA1, (q31_t)0x8275A0C0,
+	(q31_t)0xE70747C3, (q31_t)0x8582FAA4, (q31_t)0xDAD7F3A2,
+	(q31_t)0x89BE50C3, (q31_t)0xCF043AB2, (q31_t)0x8F1D343A,
+	(q31_t)0xC3A9458F, (q31_t)0x9592675B, (q31_t)0xB8E31319,
+	(q31_t)0x9D0DFE53, (q31_t)0xAECC336B, (q31_t)0xA57D8666,
+	(q31_t)0xA57D8666, (q31_t)0xAECC336B, (q31_t)0x9D0DFE53,
+	(q31_t)0xB8E31319, (q31_t)0x9592675B, (q31_t)0xC3A9458F,
+	(q31_t)0x8F1D343A, (q31_t)0xCF043AB2, (q31_t)0x89BE50C3,
+	(q31_t)0xDAD7F3A2, (q31_t)0x8582FAA4, (q31_t)0xE70747C3,
+	(q31_t)0x8275A0C0, (q31_t)0xF3742CA1, (q31_t)0x809DC970
+};
+
+/**
+* \par
+* Example code for Q31 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefQ31[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefQ31[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 128	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to Q31(Fixed point 1.31):
+*	round(twiddleCoefQ31(i) * pow(2, 31))
+*
+*/
+const q31_t twiddleCoef_128_q31[192] = {
+	(q31_t)0x7FFFFFFF, (q31_t)0x00000000, (q31_t)0x7FD8878D,
+	(q31_t)0x0647D97C, (q31_t)0x7F62368F, (q31_t)0x0C8BD35E,
+	(q31_t)0x7E9D55FC, (q31_t)0x12C8106E, (q31_t)0x7D8A5F3F,
+	(q31_t)0x18F8B83C, (q31_t)0x7C29FBEE, (q31_t)0x1F19F97B,
+	(q31_t)0x7A7D055B, (q31_t)0x25280C5D, (q31_t)0x78848413,
+	(q31_t)0x2B1F34EB, (q31_t)0x7641AF3C, (q31_t)0x30FBC54D,
+	(q31_t)0x73B5EBD0, (q31_t)0x36BA2013, (q31_t)0x70E2CBC6,
+	(q31_t)0x3C56BA70, (q31_t)0x6DCA0D14, (q31_t)0x41CE1E64,
+	(q31_t)0x6A6D98A4, (q31_t)0x471CECE6, (q31_t)0x66CF811F,
+	(q31_t)0x4C3FDFF3, (q31_t)0x62F201AC, (q31_t)0x5133CC94,
+	(q31_t)0x5ED77C89, (q31_t)0x55F5A4D2, (q31_t)0x5A82799A,
+	(q31_t)0x5A82799A, (q31_t)0x55F5A4D2, (q31_t)0x5ED77C89,
+	(q31_t)0x5133CC94, (q31_t)0x62F201AC, (q31_t)0x4C3FDFF3,
+	(q31_t)0x66CF811F, (q31_t)0x471CECE6, (q31_t)0x6A6D98A4,
+	(q31_t)0x41CE1E64, (q31_t)0x6DCA0D14, (q31_t)0x3C56BA70,
+	(q31_t)0x70E2CBC6, (q31_t)0x36BA2013, (q31_t)0x73B5EBD0,
+	(q31_t)0x30FBC54D, (q31_t)0x7641AF3C, (q31_t)0x2B1F34EB,
+	(q31_t)0x78848413, (q31_t)0x25280C5D, (q31_t)0x7A7D055B,
+	(q31_t)0x1F19F97B, (q31_t)0x7C29FBEE, (q31_t)0x18F8B83C,
+	(q31_t)0x7D8A5F3F, (q31_t)0x12C8106E, (q31_t)0x7E9D55FC,
+	(q31_t)0x0C8BD35E, (q31_t)0x7F62368F, (q31_t)0x0647D97C,
+	(q31_t)0x7FD8878D, (q31_t)0x00000000, (q31_t)0x7FFFFFFF,
+	(q31_t)0xF9B82683, (q31_t)0x7FD8878D, (q31_t)0xF3742CA1,
+	(q31_t)0x7F62368F, (q31_t)0xED37EF91, (q31_t)0x7E9D55FC,
+	(q31_t)0xE70747C3, (q31_t)0x7D8A5F3F, (q31_t)0xE0E60684,
+	(q31_t)0x7C29FBEE, (q31_t)0xDAD7F3A2, (q31_t)0x7A7D055B,
+	(q31_t)0xD4E0CB14, (q31_t)0x78848413, (q31_t)0xCF043AB2,
+	(q31_t)0x7641AF3C, (q31_t)0xC945DFEC, (q31_t)0x73B5EBD0,
+	(q31_t)0xC3A9458F, (q31_t)0x70E2CBC6, (q31_t)0xBE31E19B,
+	(q31_t)0x6DCA0D14, (q31_t)0xB8E31319, (q31_t)0x6A6D98A4,
+	(q31_t)0xB3C0200C, (q31_t)0x66CF811F, (q31_t)0xAECC336B,
+	(q31_t)0x62F201AC, (q31_t)0xAA0A5B2D, (q31_t)0x5ED77C89,
+	(q31_t)0xA57D8666, (q31_t)0x5A82799A, (q31_t)0xA1288376,
+	(q31_t)0x55F5A4D2, (q31_t)0x9D0DFE53, (q31_t)0x5133CC94,
+	(q31_t)0x99307EE0, (q31_t)0x4C3FDFF3, (q31_t)0x9592675B,
+	(q31_t)0x471CECE6, (q31_t)0x9235F2EB, (q31_t)0x41CE1E64,
+	(q31_t)0x8F1D343A, (q31_t)0x3C56BA70, (q31_t)0x8C4A142F,
+	(q31_t)0x36BA2013, (q31_t)0x89BE50C3, (q31_t)0x30FBC54D,
+	(q31_t)0x877B7BEC, (q31_t)0x2B1F34EB, (q31_t)0x8582FAA4,
+	(q31_t)0x25280C5D, (q31_t)0x83D60411, (q31_t)0x1F19F97B,
+	(q31_t)0x8275A0C0, (q31_t)0x18F8B83C, (q31_t)0x8162AA03,
+	(q31_t)0x12C8106E, (q31_t)0x809DC970, (q31_t)0x0C8BD35E,
+	(q31_t)0x80277872, (q31_t)0x0647D97C, (q31_t)0x80000000,
+	(q31_t)0x00000000, (q31_t)0x80277872, (q31_t)0xF9B82683,
+	(q31_t)0x809DC970, (q31_t)0xF3742CA1, (q31_t)0x8162AA03,
+	(q31_t)0xED37EF91, (q31_t)0x8275A0C0, (q31_t)0xE70747C3,
+	(q31_t)0x83D60411, (q31_t)0xE0E60684, (q31_t)0x8582FAA4,
+	(q31_t)0xDAD7F3A2, (q31_t)0x877B7BEC, (q31_t)0xD4E0CB14,
+	(q31_t)0x89BE50C3, (q31_t)0xCF043AB2, (q31_t)0x8C4A142F,
+	(q31_t)0xC945DFEC, (q31_t)0x8F1D343A, (q31_t)0xC3A9458F,
+	(q31_t)0x9235F2EB, (q31_t)0xBE31E19B, (q31_t)0x9592675B,
+	(q31_t)0xB8E31319, (q31_t)0x99307EE0, (q31_t)0xB3C0200C,
+	(q31_t)0x9D0DFE53, (q31_t)0xAECC336B, (q31_t)0xA1288376,
+	(q31_t)0xAA0A5B2D, (q31_t)0xA57D8666, (q31_t)0xA57D8666,
+	(q31_t)0xAA0A5B2D, (q31_t)0xA1288376, (q31_t)0xAECC336B,
+	(q31_t)0x9D0DFE53, (q31_t)0xB3C0200C, (q31_t)0x99307EE0,
+	(q31_t)0xB8E31319, (q31_t)0x9592675B, (q31_t)0xBE31E19B,
+	(q31_t)0x9235F2EB, (q31_t)0xC3A9458F, (q31_t)0x8F1D343A,
+	(q31_t)0xC945DFEC, (q31_t)0x8C4A142F, (q31_t)0xCF043AB2,
+	(q31_t)0x89BE50C3, (q31_t)0xD4E0CB14, (q31_t)0x877B7BEC,
+	(q31_t)0xDAD7F3A2, (q31_t)0x8582FAA4, (q31_t)0xE0E60684,
+	(q31_t)0x83D60411, (q31_t)0xE70747C3, (q31_t)0x8275A0C0,
+	(q31_t)0xED37EF91, (q31_t)0x8162AA03, (q31_t)0xF3742CA1,
+	(q31_t)0x809DC970, (q31_t)0xF9B82683, (q31_t)0x80277872
+};
+
+/**
+* \par
+* Example code for Q31 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefQ31[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefQ31[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 256	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to Q31(Fixed point 1.31):
+*	round(twiddleCoefQ31(i) * pow(2, 31))
+*
+*/
+const q31_t twiddleCoef_256_q31[384] = {
+	(q31_t)0x7FFFFFFF, (q31_t)0x00000000, (q31_t)0x7FF62182,
+	(q31_t)0x03242ABF, (q31_t)0x7FD8878D, (q31_t)0x0647D97C,
+	(q31_t)0x7FA736B4, (q31_t)0x096A9049, (q31_t)0x7F62368F,
+	(q31_t)0x0C8BD35E, (q31_t)0x7F0991C3, (q31_t)0x0FAB272B,
+	(q31_t)0x7E9D55FC, (q31_t)0x12C8106E, (q31_t)0x7E1D93E9,
+	(q31_t)0x15E21444, (q31_t)0x7D8A5F3F, (q31_t)0x18F8B83C,
+	(q31_t)0x7CE3CEB1, (q31_t)0x1C0B826A, (q31_t)0x7C29FBEE,
+	(q31_t)0x1F19F97B, (q31_t)0x7B5D039D, (q31_t)0x2223A4C5,
+	(q31_t)0x7A7D055B, (q31_t)0x25280C5D, (q31_t)0x798A23B1,
+	(q31_t)0x2826B928, (q31_t)0x78848413, (q31_t)0x2B1F34EB,
+	(q31_t)0x776C4EDB, (q31_t)0x2E110A62, (q31_t)0x7641AF3C,
+	(q31_t)0x30FBC54D, (q31_t)0x7504D345, (q31_t)0x33DEF287,
+	(q31_t)0x73B5EBD0, (q31_t)0x36BA2013, (q31_t)0x72552C84,
+	(q31_t)0x398CDD32, (q31_t)0x70E2CBC6, (q31_t)0x3C56BA70,
+	(q31_t)0x6F5F02B1, (q31_t)0x3F1749B7, (q31_t)0x6DCA0D14,
+	(q31_t)0x41CE1E64, (q31_t)0x6C242960, (q31_t)0x447ACD50,
+	(q31_t)0x6A6D98A4, (q31_t)0x471CECE6, (q31_t)0x68A69E81,
+	(q31_t)0x49B41533, (q31_t)0x66CF811F, (q31_t)0x4C3FDFF3,
+	(q31_t)0x64E88926, (q31_t)0x4EBFE8A4, (q31_t)0x62F201AC,
+	(q31_t)0x5133CC94, (q31_t)0x60EC3830, (q31_t)0x539B2AEF,
+	(q31_t)0x5ED77C89, (q31_t)0x55F5A4D2, (q31_t)0x5CB420DF,
+	(q31_t)0x5842DD54, (q31_t)0x5A82799A, (q31_t)0x5A82799A,
+	(q31_t)0x5842DD54, (q31_t)0x5CB420DF, (q31_t)0x55F5A4D2,
+	(q31_t)0x5ED77C89, (q31_t)0x539B2AEF, (q31_t)0x60EC3830,
+	(q31_t)0x5133CC94, (q31_t)0x62F201AC, (q31_t)0x4EBFE8A4,
+	(q31_t)0x64E88926, (q31_t)0x4C3FDFF3, (q31_t)0x66CF811F,
+	(q31_t)0x49B41533, (q31_t)0x68A69E81, (q31_t)0x471CECE6,
+	(q31_t)0x6A6D98A4, (q31_t)0x447ACD50, (q31_t)0x6C242960,
+	(q31_t)0x41CE1E64, (q31_t)0x6DCA0D14, (q31_t)0x3F1749B7,
+	(q31_t)0x6F5F02B1, (q31_t)0x3C56BA70, (q31_t)0x70E2CBC6,
+	(q31_t)0x398CDD32, (q31_t)0x72552C84, (q31_t)0x36BA2013,
+	(q31_t)0x73B5EBD0, (q31_t)0x33DEF287, (q31_t)0x7504D345,
+	(q31_t)0x30FBC54D, (q31_t)0x7641AF3C, (q31_t)0x2E110A62,
+	(q31_t)0x776C4EDB, (q31_t)0x2B1F34EB, (q31_t)0x78848413,
+	(q31_t)0x2826B928, (q31_t)0x798A23B1, (q31_t)0x25280C5D,
+	(q31_t)0x7A7D055B, (q31_t)0x2223A4C5, (q31_t)0x7B5D039D,
+	(q31_t)0x1F19F97B, (q31_t)0x7C29FBEE, (q31_t)0x1C0B826A,
+	(q31_t)0x7CE3CEB1, (q31_t)0x18F8B83C, (q31_t)0x7D8A5F3F,
+	(q31_t)0x15E21444, (q31_t)0x7E1D93E9, (q31_t)0x12C8106E,
+	(q31_t)0x7E9D55FC, (q31_t)0x0FAB272B, (q31_t)0x7F0991C3,
+	(q31_t)0x0C8BD35E, (q31_t)0x7F62368F, (q31_t)0x096A9049,
+	(q31_t)0x7FA736B4, (q31_t)0x0647D97C, (q31_t)0x7FD8878D,
+	(q31_t)0x03242ABF, (q31_t)0x7FF62182, (q31_t)0x00000000,
+	(q31_t)0x7FFFFFFF, (q31_t)0xFCDBD541, (q31_t)0x7FF62182,
+	(q31_t)0xF9B82683, (q31_t)0x7FD8878D, (q31_t)0xF6956FB6,
+	(q31_t)0x7FA736B4, (q31_t)0xF3742CA1, (q31_t)0x7F62368F,
+	(q31_t)0xF054D8D4, (q31_t)0x7F0991C3, (q31_t)0xED37EF91,
+	(q31_t)0x7E9D55FC, (q31_t)0xEA1DEBBB, (q31_t)0x7E1D93E9,
+	(q31_t)0xE70747C3, (q31_t)0x7D8A5F3F, (q31_t)0xE3F47D95,
+	(q31_t)0x7CE3CEB1, (q31_t)0xE0E60684, (q31_t)0x7C29FBEE,
+	(q31_t)0xDDDC5B3A, (q31_t)0x7B5D039D, (q31_t)0xDAD7F3A2,
+	(q31_t)0x7A7D055B, (q31_t)0xD7D946D7, (q31_t)0x798A23B1,
+	(q31_t)0xD4E0CB14, (q31_t)0x78848413, (q31_t)0xD1EEF59E,
+	(q31_t)0x776C4EDB, (q31_t)0xCF043AB2, (q31_t)0x7641AF3C,
+	(q31_t)0xCC210D78, (q31_t)0x7504D345, (q31_t)0xC945DFEC,
+	(q31_t)0x73B5EBD0, (q31_t)0xC67322CD, (q31_t)0x72552C84,
+	(q31_t)0xC3A9458F, (q31_t)0x70E2CBC6, (q31_t)0xC0E8B648,
+	(q31_t)0x6F5F02B1, (q31_t)0xBE31E19B, (q31_t)0x6DCA0D14,
+	(q31_t)0xBB8532AF, (q31_t)0x6C242960, (q31_t)0xB8E31319,
+	(q31_t)0x6A6D98A4, (q31_t)0xB64BEACC, (q31_t)0x68A69E81,
+	(q31_t)0xB3C0200C, (q31_t)0x66CF811F, (q31_t)0xB140175B,
+	(q31_t)0x64E88926, (q31_t)0xAECC336B, (q31_t)0x62F201AC,
+	(q31_t)0xAC64D510, (q31_t)0x60EC3830, (q31_t)0xAA0A5B2D,
+	(q31_t)0x5ED77C89, (q31_t)0xA7BD22AB, (q31_t)0x5CB420DF,
+	(q31_t)0xA57D8666, (q31_t)0x5A82799A, (q31_t)0xA34BDF20,
+	(q31_t)0x5842DD54, (q31_t)0xA1288376, (q31_t)0x55F5A4D2,
+	(q31_t)0x9F13C7D0, (q31_t)0x539B2AEF, (q31_t)0x9D0DFE53,
+	(q31_t)0x5133CC94, (q31_t)0x9B1776D9, (q31_t)0x4EBFE8A4,
+	(q31_t)0x99307EE0, (q31_t)0x4C3FDFF3, (q31_t)0x9759617E,
+	(q31_t)0x49B41533, (q31_t)0x9592675B, (q31_t)0x471CECE6,
+	(q31_t)0x93DBD69F, (q31_t)0x447ACD50, (q31_t)0x9235F2EB,
+	(q31_t)0x41CE1E64, (q31_t)0x90A0FD4E, (q31_t)0x3F1749B7,
+	(q31_t)0x8F1D343A, (q31_t)0x3C56BA70, (q31_t)0x8DAAD37B,
+	(q31_t)0x398CDD32, (q31_t)0x8C4A142F, (q31_t)0x36BA2013,
+	(q31_t)0x8AFB2CBA, (q31_t)0x33DEF287, (q31_t)0x89BE50C3,
+	(q31_t)0x30FBC54D, (q31_t)0x8893B124, (q31_t)0x2E110A62,
+	(q31_t)0x877B7BEC, (q31_t)0x2B1F34EB, (q31_t)0x8675DC4E,
+	(q31_t)0x2826B928, (q31_t)0x8582FAA4, (q31_t)0x25280C5D,
+	(q31_t)0x84A2FC62, (q31_t)0x2223A4C5, (q31_t)0x83D60411,
+	(q31_t)0x1F19F97B, (q31_t)0x831C314E, (q31_t)0x1C0B826A,
+	(q31_t)0x8275A0C0, (q31_t)0x18F8B83C, (q31_t)0x81E26C16,
+	(q31_t)0x15E21444, (q31_t)0x8162AA03, (q31_t)0x12C8106E,
+	(q31_t)0x80F66E3C, (q31_t)0x0FAB272B, (q31_t)0x809DC970,
+	(q31_t)0x0C8BD35E, (q31_t)0x8058C94C, (q31_t)0x096A9049,
+	(q31_t)0x80277872, (q31_t)0x0647D97C, (q31_t)0x8009DE7D,
+	(q31_t)0x03242ABF, (q31_t)0x80000000, (q31_t)0x00000000,
+	(q31_t)0x8009DE7D, (q31_t)0xFCDBD541, (q31_t)0x80277872,
+	(q31_t)0xF9B82683, (q31_t)0x8058C94C, (q31_t)0xF6956FB6,
+	(q31_t)0x809DC970, (q31_t)0xF3742CA1, (q31_t)0x80F66E3C,
+	(q31_t)0xF054D8D4, (q31_t)0x8162AA03, (q31_t)0xED37EF91,
+	(q31_t)0x81E26C16, (q31_t)0xEA1DEBBB, (q31_t)0x8275A0C0,
+	(q31_t)0xE70747C3, (q31_t)0x831C314E, (q31_t)0xE3F47D95,
+	(q31_t)0x83D60411, (q31_t)0xE0E60684, (q31_t)0x84A2FC62,
+	(q31_t)0xDDDC5B3A, (q31_t)0x8582FAA4, (q31_t)0xDAD7F3A2,
+	(q31_t)0x8675DC4E, (q31_t)0xD7D946D7, (q31_t)0x877B7BEC,
+	(q31_t)0xD4E0CB14, (q31_t)0x8893B124, (q31_t)0xD1EEF59E,
+	(q31_t)0x89BE50C3, (q31_t)0xCF043AB2, (q31_t)0x8AFB2CBA,
+	(q31_t)0xCC210D78, (q31_t)0x8C4A142F, (q31_t)0xC945DFEC,
+	(q31_t)0x8DAAD37B, (q31_t)0xC67322CD, (q31_t)0x8F1D343A,
+	(q31_t)0xC3A9458F, (q31_t)0x90A0FD4E, (q31_t)0xC0E8B648,
+	(q31_t)0x9235F2EB, (q31_t)0xBE31E19B, (q31_t)0x93DBD69F,
+	(q31_t)0xBB8532AF, (q31_t)0x9592675B, (q31_t)0xB8E31319,
+	(q31_t)0x9759617E, (q31_t)0xB64BEACC, (q31_t)0x99307EE0,
+	(q31_t)0xB3C0200C, (q31_t)0x9B1776D9, (q31_t)0xB140175B,
+	(q31_t)0x9D0DFE53, (q31_t)0xAECC336B, (q31_t)0x9F13C7D0,
+	(q31_t)0xAC64D510, (q31_t)0xA1288376, (q31_t)0xAA0A5B2D,
+	(q31_t)0xA34BDF20, (q31_t)0xA7BD22AB, (q31_t)0xA57D8666,
+	(q31_t)0xA57D8666, (q31_t)0xA7BD22AB, (q31_t)0xA34BDF20,
+	(q31_t)0xAA0A5B2D, (q31_t)0xA1288376, (q31_t)0xAC64D510,
+	(q31_t)0x9F13C7D0, (q31_t)0xAECC336B, (q31_t)0x9D0DFE53,
+	(q31_t)0xB140175B, (q31_t)0x9B1776D9, (q31_t)0xB3C0200C,
+	(q31_t)0x99307EE0, (q31_t)0xB64BEACC, (q31_t)0x9759617E,
+	(q31_t)0xB8E31319, (q31_t)0x9592675B, (q31_t)0xBB8532AF,
+	(q31_t)0x93DBD69F, (q31_t)0xBE31E19B, (q31_t)0x9235F2EB,
+	(q31_t)0xC0E8B648, (q31_t)0x90A0FD4E, (q31_t)0xC3A9458F,
+	(q31_t)0x8F1D343A, (q31_t)0xC67322CD, (q31_t)0x8DAAD37B,
+	(q31_t)0xC945DFEC, (q31_t)0x8C4A142F, (q31_t)0xCC210D78,
+	(q31_t)0x8AFB2CBA, (q31_t)0xCF043AB2, (q31_t)0x89BE50C3,
+	(q31_t)0xD1EEF59E, (q31_t)0x8893B124, (q31_t)0xD4E0CB14,
+	(q31_t)0x877B7BEC, (q31_t)0xD7D946D7, (q31_t)0x8675DC4E,
+	(q31_t)0xDAD7F3A2, (q31_t)0x8582FAA4, (q31_t)0xDDDC5B3A,
+	(q31_t)0x84A2FC62, (q31_t)0xE0E60684, (q31_t)0x83D60411,
+	(q31_t)0xE3F47D95, (q31_t)0x831C314E, (q31_t)0xE70747C3,
+	(q31_t)0x8275A0C0, (q31_t)0xEA1DEBBB, (q31_t)0x81E26C16,
+	(q31_t)0xED37EF91, (q31_t)0x8162AA03, (q31_t)0xF054D8D4,
+	(q31_t)0x80F66E3C, (q31_t)0xF3742CA1, (q31_t)0x809DC970,
+	(q31_t)0xF6956FB6, (q31_t)0x8058C94C, (q31_t)0xF9B82683,
+	(q31_t)0x80277872, (q31_t)0xFCDBD541, (q31_t)0x8009DE7D
+};
+
+/**
+* \par
+* Example code for Q31 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefQ31[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefQ31[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 512	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to Q31(Fixed point 1.31):
+*	round(twiddleCoefQ31(i) * pow(2, 31))
+*
+*/
+const q31_t twiddleCoef_512_q31[768] = {
+    (q31_t)0x7FFFFFFF, (q31_t)0x00000000, (q31_t)0x7FFD885A,
+	(q31_t)0x01921D1F, (q31_t)0x7FF62182, (q31_t)0x03242ABF,
+	(q31_t)0x7FE9CBC0, (q31_t)0x04B6195D, (q31_t)0x7FD8878D,
+	(q31_t)0x0647D97C, (q31_t)0x7FC25596, (q31_t)0x07D95B9E,
+	(q31_t)0x7FA736B4, (q31_t)0x096A9049, (q31_t)0x7F872BF3,
+	(q31_t)0x0AFB6805, (q31_t)0x7F62368F, (q31_t)0x0C8BD35E,
+	(q31_t)0x7F3857F5, (q31_t)0x0E1BC2E3, (q31_t)0x7F0991C3,
+	(q31_t)0x0FAB272B, (q31_t)0x7ED5E5C6, (q31_t)0x1139F0CE,
+	(q31_t)0x7E9D55FC, (q31_t)0x12C8106E, (q31_t)0x7E5FE493,
+	(q31_t)0x145576B1, (q31_t)0x7E1D93E9, (q31_t)0x15E21444,
+	(q31_t)0x7DD6668E, (q31_t)0x176DD9DE, (q31_t)0x7D8A5F3F,
+	(q31_t)0x18F8B83C, (q31_t)0x7D3980EC, (q31_t)0x1A82A025,
+	(q31_t)0x7CE3CEB1, (q31_t)0x1C0B826A, (q31_t)0x7C894BDD,
+	(q31_t)0x1D934FE5, (q31_t)0x7C29FBEE, (q31_t)0x1F19F97B,
+	(q31_t)0x7BC5E28F, (q31_t)0x209F701C, (q31_t)0x7B5D039D,
+	(q31_t)0x2223A4C5, (q31_t)0x7AEF6323, (q31_t)0x23A6887E,
+	(q31_t)0x7A7D055B, (q31_t)0x25280C5D, (q31_t)0x7A05EEAD,
+	(q31_t)0x26A82185, (q31_t)0x798A23B1, (q31_t)0x2826B928,
+	(q31_t)0x7909A92C, (q31_t)0x29A3C484, (q31_t)0x78848413,
+	(q31_t)0x2B1F34EB, (q31_t)0x77FAB988, (q31_t)0x2C98FBBA,
+	(q31_t)0x776C4EDB, (q31_t)0x2E110A62, (q31_t)0x76D94988,
+	(q31_t)0x2F875262, (q31_t)0x7641AF3C, (q31_t)0x30FBC54D,
+	(q31_t)0x75A585CF, (q31_t)0x326E54C7, (q31_t)0x7504D345,
+	(q31_t)0x33DEF287, (q31_t)0x745F9DD1, (q31_t)0x354D9056,
+	(q31_t)0x73B5EBD0, (q31_t)0x36BA2013, (q31_t)0x7307C3D0,
+	(q31_t)0x382493B0, (q31_t)0x72552C84, (q31_t)0x398CDD32,
+	(q31_t)0x719E2CD2, (q31_t)0x3AF2EEB7, (q31_t)0x70E2CBC6,
+	(q31_t)0x3C56BA70, (q31_t)0x70231099, (q31_t)0x3DB832A5,
+	(q31_t)0x6F5F02B1, (q31_t)0x3F1749B7, (q31_t)0x6E96A99C,
+	(q31_t)0x4073F21D, (q31_t)0x6DCA0D14, (q31_t)0x41CE1E64,
+	(q31_t)0x6CF934FB, (q31_t)0x4325C135, (q31_t)0x6C242960,
+	(q31_t)0x447ACD50, (q31_t)0x6B4AF278, (q31_t)0x45CD358F,
+	(q31_t)0x6A6D98A4, (q31_t)0x471CECE6, (q31_t)0x698C246C,
+	(q31_t)0x4869E664, (q31_t)0x68A69E81, (q31_t)0x49B41533,
+	(q31_t)0x67BD0FBC, (q31_t)0x4AFB6C97, (q31_t)0x66CF811F,
+	(q31_t)0x4C3FDFF3, (q31_t)0x65DDFBD3, (q31_t)0x4D8162C4,
+	(q31_t)0x64E88926, (q31_t)0x4EBFE8A4, (q31_t)0x63EF328F,
+	(q31_t)0x4FFB654D, (q31_t)0x62F201AC, (q31_t)0x5133CC94,
+	(q31_t)0x61F1003E, (q31_t)0x5269126E, (q31_t)0x60EC3830,
+	(q31_t)0x539B2AEF, (q31_t)0x5FE3B38D, (q31_t)0x54CA0A4A,
+	(q31_t)0x5ED77C89, (q31_t)0x55F5A4D2, (q31_t)0x5DC79D7C,
+	(q31_t)0x571DEEF9, (q31_t)0x5CB420DF, (q31_t)0x5842DD54,
+	(q31_t)0x5B9D1153, (q31_t)0x59646497, (q31_t)0x5A82799A,
+	(q31_t)0x5A82799A, (q31_t)0x59646497, (q31_t)0x5B9D1153,
+	(q31_t)0x5842DD54, (q31_t)0x5CB420DF, (q31_t)0x571DEEF9,
+	(q31_t)0x5DC79D7C, (q31_t)0x55F5A4D2, (q31_t)0x5ED77C89,
+	(q31_t)0x54CA0A4A, (q31_t)0x5FE3B38D, (q31_t)0x539B2AEF,
+	(q31_t)0x60EC3830, (q31_t)0x5269126E, (q31_t)0x61F1003E,
+	(q31_t)0x5133CC94, (q31_t)0x62F201AC, (q31_t)0x4FFB654D,
+	(q31_t)0x63EF328F, (q31_t)0x4EBFE8A4, (q31_t)0x64E88926,
+	(q31_t)0x4D8162C4, (q31_t)0x65DDFBD3, (q31_t)0x4C3FDFF3,
+	(q31_t)0x66CF811F, (q31_t)0x4AFB6C97, (q31_t)0x67BD0FBC,
+	(q31_t)0x49B41533, (q31_t)0x68A69E81, (q31_t)0x4869E664,
+	(q31_t)0x698C246C, (q31_t)0x471CECE6, (q31_t)0x6A6D98A4,
+	(q31_t)0x45CD358F, (q31_t)0x6B4AF278, (q31_t)0x447ACD50,
+	(q31_t)0x6C242960, (q31_t)0x4325C135, (q31_t)0x6CF934FB,
+	(q31_t)0x41CE1E64, (q31_t)0x6DCA0D14, (q31_t)0x4073F21D,
+	(q31_t)0x6E96A99C, (q31_t)0x3F1749B7, (q31_t)0x6F5F02B1,
+	(q31_t)0x3DB832A5, (q31_t)0x70231099, (q31_t)0x3C56BA70,
+	(q31_t)0x70E2CBC6, (q31_t)0x3AF2EEB7, (q31_t)0x719E2CD2,
+	(q31_t)0x398CDD32, (q31_t)0x72552C84, (q31_t)0x382493B0,
+	(q31_t)0x7307C3D0, (q31_t)0x36BA2013, (q31_t)0x73B5EBD0,
+	(q31_t)0x354D9056, (q31_t)0x745F9DD1, (q31_t)0x33DEF287,
+	(q31_t)0x7504D345, (q31_t)0x326E54C7, (q31_t)0x75A585CF,
+	(q31_t)0x30FBC54D, (q31_t)0x7641AF3C, (q31_t)0x2F875262,
+	(q31_t)0x76D94988, (q31_t)0x2E110A62, (q31_t)0x776C4EDB,
+	(q31_t)0x2C98FBBA, (q31_t)0x77FAB988, (q31_t)0x2B1F34EB,
+	(q31_t)0x78848413, (q31_t)0x29A3C484, (q31_t)0x7909A92C,
+	(q31_t)0x2826B928, (q31_t)0x798A23B1, (q31_t)0x26A82185,
+	(q31_t)0x7A05EEAD, (q31_t)0x25280C5D, (q31_t)0x7A7D055B,
+	(q31_t)0x23A6887E, (q31_t)0x7AEF6323, (q31_t)0x2223A4C5,
+	(q31_t)0x7B5D039D, (q31_t)0x209F701C, (q31_t)0x7BC5E28F,
+	(q31_t)0x1F19F97B, (q31_t)0x7C29FBEE, (q31_t)0x1D934FE5,
+	(q31_t)0x7C894BDD, (q31_t)0x1C0B826A, (q31_t)0x7CE3CEB1,
+	(q31_t)0x1A82A025, (q31_t)0x7D3980EC, (q31_t)0x18F8B83C,
+	(q31_t)0x7D8A5F3F, (q31_t)0x176DD9DE, (q31_t)0x7DD6668E,
+	(q31_t)0x15E21444, (q31_t)0x7E1D93E9, (q31_t)0x145576B1,
+	(q31_t)0x7E5FE493, (q31_t)0x12C8106E, (q31_t)0x7E9D55FC,
+	(q31_t)0x1139F0CE, (q31_t)0x7ED5E5C6, (q31_t)0x0FAB272B,
+	(q31_t)0x7F0991C3, (q31_t)0x0E1BC2E3, (q31_t)0x7F3857F5,
+	(q31_t)0x0C8BD35E, (q31_t)0x7F62368F, (q31_t)0x0AFB6805,
+	(q31_t)0x7F872BF3, (q31_t)0x096A9049, (q31_t)0x7FA736B4,
+	(q31_t)0x07D95B9E, (q31_t)0x7FC25596, (q31_t)0x0647D97C,
+	(q31_t)0x7FD8878D, (q31_t)0x04B6195D, (q31_t)0x7FE9CBC0,
+	(q31_t)0x03242ABF, (q31_t)0x7FF62182, (q31_t)0x01921D1F,
+	(q31_t)0x7FFD885A, (q31_t)0x00000000, (q31_t)0x7FFFFFFF,
+	(q31_t)0xFE6DE2E0, (q31_t)0x7FFD885A, (q31_t)0xFCDBD541,
+	(q31_t)0x7FF62182, (q31_t)0xFB49E6A2, (q31_t)0x7FE9CBC0,
+	(q31_t)0xF9B82683, (q31_t)0x7FD8878D, (q31_t)0xF826A461,
+	(q31_t)0x7FC25596, (q31_t)0xF6956FB6, (q31_t)0x7FA736B4,
+	(q31_t)0xF50497FA, (q31_t)0x7F872BF3, (q31_t)0xF3742CA1,
+	(q31_t)0x7F62368F, (q31_t)0xF1E43D1C, (q31_t)0x7F3857F5,
+	(q31_t)0xF054D8D4, (q31_t)0x7F0991C3, (q31_t)0xEEC60F31,
+	(q31_t)0x7ED5E5C6, (q31_t)0xED37EF91, (q31_t)0x7E9D55FC,
+	(q31_t)0xEBAA894E, (q31_t)0x7E5FE493, (q31_t)0xEA1DEBBB,
+	(q31_t)0x7E1D93E9, (q31_t)0xE8922621, (q31_t)0x7DD6668E,
+	(q31_t)0xE70747C3, (q31_t)0x7D8A5F3F, (q31_t)0xE57D5FDA,
+	(q31_t)0x7D3980EC, (q31_t)0xE3F47D95, (q31_t)0x7CE3CEB1,
+	(q31_t)0xE26CB01A, (q31_t)0x7C894BDD, (q31_t)0xE0E60684,
+	(q31_t)0x7C29FBEE, (q31_t)0xDF608FE3, (q31_t)0x7BC5E28F,
+	(q31_t)0xDDDC5B3A, (q31_t)0x7B5D039D, (q31_t)0xDC597781,
+	(q31_t)0x7AEF6323, (q31_t)0xDAD7F3A2, (q31_t)0x7A7D055B,
+	(q31_t)0xD957DE7A, (q31_t)0x7A05EEAD, (q31_t)0xD7D946D7,
+	(q31_t)0x798A23B1, (q31_t)0xD65C3B7B, (q31_t)0x7909A92C,
+	(q31_t)0xD4E0CB14, (q31_t)0x78848413, (q31_t)0xD3670445,
+	(q31_t)0x77FAB988, (q31_t)0xD1EEF59E, (q31_t)0x776C4EDB,
+	(q31_t)0xD078AD9D, (q31_t)0x76D94988, (q31_t)0xCF043AB2,
+	(q31_t)0x7641AF3C, (q31_t)0xCD91AB38, (q31_t)0x75A585CF,
+	(q31_t)0xCC210D78, (q31_t)0x7504D345, (q31_t)0xCAB26FA9,
+	(q31_t)0x745F9DD1, (q31_t)0xC945DFEC, (q31_t)0x73B5EBD0,
+	(q31_t)0xC7DB6C50, (q31_t)0x7307C3D0, (q31_t)0xC67322CD,
+	(q31_t)0x72552C84, (q31_t)0xC50D1148, (q31_t)0x719E2CD2,
+	(q31_t)0xC3A9458F, (q31_t)0x70E2CBC6, (q31_t)0xC247CD5A,
+	(q31_t)0x70231099, (q31_t)0xC0E8B648, (q31_t)0x6F5F02B1,
+	(q31_t)0xBF8C0DE2, (q31_t)0x6E96A99C, (q31_t)0xBE31E19B,
+	(q31_t)0x6DCA0D14, (q31_t)0xBCDA3ECA, (q31_t)0x6CF934FB,
+	(q31_t)0xBB8532AF, (q31_t)0x6C242960, (q31_t)0xBA32CA70,
+	(q31_t)0x6B4AF278, (q31_t)0xB8E31319, (q31_t)0x6A6D98A4,
+	(q31_t)0xB796199B, (q31_t)0x698C246C, (q31_t)0xB64BEACC,
+	(q31_t)0x68A69E81, (q31_t)0xB5049368, (q31_t)0x67BD0FBC,
+	(q31_t)0xB3C0200C, (q31_t)0x66CF811F, (q31_t)0xB27E9D3B,
+	(q31_t)0x65DDFBD3, (q31_t)0xB140175B, (q31_t)0x64E88926,
+	(q31_t)0xB0049AB2, (q31_t)0x63EF328F, (q31_t)0xAECC336B,
+	(q31_t)0x62F201AC, (q31_t)0xAD96ED91, (q31_t)0x61F1003E,
+	(q31_t)0xAC64D510, (q31_t)0x60EC3830, (q31_t)0xAB35F5B5,
+	(q31_t)0x5FE3B38D, (q31_t)0xAA0A5B2D, (q31_t)0x5ED77C89,
+	(q31_t)0xA8E21106, (q31_t)0x5DC79D7C, (q31_t)0xA7BD22AB,
+	(q31_t)0x5CB420DF, (q31_t)0xA69B9B68, (q31_t)0x5B9D1153,
+	(q31_t)0xA57D8666, (q31_t)0x5A82799A, (q31_t)0xA462EEAC,
+	(q31_t)0x59646497, (q31_t)0xA34BDF20, (q31_t)0x5842DD54,
+	(q31_t)0xA2386283, (q31_t)0x571DEEF9, (q31_t)0xA1288376,
+	(q31_t)0x55F5A4D2, (q31_t)0xA01C4C72, (q31_t)0x54CA0A4A,
+	(q31_t)0x9F13C7D0, (q31_t)0x539B2AEF, (q31_t)0x9E0EFFC1,
+	(q31_t)0x5269126E, (q31_t)0x9D0DFE53, (q31_t)0x5133CC94,
+	(q31_t)0x9C10CD70, (q31_t)0x4FFB654D, (q31_t)0x9B1776D9,
+	(q31_t)0x4EBFE8A4, (q31_t)0x9A22042C, (q31_t)0x4D8162C4,
+	(q31_t)0x99307EE0, (q31_t)0x4C3FDFF3, (q31_t)0x9842F043,
+	(q31_t)0x4AFB6C97, (q31_t)0x9759617E, (q31_t)0x49B41533,
+	(q31_t)0x9673DB94, (q31_t)0x4869E664, (q31_t)0x9592675B,
+	(q31_t)0x471CECE6, (q31_t)0x94B50D87, (q31_t)0x45CD358F,
+	(q31_t)0x93DBD69F, (q31_t)0x447ACD50, (q31_t)0x9306CB04,
+	(q31_t)0x4325C135, (q31_t)0x9235F2EB, (q31_t)0x41CE1E64,
+	(q31_t)0x91695663, (q31_t)0x4073F21D, (q31_t)0x90A0FD4E,
+	(q31_t)0x3F1749B7, (q31_t)0x8FDCEF66, (q31_t)0x3DB832A5,
+	(q31_t)0x8F1D343A, (q31_t)0x3C56BA70, (q31_t)0x8E61D32D,
+	(q31_t)0x3AF2EEB7, (q31_t)0x8DAAD37B, (q31_t)0x398CDD32,
+	(q31_t)0x8CF83C30, (q31_t)0x382493B0, (q31_t)0x8C4A142F,
+	(q31_t)0x36BA2013, (q31_t)0x8BA0622F, (q31_t)0x354D9056,
+	(q31_t)0x8AFB2CBA, (q31_t)0x33DEF287, (q31_t)0x8A5A7A30,
+	(q31_t)0x326E54C7, (q31_t)0x89BE50C3, (q31_t)0x30FBC54D,
+	(q31_t)0x8926B677, (q31_t)0x2F875262, (q31_t)0x8893B124,
+	(q31_t)0x2E110A62, (q31_t)0x88054677, (q31_t)0x2C98FBBA,
+	(q31_t)0x877B7BEC, (q31_t)0x2B1F34EB, (q31_t)0x86F656D3,
+	(q31_t)0x29A3C484, (q31_t)0x8675DC4E, (q31_t)0x2826B928,
+	(q31_t)0x85FA1152, (q31_t)0x26A82185, (q31_t)0x8582FAA4,
+	(q31_t)0x25280C5D, (q31_t)0x85109CDC, (q31_t)0x23A6887E,
+	(q31_t)0x84A2FC62, (q31_t)0x2223A4C5, (q31_t)0x843A1D70,
+	(q31_t)0x209F701C, (q31_t)0x83D60411, (q31_t)0x1F19F97B,
+	(q31_t)0x8376B422, (q31_t)0x1D934FE5, (q31_t)0x831C314E,
+	(q31_t)0x1C0B826A, (q31_t)0x82C67F13, (q31_t)0x1A82A025,
+	(q31_t)0x8275A0C0, (q31_t)0x18F8B83C, (q31_t)0x82299971,
+	(q31_t)0x176DD9DE, (q31_t)0x81E26C16, (q31_t)0x15E21444,
+	(q31_t)0x81A01B6C, (q31_t)0x145576B1, (q31_t)0x8162AA03,
+	(q31_t)0x12C8106E, (q31_t)0x812A1A39, (q31_t)0x1139F0CE,
+	(q31_t)0x80F66E3C, (q31_t)0x0FAB272B, (q31_t)0x80C7A80A,
+	(q31_t)0x0E1BC2E3, (q31_t)0x809DC970, (q31_t)0x0C8BD35E,
+	(q31_t)0x8078D40D, (q31_t)0x0AFB6805, (q31_t)0x8058C94C,
+	(q31_t)0x096A9049, (q31_t)0x803DAA69, (q31_t)0x07D95B9E,
+	(q31_t)0x80277872, (q31_t)0x0647D97C, (q31_t)0x80163440,
+	(q31_t)0x04B6195D, (q31_t)0x8009DE7D, (q31_t)0x03242ABF,
+	(q31_t)0x800277A5, (q31_t)0x01921D1F, (q31_t)0x80000000,
+	(q31_t)0x00000000, (q31_t)0x800277A5, (q31_t)0xFE6DE2E0,
+	(q31_t)0x8009DE7D, (q31_t)0xFCDBD541, (q31_t)0x80163440,
+	(q31_t)0xFB49E6A2, (q31_t)0x80277872, (q31_t)0xF9B82683,
+	(q31_t)0x803DAA69, (q31_t)0xF826A461, (q31_t)0x8058C94C,
+	(q31_t)0xF6956FB6, (q31_t)0x8078D40D, (q31_t)0xF50497FA,
+	(q31_t)0x809DC970, (q31_t)0xF3742CA1, (q31_t)0x80C7A80A,
+	(q31_t)0xF1E43D1C, (q31_t)0x80F66E3C, (q31_t)0xF054D8D4,
+	(q31_t)0x812A1A39, (q31_t)0xEEC60F31, (q31_t)0x8162AA03,
+	(q31_t)0xED37EF91, (q31_t)0x81A01B6C, (q31_t)0xEBAA894E,
+	(q31_t)0x81E26C16, (q31_t)0xEA1DEBBB, (q31_t)0x82299971,
+	(q31_t)0xE8922621, (q31_t)0x8275A0C0, (q31_t)0xE70747C3,
+	(q31_t)0x82C67F13, (q31_t)0xE57D5FDA, (q31_t)0x831C314E,
+	(q31_t)0xE3F47D95, (q31_t)0x8376B422, (q31_t)0xE26CB01A,
+	(q31_t)0x83D60411, (q31_t)0xE0E60684, (q31_t)0x843A1D70,
+	(q31_t)0xDF608FE3, (q31_t)0x84A2FC62, (q31_t)0xDDDC5B3A,
+	(q31_t)0x85109CDC, (q31_t)0xDC597781, (q31_t)0x8582FAA4,
+	(q31_t)0xDAD7F3A2, (q31_t)0x85FA1152, (q31_t)0xD957DE7A,
+	(q31_t)0x8675DC4E, (q31_t)0xD7D946D7, (q31_t)0x86F656D3,
+	(q31_t)0xD65C3B7B, (q31_t)0x877B7BEC, (q31_t)0xD4E0CB14,
+	(q31_t)0x88054677, (q31_t)0xD3670445, (q31_t)0x8893B124,
+	(q31_t)0xD1EEF59E, (q31_t)0x8926B677, (q31_t)0xD078AD9D,
+	(q31_t)0x89BE50C3, (q31_t)0xCF043AB2, (q31_t)0x8A5A7A30,
+	(q31_t)0xCD91AB38, (q31_t)0x8AFB2CBA, (q31_t)0xCC210D78,
+	(q31_t)0x8BA0622F, (q31_t)0xCAB26FA9, (q31_t)0x8C4A142F,
+	(q31_t)0xC945DFEC, (q31_t)0x8CF83C30, (q31_t)0xC7DB6C50,
+	(q31_t)0x8DAAD37B, (q31_t)0xC67322CD, (q31_t)0x8E61D32D,
+	(q31_t)0xC50D1148, (q31_t)0x8F1D343A, (q31_t)0xC3A9458F,
+	(q31_t)0x8FDCEF66, (q31_t)0xC247CD5A, (q31_t)0x90A0FD4E,
+	(q31_t)0xC0E8B648, (q31_t)0x91695663, (q31_t)0xBF8C0DE2,
+	(q31_t)0x9235F2EB, (q31_t)0xBE31E19B, (q31_t)0x9306CB04,
+	(q31_t)0xBCDA3ECA, (q31_t)0x93DBD69F, (q31_t)0xBB8532AF,
+	(q31_t)0x94B50D87, (q31_t)0xBA32CA70, (q31_t)0x9592675B,
+	(q31_t)0xB8E31319, (q31_t)0x9673DB94, (q31_t)0xB796199B,
+	(q31_t)0x9759617E, (q31_t)0xB64BEACC, (q31_t)0x9842F043,
+	(q31_t)0xB5049368, (q31_t)0x99307EE0, (q31_t)0xB3C0200C,
+	(q31_t)0x9A22042C, (q31_t)0xB27E9D3B, (q31_t)0x9B1776D9,
+	(q31_t)0xB140175B, (q31_t)0x9C10CD70, (q31_t)0xB0049AB2,
+	(q31_t)0x9D0DFE53, (q31_t)0xAECC336B, (q31_t)0x9E0EFFC1,
+	(q31_t)0xAD96ED91, (q31_t)0x9F13C7D0, (q31_t)0xAC64D510,
+	(q31_t)0xA01C4C72, (q31_t)0xAB35F5B5, (q31_t)0xA1288376,
+	(q31_t)0xAA0A5B2D, (q31_t)0xA2386283, (q31_t)0xA8E21106,
+	(q31_t)0xA34BDF20, (q31_t)0xA7BD22AB, (q31_t)0xA462EEAC,
+	(q31_t)0xA69B9B68, (q31_t)0xA57D8666, (q31_t)0xA57D8666,
+	(q31_t)0xA69B9B68, (q31_t)0xA462EEAC, (q31_t)0xA7BD22AB,
+	(q31_t)0xA34BDF20, (q31_t)0xA8E21106, (q31_t)0xA2386283,
+	(q31_t)0xAA0A5B2D, (q31_t)0xA1288376, (q31_t)0xAB35F5B5,
+	(q31_t)0xA01C4C72, (q31_t)0xAC64D510, (q31_t)0x9F13C7D0,
+	(q31_t)0xAD96ED91, (q31_t)0x9E0EFFC1, (q31_t)0xAECC336B,
+	(q31_t)0x9D0DFE53, (q31_t)0xB0049AB2, (q31_t)0x9C10CD70,
+	(q31_t)0xB140175B, (q31_t)0x9B1776D9, (q31_t)0xB27E9D3B,
+	(q31_t)0x9A22042C, (q31_t)0xB3C0200C, (q31_t)0x99307EE0,
+	(q31_t)0xB5049368, (q31_t)0x9842F043, (q31_t)0xB64BEACC,
+	(q31_t)0x9759617E, (q31_t)0xB796199B, (q31_t)0x9673DB94,
+	(q31_t)0xB8E31319, (q31_t)0x9592675B, (q31_t)0xBA32CA70,
+	(q31_t)0x94B50D87, (q31_t)0xBB8532AF, (q31_t)0x93DBD69F,
+	(q31_t)0xBCDA3ECA, (q31_t)0x9306CB04, (q31_t)0xBE31E19B,
+	(q31_t)0x9235F2EB, (q31_t)0xBF8C0DE2, (q31_t)0x91695663,
+	(q31_t)0xC0E8B648, (q31_t)0x90A0FD4E, (q31_t)0xC247CD5A,
+	(q31_t)0x8FDCEF66, (q31_t)0xC3A9458F, (q31_t)0x8F1D343A,
+	(q31_t)0xC50D1148, (q31_t)0x8E61D32D, (q31_t)0xC67322CD,
+	(q31_t)0x8DAAD37B, (q31_t)0xC7DB6C50, (q31_t)0x8CF83C30,
+	(q31_t)0xC945DFEC, (q31_t)0x8C4A142F, (q31_t)0xCAB26FA9,
+	(q31_t)0x8BA0622F, (q31_t)0xCC210D78, (q31_t)0x8AFB2CBA,
+	(q31_t)0xCD91AB38, (q31_t)0x8A5A7A30, (q31_t)0xCF043AB2,
+	(q31_t)0x89BE50C3, (q31_t)0xD078AD9D, (q31_t)0x8926B677,
+	(q31_t)0xD1EEF59E, (q31_t)0x8893B124, (q31_t)0xD3670445,
+	(q31_t)0x88054677, (q31_t)0xD4E0CB14, (q31_t)0x877B7BEC,
+	(q31_t)0xD65C3B7B, (q31_t)0x86F656D3, (q31_t)0xD7D946D7,
+	(q31_t)0x8675DC4E, (q31_t)0xD957DE7A, (q31_t)0x85FA1152,
+	(q31_t)0xDAD7F3A2, (q31_t)0x8582FAA4, (q31_t)0xDC597781,
+	(q31_t)0x85109CDC, (q31_t)0xDDDC5B3A, (q31_t)0x84A2FC62,
+	(q31_t)0xDF608FE3, (q31_t)0x843A1D70, (q31_t)0xE0E60684,
+	(q31_t)0x83D60411, (q31_t)0xE26CB01A, (q31_t)0x8376B422,
+	(q31_t)0xE3F47D95, (q31_t)0x831C314E, (q31_t)0xE57D5FDA,
+	(q31_t)0x82C67F13, (q31_t)0xE70747C3, (q31_t)0x8275A0C0,
+	(q31_t)0xE8922621, (q31_t)0x82299971, (q31_t)0xEA1DEBBB,
+	(q31_t)0x81E26C16, (q31_t)0xEBAA894E, (q31_t)0x81A01B6C,
+	(q31_t)0xED37EF91, (q31_t)0x8162AA03, (q31_t)0xEEC60F31,
+	(q31_t)0x812A1A39, (q31_t)0xF054D8D4, (q31_t)0x80F66E3C,
+	(q31_t)0xF1E43D1C, (q31_t)0x80C7A80A, (q31_t)0xF3742CA1,
+	(q31_t)0x809DC970, (q31_t)0xF50497FA, (q31_t)0x8078D40D,
+	(q31_t)0xF6956FB6, (q31_t)0x8058C94C, (q31_t)0xF826A461,
+	(q31_t)0x803DAA69, (q31_t)0xF9B82683, (q31_t)0x80277872,
+	(q31_t)0xFB49E6A2, (q31_t)0x80163440, (q31_t)0xFCDBD541,
+	(q31_t)0x8009DE7D, (q31_t)0xFE6DE2E0, (q31_t)0x800277A5
+};
+
+/**
+* \par
+* Example code for Q31 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefQ31[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefQ31[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 1024	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to Q31(Fixed point 1.31):
+*	round(twiddleCoefQ31(i) * pow(2, 31))
+*
+*/
+const q31_t twiddleCoef_1024_q31[1536] = {
+	(q31_t)0x7FFFFFFF, (q31_t)0x00000000, (q31_t)0x7FFF6216,
+	(q31_t)0x00C90F88, (q31_t)0x7FFD885A, (q31_t)0x01921D1F,
+	(q31_t)0x7FFA72D1, (q31_t)0x025B26D7, (q31_t)0x7FF62182,
+	(q31_t)0x03242ABF, (q31_t)0x7FF09477, (q31_t)0x03ED26E6,
+	(q31_t)0x7FE9CBC0, (q31_t)0x04B6195D, (q31_t)0x7FE1C76B,
+	(q31_t)0x057F0034, (q31_t)0x7FD8878D, (q31_t)0x0647D97C,
+	(q31_t)0x7FCE0C3E, (q31_t)0x0710A344, (q31_t)0x7FC25596,
+	(q31_t)0x07D95B9E, (q31_t)0x7FB563B2, (q31_t)0x08A2009A,
+	(q31_t)0x7FA736B4, (q31_t)0x096A9049, (q31_t)0x7F97CEBC,
+	(q31_t)0x0A3308BC, (q31_t)0x7F872BF3, (q31_t)0x0AFB6805,
+	(q31_t)0x7F754E7F, (q31_t)0x0BC3AC35, (q31_t)0x7F62368F,
+	(q31_t)0x0C8BD35E, (q31_t)0x7F4DE450, (q31_t)0x0D53DB92,
+	(q31_t)0x7F3857F5, (q31_t)0x0E1BC2E3, (q31_t)0x7F2191B4,
+	(q31_t)0x0EE38765, (q31_t)0x7F0991C3, (q31_t)0x0FAB272B,
+	(q31_t)0x7EF0585F, (q31_t)0x1072A047, (q31_t)0x7ED5E5C6,
+	(q31_t)0x1139F0CE, (q31_t)0x7EBA3A39, (q31_t)0x120116D4,
+	(q31_t)0x7E9D55FC, (q31_t)0x12C8106E, (q31_t)0x7E7F3956,
+	(q31_t)0x138EDBB0, (q31_t)0x7E5FE493, (q31_t)0x145576B1,
+	(q31_t)0x7E3F57FE, (q31_t)0x151BDF85, (q31_t)0x7E1D93E9,
+	(q31_t)0x15E21444, (q31_t)0x7DFA98A7, (q31_t)0x16A81305,
+	(q31_t)0x7DD6668E, (q31_t)0x176DD9DE, (q31_t)0x7DB0FDF7,
+	(q31_t)0x183366E8, (q31_t)0x7D8A5F3F, (q31_t)0x18F8B83C,
+	(q31_t)0x7D628AC5, (q31_t)0x19BDCBF2, (q31_t)0x7D3980EC,
+	(q31_t)0x1A82A025, (q31_t)0x7D0F4218, (q31_t)0x1B4732EF,
+	(q31_t)0x7CE3CEB1, (q31_t)0x1C0B826A, (q31_t)0x7CB72724,
+	(q31_t)0x1CCF8CB3, (q31_t)0x7C894BDD, (q31_t)0x1D934FE5,
+	(q31_t)0x7C5A3D4F, (q31_t)0x1E56CA1E, (q31_t)0x7C29FBEE,
+	(q31_t)0x1F19F97B, (q31_t)0x7BF88830, (q31_t)0x1FDCDC1A,
+	(q31_t)0x7BC5E28F, (q31_t)0x209F701C, (q31_t)0x7B920B89,
+	(q31_t)0x2161B39F, (q31_t)0x7B5D039D, (q31_t)0x2223A4C5,
+	(q31_t)0x7B26CB4F, (q31_t)0x22E541AE, (q31_t)0x7AEF6323,
+	(q31_t)0x23A6887E, (q31_t)0x7AB6CBA3, (q31_t)0x24677757,
+	(q31_t)0x7A7D055B, (q31_t)0x25280C5D, (q31_t)0x7A4210D8,
+	(q31_t)0x25E845B5, (q31_t)0x7A05EEAD, (q31_t)0x26A82185,
+	(q31_t)0x79C89F6D, (q31_t)0x27679DF4, (q31_t)0x798A23B1,
+	(q31_t)0x2826B928, (q31_t)0x794A7C11, (q31_t)0x28E5714A,
+	(q31_t)0x7909A92C, (q31_t)0x29A3C484, (q31_t)0x78C7ABA1,
+	(q31_t)0x2A61B101, (q31_t)0x78848413, (q31_t)0x2B1F34EB,
+	(q31_t)0x78403328, (q31_t)0x2BDC4E6F, (q31_t)0x77FAB988,
+	(q31_t)0x2C98FBBA, (q31_t)0x77B417DF, (q31_t)0x2D553AFB,
+	(q31_t)0x776C4EDB, (q31_t)0x2E110A62, (q31_t)0x77235F2D,
+	(q31_t)0x2ECC681E, (q31_t)0x76D94988, (q31_t)0x2F875262,
+	(q31_t)0x768E0EA5, (q31_t)0x3041C760, (q31_t)0x7641AF3C,
+	(q31_t)0x30FBC54D, (q31_t)0x75F42C0A, (q31_t)0x31B54A5D,
+	(q31_t)0x75A585CF, (q31_t)0x326E54C7, (q31_t)0x7555BD4B,
+	(q31_t)0x3326E2C2, (q31_t)0x7504D345, (q31_t)0x33DEF287,
+	(q31_t)0x74B2C883, (q31_t)0x3496824F, (q31_t)0x745F9DD1,
+	(q31_t)0x354D9056, (q31_t)0x740B53FA, (q31_t)0x36041AD9,
+	(q31_t)0x73B5EBD0, (q31_t)0x36BA2013, (q31_t)0x735F6626,
+	(q31_t)0x376F9E46, (q31_t)0x7307C3D0, (q31_t)0x382493B0,
+	(q31_t)0x72AF05A6, (q31_t)0x38D8FE93, (q31_t)0x72552C84,
+	(q31_t)0x398CDD32, (q31_t)0x71FA3948, (q31_t)0x3A402DD1,
+	(q31_t)0x719E2CD2, (q31_t)0x3AF2EEB7, (q31_t)0x71410804,
+	(q31_t)0x3BA51E29, (q31_t)0x70E2CBC6, (q31_t)0x3C56BA70,
+	(q31_t)0x708378FE, (q31_t)0x3D07C1D5, (q31_t)0x70231099,
+	(q31_t)0x3DB832A5, (q31_t)0x6FC19385, (q31_t)0x3E680B2C,
+	(q31_t)0x6F5F02B1, (q31_t)0x3F1749B7, (q31_t)0x6EFB5F12,
+	(q31_t)0x3FC5EC97, (q31_t)0x6E96A99C, (q31_t)0x4073F21D,
+	(q31_t)0x6E30E349, (q31_t)0x4121589A, (q31_t)0x6DCA0D14,
+	(q31_t)0x41CE1E64, (q31_t)0x6D6227FA, (q31_t)0x427A41D0,
+	(q31_t)0x6CF934FB, (q31_t)0x4325C135, (q31_t)0x6C8F351C,
+	(q31_t)0x43D09AEC, (q31_t)0x6C242960, (q31_t)0x447ACD50,
+	(q31_t)0x6BB812D0, (q31_t)0x452456BC, (q31_t)0x6B4AF278,
+	(q31_t)0x45CD358F, (q31_t)0x6ADCC964, (q31_t)0x46756827,
+	(q31_t)0x6A6D98A4, (q31_t)0x471CECE6, (q31_t)0x69FD614A,
+	(q31_t)0x47C3C22E, (q31_t)0x698C246C, (q31_t)0x4869E664,
+	(q31_t)0x6919E320, (q31_t)0x490F57EE, (q31_t)0x68A69E81,
+	(q31_t)0x49B41533, (q31_t)0x683257AA, (q31_t)0x4A581C9D,
+	(q31_t)0x67BD0FBC, (q31_t)0x4AFB6C97, (q31_t)0x6746C7D7,
+	(q31_t)0x4B9E038F, (q31_t)0x66CF811F, (q31_t)0x4C3FDFF3,
+	(q31_t)0x66573CBB, (q31_t)0x4CE10034, (q31_t)0x65DDFBD3,
+	(q31_t)0x4D8162C4, (q31_t)0x6563BF92, (q31_t)0x4E210617,
+	(q31_t)0x64E88926, (q31_t)0x4EBFE8A4, (q31_t)0x646C59BF,
+	(q31_t)0x4F5E08E3, (q31_t)0x63EF328F, (q31_t)0x4FFB654D,
+	(q31_t)0x637114CC, (q31_t)0x5097FC5E, (q31_t)0x62F201AC,
+	(q31_t)0x5133CC94, (q31_t)0x6271FA69, (q31_t)0x51CED46E,
+	(q31_t)0x61F1003E, (q31_t)0x5269126E, (q31_t)0x616F146B,
+	(q31_t)0x53028517, (q31_t)0x60EC3830, (q31_t)0x539B2AEF,
+	(q31_t)0x60686CCE, (q31_t)0x5433027D, (q31_t)0x5FE3B38D,
+	(q31_t)0x54CA0A4A, (q31_t)0x5F5E0DB3, (q31_t)0x556040E2,
+	(q31_t)0x5ED77C89, (q31_t)0x55F5A4D2, (q31_t)0x5E50015D,
+	(q31_t)0x568A34A9, (q31_t)0x5DC79D7C, (q31_t)0x571DEEF9,
+	(q31_t)0x5D3E5236, (q31_t)0x57B0D256, (q31_t)0x5CB420DF,
+	(q31_t)0x5842DD54, (q31_t)0x5C290ACC, (q31_t)0x58D40E8C,
+	(q31_t)0x5B9D1153, (q31_t)0x59646497, (q31_t)0x5B1035CF,
+	(q31_t)0x59F3DE12, (q31_t)0x5A82799A, (q31_t)0x5A82799A,
+	(q31_t)0x59F3DE12, (q31_t)0x5B1035CF, (q31_t)0x59646497,
+	(q31_t)0x5B9D1153, (q31_t)0x58D40E8C, (q31_t)0x5C290ACC,
+	(q31_t)0x5842DD54, (q31_t)0x5CB420DF, (q31_t)0x57B0D256,
+	(q31_t)0x5D3E5236, (q31_t)0x571DEEF9, (q31_t)0x5DC79D7C,
+	(q31_t)0x568A34A9, (q31_t)0x5E50015D, (q31_t)0x55F5A4D2,
+	(q31_t)0x5ED77C89, (q31_t)0x556040E2, (q31_t)0x5F5E0DB3,
+	(q31_t)0x54CA0A4A, (q31_t)0x5FE3B38D, (q31_t)0x5433027D,
+	(q31_t)0x60686CCE, (q31_t)0x539B2AEF, (q31_t)0x60EC3830,
+	(q31_t)0x53028517, (q31_t)0x616F146B, (q31_t)0x5269126E,
+	(q31_t)0x61F1003E, (q31_t)0x51CED46E, (q31_t)0x6271FA69,
+	(q31_t)0x5133CC94, (q31_t)0x62F201AC, (q31_t)0x5097FC5E,
+	(q31_t)0x637114CC, (q31_t)0x4FFB654D, (q31_t)0x63EF328F,
+	(q31_t)0x4F5E08E3, (q31_t)0x646C59BF, (q31_t)0x4EBFE8A4,
+	(q31_t)0x64E88926, (q31_t)0x4E210617, (q31_t)0x6563BF92,
+	(q31_t)0x4D8162C4, (q31_t)0x65DDFBD3, (q31_t)0x4CE10034,
+	(q31_t)0x66573CBB, (q31_t)0x4C3FDFF3, (q31_t)0x66CF811F,
+	(q31_t)0x4B9E038F, (q31_t)0x6746C7D7, (q31_t)0x4AFB6C97,
+	(q31_t)0x67BD0FBC, (q31_t)0x4A581C9D, (q31_t)0x683257AA,
+	(q31_t)0x49B41533, (q31_t)0x68A69E81, (q31_t)0x490F57EE,
+	(q31_t)0x6919E320, (q31_t)0x4869E664, (q31_t)0x698C246C,
+	(q31_t)0x47C3C22E, (q31_t)0x69FD614A, (q31_t)0x471CECE6,
+	(q31_t)0x6A6D98A4, (q31_t)0x46756827, (q31_t)0x6ADCC964,
+	(q31_t)0x45CD358F, (q31_t)0x6B4AF278, (q31_t)0x452456BC,
+	(q31_t)0x6BB812D0, (q31_t)0x447ACD50, (q31_t)0x6C242960,
+	(q31_t)0x43D09AEC, (q31_t)0x6C8F351C, (q31_t)0x4325C135,
+	(q31_t)0x6CF934FB, (q31_t)0x427A41D0, (q31_t)0x6D6227FA,
+	(q31_t)0x41CE1E64, (q31_t)0x6DCA0D14, (q31_t)0x4121589A,
+	(q31_t)0x6E30E349, (q31_t)0x4073F21D, (q31_t)0x6E96A99C,
+	(q31_t)0x3FC5EC97, (q31_t)0x6EFB5F12, (q31_t)0x3F1749B7,
+	(q31_t)0x6F5F02B1, (q31_t)0x3E680B2C, (q31_t)0x6FC19385,
+	(q31_t)0x3DB832A5, (q31_t)0x70231099, (q31_t)0x3D07C1D5,
+	(q31_t)0x708378FE, (q31_t)0x3C56BA70, (q31_t)0x70E2CBC6,
+	(q31_t)0x3BA51E29, (q31_t)0x71410804, (q31_t)0x3AF2EEB7,
+	(q31_t)0x719E2CD2, (q31_t)0x3A402DD1, (q31_t)0x71FA3948,
+	(q31_t)0x398CDD32, (q31_t)0x72552C84, (q31_t)0x38D8FE93,
+	(q31_t)0x72AF05A6, (q31_t)0x382493B0, (q31_t)0x7307C3D0,
+	(q31_t)0x376F9E46, (q31_t)0x735F6626, (q31_t)0x36BA2013,
+	(q31_t)0x73B5EBD0, (q31_t)0x36041AD9, (q31_t)0x740B53FA,
+	(q31_t)0x354D9056, (q31_t)0x745F9DD1, (q31_t)0x3496824F,
+	(q31_t)0x74B2C883, (q31_t)0x33DEF287, (q31_t)0x7504D345,
+	(q31_t)0x3326E2C2, (q31_t)0x7555BD4B, (q31_t)0x326E54C7,
+	(q31_t)0x75A585CF, (q31_t)0x31B54A5D, (q31_t)0x75F42C0A,
+	(q31_t)0x30FBC54D, (q31_t)0x7641AF3C, (q31_t)0x3041C760,
+	(q31_t)0x768E0EA5, (q31_t)0x2F875262, (q31_t)0x76D94988,
+	(q31_t)0x2ECC681E, (q31_t)0x77235F2D, (q31_t)0x2E110A62,
+	(q31_t)0x776C4EDB, (q31_t)0x2D553AFB, (q31_t)0x77B417DF,
+	(q31_t)0x2C98FBBA, (q31_t)0x77FAB988, (q31_t)0x2BDC4E6F,
+	(q31_t)0x78403328, (q31_t)0x2B1F34EB, (q31_t)0x78848413,
+	(q31_t)0x2A61B101, (q31_t)0x78C7ABA1, (q31_t)0x29A3C484,
+	(q31_t)0x7909A92C, (q31_t)0x28E5714A, (q31_t)0x794A7C11,
+	(q31_t)0x2826B928, (q31_t)0x798A23B1, (q31_t)0x27679DF4,
+	(q31_t)0x79C89F6D, (q31_t)0x26A82185, (q31_t)0x7A05EEAD,
+	(q31_t)0x25E845B5, (q31_t)0x7A4210D8, (q31_t)0x25280C5D,
+	(q31_t)0x7A7D055B, (q31_t)0x24677757, (q31_t)0x7AB6CBA3,
+	(q31_t)0x23A6887E, (q31_t)0x7AEF6323, (q31_t)0x22E541AE,
+	(q31_t)0x7B26CB4F, (q31_t)0x2223A4C5, (q31_t)0x7B5D039D,
+	(q31_t)0x2161B39F, (q31_t)0x7B920B89, (q31_t)0x209F701C,
+	(q31_t)0x7BC5E28F, (q31_t)0x1FDCDC1A, (q31_t)0x7BF88830,
+	(q31_t)0x1F19F97B, (q31_t)0x7C29FBEE, (q31_t)0x1E56CA1E,
+	(q31_t)0x7C5A3D4F, (q31_t)0x1D934FE5, (q31_t)0x7C894BDD,
+	(q31_t)0x1CCF8CB3, (q31_t)0x7CB72724, (q31_t)0x1C0B826A,
+	(q31_t)0x7CE3CEB1, (q31_t)0x1B4732EF, (q31_t)0x7D0F4218,
+	(q31_t)0x1A82A025, (q31_t)0x7D3980EC, (q31_t)0x19BDCBF2,
+	(q31_t)0x7D628AC5, (q31_t)0x18F8B83C, (q31_t)0x7D8A5F3F,
+	(q31_t)0x183366E8, (q31_t)0x7DB0FDF7, (q31_t)0x176DD9DE,
+	(q31_t)0x7DD6668E, (q31_t)0x16A81305, (q31_t)0x7DFA98A7,
+	(q31_t)0x15E21444, (q31_t)0x7E1D93E9, (q31_t)0x151BDF85,
+	(q31_t)0x7E3F57FE, (q31_t)0x145576B1, (q31_t)0x7E5FE493,
+	(q31_t)0x138EDBB0, (q31_t)0x7E7F3956, (q31_t)0x12C8106E,
+	(q31_t)0x7E9D55FC, (q31_t)0x120116D4, (q31_t)0x7EBA3A39,
+	(q31_t)0x1139F0CE, (q31_t)0x7ED5E5C6, (q31_t)0x1072A047,
+	(q31_t)0x7EF0585F, (q31_t)0x0FAB272B, (q31_t)0x7F0991C3,
+	(q31_t)0x0EE38765, (q31_t)0x7F2191B4, (q31_t)0x0E1BC2E3,
+	(q31_t)0x7F3857F5, (q31_t)0x0D53DB92, (q31_t)0x7F4DE450,
+	(q31_t)0x0C8BD35E, (q31_t)0x7F62368F, (q31_t)0x0BC3AC35,
+	(q31_t)0x7F754E7F, (q31_t)0x0AFB6805, (q31_t)0x7F872BF3,
+	(q31_t)0x0A3308BC, (q31_t)0x7F97CEBC, (q31_t)0x096A9049,
+	(q31_t)0x7FA736B4, (q31_t)0x08A2009A, (q31_t)0x7FB563B2,
+	(q31_t)0x07D95B9E, (q31_t)0x7FC25596, (q31_t)0x0710A344,
+	(q31_t)0x7FCE0C3E, (q31_t)0x0647D97C, (q31_t)0x7FD8878D,
+	(q31_t)0x057F0034, (q31_t)0x7FE1C76B, (q31_t)0x04B6195D,
+	(q31_t)0x7FE9CBC0, (q31_t)0x03ED26E6, (q31_t)0x7FF09477,
+	(q31_t)0x03242ABF, (q31_t)0x7FF62182, (q31_t)0x025B26D7,
+	(q31_t)0x7FFA72D1, (q31_t)0x01921D1F, (q31_t)0x7FFD885A,
+	(q31_t)0x00C90F88, (q31_t)0x7FFF6216, (q31_t)0x00000000,
+	(q31_t)0x7FFFFFFF, (q31_t)0xFF36F078, (q31_t)0x7FFF6216,
+	(q31_t)0xFE6DE2E0, (q31_t)0x7FFD885A, (q31_t)0xFDA4D928,
+	(q31_t)0x7FFA72D1, (q31_t)0xFCDBD541, (q31_t)0x7FF62182,
+	(q31_t)0xFC12D919, (q31_t)0x7FF09477, (q31_t)0xFB49E6A2,
+	(q31_t)0x7FE9CBC0, (q31_t)0xFA80FFCB, (q31_t)0x7FE1C76B,
+	(q31_t)0xF9B82683, (q31_t)0x7FD8878D, (q31_t)0xF8EF5CBB,
+	(q31_t)0x7FCE0C3E, (q31_t)0xF826A461, (q31_t)0x7FC25596,
+	(q31_t)0xF75DFF65, (q31_t)0x7FB563B2, (q31_t)0xF6956FB6,
+	(q31_t)0x7FA736B4, (q31_t)0xF5CCF743, (q31_t)0x7F97CEBC,
+	(q31_t)0xF50497FA, (q31_t)0x7F872BF3, (q31_t)0xF43C53CA,
+	(q31_t)0x7F754E7F, (q31_t)0xF3742CA1, (q31_t)0x7F62368F,
+	(q31_t)0xF2AC246D, (q31_t)0x7F4DE450, (q31_t)0xF1E43D1C,
+	(q31_t)0x7F3857F5, (q31_t)0xF11C789A, (q31_t)0x7F2191B4,
+	(q31_t)0xF054D8D4, (q31_t)0x7F0991C3, (q31_t)0xEF8D5FB8,
+	(q31_t)0x7EF0585F, (q31_t)0xEEC60F31, (q31_t)0x7ED5E5C6,
+	(q31_t)0xEDFEE92B, (q31_t)0x7EBA3A39, (q31_t)0xED37EF91,
+	(q31_t)0x7E9D55FC, (q31_t)0xEC71244F, (q31_t)0x7E7F3956,
+	(q31_t)0xEBAA894E, (q31_t)0x7E5FE493, (q31_t)0xEAE4207A,
+	(q31_t)0x7E3F57FE, (q31_t)0xEA1DEBBB, (q31_t)0x7E1D93E9,
+	(q31_t)0xE957ECFB, (q31_t)0x7DFA98A7, (q31_t)0xE8922621,
+	(q31_t)0x7DD6668E, (q31_t)0xE7CC9917, (q31_t)0x7DB0FDF7,
+	(q31_t)0xE70747C3, (q31_t)0x7D8A5F3F, (q31_t)0xE642340D,
+	(q31_t)0x7D628AC5, (q31_t)0xE57D5FDA, (q31_t)0x7D3980EC,
+	(q31_t)0xE4B8CD10, (q31_t)0x7D0F4218, (q31_t)0xE3F47D95,
+	(q31_t)0x7CE3CEB1, (q31_t)0xE330734C, (q31_t)0x7CB72724,
+	(q31_t)0xE26CB01A, (q31_t)0x7C894BDD, (q31_t)0xE1A935E1,
+	(q31_t)0x7C5A3D4F, (q31_t)0xE0E60684, (q31_t)0x7C29FBEE,
+	(q31_t)0xE02323E5, (q31_t)0x7BF88830, (q31_t)0xDF608FE3,
+	(q31_t)0x7BC5E28F, (q31_t)0xDE9E4C60, (q31_t)0x7B920B89,
+	(q31_t)0xDDDC5B3A, (q31_t)0x7B5D039D, (q31_t)0xDD1ABE51,
+	(q31_t)0x7B26CB4F, (q31_t)0xDC597781, (q31_t)0x7AEF6323,
+	(q31_t)0xDB9888A8, (q31_t)0x7AB6CBA3, (q31_t)0xDAD7F3A2,
+	(q31_t)0x7A7D055B, (q31_t)0xDA17BA4A, (q31_t)0x7A4210D8,
+	(q31_t)0xD957DE7A, (q31_t)0x7A05EEAD, (q31_t)0xD898620C,
+	(q31_t)0x79C89F6D, (q31_t)0xD7D946D7, (q31_t)0x798A23B1,
+	(q31_t)0xD71A8EB5, (q31_t)0x794A7C11, (q31_t)0xD65C3B7B,
+	(q31_t)0x7909A92C, (q31_t)0xD59E4EFE, (q31_t)0x78C7ABA1,
+	(q31_t)0xD4E0CB14, (q31_t)0x78848413, (q31_t)0xD423B190,
+	(q31_t)0x78403328, (q31_t)0xD3670445, (q31_t)0x77FAB988,
+	(q31_t)0xD2AAC504, (q31_t)0x77B417DF, (q31_t)0xD1EEF59E,
+	(q31_t)0x776C4EDB, (q31_t)0xD13397E1, (q31_t)0x77235F2D,
+	(q31_t)0xD078AD9D, (q31_t)0x76D94988, (q31_t)0xCFBE389F,
+	(q31_t)0x768E0EA5, (q31_t)0xCF043AB2, (q31_t)0x7641AF3C,
+	(q31_t)0xCE4AB5A2, (q31_t)0x75F42C0A, (q31_t)0xCD91AB38,
+	(q31_t)0x75A585CF, (q31_t)0xCCD91D3D, (q31_t)0x7555BD4B,
+	(q31_t)0xCC210D78, (q31_t)0x7504D345, (q31_t)0xCB697DB0,
+	(q31_t)0x74B2C883, (q31_t)0xCAB26FA9, (q31_t)0x745F9DD1,
+	(q31_t)0xC9FBE527, (q31_t)0x740B53FA, (q31_t)0xC945DFEC,
+	(q31_t)0x73B5EBD0, (q31_t)0xC89061BA, (q31_t)0x735F6626,
+	(q31_t)0xC7DB6C50, (q31_t)0x7307C3D0, (q31_t)0xC727016C,
+	(q31_t)0x72AF05A6, (q31_t)0xC67322CD, (q31_t)0x72552C84,
+	(q31_t)0xC5BFD22E, (q31_t)0x71FA3948, (q31_t)0xC50D1148,
+	(q31_t)0x719E2CD2, (q31_t)0xC45AE1D7, (q31_t)0x71410804,
+	(q31_t)0xC3A9458F, (q31_t)0x70E2CBC6, (q31_t)0xC2F83E2A,
+	(q31_t)0x708378FE, (q31_t)0xC247CD5A, (q31_t)0x70231099,
+	(q31_t)0xC197F4D3, (q31_t)0x6FC19385, (q31_t)0xC0E8B648,
+	(q31_t)0x6F5F02B1, (q31_t)0xC03A1368, (q31_t)0x6EFB5F12,
+	(q31_t)0xBF8C0DE2, (q31_t)0x6E96A99C, (q31_t)0xBEDEA765,
+	(q31_t)0x6E30E349, (q31_t)0xBE31E19B, (q31_t)0x6DCA0D14,
+	(q31_t)0xBD85BE2F, (q31_t)0x6D6227FA, (q31_t)0xBCDA3ECA,
+	(q31_t)0x6CF934FB, (q31_t)0xBC2F6513, (q31_t)0x6C8F351C,
+	(q31_t)0xBB8532AF, (q31_t)0x6C242960, (q31_t)0xBADBA943,
+	(q31_t)0x6BB812D0, (q31_t)0xBA32CA70, (q31_t)0x6B4AF278,
+	(q31_t)0xB98A97D8, (q31_t)0x6ADCC964, (q31_t)0xB8E31319,
+	(q31_t)0x6A6D98A4, (q31_t)0xB83C3DD1, (q31_t)0x69FD614A,
+	(q31_t)0xB796199B, (q31_t)0x698C246C, (q31_t)0xB6F0A811,
+	(q31_t)0x6919E320, (q31_t)0xB64BEACC, (q31_t)0x68A69E81,
+	(q31_t)0xB5A7E362, (q31_t)0x683257AA, (q31_t)0xB5049368,
+	(q31_t)0x67BD0FBC, (q31_t)0xB461FC70, (q31_t)0x6746C7D7,
+	(q31_t)0xB3C0200C, (q31_t)0x66CF811F, (q31_t)0xB31EFFCB,
+	(q31_t)0x66573CBB, (q31_t)0xB27E9D3B, (q31_t)0x65DDFBD3,
+	(q31_t)0xB1DEF9E8, (q31_t)0x6563BF92, (q31_t)0xB140175B,
+	(q31_t)0x64E88926, (q31_t)0xB0A1F71C, (q31_t)0x646C59BF,
+	(q31_t)0xB0049AB2, (q31_t)0x63EF328F, (q31_t)0xAF6803A1,
+	(q31_t)0x637114CC, (q31_t)0xAECC336B, (q31_t)0x62F201AC,
+	(q31_t)0xAE312B91, (q31_t)0x6271FA69, (q31_t)0xAD96ED91,
+	(q31_t)0x61F1003E, (q31_t)0xACFD7AE8, (q31_t)0x616F146B,
+	(q31_t)0xAC64D510, (q31_t)0x60EC3830, (q31_t)0xABCCFD82,
+	(q31_t)0x60686CCE, (q31_t)0xAB35F5B5, (q31_t)0x5FE3B38D,
+	(q31_t)0xAA9FBF1D, (q31_t)0x5F5E0DB3, (q31_t)0xAA0A5B2D,
+	(q31_t)0x5ED77C89, (q31_t)0xA975CB56, (q31_t)0x5E50015D,
+	(q31_t)0xA8E21106, (q31_t)0x5DC79D7C, (q31_t)0xA84F2DA9,
+	(q31_t)0x5D3E5236, (q31_t)0xA7BD22AB, (q31_t)0x5CB420DF,
+	(q31_t)0xA72BF173, (q31_t)0x5C290ACC, (q31_t)0xA69B9B68,
+	(q31_t)0x5B9D1153, (q31_t)0xA60C21ED, (q31_t)0x5B1035CF,
+	(q31_t)0xA57D8666, (q31_t)0x5A82799A, (q31_t)0xA4EFCA31,
+	(q31_t)0x59F3DE12, (q31_t)0xA462EEAC, (q31_t)0x59646497,
+	(q31_t)0xA3D6F533, (q31_t)0x58D40E8C, (q31_t)0xA34BDF20,
+	(q31_t)0x5842DD54, (q31_t)0xA2C1ADC9, (q31_t)0x57B0D256,
+	(q31_t)0xA2386283, (q31_t)0x571DEEF9, (q31_t)0xA1AFFEA2,
+	(q31_t)0x568A34A9, (q31_t)0xA1288376, (q31_t)0x55F5A4D2,
+	(q31_t)0xA0A1F24C, (q31_t)0x556040E2, (q31_t)0xA01C4C72,
+	(q31_t)0x54CA0A4A, (q31_t)0x9F979331, (q31_t)0x5433027D,
+	(q31_t)0x9F13C7D0, (q31_t)0x539B2AEF, (q31_t)0x9E90EB94,
+	(q31_t)0x53028517, (q31_t)0x9E0EFFC1, (q31_t)0x5269126E,
+	(q31_t)0x9D8E0596, (q31_t)0x51CED46E, (q31_t)0x9D0DFE53,
+	(q31_t)0x5133CC94, (q31_t)0x9C8EEB33, (q31_t)0x5097FC5E,
+	(q31_t)0x9C10CD70, (q31_t)0x4FFB654D, (q31_t)0x9B93A640,
+	(q31_t)0x4F5E08E3, (q31_t)0x9B1776D9, (q31_t)0x4EBFE8A4,
+	(q31_t)0x9A9C406D, (q31_t)0x4E210617, (q31_t)0x9A22042C,
+	(q31_t)0x4D8162C4, (q31_t)0x99A8C344, (q31_t)0x4CE10034,
+	(q31_t)0x99307EE0, (q31_t)0x4C3FDFF3, (q31_t)0x98B93828,
+	(q31_t)0x4B9E038F, (q31_t)0x9842F043, (q31_t)0x4AFB6C97,
+	(q31_t)0x97CDA855, (q31_t)0x4A581C9D, (q31_t)0x9759617E,
+	(q31_t)0x49B41533, (q31_t)0x96E61CDF, (q31_t)0x490F57EE,
+	(q31_t)0x9673DB94, (q31_t)0x4869E664, (q31_t)0x96029EB5,
+	(q31_t)0x47C3C22E, (q31_t)0x9592675B, (q31_t)0x471CECE6,
+	(q31_t)0x9523369B, (q31_t)0x46756827, (q31_t)0x94B50D87,
+	(q31_t)0x45CD358F, (q31_t)0x9447ED2F, (q31_t)0x452456BC,
+	(q31_t)0x93DBD69F, (q31_t)0x447ACD50, (q31_t)0x9370CAE4,
+	(q31_t)0x43D09AEC, (q31_t)0x9306CB04, (q31_t)0x4325C135,
+	(q31_t)0x929DD805, (q31_t)0x427A41D0, (q31_t)0x9235F2EB,
+	(q31_t)0x41CE1E64, (q31_t)0x91CF1CB6, (q31_t)0x4121589A,
+	(q31_t)0x91695663, (q31_t)0x4073F21D, (q31_t)0x9104A0ED,
+	(q31_t)0x3FC5EC97, (q31_t)0x90A0FD4E, (q31_t)0x3F1749B7,
+	(q31_t)0x903E6C7A, (q31_t)0x3E680B2C, (q31_t)0x8FDCEF66,
+	(q31_t)0x3DB832A5, (q31_t)0x8F7C8701, (q31_t)0x3D07C1D5,
+	(q31_t)0x8F1D343A, (q31_t)0x3C56BA70, (q31_t)0x8EBEF7FB,
+	(q31_t)0x3BA51E29, (q31_t)0x8E61D32D, (q31_t)0x3AF2EEB7,
+	(q31_t)0x8E05C6B7, (q31_t)0x3A402DD1, (q31_t)0x8DAAD37B,
+	(q31_t)0x398CDD32, (q31_t)0x8D50FA59, (q31_t)0x38D8FE93,
+	(q31_t)0x8CF83C30, (q31_t)0x382493B0, (q31_t)0x8CA099D9,
+	(q31_t)0x376F9E46, (q31_t)0x8C4A142F, (q31_t)0x36BA2013,
+	(q31_t)0x8BF4AC05, (q31_t)0x36041AD9, (q31_t)0x8BA0622F,
+	(q31_t)0x354D9056, (q31_t)0x8B4D377C, (q31_t)0x3496824F,
+	(q31_t)0x8AFB2CBA, (q31_t)0x33DEF287, (q31_t)0x8AAA42B4,
+	(q31_t)0x3326E2C2, (q31_t)0x8A5A7A30, (q31_t)0x326E54C7,
+	(q31_t)0x8A0BD3F5, (q31_t)0x31B54A5D, (q31_t)0x89BE50C3,
+	(q31_t)0x30FBC54D, (q31_t)0x8971F15A, (q31_t)0x3041C760,
+	(q31_t)0x8926B677, (q31_t)0x2F875262, (q31_t)0x88DCA0D3,
+	(q31_t)0x2ECC681E, (q31_t)0x8893B124, (q31_t)0x2E110A62,
+	(q31_t)0x884BE820, (q31_t)0x2D553AFB, (q31_t)0x88054677,
+	(q31_t)0x2C98FBBA, (q31_t)0x87BFCCD7, (q31_t)0x2BDC4E6F,
+	(q31_t)0x877B7BEC, (q31_t)0x2B1F34EB, (q31_t)0x8738545E,
+	(q31_t)0x2A61B101, (q31_t)0x86F656D3, (q31_t)0x29A3C484,
+	(q31_t)0x86B583EE, (q31_t)0x28E5714A, (q31_t)0x8675DC4E,
+	(q31_t)0x2826B928, (q31_t)0x86376092, (q31_t)0x27679DF4,
+	(q31_t)0x85FA1152, (q31_t)0x26A82185, (q31_t)0x85BDEF27,
+	(q31_t)0x25E845B5, (q31_t)0x8582FAA4, (q31_t)0x25280C5D,
+	(q31_t)0x8549345C, (q31_t)0x24677757, (q31_t)0x85109CDC,
+	(q31_t)0x23A6887E, (q31_t)0x84D934B0, (q31_t)0x22E541AE,
+	(q31_t)0x84A2FC62, (q31_t)0x2223A4C5, (q31_t)0x846DF476,
+	(q31_t)0x2161B39F, (q31_t)0x843A1D70, (q31_t)0x209F701C,
+	(q31_t)0x840777CF, (q31_t)0x1FDCDC1A, (q31_t)0x83D60411,
+	(q31_t)0x1F19F97B, (q31_t)0x83A5C2B0, (q31_t)0x1E56CA1E,
+	(q31_t)0x8376B422, (q31_t)0x1D934FE5, (q31_t)0x8348D8DB,
+	(q31_t)0x1CCF8CB3, (q31_t)0x831C314E, (q31_t)0x1C0B826A,
+	(q31_t)0x82F0BDE8, (q31_t)0x1B4732EF, (q31_t)0x82C67F13,
+	(q31_t)0x1A82A025, (q31_t)0x829D753A, (q31_t)0x19BDCBF2,
+	(q31_t)0x8275A0C0, (q31_t)0x18F8B83C, (q31_t)0x824F0208,
+	(q31_t)0x183366E8, (q31_t)0x82299971, (q31_t)0x176DD9DE,
+	(q31_t)0x82056758, (q31_t)0x16A81305, (q31_t)0x81E26C16,
+	(q31_t)0x15E21444, (q31_t)0x81C0A801, (q31_t)0x151BDF85,
+	(q31_t)0x81A01B6C, (q31_t)0x145576B1, (q31_t)0x8180C6A9,
+	(q31_t)0x138EDBB0, (q31_t)0x8162AA03, (q31_t)0x12C8106E,
+	(q31_t)0x8145C5C6, (q31_t)0x120116D4, (q31_t)0x812A1A39,
+	(q31_t)0x1139F0CE, (q31_t)0x810FA7A0, (q31_t)0x1072A047,
+	(q31_t)0x80F66E3C, (q31_t)0x0FAB272B, (q31_t)0x80DE6E4C,
+	(q31_t)0x0EE38765, (q31_t)0x80C7A80A, (q31_t)0x0E1BC2E3,
+	(q31_t)0x80B21BAF, (q31_t)0x0D53DB92, (q31_t)0x809DC970,
+	(q31_t)0x0C8BD35E, (q31_t)0x808AB180, (q31_t)0x0BC3AC35,
+	(q31_t)0x8078D40D, (q31_t)0x0AFB6805, (q31_t)0x80683143,
+	(q31_t)0x0A3308BC, (q31_t)0x8058C94C, (q31_t)0x096A9049,
+	(q31_t)0x804A9C4D, (q31_t)0x08A2009A, (q31_t)0x803DAA69,
+	(q31_t)0x07D95B9E, (q31_t)0x8031F3C1, (q31_t)0x0710A344,
+	(q31_t)0x80277872, (q31_t)0x0647D97C, (q31_t)0x801E3894,
+	(q31_t)0x057F0034, (q31_t)0x80163440, (q31_t)0x04B6195D,
+	(q31_t)0x800F6B88, (q31_t)0x03ED26E6, (q31_t)0x8009DE7D,
+	(q31_t)0x03242ABF, (q31_t)0x80058D2E, (q31_t)0x025B26D7,
+	(q31_t)0x800277A5, (q31_t)0x01921D1F, (q31_t)0x80009DE9,
+	(q31_t)0x00C90F88, (q31_t)0x80000000, (q31_t)0x00000000,
+	(q31_t)0x80009DE9, (q31_t)0xFF36F078, (q31_t)0x800277A5,
+	(q31_t)0xFE6DE2E0, (q31_t)0x80058D2E, (q31_t)0xFDA4D928,
+	(q31_t)0x8009DE7D, (q31_t)0xFCDBD541, (q31_t)0x800F6B88,
+	(q31_t)0xFC12D919, (q31_t)0x80163440, (q31_t)0xFB49E6A2,
+	(q31_t)0x801E3894, (q31_t)0xFA80FFCB, (q31_t)0x80277872,
+	(q31_t)0xF9B82683, (q31_t)0x8031F3C1, (q31_t)0xF8EF5CBB,
+	(q31_t)0x803DAA69, (q31_t)0xF826A461, (q31_t)0x804A9C4D,
+	(q31_t)0xF75DFF65, (q31_t)0x8058C94C, (q31_t)0xF6956FB6,
+	(q31_t)0x80683143, (q31_t)0xF5CCF743, (q31_t)0x8078D40D,
+	(q31_t)0xF50497FA, (q31_t)0x808AB180, (q31_t)0xF43C53CA,
+	(q31_t)0x809DC970, (q31_t)0xF3742CA1, (q31_t)0x80B21BAF,
+	(q31_t)0xF2AC246D, (q31_t)0x80C7A80A, (q31_t)0xF1E43D1C,
+	(q31_t)0x80DE6E4C, (q31_t)0xF11C789A, (q31_t)0x80F66E3C,
+	(q31_t)0xF054D8D4, (q31_t)0x810FA7A0, (q31_t)0xEF8D5FB8,
+	(q31_t)0x812A1A39, (q31_t)0xEEC60F31, (q31_t)0x8145C5C6,
+	(q31_t)0xEDFEE92B, (q31_t)0x8162AA03, (q31_t)0xED37EF91,
+	(q31_t)0x8180C6A9, (q31_t)0xEC71244F, (q31_t)0x81A01B6C,
+	(q31_t)0xEBAA894E, (q31_t)0x81C0A801, (q31_t)0xEAE4207A,
+	(q31_t)0x81E26C16, (q31_t)0xEA1DEBBB, (q31_t)0x82056758,
+	(q31_t)0xE957ECFB, (q31_t)0x82299971, (q31_t)0xE8922621,
+	(q31_t)0x824F0208, (q31_t)0xE7CC9917, (q31_t)0x8275A0C0,
+	(q31_t)0xE70747C3, (q31_t)0x829D753A, (q31_t)0xE642340D,
+	(q31_t)0x82C67F13, (q31_t)0xE57D5FDA, (q31_t)0x82F0BDE8,
+	(q31_t)0xE4B8CD10, (q31_t)0x831C314E, (q31_t)0xE3F47D95,
+	(q31_t)0x8348D8DB, (q31_t)0xE330734C, (q31_t)0x8376B422,
+	(q31_t)0xE26CB01A, (q31_t)0x83A5C2B0, (q31_t)0xE1A935E1,
+	(q31_t)0x83D60411, (q31_t)0xE0E60684, (q31_t)0x840777CF,
+	(q31_t)0xE02323E5, (q31_t)0x843A1D70, (q31_t)0xDF608FE3,
+	(q31_t)0x846DF476, (q31_t)0xDE9E4C60, (q31_t)0x84A2FC62,
+	(q31_t)0xDDDC5B3A, (q31_t)0x84D934B0, (q31_t)0xDD1ABE51,
+	(q31_t)0x85109CDC, (q31_t)0xDC597781, (q31_t)0x8549345C,
+	(q31_t)0xDB9888A8, (q31_t)0x8582FAA4, (q31_t)0xDAD7F3A2,
+	(q31_t)0x85BDEF27, (q31_t)0xDA17BA4A, (q31_t)0x85FA1152,
+	(q31_t)0xD957DE7A, (q31_t)0x86376092, (q31_t)0xD898620C,
+	(q31_t)0x8675DC4E, (q31_t)0xD7D946D7, (q31_t)0x86B583EE,
+	(q31_t)0xD71A8EB5, (q31_t)0x86F656D3, (q31_t)0xD65C3B7B,
+	(q31_t)0x8738545E, (q31_t)0xD59E4EFE, (q31_t)0x877B7BEC,
+	(q31_t)0xD4E0CB14, (q31_t)0x87BFCCD7, (q31_t)0xD423B190,
+	(q31_t)0x88054677, (q31_t)0xD3670445, (q31_t)0x884BE820,
+	(q31_t)0xD2AAC504, (q31_t)0x8893B124, (q31_t)0xD1EEF59E,
+	(q31_t)0x88DCA0D3, (q31_t)0xD13397E1, (q31_t)0x8926B677,
+	(q31_t)0xD078AD9D, (q31_t)0x8971F15A, (q31_t)0xCFBE389F,
+	(q31_t)0x89BE50C3, (q31_t)0xCF043AB2, (q31_t)0x8A0BD3F5,
+	(q31_t)0xCE4AB5A2, (q31_t)0x8A5A7A30, (q31_t)0xCD91AB38,
+	(q31_t)0x8AAA42B4, (q31_t)0xCCD91D3D, (q31_t)0x8AFB2CBA,
+	(q31_t)0xCC210D78, (q31_t)0x8B4D377C, (q31_t)0xCB697DB0,
+	(q31_t)0x8BA0622F, (q31_t)0xCAB26FA9, (q31_t)0x8BF4AC05,
+	(q31_t)0xC9FBE527, (q31_t)0x8C4A142F, (q31_t)0xC945DFEC,
+	(q31_t)0x8CA099D9, (q31_t)0xC89061BA, (q31_t)0x8CF83C30,
+	(q31_t)0xC7DB6C50, (q31_t)0x8D50FA59, (q31_t)0xC727016C,
+	(q31_t)0x8DAAD37B, (q31_t)0xC67322CD, (q31_t)0x8E05C6B7,
+	(q31_t)0xC5BFD22E, (q31_t)0x8E61D32D, (q31_t)0xC50D1148,
+	(q31_t)0x8EBEF7FB, (q31_t)0xC45AE1D7, (q31_t)0x8F1D343A,
+	(q31_t)0xC3A9458F, (q31_t)0x8F7C8701, (q31_t)0xC2F83E2A,
+	(q31_t)0x8FDCEF66, (q31_t)0xC247CD5A, (q31_t)0x903E6C7A,
+	(q31_t)0xC197F4D3, (q31_t)0x90A0FD4E, (q31_t)0xC0E8B648,
+	(q31_t)0x9104A0ED, (q31_t)0xC03A1368, (q31_t)0x91695663,
+	(q31_t)0xBF8C0DE2, (q31_t)0x91CF1CB6, (q31_t)0xBEDEA765,
+	(q31_t)0x9235F2EB, (q31_t)0xBE31E19B, (q31_t)0x929DD805,
+	(q31_t)0xBD85BE2F, (q31_t)0x9306CB04, (q31_t)0xBCDA3ECA,
+	(q31_t)0x9370CAE4, (q31_t)0xBC2F6513, (q31_t)0x93DBD69F,
+	(q31_t)0xBB8532AF, (q31_t)0x9447ED2F, (q31_t)0xBADBA943,
+	(q31_t)0x94B50D87, (q31_t)0xBA32CA70, (q31_t)0x9523369B,
+	(q31_t)0xB98A97D8, (q31_t)0x9592675B, (q31_t)0xB8E31319,
+	(q31_t)0x96029EB5, (q31_t)0xB83C3DD1, (q31_t)0x9673DB94,
+	(q31_t)0xB796199B, (q31_t)0x96E61CDF, (q31_t)0xB6F0A811,
+	(q31_t)0x9759617E, (q31_t)0xB64BEACC, (q31_t)0x97CDA855,
+	(q31_t)0xB5A7E362, (q31_t)0x9842F043, (q31_t)0xB5049368,
+	(q31_t)0x98B93828, (q31_t)0xB461FC70, (q31_t)0x99307EE0,
+	(q31_t)0xB3C0200C, (q31_t)0x99A8C344, (q31_t)0xB31EFFCB,
+	(q31_t)0x9A22042C, (q31_t)0xB27E9D3B, (q31_t)0x9A9C406D,
+	(q31_t)0xB1DEF9E8, (q31_t)0x9B1776D9, (q31_t)0xB140175B,
+	(q31_t)0x9B93A640, (q31_t)0xB0A1F71C, (q31_t)0x9C10CD70,
+	(q31_t)0xB0049AB2, (q31_t)0x9C8EEB33, (q31_t)0xAF6803A1,
+	(q31_t)0x9D0DFE53, (q31_t)0xAECC336B, (q31_t)0x9D8E0596,
+	(q31_t)0xAE312B91, (q31_t)0x9E0EFFC1, (q31_t)0xAD96ED91,
+	(q31_t)0x9E90EB94, (q31_t)0xACFD7AE8, (q31_t)0x9F13C7D0,
+	(q31_t)0xAC64D510, (q31_t)0x9F979331, (q31_t)0xABCCFD82,
+	(q31_t)0xA01C4C72, (q31_t)0xAB35F5B5, (q31_t)0xA0A1F24C,
+	(q31_t)0xAA9FBF1D, (q31_t)0xA1288376, (q31_t)0xAA0A5B2D,
+	(q31_t)0xA1AFFEA2, (q31_t)0xA975CB56, (q31_t)0xA2386283,
+	(q31_t)0xA8E21106, (q31_t)0xA2C1ADC9, (q31_t)0xA84F2DA9,
+	(q31_t)0xA34BDF20, (q31_t)0xA7BD22AB, (q31_t)0xA3D6F533,
+	(q31_t)0xA72BF173, (q31_t)0xA462EEAC, (q31_t)0xA69B9B68,
+	(q31_t)0xA4EFCA31, (q31_t)0xA60C21ED, (q31_t)0xA57D8666,
+	(q31_t)0xA57D8666, (q31_t)0xA60C21ED, (q31_t)0xA4EFCA31,
+	(q31_t)0xA69B9B68, (q31_t)0xA462EEAC, (q31_t)0xA72BF173,
+	(q31_t)0xA3D6F533, (q31_t)0xA7BD22AB, (q31_t)0xA34BDF20,
+	(q31_t)0xA84F2DA9, (q31_t)0xA2C1ADC9, (q31_t)0xA8E21106,
+	(q31_t)0xA2386283, (q31_t)0xA975CB56, (q31_t)0xA1AFFEA2,
+	(q31_t)0xAA0A5B2D, (q31_t)0xA1288376, (q31_t)0xAA9FBF1D,
+	(q31_t)0xA0A1F24C, (q31_t)0xAB35F5B5, (q31_t)0xA01C4C72,
+	(q31_t)0xABCCFD82, (q31_t)0x9F979331, (q31_t)0xAC64D510,
+	(q31_t)0x9F13C7D0, (q31_t)0xACFD7AE8, (q31_t)0x9E90EB94,
+	(q31_t)0xAD96ED91, (q31_t)0x9E0EFFC1, (q31_t)0xAE312B91,
+	(q31_t)0x9D8E0596, (q31_t)0xAECC336B, (q31_t)0x9D0DFE53,
+	(q31_t)0xAF6803A1, (q31_t)0x9C8EEB33, (q31_t)0xB0049AB2,
+	(q31_t)0x9C10CD70, (q31_t)0xB0A1F71C, (q31_t)0x9B93A640,
+	(q31_t)0xB140175B, (q31_t)0x9B1776D9, (q31_t)0xB1DEF9E8,
+	(q31_t)0x9A9C406D, (q31_t)0xB27E9D3B, (q31_t)0x9A22042C,
+	(q31_t)0xB31EFFCB, (q31_t)0x99A8C344, (q31_t)0xB3C0200C,
+	(q31_t)0x99307EE0, (q31_t)0xB461FC70, (q31_t)0x98B93828,
+	(q31_t)0xB5049368, (q31_t)0x9842F043, (q31_t)0xB5A7E362,
+	(q31_t)0x97CDA855, (q31_t)0xB64BEACC, (q31_t)0x9759617E,
+	(q31_t)0xB6F0A811, (q31_t)0x96E61CDF, (q31_t)0xB796199B,
+	(q31_t)0x9673DB94, (q31_t)0xB83C3DD1, (q31_t)0x96029EB5,
+	(q31_t)0xB8E31319, (q31_t)0x9592675B, (q31_t)0xB98A97D8,
+	(q31_t)0x9523369B, (q31_t)0xBA32CA70, (q31_t)0x94B50D87,
+	(q31_t)0xBADBA943, (q31_t)0x9447ED2F, (q31_t)0xBB8532AF,
+	(q31_t)0x93DBD69F, (q31_t)0xBC2F6513, (q31_t)0x9370CAE4,
+	(q31_t)0xBCDA3ECA, (q31_t)0x9306CB04, (q31_t)0xBD85BE2F,
+	(q31_t)0x929DD805, (q31_t)0xBE31E19B, (q31_t)0x9235F2EB,
+	(q31_t)0xBEDEA765, (q31_t)0x91CF1CB6, (q31_t)0xBF8C0DE2,
+	(q31_t)0x91695663, (q31_t)0xC03A1368, (q31_t)0x9104A0ED,
+	(q31_t)0xC0E8B648, (q31_t)0x90A0FD4E, (q31_t)0xC197F4D3,
+	(q31_t)0x903E6C7A, (q31_t)0xC247CD5A, (q31_t)0x8FDCEF66,
+	(q31_t)0xC2F83E2A, (q31_t)0x8F7C8701, (q31_t)0xC3A9458F,
+	(q31_t)0x8F1D343A, (q31_t)0xC45AE1D7, (q31_t)0x8EBEF7FB,
+	(q31_t)0xC50D1148, (q31_t)0x8E61D32D, (q31_t)0xC5BFD22E,
+	(q31_t)0x8E05C6B7, (q31_t)0xC67322CD, (q31_t)0x8DAAD37B,
+	(q31_t)0xC727016C, (q31_t)0x8D50FA59, (q31_t)0xC7DB6C50,
+	(q31_t)0x8CF83C30, (q31_t)0xC89061BA, (q31_t)0x8CA099D9,
+	(q31_t)0xC945DFEC, (q31_t)0x8C4A142F, (q31_t)0xC9FBE527,
+	(q31_t)0x8BF4AC05, (q31_t)0xCAB26FA9, (q31_t)0x8BA0622F,
+	(q31_t)0xCB697DB0, (q31_t)0x8B4D377C, (q31_t)0xCC210D78,
+	(q31_t)0x8AFB2CBA, (q31_t)0xCCD91D3D, (q31_t)0x8AAA42B4,
+	(q31_t)0xCD91AB38, (q31_t)0x8A5A7A30, (q31_t)0xCE4AB5A2,
+	(q31_t)0x8A0BD3F5, (q31_t)0xCF043AB2, (q31_t)0x89BE50C3,
+	(q31_t)0xCFBE389F, (q31_t)0x8971F15A, (q31_t)0xD078AD9D,
+	(q31_t)0x8926B677, (q31_t)0xD13397E1, (q31_t)0x88DCA0D3,
+	(q31_t)0xD1EEF59E, (q31_t)0x8893B124, (q31_t)0xD2AAC504,
+	(q31_t)0x884BE820, (q31_t)0xD3670445, (q31_t)0x88054677,
+	(q31_t)0xD423B190, (q31_t)0x87BFCCD7, (q31_t)0xD4E0CB14,
+	(q31_t)0x877B7BEC, (q31_t)0xD59E4EFE, (q31_t)0x8738545E,
+	(q31_t)0xD65C3B7B, (q31_t)0x86F656D3, (q31_t)0xD71A8EB5,
+	(q31_t)0x86B583EE, (q31_t)0xD7D946D7, (q31_t)0x8675DC4E,
+	(q31_t)0xD898620C, (q31_t)0x86376092, (q31_t)0xD957DE7A,
+	(q31_t)0x85FA1152, (q31_t)0xDA17BA4A, (q31_t)0x85BDEF27,
+	(q31_t)0xDAD7F3A2, (q31_t)0x8582FAA4, (q31_t)0xDB9888A8,
+	(q31_t)0x8549345C, (q31_t)0xDC597781, (q31_t)0x85109CDC,
+	(q31_t)0xDD1ABE51, (q31_t)0x84D934B0, (q31_t)0xDDDC5B3A,
+	(q31_t)0x84A2FC62, (q31_t)0xDE9E4C60, (q31_t)0x846DF476,
+	(q31_t)0xDF608FE3, (q31_t)0x843A1D70, (q31_t)0xE02323E5,
+	(q31_t)0x840777CF, (q31_t)0xE0E60684, (q31_t)0x83D60411,
+	(q31_t)0xE1A935E1, (q31_t)0x83A5C2B0, (q31_t)0xE26CB01A,
+	(q31_t)0x8376B422, (q31_t)0xE330734C, (q31_t)0x8348D8DB,
+	(q31_t)0xE3F47D95, (q31_t)0x831C314E, (q31_t)0xE4B8CD10,
+	(q31_t)0x82F0BDE8, (q31_t)0xE57D5FDA, (q31_t)0x82C67F13,
+	(q31_t)0xE642340D, (q31_t)0x829D753A, (q31_t)0xE70747C3,
+	(q31_t)0x8275A0C0, (q31_t)0xE7CC9917, (q31_t)0x824F0208,
+	(q31_t)0xE8922621, (q31_t)0x82299971, (q31_t)0xE957ECFB,
+	(q31_t)0x82056758, (q31_t)0xEA1DEBBB, (q31_t)0x81E26C16,
+	(q31_t)0xEAE4207A, (q31_t)0x81C0A801, (q31_t)0xEBAA894E,
+	(q31_t)0x81A01B6C, (q31_t)0xEC71244F, (q31_t)0x8180C6A9,
+	(q31_t)0xED37EF91, (q31_t)0x8162AA03, (q31_t)0xEDFEE92B,
+	(q31_t)0x8145C5C6, (q31_t)0xEEC60F31, (q31_t)0x812A1A39,
+	(q31_t)0xEF8D5FB8, (q31_t)0x810FA7A0, (q31_t)0xF054D8D4,
+	(q31_t)0x80F66E3C, (q31_t)0xF11C789A, (q31_t)0x80DE6E4C,
+	(q31_t)0xF1E43D1C, (q31_t)0x80C7A80A, (q31_t)0xF2AC246D,
+	(q31_t)0x80B21BAF, (q31_t)0xF3742CA1, (q31_t)0x809DC970,
+	(q31_t)0xF43C53CA, (q31_t)0x808AB180, (q31_t)0xF50497FA,
+	(q31_t)0x8078D40D, (q31_t)0xF5CCF743, (q31_t)0x80683143,
+	(q31_t)0xF6956FB6, (q31_t)0x8058C94C, (q31_t)0xF75DFF65,
+	(q31_t)0x804A9C4D, (q31_t)0xF826A461, (q31_t)0x803DAA69,
+	(q31_t)0xF8EF5CBB, (q31_t)0x8031F3C1, (q31_t)0xF9B82683,
+	(q31_t)0x80277872, (q31_t)0xFA80FFCB, (q31_t)0x801E3894,
+	(q31_t)0xFB49E6A2, (q31_t)0x80163440, (q31_t)0xFC12D919,
+	(q31_t)0x800F6B88, (q31_t)0xFCDBD541, (q31_t)0x8009DE7D,
+	(q31_t)0xFDA4D928, (q31_t)0x80058D2E, (q31_t)0xFE6DE2E0,
+	(q31_t)0x800277A5, (q31_t)0xFF36F078, (q31_t)0x80009DE9
+};
+
+/**
+* \par
+* Example code for Q31 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefQ31[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefQ31[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 2048	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to Q31(Fixed point 1.31):
+*	round(twiddleCoefQ31(i) * pow(2, 31))
+*
+*/
+const q31_t twiddleCoef_2048_q31[3072] = {
+	(q31_t)0x7FFFFFFF, (q31_t)0x00000000, (q31_t)0x7FFFD885,
+	(q31_t)0x006487E3, (q31_t)0x7FFF6216, (q31_t)0x00C90F88,
+	(q31_t)0x7FFE9CB2, (q31_t)0x012D96B0, (q31_t)0x7FFD885A,
+	(q31_t)0x01921D1F, (q31_t)0x7FFC250F, (q31_t)0x01F6A296,
+	(q31_t)0x7FFA72D1, (q31_t)0x025B26D7, (q31_t)0x7FF871A1,
+	(q31_t)0x02BFA9A4, (q31_t)0x7FF62182, (q31_t)0x03242ABF,
+	(q31_t)0x7FF38273, (q31_t)0x0388A9E9, (q31_t)0x7FF09477,
+	(q31_t)0x03ED26E6, (q31_t)0x7FED5790, (q31_t)0x0451A176,
+	(q31_t)0x7FE9CBC0, (q31_t)0x04B6195D, (q31_t)0x7FE5F108,
+	(q31_t)0x051A8E5C, (q31_t)0x7FE1C76B, (q31_t)0x057F0034,
+	(q31_t)0x7FDD4EEC, (q31_t)0x05E36EA9, (q31_t)0x7FD8878D,
+	(q31_t)0x0647D97C, (q31_t)0x7FD37152, (q31_t)0x06AC406F,
+	(q31_t)0x7FCE0C3E, (q31_t)0x0710A344, (q31_t)0x7FC85853,
+	(q31_t)0x077501BE, (q31_t)0x7FC25596, (q31_t)0x07D95B9E,
+	(q31_t)0x7FBC040A, (q31_t)0x083DB0A7, (q31_t)0x7FB563B2,
+	(q31_t)0x08A2009A, (q31_t)0x7FAE7494, (q31_t)0x09064B3A,
+	(q31_t)0x7FA736B4, (q31_t)0x096A9049, (q31_t)0x7F9FAA15,
+	(q31_t)0x09CECF89, (q31_t)0x7F97CEBC, (q31_t)0x0A3308BC,
+	(q31_t)0x7F8FA4AF, (q31_t)0x0A973BA5, (q31_t)0x7F872BF3,
+	(q31_t)0x0AFB6805, (q31_t)0x7F7E648B, (q31_t)0x0B5F8D9F,
+	(q31_t)0x7F754E7F, (q31_t)0x0BC3AC35, (q31_t)0x7F6BE9D4,
+	(q31_t)0x0C27C389, (q31_t)0x7F62368F, (q31_t)0x0C8BD35E,
+	(q31_t)0x7F5834B6, (q31_t)0x0CEFDB75, (q31_t)0x7F4DE450,
+	(q31_t)0x0D53DB92, (q31_t)0x7F434563, (q31_t)0x0DB7D376,
+	(q31_t)0x7F3857F5, (q31_t)0x0E1BC2E3, (q31_t)0x7F2D1C0E,
+	(q31_t)0x0E7FA99D, (q31_t)0x7F2191B4, (q31_t)0x0EE38765,
+	(q31_t)0x7F15B8EE, (q31_t)0x0F475BFE, (q31_t)0x7F0991C3,
+	(q31_t)0x0FAB272B, (q31_t)0x7EFD1C3C, (q31_t)0x100EE8AD,
+	(q31_t)0x7EF0585F, (q31_t)0x1072A047, (q31_t)0x7EE34635,
+	(q31_t)0x10D64DBC, (q31_t)0x7ED5E5C6, (q31_t)0x1139F0CE,
+	(q31_t)0x7EC8371A, (q31_t)0x119D8940, (q31_t)0x7EBA3A39,
+	(q31_t)0x120116D4, (q31_t)0x7EABEF2C, (q31_t)0x1264994E,
+	(q31_t)0x7E9D55FC, (q31_t)0x12C8106E, (q31_t)0x7E8E6EB1,
+	(q31_t)0x132B7BF9, (q31_t)0x7E7F3956, (q31_t)0x138EDBB0,
+	(q31_t)0x7E6FB5F3, (q31_t)0x13F22F57, (q31_t)0x7E5FE493,
+	(q31_t)0x145576B1, (q31_t)0x7E4FC53E, (q31_t)0x14B8B17F,
+	(q31_t)0x7E3F57FE, (q31_t)0x151BDF85, (q31_t)0x7E2E9CDF,
+	(q31_t)0x157F0086, (q31_t)0x7E1D93E9, (q31_t)0x15E21444,
+	(q31_t)0x7E0C3D29, (q31_t)0x16451A83, (q31_t)0x7DFA98A7,
+	(q31_t)0x16A81305, (q31_t)0x7DE8A670, (q31_t)0x170AFD8D,
+	(q31_t)0x7DD6668E, (q31_t)0x176DD9DE, (q31_t)0x7DC3D90D,
+	(q31_t)0x17D0A7BB, (q31_t)0x7DB0FDF7, (q31_t)0x183366E8,
+	(q31_t)0x7D9DD55A, (q31_t)0x18961727, (q31_t)0x7D8A5F3F,
+	(q31_t)0x18F8B83C, (q31_t)0x7D769BB5, (q31_t)0x195B49E9,
+	(q31_t)0x7D628AC5, (q31_t)0x19BDCBF2, (q31_t)0x7D4E2C7E,
+	(q31_t)0x1A203E1B, (q31_t)0x7D3980EC, (q31_t)0x1A82A025,
+	(q31_t)0x7D24881A, (q31_t)0x1AE4F1D6, (q31_t)0x7D0F4218,
+	(q31_t)0x1B4732EF, (q31_t)0x7CF9AEF0, (q31_t)0x1BA96334,
+	(q31_t)0x7CE3CEB1, (q31_t)0x1C0B826A, (q31_t)0x7CCDA168,
+	(q31_t)0x1C6D9053, (q31_t)0x7CB72724, (q31_t)0x1CCF8CB3,
+	(q31_t)0x7CA05FF1, (q31_t)0x1D31774D, (q31_t)0x7C894BDD,
+	(q31_t)0x1D934FE5, (q31_t)0x7C71EAF8, (q31_t)0x1DF5163F,
+	(q31_t)0x7C5A3D4F, (q31_t)0x1E56CA1E, (q31_t)0x7C4242F2,
+	(q31_t)0x1EB86B46, (q31_t)0x7C29FBEE, (q31_t)0x1F19F97B,
+	(q31_t)0x7C116853, (q31_t)0x1F7B7480, (q31_t)0x7BF88830,
+	(q31_t)0x1FDCDC1A, (q31_t)0x7BDF5B94, (q31_t)0x203E300D,
+	(q31_t)0x7BC5E28F, (q31_t)0x209F701C, (q31_t)0x7BAC1D31,
+	(q31_t)0x21009C0B, (q31_t)0x7B920B89, (q31_t)0x2161B39F,
+	(q31_t)0x7B77ADA8, (q31_t)0x21C2B69C, (q31_t)0x7B5D039D,
+	(q31_t)0x2223A4C5, (q31_t)0x7B420D7A, (q31_t)0x22847DDF,
+	(q31_t)0x7B26CB4F, (q31_t)0x22E541AE, (q31_t)0x7B0B3D2C,
+	(q31_t)0x2345EFF7, (q31_t)0x7AEF6323, (q31_t)0x23A6887E,
+	(q31_t)0x7AD33D45, (q31_t)0x24070B07, (q31_t)0x7AB6CBA3,
+	(q31_t)0x24677757, (q31_t)0x7A9A0E4F, (q31_t)0x24C7CD32,
+	(q31_t)0x7A7D055B, (q31_t)0x25280C5D, (q31_t)0x7A5FB0D8,
+	(q31_t)0x2588349D, (q31_t)0x7A4210D8, (q31_t)0x25E845B5,
+	(q31_t)0x7A24256E, (q31_t)0x26483F6C, (q31_t)0x7A05EEAD,
+	(q31_t)0x26A82185, (q31_t)0x79E76CA6, (q31_t)0x2707EBC6,
+	(q31_t)0x79C89F6D, (q31_t)0x27679DF4, (q31_t)0x79A98715,
+	(q31_t)0x27C737D2, (q31_t)0x798A23B1, (q31_t)0x2826B928,
+	(q31_t)0x796A7554, (q31_t)0x288621B9, (q31_t)0x794A7C11,
+	(q31_t)0x28E5714A, (q31_t)0x792A37FE, (q31_t)0x2944A7A2,
+	(q31_t)0x7909A92C, (q31_t)0x29A3C484, (q31_t)0x78E8CFB1,
+	(q31_t)0x2A02C7B8, (q31_t)0x78C7ABA1, (q31_t)0x2A61B101,
+	(q31_t)0x78A63D10, (q31_t)0x2AC08025, (q31_t)0x78848413,
+	(q31_t)0x2B1F34EB, (q31_t)0x786280BF, (q31_t)0x2B7DCF17,
+	(q31_t)0x78403328, (q31_t)0x2BDC4E6F, (q31_t)0x781D9B64,
+	(q31_t)0x2C3AB2B9, (q31_t)0x77FAB988, (q31_t)0x2C98FBBA,
+	(q31_t)0x77D78DAA, (q31_t)0x2CF72939, (q31_t)0x77B417DF,
+	(q31_t)0x2D553AFB, (q31_t)0x7790583D, (q31_t)0x2DB330C7,
+	(q31_t)0x776C4EDB, (q31_t)0x2E110A62, (q31_t)0x7747FBCE,
+	(q31_t)0x2E6EC792, (q31_t)0x77235F2D, (q31_t)0x2ECC681E,
+	(q31_t)0x76FE790E, (q31_t)0x2F29EBCC, (q31_t)0x76D94988,
+	(q31_t)0x2F875262, (q31_t)0x76B3D0B3, (q31_t)0x2FE49BA6,
+	(q31_t)0x768E0EA5, (q31_t)0x3041C760, (q31_t)0x76680376,
+	(q31_t)0x309ED555, (q31_t)0x7641AF3C, (q31_t)0x30FBC54D,
+	(q31_t)0x761B1211, (q31_t)0x3158970D, (q31_t)0x75F42C0A,
+	(q31_t)0x31B54A5D, (q31_t)0x75CCFD42, (q31_t)0x3211DF03,
+	(q31_t)0x75A585CF, (q31_t)0x326E54C7, (q31_t)0x757DC5CA,
+	(q31_t)0x32CAAB6F, (q31_t)0x7555BD4B, (q31_t)0x3326E2C2,
+	(q31_t)0x752D6C6C, (q31_t)0x3382FA88, (q31_t)0x7504D345,
+	(q31_t)0x33DEF287, (q31_t)0x74DBF1EF, (q31_t)0x343ACA87,
+	(q31_t)0x74B2C883, (q31_t)0x3496824F, (q31_t)0x7489571B,
+	(q31_t)0x34F219A7, (q31_t)0x745F9DD1, (q31_t)0x354D9056,
+	(q31_t)0x74359CBD, (q31_t)0x35A8E624, (q31_t)0x740B53FA,
+	(q31_t)0x36041AD9, (q31_t)0x73E0C3A3, (q31_t)0x365F2E3B,
+	(q31_t)0x73B5EBD0, (q31_t)0x36BA2013, (q31_t)0x738ACC9E,
+	(q31_t)0x3714F02A, (q31_t)0x735F6626, (q31_t)0x376F9E46,
+	(q31_t)0x7333B883, (q31_t)0x37CA2A30, (q31_t)0x7307C3D0,
+	(q31_t)0x382493B0, (q31_t)0x72DB8828, (q31_t)0x387EDA8E,
+	(q31_t)0x72AF05A6, (q31_t)0x38D8FE93, (q31_t)0x72823C66,
+	(q31_t)0x3932FF87, (q31_t)0x72552C84, (q31_t)0x398CDD32,
+	(q31_t)0x7227D61C, (q31_t)0x39E6975D, (q31_t)0x71FA3948,
+	(q31_t)0x3A402DD1, (q31_t)0x71CC5626, (q31_t)0x3A99A057,
+	(q31_t)0x719E2CD2, (q31_t)0x3AF2EEB7, (q31_t)0x716FBD68,
+	(q31_t)0x3B4C18BA, (q31_t)0x71410804, (q31_t)0x3BA51E29,
+	(q31_t)0x71120CC5, (q31_t)0x3BFDFECD, (q31_t)0x70E2CBC6,
+	(q31_t)0x3C56BA70, (q31_t)0x70B34524, (q31_t)0x3CAF50DA,
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+	(q31_t)0x22847DDF, (q31_t)0x7B420D7A, (q31_t)0x2223A4C5,
+	(q31_t)0x7B5D039D, (q31_t)0x21C2B69C, (q31_t)0x7B77ADA8,
+	(q31_t)0x2161B39F, (q31_t)0x7B920B89, (q31_t)0x21009C0B,
+	(q31_t)0x7BAC1D31, (q31_t)0x209F701C, (q31_t)0x7BC5E28F,
+	(q31_t)0x203E300D, (q31_t)0x7BDF5B94, (q31_t)0x1FDCDC1A,
+	(q31_t)0x7BF88830, (q31_t)0x1F7B7480, (q31_t)0x7C116853,
+	(q31_t)0x1F19F97B, (q31_t)0x7C29FBEE, (q31_t)0x1EB86B46,
+	(q31_t)0x7C4242F2, (q31_t)0x1E56CA1E, (q31_t)0x7C5A3D4F,
+	(q31_t)0x1DF5163F, (q31_t)0x7C71EAF8, (q31_t)0x1D934FE5,
+	(q31_t)0x7C894BDD, (q31_t)0x1D31774D, (q31_t)0x7CA05FF1,
+	(q31_t)0x1CCF8CB3, (q31_t)0x7CB72724, (q31_t)0x1C6D9053,
+	(q31_t)0x7CCDA168, (q31_t)0x1C0B826A, (q31_t)0x7CE3CEB1,
+	(q31_t)0x1BA96334, (q31_t)0x7CF9AEF0, (q31_t)0x1B4732EF,
+	(q31_t)0x7D0F4218, (q31_t)0x1AE4F1D6, (q31_t)0x7D24881A,
+	(q31_t)0x1A82A025, (q31_t)0x7D3980EC, (q31_t)0x1A203E1B,
+	(q31_t)0x7D4E2C7E, (q31_t)0x19BDCBF2, (q31_t)0x7D628AC5,
+	(q31_t)0x195B49E9, (q31_t)0x7D769BB5, (q31_t)0x18F8B83C,
+	(q31_t)0x7D8A5F3F, (q31_t)0x18961727, (q31_t)0x7D9DD55A,
+	(q31_t)0x183366E8, (q31_t)0x7DB0FDF7, (q31_t)0x17D0A7BB,
+	(q31_t)0x7DC3D90D, (q31_t)0x176DD9DE, (q31_t)0x7DD6668E,
+	(q31_t)0x170AFD8D, (q31_t)0x7DE8A670, (q31_t)0x16A81305,
+	(q31_t)0x7DFA98A7, (q31_t)0x16451A83, (q31_t)0x7E0C3D29,
+	(q31_t)0x15E21444, (q31_t)0x7E1D93E9, (q31_t)0x157F0086,
+	(q31_t)0x7E2E9CDF, (q31_t)0x151BDF85, (q31_t)0x7E3F57FE,
+	(q31_t)0x14B8B17F, (q31_t)0x7E4FC53E, (q31_t)0x145576B1,
+	(q31_t)0x7E5FE493, (q31_t)0x13F22F57, (q31_t)0x7E6FB5F3,
+	(q31_t)0x138EDBB0, (q31_t)0x7E7F3956, (q31_t)0x132B7BF9,
+	(q31_t)0x7E8E6EB1, (q31_t)0x12C8106E, (q31_t)0x7E9D55FC,
+	(q31_t)0x1264994E, (q31_t)0x7EABEF2C, (q31_t)0x120116D4,
+	(q31_t)0x7EBA3A39, (q31_t)0x119D8940, (q31_t)0x7EC8371A,
+	(q31_t)0x1139F0CE, (q31_t)0x7ED5E5C6, (q31_t)0x10D64DBC,
+	(q31_t)0x7EE34635, (q31_t)0x1072A047, (q31_t)0x7EF0585F,
+	(q31_t)0x100EE8AD, (q31_t)0x7EFD1C3C, (q31_t)0x0FAB272B,
+	(q31_t)0x7F0991C3, (q31_t)0x0F475BFE, (q31_t)0x7F15B8EE,
+	(q31_t)0x0EE38765, (q31_t)0x7F2191B4, (q31_t)0x0E7FA99D,
+	(q31_t)0x7F2D1C0E, (q31_t)0x0E1BC2E3, (q31_t)0x7F3857F5,
+	(q31_t)0x0DB7D376, (q31_t)0x7F434563, (q31_t)0x0D53DB92,
+	(q31_t)0x7F4DE450, (q31_t)0x0CEFDB75, (q31_t)0x7F5834B6,
+	(q31_t)0x0C8BD35E, (q31_t)0x7F62368F, (q31_t)0x0C27C389,
+	(q31_t)0x7F6BE9D4, (q31_t)0x0BC3AC35, (q31_t)0x7F754E7F,
+	(q31_t)0x0B5F8D9F, (q31_t)0x7F7E648B, (q31_t)0x0AFB6805,
+	(q31_t)0x7F872BF3, (q31_t)0x0A973BA5, (q31_t)0x7F8FA4AF,
+	(q31_t)0x0A3308BC, (q31_t)0x7F97CEBC, (q31_t)0x09CECF89,
+	(q31_t)0x7F9FAA15, (q31_t)0x096A9049, (q31_t)0x7FA736B4,
+	(q31_t)0x09064B3A, (q31_t)0x7FAE7494, (q31_t)0x08A2009A,
+	(q31_t)0x7FB563B2, (q31_t)0x083DB0A7, (q31_t)0x7FBC040A,
+	(q31_t)0x07D95B9E, (q31_t)0x7FC25596, (q31_t)0x077501BE,
+	(q31_t)0x7FC85853, (q31_t)0x0710A344, (q31_t)0x7FCE0C3E,
+	(q31_t)0x06AC406F, (q31_t)0x7FD37152, (q31_t)0x0647D97C,
+	(q31_t)0x7FD8878D, (q31_t)0x05E36EA9, (q31_t)0x7FDD4EEC,
+	(q31_t)0x057F0034, (q31_t)0x7FE1C76B, (q31_t)0x051A8E5C,
+	(q31_t)0x7FE5F108, (q31_t)0x04B6195D, (q31_t)0x7FE9CBC0,
+	(q31_t)0x0451A176, (q31_t)0x7FED5790, (q31_t)0x03ED26E6,
+	(q31_t)0x7FF09477, (q31_t)0x0388A9E9, (q31_t)0x7FF38273,
+	(q31_t)0x03242ABF, (q31_t)0x7FF62182, (q31_t)0x02BFA9A4,
+	(q31_t)0x7FF871A1, (q31_t)0x025B26D7, (q31_t)0x7FFA72D1,
+	(q31_t)0x01F6A296, (q31_t)0x7FFC250F, (q31_t)0x01921D1F,
+	(q31_t)0x7FFD885A, (q31_t)0x012D96B0, (q31_t)0x7FFE9CB2,
+	(q31_t)0x00C90F88, (q31_t)0x7FFF6216, (q31_t)0x006487E3,
+	(q31_t)0x7FFFD885, (q31_t)0x00000000, (q31_t)0x7FFFFFFF,
+	(q31_t)0xFF9B781D, (q31_t)0x7FFFD885, (q31_t)0xFF36F078,
+	(q31_t)0x7FFF6216, (q31_t)0xFED2694F, (q31_t)0x7FFE9CB2,
+	(q31_t)0xFE6DE2E0, (q31_t)0x7FFD885A, (q31_t)0xFE095D69,
+	(q31_t)0x7FFC250F, (q31_t)0xFDA4D928, (q31_t)0x7FFA72D1,
+	(q31_t)0xFD40565B, (q31_t)0x7FF871A1, (q31_t)0xFCDBD541,
+	(q31_t)0x7FF62182, (q31_t)0xFC775616, (q31_t)0x7FF38273,
+	(q31_t)0xFC12D919, (q31_t)0x7FF09477, (q31_t)0xFBAE5E89,
+	(q31_t)0x7FED5790, (q31_t)0xFB49E6A2, (q31_t)0x7FE9CBC0,
+	(q31_t)0xFAE571A4, (q31_t)0x7FE5F108, (q31_t)0xFA80FFCB,
+	(q31_t)0x7FE1C76B, (q31_t)0xFA1C9156, (q31_t)0x7FDD4EEC,
+	(q31_t)0xF9B82683, (q31_t)0x7FD8878D, (q31_t)0xF953BF90,
+	(q31_t)0x7FD37152, (q31_t)0xF8EF5CBB, (q31_t)0x7FCE0C3E,
+	(q31_t)0xF88AFE41, (q31_t)0x7FC85853, (q31_t)0xF826A461,
+	(q31_t)0x7FC25596, (q31_t)0xF7C24F58, (q31_t)0x7FBC040A,
+	(q31_t)0xF75DFF65, (q31_t)0x7FB563B2, (q31_t)0xF6F9B4C5,
+	(q31_t)0x7FAE7494, (q31_t)0xF6956FB6, (q31_t)0x7FA736B4,
+	(q31_t)0xF6313076, (q31_t)0x7F9FAA15, (q31_t)0xF5CCF743,
+	(q31_t)0x7F97CEBC, (q31_t)0xF568C45A, (q31_t)0x7F8FA4AF,
+	(q31_t)0xF50497FA, (q31_t)0x7F872BF3, (q31_t)0xF4A07260,
+	(q31_t)0x7F7E648B, (q31_t)0xF43C53CA, (q31_t)0x7F754E7F,
+	(q31_t)0xF3D83C76, (q31_t)0x7F6BE9D4, (q31_t)0xF3742CA1,
+	(q31_t)0x7F62368F, (q31_t)0xF310248A, (q31_t)0x7F5834B6,
+	(q31_t)0xF2AC246D, (q31_t)0x7F4DE450, (q31_t)0xF2482C89,
+	(q31_t)0x7F434563, (q31_t)0xF1E43D1C, (q31_t)0x7F3857F5,
+	(q31_t)0xF1805662, (q31_t)0x7F2D1C0E, (q31_t)0xF11C789A,
+	(q31_t)0x7F2191B4, (q31_t)0xF0B8A401, (q31_t)0x7F15B8EE,
+	(q31_t)0xF054D8D4, (q31_t)0x7F0991C3, (q31_t)0xEFF11752,
+	(q31_t)0x7EFD1C3C, (q31_t)0xEF8D5FB8, (q31_t)0x7EF0585F,
+	(q31_t)0xEF29B243, (q31_t)0x7EE34635, (q31_t)0xEEC60F31,
+	(q31_t)0x7ED5E5C6, (q31_t)0xEE6276BF, (q31_t)0x7EC8371A,
+	(q31_t)0xEDFEE92B, (q31_t)0x7EBA3A39, (q31_t)0xED9B66B2,
+	(q31_t)0x7EABEF2C, (q31_t)0xED37EF91, (q31_t)0x7E9D55FC,
+	(q31_t)0xECD48406, (q31_t)0x7E8E6EB1, (q31_t)0xEC71244F,
+	(q31_t)0x7E7F3956, (q31_t)0xEC0DD0A8, (q31_t)0x7E6FB5F3,
+	(q31_t)0xEBAA894E, (q31_t)0x7E5FE493, (q31_t)0xEB474E80,
+	(q31_t)0x7E4FC53E, (q31_t)0xEAE4207A, (q31_t)0x7E3F57FE,
+	(q31_t)0xEA80FF79, (q31_t)0x7E2E9CDF, (q31_t)0xEA1DEBBB,
+	(q31_t)0x7E1D93E9, (q31_t)0xE9BAE57C, (q31_t)0x7E0C3D29,
+	(q31_t)0xE957ECFB, (q31_t)0x7DFA98A7, (q31_t)0xE8F50273,
+	(q31_t)0x7DE8A670, (q31_t)0xE8922621, (q31_t)0x7DD6668E,
+	(q31_t)0xE82F5844, (q31_t)0x7DC3D90D, (q31_t)0xE7CC9917,
+	(q31_t)0x7DB0FDF7, (q31_t)0xE769E8D8, (q31_t)0x7D9DD55A,
+	(q31_t)0xE70747C3, (q31_t)0x7D8A5F3F, (q31_t)0xE6A4B616,
+	(q31_t)0x7D769BB5, (q31_t)0xE642340D, (q31_t)0x7D628AC5,
+	(q31_t)0xE5DFC1E4, (q31_t)0x7D4E2C7E, (q31_t)0xE57D5FDA,
+	(q31_t)0x7D3980EC, (q31_t)0xE51B0E2A, (q31_t)0x7D24881A,
+	(q31_t)0xE4B8CD10, (q31_t)0x7D0F4218, (q31_t)0xE4569CCB,
+	(q31_t)0x7CF9AEF0, (q31_t)0xE3F47D95, (q31_t)0x7CE3CEB1,
+	(q31_t)0xE3926FAC, (q31_t)0x7CCDA168, (q31_t)0xE330734C,
+	(q31_t)0x7CB72724, (q31_t)0xE2CE88B2, (q31_t)0x7CA05FF1,
+	(q31_t)0xE26CB01A, (q31_t)0x7C894BDD, (q31_t)0xE20AE9C1,
+	(q31_t)0x7C71EAF8, (q31_t)0xE1A935E1, (q31_t)0x7C5A3D4F,
+	(q31_t)0xE14794B9, (q31_t)0x7C4242F2, (q31_t)0xE0E60684,
+	(q31_t)0x7C29FBEE, (q31_t)0xE0848B7F, (q31_t)0x7C116853,
+	(q31_t)0xE02323E5, (q31_t)0x7BF88830, (q31_t)0xDFC1CFF2,
+	(q31_t)0x7BDF5B94, (q31_t)0xDF608FE3, (q31_t)0x7BC5E28F,
+	(q31_t)0xDEFF63F4, (q31_t)0x7BAC1D31, (q31_t)0xDE9E4C60,
+	(q31_t)0x7B920B89, (q31_t)0xDE3D4963, (q31_t)0x7B77ADA8,
+	(q31_t)0xDDDC5B3A, (q31_t)0x7B5D039D, (q31_t)0xDD7B8220,
+	(q31_t)0x7B420D7A, (q31_t)0xDD1ABE51, (q31_t)0x7B26CB4F,
+	(q31_t)0xDCBA1008, (q31_t)0x7B0B3D2C, (q31_t)0xDC597781,
+	(q31_t)0x7AEF6323, (q31_t)0xDBF8F4F8, (q31_t)0x7AD33D45,
+	(q31_t)0xDB9888A8, (q31_t)0x7AB6CBA3, (q31_t)0xDB3832CD,
+	(q31_t)0x7A9A0E4F, (q31_t)0xDAD7F3A2, (q31_t)0x7A7D055B,
+	(q31_t)0xDA77CB62, (q31_t)0x7A5FB0D8, (q31_t)0xDA17BA4A,
+	(q31_t)0x7A4210D8, (q31_t)0xD9B7C093, (q31_t)0x7A24256E,
+	(q31_t)0xD957DE7A, (q31_t)0x7A05EEAD, (q31_t)0xD8F81439,
+	(q31_t)0x79E76CA6, (q31_t)0xD898620C, (q31_t)0x79C89F6D,
+	(q31_t)0xD838C82D, (q31_t)0x79A98715, (q31_t)0xD7D946D7,
+	(q31_t)0x798A23B1, (q31_t)0xD779DE46, (q31_t)0x796A7554,
+	(q31_t)0xD71A8EB5, (q31_t)0x794A7C11, (q31_t)0xD6BB585D,
+	(q31_t)0x792A37FE, (q31_t)0xD65C3B7B, (q31_t)0x7909A92C,
+	(q31_t)0xD5FD3847, (q31_t)0x78E8CFB1, (q31_t)0xD59E4EFE,
+	(q31_t)0x78C7ABA1, (q31_t)0xD53F7FDA, (q31_t)0x78A63D10,
+	(q31_t)0xD4E0CB14, (q31_t)0x78848413, (q31_t)0xD48230E8,
+	(q31_t)0x786280BF, (q31_t)0xD423B190, (q31_t)0x78403328,
+	(q31_t)0xD3C54D46, (q31_t)0x781D9B64, (q31_t)0xD3670445,
+	(q31_t)0x77FAB988, (q31_t)0xD308D6C6, (q31_t)0x77D78DAA,
+	(q31_t)0xD2AAC504, (q31_t)0x77B417DF, (q31_t)0xD24CCF38,
+	(q31_t)0x7790583D, (q31_t)0xD1EEF59E, (q31_t)0x776C4EDB,
+	(q31_t)0xD191386D, (q31_t)0x7747FBCE, (q31_t)0xD13397E1,
+	(q31_t)0x77235F2D, (q31_t)0xD0D61433, (q31_t)0x76FE790E,
+	(q31_t)0xD078AD9D, (q31_t)0x76D94988, (q31_t)0xD01B6459,
+	(q31_t)0x76B3D0B3, (q31_t)0xCFBE389F, (q31_t)0x768E0EA5,
+	(q31_t)0xCF612AAA, (q31_t)0x76680376, (q31_t)0xCF043AB2,
+	(q31_t)0x7641AF3C, (q31_t)0xCEA768F2, (q31_t)0x761B1211,
+	(q31_t)0xCE4AB5A2, (q31_t)0x75F42C0A, (q31_t)0xCDEE20FC,
+	(q31_t)0x75CCFD42, (q31_t)0xCD91AB38, (q31_t)0x75A585CF,
+	(q31_t)0xCD355490, (q31_t)0x757DC5CA, (q31_t)0xCCD91D3D,
+	(q31_t)0x7555BD4B, (q31_t)0xCC7D0577, (q31_t)0x752D6C6C,
+	(q31_t)0xCC210D78, (q31_t)0x7504D345, (q31_t)0xCBC53578,
+	(q31_t)0x74DBF1EF, (q31_t)0xCB697DB0, (q31_t)0x74B2C883,
+	(q31_t)0xCB0DE658, (q31_t)0x7489571B, (q31_t)0xCAB26FA9,
+	(q31_t)0x745F9DD1, (q31_t)0xCA5719DB, (q31_t)0x74359CBD,
+	(q31_t)0xC9FBE527, (q31_t)0x740B53FA, (q31_t)0xC9A0D1C4,
+	(q31_t)0x73E0C3A3, (q31_t)0xC945DFEC, (q31_t)0x73B5EBD0,
+	(q31_t)0xC8EB0FD6, (q31_t)0x738ACC9E, (q31_t)0xC89061BA,
+	(q31_t)0x735F6626, (q31_t)0xC835D5D0, (q31_t)0x7333B883,
+	(q31_t)0xC7DB6C50, (q31_t)0x7307C3D0, (q31_t)0xC7812571,
+	(q31_t)0x72DB8828, (q31_t)0xC727016C, (q31_t)0x72AF05A6,
+	(q31_t)0xC6CD0079, (q31_t)0x72823C66, (q31_t)0xC67322CD,
+	(q31_t)0x72552C84, (q31_t)0xC61968A2, (q31_t)0x7227D61C,
+	(q31_t)0xC5BFD22E, (q31_t)0x71FA3948, (q31_t)0xC5665FA8,
+	(q31_t)0x71CC5626, (q31_t)0xC50D1148, (q31_t)0x719E2CD2,
+	(q31_t)0xC4B3E746, (q31_t)0x716FBD68, (q31_t)0xC45AE1D7,
+	(q31_t)0x71410804, (q31_t)0xC4020132, (q31_t)0x71120CC5,
+	(q31_t)0xC3A9458F, (q31_t)0x70E2CBC6, (q31_t)0xC350AF25,
+	(q31_t)0x70B34524, (q31_t)0xC2F83E2A, (q31_t)0x708378FE,
+	(q31_t)0xC29FF2D4, (q31_t)0x70536771, (q31_t)0xC247CD5A,
+	(q31_t)0x70231099, (q31_t)0xC1EFCDF2, (q31_t)0x6FF27496,
+	(q31_t)0xC197F4D3, (q31_t)0x6FC19385, (q31_t)0xC1404233,
+	(q31_t)0x6F906D84, (q31_t)0xC0E8B648, (q31_t)0x6F5F02B1,
+	(q31_t)0xC0915147, (q31_t)0x6F2D532C, (q31_t)0xC03A1368,
+	(q31_t)0x6EFB5F12, (q31_t)0xBFE2FCDF, (q31_t)0x6EC92682,
+	(q31_t)0xBF8C0DE2, (q31_t)0x6E96A99C, (q31_t)0xBF3546A8,
+	(q31_t)0x6E63E87F, (q31_t)0xBEDEA765, (q31_t)0x6E30E349,
+	(q31_t)0xBE88304F, (q31_t)0x6DFD9A1B, (q31_t)0xBE31E19B,
+	(q31_t)0x6DCA0D14, (q31_t)0xBDDBBB7F, (q31_t)0x6D963C54,
+	(q31_t)0xBD85BE2F, (q31_t)0x6D6227FA, (q31_t)0xBD2FE9E1,
+	(q31_t)0x6D2DD027, (q31_t)0xBCDA3ECA, (q31_t)0x6CF934FB,
+	(q31_t)0xBC84BD1E, (q31_t)0x6CC45697, (q31_t)0xBC2F6513,
+	(q31_t)0x6C8F351C, (q31_t)0xBBDA36DC, (q31_t)0x6C59D0A9,
+	(q31_t)0xBB8532AF, (q31_t)0x6C242960, (q31_t)0xBB3058C0,
+	(q31_t)0x6BEE3F62, (q31_t)0xBADBA943, (q31_t)0x6BB812D0,
+	(q31_t)0xBA87246C, (q31_t)0x6B81A3CD, (q31_t)0xBA32CA70,
+	(q31_t)0x6B4AF278, (q31_t)0xB9DE9B83, (q31_t)0x6B13FEF5,
+	(q31_t)0xB98A97D8, (q31_t)0x6ADCC964, (q31_t)0xB936BFA3,
+	(q31_t)0x6AA551E8, (q31_t)0xB8E31319, (q31_t)0x6A6D98A4,
+	(q31_t)0xB88F926C, (q31_t)0x6A359DB9, (q31_t)0xB83C3DD1,
+	(q31_t)0x69FD614A, (q31_t)0xB7E9157A, (q31_t)0x69C4E37A,
+	(q31_t)0xB796199B, (q31_t)0x698C246C, (q31_t)0xB7434A67,
+	(q31_t)0x69532442, (q31_t)0xB6F0A811, (q31_t)0x6919E320,
+	(q31_t)0xB69E32CD, (q31_t)0x68E06129, (q31_t)0xB64BEACC,
+	(q31_t)0x68A69E81, (q31_t)0xB5F9D042, (q31_t)0x686C9B4B,
+	(q31_t)0xB5A7E362, (q31_t)0x683257AA, (q31_t)0xB556245E,
+	(q31_t)0x67F7D3C4, (q31_t)0xB5049368, (q31_t)0x67BD0FBC,
+	(q31_t)0xB4B330B2, (q31_t)0x67820BB6, (q31_t)0xB461FC70,
+	(q31_t)0x6746C7D7, (q31_t)0xB410F6D2, (q31_t)0x670B4443,
+	(q31_t)0xB3C0200C, (q31_t)0x66CF811F, (q31_t)0xB36F784E,
+	(q31_t)0x66937E90, (q31_t)0xB31EFFCB, (q31_t)0x66573CBB,
+	(q31_t)0xB2CEB6B5, (q31_t)0x661ABBC5, (q31_t)0xB27E9D3B,
+	(q31_t)0x65DDFBD3, (q31_t)0xB22EB392, (q31_t)0x65A0FD0B,
+	(q31_t)0xB1DEF9E8, (q31_t)0x6563BF92, (q31_t)0xB18F7070,
+	(q31_t)0x6526438E, (q31_t)0xB140175B, (q31_t)0x64E88926,
+	(q31_t)0xB0F0EEDA, (q31_t)0x64AA907F, (q31_t)0xB0A1F71C,
+	(q31_t)0x646C59BF, (q31_t)0xB0533055, (q31_t)0x642DE50D,
+	(q31_t)0xB0049AB2, (q31_t)0x63EF328F, (q31_t)0xAFB63667,
+	(q31_t)0x63B0426D, (q31_t)0xAF6803A1, (q31_t)0x637114CC,
+	(q31_t)0xAF1A0293, (q31_t)0x6331A9D4, (q31_t)0xAECC336B,
+	(q31_t)0x62F201AC, (q31_t)0xAE7E965B, (q31_t)0x62B21C7B,
+	(q31_t)0xAE312B91, (q31_t)0x6271FA69, (q31_t)0xADE3F33E,
+	(q31_t)0x62319B9D, (q31_t)0xAD96ED91, (q31_t)0x61F1003E,
+	(q31_t)0xAD4A1ABA, (q31_t)0x61B02876, (q31_t)0xACFD7AE8,
+	(q31_t)0x616F146B, (q31_t)0xACB10E4A, (q31_t)0x612DC446,
+	(q31_t)0xAC64D510, (q31_t)0x60EC3830, (q31_t)0xAC18CF68,
+	(q31_t)0x60AA704F, (q31_t)0xABCCFD82, (q31_t)0x60686CCE,
+	(q31_t)0xAB815F8C, (q31_t)0x60262DD5, (q31_t)0xAB35F5B5,
+	(q31_t)0x5FE3B38D, (q31_t)0xAAEAC02B, (q31_t)0x5FA0FE1E,
+	(q31_t)0xAA9FBF1D, (q31_t)0x5F5E0DB3, (q31_t)0xAA54F2B9,
+	(q31_t)0x5F1AE273, (q31_t)0xAA0A5B2D, (q31_t)0x5ED77C89,
+	(q31_t)0xA9BFF8A8, (q31_t)0x5E93DC1F, (q31_t)0xA975CB56,
+	(q31_t)0x5E50015D, (q31_t)0xA92BD366, (q31_t)0x5E0BEC6E,
+	(q31_t)0xA8E21106, (q31_t)0x5DC79D7C, (q31_t)0xA8988463,
+	(q31_t)0x5D8314B0, (q31_t)0xA84F2DA9, (q31_t)0x5D3E5236,
+	(q31_t)0xA8060D08, (q31_t)0x5CF95638, (q31_t)0xA7BD22AB,
+	(q31_t)0x5CB420DF, (q31_t)0xA7746EC0, (q31_t)0x5C6EB258,
+	(q31_t)0xA72BF173, (q31_t)0x5C290ACC, (q31_t)0xA6E3AAF2,
+	(q31_t)0x5BE32A67, (q31_t)0xA69B9B68, (q31_t)0x5B9D1153,
+	(q31_t)0xA653C302, (q31_t)0x5B56BFBD, (q31_t)0xA60C21ED,
+	(q31_t)0x5B1035CF, (q31_t)0xA5C4B855, (q31_t)0x5AC973B4,
+	(q31_t)0xA57D8666, (q31_t)0x5A82799A, (q31_t)0xA5368C4B,
+	(q31_t)0x5A3B47AA, (q31_t)0xA4EFCA31, (q31_t)0x59F3DE12,
+	(q31_t)0xA4A94042, (q31_t)0x59AC3CFD, (q31_t)0xA462EEAC,
+	(q31_t)0x59646497, (q31_t)0xA41CD598, (q31_t)0x591C550E,
+	(q31_t)0xA3D6F533, (q31_t)0x58D40E8C, (q31_t)0xA3914DA7,
+	(q31_t)0x588B913F, (q31_t)0xA34BDF20, (q31_t)0x5842DD54,
+	(q31_t)0xA306A9C7, (q31_t)0x57F9F2F7, (q31_t)0xA2C1ADC9,
+	(q31_t)0x57B0D256, (q31_t)0xA27CEB4F, (q31_t)0x57677B9D,
+	(q31_t)0xA2386283, (q31_t)0x571DEEF9, (q31_t)0xA1F41391,
+	(q31_t)0x56D42C99, (q31_t)0xA1AFFEA2, (q31_t)0x568A34A9,
+	(q31_t)0xA16C23E1, (q31_t)0x56400757, (q31_t)0xA1288376,
+	(q31_t)0x55F5A4D2, (q31_t)0xA0E51D8C, (q31_t)0x55AB0D46,
+	(q31_t)0xA0A1F24C, (q31_t)0x556040E2, (q31_t)0xA05F01E1,
+	(q31_t)0x55153FD4, (q31_t)0xA01C4C72, (q31_t)0x54CA0A4A,
+	(q31_t)0x9FD9D22A, (q31_t)0x547EA073, (q31_t)0x9F979331,
+	(q31_t)0x5433027D, (q31_t)0x9F558FB0, (q31_t)0x53E73097,
+	(q31_t)0x9F13C7D0, (q31_t)0x539B2AEF, (q31_t)0x9ED23BB9,
+	(q31_t)0x534EF1B5, (q31_t)0x9E90EB94, (q31_t)0x53028517,
+	(q31_t)0x9E4FD789, (q31_t)0x52B5E545, (q31_t)0x9E0EFFC1,
+	(q31_t)0x5269126E, (q31_t)0x9DCE6462, (q31_t)0x521C0CC1,
+	(q31_t)0x9D8E0596, (q31_t)0x51CED46E, (q31_t)0x9D4DE384,
+	(q31_t)0x518169A4, (q31_t)0x9D0DFE53, (q31_t)0x5133CC94,
+	(q31_t)0x9CCE562B, (q31_t)0x50E5FD6C, (q31_t)0x9C8EEB33,
+	(q31_t)0x5097FC5E, (q31_t)0x9C4FBD92, (q31_t)0x5049C999,
+	(q31_t)0x9C10CD70, (q31_t)0x4FFB654D, (q31_t)0x9BD21AF2,
+	(q31_t)0x4FACCFAB, (q31_t)0x9B93A640, (q31_t)0x4F5E08E3,
+	(q31_t)0x9B556F80, (q31_t)0x4F0F1126, (q31_t)0x9B1776D9,
+	(q31_t)0x4EBFE8A4, (q31_t)0x9AD9BC71, (q31_t)0x4E708F8F,
+	(q31_t)0x9A9C406D, (q31_t)0x4E210617, (q31_t)0x9A5F02F5,
+	(q31_t)0x4DD14C6E, (q31_t)0x9A22042C, (q31_t)0x4D8162C4,
+	(q31_t)0x99E5443A, (q31_t)0x4D31494B, (q31_t)0x99A8C344,
+	(q31_t)0x4CE10034, (q31_t)0x996C816F, (q31_t)0x4C9087B1,
+	(q31_t)0x99307EE0, (q31_t)0x4C3FDFF3, (q31_t)0x98F4BBBC,
+	(q31_t)0x4BEF092D, (q31_t)0x98B93828, (q31_t)0x4B9E038F,
+	(q31_t)0x987DF449, (q31_t)0x4B4CCF4D, (q31_t)0x9842F043,
+	(q31_t)0x4AFB6C97, (q31_t)0x98082C3B, (q31_t)0x4AA9DBA1,
+	(q31_t)0x97CDA855, (q31_t)0x4A581C9D, (q31_t)0x979364B5,
+	(q31_t)0x4A062FBD, (q31_t)0x9759617E, (q31_t)0x49B41533,
+	(q31_t)0x971F9ED6, (q31_t)0x4961CD32, (q31_t)0x96E61CDF,
+	(q31_t)0x490F57EE, (q31_t)0x96ACDBBD, (q31_t)0x48BCB598,
+	(q31_t)0x9673DB94, (q31_t)0x4869E664, (q31_t)0x963B1C85,
+	(q31_t)0x4816EA85, (q31_t)0x96029EB5, (q31_t)0x47C3C22E,
+	(q31_t)0x95CA6246, (q31_t)0x47706D93, (q31_t)0x9592675B,
+	(q31_t)0x471CECE6, (q31_t)0x955AAE17, (q31_t)0x46C9405C,
+	(q31_t)0x9523369B, (q31_t)0x46756827, (q31_t)0x94EC010B,
+	(q31_t)0x4621647C, (q31_t)0x94B50D87, (q31_t)0x45CD358F,
+	(q31_t)0x947E5C32, (q31_t)0x4578DB93, (q31_t)0x9447ED2F,
+	(q31_t)0x452456BC, (q31_t)0x9411C09D, (q31_t)0x44CFA73F,
+	(q31_t)0x93DBD69F, (q31_t)0x447ACD50, (q31_t)0x93A62F56,
+	(q31_t)0x4425C923, (q31_t)0x9370CAE4, (q31_t)0x43D09AEC,
+	(q31_t)0x933BA968, (q31_t)0x437B42E1, (q31_t)0x9306CB04,
+	(q31_t)0x4325C135, (q31_t)0x92D22FD8, (q31_t)0x42D0161E,
+	(q31_t)0x929DD805, (q31_t)0x427A41D0, (q31_t)0x9269C3AC,
+	(q31_t)0x42244480, (q31_t)0x9235F2EB, (q31_t)0x41CE1E64,
+	(q31_t)0x920265E4, (q31_t)0x4177CFB0, (q31_t)0x91CF1CB6,
+	(q31_t)0x4121589A, (q31_t)0x919C1780, (q31_t)0x40CAB957,
+	(q31_t)0x91695663, (q31_t)0x4073F21D, (q31_t)0x9136D97D,
+	(q31_t)0x401D0320, (q31_t)0x9104A0ED, (q31_t)0x3FC5EC97,
+	(q31_t)0x90D2ACD3, (q31_t)0x3F6EAEB8, (q31_t)0x90A0FD4E,
+	(q31_t)0x3F1749B7, (q31_t)0x906F927B, (q31_t)0x3EBFBDCC,
+	(q31_t)0x903E6C7A, (q31_t)0x3E680B2C, (q31_t)0x900D8B69,
+	(q31_t)0x3E10320D, (q31_t)0x8FDCEF66, (q31_t)0x3DB832A5,
+	(q31_t)0x8FAC988E, (q31_t)0x3D600D2B, (q31_t)0x8F7C8701,
+	(q31_t)0x3D07C1D5, (q31_t)0x8F4CBADB, (q31_t)0x3CAF50DA,
+	(q31_t)0x8F1D343A, (q31_t)0x3C56BA70, (q31_t)0x8EEDF33B,
+	(q31_t)0x3BFDFECD, (q31_t)0x8EBEF7FB, (q31_t)0x3BA51E29,
+	(q31_t)0x8E904298, (q31_t)0x3B4C18BA, (q31_t)0x8E61D32D,
+	(q31_t)0x3AF2EEB7, (q31_t)0x8E33A9D9, (q31_t)0x3A99A057,
+	(q31_t)0x8E05C6B7, (q31_t)0x3A402DD1, (q31_t)0x8DD829E4,
+	(q31_t)0x39E6975D, (q31_t)0x8DAAD37B, (q31_t)0x398CDD32,
+	(q31_t)0x8D7DC399, (q31_t)0x3932FF87, (q31_t)0x8D50FA59,
+	(q31_t)0x38D8FE93, (q31_t)0x8D2477D8, (q31_t)0x387EDA8E,
+	(q31_t)0x8CF83C30, (q31_t)0x382493B0, (q31_t)0x8CCC477D,
+	(q31_t)0x37CA2A30, (q31_t)0x8CA099D9, (q31_t)0x376F9E46,
+	(q31_t)0x8C753361, (q31_t)0x3714F02A, (q31_t)0x8C4A142F,
+	(q31_t)0x36BA2013, (q31_t)0x8C1F3C5C, (q31_t)0x365F2E3B,
+	(q31_t)0x8BF4AC05, (q31_t)0x36041AD9, (q31_t)0x8BCA6342,
+	(q31_t)0x35A8E624, (q31_t)0x8BA0622F, (q31_t)0x354D9056,
+	(q31_t)0x8B76A8E4, (q31_t)0x34F219A7, (q31_t)0x8B4D377C,
+	(q31_t)0x3496824F, (q31_t)0x8B240E10, (q31_t)0x343ACA87,
+	(q31_t)0x8AFB2CBA, (q31_t)0x33DEF287, (q31_t)0x8AD29393,
+	(q31_t)0x3382FA88, (q31_t)0x8AAA42B4, (q31_t)0x3326E2C2,
+	(q31_t)0x8A823A35, (q31_t)0x32CAAB6F, (q31_t)0x8A5A7A30,
+	(q31_t)0x326E54C7, (q31_t)0x8A3302BD, (q31_t)0x3211DF03,
+	(q31_t)0x8A0BD3F5, (q31_t)0x31B54A5D, (q31_t)0x89E4EDEE,
+	(q31_t)0x3158970D, (q31_t)0x89BE50C3, (q31_t)0x30FBC54D,
+	(q31_t)0x8997FC89, (q31_t)0x309ED555, (q31_t)0x8971F15A,
+	(q31_t)0x3041C760, (q31_t)0x894C2F4C, (q31_t)0x2FE49BA6,
+	(q31_t)0x8926B677, (q31_t)0x2F875262, (q31_t)0x890186F1,
+	(q31_t)0x2F29EBCC, (q31_t)0x88DCA0D3, (q31_t)0x2ECC681E,
+	(q31_t)0x88B80431, (q31_t)0x2E6EC792, (q31_t)0x8893B124,
+	(q31_t)0x2E110A62, (q31_t)0x886FA7C2, (q31_t)0x2DB330C7,
+	(q31_t)0x884BE820, (q31_t)0x2D553AFB, (q31_t)0x88287255,
+	(q31_t)0x2CF72939, (q31_t)0x88054677, (q31_t)0x2C98FBBA,
+	(q31_t)0x87E2649B, (q31_t)0x2C3AB2B9, (q31_t)0x87BFCCD7,
+	(q31_t)0x2BDC4E6F, (q31_t)0x879D7F40, (q31_t)0x2B7DCF17,
+	(q31_t)0x877B7BEC, (q31_t)0x2B1F34EB, (q31_t)0x8759C2EF,
+	(q31_t)0x2AC08025, (q31_t)0x8738545E, (q31_t)0x2A61B101,
+	(q31_t)0x8717304E, (q31_t)0x2A02C7B8, (q31_t)0x86F656D3,
+	(q31_t)0x29A3C484, (q31_t)0x86D5C802, (q31_t)0x2944A7A2,
+	(q31_t)0x86B583EE, (q31_t)0x28E5714A, (q31_t)0x86958AAB,
+	(q31_t)0x288621B9, (q31_t)0x8675DC4E, (q31_t)0x2826B928,
+	(q31_t)0x865678EA, (q31_t)0x27C737D2, (q31_t)0x86376092,
+	(q31_t)0x27679DF4, (q31_t)0x86189359, (q31_t)0x2707EBC6,
+	(q31_t)0x85FA1152, (q31_t)0x26A82185, (q31_t)0x85DBDA91,
+	(q31_t)0x26483F6C, (q31_t)0x85BDEF27, (q31_t)0x25E845B5,
+	(q31_t)0x85A04F28, (q31_t)0x2588349D, (q31_t)0x8582FAA4,
+	(q31_t)0x25280C5D, (q31_t)0x8565F1B0, (q31_t)0x24C7CD32,
+	(q31_t)0x8549345C, (q31_t)0x24677757, (q31_t)0x852CC2BA,
+	(q31_t)0x24070B07, (q31_t)0x85109CDC, (q31_t)0x23A6887E,
+	(q31_t)0x84F4C2D3, (q31_t)0x2345EFF7, (q31_t)0x84D934B0,
+	(q31_t)0x22E541AE, (q31_t)0x84BDF285, (q31_t)0x22847DDF,
+	(q31_t)0x84A2FC62, (q31_t)0x2223A4C5, (q31_t)0x84885257,
+	(q31_t)0x21C2B69C, (q31_t)0x846DF476, (q31_t)0x2161B39F,
+	(q31_t)0x8453E2CE, (q31_t)0x21009C0B, (q31_t)0x843A1D70,
+	(q31_t)0x209F701C, (q31_t)0x8420A46B, (q31_t)0x203E300D,
+	(q31_t)0x840777CF, (q31_t)0x1FDCDC1A, (q31_t)0x83EE97AC,
+	(q31_t)0x1F7B7480, (q31_t)0x83D60411, (q31_t)0x1F19F97B,
+	(q31_t)0x83BDBD0D, (q31_t)0x1EB86B46, (q31_t)0x83A5C2B0,
+	(q31_t)0x1E56CA1E, (q31_t)0x838E1507, (q31_t)0x1DF5163F,
+	(q31_t)0x8376B422, (q31_t)0x1D934FE5, (q31_t)0x835FA00E,
+	(q31_t)0x1D31774D, (q31_t)0x8348D8DB, (q31_t)0x1CCF8CB3,
+	(q31_t)0x83325E97, (q31_t)0x1C6D9053, (q31_t)0x831C314E,
+	(q31_t)0x1C0B826A, (q31_t)0x8306510F, (q31_t)0x1BA96334,
+	(q31_t)0x82F0BDE8, (q31_t)0x1B4732EF, (q31_t)0x82DB77E5,
+	(q31_t)0x1AE4F1D6, (q31_t)0x82C67F13, (q31_t)0x1A82A025,
+	(q31_t)0x82B1D381, (q31_t)0x1A203E1B, (q31_t)0x829D753A,
+	(q31_t)0x19BDCBF2, (q31_t)0x8289644A, (q31_t)0x195B49E9,
+	(q31_t)0x8275A0C0, (q31_t)0x18F8B83C, (q31_t)0x82622AA5,
+	(q31_t)0x18961727, (q31_t)0x824F0208, (q31_t)0x183366E8,
+	(q31_t)0x823C26F2, (q31_t)0x17D0A7BB, (q31_t)0x82299971,
+	(q31_t)0x176DD9DE, (q31_t)0x8217598F, (q31_t)0x170AFD8D,
+	(q31_t)0x82056758, (q31_t)0x16A81305, (q31_t)0x81F3C2D7,
+	(q31_t)0x16451A83, (q31_t)0x81E26C16, (q31_t)0x15E21444,
+	(q31_t)0x81D16320, (q31_t)0x157F0086, (q31_t)0x81C0A801,
+	(q31_t)0x151BDF85, (q31_t)0x81B03AC1, (q31_t)0x14B8B17F,
+	(q31_t)0x81A01B6C, (q31_t)0x145576B1, (q31_t)0x81904A0C,
+	(q31_t)0x13F22F57, (q31_t)0x8180C6A9, (q31_t)0x138EDBB0,
+	(q31_t)0x8171914E, (q31_t)0x132B7BF9, (q31_t)0x8162AA03,
+	(q31_t)0x12C8106E, (q31_t)0x815410D3, (q31_t)0x1264994E,
+	(q31_t)0x8145C5C6, (q31_t)0x120116D4, (q31_t)0x8137C8E6,
+	(q31_t)0x119D8940, (q31_t)0x812A1A39, (q31_t)0x1139F0CE,
+	(q31_t)0x811CB9CA, (q31_t)0x10D64DBC, (q31_t)0x810FA7A0,
+	(q31_t)0x1072A047, (q31_t)0x8102E3C3, (q31_t)0x100EE8AD,
+	(q31_t)0x80F66E3C, (q31_t)0x0FAB272B, (q31_t)0x80EA4712,
+	(q31_t)0x0F475BFE, (q31_t)0x80DE6E4C, (q31_t)0x0EE38765,
+	(q31_t)0x80D2E3F1, (q31_t)0x0E7FA99D, (q31_t)0x80C7A80A,
+	(q31_t)0x0E1BC2E3, (q31_t)0x80BCBA9C, (q31_t)0x0DB7D376,
+	(q31_t)0x80B21BAF, (q31_t)0x0D53DB92, (q31_t)0x80A7CB49,
+	(q31_t)0x0CEFDB75, (q31_t)0x809DC970, (q31_t)0x0C8BD35E,
+	(q31_t)0x8094162B, (q31_t)0x0C27C389, (q31_t)0x808AB180,
+	(q31_t)0x0BC3AC35, (q31_t)0x80819B74, (q31_t)0x0B5F8D9F,
+	(q31_t)0x8078D40D, (q31_t)0x0AFB6805, (q31_t)0x80705B50,
+	(q31_t)0x0A973BA5, (q31_t)0x80683143, (q31_t)0x0A3308BC,
+	(q31_t)0x806055EA, (q31_t)0x09CECF89, (q31_t)0x8058C94C,
+	(q31_t)0x096A9049, (q31_t)0x80518B6B, (q31_t)0x09064B3A,
+	(q31_t)0x804A9C4D, (q31_t)0x08A2009A, (q31_t)0x8043FBF6,
+	(q31_t)0x083DB0A7, (q31_t)0x803DAA69, (q31_t)0x07D95B9E,
+	(q31_t)0x8037A7AC, (q31_t)0x077501BE, (q31_t)0x8031F3C1,
+	(q31_t)0x0710A344, (q31_t)0x802C8EAD, (q31_t)0x06AC406F,
+	(q31_t)0x80277872, (q31_t)0x0647D97C, (q31_t)0x8022B113,
+	(q31_t)0x05E36EA9, (q31_t)0x801E3894, (q31_t)0x057F0034,
+	(q31_t)0x801A0EF7, (q31_t)0x051A8E5C, (q31_t)0x80163440,
+	(q31_t)0x04B6195D, (q31_t)0x8012A86F, (q31_t)0x0451A176,
+	(q31_t)0x800F6B88, (q31_t)0x03ED26E6, (q31_t)0x800C7D8C,
+	(q31_t)0x0388A9E9, (q31_t)0x8009DE7D, (q31_t)0x03242ABF,
+	(q31_t)0x80078E5E, (q31_t)0x02BFA9A4, (q31_t)0x80058D2E,
+	(q31_t)0x025B26D7, (q31_t)0x8003DAF0, (q31_t)0x01F6A296,
+	(q31_t)0x800277A5, (q31_t)0x01921D1F, (q31_t)0x8001634D,
+	(q31_t)0x012D96B0, (q31_t)0x80009DE9, (q31_t)0x00C90F88,
+	(q31_t)0x8000277A, (q31_t)0x006487E3, (q31_t)0x80000000,
+	(q31_t)0x00000000, (q31_t)0x8000277A, (q31_t)0xFF9B781D,
+	(q31_t)0x80009DE9, (q31_t)0xFF36F078, (q31_t)0x8001634D,
+	(q31_t)0xFED2694F, (q31_t)0x800277A5, (q31_t)0xFE6DE2E0,
+	(q31_t)0x8003DAF0, (q31_t)0xFE095D69, (q31_t)0x80058D2E,
+	(q31_t)0xFDA4D928, (q31_t)0x80078E5E, (q31_t)0xFD40565B,
+	(q31_t)0x8009DE7D, (q31_t)0xFCDBD541, (q31_t)0x800C7D8C,
+	(q31_t)0xFC775616, (q31_t)0x800F6B88, (q31_t)0xFC12D919,
+	(q31_t)0x8012A86F, (q31_t)0xFBAE5E89, (q31_t)0x80163440,
+	(q31_t)0xFB49E6A2, (q31_t)0x801A0EF7, (q31_t)0xFAE571A4,
+	(q31_t)0x801E3894, (q31_t)0xFA80FFCB, (q31_t)0x8022B113,
+	(q31_t)0xFA1C9156, (q31_t)0x80277872, (q31_t)0xF9B82683,
+	(q31_t)0x802C8EAD, (q31_t)0xF953BF90, (q31_t)0x8031F3C1,
+	(q31_t)0xF8EF5CBB, (q31_t)0x8037A7AC, (q31_t)0xF88AFE41,
+	(q31_t)0x803DAA69, (q31_t)0xF826A461, (q31_t)0x8043FBF6,
+	(q31_t)0xF7C24F58, (q31_t)0x804A9C4D, (q31_t)0xF75DFF65,
+	(q31_t)0x80518B6B, (q31_t)0xF6F9B4C5, (q31_t)0x8058C94C,
+	(q31_t)0xF6956FB6, (q31_t)0x806055EA, (q31_t)0xF6313076,
+	(q31_t)0x80683143, (q31_t)0xF5CCF743, (q31_t)0x80705B50,
+	(q31_t)0xF568C45A, (q31_t)0x8078D40D, (q31_t)0xF50497FA,
+	(q31_t)0x80819B74, (q31_t)0xF4A07260, (q31_t)0x808AB180,
+	(q31_t)0xF43C53CA, (q31_t)0x8094162B, (q31_t)0xF3D83C76,
+	(q31_t)0x809DC970, (q31_t)0xF3742CA1, (q31_t)0x80A7CB49,
+	(q31_t)0xF310248A, (q31_t)0x80B21BAF, (q31_t)0xF2AC246D,
+	(q31_t)0x80BCBA9C, (q31_t)0xF2482C89, (q31_t)0x80C7A80A,
+	(q31_t)0xF1E43D1C, (q31_t)0x80D2E3F1, (q31_t)0xF1805662,
+	(q31_t)0x80DE6E4C, (q31_t)0xF11C789A, (q31_t)0x80EA4712,
+	(q31_t)0xF0B8A401, (q31_t)0x80F66E3C, (q31_t)0xF054D8D4,
+	(q31_t)0x8102E3C3, (q31_t)0xEFF11752, (q31_t)0x810FA7A0,
+	(q31_t)0xEF8D5FB8, (q31_t)0x811CB9CA, (q31_t)0xEF29B243,
+	(q31_t)0x812A1A39, (q31_t)0xEEC60F31, (q31_t)0x8137C8E6,
+	(q31_t)0xEE6276BF, (q31_t)0x8145C5C6, (q31_t)0xEDFEE92B,
+	(q31_t)0x815410D3, (q31_t)0xED9B66B2, (q31_t)0x8162AA03,
+	(q31_t)0xED37EF91, (q31_t)0x8171914E, (q31_t)0xECD48406,
+	(q31_t)0x8180C6A9, (q31_t)0xEC71244F, (q31_t)0x81904A0C,
+	(q31_t)0xEC0DD0A8, (q31_t)0x81A01B6C, (q31_t)0xEBAA894E,
+	(q31_t)0x81B03AC1, (q31_t)0xEB474E80, (q31_t)0x81C0A801,
+	(q31_t)0xEAE4207A, (q31_t)0x81D16320, (q31_t)0xEA80FF79,
+	(q31_t)0x81E26C16, (q31_t)0xEA1DEBBB, (q31_t)0x81F3C2D7,
+	(q31_t)0xE9BAE57C, (q31_t)0x82056758, (q31_t)0xE957ECFB,
+	(q31_t)0x8217598F, (q31_t)0xE8F50273, (q31_t)0x82299971,
+	(q31_t)0xE8922621, (q31_t)0x823C26F2, (q31_t)0xE82F5844,
+	(q31_t)0x824F0208, (q31_t)0xE7CC9917, (q31_t)0x82622AA5,
+	(q31_t)0xE769E8D8, (q31_t)0x8275A0C0, (q31_t)0xE70747C3,
+	(q31_t)0x8289644A, (q31_t)0xE6A4B616, (q31_t)0x829D753A,
+	(q31_t)0xE642340D, (q31_t)0x82B1D381, (q31_t)0xE5DFC1E4,
+	(q31_t)0x82C67F13, (q31_t)0xE57D5FDA, (q31_t)0x82DB77E5,
+	(q31_t)0xE51B0E2A, (q31_t)0x82F0BDE8, (q31_t)0xE4B8CD10,
+	(q31_t)0x8306510F, (q31_t)0xE4569CCB, (q31_t)0x831C314E,
+	(q31_t)0xE3F47D95, (q31_t)0x83325E97, (q31_t)0xE3926FAC,
+	(q31_t)0x8348D8DB, (q31_t)0xE330734C, (q31_t)0x835FA00E,
+	(q31_t)0xE2CE88B2, (q31_t)0x8376B422, (q31_t)0xE26CB01A,
+	(q31_t)0x838E1507, (q31_t)0xE20AE9C1, (q31_t)0x83A5C2B0,
+	(q31_t)0xE1A935E1, (q31_t)0x83BDBD0D, (q31_t)0xE14794B9,
+	(q31_t)0x83D60411, (q31_t)0xE0E60684, (q31_t)0x83EE97AC,
+	(q31_t)0xE0848B7F, (q31_t)0x840777CF, (q31_t)0xE02323E5,
+	(q31_t)0x8420A46B, (q31_t)0xDFC1CFF2, (q31_t)0x843A1D70,
+	(q31_t)0xDF608FE3, (q31_t)0x8453E2CE, (q31_t)0xDEFF63F4,
+	(q31_t)0x846DF476, (q31_t)0xDE9E4C60, (q31_t)0x84885257,
+	(q31_t)0xDE3D4963, (q31_t)0x84A2FC62, (q31_t)0xDDDC5B3A,
+	(q31_t)0x84BDF285, (q31_t)0xDD7B8220, (q31_t)0x84D934B0,
+	(q31_t)0xDD1ABE51, (q31_t)0x84F4C2D3, (q31_t)0xDCBA1008,
+	(q31_t)0x85109CDC, (q31_t)0xDC597781, (q31_t)0x852CC2BA,
+	(q31_t)0xDBF8F4F8, (q31_t)0x8549345C, (q31_t)0xDB9888A8,
+	(q31_t)0x8565F1B0, (q31_t)0xDB3832CD, (q31_t)0x8582FAA4,
+	(q31_t)0xDAD7F3A2, (q31_t)0x85A04F28, (q31_t)0xDA77CB62,
+	(q31_t)0x85BDEF27, (q31_t)0xDA17BA4A, (q31_t)0x85DBDA91,
+	(q31_t)0xD9B7C093, (q31_t)0x85FA1152, (q31_t)0xD957DE7A,
+	(q31_t)0x86189359, (q31_t)0xD8F81439, (q31_t)0x86376092,
+	(q31_t)0xD898620C, (q31_t)0x865678EA, (q31_t)0xD838C82D,
+	(q31_t)0x8675DC4E, (q31_t)0xD7D946D7, (q31_t)0x86958AAB,
+	(q31_t)0xD779DE46, (q31_t)0x86B583EE, (q31_t)0xD71A8EB5,
+	(q31_t)0x86D5C802, (q31_t)0xD6BB585D, (q31_t)0x86F656D3,
+	(q31_t)0xD65C3B7B, (q31_t)0x8717304E, (q31_t)0xD5FD3847,
+	(q31_t)0x8738545E, (q31_t)0xD59E4EFE, (q31_t)0x8759C2EF,
+	(q31_t)0xD53F7FDA, (q31_t)0x877B7BEC, (q31_t)0xD4E0CB14,
+	(q31_t)0x879D7F40, (q31_t)0xD48230E8, (q31_t)0x87BFCCD7,
+	(q31_t)0xD423B190, (q31_t)0x87E2649B, (q31_t)0xD3C54D46,
+	(q31_t)0x88054677, (q31_t)0xD3670445, (q31_t)0x88287255,
+	(q31_t)0xD308D6C6, (q31_t)0x884BE820, (q31_t)0xD2AAC504,
+	(q31_t)0x886FA7C2, (q31_t)0xD24CCF38, (q31_t)0x8893B124,
+	(q31_t)0xD1EEF59E, (q31_t)0x88B80431, (q31_t)0xD191386D,
+	(q31_t)0x88DCA0D3, (q31_t)0xD13397E1, (q31_t)0x890186F1,
+	(q31_t)0xD0D61433, (q31_t)0x8926B677, (q31_t)0xD078AD9D,
+	(q31_t)0x894C2F4C, (q31_t)0xD01B6459, (q31_t)0x8971F15A,
+	(q31_t)0xCFBE389F, (q31_t)0x8997FC89, (q31_t)0xCF612AAA,
+	(q31_t)0x89BE50C3, (q31_t)0xCF043AB2, (q31_t)0x89E4EDEE,
+	(q31_t)0xCEA768F2, (q31_t)0x8A0BD3F5, (q31_t)0xCE4AB5A2,
+	(q31_t)0x8A3302BD, (q31_t)0xCDEE20FC, (q31_t)0x8A5A7A30,
+	(q31_t)0xCD91AB38, (q31_t)0x8A823A35, (q31_t)0xCD355490,
+	(q31_t)0x8AAA42B4, (q31_t)0xCCD91D3D, (q31_t)0x8AD29393,
+	(q31_t)0xCC7D0577, (q31_t)0x8AFB2CBA, (q31_t)0xCC210D78,
+	(q31_t)0x8B240E10, (q31_t)0xCBC53578, (q31_t)0x8B4D377C,
+	(q31_t)0xCB697DB0, (q31_t)0x8B76A8E4, (q31_t)0xCB0DE658,
+	(q31_t)0x8BA0622F, (q31_t)0xCAB26FA9, (q31_t)0x8BCA6342,
+	(q31_t)0xCA5719DB, (q31_t)0x8BF4AC05, (q31_t)0xC9FBE527,
+	(q31_t)0x8C1F3C5C, (q31_t)0xC9A0D1C4, (q31_t)0x8C4A142F,
+	(q31_t)0xC945DFEC, (q31_t)0x8C753361, (q31_t)0xC8EB0FD6,
+	(q31_t)0x8CA099D9, (q31_t)0xC89061BA, (q31_t)0x8CCC477D,
+	(q31_t)0xC835D5D0, (q31_t)0x8CF83C30, (q31_t)0xC7DB6C50,
+	(q31_t)0x8D2477D8, (q31_t)0xC7812571, (q31_t)0x8D50FA59,
+	(q31_t)0xC727016C, (q31_t)0x8D7DC399, (q31_t)0xC6CD0079,
+	(q31_t)0x8DAAD37B, (q31_t)0xC67322CD, (q31_t)0x8DD829E4,
+	(q31_t)0xC61968A2, (q31_t)0x8E05C6B7, (q31_t)0xC5BFD22E,
+	(q31_t)0x8E33A9D9, (q31_t)0xC5665FA8, (q31_t)0x8E61D32D,
+	(q31_t)0xC50D1148, (q31_t)0x8E904298, (q31_t)0xC4B3E746,
+	(q31_t)0x8EBEF7FB, (q31_t)0xC45AE1D7, (q31_t)0x8EEDF33B,
+	(q31_t)0xC4020132, (q31_t)0x8F1D343A, (q31_t)0xC3A9458F,
+	(q31_t)0x8F4CBADB, (q31_t)0xC350AF25, (q31_t)0x8F7C8701,
+	(q31_t)0xC2F83E2A, (q31_t)0x8FAC988E, (q31_t)0xC29FF2D4,
+	(q31_t)0x8FDCEF66, (q31_t)0xC247CD5A, (q31_t)0x900D8B69,
+	(q31_t)0xC1EFCDF2, (q31_t)0x903E6C7A, (q31_t)0xC197F4D3,
+	(q31_t)0x906F927B, (q31_t)0xC1404233, (q31_t)0x90A0FD4E,
+	(q31_t)0xC0E8B648, (q31_t)0x90D2ACD3, (q31_t)0xC0915147,
+	(q31_t)0x9104A0ED, (q31_t)0xC03A1368, (q31_t)0x9136D97D,
+	(q31_t)0xBFE2FCDF, (q31_t)0x91695663, (q31_t)0xBF8C0DE2,
+	(q31_t)0x919C1780, (q31_t)0xBF3546A8, (q31_t)0x91CF1CB6,
+	(q31_t)0xBEDEA765, (q31_t)0x920265E4, (q31_t)0xBE88304F,
+	(q31_t)0x9235F2EB, (q31_t)0xBE31E19B, (q31_t)0x9269C3AC,
+	(q31_t)0xBDDBBB7F, (q31_t)0x929DD805, (q31_t)0xBD85BE2F,
+	(q31_t)0x92D22FD8, (q31_t)0xBD2FE9E1, (q31_t)0x9306CB04,
+	(q31_t)0xBCDA3ECA, (q31_t)0x933BA968, (q31_t)0xBC84BD1E,
+	(q31_t)0x9370CAE4, (q31_t)0xBC2F6513, (q31_t)0x93A62F56,
+	(q31_t)0xBBDA36DC, (q31_t)0x93DBD69F, (q31_t)0xBB8532AF,
+	(q31_t)0x9411C09D, (q31_t)0xBB3058C0, (q31_t)0x9447ED2F,
+	(q31_t)0xBADBA943, (q31_t)0x947E5C32, (q31_t)0xBA87246C,
+	(q31_t)0x94B50D87, (q31_t)0xBA32CA70, (q31_t)0x94EC010B,
+	(q31_t)0xB9DE9B83, (q31_t)0x9523369B, (q31_t)0xB98A97D8,
+	(q31_t)0x955AAE17, (q31_t)0xB936BFA3, (q31_t)0x9592675B,
+	(q31_t)0xB8E31319, (q31_t)0x95CA6246, (q31_t)0xB88F926C,
+	(q31_t)0x96029EB5, (q31_t)0xB83C3DD1, (q31_t)0x963B1C85,
+	(q31_t)0xB7E9157A, (q31_t)0x9673DB94, (q31_t)0xB796199B,
+	(q31_t)0x96ACDBBD, (q31_t)0xB7434A67, (q31_t)0x96E61CDF,
+	(q31_t)0xB6F0A811, (q31_t)0x971F9ED6, (q31_t)0xB69E32CD,
+	(q31_t)0x9759617E, (q31_t)0xB64BEACC, (q31_t)0x979364B5,
+	(q31_t)0xB5F9D042, (q31_t)0x97CDA855, (q31_t)0xB5A7E362,
+	(q31_t)0x98082C3B, (q31_t)0xB556245E, (q31_t)0x9842F043,
+	(q31_t)0xB5049368, (q31_t)0x987DF449, (q31_t)0xB4B330B2,
+	(q31_t)0x98B93828, (q31_t)0xB461FC70, (q31_t)0x98F4BBBC,
+	(q31_t)0xB410F6D2, (q31_t)0x99307EE0, (q31_t)0xB3C0200C,
+	(q31_t)0x996C816F, (q31_t)0xB36F784E, (q31_t)0x99A8C344,
+	(q31_t)0xB31EFFCB, (q31_t)0x99E5443A, (q31_t)0xB2CEB6B5,
+	(q31_t)0x9A22042C, (q31_t)0xB27E9D3B, (q31_t)0x9A5F02F5,
+	(q31_t)0xB22EB392, (q31_t)0x9A9C406D, (q31_t)0xB1DEF9E8,
+	(q31_t)0x9AD9BC71, (q31_t)0xB18F7070, (q31_t)0x9B1776D9,
+	(q31_t)0xB140175B, (q31_t)0x9B556F80, (q31_t)0xB0F0EEDA,
+	(q31_t)0x9B93A640, (q31_t)0xB0A1F71C, (q31_t)0x9BD21AF2,
+	(q31_t)0xB0533055, (q31_t)0x9C10CD70, (q31_t)0xB0049AB2,
+	(q31_t)0x9C4FBD92, (q31_t)0xAFB63667, (q31_t)0x9C8EEB33,
+	(q31_t)0xAF6803A1, (q31_t)0x9CCE562B, (q31_t)0xAF1A0293,
+	(q31_t)0x9D0DFE53, (q31_t)0xAECC336B, (q31_t)0x9D4DE384,
+	(q31_t)0xAE7E965B, (q31_t)0x9D8E0596, (q31_t)0xAE312B91,
+	(q31_t)0x9DCE6462, (q31_t)0xADE3F33E, (q31_t)0x9E0EFFC1,
+	(q31_t)0xAD96ED91, (q31_t)0x9E4FD789, (q31_t)0xAD4A1ABA,
+	(q31_t)0x9E90EB94, (q31_t)0xACFD7AE8, (q31_t)0x9ED23BB9,
+	(q31_t)0xACB10E4A, (q31_t)0x9F13C7D0, (q31_t)0xAC64D510,
+	(q31_t)0x9F558FB0, (q31_t)0xAC18CF68, (q31_t)0x9F979331,
+	(q31_t)0xABCCFD82, (q31_t)0x9FD9D22A, (q31_t)0xAB815F8C,
+	(q31_t)0xA01C4C72, (q31_t)0xAB35F5B5, (q31_t)0xA05F01E1,
+	(q31_t)0xAAEAC02B, (q31_t)0xA0A1F24C, (q31_t)0xAA9FBF1D,
+	(q31_t)0xA0E51D8C, (q31_t)0xAA54F2B9, (q31_t)0xA1288376,
+	(q31_t)0xAA0A5B2D, (q31_t)0xA16C23E1, (q31_t)0xA9BFF8A8,
+	(q31_t)0xA1AFFEA2, (q31_t)0xA975CB56, (q31_t)0xA1F41391,
+	(q31_t)0xA92BD366, (q31_t)0xA2386283, (q31_t)0xA8E21106,
+	(q31_t)0xA27CEB4F, (q31_t)0xA8988463, (q31_t)0xA2C1ADC9,
+	(q31_t)0xA84F2DA9, (q31_t)0xA306A9C7, (q31_t)0xA8060D08,
+	(q31_t)0xA34BDF20, (q31_t)0xA7BD22AB, (q31_t)0xA3914DA7,
+	(q31_t)0xA7746EC0, (q31_t)0xA3D6F533, (q31_t)0xA72BF173,
+	(q31_t)0xA41CD598, (q31_t)0xA6E3AAF2, (q31_t)0xA462EEAC,
+	(q31_t)0xA69B9B68, (q31_t)0xA4A94042, (q31_t)0xA653C302,
+	(q31_t)0xA4EFCA31, (q31_t)0xA60C21ED, (q31_t)0xA5368C4B,
+	(q31_t)0xA5C4B855, (q31_t)0xA57D8666, (q31_t)0xA57D8666,
+	(q31_t)0xA5C4B855, (q31_t)0xA5368C4B, (q31_t)0xA60C21ED,
+	(q31_t)0xA4EFCA31, (q31_t)0xA653C302, (q31_t)0xA4A94042,
+	(q31_t)0xA69B9B68, (q31_t)0xA462EEAC, (q31_t)0xA6E3AAF2,
+	(q31_t)0xA41CD598, (q31_t)0xA72BF173, (q31_t)0xA3D6F533,
+	(q31_t)0xA7746EC0, (q31_t)0xA3914DA7, (q31_t)0xA7BD22AB,
+	(q31_t)0xA34BDF20, (q31_t)0xA8060D08, (q31_t)0xA306A9C7,
+	(q31_t)0xA84F2DA9, (q31_t)0xA2C1ADC9, (q31_t)0xA8988463,
+	(q31_t)0xA27CEB4F, (q31_t)0xA8E21106, (q31_t)0xA2386283,
+	(q31_t)0xA92BD366, (q31_t)0xA1F41391, (q31_t)0xA975CB56,
+	(q31_t)0xA1AFFEA2, (q31_t)0xA9BFF8A8, (q31_t)0xA16C23E1,
+	(q31_t)0xAA0A5B2D, (q31_t)0xA1288376, (q31_t)0xAA54F2B9,
+	(q31_t)0xA0E51D8C, (q31_t)0xAA9FBF1D, (q31_t)0xA0A1F24C,
+	(q31_t)0xAAEAC02B, (q31_t)0xA05F01E1, (q31_t)0xAB35F5B5,
+	(q31_t)0xA01C4C72, (q31_t)0xAB815F8C, (q31_t)0x9FD9D22A,
+	(q31_t)0xABCCFD82, (q31_t)0x9F979331, (q31_t)0xAC18CF68,
+	(q31_t)0x9F558FB0, (q31_t)0xAC64D510, (q31_t)0x9F13C7D0,
+	(q31_t)0xACB10E4A, (q31_t)0x9ED23BB9, (q31_t)0xACFD7AE8,
+	(q31_t)0x9E90EB94, (q31_t)0xAD4A1ABA, (q31_t)0x9E4FD789,
+	(q31_t)0xAD96ED91, (q31_t)0x9E0EFFC1, (q31_t)0xADE3F33E,
+	(q31_t)0x9DCE6462, (q31_t)0xAE312B91, (q31_t)0x9D8E0596,
+	(q31_t)0xAE7E965B, (q31_t)0x9D4DE384, (q31_t)0xAECC336B,
+	(q31_t)0x9D0DFE53, (q31_t)0xAF1A0293, (q31_t)0x9CCE562B,
+	(q31_t)0xAF6803A1, (q31_t)0x9C8EEB33, (q31_t)0xAFB63667,
+	(q31_t)0x9C4FBD92, (q31_t)0xB0049AB2, (q31_t)0x9C10CD70,
+	(q31_t)0xB0533055, (q31_t)0x9BD21AF2, (q31_t)0xB0A1F71C,
+	(q31_t)0x9B93A640, (q31_t)0xB0F0EEDA, (q31_t)0x9B556F80,
+	(q31_t)0xB140175B, (q31_t)0x9B1776D9, (q31_t)0xB18F7070,
+	(q31_t)0x9AD9BC71, (q31_t)0xB1DEF9E8, (q31_t)0x9A9C406D,
+	(q31_t)0xB22EB392, (q31_t)0x9A5F02F5, (q31_t)0xB27E9D3B,
+	(q31_t)0x9A22042C, (q31_t)0xB2CEB6B5, (q31_t)0x99E5443A,
+	(q31_t)0xB31EFFCB, (q31_t)0x99A8C344, (q31_t)0xB36F784E,
+	(q31_t)0x996C816F, (q31_t)0xB3C0200C, (q31_t)0x99307EE0,
+	(q31_t)0xB410F6D2, (q31_t)0x98F4BBBC, (q31_t)0xB461FC70,
+	(q31_t)0x98B93828, (q31_t)0xB4B330B2, (q31_t)0x987DF449,
+	(q31_t)0xB5049368, (q31_t)0x9842F043, (q31_t)0xB556245E,
+	(q31_t)0x98082C3B, (q31_t)0xB5A7E362, (q31_t)0x97CDA855,
+	(q31_t)0xB5F9D042, (q31_t)0x979364B5, (q31_t)0xB64BEACC,
+	(q31_t)0x9759617E, (q31_t)0xB69E32CD, (q31_t)0x971F9ED6,
+	(q31_t)0xB6F0A811, (q31_t)0x96E61CDF, (q31_t)0xB7434A67,
+	(q31_t)0x96ACDBBD, (q31_t)0xB796199B, (q31_t)0x9673DB94,
+	(q31_t)0xB7E9157A, (q31_t)0x963B1C85, (q31_t)0xB83C3DD1,
+	(q31_t)0x96029EB5, (q31_t)0xB88F926C, (q31_t)0x95CA6246,
+	(q31_t)0xB8E31319, (q31_t)0x9592675B, (q31_t)0xB936BFA3,
+	(q31_t)0x955AAE17, (q31_t)0xB98A97D8, (q31_t)0x9523369B,
+	(q31_t)0xB9DE9B83, (q31_t)0x94EC010B, (q31_t)0xBA32CA70,
+	(q31_t)0x94B50D87, (q31_t)0xBA87246C, (q31_t)0x947E5C32,
+	(q31_t)0xBADBA943, (q31_t)0x9447ED2F, (q31_t)0xBB3058C0,
+	(q31_t)0x9411C09D, (q31_t)0xBB8532AF, (q31_t)0x93DBD69F,
+	(q31_t)0xBBDA36DC, (q31_t)0x93A62F56, (q31_t)0xBC2F6513,
+	(q31_t)0x9370CAE4, (q31_t)0xBC84BD1E, (q31_t)0x933BA968,
+	(q31_t)0xBCDA3ECA, (q31_t)0x9306CB04, (q31_t)0xBD2FE9E1,
+	(q31_t)0x92D22FD8, (q31_t)0xBD85BE2F, (q31_t)0x929DD805,
+	(q31_t)0xBDDBBB7F, (q31_t)0x9269C3AC, (q31_t)0xBE31E19B,
+	(q31_t)0x9235F2EB, (q31_t)0xBE88304F, (q31_t)0x920265E4,
+	(q31_t)0xBEDEA765, (q31_t)0x91CF1CB6, (q31_t)0xBF3546A8,
+	(q31_t)0x919C1780, (q31_t)0xBF8C0DE2, (q31_t)0x91695663,
+	(q31_t)0xBFE2FCDF, (q31_t)0x9136D97D, (q31_t)0xC03A1368,
+	(q31_t)0x9104A0ED, (q31_t)0xC0915147, (q31_t)0x90D2ACD3,
+	(q31_t)0xC0E8B648, (q31_t)0x90A0FD4E, (q31_t)0xC1404233,
+	(q31_t)0x906F927B, (q31_t)0xC197F4D3, (q31_t)0x903E6C7A,
+	(q31_t)0xC1EFCDF2, (q31_t)0x900D8B69, (q31_t)0xC247CD5A,
+	(q31_t)0x8FDCEF66, (q31_t)0xC29FF2D4, (q31_t)0x8FAC988E,
+	(q31_t)0xC2F83E2A, (q31_t)0x8F7C8701, (q31_t)0xC350AF25,
+	(q31_t)0x8F4CBADB, (q31_t)0xC3A9458F, (q31_t)0x8F1D343A,
+	(q31_t)0xC4020132, (q31_t)0x8EEDF33B, (q31_t)0xC45AE1D7,
+	(q31_t)0x8EBEF7FB, (q31_t)0xC4B3E746, (q31_t)0x8E904298,
+	(q31_t)0xC50D1148, (q31_t)0x8E61D32D, (q31_t)0xC5665FA8,
+	(q31_t)0x8E33A9D9, (q31_t)0xC5BFD22E, (q31_t)0x8E05C6B7,
+	(q31_t)0xC61968A2, (q31_t)0x8DD829E4, (q31_t)0xC67322CD,
+	(q31_t)0x8DAAD37B, (q31_t)0xC6CD0079, (q31_t)0x8D7DC399,
+	(q31_t)0xC727016C, (q31_t)0x8D50FA59, (q31_t)0xC7812571,
+	(q31_t)0x8D2477D8, (q31_t)0xC7DB6C50, (q31_t)0x8CF83C30,
+	(q31_t)0xC835D5D0, (q31_t)0x8CCC477D, (q31_t)0xC89061BA,
+	(q31_t)0x8CA099D9, (q31_t)0xC8EB0FD6, (q31_t)0x8C753361,
+	(q31_t)0xC945DFEC, (q31_t)0x8C4A142F, (q31_t)0xC9A0D1C4,
+	(q31_t)0x8C1F3C5C, (q31_t)0xC9FBE527, (q31_t)0x8BF4AC05,
+	(q31_t)0xCA5719DB, (q31_t)0x8BCA6342, (q31_t)0xCAB26FA9,
+	(q31_t)0x8BA0622F, (q31_t)0xCB0DE658, (q31_t)0x8B76A8E4,
+	(q31_t)0xCB697DB0, (q31_t)0x8B4D377C, (q31_t)0xCBC53578,
+	(q31_t)0x8B240E10, (q31_t)0xCC210D78, (q31_t)0x8AFB2CBA,
+	(q31_t)0xCC7D0577, (q31_t)0x8AD29393, (q31_t)0xCCD91D3D,
+	(q31_t)0x8AAA42B4, (q31_t)0xCD355490, (q31_t)0x8A823A35,
+	(q31_t)0xCD91AB38, (q31_t)0x8A5A7A30, (q31_t)0xCDEE20FC,
+	(q31_t)0x8A3302BD, (q31_t)0xCE4AB5A2, (q31_t)0x8A0BD3F5,
+	(q31_t)0xCEA768F2, (q31_t)0x89E4EDEE, (q31_t)0xCF043AB2,
+	(q31_t)0x89BE50C3, (q31_t)0xCF612AAA, (q31_t)0x8997FC89,
+	(q31_t)0xCFBE389F, (q31_t)0x8971F15A, (q31_t)0xD01B6459,
+	(q31_t)0x894C2F4C, (q31_t)0xD078AD9D, (q31_t)0x8926B677,
+	(q31_t)0xD0D61433, (q31_t)0x890186F1, (q31_t)0xD13397E1,
+	(q31_t)0x88DCA0D3, (q31_t)0xD191386D, (q31_t)0x88B80431,
+	(q31_t)0xD1EEF59E, (q31_t)0x8893B124, (q31_t)0xD24CCF38,
+	(q31_t)0x886FA7C2, (q31_t)0xD2AAC504, (q31_t)0x884BE820,
+	(q31_t)0xD308D6C6, (q31_t)0x88287255, (q31_t)0xD3670445,
+	(q31_t)0x88054677, (q31_t)0xD3C54D46, (q31_t)0x87E2649B,
+	(q31_t)0xD423B190, (q31_t)0x87BFCCD7, (q31_t)0xD48230E8,
+	(q31_t)0x879D7F40, (q31_t)0xD4E0CB14, (q31_t)0x877B7BEC,
+	(q31_t)0xD53F7FDA, (q31_t)0x8759C2EF, (q31_t)0xD59E4EFE,
+	(q31_t)0x8738545E, (q31_t)0xD5FD3847, (q31_t)0x8717304E,
+	(q31_t)0xD65C3B7B, (q31_t)0x86F656D3, (q31_t)0xD6BB585D,
+	(q31_t)0x86D5C802, (q31_t)0xD71A8EB5, (q31_t)0x86B583EE,
+	(q31_t)0xD779DE46, (q31_t)0x86958AAB, (q31_t)0xD7D946D7,
+	(q31_t)0x8675DC4E, (q31_t)0xD838C82D, (q31_t)0x865678EA,
+	(q31_t)0xD898620C, (q31_t)0x86376092, (q31_t)0xD8F81439,
+	(q31_t)0x86189359, (q31_t)0xD957DE7A, (q31_t)0x85FA1152,
+	(q31_t)0xD9B7C093, (q31_t)0x85DBDA91, (q31_t)0xDA17BA4A,
+	(q31_t)0x85BDEF27, (q31_t)0xDA77CB62, (q31_t)0x85A04F28,
+	(q31_t)0xDAD7F3A2, (q31_t)0x8582FAA4, (q31_t)0xDB3832CD,
+	(q31_t)0x8565F1B0, (q31_t)0xDB9888A8, (q31_t)0x8549345C,
+	(q31_t)0xDBF8F4F8, (q31_t)0x852CC2BA, (q31_t)0xDC597781,
+	(q31_t)0x85109CDC, (q31_t)0xDCBA1008, (q31_t)0x84F4C2D3,
+	(q31_t)0xDD1ABE51, (q31_t)0x84D934B0, (q31_t)0xDD7B8220,
+	(q31_t)0x84BDF285, (q31_t)0xDDDC5B3A, (q31_t)0x84A2FC62,
+	(q31_t)0xDE3D4963, (q31_t)0x84885257, (q31_t)0xDE9E4C60,
+	(q31_t)0x846DF476, (q31_t)0xDEFF63F4, (q31_t)0x8453E2CE,
+	(q31_t)0xDF608FE3, (q31_t)0x843A1D70, (q31_t)0xDFC1CFF2,
+	(q31_t)0x8420A46B, (q31_t)0xE02323E5, (q31_t)0x840777CF,
+	(q31_t)0xE0848B7F, (q31_t)0x83EE97AC, (q31_t)0xE0E60684,
+	(q31_t)0x83D60411, (q31_t)0xE14794B9, (q31_t)0x83BDBD0D,
+	(q31_t)0xE1A935E1, (q31_t)0x83A5C2B0, (q31_t)0xE20AE9C1,
+	(q31_t)0x838E1507, (q31_t)0xE26CB01A, (q31_t)0x8376B422,
+	(q31_t)0xE2CE88B2, (q31_t)0x835FA00E, (q31_t)0xE330734C,
+	(q31_t)0x8348D8DB, (q31_t)0xE3926FAC, (q31_t)0x83325E97,
+	(q31_t)0xE3F47D95, (q31_t)0x831C314E, (q31_t)0xE4569CCB,
+	(q31_t)0x8306510F, (q31_t)0xE4B8CD10, (q31_t)0x82F0BDE8,
+	(q31_t)0xE51B0E2A, (q31_t)0x82DB77E5, (q31_t)0xE57D5FDA,
+	(q31_t)0x82C67F13, (q31_t)0xE5DFC1E4, (q31_t)0x82B1D381,
+	(q31_t)0xE642340D, (q31_t)0x829D753A, (q31_t)0xE6A4B616,
+	(q31_t)0x8289644A, (q31_t)0xE70747C3, (q31_t)0x8275A0C0,
+	(q31_t)0xE769E8D8, (q31_t)0x82622AA5, (q31_t)0xE7CC9917,
+	(q31_t)0x824F0208, (q31_t)0xE82F5844, (q31_t)0x823C26F2,
+	(q31_t)0xE8922621, (q31_t)0x82299971, (q31_t)0xE8F50273,
+	(q31_t)0x8217598F, (q31_t)0xE957ECFB, (q31_t)0x82056758,
+	(q31_t)0xE9BAE57C, (q31_t)0x81F3C2D7, (q31_t)0xEA1DEBBB,
+	(q31_t)0x81E26C16, (q31_t)0xEA80FF79, (q31_t)0x81D16320,
+	(q31_t)0xEAE4207A, (q31_t)0x81C0A801, (q31_t)0xEB474E80,
+	(q31_t)0x81B03AC1, (q31_t)0xEBAA894E, (q31_t)0x81A01B6C,
+	(q31_t)0xEC0DD0A8, (q31_t)0x81904A0C, (q31_t)0xEC71244F,
+	(q31_t)0x8180C6A9, (q31_t)0xECD48406, (q31_t)0x8171914E,
+	(q31_t)0xED37EF91, (q31_t)0x8162AA03, (q31_t)0xED9B66B2,
+	(q31_t)0x815410D3, (q31_t)0xEDFEE92B, (q31_t)0x8145C5C6,
+	(q31_t)0xEE6276BF, (q31_t)0x8137C8E6, (q31_t)0xEEC60F31,
+	(q31_t)0x812A1A39, (q31_t)0xEF29B243, (q31_t)0x811CB9CA,
+	(q31_t)0xEF8D5FB8, (q31_t)0x810FA7A0, (q31_t)0xEFF11752,
+	(q31_t)0x8102E3C3, (q31_t)0xF054D8D4, (q31_t)0x80F66E3C,
+	(q31_t)0xF0B8A401, (q31_t)0x80EA4712, (q31_t)0xF11C789A,
+	(q31_t)0x80DE6E4C, (q31_t)0xF1805662, (q31_t)0x80D2E3F1,
+	(q31_t)0xF1E43D1C, (q31_t)0x80C7A80A, (q31_t)0xF2482C89,
+	(q31_t)0x80BCBA9C, (q31_t)0xF2AC246D, (q31_t)0x80B21BAF,
+	(q31_t)0xF310248A, (q31_t)0x80A7CB49, (q31_t)0xF3742CA1,
+	(q31_t)0x809DC970, (q31_t)0xF3D83C76, (q31_t)0x8094162B,
+	(q31_t)0xF43C53CA, (q31_t)0x808AB180, (q31_t)0xF4A07260,
+	(q31_t)0x80819B74, (q31_t)0xF50497FA, (q31_t)0x8078D40D,
+	(q31_t)0xF568C45A, (q31_t)0x80705B50, (q31_t)0xF5CCF743,
+	(q31_t)0x80683143, (q31_t)0xF6313076, (q31_t)0x806055EA,
+	(q31_t)0xF6956FB6, (q31_t)0x8058C94C, (q31_t)0xF6F9B4C5,
+	(q31_t)0x80518B6B, (q31_t)0xF75DFF65, (q31_t)0x804A9C4D,
+	(q31_t)0xF7C24F58, (q31_t)0x8043FBF6, (q31_t)0xF826A461,
+	(q31_t)0x803DAA69, (q31_t)0xF88AFE41, (q31_t)0x8037A7AC,
+	(q31_t)0xF8EF5CBB, (q31_t)0x8031F3C1, (q31_t)0xF953BF90,
+	(q31_t)0x802C8EAD, (q31_t)0xF9B82683, (q31_t)0x80277872,
+	(q31_t)0xFA1C9156, (q31_t)0x8022B113, (q31_t)0xFA80FFCB,
+	(q31_t)0x801E3894, (q31_t)0xFAE571A4, (q31_t)0x801A0EF7,
+	(q31_t)0xFB49E6A2, (q31_t)0x80163440, (q31_t)0xFBAE5E89,
+	(q31_t)0x8012A86F, (q31_t)0xFC12D919, (q31_t)0x800F6B88,
+	(q31_t)0xFC775616, (q31_t)0x800C7D8C, (q31_t)0xFCDBD541,
+	(q31_t)0x8009DE7D, (q31_t)0xFD40565B, (q31_t)0x80078E5E,
+	(q31_t)0xFDA4D928, (q31_t)0x80058D2E, (q31_t)0xFE095D69,
+	(q31_t)0x8003DAF0, (q31_t)0xFE6DE2E0, (q31_t)0x800277A5,
+	(q31_t)0xFED2694F, (q31_t)0x8001634D, (q31_t)0xFF36F078,
+	(q31_t)0x80009DE9, (q31_t)0xFF9B781D, (q31_t)0x8000277A
+};
+
+/**
+* \par
+* Example code for Q31 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefQ31[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefQ31[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 4096	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to Q31(Fixed point 1.31):
+*	round(twiddleCoefQ31(i) * pow(2, 31))
+*
+*/
+const q31_t twiddleCoef_4096_q31[6144] =
+{
+	(q31_t)0x7FFFFFFF, (q31_t)0x00000000, (q31_t)0x7FFFF621,
+	(q31_t)0x003243F5, (q31_t)0x7FFFD885, (q31_t)0x006487E3,
+	(q31_t)0x7FFFA72C, (q31_t)0x0096CBC1, (q31_t)0x7FFF6216,
+	(q31_t)0x00C90F88, (q31_t)0x7FFF0942, (q31_t)0x00FB532F,
+	(q31_t)0x7FFE9CB2, (q31_t)0x012D96B0, (q31_t)0x7FFE1C64,
+	(q31_t)0x015FDA03, (q31_t)0x7FFD885A, (q31_t)0x01921D1F,
+	(q31_t)0x7FFCE093, (q31_t)0x01C45FFE, (q31_t)0x7FFC250F,
+	(q31_t)0x01F6A296, (q31_t)0x7FFB55CE, (q31_t)0x0228E4E1,
+	(q31_t)0x7FFA72D1, (q31_t)0x025B26D7, (q31_t)0x7FF97C17,
+	(q31_t)0x028D6870, (q31_t)0x7FF871A1, (q31_t)0x02BFA9A4,
+	(q31_t)0x7FF7536F, (q31_t)0x02F1EA6B, (q31_t)0x7FF62182,
+	(q31_t)0x03242ABF, (q31_t)0x7FF4DBD8, (q31_t)0x03566A96,
+	(q31_t)0x7FF38273, (q31_t)0x0388A9E9, (q31_t)0x7FF21553,
+	(q31_t)0x03BAE8B1, (q31_t)0x7FF09477, (q31_t)0x03ED26E6,
+	(q31_t)0x7FEEFFE1, (q31_t)0x041F647F, (q31_t)0x7FED5790,
+	(q31_t)0x0451A176, (q31_t)0x7FEB9B85, (q31_t)0x0483DDC3,
+	(q31_t)0x7FE9CBC0, (q31_t)0x04B6195D, (q31_t)0x7FE7E840,
+	(q31_t)0x04E8543D, (q31_t)0x7FE5F108, (q31_t)0x051A8E5C,
+	(q31_t)0x7FE3E616, (q31_t)0x054CC7B0, (q31_t)0x7FE1C76B,
+	(q31_t)0x057F0034, (q31_t)0x7FDF9508, (q31_t)0x05B137DF,
+	(q31_t)0x7FDD4EEC, (q31_t)0x05E36EA9, (q31_t)0x7FDAF518,
+	(q31_t)0x0615A48A, (q31_t)0x7FD8878D, (q31_t)0x0647D97C,
+	(q31_t)0x7FD6064B, (q31_t)0x067A0D75, (q31_t)0x7FD37152,
+	(q31_t)0x06AC406F, (q31_t)0x7FD0C8A3, (q31_t)0x06DE7261,
+	(q31_t)0x7FCE0C3E, (q31_t)0x0710A344, (q31_t)0x7FCB3C23,
+	(q31_t)0x0742D310, (q31_t)0x7FC85853, (q31_t)0x077501BE,
+	(q31_t)0x7FC560CF, (q31_t)0x07A72F45, (q31_t)0x7FC25596,
+	(q31_t)0x07D95B9E, (q31_t)0x7FBF36A9, (q31_t)0x080B86C1,
+	(q31_t)0x7FBC040A, (q31_t)0x083DB0A7, (q31_t)0x7FB8BDB7,
+	(q31_t)0x086FD947, (q31_t)0x7FB563B2, (q31_t)0x08A2009A,
+	(q31_t)0x7FB1F5FC, (q31_t)0x08D42698, (q31_t)0x7FAE7494,
+	(q31_t)0x09064B3A, (q31_t)0x7FAADF7C, (q31_t)0x09386E77,
+	(q31_t)0x7FA736B4, (q31_t)0x096A9049, (q31_t)0x7FA37A3C,
+	(q31_t)0x099CB0A7, (q31_t)0x7F9FAA15, (q31_t)0x09CECF89,
+	(q31_t)0x7F9BC63F, (q31_t)0x0A00ECE8, (q31_t)0x7F97CEBC,
+	(q31_t)0x0A3308BC, (q31_t)0x7F93C38C, (q31_t)0x0A6522FE,
+	(q31_t)0x7F8FA4AF, (q31_t)0x0A973BA5, (q31_t)0x7F8B7226,
+	(q31_t)0x0AC952AA, (q31_t)0x7F872BF3, (q31_t)0x0AFB6805,
+	(q31_t)0x7F82D214, (q31_t)0x0B2D7BAE, (q31_t)0x7F7E648B,
+	(q31_t)0x0B5F8D9F, (q31_t)0x7F79E35A, (q31_t)0x0B919DCE,
+	(q31_t)0x7F754E7F, (q31_t)0x0BC3AC35, (q31_t)0x7F70A5FD,
+	(q31_t)0x0BF5B8CB, (q31_t)0x7F6BE9D4, (q31_t)0x0C27C389,
+	(q31_t)0x7F671A04, (q31_t)0x0C59CC67, (q31_t)0x7F62368F,
+	(q31_t)0x0C8BD35E, (q31_t)0x7F5D3F75, (q31_t)0x0CBDD865,
+	(q31_t)0x7F5834B6, (q31_t)0x0CEFDB75, (q31_t)0x7F531654,
+	(q31_t)0x0D21DC87, (q31_t)0x7F4DE450, (q31_t)0x0D53DB92,
+	(q31_t)0x7F489EAA, (q31_t)0x0D85D88F, (q31_t)0x7F434563,
+	(q31_t)0x0DB7D376, (q31_t)0x7F3DD87C, (q31_t)0x0DE9CC3F,
+	(q31_t)0x7F3857F5, (q31_t)0x0E1BC2E3, (q31_t)0x7F32C3D0,
+	(q31_t)0x0E4DB75B, (q31_t)0x7F2D1C0E, (q31_t)0x0E7FA99D,
+	(q31_t)0x7F2760AF, (q31_t)0x0EB199A3, (q31_t)0x7F2191B4,
+	(q31_t)0x0EE38765, (q31_t)0x7F1BAF1E, (q31_t)0x0F1572DC,
+	(q31_t)0x7F15B8EE, (q31_t)0x0F475BFE, (q31_t)0x7F0FAF24,
+	(q31_t)0x0F7942C6, (q31_t)0x7F0991C3, (q31_t)0x0FAB272B,
+	(q31_t)0x7F0360CB, (q31_t)0x0FDD0925, (q31_t)0x7EFD1C3C,
+	(q31_t)0x100EE8AD, (q31_t)0x7EF6C418, (q31_t)0x1040C5BB,
+	(q31_t)0x7EF0585F, (q31_t)0x1072A047, (q31_t)0x7EE9D913,
+	(q31_t)0x10A4784A, (q31_t)0x7EE34635, (q31_t)0x10D64DBC,
+	(q31_t)0x7EDC9FC6, (q31_t)0x11082096, (q31_t)0x7ED5E5C6,
+	(q31_t)0x1139F0CE, (q31_t)0x7ECF1837, (q31_t)0x116BBE5F,
+	(q31_t)0x7EC8371A, (q31_t)0x119D8940, (q31_t)0x7EC1426F,
+	(q31_t)0x11CF516A, (q31_t)0x7EBA3A39, (q31_t)0x120116D4,
+	(q31_t)0x7EB31E77, (q31_t)0x1232D978, (q31_t)0x7EABEF2C,
+	(q31_t)0x1264994E, (q31_t)0x7EA4AC58, (q31_t)0x1296564D,
+	(q31_t)0x7E9D55FC, (q31_t)0x12C8106E, (q31_t)0x7E95EC19,
+	(q31_t)0x12F9C7AA, (q31_t)0x7E8E6EB1, (q31_t)0x132B7BF9,
+	(q31_t)0x7E86DDC5, (q31_t)0x135D2D53, (q31_t)0x7E7F3956,
+	(q31_t)0x138EDBB0, (q31_t)0x7E778165, (q31_t)0x13C0870A,
+	(q31_t)0x7E6FB5F3, (q31_t)0x13F22F57, (q31_t)0x7E67D702,
+	(q31_t)0x1423D492, (q31_t)0x7E5FE493, (q31_t)0x145576B1,
+	(q31_t)0x7E57DEA6, (q31_t)0x148715AD, (q31_t)0x7E4FC53E,
+	(q31_t)0x14B8B17F, (q31_t)0x7E47985B, (q31_t)0x14EA4A1F,
+	(q31_t)0x7E3F57FE, (q31_t)0x151BDF85, (q31_t)0x7E37042A,
+	(q31_t)0x154D71AA, (q31_t)0x7E2E9CDF, (q31_t)0x157F0086,
+	(q31_t)0x7E26221E, (q31_t)0x15B08C11, (q31_t)0x7E1D93E9,
+	(q31_t)0x15E21444, (q31_t)0x7E14F242, (q31_t)0x16139917,
+	(q31_t)0x7E0C3D29, (q31_t)0x16451A83, (q31_t)0x7E03749F,
+	(q31_t)0x1676987F, (q31_t)0x7DFA98A7, (q31_t)0x16A81305,
+	(q31_t)0x7DF1A942, (q31_t)0x16D98A0C, (q31_t)0x7DE8A670,
+	(q31_t)0x170AFD8D, (q31_t)0x7DDF9034, (q31_t)0x173C6D80,
+	(q31_t)0x7DD6668E, (q31_t)0x176DD9DE, (q31_t)0x7DCD2981,
+	(q31_t)0x179F429F, (q31_t)0x7DC3D90D, (q31_t)0x17D0A7BB,
+	(q31_t)0x7DBA7534, (q31_t)0x1802092C, (q31_t)0x7DB0FDF7,
+	(q31_t)0x183366E8, (q31_t)0x7DA77359, (q31_t)0x1864C0E9,
+	(q31_t)0x7D9DD55A, (q31_t)0x18961727, (q31_t)0x7D9423FB,
+	(q31_t)0x18C7699B, (q31_t)0x7D8A5F3F, (q31_t)0x18F8B83C,
+	(q31_t)0x7D808727, (q31_t)0x192A0303, (q31_t)0x7D769BB5,
+	(q31_t)0x195B49E9, (q31_t)0x7D6C9CE9, (q31_t)0x198C8CE6,
+	(q31_t)0x7D628AC5, (q31_t)0x19BDCBF2, (q31_t)0x7D58654C,
+	(q31_t)0x19EF0706, (q31_t)0x7D4E2C7E, (q31_t)0x1A203E1B,
+	(q31_t)0x7D43E05E, (q31_t)0x1A517127, (q31_t)0x7D3980EC,
+	(q31_t)0x1A82A025, (q31_t)0x7D2F0E2A, (q31_t)0x1AB3CB0C,
+	(q31_t)0x7D24881A, (q31_t)0x1AE4F1D6, (q31_t)0x7D19EEBE,
+	(q31_t)0x1B161479, (q31_t)0x7D0F4218, (q31_t)0x1B4732EF,
+	(q31_t)0x7D048228, (q31_t)0x1B784D30, (q31_t)0x7CF9AEF0,
+	(q31_t)0x1BA96334, (q31_t)0x7CEEC873, (q31_t)0x1BDA74F5,
+	(q31_t)0x7CE3CEB1, (q31_t)0x1C0B826A, (q31_t)0x7CD8C1AD,
+	(q31_t)0x1C3C8B8C, (q31_t)0x7CCDA168, (q31_t)0x1C6D9053,
+	(q31_t)0x7CC26DE5, (q31_t)0x1C9E90B8, (q31_t)0x7CB72724,
+	(q31_t)0x1CCF8CB3, (q31_t)0x7CABCD27, (q31_t)0x1D00843C,
+	(q31_t)0x7CA05FF1, (q31_t)0x1D31774D, (q31_t)0x7C94DF82,
+	(q31_t)0x1D6265DD, (q31_t)0x7C894BDD, (q31_t)0x1D934FE5,
+	(q31_t)0x7C7DA504, (q31_t)0x1DC4355D, (q31_t)0x7C71EAF8,
+	(q31_t)0x1DF5163F, (q31_t)0x7C661DBB, (q31_t)0x1E25F281,
+	(q31_t)0x7C5A3D4F, (q31_t)0x1E56CA1E, (q31_t)0x7C4E49B6,
+	(q31_t)0x1E879D0C, (q31_t)0x7C4242F2, (q31_t)0x1EB86B46,
+	(q31_t)0x7C362904, (q31_t)0x1EE934C2, (q31_t)0x7C29FBEE,
+	(q31_t)0x1F19F97B, (q31_t)0x7C1DBBB2, (q31_t)0x1F4AB967,
+	(q31_t)0x7C116853, (q31_t)0x1F7B7480, (q31_t)0x7C0501D1,
+	(q31_t)0x1FAC2ABF, (q31_t)0x7BF88830, (q31_t)0x1FDCDC1A,
+	(q31_t)0x7BEBFB70, (q31_t)0x200D888C, (q31_t)0x7BDF5B94,
+	(q31_t)0x203E300D, (q31_t)0x7BD2A89E, (q31_t)0x206ED295,
+	(q31_t)0x7BC5E28F, (q31_t)0x209F701C, (q31_t)0x7BB9096A,
+	(q31_t)0x20D0089B, (q31_t)0x7BAC1D31, (q31_t)0x21009C0B,
+	(q31_t)0x7B9F1DE5, (q31_t)0x21312A65, (q31_t)0x7B920B89,
+	(q31_t)0x2161B39F, (q31_t)0x7B84E61E, (q31_t)0x219237B4,
+	(q31_t)0x7B77ADA8, (q31_t)0x21C2B69C, (q31_t)0x7B6A6227,
+	(q31_t)0x21F3304E, (q31_t)0x7B5D039D, (q31_t)0x2223A4C5,
+	(q31_t)0x7B4F920E, (q31_t)0x225413F8, (q31_t)0x7B420D7A,
+	(q31_t)0x22847DDF, (q31_t)0x7B3475E4, (q31_t)0x22B4E274,
+	(q31_t)0x7B26CB4F, (q31_t)0x22E541AE, (q31_t)0x7B190DBB,
+	(q31_t)0x23159B87, (q31_t)0x7B0B3D2C, (q31_t)0x2345EFF7,
+	(q31_t)0x7AFD59A3, (q31_t)0x23763EF7, (q31_t)0x7AEF6323,
+	(q31_t)0x23A6887E, (q31_t)0x7AE159AE, (q31_t)0x23D6CC86,
+	(q31_t)0x7AD33D45, (q31_t)0x24070B07, (q31_t)0x7AC50DEB,
+	(q31_t)0x243743FA, (q31_t)0x7AB6CBA3, (q31_t)0x24677757,
+	(q31_t)0x7AA8766E, (q31_t)0x2497A517, (q31_t)0x7A9A0E4F,
+	(q31_t)0x24C7CD32, (q31_t)0x7A8B9348, (q31_t)0x24F7EFA1,
+	(q31_t)0x7A7D055B, (q31_t)0x25280C5D, (q31_t)0x7A6E648A,
+	(q31_t)0x2558235E, (q31_t)0x7A5FB0D8, (q31_t)0x2588349D,
+	(q31_t)0x7A50EA46, (q31_t)0x25B84012, (q31_t)0x7A4210D8,
+	(q31_t)0x25E845B5, (q31_t)0x7A33248F, (q31_t)0x26184581,
+	(q31_t)0x7A24256E, (q31_t)0x26483F6C, (q31_t)0x7A151377,
+	(q31_t)0x26783370, (q31_t)0x7A05EEAD, (q31_t)0x26A82185,
+	(q31_t)0x79F6B711, (q31_t)0x26D809A5, (q31_t)0x79E76CA6,
+	(q31_t)0x2707EBC6, (q31_t)0x79D80F6F, (q31_t)0x2737C7E3,
+	(q31_t)0x79C89F6D, (q31_t)0x27679DF4, (q31_t)0x79B91CA4,
+	(q31_t)0x27976DF1, (q31_t)0x79A98715, (q31_t)0x27C737D2,
+	(q31_t)0x7999DEC3, (q31_t)0x27F6FB92, (q31_t)0x798A23B1,
+	(q31_t)0x2826B928, (q31_t)0x797A55E0, (q31_t)0x2856708C,
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+	(q31_t)0x7FE3E616, (q31_t)0x051A8E5C, (q31_t)0x7FE5F108,
+	(q31_t)0x04E8543D, (q31_t)0x7FE7E840, (q31_t)0x04B6195D,
+	(q31_t)0x7FE9CBC0, (q31_t)0x0483DDC3, (q31_t)0x7FEB9B85,
+	(q31_t)0x0451A176, (q31_t)0x7FED5790, (q31_t)0x041F647F,
+	(q31_t)0x7FEEFFE1, (q31_t)0x03ED26E6, (q31_t)0x7FF09477,
+	(q31_t)0x03BAE8B1, (q31_t)0x7FF21553, (q31_t)0x0388A9E9,
+	(q31_t)0x7FF38273, (q31_t)0x03566A96, (q31_t)0x7FF4DBD8,
+	(q31_t)0x03242ABF, (q31_t)0x7FF62182, (q31_t)0x02F1EA6B,
+	(q31_t)0x7FF7536F, (q31_t)0x02BFA9A4, (q31_t)0x7FF871A1,
+	(q31_t)0x028D6870, (q31_t)0x7FF97C17, (q31_t)0x025B26D7,
+	(q31_t)0x7FFA72D1, (q31_t)0x0228E4E1, (q31_t)0x7FFB55CE,
+	(q31_t)0x01F6A296, (q31_t)0x7FFC250F, (q31_t)0x01C45FFE,
+	(q31_t)0x7FFCE093, (q31_t)0x01921D1F, (q31_t)0x7FFD885A,
+	(q31_t)0x015FDA03, (q31_t)0x7FFE1C64, (q31_t)0x012D96B0,
+	(q31_t)0x7FFE9CB2, (q31_t)0x00FB532F, (q31_t)0x7FFF0942,
+	(q31_t)0x00C90F88, (q31_t)0x7FFF6216, (q31_t)0x0096CBC1,
+	(q31_t)0x7FFFA72C, (q31_t)0x006487E3, (q31_t)0x7FFFD885,
+	(q31_t)0x003243F5, (q31_t)0x7FFFF621, (q31_t)0x00000000,
+	(q31_t)0x7FFFFFFF, (q31_t)0xFFCDBC0A, (q31_t)0x7FFFF621,
+	(q31_t)0xFF9B781D, (q31_t)0x7FFFD885, (q31_t)0xFF69343E,
+	(q31_t)0x7FFFA72C, (q31_t)0xFF36F078, (q31_t)0x7FFF6216,
+	(q31_t)0xFF04ACD0, (q31_t)0x7FFF0942, (q31_t)0xFED2694F,
+	(q31_t)0x7FFE9CB2, (q31_t)0xFEA025FC, (q31_t)0x7FFE1C64,
+	(q31_t)0xFE6DE2E0, (q31_t)0x7FFD885A, (q31_t)0xFE3BA001,
+	(q31_t)0x7FFCE093, (q31_t)0xFE095D69, (q31_t)0x7FFC250F,
+	(q31_t)0xFDD71B1E, (q31_t)0x7FFB55CE, (q31_t)0xFDA4D928,
+	(q31_t)0x7FFA72D1, (q31_t)0xFD72978F, (q31_t)0x7FF97C17,
+	(q31_t)0xFD40565B, (q31_t)0x7FF871A1, (q31_t)0xFD0E1594,
+	(q31_t)0x7FF7536F, (q31_t)0xFCDBD541, (q31_t)0x7FF62182,
+	(q31_t)0xFCA99569, (q31_t)0x7FF4DBD8, (q31_t)0xFC775616,
+	(q31_t)0x7FF38273, (q31_t)0xFC45174E, (q31_t)0x7FF21553,
+	(q31_t)0xFC12D919, (q31_t)0x7FF09477, (q31_t)0xFBE09B80,
+	(q31_t)0x7FEEFFE1, (q31_t)0xFBAE5E89, (q31_t)0x7FED5790,
+	(q31_t)0xFB7C223C, (q31_t)0x7FEB9B85, (q31_t)0xFB49E6A2,
+	(q31_t)0x7FE9CBC0, (q31_t)0xFB17ABC2, (q31_t)0x7FE7E840,
+	(q31_t)0xFAE571A4, (q31_t)0x7FE5F108, (q31_t)0xFAB3384F,
+	(q31_t)0x7FE3E616, (q31_t)0xFA80FFCB, (q31_t)0x7FE1C76B,
+	(q31_t)0xFA4EC820, (q31_t)0x7FDF9508, (q31_t)0xFA1C9156,
+	(q31_t)0x7FDD4EEC, (q31_t)0xF9EA5B75, (q31_t)0x7FDAF518,
+	(q31_t)0xF9B82683, (q31_t)0x7FD8878D, (q31_t)0xF985F28A,
+	(q31_t)0x7FD6064B, (q31_t)0xF953BF90, (q31_t)0x7FD37152,
+	(q31_t)0xF9218D9E, (q31_t)0x7FD0C8A3, (q31_t)0xF8EF5CBB,
+	(q31_t)0x7FCE0C3E, (q31_t)0xF8BD2CEF, (q31_t)0x7FCB3C23,
+	(q31_t)0xF88AFE41, (q31_t)0x7FC85853, (q31_t)0xF858D0BA,
+	(q31_t)0x7FC560CF, (q31_t)0xF826A461, (q31_t)0x7FC25596,
+	(q31_t)0xF7F4793E, (q31_t)0x7FBF36A9, (q31_t)0xF7C24F58,
+	(q31_t)0x7FBC040A, (q31_t)0xF79026B8, (q31_t)0x7FB8BDB7,
+	(q31_t)0xF75DFF65, (q31_t)0x7FB563B2, (q31_t)0xF72BD967,
+	(q31_t)0x7FB1F5FC, (q31_t)0xF6F9B4C5, (q31_t)0x7FAE7494,
+	(q31_t)0xF6C79188, (q31_t)0x7FAADF7C, (q31_t)0xF6956FB6,
+	(q31_t)0x7FA736B4, (q31_t)0xF6634F58, (q31_t)0x7FA37A3C,
+	(q31_t)0xF6313076, (q31_t)0x7F9FAA15, (q31_t)0xF5FF1317,
+	(q31_t)0x7F9BC63F, (q31_t)0xF5CCF743, (q31_t)0x7F97CEBC,
+	(q31_t)0xF59ADD01, (q31_t)0x7F93C38C, (q31_t)0xF568C45A,
+	(q31_t)0x7F8FA4AF, (q31_t)0xF536AD55, (q31_t)0x7F8B7226,
+	(q31_t)0xF50497FA, (q31_t)0x7F872BF3, (q31_t)0xF4D28451,
+	(q31_t)0x7F82D214, (q31_t)0xF4A07260, (q31_t)0x7F7E648B,
+	(q31_t)0xF46E6231, (q31_t)0x7F79E35A, (q31_t)0xF43C53CA,
+	(q31_t)0x7F754E7F, (q31_t)0xF40A4734, (q31_t)0x7F70A5FD,
+	(q31_t)0xF3D83C76, (q31_t)0x7F6BE9D4, (q31_t)0xF3A63398,
+	(q31_t)0x7F671A04, (q31_t)0xF3742CA1, (q31_t)0x7F62368F,
+	(q31_t)0xF342279A, (q31_t)0x7F5D3F75, (q31_t)0xF310248A,
+	(q31_t)0x7F5834B6, (q31_t)0xF2DE2378, (q31_t)0x7F531654,
+	(q31_t)0xF2AC246D, (q31_t)0x7F4DE450, (q31_t)0xF27A2770,
+	(q31_t)0x7F489EAA, (q31_t)0xF2482C89, (q31_t)0x7F434563,
+	(q31_t)0xF21633C0, (q31_t)0x7F3DD87C, (q31_t)0xF1E43D1C,
+	(q31_t)0x7F3857F5, (q31_t)0xF1B248A5, (q31_t)0x7F32C3D0,
+	(q31_t)0xF1805662, (q31_t)0x7F2D1C0E, (q31_t)0xF14E665C,
+	(q31_t)0x7F2760AF, (q31_t)0xF11C789A, (q31_t)0x7F2191B4,
+	(q31_t)0xF0EA8D23, (q31_t)0x7F1BAF1E, (q31_t)0xF0B8A401,
+	(q31_t)0x7F15B8EE, (q31_t)0xF086BD39, (q31_t)0x7F0FAF24,
+	(q31_t)0xF054D8D4, (q31_t)0x7F0991C3, (q31_t)0xF022F6DA,
+	(q31_t)0x7F0360CB, (q31_t)0xEFF11752, (q31_t)0x7EFD1C3C,
+	(q31_t)0xEFBF3A44, (q31_t)0x7EF6C418, (q31_t)0xEF8D5FB8,
+	(q31_t)0x7EF0585F, (q31_t)0xEF5B87B5, (q31_t)0x7EE9D913,
+	(q31_t)0xEF29B243, (q31_t)0x7EE34635, (q31_t)0xEEF7DF6A,
+	(q31_t)0x7EDC9FC6, (q31_t)0xEEC60F31, (q31_t)0x7ED5E5C6,
+	(q31_t)0xEE9441A0, (q31_t)0x7ECF1837, (q31_t)0xEE6276BF,
+	(q31_t)0x7EC8371A, (q31_t)0xEE30AE95, (q31_t)0x7EC1426F,
+	(q31_t)0xEDFEE92B, (q31_t)0x7EBA3A39, (q31_t)0xEDCD2687,
+	(q31_t)0x7EB31E77, (q31_t)0xED9B66B2, (q31_t)0x7EABEF2C,
+	(q31_t)0xED69A9B2, (q31_t)0x7EA4AC58, (q31_t)0xED37EF91,
+	(q31_t)0x7E9D55FC, (q31_t)0xED063855, (q31_t)0x7E95EC19,
+	(q31_t)0xECD48406, (q31_t)0x7E8E6EB1, (q31_t)0xECA2D2AC,
+	(q31_t)0x7E86DDC5, (q31_t)0xEC71244F, (q31_t)0x7E7F3956,
+	(q31_t)0xEC3F78F5, (q31_t)0x7E778165, (q31_t)0xEC0DD0A8,
+	(q31_t)0x7E6FB5F3, (q31_t)0xEBDC2B6D, (q31_t)0x7E67D702,
+	(q31_t)0xEBAA894E, (q31_t)0x7E5FE493, (q31_t)0xEB78EA52,
+	(q31_t)0x7E57DEA6, (q31_t)0xEB474E80, (q31_t)0x7E4FC53E,
+	(q31_t)0xEB15B5E0, (q31_t)0x7E47985B, (q31_t)0xEAE4207A,
+	(q31_t)0x7E3F57FE, (q31_t)0xEAB28E55, (q31_t)0x7E37042A,
+	(q31_t)0xEA80FF79, (q31_t)0x7E2E9CDF, (q31_t)0xEA4F73EE,
+	(q31_t)0x7E26221E, (q31_t)0xEA1DEBBB, (q31_t)0x7E1D93E9,
+	(q31_t)0xE9EC66E8, (q31_t)0x7E14F242, (q31_t)0xE9BAE57C,
+	(q31_t)0x7E0C3D29, (q31_t)0xE9896780, (q31_t)0x7E03749F,
+	(q31_t)0xE957ECFB, (q31_t)0x7DFA98A7, (q31_t)0xE92675F4,
+	(q31_t)0x7DF1A942, (q31_t)0xE8F50273, (q31_t)0x7DE8A670,
+	(q31_t)0xE8C3927F, (q31_t)0x7DDF9034, (q31_t)0xE8922621,
+	(q31_t)0x7DD6668E, (q31_t)0xE860BD60, (q31_t)0x7DCD2981,
+	(q31_t)0xE82F5844, (q31_t)0x7DC3D90D, (q31_t)0xE7FDF6D3,
+	(q31_t)0x7DBA7534, (q31_t)0xE7CC9917, (q31_t)0x7DB0FDF7,
+	(q31_t)0xE79B3F16, (q31_t)0x7DA77359, (q31_t)0xE769E8D8,
+	(q31_t)0x7D9DD55A, (q31_t)0xE7389664, (q31_t)0x7D9423FB,
+	(q31_t)0xE70747C3, (q31_t)0x7D8A5F3F, (q31_t)0xE6D5FCFC,
+	(q31_t)0x7D808727, (q31_t)0xE6A4B616, (q31_t)0x7D769BB5,
+	(q31_t)0xE6737319, (q31_t)0x7D6C9CE9, (q31_t)0xE642340D,
+	(q31_t)0x7D628AC5, (q31_t)0xE610F8F9, (q31_t)0x7D58654C,
+	(q31_t)0xE5DFC1E4, (q31_t)0x7D4E2C7E, (q31_t)0xE5AE8ED8,
+	(q31_t)0x7D43E05E, (q31_t)0xE57D5FDA, (q31_t)0x7D3980EC,
+	(q31_t)0xE54C34F3, (q31_t)0x7D2F0E2A, (q31_t)0xE51B0E2A,
+	(q31_t)0x7D24881A, (q31_t)0xE4E9EB86, (q31_t)0x7D19EEBE,
+	(q31_t)0xE4B8CD10, (q31_t)0x7D0F4218, (q31_t)0xE487B2CF,
+	(q31_t)0x7D048228, (q31_t)0xE4569CCB, (q31_t)0x7CF9AEF0,
+	(q31_t)0xE4258B0A, (q31_t)0x7CEEC873, (q31_t)0xE3F47D95,
+	(q31_t)0x7CE3CEB1, (q31_t)0xE3C37473, (q31_t)0x7CD8C1AD,
+	(q31_t)0xE3926FAC, (q31_t)0x7CCDA168, (q31_t)0xE3616F47,
+	(q31_t)0x7CC26DE5, (q31_t)0xE330734C, (q31_t)0x7CB72724,
+	(q31_t)0xE2FF7BC3, (q31_t)0x7CABCD27, (q31_t)0xE2CE88B2,
+	(q31_t)0x7CA05FF1, (q31_t)0xE29D9A22, (q31_t)0x7C94DF82,
+	(q31_t)0xE26CB01A, (q31_t)0x7C894BDD, (q31_t)0xE23BCAA2,
+	(q31_t)0x7C7DA504, (q31_t)0xE20AE9C1, (q31_t)0x7C71EAF8,
+	(q31_t)0xE1DA0D7E, (q31_t)0x7C661DBB, (q31_t)0xE1A935E1,
+	(q31_t)0x7C5A3D4F, (q31_t)0xE17862F3, (q31_t)0x7C4E49B6,
+	(q31_t)0xE14794B9, (q31_t)0x7C4242F2, (q31_t)0xE116CB3D,
+	(q31_t)0x7C362904, (q31_t)0xE0E60684, (q31_t)0x7C29FBEE,
+	(q31_t)0xE0B54698, (q31_t)0x7C1DBBB2, (q31_t)0xE0848B7F,
+	(q31_t)0x7C116853, (q31_t)0xE053D541, (q31_t)0x7C0501D1,
+	(q31_t)0xE02323E5, (q31_t)0x7BF88830, (q31_t)0xDFF27773,
+	(q31_t)0x7BEBFB70, (q31_t)0xDFC1CFF2, (q31_t)0x7BDF5B94,
+	(q31_t)0xDF912D6A, (q31_t)0x7BD2A89E, (q31_t)0xDF608FE3,
+	(q31_t)0x7BC5E28F, (q31_t)0xDF2FF764, (q31_t)0x7BB9096A,
+	(q31_t)0xDEFF63F4, (q31_t)0x7BAC1D31, (q31_t)0xDECED59B,
+	(q31_t)0x7B9F1DE5, (q31_t)0xDE9E4C60, (q31_t)0x7B920B89,
+	(q31_t)0xDE6DC84B, (q31_t)0x7B84E61E, (q31_t)0xDE3D4963,
+	(q31_t)0x7B77ADA8, (q31_t)0xDE0CCFB1, (q31_t)0x7B6A6227,
+	(q31_t)0xDDDC5B3A, (q31_t)0x7B5D039D, (q31_t)0xDDABEC07,
+	(q31_t)0x7B4F920E, (q31_t)0xDD7B8220, (q31_t)0x7B420D7A,
+	(q31_t)0xDD4B1D8B, (q31_t)0x7B3475E4, (q31_t)0xDD1ABE51,
+	(q31_t)0x7B26CB4F, (q31_t)0xDCEA6478, (q31_t)0x7B190DBB,
+	(q31_t)0xDCBA1008, (q31_t)0x7B0B3D2C, (q31_t)0xDC89C108,
+	(q31_t)0x7AFD59A3, (q31_t)0xDC597781, (q31_t)0x7AEF6323,
+	(q31_t)0xDC293379, (q31_t)0x7AE159AE, (q31_t)0xDBF8F4F8,
+	(q31_t)0x7AD33D45, (q31_t)0xDBC8BC05, (q31_t)0x7AC50DEB,
+	(q31_t)0xDB9888A8, (q31_t)0x7AB6CBA3, (q31_t)0xDB685AE8,
+	(q31_t)0x7AA8766E, (q31_t)0xDB3832CD, (q31_t)0x7A9A0E4F,
+	(q31_t)0xDB08105E, (q31_t)0x7A8B9348, (q31_t)0xDAD7F3A2,
+	(q31_t)0x7A7D055B, (q31_t)0xDAA7DCA1, (q31_t)0x7A6E648A,
+	(q31_t)0xDA77CB62, (q31_t)0x7A5FB0D8, (q31_t)0xDA47BFED,
+	(q31_t)0x7A50EA46, (q31_t)0xDA17BA4A, (q31_t)0x7A4210D8,
+	(q31_t)0xD9E7BA7E, (q31_t)0x7A33248F, (q31_t)0xD9B7C093,
+	(q31_t)0x7A24256E, (q31_t)0xD987CC8F, (q31_t)0x7A151377,
+	(q31_t)0xD957DE7A, (q31_t)0x7A05EEAD, (q31_t)0xD927F65B,
+	(q31_t)0x79F6B711, (q31_t)0xD8F81439, (q31_t)0x79E76CA6,
+	(q31_t)0xD8C8381C, (q31_t)0x79D80F6F, (q31_t)0xD898620C,
+	(q31_t)0x79C89F6D, (q31_t)0xD868920F, (q31_t)0x79B91CA4,
+	(q31_t)0xD838C82D, (q31_t)0x79A98715, (q31_t)0xD809046D,
+	(q31_t)0x7999DEC3, (q31_t)0xD7D946D7, (q31_t)0x798A23B1,
+	(q31_t)0xD7A98F73, (q31_t)0x797A55E0, (q31_t)0xD779DE46,
+	(q31_t)0x796A7554, (q31_t)0xD74A335A, (q31_t)0x795A820E,
+	(q31_t)0xD71A8EB5, (q31_t)0x794A7C11, (q31_t)0xD6EAF05E,
+	(q31_t)0x793A6360, (q31_t)0xD6BB585D, (q31_t)0x792A37FE,
+	(q31_t)0xD68BC6BA, (q31_t)0x7919F9EB, (q31_t)0xD65C3B7B,
+	(q31_t)0x7909A92C, (q31_t)0xD62CB6A7, (q31_t)0x78F945C3,
+	(q31_t)0xD5FD3847, (q31_t)0x78E8CFB1, (q31_t)0xD5CDC062,
+	(q31_t)0x78D846FB, (q31_t)0xD59E4EFE, (q31_t)0x78C7ABA1,
+	(q31_t)0xD56EE424, (q31_t)0x78B6FDA8, (q31_t)0xD53F7FDA,
+	(q31_t)0x78A63D10, (q31_t)0xD5102227, (q31_t)0x789569DE,
+	(q31_t)0xD4E0CB14, (q31_t)0x78848413, (q31_t)0xD4B17AA7,
+	(q31_t)0x78738BB3, (q31_t)0xD48230E8, (q31_t)0x786280BF,
+	(q31_t)0xD452EDDE, (q31_t)0x7851633B, (q31_t)0xD423B190,
+	(q31_t)0x78403328, (q31_t)0xD3F47C06, (q31_t)0x782EF08B,
+	(q31_t)0xD3C54D46, (q31_t)0x781D9B64, (q31_t)0xD3962559,
+	(q31_t)0x780C33B8, (q31_t)0xD3670445, (q31_t)0x77FAB988,
+	(q31_t)0xD337EA12, (q31_t)0x77E92CD8, (q31_t)0xD308D6C6,
+	(q31_t)0x77D78DAA, (q31_t)0xD2D9CA6A, (q31_t)0x77C5DC01,
+	(q31_t)0xD2AAC504, (q31_t)0x77B417DF, (q31_t)0xD27BC69C,
+	(q31_t)0x77A24148, (q31_t)0xD24CCF38, (q31_t)0x7790583D,
+	(q31_t)0xD21DDEE1, (q31_t)0x777E5CC3, (q31_t)0xD1EEF59E,
+	(q31_t)0x776C4EDB, (q31_t)0xD1C01374, (q31_t)0x775A2E88,
+	(q31_t)0xD191386D, (q31_t)0x7747FBCE, (q31_t)0xD162648F,
+	(q31_t)0x7735B6AE, (q31_t)0xD13397E1, (q31_t)0x77235F2D,
+	(q31_t)0xD104D26B, (q31_t)0x7710F54B, (q31_t)0xD0D61433,
+	(q31_t)0x76FE790E, (q31_t)0xD0A75D42, (q31_t)0x76EBEA77,
+	(q31_t)0xD078AD9D, (q31_t)0x76D94988, (q31_t)0xD04A054D,
+	(q31_t)0x76C69646, (q31_t)0xD01B6459, (q31_t)0x76B3D0B3,
+	(q31_t)0xCFECCAC7, (q31_t)0x76A0F8D2, (q31_t)0xCFBE389F,
+	(q31_t)0x768E0EA5, (q31_t)0xCF8FADE8, (q31_t)0x767B1230,
+	(q31_t)0xCF612AAA, (q31_t)0x76680376, (q31_t)0xCF32AEEB,
+	(q31_t)0x7654E279, (q31_t)0xCF043AB2, (q31_t)0x7641AF3C,
+	(q31_t)0xCED5CE08, (q31_t)0x762E69C3, (q31_t)0xCEA768F2,
+	(q31_t)0x761B1211, (q31_t)0xCE790B78, (q31_t)0x7607A827,
+	(q31_t)0xCE4AB5A2, (q31_t)0x75F42C0A, (q31_t)0xCE1C6776,
+	(q31_t)0x75E09DBD, (q31_t)0xCDEE20FC, (q31_t)0x75CCFD42,
+	(q31_t)0xCDBFE23A, (q31_t)0x75B94A9C, (q31_t)0xCD91AB38,
+	(q31_t)0x75A585CF, (q31_t)0xCD637BFD, (q31_t)0x7591AEDD,
+	(q31_t)0xCD355490, (q31_t)0x757DC5CA, (q31_t)0xCD0734F8,
+	(q31_t)0x7569CA98, (q31_t)0xCCD91D3D, (q31_t)0x7555BD4B,
+	(q31_t)0xCCAB0D65, (q31_t)0x75419DE6, (q31_t)0xCC7D0577,
+	(q31_t)0x752D6C6C, (q31_t)0xCC4F057B, (q31_t)0x751928E0,
+	(q31_t)0xCC210D78, (q31_t)0x7504D345, (q31_t)0xCBF31D75,
+	(q31_t)0x74F06B9E, (q31_t)0xCBC53578, (q31_t)0x74DBF1EF,
+	(q31_t)0xCB975589, (q31_t)0x74C7663A, (q31_t)0xCB697DB0,
+	(q31_t)0x74B2C883, (q31_t)0xCB3BADF2, (q31_t)0x749E18CD,
+	(q31_t)0xCB0DE658, (q31_t)0x7489571B, (q31_t)0xCAE026E8,
+	(q31_t)0x74748371, (q31_t)0xCAB26FA9, (q31_t)0x745F9DD1,
+	(q31_t)0xCA84C0A2, (q31_t)0x744AA63E, (q31_t)0xCA5719DB,
+	(q31_t)0x74359CBD, (q31_t)0xCA297B5A, (q31_t)0x74208150,
+	(q31_t)0xC9FBE527, (q31_t)0x740B53FA, (q31_t)0xC9CE5748,
+	(q31_t)0x73F614C0, (q31_t)0xC9A0D1C4, (q31_t)0x73E0C3A3,
+	(q31_t)0xC97354A3, (q31_t)0x73CB60A7, (q31_t)0xC945DFEC,
+	(q31_t)0x73B5EBD0, (q31_t)0xC91873A5, (q31_t)0x73A06522,
+	(q31_t)0xC8EB0FD6, (q31_t)0x738ACC9E, (q31_t)0xC8BDB485,
+	(q31_t)0x73752249, (q31_t)0xC89061BA, (q31_t)0x735F6626,
+	(q31_t)0xC863177B, (q31_t)0x73499838, (q31_t)0xC835D5D0,
+	(q31_t)0x7333B883, (q31_t)0xC8089CBF, (q31_t)0x731DC709,
+	(q31_t)0xC7DB6C50, (q31_t)0x7307C3D0, (q31_t)0xC7AE4489,
+	(q31_t)0x72F1AED8, (q31_t)0xC7812571, (q31_t)0x72DB8828,
+	(q31_t)0xC7540F10, (q31_t)0x72C54FC0, (q31_t)0xC727016C,
+	(q31_t)0x72AF05A6, (q31_t)0xC6F9FC8D, (q31_t)0x7298A9DC,
+	(q31_t)0xC6CD0079, (q31_t)0x72823C66, (q31_t)0xC6A00D36,
+	(q31_t)0x726BBD48, (q31_t)0xC67322CD, (q31_t)0x72552C84,
+	(q31_t)0xC6464144, (q31_t)0x723E8A1F, (q31_t)0xC61968A2,
+	(q31_t)0x7227D61C, (q31_t)0xC5EC98ED, (q31_t)0x7211107D,
+	(q31_t)0xC5BFD22E, (q31_t)0x71FA3948, (q31_t)0xC593146A,
+	(q31_t)0x71E3507F, (q31_t)0xC5665FA8, (q31_t)0x71CC5626,
+	(q31_t)0xC539B3F0, (q31_t)0x71B54A40, (q31_t)0xC50D1148,
+	(q31_t)0x719E2CD2, (q31_t)0xC4E077B8, (q31_t)0x7186FDDE,
+	(q31_t)0xC4B3E746, (q31_t)0x716FBD68, (q31_t)0xC4875FF8,
+	(q31_t)0x71586B73, (q31_t)0xC45AE1D7, (q31_t)0x71410804,
+	(q31_t)0xC42E6CE8, (q31_t)0x7129931E, (q31_t)0xC4020132,
+	(q31_t)0x71120CC5, (q31_t)0xC3D59EBD, (q31_t)0x70FA74FB,
+	(q31_t)0xC3A9458F, (q31_t)0x70E2CBC6, (q31_t)0xC37CF5B0,
+	(q31_t)0x70CB1127, (q31_t)0xC350AF25, (q31_t)0x70B34524,
+	(q31_t)0xC32471F6, (q31_t)0x709B67C0, (q31_t)0xC2F83E2A,
+	(q31_t)0x708378FE, (q31_t)0xC2CC13C7, (q31_t)0x706B78E3,
+	(q31_t)0xC29FF2D4, (q31_t)0x70536771, (q31_t)0xC273DB58,
+	(q31_t)0x703B44AC, (q31_t)0xC247CD5A, (q31_t)0x70231099,
+	(q31_t)0xC21BC8E0, (q31_t)0x700ACB3B, (q31_t)0xC1EFCDF2,
+	(q31_t)0x6FF27496, (q31_t)0xC1C3DC96, (q31_t)0x6FDA0CAD,
+	(q31_t)0xC197F4D3, (q31_t)0x6FC19385, (q31_t)0xC16C16B0,
+	(q31_t)0x6FA90920, (q31_t)0xC1404233, (q31_t)0x6F906D84,
+	(q31_t)0xC1147763, (q31_t)0x6F77C0B3, (q31_t)0xC0E8B648,
+	(q31_t)0x6F5F02B1, (q31_t)0xC0BCFEE7, (q31_t)0x6F463383,
+	(q31_t)0xC0915147, (q31_t)0x6F2D532C, (q31_t)0xC065AD70,
+	(q31_t)0x6F1461AF, (q31_t)0xC03A1368, (q31_t)0x6EFB5F12,
+	(q31_t)0xC00E8335, (q31_t)0x6EE24B57, (q31_t)0xBFE2FCDF,
+	(q31_t)0x6EC92682, (q31_t)0xBFB7806C, (q31_t)0x6EAFF098,
+	(q31_t)0xBF8C0DE2, (q31_t)0x6E96A99C, (q31_t)0xBF60A54A,
+	(q31_t)0x6E7D5193, (q31_t)0xBF3546A8, (q31_t)0x6E63E87F,
+	(q31_t)0xBF09F204, (q31_t)0x6E4A6E65, (q31_t)0xBEDEA765,
+	(q31_t)0x6E30E349, (q31_t)0xBEB366D1, (q31_t)0x6E17472F,
+	(q31_t)0xBE88304F, (q31_t)0x6DFD9A1B, (q31_t)0xBE5D03E5,
+	(q31_t)0x6DE3DC11, (q31_t)0xBE31E19B, (q31_t)0x6DCA0D14,
+	(q31_t)0xBE06C977, (q31_t)0x6DB02D29, (q31_t)0xBDDBBB7F,
+	(q31_t)0x6D963C54, (q31_t)0xBDB0B7BA, (q31_t)0x6D7C3A98,
+	(q31_t)0xBD85BE2F, (q31_t)0x6D6227FA, (q31_t)0xBD5ACEE5,
+	(q31_t)0x6D48047E, (q31_t)0xBD2FE9E1, (q31_t)0x6D2DD027,
+	(q31_t)0xBD050F2C, (q31_t)0x6D138AFA, (q31_t)0xBCDA3ECA,
+	(q31_t)0x6CF934FB, (q31_t)0xBCAF78C3, (q31_t)0x6CDECE2E,
+	(q31_t)0xBC84BD1E, (q31_t)0x6CC45697, (q31_t)0xBC5A0BE1,
+	(q31_t)0x6CA9CE3A, (q31_t)0xBC2F6513, (q31_t)0x6C8F351C,
+	(q31_t)0xBC04C8BA, (q31_t)0x6C748B3F, (q31_t)0xBBDA36DC,
+	(q31_t)0x6C59D0A9, (q31_t)0xBBAFAF81, (q31_t)0x6C3F055D,
+	(q31_t)0xBB8532AF, (q31_t)0x6C242960, (q31_t)0xBB5AC06C,
+	(q31_t)0x6C093CB6, (q31_t)0xBB3058C0, (q31_t)0x6BEE3F62,
+	(q31_t)0xBB05FBB0, (q31_t)0x6BD3316A, (q31_t)0xBADBA943,
+	(q31_t)0x6BB812D0, (q31_t)0xBAB1617F, (q31_t)0x6B9CE39B,
+	(q31_t)0xBA87246C, (q31_t)0x6B81A3CD, (q31_t)0xBA5CF210,
+	(q31_t)0x6B66536A, (q31_t)0xBA32CA70, (q31_t)0x6B4AF278,
+	(q31_t)0xBA08AD94, (q31_t)0x6B2F80FA, (q31_t)0xB9DE9B83,
+	(q31_t)0x6B13FEF5, (q31_t)0xB9B49442, (q31_t)0x6AF86C6C,
+	(q31_t)0xB98A97D8, (q31_t)0x6ADCC964, (q31_t)0xB960A64B,
+	(q31_t)0x6AC115E1, (q31_t)0xB936BFA3, (q31_t)0x6AA551E8,
+	(q31_t)0xB90CE3E6, (q31_t)0x6A897D7D, (q31_t)0xB8E31319,
+	(q31_t)0x6A6D98A4, (q31_t)0xB8B94D44, (q31_t)0x6A51A361,
+	(q31_t)0xB88F926C, (q31_t)0x6A359DB9, (q31_t)0xB865E299,
+	(q31_t)0x6A1987B0, (q31_t)0xB83C3DD1, (q31_t)0x69FD614A,
+	(q31_t)0xB812A419, (q31_t)0x69E12A8C, (q31_t)0xB7E9157A,
+	(q31_t)0x69C4E37A, (q31_t)0xB7BF91F8, (q31_t)0x69A88C18,
+	(q31_t)0xB796199B, (q31_t)0x698C246C, (q31_t)0xB76CAC68,
+	(q31_t)0x696FAC78, (q31_t)0xB7434A67, (q31_t)0x69532442,
+	(q31_t)0xB719F39D, (q31_t)0x69368BCE, (q31_t)0xB6F0A811,
+	(q31_t)0x6919E320, (q31_t)0xB6C767CA, (q31_t)0x68FD2A3D,
+	(q31_t)0xB69E32CD, (q31_t)0x68E06129, (q31_t)0xB6750921,
+	(q31_t)0x68C387E9, (q31_t)0xB64BEACC, (q31_t)0x68A69E81,
+	(q31_t)0xB622D7D5, (q31_t)0x6889A4F5, (q31_t)0xB5F9D042,
+	(q31_t)0x686C9B4B, (q31_t)0xB5D0D41A, (q31_t)0x684F8186,
+	(q31_t)0xB5A7E362, (q31_t)0x683257AA, (q31_t)0xB57EFE21,
+	(q31_t)0x68151DBE, (q31_t)0xB556245E, (q31_t)0x67F7D3C4,
+	(q31_t)0xB52D561E, (q31_t)0x67DA79C2, (q31_t)0xB5049368,
+	(q31_t)0x67BD0FBC, (q31_t)0xB4DBDC42, (q31_t)0x679F95B7,
+	(q31_t)0xB4B330B2, (q31_t)0x67820BB6, (q31_t)0xB48A90C0,
+	(q31_t)0x676471C0, (q31_t)0xB461FC70, (q31_t)0x6746C7D7,
+	(q31_t)0xB43973C9, (q31_t)0x67290E02, (q31_t)0xB410F6D2,
+	(q31_t)0x670B4443, (q31_t)0xB3E88591, (q31_t)0x66ED6AA1,
+	(q31_t)0xB3C0200C, (q31_t)0x66CF811F, (q31_t)0xB397C649,
+	(q31_t)0x66B187C3, (q31_t)0xB36F784E, (q31_t)0x66937E90,
+	(q31_t)0xB3473622, (q31_t)0x6675658C, (q31_t)0xB31EFFCB,
+	(q31_t)0x66573CBB, (q31_t)0xB2F6D54F, (q31_t)0x66390422,
+	(q31_t)0xB2CEB6B5, (q31_t)0x661ABBC5, (q31_t)0xB2A6A401,
+	(q31_t)0x65FC63A9, (q31_t)0xB27E9D3B, (q31_t)0x65DDFBD3,
+	(q31_t)0xB256A26A, (q31_t)0x65BF8447, (q31_t)0xB22EB392,
+	(q31_t)0x65A0FD0B, (q31_t)0xB206D0BA, (q31_t)0x65826622,
+	(q31_t)0xB1DEF9E8, (q31_t)0x6563BF92, (q31_t)0xB1B72F23,
+	(q31_t)0x6545095F, (q31_t)0xB18F7070, (q31_t)0x6526438E,
+	(q31_t)0xB167BDD6, (q31_t)0x65076E24, (q31_t)0xB140175B,
+	(q31_t)0x64E88926, (q31_t)0xB1187D05, (q31_t)0x64C99498,
+	(q31_t)0xB0F0EEDA, (q31_t)0x64AA907F, (q31_t)0xB0C96CDF,
+	(q31_t)0x648B7CDF, (q31_t)0xB0A1F71C, (q31_t)0x646C59BF,
+	(q31_t)0xB07A8D97, (q31_t)0x644D2722, (q31_t)0xB0533055,
+	(q31_t)0x642DE50D, (q31_t)0xB02BDF5C, (q31_t)0x640E9385,
+	(q31_t)0xB0049AB2, (q31_t)0x63EF328F, (q31_t)0xAFDD625F,
+	(q31_t)0x63CFC230, (q31_t)0xAFB63667, (q31_t)0x63B0426D,
+	(q31_t)0xAF8F16D0, (q31_t)0x6390B34A, (q31_t)0xAF6803A1,
+	(q31_t)0x637114CC, (q31_t)0xAF40FCE0, (q31_t)0x635166F8,
+	(q31_t)0xAF1A0293, (q31_t)0x6331A9D4, (q31_t)0xAEF314BF,
+	(q31_t)0x6311DD63, (q31_t)0xAECC336B, (q31_t)0x62F201AC,
+	(q31_t)0xAEA55E9D, (q31_t)0x62D216B2, (q31_t)0xAE7E965B,
+	(q31_t)0x62B21C7B, (q31_t)0xAE57DAAA, (q31_t)0x6292130C,
+	(q31_t)0xAE312B91, (q31_t)0x6271FA69, (q31_t)0xAE0A8916,
+	(q31_t)0x6251D297, (q31_t)0xADE3F33E, (q31_t)0x62319B9D,
+	(q31_t)0xADBD6A10, (q31_t)0x6211557D, (q31_t)0xAD96ED91,
+	(q31_t)0x61F1003E, (q31_t)0xAD707DC8, (q31_t)0x61D09BE5,
+	(q31_t)0xAD4A1ABA, (q31_t)0x61B02876, (q31_t)0xAD23C46D,
+	(q31_t)0x618FA5F6, (q31_t)0xACFD7AE8, (q31_t)0x616F146B,
+	(q31_t)0xACD73E30, (q31_t)0x614E73D9, (q31_t)0xACB10E4A,
+	(q31_t)0x612DC446, (q31_t)0xAC8AEB3E, (q31_t)0x610D05B7,
+	(q31_t)0xAC64D510, (q31_t)0x60EC3830, (q31_t)0xAC3ECBC7,
+	(q31_t)0x60CB5BB6, (q31_t)0xAC18CF68, (q31_t)0x60AA704F,
+	(q31_t)0xABF2DFFA, (q31_t)0x60897600, (q31_t)0xABCCFD82,
+	(q31_t)0x60686CCE, (q31_t)0xABA72806, (q31_t)0x604754BE,
+	(q31_t)0xAB815F8C, (q31_t)0x60262DD5, (q31_t)0xAB5BA41A,
+	(q31_t)0x6004F818, (q31_t)0xAB35F5B5, (q31_t)0x5FE3B38D,
+	(q31_t)0xAB105464, (q31_t)0x5FC26038, (q31_t)0xAAEAC02B,
+	(q31_t)0x5FA0FE1E, (q31_t)0xAAC53912, (q31_t)0x5F7F8D46,
+	(q31_t)0xAA9FBF1D, (q31_t)0x5F5E0DB3, (q31_t)0xAA7A5253,
+	(q31_t)0x5F3C7F6B, (q31_t)0xAA54F2B9, (q31_t)0x5F1AE273,
+	(q31_t)0xAA2FA055, (q31_t)0x5EF936D1, (q31_t)0xAA0A5B2D,
+	(q31_t)0x5ED77C89, (q31_t)0xA9E52347, (q31_t)0x5EB5B3A1,
+	(q31_t)0xA9BFF8A8, (q31_t)0x5E93DC1F, (q31_t)0xA99ADB56,
+	(q31_t)0x5E71F606, (q31_t)0xA975CB56, (q31_t)0x5E50015D,
+	(q31_t)0xA950C8AF, (q31_t)0x5E2DFE28, (q31_t)0xA92BD366,
+	(q31_t)0x5E0BEC6E, (q31_t)0xA906EB81, (q31_t)0x5DE9CC32,
+	(q31_t)0xA8E21106, (q31_t)0x5DC79D7C, (q31_t)0xA8BD43FA,
+	(q31_t)0x5DA5604E, (q31_t)0xA8988463, (q31_t)0x5D8314B0,
+	(q31_t)0xA873D246, (q31_t)0x5D60BAA6, (q31_t)0xA84F2DA9,
+	(q31_t)0x5D3E5236, (q31_t)0xA82A9693, (q31_t)0x5D1BDB65,
+	(q31_t)0xA8060D08, (q31_t)0x5CF95638, (q31_t)0xA7E1910E,
+	(q31_t)0x5CD6C2B4, (q31_t)0xA7BD22AB, (q31_t)0x5CB420DF,
+	(q31_t)0xA798C1E4, (q31_t)0x5C9170BF, (q31_t)0xA7746EC0,
+	(q31_t)0x5C6EB258, (q31_t)0xA7502943, (q31_t)0x5C4BE5B0,
+	(q31_t)0xA72BF173, (q31_t)0x5C290ACC, (q31_t)0xA707C756,
+	(q31_t)0x5C0621B2, (q31_t)0xA6E3AAF2, (q31_t)0x5BE32A67,
+	(q31_t)0xA6BF9C4B, (q31_t)0x5BC024F0, (q31_t)0xA69B9B68,
+	(q31_t)0x5B9D1153, (q31_t)0xA677A84E, (q31_t)0x5B79EF96,
+	(q31_t)0xA653C302, (q31_t)0x5B56BFBD, (q31_t)0xA62FEB8B,
+	(q31_t)0x5B3381CE, (q31_t)0xA60C21ED, (q31_t)0x5B1035CF,
+	(q31_t)0xA5E8662F, (q31_t)0x5AECDBC4, (q31_t)0xA5C4B855,
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+	(q31_t)0x30705217, (q31_t)0x8971F15A, (q31_t)0x3041C760,
+	(q31_t)0x895F072D, (q31_t)0x30133538, (q31_t)0x894C2F4C,
+	(q31_t)0x2FE49BA6, (q31_t)0x893969B9, (q31_t)0x2FB5FAB2,
+	(q31_t)0x8926B677, (q31_t)0x2F875262, (q31_t)0x89141589,
+	(q31_t)0x2F58A2BD, (q31_t)0x890186F1, (q31_t)0x2F29EBCC,
+	(q31_t)0x88EF0AB4, (q31_t)0x2EFB2D94, (q31_t)0x88DCA0D3,
+	(q31_t)0x2ECC681E, (q31_t)0x88CA4951, (q31_t)0x2E9D9B70,
+	(q31_t)0x88B80431, (q31_t)0x2E6EC792, (q31_t)0x88A5D177,
+	(q31_t)0x2E3FEC8B, (q31_t)0x8893B124, (q31_t)0x2E110A62,
+	(q31_t)0x8881A33C, (q31_t)0x2DE2211E, (q31_t)0x886FA7C2,
+	(q31_t)0x2DB330C7, (q31_t)0x885DBEB7, (q31_t)0x2D843963,
+	(q31_t)0x884BE820, (q31_t)0x2D553AFB, (q31_t)0x883A23FE,
+	(q31_t)0x2D263595, (q31_t)0x88287255, (q31_t)0x2CF72939,
+	(q31_t)0x8816D327, (q31_t)0x2CC815ED, (q31_t)0x88054677,
+	(q31_t)0x2C98FBBA, (q31_t)0x87F3CC47, (q31_t)0x2C69DAA6,
+	(q31_t)0x87E2649B, (q31_t)0x2C3AB2B9, (q31_t)0x87D10F75,
+	(q31_t)0x2C0B83F9, (q31_t)0x87BFCCD7, (q31_t)0x2BDC4E6F,
+	(q31_t)0x87AE9CC5, (q31_t)0x2BAD1221, (q31_t)0x879D7F40,
+	(q31_t)0x2B7DCF17, (q31_t)0x878C744C, (q31_t)0x2B4E8558,
+	(q31_t)0x877B7BEC, (q31_t)0x2B1F34EB, (q31_t)0x876A9621,
+	(q31_t)0x2AEFDDD8, (q31_t)0x8759C2EF, (q31_t)0x2AC08025,
+	(q31_t)0x87490257, (q31_t)0x2A911BDB, (q31_t)0x8738545E,
+	(q31_t)0x2A61B101, (q31_t)0x8727B904, (q31_t)0x2A323F9D,
+	(q31_t)0x8717304E, (q31_t)0x2A02C7B8, (q31_t)0x8706BA3C,
+	(q31_t)0x29D34958, (q31_t)0x86F656D3, (q31_t)0x29A3C484,
+	(q31_t)0x86E60614, (q31_t)0x29743945, (q31_t)0x86D5C802,
+	(q31_t)0x2944A7A2, (q31_t)0x86C59C9F, (q31_t)0x29150FA1,
+	(q31_t)0x86B583EE, (q31_t)0x28E5714A, (q31_t)0x86A57DF1,
+	(q31_t)0x28B5CCA5, (q31_t)0x86958AAB, (q31_t)0x288621B9,
+	(q31_t)0x8685AA1F, (q31_t)0x2856708C, (q31_t)0x8675DC4E,
+	(q31_t)0x2826B928, (q31_t)0x8666213C, (q31_t)0x27F6FB92,
+	(q31_t)0x865678EA, (q31_t)0x27C737D2, (q31_t)0x8646E35B,
+	(q31_t)0x27976DF1, (q31_t)0x86376092, (q31_t)0x27679DF4,
+	(q31_t)0x8627F090, (q31_t)0x2737C7E3, (q31_t)0x86189359,
+	(q31_t)0x2707EBC6, (q31_t)0x860948EE, (q31_t)0x26D809A5,
+	(q31_t)0x85FA1152, (q31_t)0x26A82185, (q31_t)0x85EAEC88,
+	(q31_t)0x26783370, (q31_t)0x85DBDA91, (q31_t)0x26483F6C,
+	(q31_t)0x85CCDB70, (q31_t)0x26184581, (q31_t)0x85BDEF27,
+	(q31_t)0x25E845B5, (q31_t)0x85AF15B9, (q31_t)0x25B84012,
+	(q31_t)0x85A04F28, (q31_t)0x2588349D, (q31_t)0x85919B75,
+	(q31_t)0x2558235E, (q31_t)0x8582FAA4, (q31_t)0x25280C5D,
+	(q31_t)0x85746CB7, (q31_t)0x24F7EFA1, (q31_t)0x8565F1B0,
+	(q31_t)0x24C7CD32, (q31_t)0x85578991, (q31_t)0x2497A517,
+	(q31_t)0x8549345C, (q31_t)0x24677757, (q31_t)0x853AF214,
+	(q31_t)0x243743FA, (q31_t)0x852CC2BA, (q31_t)0x24070B07,
+	(q31_t)0x851EA652, (q31_t)0x23D6CC86, (q31_t)0x85109CDC,
+	(q31_t)0x23A6887E, (q31_t)0x8502A65C, (q31_t)0x23763EF7,
+	(q31_t)0x84F4C2D3, (q31_t)0x2345EFF7, (q31_t)0x84E6F244,
+	(q31_t)0x23159B87, (q31_t)0x84D934B0, (q31_t)0x22E541AE,
+	(q31_t)0x84CB8A1B, (q31_t)0x22B4E274, (q31_t)0x84BDF285,
+	(q31_t)0x22847DDF, (q31_t)0x84B06DF1, (q31_t)0x225413F8,
+	(q31_t)0x84A2FC62, (q31_t)0x2223A4C5, (q31_t)0x84959DD9,
+	(q31_t)0x21F3304E, (q31_t)0x84885257, (q31_t)0x21C2B69C,
+	(q31_t)0x847B19E1, (q31_t)0x219237B4, (q31_t)0x846DF476,
+	(q31_t)0x2161B39F, (q31_t)0x8460E21A, (q31_t)0x21312A65,
+	(q31_t)0x8453E2CE, (q31_t)0x21009C0B, (q31_t)0x8446F695,
+	(q31_t)0x20D0089B, (q31_t)0x843A1D70, (q31_t)0x209F701C,
+	(q31_t)0x842D5761, (q31_t)0x206ED295, (q31_t)0x8420A46B,
+	(q31_t)0x203E300D, (q31_t)0x8414048F, (q31_t)0x200D888C,
+	(q31_t)0x840777CF, (q31_t)0x1FDCDC1A, (q31_t)0x83FAFE2E,
+	(q31_t)0x1FAC2ABF, (q31_t)0x83EE97AC, (q31_t)0x1F7B7480,
+	(q31_t)0x83E2444D, (q31_t)0x1F4AB967, (q31_t)0x83D60411,
+	(q31_t)0x1F19F97B, (q31_t)0x83C9D6FB, (q31_t)0x1EE934C2,
+	(q31_t)0x83BDBD0D, (q31_t)0x1EB86B46, (q31_t)0x83B1B649,
+	(q31_t)0x1E879D0C, (q31_t)0x83A5C2B0, (q31_t)0x1E56CA1E,
+	(q31_t)0x8399E244, (q31_t)0x1E25F281, (q31_t)0x838E1507,
+	(q31_t)0x1DF5163F, (q31_t)0x83825AFB, (q31_t)0x1DC4355D,
+	(q31_t)0x8376B422, (q31_t)0x1D934FE5, (q31_t)0x836B207D,
+	(q31_t)0x1D6265DD, (q31_t)0x835FA00E, (q31_t)0x1D31774D,
+	(q31_t)0x835432D8, (q31_t)0x1D00843C, (q31_t)0x8348D8DB,
+	(q31_t)0x1CCF8CB3, (q31_t)0x833D921A, (q31_t)0x1C9E90B8,
+	(q31_t)0x83325E97, (q31_t)0x1C6D9053, (q31_t)0x83273E52,
+	(q31_t)0x1C3C8B8C, (q31_t)0x831C314E, (q31_t)0x1C0B826A,
+	(q31_t)0x8311378C, (q31_t)0x1BDA74F5, (q31_t)0x8306510F,
+	(q31_t)0x1BA96334, (q31_t)0x82FB7DD8, (q31_t)0x1B784D30,
+	(q31_t)0x82F0BDE8, (q31_t)0x1B4732EF, (q31_t)0x82E61141,
+	(q31_t)0x1B161479, (q31_t)0x82DB77E5, (q31_t)0x1AE4F1D6,
+	(q31_t)0x82D0F1D5, (q31_t)0x1AB3CB0C, (q31_t)0x82C67F13,
+	(q31_t)0x1A82A025, (q31_t)0x82BC1FA1, (q31_t)0x1A517127,
+	(q31_t)0x82B1D381, (q31_t)0x1A203E1B, (q31_t)0x82A79AB3,
+	(q31_t)0x19EF0706, (q31_t)0x829D753A, (q31_t)0x19BDCBF2,
+	(q31_t)0x82936316, (q31_t)0x198C8CE6, (q31_t)0x8289644A,
+	(q31_t)0x195B49E9, (q31_t)0x827F78D8, (q31_t)0x192A0303,
+	(q31_t)0x8275A0C0, (q31_t)0x18F8B83C, (q31_t)0x826BDC04,
+	(q31_t)0x18C7699B, (q31_t)0x82622AA5, (q31_t)0x18961727,
+	(q31_t)0x82588CA6, (q31_t)0x1864C0E9, (q31_t)0x824F0208,
+	(q31_t)0x183366E8, (q31_t)0x82458ACB, (q31_t)0x1802092C,
+	(q31_t)0x823C26F2, (q31_t)0x17D0A7BB, (q31_t)0x8232D67E,
+	(q31_t)0x179F429F, (q31_t)0x82299971, (q31_t)0x176DD9DE,
+	(q31_t)0x82206FCB, (q31_t)0x173C6D80, (q31_t)0x8217598F,
+	(q31_t)0x170AFD8D, (q31_t)0x820E56BE, (q31_t)0x16D98A0C,
+	(q31_t)0x82056758, (q31_t)0x16A81305, (q31_t)0x81FC8B60,
+	(q31_t)0x1676987F, (q31_t)0x81F3C2D7, (q31_t)0x16451A83,
+	(q31_t)0x81EB0DBD, (q31_t)0x16139917, (q31_t)0x81E26C16,
+	(q31_t)0x15E21444, (q31_t)0x81D9DDE1, (q31_t)0x15B08C11,
+	(q31_t)0x81D16320, (q31_t)0x157F0086, (q31_t)0x81C8FBD5,
+	(q31_t)0x154D71AA, (q31_t)0x81C0A801, (q31_t)0x151BDF85,
+	(q31_t)0x81B867A4, (q31_t)0x14EA4A1F, (q31_t)0x81B03AC1,
+	(q31_t)0x14B8B17F, (q31_t)0x81A82159, (q31_t)0x148715AD,
+	(q31_t)0x81A01B6C, (q31_t)0x145576B1, (q31_t)0x819828FD,
+	(q31_t)0x1423D492, (q31_t)0x81904A0C, (q31_t)0x13F22F57,
+	(q31_t)0x81887E9A, (q31_t)0x13C0870A, (q31_t)0x8180C6A9,
+	(q31_t)0x138EDBB0, (q31_t)0x8179223A, (q31_t)0x135D2D53,
+	(q31_t)0x8171914E, (q31_t)0x132B7BF9, (q31_t)0x816A13E6,
+	(q31_t)0x12F9C7AA, (q31_t)0x8162AA03, (q31_t)0x12C8106E,
+	(q31_t)0x815B53A8, (q31_t)0x1296564D, (q31_t)0x815410D3,
+	(q31_t)0x1264994E, (q31_t)0x814CE188, (q31_t)0x1232D978,
+	(q31_t)0x8145C5C6, (q31_t)0x120116D4, (q31_t)0x813EBD90,
+	(q31_t)0x11CF516A, (q31_t)0x8137C8E6, (q31_t)0x119D8940,
+	(q31_t)0x8130E7C8, (q31_t)0x116BBE5F, (q31_t)0x812A1A39,
+	(q31_t)0x1139F0CE, (q31_t)0x81236039, (q31_t)0x11082096,
+	(q31_t)0x811CB9CA, (q31_t)0x10D64DBC, (q31_t)0x811626EC,
+	(q31_t)0x10A4784A, (q31_t)0x810FA7A0, (q31_t)0x1072A047,
+	(q31_t)0x81093BE8, (q31_t)0x1040C5BB, (q31_t)0x8102E3C3,
+	(q31_t)0x100EE8AD, (q31_t)0x80FC9F35, (q31_t)0x0FDD0925,
+	(q31_t)0x80F66E3C, (q31_t)0x0FAB272B, (q31_t)0x80F050DB,
+	(q31_t)0x0F7942C6, (q31_t)0x80EA4712, (q31_t)0x0F475BFE,
+	(q31_t)0x80E450E2, (q31_t)0x0F1572DC, (q31_t)0x80DE6E4C,
+	(q31_t)0x0EE38765, (q31_t)0x80D89F51, (q31_t)0x0EB199A3,
+	(q31_t)0x80D2E3F1, (q31_t)0x0E7FA99D, (q31_t)0x80CD3C2F,
+	(q31_t)0x0E4DB75B, (q31_t)0x80C7A80A, (q31_t)0x0E1BC2E3,
+	(q31_t)0x80C22783, (q31_t)0x0DE9CC3F, (q31_t)0x80BCBA9C,
+	(q31_t)0x0DB7D376, (q31_t)0x80B76155, (q31_t)0x0D85D88F,
+	(q31_t)0x80B21BAF, (q31_t)0x0D53DB92, (q31_t)0x80ACE9AB,
+	(q31_t)0x0D21DC87, (q31_t)0x80A7CB49, (q31_t)0x0CEFDB75,
+	(q31_t)0x80A2C08B, (q31_t)0x0CBDD865, (q31_t)0x809DC970,
+	(q31_t)0x0C8BD35E, (q31_t)0x8098E5FB, (q31_t)0x0C59CC67,
+	(q31_t)0x8094162B, (q31_t)0x0C27C389, (q31_t)0x808F5A02,
+	(q31_t)0x0BF5B8CB, (q31_t)0x808AB180, (q31_t)0x0BC3AC35,
+	(q31_t)0x80861CA5, (q31_t)0x0B919DCE, (q31_t)0x80819B74,
+	(q31_t)0x0B5F8D9F, (q31_t)0x807D2DEB, (q31_t)0x0B2D7BAE,
+	(q31_t)0x8078D40D, (q31_t)0x0AFB6805, (q31_t)0x80748DD9,
+	(q31_t)0x0AC952AA, (q31_t)0x80705B50, (q31_t)0x0A973BA5,
+	(q31_t)0x806C3C73, (q31_t)0x0A6522FE, (q31_t)0x80683143,
+	(q31_t)0x0A3308BC, (q31_t)0x806439C0, (q31_t)0x0A00ECE8,
+	(q31_t)0x806055EA, (q31_t)0x09CECF89, (q31_t)0x805C85C3,
+	(q31_t)0x099CB0A7, (q31_t)0x8058C94C, (q31_t)0x096A9049,
+	(q31_t)0x80552083, (q31_t)0x09386E77, (q31_t)0x80518B6B,
+	(q31_t)0x09064B3A, (q31_t)0x804E0A03, (q31_t)0x08D42698,
+	(q31_t)0x804A9C4D, (q31_t)0x08A2009A, (q31_t)0x80474248,
+	(q31_t)0x086FD947, (q31_t)0x8043FBF6, (q31_t)0x083DB0A7,
+	(q31_t)0x8040C956, (q31_t)0x080B86C1, (q31_t)0x803DAA69,
+	(q31_t)0x07D95B9E, (q31_t)0x803A9F31, (q31_t)0x07A72F45,
+	(q31_t)0x8037A7AC, (q31_t)0x077501BE, (q31_t)0x8034C3DC,
+	(q31_t)0x0742D310, (q31_t)0x8031F3C1, (q31_t)0x0710A344,
+	(q31_t)0x802F375C, (q31_t)0x06DE7261, (q31_t)0x802C8EAD,
+	(q31_t)0x06AC406F, (q31_t)0x8029F9B4, (q31_t)0x067A0D75,
+	(q31_t)0x80277872, (q31_t)0x0647D97C, (q31_t)0x80250AE7,
+	(q31_t)0x0615A48A, (q31_t)0x8022B113, (q31_t)0x05E36EA9,
+	(q31_t)0x80206AF8, (q31_t)0x05B137DF, (q31_t)0x801E3894,
+	(q31_t)0x057F0034, (q31_t)0x801C19E9, (q31_t)0x054CC7B0,
+	(q31_t)0x801A0EF7, (q31_t)0x051A8E5C, (q31_t)0x801817BF,
+	(q31_t)0x04E8543D, (q31_t)0x80163440, (q31_t)0x04B6195D,
+	(q31_t)0x8014647A, (q31_t)0x0483DDC3, (q31_t)0x8012A86F,
+	(q31_t)0x0451A176, (q31_t)0x8011001E, (q31_t)0x041F647F,
+	(q31_t)0x800F6B88, (q31_t)0x03ED26E6, (q31_t)0x800DEAAC,
+	(q31_t)0x03BAE8B1, (q31_t)0x800C7D8C, (q31_t)0x0388A9E9,
+	(q31_t)0x800B2427, (q31_t)0x03566A96, (q31_t)0x8009DE7D,
+	(q31_t)0x03242ABF, (q31_t)0x8008AC90, (q31_t)0x02F1EA6B,
+	(q31_t)0x80078E5E, (q31_t)0x02BFA9A4, (q31_t)0x800683E8,
+	(q31_t)0x028D6870, (q31_t)0x80058D2E, (q31_t)0x025B26D7,
+	(q31_t)0x8004AA31, (q31_t)0x0228E4E1, (q31_t)0x8003DAF0,
+	(q31_t)0x01F6A296, (q31_t)0x80031F6C, (q31_t)0x01C45FFE,
+	(q31_t)0x800277A5, (q31_t)0x01921D1F, (q31_t)0x8001E39B,
+	(q31_t)0x015FDA03, (q31_t)0x8001634D, (q31_t)0x012D96B0,
+	(q31_t)0x8000F6BD, (q31_t)0x00FB532F, (q31_t)0x80009DE9,
+	(q31_t)0x00C90F88, (q31_t)0x800058D3, (q31_t)0x0096CBC1,
+	(q31_t)0x8000277A, (q31_t)0x006487E3, (q31_t)0x800009DE,
+	(q31_t)0x003243F5, (q31_t)0x80000000, (q31_t)0x00000000,
+	(q31_t)0x800009DE, (q31_t)0xFFCDBC0A, (q31_t)0x8000277A,
+	(q31_t)0xFF9B781D, (q31_t)0x800058D3, (q31_t)0xFF69343E,
+	(q31_t)0x80009DE9, (q31_t)0xFF36F078, (q31_t)0x8000F6BD,
+	(q31_t)0xFF04ACD0, (q31_t)0x8001634D, (q31_t)0xFED2694F,
+	(q31_t)0x8001E39B, (q31_t)0xFEA025FC, (q31_t)0x800277A5,
+	(q31_t)0xFE6DE2E0, (q31_t)0x80031F6C, (q31_t)0xFE3BA001,
+	(q31_t)0x8003DAF0, (q31_t)0xFE095D69, (q31_t)0x8004AA31,
+	(q31_t)0xFDD71B1E, (q31_t)0x80058D2E, (q31_t)0xFDA4D928,
+	(q31_t)0x800683E8, (q31_t)0xFD72978F, (q31_t)0x80078E5E,
+	(q31_t)0xFD40565B, (q31_t)0x8008AC90, (q31_t)0xFD0E1594,
+	(q31_t)0x8009DE7D, (q31_t)0xFCDBD541, (q31_t)0x800B2427,
+	(q31_t)0xFCA99569, (q31_t)0x800C7D8C, (q31_t)0xFC775616,
+	(q31_t)0x800DEAAC, (q31_t)0xFC45174E, (q31_t)0x800F6B88,
+	(q31_t)0xFC12D919, (q31_t)0x8011001E, (q31_t)0xFBE09B80,
+	(q31_t)0x8012A86F, (q31_t)0xFBAE5E89, (q31_t)0x8014647A,
+	(q31_t)0xFB7C223C, (q31_t)0x80163440, (q31_t)0xFB49E6A2,
+	(q31_t)0x801817BF, (q31_t)0xFB17ABC2, (q31_t)0x801A0EF7,
+	(q31_t)0xFAE571A4, (q31_t)0x801C19E9, (q31_t)0xFAB3384F,
+	(q31_t)0x801E3894, (q31_t)0xFA80FFCB, (q31_t)0x80206AF8,
+	(q31_t)0xFA4EC820, (q31_t)0x8022B113, (q31_t)0xFA1C9156,
+	(q31_t)0x80250AE7, (q31_t)0xF9EA5B75, (q31_t)0x80277872,
+	(q31_t)0xF9B82683, (q31_t)0x8029F9B4, (q31_t)0xF985F28A,
+	(q31_t)0x802C8EAD, (q31_t)0xF953BF90, (q31_t)0x802F375C,
+	(q31_t)0xF9218D9E, (q31_t)0x8031F3C1, (q31_t)0xF8EF5CBB,
+	(q31_t)0x8034C3DC, (q31_t)0xF8BD2CEF, (q31_t)0x8037A7AC,
+	(q31_t)0xF88AFE41, (q31_t)0x803A9F31, (q31_t)0xF858D0BA,
+	(q31_t)0x803DAA69, (q31_t)0xF826A461, (q31_t)0x8040C956,
+	(q31_t)0xF7F4793E, (q31_t)0x8043FBF6, (q31_t)0xF7C24F58,
+	(q31_t)0x80474248, (q31_t)0xF79026B8, (q31_t)0x804A9C4D,
+	(q31_t)0xF75DFF65, (q31_t)0x804E0A03, (q31_t)0xF72BD967,
+	(q31_t)0x80518B6B, (q31_t)0xF6F9B4C5, (q31_t)0x80552083,
+	(q31_t)0xF6C79188, (q31_t)0x8058C94C, (q31_t)0xF6956FB6,
+	(q31_t)0x805C85C3, (q31_t)0xF6634F58, (q31_t)0x806055EA,
+	(q31_t)0xF6313076, (q31_t)0x806439C0, (q31_t)0xF5FF1317,
+	(q31_t)0x80683143, (q31_t)0xF5CCF743, (q31_t)0x806C3C73,
+	(q31_t)0xF59ADD01, (q31_t)0x80705B50, (q31_t)0xF568C45A,
+	(q31_t)0x80748DD9, (q31_t)0xF536AD55, (q31_t)0x8078D40D,
+	(q31_t)0xF50497FA, (q31_t)0x807D2DEB, (q31_t)0xF4D28451,
+	(q31_t)0x80819B74, (q31_t)0xF4A07260, (q31_t)0x80861CA5,
+	(q31_t)0xF46E6231, (q31_t)0x808AB180, (q31_t)0xF43C53CA,
+	(q31_t)0x808F5A02, (q31_t)0xF40A4734, (q31_t)0x8094162B,
+	(q31_t)0xF3D83C76, (q31_t)0x8098E5FB, (q31_t)0xF3A63398,
+	(q31_t)0x809DC970, (q31_t)0xF3742CA1, (q31_t)0x80A2C08B,
+	(q31_t)0xF342279A, (q31_t)0x80A7CB49, (q31_t)0xF310248A,
+	(q31_t)0x80ACE9AB, (q31_t)0xF2DE2378, (q31_t)0x80B21BAF,
+	(q31_t)0xF2AC246D, (q31_t)0x80B76155, (q31_t)0xF27A2770,
+	(q31_t)0x80BCBA9C, (q31_t)0xF2482C89, (q31_t)0x80C22783,
+	(q31_t)0xF21633C0, (q31_t)0x80C7A80A, (q31_t)0xF1E43D1C,
+	(q31_t)0x80CD3C2F, (q31_t)0xF1B248A5, (q31_t)0x80D2E3F1,
+	(q31_t)0xF1805662, (q31_t)0x80D89F51, (q31_t)0xF14E665C,
+	(q31_t)0x80DE6E4C, (q31_t)0xF11C789A, (q31_t)0x80E450E2,
+	(q31_t)0xF0EA8D23, (q31_t)0x80EA4712, (q31_t)0xF0B8A401,
+	(q31_t)0x80F050DB, (q31_t)0xF086BD39, (q31_t)0x80F66E3C,
+	(q31_t)0xF054D8D4, (q31_t)0x80FC9F35, (q31_t)0xF022F6DA,
+	(q31_t)0x8102E3C3, (q31_t)0xEFF11752, (q31_t)0x81093BE8,
+	(q31_t)0xEFBF3A44, (q31_t)0x810FA7A0, (q31_t)0xEF8D5FB8,
+	(q31_t)0x811626EC, (q31_t)0xEF5B87B5, (q31_t)0x811CB9CA,
+	(q31_t)0xEF29B243, (q31_t)0x81236039, (q31_t)0xEEF7DF6A,
+	(q31_t)0x812A1A39, (q31_t)0xEEC60F31, (q31_t)0x8130E7C8,
+	(q31_t)0xEE9441A0, (q31_t)0x8137C8E6, (q31_t)0xEE6276BF,
+	(q31_t)0x813EBD90, (q31_t)0xEE30AE95, (q31_t)0x8145C5C6,
+	(q31_t)0xEDFEE92B, (q31_t)0x814CE188, (q31_t)0xEDCD2687,
+	(q31_t)0x815410D3, (q31_t)0xED9B66B2, (q31_t)0x815B53A8,
+	(q31_t)0xED69A9B2, (q31_t)0x8162AA03, (q31_t)0xED37EF91,
+	(q31_t)0x816A13E6, (q31_t)0xED063855, (q31_t)0x8171914E,
+	(q31_t)0xECD48406, (q31_t)0x8179223A, (q31_t)0xECA2D2AC,
+	(q31_t)0x8180C6A9, (q31_t)0xEC71244F, (q31_t)0x81887E9A,
+	(q31_t)0xEC3F78F5, (q31_t)0x81904A0C, (q31_t)0xEC0DD0A8,
+	(q31_t)0x819828FD, (q31_t)0xEBDC2B6D, (q31_t)0x81A01B6C,
+	(q31_t)0xEBAA894E, (q31_t)0x81A82159, (q31_t)0xEB78EA52,
+	(q31_t)0x81B03AC1, (q31_t)0xEB474E80, (q31_t)0x81B867A4,
+	(q31_t)0xEB15B5E0, (q31_t)0x81C0A801, (q31_t)0xEAE4207A,
+	(q31_t)0x81C8FBD5, (q31_t)0xEAB28E55, (q31_t)0x81D16320,
+	(q31_t)0xEA80FF79, (q31_t)0x81D9DDE1, (q31_t)0xEA4F73EE,
+	(q31_t)0x81E26C16, (q31_t)0xEA1DEBBB, (q31_t)0x81EB0DBD,
+	(q31_t)0xE9EC66E8, (q31_t)0x81F3C2D7, (q31_t)0xE9BAE57C,
+	(q31_t)0x81FC8B60, (q31_t)0xE9896780, (q31_t)0x82056758,
+	(q31_t)0xE957ECFB, (q31_t)0x820E56BE, (q31_t)0xE92675F4,
+	(q31_t)0x8217598F, (q31_t)0xE8F50273, (q31_t)0x82206FCB,
+	(q31_t)0xE8C3927F, (q31_t)0x82299971, (q31_t)0xE8922621,
+	(q31_t)0x8232D67E, (q31_t)0xE860BD60, (q31_t)0x823C26F2,
+	(q31_t)0xE82F5844, (q31_t)0x82458ACB, (q31_t)0xE7FDF6D3,
+	(q31_t)0x824F0208, (q31_t)0xE7CC9917, (q31_t)0x82588CA6,
+	(q31_t)0xE79B3F16, (q31_t)0x82622AA5, (q31_t)0xE769E8D8,
+	(q31_t)0x826BDC04, (q31_t)0xE7389664, (q31_t)0x8275A0C0,
+	(q31_t)0xE70747C3, (q31_t)0x827F78D8, (q31_t)0xE6D5FCFC,
+	(q31_t)0x8289644A, (q31_t)0xE6A4B616, (q31_t)0x82936316,
+	(q31_t)0xE6737319, (q31_t)0x829D753A, (q31_t)0xE642340D,
+	(q31_t)0x82A79AB3, (q31_t)0xE610F8F9, (q31_t)0x82B1D381,
+	(q31_t)0xE5DFC1E4, (q31_t)0x82BC1FA1, (q31_t)0xE5AE8ED8,
+	(q31_t)0x82C67F13, (q31_t)0xE57D5FDA, (q31_t)0x82D0F1D5,
+	(q31_t)0xE54C34F3, (q31_t)0x82DB77E5, (q31_t)0xE51B0E2A,
+	(q31_t)0x82E61141, (q31_t)0xE4E9EB86, (q31_t)0x82F0BDE8,
+	(q31_t)0xE4B8CD10, (q31_t)0x82FB7DD8, (q31_t)0xE487B2CF,
+	(q31_t)0x8306510F, (q31_t)0xE4569CCB, (q31_t)0x8311378C,
+	(q31_t)0xE4258B0A, (q31_t)0x831C314E, (q31_t)0xE3F47D95,
+	(q31_t)0x83273E52, (q31_t)0xE3C37473, (q31_t)0x83325E97,
+	(q31_t)0xE3926FAC, (q31_t)0x833D921A, (q31_t)0xE3616F47,
+	(q31_t)0x8348D8DB, (q31_t)0xE330734C, (q31_t)0x835432D8,
+	(q31_t)0xE2FF7BC3, (q31_t)0x835FA00E, (q31_t)0xE2CE88B2,
+	(q31_t)0x836B207D, (q31_t)0xE29D9A22, (q31_t)0x8376B422,
+	(q31_t)0xE26CB01A, (q31_t)0x83825AFB, (q31_t)0xE23BCAA2,
+	(q31_t)0x838E1507, (q31_t)0xE20AE9C1, (q31_t)0x8399E244,
+	(q31_t)0xE1DA0D7E, (q31_t)0x83A5C2B0, (q31_t)0xE1A935E1,
+	(q31_t)0x83B1B649, (q31_t)0xE17862F3, (q31_t)0x83BDBD0D,
+	(q31_t)0xE14794B9, (q31_t)0x83C9D6FB, (q31_t)0xE116CB3D,
+	(q31_t)0x83D60411, (q31_t)0xE0E60684, (q31_t)0x83E2444D,
+	(q31_t)0xE0B54698, (q31_t)0x83EE97AC, (q31_t)0xE0848B7F,
+	(q31_t)0x83FAFE2E, (q31_t)0xE053D541, (q31_t)0x840777CF,
+	(q31_t)0xE02323E5, (q31_t)0x8414048F, (q31_t)0xDFF27773,
+	(q31_t)0x8420A46B, (q31_t)0xDFC1CFF2, (q31_t)0x842D5761,
+	(q31_t)0xDF912D6A, (q31_t)0x843A1D70, (q31_t)0xDF608FE3,
+	(q31_t)0x8446F695, (q31_t)0xDF2FF764, (q31_t)0x8453E2CE,
+	(q31_t)0xDEFF63F4, (q31_t)0x8460E21A, (q31_t)0xDECED59B,
+	(q31_t)0x846DF476, (q31_t)0xDE9E4C60, (q31_t)0x847B19E1,
+	(q31_t)0xDE6DC84B, (q31_t)0x84885257, (q31_t)0xDE3D4963,
+	(q31_t)0x84959DD9, (q31_t)0xDE0CCFB1, (q31_t)0x84A2FC62,
+	(q31_t)0xDDDC5B3A, (q31_t)0x84B06DF1, (q31_t)0xDDABEC07,
+	(q31_t)0x84BDF285, (q31_t)0xDD7B8220, (q31_t)0x84CB8A1B,
+	(q31_t)0xDD4B1D8B, (q31_t)0x84D934B0, (q31_t)0xDD1ABE51,
+	(q31_t)0x84E6F244, (q31_t)0xDCEA6478, (q31_t)0x84F4C2D3,
+	(q31_t)0xDCBA1008, (q31_t)0x8502A65C, (q31_t)0xDC89C108,
+	(q31_t)0x85109CDC, (q31_t)0xDC597781, (q31_t)0x851EA652,
+	(q31_t)0xDC293379, (q31_t)0x852CC2BA, (q31_t)0xDBF8F4F8,
+	(q31_t)0x853AF214, (q31_t)0xDBC8BC05, (q31_t)0x8549345C,
+	(q31_t)0xDB9888A8, (q31_t)0x85578991, (q31_t)0xDB685AE8,
+	(q31_t)0x8565F1B0, (q31_t)0xDB3832CD, (q31_t)0x85746CB7,
+	(q31_t)0xDB08105E, (q31_t)0x8582FAA4, (q31_t)0xDAD7F3A2,
+	(q31_t)0x85919B75, (q31_t)0xDAA7DCA1, (q31_t)0x85A04F28,
+	(q31_t)0xDA77CB62, (q31_t)0x85AF15B9, (q31_t)0xDA47BFED,
+	(q31_t)0x85BDEF27, (q31_t)0xDA17BA4A, (q31_t)0x85CCDB70,
+	(q31_t)0xD9E7BA7E, (q31_t)0x85DBDA91, (q31_t)0xD9B7C093,
+	(q31_t)0x85EAEC88, (q31_t)0xD987CC8F, (q31_t)0x85FA1152,
+	(q31_t)0xD957DE7A, (q31_t)0x860948EE, (q31_t)0xD927F65B,
+	(q31_t)0x86189359, (q31_t)0xD8F81439, (q31_t)0x8627F090,
+	(q31_t)0xD8C8381C, (q31_t)0x86376092, (q31_t)0xD898620C,
+	(q31_t)0x8646E35B, (q31_t)0xD868920F, (q31_t)0x865678EA,
+	(q31_t)0xD838C82D, (q31_t)0x8666213C, (q31_t)0xD809046D,
+	(q31_t)0x8675DC4E, (q31_t)0xD7D946D7, (q31_t)0x8685AA1F,
+	(q31_t)0xD7A98F73, (q31_t)0x86958AAB, (q31_t)0xD779DE46,
+	(q31_t)0x86A57DF1, (q31_t)0xD74A335A, (q31_t)0x86B583EE,
+	(q31_t)0xD71A8EB5, (q31_t)0x86C59C9F, (q31_t)0xD6EAF05E,
+	(q31_t)0x86D5C802, (q31_t)0xD6BB585D, (q31_t)0x86E60614,
+	(q31_t)0xD68BC6BA, (q31_t)0x86F656D3, (q31_t)0xD65C3B7B,
+	(q31_t)0x8706BA3C, (q31_t)0xD62CB6A7, (q31_t)0x8717304E,
+	(q31_t)0xD5FD3847, (q31_t)0x8727B904, (q31_t)0xD5CDC062,
+	(q31_t)0x8738545E, (q31_t)0xD59E4EFE, (q31_t)0x87490257,
+	(q31_t)0xD56EE424, (q31_t)0x8759C2EF, (q31_t)0xD53F7FDA,
+	(q31_t)0x876A9621, (q31_t)0xD5102227, (q31_t)0x877B7BEC,
+	(q31_t)0xD4E0CB14, (q31_t)0x878C744C, (q31_t)0xD4B17AA7,
+	(q31_t)0x879D7F40, (q31_t)0xD48230E8, (q31_t)0x87AE9CC5,
+	(q31_t)0xD452EDDE, (q31_t)0x87BFCCD7, (q31_t)0xD423B190,
+	(q31_t)0x87D10F75, (q31_t)0xD3F47C06, (q31_t)0x87E2649B,
+	(q31_t)0xD3C54D46, (q31_t)0x87F3CC47, (q31_t)0xD3962559,
+	(q31_t)0x88054677, (q31_t)0xD3670445, (q31_t)0x8816D327,
+	(q31_t)0xD337EA12, (q31_t)0x88287255, (q31_t)0xD308D6C6,
+	(q31_t)0x883A23FE, (q31_t)0xD2D9CA6A, (q31_t)0x884BE820,
+	(q31_t)0xD2AAC504, (q31_t)0x885DBEB7, (q31_t)0xD27BC69C,
+	(q31_t)0x886FA7C2, (q31_t)0xD24CCF38, (q31_t)0x8881A33C,
+	(q31_t)0xD21DDEE1, (q31_t)0x8893B124, (q31_t)0xD1EEF59E,
+	(q31_t)0x88A5D177, (q31_t)0xD1C01374, (q31_t)0x88B80431,
+	(q31_t)0xD191386D, (q31_t)0x88CA4951, (q31_t)0xD162648F,
+	(q31_t)0x88DCA0D3, (q31_t)0xD13397E1, (q31_t)0x88EF0AB4,
+	(q31_t)0xD104D26B, (q31_t)0x890186F1, (q31_t)0xD0D61433,
+	(q31_t)0x89141589, (q31_t)0xD0A75D42, (q31_t)0x8926B677,
+	(q31_t)0xD078AD9D, (q31_t)0x893969B9, (q31_t)0xD04A054D,
+	(q31_t)0x894C2F4C, (q31_t)0xD01B6459, (q31_t)0x895F072D,
+	(q31_t)0xCFECCAC7, (q31_t)0x8971F15A, (q31_t)0xCFBE389F,
+	(q31_t)0x8984EDCF, (q31_t)0xCF8FADE8, (q31_t)0x8997FC89,
+	(q31_t)0xCF612AAA, (q31_t)0x89AB1D86, (q31_t)0xCF32AEEB,
+	(q31_t)0x89BE50C3, (q31_t)0xCF043AB2, (q31_t)0x89D1963C,
+	(q31_t)0xCED5CE08, (q31_t)0x89E4EDEE, (q31_t)0xCEA768F2,
+	(q31_t)0x89F857D8, (q31_t)0xCE790B78, (q31_t)0x8A0BD3F5,
+	(q31_t)0xCE4AB5A2, (q31_t)0x8A1F6242, (q31_t)0xCE1C6776,
+	(q31_t)0x8A3302BD, (q31_t)0xCDEE20FC, (q31_t)0x8A46B563,
+	(q31_t)0xCDBFE23A, (q31_t)0x8A5A7A30, (q31_t)0xCD91AB38,
+	(q31_t)0x8A6E5122, (q31_t)0xCD637BFD, (q31_t)0x8A823A35,
+	(q31_t)0xCD355490, (q31_t)0x8A963567, (q31_t)0xCD0734F8,
+	(q31_t)0x8AAA42B4, (q31_t)0xCCD91D3D, (q31_t)0x8ABE6219,
+	(q31_t)0xCCAB0D65, (q31_t)0x8AD29393, (q31_t)0xCC7D0577,
+	(q31_t)0x8AE6D71F, (q31_t)0xCC4F057B, (q31_t)0x8AFB2CBA,
+	(q31_t)0xCC210D78, (q31_t)0x8B0F9461, (q31_t)0xCBF31D75,
+	(q31_t)0x8B240E10, (q31_t)0xCBC53578, (q31_t)0x8B3899C5,
+	(q31_t)0xCB975589, (q31_t)0x8B4D377C, (q31_t)0xCB697DB0,
+	(q31_t)0x8B61E732, (q31_t)0xCB3BADF2, (q31_t)0x8B76A8E4,
+	(q31_t)0xCB0DE658, (q31_t)0x8B8B7C8F, (q31_t)0xCAE026E8,
+	(q31_t)0x8BA0622F, (q31_t)0xCAB26FA9, (q31_t)0x8BB559C1,
+	(q31_t)0xCA84C0A2, (q31_t)0x8BCA6342, (q31_t)0xCA5719DB,
+	(q31_t)0x8BDF7EAF, (q31_t)0xCA297B5A, (q31_t)0x8BF4AC05,
+	(q31_t)0xC9FBE527, (q31_t)0x8C09EB40, (q31_t)0xC9CE5748,
+	(q31_t)0x8C1F3C5C, (q31_t)0xC9A0D1C4, (q31_t)0x8C349F58,
+	(q31_t)0xC97354A3, (q31_t)0x8C4A142F, (q31_t)0xC945DFEC,
+	(q31_t)0x8C5F9ADD, (q31_t)0xC91873A5, (q31_t)0x8C753361,
+	(q31_t)0xC8EB0FD6, (q31_t)0x8C8ADDB6, (q31_t)0xC8BDB485,
+	(q31_t)0x8CA099D9, (q31_t)0xC89061BA, (q31_t)0x8CB667C7,
+	(q31_t)0xC863177B, (q31_t)0x8CCC477D, (q31_t)0xC835D5D0,
+	(q31_t)0x8CE238F6, (q31_t)0xC8089CBF, (q31_t)0x8CF83C30,
+	(q31_t)0xC7DB6C50, (q31_t)0x8D0E5127, (q31_t)0xC7AE4489,
+	(q31_t)0x8D2477D8, (q31_t)0xC7812571, (q31_t)0x8D3AB03F,
+	(q31_t)0xC7540F10, (q31_t)0x8D50FA59, (q31_t)0xC727016C,
+	(q31_t)0x8D675623, (q31_t)0xC6F9FC8D, (q31_t)0x8D7DC399,
+	(q31_t)0xC6CD0079, (q31_t)0x8D9442B7, (q31_t)0xC6A00D36,
+	(q31_t)0x8DAAD37B, (q31_t)0xC67322CD, (q31_t)0x8DC175E0,
+	(q31_t)0xC6464144, (q31_t)0x8DD829E4, (q31_t)0xC61968A2,
+	(q31_t)0x8DEEEF82, (q31_t)0xC5EC98ED, (q31_t)0x8E05C6B7,
+	(q31_t)0xC5BFD22E, (q31_t)0x8E1CAF80, (q31_t)0xC593146A,
+	(q31_t)0x8E33A9D9, (q31_t)0xC5665FA8, (q31_t)0x8E4AB5BF,
+	(q31_t)0xC539B3F0, (q31_t)0x8E61D32D, (q31_t)0xC50D1148,
+	(q31_t)0x8E790222, (q31_t)0xC4E077B8, (q31_t)0x8E904298,
+	(q31_t)0xC4B3E746, (q31_t)0x8EA7948C, (q31_t)0xC4875FF8,
+	(q31_t)0x8EBEF7FB, (q31_t)0xC45AE1D7, (q31_t)0x8ED66CE1,
+	(q31_t)0xC42E6CE8, (q31_t)0x8EEDF33B, (q31_t)0xC4020132,
+	(q31_t)0x8F058B04, (q31_t)0xC3D59EBD, (q31_t)0x8F1D343A,
+	(q31_t)0xC3A9458F, (q31_t)0x8F34EED8, (q31_t)0xC37CF5B0,
+	(q31_t)0x8F4CBADB, (q31_t)0xC350AF25, (q31_t)0x8F64983F,
+	(q31_t)0xC32471F6, (q31_t)0x8F7C8701, (q31_t)0xC2F83E2A,
+	(q31_t)0x8F94871D, (q31_t)0xC2CC13C7, (q31_t)0x8FAC988E,
+	(q31_t)0xC29FF2D4, (q31_t)0x8FC4BB53, (q31_t)0xC273DB58,
+	(q31_t)0x8FDCEF66, (q31_t)0xC247CD5A, (q31_t)0x8FF534C4,
+	(q31_t)0xC21BC8E0, (q31_t)0x900D8B69, (q31_t)0xC1EFCDF2,
+	(q31_t)0x9025F352, (q31_t)0xC1C3DC96, (q31_t)0x903E6C7A,
+	(q31_t)0xC197F4D3, (q31_t)0x9056F6DF, (q31_t)0xC16C16B0,
+	(q31_t)0x906F927B, (q31_t)0xC1404233, (q31_t)0x90883F4C,
+	(q31_t)0xC1147763, (q31_t)0x90A0FD4E, (q31_t)0xC0E8B648,
+	(q31_t)0x90B9CC7C, (q31_t)0xC0BCFEE7, (q31_t)0x90D2ACD3,
+	(q31_t)0xC0915147, (q31_t)0x90EB9E50, (q31_t)0xC065AD70,
+	(q31_t)0x9104A0ED, (q31_t)0xC03A1368, (q31_t)0x911DB4A8,
+	(q31_t)0xC00E8335, (q31_t)0x9136D97D, (q31_t)0xBFE2FCDF,
+	(q31_t)0x91500F67, (q31_t)0xBFB7806C, (q31_t)0x91695663,
+	(q31_t)0xBF8C0DE2, (q31_t)0x9182AE6C, (q31_t)0xBF60A54A,
+	(q31_t)0x919C1780, (q31_t)0xBF3546A8, (q31_t)0x91B5919A,
+	(q31_t)0xBF09F204, (q31_t)0x91CF1CB6, (q31_t)0xBEDEA765,
+	(q31_t)0x91E8B8D0, (q31_t)0xBEB366D1, (q31_t)0x920265E4,
+	(q31_t)0xBE88304F, (q31_t)0x921C23EE, (q31_t)0xBE5D03E5,
+	(q31_t)0x9235F2EB, (q31_t)0xBE31E19B, (q31_t)0x924FD2D6,
+	(q31_t)0xBE06C977, (q31_t)0x9269C3AC, (q31_t)0xBDDBBB7F,
+	(q31_t)0x9283C567, (q31_t)0xBDB0B7BA, (q31_t)0x929DD805,
+	(q31_t)0xBD85BE2F, (q31_t)0x92B7FB82, (q31_t)0xBD5ACEE5,
+	(q31_t)0x92D22FD8, (q31_t)0xBD2FE9E1, (q31_t)0x92EC7505,
+	(q31_t)0xBD050F2C, (q31_t)0x9306CB04, (q31_t)0xBCDA3ECA,
+	(q31_t)0x932131D1, (q31_t)0xBCAF78C3, (q31_t)0x933BA968,
+	(q31_t)0xBC84BD1E, (q31_t)0x935631C5, (q31_t)0xBC5A0BE1,
+	(q31_t)0x9370CAE4, (q31_t)0xBC2F6513, (q31_t)0x938B74C0,
+	(q31_t)0xBC04C8BA, (q31_t)0x93A62F56, (q31_t)0xBBDA36DC,
+	(q31_t)0x93C0FAA2, (q31_t)0xBBAFAF81, (q31_t)0x93DBD69F,
+	(q31_t)0xBB8532AF, (q31_t)0x93F6C34A, (q31_t)0xBB5AC06C,
+	(q31_t)0x9411C09D, (q31_t)0xBB3058C0, (q31_t)0x942CCE95,
+	(q31_t)0xBB05FBB0, (q31_t)0x9447ED2F, (q31_t)0xBADBA943,
+	(q31_t)0x94631C64, (q31_t)0xBAB1617F, (q31_t)0x947E5C32,
+	(q31_t)0xBA87246C, (q31_t)0x9499AC95, (q31_t)0xBA5CF210,
+	(q31_t)0x94B50D87, (q31_t)0xBA32CA70, (q31_t)0x94D07F05,
+	(q31_t)0xBA08AD94, (q31_t)0x94EC010B, (q31_t)0xB9DE9B83,
+	(q31_t)0x95079393, (q31_t)0xB9B49442, (q31_t)0x9523369B,
+	(q31_t)0xB98A97D8, (q31_t)0x953EEA1E, (q31_t)0xB960A64B,
+	(q31_t)0x955AAE17, (q31_t)0xB936BFA3, (q31_t)0x95768282,
+	(q31_t)0xB90CE3E6, (q31_t)0x9592675B, (q31_t)0xB8E31319,
+	(q31_t)0x95AE5C9E, (q31_t)0xB8B94D44, (q31_t)0x95CA6246,
+	(q31_t)0xB88F926C, (q31_t)0x95E6784F, (q31_t)0xB865E299,
+	(q31_t)0x96029EB5, (q31_t)0xB83C3DD1, (q31_t)0x961ED573,
+	(q31_t)0xB812A419, (q31_t)0x963B1C85, (q31_t)0xB7E9157A,
+	(q31_t)0x965773E7, (q31_t)0xB7BF91F8, (q31_t)0x9673DB94,
+	(q31_t)0xB796199B, (q31_t)0x96905387, (q31_t)0xB76CAC68,
+	(q31_t)0x96ACDBBD, (q31_t)0xB7434A67, (q31_t)0x96C97431,
+	(q31_t)0xB719F39D, (q31_t)0x96E61CDF, (q31_t)0xB6F0A811,
+	(q31_t)0x9702D5C2, (q31_t)0xB6C767CA, (q31_t)0x971F9ED6,
+	(q31_t)0xB69E32CD, (q31_t)0x973C7816, (q31_t)0xB6750921,
+	(q31_t)0x9759617E, (q31_t)0xB64BEACC, (q31_t)0x97765B0A,
+	(q31_t)0xB622D7D5, (q31_t)0x979364B5, (q31_t)0xB5F9D042,
+	(q31_t)0x97B07E7A, (q31_t)0xB5D0D41A, (q31_t)0x97CDA855,
+	(q31_t)0xB5A7E362, (q31_t)0x97EAE241, (q31_t)0xB57EFE21,
+	(q31_t)0x98082C3B, (q31_t)0xB556245E, (q31_t)0x9825863D,
+	(q31_t)0xB52D561E, (q31_t)0x9842F043, (q31_t)0xB5049368,
+	(q31_t)0x98606A48, (q31_t)0xB4DBDC42, (q31_t)0x987DF449,
+	(q31_t)0xB4B330B2, (q31_t)0x989B8E3F, (q31_t)0xB48A90C0,
+	(q31_t)0x98B93828, (q31_t)0xB461FC70, (q31_t)0x98D6F1FE,
+	(q31_t)0xB43973C9, (q31_t)0x98F4BBBC, (q31_t)0xB410F6D2,
+	(q31_t)0x9912955E, (q31_t)0xB3E88591, (q31_t)0x99307EE0,
+	(q31_t)0xB3C0200C, (q31_t)0x994E783C, (q31_t)0xB397C649,
+	(q31_t)0x996C816F, (q31_t)0xB36F784E, (q31_t)0x998A9A73,
+	(q31_t)0xB3473622, (q31_t)0x99A8C344, (q31_t)0xB31EFFCB,
+	(q31_t)0x99C6FBDE, (q31_t)0xB2F6D54F, (q31_t)0x99E5443A,
+	(q31_t)0xB2CEB6B5, (q31_t)0x9A039C56, (q31_t)0xB2A6A401,
+	(q31_t)0x9A22042C, (q31_t)0xB27E9D3B, (q31_t)0x9A407BB8,
+	(q31_t)0xB256A26A, (q31_t)0x9A5F02F5, (q31_t)0xB22EB392,
+	(q31_t)0x9A7D99DD, (q31_t)0xB206D0BA, (q31_t)0x9A9C406D,
+	(q31_t)0xB1DEF9E8, (q31_t)0x9ABAF6A0, (q31_t)0xB1B72F23,
+	(q31_t)0x9AD9BC71, (q31_t)0xB18F7070, (q31_t)0x9AF891DB,
+	(q31_t)0xB167BDD6, (q31_t)0x9B1776D9, (q31_t)0xB140175B,
+	(q31_t)0x9B366B67, (q31_t)0xB1187D05, (q31_t)0x9B556F80,
+	(q31_t)0xB0F0EEDA, (q31_t)0x9B748320, (q31_t)0xB0C96CDF,
+	(q31_t)0x9B93A640, (q31_t)0xB0A1F71C, (q31_t)0x9BB2D8DD,
+	(q31_t)0xB07A8D97, (q31_t)0x9BD21AF2, (q31_t)0xB0533055,
+	(q31_t)0x9BF16C7A, (q31_t)0xB02BDF5C, (q31_t)0x9C10CD70,
+	(q31_t)0xB0049AB2, (q31_t)0x9C303DCF, (q31_t)0xAFDD625F,
+	(q31_t)0x9C4FBD92, (q31_t)0xAFB63667, (q31_t)0x9C6F4CB5,
+	(q31_t)0xAF8F16D0, (q31_t)0x9C8EEB33, (q31_t)0xAF6803A1,
+	(q31_t)0x9CAE9907, (q31_t)0xAF40FCE0, (q31_t)0x9CCE562B,
+	(q31_t)0xAF1A0293, (q31_t)0x9CEE229C, (q31_t)0xAEF314BF,
+	(q31_t)0x9D0DFE53, (q31_t)0xAECC336B, (q31_t)0x9D2DE94D,
+	(q31_t)0xAEA55E9D, (q31_t)0x9D4DE384, (q31_t)0xAE7E965B,
+	(q31_t)0x9D6DECF4, (q31_t)0xAE57DAAA, (q31_t)0x9D8E0596,
+	(q31_t)0xAE312B91, (q31_t)0x9DAE2D68, (q31_t)0xAE0A8916,
+	(q31_t)0x9DCE6462, (q31_t)0xADE3F33E, (q31_t)0x9DEEAA82,
+	(q31_t)0xADBD6A10, (q31_t)0x9E0EFFC1, (q31_t)0xAD96ED91,
+	(q31_t)0x9E2F641A, (q31_t)0xAD707DC8, (q31_t)0x9E4FD789,
+	(q31_t)0xAD4A1ABA, (q31_t)0x9E705A09, (q31_t)0xAD23C46D,
+	(q31_t)0x9E90EB94, (q31_t)0xACFD7AE8, (q31_t)0x9EB18C26,
+	(q31_t)0xACD73E30, (q31_t)0x9ED23BB9, (q31_t)0xACB10E4A,
+	(q31_t)0x9EF2FA48, (q31_t)0xAC8AEB3E, (q31_t)0x9F13C7D0,
+	(q31_t)0xAC64D510, (q31_t)0x9F34A449, (q31_t)0xAC3ECBC7,
+	(q31_t)0x9F558FB0, (q31_t)0xAC18CF68, (q31_t)0x9F7689FF,
+	(q31_t)0xABF2DFFA, (q31_t)0x9F979331, (q31_t)0xABCCFD82,
+	(q31_t)0x9FB8AB41, (q31_t)0xABA72806, (q31_t)0x9FD9D22A,
+	(q31_t)0xAB815F8C, (q31_t)0x9FFB07E7, (q31_t)0xAB5BA41A,
+	(q31_t)0xA01C4C72, (q31_t)0xAB35F5B5, (q31_t)0xA03D9FC7,
+	(q31_t)0xAB105464, (q31_t)0xA05F01E1, (q31_t)0xAAEAC02B,
+	(q31_t)0xA08072BA, (q31_t)0xAAC53912, (q31_t)0xA0A1F24C,
+	(q31_t)0xAA9FBF1D, (q31_t)0xA0C38094, (q31_t)0xAA7A5253,
+	(q31_t)0xA0E51D8C, (q31_t)0xAA54F2B9, (q31_t)0xA106C92E,
+	(q31_t)0xAA2FA055, (q31_t)0xA1288376, (q31_t)0xAA0A5B2D,
+	(q31_t)0xA14A4C5E, (q31_t)0xA9E52347, (q31_t)0xA16C23E1,
+	(q31_t)0xA9BFF8A8, (q31_t)0xA18E09F9, (q31_t)0xA99ADB56,
+	(q31_t)0xA1AFFEA2, (q31_t)0xA975CB56, (q31_t)0xA1D201D7,
+	(q31_t)0xA950C8AF, (q31_t)0xA1F41391, (q31_t)0xA92BD366,
+	(q31_t)0xA21633CD, (q31_t)0xA906EB81, (q31_t)0xA2386283,
+	(q31_t)0xA8E21106, (q31_t)0xA25A9FB1, (q31_t)0xA8BD43FA,
+	(q31_t)0xA27CEB4F, (q31_t)0xA8988463, (q31_t)0xA29F4559,
+	(q31_t)0xA873D246, (q31_t)0xA2C1ADC9, (q31_t)0xA84F2DA9,
+	(q31_t)0xA2E4249A, (q31_t)0xA82A9693, (q31_t)0xA306A9C7,
+	(q31_t)0xA8060D08, (q31_t)0xA3293D4B, (q31_t)0xA7E1910E,
+	(q31_t)0xA34BDF20, (q31_t)0xA7BD22AB, (q31_t)0xA36E8F40,
+	(q31_t)0xA798C1E4, (q31_t)0xA3914DA7, (q31_t)0xA7746EC0,
+	(q31_t)0xA3B41A4F, (q31_t)0xA7502943, (q31_t)0xA3D6F533,
+	(q31_t)0xA72BF173, (q31_t)0xA3F9DE4D, (q31_t)0xA707C756,
+	(q31_t)0xA41CD598, (q31_t)0xA6E3AAF2, (q31_t)0xA43FDB0F,
+	(q31_t)0xA6BF9C4B, (q31_t)0xA462EEAC, (q31_t)0xA69B9B68,
+	(q31_t)0xA4861069, (q31_t)0xA677A84E, (q31_t)0xA4A94042,
+	(q31_t)0xA653C302, (q31_t)0xA4CC7E31, (q31_t)0xA62FEB8B,
+	(q31_t)0xA4EFCA31, (q31_t)0xA60C21ED, (q31_t)0xA513243B,
+	(q31_t)0xA5E8662F, (q31_t)0xA5368C4B, (q31_t)0xA5C4B855,
+	(q31_t)0xA55A025B, (q31_t)0xA5A11865, (q31_t)0xA57D8666,
+	(q31_t)0xA57D8666, (q31_t)0xA5A11865, (q31_t)0xA55A025B,
+	(q31_t)0xA5C4B855, (q31_t)0xA5368C4B, (q31_t)0xA5E8662F,
+	(q31_t)0xA513243B, (q31_t)0xA60C21ED, (q31_t)0xA4EFCA31,
+	(q31_t)0xA62FEB8B, (q31_t)0xA4CC7E31, (q31_t)0xA653C302,
+	(q31_t)0xA4A94042, (q31_t)0xA677A84E, (q31_t)0xA4861069,
+	(q31_t)0xA69B9B68, (q31_t)0xA462EEAC, (q31_t)0xA6BF9C4B,
+	(q31_t)0xA43FDB0F, (q31_t)0xA6E3AAF2, (q31_t)0xA41CD598,
+	(q31_t)0xA707C756, (q31_t)0xA3F9DE4D, (q31_t)0xA72BF173,
+	(q31_t)0xA3D6F533, (q31_t)0xA7502943, (q31_t)0xA3B41A4F,
+	(q31_t)0xA7746EC0, (q31_t)0xA3914DA7, (q31_t)0xA798C1E4,
+	(q31_t)0xA36E8F40, (q31_t)0xA7BD22AB, (q31_t)0xA34BDF20,
+	(q31_t)0xA7E1910E, (q31_t)0xA3293D4B, (q31_t)0xA8060D08,
+	(q31_t)0xA306A9C7, (q31_t)0xA82A9693, (q31_t)0xA2E4249A,
+	(q31_t)0xA84F2DA9, (q31_t)0xA2C1ADC9, (q31_t)0xA873D246,
+	(q31_t)0xA29F4559, (q31_t)0xA8988463, (q31_t)0xA27CEB4F,
+	(q31_t)0xA8BD43FA, (q31_t)0xA25A9FB1, (q31_t)0xA8E21106,
+	(q31_t)0xA2386283, (q31_t)0xA906EB81, (q31_t)0xA21633CD,
+	(q31_t)0xA92BD366, (q31_t)0xA1F41391, (q31_t)0xA950C8AF,
+	(q31_t)0xA1D201D7, (q31_t)0xA975CB56, (q31_t)0xA1AFFEA2,
+	(q31_t)0xA99ADB56, (q31_t)0xA18E09F9, (q31_t)0xA9BFF8A8,
+	(q31_t)0xA16C23E1, (q31_t)0xA9E52347, (q31_t)0xA14A4C5E,
+	(q31_t)0xAA0A5B2D, (q31_t)0xA1288376, (q31_t)0xAA2FA055,
+	(q31_t)0xA106C92E, (q31_t)0xAA54F2B9, (q31_t)0xA0E51D8C,
+	(q31_t)0xAA7A5253, (q31_t)0xA0C38094, (q31_t)0xAA9FBF1D,
+	(q31_t)0xA0A1F24C, (q31_t)0xAAC53912, (q31_t)0xA08072BA,
+	(q31_t)0xAAEAC02B, (q31_t)0xA05F01E1, (q31_t)0xAB105464,
+	(q31_t)0xA03D9FC7, (q31_t)0xAB35F5B5, (q31_t)0xA01C4C72,
+	(q31_t)0xAB5BA41A, (q31_t)0x9FFB07E7, (q31_t)0xAB815F8C,
+	(q31_t)0x9FD9D22A, (q31_t)0xABA72806, (q31_t)0x9FB8AB41,
+	(q31_t)0xABCCFD82, (q31_t)0x9F979331, (q31_t)0xABF2DFFA,
+	(q31_t)0x9F7689FF, (q31_t)0xAC18CF68, (q31_t)0x9F558FB0,
+	(q31_t)0xAC3ECBC7, (q31_t)0x9F34A449, (q31_t)0xAC64D510,
+	(q31_t)0x9F13C7D0, (q31_t)0xAC8AEB3E, (q31_t)0x9EF2FA48,
+	(q31_t)0xACB10E4A, (q31_t)0x9ED23BB9, (q31_t)0xACD73E30,
+	(q31_t)0x9EB18C26, (q31_t)0xACFD7AE8, (q31_t)0x9E90EB94,
+	(q31_t)0xAD23C46D, (q31_t)0x9E705A09, (q31_t)0xAD4A1ABA,
+	(q31_t)0x9E4FD789, (q31_t)0xAD707DC8, (q31_t)0x9E2F641A,
+	(q31_t)0xAD96ED91, (q31_t)0x9E0EFFC1, (q31_t)0xADBD6A10,
+	(q31_t)0x9DEEAA82, (q31_t)0xADE3F33E, (q31_t)0x9DCE6462,
+	(q31_t)0xAE0A8916, (q31_t)0x9DAE2D68, (q31_t)0xAE312B91,
+	(q31_t)0x9D8E0596, (q31_t)0xAE57DAAA, (q31_t)0x9D6DECF4,
+	(q31_t)0xAE7E965B, (q31_t)0x9D4DE384, (q31_t)0xAEA55E9D,
+	(q31_t)0x9D2DE94D, (q31_t)0xAECC336B, (q31_t)0x9D0DFE53,
+	(q31_t)0xAEF314BF, (q31_t)0x9CEE229C, (q31_t)0xAF1A0293,
+	(q31_t)0x9CCE562B, (q31_t)0xAF40FCE0, (q31_t)0x9CAE9907,
+	(q31_t)0xAF6803A1, (q31_t)0x9C8EEB33, (q31_t)0xAF8F16D0,
+	(q31_t)0x9C6F4CB5, (q31_t)0xAFB63667, (q31_t)0x9C4FBD92,
+	(q31_t)0xAFDD625F, (q31_t)0x9C303DCF, (q31_t)0xB0049AB2,
+	(q31_t)0x9C10CD70, (q31_t)0xB02BDF5C, (q31_t)0x9BF16C7A,
+	(q31_t)0xB0533055, (q31_t)0x9BD21AF2, (q31_t)0xB07A8D97,
+	(q31_t)0x9BB2D8DD, (q31_t)0xB0A1F71C, (q31_t)0x9B93A640,
+	(q31_t)0xB0C96CDF, (q31_t)0x9B748320, (q31_t)0xB0F0EEDA,
+	(q31_t)0x9B556F80, (q31_t)0xB1187D05, (q31_t)0x9B366B67,
+	(q31_t)0xB140175B, (q31_t)0x9B1776D9, (q31_t)0xB167BDD6,
+	(q31_t)0x9AF891DB, (q31_t)0xB18F7070, (q31_t)0x9AD9BC71,
+	(q31_t)0xB1B72F23, (q31_t)0x9ABAF6A0, (q31_t)0xB1DEF9E8,
+	(q31_t)0x9A9C406D, (q31_t)0xB206D0BA, (q31_t)0x9A7D99DD,
+	(q31_t)0xB22EB392, (q31_t)0x9A5F02F5, (q31_t)0xB256A26A,
+	(q31_t)0x9A407BB8, (q31_t)0xB27E9D3B, (q31_t)0x9A22042C,
+	(q31_t)0xB2A6A401, (q31_t)0x9A039C56, (q31_t)0xB2CEB6B5,
+	(q31_t)0x99E5443A, (q31_t)0xB2F6D54F, (q31_t)0x99C6FBDE,
+	(q31_t)0xB31EFFCB, (q31_t)0x99A8C344, (q31_t)0xB3473622,
+	(q31_t)0x998A9A73, (q31_t)0xB36F784E, (q31_t)0x996C816F,
+	(q31_t)0xB397C649, (q31_t)0x994E783C, (q31_t)0xB3C0200C,
+	(q31_t)0x99307EE0, (q31_t)0xB3E88591, (q31_t)0x9912955E,
+	(q31_t)0xB410F6D2, (q31_t)0x98F4BBBC, (q31_t)0xB43973C9,
+	(q31_t)0x98D6F1FE, (q31_t)0xB461FC70, (q31_t)0x98B93828,
+	(q31_t)0xB48A90C0, (q31_t)0x989B8E3F, (q31_t)0xB4B330B2,
+	(q31_t)0x987DF449, (q31_t)0xB4DBDC42, (q31_t)0x98606A48,
+	(q31_t)0xB5049368, (q31_t)0x9842F043, (q31_t)0xB52D561E,
+	(q31_t)0x9825863D, (q31_t)0xB556245E, (q31_t)0x98082C3B,
+	(q31_t)0xB57EFE21, (q31_t)0x97EAE241, (q31_t)0xB5A7E362,
+	(q31_t)0x97CDA855, (q31_t)0xB5D0D41A, (q31_t)0x97B07E7A,
+	(q31_t)0xB5F9D042, (q31_t)0x979364B5, (q31_t)0xB622D7D5,
+	(q31_t)0x97765B0A, (q31_t)0xB64BEACC, (q31_t)0x9759617E,
+	(q31_t)0xB6750921, (q31_t)0x973C7816, (q31_t)0xB69E32CD,
+	(q31_t)0x971F9ED6, (q31_t)0xB6C767CA, (q31_t)0x9702D5C2,
+	(q31_t)0xB6F0A811, (q31_t)0x96E61CDF, (q31_t)0xB719F39D,
+	(q31_t)0x96C97431, (q31_t)0xB7434A67, (q31_t)0x96ACDBBD,
+	(q31_t)0xB76CAC68, (q31_t)0x96905387, (q31_t)0xB796199B,
+	(q31_t)0x9673DB94, (q31_t)0xB7BF91F8, (q31_t)0x965773E7,
+	(q31_t)0xB7E9157A, (q31_t)0x963B1C85, (q31_t)0xB812A419,
+	(q31_t)0x961ED573, (q31_t)0xB83C3DD1, (q31_t)0x96029EB5,
+	(q31_t)0xB865E299, (q31_t)0x95E6784F, (q31_t)0xB88F926C,
+	(q31_t)0x95CA6246, (q31_t)0xB8B94D44, (q31_t)0x95AE5C9E,
+	(q31_t)0xB8E31319, (q31_t)0x9592675B, (q31_t)0xB90CE3E6,
+	(q31_t)0x95768282, (q31_t)0xB936BFA3, (q31_t)0x955AAE17,
+	(q31_t)0xB960A64B, (q31_t)0x953EEA1E, (q31_t)0xB98A97D8,
+	(q31_t)0x9523369B, (q31_t)0xB9B49442, (q31_t)0x95079393,
+	(q31_t)0xB9DE9B83, (q31_t)0x94EC010B, (q31_t)0xBA08AD94,
+	(q31_t)0x94D07F05, (q31_t)0xBA32CA70, (q31_t)0x94B50D87,
+	(q31_t)0xBA5CF210, (q31_t)0x9499AC95, (q31_t)0xBA87246C,
+	(q31_t)0x947E5C32, (q31_t)0xBAB1617F, (q31_t)0x94631C64,
+	(q31_t)0xBADBA943, (q31_t)0x9447ED2F, (q31_t)0xBB05FBB0,
+	(q31_t)0x942CCE95, (q31_t)0xBB3058C0, (q31_t)0x9411C09D,
+	(q31_t)0xBB5AC06C, (q31_t)0x93F6C34A, (q31_t)0xBB8532AF,
+	(q31_t)0x93DBD69F, (q31_t)0xBBAFAF81, (q31_t)0x93C0FAA2,
+	(q31_t)0xBBDA36DC, (q31_t)0x93A62F56, (q31_t)0xBC04C8BA,
+	(q31_t)0x938B74C0, (q31_t)0xBC2F6513, (q31_t)0x9370CAE4,
+	(q31_t)0xBC5A0BE1, (q31_t)0x935631C5, (q31_t)0xBC84BD1E,
+	(q31_t)0x933BA968, (q31_t)0xBCAF78C3, (q31_t)0x932131D1,
+	(q31_t)0xBCDA3ECA, (q31_t)0x9306CB04, (q31_t)0xBD050F2C,
+	(q31_t)0x92EC7505, (q31_t)0xBD2FE9E1, (q31_t)0x92D22FD8,
+	(q31_t)0xBD5ACEE5, (q31_t)0x92B7FB82, (q31_t)0xBD85BE2F,
+	(q31_t)0x929DD805, (q31_t)0xBDB0B7BA, (q31_t)0x9283C567,
+	(q31_t)0xBDDBBB7F, (q31_t)0x9269C3AC, (q31_t)0xBE06C977,
+	(q31_t)0x924FD2D6, (q31_t)0xBE31E19B, (q31_t)0x9235F2EB,
+	(q31_t)0xBE5D03E5, (q31_t)0x921C23EE, (q31_t)0xBE88304F,
+	(q31_t)0x920265E4, (q31_t)0xBEB366D1, (q31_t)0x91E8B8D0,
+	(q31_t)0xBEDEA765, (q31_t)0x91CF1CB6, (q31_t)0xBF09F204,
+	(q31_t)0x91B5919A, (q31_t)0xBF3546A8, (q31_t)0x919C1780,
+	(q31_t)0xBF60A54A, (q31_t)0x9182AE6C, (q31_t)0xBF8C0DE2,
+	(q31_t)0x91695663, (q31_t)0xBFB7806C, (q31_t)0x91500F67,
+	(q31_t)0xBFE2FCDF, (q31_t)0x9136D97D, (q31_t)0xC00E8335,
+	(q31_t)0x911DB4A8, (q31_t)0xC03A1368, (q31_t)0x9104A0ED,
+	(q31_t)0xC065AD70, (q31_t)0x90EB9E50, (q31_t)0xC0915147,
+	(q31_t)0x90D2ACD3, (q31_t)0xC0BCFEE7, (q31_t)0x90B9CC7C,
+	(q31_t)0xC0E8B648, (q31_t)0x90A0FD4E, (q31_t)0xC1147763,
+	(q31_t)0x90883F4C, (q31_t)0xC1404233, (q31_t)0x906F927B,
+	(q31_t)0xC16C16B0, (q31_t)0x9056F6DF, (q31_t)0xC197F4D3,
+	(q31_t)0x903E6C7A, (q31_t)0xC1C3DC96, (q31_t)0x9025F352,
+	(q31_t)0xC1EFCDF2, (q31_t)0x900D8B69, (q31_t)0xC21BC8E0,
+	(q31_t)0x8FF534C4, (q31_t)0xC247CD5A, (q31_t)0x8FDCEF66,
+	(q31_t)0xC273DB58, (q31_t)0x8FC4BB53, (q31_t)0xC29FF2D4,
+	(q31_t)0x8FAC988E, (q31_t)0xC2CC13C7, (q31_t)0x8F94871D,
+	(q31_t)0xC2F83E2A, (q31_t)0x8F7C8701, (q31_t)0xC32471F6,
+	(q31_t)0x8F64983F, (q31_t)0xC350AF25, (q31_t)0x8F4CBADB,
+	(q31_t)0xC37CF5B0, (q31_t)0x8F34EED8, (q31_t)0xC3A9458F,
+	(q31_t)0x8F1D343A, (q31_t)0xC3D59EBD, (q31_t)0x8F058B04,
+	(q31_t)0xC4020132, (q31_t)0x8EEDF33B, (q31_t)0xC42E6CE8,
+	(q31_t)0x8ED66CE1, (q31_t)0xC45AE1D7, (q31_t)0x8EBEF7FB,
+	(q31_t)0xC4875FF8, (q31_t)0x8EA7948C, (q31_t)0xC4B3E746,
+	(q31_t)0x8E904298, (q31_t)0xC4E077B8, (q31_t)0x8E790222,
+	(q31_t)0xC50D1148, (q31_t)0x8E61D32D, (q31_t)0xC539B3F0,
+	(q31_t)0x8E4AB5BF, (q31_t)0xC5665FA8, (q31_t)0x8E33A9D9,
+	(q31_t)0xC593146A, (q31_t)0x8E1CAF80, (q31_t)0xC5BFD22E,
+	(q31_t)0x8E05C6B7, (q31_t)0xC5EC98ED, (q31_t)0x8DEEEF82,
+	(q31_t)0xC61968A2, (q31_t)0x8DD829E4, (q31_t)0xC6464144,
+	(q31_t)0x8DC175E0, (q31_t)0xC67322CD, (q31_t)0x8DAAD37B,
+	(q31_t)0xC6A00D36, (q31_t)0x8D9442B7, (q31_t)0xC6CD0079,
+	(q31_t)0x8D7DC399, (q31_t)0xC6F9FC8D, (q31_t)0x8D675623,
+	(q31_t)0xC727016C, (q31_t)0x8D50FA59, (q31_t)0xC7540F10,
+	(q31_t)0x8D3AB03F, (q31_t)0xC7812571, (q31_t)0x8D2477D8,
+	(q31_t)0xC7AE4489, (q31_t)0x8D0E5127, (q31_t)0xC7DB6C50,
+	(q31_t)0x8CF83C30, (q31_t)0xC8089CBF, (q31_t)0x8CE238F6,
+	(q31_t)0xC835D5D0, (q31_t)0x8CCC477D, (q31_t)0xC863177B,
+	(q31_t)0x8CB667C7, (q31_t)0xC89061BA, (q31_t)0x8CA099D9,
+	(q31_t)0xC8BDB485, (q31_t)0x8C8ADDB6, (q31_t)0xC8EB0FD6,
+	(q31_t)0x8C753361, (q31_t)0xC91873A5, (q31_t)0x8C5F9ADD,
+	(q31_t)0xC945DFEC, (q31_t)0x8C4A142F, (q31_t)0xC97354A3,
+	(q31_t)0x8C349F58, (q31_t)0xC9A0D1C4, (q31_t)0x8C1F3C5C,
+	(q31_t)0xC9CE5748, (q31_t)0x8C09EB40, (q31_t)0xC9FBE527,
+	(q31_t)0x8BF4AC05, (q31_t)0xCA297B5A, (q31_t)0x8BDF7EAF,
+	(q31_t)0xCA5719DB, (q31_t)0x8BCA6342, (q31_t)0xCA84C0A2,
+	(q31_t)0x8BB559C1, (q31_t)0xCAB26FA9, (q31_t)0x8BA0622F,
+	(q31_t)0xCAE026E8, (q31_t)0x8B8B7C8F, (q31_t)0xCB0DE658,
+	(q31_t)0x8B76A8E4, (q31_t)0xCB3BADF2, (q31_t)0x8B61E732,
+	(q31_t)0xCB697DB0, (q31_t)0x8B4D377C, (q31_t)0xCB975589,
+	(q31_t)0x8B3899C5, (q31_t)0xCBC53578, (q31_t)0x8B240E10,
+	(q31_t)0xCBF31D75, (q31_t)0x8B0F9461, (q31_t)0xCC210D78,
+	(q31_t)0x8AFB2CBA, (q31_t)0xCC4F057B, (q31_t)0x8AE6D71F,
+	(q31_t)0xCC7D0577, (q31_t)0x8AD29393, (q31_t)0xCCAB0D65,
+	(q31_t)0x8ABE6219, (q31_t)0xCCD91D3D, (q31_t)0x8AAA42B4,
+	(q31_t)0xCD0734F8, (q31_t)0x8A963567, (q31_t)0xCD355490,
+	(q31_t)0x8A823A35, (q31_t)0xCD637BFD, (q31_t)0x8A6E5122,
+	(q31_t)0xCD91AB38, (q31_t)0x8A5A7A30, (q31_t)0xCDBFE23A,
+	(q31_t)0x8A46B563, (q31_t)0xCDEE20FC, (q31_t)0x8A3302BD,
+	(q31_t)0xCE1C6776, (q31_t)0x8A1F6242, (q31_t)0xCE4AB5A2,
+	(q31_t)0x8A0BD3F5, (q31_t)0xCE790B78, (q31_t)0x89F857D8,
+	(q31_t)0xCEA768F2, (q31_t)0x89E4EDEE, (q31_t)0xCED5CE08,
+	(q31_t)0x89D1963C, (q31_t)0xCF043AB2, (q31_t)0x89BE50C3,
+	(q31_t)0xCF32AEEB, (q31_t)0x89AB1D86, (q31_t)0xCF612AAA,
+	(q31_t)0x8997FC89, (q31_t)0xCF8FADE8, (q31_t)0x8984EDCF,
+	(q31_t)0xCFBE389F, (q31_t)0x8971F15A, (q31_t)0xCFECCAC7,
+	(q31_t)0x895F072D, (q31_t)0xD01B6459, (q31_t)0x894C2F4C,
+	(q31_t)0xD04A054D, (q31_t)0x893969B9, (q31_t)0xD078AD9D,
+	(q31_t)0x8926B677, (q31_t)0xD0A75D42, (q31_t)0x89141589,
+	(q31_t)0xD0D61433, (q31_t)0x890186F1, (q31_t)0xD104D26B,
+	(q31_t)0x88EF0AB4, (q31_t)0xD13397E1, (q31_t)0x88DCA0D3,
+	(q31_t)0xD162648F, (q31_t)0x88CA4951, (q31_t)0xD191386D,
+	(q31_t)0x88B80431, (q31_t)0xD1C01374, (q31_t)0x88A5D177,
+	(q31_t)0xD1EEF59E, (q31_t)0x8893B124, (q31_t)0xD21DDEE1,
+	(q31_t)0x8881A33C, (q31_t)0xD24CCF38, (q31_t)0x886FA7C2,
+	(q31_t)0xD27BC69C, (q31_t)0x885DBEB7, (q31_t)0xD2AAC504,
+	(q31_t)0x884BE820, (q31_t)0xD2D9CA6A, (q31_t)0x883A23FE,
+	(q31_t)0xD308D6C6, (q31_t)0x88287255, (q31_t)0xD337EA12,
+	(q31_t)0x8816D327, (q31_t)0xD3670445, (q31_t)0x88054677,
+	(q31_t)0xD3962559, (q31_t)0x87F3CC47, (q31_t)0xD3C54D46,
+	(q31_t)0x87E2649B, (q31_t)0xD3F47C06, (q31_t)0x87D10F75,
+	(q31_t)0xD423B190, (q31_t)0x87BFCCD7, (q31_t)0xD452EDDE,
+	(q31_t)0x87AE9CC5, (q31_t)0xD48230E8, (q31_t)0x879D7F40,
+	(q31_t)0xD4B17AA7, (q31_t)0x878C744C, (q31_t)0xD4E0CB14,
+	(q31_t)0x877B7BEC, (q31_t)0xD5102227, (q31_t)0x876A9621,
+	(q31_t)0xD53F7FDA, (q31_t)0x8759C2EF, (q31_t)0xD56EE424,
+	(q31_t)0x87490257, (q31_t)0xD59E4EFE, (q31_t)0x8738545E,
+	(q31_t)0xD5CDC062, (q31_t)0x8727B904, (q31_t)0xD5FD3847,
+	(q31_t)0x8717304E, (q31_t)0xD62CB6A7, (q31_t)0x8706BA3C,
+	(q31_t)0xD65C3B7B, (q31_t)0x86F656D3, (q31_t)0xD68BC6BA,
+	(q31_t)0x86E60614, (q31_t)0xD6BB585D, (q31_t)0x86D5C802,
+	(q31_t)0xD6EAF05E, (q31_t)0x86C59C9F, (q31_t)0xD71A8EB5,
+	(q31_t)0x86B583EE, (q31_t)0xD74A335A, (q31_t)0x86A57DF1,
+	(q31_t)0xD779DE46, (q31_t)0x86958AAB, (q31_t)0xD7A98F73,
+	(q31_t)0x8685AA1F, (q31_t)0xD7D946D7, (q31_t)0x8675DC4E,
+	(q31_t)0xD809046D, (q31_t)0x8666213C, (q31_t)0xD838C82D,
+	(q31_t)0x865678EA, (q31_t)0xD868920F, (q31_t)0x8646E35B,
+	(q31_t)0xD898620C, (q31_t)0x86376092, (q31_t)0xD8C8381C,
+	(q31_t)0x8627F090, (q31_t)0xD8F81439, (q31_t)0x86189359,
+	(q31_t)0xD927F65B, (q31_t)0x860948EE, (q31_t)0xD957DE7A,
+	(q31_t)0x85FA1152, (q31_t)0xD987CC8F, (q31_t)0x85EAEC88,
+	(q31_t)0xD9B7C093, (q31_t)0x85DBDA91, (q31_t)0xD9E7BA7E,
+	(q31_t)0x85CCDB70, (q31_t)0xDA17BA4A, (q31_t)0x85BDEF27,
+	(q31_t)0xDA47BFED, (q31_t)0x85AF15B9, (q31_t)0xDA77CB62,
+	(q31_t)0x85A04F28, (q31_t)0xDAA7DCA1, (q31_t)0x85919B75,
+	(q31_t)0xDAD7F3A2, (q31_t)0x8582FAA4, (q31_t)0xDB08105E,
+	(q31_t)0x85746CB7, (q31_t)0xDB3832CD, (q31_t)0x8565F1B0,
+	(q31_t)0xDB685AE8, (q31_t)0x85578991, (q31_t)0xDB9888A8,
+	(q31_t)0x8549345C, (q31_t)0xDBC8BC05, (q31_t)0x853AF214,
+	(q31_t)0xDBF8F4F8, (q31_t)0x852CC2BA, (q31_t)0xDC293379,
+	(q31_t)0x851EA652, (q31_t)0xDC597781, (q31_t)0x85109CDC,
+	(q31_t)0xDC89C108, (q31_t)0x8502A65C, (q31_t)0xDCBA1008,
+	(q31_t)0x84F4C2D3, (q31_t)0xDCEA6478, (q31_t)0x84E6F244,
+	(q31_t)0xDD1ABE51, (q31_t)0x84D934B0, (q31_t)0xDD4B1D8B,
+	(q31_t)0x84CB8A1B, (q31_t)0xDD7B8220, (q31_t)0x84BDF285,
+	(q31_t)0xDDABEC07, (q31_t)0x84B06DF1, (q31_t)0xDDDC5B3A,
+	(q31_t)0x84A2FC62, (q31_t)0xDE0CCFB1, (q31_t)0x84959DD9,
+	(q31_t)0xDE3D4963, (q31_t)0x84885257, (q31_t)0xDE6DC84B,
+	(q31_t)0x847B19E1, (q31_t)0xDE9E4C60, (q31_t)0x846DF476,
+	(q31_t)0xDECED59B, (q31_t)0x8460E21A, (q31_t)0xDEFF63F4,
+	(q31_t)0x8453E2CE, (q31_t)0xDF2FF764, (q31_t)0x8446F695,
+	(q31_t)0xDF608FE3, (q31_t)0x843A1D70, (q31_t)0xDF912D6A,
+	(q31_t)0x842D5761, (q31_t)0xDFC1CFF2, (q31_t)0x8420A46B,
+	(q31_t)0xDFF27773, (q31_t)0x8414048F, (q31_t)0xE02323E5,
+	(q31_t)0x840777CF, (q31_t)0xE053D541, (q31_t)0x83FAFE2E,
+	(q31_t)0xE0848B7F, (q31_t)0x83EE97AC, (q31_t)0xE0B54698,
+	(q31_t)0x83E2444D, (q31_t)0xE0E60684, (q31_t)0x83D60411,
+	(q31_t)0xE116CB3D, (q31_t)0x83C9D6FB, (q31_t)0xE14794B9,
+	(q31_t)0x83BDBD0D, (q31_t)0xE17862F3, (q31_t)0x83B1B649,
+	(q31_t)0xE1A935E1, (q31_t)0x83A5C2B0, (q31_t)0xE1DA0D7E,
+	(q31_t)0x8399E244, (q31_t)0xE20AE9C1, (q31_t)0x838E1507,
+	(q31_t)0xE23BCAA2, (q31_t)0x83825AFB, (q31_t)0xE26CB01A,
+	(q31_t)0x8376B422, (q31_t)0xE29D9A22, (q31_t)0x836B207D,
+	(q31_t)0xE2CE88B2, (q31_t)0x835FA00E, (q31_t)0xE2FF7BC3,
+	(q31_t)0x835432D8, (q31_t)0xE330734C, (q31_t)0x8348D8DB,
+	(q31_t)0xE3616F47, (q31_t)0x833D921A, (q31_t)0xE3926FAC,
+	(q31_t)0x83325E97, (q31_t)0xE3C37473, (q31_t)0x83273E52,
+	(q31_t)0xE3F47D95, (q31_t)0x831C314E, (q31_t)0xE4258B0A,
+	(q31_t)0x8311378C, (q31_t)0xE4569CCB, (q31_t)0x8306510F,
+	(q31_t)0xE487B2CF, (q31_t)0x82FB7DD8, (q31_t)0xE4B8CD10,
+	(q31_t)0x82F0BDE8, (q31_t)0xE4E9EB86, (q31_t)0x82E61141,
+	(q31_t)0xE51B0E2A, (q31_t)0x82DB77E5, (q31_t)0xE54C34F3,
+	(q31_t)0x82D0F1D5, (q31_t)0xE57D5FDA, (q31_t)0x82C67F13,
+	(q31_t)0xE5AE8ED8, (q31_t)0x82BC1FA1, (q31_t)0xE5DFC1E4,
+	(q31_t)0x82B1D381, (q31_t)0xE610F8F9, (q31_t)0x82A79AB3,
+	(q31_t)0xE642340D, (q31_t)0x829D753A, (q31_t)0xE6737319,
+	(q31_t)0x82936316, (q31_t)0xE6A4B616, (q31_t)0x8289644A,
+	(q31_t)0xE6D5FCFC, (q31_t)0x827F78D8, (q31_t)0xE70747C3,
+	(q31_t)0x8275A0C0, (q31_t)0xE7389664, (q31_t)0x826BDC04,
+	(q31_t)0xE769E8D8, (q31_t)0x82622AA5, (q31_t)0xE79B3F16,
+	(q31_t)0x82588CA6, (q31_t)0xE7CC9917, (q31_t)0x824F0208,
+	(q31_t)0xE7FDF6D3, (q31_t)0x82458ACB, (q31_t)0xE82F5844,
+	(q31_t)0x823C26F2, (q31_t)0xE860BD60, (q31_t)0x8232D67E,
+	(q31_t)0xE8922621, (q31_t)0x82299971, (q31_t)0xE8C3927F,
+	(q31_t)0x82206FCB, (q31_t)0xE8F50273, (q31_t)0x8217598F,
+	(q31_t)0xE92675F4, (q31_t)0x820E56BE, (q31_t)0xE957ECFB,
+	(q31_t)0x82056758, (q31_t)0xE9896780, (q31_t)0x81FC8B60,
+	(q31_t)0xE9BAE57C, (q31_t)0x81F3C2D7, (q31_t)0xE9EC66E8,
+	(q31_t)0x81EB0DBD, (q31_t)0xEA1DEBBB, (q31_t)0x81E26C16,
+	(q31_t)0xEA4F73EE, (q31_t)0x81D9DDE1, (q31_t)0xEA80FF79,
+	(q31_t)0x81D16320, (q31_t)0xEAB28E55, (q31_t)0x81C8FBD5,
+	(q31_t)0xEAE4207A, (q31_t)0x81C0A801, (q31_t)0xEB15B5E0,
+	(q31_t)0x81B867A4, (q31_t)0xEB474E80, (q31_t)0x81B03AC1,
+	(q31_t)0xEB78EA52, (q31_t)0x81A82159, (q31_t)0xEBAA894E,
+	(q31_t)0x81A01B6C, (q31_t)0xEBDC2B6D, (q31_t)0x819828FD,
+	(q31_t)0xEC0DD0A8, (q31_t)0x81904A0C, (q31_t)0xEC3F78F5,
+	(q31_t)0x81887E9A, (q31_t)0xEC71244F, (q31_t)0x8180C6A9,
+	(q31_t)0xECA2D2AC, (q31_t)0x8179223A, (q31_t)0xECD48406,
+	(q31_t)0x8171914E, (q31_t)0xED063855, (q31_t)0x816A13E6,
+	(q31_t)0xED37EF91, (q31_t)0x8162AA03, (q31_t)0xED69A9B2,
+	(q31_t)0x815B53A8, (q31_t)0xED9B66B2, (q31_t)0x815410D3,
+	(q31_t)0xEDCD2687, (q31_t)0x814CE188, (q31_t)0xEDFEE92B,
+	(q31_t)0x8145C5C6, (q31_t)0xEE30AE95, (q31_t)0x813EBD90,
+	(q31_t)0xEE6276BF, (q31_t)0x8137C8E6, (q31_t)0xEE9441A0,
+	(q31_t)0x8130E7C8, (q31_t)0xEEC60F31, (q31_t)0x812A1A39,
+	(q31_t)0xEEF7DF6A, (q31_t)0x81236039, (q31_t)0xEF29B243,
+	(q31_t)0x811CB9CA, (q31_t)0xEF5B87B5, (q31_t)0x811626EC,
+	(q31_t)0xEF8D5FB8, (q31_t)0x810FA7A0, (q31_t)0xEFBF3A44,
+	(q31_t)0x81093BE8, (q31_t)0xEFF11752, (q31_t)0x8102E3C3,
+	(q31_t)0xF022F6DA, (q31_t)0x80FC9F35, (q31_t)0xF054D8D4,
+	(q31_t)0x80F66E3C, (q31_t)0xF086BD39, (q31_t)0x80F050DB,
+	(q31_t)0xF0B8A401, (q31_t)0x80EA4712, (q31_t)0xF0EA8D23,
+	(q31_t)0x80E450E2, (q31_t)0xF11C789A, (q31_t)0x80DE6E4C,
+	(q31_t)0xF14E665C, (q31_t)0x80D89F51, (q31_t)0xF1805662,
+	(q31_t)0x80D2E3F1, (q31_t)0xF1B248A5, (q31_t)0x80CD3C2F,
+	(q31_t)0xF1E43D1C, (q31_t)0x80C7A80A, (q31_t)0xF21633C0,
+	(q31_t)0x80C22783, (q31_t)0xF2482C89, (q31_t)0x80BCBA9C,
+	(q31_t)0xF27A2770, (q31_t)0x80B76155, (q31_t)0xF2AC246D,
+	(q31_t)0x80B21BAF, (q31_t)0xF2DE2378, (q31_t)0x80ACE9AB,
+	(q31_t)0xF310248A, (q31_t)0x80A7CB49, (q31_t)0xF342279A,
+	(q31_t)0x80A2C08B, (q31_t)0xF3742CA1, (q31_t)0x809DC970,
+	(q31_t)0xF3A63398, (q31_t)0x8098E5FB, (q31_t)0xF3D83C76,
+	(q31_t)0x8094162B, (q31_t)0xF40A4734, (q31_t)0x808F5A02,
+	(q31_t)0xF43C53CA, (q31_t)0x808AB180, (q31_t)0xF46E6231,
+	(q31_t)0x80861CA5, (q31_t)0xF4A07260, (q31_t)0x80819B74,
+	(q31_t)0xF4D28451, (q31_t)0x807D2DEB, (q31_t)0xF50497FA,
+	(q31_t)0x8078D40D, (q31_t)0xF536AD55, (q31_t)0x80748DD9,
+	(q31_t)0xF568C45A, (q31_t)0x80705B50, (q31_t)0xF59ADD01,
+	(q31_t)0x806C3C73, (q31_t)0xF5CCF743, (q31_t)0x80683143,
+	(q31_t)0xF5FF1317, (q31_t)0x806439C0, (q31_t)0xF6313076,
+	(q31_t)0x806055EA, (q31_t)0xF6634F58, (q31_t)0x805C85C3,
+	(q31_t)0xF6956FB6, (q31_t)0x8058C94C, (q31_t)0xF6C79188,
+	(q31_t)0x80552083, (q31_t)0xF6F9B4C5, (q31_t)0x80518B6B,
+	(q31_t)0xF72BD967, (q31_t)0x804E0A03, (q31_t)0xF75DFF65,
+	(q31_t)0x804A9C4D, (q31_t)0xF79026B8, (q31_t)0x80474248,
+	(q31_t)0xF7C24F58, (q31_t)0x8043FBF6, (q31_t)0xF7F4793E,
+	(q31_t)0x8040C956, (q31_t)0xF826A461, (q31_t)0x803DAA69,
+	(q31_t)0xF858D0BA, (q31_t)0x803A9F31, (q31_t)0xF88AFE41,
+	(q31_t)0x8037A7AC, (q31_t)0xF8BD2CEF, (q31_t)0x8034C3DC,
+	(q31_t)0xF8EF5CBB, (q31_t)0x8031F3C1, (q31_t)0xF9218D9E,
+	(q31_t)0x802F375C, (q31_t)0xF953BF90, (q31_t)0x802C8EAD,
+	(q31_t)0xF985F28A, (q31_t)0x8029F9B4, (q31_t)0xF9B82683,
+	(q31_t)0x80277872, (q31_t)0xF9EA5B75, (q31_t)0x80250AE7,
+	(q31_t)0xFA1C9156, (q31_t)0x8022B113, (q31_t)0xFA4EC820,
+	(q31_t)0x80206AF8, (q31_t)0xFA80FFCB, (q31_t)0x801E3894,
+	(q31_t)0xFAB3384F, (q31_t)0x801C19E9, (q31_t)0xFAE571A4,
+	(q31_t)0x801A0EF7, (q31_t)0xFB17ABC2, (q31_t)0x801817BF,
+	(q31_t)0xFB49E6A2, (q31_t)0x80163440, (q31_t)0xFB7C223C,
+	(q31_t)0x8014647A, (q31_t)0xFBAE5E89, (q31_t)0x8012A86F,
+	(q31_t)0xFBE09B80, (q31_t)0x8011001E, (q31_t)0xFC12D919,
+	(q31_t)0x800F6B88, (q31_t)0xFC45174E, (q31_t)0x800DEAAC,
+	(q31_t)0xFC775616, (q31_t)0x800C7D8C, (q31_t)0xFCA99569,
+	(q31_t)0x800B2427, (q31_t)0xFCDBD541, (q31_t)0x8009DE7D,
+	(q31_t)0xFD0E1594, (q31_t)0x8008AC90, (q31_t)0xFD40565B,
+	(q31_t)0x80078E5E, (q31_t)0xFD72978F, (q31_t)0x800683E8,
+	(q31_t)0xFDA4D928, (q31_t)0x80058D2E, (q31_t)0xFDD71B1E,
+	(q31_t)0x8004AA31, (q31_t)0xFE095D69, (q31_t)0x8003DAF0,
+	(q31_t)0xFE3BA001, (q31_t)0x80031F6C, (q31_t)0xFE6DE2E0,
+	(q31_t)0x800277A5, (q31_t)0xFEA025FC, (q31_t)0x8001E39B,
+	(q31_t)0xFED2694F, (q31_t)0x8001634D, (q31_t)0xFF04ACD0,
+	(q31_t)0x8000F6BD, (q31_t)0xFF36F078, (q31_t)0x80009DE9,
+	(q31_t)0xFF69343E, (q31_t)0x800058D3, (q31_t)0xFF9B781D,
+	(q31_t)0x8000277A, (q31_t)0xFFCDBC0A, (q31_t)0x800009DE
+};
+
+
+
+/*
+* @brief  q15 Twiddle factors Table
+*/
+
+
+/**
+* \par
+* Example code for q15 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefq15[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefq15[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 16	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to q15(Fixed point 1.15):
+*	round(twiddleCoefq15(i) * pow(2, 15))
+*
+*/
+const q15_t twiddleCoef_16_q15[24] = {
+    (q15_t)0x7FFF, (q15_t)0x0000,
+    (q15_t)0x7641, (q15_t)0x30FB,
+    (q15_t)0x5A82, (q15_t)0x5A82,
+    (q15_t)0x30FB, (q15_t)0x7641,
+    (q15_t)0x0000, (q15_t)0x7FFF,
+    (q15_t)0xCF04, (q15_t)0x7641,
+    (q15_t)0xA57D, (q15_t)0x5A82,
+    (q15_t)0x89BE, (q15_t)0x30FB,
+    (q15_t)0x8000, (q15_t)0x0000,
+    (q15_t)0x89BE, (q15_t)0xCF04,
+    (q15_t)0xA57D, (q15_t)0xA57D,
+    (q15_t)0xCF04, (q15_t)0x89BE
+};
+
+/**
+* \par
+* Example code for q15 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefq15[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefq15[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 32	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to q15(Fixed point 1.15):
+*	round(twiddleCoefq15(i) * pow(2, 15))
+*
+*/
+const q15_t twiddleCoef_32_q15[48] = {
+    (q15_t)0x7FFF, (q15_t)0x0000,
+    (q15_t)0x7D8A, (q15_t)0x18F8,
+    (q15_t)0x7641, (q15_t)0x30FB,
+    (q15_t)0x6A6D, (q15_t)0x471C,
+    (q15_t)0x5A82, (q15_t)0x5A82,
+    (q15_t)0x471C, (q15_t)0x6A6D,
+    (q15_t)0x30FB, (q15_t)0x7641,
+    (q15_t)0x18F8, (q15_t)0x7D8A,
+    (q15_t)0x0000, (q15_t)0x7FFF,
+    (q15_t)0xE707, (q15_t)0x7D8A,
+    (q15_t)0xCF04, (q15_t)0x7641,
+    (q15_t)0xB8E3, (q15_t)0x6A6D,
+    (q15_t)0xA57D, (q15_t)0x5A82,
+    (q15_t)0x9592, (q15_t)0x471C,
+    (q15_t)0x89BE, (q15_t)0x30FB,
+    (q15_t)0x8275, (q15_t)0x18F8,
+    (q15_t)0x8000, (q15_t)0x0000,
+    (q15_t)0x8275, (q15_t)0xE707,
+    (q15_t)0x89BE, (q15_t)0xCF04,
+    (q15_t)0x9592, (q15_t)0xB8E3,
+    (q15_t)0xA57D, (q15_t)0xA57D,
+    (q15_t)0xB8E3, (q15_t)0x9592,
+    (q15_t)0xCF04, (q15_t)0x89BE,
+    (q15_t)0xE707, (q15_t)0x8275
+};
+
+/**
+* \par
+* Example code for q15 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefq15[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefq15[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 64	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to q15(Fixed point 1.15):
+*	round(twiddleCoefq15(i) * pow(2, 15))
+*
+*/
+const q15_t twiddleCoef_64_q15[96] = {
+	(q15_t)0x7FFF, (q15_t)0x0000, (q15_t)0x7F62, (q15_t)0x0C8B,
+	(q15_t)0x7D8A, (q15_t)0x18F8, (q15_t)0x7A7D, (q15_t)0x2528,
+	(q15_t)0x7641, (q15_t)0x30FB, (q15_t)0x70E2, (q15_t)0x3C56,
+	(q15_t)0x6A6D, (q15_t)0x471C, (q15_t)0x62F2, (q15_t)0x5133,
+	(q15_t)0x5A82, (q15_t)0x5A82, (q15_t)0x5133, (q15_t)0x62F2,
+	(q15_t)0x471C, (q15_t)0x6A6D, (q15_t)0x3C56, (q15_t)0x70E2,
+	(q15_t)0x30FB, (q15_t)0x7641, (q15_t)0x2528, (q15_t)0x7A7D,
+	(q15_t)0x18F8, (q15_t)0x7D8A, (q15_t)0x0C8B, (q15_t)0x7F62,
+	(q15_t)0x0000, (q15_t)0x7FFF, (q15_t)0xF374, (q15_t)0x7F62,
+	(q15_t)0xE707, (q15_t)0x7D8A, (q15_t)0xDAD7, (q15_t)0x7A7D,
+	(q15_t)0xCF04, (q15_t)0x7641, (q15_t)0xC3A9, (q15_t)0x70E2,
+	(q15_t)0xB8E3, (q15_t)0x6A6D, (q15_t)0xAECC, (q15_t)0x62F2,
+	(q15_t)0xA57D, (q15_t)0x5A82, (q15_t)0x9D0D, (q15_t)0x5133,
+	(q15_t)0x9592, (q15_t)0x471C, (q15_t)0x8F1D, (q15_t)0x3C56,
+	(q15_t)0x89BE, (q15_t)0x30FB, (q15_t)0x8582, (q15_t)0x2528,
+	(q15_t)0x8275, (q15_t)0x18F8, (q15_t)0x809D, (q15_t)0x0C8B,
+	(q15_t)0x8000, (q15_t)0x0000, (q15_t)0x809D, (q15_t)0xF374,
+	(q15_t)0x8275, (q15_t)0xE707, (q15_t)0x8582, (q15_t)0xDAD7,
+	(q15_t)0x89BE, (q15_t)0xCF04, (q15_t)0x8F1D, (q15_t)0xC3A9,
+	(q15_t)0x9592, (q15_t)0xB8E3, (q15_t)0x9D0D, (q15_t)0xAECC,
+	(q15_t)0xA57D, (q15_t)0xA57D, (q15_t)0xAECC, (q15_t)0x9D0D,
+	(q15_t)0xB8E3, (q15_t)0x9592, (q15_t)0xC3A9, (q15_t)0x8F1D,
+	(q15_t)0xCF04, (q15_t)0x89BE, (q15_t)0xDAD7, (q15_t)0x8582,
+	(q15_t)0xE707, (q15_t)0x8275, (q15_t)0xF374, (q15_t)0x809D
+};
+
+/**
+* \par
+* Example code for q15 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefq15[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefq15[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 128	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to q15(Fixed point 1.15):
+*	round(twiddleCoefq15(i) * pow(2, 15))
+*
+*/
+const q15_t twiddleCoef_128_q15[192] = {
+	(q15_t)0x7FFF, (q15_t)0x0000, (q15_t)0x7FD8, (q15_t)0x0647,
+	(q15_t)0x7F62, (q15_t)0x0C8B, (q15_t)0x7E9D, (q15_t)0x12C8,
+	(q15_t)0x7D8A, (q15_t)0x18F8, (q15_t)0x7C29, (q15_t)0x1F19,
+	(q15_t)0x7A7D, (q15_t)0x2528, (q15_t)0x7884, (q15_t)0x2B1F,
+	(q15_t)0x7641, (q15_t)0x30FB, (q15_t)0x73B5, (q15_t)0x36BA,
+	(q15_t)0x70E2, (q15_t)0x3C56, (q15_t)0x6DCA, (q15_t)0x41CE,
+	(q15_t)0x6A6D, (q15_t)0x471C, (q15_t)0x66CF, (q15_t)0x4C3F,
+	(q15_t)0x62F2, (q15_t)0x5133, (q15_t)0x5ED7, (q15_t)0x55F5,
+	(q15_t)0x5A82, (q15_t)0x5A82, (q15_t)0x55F5, (q15_t)0x5ED7,
+	(q15_t)0x5133, (q15_t)0x62F2, (q15_t)0x4C3F, (q15_t)0x66CF,
+	(q15_t)0x471C, (q15_t)0x6A6D, (q15_t)0x41CE, (q15_t)0x6DCA,
+	(q15_t)0x3C56, (q15_t)0x70E2, (q15_t)0x36BA, (q15_t)0x73B5,
+	(q15_t)0x30FB, (q15_t)0x7641, (q15_t)0x2B1F, (q15_t)0x7884,
+	(q15_t)0x2528, (q15_t)0x7A7D, (q15_t)0x1F19, (q15_t)0x7C29,
+	(q15_t)0x18F8, (q15_t)0x7D8A, (q15_t)0x12C8, (q15_t)0x7E9D,
+	(q15_t)0x0C8B, (q15_t)0x7F62, (q15_t)0x0647, (q15_t)0x7FD8,
+	(q15_t)0x0000, (q15_t)0x7FFF, (q15_t)0xF9B8, (q15_t)0x7FD8,
+	(q15_t)0xF374, (q15_t)0x7F62, (q15_t)0xED37, (q15_t)0x7E9D,
+	(q15_t)0xE707, (q15_t)0x7D8A, (q15_t)0xE0E6, (q15_t)0x7C29,
+	(q15_t)0xDAD7, (q15_t)0x7A7D, (q15_t)0xD4E0, (q15_t)0x7884,
+	(q15_t)0xCF04, (q15_t)0x7641, (q15_t)0xC945, (q15_t)0x73B5,
+	(q15_t)0xC3A9, (q15_t)0x70E2, (q15_t)0xBE31, (q15_t)0x6DCA,
+	(q15_t)0xB8E3, (q15_t)0x6A6D, (q15_t)0xB3C0, (q15_t)0x66CF,
+	(q15_t)0xAECC, (q15_t)0x62F2, (q15_t)0xAA0A, (q15_t)0x5ED7,
+	(q15_t)0xA57D, (q15_t)0x5A82, (q15_t)0xA128, (q15_t)0x55F5,
+	(q15_t)0x9D0D, (q15_t)0x5133, (q15_t)0x9930, (q15_t)0x4C3F,
+	(q15_t)0x9592, (q15_t)0x471C, (q15_t)0x9235, (q15_t)0x41CE,
+	(q15_t)0x8F1D, (q15_t)0x3C56, (q15_t)0x8C4A, (q15_t)0x36BA,
+	(q15_t)0x89BE, (q15_t)0x30FB, (q15_t)0x877B, (q15_t)0x2B1F,
+	(q15_t)0x8582, (q15_t)0x2528, (q15_t)0x83D6, (q15_t)0x1F19,
+	(q15_t)0x8275, (q15_t)0x18F8, (q15_t)0x8162, (q15_t)0x12C8,
+	(q15_t)0x809D, (q15_t)0x0C8B, (q15_t)0x8027, (q15_t)0x0647,
+	(q15_t)0x8000, (q15_t)0x0000, (q15_t)0x8027, (q15_t)0xF9B8,
+	(q15_t)0x809D, (q15_t)0xF374, (q15_t)0x8162, (q15_t)0xED37,
+	(q15_t)0x8275, (q15_t)0xE707, (q15_t)0x83D6, (q15_t)0xE0E6,
+	(q15_t)0x8582, (q15_t)0xDAD7, (q15_t)0x877B, (q15_t)0xD4E0,
+	(q15_t)0x89BE, (q15_t)0xCF04, (q15_t)0x8C4A, (q15_t)0xC945,
+	(q15_t)0x8F1D, (q15_t)0xC3A9, (q15_t)0x9235, (q15_t)0xBE31,
+	(q15_t)0x9592, (q15_t)0xB8E3, (q15_t)0x9930, (q15_t)0xB3C0,
+	(q15_t)0x9D0D, (q15_t)0xAECC, (q15_t)0xA128, (q15_t)0xAA0A,
+	(q15_t)0xA57D, (q15_t)0xA57D, (q15_t)0xAA0A, (q15_t)0xA128,
+	(q15_t)0xAECC, (q15_t)0x9D0D, (q15_t)0xB3C0, (q15_t)0x9930,
+	(q15_t)0xB8E3, (q15_t)0x9592, (q15_t)0xBE31, (q15_t)0x9235,
+	(q15_t)0xC3A9, (q15_t)0x8F1D, (q15_t)0xC945, (q15_t)0x8C4A,
+	(q15_t)0xCF04, (q15_t)0x89BE, (q15_t)0xD4E0, (q15_t)0x877B,
+	(q15_t)0xDAD7, (q15_t)0x8582, (q15_t)0xE0E6, (q15_t)0x83D6,
+	(q15_t)0xE707, (q15_t)0x8275, (q15_t)0xED37, (q15_t)0x8162,
+	(q15_t)0xF374, (q15_t)0x809D, (q15_t)0xF9B8, (q15_t)0x8027
+};
+
+/**
+* \par
+* Example code for q15 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefq15[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefq15[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 256	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to q15(Fixed point 1.15):
+*	round(twiddleCoefq15(i) * pow(2, 15))
+*
+*/
+const q15_t twiddleCoef_256_q15[384] = {
+	(q15_t)0x7FFF, (q15_t)0x0000, (q15_t)0x7FF6, (q15_t)0x0324,
+	(q15_t)0x7FD8, (q15_t)0x0647, (q15_t)0x7FA7, (q15_t)0x096A,
+	(q15_t)0x7F62, (q15_t)0x0C8B, (q15_t)0x7F09, (q15_t)0x0FAB,
+	(q15_t)0x7E9D, (q15_t)0x12C8, (q15_t)0x7E1D, (q15_t)0x15E2,
+	(q15_t)0x7D8A, (q15_t)0x18F8, (q15_t)0x7CE3, (q15_t)0x1C0B,
+	(q15_t)0x7C29, (q15_t)0x1F19, (q15_t)0x7B5D, (q15_t)0x2223,
+	(q15_t)0x7A7D, (q15_t)0x2528, (q15_t)0x798A, (q15_t)0x2826,
+	(q15_t)0x7884, (q15_t)0x2B1F, (q15_t)0x776C, (q15_t)0x2E11,
+	(q15_t)0x7641, (q15_t)0x30FB, (q15_t)0x7504, (q15_t)0x33DE,
+	(q15_t)0x73B5, (q15_t)0x36BA, (q15_t)0x7255, (q15_t)0x398C,
+	(q15_t)0x70E2, (q15_t)0x3C56, (q15_t)0x6F5F, (q15_t)0x3F17,
+	(q15_t)0x6DCA, (q15_t)0x41CE, (q15_t)0x6C24, (q15_t)0x447A,
+	(q15_t)0x6A6D, (q15_t)0x471C, (q15_t)0x68A6, (q15_t)0x49B4,
+	(q15_t)0x66CF, (q15_t)0x4C3F, (q15_t)0x64E8, (q15_t)0x4EBF,
+	(q15_t)0x62F2, (q15_t)0x5133, (q15_t)0x60EC, (q15_t)0x539B,
+	(q15_t)0x5ED7, (q15_t)0x55F5, (q15_t)0x5CB4, (q15_t)0x5842,
+	(q15_t)0x5A82, (q15_t)0x5A82, (q15_t)0x5842, (q15_t)0x5CB4,
+	(q15_t)0x55F5, (q15_t)0x5ED7, (q15_t)0x539B, (q15_t)0x60EC,
+	(q15_t)0x5133, (q15_t)0x62F2, (q15_t)0x4EBF, (q15_t)0x64E8,
+	(q15_t)0x4C3F, (q15_t)0x66CF, (q15_t)0x49B4, (q15_t)0x68A6,
+	(q15_t)0x471C, (q15_t)0x6A6D, (q15_t)0x447A, (q15_t)0x6C24,
+	(q15_t)0x41CE, (q15_t)0x6DCA, (q15_t)0x3F17, (q15_t)0x6F5F,
+	(q15_t)0x3C56, (q15_t)0x70E2, (q15_t)0x398C, (q15_t)0x7255,
+	(q15_t)0x36BA, (q15_t)0x73B5, (q15_t)0x33DE, (q15_t)0x7504,
+	(q15_t)0x30FB, (q15_t)0x7641, (q15_t)0x2E11, (q15_t)0x776C,
+	(q15_t)0x2B1F, (q15_t)0x7884, (q15_t)0x2826, (q15_t)0x798A,
+	(q15_t)0x2528, (q15_t)0x7A7D, (q15_t)0x2223, (q15_t)0x7B5D,
+	(q15_t)0x1F19, (q15_t)0x7C29, (q15_t)0x1C0B, (q15_t)0x7CE3,
+	(q15_t)0x18F8, (q15_t)0x7D8A, (q15_t)0x15E2, (q15_t)0x7E1D,
+	(q15_t)0x12C8, (q15_t)0x7E9D, (q15_t)0x0FAB, (q15_t)0x7F09,
+	(q15_t)0x0C8B, (q15_t)0x7F62, (q15_t)0x096A, (q15_t)0x7FA7,
+	(q15_t)0x0647, (q15_t)0x7FD8, (q15_t)0x0324, (q15_t)0x7FF6,
+	(q15_t)0x0000, (q15_t)0x7FFF, (q15_t)0xFCDB, (q15_t)0x7FF6,
+	(q15_t)0xF9B8, (q15_t)0x7FD8, (q15_t)0xF695, (q15_t)0x7FA7,
+	(q15_t)0xF374, (q15_t)0x7F62, (q15_t)0xF054, (q15_t)0x7F09,
+	(q15_t)0xED37, (q15_t)0x7E9D, (q15_t)0xEA1D, (q15_t)0x7E1D,
+	(q15_t)0xE707, (q15_t)0x7D8A, (q15_t)0xE3F4, (q15_t)0x7CE3,
+	(q15_t)0xE0E6, (q15_t)0x7C29, (q15_t)0xDDDC, (q15_t)0x7B5D,
+	(q15_t)0xDAD7, (q15_t)0x7A7D, (q15_t)0xD7D9, (q15_t)0x798A,
+	(q15_t)0xD4E0, (q15_t)0x7884, (q15_t)0xD1EE, (q15_t)0x776C,
+	(q15_t)0xCF04, (q15_t)0x7641, (q15_t)0xCC21, (q15_t)0x7504,
+	(q15_t)0xC945, (q15_t)0x73B5, (q15_t)0xC673, (q15_t)0x7255,
+	(q15_t)0xC3A9, (q15_t)0x70E2, (q15_t)0xC0E8, (q15_t)0x6F5F,
+	(q15_t)0xBE31, (q15_t)0x6DCA, (q15_t)0xBB85, (q15_t)0x6C24,
+	(q15_t)0xB8E3, (q15_t)0x6A6D, (q15_t)0xB64B, (q15_t)0x68A6,
+	(q15_t)0xB3C0, (q15_t)0x66CF, (q15_t)0xB140, (q15_t)0x64E8,
+	(q15_t)0xAECC, (q15_t)0x62F2, (q15_t)0xAC64, (q15_t)0x60EC,
+	(q15_t)0xAA0A, (q15_t)0x5ED7, (q15_t)0xA7BD, (q15_t)0x5CB4,
+	(q15_t)0xA57D, (q15_t)0x5A82, (q15_t)0xA34B, (q15_t)0x5842,
+	(q15_t)0xA128, (q15_t)0x55F5, (q15_t)0x9F13, (q15_t)0x539B,
+	(q15_t)0x9D0D, (q15_t)0x5133, (q15_t)0x9B17, (q15_t)0x4EBF,
+	(q15_t)0x9930, (q15_t)0x4C3F, (q15_t)0x9759, (q15_t)0x49B4,
+	(q15_t)0x9592, (q15_t)0x471C, (q15_t)0x93DB, (q15_t)0x447A,
+	(q15_t)0x9235, (q15_t)0x41CE, (q15_t)0x90A0, (q15_t)0x3F17,
+	(q15_t)0x8F1D, (q15_t)0x3C56, (q15_t)0x8DAA, (q15_t)0x398C,
+	(q15_t)0x8C4A, (q15_t)0x36BA, (q15_t)0x8AFB, (q15_t)0x33DE,
+	(q15_t)0x89BE, (q15_t)0x30FB, (q15_t)0x8893, (q15_t)0x2E11,
+	(q15_t)0x877B, (q15_t)0x2B1F, (q15_t)0x8675, (q15_t)0x2826,
+	(q15_t)0x8582, (q15_t)0x2528, (q15_t)0x84A2, (q15_t)0x2223,
+	(q15_t)0x83D6, (q15_t)0x1F19, (q15_t)0x831C, (q15_t)0x1C0B,
+	(q15_t)0x8275, (q15_t)0x18F8, (q15_t)0x81E2, (q15_t)0x15E2,
+	(q15_t)0x8162, (q15_t)0x12C8, (q15_t)0x80F6, (q15_t)0x0FAB,
+	(q15_t)0x809D, (q15_t)0x0C8B, (q15_t)0x8058, (q15_t)0x096A,
+	(q15_t)0x8027, (q15_t)0x0647, (q15_t)0x8009, (q15_t)0x0324,
+	(q15_t)0x8000, (q15_t)0x0000, (q15_t)0x8009, (q15_t)0xFCDB,
+	(q15_t)0x8027, (q15_t)0xF9B8, (q15_t)0x8058, (q15_t)0xF695,
+	(q15_t)0x809D, (q15_t)0xF374, (q15_t)0x80F6, (q15_t)0xF054,
+	(q15_t)0x8162, (q15_t)0xED37, (q15_t)0x81E2, (q15_t)0xEA1D,
+	(q15_t)0x8275, (q15_t)0xE707, (q15_t)0x831C, (q15_t)0xE3F4,
+	(q15_t)0x83D6, (q15_t)0xE0E6, (q15_t)0x84A2, (q15_t)0xDDDC,
+	(q15_t)0x8582, (q15_t)0xDAD7, (q15_t)0x8675, (q15_t)0xD7D9,
+	(q15_t)0x877B, (q15_t)0xD4E0, (q15_t)0x8893, (q15_t)0xD1EE,
+	(q15_t)0x89BE, (q15_t)0xCF04, (q15_t)0x8AFB, (q15_t)0xCC21,
+	(q15_t)0x8C4A, (q15_t)0xC945, (q15_t)0x8DAA, (q15_t)0xC673,
+	(q15_t)0x8F1D, (q15_t)0xC3A9, (q15_t)0x90A0, (q15_t)0xC0E8,
+	(q15_t)0x9235, (q15_t)0xBE31, (q15_t)0x93DB, (q15_t)0xBB85,
+	(q15_t)0x9592, (q15_t)0xB8E3, (q15_t)0x9759, (q15_t)0xB64B,
+	(q15_t)0x9930, (q15_t)0xB3C0, (q15_t)0x9B17, (q15_t)0xB140,
+	(q15_t)0x9D0D, (q15_t)0xAECC, (q15_t)0x9F13, (q15_t)0xAC64,
+	(q15_t)0xA128, (q15_t)0xAA0A, (q15_t)0xA34B, (q15_t)0xA7BD,
+	(q15_t)0xA57D, (q15_t)0xA57D, (q15_t)0xA7BD, (q15_t)0xA34B,
+	(q15_t)0xAA0A, (q15_t)0xA128, (q15_t)0xAC64, (q15_t)0x9F13,
+	(q15_t)0xAECC, (q15_t)0x9D0D, (q15_t)0xB140, (q15_t)0x9B17,
+	(q15_t)0xB3C0, (q15_t)0x9930, (q15_t)0xB64B, (q15_t)0x9759,
+	(q15_t)0xB8E3, (q15_t)0x9592, (q15_t)0xBB85, (q15_t)0x93DB,
+	(q15_t)0xBE31, (q15_t)0x9235, (q15_t)0xC0E8, (q15_t)0x90A0,
+	(q15_t)0xC3A9, (q15_t)0x8F1D, (q15_t)0xC673, (q15_t)0x8DAA,
+	(q15_t)0xC945, (q15_t)0x8C4A, (q15_t)0xCC21, (q15_t)0x8AFB,
+	(q15_t)0xCF04, (q15_t)0x89BE, (q15_t)0xD1EE, (q15_t)0x8893,
+	(q15_t)0xD4E0, (q15_t)0x877B, (q15_t)0xD7D9, (q15_t)0x8675,
+	(q15_t)0xDAD7, (q15_t)0x8582, (q15_t)0xDDDC, (q15_t)0x84A2,
+	(q15_t)0xE0E6, (q15_t)0x83D6, (q15_t)0xE3F4, (q15_t)0x831C,
+	(q15_t)0xE707, (q15_t)0x8275, (q15_t)0xEA1D, (q15_t)0x81E2,
+	(q15_t)0xED37, (q15_t)0x8162, (q15_t)0xF054, (q15_t)0x80F6,
+	(q15_t)0xF374, (q15_t)0x809D, (q15_t)0xF695, (q15_t)0x8058,
+	(q15_t)0xF9B8, (q15_t)0x8027, (q15_t)0xFCDB, (q15_t)0x8009
+};
+
+/**
+* \par
+* Example code for q15 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefq15[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefq15[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 512	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to q15(Fixed point 1.15):
+*	round(twiddleCoefq15(i) * pow(2, 15))
+*
+*/
+const q15_t twiddleCoef_512_q15[768] = {
+	(q15_t)0x7FFF, (q15_t)0x0000, (q15_t)0x7FFD, (q15_t)0x0192,
+	(q15_t)0x7FF6, (q15_t)0x0324, (q15_t)0x7FE9, (q15_t)0x04B6,
+	(q15_t)0x7FD8, (q15_t)0x0647, (q15_t)0x7FC2, (q15_t)0x07D9,
+	(q15_t)0x7FA7, (q15_t)0x096A, (q15_t)0x7F87, (q15_t)0x0AFB,
+	(q15_t)0x7F62, (q15_t)0x0C8B, (q15_t)0x7F38, (q15_t)0x0E1B,
+	(q15_t)0x7F09, (q15_t)0x0FAB, (q15_t)0x7ED5, (q15_t)0x1139,
+	(q15_t)0x7E9D, (q15_t)0x12C8, (q15_t)0x7E5F, (q15_t)0x1455,
+	(q15_t)0x7E1D, (q15_t)0x15E2, (q15_t)0x7DD6, (q15_t)0x176D,
+	(q15_t)0x7D8A, (q15_t)0x18F8, (q15_t)0x7D39, (q15_t)0x1A82,
+	(q15_t)0x7CE3, (q15_t)0x1C0B, (q15_t)0x7C89, (q15_t)0x1D93,
+	(q15_t)0x7C29, (q15_t)0x1F19, (q15_t)0x7BC5, (q15_t)0x209F,
+	(q15_t)0x7B5D, (q15_t)0x2223, (q15_t)0x7AEF, (q15_t)0x23A6,
+	(q15_t)0x7A7D, (q15_t)0x2528, (q15_t)0x7A05, (q15_t)0x26A8,
+	(q15_t)0x798A, (q15_t)0x2826, (q15_t)0x7909, (q15_t)0x29A3,
+	(q15_t)0x7884, (q15_t)0x2B1F, (q15_t)0x77FA, (q15_t)0x2C98,
+	(q15_t)0x776C, (q15_t)0x2E11, (q15_t)0x76D9, (q15_t)0x2F87,
+	(q15_t)0x7641, (q15_t)0x30FB, (q15_t)0x75A5, (q15_t)0x326E,
+	(q15_t)0x7504, (q15_t)0x33DE, (q15_t)0x745F, (q15_t)0x354D,
+	(q15_t)0x73B5, (q15_t)0x36BA, (q15_t)0x7307, (q15_t)0x3824,
+	(q15_t)0x7255, (q15_t)0x398C, (q15_t)0x719E, (q15_t)0x3AF2,
+	(q15_t)0x70E2, (q15_t)0x3C56, (q15_t)0x7023, (q15_t)0x3DB8,
+	(q15_t)0x6F5F, (q15_t)0x3F17, (q15_t)0x6E96, (q15_t)0x4073,
+	(q15_t)0x6DCA, (q15_t)0x41CE, (q15_t)0x6CF9, (q15_t)0x4325,
+	(q15_t)0x6C24, (q15_t)0x447A, (q15_t)0x6B4A, (q15_t)0x45CD,
+	(q15_t)0x6A6D, (q15_t)0x471C, (q15_t)0x698C, (q15_t)0x4869,
+	(q15_t)0x68A6, (q15_t)0x49B4, (q15_t)0x67BD, (q15_t)0x4AFB,
+	(q15_t)0x66CF, (q15_t)0x4C3F, (q15_t)0x65DD, (q15_t)0x4D81,
+	(q15_t)0x64E8, (q15_t)0x4EBF, (q15_t)0x63EF, (q15_t)0x4FFB,
+	(q15_t)0x62F2, (q15_t)0x5133, (q15_t)0x61F1, (q15_t)0x5269,
+	(q15_t)0x60EC, (q15_t)0x539B, (q15_t)0x5FE3, (q15_t)0x54CA,
+	(q15_t)0x5ED7, (q15_t)0x55F5, (q15_t)0x5DC7, (q15_t)0x571D,
+	(q15_t)0x5CB4, (q15_t)0x5842, (q15_t)0x5B9D, (q15_t)0x5964,
+	(q15_t)0x5A82, (q15_t)0x5A82, (q15_t)0x5964, (q15_t)0x5B9D,
+	(q15_t)0x5842, (q15_t)0x5CB4, (q15_t)0x571D, (q15_t)0x5DC7,
+	(q15_t)0x55F5, (q15_t)0x5ED7, (q15_t)0x54CA, (q15_t)0x5FE3,
+	(q15_t)0x539B, (q15_t)0x60EC, (q15_t)0x5269, (q15_t)0x61F1,
+	(q15_t)0x5133, (q15_t)0x62F2, (q15_t)0x4FFB, (q15_t)0x63EF,
+	(q15_t)0x4EBF, (q15_t)0x64E8, (q15_t)0x4D81, (q15_t)0x65DD,
+	(q15_t)0x4C3F, (q15_t)0x66CF, (q15_t)0x4AFB, (q15_t)0x67BD,
+	(q15_t)0x49B4, (q15_t)0x68A6, (q15_t)0x4869, (q15_t)0x698C,
+	(q15_t)0x471C, (q15_t)0x6A6D, (q15_t)0x45CD, (q15_t)0x6B4A,
+	(q15_t)0x447A, (q15_t)0x6C24, (q15_t)0x4325, (q15_t)0x6CF9,
+	(q15_t)0x41CE, (q15_t)0x6DCA, (q15_t)0x4073, (q15_t)0x6E96,
+	(q15_t)0x3F17, (q15_t)0x6F5F, (q15_t)0x3DB8, (q15_t)0x7023,
+	(q15_t)0x3C56, (q15_t)0x70E2, (q15_t)0x3AF2, (q15_t)0x719E,
+	(q15_t)0x398C, (q15_t)0x7255, (q15_t)0x3824, (q15_t)0x7307,
+	(q15_t)0x36BA, (q15_t)0x73B5, (q15_t)0x354D, (q15_t)0x745F,
+	(q15_t)0x33DE, (q15_t)0x7504, (q15_t)0x326E, (q15_t)0x75A5,
+	(q15_t)0x30FB, (q15_t)0x7641, (q15_t)0x2F87, (q15_t)0x76D9,
+	(q15_t)0x2E11, (q15_t)0x776C, (q15_t)0x2C98, (q15_t)0x77FA,
+	(q15_t)0x2B1F, (q15_t)0x7884, (q15_t)0x29A3, (q15_t)0x7909,
+	(q15_t)0x2826, (q15_t)0x798A, (q15_t)0x26A8, (q15_t)0x7A05,
+	(q15_t)0x2528, (q15_t)0x7A7D, (q15_t)0x23A6, (q15_t)0x7AEF,
+	(q15_t)0x2223, (q15_t)0x7B5D, (q15_t)0x209F, (q15_t)0x7BC5,
+	(q15_t)0x1F19, (q15_t)0x7C29, (q15_t)0x1D93, (q15_t)0x7C89,
+	(q15_t)0x1C0B, (q15_t)0x7CE3, (q15_t)0x1A82, (q15_t)0x7D39,
+	(q15_t)0x18F8, (q15_t)0x7D8A, (q15_t)0x176D, (q15_t)0x7DD6,
+	(q15_t)0x15E2, (q15_t)0x7E1D, (q15_t)0x1455, (q15_t)0x7E5F,
+	(q15_t)0x12C8, (q15_t)0x7E9D, (q15_t)0x1139, (q15_t)0x7ED5,
+	(q15_t)0x0FAB, (q15_t)0x7F09, (q15_t)0x0E1B, (q15_t)0x7F38,
+	(q15_t)0x0C8B, (q15_t)0x7F62, (q15_t)0x0AFB, (q15_t)0x7F87,
+	(q15_t)0x096A, (q15_t)0x7FA7, (q15_t)0x07D9, (q15_t)0x7FC2,
+	(q15_t)0x0647, (q15_t)0x7FD8, (q15_t)0x04B6, (q15_t)0x7FE9,
+	(q15_t)0x0324, (q15_t)0x7FF6, (q15_t)0x0192, (q15_t)0x7FFD,
+	(q15_t)0x0000, (q15_t)0x7FFF, (q15_t)0xFE6D, (q15_t)0x7FFD,
+	(q15_t)0xFCDB, (q15_t)0x7FF6, (q15_t)0xFB49, (q15_t)0x7FE9,
+	(q15_t)0xF9B8, (q15_t)0x7FD8, (q15_t)0xF826, (q15_t)0x7FC2,
+	(q15_t)0xF695, (q15_t)0x7FA7, (q15_t)0xF504, (q15_t)0x7F87,
+	(q15_t)0xF374, (q15_t)0x7F62, (q15_t)0xF1E4, (q15_t)0x7F38,
+	(q15_t)0xF054, (q15_t)0x7F09, (q15_t)0xEEC6, (q15_t)0x7ED5,
+	(q15_t)0xED37, (q15_t)0x7E9D, (q15_t)0xEBAA, (q15_t)0x7E5F,
+	(q15_t)0xEA1D, (q15_t)0x7E1D, (q15_t)0xE892, (q15_t)0x7DD6,
+	(q15_t)0xE707, (q15_t)0x7D8A, (q15_t)0xE57D, (q15_t)0x7D39,
+	(q15_t)0xE3F4, (q15_t)0x7CE3, (q15_t)0xE26C, (q15_t)0x7C89,
+	(q15_t)0xE0E6, (q15_t)0x7C29, (q15_t)0xDF60, (q15_t)0x7BC5,
+	(q15_t)0xDDDC, (q15_t)0x7B5D, (q15_t)0xDC59, (q15_t)0x7AEF,
+	(q15_t)0xDAD7, (q15_t)0x7A7D, (q15_t)0xD957, (q15_t)0x7A05,
+	(q15_t)0xD7D9, (q15_t)0x798A, (q15_t)0xD65C, (q15_t)0x7909,
+	(q15_t)0xD4E0, (q15_t)0x7884, (q15_t)0xD367, (q15_t)0x77FA,
+	(q15_t)0xD1EE, (q15_t)0x776C, (q15_t)0xD078, (q15_t)0x76D9,
+	(q15_t)0xCF04, (q15_t)0x7641, (q15_t)0xCD91, (q15_t)0x75A5,
+	(q15_t)0xCC21, (q15_t)0x7504, (q15_t)0xCAB2, (q15_t)0x745F,
+	(q15_t)0xC945, (q15_t)0x73B5, (q15_t)0xC7DB, (q15_t)0x7307,
+	(q15_t)0xC673, (q15_t)0x7255, (q15_t)0xC50D, (q15_t)0x719E,
+	(q15_t)0xC3A9, (q15_t)0x70E2, (q15_t)0xC247, (q15_t)0x7023,
+	(q15_t)0xC0E8, (q15_t)0x6F5F, (q15_t)0xBF8C, (q15_t)0x6E96,
+	(q15_t)0xBE31, (q15_t)0x6DCA, (q15_t)0xBCDA, (q15_t)0x6CF9,
+	(q15_t)0xBB85, (q15_t)0x6C24, (q15_t)0xBA32, (q15_t)0x6B4A,
+	(q15_t)0xB8E3, (q15_t)0x6A6D, (q15_t)0xB796, (q15_t)0x698C,
+	(q15_t)0xB64B, (q15_t)0x68A6, (q15_t)0xB504, (q15_t)0x67BD,
+	(q15_t)0xB3C0, (q15_t)0x66CF, (q15_t)0xB27E, (q15_t)0x65DD,
+	(q15_t)0xB140, (q15_t)0x64E8, (q15_t)0xB004, (q15_t)0x63EF,
+	(q15_t)0xAECC, (q15_t)0x62F2, (q15_t)0xAD96, (q15_t)0x61F1,
+	(q15_t)0xAC64, (q15_t)0x60EC, (q15_t)0xAB35, (q15_t)0x5FE3,
+	(q15_t)0xAA0A, (q15_t)0x5ED7, (q15_t)0xA8E2, (q15_t)0x5DC7,
+	(q15_t)0xA7BD, (q15_t)0x5CB4, (q15_t)0xA69B, (q15_t)0x5B9D,
+	(q15_t)0xA57D, (q15_t)0x5A82, (q15_t)0xA462, (q15_t)0x5964,
+	(q15_t)0xA34B, (q15_t)0x5842, (q15_t)0xA238, (q15_t)0x571D,
+	(q15_t)0xA128, (q15_t)0x55F5, (q15_t)0xA01C, (q15_t)0x54CA,
+	(q15_t)0x9F13, (q15_t)0x539B, (q15_t)0x9E0E, (q15_t)0x5269,
+	(q15_t)0x9D0D, (q15_t)0x5133, (q15_t)0x9C10, (q15_t)0x4FFB,
+	(q15_t)0x9B17, (q15_t)0x4EBF, (q15_t)0x9A22, (q15_t)0x4D81,
+	(q15_t)0x9930, (q15_t)0x4C3F, (q15_t)0x9842, (q15_t)0x4AFB,
+	(q15_t)0x9759, (q15_t)0x49B4, (q15_t)0x9673, (q15_t)0x4869,
+	(q15_t)0x9592, (q15_t)0x471C, (q15_t)0x94B5, (q15_t)0x45CD,
+	(q15_t)0x93DB, (q15_t)0x447A, (q15_t)0x9306, (q15_t)0x4325,
+	(q15_t)0x9235, (q15_t)0x41CE, (q15_t)0x9169, (q15_t)0x4073,
+	(q15_t)0x90A0, (q15_t)0x3F17, (q15_t)0x8FDC, (q15_t)0x3DB8,
+	(q15_t)0x8F1D, (q15_t)0x3C56, (q15_t)0x8E61, (q15_t)0x3AF2,
+	(q15_t)0x8DAA, (q15_t)0x398C, (q15_t)0x8CF8, (q15_t)0x3824,
+	(q15_t)0x8C4A, (q15_t)0x36BA, (q15_t)0x8BA0, (q15_t)0x354D,
+	(q15_t)0x8AFB, (q15_t)0x33DE, (q15_t)0x8A5A, (q15_t)0x326E,
+	(q15_t)0x89BE, (q15_t)0x30FB, (q15_t)0x8926, (q15_t)0x2F87,
+	(q15_t)0x8893, (q15_t)0x2E11, (q15_t)0x8805, (q15_t)0x2C98,
+	(q15_t)0x877B, (q15_t)0x2B1F, (q15_t)0x86F6, (q15_t)0x29A3,
+	(q15_t)0x8675, (q15_t)0x2826, (q15_t)0x85FA, (q15_t)0x26A8,
+	(q15_t)0x8582, (q15_t)0x2528, (q15_t)0x8510, (q15_t)0x23A6,
+	(q15_t)0x84A2, (q15_t)0x2223, (q15_t)0x843A, (q15_t)0x209F,
+	(q15_t)0x83D6, (q15_t)0x1F19, (q15_t)0x8376, (q15_t)0x1D93,
+	(q15_t)0x831C, (q15_t)0x1C0B, (q15_t)0x82C6, (q15_t)0x1A82,
+	(q15_t)0x8275, (q15_t)0x18F8, (q15_t)0x8229, (q15_t)0x176D,
+	(q15_t)0x81E2, (q15_t)0x15E2, (q15_t)0x81A0, (q15_t)0x1455,
+	(q15_t)0x8162, (q15_t)0x12C8, (q15_t)0x812A, (q15_t)0x1139,
+	(q15_t)0x80F6, (q15_t)0x0FAB, (q15_t)0x80C7, (q15_t)0x0E1B,
+	(q15_t)0x809D, (q15_t)0x0C8B, (q15_t)0x8078, (q15_t)0x0AFB,
+	(q15_t)0x8058, (q15_t)0x096A, (q15_t)0x803D, (q15_t)0x07D9,
+	(q15_t)0x8027, (q15_t)0x0647, (q15_t)0x8016, (q15_t)0x04B6,
+	(q15_t)0x8009, (q15_t)0x0324, (q15_t)0x8002, (q15_t)0x0192,
+	(q15_t)0x8000, (q15_t)0x0000, (q15_t)0x8002, (q15_t)0xFE6D,
+	(q15_t)0x8009, (q15_t)0xFCDB, (q15_t)0x8016, (q15_t)0xFB49,
+	(q15_t)0x8027, (q15_t)0xF9B8, (q15_t)0x803D, (q15_t)0xF826,
+	(q15_t)0x8058, (q15_t)0xF695, (q15_t)0x8078, (q15_t)0xF504,
+	(q15_t)0x809D, (q15_t)0xF374, (q15_t)0x80C7, (q15_t)0xF1E4,
+	(q15_t)0x80F6, (q15_t)0xF054, (q15_t)0x812A, (q15_t)0xEEC6,
+	(q15_t)0x8162, (q15_t)0xED37, (q15_t)0x81A0, (q15_t)0xEBAA,
+	(q15_t)0x81E2, (q15_t)0xEA1D, (q15_t)0x8229, (q15_t)0xE892,
+	(q15_t)0x8275, (q15_t)0xE707, (q15_t)0x82C6, (q15_t)0xE57D,
+	(q15_t)0x831C, (q15_t)0xE3F4, (q15_t)0x8376, (q15_t)0xE26C,
+	(q15_t)0x83D6, (q15_t)0xE0E6, (q15_t)0x843A, (q15_t)0xDF60,
+	(q15_t)0x84A2, (q15_t)0xDDDC, (q15_t)0x8510, (q15_t)0xDC59,
+	(q15_t)0x8582, (q15_t)0xDAD7, (q15_t)0x85FA, (q15_t)0xD957,
+	(q15_t)0x8675, (q15_t)0xD7D9, (q15_t)0x86F6, (q15_t)0xD65C,
+	(q15_t)0x877B, (q15_t)0xD4E0, (q15_t)0x8805, (q15_t)0xD367,
+	(q15_t)0x8893, (q15_t)0xD1EE, (q15_t)0x8926, (q15_t)0xD078,
+	(q15_t)0x89BE, (q15_t)0xCF04, (q15_t)0x8A5A, (q15_t)0xCD91,
+	(q15_t)0x8AFB, (q15_t)0xCC21, (q15_t)0x8BA0, (q15_t)0xCAB2,
+	(q15_t)0x8C4A, (q15_t)0xC945, (q15_t)0x8CF8, (q15_t)0xC7DB,
+	(q15_t)0x8DAA, (q15_t)0xC673, (q15_t)0x8E61, (q15_t)0xC50D,
+	(q15_t)0x8F1D, (q15_t)0xC3A9, (q15_t)0x8FDC, (q15_t)0xC247,
+	(q15_t)0x90A0, (q15_t)0xC0E8, (q15_t)0x9169, (q15_t)0xBF8C,
+	(q15_t)0x9235, (q15_t)0xBE31, (q15_t)0x9306, (q15_t)0xBCDA,
+	(q15_t)0x93DB, (q15_t)0xBB85, (q15_t)0x94B5, (q15_t)0xBA32,
+	(q15_t)0x9592, (q15_t)0xB8E3, (q15_t)0x9673, (q15_t)0xB796,
+	(q15_t)0x9759, (q15_t)0xB64B, (q15_t)0x9842, (q15_t)0xB504,
+	(q15_t)0x9930, (q15_t)0xB3C0, (q15_t)0x9A22, (q15_t)0xB27E,
+	(q15_t)0x9B17, (q15_t)0xB140, (q15_t)0x9C10, (q15_t)0xB004,
+	(q15_t)0x9D0D, (q15_t)0xAECC, (q15_t)0x9E0E, (q15_t)0xAD96,
+	(q15_t)0x9F13, (q15_t)0xAC64, (q15_t)0xA01C, (q15_t)0xAB35,
+	(q15_t)0xA128, (q15_t)0xAA0A, (q15_t)0xA238, (q15_t)0xA8E2,
+	(q15_t)0xA34B, (q15_t)0xA7BD, (q15_t)0xA462, (q15_t)0xA69B,
+	(q15_t)0xA57D, (q15_t)0xA57D, (q15_t)0xA69B, (q15_t)0xA462,
+	(q15_t)0xA7BD, (q15_t)0xA34B, (q15_t)0xA8E2, (q15_t)0xA238,
+	(q15_t)0xAA0A, (q15_t)0xA128, (q15_t)0xAB35, (q15_t)0xA01C,
+	(q15_t)0xAC64, (q15_t)0x9F13, (q15_t)0xAD96, (q15_t)0x9E0E,
+	(q15_t)0xAECC, (q15_t)0x9D0D, (q15_t)0xB004, (q15_t)0x9C10,
+	(q15_t)0xB140, (q15_t)0x9B17, (q15_t)0xB27E, (q15_t)0x9A22,
+	(q15_t)0xB3C0, (q15_t)0x9930, (q15_t)0xB504, (q15_t)0x9842,
+	(q15_t)0xB64B, (q15_t)0x9759, (q15_t)0xB796, (q15_t)0x9673,
+	(q15_t)0xB8E3, (q15_t)0x9592, (q15_t)0xBA32, (q15_t)0x94B5,
+	(q15_t)0xBB85, (q15_t)0x93DB, (q15_t)0xBCDA, (q15_t)0x9306,
+	(q15_t)0xBE31, (q15_t)0x9235, (q15_t)0xBF8C, (q15_t)0x9169,
+	(q15_t)0xC0E8, (q15_t)0x90A0, (q15_t)0xC247, (q15_t)0x8FDC,
+	(q15_t)0xC3A9, (q15_t)0x8F1D, (q15_t)0xC50D, (q15_t)0x8E61,
+	(q15_t)0xC673, (q15_t)0x8DAA, (q15_t)0xC7DB, (q15_t)0x8CF8,
+	(q15_t)0xC945, (q15_t)0x8C4A, (q15_t)0xCAB2, (q15_t)0x8BA0,
+	(q15_t)0xCC21, (q15_t)0x8AFB, (q15_t)0xCD91, (q15_t)0x8A5A,
+	(q15_t)0xCF04, (q15_t)0x89BE, (q15_t)0xD078, (q15_t)0x8926,
+	(q15_t)0xD1EE, (q15_t)0x8893, (q15_t)0xD367, (q15_t)0x8805,
+	(q15_t)0xD4E0, (q15_t)0x877B, (q15_t)0xD65C, (q15_t)0x86F6,
+	(q15_t)0xD7D9, (q15_t)0x8675, (q15_t)0xD957, (q15_t)0x85FA,
+	(q15_t)0xDAD7, (q15_t)0x8582, (q15_t)0xDC59, (q15_t)0x8510,
+	(q15_t)0xDDDC, (q15_t)0x84A2, (q15_t)0xDF60, (q15_t)0x843A,
+	(q15_t)0xE0E6, (q15_t)0x83D6, (q15_t)0xE26C, (q15_t)0x8376,
+	(q15_t)0xE3F4, (q15_t)0x831C, (q15_t)0xE57D, (q15_t)0x82C6,
+	(q15_t)0xE707, (q15_t)0x8275, (q15_t)0xE892, (q15_t)0x8229,
+	(q15_t)0xEA1D, (q15_t)0x81E2, (q15_t)0xEBAA, (q15_t)0x81A0,
+	(q15_t)0xED37, (q15_t)0x8162, (q15_t)0xEEC6, (q15_t)0x812A,
+	(q15_t)0xF054, (q15_t)0x80F6, (q15_t)0xF1E4, (q15_t)0x80C7,
+	(q15_t)0xF374, (q15_t)0x809D, (q15_t)0xF504, (q15_t)0x8078,
+	(q15_t)0xF695, (q15_t)0x8058, (q15_t)0xF826, (q15_t)0x803D,
+	(q15_t)0xF9B8, (q15_t)0x8027, (q15_t)0xFB49, (q15_t)0x8016,
+	(q15_t)0xFCDB, (q15_t)0x8009, (q15_t)0xFE6D, (q15_t)0x8002
+};
+
+/**
+* \par
+* Example code for q15 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefq15[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefq15[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 1024	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to q15(Fixed point 1.15):
+*	round(twiddleCoefq15(i) * pow(2, 15))
+*
+*/
+const q15_t twiddleCoef_1024_q15[1536] = {
+	(q15_t)0x7FFF, (q15_t)0x0000, (q15_t)0x7FFF, (q15_t)0x00C9,
+	(q15_t)0x7FFD, (q15_t)0x0192, (q15_t)0x7FFA, (q15_t)0x025B,
+	(q15_t)0x7FF6, (q15_t)0x0324, (q15_t)0x7FF0, (q15_t)0x03ED,
+	(q15_t)0x7FE9, (q15_t)0x04B6, (q15_t)0x7FE1, (q15_t)0x057F,
+	(q15_t)0x7FD8, (q15_t)0x0647, (q15_t)0x7FCE, (q15_t)0x0710,
+	(q15_t)0x7FC2, (q15_t)0x07D9, (q15_t)0x7FB5, (q15_t)0x08A2,
+	(q15_t)0x7FA7, (q15_t)0x096A, (q15_t)0x7F97, (q15_t)0x0A33,
+	(q15_t)0x7F87, (q15_t)0x0AFB, (q15_t)0x7F75, (q15_t)0x0BC3,
+	(q15_t)0x7F62, (q15_t)0x0C8B, (q15_t)0x7F4D, (q15_t)0x0D53,
+	(q15_t)0x7F38, (q15_t)0x0E1B, (q15_t)0x7F21, (q15_t)0x0EE3,
+	(q15_t)0x7F09, (q15_t)0x0FAB, (q15_t)0x7EF0, (q15_t)0x1072,
+	(q15_t)0x7ED5, (q15_t)0x1139, (q15_t)0x7EBA, (q15_t)0x1201,
+	(q15_t)0x7E9D, (q15_t)0x12C8, (q15_t)0x7E7F, (q15_t)0x138E,
+	(q15_t)0x7E5F, (q15_t)0x1455, (q15_t)0x7E3F, (q15_t)0x151B,
+	(q15_t)0x7E1D, (q15_t)0x15E2, (q15_t)0x7DFA, (q15_t)0x16A8,
+	(q15_t)0x7DD6, (q15_t)0x176D, (q15_t)0x7DB0, (q15_t)0x1833,
+	(q15_t)0x7D8A, (q15_t)0x18F8, (q15_t)0x7D62, (q15_t)0x19BD,
+	(q15_t)0x7D39, (q15_t)0x1A82, (q15_t)0x7D0F, (q15_t)0x1B47,
+	(q15_t)0x7CE3, (q15_t)0x1C0B, (q15_t)0x7CB7, (q15_t)0x1CCF,
+	(q15_t)0x7C89, (q15_t)0x1D93, (q15_t)0x7C5A, (q15_t)0x1E56,
+	(q15_t)0x7C29, (q15_t)0x1F19, (q15_t)0x7BF8, (q15_t)0x1FDC,
+	(q15_t)0x7BC5, (q15_t)0x209F, (q15_t)0x7B92, (q15_t)0x2161,
+	(q15_t)0x7B5D, (q15_t)0x2223, (q15_t)0x7B26, (q15_t)0x22E5,
+	(q15_t)0x7AEF, (q15_t)0x23A6, (q15_t)0x7AB6, (q15_t)0x2467,
+	(q15_t)0x7A7D, (q15_t)0x2528, (q15_t)0x7A42, (q15_t)0x25E8,
+	(q15_t)0x7A05, (q15_t)0x26A8, (q15_t)0x79C8, (q15_t)0x2767,
+	(q15_t)0x798A, (q15_t)0x2826, (q15_t)0x794A, (q15_t)0x28E5,
+	(q15_t)0x7909, (q15_t)0x29A3, (q15_t)0x78C7, (q15_t)0x2A61,
+	(q15_t)0x7884, (q15_t)0x2B1F, (q15_t)0x7840, (q15_t)0x2BDC,
+	(q15_t)0x77FA, (q15_t)0x2C98, (q15_t)0x77B4, (q15_t)0x2D55,
+	(q15_t)0x776C, (q15_t)0x2E11, (q15_t)0x7723, (q15_t)0x2ECC,
+	(q15_t)0x76D9, (q15_t)0x2F87, (q15_t)0x768E, (q15_t)0x3041,
+	(q15_t)0x7641, (q15_t)0x30FB, (q15_t)0x75F4, (q15_t)0x31B5,
+	(q15_t)0x75A5, (q15_t)0x326E, (q15_t)0x7555, (q15_t)0x3326,
+	(q15_t)0x7504, (q15_t)0x33DE, (q15_t)0x74B2, (q15_t)0x3496,
+	(q15_t)0x745F, (q15_t)0x354D, (q15_t)0x740B, (q15_t)0x3604,
+	(q15_t)0x73B5, (q15_t)0x36BA, (q15_t)0x735F, (q15_t)0x376F,
+	(q15_t)0x7307, (q15_t)0x3824, (q15_t)0x72AF, (q15_t)0x38D8,
+	(q15_t)0x7255, (q15_t)0x398C, (q15_t)0x71FA, (q15_t)0x3A40,
+	(q15_t)0x719E, (q15_t)0x3AF2, (q15_t)0x7141, (q15_t)0x3BA5,
+	(q15_t)0x70E2, (q15_t)0x3C56, (q15_t)0x7083, (q15_t)0x3D07,
+	(q15_t)0x7023, (q15_t)0x3DB8, (q15_t)0x6FC1, (q15_t)0x3E68,
+	(q15_t)0x6F5F, (q15_t)0x3F17, (q15_t)0x6EFB, (q15_t)0x3FC5,
+	(q15_t)0x6E96, (q15_t)0x4073, (q15_t)0x6E30, (q15_t)0x4121,
+	(q15_t)0x6DCA, (q15_t)0x41CE, (q15_t)0x6D62, (q15_t)0x427A,
+	(q15_t)0x6CF9, (q15_t)0x4325, (q15_t)0x6C8F, (q15_t)0x43D0,
+	(q15_t)0x6C24, (q15_t)0x447A, (q15_t)0x6BB8, (q15_t)0x4524,
+	(q15_t)0x6B4A, (q15_t)0x45CD, (q15_t)0x6ADC, (q15_t)0x4675,
+	(q15_t)0x6A6D, (q15_t)0x471C, (q15_t)0x69FD, (q15_t)0x47C3,
+	(q15_t)0x698C, (q15_t)0x4869, (q15_t)0x6919, (q15_t)0x490F,
+	(q15_t)0x68A6, (q15_t)0x49B4, (q15_t)0x6832, (q15_t)0x4A58,
+	(q15_t)0x67BD, (q15_t)0x4AFB, (q15_t)0x6746, (q15_t)0x4B9E,
+	(q15_t)0x66CF, (q15_t)0x4C3F, (q15_t)0x6657, (q15_t)0x4CE1,
+	(q15_t)0x65DD, (q15_t)0x4D81, (q15_t)0x6563, (q15_t)0x4E21,
+	(q15_t)0x64E8, (q15_t)0x4EBF, (q15_t)0x646C, (q15_t)0x4F5E,
+	(q15_t)0x63EF, (q15_t)0x4FFB, (q15_t)0x6371, (q15_t)0x5097,
+	(q15_t)0x62F2, (q15_t)0x5133, (q15_t)0x6271, (q15_t)0x51CE,
+	(q15_t)0x61F1, (q15_t)0x5269, (q15_t)0x616F, (q15_t)0x5302,
+	(q15_t)0x60EC, (q15_t)0x539B, (q15_t)0x6068, (q15_t)0x5433,
+	(q15_t)0x5FE3, (q15_t)0x54CA, (q15_t)0x5F5E, (q15_t)0x5560,
+	(q15_t)0x5ED7, (q15_t)0x55F5, (q15_t)0x5E50, (q15_t)0x568A,
+	(q15_t)0x5DC7, (q15_t)0x571D, (q15_t)0x5D3E, (q15_t)0x57B0,
+	(q15_t)0x5CB4, (q15_t)0x5842, (q15_t)0x5C29, (q15_t)0x58D4,
+	(q15_t)0x5B9D, (q15_t)0x5964, (q15_t)0x5B10, (q15_t)0x59F3,
+	(q15_t)0x5A82, (q15_t)0x5A82, (q15_t)0x59F3, (q15_t)0x5B10,
+	(q15_t)0x5964, (q15_t)0x5B9D, (q15_t)0x58D4, (q15_t)0x5C29,
+	(q15_t)0x5842, (q15_t)0x5CB4, (q15_t)0x57B0, (q15_t)0x5D3E,
+	(q15_t)0x571D, (q15_t)0x5DC7, (q15_t)0x568A, (q15_t)0x5E50,
+	(q15_t)0x55F5, (q15_t)0x5ED7, (q15_t)0x5560, (q15_t)0x5F5E,
+	(q15_t)0x54CA, (q15_t)0x5FE3, (q15_t)0x5433, (q15_t)0x6068,
+	(q15_t)0x539B, (q15_t)0x60EC, (q15_t)0x5302, (q15_t)0x616F,
+	(q15_t)0x5269, (q15_t)0x61F1, (q15_t)0x51CE, (q15_t)0x6271,
+	(q15_t)0x5133, (q15_t)0x62F2, (q15_t)0x5097, (q15_t)0x6371,
+	(q15_t)0x4FFB, (q15_t)0x63EF, (q15_t)0x4F5E, (q15_t)0x646C,
+	(q15_t)0x4EBF, (q15_t)0x64E8, (q15_t)0x4E21, (q15_t)0x6563,
+	(q15_t)0x4D81, (q15_t)0x65DD, (q15_t)0x4CE1, (q15_t)0x6657,
+	(q15_t)0x4C3F, (q15_t)0x66CF, (q15_t)0x4B9E, (q15_t)0x6746,
+	(q15_t)0x4AFB, (q15_t)0x67BD, (q15_t)0x4A58, (q15_t)0x6832,
+	(q15_t)0x49B4, (q15_t)0x68A6, (q15_t)0x490F, (q15_t)0x6919,
+	(q15_t)0x4869, (q15_t)0x698C, (q15_t)0x47C3, (q15_t)0x69FD,
+	(q15_t)0x471C, (q15_t)0x6A6D, (q15_t)0x4675, (q15_t)0x6ADC,
+	(q15_t)0x45CD, (q15_t)0x6B4A, (q15_t)0x4524, (q15_t)0x6BB8,
+	(q15_t)0x447A, (q15_t)0x6C24, (q15_t)0x43D0, (q15_t)0x6C8F,
+	(q15_t)0x4325, (q15_t)0x6CF9, (q15_t)0x427A, (q15_t)0x6D62,
+	(q15_t)0x41CE, (q15_t)0x6DCA, (q15_t)0x4121, (q15_t)0x6E30,
+	(q15_t)0x4073, (q15_t)0x6E96, (q15_t)0x3FC5, (q15_t)0x6EFB,
+	(q15_t)0x3F17, (q15_t)0x6F5F, (q15_t)0x3E68, (q15_t)0x6FC1,
+	(q15_t)0x3DB8, (q15_t)0x7023, (q15_t)0x3D07, (q15_t)0x7083,
+	(q15_t)0x3C56, (q15_t)0x70E2, (q15_t)0x3BA5, (q15_t)0x7141,
+	(q15_t)0x3AF2, (q15_t)0x719E, (q15_t)0x3A40, (q15_t)0x71FA,
+	(q15_t)0x398C, (q15_t)0x7255, (q15_t)0x38D8, (q15_t)0x72AF,
+	(q15_t)0x3824, (q15_t)0x7307, (q15_t)0x376F, (q15_t)0x735F,
+	(q15_t)0x36BA, (q15_t)0x73B5, (q15_t)0x3604, (q15_t)0x740B,
+	(q15_t)0x354D, (q15_t)0x745F, (q15_t)0x3496, (q15_t)0x74B2,
+	(q15_t)0x33DE, (q15_t)0x7504, (q15_t)0x3326, (q15_t)0x7555,
+	(q15_t)0x326E, (q15_t)0x75A5, (q15_t)0x31B5, (q15_t)0x75F4,
+	(q15_t)0x30FB, (q15_t)0x7641, (q15_t)0x3041, (q15_t)0x768E,
+	(q15_t)0x2F87, (q15_t)0x76D9, (q15_t)0x2ECC, (q15_t)0x7723,
+	(q15_t)0x2E11, (q15_t)0x776C, (q15_t)0x2D55, (q15_t)0x77B4,
+	(q15_t)0x2C98, (q15_t)0x77FA, (q15_t)0x2BDC, (q15_t)0x7840,
+	(q15_t)0x2B1F, (q15_t)0x7884, (q15_t)0x2A61, (q15_t)0x78C7,
+	(q15_t)0x29A3, (q15_t)0x7909, (q15_t)0x28E5, (q15_t)0x794A,
+	(q15_t)0x2826, (q15_t)0x798A, (q15_t)0x2767, (q15_t)0x79C8,
+	(q15_t)0x26A8, (q15_t)0x7A05, (q15_t)0x25E8, (q15_t)0x7A42,
+	(q15_t)0x2528, (q15_t)0x7A7D, (q15_t)0x2467, (q15_t)0x7AB6,
+	(q15_t)0x23A6, (q15_t)0x7AEF, (q15_t)0x22E5, (q15_t)0x7B26,
+	(q15_t)0x2223, (q15_t)0x7B5D, (q15_t)0x2161, (q15_t)0x7B92,
+	(q15_t)0x209F, (q15_t)0x7BC5, (q15_t)0x1FDC, (q15_t)0x7BF8,
+	(q15_t)0x1F19, (q15_t)0x7C29, (q15_t)0x1E56, (q15_t)0x7C5A,
+	(q15_t)0x1D93, (q15_t)0x7C89, (q15_t)0x1CCF, (q15_t)0x7CB7,
+	(q15_t)0x1C0B, (q15_t)0x7CE3, (q15_t)0x1B47, (q15_t)0x7D0F,
+	(q15_t)0x1A82, (q15_t)0x7D39, (q15_t)0x19BD, (q15_t)0x7D62,
+	(q15_t)0x18F8, (q15_t)0x7D8A, (q15_t)0x1833, (q15_t)0x7DB0,
+	(q15_t)0x176D, (q15_t)0x7DD6, (q15_t)0x16A8, (q15_t)0x7DFA,
+	(q15_t)0x15E2, (q15_t)0x7E1D, (q15_t)0x151B, (q15_t)0x7E3F,
+	(q15_t)0x1455, (q15_t)0x7E5F, (q15_t)0x138E, (q15_t)0x7E7F,
+	(q15_t)0x12C8, (q15_t)0x7E9D, (q15_t)0x1201, (q15_t)0x7EBA,
+	(q15_t)0x1139, (q15_t)0x7ED5, (q15_t)0x1072, (q15_t)0x7EF0,
+	(q15_t)0x0FAB, (q15_t)0x7F09, (q15_t)0x0EE3, (q15_t)0x7F21,
+	(q15_t)0x0E1B, (q15_t)0x7F38, (q15_t)0x0D53, (q15_t)0x7F4D,
+	(q15_t)0x0C8B, (q15_t)0x7F62, (q15_t)0x0BC3, (q15_t)0x7F75,
+	(q15_t)0x0AFB, (q15_t)0x7F87, (q15_t)0x0A33, (q15_t)0x7F97,
+	(q15_t)0x096A, (q15_t)0x7FA7, (q15_t)0x08A2, (q15_t)0x7FB5,
+	(q15_t)0x07D9, (q15_t)0x7FC2, (q15_t)0x0710, (q15_t)0x7FCE,
+	(q15_t)0x0647, (q15_t)0x7FD8, (q15_t)0x057F, (q15_t)0x7FE1,
+	(q15_t)0x04B6, (q15_t)0x7FE9, (q15_t)0x03ED, (q15_t)0x7FF0,
+	(q15_t)0x0324, (q15_t)0x7FF6, (q15_t)0x025B, (q15_t)0x7FFA,
+	(q15_t)0x0192, (q15_t)0x7FFD, (q15_t)0x00C9, (q15_t)0x7FFF,
+	(q15_t)0x0000, (q15_t)0x7FFF, (q15_t)0xFF36, (q15_t)0x7FFF,
+	(q15_t)0xFE6D, (q15_t)0x7FFD, (q15_t)0xFDA4, (q15_t)0x7FFA,
+	(q15_t)0xFCDB, (q15_t)0x7FF6, (q15_t)0xFC12, (q15_t)0x7FF0,
+	(q15_t)0xFB49, (q15_t)0x7FE9, (q15_t)0xFA80, (q15_t)0x7FE1,
+	(q15_t)0xF9B8, (q15_t)0x7FD8, (q15_t)0xF8EF, (q15_t)0x7FCE,
+	(q15_t)0xF826, (q15_t)0x7FC2, (q15_t)0xF75D, (q15_t)0x7FB5,
+	(q15_t)0xF695, (q15_t)0x7FA7, (q15_t)0xF5CC, (q15_t)0x7F97,
+	(q15_t)0xF504, (q15_t)0x7F87, (q15_t)0xF43C, (q15_t)0x7F75,
+	(q15_t)0xF374, (q15_t)0x7F62, (q15_t)0xF2AC, (q15_t)0x7F4D,
+	(q15_t)0xF1E4, (q15_t)0x7F38, (q15_t)0xF11C, (q15_t)0x7F21,
+	(q15_t)0xF054, (q15_t)0x7F09, (q15_t)0xEF8D, (q15_t)0x7EF0,
+	(q15_t)0xEEC6, (q15_t)0x7ED5, (q15_t)0xEDFE, (q15_t)0x7EBA,
+	(q15_t)0xED37, (q15_t)0x7E9D, (q15_t)0xEC71, (q15_t)0x7E7F,
+	(q15_t)0xEBAA, (q15_t)0x7E5F, (q15_t)0xEAE4, (q15_t)0x7E3F,
+	(q15_t)0xEA1D, (q15_t)0x7E1D, (q15_t)0xE957, (q15_t)0x7DFA,
+	(q15_t)0xE892, (q15_t)0x7DD6, (q15_t)0xE7CC, (q15_t)0x7DB0,
+	(q15_t)0xE707, (q15_t)0x7D8A, (q15_t)0xE642, (q15_t)0x7D62,
+	(q15_t)0xE57D, (q15_t)0x7D39, (q15_t)0xE4B8, (q15_t)0x7D0F,
+	(q15_t)0xE3F4, (q15_t)0x7CE3, (q15_t)0xE330, (q15_t)0x7CB7,
+	(q15_t)0xE26C, (q15_t)0x7C89, (q15_t)0xE1A9, (q15_t)0x7C5A,
+	(q15_t)0xE0E6, (q15_t)0x7C29, (q15_t)0xE023, (q15_t)0x7BF8,
+	(q15_t)0xDF60, (q15_t)0x7BC5, (q15_t)0xDE9E, (q15_t)0x7B92,
+	(q15_t)0xDDDC, (q15_t)0x7B5D, (q15_t)0xDD1A, (q15_t)0x7B26,
+	(q15_t)0xDC59, (q15_t)0x7AEF, (q15_t)0xDB98, (q15_t)0x7AB6,
+	(q15_t)0xDAD7, (q15_t)0x7A7D, (q15_t)0xDA17, (q15_t)0x7A42,
+	(q15_t)0xD957, (q15_t)0x7A05, (q15_t)0xD898, (q15_t)0x79C8,
+	(q15_t)0xD7D9, (q15_t)0x798A, (q15_t)0xD71A, (q15_t)0x794A,
+	(q15_t)0xD65C, (q15_t)0x7909, (q15_t)0xD59E, (q15_t)0x78C7,
+	(q15_t)0xD4E0, (q15_t)0x7884, (q15_t)0xD423, (q15_t)0x7840,
+	(q15_t)0xD367, (q15_t)0x77FA, (q15_t)0xD2AA, (q15_t)0x77B4,
+	(q15_t)0xD1EE, (q15_t)0x776C, (q15_t)0xD133, (q15_t)0x7723,
+	(q15_t)0xD078, (q15_t)0x76D9, (q15_t)0xCFBE, (q15_t)0x768E,
+	(q15_t)0xCF04, (q15_t)0x7641, (q15_t)0xCE4A, (q15_t)0x75F4,
+	(q15_t)0xCD91, (q15_t)0x75A5, (q15_t)0xCCD9, (q15_t)0x7555,
+	(q15_t)0xCC21, (q15_t)0x7504, (q15_t)0xCB69, (q15_t)0x74B2,
+	(q15_t)0xCAB2, (q15_t)0x745F, (q15_t)0xC9FB, (q15_t)0x740B,
+	(q15_t)0xC945, (q15_t)0x73B5, (q15_t)0xC890, (q15_t)0x735F,
+	(q15_t)0xC7DB, (q15_t)0x7307, (q15_t)0xC727, (q15_t)0x72AF,
+	(q15_t)0xC673, (q15_t)0x7255, (q15_t)0xC5BF, (q15_t)0x71FA,
+	(q15_t)0xC50D, (q15_t)0x719E, (q15_t)0xC45A, (q15_t)0x7141,
+	(q15_t)0xC3A9, (q15_t)0x70E2, (q15_t)0xC2F8, (q15_t)0x7083,
+	(q15_t)0xC247, (q15_t)0x7023, (q15_t)0xC197, (q15_t)0x6FC1,
+	(q15_t)0xC0E8, (q15_t)0x6F5F, (q15_t)0xC03A, (q15_t)0x6EFB,
+	(q15_t)0xBF8C, (q15_t)0x6E96, (q15_t)0xBEDE, (q15_t)0x6E30,
+	(q15_t)0xBE31, (q15_t)0x6DCA, (q15_t)0xBD85, (q15_t)0x6D62,
+	(q15_t)0xBCDA, (q15_t)0x6CF9, (q15_t)0xBC2F, (q15_t)0x6C8F,
+	(q15_t)0xBB85, (q15_t)0x6C24, (q15_t)0xBADB, (q15_t)0x6BB8,
+	(q15_t)0xBA32, (q15_t)0x6B4A, (q15_t)0xB98A, (q15_t)0x6ADC,
+	(q15_t)0xB8E3, (q15_t)0x6A6D, (q15_t)0xB83C, (q15_t)0x69FD,
+	(q15_t)0xB796, (q15_t)0x698C, (q15_t)0xB6F0, (q15_t)0x6919,
+	(q15_t)0xB64B, (q15_t)0x68A6, (q15_t)0xB5A7, (q15_t)0x6832,
+	(q15_t)0xB504, (q15_t)0x67BD, (q15_t)0xB461, (q15_t)0x6746,
+	(q15_t)0xB3C0, (q15_t)0x66CF, (q15_t)0xB31E, (q15_t)0x6657,
+	(q15_t)0xB27E, (q15_t)0x65DD, (q15_t)0xB1DE, (q15_t)0x6563,
+	(q15_t)0xB140, (q15_t)0x64E8, (q15_t)0xB0A1, (q15_t)0x646C,
+	(q15_t)0xB004, (q15_t)0x63EF, (q15_t)0xAF68, (q15_t)0x6371,
+	(q15_t)0xAECC, (q15_t)0x62F2, (q15_t)0xAE31, (q15_t)0x6271,
+	(q15_t)0xAD96, (q15_t)0x61F1, (q15_t)0xACFD, (q15_t)0x616F,
+	(q15_t)0xAC64, (q15_t)0x60EC, (q15_t)0xABCC, (q15_t)0x6068,
+	(q15_t)0xAB35, (q15_t)0x5FE3, (q15_t)0xAA9F, (q15_t)0x5F5E,
+	(q15_t)0xAA0A, (q15_t)0x5ED7, (q15_t)0xA975, (q15_t)0x5E50,
+	(q15_t)0xA8E2, (q15_t)0x5DC7, (q15_t)0xA84F, (q15_t)0x5D3E,
+	(q15_t)0xA7BD, (q15_t)0x5CB4, (q15_t)0xA72B, (q15_t)0x5C29,
+	(q15_t)0xA69B, (q15_t)0x5B9D, (q15_t)0xA60C, (q15_t)0x5B10,
+	(q15_t)0xA57D, (q15_t)0x5A82, (q15_t)0xA4EF, (q15_t)0x59F3,
+	(q15_t)0xA462, (q15_t)0x5964, (q15_t)0xA3D6, (q15_t)0x58D4,
+	(q15_t)0xA34B, (q15_t)0x5842, (q15_t)0xA2C1, (q15_t)0x57B0,
+	(q15_t)0xA238, (q15_t)0x571D, (q15_t)0xA1AF, (q15_t)0x568A,
+	(q15_t)0xA128, (q15_t)0x55F5, (q15_t)0xA0A1, (q15_t)0x5560,
+	(q15_t)0xA01C, (q15_t)0x54CA, (q15_t)0x9F97, (q15_t)0x5433,
+	(q15_t)0x9F13, (q15_t)0x539B, (q15_t)0x9E90, (q15_t)0x5302,
+	(q15_t)0x9E0E, (q15_t)0x5269, (q15_t)0x9D8E, (q15_t)0x51CE,
+	(q15_t)0x9D0D, (q15_t)0x5133, (q15_t)0x9C8E, (q15_t)0x5097,
+	(q15_t)0x9C10, (q15_t)0x4FFB, (q15_t)0x9B93, (q15_t)0x4F5E,
+	(q15_t)0x9B17, (q15_t)0x4EBF, (q15_t)0x9A9C, (q15_t)0x4E21,
+	(q15_t)0x9A22, (q15_t)0x4D81, (q15_t)0x99A8, (q15_t)0x4CE1,
+	(q15_t)0x9930, (q15_t)0x4C3F, (q15_t)0x98B9, (q15_t)0x4B9E,
+	(q15_t)0x9842, (q15_t)0x4AFB, (q15_t)0x97CD, (q15_t)0x4A58,
+	(q15_t)0x9759, (q15_t)0x49B4, (q15_t)0x96E6, (q15_t)0x490F,
+	(q15_t)0x9673, (q15_t)0x4869, (q15_t)0x9602, (q15_t)0x47C3,
+	(q15_t)0x9592, (q15_t)0x471C, (q15_t)0x9523, (q15_t)0x4675,
+	(q15_t)0x94B5, (q15_t)0x45CD, (q15_t)0x9447, (q15_t)0x4524,
+	(q15_t)0x93DB, (q15_t)0x447A, (q15_t)0x9370, (q15_t)0x43D0,
+	(q15_t)0x9306, (q15_t)0x4325, (q15_t)0x929D, (q15_t)0x427A,
+	(q15_t)0x9235, (q15_t)0x41CE, (q15_t)0x91CF, (q15_t)0x4121,
+	(q15_t)0x9169, (q15_t)0x4073, (q15_t)0x9104, (q15_t)0x3FC5,
+	(q15_t)0x90A0, (q15_t)0x3F17, (q15_t)0x903E, (q15_t)0x3E68,
+	(q15_t)0x8FDC, (q15_t)0x3DB8, (q15_t)0x8F7C, (q15_t)0x3D07,
+	(q15_t)0x8F1D, (q15_t)0x3C56, (q15_t)0x8EBE, (q15_t)0x3BA5,
+	(q15_t)0x8E61, (q15_t)0x3AF2, (q15_t)0x8E05, (q15_t)0x3A40,
+	(q15_t)0x8DAA, (q15_t)0x398C, (q15_t)0x8D50, (q15_t)0x38D8,
+	(q15_t)0x8CF8, (q15_t)0x3824, (q15_t)0x8CA0, (q15_t)0x376F,
+	(q15_t)0x8C4A, (q15_t)0x36BA, (q15_t)0x8BF4, (q15_t)0x3604,
+	(q15_t)0x8BA0, (q15_t)0x354D, (q15_t)0x8B4D, (q15_t)0x3496,
+	(q15_t)0x8AFB, (q15_t)0x33DE, (q15_t)0x8AAA, (q15_t)0x3326,
+	(q15_t)0x8A5A, (q15_t)0x326E, (q15_t)0x8A0B, (q15_t)0x31B5,
+	(q15_t)0x89BE, (q15_t)0x30FB, (q15_t)0x8971, (q15_t)0x3041,
+	(q15_t)0x8926, (q15_t)0x2F87, (q15_t)0x88DC, (q15_t)0x2ECC,
+	(q15_t)0x8893, (q15_t)0x2E11, (q15_t)0x884B, (q15_t)0x2D55,
+	(q15_t)0x8805, (q15_t)0x2C98, (q15_t)0x87BF, (q15_t)0x2BDC,
+	(q15_t)0x877B, (q15_t)0x2B1F, (q15_t)0x8738, (q15_t)0x2A61,
+	(q15_t)0x86F6, (q15_t)0x29A3, (q15_t)0x86B5, (q15_t)0x28E5,
+	(q15_t)0x8675, (q15_t)0x2826, (q15_t)0x8637, (q15_t)0x2767,
+	(q15_t)0x85FA, (q15_t)0x26A8, (q15_t)0x85BD, (q15_t)0x25E8,
+	(q15_t)0x8582, (q15_t)0x2528, (q15_t)0x8549, (q15_t)0x2467,
+	(q15_t)0x8510, (q15_t)0x23A6, (q15_t)0x84D9, (q15_t)0x22E5,
+	(q15_t)0x84A2, (q15_t)0x2223, (q15_t)0x846D, (q15_t)0x2161,
+	(q15_t)0x843A, (q15_t)0x209F, (q15_t)0x8407, (q15_t)0x1FDC,
+	(q15_t)0x83D6, (q15_t)0x1F19, (q15_t)0x83A5, (q15_t)0x1E56,
+	(q15_t)0x8376, (q15_t)0x1D93, (q15_t)0x8348, (q15_t)0x1CCF,
+	(q15_t)0x831C, (q15_t)0x1C0B, (q15_t)0x82F0, (q15_t)0x1B47,
+	(q15_t)0x82C6, (q15_t)0x1A82, (q15_t)0x829D, (q15_t)0x19BD,
+	(q15_t)0x8275, (q15_t)0x18F8, (q15_t)0x824F, (q15_t)0x1833,
+	(q15_t)0x8229, (q15_t)0x176D, (q15_t)0x8205, (q15_t)0x16A8,
+	(q15_t)0x81E2, (q15_t)0x15E2, (q15_t)0x81C0, (q15_t)0x151B,
+	(q15_t)0x81A0, (q15_t)0x1455, (q15_t)0x8180, (q15_t)0x138E,
+	(q15_t)0x8162, (q15_t)0x12C8, (q15_t)0x8145, (q15_t)0x1201,
+	(q15_t)0x812A, (q15_t)0x1139, (q15_t)0x810F, (q15_t)0x1072,
+	(q15_t)0x80F6, (q15_t)0x0FAB, (q15_t)0x80DE, (q15_t)0x0EE3,
+	(q15_t)0x80C7, (q15_t)0x0E1B, (q15_t)0x80B2, (q15_t)0x0D53,
+	(q15_t)0x809D, (q15_t)0x0C8B, (q15_t)0x808A, (q15_t)0x0BC3,
+	(q15_t)0x8078, (q15_t)0x0AFB, (q15_t)0x8068, (q15_t)0x0A33,
+	(q15_t)0x8058, (q15_t)0x096A, (q15_t)0x804A, (q15_t)0x08A2,
+	(q15_t)0x803D, (q15_t)0x07D9, (q15_t)0x8031, (q15_t)0x0710,
+	(q15_t)0x8027, (q15_t)0x0647, (q15_t)0x801E, (q15_t)0x057F,
+	(q15_t)0x8016, (q15_t)0x04B6, (q15_t)0x800F, (q15_t)0x03ED,
+	(q15_t)0x8009, (q15_t)0x0324, (q15_t)0x8005, (q15_t)0x025B,
+	(q15_t)0x8002, (q15_t)0x0192, (q15_t)0x8000, (q15_t)0x00C9,
+	(q15_t)0x8000, (q15_t)0x0000, (q15_t)0x8000, (q15_t)0xFF36,
+	(q15_t)0x8002, (q15_t)0xFE6D, (q15_t)0x8005, (q15_t)0xFDA4,
+	(q15_t)0x8009, (q15_t)0xFCDB, (q15_t)0x800F, (q15_t)0xFC12,
+	(q15_t)0x8016, (q15_t)0xFB49, (q15_t)0x801E, (q15_t)0xFA80,
+	(q15_t)0x8027, (q15_t)0xF9B8, (q15_t)0x8031, (q15_t)0xF8EF,
+	(q15_t)0x803D, (q15_t)0xF826, (q15_t)0x804A, (q15_t)0xF75D,
+	(q15_t)0x8058, (q15_t)0xF695, (q15_t)0x8068, (q15_t)0xF5CC,
+	(q15_t)0x8078, (q15_t)0xF504, (q15_t)0x808A, (q15_t)0xF43C,
+	(q15_t)0x809D, (q15_t)0xF374, (q15_t)0x80B2, (q15_t)0xF2AC,
+	(q15_t)0x80C7, (q15_t)0xF1E4, (q15_t)0x80DE, (q15_t)0xF11C,
+	(q15_t)0x80F6, (q15_t)0xF054, (q15_t)0x810F, (q15_t)0xEF8D,
+	(q15_t)0x812A, (q15_t)0xEEC6, (q15_t)0x8145, (q15_t)0xEDFE,
+	(q15_t)0x8162, (q15_t)0xED37, (q15_t)0x8180, (q15_t)0xEC71,
+	(q15_t)0x81A0, (q15_t)0xEBAA, (q15_t)0x81C0, (q15_t)0xEAE4,
+	(q15_t)0x81E2, (q15_t)0xEA1D, (q15_t)0x8205, (q15_t)0xE957,
+	(q15_t)0x8229, (q15_t)0xE892, (q15_t)0x824F, (q15_t)0xE7CC,
+	(q15_t)0x8275, (q15_t)0xE707, (q15_t)0x829D, (q15_t)0xE642,
+	(q15_t)0x82C6, (q15_t)0xE57D, (q15_t)0x82F0, (q15_t)0xE4B8,
+	(q15_t)0x831C, (q15_t)0xE3F4, (q15_t)0x8348, (q15_t)0xE330,
+	(q15_t)0x8376, (q15_t)0xE26C, (q15_t)0x83A5, (q15_t)0xE1A9,
+	(q15_t)0x83D6, (q15_t)0xE0E6, (q15_t)0x8407, (q15_t)0xE023,
+	(q15_t)0x843A, (q15_t)0xDF60, (q15_t)0x846D, (q15_t)0xDE9E,
+	(q15_t)0x84A2, (q15_t)0xDDDC, (q15_t)0x84D9, (q15_t)0xDD1A,
+	(q15_t)0x8510, (q15_t)0xDC59, (q15_t)0x8549, (q15_t)0xDB98,
+	(q15_t)0x8582, (q15_t)0xDAD7, (q15_t)0x85BD, (q15_t)0xDA17,
+	(q15_t)0x85FA, (q15_t)0xD957, (q15_t)0x8637, (q15_t)0xD898,
+	(q15_t)0x8675, (q15_t)0xD7D9, (q15_t)0x86B5, (q15_t)0xD71A,
+	(q15_t)0x86F6, (q15_t)0xD65C, (q15_t)0x8738, (q15_t)0xD59E,
+	(q15_t)0x877B, (q15_t)0xD4E0, (q15_t)0x87BF, (q15_t)0xD423,
+	(q15_t)0x8805, (q15_t)0xD367, (q15_t)0x884B, (q15_t)0xD2AA,
+	(q15_t)0x8893, (q15_t)0xD1EE, (q15_t)0x88DC, (q15_t)0xD133,
+	(q15_t)0x8926, (q15_t)0xD078, (q15_t)0x8971, (q15_t)0xCFBE,
+	(q15_t)0x89BE, (q15_t)0xCF04, (q15_t)0x8A0B, (q15_t)0xCE4A,
+	(q15_t)0x8A5A, (q15_t)0xCD91, (q15_t)0x8AAA, (q15_t)0xCCD9,
+	(q15_t)0x8AFB, (q15_t)0xCC21, (q15_t)0x8B4D, (q15_t)0xCB69,
+	(q15_t)0x8BA0, (q15_t)0xCAB2, (q15_t)0x8BF4, (q15_t)0xC9FB,
+	(q15_t)0x8C4A, (q15_t)0xC945, (q15_t)0x8CA0, (q15_t)0xC890,
+	(q15_t)0x8CF8, (q15_t)0xC7DB, (q15_t)0x8D50, (q15_t)0xC727,
+	(q15_t)0x8DAA, (q15_t)0xC673, (q15_t)0x8E05, (q15_t)0xC5BF,
+	(q15_t)0x8E61, (q15_t)0xC50D, (q15_t)0x8EBE, (q15_t)0xC45A,
+	(q15_t)0x8F1D, (q15_t)0xC3A9, (q15_t)0x8F7C, (q15_t)0xC2F8,
+	(q15_t)0x8FDC, (q15_t)0xC247, (q15_t)0x903E, (q15_t)0xC197,
+	(q15_t)0x90A0, (q15_t)0xC0E8, (q15_t)0x9104, (q15_t)0xC03A,
+	(q15_t)0x9169, (q15_t)0xBF8C, (q15_t)0x91CF, (q15_t)0xBEDE,
+	(q15_t)0x9235, (q15_t)0xBE31, (q15_t)0x929D, (q15_t)0xBD85,
+	(q15_t)0x9306, (q15_t)0xBCDA, (q15_t)0x9370, (q15_t)0xBC2F,
+	(q15_t)0x93DB, (q15_t)0xBB85, (q15_t)0x9447, (q15_t)0xBADB,
+	(q15_t)0x94B5, (q15_t)0xBA32, (q15_t)0x9523, (q15_t)0xB98A,
+	(q15_t)0x9592, (q15_t)0xB8E3, (q15_t)0x9602, (q15_t)0xB83C,
+	(q15_t)0x9673, (q15_t)0xB796, (q15_t)0x96E6, (q15_t)0xB6F0,
+	(q15_t)0x9759, (q15_t)0xB64B, (q15_t)0x97CD, (q15_t)0xB5A7,
+	(q15_t)0x9842, (q15_t)0xB504, (q15_t)0x98B9, (q15_t)0xB461,
+	(q15_t)0x9930, (q15_t)0xB3C0, (q15_t)0x99A8, (q15_t)0xB31E,
+	(q15_t)0x9A22, (q15_t)0xB27E, (q15_t)0x9A9C, (q15_t)0xB1DE,
+	(q15_t)0x9B17, (q15_t)0xB140, (q15_t)0x9B93, (q15_t)0xB0A1,
+	(q15_t)0x9C10, (q15_t)0xB004, (q15_t)0x9C8E, (q15_t)0xAF68,
+	(q15_t)0x9D0D, (q15_t)0xAECC, (q15_t)0x9D8E, (q15_t)0xAE31,
+	(q15_t)0x9E0E, (q15_t)0xAD96, (q15_t)0x9E90, (q15_t)0xACFD,
+	(q15_t)0x9F13, (q15_t)0xAC64, (q15_t)0x9F97, (q15_t)0xABCC,
+	(q15_t)0xA01C, (q15_t)0xAB35, (q15_t)0xA0A1, (q15_t)0xAA9F,
+	(q15_t)0xA128, (q15_t)0xAA0A, (q15_t)0xA1AF, (q15_t)0xA975,
+	(q15_t)0xA238, (q15_t)0xA8E2, (q15_t)0xA2C1, (q15_t)0xA84F,
+	(q15_t)0xA34B, (q15_t)0xA7BD, (q15_t)0xA3D6, (q15_t)0xA72B,
+	(q15_t)0xA462, (q15_t)0xA69B, (q15_t)0xA4EF, (q15_t)0xA60C,
+	(q15_t)0xA57D, (q15_t)0xA57D, (q15_t)0xA60C, (q15_t)0xA4EF,
+	(q15_t)0xA69B, (q15_t)0xA462, (q15_t)0xA72B, (q15_t)0xA3D6,
+	(q15_t)0xA7BD, (q15_t)0xA34B, (q15_t)0xA84F, (q15_t)0xA2C1,
+	(q15_t)0xA8E2, (q15_t)0xA238, (q15_t)0xA975, (q15_t)0xA1AF,
+	(q15_t)0xAA0A, (q15_t)0xA128, (q15_t)0xAA9F, (q15_t)0xA0A1,
+	(q15_t)0xAB35, (q15_t)0xA01C, (q15_t)0xABCC, (q15_t)0x9F97,
+	(q15_t)0xAC64, (q15_t)0x9F13, (q15_t)0xACFD, (q15_t)0x9E90,
+	(q15_t)0xAD96, (q15_t)0x9E0E, (q15_t)0xAE31, (q15_t)0x9D8E,
+	(q15_t)0xAECC, (q15_t)0x9D0D, (q15_t)0xAF68, (q15_t)0x9C8E,
+	(q15_t)0xB004, (q15_t)0x9C10, (q15_t)0xB0A1, (q15_t)0x9B93,
+	(q15_t)0xB140, (q15_t)0x9B17, (q15_t)0xB1DE, (q15_t)0x9A9C,
+	(q15_t)0xB27E, (q15_t)0x9A22, (q15_t)0xB31E, (q15_t)0x99A8,
+	(q15_t)0xB3C0, (q15_t)0x9930, (q15_t)0xB461, (q15_t)0x98B9,
+	(q15_t)0xB504, (q15_t)0x9842, (q15_t)0xB5A7, (q15_t)0x97CD,
+	(q15_t)0xB64B, (q15_t)0x9759, (q15_t)0xB6F0, (q15_t)0x96E6,
+	(q15_t)0xB796, (q15_t)0x9673, (q15_t)0xB83C, (q15_t)0x9602,
+	(q15_t)0xB8E3, (q15_t)0x9592, (q15_t)0xB98A, (q15_t)0x9523,
+	(q15_t)0xBA32, (q15_t)0x94B5, (q15_t)0xBADB, (q15_t)0x9447,
+	(q15_t)0xBB85, (q15_t)0x93DB, (q15_t)0xBC2F, (q15_t)0x9370,
+	(q15_t)0xBCDA, (q15_t)0x9306, (q15_t)0xBD85, (q15_t)0x929D,
+	(q15_t)0xBE31, (q15_t)0x9235, (q15_t)0xBEDE, (q15_t)0x91CF,
+	(q15_t)0xBF8C, (q15_t)0x9169, (q15_t)0xC03A, (q15_t)0x9104,
+	(q15_t)0xC0E8, (q15_t)0x90A0, (q15_t)0xC197, (q15_t)0x903E,
+	(q15_t)0xC247, (q15_t)0x8FDC, (q15_t)0xC2F8, (q15_t)0x8F7C,
+	(q15_t)0xC3A9, (q15_t)0x8F1D, (q15_t)0xC45A, (q15_t)0x8EBE,
+	(q15_t)0xC50D, (q15_t)0x8E61, (q15_t)0xC5BF, (q15_t)0x8E05,
+	(q15_t)0xC673, (q15_t)0x8DAA, (q15_t)0xC727, (q15_t)0x8D50,
+	(q15_t)0xC7DB, (q15_t)0x8CF8, (q15_t)0xC890, (q15_t)0x8CA0,
+	(q15_t)0xC945, (q15_t)0x8C4A, (q15_t)0xC9FB, (q15_t)0x8BF4,
+	(q15_t)0xCAB2, (q15_t)0x8BA0, (q15_t)0xCB69, (q15_t)0x8B4D,
+	(q15_t)0xCC21, (q15_t)0x8AFB, (q15_t)0xCCD9, (q15_t)0x8AAA,
+	(q15_t)0xCD91, (q15_t)0x8A5A, (q15_t)0xCE4A, (q15_t)0x8A0B,
+	(q15_t)0xCF04, (q15_t)0x89BE, (q15_t)0xCFBE, (q15_t)0x8971,
+	(q15_t)0xD078, (q15_t)0x8926, (q15_t)0xD133, (q15_t)0x88DC,
+	(q15_t)0xD1EE, (q15_t)0x8893, (q15_t)0xD2AA, (q15_t)0x884B,
+	(q15_t)0xD367, (q15_t)0x8805, (q15_t)0xD423, (q15_t)0x87BF,
+	(q15_t)0xD4E0, (q15_t)0x877B, (q15_t)0xD59E, (q15_t)0x8738,
+	(q15_t)0xD65C, (q15_t)0x86F6, (q15_t)0xD71A, (q15_t)0x86B5,
+	(q15_t)0xD7D9, (q15_t)0x8675, (q15_t)0xD898, (q15_t)0x8637,
+	(q15_t)0xD957, (q15_t)0x85FA, (q15_t)0xDA17, (q15_t)0x85BD,
+	(q15_t)0xDAD7, (q15_t)0x8582, (q15_t)0xDB98, (q15_t)0x8549,
+	(q15_t)0xDC59, (q15_t)0x8510, (q15_t)0xDD1A, (q15_t)0x84D9,
+	(q15_t)0xDDDC, (q15_t)0x84A2, (q15_t)0xDE9E, (q15_t)0x846D,
+	(q15_t)0xDF60, (q15_t)0x843A, (q15_t)0xE023, (q15_t)0x8407,
+	(q15_t)0xE0E6, (q15_t)0x83D6, (q15_t)0xE1A9, (q15_t)0x83A5,
+	(q15_t)0xE26C, (q15_t)0x8376, (q15_t)0xE330, (q15_t)0x8348,
+	(q15_t)0xE3F4, (q15_t)0x831C, (q15_t)0xE4B8, (q15_t)0x82F0,
+	(q15_t)0xE57D, (q15_t)0x82C6, (q15_t)0xE642, (q15_t)0x829D,
+	(q15_t)0xE707, (q15_t)0x8275, (q15_t)0xE7CC, (q15_t)0x824F,
+	(q15_t)0xE892, (q15_t)0x8229, (q15_t)0xE957, (q15_t)0x8205,
+	(q15_t)0xEA1D, (q15_t)0x81E2, (q15_t)0xEAE4, (q15_t)0x81C0,
+	(q15_t)0xEBAA, (q15_t)0x81A0, (q15_t)0xEC71, (q15_t)0x8180,
+	(q15_t)0xED37, (q15_t)0x8162, (q15_t)0xEDFE, (q15_t)0x8145,
+	(q15_t)0xEEC6, (q15_t)0x812A, (q15_t)0xEF8D, (q15_t)0x810F,
+	(q15_t)0xF054, (q15_t)0x80F6, (q15_t)0xF11C, (q15_t)0x80DE,
+	(q15_t)0xF1E4, (q15_t)0x80C7, (q15_t)0xF2AC, (q15_t)0x80B2,
+	(q15_t)0xF374, (q15_t)0x809D, (q15_t)0xF43C, (q15_t)0x808A,
+	(q15_t)0xF504, (q15_t)0x8078, (q15_t)0xF5CC, (q15_t)0x8068,
+	(q15_t)0xF695, (q15_t)0x8058, (q15_t)0xF75D, (q15_t)0x804A,
+	(q15_t)0xF826, (q15_t)0x803D, (q15_t)0xF8EF, (q15_t)0x8031,
+	(q15_t)0xF9B8, (q15_t)0x8027, (q15_t)0xFA80, (q15_t)0x801E,
+	(q15_t)0xFB49, (q15_t)0x8016, (q15_t)0xFC12, (q15_t)0x800F,
+	(q15_t)0xFCDB, (q15_t)0x8009, (q15_t)0xFDA4, (q15_t)0x8005,
+	(q15_t)0xFE6D, (q15_t)0x8002, (q15_t)0xFF36, (q15_t)0x8000
+};
+
+/**
+* \par
+* Example code for q15 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefq15[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefq15[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 2048	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to q15(Fixed point 1.15):
+*	round(twiddleCoefq15(i) * pow(2, 15))
+*
+*/
+const q15_t twiddleCoef_2048_q15[3072] = {
+	(q15_t)0x7FFF, (q15_t)0x0000, (q15_t)0x7FFF, (q15_t)0x0064,
+	(q15_t)0x7FFF, (q15_t)0x00C9, (q15_t)0x7FFE, (q15_t)0x012D,
+	(q15_t)0x7FFD, (q15_t)0x0192, (q15_t)0x7FFC, (q15_t)0x01F6,
+	(q15_t)0x7FFA, (q15_t)0x025B, (q15_t)0x7FF8, (q15_t)0x02BF,
+	(q15_t)0x7FF6, (q15_t)0x0324, (q15_t)0x7FF3, (q15_t)0x0388,
+	(q15_t)0x7FF0, (q15_t)0x03ED, (q15_t)0x7FED, (q15_t)0x0451,
+	(q15_t)0x7FE9, (q15_t)0x04B6, (q15_t)0x7FE5, (q15_t)0x051A,
+	(q15_t)0x7FE1, (q15_t)0x057F, (q15_t)0x7FDD, (q15_t)0x05E3,
+	(q15_t)0x7FD8, (q15_t)0x0647, (q15_t)0x7FD3, (q15_t)0x06AC,
+	(q15_t)0x7FCE, (q15_t)0x0710, (q15_t)0x7FC8, (q15_t)0x0775,
+	(q15_t)0x7FC2, (q15_t)0x07D9, (q15_t)0x7FBC, (q15_t)0x083D,
+	(q15_t)0x7FB5, (q15_t)0x08A2, (q15_t)0x7FAE, (q15_t)0x0906,
+	(q15_t)0x7FA7, (q15_t)0x096A, (q15_t)0x7F9F, (q15_t)0x09CE,
+	(q15_t)0x7F97, (q15_t)0x0A33, (q15_t)0x7F8F, (q15_t)0x0A97,
+	(q15_t)0x7F87, (q15_t)0x0AFB, (q15_t)0x7F7E, (q15_t)0x0B5F,
+	(q15_t)0x7F75, (q15_t)0x0BC3, (q15_t)0x7F6B, (q15_t)0x0C27,
+	(q15_t)0x7F62, (q15_t)0x0C8B, (q15_t)0x7F58, (q15_t)0x0CEF,
+	(q15_t)0x7F4D, (q15_t)0x0D53, (q15_t)0x7F43, (q15_t)0x0DB7,
+	(q15_t)0x7F38, (q15_t)0x0E1B, (q15_t)0x7F2D, (q15_t)0x0E7F,
+	(q15_t)0x7F21, (q15_t)0x0EE3, (q15_t)0x7F15, (q15_t)0x0F47,
+	(q15_t)0x7F09, (q15_t)0x0FAB, (q15_t)0x7EFD, (q15_t)0x100E,
+	(q15_t)0x7EF0, (q15_t)0x1072, (q15_t)0x7EE3, (q15_t)0x10D6,
+	(q15_t)0x7ED5, (q15_t)0x1139, (q15_t)0x7EC8, (q15_t)0x119D,
+	(q15_t)0x7EBA, (q15_t)0x1201, (q15_t)0x7EAB, (q15_t)0x1264,
+	(q15_t)0x7E9D, (q15_t)0x12C8, (q15_t)0x7E8E, (q15_t)0x132B,
+	(q15_t)0x7E7F, (q15_t)0x138E, (q15_t)0x7E6F, (q15_t)0x13F2,
+	(q15_t)0x7E5F, (q15_t)0x1455, (q15_t)0x7E4F, (q15_t)0x14B8,
+	(q15_t)0x7E3F, (q15_t)0x151B, (q15_t)0x7E2E, (q15_t)0x157F,
+	(q15_t)0x7E1D, (q15_t)0x15E2, (q15_t)0x7E0C, (q15_t)0x1645,
+	(q15_t)0x7DFA, (q15_t)0x16A8, (q15_t)0x7DE8, (q15_t)0x170A,
+	(q15_t)0x7DD6, (q15_t)0x176D, (q15_t)0x7DC3, (q15_t)0x17D0,
+	(q15_t)0x7DB0, (q15_t)0x1833, (q15_t)0x7D9D, (q15_t)0x1896,
+	(q15_t)0x7D8A, (q15_t)0x18F8, (q15_t)0x7D76, (q15_t)0x195B,
+	(q15_t)0x7D62, (q15_t)0x19BD, (q15_t)0x7D4E, (q15_t)0x1A20,
+	(q15_t)0x7D39, (q15_t)0x1A82, (q15_t)0x7D24, (q15_t)0x1AE4,
+	(q15_t)0x7D0F, (q15_t)0x1B47, (q15_t)0x7CF9, (q15_t)0x1BA9,
+	(q15_t)0x7CE3, (q15_t)0x1C0B, (q15_t)0x7CCD, (q15_t)0x1C6D,
+	(q15_t)0x7CB7, (q15_t)0x1CCF, (q15_t)0x7CA0, (q15_t)0x1D31,
+	(q15_t)0x7C89, (q15_t)0x1D93, (q15_t)0x7C71, (q15_t)0x1DF5,
+	(q15_t)0x7C5A, (q15_t)0x1E56, (q15_t)0x7C42, (q15_t)0x1EB8,
+	(q15_t)0x7C29, (q15_t)0x1F19, (q15_t)0x7C11, (q15_t)0x1F7B,
+	(q15_t)0x7BF8, (q15_t)0x1FDC, (q15_t)0x7BDF, (q15_t)0x203E,
+	(q15_t)0x7BC5, (q15_t)0x209F, (q15_t)0x7BAC, (q15_t)0x2100,
+	(q15_t)0x7B92, (q15_t)0x2161, (q15_t)0x7B77, (q15_t)0x21C2,
+	(q15_t)0x7B5D, (q15_t)0x2223, (q15_t)0x7B42, (q15_t)0x2284,
+	(q15_t)0x7B26, (q15_t)0x22E5, (q15_t)0x7B0B, (q15_t)0x2345,
+	(q15_t)0x7AEF, (q15_t)0x23A6, (q15_t)0x7AD3, (q15_t)0x2407,
+	(q15_t)0x7AB6, (q15_t)0x2467, (q15_t)0x7A9A, (q15_t)0x24C7,
+	(q15_t)0x7A7D, (q15_t)0x2528, (q15_t)0x7A5F, (q15_t)0x2588,
+	(q15_t)0x7A42, (q15_t)0x25E8, (q15_t)0x7A24, (q15_t)0x2648,
+	(q15_t)0x7A05, (q15_t)0x26A8, (q15_t)0x79E7, (q15_t)0x2707,
+	(q15_t)0x79C8, (q15_t)0x2767, (q15_t)0x79A9, (q15_t)0x27C7,
+	(q15_t)0x798A, (q15_t)0x2826, (q15_t)0x796A, (q15_t)0x2886,
+	(q15_t)0x794A, (q15_t)0x28E5, (q15_t)0x792A, (q15_t)0x2944,
+	(q15_t)0x7909, (q15_t)0x29A3, (q15_t)0x78E8, (q15_t)0x2A02,
+	(q15_t)0x78C7, (q15_t)0x2A61, (q15_t)0x78A6, (q15_t)0x2AC0,
+	(q15_t)0x7884, (q15_t)0x2B1F, (q15_t)0x7862, (q15_t)0x2B7D,
+	(q15_t)0x7840, (q15_t)0x2BDC, (q15_t)0x781D, (q15_t)0x2C3A,
+	(q15_t)0x77FA, (q15_t)0x2C98, (q15_t)0x77D7, (q15_t)0x2CF7,
+	(q15_t)0x77B4, (q15_t)0x2D55, (q15_t)0x7790, (q15_t)0x2DB3,
+	(q15_t)0x776C, (q15_t)0x2E11, (q15_t)0x7747, (q15_t)0x2E6E,
+	(q15_t)0x7723, (q15_t)0x2ECC, (q15_t)0x76FE, (q15_t)0x2F29,
+	(q15_t)0x76D9, (q15_t)0x2F87, (q15_t)0x76B3, (q15_t)0x2FE4,
+	(q15_t)0x768E, (q15_t)0x3041, (q15_t)0x7668, (q15_t)0x309E,
+	(q15_t)0x7641, (q15_t)0x30FB, (q15_t)0x761B, (q15_t)0x3158,
+	(q15_t)0x75F4, (q15_t)0x31B5, (q15_t)0x75CC, (q15_t)0x3211,
+	(q15_t)0x75A5, (q15_t)0x326E, (q15_t)0x757D, (q15_t)0x32CA,
+	(q15_t)0x7555, (q15_t)0x3326, (q15_t)0x752D, (q15_t)0x3382,
+	(q15_t)0x7504, (q15_t)0x33DE, (q15_t)0x74DB, (q15_t)0x343A,
+	(q15_t)0x74B2, (q15_t)0x3496, (q15_t)0x7489, (q15_t)0x34F2,
+	(q15_t)0x745F, (q15_t)0x354D, (q15_t)0x7435, (q15_t)0x35A8,
+	(q15_t)0x740B, (q15_t)0x3604, (q15_t)0x73E0, (q15_t)0x365F,
+	(q15_t)0x73B5, (q15_t)0x36BA, (q15_t)0x738A, (q15_t)0x3714,
+	(q15_t)0x735F, (q15_t)0x376F, (q15_t)0x7333, (q15_t)0x37CA,
+	(q15_t)0x7307, (q15_t)0x3824, (q15_t)0x72DB, (q15_t)0x387E,
+	(q15_t)0x72AF, (q15_t)0x38D8, (q15_t)0x7282, (q15_t)0x3932,
+	(q15_t)0x7255, (q15_t)0x398C, (q15_t)0x7227, (q15_t)0x39E6,
+	(q15_t)0x71FA, (q15_t)0x3A40, (q15_t)0x71CC, (q15_t)0x3A99,
+	(q15_t)0x719E, (q15_t)0x3AF2, (q15_t)0x716F, (q15_t)0x3B4C,
+	(q15_t)0x7141, (q15_t)0x3BA5, (q15_t)0x7112, (q15_t)0x3BFD,
+	(q15_t)0x70E2, (q15_t)0x3C56, (q15_t)0x70B3, (q15_t)0x3CAF,
+	(q15_t)0x7083, (q15_t)0x3D07, (q15_t)0x7053, (q15_t)0x3D60,
+	(q15_t)0x7023, (q15_t)0x3DB8, (q15_t)0x6FF2, (q15_t)0x3E10,
+	(q15_t)0x6FC1, (q15_t)0x3E68, (q15_t)0x6F90, (q15_t)0x3EBF,
+	(q15_t)0x6F5F, (q15_t)0x3F17, (q15_t)0x6F2D, (q15_t)0x3F6E,
+	(q15_t)0x6EFB, (q15_t)0x3FC5, (q15_t)0x6EC9, (q15_t)0x401D,
+	(q15_t)0x6E96, (q15_t)0x4073, (q15_t)0x6E63, (q15_t)0x40CA,
+	(q15_t)0x6E30, (q15_t)0x4121, (q15_t)0x6DFD, (q15_t)0x4177,
+	(q15_t)0x6DCA, (q15_t)0x41CE, (q15_t)0x6D96, (q15_t)0x4224,
+	(q15_t)0x6D62, (q15_t)0x427A, (q15_t)0x6D2D, (q15_t)0x42D0,
+	(q15_t)0x6CF9, (q15_t)0x4325, (q15_t)0x6CC4, (q15_t)0x437B,
+	(q15_t)0x6C8F, (q15_t)0x43D0, (q15_t)0x6C59, (q15_t)0x4425,
+	(q15_t)0x6C24, (q15_t)0x447A, (q15_t)0x6BEE, (q15_t)0x44CF,
+	(q15_t)0x6BB8, (q15_t)0x4524, (q15_t)0x6B81, (q15_t)0x4578,
+	(q15_t)0x6B4A, (q15_t)0x45CD, (q15_t)0x6B13, (q15_t)0x4621,
+	(q15_t)0x6ADC, (q15_t)0x4675, (q15_t)0x6AA5, (q15_t)0x46C9,
+	(q15_t)0x6A6D, (q15_t)0x471C, (q15_t)0x6A35, (q15_t)0x4770,
+	(q15_t)0x69FD, (q15_t)0x47C3, (q15_t)0x69C4, (q15_t)0x4816,
+	(q15_t)0x698C, (q15_t)0x4869, (q15_t)0x6953, (q15_t)0x48BC,
+	(q15_t)0x6919, (q15_t)0x490F, (q15_t)0x68E0, (q15_t)0x4961,
+	(q15_t)0x68A6, (q15_t)0x49B4, (q15_t)0x686C, (q15_t)0x4A06,
+	(q15_t)0x6832, (q15_t)0x4A58, (q15_t)0x67F7, (q15_t)0x4AA9,
+	(q15_t)0x67BD, (q15_t)0x4AFB, (q15_t)0x6782, (q15_t)0x4B4C,
+	(q15_t)0x6746, (q15_t)0x4B9E, (q15_t)0x670B, (q15_t)0x4BEF,
+	(q15_t)0x66CF, (q15_t)0x4C3F, (q15_t)0x6693, (q15_t)0x4C90,
+	(q15_t)0x6657, (q15_t)0x4CE1, (q15_t)0x661A, (q15_t)0x4D31,
+	(q15_t)0x65DD, (q15_t)0x4D81, (q15_t)0x65A0, (q15_t)0x4DD1,
+	(q15_t)0x6563, (q15_t)0x4E21, (q15_t)0x6526, (q15_t)0x4E70,
+	(q15_t)0x64E8, (q15_t)0x4EBF, (q15_t)0x64AA, (q15_t)0x4F0F,
+	(q15_t)0x646C, (q15_t)0x4F5E, (q15_t)0x642D, (q15_t)0x4FAC,
+	(q15_t)0x63EF, (q15_t)0x4FFB, (q15_t)0x63B0, (q15_t)0x5049,
+	(q15_t)0x6371, (q15_t)0x5097, (q15_t)0x6331, (q15_t)0x50E5,
+	(q15_t)0x62F2, (q15_t)0x5133, (q15_t)0x62B2, (q15_t)0x5181,
+	(q15_t)0x6271, (q15_t)0x51CE, (q15_t)0x6231, (q15_t)0x521C,
+	(q15_t)0x61F1, (q15_t)0x5269, (q15_t)0x61B0, (q15_t)0x52B5,
+	(q15_t)0x616F, (q15_t)0x5302, (q15_t)0x612D, (q15_t)0x534E,
+	(q15_t)0x60EC, (q15_t)0x539B, (q15_t)0x60AA, (q15_t)0x53E7,
+	(q15_t)0x6068, (q15_t)0x5433, (q15_t)0x6026, (q15_t)0x547E,
+	(q15_t)0x5FE3, (q15_t)0x54CA, (q15_t)0x5FA0, (q15_t)0x5515,
+	(q15_t)0x5F5E, (q15_t)0x5560, (q15_t)0x5F1A, (q15_t)0x55AB,
+	(q15_t)0x5ED7, (q15_t)0x55F5, (q15_t)0x5E93, (q15_t)0x5640,
+	(q15_t)0x5E50, (q15_t)0x568A, (q15_t)0x5E0B, (q15_t)0x56D4,
+	(q15_t)0x5DC7, (q15_t)0x571D, (q15_t)0x5D83, (q15_t)0x5767,
+	(q15_t)0x5D3E, (q15_t)0x57B0, (q15_t)0x5CF9, (q15_t)0x57F9,
+	(q15_t)0x5CB4, (q15_t)0x5842, (q15_t)0x5C6E, (q15_t)0x588B,
+	(q15_t)0x5C29, (q15_t)0x58D4, (q15_t)0x5BE3, (q15_t)0x591C,
+	(q15_t)0x5B9D, (q15_t)0x5964, (q15_t)0x5B56, (q15_t)0x59AC,
+	(q15_t)0x5B10, (q15_t)0x59F3, (q15_t)0x5AC9, (q15_t)0x5A3B,
+	(q15_t)0x5A82, (q15_t)0x5A82, (q15_t)0x5A3B, (q15_t)0x5AC9,
+	(q15_t)0x59F3, (q15_t)0x5B10, (q15_t)0x59AC, (q15_t)0x5B56,
+	(q15_t)0x5964, (q15_t)0x5B9D, (q15_t)0x591C, (q15_t)0x5BE3,
+	(q15_t)0x58D4, (q15_t)0x5C29, (q15_t)0x588B, (q15_t)0x5C6E,
+	(q15_t)0x5842, (q15_t)0x5CB4, (q15_t)0x57F9, (q15_t)0x5CF9,
+	(q15_t)0x57B0, (q15_t)0x5D3E, (q15_t)0x5767, (q15_t)0x5D83,
+	(q15_t)0x571D, (q15_t)0x5DC7, (q15_t)0x56D4, (q15_t)0x5E0B,
+	(q15_t)0x568A, (q15_t)0x5E50, (q15_t)0x5640, (q15_t)0x5E93,
+	(q15_t)0x55F5, (q15_t)0x5ED7, (q15_t)0x55AB, (q15_t)0x5F1A,
+	(q15_t)0x5560, (q15_t)0x5F5E, (q15_t)0x5515, (q15_t)0x5FA0,
+	(q15_t)0x54CA, (q15_t)0x5FE3, (q15_t)0x547E, (q15_t)0x6026,
+	(q15_t)0x5433, (q15_t)0x6068, (q15_t)0x53E7, (q15_t)0x60AA,
+	(q15_t)0x539B, (q15_t)0x60EC, (q15_t)0x534E, (q15_t)0x612D,
+	(q15_t)0x5302, (q15_t)0x616F, (q15_t)0x52B5, (q15_t)0x61B0,
+	(q15_t)0x5269, (q15_t)0x61F1, (q15_t)0x521C, (q15_t)0x6231,
+	(q15_t)0x51CE, (q15_t)0x6271, (q15_t)0x5181, (q15_t)0x62B2,
+	(q15_t)0x5133, (q15_t)0x62F2, (q15_t)0x50E5, (q15_t)0x6331,
+	(q15_t)0x5097, (q15_t)0x6371, (q15_t)0x5049, (q15_t)0x63B0,
+	(q15_t)0x4FFB, (q15_t)0x63EF, (q15_t)0x4FAC, (q15_t)0x642D,
+	(q15_t)0x4F5E, (q15_t)0x646C, (q15_t)0x4F0F, (q15_t)0x64AA,
+	(q15_t)0x4EBF, (q15_t)0x64E8, (q15_t)0x4E70, (q15_t)0x6526,
+	(q15_t)0x4E21, (q15_t)0x6563, (q15_t)0x4DD1, (q15_t)0x65A0,
+	(q15_t)0x4D81, (q15_t)0x65DD, (q15_t)0x4D31, (q15_t)0x661A,
+	(q15_t)0x4CE1, (q15_t)0x6657, (q15_t)0x4C90, (q15_t)0x6693,
+	(q15_t)0x4C3F, (q15_t)0x66CF, (q15_t)0x4BEF, (q15_t)0x670B,
+	(q15_t)0x4B9E, (q15_t)0x6746, (q15_t)0x4B4C, (q15_t)0x6782,
+	(q15_t)0x4AFB, (q15_t)0x67BD, (q15_t)0x4AA9, (q15_t)0x67F7,
+	(q15_t)0x4A58, (q15_t)0x6832, (q15_t)0x4A06, (q15_t)0x686C,
+	(q15_t)0x49B4, (q15_t)0x68A6, (q15_t)0x4961, (q15_t)0x68E0,
+	(q15_t)0x490F, (q15_t)0x6919, (q15_t)0x48BC, (q15_t)0x6953,
+	(q15_t)0x4869, (q15_t)0x698C, (q15_t)0x4816, (q15_t)0x69C4,
+	(q15_t)0x47C3, (q15_t)0x69FD, (q15_t)0x4770, (q15_t)0x6A35,
+	(q15_t)0x471C, (q15_t)0x6A6D, (q15_t)0x46C9, (q15_t)0x6AA5,
+	(q15_t)0x4675, (q15_t)0x6ADC, (q15_t)0x4621, (q15_t)0x6B13,
+	(q15_t)0x45CD, (q15_t)0x6B4A, (q15_t)0x4578, (q15_t)0x6B81,
+	(q15_t)0x4524, (q15_t)0x6BB8, (q15_t)0x44CF, (q15_t)0x6BEE,
+	(q15_t)0x447A, (q15_t)0x6C24, (q15_t)0x4425, (q15_t)0x6C59,
+	(q15_t)0x43D0, (q15_t)0x6C8F, (q15_t)0x437B, (q15_t)0x6CC4,
+	(q15_t)0x4325, (q15_t)0x6CF9, (q15_t)0x42D0, (q15_t)0x6D2D,
+	(q15_t)0x427A, (q15_t)0x6D62, (q15_t)0x4224, (q15_t)0x6D96,
+	(q15_t)0x41CE, (q15_t)0x6DCA, (q15_t)0x4177, (q15_t)0x6DFD,
+	(q15_t)0x4121, (q15_t)0x6E30, (q15_t)0x40CA, (q15_t)0x6E63,
+	(q15_t)0x4073, (q15_t)0x6E96, (q15_t)0x401D, (q15_t)0x6EC9,
+	(q15_t)0x3FC5, (q15_t)0x6EFB, (q15_t)0x3F6E, (q15_t)0x6F2D,
+	(q15_t)0x3F17, (q15_t)0x6F5F, (q15_t)0x3EBF, (q15_t)0x6F90,
+	(q15_t)0x3E68, (q15_t)0x6FC1, (q15_t)0x3E10, (q15_t)0x6FF2,
+	(q15_t)0x3DB8, (q15_t)0x7023, (q15_t)0x3D60, (q15_t)0x7053,
+	(q15_t)0x3D07, (q15_t)0x7083, (q15_t)0x3CAF, (q15_t)0x70B3,
+	(q15_t)0x3C56, (q15_t)0x70E2, (q15_t)0x3BFD, (q15_t)0x7112,
+	(q15_t)0x3BA5, (q15_t)0x7141, (q15_t)0x3B4C, (q15_t)0x716F,
+	(q15_t)0x3AF2, (q15_t)0x719E, (q15_t)0x3A99, (q15_t)0x71CC,
+	(q15_t)0x3A40, (q15_t)0x71FA, (q15_t)0x39E6, (q15_t)0x7227,
+	(q15_t)0x398C, (q15_t)0x7255, (q15_t)0x3932, (q15_t)0x7282,
+	(q15_t)0x38D8, (q15_t)0x72AF, (q15_t)0x387E, (q15_t)0x72DB,
+	(q15_t)0x3824, (q15_t)0x7307, (q15_t)0x37CA, (q15_t)0x7333,
+	(q15_t)0x376F, (q15_t)0x735F, (q15_t)0x3714, (q15_t)0x738A,
+	(q15_t)0x36BA, (q15_t)0x73B5, (q15_t)0x365F, (q15_t)0x73E0,
+	(q15_t)0x3604, (q15_t)0x740B, (q15_t)0x35A8, (q15_t)0x7435,
+	(q15_t)0x354D, (q15_t)0x745F, (q15_t)0x34F2, (q15_t)0x7489,
+	(q15_t)0x3496, (q15_t)0x74B2, (q15_t)0x343A, (q15_t)0x74DB,
+	(q15_t)0x33DE, (q15_t)0x7504, (q15_t)0x3382, (q15_t)0x752D,
+	(q15_t)0x3326, (q15_t)0x7555, (q15_t)0x32CA, (q15_t)0x757D,
+	(q15_t)0x326E, (q15_t)0x75A5, (q15_t)0x3211, (q15_t)0x75CC,
+	(q15_t)0x31B5, (q15_t)0x75F4, (q15_t)0x3158, (q15_t)0x761B,
+	(q15_t)0x30FB, (q15_t)0x7641, (q15_t)0x309E, (q15_t)0x7668,
+	(q15_t)0x3041, (q15_t)0x768E, (q15_t)0x2FE4, (q15_t)0x76B3,
+	(q15_t)0x2F87, (q15_t)0x76D9, (q15_t)0x2F29, (q15_t)0x76FE,
+	(q15_t)0x2ECC, (q15_t)0x7723, (q15_t)0x2E6E, (q15_t)0x7747,
+	(q15_t)0x2E11, (q15_t)0x776C, (q15_t)0x2DB3, (q15_t)0x7790,
+	(q15_t)0x2D55, (q15_t)0x77B4, (q15_t)0x2CF7, (q15_t)0x77D7,
+	(q15_t)0x2C98, (q15_t)0x77FA, (q15_t)0x2C3A, (q15_t)0x781D,
+	(q15_t)0x2BDC, (q15_t)0x7840, (q15_t)0x2B7D, (q15_t)0x7862,
+	(q15_t)0x2B1F, (q15_t)0x7884, (q15_t)0x2AC0, (q15_t)0x78A6,
+	(q15_t)0x2A61, (q15_t)0x78C7, (q15_t)0x2A02, (q15_t)0x78E8,
+	(q15_t)0x29A3, (q15_t)0x7909, (q15_t)0x2944, (q15_t)0x792A,
+	(q15_t)0x28E5, (q15_t)0x794A, (q15_t)0x2886, (q15_t)0x796A,
+	(q15_t)0x2826, (q15_t)0x798A, (q15_t)0x27C7, (q15_t)0x79A9,
+	(q15_t)0x2767, (q15_t)0x79C8, (q15_t)0x2707, (q15_t)0x79E7,
+	(q15_t)0x26A8, (q15_t)0x7A05, (q15_t)0x2648, (q15_t)0x7A24,
+	(q15_t)0x25E8, (q15_t)0x7A42, (q15_t)0x2588, (q15_t)0x7A5F,
+	(q15_t)0x2528, (q15_t)0x7A7D, (q15_t)0x24C7, (q15_t)0x7A9A,
+	(q15_t)0x2467, (q15_t)0x7AB6, (q15_t)0x2407, (q15_t)0x7AD3,
+	(q15_t)0x23A6, (q15_t)0x7AEF, (q15_t)0x2345, (q15_t)0x7B0B,
+	(q15_t)0x22E5, (q15_t)0x7B26, (q15_t)0x2284, (q15_t)0x7B42,
+	(q15_t)0x2223, (q15_t)0x7B5D, (q15_t)0x21C2, (q15_t)0x7B77,
+	(q15_t)0x2161, (q15_t)0x7B92, (q15_t)0x2100, (q15_t)0x7BAC,
+	(q15_t)0x209F, (q15_t)0x7BC5, (q15_t)0x203E, (q15_t)0x7BDF,
+	(q15_t)0x1FDC, (q15_t)0x7BF8, (q15_t)0x1F7B, (q15_t)0x7C11,
+	(q15_t)0x1F19, (q15_t)0x7C29, (q15_t)0x1EB8, (q15_t)0x7C42,
+	(q15_t)0x1E56, (q15_t)0x7C5A, (q15_t)0x1DF5, (q15_t)0x7C71,
+	(q15_t)0x1D93, (q15_t)0x7C89, (q15_t)0x1D31, (q15_t)0x7CA0,
+	(q15_t)0x1CCF, (q15_t)0x7CB7, (q15_t)0x1C6D, (q15_t)0x7CCD,
+	(q15_t)0x1C0B, (q15_t)0x7CE3, (q15_t)0x1BA9, (q15_t)0x7CF9,
+	(q15_t)0x1B47, (q15_t)0x7D0F, (q15_t)0x1AE4, (q15_t)0x7D24,
+	(q15_t)0x1A82, (q15_t)0x7D39, (q15_t)0x1A20, (q15_t)0x7D4E,
+	(q15_t)0x19BD, (q15_t)0x7D62, (q15_t)0x195B, (q15_t)0x7D76,
+	(q15_t)0x18F8, (q15_t)0x7D8A, (q15_t)0x1896, (q15_t)0x7D9D,
+	(q15_t)0x1833, (q15_t)0x7DB0, (q15_t)0x17D0, (q15_t)0x7DC3,
+	(q15_t)0x176D, (q15_t)0x7DD6, (q15_t)0x170A, (q15_t)0x7DE8,
+	(q15_t)0x16A8, (q15_t)0x7DFA, (q15_t)0x1645, (q15_t)0x7E0C,
+	(q15_t)0x15E2, (q15_t)0x7E1D, (q15_t)0x157F, (q15_t)0x7E2E,
+	(q15_t)0x151B, (q15_t)0x7E3F, (q15_t)0x14B8, (q15_t)0x7E4F,
+	(q15_t)0x1455, (q15_t)0x7E5F, (q15_t)0x13F2, (q15_t)0x7E6F,
+	(q15_t)0x138E, (q15_t)0x7E7F, (q15_t)0x132B, (q15_t)0x7E8E,
+	(q15_t)0x12C8, (q15_t)0x7E9D, (q15_t)0x1264, (q15_t)0x7EAB,
+	(q15_t)0x1201, (q15_t)0x7EBA, (q15_t)0x119D, (q15_t)0x7EC8,
+	(q15_t)0x1139, (q15_t)0x7ED5, (q15_t)0x10D6, (q15_t)0x7EE3,
+	(q15_t)0x1072, (q15_t)0x7EF0, (q15_t)0x100E, (q15_t)0x7EFD,
+	(q15_t)0x0FAB, (q15_t)0x7F09, (q15_t)0x0F47, (q15_t)0x7F15,
+	(q15_t)0x0EE3, (q15_t)0x7F21, (q15_t)0x0E7F, (q15_t)0x7F2D,
+	(q15_t)0x0E1B, (q15_t)0x7F38, (q15_t)0x0DB7, (q15_t)0x7F43,
+	(q15_t)0x0D53, (q15_t)0x7F4D, (q15_t)0x0CEF, (q15_t)0x7F58,
+	(q15_t)0x0C8B, (q15_t)0x7F62, (q15_t)0x0C27, (q15_t)0x7F6B,
+	(q15_t)0x0BC3, (q15_t)0x7F75, (q15_t)0x0B5F, (q15_t)0x7F7E,
+	(q15_t)0x0AFB, (q15_t)0x7F87, (q15_t)0x0A97, (q15_t)0x7F8F,
+	(q15_t)0x0A33, (q15_t)0x7F97, (q15_t)0x09CE, (q15_t)0x7F9F,
+	(q15_t)0x096A, (q15_t)0x7FA7, (q15_t)0x0906, (q15_t)0x7FAE,
+	(q15_t)0x08A2, (q15_t)0x7FB5, (q15_t)0x083D, (q15_t)0x7FBC,
+	(q15_t)0x07D9, (q15_t)0x7FC2, (q15_t)0x0775, (q15_t)0x7FC8,
+	(q15_t)0x0710, (q15_t)0x7FCE, (q15_t)0x06AC, (q15_t)0x7FD3,
+	(q15_t)0x0647, (q15_t)0x7FD8, (q15_t)0x05E3, (q15_t)0x7FDD,
+	(q15_t)0x057F, (q15_t)0x7FE1, (q15_t)0x051A, (q15_t)0x7FE5,
+	(q15_t)0x04B6, (q15_t)0x7FE9, (q15_t)0x0451, (q15_t)0x7FED,
+	(q15_t)0x03ED, (q15_t)0x7FF0, (q15_t)0x0388, (q15_t)0x7FF3,
+	(q15_t)0x0324, (q15_t)0x7FF6, (q15_t)0x02BF, (q15_t)0x7FF8,
+	(q15_t)0x025B, (q15_t)0x7FFA, (q15_t)0x01F6, (q15_t)0x7FFC,
+	(q15_t)0x0192, (q15_t)0x7FFD, (q15_t)0x012D, (q15_t)0x7FFE,
+	(q15_t)0x00C9, (q15_t)0x7FFF, (q15_t)0x0064, (q15_t)0x7FFF,
+	(q15_t)0x0000, (q15_t)0x7FFF, (q15_t)0xFF9B, (q15_t)0x7FFF,
+	(q15_t)0xFF36, (q15_t)0x7FFF, (q15_t)0xFED2, (q15_t)0x7FFE,
+	(q15_t)0xFE6D, (q15_t)0x7FFD, (q15_t)0xFE09, (q15_t)0x7FFC,
+	(q15_t)0xFDA4, (q15_t)0x7FFA, (q15_t)0xFD40, (q15_t)0x7FF8,
+	(q15_t)0xFCDB, (q15_t)0x7FF6, (q15_t)0xFC77, (q15_t)0x7FF3,
+	(q15_t)0xFC12, (q15_t)0x7FF0, (q15_t)0xFBAE, (q15_t)0x7FED,
+	(q15_t)0xFB49, (q15_t)0x7FE9, (q15_t)0xFAE5, (q15_t)0x7FE5,
+	(q15_t)0xFA80, (q15_t)0x7FE1, (q15_t)0xFA1C, (q15_t)0x7FDD,
+	(q15_t)0xF9B8, (q15_t)0x7FD8, (q15_t)0xF953, (q15_t)0x7FD3,
+	(q15_t)0xF8EF, (q15_t)0x7FCE, (q15_t)0xF88A, (q15_t)0x7FC8,
+	(q15_t)0xF826, (q15_t)0x7FC2, (q15_t)0xF7C2, (q15_t)0x7FBC,
+	(q15_t)0xF75D, (q15_t)0x7FB5, (q15_t)0xF6F9, (q15_t)0x7FAE,
+	(q15_t)0xF695, (q15_t)0x7FA7, (q15_t)0xF631, (q15_t)0x7F9F,
+	(q15_t)0xF5CC, (q15_t)0x7F97, (q15_t)0xF568, (q15_t)0x7F8F,
+	(q15_t)0xF504, (q15_t)0x7F87, (q15_t)0xF4A0, (q15_t)0x7F7E,
+	(q15_t)0xF43C, (q15_t)0x7F75, (q15_t)0xF3D8, (q15_t)0x7F6B,
+	(q15_t)0xF374, (q15_t)0x7F62, (q15_t)0xF310, (q15_t)0x7F58,
+	(q15_t)0xF2AC, (q15_t)0x7F4D, (q15_t)0xF248, (q15_t)0x7F43,
+	(q15_t)0xF1E4, (q15_t)0x7F38, (q15_t)0xF180, (q15_t)0x7F2D,
+	(q15_t)0xF11C, (q15_t)0x7F21, (q15_t)0xF0B8, (q15_t)0x7F15,
+	(q15_t)0xF054, (q15_t)0x7F09, (q15_t)0xEFF1, (q15_t)0x7EFD,
+	(q15_t)0xEF8D, (q15_t)0x7EF0, (q15_t)0xEF29, (q15_t)0x7EE3,
+	(q15_t)0xEEC6, (q15_t)0x7ED5, (q15_t)0xEE62, (q15_t)0x7EC8,
+	(q15_t)0xEDFE, (q15_t)0x7EBA, (q15_t)0xED9B, (q15_t)0x7EAB,
+	(q15_t)0xED37, (q15_t)0x7E9D, (q15_t)0xECD4, (q15_t)0x7E8E,
+	(q15_t)0xEC71, (q15_t)0x7E7F, (q15_t)0xEC0D, (q15_t)0x7E6F,
+	(q15_t)0xEBAA, (q15_t)0x7E5F, (q15_t)0xEB47, (q15_t)0x7E4F,
+	(q15_t)0xEAE4, (q15_t)0x7E3F, (q15_t)0xEA80, (q15_t)0x7E2E,
+	(q15_t)0xEA1D, (q15_t)0x7E1D, (q15_t)0xE9BA, (q15_t)0x7E0C,
+	(q15_t)0xE957, (q15_t)0x7DFA, (q15_t)0xE8F5, (q15_t)0x7DE8,
+	(q15_t)0xE892, (q15_t)0x7DD6, (q15_t)0xE82F, (q15_t)0x7DC3,
+	(q15_t)0xE7CC, (q15_t)0x7DB0, (q15_t)0xE769, (q15_t)0x7D9D,
+	(q15_t)0xE707, (q15_t)0x7D8A, (q15_t)0xE6A4, (q15_t)0x7D76,
+	(q15_t)0xE642, (q15_t)0x7D62, (q15_t)0xE5DF, (q15_t)0x7D4E,
+	(q15_t)0xE57D, (q15_t)0x7D39, (q15_t)0xE51B, (q15_t)0x7D24,
+	(q15_t)0xE4B8, (q15_t)0x7D0F, (q15_t)0xE456, (q15_t)0x7CF9,
+	(q15_t)0xE3F4, (q15_t)0x7CE3, (q15_t)0xE392, (q15_t)0x7CCD,
+	(q15_t)0xE330, (q15_t)0x7CB7, (q15_t)0xE2CE, (q15_t)0x7CA0,
+	(q15_t)0xE26C, (q15_t)0x7C89, (q15_t)0xE20A, (q15_t)0x7C71,
+	(q15_t)0xE1A9, (q15_t)0x7C5A, (q15_t)0xE147, (q15_t)0x7C42,
+	(q15_t)0xE0E6, (q15_t)0x7C29, (q15_t)0xE084, (q15_t)0x7C11,
+	(q15_t)0xE023, (q15_t)0x7BF8, (q15_t)0xDFC1, (q15_t)0x7BDF,
+	(q15_t)0xDF60, (q15_t)0x7BC5, (q15_t)0xDEFF, (q15_t)0x7BAC,
+	(q15_t)0xDE9E, (q15_t)0x7B92, (q15_t)0xDE3D, (q15_t)0x7B77,
+	(q15_t)0xDDDC, (q15_t)0x7B5D, (q15_t)0xDD7B, (q15_t)0x7B42,
+	(q15_t)0xDD1A, (q15_t)0x7B26, (q15_t)0xDCBA, (q15_t)0x7B0B,
+	(q15_t)0xDC59, (q15_t)0x7AEF, (q15_t)0xDBF8, (q15_t)0x7AD3,
+	(q15_t)0xDB98, (q15_t)0x7AB6, (q15_t)0xDB38, (q15_t)0x7A9A,
+	(q15_t)0xDAD7, (q15_t)0x7A7D, (q15_t)0xDA77, (q15_t)0x7A5F,
+	(q15_t)0xDA17, (q15_t)0x7A42, (q15_t)0xD9B7, (q15_t)0x7A24,
+	(q15_t)0xD957, (q15_t)0x7A05, (q15_t)0xD8F8, (q15_t)0x79E7,
+	(q15_t)0xD898, (q15_t)0x79C8, (q15_t)0xD838, (q15_t)0x79A9,
+	(q15_t)0xD7D9, (q15_t)0x798A, (q15_t)0xD779, (q15_t)0x796A,
+	(q15_t)0xD71A, (q15_t)0x794A, (q15_t)0xD6BB, (q15_t)0x792A,
+	(q15_t)0xD65C, (q15_t)0x7909, (q15_t)0xD5FD, (q15_t)0x78E8,
+	(q15_t)0xD59E, (q15_t)0x78C7, (q15_t)0xD53F, (q15_t)0x78A6,
+	(q15_t)0xD4E0, (q15_t)0x7884, (q15_t)0xD482, (q15_t)0x7862,
+	(q15_t)0xD423, (q15_t)0x7840, (q15_t)0xD3C5, (q15_t)0x781D,
+	(q15_t)0xD367, (q15_t)0x77FA, (q15_t)0xD308, (q15_t)0x77D7,
+	(q15_t)0xD2AA, (q15_t)0x77B4, (q15_t)0xD24C, (q15_t)0x7790,
+	(q15_t)0xD1EE, (q15_t)0x776C, (q15_t)0xD191, (q15_t)0x7747,
+	(q15_t)0xD133, (q15_t)0x7723, (q15_t)0xD0D6, (q15_t)0x76FE,
+	(q15_t)0xD078, (q15_t)0x76D9, (q15_t)0xD01B, (q15_t)0x76B3,
+	(q15_t)0xCFBE, (q15_t)0x768E, (q15_t)0xCF61, (q15_t)0x7668,
+	(q15_t)0xCF04, (q15_t)0x7641, (q15_t)0xCEA7, (q15_t)0x761B,
+	(q15_t)0xCE4A, (q15_t)0x75F4, (q15_t)0xCDEE, (q15_t)0x75CC,
+	(q15_t)0xCD91, (q15_t)0x75A5, (q15_t)0xCD35, (q15_t)0x757D,
+	(q15_t)0xCCD9, (q15_t)0x7555, (q15_t)0xCC7D, (q15_t)0x752D,
+	(q15_t)0xCC21, (q15_t)0x7504, (q15_t)0xCBC5, (q15_t)0x74DB,
+	(q15_t)0xCB69, (q15_t)0x74B2, (q15_t)0xCB0D, (q15_t)0x7489,
+	(q15_t)0xCAB2, (q15_t)0x745F, (q15_t)0xCA57, (q15_t)0x7435,
+	(q15_t)0xC9FB, (q15_t)0x740B, (q15_t)0xC9A0, (q15_t)0x73E0,
+	(q15_t)0xC945, (q15_t)0x73B5, (q15_t)0xC8EB, (q15_t)0x738A,
+	(q15_t)0xC890, (q15_t)0x735F, (q15_t)0xC835, (q15_t)0x7333,
+	(q15_t)0xC7DB, (q15_t)0x7307, (q15_t)0xC781, (q15_t)0x72DB,
+	(q15_t)0xC727, (q15_t)0x72AF, (q15_t)0xC6CD, (q15_t)0x7282,
+	(q15_t)0xC673, (q15_t)0x7255, (q15_t)0xC619, (q15_t)0x7227,
+	(q15_t)0xC5BF, (q15_t)0x71FA, (q15_t)0xC566, (q15_t)0x71CC,
+	(q15_t)0xC50D, (q15_t)0x719E, (q15_t)0xC4B3, (q15_t)0x716F,
+	(q15_t)0xC45A, (q15_t)0x7141, (q15_t)0xC402, (q15_t)0x7112,
+	(q15_t)0xC3A9, (q15_t)0x70E2, (q15_t)0xC350, (q15_t)0x70B3,
+	(q15_t)0xC2F8, (q15_t)0x7083, (q15_t)0xC29F, (q15_t)0x7053,
+	(q15_t)0xC247, (q15_t)0x7023, (q15_t)0xC1EF, (q15_t)0x6FF2,
+	(q15_t)0xC197, (q15_t)0x6FC1, (q15_t)0xC140, (q15_t)0x6F90,
+	(q15_t)0xC0E8, (q15_t)0x6F5F, (q15_t)0xC091, (q15_t)0x6F2D,
+	(q15_t)0xC03A, (q15_t)0x6EFB, (q15_t)0xBFE2, (q15_t)0x6EC9,
+	(q15_t)0xBF8C, (q15_t)0x6E96, (q15_t)0xBF35, (q15_t)0x6E63,
+	(q15_t)0xBEDE, (q15_t)0x6E30, (q15_t)0xBE88, (q15_t)0x6DFD,
+	(q15_t)0xBE31, (q15_t)0x6DCA, (q15_t)0xBDDB, (q15_t)0x6D96,
+	(q15_t)0xBD85, (q15_t)0x6D62, (q15_t)0xBD2F, (q15_t)0x6D2D,
+	(q15_t)0xBCDA, (q15_t)0x6CF9, (q15_t)0xBC84, (q15_t)0x6CC4,
+	(q15_t)0xBC2F, (q15_t)0x6C8F, (q15_t)0xBBDA, (q15_t)0x6C59,
+	(q15_t)0xBB85, (q15_t)0x6C24, (q15_t)0xBB30, (q15_t)0x6BEE,
+	(q15_t)0xBADB, (q15_t)0x6BB8, (q15_t)0xBA87, (q15_t)0x6B81,
+	(q15_t)0xBA32, (q15_t)0x6B4A, (q15_t)0xB9DE, (q15_t)0x6B13,
+	(q15_t)0xB98A, (q15_t)0x6ADC, (q15_t)0xB936, (q15_t)0x6AA5,
+	(q15_t)0xB8E3, (q15_t)0x6A6D, (q15_t)0xB88F, (q15_t)0x6A35,
+	(q15_t)0xB83C, (q15_t)0x69FD, (q15_t)0xB7E9, (q15_t)0x69C4,
+	(q15_t)0xB796, (q15_t)0x698C, (q15_t)0xB743, (q15_t)0x6953,
+	(q15_t)0xB6F0, (q15_t)0x6919, (q15_t)0xB69E, (q15_t)0x68E0,
+	(q15_t)0xB64B, (q15_t)0x68A6, (q15_t)0xB5F9, (q15_t)0x686C,
+	(q15_t)0xB5A7, (q15_t)0x6832, (q15_t)0xB556, (q15_t)0x67F7,
+	(q15_t)0xB504, (q15_t)0x67BD, (q15_t)0xB4B3, (q15_t)0x6782,
+	(q15_t)0xB461, (q15_t)0x6746, (q15_t)0xB410, (q15_t)0x670B,
+	(q15_t)0xB3C0, (q15_t)0x66CF, (q15_t)0xB36F, (q15_t)0x6693,
+	(q15_t)0xB31E, (q15_t)0x6657, (q15_t)0xB2CE, (q15_t)0x661A,
+	(q15_t)0xB27E, (q15_t)0x65DD, (q15_t)0xB22E, (q15_t)0x65A0,
+	(q15_t)0xB1DE, (q15_t)0x6563, (q15_t)0xB18F, (q15_t)0x6526,
+	(q15_t)0xB140, (q15_t)0x64E8, (q15_t)0xB0F0, (q15_t)0x64AA,
+	(q15_t)0xB0A1, (q15_t)0x646C, (q15_t)0xB053, (q15_t)0x642D,
+	(q15_t)0xB004, (q15_t)0x63EF, (q15_t)0xAFB6, (q15_t)0x63B0,
+	(q15_t)0xAF68, (q15_t)0x6371, (q15_t)0xAF1A, (q15_t)0x6331,
+	(q15_t)0xAECC, (q15_t)0x62F2, (q15_t)0xAE7E, (q15_t)0x62B2,
+	(q15_t)0xAE31, (q15_t)0x6271, (q15_t)0xADE3, (q15_t)0x6231,
+	(q15_t)0xAD96, (q15_t)0x61F1, (q15_t)0xAD4A, (q15_t)0x61B0,
+	(q15_t)0xACFD, (q15_t)0x616F, (q15_t)0xACB1, (q15_t)0x612D,
+	(q15_t)0xAC64, (q15_t)0x60EC, (q15_t)0xAC18, (q15_t)0x60AA,
+	(q15_t)0xABCC, (q15_t)0x6068, (q15_t)0xAB81, (q15_t)0x6026,
+	(q15_t)0xAB35, (q15_t)0x5FE3, (q15_t)0xAAEA, (q15_t)0x5FA0,
+	(q15_t)0xAA9F, (q15_t)0x5F5E, (q15_t)0xAA54, (q15_t)0x5F1A,
+	(q15_t)0xAA0A, (q15_t)0x5ED7, (q15_t)0xA9BF, (q15_t)0x5E93,
+	(q15_t)0xA975, (q15_t)0x5E50, (q15_t)0xA92B, (q15_t)0x5E0B,
+	(q15_t)0xA8E2, (q15_t)0x5DC7, (q15_t)0xA898, (q15_t)0x5D83,
+	(q15_t)0xA84F, (q15_t)0x5D3E, (q15_t)0xA806, (q15_t)0x5CF9,
+	(q15_t)0xA7BD, (q15_t)0x5CB4, (q15_t)0xA774, (q15_t)0x5C6E,
+	(q15_t)0xA72B, (q15_t)0x5C29, (q15_t)0xA6E3, (q15_t)0x5BE3,
+	(q15_t)0xA69B, (q15_t)0x5B9D, (q15_t)0xA653, (q15_t)0x5B56,
+	(q15_t)0xA60C, (q15_t)0x5B10, (q15_t)0xA5C4, (q15_t)0x5AC9,
+	(q15_t)0xA57D, (q15_t)0x5A82, (q15_t)0xA536, (q15_t)0x5A3B,
+	(q15_t)0xA4EF, (q15_t)0x59F3, (q15_t)0xA4A9, (q15_t)0x59AC,
+	(q15_t)0xA462, (q15_t)0x5964, (q15_t)0xA41C, (q15_t)0x591C,
+	(q15_t)0xA3D6, (q15_t)0x58D4, (q15_t)0xA391, (q15_t)0x588B,
+	(q15_t)0xA34B, (q15_t)0x5842, (q15_t)0xA306, (q15_t)0x57F9,
+	(q15_t)0xA2C1, (q15_t)0x57B0, (q15_t)0xA27C, (q15_t)0x5767,
+	(q15_t)0xA238, (q15_t)0x571D, (q15_t)0xA1F4, (q15_t)0x56D4,
+	(q15_t)0xA1AF, (q15_t)0x568A, (q15_t)0xA16C, (q15_t)0x5640,
+	(q15_t)0xA128, (q15_t)0x55F5, (q15_t)0xA0E5, (q15_t)0x55AB,
+	(q15_t)0xA0A1, (q15_t)0x5560, (q15_t)0xA05F, (q15_t)0x5515,
+	(q15_t)0xA01C, (q15_t)0x54CA, (q15_t)0x9FD9, (q15_t)0x547E,
+	(q15_t)0x9F97, (q15_t)0x5433, (q15_t)0x9F55, (q15_t)0x53E7,
+	(q15_t)0x9F13, (q15_t)0x539B, (q15_t)0x9ED2, (q15_t)0x534E,
+	(q15_t)0x9E90, (q15_t)0x5302, (q15_t)0x9E4F, (q15_t)0x52B5,
+	(q15_t)0x9E0E, (q15_t)0x5269, (q15_t)0x9DCE, (q15_t)0x521C,
+	(q15_t)0x9D8E, (q15_t)0x51CE, (q15_t)0x9D4D, (q15_t)0x5181,
+	(q15_t)0x9D0D, (q15_t)0x5133, (q15_t)0x9CCE, (q15_t)0x50E5,
+	(q15_t)0x9C8E, (q15_t)0x5097, (q15_t)0x9C4F, (q15_t)0x5049,
+	(q15_t)0x9C10, (q15_t)0x4FFB, (q15_t)0x9BD2, (q15_t)0x4FAC,
+	(q15_t)0x9B93, (q15_t)0x4F5E, (q15_t)0x9B55, (q15_t)0x4F0F,
+	(q15_t)0x9B17, (q15_t)0x4EBF, (q15_t)0x9AD9, (q15_t)0x4E70,
+	(q15_t)0x9A9C, (q15_t)0x4E21, (q15_t)0x9A5F, (q15_t)0x4DD1,
+	(q15_t)0x9A22, (q15_t)0x4D81, (q15_t)0x99E5, (q15_t)0x4D31,
+	(q15_t)0x99A8, (q15_t)0x4CE1, (q15_t)0x996C, (q15_t)0x4C90,
+	(q15_t)0x9930, (q15_t)0x4C3F, (q15_t)0x98F4, (q15_t)0x4BEF,
+	(q15_t)0x98B9, (q15_t)0x4B9E, (q15_t)0x987D, (q15_t)0x4B4C,
+	(q15_t)0x9842, (q15_t)0x4AFB, (q15_t)0x9808, (q15_t)0x4AA9,
+	(q15_t)0x97CD, (q15_t)0x4A58, (q15_t)0x9793, (q15_t)0x4A06,
+	(q15_t)0x9759, (q15_t)0x49B4, (q15_t)0x971F, (q15_t)0x4961,
+	(q15_t)0x96E6, (q15_t)0x490F, (q15_t)0x96AC, (q15_t)0x48BC,
+	(q15_t)0x9673, (q15_t)0x4869, (q15_t)0x963B, (q15_t)0x4816,
+	(q15_t)0x9602, (q15_t)0x47C3, (q15_t)0x95CA, (q15_t)0x4770,
+	(q15_t)0x9592, (q15_t)0x471C, (q15_t)0x955A, (q15_t)0x46C9,
+	(q15_t)0x9523, (q15_t)0x4675, (q15_t)0x94EC, (q15_t)0x4621,
+	(q15_t)0x94B5, (q15_t)0x45CD, (q15_t)0x947E, (q15_t)0x4578,
+	(q15_t)0x9447, (q15_t)0x4524, (q15_t)0x9411, (q15_t)0x44CF,
+	(q15_t)0x93DB, (q15_t)0x447A, (q15_t)0x93A6, (q15_t)0x4425,
+	(q15_t)0x9370, (q15_t)0x43D0, (q15_t)0x933B, (q15_t)0x437B,
+	(q15_t)0x9306, (q15_t)0x4325, (q15_t)0x92D2, (q15_t)0x42D0,
+	(q15_t)0x929D, (q15_t)0x427A, (q15_t)0x9269, (q15_t)0x4224,
+	(q15_t)0x9235, (q15_t)0x41CE, (q15_t)0x9202, (q15_t)0x4177,
+	(q15_t)0x91CF, (q15_t)0x4121, (q15_t)0x919C, (q15_t)0x40CA,
+	(q15_t)0x9169, (q15_t)0x4073, (q15_t)0x9136, (q15_t)0x401D,
+	(q15_t)0x9104, (q15_t)0x3FC5, (q15_t)0x90D2, (q15_t)0x3F6E,
+	(q15_t)0x90A0, (q15_t)0x3F17, (q15_t)0x906F, (q15_t)0x3EBF,
+	(q15_t)0x903E, (q15_t)0x3E68, (q15_t)0x900D, (q15_t)0x3E10,
+	(q15_t)0x8FDC, (q15_t)0x3DB8, (q15_t)0x8FAC, (q15_t)0x3D60,
+	(q15_t)0x8F7C, (q15_t)0x3D07, (q15_t)0x8F4C, (q15_t)0x3CAF,
+	(q15_t)0x8F1D, (q15_t)0x3C56, (q15_t)0x8EED, (q15_t)0x3BFD,
+	(q15_t)0x8EBE, (q15_t)0x3BA5, (q15_t)0x8E90, (q15_t)0x3B4C,
+	(q15_t)0x8E61, (q15_t)0x3AF2, (q15_t)0x8E33, (q15_t)0x3A99,
+	(q15_t)0x8E05, (q15_t)0x3A40, (q15_t)0x8DD8, (q15_t)0x39E6,
+	(q15_t)0x8DAA, (q15_t)0x398C, (q15_t)0x8D7D, (q15_t)0x3932,
+	(q15_t)0x8D50, (q15_t)0x38D8, (q15_t)0x8D24, (q15_t)0x387E,
+	(q15_t)0x8CF8, (q15_t)0x3824, (q15_t)0x8CCC, (q15_t)0x37CA,
+	(q15_t)0x8CA0, (q15_t)0x376F, (q15_t)0x8C75, (q15_t)0x3714,
+	(q15_t)0x8C4A, (q15_t)0x36BA, (q15_t)0x8C1F, (q15_t)0x365F,
+	(q15_t)0x8BF4, (q15_t)0x3604, (q15_t)0x8BCA, (q15_t)0x35A8,
+	(q15_t)0x8BA0, (q15_t)0x354D, (q15_t)0x8B76, (q15_t)0x34F2,
+	(q15_t)0x8B4D, (q15_t)0x3496, (q15_t)0x8B24, (q15_t)0x343A,
+	(q15_t)0x8AFB, (q15_t)0x33DE, (q15_t)0x8AD2, (q15_t)0x3382,
+	(q15_t)0x8AAA, (q15_t)0x3326, (q15_t)0x8A82, (q15_t)0x32CA,
+	(q15_t)0x8A5A, (q15_t)0x326E, (q15_t)0x8A33, (q15_t)0x3211,
+	(q15_t)0x8A0B, (q15_t)0x31B5, (q15_t)0x89E4, (q15_t)0x3158,
+	(q15_t)0x89BE, (q15_t)0x30FB, (q15_t)0x8997, (q15_t)0x309E,
+	(q15_t)0x8971, (q15_t)0x3041, (q15_t)0x894C, (q15_t)0x2FE4,
+	(q15_t)0x8926, (q15_t)0x2F87, (q15_t)0x8901, (q15_t)0x2F29,
+	(q15_t)0x88DC, (q15_t)0x2ECC, (q15_t)0x88B8, (q15_t)0x2E6E,
+	(q15_t)0x8893, (q15_t)0x2E11, (q15_t)0x886F, (q15_t)0x2DB3,
+	(q15_t)0x884B, (q15_t)0x2D55, (q15_t)0x8828, (q15_t)0x2CF7,
+	(q15_t)0x8805, (q15_t)0x2C98, (q15_t)0x87E2, (q15_t)0x2C3A,
+	(q15_t)0x87BF, (q15_t)0x2BDC, (q15_t)0x879D, (q15_t)0x2B7D,
+	(q15_t)0x877B, (q15_t)0x2B1F, (q15_t)0x8759, (q15_t)0x2AC0,
+	(q15_t)0x8738, (q15_t)0x2A61, (q15_t)0x8717, (q15_t)0x2A02,
+	(q15_t)0x86F6, (q15_t)0x29A3, (q15_t)0x86D5, (q15_t)0x2944,
+	(q15_t)0x86B5, (q15_t)0x28E5, (q15_t)0x8695, (q15_t)0x2886,
+	(q15_t)0x8675, (q15_t)0x2826, (q15_t)0x8656, (q15_t)0x27C7,
+	(q15_t)0x8637, (q15_t)0x2767, (q15_t)0x8618, (q15_t)0x2707,
+	(q15_t)0x85FA, (q15_t)0x26A8, (q15_t)0x85DB, (q15_t)0x2648,
+	(q15_t)0x85BD, (q15_t)0x25E8, (q15_t)0x85A0, (q15_t)0x2588,
+	(q15_t)0x8582, (q15_t)0x2528, (q15_t)0x8565, (q15_t)0x24C7,
+	(q15_t)0x8549, (q15_t)0x2467, (q15_t)0x852C, (q15_t)0x2407,
+	(q15_t)0x8510, (q15_t)0x23A6, (q15_t)0x84F4, (q15_t)0x2345,
+	(q15_t)0x84D9, (q15_t)0x22E5, (q15_t)0x84BD, (q15_t)0x2284,
+	(q15_t)0x84A2, (q15_t)0x2223, (q15_t)0x8488, (q15_t)0x21C2,
+	(q15_t)0x846D, (q15_t)0x2161, (q15_t)0x8453, (q15_t)0x2100,
+	(q15_t)0x843A, (q15_t)0x209F, (q15_t)0x8420, (q15_t)0x203E,
+	(q15_t)0x8407, (q15_t)0x1FDC, (q15_t)0x83EE, (q15_t)0x1F7B,
+	(q15_t)0x83D6, (q15_t)0x1F19, (q15_t)0x83BD, (q15_t)0x1EB8,
+	(q15_t)0x83A5, (q15_t)0x1E56, (q15_t)0x838E, (q15_t)0x1DF5,
+	(q15_t)0x8376, (q15_t)0x1D93, (q15_t)0x835F, (q15_t)0x1D31,
+	(q15_t)0x8348, (q15_t)0x1CCF, (q15_t)0x8332, (q15_t)0x1C6D,
+	(q15_t)0x831C, (q15_t)0x1C0B, (q15_t)0x8306, (q15_t)0x1BA9,
+	(q15_t)0x82F0, (q15_t)0x1B47, (q15_t)0x82DB, (q15_t)0x1AE4,
+	(q15_t)0x82C6, (q15_t)0x1A82, (q15_t)0x82B1, (q15_t)0x1A20,
+	(q15_t)0x829D, (q15_t)0x19BD, (q15_t)0x8289, (q15_t)0x195B,
+	(q15_t)0x8275, (q15_t)0x18F8, (q15_t)0x8262, (q15_t)0x1896,
+	(q15_t)0x824F, (q15_t)0x1833, (q15_t)0x823C, (q15_t)0x17D0,
+	(q15_t)0x8229, (q15_t)0x176D, (q15_t)0x8217, (q15_t)0x170A,
+	(q15_t)0x8205, (q15_t)0x16A8, (q15_t)0x81F3, (q15_t)0x1645,
+	(q15_t)0x81E2, (q15_t)0x15E2, (q15_t)0x81D1, (q15_t)0x157F,
+	(q15_t)0x81C0, (q15_t)0x151B, (q15_t)0x81B0, (q15_t)0x14B8,
+	(q15_t)0x81A0, (q15_t)0x1455, (q15_t)0x8190, (q15_t)0x13F2,
+	(q15_t)0x8180, (q15_t)0x138E, (q15_t)0x8171, (q15_t)0x132B,
+	(q15_t)0x8162, (q15_t)0x12C8, (q15_t)0x8154, (q15_t)0x1264,
+	(q15_t)0x8145, (q15_t)0x1201, (q15_t)0x8137, (q15_t)0x119D,
+	(q15_t)0x812A, (q15_t)0x1139, (q15_t)0x811C, (q15_t)0x10D6,
+	(q15_t)0x810F, (q15_t)0x1072, (q15_t)0x8102, (q15_t)0x100E,
+	(q15_t)0x80F6, (q15_t)0x0FAB, (q15_t)0x80EA, (q15_t)0x0F47,
+	(q15_t)0x80DE, (q15_t)0x0EE3, (q15_t)0x80D2, (q15_t)0x0E7F,
+	(q15_t)0x80C7, (q15_t)0x0E1B, (q15_t)0x80BC, (q15_t)0x0DB7,
+	(q15_t)0x80B2, (q15_t)0x0D53, (q15_t)0x80A7, (q15_t)0x0CEF,
+	(q15_t)0x809D, (q15_t)0x0C8B, (q15_t)0x8094, (q15_t)0x0C27,
+	(q15_t)0x808A, (q15_t)0x0BC3, (q15_t)0x8081, (q15_t)0x0B5F,
+	(q15_t)0x8078, (q15_t)0x0AFB, (q15_t)0x8070, (q15_t)0x0A97,
+	(q15_t)0x8068, (q15_t)0x0A33, (q15_t)0x8060, (q15_t)0x09CE,
+	(q15_t)0x8058, (q15_t)0x096A, (q15_t)0x8051, (q15_t)0x0906,
+	(q15_t)0x804A, (q15_t)0x08A2, (q15_t)0x8043, (q15_t)0x083D,
+	(q15_t)0x803D, (q15_t)0x07D9, (q15_t)0x8037, (q15_t)0x0775,
+	(q15_t)0x8031, (q15_t)0x0710, (q15_t)0x802C, (q15_t)0x06AC,
+	(q15_t)0x8027, (q15_t)0x0647, (q15_t)0x8022, (q15_t)0x05E3,
+	(q15_t)0x801E, (q15_t)0x057F, (q15_t)0x801A, (q15_t)0x051A,
+	(q15_t)0x8016, (q15_t)0x04B6, (q15_t)0x8012, (q15_t)0x0451,
+	(q15_t)0x800F, (q15_t)0x03ED, (q15_t)0x800C, (q15_t)0x0388,
+	(q15_t)0x8009, (q15_t)0x0324, (q15_t)0x8007, (q15_t)0x02BF,
+	(q15_t)0x8005, (q15_t)0x025B, (q15_t)0x8003, (q15_t)0x01F6,
+	(q15_t)0x8002, (q15_t)0x0192, (q15_t)0x8001, (q15_t)0x012D,
+	(q15_t)0x8000, (q15_t)0x00C9, (q15_t)0x8000, (q15_t)0x0064,
+	(q15_t)0x8000, (q15_t)0x0000, (q15_t)0x8000, (q15_t)0xFF9B,
+	(q15_t)0x8000, (q15_t)0xFF36, (q15_t)0x8001, (q15_t)0xFED2,
+	(q15_t)0x8002, (q15_t)0xFE6D, (q15_t)0x8003, (q15_t)0xFE09,
+	(q15_t)0x8005, (q15_t)0xFDA4, (q15_t)0x8007, (q15_t)0xFD40,
+	(q15_t)0x8009, (q15_t)0xFCDB, (q15_t)0x800C, (q15_t)0xFC77,
+	(q15_t)0x800F, (q15_t)0xFC12, (q15_t)0x8012, (q15_t)0xFBAE,
+	(q15_t)0x8016, (q15_t)0xFB49, (q15_t)0x801A, (q15_t)0xFAE5,
+	(q15_t)0x801E, (q15_t)0xFA80, (q15_t)0x8022, (q15_t)0xFA1C,
+	(q15_t)0x8027, (q15_t)0xF9B8, (q15_t)0x802C, (q15_t)0xF953,
+	(q15_t)0x8031, (q15_t)0xF8EF, (q15_t)0x8037, (q15_t)0xF88A,
+	(q15_t)0x803D, (q15_t)0xF826, (q15_t)0x8043, (q15_t)0xF7C2,
+	(q15_t)0x804A, (q15_t)0xF75D, (q15_t)0x8051, (q15_t)0xF6F9,
+	(q15_t)0x8058, (q15_t)0xF695, (q15_t)0x8060, (q15_t)0xF631,
+	(q15_t)0x8068, (q15_t)0xF5CC, (q15_t)0x8070, (q15_t)0xF568,
+	(q15_t)0x8078, (q15_t)0xF504, (q15_t)0x8081, (q15_t)0xF4A0,
+	(q15_t)0x808A, (q15_t)0xF43C, (q15_t)0x8094, (q15_t)0xF3D8,
+	(q15_t)0x809D, (q15_t)0xF374, (q15_t)0x80A7, (q15_t)0xF310,
+	(q15_t)0x80B2, (q15_t)0xF2AC, (q15_t)0x80BC, (q15_t)0xF248,
+	(q15_t)0x80C7, (q15_t)0xF1E4, (q15_t)0x80D2, (q15_t)0xF180,
+	(q15_t)0x80DE, (q15_t)0xF11C, (q15_t)0x80EA, (q15_t)0xF0B8,
+	(q15_t)0x80F6, (q15_t)0xF054, (q15_t)0x8102, (q15_t)0xEFF1,
+	(q15_t)0x810F, (q15_t)0xEF8D, (q15_t)0x811C, (q15_t)0xEF29,
+	(q15_t)0x812A, (q15_t)0xEEC6, (q15_t)0x8137, (q15_t)0xEE62,
+	(q15_t)0x8145, (q15_t)0xEDFE, (q15_t)0x8154, (q15_t)0xED9B,
+	(q15_t)0x8162, (q15_t)0xED37, (q15_t)0x8171, (q15_t)0xECD4,
+	(q15_t)0x8180, (q15_t)0xEC71, (q15_t)0x8190, (q15_t)0xEC0D,
+	(q15_t)0x81A0, (q15_t)0xEBAA, (q15_t)0x81B0, (q15_t)0xEB47,
+	(q15_t)0x81C0, (q15_t)0xEAE4, (q15_t)0x81D1, (q15_t)0xEA80,
+	(q15_t)0x81E2, (q15_t)0xEA1D, (q15_t)0x81F3, (q15_t)0xE9BA,
+	(q15_t)0x8205, (q15_t)0xE957, (q15_t)0x8217, (q15_t)0xE8F5,
+	(q15_t)0x8229, (q15_t)0xE892, (q15_t)0x823C, (q15_t)0xE82F,
+	(q15_t)0x824F, (q15_t)0xE7CC, (q15_t)0x8262, (q15_t)0xE769,
+	(q15_t)0x8275, (q15_t)0xE707, (q15_t)0x8289, (q15_t)0xE6A4,
+	(q15_t)0x829D, (q15_t)0xE642, (q15_t)0x82B1, (q15_t)0xE5DF,
+	(q15_t)0x82C6, (q15_t)0xE57D, (q15_t)0x82DB, (q15_t)0xE51B,
+	(q15_t)0x82F0, (q15_t)0xE4B8, (q15_t)0x8306, (q15_t)0xE456,
+	(q15_t)0x831C, (q15_t)0xE3F4, (q15_t)0x8332, (q15_t)0xE392,
+	(q15_t)0x8348, (q15_t)0xE330, (q15_t)0x835F, (q15_t)0xE2CE,
+	(q15_t)0x8376, (q15_t)0xE26C, (q15_t)0x838E, (q15_t)0xE20A,
+	(q15_t)0x83A5, (q15_t)0xE1A9, (q15_t)0x83BD, (q15_t)0xE147,
+	(q15_t)0x83D6, (q15_t)0xE0E6, (q15_t)0x83EE, (q15_t)0xE084,
+	(q15_t)0x8407, (q15_t)0xE023, (q15_t)0x8420, (q15_t)0xDFC1,
+	(q15_t)0x843A, (q15_t)0xDF60, (q15_t)0x8453, (q15_t)0xDEFF,
+	(q15_t)0x846D, (q15_t)0xDE9E, (q15_t)0x8488, (q15_t)0xDE3D,
+	(q15_t)0x84A2, (q15_t)0xDDDC, (q15_t)0x84BD, (q15_t)0xDD7B,
+	(q15_t)0x84D9, (q15_t)0xDD1A, (q15_t)0x84F4, (q15_t)0xDCBA,
+	(q15_t)0x8510, (q15_t)0xDC59, (q15_t)0x852C, (q15_t)0xDBF8,
+	(q15_t)0x8549, (q15_t)0xDB98, (q15_t)0x8565, (q15_t)0xDB38,
+	(q15_t)0x8582, (q15_t)0xDAD7, (q15_t)0x85A0, (q15_t)0xDA77,
+	(q15_t)0x85BD, (q15_t)0xDA17, (q15_t)0x85DB, (q15_t)0xD9B7,
+	(q15_t)0x85FA, (q15_t)0xD957, (q15_t)0x8618, (q15_t)0xD8F8,
+	(q15_t)0x8637, (q15_t)0xD898, (q15_t)0x8656, (q15_t)0xD838,
+	(q15_t)0x8675, (q15_t)0xD7D9, (q15_t)0x8695, (q15_t)0xD779,
+	(q15_t)0x86B5, (q15_t)0xD71A, (q15_t)0x86D5, (q15_t)0xD6BB,
+	(q15_t)0x86F6, (q15_t)0xD65C, (q15_t)0x8717, (q15_t)0xD5FD,
+	(q15_t)0x8738, (q15_t)0xD59E, (q15_t)0x8759, (q15_t)0xD53F,
+	(q15_t)0x877B, (q15_t)0xD4E0, (q15_t)0x879D, (q15_t)0xD482,
+	(q15_t)0x87BF, (q15_t)0xD423, (q15_t)0x87E2, (q15_t)0xD3C5,
+	(q15_t)0x8805, (q15_t)0xD367, (q15_t)0x8828, (q15_t)0xD308,
+	(q15_t)0x884B, (q15_t)0xD2AA, (q15_t)0x886F, (q15_t)0xD24C,
+	(q15_t)0x8893, (q15_t)0xD1EE, (q15_t)0x88B8, (q15_t)0xD191,
+	(q15_t)0x88DC, (q15_t)0xD133, (q15_t)0x8901, (q15_t)0xD0D6,
+	(q15_t)0x8926, (q15_t)0xD078, (q15_t)0x894C, (q15_t)0xD01B,
+	(q15_t)0x8971, (q15_t)0xCFBE, (q15_t)0x8997, (q15_t)0xCF61,
+	(q15_t)0x89BE, (q15_t)0xCF04, (q15_t)0x89E4, (q15_t)0xCEA7,
+	(q15_t)0x8A0B, (q15_t)0xCE4A, (q15_t)0x8A33, (q15_t)0xCDEE,
+	(q15_t)0x8A5A, (q15_t)0xCD91, (q15_t)0x8A82, (q15_t)0xCD35,
+	(q15_t)0x8AAA, (q15_t)0xCCD9, (q15_t)0x8AD2, (q15_t)0xCC7D,
+	(q15_t)0x8AFB, (q15_t)0xCC21, (q15_t)0x8B24, (q15_t)0xCBC5,
+	(q15_t)0x8B4D, (q15_t)0xCB69, (q15_t)0x8B76, (q15_t)0xCB0D,
+	(q15_t)0x8BA0, (q15_t)0xCAB2, (q15_t)0x8BCA, (q15_t)0xCA57,
+	(q15_t)0x8BF4, (q15_t)0xC9FB, (q15_t)0x8C1F, (q15_t)0xC9A0,
+	(q15_t)0x8C4A, (q15_t)0xC945, (q15_t)0x8C75, (q15_t)0xC8EB,
+	(q15_t)0x8CA0, (q15_t)0xC890, (q15_t)0x8CCC, (q15_t)0xC835,
+	(q15_t)0x8CF8, (q15_t)0xC7DB, (q15_t)0x8D24, (q15_t)0xC781,
+	(q15_t)0x8D50, (q15_t)0xC727, (q15_t)0x8D7D, (q15_t)0xC6CD,
+	(q15_t)0x8DAA, (q15_t)0xC673, (q15_t)0x8DD8, (q15_t)0xC619,
+	(q15_t)0x8E05, (q15_t)0xC5BF, (q15_t)0x8E33, (q15_t)0xC566,
+	(q15_t)0x8E61, (q15_t)0xC50D, (q15_t)0x8E90, (q15_t)0xC4B3,
+	(q15_t)0x8EBE, (q15_t)0xC45A, (q15_t)0x8EED, (q15_t)0xC402,
+	(q15_t)0x8F1D, (q15_t)0xC3A9, (q15_t)0x8F4C, (q15_t)0xC350,
+	(q15_t)0x8F7C, (q15_t)0xC2F8, (q15_t)0x8FAC, (q15_t)0xC29F,
+	(q15_t)0x8FDC, (q15_t)0xC247, (q15_t)0x900D, (q15_t)0xC1EF,
+	(q15_t)0x903E, (q15_t)0xC197, (q15_t)0x906F, (q15_t)0xC140,
+	(q15_t)0x90A0, (q15_t)0xC0E8, (q15_t)0x90D2, (q15_t)0xC091,
+	(q15_t)0x9104, (q15_t)0xC03A, (q15_t)0x9136, (q15_t)0xBFE2,
+	(q15_t)0x9169, (q15_t)0xBF8C, (q15_t)0x919C, (q15_t)0xBF35,
+	(q15_t)0x91CF, (q15_t)0xBEDE, (q15_t)0x9202, (q15_t)0xBE88,
+	(q15_t)0x9235, (q15_t)0xBE31, (q15_t)0x9269, (q15_t)0xBDDB,
+	(q15_t)0x929D, (q15_t)0xBD85, (q15_t)0x92D2, (q15_t)0xBD2F,
+	(q15_t)0x9306, (q15_t)0xBCDA, (q15_t)0x933B, (q15_t)0xBC84,
+	(q15_t)0x9370, (q15_t)0xBC2F, (q15_t)0x93A6, (q15_t)0xBBDA,
+	(q15_t)0x93DB, (q15_t)0xBB85, (q15_t)0x9411, (q15_t)0xBB30,
+	(q15_t)0x9447, (q15_t)0xBADB, (q15_t)0x947E, (q15_t)0xBA87,
+	(q15_t)0x94B5, (q15_t)0xBA32, (q15_t)0x94EC, (q15_t)0xB9DE,
+	(q15_t)0x9523, (q15_t)0xB98A, (q15_t)0x955A, (q15_t)0xB936,
+	(q15_t)0x9592, (q15_t)0xB8E3, (q15_t)0x95CA, (q15_t)0xB88F,
+	(q15_t)0x9602, (q15_t)0xB83C, (q15_t)0x963B, (q15_t)0xB7E9,
+	(q15_t)0x9673, (q15_t)0xB796, (q15_t)0x96AC, (q15_t)0xB743,
+	(q15_t)0x96E6, (q15_t)0xB6F0, (q15_t)0x971F, (q15_t)0xB69E,
+	(q15_t)0x9759, (q15_t)0xB64B, (q15_t)0x9793, (q15_t)0xB5F9,
+	(q15_t)0x97CD, (q15_t)0xB5A7, (q15_t)0x9808, (q15_t)0xB556,
+	(q15_t)0x9842, (q15_t)0xB504, (q15_t)0x987D, (q15_t)0xB4B3,
+	(q15_t)0x98B9, (q15_t)0xB461, (q15_t)0x98F4, (q15_t)0xB410,
+	(q15_t)0x9930, (q15_t)0xB3C0, (q15_t)0x996C, (q15_t)0xB36F,
+	(q15_t)0x99A8, (q15_t)0xB31E, (q15_t)0x99E5, (q15_t)0xB2CE,
+	(q15_t)0x9A22, (q15_t)0xB27E, (q15_t)0x9A5F, (q15_t)0xB22E,
+	(q15_t)0x9A9C, (q15_t)0xB1DE, (q15_t)0x9AD9, (q15_t)0xB18F,
+	(q15_t)0x9B17, (q15_t)0xB140, (q15_t)0x9B55, (q15_t)0xB0F0,
+	(q15_t)0x9B93, (q15_t)0xB0A1, (q15_t)0x9BD2, (q15_t)0xB053,
+	(q15_t)0x9C10, (q15_t)0xB004, (q15_t)0x9C4F, (q15_t)0xAFB6,
+	(q15_t)0x9C8E, (q15_t)0xAF68, (q15_t)0x9CCE, (q15_t)0xAF1A,
+	(q15_t)0x9D0D, (q15_t)0xAECC, (q15_t)0x9D4D, (q15_t)0xAE7E,
+	(q15_t)0x9D8E, (q15_t)0xAE31, (q15_t)0x9DCE, (q15_t)0xADE3,
+	(q15_t)0x9E0E, (q15_t)0xAD96, (q15_t)0x9E4F, (q15_t)0xAD4A,
+	(q15_t)0x9E90, (q15_t)0xACFD, (q15_t)0x9ED2, (q15_t)0xACB1,
+	(q15_t)0x9F13, (q15_t)0xAC64, (q15_t)0x9F55, (q15_t)0xAC18,
+	(q15_t)0x9F97, (q15_t)0xABCC, (q15_t)0x9FD9, (q15_t)0xAB81,
+	(q15_t)0xA01C, (q15_t)0xAB35, (q15_t)0xA05F, (q15_t)0xAAEA,
+	(q15_t)0xA0A1, (q15_t)0xAA9F, (q15_t)0xA0E5, (q15_t)0xAA54,
+	(q15_t)0xA128, (q15_t)0xAA0A, (q15_t)0xA16C, (q15_t)0xA9BF,
+	(q15_t)0xA1AF, (q15_t)0xA975, (q15_t)0xA1F4, (q15_t)0xA92B,
+	(q15_t)0xA238, (q15_t)0xA8E2, (q15_t)0xA27C, (q15_t)0xA898,
+	(q15_t)0xA2C1, (q15_t)0xA84F, (q15_t)0xA306, (q15_t)0xA806,
+	(q15_t)0xA34B, (q15_t)0xA7BD, (q15_t)0xA391, (q15_t)0xA774,
+	(q15_t)0xA3D6, (q15_t)0xA72B, (q15_t)0xA41C, (q15_t)0xA6E3,
+	(q15_t)0xA462, (q15_t)0xA69B, (q15_t)0xA4A9, (q15_t)0xA653,
+	(q15_t)0xA4EF, (q15_t)0xA60C, (q15_t)0xA536, (q15_t)0xA5C4,
+	(q15_t)0xA57D, (q15_t)0xA57D, (q15_t)0xA5C4, (q15_t)0xA536,
+	(q15_t)0xA60C, (q15_t)0xA4EF, (q15_t)0xA653, (q15_t)0xA4A9,
+	(q15_t)0xA69B, (q15_t)0xA462, (q15_t)0xA6E3, (q15_t)0xA41C,
+	(q15_t)0xA72B, (q15_t)0xA3D6, (q15_t)0xA774, (q15_t)0xA391,
+	(q15_t)0xA7BD, (q15_t)0xA34B, (q15_t)0xA806, (q15_t)0xA306,
+	(q15_t)0xA84F, (q15_t)0xA2C1, (q15_t)0xA898, (q15_t)0xA27C,
+	(q15_t)0xA8E2, (q15_t)0xA238, (q15_t)0xA92B, (q15_t)0xA1F4,
+	(q15_t)0xA975, (q15_t)0xA1AF, (q15_t)0xA9BF, (q15_t)0xA16C,
+	(q15_t)0xAA0A, (q15_t)0xA128, (q15_t)0xAA54, (q15_t)0xA0E5,
+	(q15_t)0xAA9F, (q15_t)0xA0A1, (q15_t)0xAAEA, (q15_t)0xA05F,
+	(q15_t)0xAB35, (q15_t)0xA01C, (q15_t)0xAB81, (q15_t)0x9FD9,
+	(q15_t)0xABCC, (q15_t)0x9F97, (q15_t)0xAC18, (q15_t)0x9F55,
+	(q15_t)0xAC64, (q15_t)0x9F13, (q15_t)0xACB1, (q15_t)0x9ED2,
+	(q15_t)0xACFD, (q15_t)0x9E90, (q15_t)0xAD4A, (q15_t)0x9E4F,
+	(q15_t)0xAD96, (q15_t)0x9E0E, (q15_t)0xADE3, (q15_t)0x9DCE,
+	(q15_t)0xAE31, (q15_t)0x9D8E, (q15_t)0xAE7E, (q15_t)0x9D4D,
+	(q15_t)0xAECC, (q15_t)0x9D0D, (q15_t)0xAF1A, (q15_t)0x9CCE,
+	(q15_t)0xAF68, (q15_t)0x9C8E, (q15_t)0xAFB6, (q15_t)0x9C4F,
+	(q15_t)0xB004, (q15_t)0x9C10, (q15_t)0xB053, (q15_t)0x9BD2,
+	(q15_t)0xB0A1, (q15_t)0x9B93, (q15_t)0xB0F0, (q15_t)0x9B55,
+	(q15_t)0xB140, (q15_t)0x9B17, (q15_t)0xB18F, (q15_t)0x9AD9,
+	(q15_t)0xB1DE, (q15_t)0x9A9C, (q15_t)0xB22E, (q15_t)0x9A5F,
+	(q15_t)0xB27E, (q15_t)0x9A22, (q15_t)0xB2CE, (q15_t)0x99E5,
+	(q15_t)0xB31E, (q15_t)0x99A8, (q15_t)0xB36F, (q15_t)0x996C,
+	(q15_t)0xB3C0, (q15_t)0x9930, (q15_t)0xB410, (q15_t)0x98F4,
+	(q15_t)0xB461, (q15_t)0x98B9, (q15_t)0xB4B3, (q15_t)0x987D,
+	(q15_t)0xB504, (q15_t)0x9842, (q15_t)0xB556, (q15_t)0x9808,
+	(q15_t)0xB5A7, (q15_t)0x97CD, (q15_t)0xB5F9, (q15_t)0x9793,
+	(q15_t)0xB64B, (q15_t)0x9759, (q15_t)0xB69E, (q15_t)0x971F,
+	(q15_t)0xB6F0, (q15_t)0x96E6, (q15_t)0xB743, (q15_t)0x96AC,
+	(q15_t)0xB796, (q15_t)0x9673, (q15_t)0xB7E9, (q15_t)0x963B,
+	(q15_t)0xB83C, (q15_t)0x9602, (q15_t)0xB88F, (q15_t)0x95CA,
+	(q15_t)0xB8E3, (q15_t)0x9592, (q15_t)0xB936, (q15_t)0x955A,
+	(q15_t)0xB98A, (q15_t)0x9523, (q15_t)0xB9DE, (q15_t)0x94EC,
+	(q15_t)0xBA32, (q15_t)0x94B5, (q15_t)0xBA87, (q15_t)0x947E,
+	(q15_t)0xBADB, (q15_t)0x9447, (q15_t)0xBB30, (q15_t)0x9411,
+	(q15_t)0xBB85, (q15_t)0x93DB, (q15_t)0xBBDA, (q15_t)0x93A6,
+	(q15_t)0xBC2F, (q15_t)0x9370, (q15_t)0xBC84, (q15_t)0x933B,
+	(q15_t)0xBCDA, (q15_t)0x9306, (q15_t)0xBD2F, (q15_t)0x92D2,
+	(q15_t)0xBD85, (q15_t)0x929D, (q15_t)0xBDDB, (q15_t)0x9269,
+	(q15_t)0xBE31, (q15_t)0x9235, (q15_t)0xBE88, (q15_t)0x9202,
+	(q15_t)0xBEDE, (q15_t)0x91CF, (q15_t)0xBF35, (q15_t)0x919C,
+	(q15_t)0xBF8C, (q15_t)0x9169, (q15_t)0xBFE2, (q15_t)0x9136,
+	(q15_t)0xC03A, (q15_t)0x9104, (q15_t)0xC091, (q15_t)0x90D2,
+	(q15_t)0xC0E8, (q15_t)0x90A0, (q15_t)0xC140, (q15_t)0x906F,
+	(q15_t)0xC197, (q15_t)0x903E, (q15_t)0xC1EF, (q15_t)0x900D,
+	(q15_t)0xC247, (q15_t)0x8FDC, (q15_t)0xC29F, (q15_t)0x8FAC,
+	(q15_t)0xC2F8, (q15_t)0x8F7C, (q15_t)0xC350, (q15_t)0x8F4C,
+	(q15_t)0xC3A9, (q15_t)0x8F1D, (q15_t)0xC402, (q15_t)0x8EED,
+	(q15_t)0xC45A, (q15_t)0x8EBE, (q15_t)0xC4B3, (q15_t)0x8E90,
+	(q15_t)0xC50D, (q15_t)0x8E61, (q15_t)0xC566, (q15_t)0x8E33,
+	(q15_t)0xC5BF, (q15_t)0x8E05, (q15_t)0xC619, (q15_t)0x8DD8,
+	(q15_t)0xC673, (q15_t)0x8DAA, (q15_t)0xC6CD, (q15_t)0x8D7D,
+	(q15_t)0xC727, (q15_t)0x8D50, (q15_t)0xC781, (q15_t)0x8D24,
+	(q15_t)0xC7DB, (q15_t)0x8CF8, (q15_t)0xC835, (q15_t)0x8CCC,
+	(q15_t)0xC890, (q15_t)0x8CA0, (q15_t)0xC8EB, (q15_t)0x8C75,
+	(q15_t)0xC945, (q15_t)0x8C4A, (q15_t)0xC9A0, (q15_t)0x8C1F,
+	(q15_t)0xC9FB, (q15_t)0x8BF4, (q15_t)0xCA57, (q15_t)0x8BCA,
+	(q15_t)0xCAB2, (q15_t)0x8BA0, (q15_t)0xCB0D, (q15_t)0x8B76,
+	(q15_t)0xCB69, (q15_t)0x8B4D, (q15_t)0xCBC5, (q15_t)0x8B24,
+	(q15_t)0xCC21, (q15_t)0x8AFB, (q15_t)0xCC7D, (q15_t)0x8AD2,
+	(q15_t)0xCCD9, (q15_t)0x8AAA, (q15_t)0xCD35, (q15_t)0x8A82,
+	(q15_t)0xCD91, (q15_t)0x8A5A, (q15_t)0xCDEE, (q15_t)0x8A33,
+	(q15_t)0xCE4A, (q15_t)0x8A0B, (q15_t)0xCEA7, (q15_t)0x89E4,
+	(q15_t)0xCF04, (q15_t)0x89BE, (q15_t)0xCF61, (q15_t)0x8997,
+	(q15_t)0xCFBE, (q15_t)0x8971, (q15_t)0xD01B, (q15_t)0x894C,
+	(q15_t)0xD078, (q15_t)0x8926, (q15_t)0xD0D6, (q15_t)0x8901,
+	(q15_t)0xD133, (q15_t)0x88DC, (q15_t)0xD191, (q15_t)0x88B8,
+	(q15_t)0xD1EE, (q15_t)0x8893, (q15_t)0xD24C, (q15_t)0x886F,
+	(q15_t)0xD2AA, (q15_t)0x884B, (q15_t)0xD308, (q15_t)0x8828,
+	(q15_t)0xD367, (q15_t)0x8805, (q15_t)0xD3C5, (q15_t)0x87E2,
+	(q15_t)0xD423, (q15_t)0x87BF, (q15_t)0xD482, (q15_t)0x879D,
+	(q15_t)0xD4E0, (q15_t)0x877B, (q15_t)0xD53F, (q15_t)0x8759,
+	(q15_t)0xD59E, (q15_t)0x8738, (q15_t)0xD5FD, (q15_t)0x8717,
+	(q15_t)0xD65C, (q15_t)0x86F6, (q15_t)0xD6BB, (q15_t)0x86D5,
+	(q15_t)0xD71A, (q15_t)0x86B5, (q15_t)0xD779, (q15_t)0x8695,
+	(q15_t)0xD7D9, (q15_t)0x8675, (q15_t)0xD838, (q15_t)0x8656,
+	(q15_t)0xD898, (q15_t)0x8637, (q15_t)0xD8F8, (q15_t)0x8618,
+	(q15_t)0xD957, (q15_t)0x85FA, (q15_t)0xD9B7, (q15_t)0x85DB,
+	(q15_t)0xDA17, (q15_t)0x85BD, (q15_t)0xDA77, (q15_t)0x85A0,
+	(q15_t)0xDAD7, (q15_t)0x8582, (q15_t)0xDB38, (q15_t)0x8565,
+	(q15_t)0xDB98, (q15_t)0x8549, (q15_t)0xDBF8, (q15_t)0x852C,
+	(q15_t)0xDC59, (q15_t)0x8510, (q15_t)0xDCBA, (q15_t)0x84F4,
+	(q15_t)0xDD1A, (q15_t)0x84D9, (q15_t)0xDD7B, (q15_t)0x84BD,
+	(q15_t)0xDDDC, (q15_t)0x84A2, (q15_t)0xDE3D, (q15_t)0x8488,
+	(q15_t)0xDE9E, (q15_t)0x846D, (q15_t)0xDEFF, (q15_t)0x8453,
+	(q15_t)0xDF60, (q15_t)0x843A, (q15_t)0xDFC1, (q15_t)0x8420,
+	(q15_t)0xE023, (q15_t)0x8407, (q15_t)0xE084, (q15_t)0x83EE,
+	(q15_t)0xE0E6, (q15_t)0x83D6, (q15_t)0xE147, (q15_t)0x83BD,
+	(q15_t)0xE1A9, (q15_t)0x83A5, (q15_t)0xE20A, (q15_t)0x838E,
+	(q15_t)0xE26C, (q15_t)0x8376, (q15_t)0xE2CE, (q15_t)0x835F,
+	(q15_t)0xE330, (q15_t)0x8348, (q15_t)0xE392, (q15_t)0x8332,
+	(q15_t)0xE3F4, (q15_t)0x831C, (q15_t)0xE456, (q15_t)0x8306,
+	(q15_t)0xE4B8, (q15_t)0x82F0, (q15_t)0xE51B, (q15_t)0x82DB,
+	(q15_t)0xE57D, (q15_t)0x82C6, (q15_t)0xE5DF, (q15_t)0x82B1,
+	(q15_t)0xE642, (q15_t)0x829D, (q15_t)0xE6A4, (q15_t)0x8289,
+	(q15_t)0xE707, (q15_t)0x8275, (q15_t)0xE769, (q15_t)0x8262,
+	(q15_t)0xE7CC, (q15_t)0x824F, (q15_t)0xE82F, (q15_t)0x823C,
+	(q15_t)0xE892, (q15_t)0x8229, (q15_t)0xE8F5, (q15_t)0x8217,
+	(q15_t)0xE957, (q15_t)0x8205, (q15_t)0xE9BA, (q15_t)0x81F3,
+	(q15_t)0xEA1D, (q15_t)0x81E2, (q15_t)0xEA80, (q15_t)0x81D1,
+	(q15_t)0xEAE4, (q15_t)0x81C0, (q15_t)0xEB47, (q15_t)0x81B0,
+	(q15_t)0xEBAA, (q15_t)0x81A0, (q15_t)0xEC0D, (q15_t)0x8190,
+	(q15_t)0xEC71, (q15_t)0x8180, (q15_t)0xECD4, (q15_t)0x8171,
+	(q15_t)0xED37, (q15_t)0x8162, (q15_t)0xED9B, (q15_t)0x8154,
+	(q15_t)0xEDFE, (q15_t)0x8145, (q15_t)0xEE62, (q15_t)0x8137,
+	(q15_t)0xEEC6, (q15_t)0x812A, (q15_t)0xEF29, (q15_t)0x811C,
+	(q15_t)0xEF8D, (q15_t)0x810F, (q15_t)0xEFF1, (q15_t)0x8102,
+	(q15_t)0xF054, (q15_t)0x80F6, (q15_t)0xF0B8, (q15_t)0x80EA,
+	(q15_t)0xF11C, (q15_t)0x80DE, (q15_t)0xF180, (q15_t)0x80D2,
+	(q15_t)0xF1E4, (q15_t)0x80C7, (q15_t)0xF248, (q15_t)0x80BC,
+	(q15_t)0xF2AC, (q15_t)0x80B2, (q15_t)0xF310, (q15_t)0x80A7,
+	(q15_t)0xF374, (q15_t)0x809D, (q15_t)0xF3D8, (q15_t)0x8094,
+	(q15_t)0xF43C, (q15_t)0x808A, (q15_t)0xF4A0, (q15_t)0x8081,
+	(q15_t)0xF504, (q15_t)0x8078, (q15_t)0xF568, (q15_t)0x8070,
+	(q15_t)0xF5CC, (q15_t)0x8068, (q15_t)0xF631, (q15_t)0x8060,
+	(q15_t)0xF695, (q15_t)0x8058, (q15_t)0xF6F9, (q15_t)0x8051,
+	(q15_t)0xF75D, (q15_t)0x804A, (q15_t)0xF7C2, (q15_t)0x8043,
+	(q15_t)0xF826, (q15_t)0x803D, (q15_t)0xF88A, (q15_t)0x8037,
+	(q15_t)0xF8EF, (q15_t)0x8031, (q15_t)0xF953, (q15_t)0x802C,
+	(q15_t)0xF9B8, (q15_t)0x8027, (q15_t)0xFA1C, (q15_t)0x8022,
+	(q15_t)0xFA80, (q15_t)0x801E, (q15_t)0xFAE5, (q15_t)0x801A,
+	(q15_t)0xFB49, (q15_t)0x8016, (q15_t)0xFBAE, (q15_t)0x8012,
+	(q15_t)0xFC12, (q15_t)0x800F, (q15_t)0xFC77, (q15_t)0x800C,
+	(q15_t)0xFCDB, (q15_t)0x8009, (q15_t)0xFD40, (q15_t)0x8007,
+	(q15_t)0xFDA4, (q15_t)0x8005, (q15_t)0xFE09, (q15_t)0x8003,
+	(q15_t)0xFE6D, (q15_t)0x8002, (q15_t)0xFED2, (q15_t)0x8001,
+	(q15_t)0xFF36, (q15_t)0x8000, (q15_t)0xFF9B, (q15_t)0x8000
+};
+
+/**
+* \par
+* Example code for q15 Twiddle factors Generation::
+* \par
+* <pre>for(i = 0; i< 3N/4; i++)
+* {
+*    twiddleCoefq15[2*i]= cos(i * 2*PI/(float)N);
+*    twiddleCoefq15[2*i+1]= sin(i * 2*PI/(float)N);
+* } </pre>
+* \par
+* where N = 4096	and PI = 3.14159265358979
+* \par
+* Cos and Sin values are interleaved fashion
+* \par
+* Convert Floating point to q15(Fixed point 1.15):
+*	round(twiddleCoefq15(i) * pow(2, 15))
+*
+*/
+const q15_t twiddleCoef_4096_q15[6144] =
+{
+	(q15_t)0x7FFF, (q15_t)0x0000, (q15_t)0x7FFF, (q15_t)0x0032,
+	(q15_t)0x7FFF, (q15_t)0x0064, (q15_t)0x7FFF, (q15_t)0x0096,
+	(q15_t)0x7FFF, (q15_t)0x00C9, (q15_t)0x7FFF, (q15_t)0x00FB,
+	(q15_t)0x7FFE, (q15_t)0x012D, (q15_t)0x7FFE, (q15_t)0x015F,
+	(q15_t)0x7FFD, (q15_t)0x0192, (q15_t)0x7FFC, (q15_t)0x01C4,
+	(q15_t)0x7FFC, (q15_t)0x01F6, (q15_t)0x7FFB, (q15_t)0x0228,
+	(q15_t)0x7FFA, (q15_t)0x025B, (q15_t)0x7FF9, (q15_t)0x028D,
+	(q15_t)0x7FF8, (q15_t)0x02BF, (q15_t)0x7FF7, (q15_t)0x02F1,
+	(q15_t)0x7FF6, (q15_t)0x0324, (q15_t)0x7FF4, (q15_t)0x0356,
+	(q15_t)0x7FF3, (q15_t)0x0388, (q15_t)0x7FF2, (q15_t)0x03BA,
+	(q15_t)0x7FF0, (q15_t)0x03ED, (q15_t)0x7FEE, (q15_t)0x041F,
+	(q15_t)0x7FED, (q15_t)0x0451, (q15_t)0x7FEB, (q15_t)0x0483,
+	(q15_t)0x7FE9, (q15_t)0x04B6, (q15_t)0x7FE7, (q15_t)0x04E8,
+	(q15_t)0x7FE5, (q15_t)0x051A, (q15_t)0x7FE3, (q15_t)0x054C,
+	(q15_t)0x7FE1, (q15_t)0x057F, (q15_t)0x7FDF, (q15_t)0x05B1,
+	(q15_t)0x7FDD, (q15_t)0x05E3, (q15_t)0x7FDA, (q15_t)0x0615,
+	(q15_t)0x7FD8, (q15_t)0x0647, (q15_t)0x7FD6, (q15_t)0x067A,
+	(q15_t)0x7FD3, (q15_t)0x06AC, (q15_t)0x7FD0, (q15_t)0x06DE,
+	(q15_t)0x7FCE, (q15_t)0x0710, (q15_t)0x7FCB, (q15_t)0x0742,
+	(q15_t)0x7FC8, (q15_t)0x0775, (q15_t)0x7FC5, (q15_t)0x07A7,
+	(q15_t)0x7FC2, (q15_t)0x07D9, (q15_t)0x7FBF, (q15_t)0x080B,
+	(q15_t)0x7FBC, (q15_t)0x083D, (q15_t)0x7FB8, (q15_t)0x086F,
+	(q15_t)0x7FB5, (q15_t)0x08A2, (q15_t)0x7FB1, (q15_t)0x08D4,
+	(q15_t)0x7FAE, (q15_t)0x0906, (q15_t)0x7FAA, (q15_t)0x0938,
+	(q15_t)0x7FA7, (q15_t)0x096A, (q15_t)0x7FA3, (q15_t)0x099C,
+	(q15_t)0x7F9F, (q15_t)0x09CE, (q15_t)0x7F9B, (q15_t)0x0A00,
+	(q15_t)0x7F97, (q15_t)0x0A33, (q15_t)0x7F93, (q15_t)0x0A65,
+	(q15_t)0x7F8F, (q15_t)0x0A97, (q15_t)0x7F8B, (q15_t)0x0AC9,
+	(q15_t)0x7F87, (q15_t)0x0AFB, (q15_t)0x7F82, (q15_t)0x0B2D,
+	(q15_t)0x7F7E, (q15_t)0x0B5F, (q15_t)0x7F79, (q15_t)0x0B91,
+	(q15_t)0x7F75, (q15_t)0x0BC3, (q15_t)0x7F70, (q15_t)0x0BF5,
+	(q15_t)0x7F6B, (q15_t)0x0C27, (q15_t)0x7F67, (q15_t)0x0C59,
+	(q15_t)0x7F62, (q15_t)0x0C8B, (q15_t)0x7F5D, (q15_t)0x0CBD,
+	(q15_t)0x7F58, (q15_t)0x0CEF, (q15_t)0x7F53, (q15_t)0x0D21,
+	(q15_t)0x7F4D, (q15_t)0x0D53, (q15_t)0x7F48, (q15_t)0x0D85,
+	(q15_t)0x7F43, (q15_t)0x0DB7, (q15_t)0x7F3D, (q15_t)0x0DE9,
+	(q15_t)0x7F38, (q15_t)0x0E1B, (q15_t)0x7F32, (q15_t)0x0E4D,
+	(q15_t)0x7F2D, (q15_t)0x0E7F, (q15_t)0x7F27, (q15_t)0x0EB1,
+	(q15_t)0x7F21, (q15_t)0x0EE3, (q15_t)0x7F1B, (q15_t)0x0F15,
+	(q15_t)0x7F15, (q15_t)0x0F47, (q15_t)0x7F0F, (q15_t)0x0F79,
+	(q15_t)0x7F09, (q15_t)0x0FAB, (q15_t)0x7F03, (q15_t)0x0FDD,
+	(q15_t)0x7EFD, (q15_t)0x100E, (q15_t)0x7EF6, (q15_t)0x1040,
+	(q15_t)0x7EF0, (q15_t)0x1072, (q15_t)0x7EE9, (q15_t)0x10A4,
+	(q15_t)0x7EE3, (q15_t)0x10D6, (q15_t)0x7EDC, (q15_t)0x1108,
+	(q15_t)0x7ED5, (q15_t)0x1139, (q15_t)0x7ECF, (q15_t)0x116B,
+	(q15_t)0x7EC8, (q15_t)0x119D, (q15_t)0x7EC1, (q15_t)0x11CF,
+	(q15_t)0x7EBA, (q15_t)0x1201, (q15_t)0x7EB3, (q15_t)0x1232,
+	(q15_t)0x7EAB, (q15_t)0x1264, (q15_t)0x7EA4, (q15_t)0x1296,
+	(q15_t)0x7E9D, (q15_t)0x12C8, (q15_t)0x7E95, (q15_t)0x12F9,
+	(q15_t)0x7E8E, (q15_t)0x132B, (q15_t)0x7E86, (q15_t)0x135D,
+	(q15_t)0x7E7F, (q15_t)0x138E, (q15_t)0x7E77, (q15_t)0x13C0,
+	(q15_t)0x7E6F, (q15_t)0x13F2, (q15_t)0x7E67, (q15_t)0x1423,
+	(q15_t)0x7E5F, (q15_t)0x1455, (q15_t)0x7E57, (q15_t)0x1487,
+	(q15_t)0x7E4F, (q15_t)0x14B8, (q15_t)0x7E47, (q15_t)0x14EA,
+	(q15_t)0x7E3F, (q15_t)0x151B, (q15_t)0x7E37, (q15_t)0x154D,
+	(q15_t)0x7E2E, (q15_t)0x157F, (q15_t)0x7E26, (q15_t)0x15B0,
+	(q15_t)0x7E1D, (q15_t)0x15E2, (q15_t)0x7E14, (q15_t)0x1613,
+	(q15_t)0x7E0C, (q15_t)0x1645, (q15_t)0x7E03, (q15_t)0x1676,
+	(q15_t)0x7DFA, (q15_t)0x16A8, (q15_t)0x7DF1, (q15_t)0x16D9,
+	(q15_t)0x7DE8, (q15_t)0x170A, (q15_t)0x7DDF, (q15_t)0x173C,
+	(q15_t)0x7DD6, (q15_t)0x176D, (q15_t)0x7DCD, (q15_t)0x179F,
+	(q15_t)0x7DC3, (q15_t)0x17D0, (q15_t)0x7DBA, (q15_t)0x1802,
+	(q15_t)0x7DB0, (q15_t)0x1833, (q15_t)0x7DA7, (q15_t)0x1864,
+	(q15_t)0x7D9D, (q15_t)0x1896, (q15_t)0x7D94, (q15_t)0x18C7,
+	(q15_t)0x7D8A, (q15_t)0x18F8, (q15_t)0x7D80, (q15_t)0x192A,
+	(q15_t)0x7D76, (q15_t)0x195B, (q15_t)0x7D6C, (q15_t)0x198C,
+	(q15_t)0x7D62, (q15_t)0x19BD, (q15_t)0x7D58, (q15_t)0x19EF,
+	(q15_t)0x7D4E, (q15_t)0x1A20, (q15_t)0x7D43, (q15_t)0x1A51,
+	(q15_t)0x7D39, (q15_t)0x1A82, (q15_t)0x7D2F, (q15_t)0x1AB3,
+	(q15_t)0x7D24, (q15_t)0x1AE4, (q15_t)0x7D19, (q15_t)0x1B16,
+	(q15_t)0x7D0F, (q15_t)0x1B47, (q15_t)0x7D04, (q15_t)0x1B78,
+	(q15_t)0x7CF9, (q15_t)0x1BA9, (q15_t)0x7CEE, (q15_t)0x1BDA,
+	(q15_t)0x7CE3, (q15_t)0x1C0B, (q15_t)0x7CD8, (q15_t)0x1C3C,
+	(q15_t)0x7CCD, (q15_t)0x1C6D, (q15_t)0x7CC2, (q15_t)0x1C9E,
+	(q15_t)0x7CB7, (q15_t)0x1CCF, (q15_t)0x7CAB, (q15_t)0x1D00,
+	(q15_t)0x7CA0, (q15_t)0x1D31, (q15_t)0x7C94, (q15_t)0x1D62,
+	(q15_t)0x7C89, (q15_t)0x1D93, (q15_t)0x7C7D, (q15_t)0x1DC4,
+	(q15_t)0x7C71, (q15_t)0x1DF5, (q15_t)0x7C66, (q15_t)0x1E25,
+	(q15_t)0x7C5A, (q15_t)0x1E56, (q15_t)0x7C4E, (q15_t)0x1E87,
+	(q15_t)0x7C42, (q15_t)0x1EB8, (q15_t)0x7C36, (q15_t)0x1EE9,
+	(q15_t)0x7C29, (q15_t)0x1F19, (q15_t)0x7C1D, (q15_t)0x1F4A,
+	(q15_t)0x7C11, (q15_t)0x1F7B, (q15_t)0x7C05, (q15_t)0x1FAC,
+	(q15_t)0x7BF8, (q15_t)0x1FDC, (q15_t)0x7BEB, (q15_t)0x200D,
+	(q15_t)0x7BDF, (q15_t)0x203E, (q15_t)0x7BD2, (q15_t)0x206E,
+	(q15_t)0x7BC5, (q15_t)0x209F, (q15_t)0x7BB9, (q15_t)0x20D0,
+	(q15_t)0x7BAC, (q15_t)0x2100, (q15_t)0x7B9F, (q15_t)0x2131,
+	(q15_t)0x7B92, (q15_t)0x2161, (q15_t)0x7B84, (q15_t)0x2192,
+	(q15_t)0x7B77, (q15_t)0x21C2, (q15_t)0x7B6A, (q15_t)0x21F3,
+	(q15_t)0x7B5D, (q15_t)0x2223, (q15_t)0x7B4F, (q15_t)0x2254,
+	(q15_t)0x7B42, (q15_t)0x2284, (q15_t)0x7B34, (q15_t)0x22B4,
+	(q15_t)0x7B26, (q15_t)0x22E5, (q15_t)0x7B19, (q15_t)0x2315,
+	(q15_t)0x7B0B, (q15_t)0x2345, (q15_t)0x7AFD, (q15_t)0x2376,
+	(q15_t)0x7AEF, (q15_t)0x23A6, (q15_t)0x7AE1, (q15_t)0x23D6,
+	(q15_t)0x7AD3, (q15_t)0x2407, (q15_t)0x7AC5, (q15_t)0x2437,
+	(q15_t)0x7AB6, (q15_t)0x2467, (q15_t)0x7AA8, (q15_t)0x2497,
+	(q15_t)0x7A9A, (q15_t)0x24C7, (q15_t)0x7A8B, (q15_t)0x24F7,
+	(q15_t)0x7A7D, (q15_t)0x2528, (q15_t)0x7A6E, (q15_t)0x2558,
+	(q15_t)0x7A5F, (q15_t)0x2588, (q15_t)0x7A50, (q15_t)0x25B8,
+	(q15_t)0x7A42, (q15_t)0x25E8, (q15_t)0x7A33, (q15_t)0x2618,
+	(q15_t)0x7A24, (q15_t)0x2648, (q15_t)0x7A15, (q15_t)0x2678,
+	(q15_t)0x7A05, (q15_t)0x26A8, (q15_t)0x79F6, (q15_t)0x26D8,
+	(q15_t)0x79E7, (q15_t)0x2707, (q15_t)0x79D8, (q15_t)0x2737,
+	(q15_t)0x79C8, (q15_t)0x2767, (q15_t)0x79B9, (q15_t)0x2797,
+	(q15_t)0x79A9, (q15_t)0x27C7, (q15_t)0x7999, (q15_t)0x27F6,
+	(q15_t)0x798A, (q15_t)0x2826, (q15_t)0x797A, (q15_t)0x2856,
+	(q15_t)0x796A, (q15_t)0x2886, (q15_t)0x795A, (q15_t)0x28B5,
+	(q15_t)0x794A, (q15_t)0x28E5, (q15_t)0x793A, (q15_t)0x2915,
+	(q15_t)0x792A, (q15_t)0x2944, (q15_t)0x7919, (q15_t)0x2974,
+	(q15_t)0x7909, (q15_t)0x29A3, (q15_t)0x78F9, (q15_t)0x29D3,
+	(q15_t)0x78E8, (q15_t)0x2A02, (q15_t)0x78D8, (q15_t)0x2A32,
+	(q15_t)0x78C7, (q15_t)0x2A61, (q15_t)0x78B6, (q15_t)0x2A91,
+	(q15_t)0x78A6, (q15_t)0x2AC0, (q15_t)0x7895, (q15_t)0x2AEF,
+	(q15_t)0x7884, (q15_t)0x2B1F, (q15_t)0x7873, (q15_t)0x2B4E,
+	(q15_t)0x7862, (q15_t)0x2B7D, (q15_t)0x7851, (q15_t)0x2BAD,
+	(q15_t)0x7840, (q15_t)0x2BDC, (q15_t)0x782E, (q15_t)0x2C0B,
+	(q15_t)0x781D, (q15_t)0x2C3A, (q15_t)0x780C, (q15_t)0x2C69,
+	(q15_t)0x77FA, (q15_t)0x2C98, (q15_t)0x77E9, (q15_t)0x2CC8,
+	(q15_t)0x77D7, (q15_t)0x2CF7, (q15_t)0x77C5, (q15_t)0x2D26,
+	(q15_t)0x77B4, (q15_t)0x2D55, (q15_t)0x77A2, (q15_t)0x2D84,
+	(q15_t)0x7790, (q15_t)0x2DB3, (q15_t)0x777E, (q15_t)0x2DE2,
+	(q15_t)0x776C, (q15_t)0x2E11, (q15_t)0x775A, (q15_t)0x2E3F,
+	(q15_t)0x7747, (q15_t)0x2E6E, (q15_t)0x7735, (q15_t)0x2E9D,
+	(q15_t)0x7723, (q15_t)0x2ECC, (q15_t)0x7710, (q15_t)0x2EFB,
+	(q15_t)0x76FE, (q15_t)0x2F29, (q15_t)0x76EB, (q15_t)0x2F58,
+	(q15_t)0x76D9, (q15_t)0x2F87, (q15_t)0x76C6, (q15_t)0x2FB5,
+	(q15_t)0x76B3, (q15_t)0x2FE4, (q15_t)0x76A0, (q15_t)0x3013,
+	(q15_t)0x768E, (q15_t)0x3041, (q15_t)0x767B, (q15_t)0x3070,
+	(q15_t)0x7668, (q15_t)0x309E, (q15_t)0x7654, (q15_t)0x30CD,
+	(q15_t)0x7641, (q15_t)0x30FB, (q15_t)0x762E, (q15_t)0x312A,
+	(q15_t)0x761B, (q15_t)0x3158, (q15_t)0x7607, (q15_t)0x3186,
+	(q15_t)0x75F4, (q15_t)0x31B5, (q15_t)0x75E0, (q15_t)0x31E3,
+	(q15_t)0x75CC, (q15_t)0x3211, (q15_t)0x75B9, (q15_t)0x3240,
+	(q15_t)0x75A5, (q15_t)0x326E, (q15_t)0x7591, (q15_t)0x329C,
+	(q15_t)0x757D, (q15_t)0x32CA, (q15_t)0x7569, (q15_t)0x32F8,
+	(q15_t)0x7555, (q15_t)0x3326, (q15_t)0x7541, (q15_t)0x3354,
+	(q15_t)0x752D, (q15_t)0x3382, (q15_t)0x7519, (q15_t)0x33B0,
+	(q15_t)0x7504, (q15_t)0x33DE, (q15_t)0x74F0, (q15_t)0x340C,
+	(q15_t)0x74DB, (q15_t)0x343A, (q15_t)0x74C7, (q15_t)0x3468,
+	(q15_t)0x74B2, (q15_t)0x3496, (q15_t)0x749E, (q15_t)0x34C4,
+	(q15_t)0x7489, (q15_t)0x34F2, (q15_t)0x7474, (q15_t)0x351F,
+	(q15_t)0x745F, (q15_t)0x354D, (q15_t)0x744A, (q15_t)0x357B,
+	(q15_t)0x7435, (q15_t)0x35A8, (q15_t)0x7420, (q15_t)0x35D6,
+	(q15_t)0x740B, (q15_t)0x3604, (q15_t)0x73F6, (q15_t)0x3631,
+	(q15_t)0x73E0, (q15_t)0x365F, (q15_t)0x73CB, (q15_t)0x368C,
+	(q15_t)0x73B5, (q15_t)0x36BA, (q15_t)0x73A0, (q15_t)0x36E7,
+	(q15_t)0x738A, (q15_t)0x3714, (q15_t)0x7375, (q15_t)0x3742,
+	(q15_t)0x735F, (q15_t)0x376F, (q15_t)0x7349, (q15_t)0x379C,
+	(q15_t)0x7333, (q15_t)0x37CA, (q15_t)0x731D, (q15_t)0x37F7,
+	(q15_t)0x7307, (q15_t)0x3824, (q15_t)0x72F1, (q15_t)0x3851,
+	(q15_t)0x72DB, (q15_t)0x387E, (q15_t)0x72C5, (q15_t)0x38AB,
+	(q15_t)0x72AF, (q15_t)0x38D8, (q15_t)0x7298, (q15_t)0x3906,
+	(q15_t)0x7282, (q15_t)0x3932, (q15_t)0x726B, (q15_t)0x395F,
+	(q15_t)0x7255, (q15_t)0x398C, (q15_t)0x723E, (q15_t)0x39B9,
+	(q15_t)0x7227, (q15_t)0x39E6, (q15_t)0x7211, (q15_t)0x3A13,
+	(q15_t)0x71FA, (q15_t)0x3A40, (q15_t)0x71E3, (q15_t)0x3A6C,
+	(q15_t)0x71CC, (q15_t)0x3A99, (q15_t)0x71B5, (q15_t)0x3AC6,
+	(q15_t)0x719E, (q15_t)0x3AF2, (q15_t)0x7186, (q15_t)0x3B1F,
+	(q15_t)0x716F, (q15_t)0x3B4C, (q15_t)0x7158, (q15_t)0x3B78,
+	(q15_t)0x7141, (q15_t)0x3BA5, (q15_t)0x7129, (q15_t)0x3BD1,
+	(q15_t)0x7112, (q15_t)0x3BFD, (q15_t)0x70FA, (q15_t)0x3C2A,
+	(q15_t)0x70E2, (q15_t)0x3C56, (q15_t)0x70CB, (q15_t)0x3C83,
+	(q15_t)0x70B3, (q15_t)0x3CAF, (q15_t)0x709B, (q15_t)0x3CDB,
+	(q15_t)0x7083, (q15_t)0x3D07, (q15_t)0x706B, (q15_t)0x3D33,
+	(q15_t)0x7053, (q15_t)0x3D60, (q15_t)0x703B, (q15_t)0x3D8C,
+	(q15_t)0x7023, (q15_t)0x3DB8, (q15_t)0x700A, (q15_t)0x3DE4,
+	(q15_t)0x6FF2, (q15_t)0x3E10, (q15_t)0x6FDA, (q15_t)0x3E3C,
+	(q15_t)0x6FC1, (q15_t)0x3E68, (q15_t)0x6FA9, (q15_t)0x3E93,
+	(q15_t)0x6F90, (q15_t)0x3EBF, (q15_t)0x6F77, (q15_t)0x3EEB,
+	(q15_t)0x6F5F, (q15_t)0x3F17, (q15_t)0x6F46, (q15_t)0x3F43,
+	(q15_t)0x6F2D, (q15_t)0x3F6E, (q15_t)0x6F14, (q15_t)0x3F9A,
+	(q15_t)0x6EFB, (q15_t)0x3FC5, (q15_t)0x6EE2, (q15_t)0x3FF1,
+	(q15_t)0x6EC9, (q15_t)0x401D, (q15_t)0x6EAF, (q15_t)0x4048,
+	(q15_t)0x6E96, (q15_t)0x4073, (q15_t)0x6E7D, (q15_t)0x409F,
+	(q15_t)0x6E63, (q15_t)0x40CA, (q15_t)0x6E4A, (q15_t)0x40F6,
+	(q15_t)0x6E30, (q15_t)0x4121, (q15_t)0x6E17, (q15_t)0x414C,
+	(q15_t)0x6DFD, (q15_t)0x4177, (q15_t)0x6DE3, (q15_t)0x41A2,
+	(q15_t)0x6DCA, (q15_t)0x41CE, (q15_t)0x6DB0, (q15_t)0x41F9,
+	(q15_t)0x6D96, (q15_t)0x4224, (q15_t)0x6D7C, (q15_t)0x424F,
+	(q15_t)0x6D62, (q15_t)0x427A, (q15_t)0x6D48, (q15_t)0x42A5,
+	(q15_t)0x6D2D, (q15_t)0x42D0, (q15_t)0x6D13, (q15_t)0x42FA,
+	(q15_t)0x6CF9, (q15_t)0x4325, (q15_t)0x6CDE, (q15_t)0x4350,
+	(q15_t)0x6CC4, (q15_t)0x437B, (q15_t)0x6CA9, (q15_t)0x43A5,
+	(q15_t)0x6C8F, (q15_t)0x43D0, (q15_t)0x6C74, (q15_t)0x43FB,
+	(q15_t)0x6C59, (q15_t)0x4425, (q15_t)0x6C3F, (q15_t)0x4450,
+	(q15_t)0x6C24, (q15_t)0x447A, (q15_t)0x6C09, (q15_t)0x44A5,
+	(q15_t)0x6BEE, (q15_t)0x44CF, (q15_t)0x6BD3, (q15_t)0x44FA,
+	(q15_t)0x6BB8, (q15_t)0x4524, (q15_t)0x6B9C, (q15_t)0x454E,
+	(q15_t)0x6B81, (q15_t)0x4578, (q15_t)0x6B66, (q15_t)0x45A3,
+	(q15_t)0x6B4A, (q15_t)0x45CD, (q15_t)0x6B2F, (q15_t)0x45F7,
+	(q15_t)0x6B13, (q15_t)0x4621, (q15_t)0x6AF8, (q15_t)0x464B,
+	(q15_t)0x6ADC, (q15_t)0x4675, (q15_t)0x6AC1, (q15_t)0x469F,
+	(q15_t)0x6AA5, (q15_t)0x46C9, (q15_t)0x6A89, (q15_t)0x46F3,
+	(q15_t)0x6A6D, (q15_t)0x471C, (q15_t)0x6A51, (q15_t)0x4746,
+	(q15_t)0x6A35, (q15_t)0x4770, (q15_t)0x6A19, (q15_t)0x479A,
+	(q15_t)0x69FD, (q15_t)0x47C3, (q15_t)0x69E1, (q15_t)0x47ED,
+	(q15_t)0x69C4, (q15_t)0x4816, (q15_t)0x69A8, (q15_t)0x4840,
+	(q15_t)0x698C, (q15_t)0x4869, (q15_t)0x696F, (q15_t)0x4893,
+	(q15_t)0x6953, (q15_t)0x48BC, (q15_t)0x6936, (q15_t)0x48E6,
+	(q15_t)0x6919, (q15_t)0x490F, (q15_t)0x68FD, (q15_t)0x4938,
+	(q15_t)0x68E0, (q15_t)0x4961, (q15_t)0x68C3, (q15_t)0x498A,
+	(q15_t)0x68A6, (q15_t)0x49B4, (q15_t)0x6889, (q15_t)0x49DD,
+	(q15_t)0x686C, (q15_t)0x4A06, (q15_t)0x684F, (q15_t)0x4A2F,
+	(q15_t)0x6832, (q15_t)0x4A58, (q15_t)0x6815, (q15_t)0x4A81,
+	(q15_t)0x67F7, (q15_t)0x4AA9, (q15_t)0x67DA, (q15_t)0x4AD2,
+	(q15_t)0x67BD, (q15_t)0x4AFB, (q15_t)0x679F, (q15_t)0x4B24,
+	(q15_t)0x6782, (q15_t)0x4B4C, (q15_t)0x6764, (q15_t)0x4B75,
+	(q15_t)0x6746, (q15_t)0x4B9E, (q15_t)0x6729, (q15_t)0x4BC6,
+	(q15_t)0x670B, (q15_t)0x4BEF, (q15_t)0x66ED, (q15_t)0x4C17,
+	(q15_t)0x66CF, (q15_t)0x4C3F, (q15_t)0x66B1, (q15_t)0x4C68,
+	(q15_t)0x6693, (q15_t)0x4C90, (q15_t)0x6675, (q15_t)0x4CB8,
+	(q15_t)0x6657, (q15_t)0x4CE1, (q15_t)0x6639, (q15_t)0x4D09,
+	(q15_t)0x661A, (q15_t)0x4D31, (q15_t)0x65FC, (q15_t)0x4D59,
+	(q15_t)0x65DD, (q15_t)0x4D81, (q15_t)0x65BF, (q15_t)0x4DA9,
+	(q15_t)0x65A0, (q15_t)0x4DD1, (q15_t)0x6582, (q15_t)0x4DF9,
+	(q15_t)0x6563, (q15_t)0x4E21, (q15_t)0x6545, (q15_t)0x4E48,
+	(q15_t)0x6526, (q15_t)0x4E70, (q15_t)0x6507, (q15_t)0x4E98,
+	(q15_t)0x64E8, (q15_t)0x4EBF, (q15_t)0x64C9, (q15_t)0x4EE7,
+	(q15_t)0x64AA, (q15_t)0x4F0F, (q15_t)0x648B, (q15_t)0x4F36,
+	(q15_t)0x646C, (q15_t)0x4F5E, (q15_t)0x644D, (q15_t)0x4F85,
+	(q15_t)0x642D, (q15_t)0x4FAC, (q15_t)0x640E, (q15_t)0x4FD4,
+	(q15_t)0x63EF, (q15_t)0x4FFB, (q15_t)0x63CF, (q15_t)0x5022,
+	(q15_t)0x63B0, (q15_t)0x5049, (q15_t)0x6390, (q15_t)0x5070,
+	(q15_t)0x6371, (q15_t)0x5097, (q15_t)0x6351, (q15_t)0x50BF,
+	(q15_t)0x6331, (q15_t)0x50E5, (q15_t)0x6311, (q15_t)0x510C,
+	(q15_t)0x62F2, (q15_t)0x5133, (q15_t)0x62D2, (q15_t)0x515A,
+	(q15_t)0x62B2, (q15_t)0x5181, (q15_t)0x6292, (q15_t)0x51A8,
+	(q15_t)0x6271, (q15_t)0x51CE, (q15_t)0x6251, (q15_t)0x51F5,
+	(q15_t)0x6231, (q15_t)0x521C, (q15_t)0x6211, (q15_t)0x5242,
+	(q15_t)0x61F1, (q15_t)0x5269, (q15_t)0x61D0, (q15_t)0x528F,
+	(q15_t)0x61B0, (q15_t)0x52B5, (q15_t)0x618F, (q15_t)0x52DC,
+	(q15_t)0x616F, (q15_t)0x5302, (q15_t)0x614E, (q15_t)0x5328,
+	(q15_t)0x612D, (q15_t)0x534E, (q15_t)0x610D, (q15_t)0x5375,
+	(q15_t)0x60EC, (q15_t)0x539B, (q15_t)0x60CB, (q15_t)0x53C1,
+	(q15_t)0x60AA, (q15_t)0x53E7, (q15_t)0x6089, (q15_t)0x540D,
+	(q15_t)0x6068, (q15_t)0x5433, (q15_t)0x6047, (q15_t)0x5458,
+	(q15_t)0x6026, (q15_t)0x547E, (q15_t)0x6004, (q15_t)0x54A4,
+	(q15_t)0x5FE3, (q15_t)0x54CA, (q15_t)0x5FC2, (q15_t)0x54EF,
+	(q15_t)0x5FA0, (q15_t)0x5515, (q15_t)0x5F7F, (q15_t)0x553A,
+	(q15_t)0x5F5E, (q15_t)0x5560, (q15_t)0x5F3C, (q15_t)0x5585,
+	(q15_t)0x5F1A, (q15_t)0x55AB, (q15_t)0x5EF9, (q15_t)0x55D0,
+	(q15_t)0x5ED7, (q15_t)0x55F5, (q15_t)0x5EB5, (q15_t)0x561A,
+	(q15_t)0x5E93, (q15_t)0x5640, (q15_t)0x5E71, (q15_t)0x5665,
+	(q15_t)0x5E50, (q15_t)0x568A, (q15_t)0x5E2D, (q15_t)0x56AF,
+	(q15_t)0x5E0B, (q15_t)0x56D4, (q15_t)0x5DE9, (q15_t)0x56F9,
+	(q15_t)0x5DC7, (q15_t)0x571D, (q15_t)0x5DA5, (q15_t)0x5742,
+	(q15_t)0x5D83, (q15_t)0x5767, (q15_t)0x5D60, (q15_t)0x578C,
+	(q15_t)0x5D3E, (q15_t)0x57B0, (q15_t)0x5D1B, (q15_t)0x57D5,
+	(q15_t)0x5CF9, (q15_t)0x57F9, (q15_t)0x5CD6, (q15_t)0x581E,
+	(q15_t)0x5CB4, (q15_t)0x5842, (q15_t)0x5C91, (q15_t)0x5867,
+	(q15_t)0x5C6E, (q15_t)0x588B, (q15_t)0x5C4B, (q15_t)0x58AF,
+	(q15_t)0x5C29, (q15_t)0x58D4, (q15_t)0x5C06, (q15_t)0x58F8,
+	(q15_t)0x5BE3, (q15_t)0x591C, (q15_t)0x5BC0, (q15_t)0x5940,
+	(q15_t)0x5B9D, (q15_t)0x5964, (q15_t)0x5B79, (q15_t)0x5988,
+	(q15_t)0x5B56, (q15_t)0x59AC, (q15_t)0x5B33, (q15_t)0x59D0,
+	(q15_t)0x5B10, (q15_t)0x59F3, (q15_t)0x5AEC, (q15_t)0x5A17,
+	(q15_t)0x5AC9, (q15_t)0x5A3B, (q15_t)0x5AA5, (q15_t)0x5A5E,
+	(q15_t)0x5A82, (q15_t)0x5A82, (q15_t)0x5A5E, (q15_t)0x5AA5,
+	(q15_t)0x5A3B, (q15_t)0x5AC9, (q15_t)0x5A17, (q15_t)0x5AEC,
+	(q15_t)0x59F3, (q15_t)0x5B10, (q15_t)0x59D0, (q15_t)0x5B33,
+	(q15_t)0x59AC, (q15_t)0x5B56, (q15_t)0x5988, (q15_t)0x5B79,
+	(q15_t)0x5964, (q15_t)0x5B9D, (q15_t)0x5940, (q15_t)0x5BC0,
+	(q15_t)0x591C, (q15_t)0x5BE3, (q15_t)0x58F8, (q15_t)0x5C06,
+	(q15_t)0x58D4, (q15_t)0x5C29, (q15_t)0x58AF, (q15_t)0x5C4B,
+	(q15_t)0x588B, (q15_t)0x5C6E, (q15_t)0x5867, (q15_t)0x5C91,
+	(q15_t)0x5842, (q15_t)0x5CB4, (q15_t)0x581E, (q15_t)0x5CD6,
+	(q15_t)0x57F9, (q15_t)0x5CF9, (q15_t)0x57D5, (q15_t)0x5D1B,
+	(q15_t)0x57B0, (q15_t)0x5D3E, (q15_t)0x578C, (q15_t)0x5D60,
+	(q15_t)0x5767, (q15_t)0x5D83, (q15_t)0x5742, (q15_t)0x5DA5,
+	(q15_t)0x571D, (q15_t)0x5DC7, (q15_t)0x56F9, (q15_t)0x5DE9,
+	(q15_t)0x56D4, (q15_t)0x5E0B, (q15_t)0x56AF, (q15_t)0x5E2D,
+	(q15_t)0x568A, (q15_t)0x5E50, (q15_t)0x5665, (q15_t)0x5E71,
+	(q15_t)0x5640, (q15_t)0x5E93, (q15_t)0x561A, (q15_t)0x5EB5,
+	(q15_t)0x55F5, (q15_t)0x5ED7, (q15_t)0x55D0, (q15_t)0x5EF9,
+	(q15_t)0x55AB, (q15_t)0x5F1A, (q15_t)0x5585, (q15_t)0x5F3C,
+	(q15_t)0x5560, (q15_t)0x5F5E, (q15_t)0x553A, (q15_t)0x5F7F,
+	(q15_t)0x5515, (q15_t)0x5FA0, (q15_t)0x54EF, (q15_t)0x5FC2,
+	(q15_t)0x54CA, (q15_t)0x5FE3, (q15_t)0x54A4, (q15_t)0x6004,
+	(q15_t)0x547E, (q15_t)0x6026, (q15_t)0x5458, (q15_t)0x6047,
+	(q15_t)0x5433, (q15_t)0x6068, (q15_t)0x540D, (q15_t)0x6089,
+	(q15_t)0x53E7, (q15_t)0x60AA, (q15_t)0x53C1, (q15_t)0x60CB,
+	(q15_t)0x539B, (q15_t)0x60EC, (q15_t)0x5375, (q15_t)0x610D,
+	(q15_t)0x534E, (q15_t)0x612D, (q15_t)0x5328, (q15_t)0x614E,
+	(q15_t)0x5302, (q15_t)0x616F, (q15_t)0x52DC, (q15_t)0x618F,
+	(q15_t)0x52B5, (q15_t)0x61B0, (q15_t)0x528F, (q15_t)0x61D0,
+	(q15_t)0x5269, (q15_t)0x61F1, (q15_t)0x5242, (q15_t)0x6211,
+	(q15_t)0x521C, (q15_t)0x6231, (q15_t)0x51F5, (q15_t)0x6251,
+	(q15_t)0x51CE, (q15_t)0x6271, (q15_t)0x51A8, (q15_t)0x6292,
+	(q15_t)0x5181, (q15_t)0x62B2, (q15_t)0x515A, (q15_t)0x62D2,
+	(q15_t)0x5133, (q15_t)0x62F2, (q15_t)0x510C, (q15_t)0x6311,
+	(q15_t)0x50E5, (q15_t)0x6331, (q15_t)0x50BF, (q15_t)0x6351,
+	(q15_t)0x5097, (q15_t)0x6371, (q15_t)0x5070, (q15_t)0x6390,
+	(q15_t)0x5049, (q15_t)0x63B0, (q15_t)0x5022, (q15_t)0x63CF,
+	(q15_t)0x4FFB, (q15_t)0x63EF, (q15_t)0x4FD4, (q15_t)0x640E,
+	(q15_t)0x4FAC, (q15_t)0x642D, (q15_t)0x4F85, (q15_t)0x644D,
+	(q15_t)0x4F5E, (q15_t)0x646C, (q15_t)0x4F36, (q15_t)0x648B,
+	(q15_t)0x4F0F, (q15_t)0x64AA, (q15_t)0x4EE7, (q15_t)0x64C9,
+	(q15_t)0x4EBF, (q15_t)0x64E8, (q15_t)0x4E98, (q15_t)0x6507,
+	(q15_t)0x4E70, (q15_t)0x6526, (q15_t)0x4E48, (q15_t)0x6545,
+	(q15_t)0x4E21, (q15_t)0x6563, (q15_t)0x4DF9, (q15_t)0x6582,
+	(q15_t)0x4DD1, (q15_t)0x65A0, (q15_t)0x4DA9, (q15_t)0x65BF,
+	(q15_t)0x4D81, (q15_t)0x65DD, (q15_t)0x4D59, (q15_t)0x65FC,
+	(q15_t)0x4D31, (q15_t)0x661A, (q15_t)0x4D09, (q15_t)0x6639,
+	(q15_t)0x4CE1, (q15_t)0x6657, (q15_t)0x4CB8, (q15_t)0x6675,
+	(q15_t)0x4C90, (q15_t)0x6693, (q15_t)0x4C68, (q15_t)0x66B1,
+	(q15_t)0x4C3F, (q15_t)0x66CF, (q15_t)0x4C17, (q15_t)0x66ED,
+	(q15_t)0x4BEF, (q15_t)0x670B, (q15_t)0x4BC6, (q15_t)0x6729,
+	(q15_t)0x4B9E, (q15_t)0x6746, (q15_t)0x4B75, (q15_t)0x6764,
+	(q15_t)0x4B4C, (q15_t)0x6782, (q15_t)0x4B24, (q15_t)0x679F,
+	(q15_t)0x4AFB, (q15_t)0x67BD, (q15_t)0x4AD2, (q15_t)0x67DA,
+	(q15_t)0x4AA9, (q15_t)0x67F7, (q15_t)0x4A81, (q15_t)0x6815,
+	(q15_t)0x4A58, (q15_t)0x6832, (q15_t)0x4A2F, (q15_t)0x684F,
+	(q15_t)0x4A06, (q15_t)0x686C, (q15_t)0x49DD, (q15_t)0x6889,
+	(q15_t)0x49B4, (q15_t)0x68A6, (q15_t)0x498A, (q15_t)0x68C3,
+	(q15_t)0x4961, (q15_t)0x68E0, (q15_t)0x4938, (q15_t)0x68FD,
+	(q15_t)0x490F, (q15_t)0x6919, (q15_t)0x48E6, (q15_t)0x6936,
+	(q15_t)0x48BC, (q15_t)0x6953, (q15_t)0x4893, (q15_t)0x696F,
+	(q15_t)0x4869, (q15_t)0x698C, (q15_t)0x4840, (q15_t)0x69A8,
+	(q15_t)0x4816, (q15_t)0x69C4, (q15_t)0x47ED, (q15_t)0x69E1,
+	(q15_t)0x47C3, (q15_t)0x69FD, (q15_t)0x479A, (q15_t)0x6A19,
+	(q15_t)0x4770, (q15_t)0x6A35, (q15_t)0x4746, (q15_t)0x6A51,
+	(q15_t)0x471C, (q15_t)0x6A6D, (q15_t)0x46F3, (q15_t)0x6A89,
+	(q15_t)0x46C9, (q15_t)0x6AA5, (q15_t)0x469F, (q15_t)0x6AC1,
+	(q15_t)0x4675, (q15_t)0x6ADC, (q15_t)0x464B, (q15_t)0x6AF8,
+	(q15_t)0x4621, (q15_t)0x6B13, (q15_t)0x45F7, (q15_t)0x6B2F,
+	(q15_t)0x45CD, (q15_t)0x6B4A, (q15_t)0x45A3, (q15_t)0x6B66,
+	(q15_t)0x4578, (q15_t)0x6B81, (q15_t)0x454E, (q15_t)0x6B9C,
+	(q15_t)0x4524, (q15_t)0x6BB8, (q15_t)0x44FA, (q15_t)0x6BD3,
+	(q15_t)0x44CF, (q15_t)0x6BEE, (q15_t)0x44A5, (q15_t)0x6C09,
+	(q15_t)0x447A, (q15_t)0x6C24, (q15_t)0x4450, (q15_t)0x6C3F,
+	(q15_t)0x4425, (q15_t)0x6C59, (q15_t)0x43FB, (q15_t)0x6C74,
+	(q15_t)0x43D0, (q15_t)0x6C8F, (q15_t)0x43A5, (q15_t)0x6CA9,
+	(q15_t)0x437B, (q15_t)0x6CC4, (q15_t)0x4350, (q15_t)0x6CDE,
+	(q15_t)0x4325, (q15_t)0x6CF9, (q15_t)0x42FA, (q15_t)0x6D13,
+	(q15_t)0x42D0, (q15_t)0x6D2D, (q15_t)0x42A5, (q15_t)0x6D48,
+	(q15_t)0x427A, (q15_t)0x6D62, (q15_t)0x424F, (q15_t)0x6D7C,
+	(q15_t)0x4224, (q15_t)0x6D96, (q15_t)0x41F9, (q15_t)0x6DB0,
+	(q15_t)0x41CE, (q15_t)0x6DCA, (q15_t)0x41A2, (q15_t)0x6DE3,
+	(q15_t)0x4177, (q15_t)0x6DFD, (q15_t)0x414C, (q15_t)0x6E17,
+	(q15_t)0x4121, (q15_t)0x6E30, (q15_t)0x40F6, (q15_t)0x6E4A,
+	(q15_t)0x40CA, (q15_t)0x6E63, (q15_t)0x409F, (q15_t)0x6E7D,
+	(q15_t)0x4073, (q15_t)0x6E96, (q15_t)0x4048, (q15_t)0x6EAF,
+	(q15_t)0x401D, (q15_t)0x6EC9, (q15_t)0x3FF1, (q15_t)0x6EE2,
+	(q15_t)0x3FC5, (q15_t)0x6EFB, (q15_t)0x3F9A, (q15_t)0x6F14,
+	(q15_t)0x3F6E, (q15_t)0x6F2D, (q15_t)0x3F43, (q15_t)0x6F46,
+	(q15_t)0x3F17, (q15_t)0x6F5F, (q15_t)0x3EEB, (q15_t)0x6F77,
+	(q15_t)0x3EBF, (q15_t)0x6F90, (q15_t)0x3E93, (q15_t)0x6FA9,
+	(q15_t)0x3E68, (q15_t)0x6FC1, (q15_t)0x3E3C, (q15_t)0x6FDA,
+	(q15_t)0x3E10, (q15_t)0x6FF2, (q15_t)0x3DE4, (q15_t)0x700A,
+	(q15_t)0x3DB8, (q15_t)0x7023, (q15_t)0x3D8C, (q15_t)0x703B,
+	(q15_t)0x3D60, (q15_t)0x7053, (q15_t)0x3D33, (q15_t)0x706B,
+	(q15_t)0x3D07, (q15_t)0x7083, (q15_t)0x3CDB, (q15_t)0x709B,
+	(q15_t)0x3CAF, (q15_t)0x70B3, (q15_t)0x3C83, (q15_t)0x70CB,
+	(q15_t)0x3C56, (q15_t)0x70E2, (q15_t)0x3C2A, (q15_t)0x70FA,
+	(q15_t)0x3BFD, (q15_t)0x7112, (q15_t)0x3BD1, (q15_t)0x7129,
+	(q15_t)0x3BA5, (q15_t)0x7141, (q15_t)0x3B78, (q15_t)0x7158,
+	(q15_t)0x3B4C, (q15_t)0x716F, (q15_t)0x3B1F, (q15_t)0x7186,
+	(q15_t)0x3AF2, (q15_t)0x719E, (q15_t)0x3AC6, (q15_t)0x71B5,
+	(q15_t)0x3A99, (q15_t)0x71CC, (q15_t)0x3A6C, (q15_t)0x71E3,
+	(q15_t)0x3A40, (q15_t)0x71FA, (q15_t)0x3A13, (q15_t)0x7211,
+	(q15_t)0x39E6, (q15_t)0x7227, (q15_t)0x39B9, (q15_t)0x723E,
+	(q15_t)0x398C, (q15_t)0x7255, (q15_t)0x395F, (q15_t)0x726B,
+	(q15_t)0x3932, (q15_t)0x7282, (q15_t)0x3906, (q15_t)0x7298,
+	(q15_t)0x38D8, (q15_t)0x72AF, (q15_t)0x38AB, (q15_t)0x72C5,
+	(q15_t)0x387E, (q15_t)0x72DB, (q15_t)0x3851, (q15_t)0x72F1,
+	(q15_t)0x3824, (q15_t)0x7307, (q15_t)0x37F7, (q15_t)0x731D,
+	(q15_t)0x37CA, (q15_t)0x7333, (q15_t)0x379C, (q15_t)0x7349,
+	(q15_t)0x376F, (q15_t)0x735F, (q15_t)0x3742, (q15_t)0x7375,
+	(q15_t)0x3714, (q15_t)0x738A, (q15_t)0x36E7, (q15_t)0x73A0,
+	(q15_t)0x36BA, (q15_t)0x73B5, (q15_t)0x368C, (q15_t)0x73CB,
+	(q15_t)0x365F, (q15_t)0x73E0, (q15_t)0x3631, (q15_t)0x73F6,
+	(q15_t)0x3604, (q15_t)0x740B, (q15_t)0x35D6, (q15_t)0x7420,
+	(q15_t)0x35A8, (q15_t)0x7435, (q15_t)0x357B, (q15_t)0x744A,
+	(q15_t)0x354D, (q15_t)0x745F, (q15_t)0x351F, (q15_t)0x7474,
+	(q15_t)0x34F2, (q15_t)0x7489, (q15_t)0x34C4, (q15_t)0x749E,
+	(q15_t)0x3496, (q15_t)0x74B2, (q15_t)0x3468, (q15_t)0x74C7,
+	(q15_t)0x343A, (q15_t)0x74DB, (q15_t)0x340C, (q15_t)0x74F0,
+	(q15_t)0x33DE, (q15_t)0x7504, (q15_t)0x33B0, (q15_t)0x7519,
+	(q15_t)0x3382, (q15_t)0x752D, (q15_t)0x3354, (q15_t)0x7541,
+	(q15_t)0x3326, (q15_t)0x7555, (q15_t)0x32F8, (q15_t)0x7569,
+	(q15_t)0x32CA, (q15_t)0x757D, (q15_t)0x329C, (q15_t)0x7591,
+	(q15_t)0x326E, (q15_t)0x75A5, (q15_t)0x3240, (q15_t)0x75B9,
+	(q15_t)0x3211, (q15_t)0x75CC, (q15_t)0x31E3, (q15_t)0x75E0,
+	(q15_t)0x31B5, (q15_t)0x75F4, (q15_t)0x3186, (q15_t)0x7607,
+	(q15_t)0x3158, (q15_t)0x761B, (q15_t)0x312A, (q15_t)0x762E,
+	(q15_t)0x30FB, (q15_t)0x7641, (q15_t)0x30CD, (q15_t)0x7654,
+	(q15_t)0x309E, (q15_t)0x7668, (q15_t)0x3070, (q15_t)0x767B,
+	(q15_t)0x3041, (q15_t)0x768E, (q15_t)0x3013, (q15_t)0x76A0,
+	(q15_t)0x2FE4, (q15_t)0x76B3, (q15_t)0x2FB5, (q15_t)0x76C6,
+	(q15_t)0x2F87, (q15_t)0x76D9, (q15_t)0x2F58, (q15_t)0x76EB,
+	(q15_t)0x2F29, (q15_t)0x76FE, (q15_t)0x2EFB, (q15_t)0x7710,
+	(q15_t)0x2ECC, (q15_t)0x7723, (q15_t)0x2E9D, (q15_t)0x7735,
+	(q15_t)0x2E6E, (q15_t)0x7747, (q15_t)0x2E3F, (q15_t)0x775A,
+	(q15_t)0x2E11, (q15_t)0x776C, (q15_t)0x2DE2, (q15_t)0x777E,
+	(q15_t)0x2DB3, (q15_t)0x7790, (q15_t)0x2D84, (q15_t)0x77A2,
+	(q15_t)0x2D55, (q15_t)0x77B4, (q15_t)0x2D26, (q15_t)0x77C5,
+	(q15_t)0x2CF7, (q15_t)0x77D7, (q15_t)0x2CC8, (q15_t)0x77E9,
+	(q15_t)0x2C98, (q15_t)0x77FA, (q15_t)0x2C69, (q15_t)0x780C,
+	(q15_t)0x2C3A, (q15_t)0x781D, (q15_t)0x2C0B, (q15_t)0x782E,
+	(q15_t)0x2BDC, (q15_t)0x7840, (q15_t)0x2BAD, (q15_t)0x7851,
+	(q15_t)0x2B7D, (q15_t)0x7862, (q15_t)0x2B4E, (q15_t)0x7873,
+	(q15_t)0x2B1F, (q15_t)0x7884, (q15_t)0x2AEF, (q15_t)0x7895,
+	(q15_t)0x2AC0, (q15_t)0x78A6, (q15_t)0x2A91, (q15_t)0x78B6,
+	(q15_t)0x2A61, (q15_t)0x78C7, (q15_t)0x2A32, (q15_t)0x78D8,
+	(q15_t)0x2A02, (q15_t)0x78E8, (q15_t)0x29D3, (q15_t)0x78F9,
+	(q15_t)0x29A3, (q15_t)0x7909, (q15_t)0x2974, (q15_t)0x7919,
+	(q15_t)0x2944, (q15_t)0x792A, (q15_t)0x2915, (q15_t)0x793A,
+	(q15_t)0x28E5, (q15_t)0x794A, (q15_t)0x28B5, (q15_t)0x795A,
+	(q15_t)0x2886, (q15_t)0x796A, (q15_t)0x2856, (q15_t)0x797A,
+	(q15_t)0x2826, (q15_t)0x798A, (q15_t)0x27F6, (q15_t)0x7999,
+	(q15_t)0x27C7, (q15_t)0x79A9, (q15_t)0x2797, (q15_t)0x79B9,
+	(q15_t)0x2767, (q15_t)0x79C8, (q15_t)0x2737, (q15_t)0x79D8,
+	(q15_t)0x2707, (q15_t)0x79E7, (q15_t)0x26D8, (q15_t)0x79F6,
+	(q15_t)0x26A8, (q15_t)0x7A05, (q15_t)0x2678, (q15_t)0x7A15,
+	(q15_t)0x2648, (q15_t)0x7A24, (q15_t)0x2618, (q15_t)0x7A33,
+	(q15_t)0x25E8, (q15_t)0x7A42, (q15_t)0x25B8, (q15_t)0x7A50,
+	(q15_t)0x2588, (q15_t)0x7A5F, (q15_t)0x2558, (q15_t)0x7A6E,
+	(q15_t)0x2528, (q15_t)0x7A7D, (q15_t)0x24F7, (q15_t)0x7A8B,
+	(q15_t)0x24C7, (q15_t)0x7A9A, (q15_t)0x2497, (q15_t)0x7AA8,
+	(q15_t)0x2467, (q15_t)0x7AB6, (q15_t)0x2437, (q15_t)0x7AC5,
+	(q15_t)0x2407, (q15_t)0x7AD3, (q15_t)0x23D6, (q15_t)0x7AE1,
+	(q15_t)0x23A6, (q15_t)0x7AEF, (q15_t)0x2376, (q15_t)0x7AFD,
+	(q15_t)0x2345, (q15_t)0x7B0B, (q15_t)0x2315, (q15_t)0x7B19,
+	(q15_t)0x22E5, (q15_t)0x7B26, (q15_t)0x22B4, (q15_t)0x7B34,
+	(q15_t)0x2284, (q15_t)0x7B42, (q15_t)0x2254, (q15_t)0x7B4F,
+	(q15_t)0x2223, (q15_t)0x7B5D, (q15_t)0x21F3, (q15_t)0x7B6A,
+	(q15_t)0x21C2, (q15_t)0x7B77, (q15_t)0x2192, (q15_t)0x7B84,
+	(q15_t)0x2161, (q15_t)0x7B92, (q15_t)0x2131, (q15_t)0x7B9F,
+	(q15_t)0x2100, (q15_t)0x7BAC, (q15_t)0x20D0, (q15_t)0x7BB9,
+	(q15_t)0x209F, (q15_t)0x7BC5, (q15_t)0x206E, (q15_t)0x7BD2,
+	(q15_t)0x203E, (q15_t)0x7BDF, (q15_t)0x200D, (q15_t)0x7BEB,
+	(q15_t)0x1FDC, (q15_t)0x7BF8, (q15_t)0x1FAC, (q15_t)0x7C05,
+	(q15_t)0x1F7B, (q15_t)0x7C11, (q15_t)0x1F4A, (q15_t)0x7C1D,
+	(q15_t)0x1F19, (q15_t)0x7C29, (q15_t)0x1EE9, (q15_t)0x7C36,
+	(q15_t)0x1EB8, (q15_t)0x7C42, (q15_t)0x1E87, (q15_t)0x7C4E,
+	(q15_t)0x1E56, (q15_t)0x7C5A, (q15_t)0x1E25, (q15_t)0x7C66,
+	(q15_t)0x1DF5, (q15_t)0x7C71, (q15_t)0x1DC4, (q15_t)0x7C7D,
+	(q15_t)0x1D93, (q15_t)0x7C89, (q15_t)0x1D62, (q15_t)0x7C94,
+	(q15_t)0x1D31, (q15_t)0x7CA0, (q15_t)0x1D00, (q15_t)0x7CAB,
+	(q15_t)0x1CCF, (q15_t)0x7CB7, (q15_t)0x1C9E, (q15_t)0x7CC2,
+	(q15_t)0x1C6D, (q15_t)0x7CCD, (q15_t)0x1C3C, (q15_t)0x7CD8,
+	(q15_t)0x1C0B, (q15_t)0x7CE3, (q15_t)0x1BDA, (q15_t)0x7CEE,
+	(q15_t)0x1BA9, (q15_t)0x7CF9, (q15_t)0x1B78, (q15_t)0x7D04,
+	(q15_t)0x1B47, (q15_t)0x7D0F, (q15_t)0x1B16, (q15_t)0x7D19,
+	(q15_t)0x1AE4, (q15_t)0x7D24, (q15_t)0x1AB3, (q15_t)0x7D2F,
+	(q15_t)0x1A82, (q15_t)0x7D39, (q15_t)0x1A51, (q15_t)0x7D43,
+	(q15_t)0x1A20, (q15_t)0x7D4E, (q15_t)0x19EF, (q15_t)0x7D58,
+	(q15_t)0x19BD, (q15_t)0x7D62, (q15_t)0x198C, (q15_t)0x7D6C,
+	(q15_t)0x195B, (q15_t)0x7D76, (q15_t)0x192A, (q15_t)0x7D80,
+	(q15_t)0x18F8, (q15_t)0x7D8A, (q15_t)0x18C7, (q15_t)0x7D94,
+	(q15_t)0x1896, (q15_t)0x7D9D, (q15_t)0x1864, (q15_t)0x7DA7,
+	(q15_t)0x1833, (q15_t)0x7DB0, (q15_t)0x1802, (q15_t)0x7DBA,
+	(q15_t)0x17D0, (q15_t)0x7DC3, (q15_t)0x179F, (q15_t)0x7DCD,
+	(q15_t)0x176D, (q15_t)0x7DD6, (q15_t)0x173C, (q15_t)0x7DDF,
+	(q15_t)0x170A, (q15_t)0x7DE8, (q15_t)0x16D9, (q15_t)0x7DF1,
+	(q15_t)0x16A8, (q15_t)0x7DFA, (q15_t)0x1676, (q15_t)0x7E03,
+	(q15_t)0x1645, (q15_t)0x7E0C, (q15_t)0x1613, (q15_t)0x7E14,
+	(q15_t)0x15E2, (q15_t)0x7E1D, (q15_t)0x15B0, (q15_t)0x7E26,
+	(q15_t)0x157F, (q15_t)0x7E2E, (q15_t)0x154D, (q15_t)0x7E37,
+	(q15_t)0x151B, (q15_t)0x7E3F, (q15_t)0x14EA, (q15_t)0x7E47,
+	(q15_t)0x14B8, (q15_t)0x7E4F, (q15_t)0x1487, (q15_t)0x7E57,
+	(q15_t)0x1455, (q15_t)0x7E5F, (q15_t)0x1423, (q15_t)0x7E67,
+	(q15_t)0x13F2, (q15_t)0x7E6F, (q15_t)0x13C0, (q15_t)0x7E77,
+	(q15_t)0x138E, (q15_t)0x7E7F, (q15_t)0x135D, (q15_t)0x7E86,
+	(q15_t)0x132B, (q15_t)0x7E8E, (q15_t)0x12F9, (q15_t)0x7E95,
+	(q15_t)0x12C8, (q15_t)0x7E9D, (q15_t)0x1296, (q15_t)0x7EA4,
+	(q15_t)0x1264, (q15_t)0x7EAB, (q15_t)0x1232, (q15_t)0x7EB3,
+	(q15_t)0x1201, (q15_t)0x7EBA, (q15_t)0x11CF, (q15_t)0x7EC1,
+	(q15_t)0x119D, (q15_t)0x7EC8, (q15_t)0x116B, (q15_t)0x7ECF,
+	(q15_t)0x1139, (q15_t)0x7ED5, (q15_t)0x1108, (q15_t)0x7EDC,
+	(q15_t)0x10D6, (q15_t)0x7EE3, (q15_t)0x10A4, (q15_t)0x7EE9,
+	(q15_t)0x1072, (q15_t)0x7EF0, (q15_t)0x1040, (q15_t)0x7EF6,
+	(q15_t)0x100E, (q15_t)0x7EFD, (q15_t)0x0FDD, (q15_t)0x7F03,
+	(q15_t)0x0FAB, (q15_t)0x7F09, (q15_t)0x0F79, (q15_t)0x7F0F,
+	(q15_t)0x0F47, (q15_t)0x7F15, (q15_t)0x0F15, (q15_t)0x7F1B,
+	(q15_t)0x0EE3, (q15_t)0x7F21, (q15_t)0x0EB1, (q15_t)0x7F27,
+	(q15_t)0x0E7F, (q15_t)0x7F2D, (q15_t)0x0E4D, (q15_t)0x7F32,
+	(q15_t)0x0E1B, (q15_t)0x7F38, (q15_t)0x0DE9, (q15_t)0x7F3D,
+	(q15_t)0x0DB7, (q15_t)0x7F43, (q15_t)0x0D85, (q15_t)0x7F48,
+	(q15_t)0x0D53, (q15_t)0x7F4D, (q15_t)0x0D21, (q15_t)0x7F53,
+	(q15_t)0x0CEF, (q15_t)0x7F58, (q15_t)0x0CBD, (q15_t)0x7F5D,
+	(q15_t)0x0C8B, (q15_t)0x7F62, (q15_t)0x0C59, (q15_t)0x7F67,
+	(q15_t)0x0C27, (q15_t)0x7F6B, (q15_t)0x0BF5, (q15_t)0x7F70,
+	(q15_t)0x0BC3, (q15_t)0x7F75, (q15_t)0x0B91, (q15_t)0x7F79,
+	(q15_t)0x0B5F, (q15_t)0x7F7E, (q15_t)0x0B2D, (q15_t)0x7F82,
+	(q15_t)0x0AFB, (q15_t)0x7F87, (q15_t)0x0AC9, (q15_t)0x7F8B,
+	(q15_t)0x0A97, (q15_t)0x7F8F, (q15_t)0x0A65, (q15_t)0x7F93,
+	(q15_t)0x0A33, (q15_t)0x7F97, (q15_t)0x0A00, (q15_t)0x7F9B,
+	(q15_t)0x09CE, (q15_t)0x7F9F, (q15_t)0x099C, (q15_t)0x7FA3,
+	(q15_t)0x096A, (q15_t)0x7FA7, (q15_t)0x0938, (q15_t)0x7FAA,
+	(q15_t)0x0906, (q15_t)0x7FAE, (q15_t)0x08D4, (q15_t)0x7FB1,
+	(q15_t)0x08A2, (q15_t)0x7FB5, (q15_t)0x086F, (q15_t)0x7FB8,
+	(q15_t)0x083D, (q15_t)0x7FBC, (q15_t)0x080B, (q15_t)0x7FBF,
+	(q15_t)0x07D9, (q15_t)0x7FC2, (q15_t)0x07A7, (q15_t)0x7FC5,
+	(q15_t)0x0775, (q15_t)0x7FC8, (q15_t)0x0742, (q15_t)0x7FCB,
+	(q15_t)0x0710, (q15_t)0x7FCE, (q15_t)0x06DE, (q15_t)0x7FD0,
+	(q15_t)0x06AC, (q15_t)0x7FD3, (q15_t)0x067A, (q15_t)0x7FD6,
+	(q15_t)0x0647, (q15_t)0x7FD8, (q15_t)0x0615, (q15_t)0x7FDA,
+	(q15_t)0x05E3, (q15_t)0x7FDD, (q15_t)0x05B1, (q15_t)0x7FDF,
+	(q15_t)0x057F, (q15_t)0x7FE1, (q15_t)0x054C, (q15_t)0x7FE3,
+	(q15_t)0x051A, (q15_t)0x7FE5, (q15_t)0x04E8, (q15_t)0x7FE7,
+	(q15_t)0x04B6, (q15_t)0x7FE9, (q15_t)0x0483, (q15_t)0x7FEB,
+	(q15_t)0x0451, (q15_t)0x7FED, (q15_t)0x041F, (q15_t)0x7FEE,
+	(q15_t)0x03ED, (q15_t)0x7FF0, (q15_t)0x03BA, (q15_t)0x7FF2,
+	(q15_t)0x0388, (q15_t)0x7FF3, (q15_t)0x0356, (q15_t)0x7FF4,
+	(q15_t)0x0324, (q15_t)0x7FF6, (q15_t)0x02F1, (q15_t)0x7FF7,
+	(q15_t)0x02BF, (q15_t)0x7FF8, (q15_t)0x028D, (q15_t)0x7FF9,
+	(q15_t)0x025B, (q15_t)0x7FFA, (q15_t)0x0228, (q15_t)0x7FFB,
+	(q15_t)0x01F6, (q15_t)0x7FFC, (q15_t)0x01C4, (q15_t)0x7FFC,
+	(q15_t)0x0192, (q15_t)0x7FFD, (q15_t)0x015F, (q15_t)0x7FFE,
+	(q15_t)0x012D, (q15_t)0x7FFE, (q15_t)0x00FB, (q15_t)0x7FFF,
+	(q15_t)0x00C9, (q15_t)0x7FFF, (q15_t)0x0096, (q15_t)0x7FFF,
+	(q15_t)0x0064, (q15_t)0x7FFF, (q15_t)0x0032, (q15_t)0x7FFF,
+	(q15_t)0x0000, (q15_t)0x7FFF, (q15_t)0xFFCD, (q15_t)0x7FFF,
+	(q15_t)0xFF9B, (q15_t)0x7FFF, (q15_t)0xFF69, (q15_t)0x7FFF,
+	(q15_t)0xFF36, (q15_t)0x7FFF, (q15_t)0xFF04, (q15_t)0x7FFF,
+	(q15_t)0xFED2, (q15_t)0x7FFE, (q15_t)0xFEA0, (q15_t)0x7FFE,
+	(q15_t)0xFE6D, (q15_t)0x7FFD, (q15_t)0xFE3B, (q15_t)0x7FFC,
+	(q15_t)0xFE09, (q15_t)0x7FFC, (q15_t)0xFDD7, (q15_t)0x7FFB,
+	(q15_t)0xFDA4, (q15_t)0x7FFA, (q15_t)0xFD72, (q15_t)0x7FF9,
+	(q15_t)0xFD40, (q15_t)0x7FF8, (q15_t)0xFD0E, (q15_t)0x7FF7,
+	(q15_t)0xFCDB, (q15_t)0x7FF6, (q15_t)0xFCA9, (q15_t)0x7FF4,
+	(q15_t)0xFC77, (q15_t)0x7FF3, (q15_t)0xFC45, (q15_t)0x7FF2,
+	(q15_t)0xFC12, (q15_t)0x7FF0, (q15_t)0xFBE0, (q15_t)0x7FEE,
+	(q15_t)0xFBAE, (q15_t)0x7FED, (q15_t)0xFB7C, (q15_t)0x7FEB,
+	(q15_t)0xFB49, (q15_t)0x7FE9, (q15_t)0xFB17, (q15_t)0x7FE7,
+	(q15_t)0xFAE5, (q15_t)0x7FE5, (q15_t)0xFAB3, (q15_t)0x7FE3,
+	(q15_t)0xFA80, (q15_t)0x7FE1, (q15_t)0xFA4E, (q15_t)0x7FDF,
+	(q15_t)0xFA1C, (q15_t)0x7FDD, (q15_t)0xF9EA, (q15_t)0x7FDA,
+	(q15_t)0xF9B8, (q15_t)0x7FD8, (q15_t)0xF985, (q15_t)0x7FD6,
+	(q15_t)0xF953, (q15_t)0x7FD3, (q15_t)0xF921, (q15_t)0x7FD0,
+	(q15_t)0xF8EF, (q15_t)0x7FCE, (q15_t)0xF8BD, (q15_t)0x7FCB,
+	(q15_t)0xF88A, (q15_t)0x7FC8, (q15_t)0xF858, (q15_t)0x7FC5,
+	(q15_t)0xF826, (q15_t)0x7FC2, (q15_t)0xF7F4, (q15_t)0x7FBF,
+	(q15_t)0xF7C2, (q15_t)0x7FBC, (q15_t)0xF790, (q15_t)0x7FB8,
+	(q15_t)0xF75D, (q15_t)0x7FB5, (q15_t)0xF72B, (q15_t)0x7FB1,
+	(q15_t)0xF6F9, (q15_t)0x7FAE, (q15_t)0xF6C7, (q15_t)0x7FAA,
+	(q15_t)0xF695, (q15_t)0x7FA7, (q15_t)0xF663, (q15_t)0x7FA3,
+	(q15_t)0xF631, (q15_t)0x7F9F, (q15_t)0xF5FF, (q15_t)0x7F9B,
+	(q15_t)0xF5CC, (q15_t)0x7F97, (q15_t)0xF59A, (q15_t)0x7F93,
+	(q15_t)0xF568, (q15_t)0x7F8F, (q15_t)0xF536, (q15_t)0x7F8B,
+	(q15_t)0xF504, (q15_t)0x7F87, (q15_t)0xF4D2, (q15_t)0x7F82,
+	(q15_t)0xF4A0, (q15_t)0x7F7E, (q15_t)0xF46E, (q15_t)0x7F79,
+	(q15_t)0xF43C, (q15_t)0x7F75, (q15_t)0xF40A, (q15_t)0x7F70,
+	(q15_t)0xF3D8, (q15_t)0x7F6B, (q15_t)0xF3A6, (q15_t)0x7F67,
+	(q15_t)0xF374, (q15_t)0x7F62, (q15_t)0xF342, (q15_t)0x7F5D,
+	(q15_t)0xF310, (q15_t)0x7F58, (q15_t)0xF2DE, (q15_t)0x7F53,
+	(q15_t)0xF2AC, (q15_t)0x7F4D, (q15_t)0xF27A, (q15_t)0x7F48,
+	(q15_t)0xF248, (q15_t)0x7F43, (q15_t)0xF216, (q15_t)0x7F3D,
+	(q15_t)0xF1E4, (q15_t)0x7F38, (q15_t)0xF1B2, (q15_t)0x7F32,
+	(q15_t)0xF180, (q15_t)0x7F2D, (q15_t)0xF14E, (q15_t)0x7F27,
+	(q15_t)0xF11C, (q15_t)0x7F21, (q15_t)0xF0EA, (q15_t)0x7F1B,
+	(q15_t)0xF0B8, (q15_t)0x7F15, (q15_t)0xF086, (q15_t)0x7F0F,
+	(q15_t)0xF054, (q15_t)0x7F09, (q15_t)0xF022, (q15_t)0x7F03,
+	(q15_t)0xEFF1, (q15_t)0x7EFD, (q15_t)0xEFBF, (q15_t)0x7EF6,
+	(q15_t)0xEF8D, (q15_t)0x7EF0, (q15_t)0xEF5B, (q15_t)0x7EE9,
+	(q15_t)0xEF29, (q15_t)0x7EE3, (q15_t)0xEEF7, (q15_t)0x7EDC,
+	(q15_t)0xEEC6, (q15_t)0x7ED5, (q15_t)0xEE94, (q15_t)0x7ECF,
+	(q15_t)0xEE62, (q15_t)0x7EC8, (q15_t)0xEE30, (q15_t)0x7EC1,
+	(q15_t)0xEDFE, (q15_t)0x7EBA, (q15_t)0xEDCD, (q15_t)0x7EB3,
+	(q15_t)0xED9B, (q15_t)0x7EAB, (q15_t)0xED69, (q15_t)0x7EA4,
+	(q15_t)0xED37, (q15_t)0x7E9D, (q15_t)0xED06, (q15_t)0x7E95,
+	(q15_t)0xECD4, (q15_t)0x7E8E, (q15_t)0xECA2, (q15_t)0x7E86,
+	(q15_t)0xEC71, (q15_t)0x7E7F, (q15_t)0xEC3F, (q15_t)0x7E77,
+	(q15_t)0xEC0D, (q15_t)0x7E6F, (q15_t)0xEBDC, (q15_t)0x7E67,
+	(q15_t)0xEBAA, (q15_t)0x7E5F, (q15_t)0xEB78, (q15_t)0x7E57,
+	(q15_t)0xEB47, (q15_t)0x7E4F, (q15_t)0xEB15, (q15_t)0x7E47,
+	(q15_t)0xEAE4, (q15_t)0x7E3F, (q15_t)0xEAB2, (q15_t)0x7E37,
+	(q15_t)0xEA80, (q15_t)0x7E2E, (q15_t)0xEA4F, (q15_t)0x7E26,
+	(q15_t)0xEA1D, (q15_t)0x7E1D, (q15_t)0xE9EC, (q15_t)0x7E14,
+	(q15_t)0xE9BA, (q15_t)0x7E0C, (q15_t)0xE989, (q15_t)0x7E03,
+	(q15_t)0xE957, (q15_t)0x7DFA, (q15_t)0xE926, (q15_t)0x7DF1,
+	(q15_t)0xE8F5, (q15_t)0x7DE8, (q15_t)0xE8C3, (q15_t)0x7DDF,
+	(q15_t)0xE892, (q15_t)0x7DD6, (q15_t)0xE860, (q15_t)0x7DCD,
+	(q15_t)0xE82F, (q15_t)0x7DC3, (q15_t)0xE7FD, (q15_t)0x7DBA,
+	(q15_t)0xE7CC, (q15_t)0x7DB0, (q15_t)0xE79B, (q15_t)0x7DA7,
+	(q15_t)0xE769, (q15_t)0x7D9D, (q15_t)0xE738, (q15_t)0x7D94,
+	(q15_t)0xE707, (q15_t)0x7D8A, (q15_t)0xE6D5, (q15_t)0x7D80,
+	(q15_t)0xE6A4, (q15_t)0x7D76, (q15_t)0xE673, (q15_t)0x7D6C,
+	(q15_t)0xE642, (q15_t)0x7D62, (q15_t)0xE610, (q15_t)0x7D58,
+	(q15_t)0xE5DF, (q15_t)0x7D4E, (q15_t)0xE5AE, (q15_t)0x7D43,
+	(q15_t)0xE57D, (q15_t)0x7D39, (q15_t)0xE54C, (q15_t)0x7D2F,
+	(q15_t)0xE51B, (q15_t)0x7D24, (q15_t)0xE4E9, (q15_t)0x7D19,
+	(q15_t)0xE4B8, (q15_t)0x7D0F, (q15_t)0xE487, (q15_t)0x7D04,
+	(q15_t)0xE456, (q15_t)0x7CF9, (q15_t)0xE425, (q15_t)0x7CEE,
+	(q15_t)0xE3F4, (q15_t)0x7CE3, (q15_t)0xE3C3, (q15_t)0x7CD8,
+	(q15_t)0xE392, (q15_t)0x7CCD, (q15_t)0xE361, (q15_t)0x7CC2,
+	(q15_t)0xE330, (q15_t)0x7CB7, (q15_t)0xE2FF, (q15_t)0x7CAB,
+	(q15_t)0xE2CE, (q15_t)0x7CA0, (q15_t)0xE29D, (q15_t)0x7C94,
+	(q15_t)0xE26C, (q15_t)0x7C89, (q15_t)0xE23B, (q15_t)0x7C7D,
+	(q15_t)0xE20A, (q15_t)0x7C71, (q15_t)0xE1DA, (q15_t)0x7C66,
+	(q15_t)0xE1A9, (q15_t)0x7C5A, (q15_t)0xE178, (q15_t)0x7C4E,
+	(q15_t)0xE147, (q15_t)0x7C42, (q15_t)0xE116, (q15_t)0x7C36,
+	(q15_t)0xE0E6, (q15_t)0x7C29, (q15_t)0xE0B5, (q15_t)0x7C1D,
+	(q15_t)0xE084, (q15_t)0x7C11, (q15_t)0xE053, (q15_t)0x7C05,
+	(q15_t)0xE023, (q15_t)0x7BF8, (q15_t)0xDFF2, (q15_t)0x7BEB,
+	(q15_t)0xDFC1, (q15_t)0x7BDF, (q15_t)0xDF91, (q15_t)0x7BD2,
+	(q15_t)0xDF60, (q15_t)0x7BC5, (q15_t)0xDF2F, (q15_t)0x7BB9,
+	(q15_t)0xDEFF, (q15_t)0x7BAC, (q15_t)0xDECE, (q15_t)0x7B9F,
+	(q15_t)0xDE9E, (q15_t)0x7B92, (q15_t)0xDE6D, (q15_t)0x7B84,
+	(q15_t)0xDE3D, (q15_t)0x7B77, (q15_t)0xDE0C, (q15_t)0x7B6A,
+	(q15_t)0xDDDC, (q15_t)0x7B5D, (q15_t)0xDDAB, (q15_t)0x7B4F,
+	(q15_t)0xDD7B, (q15_t)0x7B42, (q15_t)0xDD4B, (q15_t)0x7B34,
+	(q15_t)0xDD1A, (q15_t)0x7B26, (q15_t)0xDCEA, (q15_t)0x7B19,
+	(q15_t)0xDCBA, (q15_t)0x7B0B, (q15_t)0xDC89, (q15_t)0x7AFD,
+	(q15_t)0xDC59, (q15_t)0x7AEF, (q15_t)0xDC29, (q15_t)0x7AE1,
+	(q15_t)0xDBF8, (q15_t)0x7AD3, (q15_t)0xDBC8, (q15_t)0x7AC5,
+	(q15_t)0xDB98, (q15_t)0x7AB6, (q15_t)0xDB68, (q15_t)0x7AA8,
+	(q15_t)0xDB38, (q15_t)0x7A9A, (q15_t)0xDB08, (q15_t)0x7A8B,
+	(q15_t)0xDAD7, (q15_t)0x7A7D, (q15_t)0xDAA7, (q15_t)0x7A6E,
+	(q15_t)0xDA77, (q15_t)0x7A5F, (q15_t)0xDA47, (q15_t)0x7A50,
+	(q15_t)0xDA17, (q15_t)0x7A42, (q15_t)0xD9E7, (q15_t)0x7A33,
+	(q15_t)0xD9B7, (q15_t)0x7A24, (q15_t)0xD987, (q15_t)0x7A15,
+	(q15_t)0xD957, (q15_t)0x7A05, (q15_t)0xD927, (q15_t)0x79F6,
+	(q15_t)0xD8F8, (q15_t)0x79E7, (q15_t)0xD8C8, (q15_t)0x79D8,
+	(q15_t)0xD898, (q15_t)0x79C8, (q15_t)0xD868, (q15_t)0x79B9,
+	(q15_t)0xD838, (q15_t)0x79A9, (q15_t)0xD809, (q15_t)0x7999,
+	(q15_t)0xD7D9, (q15_t)0x798A, (q15_t)0xD7A9, (q15_t)0x797A,
+	(q15_t)0xD779, (q15_t)0x796A, (q15_t)0xD74A, (q15_t)0x795A,
+	(q15_t)0xD71A, (q15_t)0x794A, (q15_t)0xD6EA, (q15_t)0x793A,
+	(q15_t)0xD6BB, (q15_t)0x792A, (q15_t)0xD68B, (q15_t)0x7919,
+	(q15_t)0xD65C, (q15_t)0x7909, (q15_t)0xD62C, (q15_t)0x78F9,
+	(q15_t)0xD5FD, (q15_t)0x78E8, (q15_t)0xD5CD, (q15_t)0x78D8,
+	(q15_t)0xD59E, (q15_t)0x78C7, (q15_t)0xD56E, (q15_t)0x78B6,
+	(q15_t)0xD53F, (q15_t)0x78A6, (q15_t)0xD510, (q15_t)0x7895,
+	(q15_t)0xD4E0, (q15_t)0x7884, (q15_t)0xD4B1, (q15_t)0x7873,
+	(q15_t)0xD482, (q15_t)0x7862, (q15_t)0xD452, (q15_t)0x7851,
+	(q15_t)0xD423, (q15_t)0x7840, (q15_t)0xD3F4, (q15_t)0x782E,
+	(q15_t)0xD3C5, (q15_t)0x781D, (q15_t)0xD396, (q15_t)0x780C,
+	(q15_t)0xD367, (q15_t)0x77FA, (q15_t)0xD337, (q15_t)0x77E9,
+	(q15_t)0xD308, (q15_t)0x77D7, (q15_t)0xD2D9, (q15_t)0x77C5,
+	(q15_t)0xD2AA, (q15_t)0x77B4, (q15_t)0xD27B, (q15_t)0x77A2,
+	(q15_t)0xD24C, (q15_t)0x7790, (q15_t)0xD21D, (q15_t)0x777E,
+	(q15_t)0xD1EE, (q15_t)0x776C, (q15_t)0xD1C0, (q15_t)0x775A,
+	(q15_t)0xD191, (q15_t)0x7747, (q15_t)0xD162, (q15_t)0x7735,
+	(q15_t)0xD133, (q15_t)0x7723, (q15_t)0xD104, (q15_t)0x7710,
+	(q15_t)0xD0D6, (q15_t)0x76FE, (q15_t)0xD0A7, (q15_t)0x76EB,
+	(q15_t)0xD078, (q15_t)0x76D9, (q15_t)0xD04A, (q15_t)0x76C6,
+	(q15_t)0xD01B, (q15_t)0x76B3, (q15_t)0xCFEC, (q15_t)0x76A0,
+	(q15_t)0xCFBE, (q15_t)0x768E, (q15_t)0xCF8F, (q15_t)0x767B,
+	(q15_t)0xCF61, (q15_t)0x7668, (q15_t)0xCF32, (q15_t)0x7654,
+	(q15_t)0xCF04, (q15_t)0x7641, (q15_t)0xCED5, (q15_t)0x762E,
+	(q15_t)0xCEA7, (q15_t)0x761B, (q15_t)0xCE79, (q15_t)0x7607,
+	(q15_t)0xCE4A, (q15_t)0x75F4, (q15_t)0xCE1C, (q15_t)0x75E0,
+	(q15_t)0xCDEE, (q15_t)0x75CC, (q15_t)0xCDBF, (q15_t)0x75B9,
+	(q15_t)0xCD91, (q15_t)0x75A5, (q15_t)0xCD63, (q15_t)0x7591,
+	(q15_t)0xCD35, (q15_t)0x757D, (q15_t)0xCD07, (q15_t)0x7569,
+	(q15_t)0xCCD9, (q15_t)0x7555, (q15_t)0xCCAB, (q15_t)0x7541,
+	(q15_t)0xCC7D, (q15_t)0x752D, (q15_t)0xCC4F, (q15_t)0x7519,
+	(q15_t)0xCC21, (q15_t)0x7504, (q15_t)0xCBF3, (q15_t)0x74F0,
+	(q15_t)0xCBC5, (q15_t)0x74DB, (q15_t)0xCB97, (q15_t)0x74C7,
+	(q15_t)0xCB69, (q15_t)0x74B2, (q15_t)0xCB3B, (q15_t)0x749E,
+	(q15_t)0xCB0D, (q15_t)0x7489, (q15_t)0xCAE0, (q15_t)0x7474,
+	(q15_t)0xCAB2, (q15_t)0x745F, (q15_t)0xCA84, (q15_t)0x744A,
+	(q15_t)0xCA57, (q15_t)0x7435, (q15_t)0xCA29, (q15_t)0x7420,
+	(q15_t)0xC9FB, (q15_t)0x740B, (q15_t)0xC9CE, (q15_t)0x73F6,
+	(q15_t)0xC9A0, (q15_t)0x73E0, (q15_t)0xC973, (q15_t)0x73CB,
+	(q15_t)0xC945, (q15_t)0x73B5, (q15_t)0xC918, (q15_t)0x73A0,
+	(q15_t)0xC8EB, (q15_t)0x738A, (q15_t)0xC8BD, (q15_t)0x7375,
+	(q15_t)0xC890, (q15_t)0x735F, (q15_t)0xC863, (q15_t)0x7349,
+	(q15_t)0xC835, (q15_t)0x7333, (q15_t)0xC808, (q15_t)0x731D,
+	(q15_t)0xC7DB, (q15_t)0x7307, (q15_t)0xC7AE, (q15_t)0x72F1,
+	(q15_t)0xC781, (q15_t)0x72DB, (q15_t)0xC754, (q15_t)0x72C5,
+	(q15_t)0xC727, (q15_t)0x72AF, (q15_t)0xC6F9, (q15_t)0x7298,
+	(q15_t)0xC6CD, (q15_t)0x7282, (q15_t)0xC6A0, (q15_t)0x726B,
+	(q15_t)0xC673, (q15_t)0x7255, (q15_t)0xC646, (q15_t)0x723E,
+	(q15_t)0xC619, (q15_t)0x7227, (q15_t)0xC5EC, (q15_t)0x7211,
+	(q15_t)0xC5BF, (q15_t)0x71FA, (q15_t)0xC593, (q15_t)0x71E3,
+	(q15_t)0xC566, (q15_t)0x71CC, (q15_t)0xC539, (q15_t)0x71B5,
+	(q15_t)0xC50D, (q15_t)0x719E, (q15_t)0xC4E0, (q15_t)0x7186,
+	(q15_t)0xC4B3, (q15_t)0x716F, (q15_t)0xC487, (q15_t)0x7158,
+	(q15_t)0xC45A, (q15_t)0x7141, (q15_t)0xC42E, (q15_t)0x7129,
+	(q15_t)0xC402, (q15_t)0x7112, (q15_t)0xC3D5, (q15_t)0x70FA,
+	(q15_t)0xC3A9, (q15_t)0x70E2, (q15_t)0xC37C, (q15_t)0x70CB,
+	(q15_t)0xC350, (q15_t)0x70B3, (q15_t)0xC324, (q15_t)0x709B,
+	(q15_t)0xC2F8, (q15_t)0x7083, (q15_t)0xC2CC, (q15_t)0x706B,
+	(q15_t)0xC29F, (q15_t)0x7053, (q15_t)0xC273, (q15_t)0x703B,
+	(q15_t)0xC247, (q15_t)0x7023, (q15_t)0xC21B, (q15_t)0x700A,
+	(q15_t)0xC1EF, (q15_t)0x6FF2, (q15_t)0xC1C3, (q15_t)0x6FDA,
+	(q15_t)0xC197, (q15_t)0x6FC1, (q15_t)0xC16C, (q15_t)0x6FA9,
+	(q15_t)0xC140, (q15_t)0x6F90, (q15_t)0xC114, (q15_t)0x6F77,
+	(q15_t)0xC0E8, (q15_t)0x6F5F, (q15_t)0xC0BC, (q15_t)0x6F46,
+	(q15_t)0xC091, (q15_t)0x6F2D, (q15_t)0xC065, (q15_t)0x6F14,
+	(q15_t)0xC03A, (q15_t)0x6EFB, (q15_t)0xC00E, (q15_t)0x6EE2,
+	(q15_t)0xBFE2, (q15_t)0x6EC9, (q15_t)0xBFB7, (q15_t)0x6EAF,
+	(q15_t)0xBF8C, (q15_t)0x6E96, (q15_t)0xBF60, (q15_t)0x6E7D,
+	(q15_t)0xBF35, (q15_t)0x6E63, (q15_t)0xBF09, (q15_t)0x6E4A,
+	(q15_t)0xBEDE, (q15_t)0x6E30, (q15_t)0xBEB3, (q15_t)0x6E17,
+	(q15_t)0xBE88, (q15_t)0x6DFD, (q15_t)0xBE5D, (q15_t)0x6DE3,
+	(q15_t)0xBE31, (q15_t)0x6DCA, (q15_t)0xBE06, (q15_t)0x6DB0,
+	(q15_t)0xBDDB, (q15_t)0x6D96, (q15_t)0xBDB0, (q15_t)0x6D7C,
+	(q15_t)0xBD85, (q15_t)0x6D62, (q15_t)0xBD5A, (q15_t)0x6D48,
+	(q15_t)0xBD2F, (q15_t)0x6D2D, (q15_t)0xBD05, (q15_t)0x6D13,
+	(q15_t)0xBCDA, (q15_t)0x6CF9, (q15_t)0xBCAF, (q15_t)0x6CDE,
+	(q15_t)0xBC84, (q15_t)0x6CC4, (q15_t)0xBC5A, (q15_t)0x6CA9,
+	(q15_t)0xBC2F, (q15_t)0x6C8F, (q15_t)0xBC04, (q15_t)0x6C74,
+	(q15_t)0xBBDA, (q15_t)0x6C59, (q15_t)0xBBAF, (q15_t)0x6C3F,
+	(q15_t)0xBB85, (q15_t)0x6C24, (q15_t)0xBB5A, (q15_t)0x6C09,
+	(q15_t)0xBB30, (q15_t)0x6BEE, (q15_t)0xBB05, (q15_t)0x6BD3,
+	(q15_t)0xBADB, (q15_t)0x6BB8, (q15_t)0xBAB1, (q15_t)0x6B9C,
+	(q15_t)0xBA87, (q15_t)0x6B81, (q15_t)0xBA5C, (q15_t)0x6B66,
+	(q15_t)0xBA32, (q15_t)0x6B4A, (q15_t)0xBA08, (q15_t)0x6B2F,
+	(q15_t)0xB9DE, (q15_t)0x6B13, (q15_t)0xB9B4, (q15_t)0x6AF8,
+	(q15_t)0xB98A, (q15_t)0x6ADC, (q15_t)0xB960, (q15_t)0x6AC1,
+	(q15_t)0xB936, (q15_t)0x6AA5, (q15_t)0xB90C, (q15_t)0x6A89,
+	(q15_t)0xB8E3, (q15_t)0x6A6D, (q15_t)0xB8B9, (q15_t)0x6A51,
+	(q15_t)0xB88F, (q15_t)0x6A35, (q15_t)0xB865, (q15_t)0x6A19,
+	(q15_t)0xB83C, (q15_t)0x69FD, (q15_t)0xB812, (q15_t)0x69E1,
+	(q15_t)0xB7E9, (q15_t)0x69C4, (q15_t)0xB7BF, (q15_t)0x69A8,
+	(q15_t)0xB796, (q15_t)0x698C, (q15_t)0xB76C, (q15_t)0x696F,
+	(q15_t)0xB743, (q15_t)0x6953, (q15_t)0xB719, (q15_t)0x6936,
+	(q15_t)0xB6F0, (q15_t)0x6919, (q15_t)0xB6C7, (q15_t)0x68FD,
+	(q15_t)0xB69E, (q15_t)0x68E0, (q15_t)0xB675, (q15_t)0x68C3,
+	(q15_t)0xB64B, (q15_t)0x68A6, (q15_t)0xB622, (q15_t)0x6889,
+	(q15_t)0xB5F9, (q15_t)0x686C, (q15_t)0xB5D0, (q15_t)0x684F,
+	(q15_t)0xB5A7, (q15_t)0x6832, (q15_t)0xB57E, (q15_t)0x6815,
+	(q15_t)0xB556, (q15_t)0x67F7, (q15_t)0xB52D, (q15_t)0x67DA,
+	(q15_t)0xB504, (q15_t)0x67BD, (q15_t)0xB4DB, (q15_t)0x679F,
+	(q15_t)0xB4B3, (q15_t)0x6782, (q15_t)0xB48A, (q15_t)0x6764,
+	(q15_t)0xB461, (q15_t)0x6746, (q15_t)0xB439, (q15_t)0x6729,
+	(q15_t)0xB410, (q15_t)0x670B, (q15_t)0xB3E8, (q15_t)0x66ED,
+	(q15_t)0xB3C0, (q15_t)0x66CF, (q15_t)0xB397, (q15_t)0x66B1,
+	(q15_t)0xB36F, (q15_t)0x6693, (q15_t)0xB347, (q15_t)0x6675,
+	(q15_t)0xB31E, (q15_t)0x6657, (q15_t)0xB2F6, (q15_t)0x6639,
+	(q15_t)0xB2CE, (q15_t)0x661A, (q15_t)0xB2A6, (q15_t)0x65FC,
+	(q15_t)0xB27E, (q15_t)0x65DD, (q15_t)0xB256, (q15_t)0x65BF,
+	(q15_t)0xB22E, (q15_t)0x65A0, (q15_t)0xB206, (q15_t)0x6582,
+	(q15_t)0xB1DE, (q15_t)0x6563, (q15_t)0xB1B7, (q15_t)0x6545,
+	(q15_t)0xB18F, (q15_t)0x6526, (q15_t)0xB167, (q15_t)0x6507,
+	(q15_t)0xB140, (q15_t)0x64E8, (q15_t)0xB118, (q15_t)0x64C9,
+	(q15_t)0xB0F0, (q15_t)0x64AA, (q15_t)0xB0C9, (q15_t)0x648B,
+	(q15_t)0xB0A1, (q15_t)0x646C, (q15_t)0xB07A, (q15_t)0x644D,
+	(q15_t)0xB053, (q15_t)0x642D, (q15_t)0xB02B, (q15_t)0x640E,
+	(q15_t)0xB004, (q15_t)0x63EF, (q15_t)0xAFDD, (q15_t)0x63CF,
+	(q15_t)0xAFB6, (q15_t)0x63B0, (q15_t)0xAF8F, (q15_t)0x6390,
+	(q15_t)0xAF68, (q15_t)0x6371, (q15_t)0xAF40, (q15_t)0x6351,
+	(q15_t)0xAF1A, (q15_t)0x6331, (q15_t)0xAEF3, (q15_t)0x6311,
+	(q15_t)0xAECC, (q15_t)0x62F2, (q15_t)0xAEA5, (q15_t)0x62D2,
+	(q15_t)0xAE7E, (q15_t)0x62B2, (q15_t)0xAE57, (q15_t)0x6292,
+	(q15_t)0xAE31, (q15_t)0x6271, (q15_t)0xAE0A, (q15_t)0x6251,
+	(q15_t)0xADE3, (q15_t)0x6231, (q15_t)0xADBD, (q15_t)0x6211,
+	(q15_t)0xAD96, (q15_t)0x61F1, (q15_t)0xAD70, (q15_t)0x61D0,
+	(q15_t)0xAD4A, (q15_t)0x61B0, (q15_t)0xAD23, (q15_t)0x618F,
+	(q15_t)0xACFD, (q15_t)0x616F, (q15_t)0xACD7, (q15_t)0x614E,
+	(q15_t)0xACB1, (q15_t)0x612D, (q15_t)0xAC8A, (q15_t)0x610D,
+	(q15_t)0xAC64, (q15_t)0x60EC, (q15_t)0xAC3E, (q15_t)0x60CB,
+	(q15_t)0xAC18, (q15_t)0x60AA, (q15_t)0xABF2, (q15_t)0x6089,
+	(q15_t)0xABCC, (q15_t)0x6068, (q15_t)0xABA7, (q15_t)0x6047,
+	(q15_t)0xAB81, (q15_t)0x6026, (q15_t)0xAB5B, (q15_t)0x6004,
+	(q15_t)0xAB35, (q15_t)0x5FE3, (q15_t)0xAB10, (q15_t)0x5FC2,
+	(q15_t)0xAAEA, (q15_t)0x5FA0, (q15_t)0xAAC5, (q15_t)0x5F7F,
+	(q15_t)0xAA9F, (q15_t)0x5F5E, (q15_t)0xAA7A, (q15_t)0x5F3C,
+	(q15_t)0xAA54, (q15_t)0x5F1A, (q15_t)0xAA2F, (q15_t)0x5EF9,
+	(q15_t)0xAA0A, (q15_t)0x5ED7, (q15_t)0xA9E5, (q15_t)0x5EB5,
+	(q15_t)0xA9BF, (q15_t)0x5E93, (q15_t)0xA99A, (q15_t)0x5E71,
+	(q15_t)0xA975, (q15_t)0x5E50, (q15_t)0xA950, (q15_t)0x5E2D,
+	(q15_t)0xA92B, (q15_t)0x5E0B, (q15_t)0xA906, (q15_t)0x5DE9,
+	(q15_t)0xA8E2, (q15_t)0x5DC7, (q15_t)0xA8BD, (q15_t)0x5DA5,
+	(q15_t)0xA898, (q15_t)0x5D83, (q15_t)0xA873, (q15_t)0x5D60,
+	(q15_t)0xA84F, (q15_t)0x5D3E, (q15_t)0xA82A, (q15_t)0x5D1B,
+	(q15_t)0xA806, (q15_t)0x5CF9, (q15_t)0xA7E1, (q15_t)0x5CD6,
+	(q15_t)0xA7BD, (q15_t)0x5CB4, (q15_t)0xA798, (q15_t)0x5C91,
+	(q15_t)0xA774, (q15_t)0x5C6E, (q15_t)0xA750, (q15_t)0x5C4B,
+	(q15_t)0xA72B, (q15_t)0x5C29, (q15_t)0xA707, (q15_t)0x5C06,
+	(q15_t)0xA6E3, (q15_t)0x5BE3, (q15_t)0xA6BF, (q15_t)0x5BC0,
+	(q15_t)0xA69B, (q15_t)0x5B9D, (q15_t)0xA677, (q15_t)0x5B79,
+	(q15_t)0xA653, (q15_t)0x5B56, (q15_t)0xA62F, (q15_t)0x5B33,
+	(q15_t)0xA60C, (q15_t)0x5B10, (q15_t)0xA5E8, (q15_t)0x5AEC,
+	(q15_t)0xA5C4, (q15_t)0x5AC9, (q15_t)0xA5A1, (q15_t)0x5AA5,
+	(q15_t)0xA57D, (q15_t)0x5A82, (q15_t)0xA55A, (q15_t)0x5A5E,
+	(q15_t)0xA536, (q15_t)0x5A3B, (q15_t)0xA513, (q15_t)0x5A17,
+	(q15_t)0xA4EF, (q15_t)0x59F3, (q15_t)0xA4CC, (q15_t)0x59D0,
+	(q15_t)0xA4A9, (q15_t)0x59AC, (q15_t)0xA486, (q15_t)0x5988,
+	(q15_t)0xA462, (q15_t)0x5964, (q15_t)0xA43F, (q15_t)0x5940,
+	(q15_t)0xA41C, (q15_t)0x591C, (q15_t)0xA3F9, (q15_t)0x58F8,
+	(q15_t)0xA3D6, (q15_t)0x58D4, (q15_t)0xA3B4, (q15_t)0x58AF,
+	(q15_t)0xA391, (q15_t)0x588B, (q15_t)0xA36E, (q15_t)0x5867,
+	(q15_t)0xA34B, (q15_t)0x5842, (q15_t)0xA329, (q15_t)0x581E,
+	(q15_t)0xA306, (q15_t)0x57F9, (q15_t)0xA2E4, (q15_t)0x57D5,
+	(q15_t)0xA2C1, (q15_t)0x57B0, (q15_t)0xA29F, (q15_t)0x578C,
+	(q15_t)0xA27C, (q15_t)0x5767, (q15_t)0xA25A, (q15_t)0x5742,
+	(q15_t)0xA238, (q15_t)0x571D, (q15_t)0xA216, (q15_t)0x56F9,
+	(q15_t)0xA1F4, (q15_t)0x56D4, (q15_t)0xA1D2, (q15_t)0x56AF,
+	(q15_t)0xA1AF, (q15_t)0x568A, (q15_t)0xA18E, (q15_t)0x5665,
+	(q15_t)0xA16C, (q15_t)0x5640, (q15_t)0xA14A, (q15_t)0x561A,
+	(q15_t)0xA128, (q15_t)0x55F5, (q15_t)0xA106, (q15_t)0x55D0,
+	(q15_t)0xA0E5, (q15_t)0x55AB, (q15_t)0xA0C3, (q15_t)0x5585,
+	(q15_t)0xA0A1, (q15_t)0x5560, (q15_t)0xA080, (q15_t)0x553A,
+	(q15_t)0xA05F, (q15_t)0x5515, (q15_t)0xA03D, (q15_t)0x54EF,
+	(q15_t)0xA01C, (q15_t)0x54CA, (q15_t)0x9FFB, (q15_t)0x54A4,
+	(q15_t)0x9FD9, (q15_t)0x547E, (q15_t)0x9FB8, (q15_t)0x5458,
+	(q15_t)0x9F97, (q15_t)0x5433, (q15_t)0x9F76, (q15_t)0x540D,
+	(q15_t)0x9F55, (q15_t)0x53E7, (q15_t)0x9F34, (q15_t)0x53C1,
+	(q15_t)0x9F13, (q15_t)0x539B, (q15_t)0x9EF2, (q15_t)0x5375,
+	(q15_t)0x9ED2, (q15_t)0x534E, (q15_t)0x9EB1, (q15_t)0x5328,
+	(q15_t)0x9E90, (q15_t)0x5302, (q15_t)0x9E70, (q15_t)0x52DC,
+	(q15_t)0x9E4F, (q15_t)0x52B5, (q15_t)0x9E2F, (q15_t)0x528F,
+	(q15_t)0x9E0E, (q15_t)0x5269, (q15_t)0x9DEE, (q15_t)0x5242,
+	(q15_t)0x9DCE, (q15_t)0x521C, (q15_t)0x9DAE, (q15_t)0x51F5,
+	(q15_t)0x9D8E, (q15_t)0x51CE, (q15_t)0x9D6D, (q15_t)0x51A8,
+	(q15_t)0x9D4D, (q15_t)0x5181, (q15_t)0x9D2D, (q15_t)0x515A,
+	(q15_t)0x9D0D, (q15_t)0x5133, (q15_t)0x9CEE, (q15_t)0x510C,
+	(q15_t)0x9CCE, (q15_t)0x50E5, (q15_t)0x9CAE, (q15_t)0x50BF,
+	(q15_t)0x9C8E, (q15_t)0x5097, (q15_t)0x9C6F, (q15_t)0x5070,
+	(q15_t)0x9C4F, (q15_t)0x5049, (q15_t)0x9C30, (q15_t)0x5022,
+	(q15_t)0x9C10, (q15_t)0x4FFB, (q15_t)0x9BF1, (q15_t)0x4FD4,
+	(q15_t)0x9BD2, (q15_t)0x4FAC, (q15_t)0x9BB2, (q15_t)0x4F85,
+	(q15_t)0x9B93, (q15_t)0x4F5E, (q15_t)0x9B74, (q15_t)0x4F36,
+	(q15_t)0x9B55, (q15_t)0x4F0F, (q15_t)0x9B36, (q15_t)0x4EE7,
+	(q15_t)0x9B17, (q15_t)0x4EBF, (q15_t)0x9AF8, (q15_t)0x4E98,
+	(q15_t)0x9AD9, (q15_t)0x4E70, (q15_t)0x9ABA, (q15_t)0x4E48,
+	(q15_t)0x9A9C, (q15_t)0x4E21, (q15_t)0x9A7D, (q15_t)0x4DF9,
+	(q15_t)0x9A5F, (q15_t)0x4DD1, (q15_t)0x9A40, (q15_t)0x4DA9,
+	(q15_t)0x9A22, (q15_t)0x4D81, (q15_t)0x9A03, (q15_t)0x4D59,
+	(q15_t)0x99E5, (q15_t)0x4D31, (q15_t)0x99C6, (q15_t)0x4D09,
+	(q15_t)0x99A8, (q15_t)0x4CE1, (q15_t)0x998A, (q15_t)0x4CB8,
+	(q15_t)0x996C, (q15_t)0x4C90, (q15_t)0x994E, (q15_t)0x4C68,
+	(q15_t)0x9930, (q15_t)0x4C3F, (q15_t)0x9912, (q15_t)0x4C17,
+	(q15_t)0x98F4, (q15_t)0x4BEF, (q15_t)0x98D6, (q15_t)0x4BC6,
+	(q15_t)0x98B9, (q15_t)0x4B9E, (q15_t)0x989B, (q15_t)0x4B75,
+	(q15_t)0x987D, (q15_t)0x4B4C, (q15_t)0x9860, (q15_t)0x4B24,
+	(q15_t)0x9842, (q15_t)0x4AFB, (q15_t)0x9825, (q15_t)0x4AD2,
+	(q15_t)0x9808, (q15_t)0x4AA9, (q15_t)0x97EA, (q15_t)0x4A81,
+	(q15_t)0x97CD, (q15_t)0x4A58, (q15_t)0x97B0, (q15_t)0x4A2F,
+	(q15_t)0x9793, (q15_t)0x4A06, (q15_t)0x9776, (q15_t)0x49DD,
+	(q15_t)0x9759, (q15_t)0x49B4, (q15_t)0x973C, (q15_t)0x498A,
+	(q15_t)0x971F, (q15_t)0x4961, (q15_t)0x9702, (q15_t)0x4938,
+	(q15_t)0x96E6, (q15_t)0x490F, (q15_t)0x96C9, (q15_t)0x48E6,
+	(q15_t)0x96AC, (q15_t)0x48BC, (q15_t)0x9690, (q15_t)0x4893,
+	(q15_t)0x9673, (q15_t)0x4869, (q15_t)0x9657, (q15_t)0x4840,
+	(q15_t)0x963B, (q15_t)0x4816, (q15_t)0x961E, (q15_t)0x47ED,
+	(q15_t)0x9602, (q15_t)0x47C3, (q15_t)0x95E6, (q15_t)0x479A,
+	(q15_t)0x95CA, (q15_t)0x4770, (q15_t)0x95AE, (q15_t)0x4746,
+	(q15_t)0x9592, (q15_t)0x471C, (q15_t)0x9576, (q15_t)0x46F3,
+	(q15_t)0x955A, (q15_t)0x46C9, (q15_t)0x953E, (q15_t)0x469F,
+	(q15_t)0x9523, (q15_t)0x4675, (q15_t)0x9507, (q15_t)0x464B,
+	(q15_t)0x94EC, (q15_t)0x4621, (q15_t)0x94D0, (q15_t)0x45F7,
+	(q15_t)0x94B5, (q15_t)0x45CD, (q15_t)0x9499, (q15_t)0x45A3,
+	(q15_t)0x947E, (q15_t)0x4578, (q15_t)0x9463, (q15_t)0x454E,
+	(q15_t)0x9447, (q15_t)0x4524, (q15_t)0x942C, (q15_t)0x44FA,
+	(q15_t)0x9411, (q15_t)0x44CF, (q15_t)0x93F6, (q15_t)0x44A5,
+	(q15_t)0x93DB, (q15_t)0x447A, (q15_t)0x93C0, (q15_t)0x4450,
+	(q15_t)0x93A6, (q15_t)0x4425, (q15_t)0x938B, (q15_t)0x43FB,
+	(q15_t)0x9370, (q15_t)0x43D0, (q15_t)0x9356, (q15_t)0x43A5,
+	(q15_t)0x933B, (q15_t)0x437B, (q15_t)0x9321, (q15_t)0x4350,
+	(q15_t)0x9306, (q15_t)0x4325, (q15_t)0x92EC, (q15_t)0x42FA,
+	(q15_t)0x92D2, (q15_t)0x42D0, (q15_t)0x92B7, (q15_t)0x42A5,
+	(q15_t)0x929D, (q15_t)0x427A, (q15_t)0x9283, (q15_t)0x424F,
+	(q15_t)0x9269, (q15_t)0x4224, (q15_t)0x924F, (q15_t)0x41F9,
+	(q15_t)0x9235, (q15_t)0x41CE, (q15_t)0x921C, (q15_t)0x41A2,
+	(q15_t)0x9202, (q15_t)0x4177, (q15_t)0x91E8, (q15_t)0x414C,
+	(q15_t)0x91CF, (q15_t)0x4121, (q15_t)0x91B5, (q15_t)0x40F6,
+	(q15_t)0x919C, (q15_t)0x40CA, (q15_t)0x9182, (q15_t)0x409F,
+	(q15_t)0x9169, (q15_t)0x4073, (q15_t)0x9150, (q15_t)0x4048,
+	(q15_t)0x9136, (q15_t)0x401D, (q15_t)0x911D, (q15_t)0x3FF1,
+	(q15_t)0x9104, (q15_t)0x3FC5, (q15_t)0x90EB, (q15_t)0x3F9A,
+	(q15_t)0x90D2, (q15_t)0x3F6E, (q15_t)0x90B9, (q15_t)0x3F43,
+	(q15_t)0x90A0, (q15_t)0x3F17, (q15_t)0x9088, (q15_t)0x3EEB,
+	(q15_t)0x906F, (q15_t)0x3EBF, (q15_t)0x9056, (q15_t)0x3E93,
+	(q15_t)0x903E, (q15_t)0x3E68, (q15_t)0x9025, (q15_t)0x3E3C,
+	(q15_t)0x900D, (q15_t)0x3E10, (q15_t)0x8FF5, (q15_t)0x3DE4,
+	(q15_t)0x8FDC, (q15_t)0x3DB8, (q15_t)0x8FC4, (q15_t)0x3D8C,
+	(q15_t)0x8FAC, (q15_t)0x3D60, (q15_t)0x8F94, (q15_t)0x3D33,
+	(q15_t)0x8F7C, (q15_t)0x3D07, (q15_t)0x8F64, (q15_t)0x3CDB,
+	(q15_t)0x8F4C, (q15_t)0x3CAF, (q15_t)0x8F34, (q15_t)0x3C83,
+	(q15_t)0x8F1D, (q15_t)0x3C56, (q15_t)0x8F05, (q15_t)0x3C2A,
+	(q15_t)0x8EED, (q15_t)0x3BFD, (q15_t)0x8ED6, (q15_t)0x3BD1,
+	(q15_t)0x8EBE, (q15_t)0x3BA5, (q15_t)0x8EA7, (q15_t)0x3B78,
+	(q15_t)0x8E90, (q15_t)0x3B4C, (q15_t)0x8E79, (q15_t)0x3B1F,
+	(q15_t)0x8E61, (q15_t)0x3AF2, (q15_t)0x8E4A, (q15_t)0x3AC6,
+	(q15_t)0x8E33, (q15_t)0x3A99, (q15_t)0x8E1C, (q15_t)0x3A6C,
+	(q15_t)0x8E05, (q15_t)0x3A40, (q15_t)0x8DEE, (q15_t)0x3A13,
+	(q15_t)0x8DD8, (q15_t)0x39E6, (q15_t)0x8DC1, (q15_t)0x39B9,
+	(q15_t)0x8DAA, (q15_t)0x398C, (q15_t)0x8D94, (q15_t)0x395F,
+	(q15_t)0x8D7D, (q15_t)0x3932, (q15_t)0x8D67, (q15_t)0x3906,
+	(q15_t)0x8D50, (q15_t)0x38D8, (q15_t)0x8D3A, (q15_t)0x38AB,
+	(q15_t)0x8D24, (q15_t)0x387E, (q15_t)0x8D0E, (q15_t)0x3851,
+	(q15_t)0x8CF8, (q15_t)0x3824, (q15_t)0x8CE2, (q15_t)0x37F7,
+	(q15_t)0x8CCC, (q15_t)0x37CA, (q15_t)0x8CB6, (q15_t)0x379C,
+	(q15_t)0x8CA0, (q15_t)0x376F, (q15_t)0x8C8A, (q15_t)0x3742,
+	(q15_t)0x8C75, (q15_t)0x3714, (q15_t)0x8C5F, (q15_t)0x36E7,
+	(q15_t)0x8C4A, (q15_t)0x36BA, (q15_t)0x8C34, (q15_t)0x368C,
+	(q15_t)0x8C1F, (q15_t)0x365F, (q15_t)0x8C09, (q15_t)0x3631,
+	(q15_t)0x8BF4, (q15_t)0x3604, (q15_t)0x8BDF, (q15_t)0x35D6,
+	(q15_t)0x8BCA, (q15_t)0x35A8, (q15_t)0x8BB5, (q15_t)0x357B,
+	(q15_t)0x8BA0, (q15_t)0x354D, (q15_t)0x8B8B, (q15_t)0x351F,
+	(q15_t)0x8B76, (q15_t)0x34F2, (q15_t)0x8B61, (q15_t)0x34C4,
+	(q15_t)0x8B4D, (q15_t)0x3496, (q15_t)0x8B38, (q15_t)0x3468,
+	(q15_t)0x8B24, (q15_t)0x343A, (q15_t)0x8B0F, (q15_t)0x340C,
+	(q15_t)0x8AFB, (q15_t)0x33DE, (q15_t)0x8AE6, (q15_t)0x33B0,
+	(q15_t)0x8AD2, (q15_t)0x3382, (q15_t)0x8ABE, (q15_t)0x3354,
+	(q15_t)0x8AAA, (q15_t)0x3326, (q15_t)0x8A96, (q15_t)0x32F8,
+	(q15_t)0x8A82, (q15_t)0x32CA, (q15_t)0x8A6E, (q15_t)0x329C,
+	(q15_t)0x8A5A, (q15_t)0x326E, (q15_t)0x8A46, (q15_t)0x3240,
+	(q15_t)0x8A33, (q15_t)0x3211, (q15_t)0x8A1F, (q15_t)0x31E3,
+	(q15_t)0x8A0B, (q15_t)0x31B5, (q15_t)0x89F8, (q15_t)0x3186,
+	(q15_t)0x89E4, (q15_t)0x3158, (q15_t)0x89D1, (q15_t)0x312A,
+	(q15_t)0x89BE, (q15_t)0x30FB, (q15_t)0x89AB, (q15_t)0x30CD,
+	(q15_t)0x8997, (q15_t)0x309E, (q15_t)0x8984, (q15_t)0x3070,
+	(q15_t)0x8971, (q15_t)0x3041, (q15_t)0x895F, (q15_t)0x3013,
+	(q15_t)0x894C, (q15_t)0x2FE4, (q15_t)0x8939, (q15_t)0x2FB5,
+	(q15_t)0x8926, (q15_t)0x2F87, (q15_t)0x8914, (q15_t)0x2F58,
+	(q15_t)0x8901, (q15_t)0x2F29, (q15_t)0x88EF, (q15_t)0x2EFB,
+	(q15_t)0x88DC, (q15_t)0x2ECC, (q15_t)0x88CA, (q15_t)0x2E9D,
+	(q15_t)0x88B8, (q15_t)0x2E6E, (q15_t)0x88A5, (q15_t)0x2E3F,
+	(q15_t)0x8893, (q15_t)0x2E11, (q15_t)0x8881, (q15_t)0x2DE2,
+	(q15_t)0x886F, (q15_t)0x2DB3, (q15_t)0x885D, (q15_t)0x2D84,
+	(q15_t)0x884B, (q15_t)0x2D55, (q15_t)0x883A, (q15_t)0x2D26,
+	(q15_t)0x8828, (q15_t)0x2CF7, (q15_t)0x8816, (q15_t)0x2CC8,
+	(q15_t)0x8805, (q15_t)0x2C98, (q15_t)0x87F3, (q15_t)0x2C69,
+	(q15_t)0x87E2, (q15_t)0x2C3A, (q15_t)0x87D1, (q15_t)0x2C0B,
+	(q15_t)0x87BF, (q15_t)0x2BDC, (q15_t)0x87AE, (q15_t)0x2BAD,
+	(q15_t)0x879D, (q15_t)0x2B7D, (q15_t)0x878C, (q15_t)0x2B4E,
+	(q15_t)0x877B, (q15_t)0x2B1F, (q15_t)0x876A, (q15_t)0x2AEF,
+	(q15_t)0x8759, (q15_t)0x2AC0, (q15_t)0x8749, (q15_t)0x2A91,
+	(q15_t)0x8738, (q15_t)0x2A61, (q15_t)0x8727, (q15_t)0x2A32,
+	(q15_t)0x8717, (q15_t)0x2A02, (q15_t)0x8706, (q15_t)0x29D3,
+	(q15_t)0x86F6, (q15_t)0x29A3, (q15_t)0x86E6, (q15_t)0x2974,
+	(q15_t)0x86D5, (q15_t)0x2944, (q15_t)0x86C5, (q15_t)0x2915,
+	(q15_t)0x86B5, (q15_t)0x28E5, (q15_t)0x86A5, (q15_t)0x28B5,
+	(q15_t)0x8695, (q15_t)0x2886, (q15_t)0x8685, (q15_t)0x2856,
+	(q15_t)0x8675, (q15_t)0x2826, (q15_t)0x8666, (q15_t)0x27F6,
+	(q15_t)0x8656, (q15_t)0x27C7, (q15_t)0x8646, (q15_t)0x2797,
+	(q15_t)0x8637, (q15_t)0x2767, (q15_t)0x8627, (q15_t)0x2737,
+	(q15_t)0x8618, (q15_t)0x2707, (q15_t)0x8609, (q15_t)0x26D8,
+	(q15_t)0x85FA, (q15_t)0x26A8, (q15_t)0x85EA, (q15_t)0x2678,
+	(q15_t)0x85DB, (q15_t)0x2648, (q15_t)0x85CC, (q15_t)0x2618,
+	(q15_t)0x85BD, (q15_t)0x25E8, (q15_t)0x85AF, (q15_t)0x25B8,
+	(q15_t)0x85A0, (q15_t)0x2588, (q15_t)0x8591, (q15_t)0x2558,
+	(q15_t)0x8582, (q15_t)0x2528, (q15_t)0x8574, (q15_t)0x24F7,
+	(q15_t)0x8565, (q15_t)0x24C7, (q15_t)0x8557, (q15_t)0x2497,
+	(q15_t)0x8549, (q15_t)0x2467, (q15_t)0x853A, (q15_t)0x2437,
+	(q15_t)0x852C, (q15_t)0x2407, (q15_t)0x851E, (q15_t)0x23D6,
+	(q15_t)0x8510, (q15_t)0x23A6, (q15_t)0x8502, (q15_t)0x2376,
+	(q15_t)0x84F4, (q15_t)0x2345, (q15_t)0x84E6, (q15_t)0x2315,
+	(q15_t)0x84D9, (q15_t)0x22E5, (q15_t)0x84CB, (q15_t)0x22B4,
+	(q15_t)0x84BD, (q15_t)0x2284, (q15_t)0x84B0, (q15_t)0x2254,
+	(q15_t)0x84A2, (q15_t)0x2223, (q15_t)0x8495, (q15_t)0x21F3,
+	(q15_t)0x8488, (q15_t)0x21C2, (q15_t)0x847B, (q15_t)0x2192,
+	(q15_t)0x846D, (q15_t)0x2161, (q15_t)0x8460, (q15_t)0x2131,
+	(q15_t)0x8453, (q15_t)0x2100, (q15_t)0x8446, (q15_t)0x20D0,
+	(q15_t)0x843A, (q15_t)0x209F, (q15_t)0x842D, (q15_t)0x206E,
+	(q15_t)0x8420, (q15_t)0x203E, (q15_t)0x8414, (q15_t)0x200D,
+	(q15_t)0x8407, (q15_t)0x1FDC, (q15_t)0x83FA, (q15_t)0x1FAC,
+	(q15_t)0x83EE, (q15_t)0x1F7B, (q15_t)0x83E2, (q15_t)0x1F4A,
+	(q15_t)0x83D6, (q15_t)0x1F19, (q15_t)0x83C9, (q15_t)0x1EE9,
+	(q15_t)0x83BD, (q15_t)0x1EB8, (q15_t)0x83B1, (q15_t)0x1E87,
+	(q15_t)0x83A5, (q15_t)0x1E56, (q15_t)0x8399, (q15_t)0x1E25,
+	(q15_t)0x838E, (q15_t)0x1DF5, (q15_t)0x8382, (q15_t)0x1DC4,
+	(q15_t)0x8376, (q15_t)0x1D93, (q15_t)0x836B, (q15_t)0x1D62,
+	(q15_t)0x835F, (q15_t)0x1D31, (q15_t)0x8354, (q15_t)0x1D00,
+	(q15_t)0x8348, (q15_t)0x1CCF, (q15_t)0x833D, (q15_t)0x1C9E,
+	(q15_t)0x8332, (q15_t)0x1C6D, (q15_t)0x8327, (q15_t)0x1C3C,
+	(q15_t)0x831C, (q15_t)0x1C0B, (q15_t)0x8311, (q15_t)0x1BDA,
+	(q15_t)0x8306, (q15_t)0x1BA9, (q15_t)0x82FB, (q15_t)0x1B78,
+	(q15_t)0x82F0, (q15_t)0x1B47, (q15_t)0x82E6, (q15_t)0x1B16,
+	(q15_t)0x82DB, (q15_t)0x1AE4, (q15_t)0x82D0, (q15_t)0x1AB3,
+	(q15_t)0x82C6, (q15_t)0x1A82, (q15_t)0x82BC, (q15_t)0x1A51,
+	(q15_t)0x82B1, (q15_t)0x1A20, (q15_t)0x82A7, (q15_t)0x19EF,
+	(q15_t)0x829D, (q15_t)0x19BD, (q15_t)0x8293, (q15_t)0x198C,
+	(q15_t)0x8289, (q15_t)0x195B, (q15_t)0x827F, (q15_t)0x192A,
+	(q15_t)0x8275, (q15_t)0x18F8, (q15_t)0x826B, (q15_t)0x18C7,
+	(q15_t)0x8262, (q15_t)0x1896, (q15_t)0x8258, (q15_t)0x1864,
+	(q15_t)0x824F, (q15_t)0x1833, (q15_t)0x8245, (q15_t)0x1802,
+	(q15_t)0x823C, (q15_t)0x17D0, (q15_t)0x8232, (q15_t)0x179F,
+	(q15_t)0x8229, (q15_t)0x176D, (q15_t)0x8220, (q15_t)0x173C,
+	(q15_t)0x8217, (q15_t)0x170A, (q15_t)0x820E, (q15_t)0x16D9,
+	(q15_t)0x8205, (q15_t)0x16A8, (q15_t)0x81FC, (q15_t)0x1676,
+	(q15_t)0x81F3, (q15_t)0x1645, (q15_t)0x81EB, (q15_t)0x1613,
+	(q15_t)0x81E2, (q15_t)0x15E2, (q15_t)0x81D9, (q15_t)0x15B0,
+	(q15_t)0x81D1, (q15_t)0x157F, (q15_t)0x81C8, (q15_t)0x154D,
+	(q15_t)0x81C0, (q15_t)0x151B, (q15_t)0x81B8, (q15_t)0x14EA,
+	(q15_t)0x81B0, (q15_t)0x14B8, (q15_t)0x81A8, (q15_t)0x1487,
+	(q15_t)0x81A0, (q15_t)0x1455, (q15_t)0x8198, (q15_t)0x1423,
+	(q15_t)0x8190, (q15_t)0x13F2, (q15_t)0x8188, (q15_t)0x13C0,
+	(q15_t)0x8180, (q15_t)0x138E, (q15_t)0x8179, (q15_t)0x135D,
+	(q15_t)0x8171, (q15_t)0x132B, (q15_t)0x816A, (q15_t)0x12F9,
+	(q15_t)0x8162, (q15_t)0x12C8, (q15_t)0x815B, (q15_t)0x1296,
+	(q15_t)0x8154, (q15_t)0x1264, (q15_t)0x814C, (q15_t)0x1232,
+	(q15_t)0x8145, (q15_t)0x1201, (q15_t)0x813E, (q15_t)0x11CF,
+	(q15_t)0x8137, (q15_t)0x119D, (q15_t)0x8130, (q15_t)0x116B,
+	(q15_t)0x812A, (q15_t)0x1139, (q15_t)0x8123, (q15_t)0x1108,
+	(q15_t)0x811C, (q15_t)0x10D6, (q15_t)0x8116, (q15_t)0x10A4,
+	(q15_t)0x810F, (q15_t)0x1072, (q15_t)0x8109, (q15_t)0x1040,
+	(q15_t)0x8102, (q15_t)0x100E, (q15_t)0x80FC, (q15_t)0x0FDD,
+	(q15_t)0x80F6, (q15_t)0x0FAB, (q15_t)0x80F0, (q15_t)0x0F79,
+	(q15_t)0x80EA, (q15_t)0x0F47, (q15_t)0x80E4, (q15_t)0x0F15,
+	(q15_t)0x80DE, (q15_t)0x0EE3, (q15_t)0x80D8, (q15_t)0x0EB1,
+	(q15_t)0x80D2, (q15_t)0x0E7F, (q15_t)0x80CD, (q15_t)0x0E4D,
+	(q15_t)0x80C7, (q15_t)0x0E1B, (q15_t)0x80C2, (q15_t)0x0DE9,
+	(q15_t)0x80BC, (q15_t)0x0DB7, (q15_t)0x80B7, (q15_t)0x0D85,
+	(q15_t)0x80B2, (q15_t)0x0D53, (q15_t)0x80AC, (q15_t)0x0D21,
+	(q15_t)0x80A7, (q15_t)0x0CEF, (q15_t)0x80A2, (q15_t)0x0CBD,
+	(q15_t)0x809D, (q15_t)0x0C8B, (q15_t)0x8098, (q15_t)0x0C59,
+	(q15_t)0x8094, (q15_t)0x0C27, (q15_t)0x808F, (q15_t)0x0BF5,
+	(q15_t)0x808A, (q15_t)0x0BC3, (q15_t)0x8086, (q15_t)0x0B91,
+	(q15_t)0x8081, (q15_t)0x0B5F, (q15_t)0x807D, (q15_t)0x0B2D,
+	(q15_t)0x8078, (q15_t)0x0AFB, (q15_t)0x8074, (q15_t)0x0AC9,
+	(q15_t)0x8070, (q15_t)0x0A97, (q15_t)0x806C, (q15_t)0x0A65,
+	(q15_t)0x8068, (q15_t)0x0A33, (q15_t)0x8064, (q15_t)0x0A00,
+	(q15_t)0x8060, (q15_t)0x09CE, (q15_t)0x805C, (q15_t)0x099C,
+	(q15_t)0x8058, (q15_t)0x096A, (q15_t)0x8055, (q15_t)0x0938,
+	(q15_t)0x8051, (q15_t)0x0906, (q15_t)0x804E, (q15_t)0x08D4,
+	(q15_t)0x804A, (q15_t)0x08A2, (q15_t)0x8047, (q15_t)0x086F,
+	(q15_t)0x8043, (q15_t)0x083D, (q15_t)0x8040, (q15_t)0x080B,
+	(q15_t)0x803D, (q15_t)0x07D9, (q15_t)0x803A, (q15_t)0x07A7,
+	(q15_t)0x8037, (q15_t)0x0775, (q15_t)0x8034, (q15_t)0x0742,
+	(q15_t)0x8031, (q15_t)0x0710, (q15_t)0x802F, (q15_t)0x06DE,
+	(q15_t)0x802C, (q15_t)0x06AC, (q15_t)0x8029, (q15_t)0x067A,
+	(q15_t)0x8027, (q15_t)0x0647, (q15_t)0x8025, (q15_t)0x0615,
+	(q15_t)0x8022, (q15_t)0x05E3, (q15_t)0x8020, (q15_t)0x05B1,
+	(q15_t)0x801E, (q15_t)0x057F, (q15_t)0x801C, (q15_t)0x054C,
+	(q15_t)0x801A, (q15_t)0x051A, (q15_t)0x8018, (q15_t)0x04E8,
+	(q15_t)0x8016, (q15_t)0x04B6, (q15_t)0x8014, (q15_t)0x0483,
+	(q15_t)0x8012, (q15_t)0x0451, (q15_t)0x8011, (q15_t)0x041F,
+	(q15_t)0x800F, (q15_t)0x03ED, (q15_t)0x800D, (q15_t)0x03BA,
+	(q15_t)0x800C, (q15_t)0x0388, (q15_t)0x800B, (q15_t)0x0356,
+	(q15_t)0x8009, (q15_t)0x0324, (q15_t)0x8008, (q15_t)0x02F1,
+	(q15_t)0x8007, (q15_t)0x02BF, (q15_t)0x8006, (q15_t)0x028D,
+	(q15_t)0x8005, (q15_t)0x025B, (q15_t)0x8004, (q15_t)0x0228,
+	(q15_t)0x8003, (q15_t)0x01F6, (q15_t)0x8003, (q15_t)0x01C4,
+	(q15_t)0x8002, (q15_t)0x0192, (q15_t)0x8001, (q15_t)0x015F,
+	(q15_t)0x8001, (q15_t)0x012D, (q15_t)0x8000, (q15_t)0x00FB,
+	(q15_t)0x8000, (q15_t)0x00C9, (q15_t)0x8000, (q15_t)0x0096,
+	(q15_t)0x8000, (q15_t)0x0064, (q15_t)0x8000, (q15_t)0x0032,
+	(q15_t)0x8000, (q15_t)0x0000, (q15_t)0x8000, (q15_t)0xFFCD,
+	(q15_t)0x8000, (q15_t)0xFF9B, (q15_t)0x8000, (q15_t)0xFF69,
+	(q15_t)0x8000, (q15_t)0xFF36, (q15_t)0x8000, (q15_t)0xFF04,
+	(q15_t)0x8001, (q15_t)0xFED2, (q15_t)0x8001, (q15_t)0xFEA0,
+	(q15_t)0x8002, (q15_t)0xFE6D, (q15_t)0x8003, (q15_t)0xFE3B,
+	(q15_t)0x8003, (q15_t)0xFE09, (q15_t)0x8004, (q15_t)0xFDD7,
+	(q15_t)0x8005, (q15_t)0xFDA4, (q15_t)0x8006, (q15_t)0xFD72,
+	(q15_t)0x8007, (q15_t)0xFD40, (q15_t)0x8008, (q15_t)0xFD0E,
+	(q15_t)0x8009, (q15_t)0xFCDB, (q15_t)0x800B, (q15_t)0xFCA9,
+	(q15_t)0x800C, (q15_t)0xFC77, (q15_t)0x800D, (q15_t)0xFC45,
+	(q15_t)0x800F, (q15_t)0xFC12, (q15_t)0x8011, (q15_t)0xFBE0,
+	(q15_t)0x8012, (q15_t)0xFBAE, (q15_t)0x8014, (q15_t)0xFB7C,
+	(q15_t)0x8016, (q15_t)0xFB49, (q15_t)0x8018, (q15_t)0xFB17,
+	(q15_t)0x801A, (q15_t)0xFAE5, (q15_t)0x801C, (q15_t)0xFAB3,
+	(q15_t)0x801E, (q15_t)0xFA80, (q15_t)0x8020, (q15_t)0xFA4E,
+	(q15_t)0x8022, (q15_t)0xFA1C, (q15_t)0x8025, (q15_t)0xF9EA,
+	(q15_t)0x8027, (q15_t)0xF9B8, (q15_t)0x8029, (q15_t)0xF985,
+	(q15_t)0x802C, (q15_t)0xF953, (q15_t)0x802F, (q15_t)0xF921,
+	(q15_t)0x8031, (q15_t)0xF8EF, (q15_t)0x8034, (q15_t)0xF8BD,
+	(q15_t)0x8037, (q15_t)0xF88A, (q15_t)0x803A, (q15_t)0xF858,
+	(q15_t)0x803D, (q15_t)0xF826, (q15_t)0x8040, (q15_t)0xF7F4,
+	(q15_t)0x8043, (q15_t)0xF7C2, (q15_t)0x8047, (q15_t)0xF790,
+	(q15_t)0x804A, (q15_t)0xF75D, (q15_t)0x804E, (q15_t)0xF72B,
+	(q15_t)0x8051, (q15_t)0xF6F9, (q15_t)0x8055, (q15_t)0xF6C7,
+	(q15_t)0x8058, (q15_t)0xF695, (q15_t)0x805C, (q15_t)0xF663,
+	(q15_t)0x8060, (q15_t)0xF631, (q15_t)0x8064, (q15_t)0xF5FF,
+	(q15_t)0x8068, (q15_t)0xF5CC, (q15_t)0x806C, (q15_t)0xF59A,
+	(q15_t)0x8070, (q15_t)0xF568, (q15_t)0x8074, (q15_t)0xF536,
+	(q15_t)0x8078, (q15_t)0xF504, (q15_t)0x807D, (q15_t)0xF4D2,
+	(q15_t)0x8081, (q15_t)0xF4A0, (q15_t)0x8086, (q15_t)0xF46E,
+	(q15_t)0x808A, (q15_t)0xF43C, (q15_t)0x808F, (q15_t)0xF40A,
+	(q15_t)0x8094, (q15_t)0xF3D8, (q15_t)0x8098, (q15_t)0xF3A6,
+	(q15_t)0x809D, (q15_t)0xF374, (q15_t)0x80A2, (q15_t)0xF342,
+	(q15_t)0x80A7, (q15_t)0xF310, (q15_t)0x80AC, (q15_t)0xF2DE,
+	(q15_t)0x80B2, (q15_t)0xF2AC, (q15_t)0x80B7, (q15_t)0xF27A,
+	(q15_t)0x80BC, (q15_t)0xF248, (q15_t)0x80C2, (q15_t)0xF216,
+	(q15_t)0x80C7, (q15_t)0xF1E4, (q15_t)0x80CD, (q15_t)0xF1B2,
+	(q15_t)0x80D2, (q15_t)0xF180, (q15_t)0x80D8, (q15_t)0xF14E,
+	(q15_t)0x80DE, (q15_t)0xF11C, (q15_t)0x80E4, (q15_t)0xF0EA,
+	(q15_t)0x80EA, (q15_t)0xF0B8, (q15_t)0x80F0, (q15_t)0xF086,
+	(q15_t)0x80F6, (q15_t)0xF054, (q15_t)0x80FC, (q15_t)0xF022,
+	(q15_t)0x8102, (q15_t)0xEFF1, (q15_t)0x8109, (q15_t)0xEFBF,
+	(q15_t)0x810F, (q15_t)0xEF8D, (q15_t)0x8116, (q15_t)0xEF5B,
+	(q15_t)0x811C, (q15_t)0xEF29, (q15_t)0x8123, (q15_t)0xEEF7,
+	(q15_t)0x812A, (q15_t)0xEEC6, (q15_t)0x8130, (q15_t)0xEE94,
+	(q15_t)0x8137, (q15_t)0xEE62, (q15_t)0x813E, (q15_t)0xEE30,
+	(q15_t)0x8145, (q15_t)0xEDFE, (q15_t)0x814C, (q15_t)0xEDCD,
+	(q15_t)0x8154, (q15_t)0xED9B, (q15_t)0x815B, (q15_t)0xED69,
+	(q15_t)0x8162, (q15_t)0xED37, (q15_t)0x816A, (q15_t)0xED06,
+	(q15_t)0x8171, (q15_t)0xECD4, (q15_t)0x8179, (q15_t)0xECA2,
+	(q15_t)0x8180, (q15_t)0xEC71, (q15_t)0x8188, (q15_t)0xEC3F,
+	(q15_t)0x8190, (q15_t)0xEC0D, (q15_t)0x8198, (q15_t)0xEBDC,
+	(q15_t)0x81A0, (q15_t)0xEBAA, (q15_t)0x81A8, (q15_t)0xEB78,
+	(q15_t)0x81B0, (q15_t)0xEB47, (q15_t)0x81B8, (q15_t)0xEB15,
+	(q15_t)0x81C0, (q15_t)0xEAE4, (q15_t)0x81C8, (q15_t)0xEAB2,
+	(q15_t)0x81D1, (q15_t)0xEA80, (q15_t)0x81D9, (q15_t)0xEA4F,
+	(q15_t)0x81E2, (q15_t)0xEA1D, (q15_t)0x81EB, (q15_t)0xE9EC,
+	(q15_t)0x81F3, (q15_t)0xE9BA, (q15_t)0x81FC, (q15_t)0xE989,
+	(q15_t)0x8205, (q15_t)0xE957, (q15_t)0x820E, (q15_t)0xE926,
+	(q15_t)0x8217, (q15_t)0xE8F5, (q15_t)0x8220, (q15_t)0xE8C3,
+	(q15_t)0x8229, (q15_t)0xE892, (q15_t)0x8232, (q15_t)0xE860,
+	(q15_t)0x823C, (q15_t)0xE82F, (q15_t)0x8245, (q15_t)0xE7FD,
+	(q15_t)0x824F, (q15_t)0xE7CC, (q15_t)0x8258, (q15_t)0xE79B,
+	(q15_t)0x8262, (q15_t)0xE769, (q15_t)0x826B, (q15_t)0xE738,
+	(q15_t)0x8275, (q15_t)0xE707, (q15_t)0x827F, (q15_t)0xE6D5,
+	(q15_t)0x8289, (q15_t)0xE6A4, (q15_t)0x8293, (q15_t)0xE673,
+	(q15_t)0x829D, (q15_t)0xE642, (q15_t)0x82A7, (q15_t)0xE610,
+	(q15_t)0x82B1, (q15_t)0xE5DF, (q15_t)0x82BC, (q15_t)0xE5AE,
+	(q15_t)0x82C6, (q15_t)0xE57D, (q15_t)0x82D0, (q15_t)0xE54C,
+	(q15_t)0x82DB, (q15_t)0xE51B, (q15_t)0x82E6, (q15_t)0xE4E9,
+	(q15_t)0x82F0, (q15_t)0xE4B8, (q15_t)0x82FB, (q15_t)0xE487,
+	(q15_t)0x8306, (q15_t)0xE456, (q15_t)0x8311, (q15_t)0xE425,
+	(q15_t)0x831C, (q15_t)0xE3F4, (q15_t)0x8327, (q15_t)0xE3C3,
+	(q15_t)0x8332, (q15_t)0xE392, (q15_t)0x833D, (q15_t)0xE361,
+	(q15_t)0x8348, (q15_t)0xE330, (q15_t)0x8354, (q15_t)0xE2FF,
+	(q15_t)0x835F, (q15_t)0xE2CE, (q15_t)0x836B, (q15_t)0xE29D,
+	(q15_t)0x8376, (q15_t)0xE26C, (q15_t)0x8382, (q15_t)0xE23B,
+	(q15_t)0x838E, (q15_t)0xE20A, (q15_t)0x8399, (q15_t)0xE1DA,
+	(q15_t)0x83A5, (q15_t)0xE1A9, (q15_t)0x83B1, (q15_t)0xE178,
+	(q15_t)0x83BD, (q15_t)0xE147, (q15_t)0x83C9, (q15_t)0xE116,
+	(q15_t)0x83D6, (q15_t)0xE0E6, (q15_t)0x83E2, (q15_t)0xE0B5,
+	(q15_t)0x83EE, (q15_t)0xE084, (q15_t)0x83FA, (q15_t)0xE053,
+	(q15_t)0x8407, (q15_t)0xE023, (q15_t)0x8414, (q15_t)0xDFF2,
+	(q15_t)0x8420, (q15_t)0xDFC1, (q15_t)0x842D, (q15_t)0xDF91,
+	(q15_t)0x843A, (q15_t)0xDF60, (q15_t)0x8446, (q15_t)0xDF2F,
+	(q15_t)0x8453, (q15_t)0xDEFF, (q15_t)0x8460, (q15_t)0xDECE,
+	(q15_t)0x846D, (q15_t)0xDE9E, (q15_t)0x847B, (q15_t)0xDE6D,
+	(q15_t)0x8488, (q15_t)0xDE3D, (q15_t)0x8495, (q15_t)0xDE0C,
+	(q15_t)0x84A2, (q15_t)0xDDDC, (q15_t)0x84B0, (q15_t)0xDDAB,
+	(q15_t)0x84BD, (q15_t)0xDD7B, (q15_t)0x84CB, (q15_t)0xDD4B,
+	(q15_t)0x84D9, (q15_t)0xDD1A, (q15_t)0x84E6, (q15_t)0xDCEA,
+	(q15_t)0x84F4, (q15_t)0xDCBA, (q15_t)0x8502, (q15_t)0xDC89,
+	(q15_t)0x8510, (q15_t)0xDC59, (q15_t)0x851E, (q15_t)0xDC29,
+	(q15_t)0x852C, (q15_t)0xDBF8, (q15_t)0x853A, (q15_t)0xDBC8,
+	(q15_t)0x8549, (q15_t)0xDB98, (q15_t)0x8557, (q15_t)0xDB68,
+	(q15_t)0x8565, (q15_t)0xDB38, (q15_t)0x8574, (q15_t)0xDB08,
+	(q15_t)0x8582, (q15_t)0xDAD7, (q15_t)0x8591, (q15_t)0xDAA7,
+	(q15_t)0x85A0, (q15_t)0xDA77, (q15_t)0x85AF, (q15_t)0xDA47,
+	(q15_t)0x85BD, (q15_t)0xDA17, (q15_t)0x85CC, (q15_t)0xD9E7,
+	(q15_t)0x85DB, (q15_t)0xD9B7, (q15_t)0x85EA, (q15_t)0xD987,
+	(q15_t)0x85FA, (q15_t)0xD957, (q15_t)0x8609, (q15_t)0xD927,
+	(q15_t)0x8618, (q15_t)0xD8F8, (q15_t)0x8627, (q15_t)0xD8C8,
+	(q15_t)0x8637, (q15_t)0xD898, (q15_t)0x8646, (q15_t)0xD868,
+	(q15_t)0x8656, (q15_t)0xD838, (q15_t)0x8666, (q15_t)0xD809,
+	(q15_t)0x8675, (q15_t)0xD7D9, (q15_t)0x8685, (q15_t)0xD7A9,
+	(q15_t)0x8695, (q15_t)0xD779, (q15_t)0x86A5, (q15_t)0xD74A,
+	(q15_t)0x86B5, (q15_t)0xD71A, (q15_t)0x86C5, (q15_t)0xD6EA,
+	(q15_t)0x86D5, (q15_t)0xD6BB, (q15_t)0x86E6, (q15_t)0xD68B,
+	(q15_t)0x86F6, (q15_t)0xD65C, (q15_t)0x8706, (q15_t)0xD62C,
+	(q15_t)0x8717, (q15_t)0xD5FD, (q15_t)0x8727, (q15_t)0xD5CD,
+	(q15_t)0x8738, (q15_t)0xD59E, (q15_t)0x8749, (q15_t)0xD56E,
+	(q15_t)0x8759, (q15_t)0xD53F, (q15_t)0x876A, (q15_t)0xD510,
+	(q15_t)0x877B, (q15_t)0xD4E0, (q15_t)0x878C, (q15_t)0xD4B1,
+	(q15_t)0x879D, (q15_t)0xD482, (q15_t)0x87AE, (q15_t)0xD452,
+	(q15_t)0x87BF, (q15_t)0xD423, (q15_t)0x87D1, (q15_t)0xD3F4,
+	(q15_t)0x87E2, (q15_t)0xD3C5, (q15_t)0x87F3, (q15_t)0xD396,
+	(q15_t)0x8805, (q15_t)0xD367, (q15_t)0x8816, (q15_t)0xD337,
+	(q15_t)0x8828, (q15_t)0xD308, (q15_t)0x883A, (q15_t)0xD2D9,
+	(q15_t)0x884B, (q15_t)0xD2AA, (q15_t)0x885D, (q15_t)0xD27B,
+	(q15_t)0x886F, (q15_t)0xD24C, (q15_t)0x8881, (q15_t)0xD21D,
+	(q15_t)0x8893, (q15_t)0xD1EE, (q15_t)0x88A5, (q15_t)0xD1C0,
+	(q15_t)0x88B8, (q15_t)0xD191, (q15_t)0x88CA, (q15_t)0xD162,
+	(q15_t)0x88DC, (q15_t)0xD133, (q15_t)0x88EF, (q15_t)0xD104,
+	(q15_t)0x8901, (q15_t)0xD0D6, (q15_t)0x8914, (q15_t)0xD0A7,
+	(q15_t)0x8926, (q15_t)0xD078, (q15_t)0x8939, (q15_t)0xD04A,
+	(q15_t)0x894C, (q15_t)0xD01B, (q15_t)0x895F, (q15_t)0xCFEC,
+	(q15_t)0x8971, (q15_t)0xCFBE, (q15_t)0x8984, (q15_t)0xCF8F,
+	(q15_t)0x8997, (q15_t)0xCF61, (q15_t)0x89AB, (q15_t)0xCF32,
+	(q15_t)0x89BE, (q15_t)0xCF04, (q15_t)0x89D1, (q15_t)0xCED5,
+	(q15_t)0x89E4, (q15_t)0xCEA7, (q15_t)0x89F8, (q15_t)0xCE79,
+	(q15_t)0x8A0B, (q15_t)0xCE4A, (q15_t)0x8A1F, (q15_t)0xCE1C,
+	(q15_t)0x8A33, (q15_t)0xCDEE, (q15_t)0x8A46, (q15_t)0xCDBF,
+	(q15_t)0x8A5A, (q15_t)0xCD91, (q15_t)0x8A6E, (q15_t)0xCD63,
+	(q15_t)0x8A82, (q15_t)0xCD35, (q15_t)0x8A96, (q15_t)0xCD07,
+	(q15_t)0x8AAA, (q15_t)0xCCD9, (q15_t)0x8ABE, (q15_t)0xCCAB,
+	(q15_t)0x8AD2, (q15_t)0xCC7D, (q15_t)0x8AE6, (q15_t)0xCC4F,
+	(q15_t)0x8AFB, (q15_t)0xCC21, (q15_t)0x8B0F, (q15_t)0xCBF3,
+	(q15_t)0x8B24, (q15_t)0xCBC5, (q15_t)0x8B38, (q15_t)0xCB97,
+	(q15_t)0x8B4D, (q15_t)0xCB69, (q15_t)0x8B61, (q15_t)0xCB3B,
+	(q15_t)0x8B76, (q15_t)0xCB0D, (q15_t)0x8B8B, (q15_t)0xCAE0,
+	(q15_t)0x8BA0, (q15_t)0xCAB2, (q15_t)0x8BB5, (q15_t)0xCA84,
+	(q15_t)0x8BCA, (q15_t)0xCA57, (q15_t)0x8BDF, (q15_t)0xCA29,
+	(q15_t)0x8BF4, (q15_t)0xC9FB, (q15_t)0x8C09, (q15_t)0xC9CE,
+	(q15_t)0x8C1F, (q15_t)0xC9A0, (q15_t)0x8C34, (q15_t)0xC973,
+	(q15_t)0x8C4A, (q15_t)0xC945, (q15_t)0x8C5F, (q15_t)0xC918,
+	(q15_t)0x8C75, (q15_t)0xC8EB, (q15_t)0x8C8A, (q15_t)0xC8BD,
+	(q15_t)0x8CA0, (q15_t)0xC890, (q15_t)0x8CB6, (q15_t)0xC863,
+	(q15_t)0x8CCC, (q15_t)0xC835, (q15_t)0x8CE2, (q15_t)0xC808,
+	(q15_t)0x8CF8, (q15_t)0xC7DB, (q15_t)0x8D0E, (q15_t)0xC7AE,
+	(q15_t)0x8D24, (q15_t)0xC781, (q15_t)0x8D3A, (q15_t)0xC754,
+	(q15_t)0x8D50, (q15_t)0xC727, (q15_t)0x8D67, (q15_t)0xC6F9,
+	(q15_t)0x8D7D, (q15_t)0xC6CD, (q15_t)0x8D94, (q15_t)0xC6A0,
+	(q15_t)0x8DAA, (q15_t)0xC673, (q15_t)0x8DC1, (q15_t)0xC646,
+	(q15_t)0x8DD8, (q15_t)0xC619, (q15_t)0x8DEE, (q15_t)0xC5EC,
+	(q15_t)0x8E05, (q15_t)0xC5BF, (q15_t)0x8E1C, (q15_t)0xC593,
+	(q15_t)0x8E33, (q15_t)0xC566, (q15_t)0x8E4A, (q15_t)0xC539,
+	(q15_t)0x8E61, (q15_t)0xC50D, (q15_t)0x8E79, (q15_t)0xC4E0,
+	(q15_t)0x8E90, (q15_t)0xC4B3, (q15_t)0x8EA7, (q15_t)0xC487,
+	(q15_t)0x8EBE, (q15_t)0xC45A, (q15_t)0x8ED6, (q15_t)0xC42E,
+	(q15_t)0x8EED, (q15_t)0xC402, (q15_t)0x8F05, (q15_t)0xC3D5,
+	(q15_t)0x8F1D, (q15_t)0xC3A9, (q15_t)0x8F34, (q15_t)0xC37C,
+	(q15_t)0x8F4C, (q15_t)0xC350, (q15_t)0x8F64, (q15_t)0xC324,
+	(q15_t)0x8F7C, (q15_t)0xC2F8, (q15_t)0x8F94, (q15_t)0xC2CC,
+	(q15_t)0x8FAC, (q15_t)0xC29F, (q15_t)0x8FC4, (q15_t)0xC273,
+	(q15_t)0x8FDC, (q15_t)0xC247, (q15_t)0x8FF5, (q15_t)0xC21B,
+	(q15_t)0x900D, (q15_t)0xC1EF, (q15_t)0x9025, (q15_t)0xC1C3,
+	(q15_t)0x903E, (q15_t)0xC197, (q15_t)0x9056, (q15_t)0xC16C,
+	(q15_t)0x906F, (q15_t)0xC140, (q15_t)0x9088, (q15_t)0xC114,
+	(q15_t)0x90A0, (q15_t)0xC0E8, (q15_t)0x90B9, (q15_t)0xC0BC,
+	(q15_t)0x90D2, (q15_t)0xC091, (q15_t)0x90EB, (q15_t)0xC065,
+	(q15_t)0x9104, (q15_t)0xC03A, (q15_t)0x911D, (q15_t)0xC00E,
+	(q15_t)0x9136, (q15_t)0xBFE2, (q15_t)0x9150, (q15_t)0xBFB7,
+	(q15_t)0x9169, (q15_t)0xBF8C, (q15_t)0x9182, (q15_t)0xBF60,
+	(q15_t)0x919C, (q15_t)0xBF35, (q15_t)0x91B5, (q15_t)0xBF09,
+	(q15_t)0x91CF, (q15_t)0xBEDE, (q15_t)0x91E8, (q15_t)0xBEB3,
+	(q15_t)0x9202, (q15_t)0xBE88, (q15_t)0x921C, (q15_t)0xBE5D,
+	(q15_t)0x9235, (q15_t)0xBE31, (q15_t)0x924F, (q15_t)0xBE06,
+	(q15_t)0x9269, (q15_t)0xBDDB, (q15_t)0x9283, (q15_t)0xBDB0,
+	(q15_t)0x929D, (q15_t)0xBD85, (q15_t)0x92B7, (q15_t)0xBD5A,
+	(q15_t)0x92D2, (q15_t)0xBD2F, (q15_t)0x92EC, (q15_t)0xBD05,
+	(q15_t)0x9306, (q15_t)0xBCDA, (q15_t)0x9321, (q15_t)0xBCAF,
+	(q15_t)0x933B, (q15_t)0xBC84, (q15_t)0x9356, (q15_t)0xBC5A,
+	(q15_t)0x9370, (q15_t)0xBC2F, (q15_t)0x938B, (q15_t)0xBC04,
+	(q15_t)0x93A6, (q15_t)0xBBDA, (q15_t)0x93C0, (q15_t)0xBBAF,
+	(q15_t)0x93DB, (q15_t)0xBB85, (q15_t)0x93F6, (q15_t)0xBB5A,
+	(q15_t)0x9411, (q15_t)0xBB30, (q15_t)0x942C, (q15_t)0xBB05,
+	(q15_t)0x9447, (q15_t)0xBADB, (q15_t)0x9463, (q15_t)0xBAB1,
+	(q15_t)0x947E, (q15_t)0xBA87, (q15_t)0x9499, (q15_t)0xBA5C,
+	(q15_t)0x94B5, (q15_t)0xBA32, (q15_t)0x94D0, (q15_t)0xBA08,
+	(q15_t)0x94EC, (q15_t)0xB9DE, (q15_t)0x9507, (q15_t)0xB9B4,
+	(q15_t)0x9523, (q15_t)0xB98A, (q15_t)0x953E, (q15_t)0xB960,
+	(q15_t)0x955A, (q15_t)0xB936, (q15_t)0x9576, (q15_t)0xB90C,
+	(q15_t)0x9592, (q15_t)0xB8E3, (q15_t)0x95AE, (q15_t)0xB8B9,
+	(q15_t)0x95CA, (q15_t)0xB88F, (q15_t)0x95E6, (q15_t)0xB865,
+	(q15_t)0x9602, (q15_t)0xB83C, (q15_t)0x961E, (q15_t)0xB812,
+	(q15_t)0x963B, (q15_t)0xB7E9, (q15_t)0x9657, (q15_t)0xB7BF,
+	(q15_t)0x9673, (q15_t)0xB796, (q15_t)0x9690, (q15_t)0xB76C,
+	(q15_t)0x96AC, (q15_t)0xB743, (q15_t)0x96C9, (q15_t)0xB719,
+	(q15_t)0x96E6, (q15_t)0xB6F0, (q15_t)0x9702, (q15_t)0xB6C7,
+	(q15_t)0x971F, (q15_t)0xB69E, (q15_t)0x973C, (q15_t)0xB675,
+	(q15_t)0x9759, (q15_t)0xB64B, (q15_t)0x9776, (q15_t)0xB622,
+	(q15_t)0x9793, (q15_t)0xB5F9, (q15_t)0x97B0, (q15_t)0xB5D0,
+	(q15_t)0x97CD, (q15_t)0xB5A7, (q15_t)0x97EA, (q15_t)0xB57E,
+	(q15_t)0x9808, (q15_t)0xB556, (q15_t)0x9825, (q15_t)0xB52D,
+	(q15_t)0x9842, (q15_t)0xB504, (q15_t)0x9860, (q15_t)0xB4DB,
+	(q15_t)0x987D, (q15_t)0xB4B3, (q15_t)0x989B, (q15_t)0xB48A,
+	(q15_t)0x98B9, (q15_t)0xB461, (q15_t)0x98D6, (q15_t)0xB439,
+	(q15_t)0x98F4, (q15_t)0xB410, (q15_t)0x9912, (q15_t)0xB3E8,
+	(q15_t)0x9930, (q15_t)0xB3C0, (q15_t)0x994E, (q15_t)0xB397,
+	(q15_t)0x996C, (q15_t)0xB36F, (q15_t)0x998A, (q15_t)0xB347,
+	(q15_t)0x99A8, (q15_t)0xB31E, (q15_t)0x99C6, (q15_t)0xB2F6,
+	(q15_t)0x99E5, (q15_t)0xB2CE, (q15_t)0x9A03, (q15_t)0xB2A6,
+	(q15_t)0x9A22, (q15_t)0xB27E, (q15_t)0x9A40, (q15_t)0xB256,
+	(q15_t)0x9A5F, (q15_t)0xB22E, (q15_t)0x9A7D, (q15_t)0xB206,
+	(q15_t)0x9A9C, (q15_t)0xB1DE, (q15_t)0x9ABA, (q15_t)0xB1B7,
+	(q15_t)0x9AD9, (q15_t)0xB18F, (q15_t)0x9AF8, (q15_t)0xB167,
+	(q15_t)0x9B17, (q15_t)0xB140, (q15_t)0x9B36, (q15_t)0xB118,
+	(q15_t)0x9B55, (q15_t)0xB0F0, (q15_t)0x9B74, (q15_t)0xB0C9,
+	(q15_t)0x9B93, (q15_t)0xB0A1, (q15_t)0x9BB2, (q15_t)0xB07A,
+	(q15_t)0x9BD2, (q15_t)0xB053, (q15_t)0x9BF1, (q15_t)0xB02B,
+	(q15_t)0x9C10, (q15_t)0xB004, (q15_t)0x9C30, (q15_t)0xAFDD,
+	(q15_t)0x9C4F, (q15_t)0xAFB6, (q15_t)0x9C6F, (q15_t)0xAF8F,
+	(q15_t)0x9C8E, (q15_t)0xAF68, (q15_t)0x9CAE, (q15_t)0xAF40,
+	(q15_t)0x9CCE, (q15_t)0xAF1A, (q15_t)0x9CEE, (q15_t)0xAEF3,
+	(q15_t)0x9D0D, (q15_t)0xAECC, (q15_t)0x9D2D, (q15_t)0xAEA5,
+	(q15_t)0x9D4D, (q15_t)0xAE7E, (q15_t)0x9D6D, (q15_t)0xAE57,
+	(q15_t)0x9D8E, (q15_t)0xAE31, (q15_t)0x9DAE, (q15_t)0xAE0A,
+	(q15_t)0x9DCE, (q15_t)0xADE3, (q15_t)0x9DEE, (q15_t)0xADBD,
+	(q15_t)0x9E0E, (q15_t)0xAD96, (q15_t)0x9E2F, (q15_t)0xAD70,
+	(q15_t)0x9E4F, (q15_t)0xAD4A, (q15_t)0x9E70, (q15_t)0xAD23,
+	(q15_t)0x9E90, (q15_t)0xACFD, (q15_t)0x9EB1, (q15_t)0xACD7,
+	(q15_t)0x9ED2, (q15_t)0xACB1, (q15_t)0x9EF2, (q15_t)0xAC8A,
+	(q15_t)0x9F13, (q15_t)0xAC64, (q15_t)0x9F34, (q15_t)0xAC3E,
+	(q15_t)0x9F55, (q15_t)0xAC18, (q15_t)0x9F76, (q15_t)0xABF2,
+	(q15_t)0x9F97, (q15_t)0xABCC, (q15_t)0x9FB8, (q15_t)0xABA7,
+	(q15_t)0x9FD9, (q15_t)0xAB81, (q15_t)0x9FFB, (q15_t)0xAB5B,
+	(q15_t)0xA01C, (q15_t)0xAB35, (q15_t)0xA03D, (q15_t)0xAB10,
+	(q15_t)0xA05F, (q15_t)0xAAEA, (q15_t)0xA080, (q15_t)0xAAC5,
+	(q15_t)0xA0A1, (q15_t)0xAA9F, (q15_t)0xA0C3, (q15_t)0xAA7A,
+	(q15_t)0xA0E5, (q15_t)0xAA54, (q15_t)0xA106, (q15_t)0xAA2F,
+	(q15_t)0xA128, (q15_t)0xAA0A, (q15_t)0xA14A, (q15_t)0xA9E5,
+	(q15_t)0xA16C, (q15_t)0xA9BF, (q15_t)0xA18E, (q15_t)0xA99A,
+	(q15_t)0xA1AF, (q15_t)0xA975, (q15_t)0xA1D2, (q15_t)0xA950,
+	(q15_t)0xA1F4, (q15_t)0xA92B, (q15_t)0xA216, (q15_t)0xA906,
+	(q15_t)0xA238, (q15_t)0xA8E2, (q15_t)0xA25A, (q15_t)0xA8BD,
+	(q15_t)0xA27C, (q15_t)0xA898, (q15_t)0xA29F, (q15_t)0xA873,
+	(q15_t)0xA2C1, (q15_t)0xA84F, (q15_t)0xA2E4, (q15_t)0xA82A,
+	(q15_t)0xA306, (q15_t)0xA806, (q15_t)0xA329, (q15_t)0xA7E1,
+	(q15_t)0xA34B, (q15_t)0xA7BD, (q15_t)0xA36E, (q15_t)0xA798,
+	(q15_t)0xA391, (q15_t)0xA774, (q15_t)0xA3B4, (q15_t)0xA750,
+	(q15_t)0xA3D6, (q15_t)0xA72B, (q15_t)0xA3F9, (q15_t)0xA707,
+	(q15_t)0xA41C, (q15_t)0xA6E3, (q15_t)0xA43F, (q15_t)0xA6BF,
+	(q15_t)0xA462, (q15_t)0xA69B, (q15_t)0xA486, (q15_t)0xA677,
+	(q15_t)0xA4A9, (q15_t)0xA653, (q15_t)0xA4CC, (q15_t)0xA62F,
+	(q15_t)0xA4EF, (q15_t)0xA60C, (q15_t)0xA513, (q15_t)0xA5E8,
+	(q15_t)0xA536, (q15_t)0xA5C4, (q15_t)0xA55A, (q15_t)0xA5A1,
+	(q15_t)0xA57D, (q15_t)0xA57D, (q15_t)0xA5A1, (q15_t)0xA55A,
+	(q15_t)0xA5C4, (q15_t)0xA536, (q15_t)0xA5E8, (q15_t)0xA513,
+	(q15_t)0xA60C, (q15_t)0xA4EF, (q15_t)0xA62F, (q15_t)0xA4CC,
+	(q15_t)0xA653, (q15_t)0xA4A9, (q15_t)0xA677, (q15_t)0xA486,
+	(q15_t)0xA69B, (q15_t)0xA462, (q15_t)0xA6BF, (q15_t)0xA43F,
+	(q15_t)0xA6E3, (q15_t)0xA41C, (q15_t)0xA707, (q15_t)0xA3F9,
+	(q15_t)0xA72B, (q15_t)0xA3D6, (q15_t)0xA750, (q15_t)0xA3B4,
+	(q15_t)0xA774, (q15_t)0xA391, (q15_t)0xA798, (q15_t)0xA36E,
+	(q15_t)0xA7BD, (q15_t)0xA34B, (q15_t)0xA7E1, (q15_t)0xA329,
+	(q15_t)0xA806, (q15_t)0xA306, (q15_t)0xA82A, (q15_t)0xA2E4,
+	(q15_t)0xA84F, (q15_t)0xA2C1, (q15_t)0xA873, (q15_t)0xA29F,
+	(q15_t)0xA898, (q15_t)0xA27C, (q15_t)0xA8BD, (q15_t)0xA25A,
+	(q15_t)0xA8E2, (q15_t)0xA238, (q15_t)0xA906, (q15_t)0xA216,
+	(q15_t)0xA92B, (q15_t)0xA1F4, (q15_t)0xA950, (q15_t)0xA1D2,
+	(q15_t)0xA975, (q15_t)0xA1AF, (q15_t)0xA99A, (q15_t)0xA18E,
+	(q15_t)0xA9BF, (q15_t)0xA16C, (q15_t)0xA9E5, (q15_t)0xA14A,
+	(q15_t)0xAA0A, (q15_t)0xA128, (q15_t)0xAA2F, (q15_t)0xA106,
+	(q15_t)0xAA54, (q15_t)0xA0E5, (q15_t)0xAA7A, (q15_t)0xA0C3,
+	(q15_t)0xAA9F, (q15_t)0xA0A1, (q15_t)0xAAC5, (q15_t)0xA080,
+	(q15_t)0xAAEA, (q15_t)0xA05F, (q15_t)0xAB10, (q15_t)0xA03D,
+	(q15_t)0xAB35, (q15_t)0xA01C, (q15_t)0xAB5B, (q15_t)0x9FFB,
+	(q15_t)0xAB81, (q15_t)0x9FD9, (q15_t)0xABA7, (q15_t)0x9FB8,
+	(q15_t)0xABCC, (q15_t)0x9F97, (q15_t)0xABF2, (q15_t)0x9F76,
+	(q15_t)0xAC18, (q15_t)0x9F55, (q15_t)0xAC3E, (q15_t)0x9F34,
+	(q15_t)0xAC64, (q15_t)0x9F13, (q15_t)0xAC8A, (q15_t)0x9EF2,
+	(q15_t)0xACB1, (q15_t)0x9ED2, (q15_t)0xACD7, (q15_t)0x9EB1,
+	(q15_t)0xACFD, (q15_t)0x9E90, (q15_t)0xAD23, (q15_t)0x9E70,
+	(q15_t)0xAD4A, (q15_t)0x9E4F, (q15_t)0xAD70, (q15_t)0x9E2F,
+	(q15_t)0xAD96, (q15_t)0x9E0E, (q15_t)0xADBD, (q15_t)0x9DEE,
+	(q15_t)0xADE3, (q15_t)0x9DCE, (q15_t)0xAE0A, (q15_t)0x9DAE,
+	(q15_t)0xAE31, (q15_t)0x9D8E, (q15_t)0xAE57, (q15_t)0x9D6D,
+	(q15_t)0xAE7E, (q15_t)0x9D4D, (q15_t)0xAEA5, (q15_t)0x9D2D,
+	(q15_t)0xAECC, (q15_t)0x9D0D, (q15_t)0xAEF3, (q15_t)0x9CEE,
+	(q15_t)0xAF1A, (q15_t)0x9CCE, (q15_t)0xAF40, (q15_t)0x9CAE,
+	(q15_t)0xAF68, (q15_t)0x9C8E, (q15_t)0xAF8F, (q15_t)0x9C6F,
+	(q15_t)0xAFB6, (q15_t)0x9C4F, (q15_t)0xAFDD, (q15_t)0x9C30,
+	(q15_t)0xB004, (q15_t)0x9C10, (q15_t)0xB02B, (q15_t)0x9BF1,
+	(q15_t)0xB053, (q15_t)0x9BD2, (q15_t)0xB07A, (q15_t)0x9BB2,
+	(q15_t)0xB0A1, (q15_t)0x9B93, (q15_t)0xB0C9, (q15_t)0x9B74,
+	(q15_t)0xB0F0, (q15_t)0x9B55, (q15_t)0xB118, (q15_t)0x9B36,
+	(q15_t)0xB140, (q15_t)0x9B17, (q15_t)0xB167, (q15_t)0x9AF8,
+	(q15_t)0xB18F, (q15_t)0x9AD9, (q15_t)0xB1B7, (q15_t)0x9ABA,
+	(q15_t)0xB1DE, (q15_t)0x9A9C, (q15_t)0xB206, (q15_t)0x9A7D,
+	(q15_t)0xB22E, (q15_t)0x9A5F, (q15_t)0xB256, (q15_t)0x9A40,
+	(q15_t)0xB27E, (q15_t)0x9A22, (q15_t)0xB2A6, (q15_t)0x9A03,
+	(q15_t)0xB2CE, (q15_t)0x99E5, (q15_t)0xB2F6, (q15_t)0x99C6,
+	(q15_t)0xB31E, (q15_t)0x99A8, (q15_t)0xB347, (q15_t)0x998A,
+	(q15_t)0xB36F, (q15_t)0x996C, (q15_t)0xB397, (q15_t)0x994E,
+	(q15_t)0xB3C0, (q15_t)0x9930, (q15_t)0xB3E8, (q15_t)0x9912,
+	(q15_t)0xB410, (q15_t)0x98F4, (q15_t)0xB439, (q15_t)0x98D6,
+	(q15_t)0xB461, (q15_t)0x98B9, (q15_t)0xB48A, (q15_t)0x989B,
+	(q15_t)0xB4B3, (q15_t)0x987D, (q15_t)0xB4DB, (q15_t)0x9860,
+	(q15_t)0xB504, (q15_t)0x9842, (q15_t)0xB52D, (q15_t)0x9825,
+	(q15_t)0xB556, (q15_t)0x9808, (q15_t)0xB57E, (q15_t)0x97EA,
+	(q15_t)0xB5A7, (q15_t)0x97CD, (q15_t)0xB5D0, (q15_t)0x97B0,
+	(q15_t)0xB5F9, (q15_t)0x9793, (q15_t)0xB622, (q15_t)0x9776,
+	(q15_t)0xB64B, (q15_t)0x9759, (q15_t)0xB675, (q15_t)0x973C,
+	(q15_t)0xB69E, (q15_t)0x971F, (q15_t)0xB6C7, (q15_t)0x9702,
+	(q15_t)0xB6F0, (q15_t)0x96E6, (q15_t)0xB719, (q15_t)0x96C9,
+	(q15_t)0xB743, (q15_t)0x96AC, (q15_t)0xB76C, (q15_t)0x9690,
+	(q15_t)0xB796, (q15_t)0x9673, (q15_t)0xB7BF, (q15_t)0x9657,
+	(q15_t)0xB7E9, (q15_t)0x963B, (q15_t)0xB812, (q15_t)0x961E,
+	(q15_t)0xB83C, (q15_t)0x9602, (q15_t)0xB865, (q15_t)0x95E6,
+	(q15_t)0xB88F, (q15_t)0x95CA, (q15_t)0xB8B9, (q15_t)0x95AE,
+	(q15_t)0xB8E3, (q15_t)0x9592, (q15_t)0xB90C, (q15_t)0x9576,
+	(q15_t)0xB936, (q15_t)0x955A, (q15_t)0xB960, (q15_t)0x953E,
+	(q15_t)0xB98A, (q15_t)0x9523, (q15_t)0xB9B4, (q15_t)0x9507,
+	(q15_t)0xB9DE, (q15_t)0x94EC, (q15_t)0xBA08, (q15_t)0x94D0,
+	(q15_t)0xBA32, (q15_t)0x94B5, (q15_t)0xBA5C, (q15_t)0x9499,
+	(q15_t)0xBA87, (q15_t)0x947E, (q15_t)0xBAB1, (q15_t)0x9463,
+	(q15_t)0xBADB, (q15_t)0x9447, (q15_t)0xBB05, (q15_t)0x942C,
+	(q15_t)0xBB30, (q15_t)0x9411, (q15_t)0xBB5A, (q15_t)0x93F6,
+	(q15_t)0xBB85, (q15_t)0x93DB, (q15_t)0xBBAF, (q15_t)0x93C0,
+	(q15_t)0xBBDA, (q15_t)0x93A6, (q15_t)0xBC04, (q15_t)0x938B,
+	(q15_t)0xBC2F, (q15_t)0x9370, (q15_t)0xBC5A, (q15_t)0x9356,
+	(q15_t)0xBC84, (q15_t)0x933B, (q15_t)0xBCAF, (q15_t)0x9321,
+	(q15_t)0xBCDA, (q15_t)0x9306, (q15_t)0xBD05, (q15_t)0x92EC,
+	(q15_t)0xBD2F, (q15_t)0x92D2, (q15_t)0xBD5A, (q15_t)0x92B7,
+	(q15_t)0xBD85, (q15_t)0x929D, (q15_t)0xBDB0, (q15_t)0x9283,
+	(q15_t)0xBDDB, (q15_t)0x9269, (q15_t)0xBE06, (q15_t)0x924F,
+	(q15_t)0xBE31, (q15_t)0x9235, (q15_t)0xBE5D, (q15_t)0x921C,
+	(q15_t)0xBE88, (q15_t)0x9202, (q15_t)0xBEB3, (q15_t)0x91E8,
+	(q15_t)0xBEDE, (q15_t)0x91CF, (q15_t)0xBF09, (q15_t)0x91B5,
+	(q15_t)0xBF35, (q15_t)0x919C, (q15_t)0xBF60, (q15_t)0x9182,
+	(q15_t)0xBF8C, (q15_t)0x9169, (q15_t)0xBFB7, (q15_t)0x9150,
+	(q15_t)0xBFE2, (q15_t)0x9136, (q15_t)0xC00E, (q15_t)0x911D,
+	(q15_t)0xC03A, (q15_t)0x9104, (q15_t)0xC065, (q15_t)0x90EB,
+	(q15_t)0xC091, (q15_t)0x90D2, (q15_t)0xC0BC, (q15_t)0x90B9,
+	(q15_t)0xC0E8, (q15_t)0x90A0, (q15_t)0xC114, (q15_t)0x9088,
+	(q15_t)0xC140, (q15_t)0x906F, (q15_t)0xC16C, (q15_t)0x9056,
+	(q15_t)0xC197, (q15_t)0x903E, (q15_t)0xC1C3, (q15_t)0x9025,
+	(q15_t)0xC1EF, (q15_t)0x900D, (q15_t)0xC21B, (q15_t)0x8FF5,
+	(q15_t)0xC247, (q15_t)0x8FDC, (q15_t)0xC273, (q15_t)0x8FC4,
+	(q15_t)0xC29F, (q15_t)0x8FAC, (q15_t)0xC2CC, (q15_t)0x8F94,
+	(q15_t)0xC2F8, (q15_t)0x8F7C, (q15_t)0xC324, (q15_t)0x8F64,
+	(q15_t)0xC350, (q15_t)0x8F4C, (q15_t)0xC37C, (q15_t)0x8F34,
+	(q15_t)0xC3A9, (q15_t)0x8F1D, (q15_t)0xC3D5, (q15_t)0x8F05,
+	(q15_t)0xC402, (q15_t)0x8EED, (q15_t)0xC42E, (q15_t)0x8ED6,
+	(q15_t)0xC45A, (q15_t)0x8EBE, (q15_t)0xC487, (q15_t)0x8EA7,
+	(q15_t)0xC4B3, (q15_t)0x8E90, (q15_t)0xC4E0, (q15_t)0x8E79,
+	(q15_t)0xC50D, (q15_t)0x8E61, (q15_t)0xC539, (q15_t)0x8E4A,
+	(q15_t)0xC566, (q15_t)0x8E33, (q15_t)0xC593, (q15_t)0x8E1C,
+	(q15_t)0xC5BF, (q15_t)0x8E05, (q15_t)0xC5EC, (q15_t)0x8DEE,
+	(q15_t)0xC619, (q15_t)0x8DD8, (q15_t)0xC646, (q15_t)0x8DC1,
+	(q15_t)0xC673, (q15_t)0x8DAA, (q15_t)0xC6A0, (q15_t)0x8D94,
+	(q15_t)0xC6CD, (q15_t)0x8D7D, (q15_t)0xC6F9, (q15_t)0x8D67,
+	(q15_t)0xC727, (q15_t)0x8D50, (q15_t)0xC754, (q15_t)0x8D3A,
+	(q15_t)0xC781, (q15_t)0x8D24, (q15_t)0xC7AE, (q15_t)0x8D0E,
+	(q15_t)0xC7DB, (q15_t)0x8CF8, (q15_t)0xC808, (q15_t)0x8CE2,
+	(q15_t)0xC835, (q15_t)0x8CCC, (q15_t)0xC863, (q15_t)0x8CB6,
+	(q15_t)0xC890, (q15_t)0x8CA0, (q15_t)0xC8BD, (q15_t)0x8C8A,
+	(q15_t)0xC8EB, (q15_t)0x8C75, (q15_t)0xC918, (q15_t)0x8C5F,
+	(q15_t)0xC945, (q15_t)0x8C4A, (q15_t)0xC973, (q15_t)0x8C34,
+	(q15_t)0xC9A0, (q15_t)0x8C1F, (q15_t)0xC9CE, (q15_t)0x8C09,
+	(q15_t)0xC9FB, (q15_t)0x8BF4, (q15_t)0xCA29, (q15_t)0x8BDF,
+	(q15_t)0xCA57, (q15_t)0x8BCA, (q15_t)0xCA84, (q15_t)0x8BB5,
+	(q15_t)0xCAB2, (q15_t)0x8BA0, (q15_t)0xCAE0, (q15_t)0x8B8B,
+	(q15_t)0xCB0D, (q15_t)0x8B76, (q15_t)0xCB3B, (q15_t)0x8B61,
+	(q15_t)0xCB69, (q15_t)0x8B4D, (q15_t)0xCB97, (q15_t)0x8B38,
+	(q15_t)0xCBC5, (q15_t)0x8B24, (q15_t)0xCBF3, (q15_t)0x8B0F,
+	(q15_t)0xCC21, (q15_t)0x8AFB, (q15_t)0xCC4F, (q15_t)0x8AE6,
+	(q15_t)0xCC7D, (q15_t)0x8AD2, (q15_t)0xCCAB, (q15_t)0x8ABE,
+	(q15_t)0xCCD9, (q15_t)0x8AAA, (q15_t)0xCD07, (q15_t)0x8A96,
+	(q15_t)0xCD35, (q15_t)0x8A82, (q15_t)0xCD63, (q15_t)0x8A6E,
+	(q15_t)0xCD91, (q15_t)0x8A5A, (q15_t)0xCDBF, (q15_t)0x8A46,
+	(q15_t)0xCDEE, (q15_t)0x8A33, (q15_t)0xCE1C, (q15_t)0x8A1F,
+	(q15_t)0xCE4A, (q15_t)0x8A0B, (q15_t)0xCE79, (q15_t)0x89F8,
+	(q15_t)0xCEA7, (q15_t)0x89E4, (q15_t)0xCED5, (q15_t)0x89D1,
+	(q15_t)0xCF04, (q15_t)0x89BE, (q15_t)0xCF32, (q15_t)0x89AB,
+	(q15_t)0xCF61, (q15_t)0x8997, (q15_t)0xCF8F, (q15_t)0x8984,
+	(q15_t)0xCFBE, (q15_t)0x8971, (q15_t)0xCFEC, (q15_t)0x895F,
+	(q15_t)0xD01B, (q15_t)0x894C, (q15_t)0xD04A, (q15_t)0x8939,
+	(q15_t)0xD078, (q15_t)0x8926, (q15_t)0xD0A7, (q15_t)0x8914,
+	(q15_t)0xD0D6, (q15_t)0x8901, (q15_t)0xD104, (q15_t)0x88EF,
+	(q15_t)0xD133, (q15_t)0x88DC, (q15_t)0xD162, (q15_t)0x88CA,
+	(q15_t)0xD191, (q15_t)0x88B8, (q15_t)0xD1C0, (q15_t)0x88A5,
+	(q15_t)0xD1EE, (q15_t)0x8893, (q15_t)0xD21D, (q15_t)0x8881,
+	(q15_t)0xD24C, (q15_t)0x886F, (q15_t)0xD27B, (q15_t)0x885D,
+	(q15_t)0xD2AA, (q15_t)0x884B, (q15_t)0xD2D9, (q15_t)0x883A,
+	(q15_t)0xD308, (q15_t)0x8828, (q15_t)0xD337, (q15_t)0x8816,
+	(q15_t)0xD367, (q15_t)0x8805, (q15_t)0xD396, (q15_t)0x87F3,
+	(q15_t)0xD3C5, (q15_t)0x87E2, (q15_t)0xD3F4, (q15_t)0x87D1,
+	(q15_t)0xD423, (q15_t)0x87BF, (q15_t)0xD452, (q15_t)0x87AE,
+	(q15_t)0xD482, (q15_t)0x879D, (q15_t)0xD4B1, (q15_t)0x878C,
+	(q15_t)0xD4E0, (q15_t)0x877B, (q15_t)0xD510, (q15_t)0x876A,
+	(q15_t)0xD53F, (q15_t)0x8759, (q15_t)0xD56E, (q15_t)0x8749,
+	(q15_t)0xD59E, (q15_t)0x8738, (q15_t)0xD5CD, (q15_t)0x8727,
+	(q15_t)0xD5FD, (q15_t)0x8717, (q15_t)0xD62C, (q15_t)0x8706,
+	(q15_t)0xD65C, (q15_t)0x86F6, (q15_t)0xD68B, (q15_t)0x86E6,
+	(q15_t)0xD6BB, (q15_t)0x86D5, (q15_t)0xD6EA, (q15_t)0x86C5,
+	(q15_t)0xD71A, (q15_t)0x86B5, (q15_t)0xD74A, (q15_t)0x86A5,
+	(q15_t)0xD779, (q15_t)0x8695, (q15_t)0xD7A9, (q15_t)0x8685,
+	(q15_t)0xD7D9, (q15_t)0x8675, (q15_t)0xD809, (q15_t)0x8666,
+	(q15_t)0xD838, (q15_t)0x8656, (q15_t)0xD868, (q15_t)0x8646,
+	(q15_t)0xD898, (q15_t)0x8637, (q15_t)0xD8C8, (q15_t)0x8627,
+	(q15_t)0xD8F8, (q15_t)0x8618, (q15_t)0xD927, (q15_t)0x8609,
+	(q15_t)0xD957, (q15_t)0x85FA, (q15_t)0xD987, (q15_t)0x85EA,
+	(q15_t)0xD9B7, (q15_t)0x85DB, (q15_t)0xD9E7, (q15_t)0x85CC,
+	(q15_t)0xDA17, (q15_t)0x85BD, (q15_t)0xDA47, (q15_t)0x85AF,
+	(q15_t)0xDA77, (q15_t)0x85A0, (q15_t)0xDAA7, (q15_t)0x8591,
+	(q15_t)0xDAD7, (q15_t)0x8582, (q15_t)0xDB08, (q15_t)0x8574,
+	(q15_t)0xDB38, (q15_t)0x8565, (q15_t)0xDB68, (q15_t)0x8557,
+	(q15_t)0xDB98, (q15_t)0x8549, (q15_t)0xDBC8, (q15_t)0x853A,
+	(q15_t)0xDBF8, (q15_t)0x852C, (q15_t)0xDC29, (q15_t)0x851E,
+	(q15_t)0xDC59, (q15_t)0x8510, (q15_t)0xDC89, (q15_t)0x8502,
+	(q15_t)0xDCBA, (q15_t)0x84F4, (q15_t)0xDCEA, (q15_t)0x84E6,
+	(q15_t)0xDD1A, (q15_t)0x84D9, (q15_t)0xDD4B, (q15_t)0x84CB,
+	(q15_t)0xDD7B, (q15_t)0x84BD, (q15_t)0xDDAB, (q15_t)0x84B0,
+	(q15_t)0xDDDC, (q15_t)0x84A2, (q15_t)0xDE0C, (q15_t)0x8495,
+	(q15_t)0xDE3D, (q15_t)0x8488, (q15_t)0xDE6D, (q15_t)0x847B,
+	(q15_t)0xDE9E, (q15_t)0x846D, (q15_t)0xDECE, (q15_t)0x8460,
+	(q15_t)0xDEFF, (q15_t)0x8453, (q15_t)0xDF2F, (q15_t)0x8446,
+	(q15_t)0xDF60, (q15_t)0x843A, (q15_t)0xDF91, (q15_t)0x842D,
+	(q15_t)0xDFC1, (q15_t)0x8420, (q15_t)0xDFF2, (q15_t)0x8414,
+	(q15_t)0xE023, (q15_t)0x8407, (q15_t)0xE053, (q15_t)0x83FA,
+	(q15_t)0xE084, (q15_t)0x83EE, (q15_t)0xE0B5, (q15_t)0x83E2,
+	(q15_t)0xE0E6, (q15_t)0x83D6, (q15_t)0xE116, (q15_t)0x83C9,
+	(q15_t)0xE147, (q15_t)0x83BD, (q15_t)0xE178, (q15_t)0x83B1,
+	(q15_t)0xE1A9, (q15_t)0x83A5, (q15_t)0xE1DA, (q15_t)0x8399,
+	(q15_t)0xE20A, (q15_t)0x838E, (q15_t)0xE23B, (q15_t)0x8382,
+	(q15_t)0xE26C, (q15_t)0x8376, (q15_t)0xE29D, (q15_t)0x836B,
+	(q15_t)0xE2CE, (q15_t)0x835F, (q15_t)0xE2FF, (q15_t)0x8354,
+	(q15_t)0xE330, (q15_t)0x8348, (q15_t)0xE361, (q15_t)0x833D,
+	(q15_t)0xE392, (q15_t)0x8332, (q15_t)0xE3C3, (q15_t)0x8327,
+	(q15_t)0xE3F4, (q15_t)0x831C, (q15_t)0xE425, (q15_t)0x8311,
+	(q15_t)0xE456, (q15_t)0x8306, (q15_t)0xE487, (q15_t)0x82FB,
+	(q15_t)0xE4B8, (q15_t)0x82F0, (q15_t)0xE4E9, (q15_t)0x82E6,
+	(q15_t)0xE51B, (q15_t)0x82DB, (q15_t)0xE54C, (q15_t)0x82D0,
+	(q15_t)0xE57D, (q15_t)0x82C6, (q15_t)0xE5AE, (q15_t)0x82BC,
+	(q15_t)0xE5DF, (q15_t)0x82B1, (q15_t)0xE610, (q15_t)0x82A7,
+	(q15_t)0xE642, (q15_t)0x829D, (q15_t)0xE673, (q15_t)0x8293,
+	(q15_t)0xE6A4, (q15_t)0x8289, (q15_t)0xE6D5, (q15_t)0x827F,
+	(q15_t)0xE707, (q15_t)0x8275, (q15_t)0xE738, (q15_t)0x826B,
+	(q15_t)0xE769, (q15_t)0x8262, (q15_t)0xE79B, (q15_t)0x8258,
+	(q15_t)0xE7CC, (q15_t)0x824F, (q15_t)0xE7FD, (q15_t)0x8245,
+	(q15_t)0xE82F, (q15_t)0x823C, (q15_t)0xE860, (q15_t)0x8232,
+	(q15_t)0xE892, (q15_t)0x8229, (q15_t)0xE8C3, (q15_t)0x8220,
+	(q15_t)0xE8F5, (q15_t)0x8217, (q15_t)0xE926, (q15_t)0x820E,
+	(q15_t)0xE957, (q15_t)0x8205, (q15_t)0xE989, (q15_t)0x81FC,
+	(q15_t)0xE9BA, (q15_t)0x81F3, (q15_t)0xE9EC, (q15_t)0x81EB,
+	(q15_t)0xEA1D, (q15_t)0x81E2, (q15_t)0xEA4F, (q15_t)0x81D9,
+	(q15_t)0xEA80, (q15_t)0x81D1, (q15_t)0xEAB2, (q15_t)0x81C8,
+	(q15_t)0xEAE4, (q15_t)0x81C0, (q15_t)0xEB15, (q15_t)0x81B8,
+	(q15_t)0xEB47, (q15_t)0x81B0, (q15_t)0xEB78, (q15_t)0x81A8,
+	(q15_t)0xEBAA, (q15_t)0x81A0, (q15_t)0xEBDC, (q15_t)0x8198,
+	(q15_t)0xEC0D, (q15_t)0x8190, (q15_t)0xEC3F, (q15_t)0x8188,
+	(q15_t)0xEC71, (q15_t)0x8180, (q15_t)0xECA2, (q15_t)0x8179,
+	(q15_t)0xECD4, (q15_t)0x8171, (q15_t)0xED06, (q15_t)0x816A,
+	(q15_t)0xED37, (q15_t)0x8162, (q15_t)0xED69, (q15_t)0x815B,
+	(q15_t)0xED9B, (q15_t)0x8154, (q15_t)0xEDCD, (q15_t)0x814C,
+	(q15_t)0xEDFE, (q15_t)0x8145, (q15_t)0xEE30, (q15_t)0x813E,
+	(q15_t)0xEE62, (q15_t)0x8137, (q15_t)0xEE94, (q15_t)0x8130,
+	(q15_t)0xEEC6, (q15_t)0x812A, (q15_t)0xEEF7, (q15_t)0x8123,
+	(q15_t)0xEF29, (q15_t)0x811C, (q15_t)0xEF5B, (q15_t)0x8116,
+	(q15_t)0xEF8D, (q15_t)0x810F, (q15_t)0xEFBF, (q15_t)0x8109,
+	(q15_t)0xEFF1, (q15_t)0x8102, (q15_t)0xF022, (q15_t)0x80FC,
+	(q15_t)0xF054, (q15_t)0x80F6, (q15_t)0xF086, (q15_t)0x80F0,
+	(q15_t)0xF0B8, (q15_t)0x80EA, (q15_t)0xF0EA, (q15_t)0x80E4,
+	(q15_t)0xF11C, (q15_t)0x80DE, (q15_t)0xF14E, (q15_t)0x80D8,
+	(q15_t)0xF180, (q15_t)0x80D2, (q15_t)0xF1B2, (q15_t)0x80CD,
+	(q15_t)0xF1E4, (q15_t)0x80C7, (q15_t)0xF216, (q15_t)0x80C2,
+	(q15_t)0xF248, (q15_t)0x80BC, (q15_t)0xF27A, (q15_t)0x80B7,
+	(q15_t)0xF2AC, (q15_t)0x80B2, (q15_t)0xF2DE, (q15_t)0x80AC,
+	(q15_t)0xF310, (q15_t)0x80A7, (q15_t)0xF342, (q15_t)0x80A2,
+	(q15_t)0xF374, (q15_t)0x809D, (q15_t)0xF3A6, (q15_t)0x8098,
+	(q15_t)0xF3D8, (q15_t)0x8094, (q15_t)0xF40A, (q15_t)0x808F,
+	(q15_t)0xF43C, (q15_t)0x808A, (q15_t)0xF46E, (q15_t)0x8086,
+	(q15_t)0xF4A0, (q15_t)0x8081, (q15_t)0xF4D2, (q15_t)0x807D,
+	(q15_t)0xF504, (q15_t)0x8078, (q15_t)0xF536, (q15_t)0x8074,
+	(q15_t)0xF568, (q15_t)0x8070, (q15_t)0xF59A, (q15_t)0x806C,
+	(q15_t)0xF5CC, (q15_t)0x8068, (q15_t)0xF5FF, (q15_t)0x8064,
+	(q15_t)0xF631, (q15_t)0x8060, (q15_t)0xF663, (q15_t)0x805C,
+	(q15_t)0xF695, (q15_t)0x8058, (q15_t)0xF6C7, (q15_t)0x8055,
+	(q15_t)0xF6F9, (q15_t)0x8051, (q15_t)0xF72B, (q15_t)0x804E,
+	(q15_t)0xF75D, (q15_t)0x804A, (q15_t)0xF790, (q15_t)0x8047,
+	(q15_t)0xF7C2, (q15_t)0x8043, (q15_t)0xF7F4, (q15_t)0x8040,
+	(q15_t)0xF826, (q15_t)0x803D, (q15_t)0xF858, (q15_t)0x803A,
+	(q15_t)0xF88A, (q15_t)0x8037, (q15_t)0xF8BD, (q15_t)0x8034,
+	(q15_t)0xF8EF, (q15_t)0x8031, (q15_t)0xF921, (q15_t)0x802F,
+	(q15_t)0xF953, (q15_t)0x802C, (q15_t)0xF985, (q15_t)0x8029,
+	(q15_t)0xF9B8, (q15_t)0x8027, (q15_t)0xF9EA, (q15_t)0x8025,
+	(q15_t)0xFA1C, (q15_t)0x8022, (q15_t)0xFA4E, (q15_t)0x8020,
+	(q15_t)0xFA80, (q15_t)0x801E, (q15_t)0xFAB3, (q15_t)0x801C,
+	(q15_t)0xFAE5, (q15_t)0x801A, (q15_t)0xFB17, (q15_t)0x8018,
+	(q15_t)0xFB49, (q15_t)0x8016, (q15_t)0xFB7C, (q15_t)0x8014,
+	(q15_t)0xFBAE, (q15_t)0x8012, (q15_t)0xFBE0, (q15_t)0x8011,
+	(q15_t)0xFC12, (q15_t)0x800F, (q15_t)0xFC45, (q15_t)0x800D,
+	(q15_t)0xFC77, (q15_t)0x800C, (q15_t)0xFCA9, (q15_t)0x800B,
+	(q15_t)0xFCDB, (q15_t)0x8009, (q15_t)0xFD0E, (q15_t)0x8008,
+	(q15_t)0xFD40, (q15_t)0x8007, (q15_t)0xFD72, (q15_t)0x8006,
+	(q15_t)0xFDA4, (q15_t)0x8005, (q15_t)0xFDD7, (q15_t)0x8004,
+	(q15_t)0xFE09, (q15_t)0x8003, (q15_t)0xFE3B, (q15_t)0x8003,
+	(q15_t)0xFE6D, (q15_t)0x8002, (q15_t)0xFEA0, (q15_t)0x8001,
+	(q15_t)0xFED2, (q15_t)0x8001, (q15_t)0xFF04, (q15_t)0x8000,
+	(q15_t)0xFF36, (q15_t)0x8000, (q15_t)0xFF69, (q15_t)0x8000,
+	(q15_t)0xFF9B, (q15_t)0x8000, (q15_t)0xFFCD, (q15_t)0x8000
+};
+
+
+/**
+* @} end of CFFT_CIFFT group
+*/
+
+/*
+* @brief  Q15 table for reciprocal
+*/
+const q15_t ALIGN4 armRecipTableQ15[64] = {
+ 0x7F03, 0x7D13, 0x7B31, 0x795E, 0x7798, 0x75E0,
+ 0x7434, 0x7294, 0x70FF, 0x6F76, 0x6DF6, 0x6C82,
+ 0x6B16, 0x69B5, 0x685C, 0x670C, 0x65C4, 0x6484,
+ 0x634C, 0x621C, 0x60F3, 0x5FD0, 0x5EB5, 0x5DA0,
+ 0x5C91, 0x5B88, 0x5A85, 0x5988, 0x5890, 0x579E,
+ 0x56B0, 0x55C8, 0x54E4, 0x5405, 0x532B, 0x5255,
+ 0x5183, 0x50B6, 0x4FEC, 0x4F26, 0x4E64, 0x4DA6,
+ 0x4CEC, 0x4C34, 0x4B81, 0x4AD0, 0x4A23, 0x4978,
+ 0x48D1, 0x482D, 0x478C, 0x46ED, 0x4651, 0x45B8,
+ 0x4521, 0x448D, 0x43FC, 0x436C, 0x42DF, 0x4255,
+ 0x41CC, 0x4146, 0x40C2, 0x4040
+};
+
+/*
+* @brief  Q31 table for reciprocal
+*/
+const q31_t armRecipTableQ31[64] = {
+  0x7F03F03F, 0x7D137420, 0x7B31E739, 0x795E9F94, 0x7798FD29, 0x75E06928,
+  0x7434554D, 0x72943B4B, 0x70FF9C40, 0x6F760031, 0x6DF6F593, 0x6C8210E3,
+  0x6B16EC3A, 0x69B526F6, 0x685C655F, 0x670C505D, 0x65C4952D, 0x6484E519,
+  0x634CF53E, 0x621C7E4F, 0x60F33C61, 0x5FD0EEB3, 0x5EB55785, 0x5DA03BEB,
+  0x5C9163A1, 0x5B8898E6, 0x5A85A85A, 0x598860DF, 0x58909373, 0x579E1318,
+  0x56B0B4B8, 0x55C84F0B, 0x54E4BA80, 0x5405D124, 0x532B6E8F, 0x52556FD0,
+  0x5183B35A, 0x50B618F3, 0x4FEC81A2, 0x4F26CFA2, 0x4E64E64E, 0x4DA6AA1D,
+  0x4CEC008B, 0x4C34D010, 0x4B810016, 0x4AD078EF, 0x4A2323C4, 0x4978EA96,
+  0x48D1B827, 0x482D77FE, 0x478C1657, 0x46ED801D, 0x4651A2E5, 0x45B86CE2,
+  0x4521CCE1, 0x448DB244, 0x43FC0CFA, 0x436CCD78, 0x42DFE4B4, 0x42554426,
+  0x41CCDDB6, 0x4146A3C6, 0x40C28923, 0x40408102
+};
+
+const uint16_t armBitRevIndexTable16[ARMBITREVINDEXTABLE_16_TABLE_LENGTH] =
+{
+   /* 8x2, size 20 */
+   8,64, 24,72, 16,64, 40,80, 32,64, 56,88, 48,72, 88,104, 72,96, 104,112
+};
+
+const uint16_t armBitRevIndexTable32[ARMBITREVINDEXTABLE_32_TABLE_LENGTH] =
+{
+   /* 8x4, size 48 */
+   8,64, 16,128, 24,192, 32,64, 40,72, 48,136, 56,200, 64,128, 72,80, 88,208,
+   80,144, 96,192, 104,208, 112,152, 120,216, 136,192, 144,160, 168,208,
+   152,224, 176,208, 184,232, 216,240, 200,224, 232,240
+};
+
+const uint16_t armBitRevIndexTable64[ARMBITREVINDEXTABLE_64_TABLE_LENGTH] =
+{
+   /* radix 8, size 56 */
+   8,64, 16,128, 24,192, 32,256, 40,320, 48,384, 56,448, 80,136, 88,200,
+   96,264, 104,328, 112,392, 120,456, 152,208, 160,272, 168,336, 176,400,
+   184,464, 224,280, 232,344, 240,408, 248,472, 296,352, 304,416, 312,480,
+   368,424, 376,488, 440,496
+};
+
+const uint16_t armBitRevIndexTable128[ARMBITREVINDEXTABLE_128_TABLE_LENGTH] =
+{
+   /* 8x2, size 208 */
+   8,512, 16,64, 24,576, 32,128, 40,640, 48,192, 56,704, 64,256, 72,768,
+   80,320, 88,832, 96,384, 104,896, 112,448, 120,960, 128,512, 136,520,
+   144,768, 152,584, 160,520, 168,648, 176,200, 184,712, 192,264, 200,776,
+   208,328, 216,840, 224,392, 232,904, 240,456, 248,968, 264,528, 272,320,
+   280,592, 288,768, 296,656, 304,328, 312,720, 328,784, 344,848, 352,400,
+   360,912, 368,464, 376,976, 384,576, 392,536, 400,832, 408,600, 416,584,
+   424,664, 432,840, 440,728, 448,592, 456,792, 464,848, 472,856, 480,600,
+   488,920, 496,856, 504,984, 520,544, 528,576, 536,608, 552,672, 560,608,
+   568,736, 576,768, 584,800, 592,832, 600,864, 608,800, 616,928, 624,864,
+   632,992, 648,672, 656,896, 664,928, 688,904, 696,744, 704,896, 712,808,
+   720,912, 728,872, 736,928, 744,936, 752,920, 760,1000, 776,800, 784,832,
+   792,864, 808,904, 816,864, 824,920, 840,864, 856,880, 872,944, 888,1008,
+   904,928, 912,960, 920,992, 944,968, 952,1000, 968,992, 984,1008
+};
+
+const uint16_t armBitRevIndexTable256[ARMBITREVINDEXTABLE_256_TABLE_LENGTH] =
+{
+   /* 8x4, size 440 */
+   8,512, 16,1024, 24,1536, 32,64, 40,576, 48,1088, 56,1600, 64,128, 72,640,
+   80,1152, 88,1664, 96,192, 104,704, 112,1216, 120,1728, 128,256, 136,768,
+   144,1280, 152,1792, 160,320, 168,832, 176,1344, 184,1856, 192,384,
+   200,896, 208,1408, 216,1920, 224,448, 232,960, 240,1472, 248,1984,
+   256,512, 264,520, 272,1032, 280,1544, 288,640, 296,584, 304,1096, 312,1608,
+   320,768, 328,648, 336,1160, 344,1672, 352,896, 360,712, 368,1224, 376,1736,
+   384,520, 392,776, 400,1288, 408,1800, 416,648, 424,840, 432,1352, 440,1864,
+   448,776, 456,904, 464,1416, 472,1928, 480,904, 488,968, 496,1480, 504,1992,
+   520,528, 512,1024, 528,1040, 536,1552, 544,1152, 552,592, 560,1104,
+   568,1616, 576,1280, 584,656, 592,1168, 600,1680, 608,1408, 616,720,
+   624,1232, 632,1744, 640,1032, 648,784, 656,1296, 664,1808, 672,1160,
+   680,848, 688,1360, 696,1872, 704,1288, 712,912, 720,1424, 728,1936,
+   736,1416, 744,976, 752,1488, 760,2000, 768,1536, 776,1552, 784,1048,
+   792,1560, 800,1664, 808,1680, 816,1112, 824,1624, 832,1792, 840,1808,
+   848,1176, 856,1688, 864,1920, 872,1936, 880,1240, 888,1752, 896,1544,
+   904,1560, 912,1304, 920,1816, 928,1672, 936,1688, 944,1368, 952,1880,
+   960,1800, 968,1816, 976,1432, 984,1944, 992,1928, 1000,1944, 1008,1496,
+   1016,2008, 1032,1152, 1040,1056, 1048,1568, 1064,1408, 1072,1120,
+   1080,1632, 1088,1536, 1096,1160, 1104,1184, 1112,1696, 1120,1552,
+   1128,1416, 1136,1248, 1144,1760, 1160,1664, 1168,1312, 1176,1824,
+   1184,1544, 1192,1920, 1200,1376, 1208,1888, 1216,1568, 1224,1672,
+   1232,1440, 1240,1952, 1248,1560, 1256,1928, 1264,1504, 1272,2016,
+   1288,1312, 1296,1408, 1304,1576, 1320,1424, 1328,1416, 1336,1640,
+   1344,1792, 1352,1824, 1360,1920, 1368,1704, 1376,1800, 1384,1432,
+   1392,1928, 1400,1768, 1416,1680, 1432,1832, 1440,1576, 1448,1936,
+   1456,1832, 1464,1896, 1472,1808, 1480,1688, 1488,1936, 1496,1960,
+   1504,1816, 1512,1944, 1520,1944, 1528,2024, 1560,1584, 1592,1648,
+   1600,1792, 1608,1920, 1616,1800, 1624,1712, 1632,1808, 1640,1936,
+   1648,1816, 1656,1776, 1672,1696, 1688,1840, 1704,1952, 1712,1928,
+   1720,1904, 1728,1824, 1736,1952, 1744,1832, 1752,1968, 1760,1840,
+   1768,1960, 1776,1944, 1784,2032, 1864,1872, 1848,1944, 1872,1888,
+   1880,1904, 1888,1984, 1896,2000, 1912,2032, 1904,2016, 1976,2032,
+   1960,1968, 2008,2032, 1992,2016, 2024,2032
+};
+
+const uint16_t armBitRevIndexTable512[ARMBITREVINDEXTABLE_512_TABLE_LENGTH] =
+{
+   /* radix 8, size 448 */
+   8,512, 16,1024, 24,1536, 32,2048, 40,2560, 48,3072, 56,3584, 72,576,
+   80,1088, 88,1600, 96,2112, 104,2624, 112,3136, 120,3648, 136,640, 144,1152,
+   152,1664, 160,2176, 168,2688, 176,3200, 184,3712, 200,704, 208,1216,
+   216,1728, 224,2240, 232,2752, 240,3264, 248,3776, 264,768, 272,1280,
+   280,1792, 288,2304, 296,2816, 304,3328, 312,3840, 328,832, 336,1344,
+   344,1856, 352,2368, 360,2880, 368,3392, 376,3904, 392,896, 400,1408,
+   408,1920, 416,2432, 424,2944, 432,3456, 440,3968, 456,960, 464,1472,
+   472,1984, 480,2496, 488,3008, 496,3520, 504,4032, 528,1032, 536,1544,
+   544,2056, 552,2568, 560,3080, 568,3592, 592,1096, 600,1608, 608,2120,
+   616,2632, 624,3144, 632,3656, 656,1160, 664,1672, 672,2184, 680,2696,
+   688,3208, 696,3720, 720,1224, 728,1736, 736,2248, 744,2760, 752,3272,
+   760,3784, 784,1288, 792,1800, 800,2312, 808,2824, 816,3336, 824,3848,
+   848,1352, 856,1864, 864,2376, 872,2888, 880,3400, 888,3912, 912,1416,
+   920,1928, 928,2440, 936,2952, 944,3464, 952,3976, 976,1480, 984,1992,
+   992,2504, 1000,3016, 1008,3528, 1016,4040, 1048,1552, 1056,2064, 1064,2576,
+   1072,3088, 1080,3600, 1112,1616, 1120,2128, 1128,2640, 1136,3152,
+   1144,3664, 1176,1680, 1184,2192, 1192,2704, 1200,3216, 1208,3728,
+   1240,1744, 1248,2256, 1256,2768, 1264,3280, 1272,3792, 1304,1808,
+   1312,2320, 1320,2832, 1328,3344, 1336,3856, 1368,1872, 1376,2384,
+   1384,2896, 1392,3408, 1400,3920, 1432,1936, 1440,2448, 1448,2960,
+   1456,3472, 1464,3984, 1496,2000, 1504,2512, 1512,3024, 1520,3536,
+   1528,4048, 1568,2072, 1576,2584, 1584,3096, 1592,3608, 1632,2136,
+   1640,2648, 1648,3160, 1656,3672, 1696,2200, 1704,2712, 1712,3224,
+   1720,3736, 1760,2264, 1768,2776, 1776,3288, 1784,3800, 1824,2328,
+   1832,2840, 1840,3352, 1848,3864, 1888,2392, 1896,2904, 1904,3416,
+   1912,3928, 1952,2456, 1960,2968, 1968,3480, 1976,3992, 2016,2520,
+   2024,3032, 2032,3544, 2040,4056, 2088,2592, 2096,3104, 2104,3616,
+   2152,2656, 2160,3168, 2168,3680, 2216,2720, 2224,3232, 2232,3744,
+   2280,2784, 2288,3296, 2296,3808, 2344,2848, 2352,3360, 2360,3872,
+   2408,2912, 2416,3424, 2424,3936, 2472,2976, 2480,3488, 2488,4000,
+   2536,3040, 2544,3552, 2552,4064, 2608,3112, 2616,3624, 2672,3176,
+   2680,3688, 2736,3240, 2744,3752, 2800,3304, 2808,3816, 2864,3368,
+   2872,3880, 2928,3432, 2936,3944, 2992,3496, 3000,4008, 3056,3560,
+   3064,4072, 3128,3632, 3192,3696, 3256,3760, 3320,3824, 3384,3888,
+   3448,3952, 3512,4016, 3576,4080
+};
+
+const uint16_t armBitRevIndexTable1024[ARMBITREVINDEXTABLE_1024_TABLE_LENGTH] =
+{
+   /* 8x2, size 1800 */
+   8,4096, 16,512, 24,4608, 32,1024, 40,5120, 48,1536, 56,5632, 64,2048,
+   72,6144, 80,2560, 88,6656, 96,3072, 104,7168, 112,3584, 120,7680, 128,2048,
+   136,4160, 144,576, 152,4672, 160,1088, 168,5184, 176,1600, 184,5696,
+   192,2112, 200,6208, 208,2624, 216,6720, 224,3136, 232,7232, 240,3648,
+   248,7744, 256,2048, 264,4224, 272,640, 280,4736, 288,1152, 296,5248,
+   304,1664, 312,5760, 320,2176, 328,6272, 336,2688, 344,6784, 352,3200,
+   360,7296, 368,3712, 376,7808, 384,2112, 392,4288, 400,704, 408,4800,
+   416,1216, 424,5312, 432,1728, 440,5824, 448,2240, 456,6336, 464,2752,
+   472,6848, 480,3264, 488,7360, 496,3776, 504,7872, 512,2048, 520,4352,
+   528,768, 536,4864, 544,1280, 552,5376, 560,1792, 568,5888, 576,2304,
+   584,6400, 592,2816, 600,6912, 608,3328, 616,7424, 624,3840, 632,7936,
+   640,2176, 648,4416, 656,832, 664,4928, 672,1344, 680,5440, 688,1856,
+   696,5952, 704,2368, 712,6464, 720,2880, 728,6976, 736,3392, 744,7488,
+   752,3904, 760,8000, 768,2112, 776,4480, 784,896, 792,4992, 800,1408,
+   808,5504, 816,1920, 824,6016, 832,2432, 840,6528, 848,2944, 856,7040,
+   864,3456, 872,7552, 880,3968, 888,8064, 896,2240, 904,4544, 912,960,
+   920,5056, 928,1472, 936,5568, 944,1984, 952,6080, 960,2496, 968,6592,
+   976,3008, 984,7104, 992,3520, 1000,7616, 1008,4032, 1016,8128, 1024,4096,
+   1032,4104, 1040,4352, 1048,4616, 1056,4104, 1064,5128, 1072,1544,
+   1080,5640, 1088,2056, 1096,6152, 1104,2568, 1112,6664, 1120,3080,
+   1128,7176, 1136,3592, 1144,7688, 1152,6144, 1160,4168, 1168,6400,
+   1176,4680, 1184,6152, 1192,5192, 1200,1608, 1208,5704, 1216,2120,
+   1224,6216, 1232,2632, 1240,6728, 1248,3144, 1256,7240, 1264,3656,
+   1272,7752, 1280,4160, 1288,4232, 1296,4416, 1304,4744, 1312,4168,
+   1320,5256, 1328,1672, 1336,5768, 1344,2184, 1352,6280, 1360,2696,
+   1368,6792, 1376,3208, 1384,7304, 1392,3720, 1400,7816, 1408,6208,
+   1416,4296, 1424,6464, 1432,4808, 1440,6216, 1448,5320, 1456,1736,
+   1464,5832, 1472,2248, 1480,6344, 1488,2760, 1496,6856, 1504,3272,
+   1512,7368, 1520,3784, 1528,7880, 1536,4224, 1544,4360, 1552,4480,
+   1560,4872, 1568,4232, 1576,5384, 1584,1800, 1592,5896, 1600,2312,
+   1608,6408, 1616,2824, 1624,6920, 1632,3336, 1640,7432, 1648,3848,
+   1656,7944, 1664,6272, 1672,4424, 1680,6528, 1688,4936, 1696,6280,
+   1704,5448, 1712,1864, 1720,5960, 1728,2376, 1736,6472, 1744,2888,
+   1752,6984, 1760,3400, 1768,7496, 1776,3912, 1784,8008, 1792,4288,
+   1800,4488, 1808,4544, 1816,5000, 1824,4296, 1832,5512, 1840,1928,
+   1848,6024, 1856,2440, 1864,6536, 1872,2952, 1880,7048, 1888,3464,
+   1896,7560, 1904,3976, 1912,8072, 1920,6336, 1928,4552, 1936,6592,
+   1944,5064, 1952,6344, 1960,5576, 1968,1992, 1976,6088, 1984,2504,
+   1992,6600, 2000,3016, 2008,7112, 2016,3528, 2024,7624, 2032,4040,
+   2040,8136, 2056,4112, 2064,2112, 2072,4624, 2080,4352, 2088,5136,
+   2096,4480, 2104,5648, 2120,6160, 2128,2576, 2136,6672, 2144,3088,
+   2152,7184, 2160,3600, 2168,7696, 2176,2560, 2184,4176, 2192,2816,
+   2200,4688, 2208,2568, 2216,5200, 2224,2824, 2232,5712, 2240,2576,
+   2248,6224, 2256,2640, 2264,6736, 2272,3152, 2280,7248, 2288,3664,
+   2296,7760, 2312,4240, 2320,2432, 2328,4752, 2336,6400, 2344,5264,
+   2352,6528, 2360,5776, 2368,2816, 2376,6288, 2384,2704, 2392,6800,
+   2400,3216, 2408,7312, 2416,3728, 2424,7824, 2432,2624, 2440,4304,
+   2448,2880, 2456,4816, 2464,2632, 2472,5328, 2480,2888, 2488,5840,
+   2496,2640, 2504,6352, 2512,2768, 2520,6864, 2528,3280, 2536,7376,
+   2544,3792, 2552,7888, 2568,4368, 2584,4880, 2592,4416, 2600,5392,
+   2608,4544, 2616,5904, 2632,6416, 2640,2832, 2648,6928, 2656,3344,
+   2664,7440, 2672,3856, 2680,7952, 2696,4432, 2704,2944, 2712,4944,
+   2720,4432, 2728,5456, 2736,2952, 2744,5968, 2752,2944, 2760,6480,
+   2768,2896, 2776,6992, 2784,3408, 2792,7504, 2800,3920, 2808,8016,
+   2824,4496, 2840,5008, 2848,6464, 2856,5520, 2864,6592, 2872,6032,
+   2888,6544, 2896,2960, 2904,7056, 2912,3472, 2920,7568, 2928,3984,
+   2936,8080, 2952,4560, 2960,3008, 2968,5072, 2976,6480, 2984,5584,
+   2992,3016, 3000,6096, 3016,6608, 3032,7120, 3040,3536, 3048,7632,
+   3056,4048, 3064,8144, 3072,4608, 3080,4120, 3088,4864, 3096,4632,
+   3104,4616, 3112,5144, 3120,4872, 3128,5656, 3136,4624, 3144,6168,
+   3152,4880, 3160,6680, 3168,4632, 3176,7192, 3184,3608, 3192,7704,
+   3200,6656, 3208,4184, 3216,6912, 3224,4696, 3232,6664, 3240,5208,
+   3248,6920, 3256,5720, 3264,6672, 3272,6232, 3280,6928, 3288,6744,
+   3296,6680, 3304,7256, 3312,3672, 3320,7768, 3328,4672, 3336,4248,
+   3344,4928, 3352,4760, 3360,4680, 3368,5272, 3376,4936, 3384,5784,
+   3392,4688, 3400,6296, 3408,4944, 3416,6808, 3424,4696, 3432,7320,
+   3440,3736, 3448,7832, 3456,6720, 3464,4312, 3472,6976, 3480,4824,
+   3488,6728, 3496,5336, 3504,6984, 3512,5848, 3520,6736, 3528,6360,
+   3536,6992, 3544,6872, 3552,6744, 3560,7384, 3568,3800, 3576,7896,
+   3584,4736, 3592,4376, 3600,4992, 3608,4888, 3616,4744, 3624,5400,
+   3632,5000, 3640,5912, 3648,4752, 3656,6424, 3664,5008, 3672,6936,
+   3680,4760, 3688,7448, 3696,3864, 3704,7960, 3712,6784, 3720,4440,
+   3728,7040, 3736,4952, 3744,6792, 3752,5464, 3760,7048, 3768,5976,
+   3776,6800, 3784,6488, 3792,7056, 3800,7000, 3808,6808, 3816,7512,
+   3824,3928, 3832,8024, 3840,4800, 3848,4504, 3856,5056, 3864,5016,
+   3872,4808, 3880,5528, 3888,5064, 3896,6040, 3904,4816, 3912,6552,
+   3920,5072, 3928,7064, 3936,4824, 3944,7576, 3952,3992, 3960,8088,
+   3968,6848, 3976,4568, 3984,7104, 3992,5080, 4000,6856, 4008,5592,
+   4016,7112, 4024,6104, 4032,6864, 4040,6616, 4048,7120, 4056,7128,
+   4064,6872, 4072,7640, 4080,7128, 4088,8152, 4104,4128, 4112,4160,
+   4120,4640, 4136,5152, 4144,4232, 4152,5664, 4160,4352, 4168,6176,
+   4176,4416, 4184,6688, 4192,4616, 4200,7200, 4208,4744, 4216,7712,
+   4224,4608, 4232,4616, 4240,4672, 4248,4704, 4256,4640, 4264,5216,
+   4272,4704, 4280,5728, 4288,4864, 4296,6240, 4304,4928, 4312,6752,
+   4320,4632, 4328,7264, 4336,4760, 4344,7776, 4360,4640, 4368,4416,
+   4376,4768, 4384,6152, 4392,5280, 4400,6280, 4408,5792, 4424,6304,
+   4440,6816, 4448,6664, 4456,7328, 4464,6792, 4472,7840, 4480,4624,
+   4488,4632, 4496,4688, 4504,4832, 4512,6168, 4520,5344, 4528,6296,
+   4536,5856, 4544,4880, 4552,6368, 4560,4944, 4568,6880, 4576,6680,
+   4584,7392, 4592,6808, 4600,7904, 4608,6144, 4616,6152, 4624,6208,
+   4632,4896, 4640,6176, 4648,5408, 4656,6240, 4664,5920, 4672,6400,
+   4680,6432, 4688,6464, 4696,6944, 4704,6432, 4712,7456, 4720,4808,
+   4728,7968, 4736,6656, 4744,6664, 4752,6720, 4760,4960, 4768,6688,
+   4776,5472, 4784,6752, 4792,5984, 4800,6912, 4808,6496, 4816,6976,
+   4824,7008, 4832,6944, 4840,7520, 4848,7008, 4856,8032, 4864,6160,
+   4872,6168, 4880,6224, 4888,5024, 4896,6216, 4904,5536, 4912,6344,
+   4920,6048, 4928,6416, 4936,6560, 4944,6480, 4952,7072, 4960,6728,
+   4968,7584, 4976,6856, 4984,8096, 4992,6672, 5000,6680, 5008,6736,
+   5016,5088, 5024,6232, 5032,5600, 5040,6360, 5048,6112, 5056,6928,
+   5064,6624, 5072,6992, 5080,7136, 5088,6744, 5096,7648, 5104,6872,
+   5112,8160, 5128,5152, 5136,5376, 5144,5408, 5168,5384, 5176,5672,
+   5184,5376, 5192,6184, 5200,5392, 5208,6696, 5216,5408, 5224,7208,
+   5232,5400, 5240,7720, 5248,7168, 5256,7200, 5264,7424, 5272,7456,
+   5280,7176, 5288,7208, 5296,7432, 5304,5736, 5312,7184, 5320,6248,
+   5328,7440, 5336,6760, 5344,7192, 5352,7272, 5360,7448, 5368,7784,
+   5384,5408, 5392,5440, 5400,5472, 5408,6184, 5416,7208, 5424,5448,
+   5432,5800, 5448,6312, 5464,6824, 5472,6696, 5480,7336, 5488,6824,
+   5496,7848, 5504,7232, 5512,7264, 5520,7488, 5528,7520, 5536,7240,
+   5544,7272, 5552,7496, 5560,5864, 5568,7248, 5576,6376, 5584,7504,
+   5592,6888, 5600,7256, 5608,7400, 5616,7512, 5624,7912, 5632,7168,
+   5640,7176, 5648,7232, 5656,7240, 5664,7200, 5672,7208, 5680,7264,
+   5688,5928, 5696,7424, 5704,6440, 5712,7488, 5720,6952, 5728,7456,
+   5736,7464, 5744,7520, 5752,7976, 5760,7296, 5768,7328, 5776,7552,
+   5784,7584, 5792,7304, 5800,7336, 5808,7560, 5816,5992, 5824,7312,
+   5832,6504, 5840,7568, 5848,7016, 5856,7320, 5864,7528, 5872,7576,
+   5880,8040, 5888,7184, 5896,7192, 5904,7248, 5912,7256, 5920,6248,
+   5928,7272, 5936,6376, 5944,6056, 5952,7440, 5960,6568, 5968,7504,
+   5976,7080, 5984,6760, 5992,7592, 6000,6888, 6008,8104, 6016,7360,
+   6024,7392, 6032,7616, 6040,7648, 6048,7368, 6056,7400, 6064,7624,
+   6072,6120, 6080,7376, 6088,6632, 6096,7632, 6104,7144, 6112,7384,
+   6120,7656, 6128,7640, 6136,8168, 6168,6240, 6192,6216, 6200,7264,
+   6232,6704, 6248,7216, 6256,6680, 6264,7728, 6272,6656, 6280,6664,
+   6288,6912, 6296,6496, 6304,6688, 6312,6696, 6320,6944, 6328,7520,
+   6336,6672, 6344,6680, 6352,6928, 6360,6768, 6368,6704, 6376,7280,
+   6384,6744, 6392,7792, 6408,6432, 6424,6752, 6440,7432, 6448,6536,
+   6456,7560, 6472,6944, 6488,6832, 6496,6920, 6504,7344, 6512,7048,
+   6520,7856, 6528,6720, 6536,6728, 6544,6976, 6552,7008, 6560,6752,
+   6568,7448, 6576,7008, 6584,7576, 6592,6736, 6600,6744, 6608,6992,
+   6616,6896, 6624,6936, 6632,7408, 6640,7064, 6648,7920, 6712,7280,
+   6744,6960, 6760,7472, 6768,6936, 6776,7984, 6800,6848, 6808,6856,
+   6832,6880, 6840,6888, 6848,7040, 6856,7048, 6864,7104, 6872,7024,
+   6880,7072, 6888,7536, 6896,7136, 6904,8048, 6952,7496, 6968,7624,
+   6984,7008, 7000,7088, 7016,7600, 7024,7112, 7032,8112, 7056,7104,
+   7064,7112, 7080,7512, 7088,7136, 7096,7640, 7128,7152, 7144,7664,
+   7160,8176, 7176,7200, 7192,7216, 7224,7272, 7240,7264, 7256,7280,
+   7288,7736, 7296,7680, 7304,7712, 7312,7936, 7320,7968, 7328,7688,
+   7336,7720, 7344,7944, 7352,7976, 7360,7696, 7368,7728, 7376,7952,
+   7384,7984, 7392,7704, 7400,7736, 7408,7960, 7416,7800, 7432,7456,
+   7448,7472, 7480,7592, 7496,7520, 7512,7536, 7528,7976, 7544,7864,
+   7552,7744, 7560,7776, 7568,8000, 7576,8032, 7584,7752, 7592,7784,
+   7600,8008, 7608,8040, 7616,7760, 7624,7792, 7632,8016, 7640,8048,
+   7648,7768, 7656,7800, 7664,8024, 7672,7928, 7688,7712, 7704,7728,
+   7752,7776, 7768,7792, 7800,7992, 7816,7840, 7824,8064, 7832,8096,
+   7856,8072, 7864,8104, 7872,8064, 7880,8072, 7888,8080, 7896,8112,
+   7904,8096, 7912,8104, 7920,8088, 7928,8056, 7944,7968, 7960,7984,
+   8008,8032, 8024,8048, 8056,8120, 8072,8096, 8080,8128, 8088,8160,
+   8112,8136, 8120,8168, 8136,8160, 8152,8176
+};
+
+const uint16_t armBitRevIndexTable2048[ARMBITREVINDEXTABLE_2048_TABLE_LENGTH] =
+{
+   /* 8x2, size 3808 */
+   8,4096, 16,8192, 24,12288, 32,512, 40,4608, 48,8704, 56,12800, 64,1024,
+   72,5120, 80,9216, 88,13312, 96,1536, 104,5632, 112,9728, 120,13824,
+   128,2048, 136,6144, 144,10240, 152,14336, 160,2560, 168,6656, 176,10752,
+   184,14848, 192,3072, 200,7168, 208,11264, 216,15360, 224,3584, 232,7680,
+   240,11776, 248,15872, 256,1024, 264,4160, 272,8256, 280,12352, 288,576,
+   296,4672, 304,8768, 312,12864, 320,1088, 328,5184, 336,9280, 344,13376,
+   352,1600, 360,5696, 368,9792, 376,13888, 384,2112, 392,6208, 400,10304,
+   408,14400, 416,2624, 424,6720, 432,10816, 440,14912, 448,3136, 456,7232,
+   464,11328, 472,15424, 480,3648, 488,7744, 496,11840, 504,15936, 512,2048,
+   520,4224, 528,8320, 536,12416, 544,640, 552,4736, 560,8832, 568,12928,
+   576,1152, 584,5248, 592,9344, 600,13440, 608,1664, 616,5760, 624,9856,
+   632,13952, 640,2176, 648,6272, 656,10368, 664,14464, 672,2688, 680,6784,
+   688,10880, 696,14976, 704,3200, 712,7296, 720,11392, 728,15488, 736,3712,
+   744,7808, 752,11904, 760,16000, 768,3072, 776,4288, 784,8384, 792,12480,
+   800,3200, 808,4800, 816,8896, 824,12992, 832,1216, 840,5312, 848,9408,
+   856,13504, 864,1728, 872,5824, 880,9920, 888,14016, 896,2240, 904,6336,
+   912,10432, 920,14528, 928,2752, 936,6848, 944,10944, 952,15040, 960,3264,
+   968,7360, 976,11456, 984,15552, 992,3776, 1000,7872, 1008,11968, 1016,16064,
+   1032,4352, 1040,8448, 1048,12544, 1056,3072, 1064,4864, 1072,8960,
+   1080,13056, 1088,1280, 1096,5376, 1104,9472, 1112,13568, 1120,1792,
+   1128,5888, 1136,9984, 1144,14080, 1152,2304, 1160,6400, 1168,10496,
+   1176,14592, 1184,2816, 1192,6912, 1200,11008, 1208,15104, 1216,3328,
+   1224,7424, 1232,11520, 1240,15616, 1248,3840, 1256,7936, 1264,12032,
+   1272,16128, 1288,4416, 1296,8512, 1304,12608, 1312,3328, 1320,4928,
+   1328,9024, 1336,13120, 1352,5440, 1360,9536, 1368,13632, 1376,1856,
+   1384,5952, 1392,10048, 1400,14144, 1408,2368, 1416,6464, 1424,10560,
+   1432,14656, 1440,2880, 1448,6976, 1456,11072, 1464,15168, 1472,3392,
+   1480,7488, 1488,11584, 1496,15680, 1504,3904, 1512,8000, 1520,12096,
+   1528,16192, 1536,2112, 1544,4480, 1552,8576, 1560,12672, 1568,2240,
+   1576,4992, 1584,9088, 1592,13184, 1600,2368, 1608,5504, 1616,9600,
+   1624,13696, 1632,1920, 1640,6016, 1648,10112, 1656,14208, 1664,2432,
+   1672,6528, 1680,10624, 1688,14720, 1696,2944, 1704,7040, 1712,11136,
+   1720,15232, 1728,3456, 1736,7552, 1744,11648, 1752,15744, 1760,3968,
+   1768,8064, 1776,12160, 1784,16256, 1792,3136, 1800,4544, 1808,8640,
+   1816,12736, 1824,3264, 1832,5056, 1840,9152, 1848,13248, 1856,3392,
+   1864,5568, 1872,9664, 1880,13760, 1888,1984, 1896,6080, 1904,10176,
+   1912,14272, 1920,2496, 1928,6592, 1936,10688, 1944,14784, 1952,3008,
+   1960,7104, 1968,11200, 1976,15296, 1984,3520, 1992,7616, 2000,11712,
+   2008,15808, 2016,4032, 2024,8128, 2032,12224, 2040,16320, 2048,4096,
+   2056,4104, 2064,8200, 2072,12296, 2080,4224, 2088,4616, 2096,8712,
+   2104,12808, 2112,4352, 2120,5128, 2128,9224, 2136,13320, 2144,4480,
+   2152,5640, 2160,9736, 2168,13832, 2176,4104, 2184,6152, 2192,10248,
+   2200,14344, 2208,2568, 2216,6664, 2224,10760, 2232,14856, 2240,3080,
+   2248,7176, 2256,11272, 2264,15368, 2272,3592, 2280,7688, 2288,11784,
+   2296,15880, 2304,5120, 2312,4168, 2320,8264, 2328,12360, 2336,5248,
+   2344,4680, 2352,8776, 2360,12872, 2368,5376, 2376,5192, 2384,9288,
+   2392,13384, 2400,5504, 2408,5704, 2416,9800, 2424,13896, 2432,5128,
+   2440,6216, 2448,10312, 2456,14408, 2464,2632, 2472,6728, 2480,10824,
+   2488,14920, 2496,3144, 2504,7240, 2512,11336, 2520,15432, 2528,3656,
+   2536,7752, 2544,11848, 2552,15944, 2560,6144, 2568,4232, 2576,8328,
+   2584,12424, 2592,6272, 2600,4744, 2608,8840, 2616,12936, 2624,6400,
+   2632,5256, 2640,9352, 2648,13448, 2656,6528, 2664,5768, 2672,9864,
+   2680,13960, 2688,6152, 2696,6280, 2704,10376, 2712,14472, 2720,6280,
+   2728,6792, 2736,10888, 2744,14984, 2752,3208, 2760,7304, 2768,11400,
+   2776,15496, 2784,3720, 2792,7816, 2800,11912, 2808,16008, 2816,7168,
+   2824,4296, 2832,8392, 2840,12488, 2848,7296, 2856,4808, 2864,8904,
+   2872,13000, 2880,7424, 2888,5320, 2896,9416, 2904,13512, 2912,7552,
+   2920,5832, 2928,9928, 2936,14024, 2944,7176, 2952,6344, 2960,10440,
+   2968,14536, 2976,7304, 2984,6856, 2992,10952, 3000,15048, 3008,3272,
+   3016,7368, 3024,11464, 3032,15560, 3040,3784, 3048,7880, 3056,11976,
+   3064,16072, 3072,4160, 3080,4360, 3088,8456, 3096,12552, 3104,4288,
+   3112,4872, 3120,8968, 3128,13064, 3136,4416, 3144,5384, 3152,9480,
+   3160,13576, 3168,4544, 3176,5896, 3184,9992, 3192,14088, 3200,4168,
+   3208,6408, 3216,10504, 3224,14600, 3232,4296, 3240,6920, 3248,11016,
+   3256,15112, 3264,3336, 3272,7432, 3280,11528, 3288,15624, 3296,3848,
+   3304,7944, 3312,12040, 3320,16136, 3328,5184, 3336,4424, 3344,8520,
+   3352,12616, 3360,5312, 3368,4936, 3376,9032, 3384,13128, 3392,5440,
+   3400,5448, 3408,9544, 3416,13640, 3424,5568, 3432,5960, 3440,10056,
+   3448,14152, 3456,5192, 3464,6472, 3472,10568, 3480,14664, 3488,5320,
+   3496,6984, 3504,11080, 3512,15176, 3520,5448, 3528,7496, 3536,11592,
+   3544,15688, 3552,3912, 3560,8008, 3568,12104, 3576,16200, 3584,6208,
+   3592,4488, 3600,8584, 3608,12680, 3616,6336, 3624,5000, 3632,9096,
+   3640,13192, 3648,6464, 3656,5512, 3664,9608, 3672,13704, 3680,6592,
+   3688,6024, 3696,10120, 3704,14216, 3712,6216, 3720,6536, 3728,10632,
+   3736,14728, 3744,6344, 3752,7048, 3760,11144, 3768,15240, 3776,6472,
+   3784,7560, 3792,11656, 3800,15752, 3808,3976, 3816,8072, 3824,12168,
+   3832,16264, 3840,7232, 3848,4552, 3856,8648, 3864,12744, 3872,7360,
+   3880,5064, 3888,9160, 3896,13256, 3904,7488, 3912,5576, 3920,9672,
+   3928,13768, 3936,7616, 3944,6088, 3952,10184, 3960,14280, 3968,7240,
+   3976,6600, 3984,10696, 3992,14792, 4000,7368, 4008,7112, 4016,11208,
+   4024,15304, 4032,7496, 4040,7624, 4048,11720, 4056,15816, 4064,7624,
+   4072,8136, 4080,12232, 4088,16328, 4096,8192, 4104,4112, 4112,8208,
+   4120,12304, 4128,8320, 4136,4624, 4144,8720, 4152,12816, 4160,8448,
+   4168,5136, 4176,9232, 4184,13328, 4192,8576, 4200,5648, 4208,9744,
+   4216,13840, 4224,8200, 4232,6160, 4240,10256, 4248,14352, 4256,8328,
+   4264,6672, 4272,10768, 4280,14864, 4288,8456, 4296,7184, 4304,11280,
+   4312,15376, 4320,8584, 4328,7696, 4336,11792, 4344,15888, 4352,9216,
+   4360,9232, 4368,8272, 4376,12368, 4384,9344, 4392,4688, 4400,8784,
+   4408,12880, 4416,9472, 4424,5200, 4432,9296, 4440,13392, 4448,9600,
+   4456,5712, 4464,9808, 4472,13904, 4480,9224, 4488,6224, 4496,10320,
+   4504,14416, 4512,9352, 4520,6736, 4528,10832, 4536,14928, 4544,9480,
+   4552,7248, 4560,11344, 4568,15440, 4576,9608, 4584,7760, 4592,11856,
+   4600,15952, 4608,10240, 4616,10256, 4624,8336, 4632,12432, 4640,10368,
+   4648,4752, 4656,8848, 4664,12944, 4672,10496, 4680,5264, 4688,9360,
+   4696,13456, 4704,10624, 4712,5776, 4720,9872, 4728,13968, 4736,10248,
+   4744,6288, 4752,10384, 4760,14480, 4768,10376, 4776,6800, 4784,10896,
+   4792,14992, 4800,10504, 4808,7312, 4816,11408, 4824,15504, 4832,10632,
+   4840,7824, 4848,11920, 4856,16016, 4864,11264, 4872,11280, 4880,8400,
+   4888,12496, 4896,11392, 4904,11408, 4912,8912, 4920,13008, 4928,11520,
+   4936,5328, 4944,9424, 4952,13520, 4960,11648, 4968,5840, 4976,9936,
+   4984,14032, 4992,11272, 5000,6352, 5008,10448, 5016,14544, 5024,11400,
+   5032,6864, 5040,10960, 5048,15056, 5056,11528, 5064,7376, 5072,11472,
+   5080,15568, 5088,11656, 5096,7888, 5104,11984, 5112,16080, 5120,8256,
+   5128,8272, 5136,8464, 5144,12560, 5152,8384, 5160,8400, 5168,8976,
+   5176,13072, 5184,8512, 5192,5392, 5200,9488, 5208,13584, 5216,8640,
+   5224,5904, 5232,10000, 5240,14096, 5248,8264, 5256,6416, 5264,10512,
+   5272,14608, 5280,8392, 5288,6928, 5296,11024, 5304,15120, 5312,8520,
+   5320,7440, 5328,11536, 5336,15632, 5344,8648, 5352,7952, 5360,12048,
+   5368,16144, 5376,9280, 5384,9296, 5392,8528, 5400,12624, 5408,9408,
+   5416,9424, 5424,9040, 5432,13136, 5440,9536, 5448,5456, 5456,9552,
+   5464,13648, 5472,9664, 5480,5968, 5488,10064, 5496,14160, 5504,9288,
+   5512,6480, 5520,10576, 5528,14672, 5536,9416, 5544,6992, 5552,11088,
+   5560,15184, 5568,9544, 5576,7504, 5584,11600, 5592,15696, 5600,9672,
+   5608,8016, 5616,12112, 5624,16208, 5632,10304, 5640,10320, 5648,8592,
+   5656,12688, 5664,10432, 5672,10448, 5680,9104, 5688,13200, 5696,10560,
+   5704,10576, 5712,9616, 5720,13712, 5728,10688, 5736,6032, 5744,10128,
+   5752,14224, 5760,10312, 5768,6544, 5776,10640, 5784,14736, 5792,10440,
+   5800,7056, 5808,11152, 5816,15248, 5824,10568, 5832,7568, 5840,11664,
+   5848,15760, 5856,10696, 5864,8080, 5872,12176, 5880,16272, 5888,11328,
+   5896,11344, 5904,8656, 5912,12752, 5920,11456, 5928,11472, 5936,9168,
+   5944,13264, 5952,11584, 5960,11600, 5968,9680, 5976,13776, 5984,11712,
+   5992,6096, 6000,10192, 6008,14288, 6016,11336, 6024,6608, 6032,10704,
+   6040,14800, 6048,11464, 6056,7120, 6064,11216, 6072,15312, 6080,11592,
+   6088,7632, 6096,11728, 6104,15824, 6112,11720, 6120,8144, 6128,12240,
+   6136,16336, 6144,12288, 6152,12304, 6160,8216, 6168,12312, 6176,12416,
+   6184,12432, 6192,8728, 6200,12824, 6208,12544, 6216,12560, 6224,9240,
+   6232,13336, 6240,12672, 6248,12688, 6256,9752, 6264,13848, 6272,12296,
+   6280,12312, 6288,10264, 6296,14360, 6304,12424, 6312,6680, 6320,10776,
+   6328,14872, 6336,12552, 6344,7192, 6352,11288, 6360,15384, 6368,12680,
+   6376,7704, 6384,11800, 6392,15896, 6400,13312, 6408,13328, 6416,8280,
+   6424,12376, 6432,13440, 6440,13456, 6448,8792, 6456,12888, 6464,13568,
+   6472,13584, 6480,9304, 6488,13400, 6496,13696, 6504,13712, 6512,9816,
+   6520,13912, 6528,13320, 6536,13336, 6544,10328, 6552,14424, 6560,13448,
+   6568,6744, 6576,10840, 6584,14936, 6592,13576, 6600,7256, 6608,11352,
+   6616,15448, 6624,13704, 6632,7768, 6640,11864, 6648,15960, 6656,14336,
+   6664,14352, 6672,8344, 6680,12440, 6688,14464, 6696,14480, 6704,8856,
+   6712,12952, 6720,14592, 6728,14608, 6736,9368, 6744,13464, 6752,14720,
+   6760,14736, 6768,9880, 6776,13976, 6784,14344, 6792,14360, 6800,10392,
+   6808,14488, 6816,14472, 6824,14488, 6832,10904, 6840,15000, 6848,14600,
+   6856,7320, 6864,11416, 6872,15512, 6880,14728, 6888,7832, 6896,11928,
+   6904,16024, 6912,15360, 6920,15376, 6928,8408, 6936,12504, 6944,15488,
+   6952,15504, 6960,8920, 6968,13016, 6976,15616, 6984,15632, 6992,9432,
+   7000,13528, 7008,15744, 7016,15760, 7024,9944, 7032,14040, 7040,15368,
+   7048,15384, 7056,10456, 7064,14552, 7072,15496, 7080,15512, 7088,10968,
+   7096,15064, 7104,15624, 7112,7384, 7120,11480, 7128,15576, 7136,15752,
+   7144,7896, 7152,11992, 7160,16088, 7168,12352, 7176,12368, 7184,8472,
+   7192,12568, 7200,12480, 7208,12496, 7216,8984, 7224,13080, 7232,12608,
+   7240,12624, 7248,9496, 7256,13592, 7264,12736, 7272,12752, 7280,10008,
+   7288,14104, 7296,12360, 7304,12376, 7312,10520, 7320,14616, 7328,12488,
+   7336,12504, 7344,11032, 7352,15128, 7360,12616, 7368,7448, 7376,11544,
+   7384,15640, 7392,12744, 7400,7960, 7408,12056, 7416,16152, 7424,13376,
+   7432,13392, 7440,8536, 7448,12632, 7456,13504, 7464,13520, 7472,9048,
+   7480,13144, 7488,13632, 7496,13648, 7504,9560, 7512,13656, 7520,13760,
+   7528,13776, 7536,10072, 7544,14168, 7552,13384, 7560,13400, 7568,10584,
+   7576,14680, 7584,13512, 7592,13528, 7600,11096, 7608,15192, 7616,13640,
+   7624,13656, 7632,11608, 7640,15704, 7648,13768, 7656,8024, 7664,12120,
+   7672,16216, 7680,14400, 7688,14416, 7696,8600, 7704,12696, 7712,14528,
+   7720,14544, 7728,9112, 7736,13208, 7744,14656, 7752,14672, 7760,9624,
+   7768,13720, 7776,14784, 7784,14800, 7792,10136, 7800,14232, 7808,14408,
+   7816,14424, 7824,10648, 7832,14744, 7840,14536, 7848,14552, 7856,11160,
+   7864,15256, 7872,14664, 7880,14680, 7888,11672, 7896,15768, 7904,14792,
+   7912,8088, 7920,12184, 7928,16280, 7936,15424, 7944,15440, 7952,8664,
+   7960,12760, 7968,15552, 7976,15568, 7984,9176, 7992,13272, 8000,15680,
+   8008,15696, 8016,9688, 8024,13784, 8032,15808, 8040,15824, 8048,10200,
+   8056,14296, 8064,15432, 8072,15448, 8080,10712, 8088,14808, 8096,15560,
+   8104,15576, 8112,11224, 8120,15320, 8128,15688, 8136,15704, 8144,11736,
+   8152,15832, 8160,15816, 8168,15832, 8176,12248, 8184,16344, 8200,8320,
+   8208,8224, 8216,12320, 8232,10368, 8240,8736, 8248,12832, 8256,8448,
+   8264,8384, 8272,9248, 8280,13344, 8288,9232, 8296,10432, 8304,9760,
+   8312,13856, 8328,12416, 8336,10272, 8344,14368, 8352,12296, 8360,14464,
+   8368,10784, 8376,14880, 8384,8456, 8392,12480, 8400,11296, 8408,15392,
+   8416,12552, 8424,14528, 8432,11808, 8440,15904, 8448,9216, 8456,8576,
+   8464,9232, 8472,12384, 8480,9248, 8488,10624, 8496,8800, 8504,12896,
+   8512,9472, 8520,8640, 8528,9312, 8536,13408, 8544,9296, 8552,10688,
+   8560,9824, 8568,13920, 8576,9224, 8584,12672, 8592,10336, 8600,14432,
+   8608,13320, 8616,14720, 8624,10848, 8632,14944, 8640,9480, 8648,12736,
+   8656,11360, 8664,15456, 8672,13576, 8680,14784, 8688,11872, 8696,15968,
+   8704,12288, 8712,12416, 8720,12296, 8728,12448, 8736,12304, 8744,10376,
+   8752,8864, 8760,12960, 8768,12352, 8776,12480, 8784,9376, 8792,13472,
+   8800,12368, 8808,10440, 8816,9888, 8824,13984, 8832,12320, 8840,12424,
+   8848,10400, 8856,14496, 8864,12312, 8872,14472, 8880,10912, 8888,15008,
+   8896,12384, 8904,12488, 8912,11424, 8920,15520, 8928,12568, 8936,14536,
+   8944,11936, 8952,16032, 8960,12544, 8968,12672, 8976,12552, 8984,12512,
+   8992,12560, 9000,10632, 9008,12568, 9016,13024, 9024,12608, 9032,12736,
+   9040,9440, 9048,13536, 9056,12624, 9064,10696, 9072,9952, 9080,14048,
+   9088,9240, 9096,12680, 9104,10464, 9112,14560, 9120,13336, 9128,14728,
+   9136,10976, 9144,15072, 9152,9496, 9160,12744, 9168,11488, 9176,15584,
+   9184,13592, 9192,14792, 9200,12000, 9208,16096, 9224,9344, 9232,9248,
+   9240,12576, 9256,11392, 9264,12560, 9272,13088, 9280,9472, 9288,9408,
+   9296,9504, 9304,13600, 9312,9488, 9320,11456, 9328,10016, 9336,14112,
+   9352,13440, 9360,10528, 9368,14624, 9376,12360, 9384,15488, 9392,11040,
+   9400,15136, 9408,9480, 9416,13504, 9424,11552, 9432,15648, 9440,12616,
+   9448,15552, 9456,12064, 9464,16160, 9480,9600, 9488,9504, 9496,12640,
+   9512,11648, 9520,12624, 9528,13152, 9544,9664, 9552,9568, 9560,13664,
+   9576,11712, 9584,10080, 9592,14176, 9608,13696, 9616,10592, 9624,14688,
+   9632,13384, 9640,15744, 9648,11104, 9656,15200, 9672,13760, 9680,11616,
+   9688,15712, 9696,13640, 9704,15808, 9712,12128, 9720,16224, 9728,13312,
+   9736,13440, 9744,13320, 9752,12704, 9760,13328, 9768,11400, 9776,13336,
+   9784,13216, 9792,13376, 9800,13504, 9808,13384, 9816,13728, 9824,13392,
+   9832,11464, 9840,10144, 9848,14240, 9856,13344, 9864,13448, 9872,10656,
+   9880,14752, 9888,12376, 9896,15496, 9904,11168, 9912,15264, 9920,13408,
+   9928,13512, 9936,11680, 9944,15776, 9952,12632, 9960,15560, 9968,12192,
+   9976,16288, 9984,13568, 9992,13696, 10000,13576, 10008,12768, 10016,13584,
+   10024,11656, 10032,13592, 10040,13280, 10048,13632, 10056,13760,
+   10064,13640, 10072,13792, 10080,13648, 10088,11720, 10096,10208,
+   10104,14304, 10112,13600, 10120,13704, 10128,10720, 10136,14816,
+   10144,13400, 10152,15752, 10160,11232, 10168,15328, 10176,13664,
+   10184,13768, 10192,11744, 10200,15840, 10208,13656, 10216,15816,
+   10224,12256, 10232,16352, 10248,10272, 10256,10368, 10264,12328,
+   10280,10384, 10288,10376, 10296,12840, 10304,11264, 10312,11296,
+   10320,11392, 10328,13352, 10336,11272, 10344,10448, 10352,11400,
+   10360,13864, 10376,12432, 10392,14376, 10400,12328, 10408,14480,
+   10416,10792, 10424,14888, 10432,11280, 10440,12496, 10448,11304,
+   10456,15400, 10464,11288, 10472,14544, 10480,11816, 10488,15912,
+   10496,11264, 10504,11272, 10512,11280, 10520,12392, 10528,11296,
+   10536,10640, 10544,12496, 10552,12904, 10560,11328, 10568,11360,
+   10576,11456, 10584,13416, 10592,11336, 10600,10704, 10608,11464,
+   10616,13928, 10624,11392, 10632,12688, 10640,11304, 10648,14440,
+   10656,13352, 10664,14736, 10672,10856, 10680,14952, 10688,11344,
+   10696,12752, 10704,11368, 10712,15464, 10720,11352, 10728,14800,
+   10736,11880, 10744,15976, 10752,14336, 10760,14368, 10768,14464,
+   10776,12456, 10784,14344, 10792,14376, 10800,14472, 10808,12968,
+   10816,15360, 10824,15392, 10832,15488, 10840,13480, 10848,15368,
+   10856,15400, 10864,15496, 10872,13992, 10880,14352, 10888,12440,
+   10896,14480, 10904,14504, 10912,14360, 10920,14488, 10928,14488,
+   10936,15016, 10944,15376, 10952,12504, 10960,11432, 10968,15528,
+   10976,15384, 10984,14552, 10992,11944, 11000,16040, 11008,14400,
+   11016,14432, 11024,14528, 11032,12520, 11040,14408, 11048,14440,
+   11056,14536, 11064,13032, 11072,15424, 11080,15456, 11088,15552,
+   11096,13544, 11104,15432, 11112,15464, 11120,15560, 11128,14056,
+   11136,14416, 11144,12696, 11152,14544, 11160,14568, 11168,14424,
+   11176,14744, 11184,14552, 11192,15080, 11200,15440, 11208,12760,
+   11216,11496, 11224,15592, 11232,15448, 11240,14808, 11248,12008,
+   11256,16104, 11272,11296, 11280,11392, 11288,12584, 11304,11408,
+   11312,12688, 11320,13096, 11328,11520, 11336,11552, 11344,11648,
+   11352,13608, 11360,11528, 11368,11472, 11376,11656, 11384,14120,
+   11400,13456, 11416,14632, 11424,12392, 11432,15504, 11440,14440,
+   11448,15144, 11456,11536, 11464,13520, 11472,11560, 11480,15656,
+   11488,11544, 11496,15568, 11504,12072, 11512,16168, 11528,11552,
+   11536,11648, 11544,12648, 11560,11664, 11568,12752, 11576,13160,
+   11592,11616, 11600,11712, 11608,13672, 11624,11728, 11632,11720,
+   11640,14184, 11656,13712, 11672,14696, 11680,13416, 11688,15760,
+   11696,15464, 11704,15208, 11720,13776, 11736,15720, 11744,13672,
+   11752,15824, 11760,12136, 11768,16232, 11776,14592, 11784,14624,
+   11792,14720, 11800,12712, 11808,14600, 11816,14632, 11824,14728,
+   11832,13224, 11840,15616, 11848,15648, 11856,15744, 11864,13736,
+   11872,15624, 11880,15656, 11888,15752, 11896,14248, 11904,14608,
+   11912,13464, 11920,14736, 11928,14760, 11936,14616, 11944,15512,
+   11952,14744, 11960,15272, 11968,15632, 11976,13528, 11984,15760,
+   11992,15784, 12000,15640, 12008,15576, 12016,12200, 12024,16296,
+   12032,14656, 12040,14688, 12048,14784, 12056,12776, 12064,14664,
+   12072,14696, 12080,14792, 12088,13288, 12096,15680, 12104,15712,
+   12112,15808, 12120,13800, 12128,15688, 12136,15720, 12144,15816,
+   12152,14312, 12160,14672, 12168,13720, 12176,14800, 12184,14824,
+   12192,14680, 12200,15768, 12208,14808, 12216,15336, 12224,15696,
+   12232,13784, 12240,15824, 12248,15848, 12256,15704, 12264,15832,
+   12272,15832, 12280,16360, 12312,12336, 12344,12848, 12352,12544,
+   12360,12552, 12368,12560, 12376,13360, 12384,12576, 12392,12584,
+   12400,13336, 12408,13872, 12424,12448, 12440,14384, 12456,14496,
+   12464,14472, 12472,14896, 12480,12672, 12488,12512, 12496,12688,
+   12504,15408, 12512,12680, 12520,14560, 12528,14728, 12536,15920,
+   12544,13312, 12552,13320, 12560,13328, 12568,13336, 12576,13344,
+   12584,13352, 12592,13360, 12600,12912, 12608,13568, 12616,13576,
+   12624,13584, 12632,13424, 12640,13600, 12648,13608, 12656,13400,
+   12664,13936, 12672,13440, 12680,12704, 12688,13456, 12696,14448,
+   12704,13448, 12712,14752, 12720,15496, 12728,14960, 12736,13696,
+   12744,12768, 12752,13712, 12760,15472, 12768,13704, 12776,14816,
+   12784,15752, 12792,15984, 12800,14336, 12808,14464, 12816,14344,
+   12824,14472, 12832,14352, 12840,14480, 12848,14360, 12856,12976,
+   12864,14400, 12872,14528, 12880,14408, 12888,13488, 12896,14416,
+   12904,14544, 12912,14424, 12920,14000, 12928,14368, 12936,14496,
+   12944,14376, 12952,14512, 12960,14384, 12968,14504, 12976,14488,
+   12984,15024, 12992,14432, 13000,14560, 13008,14440, 13016,15536,
+   13024,14448, 13032,14568, 13040,14744, 13048,16048, 13056,14592,
+   13064,14720, 13072,14600, 13080,14728, 13088,14608, 13096,14736,
+   13104,14616, 13112,14744, 13120,14656, 13128,14784, 13136,14664,
+   13144,13552, 13152,14672, 13160,14800, 13168,14680, 13176,14064,
+   13184,14624, 13192,14752, 13200,14632, 13208,14576, 13216,13464,
+   13224,14760, 13232,15512, 13240,15088, 13248,14688, 13256,14816,
+   13264,14696, 13272,15600, 13280,13720, 13288,14824, 13296,15768,
+   13304,16112, 13336,13360, 13368,14616, 13376,13568, 13384,13576,
+   13392,13584, 13400,13616, 13408,13600, 13416,13608, 13424,13592,
+   13432,14128, 13448,13472, 13464,14640, 13480,15520, 13488,14536,
+   13496,15152, 13504,13696, 13512,13536, 13520,13712, 13528,15664,
+   13536,13704, 13544,15584, 13552,14792, 13560,16176, 13592,13616,
+   13624,14680, 13656,13680, 13688,14192, 13704,13728, 13720,14704,
+   13736,15776, 13744,15560, 13752,15216, 13768,13792, 13784,15728,
+   13800,15840, 13808,15816, 13816,16240, 13824,15360, 13832,15488,
+   13840,15368, 13848,15496, 13856,15376, 13864,15504, 13872,15384,
+   13880,15512, 13888,15424, 13896,15552, 13904,15432, 13912,15560,
+   13920,15440, 13928,15568, 13936,15448, 13944,14256, 13952,15392,
+   13960,15520, 13968,15400, 13976,14768, 13984,15408, 13992,15528,
+   14000,14552, 14008,15280, 14016,15456, 14024,15584, 14032,15464,
+   14040,15792, 14048,15472, 14056,15592, 14064,14808, 14072,16304,
+   14080,15616, 14088,15744, 14096,15624, 14104,15752, 14112,15632,
+   14120,15760, 14128,15640, 14136,15768, 14144,15680, 14152,15808,
+   14160,15688, 14168,15816, 14176,15696, 14184,15824, 14192,15704,
+   14200,14320, 14208,15648, 14216,15776, 14224,15656, 14232,14832,
+   14240,15664, 14248,15784, 14256,15576, 14264,15344, 14272,15712,
+   14280,15840, 14288,15720, 14296,15856, 14304,15728, 14312,15848,
+   14320,15832, 14328,16368, 14392,14488, 14400,14592, 14408,14600,
+   14416,14608, 14424,14616, 14432,14624, 14440,14632, 14448,14640,
+   14456,15512, 14504,14512, 14520,14904, 14528,14720, 14536,14728,
+   14544,14736, 14552,15416, 14560,14752, 14568,14576, 14584,15928,
+   14576,14760, 14592,15360, 14600,15368, 14608,15376, 14616,15384,
+   14624,15392, 14632,15400, 14640,15408, 14648,15416, 14656,15616,
+   14664,15624, 14672,15632, 14680,15640, 14688,15648, 14696,15656,
+   14704,15664, 14712,15576, 14720,15488, 14728,15496, 14736,15504,
+   14744,15512, 14752,15520, 14760,14768, 14776,14968, 14768,15528,
+   14784,15744, 14792,15752, 14800,15760, 14808,15480, 14816,15776,
+   14824,14832, 14840,15992, 14832,15784, 14856,14864, 14864,14880,
+   14872,14896, 14880,14976, 14888,14992, 14896,15008, 14904,15024,
+   14912,15104, 14920,15120, 14928,15136, 14936,15152, 14944,15232,
+   14952,15248, 14960,15264, 14968,15280, 14984,15008, 15000,15024,
+   15016,15024, 15040,15112, 15048,15128, 15056,15144, 15064,15544,
+   15072,15240, 15080,15256, 15088,15272, 15096,16056, 15104,15872,
+   15112,15888, 15120,15904, 15128,15920, 15136,16000, 15144,16016,
+   15152,16032, 15160,16048, 15168,16128, 15176,16144, 15184,16160,
+   15192,16176, 15200,16256, 15208,16272, 15216,16288, 15224,16304,
+   15232,15880, 15240,15896, 15248,15912, 15256,15928, 15264,16008,
+   15272,16024, 15280,16040, 15288,16056, 15296,16136, 15304,16152,
+   15312,16168, 15320,15608, 15328,16264, 15336,16280, 15344,16296,
+   15352,16120, 15416,15512, 15424,15616, 15432,15624, 15440,15632,
+   15448,15640, 15456,15648, 15464,15656, 15472,15664, 15480,15768,
+   15528,15536, 15544,16048, 15552,15744, 15560,15752, 15568,15760,
+   15576,15672, 15584,15776, 15592,15600, 15600,15784, 15608,16184,
+   15672,15768, 15736,15832, 15784,15792, 15800,16304, 15848,15856,
+   15880,16000, 15864,16248, 15888,16000, 15896,16008, 15904,16000,
+   15912,16016, 15920,16008, 15928,16024, 15936,16128, 15944,16160,
+   15952,16256, 15960,16288, 15968,16136, 15976,16168, 15984,16264,
+   15992,16296, 16008,16032, 16024,16040, 16064,16144, 16040,16048,
+   16072,16176, 16080,16272, 16088,16304, 16096,16152, 16104,16184,
+   16112,16280, 16136,16256, 16120,16312, 16144,16256, 16152,16264,
+   16160,16256, 16168,16272, 16176,16264, 16184,16280, 16200,16208,
+   16208,16224, 16216,16240, 16224,16320, 16232,16336, 16240,16352,
+   16248,16368, 16264,16288, 16280,16296, 16296,16304, 16344,16368,
+   16328,16352, 16360,16368
+};
+
+const uint16_t armBitRevIndexTable4096[ARMBITREVINDEXTABLE_4096_TABLE_LENGTH] =
+{
+   /* radix 8, size 4032 */
+   8,4096, 16,8192, 24,12288, 32,16384, 40,20480, 48,24576, 56,28672, 64,512,
+   72,4608, 80,8704, 88,12800, 96,16896, 104,20992, 112,25088, 120,29184,
+   128,1024, 136,5120, 144,9216, 152,13312, 160,17408, 168,21504, 176,25600,
+   184,29696, 192,1536, 200,5632, 208,9728, 216,13824, 224,17920, 232,22016,
+   240,26112, 248,30208, 256,2048, 264,6144, 272,10240, 280,14336, 288,18432,
+   296,22528, 304,26624, 312,30720, 320,2560, 328,6656, 336,10752, 344,14848,
+   352,18944, 360,23040, 368,27136, 376,31232, 384,3072, 392,7168, 400,11264,
+   408,15360, 416,19456, 424,23552, 432,27648, 440,31744, 448,3584, 456,7680,
+   464,11776, 472,15872, 480,19968, 488,24064, 496,28160, 504,32256, 520,4160,
+   528,8256, 536,12352, 544,16448, 552,20544, 560,24640, 568,28736, 584,4672,
+   592,8768, 600,12864, 608,16960, 616,21056, 624,25152, 632,29248, 640,1088,
+   648,5184, 656,9280, 664,13376, 672,17472, 680,21568, 688,25664, 696,29760,
+   704,1600, 712,5696, 720,9792, 728,13888, 736,17984, 744,22080, 752,26176,
+   760,30272, 768,2112, 776,6208, 784,10304, 792,14400, 800,18496, 808,22592,
+   816,26688, 824,30784, 832,2624, 840,6720, 848,10816, 856,14912, 864,19008,
+   872,23104, 880,27200, 888,31296, 896,3136, 904,7232, 912,11328, 920,15424,
+   928,19520, 936,23616, 944,27712, 952,31808, 960,3648, 968,7744, 976,11840,
+   984,15936, 992,20032, 1000,24128, 1008,28224, 1016,32320, 1032,4224,
+   1040,8320, 1048,12416, 1056,16512, 1064,20608, 1072,24704, 1080,28800,
+   1096,4736, 1104,8832, 1112,12928, 1120,17024, 1128,21120, 1136,25216,
+   1144,29312, 1160,5248, 1168,9344, 1176,13440, 1184,17536, 1192,21632,
+   1200,25728, 1208,29824, 1216,1664, 1224,5760, 1232,9856, 1240,13952,
+   1248,18048, 1256,22144, 1264,26240, 1272,30336, 1280,2176, 1288,6272,
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+   14000,25816, 14008,29912, 14048,18136, 14056,22232, 14064,26328,
+   14072,30424, 14104,14552, 14112,18648, 14120,22744, 14128,26840,
+   14136,30936, 14168,15064, 14176,19160, 14184,23256, 14192,27352,
+   14200,31448, 14232,15576, 14240,19672, 14248,23768, 14256,27864,
+   14264,31960, 14296,16088, 14304,20184, 14312,24280, 14320,28376,
+   14328,32472, 14368,16664, 14376,20760, 14384,24856, 14392,28952,
+   14432,17176, 14440,21272, 14448,25368, 14456,29464, 14496,17688,
+   14504,21784, 14512,25880, 14520,29976, 14560,18200, 14568,22296,
+   14576,26392, 14584,30488, 14624,18712, 14632,22808, 14640,26904,
+   14648,31000, 14680,15128, 14688,19224, 14696,23320, 14704,27416,
+   14712,31512, 14744,15640, 14752,19736, 14760,23832, 14768,27928,
+   14776,32024, 14808,16152, 14816,20248, 14824,24344, 14832,28440,
+   14840,32536, 14880,16728, 14888,20824, 14896,24920, 14904,29016,
+   14944,17240, 14952,21336, 14960,25432, 14968,29528, 15008,17752,
+   15016,21848, 15024,25944, 15032,30040, 15072,18264, 15080,22360,
+   15088,26456, 15096,30552, 15136,18776, 15144,22872, 15152,26968,
+   15160,31064, 15200,19288, 15208,23384, 15216,27480, 15224,31576,
+   15256,15704, 15264,19800, 15272,23896, 15280,27992, 15288,32088,
+   15320,16216, 15328,20312, 15336,24408, 15344,28504, 15352,32600,
+   15392,16792, 15400,20888, 15408,24984, 15416,29080, 15456,17304,
+   15464,21400, 15472,25496, 15480,29592, 15520,17816, 15528,21912,
+   15536,26008, 15544,30104, 15584,18328, 15592,22424, 15600,26520,
+   15608,30616, 15648,18840, 15656,22936, 15664,27032, 15672,31128,
+   15712,19352, 15720,23448, 15728,27544, 15736,31640, 15776,19864,
+   15784,23960, 15792,28056, 15800,32152, 15832,16280, 15840,20376,
+   15848,24472, 15856,28568, 15864,32664, 15904,16856, 15912,20952,
+   15920,25048, 15928,29144, 15968,17368, 15976,21464, 15984,25560,
+   15992,29656, 16032,17880, 16040,21976, 16048,26072, 16056,30168,
+   16096,18392, 16104,22488, 16112,26584, 16120,30680, 16160,18904,
+   16168,23000, 16176,27096, 16184,31192, 16224,19416, 16232,23512,
+   16240,27608, 16248,31704, 16288,19928, 16296,24024, 16304,28120,
+   16312,32216, 16352,20440, 16360,24536, 16368,28632, 16376,32728,
+   16424,20512, 16432,24608, 16440,28704, 16480,16928, 16488,21024,
+   16496,25120, 16504,29216, 16544,17440, 16552,21536, 16560,25632,
+   16568,29728, 16608,17952, 16616,22048, 16624,26144, 16632,30240,
+   16672,18464, 16680,22560, 16688,26656, 16696,30752, 16736,18976,
+   16744,23072, 16752,27168, 16760,31264, 16800,19488, 16808,23584,
+   16816,27680, 16824,31776, 16864,20000, 16872,24096, 16880,28192,
+   16888,32288, 16936,20576, 16944,24672, 16952,28768, 17000,21088,
+   17008,25184, 17016,29280, 17056,17504, 17064,21600, 17072,25696,
+   17080,29792, 17120,18016, 17128,22112, 17136,26208, 17144,30304,
+   17184,18528, 17192,22624, 17200,26720, 17208,30816, 17248,19040,
+   17256,23136, 17264,27232, 17272,31328, 17312,19552, 17320,23648,
+   17328,27744, 17336,31840, 17376,20064, 17384,24160, 17392,28256,
+   17400,32352, 17448,20640, 17456,24736, 17464,28832, 17512,21152,
+   17520,25248, 17528,29344, 17576,21664, 17584,25760, 17592,29856,
+   17632,18080, 17640,22176, 17648,26272, 17656,30368, 17696,18592,
+   17704,22688, 17712,26784, 17720,30880, 17760,19104, 17768,23200,
+   17776,27296, 17784,31392, 17824,19616, 17832,23712, 17840,27808,
+   17848,31904, 17888,20128, 17896,24224, 17904,28320, 17912,32416,
+   17960,20704, 17968,24800, 17976,28896, 18024,21216, 18032,25312,
+   18040,29408, 18088,21728, 18096,25824, 18104,29920, 18152,22240,
+   18160,26336, 18168,30432, 18208,18656, 18216,22752, 18224,26848,
+   18232,30944, 18272,19168, 18280,23264, 18288,27360, 18296,31456,
+   18336,19680, 18344,23776, 18352,27872, 18360,31968, 18400,20192,
+   18408,24288, 18416,28384, 18424,32480, 18472,20768, 18480,24864,
+   18488,28960, 18536,21280, 18544,25376, 18552,29472, 18600,21792,
+   18608,25888, 18616,29984, 18664,22304, 18672,26400, 18680,30496,
+   18728,22816, 18736,26912, 18744,31008, 18784,19232, 18792,23328,
+   18800,27424, 18808,31520, 18848,19744, 18856,23840, 18864,27936,
+   18872,32032, 18912,20256, 18920,24352, 18928,28448, 18936,32544,
+   18984,20832, 18992,24928, 19000,29024, 19048,21344, 19056,25440,
+   19064,29536, 19112,21856, 19120,25952, 19128,30048, 19176,22368,
+   19184,26464, 19192,30560, 19240,22880, 19248,26976, 19256,31072,
+   19304,23392, 19312,27488, 19320,31584, 19360,19808, 19368,23904,
+   19376,28000, 19384,32096, 19424,20320, 19432,24416, 19440,28512,
+   19448,32608, 19496,20896, 19504,24992, 19512,29088, 19560,21408,
+   19568,25504, 19576,29600, 19624,21920, 19632,26016, 19640,30112,
+   19688,22432, 19696,26528, 19704,30624, 19752,22944, 19760,27040,
+   19768,31136, 19816,23456, 19824,27552, 19832,31648, 19880,23968,
+   19888,28064, 19896,32160, 19936,20384, 19944,24480, 19952,28576,
+   19960,32672, 20008,20960, 20016,25056, 20024,29152, 20072,21472,
+   20080,25568, 20088,29664, 20136,21984, 20144,26080, 20152,30176,
+   20200,22496, 20208,26592, 20216,30688, 20264,23008, 20272,27104,
+   20280,31200, 20328,23520, 20336,27616, 20344,31712, 20392,24032,
+   20400,28128, 20408,32224, 20456,24544, 20464,28640, 20472,32736,
+   20528,24616, 20536,28712, 20584,21032, 20592,25128, 20600,29224,
+   20648,21544, 20656,25640, 20664,29736, 20712,22056, 20720,26152,
+   20728,30248, 20776,22568, 20784,26664, 20792,30760, 20840,23080,
+   20848,27176, 20856,31272, 20904,23592, 20912,27688, 20920,31784,
+   20968,24104, 20976,28200, 20984,32296, 21040,24680, 21048,28776,
+   21104,25192, 21112,29288, 21160,21608, 21168,25704, 21176,29800,
+   21224,22120, 21232,26216, 21240,30312, 21288,22632, 21296,26728,
+   21304,30824, 21352,23144, 21360,27240, 21368,31336, 21416,23656,
+   21424,27752, 21432,31848, 21480,24168, 21488,28264, 21496,32360,
+   21552,24744, 21560,28840, 21616,25256, 21624,29352, 21680,25768,
+   21688,29864, 21736,22184, 21744,26280, 21752,30376, 21800,22696,
+   21808,26792, 21816,30888, 21864,23208, 21872,27304, 21880,31400,
+   21928,23720, 21936,27816, 21944,31912, 21992,24232, 22000,28328,
+   22008,32424, 22064,24808, 22072,28904, 22128,25320, 22136,29416,
+   22192,25832, 22200,29928, 22256,26344, 22264,30440, 22312,22760,
+   22320,26856, 22328,30952, 22376,23272, 22384,27368, 22392,31464,
+   22440,23784, 22448,27880, 22456,31976, 22504,24296, 22512,28392,
+   22520,32488, 22576,24872, 22584,28968, 22640,25384, 22648,29480,
+   22704,25896, 22712,29992, 22768,26408, 22776,30504, 22832,26920,
+   22840,31016, 22888,23336, 22896,27432, 22904,31528, 22952,23848,
+   22960,27944, 22968,32040, 23016,24360, 23024,28456, 23032,32552,
+   23088,24936, 23096,29032, 23152,25448, 23160,29544, 23216,25960,
+   23224,30056, 23280,26472, 23288,30568, 23344,26984, 23352,31080,
+   23408,27496, 23416,31592, 23464,23912, 23472,28008, 23480,32104,
+   23528,24424, 23536,28520, 23544,32616, 23600,25000, 23608,29096,
+   23664,25512, 23672,29608, 23728,26024, 23736,30120, 23792,26536,
+   23800,30632, 23856,27048, 23864,31144, 23920,27560, 23928,31656,
+   23984,28072, 23992,32168, 24040,24488, 24048,28584, 24056,32680,
+   24112,25064, 24120,29160, 24176,25576, 24184,29672, 24240,26088,
+   24248,30184, 24304,26600, 24312,30696, 24368,27112, 24376,31208,
+   24432,27624, 24440,31720, 24496,28136, 24504,32232, 24560,28648,
+   24568,32744, 24632,28720, 24688,25136, 24696,29232, 24752,25648,
+   24760,29744, 24816,26160, 24824,30256, 24880,26672, 24888,30768,
+   24944,27184, 24952,31280, 25008,27696, 25016,31792, 25072,28208,
+   25080,32304, 25144,28784, 25208,29296, 25264,25712, 25272,29808,
+   25328,26224, 25336,30320, 25392,26736, 25400,30832, 25456,27248,
+   25464,31344, 25520,27760, 25528,31856, 25584,28272, 25592,32368,
+   25656,28848, 25720,29360, 25784,29872, 25840,26288, 25848,30384,
+   25904,26800, 25912,30896, 25968,27312, 25976,31408, 26032,27824,
+   26040,31920, 26096,28336, 26104,32432, 26168,28912, 26232,29424,
+   26296,29936, 26360,30448, 26416,26864, 26424,30960, 26480,27376,
+   26488,31472, 26544,27888, 26552,31984, 26608,28400, 26616,32496,
+   26680,28976, 26744,29488, 26808,30000, 26872,30512, 26936,31024,
+   26992,27440, 27000,31536, 27056,27952, 27064,32048, 27120,28464,
+   27128,32560, 27192,29040, 27256,29552, 27320,30064, 27384,30576,
+   27448,31088, 27512,31600, 27568,28016, 27576,32112, 27632,28528,
+   27640,32624, 27704,29104, 27768,29616, 27832,30128, 27896,30640,
+   27960,31152, 28024,31664, 28088,32176, 28144,28592, 28152,32688,
+   28216,29168, 28280,29680, 28344,30192, 28408,30704, 28472,31216,
+   28536,31728, 28600,32240, 28664,32752, 28792,29240, 28856,29752,
+   28920,30264, 28984,30776, 29048,31288, 29112,31800, 29176,32312,
+   29368,29816, 29432,30328, 29496,30840, 29560,31352, 29624,31864,
+   29688,32376, 29944,30392, 30008,30904, 30072,31416, 30136,31928,
+   30200,32440, 30520,30968, 30584,31480, 30648,31992, 30712,32504,
+   31096,31544, 31160,32056, 31224,32568, 31672,32120, 31736,32632,
+   32248,32696
+};
+
+
+const uint16_t armBitRevIndexTable_fixed_16[ARMBITREVINDEXTABLE_FIXED_16_TABLE_LENGTH] =
+{
+   /* radix 4, size 12 */
+   8,64, 16,32, 24,96, 40,80, 56,112, 88,104
+};
+
+const uint16_t armBitRevIndexTable_fixed_32[ARMBITREVINDEXTABLE_FIXED_32_TABLE_LENGTH] =
+{
+   /* 4x2, size 24 */
+   8,128, 16,64, 24,192, 40,160, 48,96, 56,224, 72,144,
+   88,208, 104,176, 120,240, 152,200, 184,232
+};
+
+const uint16_t armBitRevIndexTable_fixed_64[ARMBITREVINDEXTABLE_FIXED_64_TABLE_LENGTH] =
+{
+   /* radix 4, size 56 */
+   8,256, 16,128, 24,384, 32,64, 40,320, 48,192, 56,448, 72,288, 80,160, 88,416, 104,352,
+   112,224, 120,480, 136,272, 152,400, 168,336, 176,208, 184,464, 200,304, 216,432,
+   232,368, 248,496, 280,392, 296,328, 312,456, 344,424, 376,488, 440,472
+};
+
+const uint16_t armBitRevIndexTable_fixed_128[ARMBITREVINDEXTABLE_FIXED_128_TABLE_LENGTH] =
+{
+   /* 4x2, size 112 */
+   8,512, 16,256, 24,768, 32,128, 40,640, 48,384, 56,896, 72,576, 80,320, 88,832, 96,192,
+   104,704, 112,448, 120,960, 136,544, 144,288, 152,800, 168,672, 176,416, 184,928, 200,608,
+   208,352, 216,864, 232,736, 240,480, 248,992, 264,528, 280,784, 296,656, 304,400, 312,912,
+   328,592, 344,848, 360,720, 368,464, 376,976, 392,560, 408,816, 424,688, 440,944, 456,624,
+   472,880, 488,752, 504,1008, 536,776, 552,648, 568,904, 600,840, 616,712, 632,968,
+   664,808, 696,936, 728,872, 760,1000, 824,920, 888,984
+};
+
+const uint16_t armBitRevIndexTable_fixed_256[ARMBITREVINDEXTABLE_FIXED_256_TABLE_LENGTH] =
+{
+   /* radix 4, size 240 */
+   8,1024, 16,512, 24,1536, 32,256, 40,1280, 48,768, 56,1792, 64,128, 72,1152, 80,640,
+   88,1664, 96,384, 104,1408, 112,896, 120,1920, 136,1088, 144,576, 152,1600, 160,320,
+   168,1344, 176,832, 184,1856, 200,1216, 208,704, 216,1728, 224,448, 232,1472, 240,960,
+   248,1984, 264,1056, 272,544, 280,1568, 296,1312, 304,800, 312,1824, 328,1184, 336,672,
+   344,1696, 352,416, 360,1440, 368,928, 376,1952, 392,1120, 400,608, 408,1632, 424,1376,
+   432,864, 440,1888, 456,1248, 464,736, 472,1760, 488,1504, 496,992, 504,2016, 520,1040,
+   536,1552, 552,1296, 560,784, 568,1808, 584,1168, 592,656, 600,1680, 616,1424, 624,912,
+   632,1936, 648,1104, 664,1616, 680,1360, 688,848, 696,1872, 712,1232, 728,1744, 744,1488,
+   752,976, 760,2000, 776,1072, 792,1584, 808,1328, 824,1840, 840,1200, 856,1712, 872,1456,
+   880,944, 888,1968, 904,1136, 920,1648, 936,1392, 952,1904, 968,1264, 984,1776, 1000,1520,
+   1016,2032, 1048,1544, 1064,1288, 1080,1800, 1096,1160, 1112,1672, 1128,1416, 1144,1928,
+   1176,1608, 1192,1352, 1208,1864, 1240,1736, 1256,1480, 1272,1992, 1304,1576, 1336,1832,
+   1368,1704, 1384,1448, 1400,1960, 1432,1640, 1464,1896, 1496,1768, 1528,2024, 1592,1816,
+   1624,1688, 1656,1944, 1720,1880, 1784,2008, 1912,1976
+};
+
+const uint16_t armBitRevIndexTable_fixed_512[ARMBITREVINDEXTABLE_FIXED_512_TABLE_LENGTH] =
+{
+   /* 4x2, size 480 */
+   8,2048, 16,1024, 24,3072, 32,512, 40,2560, 48,1536, 56,3584, 64,256, 72,2304, 80,1280,
+   88,3328, 96,768, 104,2816, 112,1792, 120,3840, 136,2176, 144,1152, 152,3200, 160,640,
+   168,2688, 176,1664, 184,3712, 192,384, 200,2432, 208,1408, 216,3456, 224,896, 232,2944,
+   240,1920, 248,3968, 264,2112, 272,1088, 280,3136, 288,576, 296,2624, 304,1600, 312,3648,
+   328,2368, 336,1344, 344,3392, 352,832, 360,2880, 368,1856, 376,3904, 392,2240, 400,1216,
+   408,3264, 416,704, 424,2752, 432,1728, 440,3776, 456,2496, 464,1472, 472,3520, 480,960,
+   488,3008, 496,1984, 504,4032, 520,2080, 528,1056, 536,3104, 552,2592, 560,1568, 568,3616,
+   584,2336, 592,1312, 600,3360, 608,800, 616,2848, 624,1824, 632,3872, 648,2208, 656,1184,
+   664,3232, 680,2720, 688,1696, 696,3744, 712,2464, 720,1440, 728,3488, 736,928, 744,2976,
+   752,1952, 760,4000, 776,2144, 784,1120, 792,3168, 808,2656, 816,1632, 824,3680, 840,2400,
+   848,1376, 856,3424, 872,2912, 880,1888, 888,3936, 904,2272, 912,1248, 920,3296, 936,2784,
+   944,1760, 952,3808, 968,2528, 976,1504, 984,3552, 1000,3040, 1008,2016, 1016,4064,
+   1032,2064, 1048,3088, 1064,2576, 1072,1552, 1080,3600, 1096,2320, 1104,1296, 1112,3344,
+   1128,2832, 1136,1808, 1144,3856, 1160,2192, 1176,3216, 1192,2704, 1200,1680, 1208,3728,
+   1224,2448, 1232,1424, 1240,3472, 1256,2960, 1264,1936, 1272,3984, 1288,2128, 1304,3152,
+   1320,2640, 1328,1616, 1336,3664, 1352,2384, 1368,3408, 1384,2896, 1392,1872, 1400,3920,
+   1416,2256, 1432,3280, 1448,2768, 1456,1744, 1464,3792, 1480,2512, 1496,3536, 1512,3024,
+   1520,2000, 1528,4048, 1544,2096, 1560,3120, 1576,2608, 1592,3632, 1608,2352, 1624,3376,
+   1640,2864, 1648,1840, 1656,3888, 1672,2224, 1688,3248, 1704,2736, 1720,3760, 1736,2480,
+   1752,3504, 1768,2992, 1776,1968, 1784,4016, 1800,2160, 1816,3184, 1832,2672, 1848,3696,
+   1864,2416, 1880,3440, 1896,2928, 1912,3952, 1928,2288, 1944,3312, 1960,2800, 1976,3824,
+   1992,2544, 2008,3568, 2024,3056, 2040,4080, 2072,3080, 2088,2568, 2104,3592, 2120,2312,
+   2136,3336, 2152,2824, 2168,3848, 2200,3208, 2216,2696, 2232,3720, 2248,2440, 2264,3464,
+   2280,2952, 2296,3976, 2328,3144, 2344,2632, 2360,3656, 2392,3400, 2408,2888, 2424,3912,
+   2456,3272, 2472,2760, 2488,3784, 2520,3528, 2536,3016, 2552,4040, 2584,3112, 2616,3624,
+   2648,3368, 2664,2856, 2680,3880, 2712,3240, 2744,3752, 2776,3496, 2792,2984, 2808,4008,
+   2840,3176, 2872,3688, 2904,3432, 2936,3944, 2968,3304, 3000,3816, 3032,3560, 3064,4072,
+   3128,3608, 3160,3352, 3192,3864, 3256,3736, 3288,3480, 3320,3992, 3384,3672, 3448,3928,
+   3512,3800, 3576,4056, 3704,3896, 3832,4024
+};
+
+const uint16_t armBitRevIndexTable_fixed_1024[ARMBITREVINDEXTABLE_FIXED_1024_TABLE_LENGTH] =
+{
+    /* radix 4, size 992 */
+    8,4096, 16,2048, 24,6144, 32,1024, 40,5120, 48,3072, 56,7168, 64,512, 72,4608,
+    80,2560, 88,6656, 96,1536, 104,5632, 112,3584, 120,7680, 128,256, 136,4352,
+    144,2304, 152,6400, 160,1280, 168,5376, 176,3328, 184,7424, 192,768, 200,4864,
+    208,2816, 216,6912, 224,1792, 232,5888, 240,3840, 248,7936, 264,4224, 272,2176,
+    280,6272, 288,1152, 296,5248, 304,3200, 312,7296, 320,640, 328,4736, 336,2688,
+    344,6784, 352,1664, 360,5760, 368,3712, 376,7808, 392,4480, 400,2432, 408,6528,
+    416,1408, 424,5504, 432,3456, 440,7552, 448,896, 456,4992, 464,2944, 472,7040,
+    480,1920, 488,6016, 496,3968, 504,8064, 520,4160, 528,2112, 536,6208, 544,1088,
+    552,5184, 560,3136, 568,7232, 584,4672, 592,2624, 600,6720, 608,1600, 616,5696,
+    624,3648, 632,7744, 648,4416, 656,2368, 664,6464, 672,1344, 680,5440, 688,3392,
+    696,7488, 704,832, 712,4928, 720,2880, 728,6976, 736,1856, 744,5952, 752,3904,
+    760,8000, 776,4288, 784,2240, 792,6336, 800,1216, 808,5312, 816,3264, 824,7360,
+    840,4800, 848,2752, 856,6848, 864,1728, 872,5824, 880,3776, 888,7872, 904,4544,
+    912,2496, 920,6592, 928,1472, 936,5568, 944,3520, 952,7616, 968,5056, 976,3008,
+    984,7104, 992,1984, 1000,6080, 1008,4032, 1016,8128, 1032,4128, 1040,2080,
+    1048,6176, 1064,5152, 1072,3104, 1080,7200, 1096,4640, 1104,2592, 1112,6688,
+    1120,1568, 1128,5664, 1136,3616, 1144,7712, 1160,4384, 1168,2336, 1176,6432,
+    1184,1312, 1192,5408, 1200,3360, 1208,7456, 1224,4896, 1232,2848, 1240,6944,
+    1248,1824, 1256,5920, 1264,3872, 1272,7968, 1288,4256, 1296,2208, 1304,6304,
+    1320,5280, 1328,3232, 1336,7328, 1352,4768, 1360,2720, 1368,6816, 1376,1696,
+    1384,5792, 1392,3744, 1400,7840, 1416,4512, 1424,2464, 1432,6560, 1448,5536,
+    1456,3488, 1464,7584, 1480,5024, 1488,2976, 1496,7072, 1504,1952, 1512,6048,
+    1520,4000, 1528,8096, 1544,4192, 1552,2144, 1560,6240, 1576,5216, 1584,3168,
+    1592,7264, 1608,4704, 1616,2656, 1624,6752, 1640,5728, 1648,3680, 1656,7776,
+    1672,4448, 1680,2400, 1688,6496, 1704,5472, 1712,3424, 1720,7520, 1736,4960,
+    1744,2912, 1752,7008, 1760,1888, 1768,5984, 1776,3936, 1784,8032, 1800,4320,
+    1808,2272, 1816,6368, 1832,5344, 1840,3296, 1848,7392, 1864,4832, 1872,2784,
+    1880,6880, 1896,5856, 1904,3808, 1912,7904, 1928,4576, 1936,2528, 1944,6624,
+    1960,5600, 1968,3552, 1976,7648, 1992,5088, 2000,3040, 2008,7136, 2024,6112,
+    2032,4064, 2040,8160, 2056,4112, 2072,6160, 2088,5136, 2096,3088, 2104,7184,
+    2120,4624, 2128,2576, 2136,6672, 2152,5648, 2160,3600, 2168,7696, 2184,4368,
+    2192,2320, 2200,6416, 2216,5392, 2224,3344, 2232,7440, 2248,4880, 2256,2832,
+    2264,6928, 2280,5904, 2288,3856, 2296,7952, 2312,4240, 2328,6288, 2344,5264,
+    2352,3216, 2360,7312, 2376,4752, 2384,2704, 2392,6800, 2408,5776, 2416,3728,
+    2424,7824, 2440,4496, 2456,6544, 2472,5520, 2480,3472, 2488,7568, 2504,5008,
+    2512,2960, 2520,7056, 2536,6032, 2544,3984, 2552,8080, 2568,4176, 2584,6224,
+    2600,5200, 2608,3152, 2616,7248, 2632,4688, 2648,6736, 2664,5712, 2672,3664,
+    2680,7760, 2696,4432, 2712,6480, 2728,5456, 2736,3408, 2744,7504, 2760,4944,
+    2768,2896, 2776,6992, 2792,5968, 2800,3920, 2808,8016, 2824,4304, 2840,6352,
+    2856,5328, 2864,3280, 2872,7376, 2888,4816, 2904,6864, 2920,5840, 2928,3792,
+    2936,7888, 2952,4560, 2968,6608, 2984,5584, 2992,3536, 3000,7632, 3016,5072,
+    3032,7120, 3048,6096, 3056,4048, 3064,8144, 3080,4144, 3096,6192, 3112,5168,
+    3128,7216, 3144,4656, 3160,6704, 3176,5680, 3184,3632, 3192,7728, 3208,4400,
+    3224,6448, 3240,5424, 3248,3376, 3256,7472, 3272,4912, 3288,6960, 3304,5936,
+    3312,3888, 3320,7984, 3336,4272, 3352,6320, 3368,5296, 3384,7344, 3400,4784,
+    3416,6832, 3432,5808, 3440,3760, 3448,7856, 3464,4528, 3480,6576, 3496,5552,
+    3512,7600, 3528,5040, 3544,7088, 3560,6064, 3568,4016, 3576,8112, 3592,4208,
+    3608,6256, 3624,5232, 3640,7280, 3656,4720, 3672,6768, 3688,5744, 3704,7792,
+    3720,4464, 3736,6512, 3752,5488, 3768,7536, 3784,4976, 3800,7024, 3816,6000,
+    3824,3952, 3832,8048, 3848,4336, 3864,6384, 3880,5360, 3896,7408, 3912,4848,
+    3928,6896, 3944,5872, 3960,7920, 3976,4592, 3992,6640, 4008,5616, 4024,7664,
+    4040,5104, 4056,7152, 4072,6128, 4088,8176, 4120,6152, 4136,5128, 4152,7176,
+    4168,4616, 4184,6664, 4200,5640, 4216,7688, 4232,4360, 4248,6408, 4264,5384,
+    4280,7432, 4296,4872, 4312,6920, 4328,5896, 4344,7944, 4376,6280, 4392,5256,
+    4408,7304, 4424,4744, 4440,6792, 4456,5768, 4472,7816, 4504,6536, 4520,5512,
+    4536,7560, 4552,5000, 4568,7048, 4584,6024, 4600,8072, 4632,6216, 4648,5192,
+    4664,7240, 4696,6728, 4712,5704, 4728,7752, 4760,6472, 4776,5448, 4792,7496,
+    4808,4936, 4824,6984, 4840,5960, 4856,8008, 4888,6344, 4904,5320, 4920,7368,
+    4952,6856, 4968,5832, 4984,7880, 5016,6600, 5032,5576, 5048,7624, 5080,7112,
+    5096,6088, 5112,8136, 5144,6184, 5176,7208, 5208,6696, 5224,5672, 5240,7720,
+    5272,6440, 5288,5416, 5304,7464, 5336,6952, 5352,5928, 5368,7976, 5400,6312,
+    5432,7336, 5464,6824, 5480,5800, 5496,7848, 5528,6568, 5560,7592, 5592,7080,
+    5608,6056, 5624,8104, 5656,6248, 5688,7272, 5720,6760, 5752,7784, 5784,6504,
+    5816,7528, 5848,7016, 5864,5992, 5880,8040, 5912,6376, 5944,7400, 5976,6888,
+    6008,7912, 6040,6632, 6072,7656, 6104,7144, 6136,8168, 6200,7192, 6232,6680,
+    6264,7704, 6296,6424, 6328,7448, 6360,6936, 6392,7960, 6456,7320, 6488,6808,
+    6520,7832, 6584,7576, 6616,7064, 6648,8088, 6712,7256, 6776,7768, 6840,7512,
+    6872,7000, 6904,8024, 6968,7384, 7032,7896, 7096,7640, 7160,8152, 7288,7736,
+    7352,7480, 7416,7992, 7544,7864, 7672,8120, 7928,8056
+};
+
+const uint16_t armBitRevIndexTable_fixed_2048[ARMBITREVINDEXTABLE_FIXED_2048_TABLE_LENGTH] =
+{
+    /* 4x2, size 1984 */
+    8,8192, 16,4096, 24,12288, 32,2048, 40,10240, 48,6144, 56,14336, 64,1024,
+    72,9216, 80,5120, 88,13312, 96,3072, 104,11264, 112,7168, 120,15360, 128,512,
+    136,8704, 144,4608, 152,12800, 160,2560, 168,10752, 176,6656, 184,14848,
+    192,1536, 200,9728, 208,5632, 216,13824, 224,3584, 232,11776, 240,7680,
+    248,15872, 264,8448, 272,4352, 280,12544, 288,2304, 296,10496, 304,6400,
+    312,14592, 320,1280, 328,9472, 336,5376, 344,13568, 352,3328, 360,11520,
+    368,7424, 376,15616, 384,768, 392,8960, 400,4864, 408,13056, 416,2816,
+    424,11008, 432,6912, 440,15104, 448,1792, 456,9984, 464,5888, 472,14080,
+    480,3840, 488,12032, 496,7936, 504,16128, 520,8320, 528,4224, 536,12416,
+    544,2176, 552,10368, 560,6272, 568,14464, 576,1152, 584,9344, 592,5248,
+    600,13440, 608,3200, 616,11392, 624,7296, 632,15488, 648,8832, 656,4736,
+    664,12928, 672,2688, 680,10880, 688,6784, 696,14976, 704,1664, 712,9856,
+    720,5760, 728,13952, 736,3712, 744,11904, 752,7808, 760,16000, 776,8576,
+    784,4480, 792,12672, 800,2432, 808,10624, 816,6528, 824,14720, 832,1408,
+    840,9600, 848,5504, 856,13696, 864,3456, 872,11648, 880,7552, 888,15744,
+    904,9088, 912,4992, 920,13184, 928,2944, 936,11136, 944,7040, 952,15232,
+    960,1920, 968,10112, 976,6016, 984,14208, 992,3968, 1000,12160, 1008,8064,
+    1016,16256, 1032,8256, 1040,4160, 1048,12352, 1056,2112, 1064,10304, 1072,6208,
+    1080,14400, 1096,9280, 1104,5184, 1112,13376, 1120,3136, 1128,11328, 1136,7232,
+    1144,15424, 1160,8768, 1168,4672, 1176,12864, 1184,2624, 1192,10816, 1200,6720,
+    1208,14912, 1216,1600, 1224,9792, 1232,5696, 1240,13888, 1248,3648, 1256,11840,
+    1264,7744, 1272,15936, 1288,8512, 1296,4416, 1304,12608, 1312,2368, 1320,10560,
+    1328,6464, 1336,14656, 1352,9536, 1360,5440, 1368,13632, 1376,3392, 1384,11584,
+    1392,7488, 1400,15680, 1416,9024, 1424,4928, 1432,13120, 1440,2880, 1448,11072,
+    1456,6976, 1464,15168, 1472,1856, 1480,10048, 1488,5952, 1496,14144, 1504,3904,
+    1512,12096, 1520,8000, 1528,16192, 1544,8384, 1552,4288, 1560,12480, 1568,2240,
+    1576,10432, 1584,6336, 1592,14528, 1608,9408, 1616,5312, 1624,13504, 1632,3264,
+    1640,11456, 1648,7360, 1656,15552, 1672,8896, 1680,4800, 1688,12992, 1696,2752,
+    1704,10944, 1712,6848, 1720,15040, 1736,9920, 1744,5824, 1752,14016, 1760,3776,
+    1768,11968, 1776,7872, 1784,16064, 1800,8640, 1808,4544, 1816,12736, 1824,2496,
+    1832,10688, 1840,6592, 1848,14784, 1864,9664, 1872,5568, 1880,13760, 1888,3520,
+    1896,11712, 1904,7616, 1912,15808, 1928,9152, 1936,5056, 1944,13248, 1952,3008,
+    1960,11200, 1968,7104, 1976,15296, 1992,10176, 2000,6080, 2008,14272, 2016,4032,
+    2024,12224, 2032,8128, 2040,16320, 2056,8224, 2064,4128, 2072,12320, 2088,10272,
+    2096,6176, 2104,14368, 2120,9248, 2128,5152, 2136,13344, 2144,3104, 2152,11296,
+    2160,7200, 2168,15392, 2184,8736, 2192,4640, 2200,12832, 2208,2592, 2216,10784,
+    2224,6688, 2232,14880, 2248,9760, 2256,5664, 2264,13856, 2272,3616, 2280,11808,
+    2288,7712, 2296,15904, 2312,8480, 2320,4384, 2328,12576, 2344,10528, 2352,6432,
+    2360,14624, 2376,9504, 2384,5408, 2392,13600, 2400,3360, 2408,11552, 2416,7456,
+    2424,15648, 2440,8992, 2448,4896, 2456,13088, 2464,2848, 2472,11040, 2480,6944,
+    2488,15136, 2504,10016, 2512,5920, 2520,14112, 2528,3872, 2536,12064, 2544,7968,
+    2552,16160, 2568,8352, 2576,4256, 2584,12448, 2600,10400, 2608,6304, 2616,14496,
+    2632,9376, 2640,5280, 2648,13472, 2656,3232, 2664,11424, 2672,7328, 2680,15520,
+    2696,8864, 2704,4768, 2712,12960, 2728,10912, 2736,6816, 2744,15008, 2760,9888,
+    2768,5792, 2776,13984, 2784,3744, 2792,11936, 2800,7840, 2808,16032, 2824,8608,
+    2832,4512, 2840,12704, 2856,10656, 2864,6560, 2872,14752, 2888,9632, 2896,5536,
+    2904,13728, 2912,3488, 2920,11680, 2928,7584, 2936,15776, 2952,9120, 2960,5024,
+    2968,13216, 2984,11168, 2992,7072, 3000,15264, 3016,10144, 3024,6048,
+    3032,14240, 3040,4000, 3048,12192, 3056,8096, 3064,16288, 3080,8288, 3088,4192,
+    3096,12384, 3112,10336, 3120,6240, 3128,14432, 3144,9312, 3152,5216, 3160,13408,
+    3176,11360, 3184,7264, 3192,15456, 3208,8800, 3216,4704, 3224,12896, 3240,10848,
+    3248,6752, 3256,14944, 3272,9824, 3280,5728, 3288,13920, 3296,3680, 3304,11872,
+    3312,7776, 3320,15968, 3336,8544, 3344,4448, 3352,12640, 3368,10592, 3376,6496,
+    3384,14688, 3400,9568, 3408,5472, 3416,13664, 3432,11616, 3440,7520, 3448,15712,
+    3464,9056, 3472,4960, 3480,13152, 3496,11104, 3504,7008, 3512,15200, 3528,10080,
+    3536,5984, 3544,14176, 3552,3936, 3560,12128, 3568,8032, 3576,16224, 3592,8416,
+    3600,4320, 3608,12512, 3624,10464, 3632,6368, 3640,14560, 3656,9440, 3664,5344,
+    3672,13536, 3688,11488, 3696,7392, 3704,15584, 3720,8928, 3728,4832, 3736,13024,
+    3752,10976, 3760,6880, 3768,15072, 3784,9952, 3792,5856, 3800,14048, 3816,12000,
+    3824,7904, 3832,16096, 3848,8672, 3856,4576, 3864,12768, 3880,10720, 3888,6624,
+    3896,14816, 3912,9696, 3920,5600, 3928,13792, 3944,11744, 3952,7648, 3960,15840,
+    3976,9184, 3984,5088, 3992,13280, 4008,11232, 4016,7136, 4024,15328, 4040,10208,
+    4048,6112, 4056,14304, 4072,12256, 4080,8160, 4088,16352, 4104,8208, 4120,12304,
+    4136,10256, 4144,6160, 4152,14352, 4168,9232, 4176,5136, 4184,13328, 4200,11280,
+    4208,7184, 4216,15376, 4232,8720, 4240,4624, 4248,12816, 4264,10768, 4272,6672,
+    4280,14864, 4296,9744, 4304,5648, 4312,13840, 4328,11792, 4336,7696, 4344,15888,
+    4360,8464, 4376,12560, 4392,10512, 4400,6416, 4408,14608, 4424,9488, 4432,5392,
+    4440,13584, 4456,11536, 4464,7440, 4472,15632, 4488,8976, 4496,4880, 4504,13072,
+    4520,11024, 4528,6928, 4536,15120, 4552,10000, 4560,5904, 4568,14096,
+    4584,12048, 4592,7952, 4600,16144, 4616,8336, 4632,12432, 4648,10384, 4656,6288,
+    4664,14480, 4680,9360, 4688,5264, 4696,13456, 4712,11408, 4720,7312, 4728,15504,
+    4744,8848, 4760,12944, 4776,10896, 4784,6800, 4792,14992, 4808,9872, 4816,5776,
+    4824,13968, 4840,11920, 4848,7824, 4856,16016, 4872,8592, 4888,12688,
+    4904,10640, 4912,6544, 4920,14736, 4936,9616, 4944,5520, 4952,13712, 4968,11664,
+    4976,7568, 4984,15760, 5000,9104, 5016,13200, 5032,11152, 5040,7056, 5048,15248,
+    5064,10128, 5072,6032, 5080,14224, 5096,12176, 5104,8080, 5112,16272, 5128,8272,
+    5144,12368, 5160,10320, 5168,6224, 5176,14416, 5192,9296, 5208,13392,
+    5224,11344, 5232,7248, 5240,15440, 5256,8784, 5272,12880, 5288,10832, 5296,6736,
+    5304,14928, 5320,9808, 5328,5712, 5336,13904, 5352,11856, 5360,7760, 5368,15952,
+    5384,8528, 5400,12624, 5416,10576, 5424,6480, 5432,14672, 5448,9552, 5464,13648,
+    5480,11600, 5488,7504, 5496,15696, 5512,9040, 5528,13136, 5544,11088, 5552,6992,
+    5560,15184, 5576,10064, 5584,5968, 5592,14160, 5608,12112, 5616,8016,
+    5624,16208, 5640,8400, 5656,12496, 5672,10448, 5680,6352, 5688,14544, 5704,9424,
+    5720,13520, 5736,11472, 5744,7376, 5752,15568, 5768,8912, 5784,13008,
+    5800,10960, 5808,6864, 5816,15056, 5832,9936, 5848,14032, 5864,11984, 5872,7888,
+    5880,16080, 5896,8656, 5912,12752, 5928,10704, 5936,6608, 5944,14800, 5960,9680,
+    5976,13776, 5992,11728, 6000,7632, 6008,15824, 6024,9168, 6040,13264,
+    6056,11216, 6064,7120, 6072,15312, 6088,10192, 6104,14288, 6120,12240,
+    6128,8144, 6136,16336, 6152,8240, 6168,12336, 6184,10288, 6200,14384, 6216,9264,
+    6232,13360, 6248,11312, 6256,7216, 6264,15408, 6280,8752, 6296,12848,
+    6312,10800, 6320,6704, 6328,14896, 6344,9776, 6360,13872, 6376,11824, 6384,7728,
+    6392,15920, 6408,8496, 6424,12592, 6440,10544, 6456,14640, 6472,9520,
+    6488,13616, 6504,11568, 6512,7472, 6520,15664, 6536,9008, 6552,13104,
+    6568,11056, 6576,6960, 6584,15152, 6600,10032, 6616,14128, 6632,12080,
+    6640,7984, 6648,16176, 6664,8368, 6680,12464, 6696,10416, 6712,14512, 6728,9392,
+    6744,13488, 6760,11440, 6768,7344, 6776,15536, 6792,8880, 6808,12976,
+    6824,10928, 6840,15024, 6856,9904, 6872,14000, 6888,11952, 6896,7856,
+    6904,16048, 6920,8624, 6936,12720, 6952,10672, 6968,14768, 6984,9648,
+    7000,13744, 7016,11696, 7024,7600, 7032,15792, 7048,9136, 7064,13232,
+    7080,11184, 7096,15280, 7112,10160, 7128,14256, 7144,12208, 7152,8112,
+    7160,16304, 7176,8304, 7192,12400, 7208,10352, 7224,14448, 7240,9328,
+    7256,13424, 7272,11376, 7288,15472, 7304,8816, 7320,12912, 7336,10864,
+    7352,14960, 7368,9840, 7384,13936, 7400,11888, 7408,7792, 7416,15984, 7432,8560,
+    7448,12656, 7464,10608, 7480,14704, 7496,9584, 7512,13680, 7528,11632,
+    7544,15728, 7560,9072, 7576,13168, 7592,11120, 7608,15216, 7624,10096,
+    7640,14192, 7656,12144, 7664,8048, 7672,16240, 7688,8432, 7704,12528,
+    7720,10480, 7736,14576, 7752,9456, 7768,13552, 7784,11504, 7800,15600,
+    7816,8944, 7832,13040, 7848,10992, 7864,15088, 7880,9968, 7896,14064,
+    7912,12016, 7928,16112, 7944,8688, 7960,12784, 7976,10736, 7992,14832,
+    8008,9712, 8024,13808, 8040,11760, 8056,15856, 8072,9200, 8088,13296,
+    8104,11248, 8120,15344, 8136,10224, 8152,14320, 8168,12272, 8184,16368,
+    8216,12296, 8232,10248, 8248,14344, 8264,9224, 8280,13320, 8296,11272,
+    8312,15368, 8328,8712, 8344,12808, 8360,10760, 8376,14856, 8392,9736,
+    8408,13832, 8424,11784, 8440,15880, 8472,12552, 8488,10504, 8504,14600,
+    8520,9480, 8536,13576, 8552,11528, 8568,15624, 8584,8968, 8600,13064,
+    8616,11016, 8632,15112, 8648,9992, 8664,14088, 8680,12040, 8696,16136,
+    8728,12424, 8744,10376, 8760,14472, 8776,9352, 8792,13448, 8808,11400,
+    8824,15496, 8856,12936, 8872,10888, 8888,14984, 8904,9864, 8920,13960,
+    8936,11912, 8952,16008, 8984,12680, 9000,10632, 9016,14728, 9032,9608,
+    9048,13704, 9064,11656, 9080,15752, 9112,13192, 9128,11144, 9144,15240,
+    9160,10120, 9176,14216, 9192,12168, 9208,16264, 9240,12360, 9256,10312,
+    9272,14408, 9304,13384, 9320,11336, 9336,15432, 9368,12872, 9384,10824,
+    9400,14920, 9416,9800, 9432,13896, 9448,11848, 9464,15944, 9496,12616,
+    9512,10568, 9528,14664, 9560,13640, 9576,11592, 9592,15688, 9624,13128,
+    9640,11080, 9656,15176, 9672,10056, 9688,14152, 9704,12104, 9720,16200,
+    9752,12488, 9768,10440, 9784,14536, 9816,13512, 9832,11464, 9848,15560,
+    9880,13000, 9896,10952, 9912,15048, 9944,14024, 9960,11976, 9976,16072,
+    10008,12744, 10024,10696, 10040,14792, 10072,13768, 10088,11720, 10104,15816,
+    10136,13256, 10152,11208, 10168,15304, 10200,14280, 10216,12232, 10232,16328,
+    10264,12328, 10296,14376, 10328,13352, 10344,11304, 10360,15400, 10392,12840,
+    10408,10792, 10424,14888, 10456,13864, 10472,11816, 10488,15912, 10520,12584,
+    10552,14632, 10584,13608, 10600,11560, 10616,15656, 10648,13096, 10664,11048,
+    10680,15144, 10712,14120, 10728,12072, 10744,16168, 10776,12456, 10808,14504,
+    10840,13480, 10856,11432, 10872,15528, 10904,12968, 10936,15016, 10968,13992,
+    10984,11944, 11000,16040, 11032,12712, 11064,14760, 11096,13736, 11112,11688,
+    11128,15784, 11160,13224, 11192,15272, 11224,14248, 11240,12200, 11256,16296,
+    11288,12392, 11320,14440, 11352,13416, 11384,15464, 11416,12904, 11448,14952,
+    11480,13928, 11496,11880, 11512,15976, 11544,12648, 11576,14696, 11608,13672,
+    11640,15720, 11672,13160, 11704,15208, 11736,14184, 11752,12136, 11768,16232,
+    11800,12520, 11832,14568, 11864,13544, 11896,15592, 11928,13032, 11960,15080,
+    11992,14056, 12024,16104, 12056,12776, 12088,14824, 12120,13800, 12152,15848,
+    12184,13288, 12216,15336, 12248,14312, 12280,16360, 12344,14360, 12376,13336,
+    12408,15384, 12440,12824, 12472,14872, 12504,13848, 12536,15896, 12600,14616,
+    12632,13592, 12664,15640, 12696,13080, 12728,15128, 12760,14104, 12792,16152,
+    12856,14488, 12888,13464, 12920,15512, 12984,15000, 13016,13976, 13048,16024,
+    13112,14744, 13144,13720, 13176,15768, 13240,15256, 13272,14232, 13304,16280,
+    13368,14424, 13432,15448, 13496,14936, 13528,13912, 13560,15960, 13624,14680,
+    13688,15704, 13752,15192, 13784,14168, 13816,16216, 13880,14552, 13944,15576,
+    14008,15064, 14072,16088, 14136,14808, 14200,15832, 14264,15320, 14328,16344,
+    14456,15416, 14520,14904, 14584,15928, 14712,15672, 14776,15160, 14840,16184,
+    14968,15544, 15096,16056, 15224,15800, 15352,16312, 15608,15992, 15864,16248
+};
+
+const uint16_t armBitRevIndexTable_fixed_4096[ARMBITREVINDEXTABLE_FIXED_4096_TABLE_LENGTH] =
+{
+    /* radix 4, size 4032 */
+    8,16384, 16,8192, 24,24576, 32,4096, 40,20480, 48,12288, 56,28672, 64,2048,
+    72,18432, 80,10240, 88,26624, 96,6144, 104,22528, 112,14336, 120,30720,
+    128,1024, 136,17408, 144,9216, 152,25600, 160,5120, 168,21504, 176,13312,
+    184,29696, 192,3072, 200,19456, 208,11264, 216,27648, 224,7168, 232,23552,
+    240,15360, 248,31744, 256,512, 264,16896, 272,8704, 280,25088, 288,4608,
+    296,20992, 304,12800, 312,29184, 320,2560, 328,18944, 336,10752, 344,27136,
+    352,6656, 360,23040, 368,14848, 376,31232, 384,1536, 392,17920, 400,9728,
+    408,26112, 416,5632, 424,22016, 432,13824, 440,30208, 448,3584, 456,19968,
+    464,11776, 472,28160, 480,7680, 488,24064, 496,15872, 504,32256, 520,16640,
+    528,8448, 536,24832, 544,4352, 552,20736, 560,12544, 568,28928, 576,2304,
+    584,18688, 592,10496, 600,26880, 608,6400, 616,22784, 624,14592, 632,30976,
+    640,1280, 648,17664, 656,9472, 664,25856, 672,5376, 680,21760, 688,13568,
+    696,29952, 704,3328, 712,19712, 720,11520, 728,27904, 736,7424, 744,23808,
+    752,15616, 760,32000, 776,17152, 784,8960, 792,25344, 800,4864, 808,21248,
+    816,13056, 824,29440, 832,2816, 840,19200, 848,11008, 856,27392, 864,6912,
+    872,23296, 880,15104, 888,31488, 896,1792, 904,18176, 912,9984, 920,26368,
+    928,5888, 936,22272, 944,14080, 952,30464, 960,3840, 968,20224, 976,12032,
+    984,28416, 992,7936, 1000,24320, 1008,16128, 1016,32512, 1032,16512, 1040,8320,
+    1048,24704, 1056,4224, 1064,20608, 1072,12416, 1080,28800, 1088,2176,
+    1096,18560, 1104,10368, 1112,26752, 1120,6272, 1128,22656, 1136,14464,
+    1144,30848, 1160,17536, 1168,9344, 1176,25728, 1184,5248, 1192,21632,
+    1200,13440, 1208,29824, 1216,3200, 1224,19584, 1232,11392, 1240,27776,
+    1248,7296, 1256,23680, 1264,15488, 1272,31872, 1288,17024, 1296,8832,
+    1304,25216, 1312,4736, 1320,21120, 1328,12928, 1336,29312, 1344,2688,
+    1352,19072, 1360,10880, 1368,27264, 1376,6784, 1384,23168, 1392,14976,
+    1400,31360, 1408,1664, 1416,18048, 1424,9856, 1432,26240, 1440,5760, 1448,22144,
+    1456,13952, 1464,30336, 1472,3712, 1480,20096, 1488,11904, 1496,28288,
+    1504,7808, 1512,24192, 1520,16000, 1528,32384, 1544,16768, 1552,8576,
+    1560,24960, 1568,4480, 1576,20864, 1584,12672, 1592,29056, 1600,2432,
+    1608,18816, 1616,10624, 1624,27008, 1632,6528, 1640,22912, 1648,14720,
+    1656,31104, 1672,17792, 1680,9600, 1688,25984, 1696,5504, 1704,21888,
+    1712,13696, 1720,30080, 1728,3456, 1736,19840, 1744,11648, 1752,28032,
+    1760,7552, 1768,23936, 1776,15744, 1784,32128, 1800,17280, 1808,9088,
+    1816,25472, 1824,4992, 1832,21376, 1840,13184, 1848,29568, 1856,2944,
+    1864,19328, 1872,11136, 1880,27520, 1888,7040, 1896,23424, 1904,15232,
+    1912,31616, 1928,18304, 1936,10112, 1944,26496, 1952,6016, 1960,22400,
+    1968,14208, 1976,30592, 1984,3968, 1992,20352, 2000,12160, 2008,28544,
+    2016,8064, 2024,24448, 2032,16256, 2040,32640, 2056,16448, 2064,8256,
+    2072,24640, 2080,4160, 2088,20544, 2096,12352, 2104,28736, 2120,18496,
+    2128,10304, 2136,26688, 2144,6208, 2152,22592, 2160,14400, 2168,30784,
+    2184,17472, 2192,9280, 2200,25664, 2208,5184, 2216,21568, 2224,13376,
+    2232,29760, 2240,3136, 2248,19520, 2256,11328, 2264,27712, 2272,7232,
+    2280,23616, 2288,15424, 2296,31808, 2312,16960, 2320,8768, 2328,25152,
+    2336,4672, 2344,21056, 2352,12864, 2360,29248, 2368,2624, 2376,19008,
+    2384,10816, 2392,27200, 2400,6720, 2408,23104, 2416,14912, 2424,31296,
+    2440,17984, 2448,9792, 2456,26176, 2464,5696, 2472,22080, 2480,13888,
+    2488,30272, 2496,3648, 2504,20032, 2512,11840, 2520,28224, 2528,7744,
+    2536,24128, 2544,15936, 2552,32320, 2568,16704, 2576,8512, 2584,24896,
+    2592,4416, 2600,20800, 2608,12608, 2616,28992, 2632,18752, 2640,10560,
+    2648,26944, 2656,6464, 2664,22848, 2672,14656, 2680,31040, 2696,17728,
+    2704,9536, 2712,25920, 2720,5440, 2728,21824, 2736,13632, 2744,30016, 2752,3392,
+    2760,19776, 2768,11584, 2776,27968, 2784,7488, 2792,23872, 2800,15680,
+    2808,32064, 2824,17216, 2832,9024, 2840,25408, 2848,4928, 2856,21312,
+    2864,13120, 2872,29504, 2888,19264, 2896,11072, 2904,27456, 2912,6976,
+    2920,23360, 2928,15168, 2936,31552, 2952,18240, 2960,10048, 2968,26432,
+    2976,5952, 2984,22336, 2992,14144, 3000,30528, 3008,3904, 3016,20288,
+    3024,12096, 3032,28480, 3040,8000, 3048,24384, 3056,16192, 3064,32576,
+    3080,16576, 3088,8384, 3096,24768, 3104,4288, 3112,20672, 3120,12480,
+    3128,28864, 3144,18624, 3152,10432, 3160,26816, 3168,6336, 3176,22720,
+    3184,14528, 3192,30912, 3208,17600, 3216,9408, 3224,25792, 3232,5312,
+    3240,21696, 3248,13504, 3256,29888, 3272,19648, 3280,11456, 3288,27840,
+    3296,7360, 3304,23744, 3312,15552, 3320,31936, 3336,17088, 3344,8896,
+    3352,25280, 3360,4800, 3368,21184, 3376,12992, 3384,29376, 3400,19136,
+    3408,10944, 3416,27328, 3424,6848, 3432,23232, 3440,15040, 3448,31424,
+    3464,18112, 3472,9920, 3480,26304, 3488,5824, 3496,22208, 3504,14016,
+    3512,30400, 3520,3776, 3528,20160, 3536,11968, 3544,28352, 3552,7872,
+    3560,24256, 3568,16064, 3576,32448, 3592,16832, 3600,8640, 3608,25024,
+    3616,4544, 3624,20928, 3632,12736, 3640,29120, 3656,18880, 3664,10688,
+    3672,27072, 3680,6592, 3688,22976, 3696,14784, 3704,31168, 3720,17856,
+    3728,9664, 3736,26048, 3744,5568, 3752,21952, 3760,13760, 3768,30144,
+    3784,19904, 3792,11712, 3800,28096, 3808,7616, 3816,24000, 3824,15808,
+    3832,32192, 3848,17344, 3856,9152, 3864,25536, 3872,5056, 3880,21440,
+    3888,13248, 3896,29632, 3912,19392, 3920,11200, 3928,27584, 3936,7104,
+    3944,23488, 3952,15296, 3960,31680, 3976,18368, 3984,10176, 3992,26560,
+    4000,6080, 4008,22464, 4016,14272, 4024,30656, 4040,20416, 4048,12224,
+    4056,28608, 4064,8128, 4072,24512, 4080,16320, 4088,32704, 4104,16416,
+    4112,8224, 4120,24608, 4136,20512, 4144,12320, 4152,28704, 4168,18464,
+    4176,10272, 4184,26656, 4192,6176, 4200,22560, 4208,14368, 4216,30752,
+    4232,17440, 4240,9248, 4248,25632, 4256,5152, 4264,21536, 4272,13344,
+    4280,29728, 4296,19488, 4304,11296, 4312,27680, 4320,7200, 4328,23584,
+    4336,15392, 4344,31776, 4360,16928, 4368,8736, 4376,25120, 4384,4640,
+    4392,21024, 4400,12832, 4408,29216, 4424,18976, 4432,10784, 4440,27168,
+    4448,6688, 4456,23072, 4464,14880, 4472,31264, 4488,17952, 4496,9760,
+    4504,26144, 4512,5664, 4520,22048, 4528,13856, 4536,30240, 4552,20000,
+    4560,11808, 4568,28192, 4576,7712, 4584,24096, 4592,15904, 4600,32288,
+    4616,16672, 4624,8480, 4632,24864, 4648,20768, 4656,12576, 4664,28960,
+    4680,18720, 4688,10528, 4696,26912, 4704,6432, 4712,22816, 4720,14624,
+    4728,31008, 4744,17696, 4752,9504, 4760,25888, 4768,5408, 4776,21792,
+    4784,13600, 4792,29984, 4808,19744, 4816,11552, 4824,27936, 4832,7456,
+    4840,23840, 4848,15648, 4856,32032, 4872,17184, 4880,8992, 4888,25376,
+    4904,21280, 4912,13088, 4920,29472, 4936,19232, 4944,11040, 4952,27424,
+    4960,6944, 4968,23328, 4976,15136, 4984,31520, 5000,18208, 5008,10016,
+    5016,26400, 5024,5920, 5032,22304, 5040,14112, 5048,30496, 5064,20256,
+    5072,12064, 5080,28448, 5088,7968, 5096,24352, 5104,16160, 5112,32544,
+    5128,16544, 5136,8352, 5144,24736, 5160,20640, 5168,12448, 5176,28832,
+    5192,18592, 5200,10400, 5208,26784, 5216,6304, 5224,22688, 5232,14496,
+    5240,30880, 5256,17568, 5264,9376, 5272,25760, 5288,21664, 5296,13472,
+    5304,29856, 5320,19616, 5328,11424, 5336,27808, 5344,7328, 5352,23712,
+    5360,15520, 5368,31904, 5384,17056, 5392,8864, 5400,25248, 5416,21152,
+    5424,12960, 5432,29344, 5448,19104, 5456,10912, 5464,27296, 5472,6816,
+    5480,23200, 5488,15008, 5496,31392, 5512,18080, 5520,9888, 5528,26272,
+    5536,5792, 5544,22176, 5552,13984, 5560,30368, 5576,20128, 5584,11936,
+    5592,28320, 5600,7840, 5608,24224, 5616,16032, 5624,32416, 5640,16800,
+    5648,8608, 5656,24992, 5672,20896, 5680,12704, 5688,29088, 5704,18848,
+    5712,10656, 5720,27040, 5728,6560, 5736,22944, 5744,14752, 5752,31136,
+    5768,17824, 5776,9632, 5784,26016, 5800,21920, 5808,13728, 5816,30112,
+    5832,19872, 5840,11680, 5848,28064, 5856,7584, 5864,23968, 5872,15776,
+    5880,32160, 5896,17312, 5904,9120, 5912,25504, 5928,21408, 5936,13216,
+    5944,29600, 5960,19360, 5968,11168, 5976,27552, 5984,7072, 5992,23456,
+    6000,15264, 6008,31648, 6024,18336, 6032,10144, 6040,26528, 6056,22432,
+    6064,14240, 6072,30624, 6088,20384, 6096,12192, 6104,28576, 6112,8096,
+    6120,24480, 6128,16288, 6136,32672, 6152,16480, 6160,8288, 6168,24672,
+    6184,20576, 6192,12384, 6200,28768, 6216,18528, 6224,10336, 6232,26720,
+    6248,22624, 6256,14432, 6264,30816, 6280,17504, 6288,9312, 6296,25696,
+    6312,21600, 6320,13408, 6328,29792, 6344,19552, 6352,11360, 6360,27744,
+    6368,7264, 6376,23648, 6384,15456, 6392,31840, 6408,16992, 6416,8800,
+    6424,25184, 6440,21088, 6448,12896, 6456,29280, 6472,19040, 6480,10848,
+    6488,27232, 6496,6752, 6504,23136, 6512,14944, 6520,31328, 6536,18016,
+    6544,9824, 6552,26208, 6568,22112, 6576,13920, 6584,30304, 6600,20064,
+    6608,11872, 6616,28256, 6624,7776, 6632,24160, 6640,15968, 6648,32352,
+    6664,16736, 6672,8544, 6680,24928, 6696,20832, 6704,12640, 6712,29024,
+    6728,18784, 6736,10592, 6744,26976, 6760,22880, 6768,14688, 6776,31072,
+    6792,17760, 6800,9568, 6808,25952, 6824,21856, 6832,13664, 6840,30048,
+    6856,19808, 6864,11616, 6872,28000, 6880,7520, 6888,23904, 6896,15712,
+    6904,32096, 6920,17248, 6928,9056, 6936,25440, 6952,21344, 6960,13152,
+    6968,29536, 6984,19296, 6992,11104, 7000,27488, 7016,23392, 7024,15200,
+    7032,31584, 7048,18272, 7056,10080, 7064,26464, 7080,22368, 7088,14176,
+    7096,30560, 7112,20320, 7120,12128, 7128,28512, 7136,8032, 7144,24416,
+    7152,16224, 7160,32608, 7176,16608, 7184,8416, 7192,24800, 7208,20704,
+    7216,12512, 7224,28896, 7240,18656, 7248,10464, 7256,26848, 7272,22752,
+    7280,14560, 7288,30944, 7304,17632, 7312,9440, 7320,25824, 7336,21728,
+    7344,13536, 7352,29920, 7368,19680, 7376,11488, 7384,27872, 7400,23776,
+    7408,15584, 7416,31968, 7432,17120, 7440,8928, 7448,25312, 7464,21216,
+    7472,13024, 7480,29408, 7496,19168, 7504,10976, 7512,27360, 7528,23264,
+    7536,15072, 7544,31456, 7560,18144, 7568,9952, 7576,26336, 7592,22240,
+    7600,14048, 7608,30432, 7624,20192, 7632,12000, 7640,28384, 7648,7904,
+    7656,24288, 7664,16096, 7672,32480, 7688,16864, 7696,8672, 7704,25056,
+    7720,20960, 7728,12768, 7736,29152, 7752,18912, 7760,10720, 7768,27104,
+    7784,23008, 7792,14816, 7800,31200, 7816,17888, 7824,9696, 7832,26080,
+    7848,21984, 7856,13792, 7864,30176, 7880,19936, 7888,11744, 7896,28128,
+    7912,24032, 7920,15840, 7928,32224, 7944,17376, 7952,9184, 7960,25568,
+    7976,21472, 7984,13280, 7992,29664, 8008,19424, 8016,11232, 8024,27616,
+    8040,23520, 8048,15328, 8056,31712, 8072,18400, 8080,10208, 8088,26592,
+    8104,22496, 8112,14304, 8120,30688, 8136,20448, 8144,12256, 8152,28640,
+    8168,24544, 8176,16352, 8184,32736, 8200,16400, 8216,24592, 8232,20496,
+    8240,12304, 8248,28688, 8264,18448, 8272,10256, 8280,26640, 8296,22544,
+    8304,14352, 8312,30736, 8328,17424, 8336,9232, 8344,25616, 8360,21520,
+    8368,13328, 8376,29712, 8392,19472, 8400,11280, 8408,27664, 8424,23568,
+    8432,15376, 8440,31760, 8456,16912, 8464,8720, 8472,25104, 8488,21008,
+    8496,12816, 8504,29200, 8520,18960, 8528,10768, 8536,27152, 8552,23056,
+    8560,14864, 8568,31248, 8584,17936, 8592,9744, 8600,26128, 8616,22032,
+    8624,13840, 8632,30224, 8648,19984, 8656,11792, 8664,28176, 8680,24080,
+    8688,15888, 8696,32272, 8712,16656, 8728,24848, 8744,20752, 8752,12560,
+    8760,28944, 8776,18704, 8784,10512, 8792,26896, 8808,22800, 8816,14608,
+    8824,30992, 8840,17680, 8848,9488, 8856,25872, 8872,21776, 8880,13584,
+    8888,29968, 8904,19728, 8912,11536, 8920,27920, 8936,23824, 8944,15632,
+    8952,32016, 8968,17168, 8984,25360, 9000,21264, 9008,13072, 9016,29456,
+    9032,19216, 9040,11024, 9048,27408, 9064,23312, 9072,15120, 9080,31504,
+    9096,18192, 9104,10000, 9112,26384, 9128,22288, 9136,14096, 9144,30480,
+    9160,20240, 9168,12048, 9176,28432, 9192,24336, 9200,16144, 9208,32528,
+    9224,16528, 9240,24720, 9256,20624, 9264,12432, 9272,28816, 9288,18576,
+    9296,10384, 9304,26768, 9320,22672, 9328,14480, 9336,30864, 9352,17552,
+    9368,25744, 9384,21648, 9392,13456, 9400,29840, 9416,19600, 9424,11408,
+    9432,27792, 9448,23696, 9456,15504, 9464,31888, 9480,17040, 9496,25232,
+    9512,21136, 9520,12944, 9528,29328, 9544,19088, 9552,10896, 9560,27280,
+    9576,23184, 9584,14992, 9592,31376, 9608,18064, 9616,9872, 9624,26256,
+    9640,22160, 9648,13968, 9656,30352, 9672,20112, 9680,11920, 9688,28304,
+    9704,24208, 9712,16016, 9720,32400, 9736,16784, 9752,24976, 9768,20880,
+    9776,12688, 9784,29072, 9800,18832, 9808,10640, 9816,27024, 9832,22928,
+    9840,14736, 9848,31120, 9864,17808, 9880,26000, 9896,21904, 9904,13712,
+    9912,30096, 9928,19856, 9936,11664, 9944,28048, 9960,23952, 9968,15760,
+    9976,32144, 9992,17296, 10008,25488, 10024,21392, 10032,13200, 10040,29584,
+    10056,19344, 10064,11152, 10072,27536, 10088,23440, 10096,15248, 10104,31632,
+    10120,18320, 10136,26512, 10152,22416, 10160,14224, 10168,30608, 10184,20368,
+    10192,12176, 10200,28560, 10216,24464, 10224,16272, 10232,32656, 10248,16464,
+    10264,24656, 10280,20560, 10288,12368, 10296,28752, 10312,18512, 10328,26704,
+    10344,22608, 10352,14416, 10360,30800, 10376,17488, 10392,25680, 10408,21584,
+    10416,13392, 10424,29776, 10440,19536, 10448,11344, 10456,27728, 10472,23632,
+    10480,15440, 10488,31824, 10504,16976, 10520,25168, 10536,21072, 10544,12880,
+    10552,29264, 10568,19024, 10576,10832, 10584,27216, 10600,23120, 10608,14928,
+    10616,31312, 10632,18000, 10648,26192, 10664,22096, 10672,13904, 10680,30288,
+    10696,20048, 10704,11856, 10712,28240, 10728,24144, 10736,15952, 10744,32336,
+    10760,16720, 10776,24912, 10792,20816, 10800,12624, 10808,29008, 10824,18768,
+    10840,26960, 10856,22864, 10864,14672, 10872,31056, 10888,17744, 10904,25936,
+    10920,21840, 10928,13648, 10936,30032, 10952,19792, 10960,11600, 10968,27984,
+    10984,23888, 10992,15696, 11000,32080, 11016,17232, 11032,25424, 11048,21328,
+    11056,13136, 11064,29520, 11080,19280, 11096,27472, 11112,23376, 11120,15184,
+    11128,31568, 11144,18256, 11160,26448, 11176,22352, 11184,14160, 11192,30544,
+    11208,20304, 11216,12112, 11224,28496, 11240,24400, 11248,16208, 11256,32592,
+    11272,16592, 11288,24784, 11304,20688, 11312,12496, 11320,28880, 11336,18640,
+    11352,26832, 11368,22736, 11376,14544, 11384,30928, 11400,17616, 11416,25808,
+    11432,21712, 11440,13520, 11448,29904, 11464,19664, 11480,27856, 11496,23760,
+    11504,15568, 11512,31952, 11528,17104, 11544,25296, 11560,21200, 11568,13008,
+    11576,29392, 11592,19152, 11608,27344, 11624,23248, 11632,15056, 11640,31440,
+    11656,18128, 11672,26320, 11688,22224, 11696,14032, 11704,30416, 11720,20176,
+    11728,11984, 11736,28368, 11752,24272, 11760,16080, 11768,32464, 11784,16848,
+    11800,25040, 11816,20944, 11824,12752, 11832,29136, 11848,18896, 11864,27088,
+    11880,22992, 11888,14800, 11896,31184, 11912,17872, 11928,26064, 11944,21968,
+    11952,13776, 11960,30160, 11976,19920, 11992,28112, 12008,24016, 12016,15824,
+    12024,32208, 12040,17360, 12056,25552, 12072,21456, 12080,13264, 12088,29648,
+    12104,19408, 12120,27600, 12136,23504, 12144,15312, 12152,31696, 12168,18384,
+    12184,26576, 12200,22480, 12208,14288, 12216,30672, 12232,20432, 12248,28624,
+    12264,24528, 12272,16336, 12280,32720, 12296,16432, 12312,24624, 12328,20528,
+    12344,28720, 12360,18480, 12376,26672, 12392,22576, 12400,14384, 12408,30768,
+    12424,17456, 12440,25648, 12456,21552, 12464,13360, 12472,29744, 12488,19504,
+    12504,27696, 12520,23600, 12528,15408, 12536,31792, 12552,16944, 12568,25136,
+    12584,21040, 12592,12848, 12600,29232, 12616,18992, 12632,27184, 12648,23088,
+    12656,14896, 12664,31280, 12680,17968, 12696,26160, 12712,22064, 12720,13872,
+    12728,30256, 12744,20016, 12760,28208, 12776,24112, 12784,15920, 12792,32304,
+    12808,16688, 12824,24880, 12840,20784, 12856,28976, 12872,18736, 12888,26928,
+    12904,22832, 12912,14640, 12920,31024, 12936,17712, 12952,25904, 12968,21808,
+    12976,13616, 12984,30000, 13000,19760, 13016,27952, 13032,23856, 13040,15664,
+    13048,32048, 13064,17200, 13080,25392, 13096,21296, 13112,29488, 13128,19248,
+    13144,27440, 13160,23344, 13168,15152, 13176,31536, 13192,18224, 13208,26416,
+    13224,22320, 13232,14128, 13240,30512, 13256,20272, 13272,28464, 13288,24368,
+    13296,16176, 13304,32560, 13320,16560, 13336,24752, 13352,20656, 13368,28848,
+    13384,18608, 13400,26800, 13416,22704, 13424,14512, 13432,30896, 13448,17584,
+    13464,25776, 13480,21680, 13496,29872, 13512,19632, 13528,27824, 13544,23728,
+    13552,15536, 13560,31920, 13576,17072, 13592,25264, 13608,21168, 13624,29360,
+    13640,19120, 13656,27312, 13672,23216, 13680,15024, 13688,31408, 13704,18096,
+    13720,26288, 13736,22192, 13744,14000, 13752,30384, 13768,20144, 13784,28336,
+    13800,24240, 13808,16048, 13816,32432, 13832,16816, 13848,25008, 13864,20912,
+    13880,29104, 13896,18864, 13912,27056, 13928,22960, 13936,14768, 13944,31152,
+    13960,17840, 13976,26032, 13992,21936, 14008,30128, 14024,19888, 14040,28080,
+    14056,23984, 14064,15792, 14072,32176, 14088,17328, 14104,25520, 14120,21424,
+    14136,29616, 14152,19376, 14168,27568, 14184,23472, 14192,15280, 14200,31664,
+    14216,18352, 14232,26544, 14248,22448, 14264,30640, 14280,20400, 14296,28592,
+    14312,24496, 14320,16304, 14328,32688, 14344,16496, 14360,24688, 14376,20592,
+    14392,28784, 14408,18544, 14424,26736, 14440,22640, 14456,30832, 14472,17520,
+    14488,25712, 14504,21616, 14520,29808, 14536,19568, 14552,27760, 14568,23664,
+    14576,15472, 14584,31856, 14600,17008, 14616,25200, 14632,21104, 14648,29296,
+    14664,19056, 14680,27248, 14696,23152, 14704,14960, 14712,31344, 14728,18032,
+    14744,26224, 14760,22128, 14776,30320, 14792,20080, 14808,28272, 14824,24176,
+    14832,15984, 14840,32368, 14856,16752, 14872,24944, 14888,20848, 14904,29040,
+    14920,18800, 14936,26992, 14952,22896, 14968,31088, 14984,17776, 15000,25968,
+    15016,21872, 15032,30064, 15048,19824, 15064,28016, 15080,23920, 15088,15728,
+    15096,32112, 15112,17264, 15128,25456, 15144,21360, 15160,29552, 15176,19312,
+    15192,27504, 15208,23408, 15224,31600, 15240,18288, 15256,26480, 15272,22384,
+    15288,30576, 15304,20336, 15320,28528, 15336,24432, 15344,16240, 15352,32624,
+    15368,16624, 15384,24816, 15400,20720, 15416,28912, 15432,18672, 15448,26864,
+    15464,22768, 15480,30960, 15496,17648, 15512,25840, 15528,21744, 15544,29936,
+    15560,19696, 15576,27888, 15592,23792, 15608,31984, 15624,17136, 15640,25328,
+    15656,21232, 15672,29424, 15688,19184, 15704,27376, 15720,23280, 15736,31472,
+    15752,18160, 15768,26352, 15784,22256, 15800,30448, 15816,20208, 15832,28400,
+    15848,24304, 15856,16112, 15864,32496, 15880,16880, 15896,25072, 15912,20976,
+    15928,29168, 15944,18928, 15960,27120, 15976,23024, 15992,31216, 16008,17904,
+    16024,26096, 16040,22000, 16056,30192, 16072,19952, 16088,28144, 16104,24048,
+    16120,32240, 16136,17392, 16152,25584, 16168,21488, 16184,29680, 16200,19440,
+    16216,27632, 16232,23536, 16248,31728, 16264,18416, 16280,26608, 16296,22512,
+    16312,30704, 16328,20464, 16344,28656, 16360,24560, 16376,32752, 16408,24584,
+    16424,20488, 16440,28680, 16456,18440, 16472,26632, 16488,22536, 16504,30728,
+    16520,17416, 16536,25608, 16552,21512, 16568,29704, 16584,19464, 16600,27656,
+    16616,23560, 16632,31752, 16648,16904, 16664,25096, 16680,21000, 16696,29192,
+    16712,18952, 16728,27144, 16744,23048, 16760,31240, 16776,17928, 16792,26120,
+    16808,22024, 16824,30216, 16840,19976, 16856,28168, 16872,24072, 16888,32264,
+    16920,24840, 16936,20744, 16952,28936, 16968,18696, 16984,26888, 17000,22792,
+    17016,30984, 17032,17672, 17048,25864, 17064,21768, 17080,29960, 17096,19720,
+    17112,27912, 17128,23816, 17144,32008, 17176,25352, 17192,21256, 17208,29448,
+    17224,19208, 17240,27400, 17256,23304, 17272,31496, 17288,18184, 17304,26376,
+    17320,22280, 17336,30472, 17352,20232, 17368,28424, 17384,24328, 17400,32520,
+    17432,24712, 17448,20616, 17464,28808, 17480,18568, 17496,26760, 17512,22664,
+    17528,30856, 17560,25736, 17576,21640, 17592,29832, 17608,19592, 17624,27784,
+    17640,23688, 17656,31880, 17688,25224, 17704,21128, 17720,29320, 17736,19080,
+    17752,27272, 17768,23176, 17784,31368, 17800,18056, 17816,26248, 17832,22152,
+    17848,30344, 17864,20104, 17880,28296, 17896,24200, 17912,32392, 17944,24968,
+    17960,20872, 17976,29064, 17992,18824, 18008,27016, 18024,22920, 18040,31112,
+    18072,25992, 18088,21896, 18104,30088, 18120,19848, 18136,28040, 18152,23944,
+    18168,32136, 18200,25480, 18216,21384, 18232,29576, 18248,19336, 18264,27528,
+    18280,23432, 18296,31624, 18328,26504, 18344,22408, 18360,30600, 18376,20360,
+    18392,28552, 18408,24456, 18424,32648, 18456,24648, 18472,20552, 18488,28744,
+    18520,26696, 18536,22600, 18552,30792, 18584,25672, 18600,21576, 18616,29768,
+    18632,19528, 18648,27720, 18664,23624, 18680,31816, 18712,25160, 18728,21064,
+    18744,29256, 18760,19016, 18776,27208, 18792,23112, 18808,31304, 18840,26184,
+    18856,22088, 18872,30280, 18888,20040, 18904,28232, 18920,24136, 18936,32328,
+    18968,24904, 18984,20808, 19000,29000, 19032,26952, 19048,22856, 19064,31048,
+    19096,25928, 19112,21832, 19128,30024, 19144,19784, 19160,27976, 19176,23880,
+    19192,32072, 19224,25416, 19240,21320, 19256,29512, 19288,27464, 19304,23368,
+    19320,31560, 19352,26440, 19368,22344, 19384,30536, 19400,20296, 19416,28488,
+    19432,24392, 19448,32584, 19480,24776, 19496,20680, 19512,28872, 19544,26824,
+    19560,22728, 19576,30920, 19608,25800, 19624,21704, 19640,29896, 19672,27848,
+    19688,23752, 19704,31944, 19736,25288, 19752,21192, 19768,29384, 19800,27336,
+    19816,23240, 19832,31432, 19864,26312, 19880,22216, 19896,30408, 19912,20168,
+    19928,28360, 19944,24264, 19960,32456, 19992,25032, 20008,20936, 20024,29128,
+    20056,27080, 20072,22984, 20088,31176, 20120,26056, 20136,21960, 20152,30152,
+    20184,28104, 20200,24008, 20216,32200, 20248,25544, 20264,21448, 20280,29640,
+    20312,27592, 20328,23496, 20344,31688, 20376,26568, 20392,22472, 20408,30664,
+    20440,28616, 20456,24520, 20472,32712, 20504,24616, 20536,28712, 20568,26664,
+    20584,22568, 20600,30760, 20632,25640, 20648,21544, 20664,29736, 20696,27688,
+    20712,23592, 20728,31784, 20760,25128, 20776,21032, 20792,29224, 20824,27176,
+    20840,23080, 20856,31272, 20888,26152, 20904,22056, 20920,30248, 20952,28200,
+    20968,24104, 20984,32296, 21016,24872, 21048,28968, 21080,26920, 21096,22824,
+    21112,31016, 21144,25896, 21160,21800, 21176,29992, 21208,27944, 21224,23848,
+    21240,32040, 21272,25384, 21304,29480, 21336,27432, 21352,23336, 21368,31528,
+    21400,26408, 21416,22312, 21432,30504, 21464,28456, 21480,24360, 21496,32552,
+    21528,24744, 21560,28840, 21592,26792, 21608,22696, 21624,30888, 21656,25768,
+    21688,29864, 21720,27816, 21736,23720, 21752,31912, 21784,25256, 21816,29352,
+    21848,27304, 21864,23208, 21880,31400, 21912,26280, 21928,22184, 21944,30376,
+    21976,28328, 21992,24232, 22008,32424, 22040,25000, 22072,29096, 22104,27048,
+    22120,22952, 22136,31144, 22168,26024, 22200,30120, 22232,28072, 22248,23976,
+    22264,32168, 22296,25512, 22328,29608, 22360,27560, 22376,23464, 22392,31656,
+    22424,26536, 22456,30632, 22488,28584, 22504,24488, 22520,32680, 22552,24680,
+    22584,28776, 22616,26728, 22648,30824, 22680,25704, 22712,29800, 22744,27752,
+    22760,23656, 22776,31848, 22808,25192, 22840,29288, 22872,27240, 22888,23144,
+    22904,31336, 22936,26216, 22968,30312, 23000,28264, 23016,24168, 23032,32360,
+    23064,24936, 23096,29032, 23128,26984, 23160,31080, 23192,25960, 23224,30056,
+    23256,28008, 23272,23912, 23288,32104, 23320,25448, 23352,29544, 23384,27496,
+    23416,31592, 23448,26472, 23480,30568, 23512,28520, 23528,24424, 23544,32616,
+    23576,24808, 23608,28904, 23640,26856, 23672,30952, 23704,25832, 23736,29928,
+    23768,27880, 23800,31976, 23832,25320, 23864,29416, 23896,27368, 23928,31464,
+    23960,26344, 23992,30440, 24024,28392, 24040,24296, 24056,32488, 24088,25064,
+    24120,29160, 24152,27112, 24184,31208, 24216,26088, 24248,30184, 24280,28136,
+    24312,32232, 24344,25576, 24376,29672, 24408,27624, 24440,31720, 24472,26600,
+    24504,30696, 24536,28648, 24568,32744, 24632,28696, 24664,26648, 24696,30744,
+    24728,25624, 24760,29720, 24792,27672, 24824,31768, 24856,25112, 24888,29208,
+    24920,27160, 24952,31256, 24984,26136, 25016,30232, 25048,28184, 25080,32280,
+    25144,28952, 25176,26904, 25208,31000, 25240,25880, 25272,29976, 25304,27928,
+    25336,32024, 25400,29464, 25432,27416, 25464,31512, 25496,26392, 25528,30488,
+    25560,28440, 25592,32536, 25656,28824, 25688,26776, 25720,30872, 25784,29848,
+    25816,27800, 25848,31896, 25912,29336, 25944,27288, 25976,31384, 26008,26264,
+    26040,30360, 26072,28312, 26104,32408, 26168,29080, 26200,27032, 26232,31128,
+    26296,30104, 26328,28056, 26360,32152, 26424,29592, 26456,27544, 26488,31640,
+    26552,30616, 26584,28568, 26616,32664, 26680,28760, 26744,30808, 26808,29784,
+    26840,27736, 26872,31832, 26936,29272, 26968,27224, 27000,31320, 27064,30296,
+    27096,28248, 27128,32344, 27192,29016, 27256,31064, 27320,30040, 27352,27992,
+    27384,32088, 27448,29528, 27512,31576, 27576,30552, 27608,28504, 27640,32600,
+    27704,28888, 27768,30936, 27832,29912, 27896,31960, 27960,29400, 28024,31448,
+    28088,30424, 28120,28376, 28152,32472, 28216,29144, 28280,31192, 28344,30168,
+    28408,32216, 28472,29656, 28536,31704, 28600,30680, 28664,32728, 28792,30776,
+    28856,29752, 28920,31800, 28984,29240, 29048,31288, 29112,30264, 29176,32312,
+    29304,31032, 29368,30008, 29432,32056, 29560,31544, 29624,30520, 29688,32568,
+    29816,30904, 29944,31928, 30072,31416, 30136,30392, 30200,32440, 30328,31160,
+    30456,32184, 30584,31672, 30712,32696, 30968,31864, 31096,31352, 31224,32376,
+    31480,32120, 31736,32632, 32248,32504
+};
+
+/**
+* \par
+* Example code for Floating-point RFFT Twiddle factors Generation:
+* \par
+* <pre>TW = exp(2*pi*i*[0:L/2-1]/L - pi/2*i).' </pre>
+* \par
+* Real and Imag values are in interleaved fashion
+*/
+const float32_t twiddleCoef_rfft_32[32] = {
+    0.000000000f,  1.000000000f,
+    0.195090322f,  0.980785280f,
+    0.382683432f,  0.923879533f,
+    0.555570233f,  0.831469612f,
+    0.707106781f,  0.707106781f,
+    0.831469612f,  0.555570233f,
+    0.923879533f,  0.382683432f,
+    0.980785280f,  0.195090322f,
+    1.000000000f,  0.000000000f,
+    0.980785280f, -0.195090322f,
+    0.923879533f, -0.382683432f,
+    0.831469612f, -0.555570233f,
+    0.707106781f, -0.707106781f,
+    0.555570233f, -0.831469612f,
+    0.382683432f, -0.923879533f,
+    0.195090322f, -0.980785280f
+};
+
+const float32_t twiddleCoef_rfft_64[64] = {
+    0.000000000000000f,  1.000000000000000f,
+    0.098017140329561f,  0.995184726672197f,
+    0.195090322016128f,  0.980785280403230f,
+    0.290284677254462f,  0.956940335732209f,
+    0.382683432365090f,  0.923879532511287f,
+    0.471396736825998f,  0.881921264348355f,
+    0.555570233019602f,  0.831469612302545f,
+    0.634393284163645f,  0.773010453362737f,
+    0.707106781186547f,  0.707106781186548f,
+    0.773010453362737f,  0.634393284163645f,
+    0.831469612302545f,  0.555570233019602f,
+    0.881921264348355f,  0.471396736825998f,
+    0.923879532511287f,  0.382683432365090f,
+    0.956940335732209f,  0.290284677254462f,
+    0.980785280403230f,  0.195090322016128f,
+    0.995184726672197f,  0.098017140329561f,
+    1.000000000000000f,  0.000000000000000f,
+    0.995184726672197f, -0.098017140329561f,
+    0.980785280403230f, -0.195090322016128f,
+    0.956940335732209f, -0.290284677254462f,
+    0.923879532511287f, -0.382683432365090f,
+    0.881921264348355f, -0.471396736825998f,
+    0.831469612302545f, -0.555570233019602f,
+    0.773010453362737f, -0.634393284163645f,
+    0.707106781186548f, -0.707106781186547f,
+    0.634393284163645f, -0.773010453362737f,
+    0.555570233019602f, -0.831469612302545f,
+    0.471396736825998f, -0.881921264348355f,
+    0.382683432365090f, -0.923879532511287f,
+    0.290284677254462f, -0.956940335732209f,
+    0.195090322016129f, -0.980785280403230f,
+    0.098017140329561f, -0.995184726672197f
+};
+
+const float32_t twiddleCoef_rfft_128[128] = {
+    0.000000000f,  1.000000000f,
+    0.049067674f,  0.998795456f,
+    0.098017140f,  0.995184727f,
+    0.146730474f,  0.989176510f,
+    0.195090322f,  0.980785280f,
+    0.242980180f,  0.970031253f,
+    0.290284677f,  0.956940336f,
+    0.336889853f,  0.941544065f,
+    0.382683432f,  0.923879533f,
+    0.427555093f,  0.903989293f,
+    0.471396737f,  0.881921264f,
+    0.514102744f,  0.857728610f,
+    0.555570233f,  0.831469612f,
+    0.595699304f,  0.803207531f,
+    0.634393284f,  0.773010453f,
+    0.671558955f,  0.740951125f,
+    0.707106781f,  0.707106781f,
+    0.740951125f,  0.671558955f,
+    0.773010453f,  0.634393284f,
+    0.803207531f,  0.595699304f,
+    0.831469612f,  0.555570233f,
+    0.857728610f,  0.514102744f,
+    0.881921264f,  0.471396737f,
+    0.903989293f,  0.427555093f,
+    0.923879533f,  0.382683432f,
+    0.941544065f,  0.336889853f,
+    0.956940336f,  0.290284677f,
+    0.970031253f,  0.242980180f,
+    0.980785280f,  0.195090322f,
+    0.989176510f,  0.146730474f,
+    0.995184727f,  0.098017140f,
+    0.998795456f,  0.049067674f,
+    1.000000000f,  0.000000000f,
+    0.998795456f, -0.049067674f,
+    0.995184727f, -0.098017140f,
+    0.989176510f, -0.146730474f,
+    0.980785280f, -0.195090322f,
+    0.970031253f, -0.242980180f,
+    0.956940336f, -0.290284677f,
+    0.941544065f, -0.336889853f,
+    0.923879533f, -0.382683432f,
+    0.903989293f, -0.427555093f,
+    0.881921264f, -0.471396737f,
+    0.857728610f, -0.514102744f,
+    0.831469612f, -0.555570233f,
+    0.803207531f, -0.595699304f,
+    0.773010453f, -0.634393284f,
+    0.740951125f, -0.671558955f,
+    0.707106781f, -0.707106781f,
+    0.671558955f, -0.740951125f,
+    0.634393284f, -0.773010453f,
+    0.595699304f, -0.803207531f,
+    0.555570233f, -0.831469612f,
+    0.514102744f, -0.857728610f,
+    0.471396737f, -0.881921264f,
+    0.427555093f, -0.903989293f,
+    0.382683432f, -0.923879533f,
+    0.336889853f, -0.941544065f,
+    0.290284677f, -0.956940336f,
+    0.242980180f, -0.970031253f,
+    0.195090322f, -0.980785280f,
+    0.146730474f, -0.989176510f,
+    0.098017140f, -0.995184727f,
+    0.049067674f, -0.998795456f
+};
+
+const float32_t twiddleCoef_rfft_256[256] = {
+    0.000000000f,  1.000000000f,
+    0.024541229f,  0.999698819f,
+    0.049067674f,  0.998795456f,
+    0.073564564f,  0.997290457f,
+    0.098017140f,  0.995184727f,
+    0.122410675f,  0.992479535f,
+    0.146730474f,  0.989176510f,
+    0.170961889f,  0.985277642f,
+    0.195090322f,  0.980785280f,
+    0.219101240f,  0.975702130f,
+    0.242980180f,  0.970031253f,
+    0.266712757f,  0.963776066f,
+    0.290284677f,  0.956940336f,
+    0.313681740f,  0.949528181f,
+    0.336889853f,  0.941544065f,
+    0.359895037f,  0.932992799f,
+    0.382683432f,  0.923879533f,
+    0.405241314f,  0.914209756f,
+    0.427555093f,  0.903989293f,
+    0.449611330f,  0.893224301f,
+    0.471396737f,  0.881921264f,
+    0.492898192f,  0.870086991f,
+    0.514102744f,  0.857728610f,
+    0.534997620f,  0.844853565f,
+    0.555570233f,  0.831469612f,
+    0.575808191f,  0.817584813f,
+    0.595699304f,  0.803207531f,
+    0.615231591f,  0.788346428f,
+    0.634393284f,  0.773010453f,
+    0.653172843f,  0.757208847f,
+    0.671558955f,  0.740951125f,
+    0.689540545f,  0.724247083f,
+    0.707106781f,  0.707106781f,
+    0.724247083f,  0.689540545f,
+    0.740951125f,  0.671558955f,
+    0.757208847f,  0.653172843f,
+    0.773010453f,  0.634393284f,
+    0.788346428f,  0.615231591f,
+    0.803207531f,  0.595699304f,
+    0.817584813f,  0.575808191f,
+    0.831469612f,  0.555570233f,
+    0.844853565f,  0.534997620f,
+    0.857728610f,  0.514102744f,
+    0.870086991f,  0.492898192f,
+    0.881921264f,  0.471396737f,
+    0.893224301f,  0.449611330f,
+    0.903989293f,  0.427555093f,
+    0.914209756f,  0.405241314f,
+    0.923879533f,  0.382683432f,
+    0.932992799f,  0.359895037f,
+    0.941544065f,  0.336889853f,
+    0.949528181f,  0.313681740f,
+    0.956940336f,  0.290284677f,
+    0.963776066f,  0.266712757f,
+    0.970031253f,  0.242980180f,
+    0.975702130f,  0.219101240f,
+    0.980785280f,  0.195090322f,
+    0.985277642f,  0.170961889f,
+    0.989176510f,  0.146730474f,
+    0.992479535f,  0.122410675f,
+    0.995184727f,  0.098017140f,
+    0.997290457f,  0.073564564f,
+    0.998795456f,  0.049067674f,
+    0.999698819f,  0.024541229f,
+    1.000000000f,  0.000000000f,
+    0.999698819f, -0.024541229f,
+    0.998795456f, -0.049067674f,
+    0.997290457f, -0.073564564f,
+    0.995184727f, -0.098017140f,
+    0.992479535f, -0.122410675f,
+    0.989176510f, -0.146730474f,
+    0.985277642f, -0.170961889f,
+    0.980785280f, -0.195090322f,
+    0.975702130f, -0.219101240f,
+    0.970031253f, -0.242980180f,
+    0.963776066f, -0.266712757f,
+    0.956940336f, -0.290284677f,
+    0.949528181f, -0.313681740f,
+    0.941544065f, -0.336889853f,
+    0.932992799f, -0.359895037f,
+    0.923879533f, -0.382683432f,
+    0.914209756f, -0.405241314f,
+    0.903989293f, -0.427555093f,
+    0.893224301f, -0.449611330f,
+    0.881921264f, -0.471396737f,
+    0.870086991f, -0.492898192f,
+    0.857728610f, -0.514102744f,
+    0.844853565f, -0.534997620f,
+    0.831469612f, -0.555570233f,
+    0.817584813f, -0.575808191f,
+    0.803207531f, -0.595699304f,
+    0.788346428f, -0.615231591f,
+    0.773010453f, -0.634393284f,
+    0.757208847f, -0.653172843f,
+    0.740951125f, -0.671558955f,
+    0.724247083f, -0.689540545f,
+    0.707106781f, -0.707106781f,
+    0.689540545f, -0.724247083f,
+    0.671558955f, -0.740951125f,
+    0.653172843f, -0.757208847f,
+    0.634393284f, -0.773010453f,
+    0.615231591f, -0.788346428f,
+    0.595699304f, -0.803207531f,
+    0.575808191f, -0.817584813f,
+    0.555570233f, -0.831469612f,
+    0.534997620f, -0.844853565f,
+    0.514102744f, -0.857728610f,
+    0.492898192f, -0.870086991f,
+    0.471396737f, -0.881921264f,
+    0.449611330f, -0.893224301f,
+    0.427555093f, -0.903989293f,
+    0.405241314f, -0.914209756f,
+    0.382683432f, -0.923879533f,
+    0.359895037f, -0.932992799f,
+    0.336889853f, -0.941544065f,
+    0.313681740f, -0.949528181f,
+    0.290284677f, -0.956940336f,
+    0.266712757f, -0.963776066f,
+    0.242980180f, -0.970031253f,
+    0.219101240f, -0.975702130f,
+    0.195090322f, -0.980785280f,
+    0.170961889f, -0.985277642f,
+    0.146730474f, -0.989176510f,
+    0.122410675f, -0.992479535f,
+    0.098017140f, -0.995184727f,
+    0.073564564f, -0.997290457f,
+    0.049067674f, -0.998795456f,
+    0.024541229f, -0.999698819f
+};
+
+const float32_t twiddleCoef_rfft_512[512] = {
+    0.000000000f,  1.000000000f,
+    0.012271538f,  0.999924702f,
+    0.024541229f,  0.999698819f,
+    0.036807223f,  0.999322385f,
+    0.049067674f,  0.998795456f,
+    0.061320736f,  0.998118113f,
+    0.073564564f,  0.997290457f,
+    0.085797312f,  0.996312612f,
+    0.098017140f,  0.995184727f,
+    0.110222207f,  0.993906970f,
+    0.122410675f,  0.992479535f,
+    0.134580709f,  0.990902635f,
+    0.146730474f,  0.989176510f,
+    0.158858143f,  0.987301418f,
+    0.170961889f,  0.985277642f,
+    0.183039888f,  0.983105487f,
+    0.195090322f,  0.980785280f,
+    0.207111376f,  0.978317371f,
+    0.219101240f,  0.975702130f,
+    0.231058108f,  0.972939952f,
+    0.242980180f,  0.970031253f,
+    0.254865660f,  0.966976471f,
+    0.266712757f,  0.963776066f,
+    0.278519689f,  0.960430519f,
+    0.290284677f,  0.956940336f,
+    0.302005949f,  0.953306040f,
+    0.313681740f,  0.949528181f,
+    0.325310292f,  0.945607325f,
+    0.336889853f,  0.941544065f,
+    0.348418680f,  0.937339012f,
+    0.359895037f,  0.932992799f,
+    0.371317194f,  0.928506080f,
+    0.382683432f,  0.923879533f,
+    0.393992040f,  0.919113852f,
+    0.405241314f,  0.914209756f,
+    0.416429560f,  0.909167983f,
+    0.427555093f,  0.903989293f,
+    0.438616239f,  0.898674466f,
+    0.449611330f,  0.893224301f,
+    0.460538711f,  0.887639620f,
+    0.471396737f,  0.881921264f,
+    0.482183772f,  0.876070094f,
+    0.492898192f,  0.870086991f,
+    0.503538384f,  0.863972856f,
+    0.514102744f,  0.857728610f,
+    0.524589683f,  0.851355193f,
+    0.534997620f,  0.844853565f,
+    0.545324988f,  0.838224706f,
+    0.555570233f,  0.831469612f,
+    0.565731811f,  0.824589303f,
+    0.575808191f,  0.817584813f,
+    0.585797857f,  0.810457198f,
+    0.595699304f,  0.803207531f,
+    0.605511041f,  0.795836905f,
+    0.615231591f,  0.788346428f,
+    0.624859488f,  0.780737229f,
+    0.634393284f,  0.773010453f,
+    0.643831543f,  0.765167266f,
+    0.653172843f,  0.757208847f,
+    0.662415778f,  0.749136395f,
+    0.671558955f,  0.740951125f,
+    0.680600998f,  0.732654272f,
+    0.689540545f,  0.724247083f,
+    0.698376249f,  0.715730825f,
+    0.707106781f,  0.707106781f,
+    0.715730825f,  0.698376249f,
+    0.724247083f,  0.689540545f,
+    0.732654272f,  0.680600998f,
+    0.740951125f,  0.671558955f,
+    0.749136395f,  0.662415778f,
+    0.757208847f,  0.653172843f,
+    0.765167266f,  0.643831543f,
+    0.773010453f,  0.634393284f,
+    0.780737229f,  0.624859488f,
+    0.788346428f,  0.615231591f,
+    0.795836905f,  0.605511041f,
+    0.803207531f,  0.595699304f,
+    0.810457198f,  0.585797857f,
+    0.817584813f,  0.575808191f,
+    0.824589303f,  0.565731811f,
+    0.831469612f,  0.555570233f,
+    0.838224706f,  0.545324988f,
+    0.844853565f,  0.534997620f,
+    0.851355193f,  0.524589683f,
+    0.857728610f,  0.514102744f,
+    0.863972856f,  0.503538384f,
+    0.870086991f,  0.492898192f,
+    0.876070094f,  0.482183772f,
+    0.881921264f,  0.471396737f,
+    0.887639620f,  0.460538711f,
+    0.893224301f,  0.449611330f,
+    0.898674466f,  0.438616239f,
+    0.903989293f,  0.427555093f,
+    0.909167983f,  0.416429560f,
+    0.914209756f,  0.405241314f,
+    0.919113852f,  0.393992040f,
+    0.923879533f,  0.382683432f,
+    0.928506080f,  0.371317194f,
+    0.932992799f,  0.359895037f,
+    0.937339012f,  0.348418680f,
+    0.941544065f,  0.336889853f,
+    0.945607325f,  0.325310292f,
+    0.949528181f,  0.313681740f,
+    0.953306040f,  0.302005949f,
+    0.956940336f,  0.290284677f,
+    0.960430519f,  0.278519689f,
+    0.963776066f,  0.266712757f,
+    0.966976471f,  0.254865660f,
+    0.970031253f,  0.242980180f,
+    0.972939952f,  0.231058108f,
+    0.975702130f,  0.219101240f,
+    0.978317371f,  0.207111376f,
+    0.980785280f,  0.195090322f,
+    0.983105487f,  0.183039888f,
+    0.985277642f,  0.170961889f,
+    0.987301418f,  0.158858143f,
+    0.989176510f,  0.146730474f,
+    0.990902635f,  0.134580709f,
+    0.992479535f,  0.122410675f,
+    0.993906970f,  0.110222207f,
+    0.995184727f,  0.098017140f,
+    0.996312612f,  0.085797312f,
+    0.997290457f,  0.073564564f,
+    0.998118113f,  0.061320736f,
+    0.998795456f,  0.049067674f,
+    0.999322385f,  0.036807223f,
+    0.999698819f,  0.024541229f,
+    0.999924702f,  0.012271538f,
+    1.000000000f,  0.000000000f,
+    0.999924702f, -0.012271538f,
+    0.999698819f, -0.024541229f,
+    0.999322385f, -0.036807223f,
+    0.998795456f, -0.049067674f,
+    0.998118113f, -0.061320736f,
+    0.997290457f, -0.073564564f,
+    0.996312612f, -0.085797312f,
+    0.995184727f, -0.098017140f,
+    0.993906970f, -0.110222207f,
+    0.992479535f, -0.122410675f,
+    0.990902635f, -0.134580709f,
+    0.989176510f, -0.146730474f,
+    0.987301418f, -0.158858143f,
+    0.985277642f, -0.170961889f,
+    0.983105487f, -0.183039888f,
+    0.980785280f, -0.195090322f,
+    0.978317371f, -0.207111376f,
+    0.975702130f, -0.219101240f,
+    0.972939952f, -0.231058108f,
+    0.970031253f, -0.242980180f,
+    0.966976471f, -0.254865660f,
+    0.963776066f, -0.266712757f,
+    0.960430519f, -0.278519689f,
+    0.956940336f, -0.290284677f,
+    0.953306040f, -0.302005949f,
+    0.949528181f, -0.313681740f,
+    0.945607325f, -0.325310292f,
+    0.941544065f, -0.336889853f,
+    0.937339012f, -0.348418680f,
+    0.932992799f, -0.359895037f,
+    0.928506080f, -0.371317194f,
+    0.923879533f, -0.382683432f,
+    0.919113852f, -0.393992040f,
+    0.914209756f, -0.405241314f,
+    0.909167983f, -0.416429560f,
+    0.903989293f, -0.427555093f,
+    0.898674466f, -0.438616239f,
+    0.893224301f, -0.449611330f,
+    0.887639620f, -0.460538711f,
+    0.881921264f, -0.471396737f,
+    0.876070094f, -0.482183772f,
+    0.870086991f, -0.492898192f,
+    0.863972856f, -0.503538384f,
+    0.857728610f, -0.514102744f,
+    0.851355193f, -0.524589683f,
+    0.844853565f, -0.534997620f,
+    0.838224706f, -0.545324988f,
+    0.831469612f, -0.555570233f,
+    0.824589303f, -0.565731811f,
+    0.817584813f, -0.575808191f,
+    0.810457198f, -0.585797857f,
+    0.803207531f, -0.595699304f,
+    0.795836905f, -0.605511041f,
+    0.788346428f, -0.615231591f,
+    0.780737229f, -0.624859488f,
+    0.773010453f, -0.634393284f,
+    0.765167266f, -0.643831543f,
+    0.757208847f, -0.653172843f,
+    0.749136395f, -0.662415778f,
+    0.740951125f, -0.671558955f,
+    0.732654272f, -0.680600998f,
+    0.724247083f, -0.689540545f,
+    0.715730825f, -0.698376249f,
+    0.707106781f, -0.707106781f,
+    0.698376249f, -0.715730825f,
+    0.689540545f, -0.724247083f,
+    0.680600998f, -0.732654272f,
+    0.671558955f, -0.740951125f,
+    0.662415778f, -0.749136395f,
+    0.653172843f, -0.757208847f,
+    0.643831543f, -0.765167266f,
+    0.634393284f, -0.773010453f,
+    0.624859488f, -0.780737229f,
+    0.615231591f, -0.788346428f,
+    0.605511041f, -0.795836905f,
+    0.595699304f, -0.803207531f,
+    0.585797857f, -0.810457198f,
+    0.575808191f, -0.817584813f,
+    0.565731811f, -0.824589303f,
+    0.555570233f, -0.831469612f,
+    0.545324988f, -0.838224706f,
+    0.534997620f, -0.844853565f,
+    0.524589683f, -0.851355193f,
+    0.514102744f, -0.857728610f,
+    0.503538384f, -0.863972856f,
+    0.492898192f, -0.870086991f,
+    0.482183772f, -0.876070094f,
+    0.471396737f, -0.881921264f,
+    0.460538711f, -0.887639620f,
+    0.449611330f, -0.893224301f,
+    0.438616239f, -0.898674466f,
+    0.427555093f, -0.903989293f,
+    0.416429560f, -0.909167983f,
+    0.405241314f, -0.914209756f,
+    0.393992040f, -0.919113852f,
+    0.382683432f, -0.923879533f,
+    0.371317194f, -0.928506080f,
+    0.359895037f, -0.932992799f,
+    0.348418680f, -0.937339012f,
+    0.336889853f, -0.941544065f,
+    0.325310292f, -0.945607325f,
+    0.313681740f, -0.949528181f,
+    0.302005949f, -0.953306040f,
+    0.290284677f, -0.956940336f,
+    0.278519689f, -0.960430519f,
+    0.266712757f, -0.963776066f,
+    0.254865660f, -0.966976471f,
+    0.242980180f, -0.970031253f,
+    0.231058108f, -0.972939952f,
+    0.219101240f, -0.975702130f,
+    0.207111376f, -0.978317371f,
+    0.195090322f, -0.980785280f,
+    0.183039888f, -0.983105487f,
+    0.170961889f, -0.985277642f,
+    0.158858143f, -0.987301418f,
+    0.146730474f, -0.989176510f,
+    0.134580709f, -0.990902635f,
+    0.122410675f, -0.992479535f,
+    0.110222207f, -0.993906970f,
+    0.098017140f, -0.995184727f,
+    0.085797312f, -0.996312612f,
+    0.073564564f, -0.997290457f,
+    0.061320736f, -0.998118113f,
+    0.049067674f, -0.998795456f,
+    0.036807223f, -0.999322385f,
+    0.024541229f, -0.999698819f,
+    0.012271538f, -0.999924702f
+};
+
+const float32_t twiddleCoef_rfft_1024[1024] = {
+    0.000000000f,  1.000000000f,
+    0.006135885f,  0.999981175f,
+    0.012271538f,  0.999924702f,
+    0.018406730f,  0.999830582f,
+    0.024541229f,  0.999698819f,
+    0.030674803f,  0.999529418f,
+    0.036807223f,  0.999322385f,
+    0.042938257f,  0.999077728f,
+    0.049067674f,  0.998795456f,
+    0.055195244f,  0.998475581f,
+    0.061320736f,  0.998118113f,
+    0.067443920f,  0.997723067f,
+    0.073564564f,  0.997290457f,
+    0.079682438f,  0.996820299f,
+    0.085797312f,  0.996312612f,
+    0.091908956f,  0.995767414f,
+    0.098017140f,  0.995184727f,
+    0.104121634f,  0.994564571f,
+    0.110222207f,  0.993906970f,
+    0.116318631f,  0.993211949f,
+    0.122410675f,  0.992479535f,
+    0.128498111f,  0.991709754f,
+    0.134580709f,  0.990902635f,
+    0.140658239f,  0.990058210f,
+    0.146730474f,  0.989176510f,
+    0.152797185f,  0.988257568f,
+    0.158858143f,  0.987301418f,
+    0.164913120f,  0.986308097f,
+    0.170961889f,  0.985277642f,
+    0.177004220f,  0.984210092f,
+    0.183039888f,  0.983105487f,
+    0.189068664f,  0.981963869f,
+    0.195090322f,  0.980785280f,
+    0.201104635f,  0.979569766f,
+    0.207111376f,  0.978317371f,
+    0.213110320f,  0.977028143f,
+    0.219101240f,  0.975702130f,
+    0.225083911f,  0.974339383f,
+    0.231058108f,  0.972939952f,
+    0.237023606f,  0.971503891f,
+    0.242980180f,  0.970031253f,
+    0.248927606f,  0.968522094f,
+    0.254865660f,  0.966976471f,
+    0.260794118f,  0.965394442f,
+    0.266712757f,  0.963776066f,
+    0.272621355f,  0.962121404f,
+    0.278519689f,  0.960430519f,
+    0.284407537f,  0.958703475f,
+    0.290284677f,  0.956940336f,
+    0.296150888f,  0.955141168f,
+    0.302005949f,  0.953306040f,
+    0.307849640f,  0.951435021f,
+    0.313681740f,  0.949528181f,
+    0.319502031f,  0.947585591f,
+    0.325310292f,  0.945607325f,
+    0.331106306f,  0.943593458f,
+    0.336889853f,  0.941544065f,
+    0.342660717f,  0.939459224f,
+    0.348418680f,  0.937339012f,
+    0.354163525f,  0.935183510f,
+    0.359895037f,  0.932992799f,
+    0.365612998f,  0.930766961f,
+    0.371317194f,  0.928506080f,
+    0.377007410f,  0.926210242f,
+    0.382683432f,  0.923879533f,
+    0.388345047f,  0.921514039f,
+    0.393992040f,  0.919113852f,
+    0.399624200f,  0.916679060f,
+    0.405241314f,  0.914209756f,
+    0.410843171f,  0.911706032f,
+    0.416429560f,  0.909167983f,
+    0.422000271f,  0.906595705f,
+    0.427555093f,  0.903989293f,
+    0.433093819f,  0.901348847f,
+    0.438616239f,  0.898674466f,
+    0.444122145f,  0.895966250f,
+    0.449611330f,  0.893224301f,
+    0.455083587f,  0.890448723f,
+    0.460538711f,  0.887639620f,
+    0.465976496f,  0.884797098f,
+    0.471396737f,  0.881921264f,
+    0.476799230f,  0.879012226f,
+    0.482183772f,  0.876070094f,
+    0.487550160f,  0.873094978f,
+    0.492898192f,  0.870086991f,
+    0.498227667f,  0.867046246f,
+    0.503538384f,  0.863972856f,
+    0.508830143f,  0.860866939f,
+    0.514102744f,  0.857728610f,
+    0.519355990f,  0.854557988f,
+    0.524589683f,  0.851355193f,
+    0.529803625f,  0.848120345f,
+    0.534997620f,  0.844853565f,
+    0.540171473f,  0.841554977f,
+    0.545324988f,  0.838224706f,
+    0.550457973f,  0.834862875f,
+    0.555570233f,  0.831469612f,
+    0.560661576f,  0.828045045f,
+    0.565731811f,  0.824589303f,
+    0.570780746f,  0.821102515f,
+    0.575808191f,  0.817584813f,
+    0.580813958f,  0.814036330f,
+    0.585797857f,  0.810457198f,
+    0.590759702f,  0.806847554f,
+    0.595699304f,  0.803207531f,
+    0.600616479f,  0.799537269f,
+    0.605511041f,  0.795836905f,
+    0.610382806f,  0.792106577f,
+    0.615231591f,  0.788346428f,
+    0.620057212f,  0.784556597f,
+    0.624859488f,  0.780737229f,
+    0.629638239f,  0.776888466f,
+    0.634393284f,  0.773010453f,
+    0.639124445f,  0.769103338f,
+    0.643831543f,  0.765167266f,
+    0.648514401f,  0.761202385f,
+    0.653172843f,  0.757208847f,
+    0.657806693f,  0.753186799f,
+    0.662415778f,  0.749136395f,
+    0.666999922f,  0.745057785f,
+    0.671558955f,  0.740951125f,
+    0.676092704f,  0.736816569f,
+    0.680600998f,  0.732654272f,
+    0.685083668f,  0.728464390f,
+    0.689540545f,  0.724247083f,
+    0.693971461f,  0.720002508f,
+    0.698376249f,  0.715730825f,
+    0.702754744f,  0.711432196f,
+    0.707106781f,  0.707106781f,
+    0.711432196f,  0.702754744f,
+    0.715730825f,  0.698376249f,
+    0.720002508f,  0.693971461f,
+    0.724247083f,  0.689540545f,
+    0.728464390f,  0.685083668f,
+    0.732654272f,  0.680600998f,
+    0.736816569f,  0.676092704f,
+    0.740951125f,  0.671558955f,
+    0.745057785f,  0.666999922f,
+    0.749136395f,  0.662415778f,
+    0.753186799f,  0.657806693f,
+    0.757208847f,  0.653172843f,
+    0.761202385f,  0.648514401f,
+    0.765167266f,  0.643831543f,
+    0.769103338f,  0.639124445f,
+    0.773010453f,  0.634393284f,
+    0.776888466f,  0.629638239f,
+    0.780737229f,  0.624859488f,
+    0.784556597f,  0.620057212f,
+    0.788346428f,  0.615231591f,
+    0.792106577f,  0.610382806f,
+    0.795836905f,  0.605511041f,
+    0.799537269f,  0.600616479f,
+    0.803207531f,  0.595699304f,
+    0.806847554f,  0.590759702f,
+    0.810457198f,  0.585797857f,
+    0.814036330f,  0.580813958f,
+    0.817584813f,  0.575808191f,
+    0.821102515f,  0.570780746f,
+    0.824589303f,  0.565731811f,
+    0.828045045f,  0.560661576f,
+    0.831469612f,  0.555570233f,
+    0.834862875f,  0.550457973f,
+    0.838224706f,  0.545324988f,
+    0.841554977f,  0.540171473f,
+    0.844853565f,  0.534997620f,
+    0.848120345f,  0.529803625f,
+    0.851355193f,  0.524589683f,
+    0.854557988f,  0.519355990f,
+    0.857728610f,  0.514102744f,
+    0.860866939f,  0.508830143f,
+    0.863972856f,  0.503538384f,
+    0.867046246f,  0.498227667f,
+    0.870086991f,  0.492898192f,
+    0.873094978f,  0.487550160f,
+    0.876070094f,  0.482183772f,
+    0.879012226f,  0.476799230f,
+    0.881921264f,  0.471396737f,
+    0.884797098f,  0.465976496f,
+    0.887639620f,  0.460538711f,
+    0.890448723f,  0.455083587f,
+    0.893224301f,  0.449611330f,
+    0.895966250f,  0.444122145f,
+    0.898674466f,  0.438616239f,
+    0.901348847f,  0.433093819f,
+    0.903989293f,  0.427555093f,
+    0.906595705f,  0.422000271f,
+    0.909167983f,  0.416429560f,
+    0.911706032f,  0.410843171f,
+    0.914209756f,  0.405241314f,
+    0.916679060f,  0.399624200f,
+    0.919113852f,  0.393992040f,
+    0.921514039f,  0.388345047f,
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+    0.926210242f,  0.377007410f,
+    0.928506080f,  0.371317194f,
+    0.930766961f,  0.365612998f,
+    0.932992799f,  0.359895037f,
+    0.935183510f,  0.354163525f,
+    0.937339012f,  0.348418680f,
+    0.939459224f,  0.342660717f,
+    0.941544065f,  0.336889853f,
+    0.943593458f,  0.331106306f,
+    0.945607325f,  0.325310292f,
+    0.947585591f,  0.319502031f,
+    0.949528181f,  0.313681740f,
+    0.951435021f,  0.307849640f,
+    0.953306040f,  0.302005949f,
+    0.955141168f,  0.296150888f,
+    0.956940336f,  0.290284677f,
+    0.958703475f,  0.284407537f,
+    0.960430519f,  0.278519689f,
+    0.962121404f,  0.272621355f,
+    0.963776066f,  0.266712757f,
+    0.965394442f,  0.260794118f,
+    0.966976471f,  0.254865660f,
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+    0.999322385f,  0.036807223f,
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+    0.795836905f, -0.605511041f,
+    0.792106577f, -0.610382806f,
+    0.788346428f, -0.615231591f,
+    0.784556597f, -0.620057212f,
+    0.780737229f, -0.624859488f,
+    0.776888466f, -0.629638239f,
+    0.773010453f, -0.634393284f,
+    0.769103338f, -0.639124445f,
+    0.765167266f, -0.643831543f,
+    0.761202385f, -0.648514401f,
+    0.757208847f, -0.653172843f,
+    0.753186799f, -0.657806693f,
+    0.749136395f, -0.662415778f,
+    0.745057785f, -0.666999922f,
+    0.740951125f, -0.671558955f,
+    0.736816569f, -0.676092704f,
+    0.732654272f, -0.680600998f,
+    0.728464390f, -0.685083668f,
+    0.724247083f, -0.689540545f,
+    0.720002508f, -0.693971461f,
+    0.715730825f, -0.698376249f,
+    0.711432196f, -0.702754744f,
+    0.707106781f, -0.707106781f,
+    0.702754744f, -0.711432196f,
+    0.698376249f, -0.715730825f,
+    0.693971461f, -0.720002508f,
+    0.689540545f, -0.724247083f,
+    0.685083668f, -0.728464390f,
+    0.680600998f, -0.732654272f,
+    0.676092704f, -0.736816569f,
+    0.671558955f, -0.740951125f,
+    0.666999922f, -0.745057785f,
+    0.662415778f, -0.749136395f,
+    0.657806693f, -0.753186799f,
+    0.653172843f, -0.757208847f,
+    0.648514401f, -0.761202385f,
+    0.643831543f, -0.765167266f,
+    0.639124445f, -0.769103338f,
+    0.634393284f, -0.773010453f,
+    0.629638239f, -0.776888466f,
+    0.624859488f, -0.780737229f,
+    0.620057212f, -0.784556597f,
+    0.615231591f, -0.788346428f,
+    0.610382806f, -0.792106577f,
+    0.605511041f, -0.795836905f,
+    0.600616479f, -0.799537269f,
+    0.595699304f, -0.803207531f,
+    0.590759702f, -0.806847554f,
+    0.585797857f, -0.810457198f,
+    0.580813958f, -0.814036330f,
+    0.575808191f, -0.817584813f,
+    0.570780746f, -0.821102515f,
+    0.565731811f, -0.824589303f,
+    0.560661576f, -0.828045045f,
+    0.555570233f, -0.831469612f,
+    0.550457973f, -0.834862875f,
+    0.545324988f, -0.838224706f,
+    0.540171473f, -0.841554977f,
+    0.534997620f, -0.844853565f,
+    0.529803625f, -0.848120345f,
+    0.524589683f, -0.851355193f,
+    0.519355990f, -0.854557988f,
+    0.514102744f, -0.857728610f,
+    0.508830143f, -0.860866939f,
+    0.503538384f, -0.863972856f,
+    0.498227667f, -0.867046246f,
+    0.492898192f, -0.870086991f,
+    0.487550160f, -0.873094978f,
+    0.482183772f, -0.876070094f,
+    0.476799230f, -0.879012226f,
+    0.471396737f, -0.881921264f,
+    0.465976496f, -0.884797098f,
+    0.460538711f, -0.887639620f,
+    0.455083587f, -0.890448723f,
+    0.449611330f, -0.893224301f,
+    0.444122145f, -0.895966250f,
+    0.438616239f, -0.898674466f,
+    0.433093819f, -0.901348847f,
+    0.427555093f, -0.903989293f,
+    0.422000271f, -0.906595705f,
+    0.416429560f, -0.909167983f,
+    0.410843171f, -0.911706032f,
+    0.405241314f, -0.914209756f,
+    0.399624200f, -0.916679060f,
+    0.393992040f, -0.919113852f,
+    0.388345047f, -0.921514039f,
+    0.382683432f, -0.923879533f,
+    0.377007410f, -0.926210242f,
+    0.371317194f, -0.928506080f,
+    0.365612998f, -0.930766961f,
+    0.359895037f, -0.932992799f,
+    0.354163525f, -0.935183510f,
+    0.348418680f, -0.937339012f,
+    0.342660717f, -0.939459224f,
+    0.336889853f, -0.941544065f,
+    0.331106306f, -0.943593458f,
+    0.325310292f, -0.945607325f,
+    0.319502031f, -0.947585591f,
+    0.313681740f, -0.949528181f,
+    0.307849640f, -0.951435021f,
+    0.302005949f, -0.953306040f,
+    0.296150888f, -0.955141168f,
+    0.290284677f, -0.956940336f,
+    0.284407537f, -0.958703475f,
+    0.278519689f, -0.960430519f,
+    0.272621355f, -0.962121404f,
+    0.266712757f, -0.963776066f,
+    0.260794118f, -0.965394442f,
+    0.254865660f, -0.966976471f,
+    0.248927606f, -0.968522094f,
+    0.242980180f, -0.970031253f,
+    0.237023606f, -0.971503891f,
+    0.231058108f, -0.972939952f,
+    0.225083911f, -0.974339383f,
+    0.219101240f, -0.975702130f,
+    0.213110320f, -0.977028143f,
+    0.207111376f, -0.978317371f,
+    0.201104635f, -0.979569766f,
+    0.195090322f, -0.980785280f,
+    0.189068664f, -0.981963869f,
+    0.183039888f, -0.983105487f,
+    0.177004220f, -0.984210092f,
+    0.170961889f, -0.985277642f,
+    0.164913120f, -0.986308097f,
+    0.158858143f, -0.987301418f,
+    0.152797185f, -0.988257568f,
+    0.146730474f, -0.989176510f,
+    0.140658239f, -0.990058210f,
+    0.134580709f, -0.990902635f,
+    0.128498111f, -0.991709754f,
+    0.122410675f, -0.992479535f,
+    0.116318631f, -0.993211949f,
+    0.110222207f, -0.993906970f,
+    0.104121634f, -0.994564571f,
+    0.098017140f, -0.995184727f,
+    0.091908956f, -0.995767414f,
+    0.085797312f, -0.996312612f,
+    0.079682438f, -0.996820299f,
+    0.073564564f, -0.997290457f,
+    0.067443920f, -0.997723067f,
+    0.061320736f, -0.998118113f,
+    0.055195244f, -0.998475581f,
+    0.049067674f, -0.998795456f,
+    0.042938257f, -0.999077728f,
+    0.036807223f, -0.999322385f,
+    0.030674803f, -0.999529418f,
+    0.024541229f, -0.999698819f,
+    0.018406730f, -0.999830582f,
+    0.012271538f, -0.999924702f,
+    0.006135885f, -0.999981175f
+};
+
+const float32_t twiddleCoef_rfft_2048[2048] = {
+    0.000000000f,  1.000000000f,
+    0.003067957f,  0.999995294f,
+    0.006135885f,  0.999981175f,
+    0.009203755f,  0.999957645f,
+    0.012271538f,  0.999924702f,
+    0.015339206f,  0.999882347f,
+    0.018406730f,  0.999830582f,
+    0.021474080f,  0.999769405f,
+    0.024541229f,  0.999698819f,
+    0.027608146f,  0.999618822f,
+    0.030674803f,  0.999529418f,
+    0.033741172f,  0.999430605f,
+    0.036807223f,  0.999322385f,
+    0.039872928f,  0.999204759f,
+    0.042938257f,  0.999077728f,
+    0.046003182f,  0.998941293f,
+    0.049067674f,  0.998795456f,
+    0.052131705f,  0.998640218f,
+    0.055195244f,  0.998475581f,
+    0.058258265f,  0.998301545f,
+    0.061320736f,  0.998118113f,
+    0.064382631f,  0.997925286f,
+    0.067443920f,  0.997723067f,
+    0.070504573f,  0.997511456f,
+    0.073564564f,  0.997290457f,
+    0.076623861f,  0.997060070f,
+    0.079682438f,  0.996820299f,
+    0.082740265f,  0.996571146f,
+    0.085797312f,  0.996312612f,
+    0.088853553f,  0.996044701f,
+    0.091908956f,  0.995767414f,
+    0.094963495f,  0.995480755f,
+    0.098017140f,  0.995184727f,
+    0.101069863f,  0.994879331f,
+    0.104121634f,  0.994564571f,
+    0.107172425f,  0.994240449f,
+    0.110222207f,  0.993906970f,
+    0.113270952f,  0.993564136f,
+    0.116318631f,  0.993211949f,
+    0.119365215f,  0.992850414f,
+    0.122410675f,  0.992479535f,
+    0.125454983f,  0.992099313f,
+    0.128498111f,  0.991709754f,
+    0.131540029f,  0.991310860f,
+    0.134580709f,  0.990902635f,
+    0.137620122f,  0.990485084f,
+    0.140658239f,  0.990058210f,
+    0.143695033f,  0.989622017f,
+    0.146730474f,  0.989176510f,
+    0.149764535f,  0.988721692f,
+    0.152797185f,  0.988257568f,
+    0.155828398f,  0.987784142f,
+    0.158858143f,  0.987301418f,
+    0.161886394f,  0.986809402f,
+    0.164913120f,  0.986308097f,
+    0.167938295f,  0.985797509f,
+    0.170961889f,  0.985277642f,
+    0.173983873f,  0.984748502f,
+    0.177004220f,  0.984210092f,
+    0.180022901f,  0.983662419f,
+    0.183039888f,  0.983105487f,
+    0.186055152f,  0.982539302f,
+    0.189068664f,  0.981963869f,
+    0.192080397f,  0.981379193f,
+    0.195090322f,  0.980785280f,
+    0.198098411f,  0.980182136f,
+    0.201104635f,  0.979569766f,
+    0.204108966f,  0.978948175f,
+    0.207111376f,  0.978317371f,
+    0.210111837f,  0.977677358f,
+    0.213110320f,  0.977028143f,
+    0.216106797f,  0.976369731f,
+    0.219101240f,  0.975702130f,
+    0.222093621f,  0.975025345f,
+    0.225083911f,  0.974339383f,
+    0.228072083f,  0.973644250f,
+    0.231058108f,  0.972939952f,
+    0.234041959f,  0.972226497f,
+    0.237023606f,  0.971503891f,
+    0.240003022f,  0.970772141f,
+    0.242980180f,  0.970031253f,
+    0.245955050f,  0.969281235f,
+    0.248927606f,  0.968522094f,
+    0.251897818f,  0.967753837f,
+    0.254865660f,  0.966976471f,
+    0.257831102f,  0.966190003f,
+    0.260794118f,  0.965394442f,
+    0.263754679f,  0.964589793f,
+    0.266712757f,  0.963776066f,
+    0.269668326f,  0.962953267f,
+    0.272621355f,  0.962121404f,
+    0.275571819f,  0.961280486f,
+    0.278519689f,  0.960430519f,
+    0.281464938f,  0.959571513f,
+    0.284407537f,  0.958703475f,
+    0.287347460f,  0.957826413f,
+    0.290284677f,  0.956940336f,
+    0.293219163f,  0.956045251f,
+    0.296150888f,  0.955141168f,
+    0.299079826f,  0.954228095f,
+    0.302005949f,  0.953306040f,
+    0.304929230f,  0.952375013f,
+    0.307849640f,  0.951435021f,
+    0.310767153f,  0.950486074f,
+    0.313681740f,  0.949528181f,
+    0.316593376f,  0.948561350f,
+    0.319502031f,  0.947585591f,
+    0.322407679f,  0.946600913f,
+    0.325310292f,  0.945607325f,
+    0.328209844f,  0.944604837f,
+    0.331106306f,  0.943593458f,
+    0.333999651f,  0.942573198f,
+    0.336889853f,  0.941544065f,
+    0.339776884f,  0.940506071f,
+    0.342660717f,  0.939459224f,
+    0.345541325f,  0.938403534f,
+    0.348418680f,  0.937339012f,
+    0.351292756f,  0.936265667f,
+    0.354163525f,  0.935183510f,
+    0.357030961f,  0.934092550f,
+    0.359895037f,  0.932992799f,
+    0.362755724f,  0.931884266f,
+    0.365612998f,  0.930766961f,
+    0.368466830f,  0.929640896f,
+    0.371317194f,  0.928506080f,
+    0.374164063f,  0.927362526f,
+    0.377007410f,  0.926210242f,
+    0.379847209f,  0.925049241f,
+    0.382683432f,  0.923879533f,
+    0.385516054f,  0.922701128f,
+    0.388345047f,  0.921514039f,
+    0.391170384f,  0.920318277f,
+    0.393992040f,  0.919113852f,
+    0.396809987f,  0.917900776f,
+    0.399624200f,  0.916679060f,
+    0.402434651f,  0.915448716f,
+    0.405241314f,  0.914209756f,
+    0.408044163f,  0.912962190f,
+    0.410843171f,  0.911706032f,
+    0.413638312f,  0.910441292f,
+    0.416429560f,  0.909167983f,
+    0.419216888f,  0.907886116f,
+    0.422000271f,  0.906595705f,
+    0.424779681f,  0.905296759f,
+    0.427555093f,  0.903989293f,
+    0.430326481f,  0.902673318f,
+    0.433093819f,  0.901348847f,
+    0.435857080f,  0.900015892f,
+    0.438616239f,  0.898674466f,
+    0.441371269f,  0.897324581f,
+    0.444122145f,  0.895966250f,
+    0.446868840f,  0.894599486f,
+    0.449611330f,  0.893224301f,
+    0.452349587f,  0.891840709f,
+    0.455083587f,  0.890448723f,
+    0.457813304f,  0.889048356f,
+    0.460538711f,  0.887639620f,
+    0.463259784f,  0.886222530f,
+    0.465976496f,  0.884797098f,
+    0.468688822f,  0.883363339f,
+    0.471396737f,  0.881921264f,
+    0.474100215f,  0.880470889f,
+    0.476799230f,  0.879012226f,
+    0.479493758f,  0.877545290f,
+    0.482183772f,  0.876070094f,
+    0.484869248f,  0.874586652f,
+    0.487550160f,  0.873094978f,
+    0.490226483f,  0.871595087f,
+    0.492898192f,  0.870086991f,
+    0.495565262f,  0.868570706f,
+    0.498227667f,  0.867046246f,
+    0.500885383f,  0.865513624f,
+    0.503538384f,  0.863972856f,
+    0.506186645f,  0.862423956f,
+    0.508830143f,  0.860866939f,
+    0.511468850f,  0.859301818f,
+    0.514102744f,  0.857728610f,
+    0.516731799f,  0.856147328f,
+    0.519355990f,  0.854557988f,
+    0.521975293f,  0.852960605f,
+    0.524589683f,  0.851355193f,
+    0.527199135f,  0.849741768f,
+    0.529803625f,  0.848120345f,
+    0.532403128f,  0.846490939f,
+    0.534997620f,  0.844853565f,
+    0.537587076f,  0.843208240f,
+    0.540171473f,  0.841554977f,
+    0.542750785f,  0.839893794f,
+    0.545324988f,  0.838224706f,
+    0.547894059f,  0.836547727f,
+    0.550457973f,  0.834862875f,
+    0.553016706f,  0.833170165f,
+    0.555570233f,  0.831469612f,
+    0.558118531f,  0.829761234f,
+    0.560661576f,  0.828045045f,
+    0.563199344f,  0.826321063f,
+    0.565731811f,  0.824589303f,
+    0.568258953f,  0.822849781f,
+    0.570780746f,  0.821102515f,
+    0.573297167f,  0.819347520f,
+    0.575808191f,  0.817584813f,
+    0.578313796f,  0.815814411f,
+    0.580813958f,  0.814036330f,
+    0.583308653f,  0.812250587f,
+    0.585797857f,  0.810457198f,
+    0.588281548f,  0.808656182f,
+    0.590759702f,  0.806847554f,
+    0.593232295f,  0.805031331f,
+    0.595699304f,  0.803207531f,
+    0.598160707f,  0.801376172f,
+    0.600616479f,  0.799537269f,
+    0.603066599f,  0.797690841f,
+    0.605511041f,  0.795836905f,
+    0.607949785f,  0.793975478f,
+    0.610382806f,  0.792106577f,
+    0.612810082f,  0.790230221f,
+    0.615231591f,  0.788346428f,
+    0.617647308f,  0.786455214f,
+    0.620057212f,  0.784556597f,
+    0.622461279f,  0.782650596f,
+    0.624859488f,  0.780737229f,
+    0.627251815f,  0.778816512f,
+    0.629638239f,  0.776888466f,
+    0.632018736f,  0.774953107f,
+    0.634393284f,  0.773010453f,
+    0.636761861f,  0.771060524f,
+    0.639124445f,  0.769103338f,
+    0.641481013f,  0.767138912f,
+    0.643831543f,  0.765167266f,
+    0.646176013f,  0.763188417f,
+    0.648514401f,  0.761202385f,
+    0.650846685f,  0.759209189f,
+    0.653172843f,  0.757208847f,
+    0.655492853f,  0.755201377f,
+    0.657806693f,  0.753186799f,
+    0.660114342f,  0.751165132f,
+    0.662415778f,  0.749136395f,
+    0.664710978f,  0.747100606f,
+    0.666999922f,  0.745057785f,
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+const float32_t twiddleCoef_rfft_4096[4096] = {
+    0.000000000f,  1.000000000f,
+    0.001533980f,  0.999998823f,
+    0.003067957f,  0.999995294f,
+    0.004601926f,  0.999989411f,
+    0.006135885f,  0.999981175f,
+    0.007669829f,  0.999970586f,
+    0.009203755f,  0.999957645f,
+    0.010737659f,  0.999942350f,
+    0.012271538f,  0.999924702f,
+    0.013805389f,  0.999904701f,
+    0.015339206f,  0.999882347f,
+    0.016872988f,  0.999857641f,
+    0.018406730f,  0.999830582f,
+    0.019940429f,  0.999801170f,
+    0.021474080f,  0.999769405f,
+    0.023007681f,  0.999735288f,
+    0.024541229f,  0.999698819f,
+    0.026074718f,  0.999659997f,
+    0.027608146f,  0.999618822f,
+    0.029141509f,  0.999575296f,
+    0.030674803f,  0.999529418f,
+    0.032208025f,  0.999481187f,
+    0.033741172f,  0.999430605f,
+    0.035274239f,  0.999377670f,
+    0.036807223f,  0.999322385f,
+    0.038340120f,  0.999264747f,
+    0.039872928f,  0.999204759f,
+    0.041405641f,  0.999142419f,
+    0.042938257f,  0.999077728f,
+    0.044470772f,  0.999010686f,
+    0.046003182f,  0.998941293f,
+    0.047535484f,  0.998869550f,
+    0.049067674f,  0.998795456f,
+    0.050599749f,  0.998719012f,
+    0.052131705f,  0.998640218f,
+    0.053663538f,  0.998559074f,
+    0.055195244f,  0.998475581f,
+    0.056726821f,  0.998389737f,
+    0.058258265f,  0.998301545f,
+    0.059789571f,  0.998211003f,
+    0.061320736f,  0.998118113f,
+    0.062851758f,  0.998022874f,
+    0.064382631f,  0.997925286f,
+    0.065913353f,  0.997825350f,
+    0.067443920f,  0.997723067f,
+    0.068974328f,  0.997618435f,
+    0.070504573f,  0.997511456f,
+    0.072034653f,  0.997402130f,
+    0.073564564f,  0.997290457f,
+    0.075094301f,  0.997176437f,
+    0.076623861f,  0.997060070f,
+    0.078153242f,  0.996941358f,
+    0.079682438f,  0.996820299f,
+    0.081211447f,  0.996696895f,
+    0.082740265f,  0.996571146f,
+    0.084268888f,  0.996443051f,
+    0.085797312f,  0.996312612f,
+    0.087325535f,  0.996179829f,
+    0.088853553f,  0.996044701f,
+    0.090381361f,  0.995907229f,
+    0.091908956f,  0.995767414f,
+    0.093436336f,  0.995625256f,
+    0.094963495f,  0.995480755f,
+    0.096490431f,  0.995333912f,
+    0.098017140f,  0.995184727f,
+    0.099543619f,  0.995033199f,
+    0.101069863f,  0.994879331f,
+    0.102595869f,  0.994723121f,
+    0.104121634f,  0.994564571f,
+    0.105647154f,  0.994403680f,
+    0.107172425f,  0.994240449f,
+    0.108697444f,  0.994074879f,
+    0.110222207f,  0.993906970f,
+    0.111746711f,  0.993736722f,
+    0.113270952f,  0.993564136f,
+    0.114794927f,  0.993389211f,
+    0.116318631f,  0.993211949f,
+    0.117842062f,  0.993032350f,
+    0.119365215f,  0.992850414f,
+    0.120888087f,  0.992666142f,
+    0.122410675f,  0.992479535f,
+    0.123932975f,  0.992290591f,
+    0.125454983f,  0.992099313f,
+    0.126976696f,  0.991905700f,
+    0.128498111f,  0.991709754f,
+    0.130019223f,  0.991511473f,
+    0.131540029f,  0.991310860f,
+    0.133060525f,  0.991107914f,
+    0.134580709f,  0.990902635f,
+    0.136100575f,  0.990695025f,
+    0.137620122f,  0.990485084f,
+    0.139139344f,  0.990272812f,
+    0.140658239f,  0.990058210f,
+    0.142176804f,  0.989841278f,
+    0.143695033f,  0.989622017f,
+    0.145212925f,  0.989400428f,
+    0.146730474f,  0.989176510f,
+    0.148247679f,  0.988950265f,
+    0.149764535f,  0.988721692f,
+    0.151281038f,  0.988490793f,
+    0.152797185f,  0.988257568f,
+    0.154312973f,  0.988022017f,
+    0.155828398f,  0.987784142f,
+    0.157343456f,  0.987543942f,
+    0.158858143f,  0.987301418f,
+    0.160372457f,  0.987056571f,
+    0.161886394f,  0.986809402f,
+    0.163399949f,  0.986559910f,
+    0.164913120f,  0.986308097f,
+    0.166425904f,  0.986053963f,
+    0.167938295f,  0.985797509f,
+    0.169450291f,  0.985538735f,
+    0.170961889f,  0.985277642f,
+    0.172473084f,  0.985014231f,
+    0.173983873f,  0.984748502f,
+    0.175494253f,  0.984480455f,
+    0.177004220f,  0.984210092f,
+    0.178513771f,  0.983937413f,
+    0.180022901f,  0.983662419f,
+    0.181531608f,  0.983385110f,
+    0.183039888f,  0.983105487f,
+    0.184547737f,  0.982823551f,
+    0.186055152f,  0.982539302f,
+    0.187562129f,  0.982252741f,
+    0.189068664f,  0.981963869f,
+    0.190574755f,  0.981672686f,
+    0.192080397f,  0.981379193f,
+    0.193585587f,  0.981083391f,
+    0.195090322f,  0.980785280f,
+    0.196594598f,  0.980484862f,
+    0.198098411f,  0.980182136f,
+    0.199601758f,  0.979877104f,
+    0.201104635f,  0.979569766f,
+    0.202607039f,  0.979260123f,
+    0.204108966f,  0.978948175f,
+    0.205610413f,  0.978633924f,
+    0.207111376f,  0.978317371f,
+    0.208611852f,  0.977998515f,
+    0.210111837f,  0.977677358f,
+    0.211611327f,  0.977353900f,
+    0.213110320f,  0.977028143f,
+    0.214608811f,  0.976700086f,
+    0.216106797f,  0.976369731f,
+    0.217604275f,  0.976037079f,
+    0.219101240f,  0.975702130f,
+    0.220597690f,  0.975364885f,
+    0.222093621f,  0.975025345f,
+    0.223589029f,  0.974683511f,
+    0.225083911f,  0.974339383f,
+    0.226578264f,  0.973992962f,
+    0.228072083f,  0.973644250f,
+    0.229565366f,  0.973293246f,
+    0.231058108f,  0.972939952f,
+    0.232550307f,  0.972584369f,
+    0.234041959f,  0.972226497f,
+    0.235533059f,  0.971866337f,
+    0.237023606f,  0.971503891f,
+    0.238513595f,  0.971139158f,
+    0.240003022f,  0.970772141f,
+    0.241491885f,  0.970402839f,
+    0.242980180f,  0.970031253f,
+    0.244467903f,  0.969657385f,
+    0.245955050f,  0.969281235f,
+    0.247441619f,  0.968902805f,
+    0.248927606f,  0.968522094f,
+    0.250413007f,  0.968139105f,
+    0.251897818f,  0.967753837f,
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+    0.256348682f,  0.966584374f,
+    0.257831102f,  0.966190003f,
+    0.259312915f,  0.965793359f,
+    0.260794118f,  0.965394442f,
+    0.262274707f,  0.964993253f,
+    0.263754679f,  0.964589793f,
+    0.265234030f,  0.964184064f,
+    0.266712757f,  0.963776066f,
+    0.268190857f,  0.963365800f,
+    0.269668326f,  0.962953267f,
+    0.271145160f,  0.962538468f,
+    0.272621355f,  0.962121404f,
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+    0.275571819f,  0.961280486f,
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+    0.279992643f,  0.960002146f,
+    0.281464938f,  0.959571513f,
+    0.282936570f,  0.959138622f,
+    0.284407537f,  0.958703475f,
+    0.285877835f,  0.958266071f,
+    0.287347460f,  0.957826413f,
+    0.288816408f,  0.957384501f,
+    0.290284677f,  0.956940336f,
+    0.291752263f,  0.956493919f,
+    0.293219163f,  0.956045251f,
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+    0.296150888f,  0.955141168f,
+    0.297615707f,  0.954685755f,
+    0.299079826f,  0.954228095f,
+    0.300543241f,  0.953768190f,
+    0.302005949f,  0.953306040f,
+    0.303467947f,  0.952841648f,
+    0.304929230f,  0.952375013f,
+    0.306389795f,  0.951906137f,
+    0.307849640f,  0.951435021f,
+    0.309308760f,  0.950961666f,
+    0.310767153f,  0.950486074f,
+    0.312224814f,  0.950008245f,
+    0.313681740f,  0.949528181f,
+    0.315137929f,  0.949045882f,
+    0.316593376f,  0.948561350f,
+    0.318048077f,  0.948074586f,
+    0.319502031f,  0.947585591f,
+    0.320955232f,  0.947094366f,
+    0.322407679f,  0.946600913f,
+    0.323859367f,  0.946105232f,
+    0.325310292f,  0.945607325f,
+    0.326760452f,  0.945107193f,
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+    0.338333767f,  0.941026175f,
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+    0.137620122f, -0.990485084f,
+    0.136100575f, -0.990695025f,
+    0.134580709f, -0.990902635f,
+    0.133060525f, -0.991107914f,
+    0.131540029f, -0.991310860f,
+    0.130019223f, -0.991511473f,
+    0.128498111f, -0.991709754f,
+    0.126976696f, -0.991905700f,
+    0.125454983f, -0.992099313f,
+    0.123932975f, -0.992290591f,
+    0.122410675f, -0.992479535f,
+    0.120888087f, -0.992666142f,
+    0.119365215f, -0.992850414f,
+    0.117842062f, -0.993032350f,
+    0.116318631f, -0.993211949f,
+    0.114794927f, -0.993389211f,
+    0.113270952f, -0.993564136f,
+    0.111746711f, -0.993736722f,
+    0.110222207f, -0.993906970f,
+    0.108697444f, -0.994074879f,
+    0.107172425f, -0.994240449f,
+    0.105647154f, -0.994403680f,
+    0.104121634f, -0.994564571f,
+    0.102595869f, -0.994723121f,
+    0.101069863f, -0.994879331f,
+    0.099543619f, -0.995033199f,
+    0.098017140f, -0.995184727f,
+    0.096490431f, -0.995333912f,
+    0.094963495f, -0.995480755f,
+    0.093436336f, -0.995625256f,
+    0.091908956f, -0.995767414f,
+    0.090381361f, -0.995907229f,
+    0.088853553f, -0.996044701f,
+    0.087325535f, -0.996179829f,
+    0.085797312f, -0.996312612f,
+    0.084268888f, -0.996443051f,
+    0.082740265f, -0.996571146f,
+    0.081211447f, -0.996696895f,
+    0.079682438f, -0.996820299f,
+    0.078153242f, -0.996941358f,
+    0.076623861f, -0.997060070f,
+    0.075094301f, -0.997176437f,
+    0.073564564f, -0.997290457f,
+    0.072034653f, -0.997402130f,
+    0.070504573f, -0.997511456f,
+    0.068974328f, -0.997618435f,
+    0.067443920f, -0.997723067f,
+    0.065913353f, -0.997825350f,
+    0.064382631f, -0.997925286f,
+    0.062851758f, -0.998022874f,
+    0.061320736f, -0.998118113f,
+    0.059789571f, -0.998211003f,
+    0.058258265f, -0.998301545f,
+    0.056726821f, -0.998389737f,
+    0.055195244f, -0.998475581f,
+    0.053663538f, -0.998559074f,
+    0.052131705f, -0.998640218f,
+    0.050599749f, -0.998719012f,
+    0.049067674f, -0.998795456f,
+    0.047535484f, -0.998869550f,
+    0.046003182f, -0.998941293f,
+    0.044470772f, -0.999010686f,
+    0.042938257f, -0.999077728f,
+    0.041405641f, -0.999142419f,
+    0.039872928f, -0.999204759f,
+    0.038340120f, -0.999264747f,
+    0.036807223f, -0.999322385f,
+    0.035274239f, -0.999377670f,
+    0.033741172f, -0.999430605f,
+    0.032208025f, -0.999481187f,
+    0.030674803f, -0.999529418f,
+    0.029141509f, -0.999575296f,
+    0.027608146f, -0.999618822f,
+    0.026074718f, -0.999659997f,
+    0.024541229f, -0.999698819f,
+    0.023007681f, -0.999735288f,
+    0.021474080f, -0.999769405f,
+    0.019940429f, -0.999801170f,
+    0.018406730f, -0.999830582f,
+    0.016872988f, -0.999857641f,
+    0.015339206f, -0.999882347f,
+    0.013805389f, -0.999904701f,
+    0.012271538f, -0.999924702f,
+    0.010737659f, -0.999942350f,
+    0.009203755f, -0.999957645f,
+    0.007669829f, -0.999970586f,
+    0.006135885f, -0.999981175f,
+    0.004601926f, -0.999989411f,
+    0.003067957f, -0.999995294f,
+    0.001533980f, -0.999998823f
+};
+
+
+/**
+ * \par
+ * Example code for the generation of the floating-point sine table:
+ * <pre>
+ * tableSize = 512;
+ * for(n = 0; n < (tableSize + 1); n++)
+ * {
+ *	sinTable[n]=sin(2*pi*n/tableSize);
+ * }</pre>
+ * \par
+ * where pi value is  3.14159265358979
+ */
+
+const float32_t sinTable_f32[FAST_MATH_TABLE_SIZE + 1] = {
+   0.00000000f, 0.01227154f, 0.02454123f, 0.03680722f, 0.04906767f, 0.06132074f,
+   0.07356456f, 0.08579731f, 0.09801714f, 0.11022221f, 0.12241068f, 0.13458071f,
+   0.14673047f, 0.15885814f, 0.17096189f, 0.18303989f, 0.19509032f, 0.20711138f,
+   0.21910124f, 0.23105811f, 0.24298018f, 0.25486566f, 0.26671276f, 0.27851969f,
+   0.29028468f, 0.30200595f, 0.31368174f, 0.32531029f, 0.33688985f, 0.34841868f,
+   0.35989504f, 0.37131719f, 0.38268343f, 0.39399204f, 0.40524131f, 0.41642956f,
+   0.42755509f, 0.43861624f, 0.44961133f, 0.46053871f, 0.47139674f, 0.48218377f,
+   0.49289819f, 0.50353838f, 0.51410274f, 0.52458968f, 0.53499762f, 0.54532499f,
+   0.55557023f, 0.56573181f, 0.57580819f, 0.58579786f, 0.59569930f, 0.60551104f,
+   0.61523159f, 0.62485949f, 0.63439328f, 0.64383154f, 0.65317284f, 0.66241578f,
+   0.67155895f, 0.68060100f, 0.68954054f, 0.69837625f, 0.70710678f, 0.71573083f,
+   0.72424708f, 0.73265427f, 0.74095113f, 0.74913639f, 0.75720885f, 0.76516727f,
+   0.77301045f, 0.78073723f, 0.78834643f, 0.79583690f, 0.80320753f, 0.81045720f,
+   0.81758481f, 0.82458930f, 0.83146961f, 0.83822471f, 0.84485357f, 0.85135519f,
+   0.85772861f, 0.86397286f, 0.87008699f, 0.87607009f, 0.88192126f, 0.88763962f,
+   0.89322430f, 0.89867447f, 0.90398929f, 0.90916798f, 0.91420976f, 0.91911385f,
+   0.92387953f, 0.92850608f, 0.93299280f, 0.93733901f, 0.94154407f, 0.94560733f,
+   0.94952818f, 0.95330604f, 0.95694034f, 0.96043052f, 0.96377607f, 0.96697647f,
+   0.97003125f, 0.97293995f, 0.97570213f, 0.97831737f, 0.98078528f, 0.98310549f,
+   0.98527764f, 0.98730142f, 0.98917651f, 0.99090264f, 0.99247953f, 0.99390697f,
+   0.99518473f, 0.99631261f, 0.99729046f, 0.99811811f, 0.99879546f, 0.99932238f,
+   0.99969882f, 0.99992470f, 1.00000000f, 0.99992470f, 0.99969882f, 0.99932238f,
+   0.99879546f, 0.99811811f, 0.99729046f, 0.99631261f, 0.99518473f, 0.99390697f,
+   0.99247953f, 0.99090264f, 0.98917651f, 0.98730142f, 0.98527764f, 0.98310549f,
+   0.98078528f, 0.97831737f, 0.97570213f, 0.97293995f, 0.97003125f, 0.96697647f,
+   0.96377607f, 0.96043052f, 0.95694034f, 0.95330604f, 0.94952818f, 0.94560733f,
+   0.94154407f, 0.93733901f, 0.93299280f, 0.92850608f, 0.92387953f, 0.91911385f,
+   0.91420976f, 0.90916798f, 0.90398929f, 0.89867447f, 0.89322430f, 0.88763962f,
+   0.88192126f, 0.87607009f, 0.87008699f, 0.86397286f, 0.85772861f, 0.85135519f,
+   0.84485357f, 0.83822471f, 0.83146961f, 0.82458930f, 0.81758481f, 0.81045720f,
+   0.80320753f, 0.79583690f, 0.78834643f, 0.78073723f, 0.77301045f, 0.76516727f,
+   0.75720885f, 0.74913639f, 0.74095113f, 0.73265427f, 0.72424708f, 0.71573083f,
+   0.70710678f, 0.69837625f, 0.68954054f, 0.68060100f, 0.67155895f, 0.66241578f,
+   0.65317284f, 0.64383154f, 0.63439328f, 0.62485949f, 0.61523159f, 0.60551104f,
+   0.59569930f, 0.58579786f, 0.57580819f, 0.56573181f, 0.55557023f, 0.54532499f,
+   0.53499762f, 0.52458968f, 0.51410274f, 0.50353838f, 0.49289819f, 0.48218377f,
+   0.47139674f, 0.46053871f, 0.44961133f, 0.43861624f, 0.42755509f, 0.41642956f,
+   0.40524131f, 0.39399204f, 0.38268343f, 0.37131719f, 0.35989504f, 0.34841868f,
+   0.33688985f, 0.32531029f, 0.31368174f, 0.30200595f, 0.29028468f, 0.27851969f,
+   0.26671276f, 0.25486566f, 0.24298018f, 0.23105811f, 0.21910124f, 0.20711138f,
+   0.19509032f, 0.18303989f, 0.17096189f, 0.15885814f, 0.14673047f, 0.13458071f,
+   0.12241068f, 0.11022221f, 0.09801714f, 0.08579731f, 0.07356456f, 0.06132074f,
+   0.04906767f, 0.03680722f, 0.02454123f, 0.01227154f, 0.00000000f, -0.01227154f,
+   -0.02454123f, -0.03680722f, -0.04906767f, -0.06132074f, -0.07356456f,
+   -0.08579731f, -0.09801714f, -0.11022221f, -0.12241068f, -0.13458071f,
+   -0.14673047f, -0.15885814f, -0.17096189f, -0.18303989f, -0.19509032f,
+   -0.20711138f, -0.21910124f, -0.23105811f, -0.24298018f, -0.25486566f,
+   -0.26671276f, -0.27851969f, -0.29028468f, -0.30200595f, -0.31368174f,
+   -0.32531029f, -0.33688985f, -0.34841868f, -0.35989504f, -0.37131719f,
+   -0.38268343f, -0.39399204f, -0.40524131f, -0.41642956f, -0.42755509f,
+   -0.43861624f, -0.44961133f, -0.46053871f, -0.47139674f, -0.48218377f,
+   -0.49289819f, -0.50353838f, -0.51410274f, -0.52458968f, -0.53499762f,
+   -0.54532499f, -0.55557023f, -0.56573181f, -0.57580819f, -0.58579786f,
+   -0.59569930f, -0.60551104f, -0.61523159f, -0.62485949f, -0.63439328f,
+   -0.64383154f, -0.65317284f, -0.66241578f, -0.67155895f, -0.68060100f,
+   -0.68954054f, -0.69837625f, -0.70710678f, -0.71573083f, -0.72424708f,
+   -0.73265427f, -0.74095113f, -0.74913639f, -0.75720885f, -0.76516727f,
+   -0.77301045f, -0.78073723f, -0.78834643f, -0.79583690f, -0.80320753f,
+   -0.81045720f, -0.81758481f, -0.82458930f, -0.83146961f, -0.83822471f,
+   -0.84485357f, -0.85135519f, -0.85772861f, -0.86397286f, -0.87008699f,
+   -0.87607009f, -0.88192126f, -0.88763962f, -0.89322430f, -0.89867447f,
+   -0.90398929f, -0.90916798f, -0.91420976f, -0.91911385f, -0.92387953f,
+   -0.92850608f, -0.93299280f, -0.93733901f, -0.94154407f, -0.94560733f,
+   -0.94952818f, -0.95330604f, -0.95694034f, -0.96043052f, -0.96377607f,
+   -0.96697647f, -0.97003125f, -0.97293995f, -0.97570213f, -0.97831737f,
+   -0.98078528f, -0.98310549f, -0.98527764f, -0.98730142f, -0.98917651f,
+   -0.99090264f, -0.99247953f, -0.99390697f, -0.99518473f, -0.99631261f,
+   -0.99729046f, -0.99811811f, -0.99879546f, -0.99932238f, -0.99969882f,
+   -0.99992470f, -1.00000000f, -0.99992470f, -0.99969882f, -0.99932238f,
+   -0.99879546f, -0.99811811f, -0.99729046f, -0.99631261f, -0.99518473f,
+   -0.99390697f, -0.99247953f, -0.99090264f, -0.98917651f, -0.98730142f,
+   -0.98527764f, -0.98310549f, -0.98078528f, -0.97831737f, -0.97570213f,
+   -0.97293995f, -0.97003125f, -0.96697647f, -0.96377607f, -0.96043052f,
+   -0.95694034f, -0.95330604f, -0.94952818f, -0.94560733f, -0.94154407f,
+   -0.93733901f, -0.93299280f, -0.92850608f, -0.92387953f, -0.91911385f,
+   -0.91420976f, -0.90916798f, -0.90398929f, -0.89867447f, -0.89322430f,
+   -0.88763962f, -0.88192126f, -0.87607009f, -0.87008699f, -0.86397286f,
+   -0.85772861f, -0.85135519f, -0.84485357f, -0.83822471f, -0.83146961f,
+   -0.82458930f, -0.81758481f, -0.81045720f, -0.80320753f, -0.79583690f,
+   -0.78834643f, -0.78073723f, -0.77301045f, -0.76516727f, -0.75720885f,
+   -0.74913639f, -0.74095113f, -0.73265427f, -0.72424708f, -0.71573083f,
+   -0.70710678f, -0.69837625f, -0.68954054f, -0.68060100f, -0.67155895f,
+   -0.66241578f, -0.65317284f, -0.64383154f, -0.63439328f, -0.62485949f,
+   -0.61523159f, -0.60551104f, -0.59569930f, -0.58579786f, -0.57580819f,
+   -0.56573181f, -0.55557023f, -0.54532499f, -0.53499762f, -0.52458968f,
+   -0.51410274f, -0.50353838f, -0.49289819f, -0.48218377f, -0.47139674f,
+   -0.46053871f, -0.44961133f, -0.43861624f, -0.42755509f, -0.41642956f,
+   -0.40524131f, -0.39399204f, -0.38268343f, -0.37131719f, -0.35989504f,
+   -0.34841868f, -0.33688985f, -0.32531029f, -0.31368174f, -0.30200595f,
+   -0.29028468f, -0.27851969f, -0.26671276f, -0.25486566f, -0.24298018f,
+   -0.23105811f, -0.21910124f, -0.20711138f, -0.19509032f, -0.18303989f,
+   -0.17096189f, -0.15885814f, -0.14673047f, -0.13458071f, -0.12241068f,
+   -0.11022221f, -0.09801714f, -0.08579731f, -0.07356456f, -0.06132074f,
+   -0.04906767f, -0.03680722f, -0.02454123f, -0.01227154f, -0.00000000f
+};
+
+/**
+ * \par
+ * Table values are in Q31 (1.31 fixed-point format) and generation is done in
+ * three steps.  First,  generate sin values in floating point:
+ * <pre>
+ * tableSize = 512;
+ * for(n = 0; n < (tableSize + 1); n++)
+ * {
+ *	sinTable[n]= sin(2*pi*n/tableSize);
+ * } </pre>
+ * where pi value is  3.14159265358979
+ * \par
+ * Second, convert floating-point to Q31 (Fixed point):
+ *	(sinTable[i] * pow(2, 31))
+ * \par
+ * Finally, round to the nearest integer value:
+ * 	sinTable[i] += (sinTable[i] > 0 ? 0.5 :-0.5);
+ */
+const q31_t sinTable_q31[FAST_MATH_TABLE_SIZE + 1] = {
+	0L, 26352928L, 52701887L, 79042909L, 105372028L, 131685278L, 157978697L,
+	184248325L, 210490206L, 236700388L, 262874923L, 289009871L, 315101295L,
+	341145265L, 367137861L, 393075166L, 418953276L, 444768294L, 470516330L,
+	496193509L, 521795963L, 547319836L, 572761285L, 598116479L, 623381598L,
+	648552838L, 673626408L, 698598533L, 723465451L, 748223418L, 772868706L,
+	797397602L, 821806413L, 846091463L, 870249095L, 894275671L, 918167572L,
+	941921200L, 965532978L, 988999351L, 1012316784L, 1035481766L, 1058490808L,
+	1081340445L, 1104027237L, 1126547765L, 1148898640L, 1171076495L, 1193077991L,
+	1214899813L, 1236538675L, 1257991320L, 1279254516L, 1300325060L, 1321199781L,
+	1341875533L, 1362349204L, 1382617710L, 1402678000L, 1422527051L, 1442161874L,
+	1461579514L, 1480777044L, 1499751576L, 1518500250L, 1537020244L, 1555308768L,
+	1573363068L, 1591180426L, 1608758157L, 1626093616L, 1643184191L, 1660027308L,
+	1676620432L, 1692961062L, 1709046739L, 1724875040L, 1740443581L, 1755750017L,
+	1770792044L, 1785567396L, 1800073849L, 1814309216L, 1828271356L, 1841958164L,
+	1855367581L, 1868497586L, 1881346202L, 1893911494L, 1906191570L, 1918184581L,
+	1929888720L, 1941302225L, 1952423377L, 1963250501L, 1973781967L, 1984016189L,
+	1993951625L, 2003586779L, 2012920201L, 2021950484L, 2030676269L, 2039096241L,
+	2047209133L, 2055013723L, 2062508835L, 2069693342L, 2076566160L, 2083126254L,
+	2089372638L, 2095304370L, 2100920556L, 2106220352L, 2111202959L, 2115867626L,
+	2120213651L, 2124240380L, 2127947206L, 2131333572L, 2134398966L, 2137142927L,
+	2139565043L, 2141664948L, 2143442326L, 2144896910L, 2146028480L, 2146836866L,
+	2147321946L, 2147483647L, 2147321946L, 2146836866L, 2146028480L, 2144896910L,
+	2143442326L, 2141664948L, 2139565043L, 2137142927L, 2134398966L, 2131333572L,
+	2127947206L, 2124240380L, 2120213651L, 2115867626L, 2111202959L, 2106220352L,
+	2100920556L, 2095304370L, 2089372638L, 2083126254L, 2076566160L, 2069693342L,
+	2062508835L, 2055013723L, 2047209133L, 2039096241L, 2030676269L, 2021950484L,
+	2012920201L, 2003586779L, 1993951625L, 1984016189L, 1973781967L, 1963250501L,
+	1952423377L, 1941302225L, 1929888720L, 1918184581L, 1906191570L, 1893911494L,
+	1881346202L, 1868497586L, 1855367581L, 1841958164L, 1828271356L, 1814309216L,
+	1800073849L, 1785567396L, 1770792044L, 1755750017L, 1740443581L, 1724875040L,
+	1709046739L, 1692961062L, 1676620432L, 1660027308L, 1643184191L, 1626093616L,
+	1608758157L, 1591180426L, 1573363068L, 1555308768L, 1537020244L, 1518500250L,
+	1499751576L, 1480777044L, 1461579514L, 1442161874L, 1422527051L, 1402678000L,
+	1382617710L, 1362349204L, 1341875533L, 1321199781L, 1300325060L, 1279254516L,
+	1257991320L, 1236538675L, 1214899813L, 1193077991L, 1171076495L, 1148898640L,
+	1126547765L, 1104027237L, 1081340445L, 1058490808L, 1035481766L, 1012316784L,
+	988999351L, 965532978L, 941921200L, 918167572L, 894275671L, 870249095L,
+	846091463L, 821806413L, 797397602L, 772868706L, 748223418L, 723465451L,
+	698598533L, 673626408L, 648552838L, 623381598L, 598116479L, 572761285L,
+	547319836L, 521795963L, 496193509L, 470516330L, 444768294L, 418953276L,
+	393075166L, 367137861L, 341145265L, 315101295L, 289009871L, 262874923L,
+	236700388L, 210490206L, 184248325L, 157978697L, 131685278L, 105372028L,
+	79042909L, 52701887L, 26352928L, 0L, -26352928L, -52701887L, -79042909L,
+	-105372028L, -131685278L, -157978697L, -184248325L, -210490206L, -236700388L,
+	-262874923L, -289009871L, -315101295L, -341145265L, -367137861L, -393075166L,
+	-418953276L, -444768294L, -470516330L, -496193509L, -521795963L, -547319836L,
+	-572761285L, -598116479L, -623381598L, -648552838L, -673626408L, -698598533L,
+	-723465451L, -748223418L, -772868706L, -797397602L, -821806413L, -846091463L,
+	-870249095L, -894275671L, -918167572L, -941921200L, -965532978L, -988999351L,
+	-1012316784L, -1035481766L, -1058490808L, -1081340445L, -1104027237L,
+	-1126547765L, -1148898640L, -1171076495L, -1193077991L, -1214899813L,
+	-1236538675L, -1257991320L, -1279254516L, -1300325060L, -1321199781L,
+	-1341875533L, -1362349204L, -1382617710L, -1402678000L, -1422527051L,
+	-1442161874L, -1461579514L, -1480777044L, -1499751576L, -1518500250L,
+	-1537020244L, -1555308768L, -1573363068L, -1591180426L, -1608758157L,
+	-1626093616L, -1643184191L, -1660027308L, -1676620432L, -1692961062L,
+	-1709046739L, -1724875040L, -1740443581L, -1755750017L, -1770792044L,
+	-1785567396L, -1800073849L, -1814309216L, -1828271356L, -1841958164L,
+	-1855367581L, -1868497586L, -1881346202L, -1893911494L, -1906191570L,
+	-1918184581L, -1929888720L, -1941302225L, -1952423377L, -1963250501L,
+	-1973781967L, -1984016189L, -1993951625L, -2003586779L, -2012920201L,
+	-2021950484L, -2030676269L, -2039096241L, -2047209133L, -2055013723L,
+	-2062508835L, -2069693342L, -2076566160L, -2083126254L, -2089372638L,
+	-2095304370L, -2100920556L, -2106220352L, -2111202959L, -2115867626L,
+	-2120213651L, -2124240380L, -2127947206L, -2131333572L, -2134398966L,
+	-2137142927L, -2139565043L, -2141664948L, -2143442326L, -2144896910L,
+	-2146028480L, -2146836866L, -2147321946L, (q31_t)0x80000000, -2147321946L,
+	-2146836866L, -2146028480L, -2144896910L, -2143442326L, -2141664948L,
+	-2139565043L, -2137142927L, -2134398966L, -2131333572L, -2127947206L,
+	-2124240380L, -2120213651L, -2115867626L, -2111202959L, -2106220352L,
+	-2100920556L, -2095304370L, -2089372638L, -2083126254L, -2076566160L,
+	-2069693342L, -2062508835L, -2055013723L, -2047209133L, -2039096241L,
+	-2030676269L, -2021950484L, -2012920201L, -2003586779L, -1993951625L,
+	-1984016189L, -1973781967L, -1963250501L, -1952423377L, -1941302225L,
+	-1929888720L, -1918184581L, -1906191570L, -1893911494L, -1881346202L,
+	-1868497586L, -1855367581L, -1841958164L, -1828271356L, -1814309216L,
+	-1800073849L, -1785567396L, -1770792044L, -1755750017L, -1740443581L,
+	-1724875040L, -1709046739L, -1692961062L, -1676620432L, -1660027308L,
+	-1643184191L, -1626093616L, -1608758157L, -1591180426L, -1573363068L,
+	-1555308768L, -1537020244L, -1518500250L, -1499751576L, -1480777044L,
+	-1461579514L, -1442161874L, -1422527051L, -1402678000L, -1382617710L,
+	-1362349204L, -1341875533L, -1321199781L, -1300325060L, -1279254516L,
+	-1257991320L, -1236538675L, -1214899813L, -1193077991L, -1171076495L,
+	-1148898640L, -1126547765L, -1104027237L, -1081340445L, -1058490808L,
+	-1035481766L, -1012316784L, -988999351L, -965532978L, -941921200L,
+	-918167572L, -894275671L, -870249095L, -846091463L, -821806413L, -797397602L,
+	-772868706L, -748223418L, -723465451L, -698598533L, -673626408L, -648552838L,
+	-623381598L, -598116479L, -572761285L, -547319836L, -521795963L, -496193509L,
+	-470516330L, -444768294L, -418953276L, -393075166L, -367137861L, -341145265L,
+	-315101295L, -289009871L, -262874923L, -236700388L, -210490206L, -184248325L,
+	-157978697L, -131685278L, -105372028L, -79042909L, -52701887L, -26352928L, 0
+};
+
+/**
+ * \par
+ * Table values are in Q15 (1.15 fixed-point format) and generation is done in
+ * three steps.  First,  generate sin values in floating point:
+ * <pre>
+ * tableSize = 512;
+ * for(n = 0; n < (tableSize + 1); n++)
+ * {
+ *	sinTable[n]= sin(2*pi*n/tableSize);
+ * } </pre>
+ * where pi value is  3.14159265358979
+ * \par
+ * Second, convert floating-point to Q15 (Fixed point):
+ *	(sinTable[i] * pow(2, 15))
+ * \par
+ * Finally, round to the nearest integer value:
+ * 	sinTable[i] += (sinTable[i] > 0 ? 0.5 :-0.5);
+ */
+const q15_t sinTable_q15[FAST_MATH_TABLE_SIZE + 1] = {
+	0, 402, 804, 1206, 1608, 2009, 2411, 2811, 3212, 3612, 4011, 4410, 4808,
+	5205, 5602, 5998, 6393, 6787, 7180, 7571, 7962, 8351, 8740, 9127, 9512,
+	9896, 10279, 10660, 11039, 11417, 11793, 12167, 12540, 12910, 13279,
+	13646, 14010, 14373, 14733, 15091, 15447, 15800, 16151, 16500, 16846,
+	17190, 17531, 17869, 18205, 18538, 18868, 19195, 19520, 19841, 20160,
+	20475, 20788, 21097, 21403, 21706, 22006, 22302, 22595, 22884, 23170,
+	23453, 23732, 24008, 24279, 24548, 24812, 25073, 25330, 25583, 25833,
+	26078, 26320, 26557, 26791, 27020, 27246, 27467, 27684, 27897, 28106,
+	28311, 28511, 28707, 28899, 29086, 29269, 29448, 29622, 29792, 29957,
+	30118, 30274, 30425, 30572, 30715, 30853, 30986, 31114, 31238, 31357,
+	31471, 31581, 31686, 31786, 31881, 31972, 32058, 32138, 32214, 32286,
+	32352, 32413, 32470, 32522, 32568, 32610, 32647, 32679, 32706, 32729,
+	32746, 32758, 32766, 32767, 32766, 32758, 32746, 32729, 32706, 32679,
+	32647, 32610, 32568, 32522, 32470, 32413, 32352, 32286, 32214, 32138,
+	32058, 31972, 31881, 31786, 31686, 31581, 31471, 31357, 31238, 31114,
+	30986, 30853, 30715, 30572, 30425, 30274, 30118, 29957, 29792, 29622,
+	29448, 29269, 29086, 28899, 28707, 28511, 28311, 28106, 27897, 27684,
+	27467, 27246, 27020, 26791, 26557, 26320, 26078, 25833, 25583, 25330,
+	25073, 24812, 24548, 24279, 24008, 23732, 23453, 23170, 22884, 22595,
+	22302, 22006, 21706, 21403, 21097, 20788, 20475, 20160, 19841, 19520,
+	19195, 18868, 18538, 18205, 17869, 17531, 17190, 16846, 16500, 16151,
+	15800, 15447, 15091, 14733, 14373, 14010, 13646, 13279, 12910, 12540,
+	12167, 11793, 11417, 11039, 10660, 10279, 9896, 9512, 9127, 8740, 8351,
+	7962, 7571, 7180, 6787, 6393, 5998, 5602, 5205, 4808, 4410, 4011, 3612,
+	3212, 2811, 2411, 2009, 1608, 1206, 804, 402, 0, -402, -804, -1206,
+	-1608, -2009, -2411, -2811, -3212, -3612, -4011, -4410, -4808, -5205,
+	-5602, -5998, -6393, -6787, -7180, -7571, -7962, -8351, -8740, -9127,
+	-9512, -9896, -10279, -10660, -11039, -11417, -11793, -12167, -12540,
+	-12910, -13279, -13646, -14010, -14373, -14733, -15091, -15447, -15800,
+	-16151, -16500, -16846, -17190, -17531, -17869, -18205, -18538, -18868,
+	-19195, -19520, -19841, -20160, -20475, -20788, -21097, -21403, -21706,
+	-22006, -22302, -22595, -22884, -23170, -23453, -23732, -24008, -24279,
+	-24548, -24812, -25073, -25330, -25583, -25833, -26078, -26320, -26557,
+	-26791, -27020, -27246, -27467, -27684, -27897, -28106, -28311, -28511,
+	-28707, -28899, -29086, -29269, -29448, -29622, -29792, -29957, -30118,
+	-30274, -30425, -30572, -30715, -30853, -30986, -31114, -31238, -31357,
+	-31471, -31581, -31686, -31786, -31881, -31972, -32058, -32138, -32214,
+	-32286, -32352, -32413, -32470, -32522, -32568, -32610, -32647, -32679,
+	-32706, -32729, -32746, -32758, -32766, -32768, -32766, -32758, -32746,
+	-32729, -32706, -32679, -32647, -32610, -32568, -32522, -32470, -32413,
+	-32352, -32286, -32214, -32138, -32058, -31972, -31881, -31786, -31686,
+	-31581, -31471, -31357, -31238, -31114, -30986, -30853, -30715, -30572,
+	-30425, -30274, -30118, -29957, -29792, -29622, -29448, -29269, -29086,
+	-28899, -28707, -28511, -28311, -28106, -27897, -27684, -27467, -27246,
+	-27020, -26791, -26557, -26320, -26078, -25833, -25583, -25330, -25073,
+	-24812, -24548, -24279, -24008, -23732, -23453, -23170, -22884, -22595,
+	-22302, -22006, -21706, -21403, -21097, -20788, -20475, -20160, -19841,
+	-19520, -19195, -18868, -18538, -18205, -17869, -17531, -17190, -16846,
+	-16500, -16151, -15800, -15447, -15091, -14733, -14373, -14010, -13646,
+	-13279, -12910, -12540, -12167, -11793, -11417, -11039, -10660, -10279,
+	-9896, -9512, -9127, -8740, -8351, -7962, -7571, -7180, -6787, -6393,
+	-5998, -5602, -5205, -4808, -4410, -4011, -3612, -3212, -2811, -2411,
+	-2009, -1608, -1206, -804, -402, 0
+};

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/CommonTables/arm_const_structs.c
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/CommonTables/arm_const_structs.c	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,379 @@
+/* ----------------------------------------------------------------------
+ * Project:      CMSIS DSP Library
+ * Title:        arm_const_structs.c
+ * Description:  Constant structs that are initialized for user convenience.
+ *               For example, some can be given as arguments to the arm_cfft_f32() or arm_rfft_f32() functions.
+ *
+ * $Date:        27. January 2017
+ * $Revision:    V.1.5.1
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+/*
+ * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "arm_const_structs.h"
+
+/* Floating-point structs */
+const arm_cfft_instance_f32 arm_cfft_sR_f32_len16 = {
+	16, twiddleCoef_16, armBitRevIndexTable16, ARMBITREVINDEXTABLE_16_TABLE_LENGTH
+};
+
+const arm_cfft_instance_f32 arm_cfft_sR_f32_len32 = {
+	32, twiddleCoef_32, armBitRevIndexTable32, ARMBITREVINDEXTABLE_32_TABLE_LENGTH
+};
+
+const arm_cfft_instance_f32 arm_cfft_sR_f32_len64 = {
+	64, twiddleCoef_64, armBitRevIndexTable64, ARMBITREVINDEXTABLE_64_TABLE_LENGTH
+};
+
+const arm_cfft_instance_f32 arm_cfft_sR_f32_len128 = {
+	128, twiddleCoef_128, armBitRevIndexTable128, ARMBITREVINDEXTABLE_128_TABLE_LENGTH
+};
+
+const arm_cfft_instance_f32 arm_cfft_sR_f32_len256 = {
+	256, twiddleCoef_256, armBitRevIndexTable256, ARMBITREVINDEXTABLE_256_TABLE_LENGTH
+};
+
+const arm_cfft_instance_f32 arm_cfft_sR_f32_len512 = {
+	512, twiddleCoef_512, armBitRevIndexTable512, ARMBITREVINDEXTABLE_512_TABLE_LENGTH
+};
+
+const arm_cfft_instance_f32 arm_cfft_sR_f32_len1024 = {
+	1024, twiddleCoef_1024, armBitRevIndexTable1024, ARMBITREVINDEXTABLE_1024_TABLE_LENGTH
+};
+
+const arm_cfft_instance_f32 arm_cfft_sR_f32_len2048 = {
+	2048, twiddleCoef_2048, armBitRevIndexTable2048, ARMBITREVINDEXTABLE_2048_TABLE_LENGTH
+};
+
+const arm_cfft_instance_f32 arm_cfft_sR_f32_len4096 = {
+	4096, twiddleCoef_4096, armBitRevIndexTable4096, ARMBITREVINDEXTABLE_4096_TABLE_LENGTH
+};
+
+/* Fixed-point structs */
+const arm_cfft_instance_q31 arm_cfft_sR_q31_len16 = {
+	16, twiddleCoef_16_q31, armBitRevIndexTable_fixed_16, ARMBITREVINDEXTABLE_FIXED_16_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q31 arm_cfft_sR_q31_len32 = {
+	32, twiddleCoef_32_q31, armBitRevIndexTable_fixed_32, ARMBITREVINDEXTABLE_FIXED_32_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q31 arm_cfft_sR_q31_len64 = {
+	64, twiddleCoef_64_q31, armBitRevIndexTable_fixed_64, ARMBITREVINDEXTABLE_FIXED_64_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q31 arm_cfft_sR_q31_len128 = {
+	128, twiddleCoef_128_q31, armBitRevIndexTable_fixed_128, ARMBITREVINDEXTABLE_FIXED_128_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q31 arm_cfft_sR_q31_len256 = {
+	256, twiddleCoef_256_q31, armBitRevIndexTable_fixed_256, ARMBITREVINDEXTABLE_FIXED_256_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q31 arm_cfft_sR_q31_len512 = {
+	512, twiddleCoef_512_q31, armBitRevIndexTable_fixed_512, ARMBITREVINDEXTABLE_FIXED_512_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q31 arm_cfft_sR_q31_len1024 = {
+	1024, twiddleCoef_1024_q31, armBitRevIndexTable_fixed_1024, ARMBITREVINDEXTABLE_FIXED_1024_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q31 arm_cfft_sR_q31_len2048 = {
+	2048, twiddleCoef_2048_q31, armBitRevIndexTable_fixed_2048, ARMBITREVINDEXTABLE_FIXED_2048_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q31 arm_cfft_sR_q31_len4096 = {
+	4096, twiddleCoef_4096_q31, armBitRevIndexTable_fixed_4096, ARMBITREVINDEXTABLE_FIXED_4096_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q15 arm_cfft_sR_q15_len16 = {
+	16, twiddleCoef_16_q15, armBitRevIndexTable_fixed_16, ARMBITREVINDEXTABLE_FIXED_16_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q15 arm_cfft_sR_q15_len32 = {
+	32, twiddleCoef_32_q15, armBitRevIndexTable_fixed_32, ARMBITREVINDEXTABLE_FIXED_32_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q15 arm_cfft_sR_q15_len64 = {
+	64, twiddleCoef_64_q15, armBitRevIndexTable_fixed_64, ARMBITREVINDEXTABLE_FIXED_64_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q15 arm_cfft_sR_q15_len128 = {
+	128, twiddleCoef_128_q15, armBitRevIndexTable_fixed_128, ARMBITREVINDEXTABLE_FIXED_128_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q15 arm_cfft_sR_q15_len256 = {
+	256, twiddleCoef_256_q15, armBitRevIndexTable_fixed_256, ARMBITREVINDEXTABLE_FIXED_256_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q15 arm_cfft_sR_q15_len512 = {
+	512, twiddleCoef_512_q15, armBitRevIndexTable_fixed_512, ARMBITREVINDEXTABLE_FIXED_512_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q15 arm_cfft_sR_q15_len1024 = {
+	1024, twiddleCoef_1024_q15, armBitRevIndexTable_fixed_1024, ARMBITREVINDEXTABLE_FIXED_1024_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q15 arm_cfft_sR_q15_len2048 = {
+	2048, twiddleCoef_2048_q15, armBitRevIndexTable_fixed_2048, ARMBITREVINDEXTABLE_FIXED_2048_TABLE_LENGTH
+};
+
+const arm_cfft_instance_q15 arm_cfft_sR_q15_len4096 = {
+	4096, twiddleCoef_4096_q15, armBitRevIndexTable_fixed_4096, ARMBITREVINDEXTABLE_FIXED_4096_TABLE_LENGTH
+};
+
+/* Structure for real-value inputs */
+/* Floating-point structs */
+const arm_rfft_fast_instance_f32 arm_rfft_fast_sR_f32_len32 = {
+	{ 16, twiddleCoef_32, armBitRevIndexTable32, ARMBITREVINDEXTABLE_16_TABLE_LENGTH },
+	32U,
+	(float32_t *)twiddleCoef_rfft_32
+};
+
+const arm_rfft_fast_instance_f32 arm_rfft_fast_sR_f32_len64 = {
+	 { 32, twiddleCoef_32, armBitRevIndexTable32, ARMBITREVINDEXTABLE_32_TABLE_LENGTH },
+	64U,
+	(float32_t *)twiddleCoef_rfft_64
+};
+
+const arm_rfft_fast_instance_f32 arm_rfft_fast_sR_f32_len128 = {
+	{ 64, twiddleCoef_64, armBitRevIndexTable64, ARMBITREVINDEXTABLE_64_TABLE_LENGTH },
+	128U,
+	(float32_t *)twiddleCoef_rfft_128
+};
+
+const arm_rfft_fast_instance_f32 arm_rfft_fast_sR_f32_len256 = {
+	{ 128, twiddleCoef_128, armBitRevIndexTable128, ARMBITREVINDEXTABLE_128_TABLE_LENGTH },
+	256U,
+	(float32_t *)twiddleCoef_rfft_256
+};
+
+const arm_rfft_fast_instance_f32 arm_rfft_fast_sR_f32_len512 = {
+	{ 256, twiddleCoef_256, armBitRevIndexTable256, ARMBITREVINDEXTABLE_256_TABLE_LENGTH },
+	512U,
+	(float32_t *)twiddleCoef_rfft_512
+};
+
+const arm_rfft_fast_instance_f32 arm_rfft_fast_sR_f32_len1024 = {
+	{ 512, twiddleCoef_512, armBitRevIndexTable512, ARMBITREVINDEXTABLE_512_TABLE_LENGTH },
+	1024U,
+	(float32_t *)twiddleCoef_rfft_1024
+};
+
+const arm_rfft_fast_instance_f32 arm_rfft_fast_sR_f32_len2048 = {
+	{ 1024, twiddleCoef_1024, armBitRevIndexTable1024, ARMBITREVINDEXTABLE_1024_TABLE_LENGTH },
+	2048U,
+	(float32_t *)twiddleCoef_rfft_2048
+};
+
+const arm_rfft_fast_instance_f32 arm_rfft_fast_sR_f32_len4096 = {
+	{ 2048, twiddleCoef_2048, armBitRevIndexTable2048, ARMBITREVINDEXTABLE_2048_TABLE_LENGTH },
+	4096U,
+	(float32_t *)twiddleCoef_rfft_4096
+};
+
+/* Fixed-point structs */
+/* q31_t */
+extern const q31_t realCoefAQ31[8192];
+extern const q31_t realCoefBQ31[8192];
+
+const arm_rfft_instance_q31 arm_rfft_sR_q31_len32 = {
+	32U,
+	0,
+	1,
+	256U,
+	(q31_t*)realCoefAQ31,
+	(q31_t*)realCoefBQ31,
+	&arm_cfft_sR_q31_len16
+};
+
+const arm_rfft_instance_q31 arm_rfft_sR_q31_len64 = {
+	64U,
+	0,
+	1,
+	128U,
+	(q31_t*)realCoefAQ31,
+	(q31_t*)realCoefBQ31,
+	&arm_cfft_sR_q31_len32
+};
+
+const arm_rfft_instance_q31 arm_rfft_sR_q31_len128 = {
+	128U,
+	0,
+	1,
+	64U,
+	(q31_t*)realCoefAQ31,
+	(q31_t*)realCoefBQ31,
+	&arm_cfft_sR_q31_len64
+};
+
+const arm_rfft_instance_q31 arm_rfft_sR_q31_len256 = {
+	256U,
+	0,
+	1,
+	32U,
+	(q31_t*)realCoefAQ31,
+	(q31_t*)realCoefBQ31,
+	&arm_cfft_sR_q31_len128
+};
+
+const arm_rfft_instance_q31 arm_rfft_sR_q31_len512 = {
+	512U,
+	0,
+	1,
+	16U,
+	(q31_t*)realCoefAQ31,
+	(q31_t*)realCoefBQ31,
+	&arm_cfft_sR_q31_len256
+};
+
+const arm_rfft_instance_q31 arm_rfft_sR_q31_len1024 = {
+	1024U,
+	0,
+	1,
+	8U,
+	(q31_t*)realCoefAQ31,
+	(q31_t*)realCoefBQ31,
+	&arm_cfft_sR_q31_len512
+};
+
+const arm_rfft_instance_q31 arm_rfft_sR_q31_len2048 = {
+	2048U,
+	0,
+	1,
+	4U,
+	(q31_t*)realCoefAQ31,
+	(q31_t*)realCoefBQ31,
+	&arm_cfft_sR_q31_len1024
+};
+
+const arm_rfft_instance_q31 arm_rfft_sR_q31_len4096 = {
+	4096U,
+	0,
+	1,
+	2U,
+	(q31_t*)realCoefAQ31,
+	(q31_t*)realCoefBQ31,
+	&arm_cfft_sR_q31_len2048
+};
+
+const arm_rfft_instance_q31 arm_rfft_sR_q31_len8192 = {
+	8192U,
+	0,
+	1,
+	1U,
+	(q31_t*)realCoefAQ31,
+	(q31_t*)realCoefBQ31,
+	&arm_cfft_sR_q31_len4096
+};
+
+/* q15_t */
+extern const q15_t realCoefAQ15[8192];
+extern const q15_t realCoefBQ15[8192];
+
+const arm_rfft_instance_q15 arm_rfft_sR_q15_len32 = {
+	32U,
+	0,
+	1,
+	256U,
+	(q15_t*)realCoefAQ15,
+	(q15_t*)realCoefBQ15,
+	&arm_cfft_sR_q15_len16
+};
+
+const arm_rfft_instance_q15 arm_rfft_sR_q15_len64 = {
+	64U,
+	0,
+	1,
+	128U,
+	(q15_t*)realCoefAQ15,
+	(q15_t*)realCoefBQ15,
+	&arm_cfft_sR_q15_len32
+};
+
+const arm_rfft_instance_q15 arm_rfft_sR_q15_len128 = {
+	128U,
+	0,
+	1,
+	64U,
+	(q15_t*)realCoefAQ15,
+	(q15_t*)realCoefBQ15,
+	&arm_cfft_sR_q15_len64
+};
+
+const arm_rfft_instance_q15 arm_rfft_sR_q15_len256 = {
+	256U,
+	0,
+	1,
+	32U,
+	(q15_t*)realCoefAQ15,
+	(q15_t*)realCoefBQ15,
+	&arm_cfft_sR_q15_len128
+};
+
+const arm_rfft_instance_q15 arm_rfft_sR_q15_len512 = {
+	512U,
+	0,
+	1,
+	16U,
+	(q15_t*)realCoefAQ15,
+	(q15_t*)realCoefBQ15,
+	&arm_cfft_sR_q15_len256
+};
+
+const arm_rfft_instance_q15 arm_rfft_sR_q15_len1024 = {
+	1024U,
+	0,
+	1,
+	8U,
+	(q15_t*)realCoefAQ15,
+	(q15_t*)realCoefBQ15,
+	&arm_cfft_sR_q15_len512
+};
+
+const arm_rfft_instance_q15 arm_rfft_sR_q15_len2048 = {
+	2048U,
+	0,
+	1,
+	4U,
+	(q15_t*)realCoefAQ15,
+	(q15_t*)realCoefBQ15,
+	&arm_cfft_sR_q15_len1024
+};
+
+const arm_rfft_instance_q15 arm_rfft_sR_q15_len4096 = {
+	4096U,
+	0,
+	1,
+	2U,
+	(q15_t*)realCoefAQ15,
+	(q15_t*)realCoefBQ15,
+	&arm_cfft_sR_q15_len2048
+};
+
+const arm_rfft_instance_q15 arm_rfft_sR_q15_len8192 = {
+	8192U,
+	0,
+	1,
+	1U,
+	(q15_t*)realCoefAQ15,
+	(q15_t*)realCoefBQ15,
+	&arm_cfft_sR_q15_len4096
+};

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/StatisticsFunctions/arm_max_q7.c
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/StatisticsFunctions/arm_max_q7.c	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,162 @@
+/* ----------------------------------------------------------------------
+ * Project:      CMSIS DSP Library
+ * Title:        arm_max_q7.c
+ * Description:  Maximum value of a Q7 vector
+ *
+ * $Date:        27. January 2017
+ * $Revision:    V.1.5.1
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+/*
+ * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "arm_math.h"
+
+/**
+ * @ingroup groupStats
+ */
+
+/**
+ * @addtogroup Max
+ * @{
+ */
+
+
+/**
+ * @brief Maximum value of a Q7 vector.
+ * @param[in]       *pSrc points to the input vector
+ * @param[in]       blockSize length of the input vector
+ * @param[out]      *pResult maximum value returned here
+ * @param[out]      *pIndex index of maximum value returned here
+ * @return none.
+ */
+
+void arm_max_q7(
+  q7_t * pSrc,
+  uint32_t blockSize,
+  q7_t * pResult,
+  uint32_t * pIndex)
+{
+#if defined (ARM_MATH_DSP)
+  /* Run the below code for Cortex-M4 and Cortex-M3 */
+
+  q7_t maxVal1, maxVal2, out;                    /* Temporary variables to store the output value. */
+  uint32_t blkCnt, outIndex, count;              /* loop counter */
+
+  /* Initialise the count value. */
+  count = 0U;
+  /* Initialise the index value to zero. */
+  outIndex = 0U;
+  /* Load first input value that act as reference value for comparision */
+  out = *pSrc++;
+
+  /* Loop unrolling */
+  blkCnt = (blockSize - 1U) >> 2U;
+
+  while (blkCnt > 0U)
+  {
+    /* Initialize maxVal to the next consecutive values one by one */
+    maxVal1 = *pSrc++;
+    maxVal2 = *pSrc++;
+
+    /* compare for the maximum value */
+    if (out < maxVal1)
+    {
+      /* Update the maximum value and its index */
+      out = maxVal1;
+      outIndex = count + 1U;
+    }
+
+    /* compare for the maximum value */
+    if (out < maxVal2)
+    {
+      /* Update the maximum value and its index */
+      out = maxVal2;
+      outIndex = count + 2U;
+    }
+
+    /* Initialize maxVal to the next consecutive values one by one */
+    maxVal1 = *pSrc++;
+    maxVal2 = *pSrc++;
+
+    /* compare for the maximum value */
+    if (out < maxVal1)
+    {
+      /* Update the maximum value and its index */
+      out = maxVal1;
+      outIndex = count + 3U;
+    }
+
+    /* compare for the maximum value */
+    if (out < maxVal2)
+    {
+      /* Update the maximum value and its index */
+      out = maxVal2;
+      outIndex = count + 4U;
+    }
+
+    count += 4U;
+
+    /* Decrement the loop counter */
+    blkCnt--;
+  }
+
+  /* if (blockSize - 1U) is not multiple of 4 */
+  blkCnt = (blockSize - 1U) % 4U;
+
+#else
+  /* Run the below code for Cortex-M0 */
+
+  q7_t maxVal1, out;                             /* Temporary variables to store the output value. */
+  uint32_t blkCnt, outIndex;                     /* loop counter */
+
+  /* Initialise the index value to zero. */
+  outIndex = 0U;
+  /* Load first input value that act as reference value for comparision */
+  out = *pSrc++;
+
+  blkCnt = (blockSize - 1U);
+
+#endif /* #if defined (ARM_MATH_DSP) */
+
+  while (blkCnt > 0U)
+  {
+    /* Initialize maxVal to the next consecutive values one by one */
+    maxVal1 = *pSrc++;
+
+    /* compare for the maximum value */
+    if (out < maxVal1)
+    {
+      /* Update the maximum value and it's index */
+      out = maxVal1;
+      outIndex = blockSize - blkCnt;
+    }
+
+    /* Decrement the loop counter */
+    blkCnt--;
+  }
+
+  /* Store the maximum value and it's index into destination pointers */
+  *pResult = out;
+  *pIndex = outIndex;
+}
+
+/**
+ * @} end of Max group
+ */

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/StatisticsFunctions/arm_mean_q15.c
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/StatisticsFunctions/arm_mean_q15.c	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,120 @@
+/* ----------------------------------------------------------------------
+ * Project:      CMSIS DSP Library
+ * Title:        arm_mean_q15.c
+ * Description:  Mean value of a Q15 vector
+ *
+ * $Date:        27. January 2017
+ * $Revision:    V.1.5.1
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+/*
+ * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "arm_math.h"
+
+/**
+ * @ingroup groupStats
+ */
+
+/**
+ * @addtogroup mean
+ * @{
+ */
+
+
+/**
+ * @brief Mean value of a Q15 vector.
+ * @param[in]       *pSrc points to the input vector
+ * @param[in]       blockSize length of the input vector
+ * @param[out]      *pResult mean value returned here
+ * @return none.
+ *
+ * @details
+ * <b>Scaling and Overflow Behavior:</b>
+ * \par
+ * The function is implemented using a 32-bit internal accumulator.
+ * The input is represented in 1.15 format and is accumulated in a 32-bit
+ * accumulator in 17.15 format.
+ * There is no risk of internal overflow with this approach, and the
+ * full precision of intermediate result is preserved.
+ * Finally, the accumulator is saturated and truncated to yield a result of 1.15 format.
+ *
+ */
+
+void arm_mean_q15(
+  q15_t * pSrc,
+  uint32_t blockSize,
+  q15_t * pResult)
+{
+  q31_t sum = 0;                                 /* Temporary result storage */
+  uint32_t blkCnt;                               /* loop counter */
+
+#if defined (ARM_MATH_DSP)
+  /* Run the below code for Cortex-M4 and Cortex-M3 */
+
+  q31_t in;
+
+  /*loop Unrolling */
+  blkCnt = blockSize >> 2U;
+
+  /* First part of the processing with loop unrolling.  Compute 4 outputs at a time.
+   ** a second loop below computes the remaining 1 to 3 samples. */
+  while (blkCnt > 0U)
+  {
+    /* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) */
+    in = *__SIMD32(pSrc)++;
+    sum += ((in << 16U) >> 16U);
+    sum +=  (in >> 16U);
+    in = *__SIMD32(pSrc)++;
+    sum += ((in << 16U) >> 16U);
+    sum +=  (in >> 16U);
+
+    /* Decrement the loop counter */
+    blkCnt--;
+  }
+
+  /* If the blockSize is not a multiple of 4, compute any remaining output samples here.
+   ** No loop unrolling is used. */
+  blkCnt = blockSize % 0x4U;
+
+#else
+  /* Run the below code for Cortex-M0 */
+
+  /* Loop over blockSize number of values */
+  blkCnt = blockSize;
+
+#endif /* #if defined (ARM_MATH_DSP) */
+
+  while (blkCnt > 0U)
+  {
+    /* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) */
+    sum += *pSrc++;
+
+    /* Decrement the loop counter */
+    blkCnt--;
+  }
+
+  /* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) / blockSize  */
+  /* Store the result to the destination */
+  *pResult = (q15_t) (sum / (q31_t)blockSize);
+}
+
+/**
+ * @} end of mean group
+ */

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/TransformFunctions/arm_bitreversal.c
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/TransformFunctions/arm_bitreversal.c	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,230 @@
+/* ----------------------------------------------------------------------
+ * Project:      CMSIS DSP Library
+ * Title:        arm_bitreversal.c
+ * Description:  Bitreversal functions
+ *
+ * $Date:        27. January 2017
+ * $Revision:    V.1.5.1
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+/*
+ * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "arm_math.h"
+#include "arm_common_tables.h"
+
+/*
+* @brief  In-place bit reversal function.
+* @param[in, out] *pSrc        points to the in-place buffer of floating-point data type.
+* @param[in]      fftSize      length of the FFT.
+* @param[in]      bitRevFactor bit reversal modifier that supports different size FFTs with the same bit reversal table.
+* @param[in]      *pBitRevTab  points to the bit reversal table.
+* @return none.
+*/
+
+void arm_bitreversal_f32(
+float32_t * pSrc,
+uint16_t fftSize,
+uint16_t bitRevFactor,
+uint16_t * pBitRevTab)
+{
+   uint16_t fftLenBy2, fftLenBy2p1;
+   uint16_t i, j;
+   float32_t in;
+
+   /*  Initializations */
+   j = 0U;
+   fftLenBy2 = fftSize >> 1U;
+   fftLenBy2p1 = (fftSize >> 1U) + 1U;
+
+   /* Bit Reversal Implementation */
+   for (i = 0U; i <= (fftLenBy2 - 2U); i += 2U)
+   {
+      if (i < j)
+      {
+         /*  pSrc[i] <-> pSrc[j]; */
+         in = pSrc[2U * i];
+         pSrc[2U * i] = pSrc[2U * j];
+         pSrc[2U * j] = in;
+
+         /*  pSrc[i+1U] <-> pSrc[j+1U] */
+         in = pSrc[(2U * i) + 1U];
+         pSrc[(2U * i) + 1U] = pSrc[(2U * j) + 1U];
+         pSrc[(2U * j) + 1U] = in;
+
+         /*  pSrc[i+fftLenBy2p1] <-> pSrc[j+fftLenBy2p1] */
+         in = pSrc[2U * (i + fftLenBy2p1)];
+         pSrc[2U * (i + fftLenBy2p1)] = pSrc[2U * (j + fftLenBy2p1)];
+         pSrc[2U * (j + fftLenBy2p1)] = in;
+
+         /*  pSrc[i+fftLenBy2p1+1U] <-> pSrc[j+fftLenBy2p1+1U] */
+         in = pSrc[(2U * (i + fftLenBy2p1)) + 1U];
+         pSrc[(2U * (i + fftLenBy2p1)) + 1U] =
+         pSrc[(2U * (j + fftLenBy2p1)) + 1U];
+         pSrc[(2U * (j + fftLenBy2p1)) + 1U] = in;
+
+      }
+
+      /*  pSrc[i+1U] <-> pSrc[j+1U] */
+      in = pSrc[2U * (i + 1U)];
+      pSrc[2U * (i + 1U)] = pSrc[2U * (j + fftLenBy2)];
+      pSrc[2U * (j + fftLenBy2)] = in;
+
+      /*  pSrc[i+2U] <-> pSrc[j+2U] */
+      in = pSrc[(2U * (i + 1U)) + 1U];
+      pSrc[(2U * (i + 1U)) + 1U] = pSrc[(2U * (j + fftLenBy2)) + 1U];
+      pSrc[(2U * (j + fftLenBy2)) + 1U] = in;
+
+      /*  Reading the index for the bit reversal */
+      j = *pBitRevTab;
+
+      /*  Updating the bit reversal index depending on the fft length  */
+      pBitRevTab += bitRevFactor;
+   }
+}
+
+
+
+/*
+* @brief  In-place bit reversal function.
+* @param[in, out] *pSrc        points to the in-place buffer of Q31 data type.
+* @param[in]      fftLen       length of the FFT.
+* @param[in]      bitRevFactor bit reversal modifier that supports different size FFTs with the same bit reversal table
+* @param[in]      *pBitRevTab  points to bit reversal table.
+* @return none.
+*/
+
+void arm_bitreversal_q31(
+q31_t * pSrc,
+uint32_t fftLen,
+uint16_t bitRevFactor,
+uint16_t * pBitRevTable)
+{
+   uint32_t fftLenBy2, fftLenBy2p1, i, j;
+   q31_t in;
+
+   /*  Initializations      */
+   j = 0U;
+   fftLenBy2 = fftLen / 2U;
+   fftLenBy2p1 = (fftLen / 2U) + 1U;
+
+   /* Bit Reversal Implementation */
+   for (i = 0U; i <= (fftLenBy2 - 2U); i += 2U)
+   {
+      if (i < j)
+      {
+         /*  pSrc[i] <-> pSrc[j]; */
+         in = pSrc[2U * i];
+         pSrc[2U * i] = pSrc[2U * j];
+         pSrc[2U * j] = in;
+
+         /*  pSrc[i+1U] <-> pSrc[j+1U] */
+         in = pSrc[(2U * i) + 1U];
+         pSrc[(2U * i) + 1U] = pSrc[(2U * j) + 1U];
+         pSrc[(2U * j) + 1U] = in;
+
+         /*  pSrc[i+fftLenBy2p1] <-> pSrc[j+fftLenBy2p1] */
+         in = pSrc[2U * (i + fftLenBy2p1)];
+         pSrc[2U * (i + fftLenBy2p1)] = pSrc[2U * (j + fftLenBy2p1)];
+         pSrc[2U * (j + fftLenBy2p1)] = in;
+
+         /*  pSrc[i+fftLenBy2p1+1U] <-> pSrc[j+fftLenBy2p1+1U] */
+         in = pSrc[(2U * (i + fftLenBy2p1)) + 1U];
+         pSrc[(2U * (i + fftLenBy2p1)) + 1U] =
+         pSrc[(2U * (j + fftLenBy2p1)) + 1U];
+         pSrc[(2U * (j + fftLenBy2p1)) + 1U] = in;
+
+      }
+
+      /*  pSrc[i+1U] <-> pSrc[j+1U] */
+      in = pSrc[2U * (i + 1U)];
+      pSrc[2U * (i + 1U)] = pSrc[2U * (j + fftLenBy2)];
+      pSrc[2U * (j + fftLenBy2)] = in;
+
+      /*  pSrc[i+2U] <-> pSrc[j+2U] */
+      in = pSrc[(2U * (i + 1U)) + 1U];
+      pSrc[(2U * (i + 1U)) + 1U] = pSrc[(2U * (j + fftLenBy2)) + 1U];
+      pSrc[(2U * (j + fftLenBy2)) + 1U] = in;
+
+      /*  Reading the index for the bit reversal */
+      j = *pBitRevTable;
+
+      /*  Updating the bit reversal index depending on the fft length */
+      pBitRevTable += bitRevFactor;
+   }
+}
+
+
+
+/*
+   * @brief  In-place bit reversal function.
+   * @param[in, out] *pSrc        points to the in-place buffer of Q15 data type.
+   * @param[in]      fftLen       length of the FFT.
+   * @param[in]      bitRevFactor bit reversal modifier that supports different size FFTs with the same bit reversal table
+   * @param[in]      *pBitRevTab  points to bit reversal table.
+   * @return none.
+*/
+
+void arm_bitreversal_q15(
+q15_t * pSrc16,
+uint32_t fftLen,
+uint16_t bitRevFactor,
+uint16_t * pBitRevTab)
+{
+   q31_t *pSrc = (q31_t *) pSrc16;
+   q31_t in;
+   uint32_t fftLenBy2, fftLenBy2p1;
+   uint32_t i, j;
+
+   /*  Initializations */
+   j = 0U;
+   fftLenBy2 = fftLen / 2U;
+   fftLenBy2p1 = (fftLen / 2U) + 1U;
+
+   /* Bit Reversal Implementation */
+   for (i = 0U; i <= (fftLenBy2 - 2U); i += 2U)
+   {
+      if (i < j)
+      {
+         /*  pSrc[i] <-> pSrc[j]; */
+         /*  pSrc[i+1U] <-> pSrc[j+1U] */
+         in = pSrc[i];
+         pSrc[i] = pSrc[j];
+         pSrc[j] = in;
+
+         /*  pSrc[i + fftLenBy2p1] <-> pSrc[j + fftLenBy2p1];  */
+         /*  pSrc[i + fftLenBy2p1+1U] <-> pSrc[j + fftLenBy2p1+1U] */
+         in = pSrc[i + fftLenBy2p1];
+         pSrc[i + fftLenBy2p1] = pSrc[j + fftLenBy2p1];
+         pSrc[j + fftLenBy2p1] = in;
+      }
+
+      /*  pSrc[i+1U] <-> pSrc[j+fftLenBy2];         */
+      /*  pSrc[i+2] <-> pSrc[j+fftLenBy2+1U]  */
+      in = pSrc[i + 1U];
+      pSrc[i + 1U] = pSrc[j + fftLenBy2];
+      pSrc[j + fftLenBy2] = in;
+
+      /*  Reading the index for the bit reversal */
+      j = *pBitRevTab;
+
+      /*  Updating the bit reversal index depending on the fft length  */
+      pBitRevTab += bitRevFactor;
+   }
+}

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/TransformFunctions/arm_bitreversal2.S
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/TransformFunctions/arm_bitreversal2.S	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,216 @@
+;/* ----------------------------------------------------------------------
+; * Project:      CMSIS DSP Library
+; * Title:        arm_bitreversal2.S
+; * Description:  arm_bitreversal_32 function done in assembly for maximum speed.
+; *               Called after doing an fft to reorder the output.
+; *               The function is loop unrolled by 2. arm_bitreversal_16 as well.
+; *
+; * $Date:        27. January 2017
+; * $Revision:    V.1.5.1
+; *
+; * Target Processor: Cortex-M cores
+; * -------------------------------------------------------------------- */
+;/*
+; * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+; *
+; * SPDX-License-Identifier: Apache-2.0
+; *
+; * Licensed under the Apache License, Version 2.0 (the License); you may
+; * not use this file except in compliance with the License.
+; * You may obtain a copy of the License at
+; *
+; * www.apache.org/licenses/LICENSE-2.0
+; *
+; * Unless required by applicable law or agreed to in writing, software
+; * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+; * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+; * See the License for the specific language governing permissions and
+; * limitations under the License.
+; */
+
+#if   defined ( __CC_ARM )     /* Keil */
+    #define CODESECT AREA     ||.text||, CODE, READONLY, ALIGN=2
+    #define LABEL
+#elif defined ( __IASMARM__ )  /* IAR */
+    #define CODESECT SECTION `.text`:CODE
+    #define PROC
+    #define LABEL
+    #define ENDP
+    #define EXPORT PUBLIC
+#elif defined ( __CSMC__ )	   /* Cosmic */
+	#define	CODESECT	switch .text
+	#define THUMB
+	#define EXPORT	xdef
+	#define PROC	:
+	#define LABEL	:
+	#define ENDP
+	#define arm_bitreversal_32 _arm_bitreversal_32
+#elif defined ( __TI_ARM__ )   /* TI ARM */
+    #define THUMB    .thumb
+    #define CODESECT .text
+    #define EXPORT   .global
+    #define PROC     : .asmfunc
+    #define LABEL    :
+    #define ENDP     .endasmfunc
+    #define END
+#elif defined ( __GNUC__ )     /* GCC */
+    #define THUMB .thumb
+    #define CODESECT .section .text
+    #define EXPORT .global
+    #define PROC :
+    #define LABEL :
+    #define ENDP
+    #define END
+
+    .syntax unified
+#endif
+
+	CODESECT
+	THUMB
+
+;/*
+;* @brief  In-place bit reversal function.
+;* @param[in, out] *pSrc        points to the in-place buffer of unknown 32-bit data type.
+;* @param[in]      bitRevLen    bit reversal table length
+;* @param[in]      *pBitRevTab  points to bit reversal table.
+;* @return none.
+;*/
+	EXPORT arm_bitreversal_32
+	EXPORT arm_bitreversal_16
+
+#if   defined ( __CC_ARM )     /* Keil */
+#elif defined ( __IASMARM__ )  /* IAR */
+#elif defined ( __CSMC__ )	   /* Cosmic */
+#elif defined ( __TI_ARM__ )   /* TI ARM */
+#elif defined ( __GNUC__ )     /* GCC */
+	.type   arm_bitreversal_16, %function
+	.type   arm_bitreversal_32, %function
+#endif
+
+#if defined(ARM_MATH_CM0) || defined(ARM_MATH_CM0PLUS) || defined(ARM_MATH_ARMV8MBL)
+
+arm_bitreversal_32 PROC
+	ADDS     r3,r1,#1
+	PUSH     {r4-r6}
+	ADDS     r1,r2,#0
+	LSRS     r3,r3,#1
+arm_bitreversal_32_0 LABEL
+	LDRH     r2,[r1,#2]
+	LDRH     r6,[r1,#0]
+	ADD      r2,r0,r2
+	ADD      r6,r0,r6
+	LDR      r5,[r2,#0]
+	LDR      r4,[r6,#0]
+	STR      r5,[r6,#0]
+	STR      r4,[r2,#0]
+	LDR      r5,[r2,#4]
+	LDR      r4,[r6,#4]
+	STR      r5,[r6,#4]
+	STR      r4,[r2,#4]
+	ADDS     r1,r1,#4
+	SUBS     r3,r3,#1
+	BNE      arm_bitreversal_32_0
+	POP      {r4-r6}
+	BX       lr
+	ENDP
+
+arm_bitreversal_16 PROC
+	ADDS     r3,r1,#1
+	PUSH     {r4-r6}
+	ADDS     r1,r2,#0
+	LSRS     r3,r3,#1
+arm_bitreversal_16_0 LABEL
+	LDRH     r2,[r1,#2]
+	LDRH     r6,[r1,#0]
+    LSRS     r2,r2,#1
+    LSRS     r6,r6,#1
+	ADD      r2,r0,r2
+	ADD      r6,r0,r6
+	LDR      r5,[r2,#0]
+	LDR      r4,[r6,#0]
+	STR      r5,[r6,#0]
+	STR      r4,[r2,#0]
+	ADDS     r1,r1,#4
+	SUBS     r3,r3,#1
+	BNE      arm_bitreversal_16_0
+	POP      {r4-r6}
+	BX       lr
+	ENDP
+
+#else
+
+arm_bitreversal_32 PROC
+	ADDS     r3,r1,#1
+	CMP      r3,#1
+	IT       LS
+	BXLS     lr
+	PUSH     {r4-r9}
+	ADDS     r1,r2,#2
+	LSRS     r3,r3,#2
+arm_bitreversal_32_0 LABEL       ;/* loop unrolled by 2 */
+	LDRH     r8,[r1,#4]
+	LDRH     r9,[r1,#2]
+	LDRH     r2,[r1,#0]
+	LDRH     r12,[r1,#-2]
+	ADD      r8,r0,r8
+	ADD      r9,r0,r9
+	ADD      r2,r0,r2
+	ADD      r12,r0,r12
+	LDR      r7,[r9,#0]
+	LDR      r6,[r8,#0]
+	LDR      r5,[r2,#0]
+	LDR      r4,[r12,#0]
+	STR      r6,[r9,#0]
+	STR      r7,[r8,#0]
+	STR      r5,[r12,#0]
+	STR      r4,[r2,#0]
+	LDR      r7,[r9,#4]
+	LDR      r6,[r8,#4]
+	LDR      r5,[r2,#4]
+	LDR      r4,[r12,#4]
+	STR      r6,[r9,#4]
+	STR      r7,[r8,#4]
+	STR      r5,[r12,#4]
+	STR      r4,[r2,#4]
+	ADDS     r1,r1,#8
+	SUBS     r3,r3,#1
+	BNE      arm_bitreversal_32_0
+	POP      {r4-r9}
+	BX       lr
+	ENDP
+
+arm_bitreversal_16 PROC
+	ADDS     r3,r1,#1
+	CMP      r3,#1
+	IT       LS
+	BXLS     lr
+	PUSH     {r4-r9}
+	ADDS     r1,r2,#2
+	LSRS     r3,r3,#2
+arm_bitreversal_16_0 LABEL       ;/* loop unrolled by 2 */
+	LDRH     r8,[r1,#4]
+	LDRH     r9,[r1,#2]
+	LDRH     r2,[r1,#0]
+	LDRH     r12,[r1,#-2]
+	ADD      r8,r0,r8,LSR #1
+	ADD      r9,r0,r9,LSR #1
+	ADD      r2,r0,r2,LSR #1
+	ADD      r12,r0,r12,LSR #1
+	LDR      r7,[r9,#0]
+	LDR      r6,[r8,#0]
+	LDR      r5,[r2,#0]
+	LDR      r4,[r12,#0]
+	STR      r6,[r9,#0]
+	STR      r7,[r8,#0]
+	STR      r5,[r12,#0]
+	STR      r4,[r2,#0]
+	ADDS     r1,r1,#8
+	SUBS     r3,r3,#1
+	BNE      arm_bitreversal_16_0
+	POP      {r4-r9}
+	BX       lr
+	ENDP
+
+#endif
+
+	END

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/TransformFunctions/arm_cfft_q15.c
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/TransformFunctions/arm_cfft_q15.c	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,345 @@
+/* ----------------------------------------------------------------------
+ * Project:      CMSIS DSP Library
+ * Title:        arm_cfft_q15.c
+ * Description:  Combined Radix Decimation in Q15 Frequency CFFT processing function
+ *
+ * $Date:        27. January 2017
+ * $Revision:    V.1.5.1
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+/*
+ * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "arm_math.h"
+
+extern void arm_radix4_butterfly_q15(
+    q15_t * pSrc,
+    uint32_t fftLen,
+    q15_t * pCoef,
+    uint32_t twidCoefModifier);
+
+extern void arm_radix4_butterfly_inverse_q15(
+    q15_t * pSrc,
+    uint32_t fftLen,
+    q15_t * pCoef,
+    uint32_t twidCoefModifier);
+
+extern void arm_bitreversal_16(
+    uint16_t * pSrc,
+    const uint16_t bitRevLen,
+    const uint16_t * pBitRevTable);
+
+void arm_cfft_radix4by2_q15(
+    q15_t * pSrc,
+    uint32_t fftLen,
+    const q15_t * pCoef);
+
+void arm_cfft_radix4by2_inverse_q15(
+    q15_t * pSrc,
+    uint32_t fftLen,
+    const q15_t * pCoef);
+
+/**
+* @ingroup groupTransforms
+*/
+
+/**
+* @addtogroup ComplexFFT
+* @{
+*/
+
+/**
+* @details
+* @brief       Processing function for the Q15 complex FFT.
+* @param[in]      *S    points to an instance of the Q15 CFFT structure.
+* @param[in, out] *p1   points to the complex data buffer of size <code>2*fftLen</code>. Processing occurs in-place.
+* @param[in]     ifftFlag       flag that selects forward (ifftFlag=0) or inverse (ifftFlag=1) transform.
+* @param[in]     bitReverseFlag flag that enables (bitReverseFlag=1) or disables (bitReverseFlag=0) bit reversal of output.
+* @return none.
+*/
+
+void arm_cfft_q15(
+    const arm_cfft_instance_q15 * S,
+    q15_t * p1,
+    uint8_t ifftFlag,
+    uint8_t bitReverseFlag)
+{
+    uint32_t L = S->fftLen;
+
+    if (ifftFlag == 1U)
+    {
+        switch (L)
+        {
+        case 16:
+        case 64:
+        case 256:
+        case 1024:
+        case 4096:
+            arm_radix4_butterfly_inverse_q15  ( p1, L, (q15_t*)S->pTwiddle, 1 );
+            break;
+
+        case 32:
+        case 128:
+        case 512:
+        case 2048:
+            arm_cfft_radix4by2_inverse_q15  ( p1, L, S->pTwiddle );
+            break;
+        }
+    }
+    else
+    {
+        switch (L)
+        {
+        case 16:
+        case 64:
+        case 256:
+        case 1024:
+        case 4096:
+            arm_radix4_butterfly_q15  ( p1, L, (q15_t*)S->pTwiddle, 1 );
+            break;
+
+        case 32:
+        case 128:
+        case 512:
+        case 2048:
+            arm_cfft_radix4by2_q15  ( p1, L, S->pTwiddle );
+            break;
+        }
+    }
+
+    if ( bitReverseFlag )
+        arm_bitreversal_16((uint16_t*)p1,S->bitRevLength,S->pBitRevTable);
+}
+
+/**
+* @} end of ComplexFFT group
+*/
+
+void arm_cfft_radix4by2_q15(
+    q15_t * pSrc,
+    uint32_t fftLen,
+    const q15_t * pCoef)
+{
+    uint32_t i;
+    uint32_t n2;
+    q15_t p0, p1, p2, p3;
+#if defined (ARM_MATH_DSP)
+    q31_t T, S, R;
+    q31_t coeff, out1, out2;
+    const q15_t *pC = pCoef;
+    q15_t *pSi = pSrc;
+    q15_t *pSl = pSrc + fftLen;
+#else
+    uint32_t ia, l;
+    q15_t xt, yt, cosVal, sinVal;
+#endif
+
+    n2 = fftLen >> 1;
+
+#if defined (ARM_MATH_DSP)
+
+    for (i = n2; i > 0; i--)
+    {
+        coeff = _SIMD32_OFFSET(pC);
+        pC += 2;
+
+        T = _SIMD32_OFFSET(pSi);
+        T = __SHADD16(T, 0); // this is just a SIMD arithmetic shift right by 1
+
+        S = _SIMD32_OFFSET(pSl);
+        S = __SHADD16(S, 0); // this is just a SIMD arithmetic shift right by 1
+
+        R = __QSUB16(T, S);
+
+        _SIMD32_OFFSET(pSi) = __SHADD16(T, S);
+        pSi += 2;
+
+    #ifndef ARM_MATH_BIG_ENDIAN
+
+        out1 = __SMUAD(coeff, R) >> 16;
+        out2 = __SMUSDX(coeff, R);
+
+    #else
+
+        out1 = __SMUSDX(R, coeff) >> 16U;
+        out2 = __SMUAD(coeff, R);
+
+    #endif //     #ifndef ARM_MATH_BIG_ENDIAN
+
+        _SIMD32_OFFSET(pSl) =
+        (q31_t) ((out2) & 0xFFFF0000) | (out1 & 0x0000FFFF);
+        pSl += 2;
+    }
+
+#else //    #if defined (ARM_MATH_DSP)
+
+    ia = 0;
+    for (i = 0; i < n2; i++)
+    {
+        cosVal = pCoef[ia * 2];
+        sinVal = pCoef[(ia * 2) + 1];
+        ia++;
+
+        l = i + n2;
+
+        xt = (pSrc[2 * i] >> 1U) - (pSrc[2 * l] >> 1U);
+        pSrc[2 * i] = ((pSrc[2 * i] >> 1U) + (pSrc[2 * l] >> 1U)) >> 1U;
+
+        yt = (pSrc[2 * i + 1] >> 1U) - (pSrc[2 * l + 1] >> 1U);
+        pSrc[2 * i + 1] =
+        ((pSrc[2 * l + 1] >> 1U) + (pSrc[2 * i + 1] >> 1U)) >> 1U;
+
+        pSrc[2U * l] = (((int16_t) (((q31_t) xt * cosVal) >> 16)) +
+                  ((int16_t) (((q31_t) yt * sinVal) >> 16)));
+
+        pSrc[2U * l + 1U] = (((int16_t) (((q31_t) yt * cosVal) >> 16)) -
+                       ((int16_t) (((q31_t) xt * sinVal) >> 16)));
+    }
+
+#endif //    #if defined (ARM_MATH_DSP)
+
+    // first col
+    arm_radix4_butterfly_q15( pSrc, n2, (q15_t*)pCoef, 2U);
+    // second col
+    arm_radix4_butterfly_q15( pSrc + fftLen, n2, (q15_t*)pCoef, 2U);
+
+    for (i = 0; i < fftLen >> 1; i++)
+    {
+        p0 = pSrc[4*i+0];
+        p1 = pSrc[4*i+1];
+        p2 = pSrc[4*i+2];
+        p3 = pSrc[4*i+3];
+
+        p0 <<= 1;
+        p1 <<= 1;
+        p2 <<= 1;
+        p3 <<= 1;
+
+        pSrc[4*i+0] = p0;
+        pSrc[4*i+1] = p1;
+        pSrc[4*i+2] = p2;
+        pSrc[4*i+3] = p3;
+    }
+}
+
+void arm_cfft_radix4by2_inverse_q15(
+    q15_t * pSrc,
+    uint32_t fftLen,
+    const q15_t * pCoef)
+{
+    uint32_t i;
+    uint32_t n2;
+    q15_t p0, p1, p2, p3;
+#if defined (ARM_MATH_DSP)
+    q31_t T, S, R;
+    q31_t coeff, out1, out2;
+    const q15_t *pC = pCoef;
+    q15_t *pSi = pSrc;
+    q15_t *pSl = pSrc + fftLen;
+#else
+    uint32_t ia, l;
+    q15_t xt, yt, cosVal, sinVal;
+#endif
+
+    n2 = fftLen >> 1;
+
+#if defined (ARM_MATH_DSP)
+
+    for (i = n2; i > 0; i--)
+    {
+        coeff = _SIMD32_OFFSET(pC);
+        pC += 2;
+
+        T = _SIMD32_OFFSET(pSi);
+        T = __SHADD16(T, 0); // this is just a SIMD arithmetic shift right by 1
+
+        S = _SIMD32_OFFSET(pSl);
+        S = __SHADD16(S, 0); // this is just a SIMD arithmetic shift right by 1
+
+        R = __QSUB16(T, S);
+
+        _SIMD32_OFFSET(pSi) = __SHADD16(T, S);
+        pSi += 2;
+
+    #ifndef ARM_MATH_BIG_ENDIAN
+
+        out1 = __SMUSD(coeff, R) >> 16;
+        out2 = __SMUADX(coeff, R);
+    #else
+
+        out1 = __SMUADX(R, coeff) >> 16U;
+        out2 = __SMUSD(__QSUB(0, coeff), R);
+
+    #endif //     #ifndef ARM_MATH_BIG_ENDIAN
+
+        _SIMD32_OFFSET(pSl) =
+        (q31_t) ((out2) & 0xFFFF0000) | (out1 & 0x0000FFFF);
+        pSl += 2;
+    }
+
+#else //    #if defined (ARM_MATH_DSP)
+
+    ia = 0;
+    for (i = 0; i < n2; i++)
+    {
+        cosVal = pCoef[ia * 2];
+        sinVal = pCoef[(ia * 2) + 1];
+        ia++;
+
+        l = i + n2;
+        xt = (pSrc[2 * i] >> 1U) - (pSrc[2 * l] >> 1U);
+        pSrc[2 * i] = ((pSrc[2 * i] >> 1U) + (pSrc[2 * l] >> 1U)) >> 1U;
+
+        yt = (pSrc[2 * i + 1] >> 1U) - (pSrc[2 * l + 1] >> 1U);
+        pSrc[2 * i + 1] =
+          ((pSrc[2 * l + 1] >> 1U) + (pSrc[2 * i + 1] >> 1U)) >> 1U;
+
+        pSrc[2U * l] = (((int16_t) (((q31_t) xt * cosVal) >> 16)) -
+                        ((int16_t) (((q31_t) yt * sinVal) >> 16)));
+
+        pSrc[2U * l + 1U] = (((int16_t) (((q31_t) yt * cosVal) >> 16)) +
+                           ((int16_t) (((q31_t) xt * sinVal) >> 16)));
+    }
+
+#endif //    #if defined (ARM_MATH_DSP)
+
+    // first col
+    arm_radix4_butterfly_inverse_q15( pSrc, n2, (q15_t*)pCoef, 2U);
+    // second col
+    arm_radix4_butterfly_inverse_q15( pSrc + fftLen, n2, (q15_t*)pCoef, 2U);
+
+    for (i = 0; i < fftLen >> 1; i++)
+    {
+        p0 = pSrc[4*i+0];
+        p1 = pSrc[4*i+1];
+        p2 = pSrc[4*i+2];
+        p3 = pSrc[4*i+3];
+
+        p0 <<= 1;
+        p1 <<= 1;
+        p2 <<= 1;
+        p3 <<= 1;
+
+        pSrc[4*i+0] = p0;
+        pSrc[4*i+1] = p1;
+        pSrc[4*i+2] = p2;
+        pSrc[4*i+3] = p3;
+    }
+}
+

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/TransformFunctions/arm_cfft_radix4_q15.c
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/TransformFunctions/arm_cfft_radix4_q15.c	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,1910 @@
+/* ----------------------------------------------------------------------
+ * Project:      CMSIS DSP Library
+ * Title:        arm_cfft_radix4_q15.c
+ * Description:  This file has function definition of Radix-4 FFT & IFFT function and
+ *               In-place bit reversal using bit reversal table
+ *
+ * $Date:        27. January 2017
+ * $Revision:    V.1.5.1
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+/*
+ * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "arm_math.h"
+
+
+void arm_radix4_butterfly_q15(
+  q15_t * pSrc16,
+  uint32_t fftLen,
+  q15_t * pCoef16,
+  uint32_t twidCoefModifier);
+
+void arm_radix4_butterfly_inverse_q15(
+  q15_t * pSrc16,
+  uint32_t fftLen,
+  q15_t * pCoef16,
+  uint32_t twidCoefModifier);
+
+void arm_bitreversal_q15(
+  q15_t * pSrc,
+  uint32_t fftLen,
+  uint16_t bitRevFactor,
+  uint16_t * pBitRevTab);
+
+/**
+ * @ingroup groupTransforms
+ */
+
+/**
+ * @addtogroup ComplexFFT
+ * @{
+ */
+
+
+/**
+ * @details
+ * @brief Processing function for the Q15 CFFT/CIFFT.
+ * @deprecated Do not use this function.  It has been superseded by \ref arm_cfft_q15 and will be removed
+ * @param[in]      *S    points to an instance of the Q15 CFFT/CIFFT structure.
+ * @param[in, out] *pSrc points to the complex data buffer. Processing occurs in-place.
+ * @return none.
+ *
+ * \par Input and output formats:
+ * \par
+ * Internally input is downscaled by 2 for every stage to avoid saturations inside CFFT/CIFFT process.
+ * Hence the output format is different for different FFT sizes.
+ * The input and output formats for different FFT sizes and number of bits to upscale are mentioned in the tables below for CFFT and CIFFT:
+ * \par
+ * \image html CFFTQ15.gif "Input and Output Formats for Q15 CFFT"
+ * \image html CIFFTQ15.gif "Input and Output Formats for Q15 CIFFT"
+ */
+
+void arm_cfft_radix4_q15(
+  const arm_cfft_radix4_instance_q15 * S,
+  q15_t * pSrc)
+{
+  if (S->ifftFlag == 1U)
+  {
+    /*  Complex IFFT radix-4  */
+    arm_radix4_butterfly_inverse_q15(pSrc, S->fftLen, S->pTwiddle, S->twidCoefModifier);
+  }
+  else
+  {
+    /*  Complex FFT radix-4  */
+    arm_radix4_butterfly_q15(pSrc, S->fftLen, S->pTwiddle, S->twidCoefModifier);
+  }
+
+  if (S->bitReverseFlag == 1U)
+  {
+    /*  Bit Reversal */
+    arm_bitreversal_q15(pSrc, S->fftLen, S->bitRevFactor, S->pBitRevTable);
+  }
+
+}
+
+/**
+ * @} end of ComplexFFT group
+ */
+
+/*
+* Radix-4 FFT algorithm used is :
+*
+* Input real and imaginary data:
+* x(n) = xa + j * ya
+* x(n+N/4 ) = xb + j * yb
+* x(n+N/2 ) = xc + j * yc
+* x(n+3N 4) = xd + j * yd
+*
+*
+* Output real and imaginary data:
+* x(4r) = xa'+ j * ya'
+* x(4r+1) = xb'+ j * yb'
+* x(4r+2) = xc'+ j * yc'
+* x(4r+3) = xd'+ j * yd'
+*
+*
+* Twiddle factors for radix-4 FFT:
+* Wn = co1 + j * (- si1)
+* W2n = co2 + j * (- si2)
+* W3n = co3 + j * (- si3)
+
+* The real and imaginary output values for the radix-4 butterfly are
+* xa' = xa + xb + xc + xd
+* ya' = ya + yb + yc + yd
+* xb' = (xa+yb-xc-yd)* co1 + (ya-xb-yc+xd)* (si1)
+* yb' = (ya-xb-yc+xd)* co1 - (xa+yb-xc-yd)* (si1)
+* xc' = (xa-xb+xc-xd)* co2 + (ya-yb+yc-yd)* (si2)
+* yc' = (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2)
+* xd' = (xa-yb-xc+yd)* co3 + (ya+xb-yc-xd)* (si3)
+* yd' = (ya+xb-yc-xd)* co3 - (xa-yb-xc+yd)* (si3)
+*
+*/
+
+/**
+ * @brief  Core function for the Q15 CFFT butterfly process.
+ * @param[in, out] *pSrc16          points to the in-place buffer of Q15 data type.
+ * @param[in]      fftLen           length of the FFT.
+ * @param[in]      *pCoef16         points to twiddle coefficient buffer.
+ * @param[in]      twidCoefModifier twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table.
+ * @return none.
+ */
+
+void arm_radix4_butterfly_q15(
+  q15_t * pSrc16,
+  uint32_t fftLen,
+  q15_t * pCoef16,
+  uint32_t twidCoefModifier)
+{
+
+#if defined (ARM_MATH_DSP)
+
+  /* Run the below code for Cortex-M4 and Cortex-M3 */
+
+  q31_t R, S, T, U;
+  q31_t C1, C2, C3, out1, out2;
+  uint32_t n1, n2, ic, i0, j, k;
+
+  q15_t *ptr1;
+  q15_t *pSi0;
+  q15_t *pSi1;
+  q15_t *pSi2;
+  q15_t *pSi3;
+
+  q31_t xaya, xbyb, xcyc, xdyd;
+
+  /* Total process is divided into three stages */
+
+  /* process first stage, middle stages, & last stage */
+
+  /*  Initializations for the first stage */
+  n2 = fftLen;
+  n1 = n2;
+
+  /* n2 = fftLen/4 */
+  n2 >>= 2U;
+
+  /* Index for twiddle coefficient */
+  ic = 0U;
+
+  /* Index for input read and output write */
+  j = n2;
+
+  pSi0 = pSrc16;
+  pSi1 = pSi0 + 2 * n2;
+  pSi2 = pSi1 + 2 * n2;
+  pSi3 = pSi2 + 2 * n2;
+
+  /* Input is in 1.15(q15) format */
+
+  /*  start of first stage process */
+  do
+  {
+    /*  Butterfly implementation */
+
+    /*  Reading i0, i0+fftLen/2 inputs */
+    /* Read ya (real), xa(imag) input */
+    T = _SIMD32_OFFSET(pSi0);
+    T = __SHADD16(T, 0); // this is just a SIMD arithmetic shift right by 1
+    T = __SHADD16(T, 0); // it turns out doing this twice is 2 cycles, the alternative takes 3 cycles
+    //in = ((int16_t) (T & 0xFFFF)) >> 2;       // alternative code that takes 3 cycles
+    //T = ((T >> 2) & 0xFFFF0000) | (in & 0xFFFF);
+
+    /* Read yc (real), xc(imag) input */
+    S = _SIMD32_OFFSET(pSi2);
+    S = __SHADD16(S, 0);
+    S = __SHADD16(S, 0);
+
+    /* R = packed((ya + yc), (xa + xc) ) */
+    R = __QADD16(T, S);
+
+    /* S = packed((ya - yc), (xa - xc) ) */
+    S = __QSUB16(T, S);
+
+    /*  Reading i0+fftLen/4 , i0+3fftLen/4 inputs */
+    /* Read yb (real), xb(imag) input */
+    T = _SIMD32_OFFSET(pSi1);
+    T = __SHADD16(T, 0);
+    T = __SHADD16(T, 0);
+
+    /* Read yd (real), xd(imag) input */
+    U = _SIMD32_OFFSET(pSi3);
+    U = __SHADD16(U, 0);
+    U = __SHADD16(U, 0);
+
+    /* T = packed((yb + yd), (xb + xd) ) */
+    T = __QADD16(T, U);
+
+    /*  writing the butterfly processed i0 sample */
+    /* xa' = xa + xb + xc + xd */
+    /* ya' = ya + yb + yc + yd */
+    _SIMD32_OFFSET(pSi0) = __SHADD16(R, T);
+    pSi0 += 2;
+
+    /* R = packed((ya + yc) - (yb + yd), (xa + xc)- (xb + xd)) */
+    R = __QSUB16(R, T);
+
+    /* co2 & si2 are read from SIMD Coefficient pointer */
+    C2 = _SIMD32_OFFSET(pCoef16 + (4U * ic));
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+    /* xc' = (xa-xb+xc-xd)* co2 + (ya-yb+yc-yd)* (si2) */
+    out1 = __SMUAD(C2, R) >> 16U;
+    /* yc' = (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2) */
+    out2 = __SMUSDX(C2, R);
+
+#else
+
+    /* xc' = (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2) */
+    out1 = __SMUSDX(R, C2) >> 16U;
+    /* yc' = (xa-xb+xc-xd)* co2 + (ya-yb+yc-yd)* (si2) */
+    out2 = __SMUAD(C2, R);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+    /*  Reading i0+fftLen/4 */
+    /* T = packed(yb, xb) */
+    T = _SIMD32_OFFSET(pSi1);
+    T = __SHADD16(T, 0);
+    T = __SHADD16(T, 0);
+
+    /* writing the butterfly processed i0 + fftLen/4 sample */
+    /* writing output(xc', yc') in little endian format */
+    _SIMD32_OFFSET(pSi1) =
+      (q31_t) ((out2) & 0xFFFF0000) | (out1 & 0x0000FFFF);
+    pSi1 += 2;
+
+    /*  Butterfly calculations */
+    /* U = packed(yd, xd) */
+    U = _SIMD32_OFFSET(pSi3);
+    U = __SHADD16(U, 0);
+    U = __SHADD16(U, 0);
+
+    /* T = packed(yb-yd, xb-xd) */
+    T = __QSUB16(T, U);
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+    /* R = packed((ya-yc) + (xb- xd) , (xa-xc) - (yb-yd)) */
+    R = __QASX(S, T);
+    /* S = packed((ya-yc) - (xb- xd),  (xa-xc) + (yb-yd)) */
+    S = __QSAX(S, T);
+
+#else
+
+    /* R = packed((ya-yc) + (xb- xd) , (xa-xc) - (yb-yd)) */
+    R = __QSAX(S, T);
+    /* S = packed((ya-yc) - (xb- xd),  (xa-xc) + (yb-yd)) */
+    S = __QASX(S, T);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+    /* co1 & si1 are read from SIMD Coefficient pointer */
+    C1 = _SIMD32_OFFSET(pCoef16 + (2U * ic));
+    /*  Butterfly process for the i0+fftLen/2 sample */
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+    /* xb' = (xa+yb-xc-yd)* co1 + (ya-xb-yc+xd)* (si1) */
+    out1 = __SMUAD(C1, S) >> 16U;
+    /* yb' = (ya-xb-yc+xd)* co1 - (xa+yb-xc-yd)* (si1) */
+    out2 = __SMUSDX(C1, S);
+
+#else
+
+    /* xb' = (ya-xb-yc+xd)* co1 - (xa+yb-xc-yd)* (si1) */
+    out1 = __SMUSDX(S, C1) >> 16U;
+    /* yb' = (xa+yb-xc-yd)* co1 + (ya-xb-yc+xd)* (si1) */
+    out2 = __SMUAD(C1, S);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+    /* writing output(xb', yb') in little endian format */
+    _SIMD32_OFFSET(pSi2) =
+      ((out2) & 0xFFFF0000) | ((out1) & 0x0000FFFF);
+    pSi2 += 2;
+
+
+    /* co3 & si3 are read from SIMD Coefficient pointer */
+    C3 = _SIMD32_OFFSET(pCoef16 + (6U * ic));
+    /*  Butterfly process for the i0+3fftLen/4 sample */
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+    /* xd' = (xa-yb-xc+yd)* co3 + (ya+xb-yc-xd)* (si3) */
+    out1 = __SMUAD(C3, R) >> 16U;
+    /* yd' = (ya+xb-yc-xd)* co3 - (xa-yb-xc+yd)* (si3) */
+    out2 = __SMUSDX(C3, R);
+
+#else
+
+    /* xd' = (ya+xb-yc-xd)* co3 - (xa-yb-xc+yd)* (si3) */
+    out1 = __SMUSDX(R, C3) >> 16U;
+    /* yd' = (xa-yb-xc+yd)* co3 + (ya+xb-yc-xd)* (si3) */
+    out2 = __SMUAD(C3, R);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+    /* writing output(xd', yd') in little endian format */
+    _SIMD32_OFFSET(pSi3) =
+      ((out2) & 0xFFFF0000) | (out1 & 0x0000FFFF);
+    pSi3 += 2;
+
+    /*  Twiddle coefficients index modifier */
+    ic = ic + twidCoefModifier;
+
+  } while (--j);
+  /* data is in 4.11(q11) format */
+
+  /* end of first stage process */
+
+
+  /* start of middle stage process */
+
+  /*  Twiddle coefficients index modifier */
+  twidCoefModifier <<= 2U;
+
+  /*  Calculation of Middle stage */
+  for (k = fftLen / 4U; k > 4U; k >>= 2U)
+  {
+    /*  Initializations for the middle stage */
+    n1 = n2;
+    n2 >>= 2U;
+    ic = 0U;
+
+    for (j = 0U; j <= (n2 - 1U); j++)
+    {
+      /*  index calculation for the coefficients */
+      C1 = _SIMD32_OFFSET(pCoef16 + (2U * ic));
+      C2 = _SIMD32_OFFSET(pCoef16 + (4U * ic));
+      C3 = _SIMD32_OFFSET(pCoef16 + (6U * ic));
+
+      /*  Twiddle coefficients index modifier */
+      ic = ic + twidCoefModifier;
+
+      pSi0 = pSrc16 + 2 * j;
+      pSi1 = pSi0 + 2 * n2;
+      pSi2 = pSi1 + 2 * n2;
+      pSi3 = pSi2 + 2 * n2;
+
+      /*  Butterfly implementation */
+      for (i0 = j; i0 < fftLen; i0 += n1)
+      {
+        /*  Reading i0, i0+fftLen/2 inputs */
+        /* Read ya (real), xa(imag) input */
+        T = _SIMD32_OFFSET(pSi0);
+
+        /* Read yc (real), xc(imag) input */
+        S = _SIMD32_OFFSET(pSi2);
+
+        /* R = packed( (ya + yc), (xa + xc)) */
+        R = __QADD16(T, S);
+
+        /* S = packed((ya - yc), (xa - xc)) */
+        S = __QSUB16(T, S);
+
+        /*  Reading i0+fftLen/4 , i0+3fftLen/4 inputs */
+        /* Read yb (real), xb(imag) input */
+        T = _SIMD32_OFFSET(pSi1);
+
+        /* Read yd (real), xd(imag) input */
+        U = _SIMD32_OFFSET(pSi3);
+
+        /* T = packed( (yb + yd), (xb + xd)) */
+        T = __QADD16(T, U);
+
+        /*  writing the butterfly processed i0 sample */
+
+        /* xa' = xa + xb + xc + xd */
+        /* ya' = ya + yb + yc + yd */
+        out1 = __SHADD16(R, T);
+        out1 = __SHADD16(out1, 0);
+        _SIMD32_OFFSET(pSi0) = out1;
+        pSi0 += 2 * n1;
+
+        /* R = packed( (ya + yc) - (yb + yd), (xa + xc) - (xb + xd)) */
+        R = __SHSUB16(R, T);
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+        /* (ya-yb+yc-yd)* (si2) + (xa-xb+xc-xd)* co2 */
+        out1 = __SMUAD(C2, R) >> 16U;
+
+        /* (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2) */
+        out2 = __SMUSDX(C2, R);
+
+#else
+
+        /* (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2) */
+        out1 = __SMUSDX(R, C2) >> 16U;
+
+        /* (ya-yb+yc-yd)* (si2) + (xa-xb+xc-xd)* co2 */
+        out2 = __SMUAD(C2, R);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+        /*  Reading i0+3fftLen/4 */
+        /* Read yb (real), xb(imag) input */
+        T = _SIMD32_OFFSET(pSi1);
+
+        /*  writing the butterfly processed i0 + fftLen/4 sample */
+        /* xc' = (xa-xb+xc-xd)* co2 + (ya-yb+yc-yd)* (si2) */
+        /* yc' = (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2) */
+        _SIMD32_OFFSET(pSi1) =
+          ((out2) & 0xFFFF0000) | (out1 & 0x0000FFFF);
+        pSi1 += 2 * n1;
+
+        /*  Butterfly calculations */
+
+        /* Read yd (real), xd(imag) input */
+        U = _SIMD32_OFFSET(pSi3);
+
+        /* T = packed(yb-yd, xb-xd) */
+        T = __QSUB16(T, U);
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+        /* R = packed((ya-yc) + (xb- xd) , (xa-xc) - (yb-yd)) */
+        R = __SHASX(S, T);
+
+        /* S = packed((ya-yc) - (xb- xd),  (xa-xc) + (yb-yd)) */
+        S = __SHSAX(S, T);
+
+
+        /*  Butterfly process for the i0+fftLen/2 sample */
+        out1 = __SMUAD(C1, S) >> 16U;
+        out2 = __SMUSDX(C1, S);
+
+#else
+
+        /* R = packed((ya-yc) + (xb- xd) , (xa-xc) - (yb-yd)) */
+        R = __SHSAX(S, T);
+
+        /* S = packed((ya-yc) - (xb- xd),  (xa-xc) + (yb-yd)) */
+        S = __SHASX(S, T);
+
+
+        /*  Butterfly process for the i0+fftLen/2 sample */
+        out1 = __SMUSDX(S, C1) >> 16U;
+        out2 = __SMUAD(C1, S);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+        /* xb' = (xa+yb-xc-yd)* co1 + (ya-xb-yc+xd)* (si1) */
+        /* yb' = (ya-xb-yc+xd)* co1 - (xa+yb-xc-yd)* (si1) */
+        _SIMD32_OFFSET(pSi2) =
+          ((out2) & 0xFFFF0000) | (out1 & 0x0000FFFF);
+        pSi2 += 2 * n1;
+
+        /*  Butterfly process for the i0+3fftLen/4 sample */
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+        out1 = __SMUAD(C3, R) >> 16U;
+        out2 = __SMUSDX(C3, R);
+
+#else
+
+        out1 = __SMUSDX(R, C3) >> 16U;
+        out2 = __SMUAD(C3, R);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+        /* xd' = (xa-yb-xc+yd)* co3 + (ya+xb-yc-xd)* (si3) */
+        /* yd' = (ya+xb-yc-xd)* co3 - (xa-yb-xc+yd)* (si3) */
+        _SIMD32_OFFSET(pSi3) =
+          ((out2) & 0xFFFF0000) | (out1 & 0x0000FFFF);
+        pSi3 += 2 * n1;
+      }
+    }
+    /*  Twiddle coefficients index modifier */
+    twidCoefModifier <<= 2U;
+  }
+  /* end of middle stage process */
+
+
+  /* data is in 10.6(q6) format for the 1024 point */
+  /* data is in 8.8(q8) format for the 256 point */
+  /* data is in 6.10(q10) format for the 64 point */
+  /* data is in 4.12(q12) format for the 16 point */
+
+  /*  Initializations for the last stage */
+  j = fftLen >> 2;
+
+  ptr1 = &pSrc16[0];
+
+  /* start of last stage process */
+
+  /*  Butterfly implementation */
+  do
+  {
+    /* Read xa (real), ya(imag) input */
+    xaya = *__SIMD32(ptr1)++;
+
+    /* Read xb (real), yb(imag) input */
+    xbyb = *__SIMD32(ptr1)++;
+
+    /* Read xc (real), yc(imag) input */
+    xcyc = *__SIMD32(ptr1)++;
+
+    /* Read xd (real), yd(imag) input */
+    xdyd = *__SIMD32(ptr1)++;
+
+    /* R = packed((ya + yc), (xa + xc)) */
+    R = __QADD16(xaya, xcyc);
+
+    /* T = packed((yb + yd), (xb + xd)) */
+    T = __QADD16(xbyb, xdyd);
+
+    /* pointer updation for writing */
+    ptr1 = ptr1 - 8U;
+
+
+    /* xa' = xa + xb + xc + xd */
+    /* ya' = ya + yb + yc + yd */
+    *__SIMD32(ptr1)++ = __SHADD16(R, T);
+
+    /* T = packed((yb + yd), (xb + xd)) */
+    T = __QADD16(xbyb, xdyd);
+
+    /* xc' = (xa-xb+xc-xd) */
+    /* yc' = (ya-yb+yc-yd) */
+    *__SIMD32(ptr1)++ = __SHSUB16(R, T);
+
+    /* S = packed((ya - yc), (xa - xc)) */
+    S = __QSUB16(xaya, xcyc);
+
+    /* Read yd (real), xd(imag) input */
+    /* T = packed( (yb - yd), (xb - xd))  */
+    U = __QSUB16(xbyb, xdyd);
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+    /* xb' = (xa+yb-xc-yd) */
+    /* yb' = (ya-xb-yc+xd) */
+    *__SIMD32(ptr1)++ = __SHSAX(S, U);
+
+
+    /* xd' = (xa-yb-xc+yd) */
+    /* yd' = (ya+xb-yc-xd) */
+    *__SIMD32(ptr1)++ = __SHASX(S, U);
+
+#else
+
+    /* xb' = (xa+yb-xc-yd) */
+    /* yb' = (ya-xb-yc+xd) */
+    *__SIMD32(ptr1)++ = __SHASX(S, U);
+
+
+    /* xd' = (xa-yb-xc+yd) */
+    /* yd' = (ya+xb-yc-xd) */
+    *__SIMD32(ptr1)++ = __SHSAX(S, U);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+  } while (--j);
+
+  /* end of last stage process */
+
+  /* output is in 11.5(q5) format for the 1024 point */
+  /* output is in 9.7(q7) format for the 256 point   */
+  /* output is in 7.9(q9) format for the 64 point  */
+  /* output is in 5.11(q11) format for the 16 point  */
+
+
+#else
+
+  /* Run the below code for Cortex-M0 */
+
+  q15_t R0, R1, S0, S1, T0, T1, U0, U1;
+  q15_t Co1, Si1, Co2, Si2, Co3, Si3, out1, out2;
+  uint32_t n1, n2, ic, i0, i1, i2, i3, j, k;
+
+  /* Total process is divided into three stages */
+
+  /* process first stage, middle stages, & last stage */
+
+  /*  Initializations for the first stage */
+  n2 = fftLen;
+  n1 = n2;
+
+  /* n2 = fftLen/4 */
+  n2 >>= 2U;
+
+  /* Index for twiddle coefficient */
+  ic = 0U;
+
+  /* Index for input read and output write */
+  i0 = 0U;
+  j = n2;
+
+  /* Input is in 1.15(q15) format */
+
+  /*  start of first stage process */
+  do
+  {
+    /*  Butterfly implementation */
+
+    /*  index calculation for the input as, */
+    /*  pSrc16[i0 + 0], pSrc16[i0 + fftLen/4], pSrc16[i0 + fftLen/2], pSrc16[i0 + 3fftLen/4] */
+    i1 = i0 + n2;
+    i2 = i1 + n2;
+    i3 = i2 + n2;
+
+    /*  Reading i0, i0+fftLen/2 inputs */
+
+    /* input is down scale by 4 to avoid overflow */
+    /* Read ya (real), xa(imag) input */
+    T0 = pSrc16[i0 * 2U] >> 2U;
+    T1 = pSrc16[(i0 * 2U) + 1U] >> 2U;
+
+    /* input is down scale by 4 to avoid overflow */
+    /* Read yc (real), xc(imag) input */
+    S0 = pSrc16[i2 * 2U] >> 2U;
+    S1 = pSrc16[(i2 * 2U) + 1U] >> 2U;
+
+    /* R0 = (ya + yc) */
+    R0 = __SSAT(T0 + S0, 16U);
+    /* R1 = (xa + xc) */
+    R1 = __SSAT(T1 + S1, 16U);
+
+    /* S0 = (ya - yc) */
+    S0 = __SSAT(T0 - S0, 16);
+    /* S1 = (xa - xc) */
+    S1 = __SSAT(T1 - S1, 16);
+
+    /*  Reading i0+fftLen/4 , i0+3fftLen/4 inputs */
+    /* input is down scale by 4 to avoid overflow */
+    /* Read yb (real), xb(imag) input */
+    T0 = pSrc16[i1 * 2U] >> 2U;
+    T1 = pSrc16[(i1 * 2U) + 1U] >> 2U;
+
+    /* input is down scale by 4 to avoid overflow */
+    /* Read yd (real), xd(imag) input */
+    U0 = pSrc16[i3 * 2U] >> 2U;
+    U1 = pSrc16[(i3 * 2U) + 1] >> 2U;
+
+    /* T0 = (yb + yd) */
+    T0 = __SSAT(T0 + U0, 16U);
+    /* T1 = (xb + xd) */
+    T1 = __SSAT(T1 + U1, 16U);
+
+    /*  writing the butterfly processed i0 sample */
+    /* ya' = ya + yb + yc + yd */
+    /* xa' = xa + xb + xc + xd */
+    pSrc16[i0 * 2U] = (R0 >> 1U) + (T0 >> 1U);
+    pSrc16[(i0 * 2U) + 1U] = (R1 >> 1U) + (T1 >> 1U);
+
+    /* R0 = (ya + yc) - (yb + yd) */
+    /* R1 = (xa + xc) - (xb + xd) */
+    R0 = __SSAT(R0 - T0, 16U);
+    R1 = __SSAT(R1 - T1, 16U);
+
+    /* co2 & si2 are read from Coefficient pointer */
+    Co2 = pCoef16[2U * ic * 2U];
+    Si2 = pCoef16[(2U * ic * 2U) + 1];
+
+    /* xc' = (xa-xb+xc-xd)* co2 + (ya-yb+yc-yd)* (si2) */
+    out1 = (q15_t) ((Co2 * R0 + Si2 * R1) >> 16U);
+    /* yc' = (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2) */
+    out2 = (q15_t) ((-Si2 * R0 + Co2 * R1) >> 16U);
+
+    /*  Reading i0+fftLen/4 */
+    /* input is down scale by 4 to avoid overflow */
+    /* T0 = yb, T1 =  xb */
+    T0 = pSrc16[i1 * 2U] >> 2;
+    T1 = pSrc16[(i1 * 2U) + 1] >> 2;
+
+    /* writing the butterfly processed i0 + fftLen/4 sample */
+    /* writing output(xc', yc') in little endian format */
+    pSrc16[i1 * 2U] = out1;
+    pSrc16[(i1 * 2U) + 1] = out2;
+
+    /*  Butterfly calculations */
+    /* input is down scale by 4 to avoid overflow */
+    /* U0 = yd, U1 = xd */
+    U0 = pSrc16[i3 * 2U] >> 2;
+    U1 = pSrc16[(i3 * 2U) + 1] >> 2;
+    /* T0 = yb-yd */
+    T0 = __SSAT(T0 - U0, 16);
+    /* T1 = xb-xd */
+    T1 = __SSAT(T1 - U1, 16);
+
+    /* R1 = (ya-yc) + (xb- xd),  R0 = (xa-xc) - (yb-yd)) */
+    R0 = (q15_t) __SSAT((q31_t) (S0 - T1), 16);
+    R1 = (q15_t) __SSAT((q31_t) (S1 + T0), 16);
+
+    /* S1 = (ya-yc) - (xb- xd), S0 = (xa-xc) + (yb-yd)) */
+    S0 = (q15_t) __SSAT(((q31_t) S0 + T1), 16U);
+    S1 = (q15_t) __SSAT(((q31_t) S1 - T0), 16U);
+
+    /* co1 & si1 are read from Coefficient pointer */
+    Co1 = pCoef16[ic * 2U];
+    Si1 = pCoef16[(ic * 2U) + 1];
+    /*  Butterfly process for the i0+fftLen/2 sample */
+    /* xb' = (xa+yb-xc-yd)* co1 + (ya-xb-yc+xd)* (si1) */
+    out1 = (q15_t) ((Si1 * S1 + Co1 * S0) >> 16);
+    /* yb' = (ya-xb-yc+xd)* co1 - (xa+yb-xc-yd)* (si1) */
+    out2 = (q15_t) ((-Si1 * S0 + Co1 * S1) >> 16);
+
+    /* writing output(xb', yb') in little endian format */
+    pSrc16[i2 * 2U] = out1;
+    pSrc16[(i2 * 2U) + 1] = out2;
+
+    /* Co3 & si3 are read from Coefficient pointer */
+    Co3 = pCoef16[3U * (ic * 2U)];
+    Si3 = pCoef16[(3U * (ic * 2U)) + 1];
+    /*  Butterfly process for the i0+3fftLen/4 sample */
+    /* xd' = (xa-yb-xc+yd)* Co3 + (ya+xb-yc-xd)* (si3) */
+    out1 = (q15_t) ((Si3 * R1 + Co3 * R0) >> 16U);
+    /* yd' = (ya+xb-yc-xd)* Co3 - (xa-yb-xc+yd)* (si3) */
+    out2 = (q15_t) ((-Si3 * R0 + Co3 * R1) >> 16U);
+    /* writing output(xd', yd') in little endian format */
+    pSrc16[i3 * 2U] = out1;
+    pSrc16[(i3 * 2U) + 1] = out2;
+
+    /*  Twiddle coefficients index modifier */
+    ic = ic + twidCoefModifier;
+
+    /*  Updating input index */
+    i0 = i0 + 1U;
+
+  } while (--j);
+  /* data is in 4.11(q11) format */
+
+  /* end of first stage process */
+
+
+  /* start of middle stage process */
+
+  /*  Twiddle coefficients index modifier */
+  twidCoefModifier <<= 2U;
+
+  /*  Calculation of Middle stage */
+  for (k = fftLen / 4U; k > 4U; k >>= 2U)
+  {
+    /*  Initializations for the middle stage */
+    n1 = n2;
+    n2 >>= 2U;
+    ic = 0U;
+
+    for (j = 0U; j <= (n2 - 1U); j++)
+    {
+      /*  index calculation for the coefficients */
+      Co1 = pCoef16[ic * 2U];
+      Si1 = pCoef16[(ic * 2U) + 1U];
+      Co2 = pCoef16[2U * (ic * 2U)];
+      Si2 = pCoef16[(2U * (ic * 2U)) + 1U];
+      Co3 = pCoef16[3U * (ic * 2U)];
+      Si3 = pCoef16[(3U * (ic * 2U)) + 1U];
+
+      /*  Twiddle coefficients index modifier */
+      ic = ic + twidCoefModifier;
+
+      /*  Butterfly implementation */
+      for (i0 = j; i0 < fftLen; i0 += n1)
+      {
+        /*  index calculation for the input as, */
+        /*  pSrc16[i0 + 0], pSrc16[i0 + fftLen/4], pSrc16[i0 + fftLen/2], pSrc16[i0 + 3fftLen/4] */
+        i1 = i0 + n2;
+        i2 = i1 + n2;
+        i3 = i2 + n2;
+
+        /*  Reading i0, i0+fftLen/2 inputs */
+        /* Read ya (real), xa(imag) input */
+        T0 = pSrc16[i0 * 2U];
+        T1 = pSrc16[(i0 * 2U) + 1U];
+
+        /* Read yc (real), xc(imag) input */
+        S0 = pSrc16[i2 * 2U];
+        S1 = pSrc16[(i2 * 2U) + 1U];
+
+        /* R0 = (ya + yc), R1 = (xa + xc) */
+        R0 = __SSAT(T0 + S0, 16);
+        R1 = __SSAT(T1 + S1, 16);
+
+        /* S0 = (ya - yc), S1 =(xa - xc) */
+        S0 = __SSAT(T0 - S0, 16);
+        S1 = __SSAT(T1 - S1, 16);
+
+        /*  Reading i0+fftLen/4 , i0+3fftLen/4 inputs */
+        /* Read yb (real), xb(imag) input */
+        T0 = pSrc16[i1 * 2U];
+        T1 = pSrc16[(i1 * 2U) + 1U];
+
+        /* Read yd (real), xd(imag) input */
+        U0 = pSrc16[i3 * 2U];
+        U1 = pSrc16[(i3 * 2U) + 1U];
+
+
+        /* T0 = (yb + yd), T1 = (xb + xd) */
+        T0 = __SSAT(T0 + U0, 16);
+        T1 = __SSAT(T1 + U1, 16);
+
+        /*  writing the butterfly processed i0 sample */
+
+        /* xa' = xa + xb + xc + xd */
+        /* ya' = ya + yb + yc + yd */
+        out1 = ((R0 >> 1U) + (T0 >> 1U)) >> 1U;
+        out2 = ((R1 >> 1U) + (T1 >> 1U)) >> 1U;
+
+        pSrc16[i0 * 2U] = out1;
+        pSrc16[(2U * i0) + 1U] = out2;
+
+        /* R0 = (ya + yc) - (yb + yd), R1 = (xa + xc) - (xb + xd) */
+        R0 = (R0 >> 1U) - (T0 >> 1U);
+        R1 = (R1 >> 1U) - (T1 >> 1U);
+
+        /* (ya-yb+yc-yd)* (si2) + (xa-xb+xc-xd)* co2 */
+        out1 = (q15_t) ((Co2 * R0 + Si2 * R1) >> 16U);
+
+        /* (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2) */
+        out2 = (q15_t) ((-Si2 * R0 + Co2 * R1) >> 16U);
+
+        /*  Reading i0+3fftLen/4 */
+        /* Read yb (real), xb(imag) input */
+        T0 = pSrc16[i1 * 2U];
+        T1 = pSrc16[(i1 * 2U) + 1U];
+
+        /*  writing the butterfly processed i0 + fftLen/4 sample */
+        /* xc' = (xa-xb+xc-xd)* co2 + (ya-yb+yc-yd)* (si2) */
+        /* yc' = (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2) */
+        pSrc16[i1 * 2U] = out1;
+        pSrc16[(i1 * 2U) + 1U] = out2;
+
+        /*  Butterfly calculations */
+
+        /* Read yd (real), xd(imag) input */
+        U0 = pSrc16[i3 * 2U];
+        U1 = pSrc16[(i3 * 2U) + 1U];
+
+        /* T0 = yb-yd, T1 = xb-xd */
+        T0 = __SSAT(T0 - U0, 16);
+        T1 = __SSAT(T1 - U1, 16);
+
+        /* R0 = (ya-yc) + (xb- xd), R1 = (xa-xc) - (yb-yd)) */
+        R0 = (S0 >> 1U) - (T1 >> 1U);
+        R1 = (S1 >> 1U) + (T0 >> 1U);
+
+        /* S0 = (ya-yc) - (xb- xd), S1 = (xa-xc) + (yb-yd)) */
+        S0 = (S0 >> 1U) + (T1 >> 1U);
+        S1 = (S1 >> 1U) - (T0 >> 1U);
+
+        /*  Butterfly process for the i0+fftLen/2 sample */
+        out1 = (q15_t) ((Co1 * S0 + Si1 * S1) >> 16U);
+
+        out2 = (q15_t) ((-Si1 * S0 + Co1 * S1) >> 16U);
+
+        /* xb' = (xa+yb-xc-yd)* co1 + (ya-xb-yc+xd)* (si1) */
+        /* yb' = (ya-xb-yc+xd)* co1 - (xa+yb-xc-yd)* (si1) */
+        pSrc16[i2 * 2U] = out1;
+        pSrc16[(i2 * 2U) + 1U] = out2;
+
+        /*  Butterfly process for the i0+3fftLen/4 sample */
+        out1 = (q15_t) ((Si3 * R1 + Co3 * R0) >> 16U);
+
+        out2 = (q15_t) ((-Si3 * R0 + Co3 * R1) >> 16U);
+        /* xd' = (xa-yb-xc+yd)* Co3 + (ya+xb-yc-xd)* (si3) */
+        /* yd' = (ya+xb-yc-xd)* Co3 - (xa-yb-xc+yd)* (si3) */
+        pSrc16[i3 * 2U] = out1;
+        pSrc16[(i3 * 2U) + 1U] = out2;
+      }
+    }
+    /*  Twiddle coefficients index modifier */
+    twidCoefModifier <<= 2U;
+  }
+  /* end of middle stage process */
+
+
+  /* data is in 10.6(q6) format for the 1024 point */
+  /* data is in 8.8(q8) format for the 256 point */
+  /* data is in 6.10(q10) format for the 64 point */
+  /* data is in 4.12(q12) format for the 16 point */
+
+  /*  Initializations for the last stage */
+  n1 = n2;
+  n2 >>= 2U;
+
+  /* start of last stage process */
+
+  /*  Butterfly implementation */
+  for (i0 = 0U; i0 <= (fftLen - n1); i0 += n1)
+  {
+    /*  index calculation for the input as, */
+    /*  pSrc16[i0 + 0], pSrc16[i0 + fftLen/4], pSrc16[i0 + fftLen/2], pSrc16[i0 + 3fftLen/4] */
+    i1 = i0 + n2;
+    i2 = i1 + n2;
+    i3 = i2 + n2;
+
+    /*  Reading i0, i0+fftLen/2 inputs */
+    /* Read ya (real), xa(imag) input */
+    T0 = pSrc16[i0 * 2U];
+    T1 = pSrc16[(i0 * 2U) + 1U];
+
+    /* Read yc (real), xc(imag) input */
+    S0 = pSrc16[i2 * 2U];
+    S1 = pSrc16[(i2 * 2U) + 1U];
+
+    /* R0 = (ya + yc), R1 = (xa + xc) */
+    R0 = __SSAT(T0 + S0, 16U);
+    R1 = __SSAT(T1 + S1, 16U);
+
+    /* S0 = (ya - yc), S1 = (xa - xc) */
+    S0 = __SSAT(T0 - S0, 16U);
+    S1 = __SSAT(T1 - S1, 16U);
+
+    /*  Reading i0+fftLen/4 , i0+3fftLen/4 inputs */
+    /* Read yb (real), xb(imag) input */
+    T0 = pSrc16[i1 * 2U];
+    T1 = pSrc16[(i1 * 2U) + 1U];
+    /* Read yd (real), xd(imag) input */
+    U0 = pSrc16[i3 * 2U];
+    U1 = pSrc16[(i3 * 2U) + 1U];
+
+    /* T0 = (yb + yd), T1 = (xb + xd)) */
+    T0 = __SSAT(T0 + U0, 16U);
+    T1 = __SSAT(T1 + U1, 16U);
+
+    /*  writing the butterfly processed i0 sample */
+    /* xa' = xa + xb + xc + xd */
+    /* ya' = ya + yb + yc + yd */
+    pSrc16[i0 * 2U] = (R0 >> 1U) + (T0 >> 1U);
+    pSrc16[(i0 * 2U) + 1U] = (R1 >> 1U) + (T1 >> 1U);
+
+    /* R0 = (ya + yc) - (yb + yd), R1 = (xa + xc) - (xb + xd) */
+    R0 = (R0 >> 1U) - (T0 >> 1U);
+    R1 = (R1 >> 1U) - (T1 >> 1U);
+    /* Read yb (real), xb(imag) input */
+    T0 = pSrc16[i1 * 2U];
+    T1 = pSrc16[(i1 * 2U) + 1U];
+
+    /*  writing the butterfly processed i0 + fftLen/4 sample */
+    /* xc' = (xa-xb+xc-xd) */
+    /* yc' = (ya-yb+yc-yd) */
+    pSrc16[i1 * 2U] = R0;
+    pSrc16[(i1 * 2U) + 1U] = R1;
+
+    /* Read yd (real), xd(imag) input */
+    U0 = pSrc16[i3 * 2U];
+    U1 = pSrc16[(i3 * 2U) + 1U];
+    /* T0 = (yb - yd), T1 = (xb - xd)  */
+    T0 = __SSAT(T0 - U0, 16U);
+    T1 = __SSAT(T1 - U1, 16U);
+
+    /*  writing the butterfly processed i0 + fftLen/2 sample */
+    /* xb' = (xa+yb-xc-yd) */
+    /* yb' = (ya-xb-yc+xd) */
+    pSrc16[i2 * 2U] = (S0 >> 1U) + (T1 >> 1U);
+    pSrc16[(i2 * 2U) + 1U] = (S1 >> 1U) - (T0 >> 1U);
+
+    /*  writing the butterfly processed i0 + 3fftLen/4 sample */
+    /* xd' = (xa-yb-xc+yd) */
+    /* yd' = (ya+xb-yc-xd) */
+    pSrc16[i3 * 2U] = (S0 >> 1U) - (T1 >> 1U);
+    pSrc16[(i3 * 2U) + 1U] = (S1 >> 1U) + (T0 >> 1U);
+
+  }
+
+  /* end of last stage process */
+
+  /* output is in 11.5(q5) format for the 1024 point */
+  /* output is in 9.7(q7) format for the 256 point   */
+  /* output is in 7.9(q9) format for the 64 point  */
+  /* output is in 5.11(q11) format for the 16 point  */
+
+#endif /* #if defined (ARM_MATH_DSP) */
+
+}
+
+
+/**
+ * @brief  Core function for the Q15 CIFFT butterfly process.
+ * @param[in, out] *pSrc16          points to the in-place buffer of Q15 data type.
+ * @param[in]      fftLen           length of the FFT.
+ * @param[in]      *pCoef16         points to twiddle coefficient buffer.
+ * @param[in]      twidCoefModifier twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table.
+ * @return none.
+ */
+
+/*
+* Radix-4 IFFT algorithm used is :
+*
+* CIFFT uses same twiddle coefficients as CFFT function
+*  x[k] = x[n] + (j)k * x[n + fftLen/4] + (-1)k * x[n+fftLen/2] + (-j)k * x[n+3*fftLen/4]
+*
+*
+* IFFT is implemented with following changes in equations from FFT
+*
+* Input real and imaginary data:
+* x(n) = xa + j * ya
+* x(n+N/4 ) = xb + j * yb
+* x(n+N/2 ) = xc + j * yc
+* x(n+3N 4) = xd + j * yd
+*
+*
+* Output real and imaginary data:
+* x(4r) = xa'+ j * ya'
+* x(4r+1) = xb'+ j * yb'
+* x(4r+2) = xc'+ j * yc'
+* x(4r+3) = xd'+ j * yd'
+*
+*
+* Twiddle factors for radix-4 IFFT:
+* Wn = co1 + j * (si1)
+* W2n = co2 + j * (si2)
+* W3n = co3 + j * (si3)
+
+* The real and imaginary output values for the radix-4 butterfly are
+* xa' = xa + xb + xc + xd
+* ya' = ya + yb + yc + yd
+* xb' = (xa-yb-xc+yd)* co1 - (ya+xb-yc-xd)* (si1)
+* yb' = (ya+xb-yc-xd)* co1 + (xa-yb-xc+yd)* (si1)
+* xc' = (xa-xb+xc-xd)* co2 - (ya-yb+yc-yd)* (si2)
+* yc' = (ya-yb+yc-yd)* co2 + (xa-xb+xc-xd)* (si2)
+* xd' = (xa+yb-xc-yd)* co3 - (ya-xb-yc+xd)* (si3)
+* yd' = (ya-xb-yc+xd)* co3 + (xa+yb-xc-yd)* (si3)
+*
+*/
+
+void arm_radix4_butterfly_inverse_q15(
+  q15_t * pSrc16,
+  uint32_t fftLen,
+  q15_t * pCoef16,
+  uint32_t twidCoefModifier)
+{
+
+#if defined (ARM_MATH_DSP)
+
+  /* Run the below code for Cortex-M4 and Cortex-M3 */
+
+  q31_t R, S, T, U;
+  q31_t C1, C2, C3, out1, out2;
+  uint32_t n1, n2, ic, i0, j, k;
+
+  q15_t *ptr1;
+  q15_t *pSi0;
+  q15_t *pSi1;
+  q15_t *pSi2;
+  q15_t *pSi3;
+
+  q31_t xaya, xbyb, xcyc, xdyd;
+
+  /* Total process is divided into three stages */
+
+  /* process first stage, middle stages, & last stage */
+
+  /*  Initializations for the first stage */
+  n2 = fftLen;
+  n1 = n2;
+
+  /* n2 = fftLen/4 */
+  n2 >>= 2U;
+
+  /* Index for twiddle coefficient */
+  ic = 0U;
+
+  /* Index for input read and output write */
+  j = n2;
+
+  pSi0 = pSrc16;
+  pSi1 = pSi0 + 2 * n2;
+  pSi2 = pSi1 + 2 * n2;
+  pSi3 = pSi2 + 2 * n2;
+
+  /* Input is in 1.15(q15) format */
+
+  /*  start of first stage process */
+  do
+  {
+    /*  Butterfly implementation */
+
+    /*  Reading i0, i0+fftLen/2 inputs */
+    /* Read ya (real), xa(imag) input */
+    T = _SIMD32_OFFSET(pSi0);
+    T = __SHADD16(T, 0);
+    T = __SHADD16(T, 0);
+
+    /* Read yc (real), xc(imag) input */
+    S = _SIMD32_OFFSET(pSi2);
+    S = __SHADD16(S, 0);
+    S = __SHADD16(S, 0);
+
+    /* R = packed((ya + yc), (xa + xc) ) */
+    R = __QADD16(T, S);
+
+    /* S = packed((ya - yc), (xa - xc) ) */
+    S = __QSUB16(T, S);
+
+    /*  Reading i0+fftLen/4 , i0+3fftLen/4 inputs */
+    /* Read yb (real), xb(imag) input */
+    T = _SIMD32_OFFSET(pSi1);
+    T = __SHADD16(T, 0);
+    T = __SHADD16(T, 0);
+
+    /* Read yd (real), xd(imag) input */
+    U = _SIMD32_OFFSET(pSi3);
+    U = __SHADD16(U, 0);
+    U = __SHADD16(U, 0);
+
+    /* T = packed((yb + yd), (xb + xd) ) */
+    T = __QADD16(T, U);
+
+    /*  writing the butterfly processed i0 sample */
+    /* xa' = xa + xb + xc + xd */
+    /* ya' = ya + yb + yc + yd */
+    _SIMD32_OFFSET(pSi0) = __SHADD16(R, T);
+    pSi0 += 2;
+
+    /* R = packed((ya + yc) - (yb + yd), (xa + xc)- (xb + xd)) */
+    R = __QSUB16(R, T);
+
+    /* co2 & si2 are read from SIMD Coefficient pointer */
+    C2 = _SIMD32_OFFSET(pCoef16 + (4U * ic));
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+    /* xc' = (xa-xb+xc-xd)* co2 + (ya-yb+yc-yd)* (si2) */
+    out1 = __SMUSD(C2, R) >> 16U;
+    /* yc' = (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2) */
+    out2 = __SMUADX(C2, R);
+
+#else
+
+    /* xc' = (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2) */
+    out1 = __SMUADX(C2, R) >> 16U;
+    /* yc' = (xa-xb+xc-xd)* co2 + (ya-yb+yc-yd)* (si2) */
+    out2 = __SMUSD(__QSUB16(0, C2), R);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+    /*  Reading i0+fftLen/4 */
+    /* T = packed(yb, xb) */
+    T = _SIMD32_OFFSET(pSi1);
+    T = __SHADD16(T, 0);
+    T = __SHADD16(T, 0);
+
+    /* writing the butterfly processed i0 + fftLen/4 sample */
+    /* writing output(xc', yc') in little endian format */
+    _SIMD32_OFFSET(pSi1) =
+      (q31_t) ((out2) & 0xFFFF0000) | (out1 & 0x0000FFFF);
+    pSi1 += 2;
+
+    /*  Butterfly calculations */
+    /* U = packed(yd, xd) */
+    U = _SIMD32_OFFSET(pSi3);
+    U = __SHADD16(U, 0);
+    U = __SHADD16(U, 0);
+
+    /* T = packed(yb-yd, xb-xd) */
+    T = __QSUB16(T, U);
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+    /* R = packed((ya-yc) + (xb- xd) , (xa-xc) - (yb-yd)) */
+    R = __QSAX(S, T);
+    /* S = packed((ya-yc) + (xb- xd),  (xa-xc) - (yb-yd)) */
+    S = __QASX(S, T);
+
+#else
+
+    /* R = packed((ya-yc) + (xb- xd) , (xa-xc) - (yb-yd)) */
+    R = __QASX(S, T);
+    /* S = packed((ya-yc) - (xb- xd),  (xa-xc) + (yb-yd)) */
+    S = __QSAX(S, T);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+    /* co1 & si1 are read from SIMD Coefficient pointer */
+    C1 = _SIMD32_OFFSET(pCoef16 + (2U * ic));
+    /*  Butterfly process for the i0+fftLen/2 sample */
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+    /* xb' = (xa+yb-xc-yd)* co1 + (ya-xb-yc+xd)* (si1) */
+    out1 = __SMUSD(C1, S) >> 16U;
+    /* yb' = (ya-xb-yc+xd)* co1 - (xa+yb-xc-yd)* (si1) */
+    out2 = __SMUADX(C1, S);
+
+#else
+
+    /* xb' = (ya-xb-yc+xd)* co1 - (xa+yb-xc-yd)* (si1) */
+    out1 = __SMUADX(C1, S) >> 16U;
+    /* yb' = (xa+yb-xc-yd)* co1 + (ya-xb-yc+xd)* (si1) */
+    out2 = __SMUSD(__QSUB16(0, C1), S);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+    /* writing output(xb', yb') in little endian format */
+    _SIMD32_OFFSET(pSi2) =
+      ((out2) & 0xFFFF0000) | ((out1) & 0x0000FFFF);
+    pSi2 += 2;
+
+
+    /* co3 & si3 are read from SIMD Coefficient pointer */
+    C3 = _SIMD32_OFFSET(pCoef16 + (6U * ic));
+    /*  Butterfly process for the i0+3fftLen/4 sample */
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+    /* xd' = (xa-yb-xc+yd)* co3 + (ya+xb-yc-xd)* (si3) */
+    out1 = __SMUSD(C3, R) >> 16U;
+    /* yd' = (ya+xb-yc-xd)* co3 - (xa-yb-xc+yd)* (si3) */
+    out2 = __SMUADX(C3, R);
+
+#else
+
+    /* xd' = (ya+xb-yc-xd)* co3 - (xa-yb-xc+yd)* (si3) */
+    out1 = __SMUADX(C3, R) >> 16U;
+    /* yd' = (xa-yb-xc+yd)* co3 + (ya+xb-yc-xd)* (si3) */
+    out2 = __SMUSD(__QSUB16(0, C3), R);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+    /* writing output(xd', yd') in little endian format */
+    _SIMD32_OFFSET(pSi3) =
+      ((out2) & 0xFFFF0000) | (out1 & 0x0000FFFF);
+    pSi3 += 2;
+
+    /*  Twiddle coefficients index modifier */
+    ic = ic + twidCoefModifier;
+
+  } while (--j);
+  /* data is in 4.11(q11) format */
+
+  /* end of first stage process */
+
+
+  /* start of middle stage process */
+
+  /*  Twiddle coefficients index modifier */
+  twidCoefModifier <<= 2U;
+
+  /*  Calculation of Middle stage */
+  for (k = fftLen / 4U; k > 4U; k >>= 2U)
+  {
+    /*  Initializations for the middle stage */
+    n1 = n2;
+    n2 >>= 2U;
+    ic = 0U;
+
+    for (j = 0U; j <= (n2 - 1U); j++)
+    {
+      /*  index calculation for the coefficients */
+      C1 = _SIMD32_OFFSET(pCoef16 + (2U * ic));
+      C2 = _SIMD32_OFFSET(pCoef16 + (4U * ic));
+      C3 = _SIMD32_OFFSET(pCoef16 + (6U * ic));
+
+      /*  Twiddle coefficients index modifier */
+      ic = ic + twidCoefModifier;
+
+      pSi0 = pSrc16 + 2 * j;
+      pSi1 = pSi0 + 2 * n2;
+      pSi2 = pSi1 + 2 * n2;
+      pSi3 = pSi2 + 2 * n2;
+
+      /*  Butterfly implementation */
+      for (i0 = j; i0 < fftLen; i0 += n1)
+      {
+        /*  Reading i0, i0+fftLen/2 inputs */
+        /* Read ya (real), xa(imag) input */
+        T = _SIMD32_OFFSET(pSi0);
+
+        /* Read yc (real), xc(imag) input */
+        S = _SIMD32_OFFSET(pSi2);
+
+        /* R = packed( (ya + yc), (xa + xc)) */
+        R = __QADD16(T, S);
+
+        /* S = packed((ya - yc), (xa - xc)) */
+        S = __QSUB16(T, S);
+
+        /*  Reading i0+fftLen/4 , i0+3fftLen/4 inputs */
+        /* Read yb (real), xb(imag) input */
+        T = _SIMD32_OFFSET(pSi1);
+
+        /* Read yd (real), xd(imag) input */
+        U = _SIMD32_OFFSET(pSi3);
+
+        /* T = packed( (yb + yd), (xb + xd)) */
+        T = __QADD16(T, U);
+
+        /*  writing the butterfly processed i0 sample */
+
+        /* xa' = xa + xb + xc + xd */
+        /* ya' = ya + yb + yc + yd */
+        out1 = __SHADD16(R, T);
+        out1 = __SHADD16(out1, 0);
+        _SIMD32_OFFSET(pSi0) = out1;
+        pSi0 += 2 * n1;
+
+        /* R = packed( (ya + yc) - (yb + yd), (xa + xc) - (xb + xd)) */
+        R = __SHSUB16(R, T);
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+        /* (ya-yb+yc-yd)* (si2) + (xa-xb+xc-xd)* co2 */
+        out1 = __SMUSD(C2, R) >> 16U;
+
+        /* (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2) */
+        out2 = __SMUADX(C2, R);
+
+#else
+
+        /* (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2) */
+        out1 = __SMUADX(R, C2) >> 16U;
+
+        /* (ya-yb+yc-yd)* (si2) + (xa-xb+xc-xd)* co2 */
+        out2 = __SMUSD(__QSUB16(0, C2), R);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+        /*  Reading i0+3fftLen/4 */
+        /* Read yb (real), xb(imag) input */
+        T = _SIMD32_OFFSET(pSi1);
+
+        /*  writing the butterfly processed i0 + fftLen/4 sample */
+        /* xc' = (xa-xb+xc-xd)* co2 + (ya-yb+yc-yd)* (si2) */
+        /* yc' = (ya-yb+yc-yd)* co2 - (xa-xb+xc-xd)* (si2) */
+        _SIMD32_OFFSET(pSi1) =
+          ((out2) & 0xFFFF0000) | (out1 & 0x0000FFFF);
+        pSi1 += 2 * n1;
+
+        /*  Butterfly calculations */
+
+        /* Read yd (real), xd(imag) input */
+        U = _SIMD32_OFFSET(pSi3);
+
+        /* T = packed(yb-yd, xb-xd) */
+        T = __QSUB16(T, U);
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+        /* R = packed((ya-yc) + (xb- xd) , (xa-xc) - (yb-yd)) */
+        R = __SHSAX(S, T);
+
+        /* S = packed((ya-yc) - (xb- xd),  (xa-xc) + (yb-yd)) */
+        S = __SHASX(S, T);
+
+
+        /*  Butterfly process for the i0+fftLen/2 sample */
+        out1 = __SMUSD(C1, S) >> 16U;
+        out2 = __SMUADX(C1, S);
+
+#else
+
+        /* R = packed((ya-yc) + (xb- xd) , (xa-xc) - (yb-yd)) */
+        R = __SHASX(S, T);
+
+        /* S = packed((ya-yc) - (xb- xd),  (xa-xc) + (yb-yd)) */
+        S = __SHSAX(S, T);
+
+
+        /*  Butterfly process for the i0+fftLen/2 sample */
+        out1 = __SMUADX(S, C1) >> 16U;
+        out2 = __SMUSD(__QSUB16(0, C1), S);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+        /* xb' = (xa+yb-xc-yd)* co1 + (ya-xb-yc+xd)* (si1) */
+        /* yb' = (ya-xb-yc+xd)* co1 - (xa+yb-xc-yd)* (si1) */
+        _SIMD32_OFFSET(pSi2) =
+          ((out2) & 0xFFFF0000) | (out1 & 0x0000FFFF);
+        pSi2 += 2 * n1;
+
+        /*  Butterfly process for the i0+3fftLen/4 sample */
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+        out1 = __SMUSD(C3, R) >> 16U;
+        out2 = __SMUADX(C3, R);
+
+#else
+
+        out1 = __SMUADX(C3, R) >> 16U;
+        out2 = __SMUSD(__QSUB16(0, C3), R);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+        /* xd' = (xa-yb-xc+yd)* co3 + (ya+xb-yc-xd)* (si3) */
+        /* yd' = (ya+xb-yc-xd)* co3 - (xa-yb-xc+yd)* (si3) */
+        _SIMD32_OFFSET(pSi3) =
+          ((out2) & 0xFFFF0000) | (out1 & 0x0000FFFF);
+        pSi3 += 2 * n1;
+      }
+    }
+    /*  Twiddle coefficients index modifier */
+    twidCoefModifier <<= 2U;
+  }
+  /* end of middle stage process */
+
+  /* data is in 10.6(q6) format for the 1024 point */
+  /* data is in 8.8(q8) format for the 256 point */
+  /* data is in 6.10(q10) format for the 64 point */
+  /* data is in 4.12(q12) format for the 16 point */
+
+  /*  Initializations for the last stage */
+  j = fftLen >> 2;
+
+  ptr1 = &pSrc16[0];
+
+  /* start of last stage process */
+
+  /*  Butterfly implementation */
+  do
+  {
+    /* Read xa (real), ya(imag) input */
+    xaya = *__SIMD32(ptr1)++;
+
+    /* Read xb (real), yb(imag) input */
+    xbyb = *__SIMD32(ptr1)++;
+
+    /* Read xc (real), yc(imag) input */
+    xcyc = *__SIMD32(ptr1)++;
+
+    /* Read xd (real), yd(imag) input */
+    xdyd = *__SIMD32(ptr1)++;
+
+    /* R = packed((ya + yc), (xa + xc)) */
+    R = __QADD16(xaya, xcyc);
+
+    /* T = packed((yb + yd), (xb + xd)) */
+    T = __QADD16(xbyb, xdyd);
+
+    /* pointer updation for writing */
+    ptr1 = ptr1 - 8U;
+
+
+    /* xa' = xa + xb + xc + xd */
+    /* ya' = ya + yb + yc + yd */
+    *__SIMD32(ptr1)++ = __SHADD16(R, T);
+
+    /* T = packed((yb + yd), (xb + xd)) */
+    T = __QADD16(xbyb, xdyd);
+
+    /* xc' = (xa-xb+xc-xd) */
+    /* yc' = (ya-yb+yc-yd) */
+    *__SIMD32(ptr1)++ = __SHSUB16(R, T);
+
+    /* S = packed((ya - yc), (xa - xc)) */
+    S = __QSUB16(xaya, xcyc);
+
+    /* Read yd (real), xd(imag) input */
+    /* T = packed( (yb - yd), (xb - xd))  */
+    U = __QSUB16(xbyb, xdyd);
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+    /* xb' = (xa+yb-xc-yd) */
+    /* yb' = (ya-xb-yc+xd) */
+    *__SIMD32(ptr1)++ = __SHASX(S, U);
+
+
+    /* xd' = (xa-yb-xc+yd) */
+    /* yd' = (ya+xb-yc-xd) */
+    *__SIMD32(ptr1)++ = __SHSAX(S, U);
+
+#else
+
+    /* xb' = (xa+yb-xc-yd) */
+    /* yb' = (ya-xb-yc+xd) */
+    *__SIMD32(ptr1)++ = __SHSAX(S, U);
+
+
+    /* xd' = (xa-yb-xc+yd) */
+    /* yd' = (ya+xb-yc-xd) */
+    *__SIMD32(ptr1)++ = __SHASX(S, U);
+
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+  } while (--j);
+
+  /* end of last stage  process */
+
+  /* output is in 11.5(q5) format for the 1024 point */
+  /* output is in 9.7(q7) format for the 256 point   */
+  /* output is in 7.9(q9) format for the 64 point  */
+  /* output is in 5.11(q11) format for the 16 point  */
+
+
+#else
+
+  /* Run the below code for Cortex-M0 */
+
+  q15_t R0, R1, S0, S1, T0, T1, U0, U1;
+  q15_t Co1, Si1, Co2, Si2, Co3, Si3, out1, out2;
+  uint32_t n1, n2, ic, i0, i1, i2, i3, j, k;
+
+  /* Total process is divided into three stages */
+
+  /* process first stage, middle stages, & last stage */
+
+  /*  Initializations for the first stage */
+  n2 = fftLen;
+  n1 = n2;
+
+  /* n2 = fftLen/4 */
+  n2 >>= 2U;
+
+  /* Index for twiddle coefficient */
+  ic = 0U;
+
+  /* Index for input read and output write */
+  i0 = 0U;
+
+  j = n2;
+
+  /* Input is in 1.15(q15) format */
+
+  /*  Start of first stage process */
+  do
+  {
+    /*  Butterfly implementation */
+
+    /*  index calculation for the input as, */
+    /*  pSrc16[i0 + 0], pSrc16[i0 + fftLen/4], pSrc16[i0 + fftLen/2], pSrc16[i0 + 3fftLen/4] */
+    i1 = i0 + n2;
+    i2 = i1 + n2;
+    i3 = i2 + n2;
+
+    /*  Reading i0, i0+fftLen/2 inputs */
+    /* input is down scale by 4 to avoid overflow */
+    /* Read ya (real), xa(imag) input */
+    T0 = pSrc16[i0 * 2U] >> 2U;
+    T1 = pSrc16[(i0 * 2U) + 1U] >> 2U;
+    /* input is down scale by 4 to avoid overflow */
+    /* Read yc (real), xc(imag) input */
+    S0 = pSrc16[i2 * 2U] >> 2U;
+    S1 = pSrc16[(i2 * 2U) + 1U] >> 2U;
+
+    /* R0 = (ya + yc), R1 = (xa + xc) */
+    R0 = __SSAT(T0 + S0, 16U);
+    R1 = __SSAT(T1 + S1, 16U);
+    /* S0 = (ya - yc), S1 = (xa - xc) */
+    S0 = __SSAT(T0 - S0, 16U);
+    S1 = __SSAT(T1 - S1, 16U);
+
+    /*  Reading i0+fftLen/4 , i0+3fftLen/4 inputs */
+    /* input is down scale by 4 to avoid overflow */
+    /* Read yb (real), xb(imag) input */
+    T0 = pSrc16[i1 * 2U] >> 2U;
+    T1 = pSrc16[(i1 * 2U) + 1U] >> 2U;
+    /* Read yd (real), xd(imag) input */
+    /* input is down scale by 4 to avoid overflow */
+    U0 = pSrc16[i3 * 2U] >> 2U;
+    U1 = pSrc16[(i3 * 2U) + 1U] >> 2U;
+
+    /* T0 = (yb + yd), T1 = (xb + xd) */
+    T0 = __SSAT(T0 + U0, 16U);
+    T1 = __SSAT(T1 + U1, 16U);
+
+    /*  writing the butterfly processed i0 sample */
+    /* xa' = xa + xb + xc + xd */
+    /* ya' = ya + yb + yc + yd */
+    pSrc16[i0 * 2U] = (R0 >> 1U) + (T0 >> 1U);
+    pSrc16[(i0 * 2U) + 1U] = (R1 >> 1U) + (T1 >> 1U);
+
+    /* R0 = (ya + yc) - (yb + yd), R1 = (xa + xc)- (xb + xd) */
+    R0 = __SSAT(R0 - T0, 16U);
+    R1 = __SSAT(R1 - T1, 16U);
+    /* co2 & si2 are read from Coefficient pointer */
+    Co2 = pCoef16[2U * ic * 2U];
+    Si2 = pCoef16[(2U * ic * 2U) + 1U];
+    /* xc' = (xa-xb+xc-xd)* co2 - (ya-yb+yc-yd)* (si2) */
+    out1 = (q15_t) ((Co2 * R0 - Si2 * R1) >> 16U);
+    /* yc' = (ya-yb+yc-yd)* co2 + (xa-xb+xc-xd)* (si2) */
+    out2 = (q15_t) ((Si2 * R0 + Co2 * R1) >> 16U);
+
+    /*  Reading i0+fftLen/4 */
+    /* input is down scale by 4 to avoid overflow */
+    /* T0 = yb, T1 = xb */
+    T0 = pSrc16[i1 * 2U] >> 2U;
+    T1 = pSrc16[(i1 * 2U) + 1U] >> 2U;
+
+    /* writing the butterfly processed i0 + fftLen/4 sample */
+    /* writing output(xc', yc') in little endian format */
+    pSrc16[i1 * 2U] = out1;
+    pSrc16[(i1 * 2U) + 1U] = out2;
+
+    /*  Butterfly calculations */
+    /* input is down scale by 4 to avoid overflow */
+    /* U0 = yd, U1 = xd) */
+    U0 = pSrc16[i3 * 2U] >> 2U;
+    U1 = pSrc16[(i3 * 2U) + 1U] >> 2U;
+
+    /* T0 = yb-yd, T1 = xb-xd) */
+    T0 = __SSAT(T0 - U0, 16U);
+    T1 = __SSAT(T1 - U1, 16U);
+    /* R0 = (ya-yc) - (xb- xd) , R1 = (xa-xc) + (yb-yd) */
+    R0 = (q15_t) __SSAT((q31_t) (S0 + T1), 16);
+    R1 = (q15_t) __SSAT((q31_t) (S1 - T0), 16);
+    /* S = (ya-yc) + (xb- xd), S1 = (xa-xc) - (yb-yd) */
+    S0 = (q15_t) __SSAT((q31_t) (S0 - T1), 16);
+    S1 = (q15_t) __SSAT((q31_t) (S1 + T0), 16);
+
+    /* co1 & si1 are read from Coefficient pointer */
+    Co1 = pCoef16[ic * 2U];
+    Si1 = pCoef16[(ic * 2U) + 1U];
+    /*  Butterfly process for the i0+fftLen/2 sample */
+    /* xb' = (xa-yb-xc+yd)* co1 - (ya+xb-yc-xd)* (si1) */
+    out1 = (q15_t) ((Co1 * S0 - Si1 * S1) >> 16U);
+    /* yb' = (ya+xb-yc-xd)* co1 + (xa-yb-xc+yd)* (si1) */
+    out2 = (q15_t) ((Si1 * S0 + Co1 * S1) >> 16U);
+    /* writing output(xb', yb') in little endian format */
+    pSrc16[i2 * 2U] = out1;
+    pSrc16[(i2 * 2U) + 1U] = out2;
+
+    /* Co3 & si3 are read from Coefficient pointer */
+    Co3 = pCoef16[3U * ic * 2U];
+    Si3 = pCoef16[(3U * ic * 2U) + 1U];
+    /*  Butterfly process for the i0+3fftLen/4 sample */
+    /* xd' = (xa+yb-xc-yd)* Co3 - (ya-xb-yc+xd)* (si3) */
+    out1 = (q15_t) ((Co3 * R0 - Si3 * R1) >> 16U);
+    /* yd' = (ya-xb-yc+xd)* Co3 + (xa+yb-xc-yd)* (si3) */
+    out2 = (q15_t) ((Si3 * R0 + Co3 * R1) >> 16U);
+    /* writing output(xd', yd') in little endian format */
+    pSrc16[i3 * 2U] = out1;
+    pSrc16[(i3 * 2U) + 1U] = out2;
+
+    /*  Twiddle coefficients index modifier */
+    ic = ic + twidCoefModifier;
+
+    /*  Updating input index */
+    i0 = i0 + 1U;
+
+  } while (--j);
+
+  /*  End of first stage process */
+
+  /* data is in 4.11(q11) format */
+
+
+  /*  Start of Middle stage process */
+
+  /*  Twiddle coefficients index modifier */
+  twidCoefModifier <<= 2U;
+
+  /*  Calculation of Middle stage */
+  for (k = fftLen / 4U; k > 4U; k >>= 2U)
+  {
+    /*  Initializations for the middle stage */
+    n1 = n2;
+    n2 >>= 2U;
+    ic = 0U;
+
+    for (j = 0U; j <= (n2 - 1U); j++)
+    {
+      /*  index calculation for the coefficients */
+      Co1 = pCoef16[ic * 2U];
+      Si1 = pCoef16[(ic * 2U) + 1U];
+      Co2 = pCoef16[2U * ic * 2U];
+      Si2 = pCoef16[2U * ic * 2U + 1U];
+      Co3 = pCoef16[3U * ic * 2U];
+      Si3 = pCoef16[(3U * ic * 2U) + 1U];
+
+      /*  Twiddle coefficients index modifier */
+      ic = ic + twidCoefModifier;
+
+      /*  Butterfly implementation */
+      for (i0 = j; i0 < fftLen; i0 += n1)
+      {
+        /*  index calculation for the input as, */
+        /*  pSrc16[i0 + 0], pSrc16[i0 + fftLen/4], pSrc16[i0 + fftLen/2], pSrc16[i0 + 3fftLen/4] */
+        i1 = i0 + n2;
+        i2 = i1 + n2;
+        i3 = i2 + n2;
+
+        /*  Reading i0, i0+fftLen/2 inputs */
+        /* Read ya (real), xa(imag) input */
+        T0 = pSrc16[i0 * 2U];
+        T1 = pSrc16[(i0 * 2U) + 1U];
+
+        /* Read yc (real), xc(imag) input */
+        S0 = pSrc16[i2 * 2U];
+        S1 = pSrc16[(i2 * 2U) + 1U];
+
+
+        /* R0 = (ya + yc), R1 = (xa + xc) */
+        R0 = __SSAT(T0 + S0, 16U);
+        R1 = __SSAT(T1 + S1, 16U);
+        /* S0 = (ya - yc), S1 = (xa - xc) */
+        S0 = __SSAT(T0 - S0, 16U);
+        S1 = __SSAT(T1 - S1, 16U);
+
+        /*  Reading i0+fftLen/4 , i0+3fftLen/4 inputs */
+        /* Read yb (real), xb(imag) input */
+        T0 = pSrc16[i1 * 2U];
+        T1 = pSrc16[(i1 * 2U) + 1U];
+
+        /* Read yd (real), xd(imag) input */
+        U0 = pSrc16[i3 * 2U];
+        U1 = pSrc16[(i3 * 2U) + 1U];
+
+        /* T0 = (yb + yd), T1 = (xb + xd) */
+        T0 = __SSAT(T0 + U0, 16U);
+        T1 = __SSAT(T1 + U1, 16U);
+
+        /*  writing the butterfly processed i0 sample */
+        /* xa' = xa + xb + xc + xd */
+        /* ya' = ya + yb + yc + yd */
+        pSrc16[i0 * 2U] = ((R0 >> 1U) + (T0 >> 1U)) >> 1U;
+        pSrc16[(i0 * 2U) + 1U] = ((R1 >> 1U) + (T1 >> 1U)) >> 1U;
+
+        /* R0 = (ya + yc) - (yb + yd), R1 = (xa + xc) - (xb + xd) */
+        R0 = (R0 >> 1U) - (T0 >> 1U);
+        R1 = (R1 >> 1U) - (T1 >> 1U);
+
+        /* (ya-yb+yc-yd)* (si2) - (xa-xb+xc-xd)* co2 */
+        out1 = (q15_t) ((Co2 * R0 - Si2 * R1) >> 16);
+        /* (ya-yb+yc-yd)* co2 + (xa-xb+xc-xd)* (si2) */
+        out2 = (q15_t) ((Si2 * R0 + Co2 * R1) >> 16);
+
+        /*  Reading i0+3fftLen/4 */
+        /* Read yb (real), xb(imag) input */
+        T0 = pSrc16[i1 * 2U];
+        T1 = pSrc16[(i1 * 2U) + 1U];
+
+        /*  writing the butterfly processed i0 + fftLen/4 sample */
+        /* xc' = (xa-xb+xc-xd)* co2 - (ya-yb+yc-yd)* (si2) */
+        /* yc' = (ya-yb+yc-yd)* co2 + (xa-xb+xc-xd)* (si2) */
+        pSrc16[i1 * 2U] = out1;
+        pSrc16[(i1 * 2U) + 1U] = out2;
+
+        /*  Butterfly calculations */
+        /* Read yd (real), xd(imag) input */
+        U0 = pSrc16[i3 * 2U];
+        U1 = pSrc16[(i3 * 2U) + 1U];
+
+        /* T0 = yb-yd, T1 = xb-xd) */
+        T0 = __SSAT(T0 - U0, 16U);
+        T1 = __SSAT(T1 - U1, 16U);
+
+        /* R0 = (ya-yc) - (xb- xd) , R1 = (xa-xc) + (yb-yd) */
+        R0 = (S0 >> 1U) + (T1 >> 1U);
+        R1 = (S1 >> 1U) - (T0 >> 1U);
+
+        /* S1 = (ya-yc) + (xb- xd), S1 = (xa-xc) - (yb-yd) */
+        S0 = (S0 >> 1U) - (T1 >> 1U);
+        S1 = (S1 >> 1U) + (T0 >> 1U);
+
+        /*  Butterfly process for the i0+fftLen/2 sample */
+        out1 = (q15_t) ((Co1 * S0 - Si1 * S1) >> 16U);
+        out2 = (q15_t) ((Si1 * S0 + Co1 * S1) >> 16U);
+        /* xb' = (xa-yb-xc+yd)* co1 - (ya+xb-yc-xd)* (si1) */
+        /* yb' = (ya+xb-yc-xd)* co1 + (xa-yb-xc+yd)* (si1) */
+        pSrc16[i2 * 2U] = out1;
+        pSrc16[(i2 * 2U) + 1U] = out2;
+
+        /*  Butterfly process for the i0+3fftLen/4 sample */
+        out1 = (q15_t) ((Co3 * R0 - Si3 * R1) >> 16U);
+
+        out2 = (q15_t) ((Si3 * R0 + Co3 * R1) >> 16U);
+        /* xd' = (xa+yb-xc-yd)* Co3 - (ya-xb-yc+xd)* (si3) */
+        /* yd' = (ya-xb-yc+xd)* Co3 + (xa+yb-xc-yd)* (si3) */
+        pSrc16[i3 * 2U] = out1;
+        pSrc16[(i3 * 2U) + 1U] = out2;
+
+
+      }
+    }
+    /*  Twiddle coefficients index modifier */
+    twidCoefModifier <<= 2U;
+  }
+  /*  End of Middle stages process */
+
+
+  /* data is in 10.6(q6) format for the 1024 point */
+  /* data is in 8.8(q8) format for the 256 point   */
+  /* data is in 6.10(q10) format for the 64 point  */
+  /* data is in 4.12(q12) format for the 16 point  */
+
+  /* start of last stage process */
+
+
+  /*  Initializations for the last stage */
+  n1 = n2;
+  n2 >>= 2U;
+
+  /*  Butterfly implementation */
+  for (i0 = 0U; i0 <= (fftLen - n1); i0 += n1)
+  {
+    /*  index calculation for the input as, */
+    /*  pSrc16[i0 + 0], pSrc16[i0 + fftLen/4], pSrc16[i0 + fftLen/2], pSrc16[i0 + 3fftLen/4] */
+    i1 = i0 + n2;
+    i2 = i1 + n2;
+    i3 = i2 + n2;
+
+    /*  Reading i0, i0+fftLen/2 inputs */
+    /* Read ya (real), xa(imag) input */
+    T0 = pSrc16[i0 * 2U];
+    T1 = pSrc16[(i0 * 2U) + 1U];
+    /* Read yc (real), xc(imag) input */
+    S0 = pSrc16[i2 * 2U];
+    S1 = pSrc16[(i2 * 2U) + 1U];
+
+    /* R0 = (ya + yc), R1 = (xa + xc) */
+    R0 = __SSAT(T0 + S0, 16U);
+    R1 = __SSAT(T1 + S1, 16U);
+    /* S0 = (ya - yc), S1 = (xa - xc) */
+    S0 = __SSAT(T0 - S0, 16U);
+    S1 = __SSAT(T1 - S1, 16U);
+
+    /*  Reading i0+fftLen/4 , i0+3fftLen/4 inputs */
+    /* Read yb (real), xb(imag) input */
+    T0 = pSrc16[i1 * 2U];
+    T1 = pSrc16[(i1 * 2U) + 1U];
+    /* Read yd (real), xd(imag) input */
+    U0 = pSrc16[i3 * 2U];
+    U1 = pSrc16[(i3 * 2U) + 1U];
+
+    /* T0 = (yb + yd), T1 = (xb + xd) */
+    T0 = __SSAT(T0 + U0, 16U);
+    T1 = __SSAT(T1 + U1, 16U);
+
+    /*  writing the butterfly processed i0 sample */
+    /* xa' = xa + xb + xc + xd */
+    /* ya' = ya + yb + yc + yd */
+    pSrc16[i0 * 2U] = (R0 >> 1U) + (T0 >> 1U);
+    pSrc16[(i0 * 2U) + 1U] = (R1 >> 1U) + (T1 >> 1U);
+
+    /* R0 = (ya + yc) - (yb + yd), R1 = (xa + xc) - (xb + xd) */
+    R0 = (R0 >> 1U) - (T0 >> 1U);
+    R1 = (R1 >> 1U) - (T1 >> 1U);
+
+    /* Read yb (real), xb(imag) input */
+    T0 = pSrc16[i1 * 2U];
+    T1 = pSrc16[(i1 * 2U) + 1U];
+
+    /*  writing the butterfly processed i0 + fftLen/4 sample */
+    /* xc' = (xa-xb+xc-xd) */
+    /* yc' = (ya-yb+yc-yd) */
+    pSrc16[i1 * 2U] = R0;
+    pSrc16[(i1 * 2U) + 1U] = R1;
+
+    /* Read yd (real), xd(imag) input */
+    U0 = pSrc16[i3 * 2U];
+    U1 = pSrc16[(i3 * 2U) + 1U];
+    /* T0 = (yb - yd), T1 = (xb - xd) */
+    T0 = __SSAT(T0 - U0, 16U);
+    T1 = __SSAT(T1 - U1, 16U);
+
+    /*  writing the butterfly processed i0 + fftLen/2 sample */
+    /* xb' = (xa-yb-xc+yd) */
+    /* yb' = (ya+xb-yc-xd) */
+    pSrc16[i2 * 2U] = (S0 >> 1U) - (T1 >> 1U);
+    pSrc16[(i2 * 2U) + 1U] = (S1 >> 1U) + (T0 >> 1U);
+
+
+    /*  writing the butterfly processed i0 + 3fftLen/4 sample */
+    /* xd' = (xa+yb-xc-yd) */
+    /* yd' = (ya-xb-yc+xd) */
+    pSrc16[i3 * 2U] = (S0 >> 1U) + (T1 >> 1U);
+    pSrc16[(i3 * 2U) + 1U] = (S1 >> 1U) - (T0 >> 1U);
+  }
+  /* end of last stage  process */
+
+  /* output is in 11.5(q5) format for the 1024 point */
+  /* output is in 9.7(q7) format for the 256 point   */
+  /* output is in 7.9(q9) format for the 64 point  */
+  /* output is in 5.11(q11) format for the 16 point  */
+
+#endif /* #if defined (ARM_MATH_DSP) */
+
+}

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/TransformFunctions/arm_rfft_init_q15.c
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/TransformFunctions/arm_rfft_init_q15.c	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,2229 @@
+/* ----------------------------------------------------------------------
+ * Project:      CMSIS DSP Library
+ * Title:        arm_rfft_init_q15.c
+ * Description:  RFFT & RIFFT Q15 initialisation function
+ *
+ * $Date:        27. January 2017
+ * $Revision:    V.1.5.1
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+/*
+ * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "arm_math.h"
+#include "arm_common_tables.h"
+#include "arm_const_structs.h"
+
+/**
+* @ingroup RealFFT
+*/
+
+/**
+ * @addtogroup RealFFT_Table Real FFT Tables
+* @{
+*/
+
+/**
+* \par
+* Generation fixed-point realCoefAQ15 array in Q15 format:
+* \par
+* n = 4096
+* <pre>for (i = 0; i < n; i++)
+*  {
+*    pATable[2 * i] = 0.5 * (1.0 - sin (2 * PI / (double) (2 * n) * (double) i));
+*    pATable[2 * i + 1] = 0.5 * (-1.0 * cos (2 * PI / (double) (2 * n) * (double) i));
+*  } </pre>
+* \par
+* Convert to fixed point Q15 format
+*       round(pATable[i] * pow(2, 15))
+*/
+const q15_t ALIGN4 realCoefAQ15[8192] = {
+    (q15_t)0x4000, (q15_t)0xc000, (q15_t)0x3ff3, (q15_t)0xc000, (q15_t)0x3fe7, (q15_t)0xc000, (q15_t)0x3fda, (q15_t)0xc000,
+    (q15_t)0x3fce, (q15_t)0xc000, (q15_t)0x3fc1, (q15_t)0xc000, (q15_t)0x3fb5, (q15_t)0xc000, (q15_t)0x3fa8, (q15_t)0xc000,
+    (q15_t)0x3f9b, (q15_t)0xc000, (q15_t)0x3f8f, (q15_t)0xc000, (q15_t)0x3f82, (q15_t)0xc000, (q15_t)0x3f76, (q15_t)0xc001,
+    (q15_t)0x3f69, (q15_t)0xc001, (q15_t)0x3f5d, (q15_t)0xc001, (q15_t)0x3f50, (q15_t)0xc001, (q15_t)0x3f44, (q15_t)0xc001,
+    (q15_t)0x3f37, (q15_t)0xc001, (q15_t)0x3f2a, (q15_t)0xc001, (q15_t)0x3f1e, (q15_t)0xc002, (q15_t)0x3f11, (q15_t)0xc002,
+    (q15_t)0x3f05, (q15_t)0xc002, (q15_t)0x3ef8, (q15_t)0xc002, (q15_t)0x3eec, (q15_t)0xc002, (q15_t)0x3edf, (q15_t)0xc003,
+    (q15_t)0x3ed2, (q15_t)0xc003, (q15_t)0x3ec6, (q15_t)0xc003, (q15_t)0x3eb9, (q15_t)0xc003, (q15_t)0x3ead, (q15_t)0xc004,
+    (q15_t)0x3ea0, (q15_t)0xc004, (q15_t)0x3e94, (q15_t)0xc004, (q15_t)0x3e87, (q15_t)0xc004, (q15_t)0x3e7a, (q15_t)0xc005,
+    (q15_t)0x3e6e, (q15_t)0xc005, (q15_t)0x3e61, (q15_t)0xc005, (q15_t)0x3e55, (q15_t)0xc006, (q15_t)0x3e48, (q15_t)0xc006,
+    (q15_t)0x3e3c, (q15_t)0xc006, (q15_t)0x3e2f, (q15_t)0xc007, (q15_t)0x3e23, (q15_t)0xc007, (q15_t)0x3e16, (q15_t)0xc007,
+    (q15_t)0x3e09, (q15_t)0xc008, (q15_t)0x3dfd, (q15_t)0xc008, (q15_t)0x3df0, (q15_t)0xc009, (q15_t)0x3de4, (q15_t)0xc009,
+    (q15_t)0x3dd7, (q15_t)0xc009, (q15_t)0x3dcb, (q15_t)0xc00a, (q15_t)0x3dbe, (q15_t)0xc00a, (q15_t)0x3db2, (q15_t)0xc00b,
+    (q15_t)0x3da5, (q15_t)0xc00b, (q15_t)0x3d98, (q15_t)0xc00c, (q15_t)0x3d8c, (q15_t)0xc00c, (q15_t)0x3d7f, (q15_t)0xc00d,
+    (q15_t)0x3d73, (q15_t)0xc00d, (q15_t)0x3d66, (q15_t)0xc00e, (q15_t)0x3d5a, (q15_t)0xc00e, (q15_t)0x3d4d, (q15_t)0xc00f,
+    (q15_t)0x3d40, (q15_t)0xc00f, (q15_t)0x3d34, (q15_t)0xc010, (q15_t)0x3d27, (q15_t)0xc010, (q15_t)0x3d1b, (q15_t)0xc011,
+    (q15_t)0x3d0e, (q15_t)0xc011, (q15_t)0x3d02, (q15_t)0xc012, (q15_t)0x3cf5, (q15_t)0xc013, (q15_t)0x3ce9, (q15_t)0xc013,
+    (q15_t)0x3cdc, (q15_t)0xc014, (q15_t)0x3cd0, (q15_t)0xc014, (q15_t)0x3cc3, (q15_t)0xc015, (q15_t)0x3cb6, (q15_t)0xc016,
+    (q15_t)0x3caa, (q15_t)0xc016, (q15_t)0x3c9d, (q15_t)0xc017, (q15_t)0x3c91, (q15_t)0xc018, (q15_t)0x3c84, (q15_t)0xc018,
+    (q15_t)0x3c78, (q15_t)0xc019, (q15_t)0x3c6b, (q15_t)0xc01a, (q15_t)0x3c5f, (q15_t)0xc01a, (q15_t)0x3c52, (q15_t)0xc01b,
+    (q15_t)0x3c45, (q15_t)0xc01c, (q15_t)0x3c39, (q15_t)0xc01d, (q15_t)0x3c2c, (q15_t)0xc01d, (q15_t)0x3c20, (q15_t)0xc01e,
+    (q15_t)0x3c13, (q15_t)0xc01f, (q15_t)0x3c07, (q15_t)0xc020, (q15_t)0x3bfa, (q15_t)0xc020, (q15_t)0x3bee, (q15_t)0xc021,
+    (q15_t)0x3be1, (q15_t)0xc022, (q15_t)0x3bd5, (q15_t)0xc023, (q15_t)0x3bc8, (q15_t)0xc024, (q15_t)0x3bbc, (q15_t)0xc024,
+    (q15_t)0x3baf, (q15_t)0xc025, (q15_t)0x3ba2, (q15_t)0xc026, (q15_t)0x3b96, (q15_t)0xc027, (q15_t)0x3b89, (q15_t)0xc028,
+    (q15_t)0x3b7d, (q15_t)0xc029, (q15_t)0x3b70, (q15_t)0xc02a, (q15_t)0x3b64, (q15_t)0xc02b, (q15_t)0x3b57, (q15_t)0xc02b,
+    (q15_t)0x3b4b, (q15_t)0xc02c, (q15_t)0x3b3e, (q15_t)0xc02d, (q15_t)0x3b32, (q15_t)0xc02e, (q15_t)0x3b25, (q15_t)0xc02f,
+    (q15_t)0x3b19, (q15_t)0xc030, (q15_t)0x3b0c, (q15_t)0xc031, (q15_t)0x3b00, (q15_t)0xc032, (q15_t)0x3af3, (q15_t)0xc033,
+    (q15_t)0x3ae6, (q15_t)0xc034, (q15_t)0x3ada, (q15_t)0xc035, (q15_t)0x3acd, (q15_t)0xc036, (q15_t)0x3ac1, (q15_t)0xc037,
+    (q15_t)0x3ab4, (q15_t)0xc038, (q15_t)0x3aa8, (q15_t)0xc039, (q15_t)0x3a9b, (q15_t)0xc03a, (q15_t)0x3a8f, (q15_t)0xc03b,
+    (q15_t)0x3a82, (q15_t)0xc03c, (q15_t)0x3a76, (q15_t)0xc03d, (q15_t)0x3a69, (q15_t)0xc03f, (q15_t)0x3a5d, (q15_t)0xc040,
+    (q15_t)0x3a50, (q15_t)0xc041, (q15_t)0x3a44, (q15_t)0xc042, (q15_t)0x3a37, (q15_t)0xc043, (q15_t)0x3a2b, (q15_t)0xc044,
+    (q15_t)0x3a1e, (q15_t)0xc045, (q15_t)0x3a12, (q15_t)0xc047, (q15_t)0x3a05, (q15_t)0xc048, (q15_t)0x39f9, (q15_t)0xc049,
+    (q15_t)0x39ec, (q15_t)0xc04a, (q15_t)0x39e0, (q15_t)0xc04b, (q15_t)0x39d3, (q15_t)0xc04c, (q15_t)0x39c7, (q15_t)0xc04e,
+    (q15_t)0x39ba, (q15_t)0xc04f, (q15_t)0x39ae, (q15_t)0xc050, (q15_t)0x39a1, (q15_t)0xc051, (q15_t)0x3995, (q15_t)0xc053,
+    (q15_t)0x3988, (q15_t)0xc054, (q15_t)0x397c, (q15_t)0xc055, (q15_t)0x396f, (q15_t)0xc056, (q15_t)0x3963, (q15_t)0xc058,
+    (q15_t)0x3956, (q15_t)0xc059, (q15_t)0x394a, (q15_t)0xc05a, (q15_t)0x393d, (q15_t)0xc05c, (q15_t)0x3931, (q15_t)0xc05d,
+    (q15_t)0x3924, (q15_t)0xc05e, (q15_t)0x3918, (q15_t)0xc060, (q15_t)0x390b, (q15_t)0xc061, (q15_t)0x38ff, (q15_t)0xc062,
+    (q15_t)0x38f2, (q15_t)0xc064, (q15_t)0x38e6, (q15_t)0xc065, (q15_t)0x38d9, (q15_t)0xc067, (q15_t)0x38cd, (q15_t)0xc068,
+    (q15_t)0x38c0, (q15_t)0xc069, (q15_t)0x38b4, (q15_t)0xc06b, (q15_t)0x38a7, (q15_t)0xc06c, (q15_t)0x389b, (q15_t)0xc06e,
+    (q15_t)0x388e, (q15_t)0xc06f, (q15_t)0x3882, (q15_t)0xc071, (q15_t)0x3875, (q15_t)0xc072, (q15_t)0x3869, (q15_t)0xc074,
+    (q15_t)0x385c, (q15_t)0xc075, (q15_t)0x3850, (q15_t)0xc077, (q15_t)0x3843, (q15_t)0xc078, (q15_t)0x3837, (q15_t)0xc07a,
+    (q15_t)0x382a, (q15_t)0xc07b, (q15_t)0x381e, (q15_t)0xc07d, (q15_t)0x3811, (q15_t)0xc07e, (q15_t)0x3805, (q15_t)0xc080,
+    (q15_t)0x37f9, (q15_t)0xc081, (q15_t)0x37ec, (q15_t)0xc083, (q15_t)0x37e0, (q15_t)0xc085, (q15_t)0x37d3, (q15_t)0xc086,
+    (q15_t)0x37c7, (q15_t)0xc088, (q15_t)0x37ba, (q15_t)0xc089, (q15_t)0x37ae, (q15_t)0xc08b, (q15_t)0x37a1, (q15_t)0xc08d,
+    (q15_t)0x3795, (q15_t)0xc08e, (q15_t)0x3788, (q15_t)0xc090, (q15_t)0x377c, (q15_t)0xc092, (q15_t)0x376f, (q15_t)0xc093,
+    (q15_t)0x3763, (q15_t)0xc095, (q15_t)0x3757, (q15_t)0xc097, (q15_t)0x374a, (q15_t)0xc098, (q15_t)0x373e, (q15_t)0xc09a,
+    (q15_t)0x3731, (q15_t)0xc09c, (q15_t)0x3725, (q15_t)0xc09e, (q15_t)0x3718, (q15_t)0xc09f, (q15_t)0x370c, (q15_t)0xc0a1,
+    (q15_t)0x36ff, (q15_t)0xc0a3, (q15_t)0x36f3, (q15_t)0xc0a5, (q15_t)0x36e7, (q15_t)0xc0a6, (q15_t)0x36da, (q15_t)0xc0a8,
+    (q15_t)0x36ce, (q15_t)0xc0aa, (q15_t)0x36c1, (q15_t)0xc0ac, (q15_t)0x36b5, (q15_t)0xc0ae, (q15_t)0x36a8, (q15_t)0xc0af,
+    (q15_t)0x369c, (q15_t)0xc0b1, (q15_t)0x3690, (q15_t)0xc0b3, (q15_t)0x3683, (q15_t)0xc0b5, (q15_t)0x3677, (q15_t)0xc0b7,
+    (q15_t)0x366a, (q15_t)0xc0b9, (q15_t)0x365e, (q15_t)0xc0bb, (q15_t)0x3651, (q15_t)0xc0bd, (q15_t)0x3645, (q15_t)0xc0be,
+    (q15_t)0x3639, (q15_t)0xc0c0, (q15_t)0x362c, (q15_t)0xc0c2, (q15_t)0x3620, (q15_t)0xc0c4, (q15_t)0x3613, (q15_t)0xc0c6,
+    (q15_t)0x3607, (q15_t)0xc0c8, (q15_t)0x35fa, (q15_t)0xc0ca, (q15_t)0x35ee, (q15_t)0xc0cc, (q15_t)0x35e2, (q15_t)0xc0ce,
+    (q15_t)0x35d5, (q15_t)0xc0d0, (q15_t)0x35c9, (q15_t)0xc0d2, (q15_t)0x35bc, (q15_t)0xc0d4, (q15_t)0x35b0, (q15_t)0xc0d6,
+    (q15_t)0x35a4, (q15_t)0xc0d8, (q15_t)0x3597, (q15_t)0xc0da, (q15_t)0x358b, (q15_t)0xc0dc, (q15_t)0x357e, (q15_t)0xc0de,
+    (q15_t)0x3572, (q15_t)0xc0e0, (q15_t)0x3566, (q15_t)0xc0e2, (q15_t)0x3559, (q15_t)0xc0e4, (q15_t)0x354d, (q15_t)0xc0e7,
+    (q15_t)0x3540, (q15_t)0xc0e9, (q15_t)0x3534, (q15_t)0xc0eb, (q15_t)0x3528, (q15_t)0xc0ed, (q15_t)0x351b, (q15_t)0xc0ef,
+    (q15_t)0x350f, (q15_t)0xc0f1, (q15_t)0x3503, (q15_t)0xc0f3, (q15_t)0x34f6, (q15_t)0xc0f6, (q15_t)0x34ea, (q15_t)0xc0f8,
+    (q15_t)0x34dd, (q15_t)0xc0fa, (q15_t)0x34d1, (q15_t)0xc0fc, (q15_t)0x34c5, (q15_t)0xc0fe, (q15_t)0x34b8, (q15_t)0xc100,
+    (q15_t)0x34ac, (q15_t)0xc103, (q15_t)0x34a0, (q15_t)0xc105, (q15_t)0x3493, (q15_t)0xc107, (q15_t)0x3487, (q15_t)0xc109,
+    (q15_t)0x347b, (q15_t)0xc10c, (q15_t)0x346e, (q15_t)0xc10e, (q15_t)0x3462, (q15_t)0xc110, (q15_t)0x3455, (q15_t)0xc113,
+    (q15_t)0x3449, (q15_t)0xc115, (q15_t)0x343d, (q15_t)0xc117, (q15_t)0x3430, (q15_t)0xc119, (q15_t)0x3424, (q15_t)0xc11c,
+    (q15_t)0x3418, (q15_t)0xc11e, (q15_t)0x340b, (q15_t)0xc120, (q15_t)0x33ff, (q15_t)0xc123, (q15_t)0x33f3, (q15_t)0xc125,
+    (q15_t)0x33e6, (q15_t)0xc128, (q15_t)0x33da, (q15_t)0xc12a, (q15_t)0x33ce, (q15_t)0xc12c, (q15_t)0x33c1, (q15_t)0xc12f,
+    (q15_t)0x33b5, (q15_t)0xc131, (q15_t)0x33a9, (q15_t)0xc134, (q15_t)0x339c, (q15_t)0xc136, (q15_t)0x3390, (q15_t)0xc138,
+    (q15_t)0x3384, (q15_t)0xc13b, (q15_t)0x3377, (q15_t)0xc13d, (q15_t)0x336b, (q15_t)0xc140, (q15_t)0x335f, (q15_t)0xc142,
+    (q15_t)0x3352, (q15_t)0xc145, (q15_t)0x3346, (q15_t)0xc147, (q15_t)0x333a, (q15_t)0xc14a, (q15_t)0x332d, (q15_t)0xc14c,
+    (q15_t)0x3321, (q15_t)0xc14f, (q15_t)0x3315, (q15_t)0xc151, (q15_t)0x3308, (q15_t)0xc154, (q15_t)0x32fc, (q15_t)0xc156,
+    (q15_t)0x32f0, (q15_t)0xc159, (q15_t)0x32e4, (q15_t)0xc15b, (q15_t)0x32d7, (q15_t)0xc15e, (q15_t)0x32cb, (q15_t)0xc161,
+    (q15_t)0x32bf, (q15_t)0xc163, (q15_t)0x32b2, (q15_t)0xc166, (q15_t)0x32a6, (q15_t)0xc168, (q15_t)0x329a, (q15_t)0xc16b,
+    (q15_t)0x328e, (q15_t)0xc16e, (q15_t)0x3281, (q15_t)0xc170, (q15_t)0x3275, (q15_t)0xc173, (q15_t)0x3269, (q15_t)0xc176,
+    (q15_t)0x325c, (q15_t)0xc178, (q15_t)0x3250, (q15_t)0xc17b, (q15_t)0x3244, (q15_t)0xc17e, (q15_t)0x3238, (q15_t)0xc180,
+    (q15_t)0x322b, (q15_t)0xc183, (q15_t)0x321f, (q15_t)0xc186, (q15_t)0x3213, (q15_t)0xc189, (q15_t)0x3207, (q15_t)0xc18b,
+    (q15_t)0x31fa, (q15_t)0xc18e, (q15_t)0x31ee, (q15_t)0xc191, (q15_t)0x31e2, (q15_t)0xc194, (q15_t)0x31d5, (q15_t)0xc196,
+    (q15_t)0x31c9, (q15_t)0xc199, (q15_t)0x31bd, (q15_t)0xc19c, (q15_t)0x31b1, (q15_t)0xc19f, (q15_t)0x31a4, (q15_t)0xc1a2,
+    (q15_t)0x3198, (q15_t)0xc1a4, (q15_t)0x318c, (q15_t)0xc1a7, (q15_t)0x3180, (q15_t)0xc1aa, (q15_t)0x3174, (q15_t)0xc1ad,
+    (q15_t)0x3167, (q15_t)0xc1b0, (q15_t)0x315b, (q15_t)0xc1b3, (q15_t)0x314f, (q15_t)0xc1b6, (q15_t)0x3143, (q15_t)0xc1b8,
+    (q15_t)0x3136, (q15_t)0xc1bb, (q15_t)0x312a, (q15_t)0xc1be, (q15_t)0x311e, (q15_t)0xc1c1, (q15_t)0x3112, (q15_t)0xc1c4,
+    (q15_t)0x3105, (q15_t)0xc1c7, (q15_t)0x30f9, (q15_t)0xc1ca, (q15_t)0x30ed, (q15_t)0xc1cd, (q15_t)0x30e1, (q15_t)0xc1d0,
+    (q15_t)0x30d5, (q15_t)0xc1d3, (q15_t)0x30c8, (q15_t)0xc1d6, (q15_t)0x30bc, (q15_t)0xc1d9, (q15_t)0x30b0, (q15_t)0xc1dc,
+    (q15_t)0x30a4, (q15_t)0xc1df, (q15_t)0x3098, (q15_t)0xc1e2, (q15_t)0x308b, (q15_t)0xc1e5, (q15_t)0x307f, (q15_t)0xc1e8,
+    (q15_t)0x3073, (q15_t)0xc1eb, (q15_t)0x3067, (q15_t)0xc1ee, (q15_t)0x305b, (q15_t)0xc1f1, (q15_t)0x304e, (q15_t)0xc1f4,
+    (q15_t)0x3042, (q15_t)0xc1f7, (q15_t)0x3036, (q15_t)0xc1fa, (q15_t)0x302a, (q15_t)0xc1fd, (q15_t)0x301e, (q15_t)0xc201,
+    (q15_t)0x3012, (q15_t)0xc204, (q15_t)0x3005, (q15_t)0xc207, (q15_t)0x2ff9, (q15_t)0xc20a, (q15_t)0x2fed, (q15_t)0xc20d,
+    (q15_t)0x2fe1, (q15_t)0xc210, (q15_t)0x2fd5, (q15_t)0xc213, (q15_t)0x2fc9, (q15_t)0xc217, (q15_t)0x2fbc, (q15_t)0xc21a,
+    (q15_t)0x2fb0, (q15_t)0xc21d, (q15_t)0x2fa4, (q15_t)0xc220, (q15_t)0x2f98, (q15_t)0xc223, (q15_t)0x2f8c, (q15_t)0xc227,
+    (q15_t)0x2f80, (q15_t)0xc22a, (q15_t)0x2f74, (q15_t)0xc22d, (q15_t)0x2f67, (q15_t)0xc230, (q15_t)0x2f5b, (q15_t)0xc234,
+    (q15_t)0x2f4f, (q15_t)0xc237, (q15_t)0x2f43, (q15_t)0xc23a, (q15_t)0x2f37, (q15_t)0xc23e, (q15_t)0x2f2b, (q15_t)0xc241,
+    (q15_t)0x2f1f, (q15_t)0xc244, (q15_t)0x2f13, (q15_t)0xc247, (q15_t)0x2f06, (q15_t)0xc24b, (q15_t)0x2efa, (q15_t)0xc24e,
+    (q15_t)0x2eee, (q15_t)0xc251, (q15_t)0x2ee2, (q15_t)0xc255, (q15_t)0x2ed6, (q15_t)0xc258, (q15_t)0x2eca, (q15_t)0xc25c,
+    (q15_t)0x2ebe, (q15_t)0xc25f, (q15_t)0x2eb2, (q15_t)0xc262, (q15_t)0x2ea6, (q15_t)0xc266, (q15_t)0x2e99, (q15_t)0xc269,
+    (q15_t)0x2e8d, (q15_t)0xc26d, (q15_t)0x2e81, (q15_t)0xc270, (q15_t)0x2e75, (q15_t)0xc273, (q15_t)0x2e69, (q15_t)0xc277,
+    (q15_t)0x2e5d, (q15_t)0xc27a, (q15_t)0x2e51, (q15_t)0xc27e, (q15_t)0x2e45, (q15_t)0xc281, (q15_t)0x2e39, (q15_t)0xc285,
+    (q15_t)0x2e2d, (q15_t)0xc288, (q15_t)0x2e21, (q15_t)0xc28c, (q15_t)0x2e15, (q15_t)0xc28f, (q15_t)0x2e09, (q15_t)0xc293,
+    (q15_t)0x2dfc, (q15_t)0xc296, (q15_t)0x2df0, (q15_t)0xc29a, (q15_t)0x2de4, (q15_t)0xc29d, (q15_t)0x2dd8, (q15_t)0xc2a1,
+    (q15_t)0x2dcc, (q15_t)0xc2a5, (q15_t)0x2dc0, (q15_t)0xc2a8, (q15_t)0x2db4, (q15_t)0xc2ac, (q15_t)0x2da8, (q15_t)0xc2af,
+    (q15_t)0x2d9c, (q15_t)0xc2b3, (q15_t)0x2d90, (q15_t)0xc2b7, (q15_t)0x2d84, (q15_t)0xc2ba, (q15_t)0x2d78, (q15_t)0xc2be,
+    (q15_t)0x2d6c, (q15_t)0xc2c1, (q15_t)0x2d60, (q15_t)0xc2c5, (q15_t)0x2d54, (q15_t)0xc2c9, (q15_t)0x2d48, (q15_t)0xc2cc,
+    (q15_t)0x2d3c, (q15_t)0xc2d0, (q15_t)0x2d30, (q15_t)0xc2d4, (q15_t)0x2d24, (q15_t)0xc2d8, (q15_t)0x2d18, (q15_t)0xc2db,
+    (q15_t)0x2d0c, (q15_t)0xc2df, (q15_t)0x2d00, (q15_t)0xc2e3, (q15_t)0x2cf4, (q15_t)0xc2e6, (q15_t)0x2ce8, (q15_t)0xc2ea,
+    (q15_t)0x2cdc, (q15_t)0xc2ee, (q15_t)0x2cd0, (q15_t)0xc2f2, (q15_t)0x2cc4, (q15_t)0xc2f5, (q15_t)0x2cb8, (q15_t)0xc2f9,
+    (q15_t)0x2cac, (q15_t)0xc2fd, (q15_t)0x2ca0, (q15_t)0xc301, (q15_t)0x2c94, (q15_t)0xc305, (q15_t)0x2c88, (q15_t)0xc308,
+    (q15_t)0x2c7c, (q15_t)0xc30c, (q15_t)0x2c70, (q15_t)0xc310, (q15_t)0x2c64, (q15_t)0xc314, (q15_t)0x2c58, (q15_t)0xc318,
+    (q15_t)0x2c4c, (q15_t)0xc31c, (q15_t)0x2c40, (q15_t)0xc320, (q15_t)0x2c34, (q15_t)0xc323, (q15_t)0x2c28, (q15_t)0xc327,
+    (q15_t)0x2c1c, (q15_t)0xc32b, (q15_t)0x2c10, (q15_t)0xc32f, (q15_t)0x2c05, (q15_t)0xc333, (q15_t)0x2bf9, (q15_t)0xc337,
+    (q15_t)0x2bed, (q15_t)0xc33b, (q15_t)0x2be1, (q15_t)0xc33f, (q15_t)0x2bd5, (q15_t)0xc343, (q15_t)0x2bc9, (q15_t)0xc347,
+    (q15_t)0x2bbd, (q15_t)0xc34b, (q15_t)0x2bb1, (q15_t)0xc34f, (q15_t)0x2ba5, (q15_t)0xc353, (q15_t)0x2b99, (q15_t)0xc357,
+    (q15_t)0x2b8d, (q15_t)0xc35b, (q15_t)0x2b81, (q15_t)0xc35f, (q15_t)0x2b75, (q15_t)0xc363, (q15_t)0x2b6a, (q15_t)0xc367,
+    (q15_t)0x2b5e, (q15_t)0xc36b, (q15_t)0x2b52, (q15_t)0xc36f, (q15_t)0x2b46, (q15_t)0xc373, (q15_t)0x2b3a, (q15_t)0xc377,
+    (q15_t)0x2b2e, (q15_t)0xc37b, (q15_t)0x2b22, (q15_t)0xc37f, (q15_t)0x2b16, (q15_t)0xc383, (q15_t)0x2b0a, (q15_t)0xc387,
+    (q15_t)0x2aff, (q15_t)0xc38c, (q15_t)0x2af3, (q15_t)0xc390, (q15_t)0x2ae7, (q15_t)0xc394, (q15_t)0x2adb, (q15_t)0xc398,
+    (q15_t)0x2acf, (q15_t)0xc39c, (q15_t)0x2ac3, (q15_t)0xc3a0, (q15_t)0x2ab7, (q15_t)0xc3a5, (q15_t)0x2aac, (q15_t)0xc3a9,
+    (q15_t)0x2aa0, (q15_t)0xc3ad, (q15_t)0x2a94, (q15_t)0xc3b1, (q15_t)0x2a88, (q15_t)0xc3b5, (q15_t)0x2a7c, (q15_t)0xc3ba,
+    (q15_t)0x2a70, (q15_t)0xc3be, (q15_t)0x2a65, (q15_t)0xc3c2, (q15_t)0x2a59, (q15_t)0xc3c6, (q15_t)0x2a4d, (q15_t)0xc3ca,
+    (q15_t)0x2a41, (q15_t)0xc3cf, (q15_t)0x2a35, (q15_t)0xc3d3, (q15_t)0x2a29, (q15_t)0xc3d7, (q15_t)0x2a1e, (q15_t)0xc3dc,
+    (q15_t)0x2a12, (q15_t)0xc3e0, (q15_t)0x2a06, (q15_t)0xc3e4, (q15_t)0x29fa, (q15_t)0xc3e9, (q15_t)0x29ee, (q15_t)0xc3ed,
+    (q15_t)0x29e3, (q15_t)0xc3f1, (q15_t)0x29d7, (q15_t)0xc3f6, (q15_t)0x29cb, (q15_t)0xc3fa, (q15_t)0x29bf, (q15_t)0xc3fe,
+    (q15_t)0x29b4, (q15_t)0xc403, (q15_t)0x29a8, (q15_t)0xc407, (q15_t)0x299c, (q15_t)0xc40b, (q15_t)0x2990, (q15_t)0xc410,
+    (q15_t)0x2984, (q15_t)0xc414, (q15_t)0x2979, (q15_t)0xc419, (q15_t)0x296d, (q15_t)0xc41d, (q15_t)0x2961, (q15_t)0xc422,
+    (q15_t)0x2955, (q15_t)0xc426, (q15_t)0x294a, (q15_t)0xc42a, (q15_t)0x293e, (q15_t)0xc42f, (q15_t)0x2932, (q15_t)0xc433,
+    (q15_t)0x2926, (q15_t)0xc438, (q15_t)0x291b, (q15_t)0xc43c, (q15_t)0x290f, (q15_t)0xc441, (q15_t)0x2903, (q15_t)0xc445,
+    (q15_t)0x28f7, (q15_t)0xc44a, (q15_t)0x28ec, (q15_t)0xc44e, (q15_t)0x28e0, (q15_t)0xc453, (q15_t)0x28d4, (q15_t)0xc457,
+    (q15_t)0x28c9, (q15_t)0xc45c, (q15_t)0x28bd, (q15_t)0xc461, (q15_t)0x28b1, (q15_t)0xc465, (q15_t)0x28a5, (q15_t)0xc46a,
+    (q15_t)0x289a, (q15_t)0xc46e, (q15_t)0x288e, (q15_t)0xc473, (q15_t)0x2882, (q15_t)0xc478, (q15_t)0x2877, (q15_t)0xc47c,
+    (q15_t)0x286b, (q15_t)0xc481, (q15_t)0x285f, (q15_t)0xc485, (q15_t)0x2854, (q15_t)0xc48a, (q15_t)0x2848, (q15_t)0xc48f,
+    (q15_t)0x283c, (q15_t)0xc493, (q15_t)0x2831, (q15_t)0xc498, (q15_t)0x2825, (q15_t)0xc49d, (q15_t)0x2819, (q15_t)0xc4a1,
+    (q15_t)0x280e, (q15_t)0xc4a6, (q15_t)0x2802, (q15_t)0xc4ab, (q15_t)0x27f6, (q15_t)0xc4b0, (q15_t)0x27eb, (q15_t)0xc4b4,
+    (q15_t)0x27df, (q15_t)0xc4b9, (q15_t)0x27d3, (q15_t)0xc4be, (q15_t)0x27c8, (q15_t)0xc4c2, (q15_t)0x27bc, (q15_t)0xc4c7,
+    (q15_t)0x27b1, (q15_t)0xc4cc, (q15_t)0x27a5, (q15_t)0xc4d1, (q15_t)0x2799, (q15_t)0xc4d6, (q15_t)0x278e, (q15_t)0xc4da,
+    (q15_t)0x2782, (q15_t)0xc4df, (q15_t)0x2777, (q15_t)0xc4e4, (q15_t)0x276b, (q15_t)0xc4e9, (q15_t)0x275f, (q15_t)0xc4ee,
+    (q15_t)0x2754, (q15_t)0xc4f2, (q15_t)0x2748, (q15_t)0xc4f7, (q15_t)0x273d, (q15_t)0xc4fc, (q15_t)0x2731, (q15_t)0xc501,
+    (q15_t)0x2725, (q15_t)0xc506, (q15_t)0x271a, (q15_t)0xc50b, (q15_t)0x270e, (q15_t)0xc510, (q15_t)0x2703, (q15_t)0xc515,
+    (q15_t)0x26f7, (q15_t)0xc51a, (q15_t)0x26ec, (q15_t)0xc51e, (q15_t)0x26e0, (q15_t)0xc523, (q15_t)0x26d4, (q15_t)0xc528,
+    (q15_t)0x26c9, (q15_t)0xc52d, (q15_t)0x26bd, (q15_t)0xc532, (q15_t)0x26b2, (q15_t)0xc537, (q15_t)0x26a6, (q15_t)0xc53c,
+    (q15_t)0x269b, (q15_t)0xc541, (q15_t)0x268f, (q15_t)0xc546, (q15_t)0x2684, (q15_t)0xc54b, (q15_t)0x2678, (q15_t)0xc550,
+    (q15_t)0x266d, (q15_t)0xc555, (q15_t)0x2661, (q15_t)0xc55a, (q15_t)0x2656, (q15_t)0xc55f, (q15_t)0x264a, (q15_t)0xc564,
+    (q15_t)0x263f, (q15_t)0xc569, (q15_t)0x2633, (q15_t)0xc56e, (q15_t)0x2628, (q15_t)0xc573, (q15_t)0x261c, (q15_t)0xc578,
+    (q15_t)0x2611, (q15_t)0xc57e, (q15_t)0x2605, (q15_t)0xc583, (q15_t)0x25fa, (q15_t)0xc588, (q15_t)0x25ee, (q15_t)0xc58d,
+    (q15_t)0x25e3, (q15_t)0xc592, (q15_t)0x25d7, (q15_t)0xc597, (q15_t)0x25cc, (q15_t)0xc59c, (q15_t)0x25c0, (q15_t)0xc5a1,
+    (q15_t)0x25b5, (q15_t)0xc5a7, (q15_t)0x25a9, (q15_t)0xc5ac, (q15_t)0x259e, (q15_t)0xc5b1, (q15_t)0x2592, (q15_t)0xc5b6,
+    (q15_t)0x2587, (q15_t)0xc5bb, (q15_t)0x257c, (q15_t)0xc5c1, (q15_t)0x2570, (q15_t)0xc5c6, (q15_t)0x2565, (q15_t)0xc5cb,
+    (q15_t)0x2559, (q15_t)0xc5d0, (q15_t)0x254e, (q15_t)0xc5d5, (q15_t)0x2542, (q15_t)0xc5db, (q15_t)0x2537, (q15_t)0xc5e0,
+    (q15_t)0x252c, (q15_t)0xc5e5, (q15_t)0x2520, (q15_t)0xc5ea, (q15_t)0x2515, (q15_t)0xc5f0, (q15_t)0x2509, (q15_t)0xc5f5,
+    (q15_t)0x24fe, (q15_t)0xc5fa, (q15_t)0x24f3, (q15_t)0xc600, (q15_t)0x24e7, (q15_t)0xc605, (q15_t)0x24dc, (q15_t)0xc60a,
+    (q15_t)0x24d0, (q15_t)0xc610, (q15_t)0x24c5, (q15_t)0xc615, (q15_t)0x24ba, (q15_t)0xc61a, (q15_t)0x24ae, (q15_t)0xc620,
+    (q15_t)0x24a3, (q15_t)0xc625, (q15_t)0x2498, (q15_t)0xc62a, (q15_t)0x248c, (q15_t)0xc630, (q15_t)0x2481, (q15_t)0xc635,
+    (q15_t)0x2476, (q15_t)0xc63b, (q15_t)0x246a, (q15_t)0xc640, (q15_t)0x245f, (q15_t)0xc645, (q15_t)0x2454, (q15_t)0xc64b,
+    (q15_t)0x2448, (q15_t)0xc650, (q15_t)0x243d, (q15_t)0xc656, (q15_t)0x2432, (q15_t)0xc65b, (q15_t)0x2426, (q15_t)0xc661,
+    (q15_t)0x241b, (q15_t)0xc666, (q15_t)0x2410, (q15_t)0xc66c, (q15_t)0x2404, (q15_t)0xc671, (q15_t)0x23f9, (q15_t)0xc677,
+    (q15_t)0x23ee, (q15_t)0xc67c, (q15_t)0x23e2, (q15_t)0xc682, (q15_t)0x23d7, (q15_t)0xc687, (q15_t)0x23cc, (q15_t)0xc68d,
+    (q15_t)0x23c1, (q15_t)0xc692, (q15_t)0x23b5, (q15_t)0xc698, (q15_t)0x23aa, (q15_t)0xc69d, (q15_t)0x239f, (q15_t)0xc6a3,
+    (q15_t)0x2394, (q15_t)0xc6a8, (q15_t)0x2388, (q15_t)0xc6ae, (q15_t)0x237d, (q15_t)0xc6b4, (q15_t)0x2372, (q15_t)0xc6b9,
+    (q15_t)0x2367, (q15_t)0xc6bf, (q15_t)0x235b, (q15_t)0xc6c5, (q15_t)0x2350, (q15_t)0xc6ca, (q15_t)0x2345, (q15_t)0xc6d0,
+    (q15_t)0x233a, (q15_t)0xc6d5, (q15_t)0x232e, (q15_t)0xc6db, (q15_t)0x2323, (q15_t)0xc6e1, (q15_t)0x2318, (q15_t)0xc6e6,
+    (q15_t)0x230d, (q15_t)0xc6ec, (q15_t)0x2301, (q15_t)0xc6f2, (q15_t)0x22f6, (q15_t)0xc6f7, (q15_t)0x22eb, (q15_t)0xc6fd,
+    (q15_t)0x22e0, (q15_t)0xc703, (q15_t)0x22d5, (q15_t)0xc709, (q15_t)0x22ca, (q15_t)0xc70e, (q15_t)0x22be, (q15_t)0xc714,
+    (q15_t)0x22b3, (q15_t)0xc71a, (q15_t)0x22a8, (q15_t)0xc720, (q15_t)0x229d, (q15_t)0xc725, (q15_t)0x2292, (q15_t)0xc72b,
+    (q15_t)0x2287, (q15_t)0xc731, (q15_t)0x227b, (q15_t)0xc737, (q15_t)0x2270, (q15_t)0xc73d, (q15_t)0x2265, (q15_t)0xc742,
+    (q15_t)0x225a, (q15_t)0xc748, (q15_t)0x224f, (q15_t)0xc74e, (q15_t)0x2244, (q15_t)0xc754, (q15_t)0x2239, (q15_t)0xc75a,
+    (q15_t)0x222d, (q15_t)0xc75f, (q15_t)0x2222, (q15_t)0xc765, (q15_t)0x2217, (q15_t)0xc76b, (q15_t)0x220c, (q15_t)0xc771,
+    (q15_t)0x2201, (q15_t)0xc777, (q15_t)0x21f6, (q15_t)0xc77d, (q15_t)0x21eb, (q15_t)0xc783, (q15_t)0x21e0, (q15_t)0xc789,
+    (q15_t)0x21d5, (q15_t)0xc78f, (q15_t)0x21ca, (q15_t)0xc795, (q15_t)0x21be, (q15_t)0xc79a, (q15_t)0x21b3, (q15_t)0xc7a0,
+    (q15_t)0x21a8, (q15_t)0xc7a6, (q15_t)0x219d, (q15_t)0xc7ac, (q15_t)0x2192, (q15_t)0xc7b2, (q15_t)0x2187, (q15_t)0xc7b8,
+    (q15_t)0x217c, (q15_t)0xc7be, (q15_t)0x2171, (q15_t)0xc7c4, (q15_t)0x2166, (q15_t)0xc7ca, (q15_t)0x215b, (q15_t)0xc7d0,
+    (q15_t)0x2150, (q15_t)0xc7d6, (q15_t)0x2145, (q15_t)0xc7dc, (q15_t)0x213a, (q15_t)0xc7e2, (q15_t)0x212f, (q15_t)0xc7e8,
+    (q15_t)0x2124, (q15_t)0xc7ee, (q15_t)0x2119, (q15_t)0xc7f5, (q15_t)0x210e, (q15_t)0xc7fb, (q15_t)0x2103, (q15_t)0xc801,
+    (q15_t)0x20f8, (q15_t)0xc807, (q15_t)0x20ed, (q15_t)0xc80d, (q15_t)0x20e2, (q15_t)0xc813, (q15_t)0x20d7, (q15_t)0xc819,
+    (q15_t)0x20cc, (q15_t)0xc81f, (q15_t)0x20c1, (q15_t)0xc825, (q15_t)0x20b6, (q15_t)0xc82b, (q15_t)0x20ab, (q15_t)0xc832,
+    (q15_t)0x20a0, (q15_t)0xc838, (q15_t)0x2095, (q15_t)0xc83e, (q15_t)0x208a, (q15_t)0xc844, (q15_t)0x207f, (q15_t)0xc84a,
+    (q15_t)0x2074, (q15_t)0xc850, (q15_t)0x2069, (q15_t)0xc857, (q15_t)0x205e, (q15_t)0xc85d, (q15_t)0x2054, (q15_t)0xc863,
+    (q15_t)0x2049, (q15_t)0xc869, (q15_t)0x203e, (q15_t)0xc870, (q15_t)0x2033, (q15_t)0xc876, (q15_t)0x2028, (q15_t)0xc87c,
+    (q15_t)0x201d, (q15_t)0xc882, (q15_t)0x2012, (q15_t)0xc889, (q15_t)0x2007, (q15_t)0xc88f, (q15_t)0x1ffc, (q15_t)0xc895,
+    (q15_t)0x1ff1, (q15_t)0xc89b, (q15_t)0x1fe7, (q15_t)0xc8a2, (q15_t)0x1fdc, (q15_t)0xc8a8, (q15_t)0x1fd1, (q15_t)0xc8ae,
+    (q15_t)0x1fc6, (q15_t)0xc8b5, (q15_t)0x1fbb, (q15_t)0xc8bb, (q15_t)0x1fb0, (q15_t)0xc8c1, (q15_t)0x1fa5, (q15_t)0xc8c8,
+    (q15_t)0x1f9b, (q15_t)0xc8ce, (q15_t)0x1f90, (q15_t)0xc8d4, (q15_t)0x1f85, (q15_t)0xc8db, (q15_t)0x1f7a, (q15_t)0xc8e1,
+    (q15_t)0x1f6f, (q15_t)0xc8e8, (q15_t)0x1f65, (q15_t)0xc8ee, (q15_t)0x1f5a, (q15_t)0xc8f4, (q15_t)0x1f4f, (q15_t)0xc8fb,
+    (q15_t)0x1f44, (q15_t)0xc901, (q15_t)0x1f39, (q15_t)0xc908, (q15_t)0x1f2f, (q15_t)0xc90e, (q15_t)0x1f24, (q15_t)0xc915,
+    (q15_t)0x1f19, (q15_t)0xc91b, (q15_t)0x1f0e, (q15_t)0xc921, (q15_t)0x1f03, (q15_t)0xc928, (q15_t)0x1ef9, (q15_t)0xc92e,
+    (q15_t)0x1eee, (q15_t)0xc935, (q15_t)0x1ee3, (q15_t)0xc93b, (q15_t)0x1ed8, (q15_t)0xc942, (q15_t)0x1ece, (q15_t)0xc948,
+    (q15_t)0x1ec3, (q15_t)0xc94f, (q15_t)0x1eb8, (q15_t)0xc955, (q15_t)0x1ead, (q15_t)0xc95c, (q15_t)0x1ea3, (q15_t)0xc963,
+    (q15_t)0x1e98, (q15_t)0xc969, (q15_t)0x1e8d, (q15_t)0xc970, (q15_t)0x1e83, (q15_t)0xc976, (q15_t)0x1e78, (q15_t)0xc97d,
+    (q15_t)0x1e6d, (q15_t)0xc983, (q15_t)0x1e62, (q15_t)0xc98a, (q15_t)0x1e58, (q15_t)0xc991, (q15_t)0x1e4d, (q15_t)0xc997,
+    (q15_t)0x1e42, (q15_t)0xc99e, (q15_t)0x1e38, (q15_t)0xc9a4, (q15_t)0x1e2d, (q15_t)0xc9ab, (q15_t)0x1e22, (q15_t)0xc9b2,
+    (q15_t)0x1e18, (q15_t)0xc9b8, (q15_t)0x1e0d, (q15_t)0xc9bf, (q15_t)0x1e02, (q15_t)0xc9c6, (q15_t)0x1df8, (q15_t)0xc9cc,
+    (q15_t)0x1ded, (q15_t)0xc9d3, (q15_t)0x1de2, (q15_t)0xc9da, (q15_t)0x1dd8, (q15_t)0xc9e0, (q15_t)0x1dcd, (q15_t)0xc9e7,
+    (q15_t)0x1dc3, (q15_t)0xc9ee, (q15_t)0x1db8, (q15_t)0xc9f5, (q15_t)0x1dad, (q15_t)0xc9fb, (q15_t)0x1da3, (q15_t)0xca02,
+    (q15_t)0x1d98, (q15_t)0xca09, (q15_t)0x1d8e, (q15_t)0xca10, (q15_t)0x1d83, (q15_t)0xca16, (q15_t)0x1d78, (q15_t)0xca1d,
+    (q15_t)0x1d6e, (q15_t)0xca24, (q15_t)0x1d63, (q15_t)0xca2b, (q15_t)0x1d59, (q15_t)0xca32, (q15_t)0x1d4e, (q15_t)0xca38,
+    (q15_t)0x1d44, (q15_t)0xca3f, (q15_t)0x1d39, (q15_t)0xca46, (q15_t)0x1d2e, (q15_t)0xca4d, (q15_t)0x1d24, (q15_t)0xca54,
+    (q15_t)0x1d19, (q15_t)0xca5b, (q15_t)0x1d0f, (q15_t)0xca61, (q15_t)0x1d04, (q15_t)0xca68, (q15_t)0x1cfa, (q15_t)0xca6f,
+    (q15_t)0x1cef, (q15_t)0xca76, (q15_t)0x1ce5, (q15_t)0xca7d, (q15_t)0x1cda, (q15_t)0xca84, (q15_t)0x1cd0, (q15_t)0xca8b,
+    (q15_t)0x1cc5, (q15_t)0xca92, (q15_t)0x1cbb, (q15_t)0xca99, (q15_t)0x1cb0, (q15_t)0xca9f, (q15_t)0x1ca6, (q15_t)0xcaa6,
+    (q15_t)0x1c9b, (q15_t)0xcaad, (q15_t)0x1c91, (q15_t)0xcab4, (q15_t)0x1c86, (q15_t)0xcabb, (q15_t)0x1c7c, (q15_t)0xcac2,
+    (q15_t)0x1c72, (q15_t)0xcac9, (q15_t)0x1c67, (q15_t)0xcad0, (q15_t)0x1c5d, (q15_t)0xcad7, (q15_t)0x1c52, (q15_t)0xcade,
+    (q15_t)0x1c48, (q15_t)0xcae5, (q15_t)0x1c3d, (q15_t)0xcaec, (q15_t)0x1c33, (q15_t)0xcaf3, (q15_t)0x1c29, (q15_t)0xcafa,
+    (q15_t)0x1c1e, (q15_t)0xcb01, (q15_t)0x1c14, (q15_t)0xcb08, (q15_t)0x1c09, (q15_t)0xcb0f, (q15_t)0x1bff, (q15_t)0xcb16,
+    (q15_t)0x1bf5, (q15_t)0xcb1e, (q15_t)0x1bea, (q15_t)0xcb25, (q15_t)0x1be0, (q15_t)0xcb2c, (q15_t)0x1bd5, (q15_t)0xcb33,
+    (q15_t)0x1bcb, (q15_t)0xcb3a, (q15_t)0x1bc1, (q15_t)0xcb41, (q15_t)0x1bb6, (q15_t)0xcb48, (q15_t)0x1bac, (q15_t)0xcb4f,
+    (q15_t)0x1ba2, (q15_t)0xcb56, (q15_t)0x1b97, (q15_t)0xcb5e, (q15_t)0x1b8d, (q15_t)0xcb65, (q15_t)0x1b83, (q15_t)0xcb6c,
+    (q15_t)0x1b78, (q15_t)0xcb73, (q15_t)0x1b6e, (q15_t)0xcb7a, (q15_t)0x1b64, (q15_t)0xcb81, (q15_t)0x1b59, (q15_t)0xcb89,
+    (q15_t)0x1b4f, (q15_t)0xcb90, (q15_t)0x1b45, (q15_t)0xcb97, (q15_t)0x1b3b, (q15_t)0xcb9e, (q15_t)0x1b30, (q15_t)0xcba5,
+    (q15_t)0x1b26, (q15_t)0xcbad, (q15_t)0x1b1c, (q15_t)0xcbb4, (q15_t)0x1b11, (q15_t)0xcbbb, (q15_t)0x1b07, (q15_t)0xcbc2,
+    (q15_t)0x1afd, (q15_t)0xcbca, (q15_t)0x1af3, (q15_t)0xcbd1, (q15_t)0x1ae8, (q15_t)0xcbd8, (q15_t)0x1ade, (q15_t)0xcbe0,
+    (q15_t)0x1ad4, (q15_t)0xcbe7, (q15_t)0x1aca, (q15_t)0xcbee, (q15_t)0x1abf, (q15_t)0xcbf5, (q15_t)0x1ab5, (q15_t)0xcbfd,
+    (q15_t)0x1aab, (q15_t)0xcc04, (q15_t)0x1aa1, (q15_t)0xcc0b, (q15_t)0x1a97, (q15_t)0xcc13, (q15_t)0x1a8c, (q15_t)0xcc1a,
+    (q15_t)0x1a82, (q15_t)0xcc21, (q15_t)0x1a78, (q15_t)0xcc29, (q15_t)0x1a6e, (q15_t)0xcc30, (q15_t)0x1a64, (q15_t)0xcc38,
+    (q15_t)0x1a5a, (q15_t)0xcc3f, (q15_t)0x1a4f, (q15_t)0xcc46, (q15_t)0x1a45, (q15_t)0xcc4e, (q15_t)0x1a3b, (q15_t)0xcc55,
+    (q15_t)0x1a31, (q15_t)0xcc5d, (q15_t)0x1a27, (q15_t)0xcc64, (q15_t)0x1a1d, (q15_t)0xcc6b, (q15_t)0x1a13, (q15_t)0xcc73,
+    (q15_t)0x1a08, (q15_t)0xcc7a, (q15_t)0x19fe, (q15_t)0xcc82, (q15_t)0x19f4, (q15_t)0xcc89, (q15_t)0x19ea, (q15_t)0xcc91,
+    (q15_t)0x19e0, (q15_t)0xcc98, (q15_t)0x19d6, (q15_t)0xcca0, (q15_t)0x19cc, (q15_t)0xcca7, (q15_t)0x19c2, (q15_t)0xccaf,
+    (q15_t)0x19b8, (q15_t)0xccb6, (q15_t)0x19ae, (q15_t)0xccbe, (q15_t)0x19a4, (q15_t)0xccc5, (q15_t)0x199a, (q15_t)0xcccd,
+    (q15_t)0x198f, (q15_t)0xccd4, (q15_t)0x1985, (q15_t)0xccdc, (q15_t)0x197b, (q15_t)0xcce3, (q15_t)0x1971, (q15_t)0xcceb,
+    (q15_t)0x1967, (q15_t)0xccf3, (q15_t)0x195d, (q15_t)0xccfa, (q15_t)0x1953, (q15_t)0xcd02, (q15_t)0x1949, (q15_t)0xcd09,
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+    (q15_t)0x18ef, (q15_t)0xcd4e, (q15_t)0x18e6, (q15_t)0xcd56, (q15_t)0x18dc, (q15_t)0xcd5d, (q15_t)0x18d2, (q15_t)0xcd65,
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+    (q15_t)0x1851, (q15_t)0xcdca, (q15_t)0x1847, (q15_t)0xcdd2, (q15_t)0x183d, (q15_t)0xcdd9, (q15_t)0x1833, (q15_t)0xcde1,
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+    (q15_t)0xf8a, (q15_t)0xd632, (q15_t)0xf82, (q15_t)0xd63c, (q15_t)0xf79, (q15_t)0xd645, (q15_t)0xf71, (q15_t)0xd64f,
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+    (q15_t)0xf07, (q15_t)0xd6cb, (q15_t)0xeff, (q15_t)0xd6d5, (q15_t)0xef7, (q15_t)0xd6df, (q15_t)0xeef, (q15_t)0xd6e8,
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+    (q15_t)0xe08, (q15_t)0xd802, (q15_t)0xe01, (q15_t)0xd80c, (q15_t)0xdf9, (q15_t)0xd816, (q15_t)0xdf1, (q15_t)0xd820,
+    (q15_t)0xde9, (q15_t)0xd82a, (q15_t)0xde1, (q15_t)0xd833, (q15_t)0xdd9, (q15_t)0xd83d, (q15_t)0xdd2, (q15_t)0xd847,
+    (q15_t)0xdca, (q15_t)0xd851, (q15_t)0xdc2, (q15_t)0xd85b, (q15_t)0xdba, (q15_t)0xd865, (q15_t)0xdb2, (q15_t)0xd86f,
+    (q15_t)0xdab, (q15_t)0xd878, (q15_t)0xda3, (q15_t)0xd882, (q15_t)0xd9b, (q15_t)0xd88c, (q15_t)0xd93, (q15_t)0xd896,
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+    (q15_t)0xd6d, (q15_t)0xd8c8, (q15_t)0xd65, (q15_t)0xd8d2, (q15_t)0xd5d, (q15_t)0xd8dc, (q15_t)0xd56, (q15_t)0xd8e6,
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+    (q15_t)0xcb6, (q15_t)0xd9b8, (q15_t)0xcaf, (q15_t)0xd9c2, (q15_t)0xca7, (q15_t)0xd9cc, (q15_t)0xca0, (q15_t)0xd9d6,
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+    (q15_t)0xc7a, (q15_t)0xda08, (q15_t)0xc73, (q15_t)0xda13, (q15_t)0xc6b, (q15_t)0xda1d, (q15_t)0xc64, (q15_t)0xda27,
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+    (q15_t)0xaa, (q15_t)0xf6ce, (q15_t)0xa8, (q15_t)0xf6da, (q15_t)0xa6, (q15_t)0xf6e7, (q15_t)0xa5, (q15_t)0xf6f3,
+    (q15_t)0xa3, (q15_t)0xf6ff, (q15_t)0xa1, (q15_t)0xf70c, (q15_t)0x9f, (q15_t)0xf718, (q15_t)0x9e, (q15_t)0xf725,
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+    (q15_t)0x8e, (q15_t)0xf795, (q15_t)0x8d, (q15_t)0xf7a1, (q15_t)0x8b, (q15_t)0xf7ae, (q15_t)0x89, (q15_t)0xf7ba,
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+    (q15_t)0x7b, (q15_t)0xf82a, (q15_t)0x7a, (q15_t)0xf837, (q15_t)0x78, (q15_t)0xf843, (q15_t)0x77, (q15_t)0xf850,
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+    (q15_t)0x69, (q15_t)0x740, (q15_t)0x6b, (q15_t)0x74c, (q15_t)0x6c, (q15_t)0x759, (q15_t)0x6e, (q15_t)0x765,
+    (q15_t)0x6f, (q15_t)0x772, (q15_t)0x71, (q15_t)0x77e, (q15_t)0x72, (q15_t)0x78b, (q15_t)0x74, (q15_t)0x797,
+    (q15_t)0x75, (q15_t)0x7a4, (q15_t)0x77, (q15_t)0x7b0, (q15_t)0x78, (q15_t)0x7bd, (q15_t)0x7a, (q15_t)0x7c9,
+    (q15_t)0x7b, (q15_t)0x7d6, (q15_t)0x7d, (q15_t)0x7e2, (q15_t)0x7e, (q15_t)0x7ef, (q15_t)0x80, (q15_t)0x7fb,
+    (q15_t)0x81, (q15_t)0x807, (q15_t)0x83, (q15_t)0x814, (q15_t)0x85, (q15_t)0x820, (q15_t)0x86, (q15_t)0x82d,
+    (q15_t)0x88, (q15_t)0x839, (q15_t)0x89, (q15_t)0x846, (q15_t)0x8b, (q15_t)0x852, (q15_t)0x8d, (q15_t)0x85f,
+    (q15_t)0x8e, (q15_t)0x86b, (q15_t)0x90, (q15_t)0x878, (q15_t)0x92, (q15_t)0x884, (q15_t)0x93, (q15_t)0x891,
+    (q15_t)0x95, (q15_t)0x89d, (q15_t)0x97, (q15_t)0x8a9, (q15_t)0x98, (q15_t)0x8b6, (q15_t)0x9a, (q15_t)0x8c2,
+    (q15_t)0x9c, (q15_t)0x8cf, (q15_t)0x9e, (q15_t)0x8db, (q15_t)0x9f, (q15_t)0x8e8, (q15_t)0xa1, (q15_t)0x8f4,
+    (q15_t)0xa3, (q15_t)0x901, (q15_t)0xa5, (q15_t)0x90d, (q15_t)0xa6, (q15_t)0x919, (q15_t)0xa8, (q15_t)0x926,
+    (q15_t)0xaa, (q15_t)0x932, (q15_t)0xac, (q15_t)0x93f, (q15_t)0xae, (q15_t)0x94b, (q15_t)0xaf, (q15_t)0x958,
+    (q15_t)0xb1, (q15_t)0x964, (q15_t)0xb3, (q15_t)0x970, (q15_t)0xb5, (q15_t)0x97d, (q15_t)0xb7, (q15_t)0x989,
+    (q15_t)0xb9, (q15_t)0x996, (q15_t)0xbb, (q15_t)0x9a2, (q15_t)0xbd, (q15_t)0x9af, (q15_t)0xbe, (q15_t)0x9bb,
+    (q15_t)0xc0, (q15_t)0x9c7, (q15_t)0xc2, (q15_t)0x9d4, (q15_t)0xc4, (q15_t)0x9e0, (q15_t)0xc6, (q15_t)0x9ed,
+    (q15_t)0xc8, (q15_t)0x9f9, (q15_t)0xca, (q15_t)0xa06, (q15_t)0xcc, (q15_t)0xa12, (q15_t)0xce, (q15_t)0xa1e,
+    (q15_t)0xd0, (q15_t)0xa2b, (q15_t)0xd2, (q15_t)0xa37, (q15_t)0xd4, (q15_t)0xa44, (q15_t)0xd6, (q15_t)0xa50,
+    (q15_t)0xd8, (q15_t)0xa5c, (q15_t)0xda, (q15_t)0xa69, (q15_t)0xdc, (q15_t)0xa75, (q15_t)0xde, (q15_t)0xa82,
+    (q15_t)0xe0, (q15_t)0xa8e, (q15_t)0xe2, (q15_t)0xa9a, (q15_t)0xe4, (q15_t)0xaa7, (q15_t)0xe7, (q15_t)0xab3,
+    (q15_t)0xe9, (q15_t)0xac0, (q15_t)0xeb, (q15_t)0xacc, (q15_t)0xed, (q15_t)0xad8, (q15_t)0xef, (q15_t)0xae5,
+    (q15_t)0xf1, (q15_t)0xaf1, (q15_t)0xf3, (q15_t)0xafd, (q15_t)0xf6, (q15_t)0xb0a, (q15_t)0xf8, (q15_t)0xb16,
+    (q15_t)0xfa, (q15_t)0xb23, (q15_t)0xfc, (q15_t)0xb2f, (q15_t)0xfe, (q15_t)0xb3b, (q15_t)0x100, (q15_t)0xb48,
+    (q15_t)0x103, (q15_t)0xb54, (q15_t)0x105, (q15_t)0xb60, (q15_t)0x107, (q15_t)0xb6d, (q15_t)0x109, (q15_t)0xb79,
+    (q15_t)0x10c, (q15_t)0xb85, (q15_t)0x10e, (q15_t)0xb92, (q15_t)0x110, (q15_t)0xb9e, (q15_t)0x113, (q15_t)0xbab,
+    (q15_t)0x115, (q15_t)0xbb7, (q15_t)0x117, (q15_t)0xbc3, (q15_t)0x119, (q15_t)0xbd0, (q15_t)0x11c, (q15_t)0xbdc,
+    (q15_t)0x11e, (q15_t)0xbe8, (q15_t)0x120, (q15_t)0xbf5, (q15_t)0x123, (q15_t)0xc01, (q15_t)0x125, (q15_t)0xc0d,
+    (q15_t)0x128, (q15_t)0xc1a, (q15_t)0x12a, (q15_t)0xc26, (q15_t)0x12c, (q15_t)0xc32, (q15_t)0x12f, (q15_t)0xc3f,
+    (q15_t)0x131, (q15_t)0xc4b, (q15_t)0x134, (q15_t)0xc57, (q15_t)0x136, (q15_t)0xc64, (q15_t)0x138, (q15_t)0xc70,
+    (q15_t)0x13b, (q15_t)0xc7c, (q15_t)0x13d, (q15_t)0xc89, (q15_t)0x140, (q15_t)0xc95, (q15_t)0x142, (q15_t)0xca1,
+    (q15_t)0x145, (q15_t)0xcae, (q15_t)0x147, (q15_t)0xcba, (q15_t)0x14a, (q15_t)0xcc6, (q15_t)0x14c, (q15_t)0xcd3,
+    (q15_t)0x14f, (q15_t)0xcdf, (q15_t)0x151, (q15_t)0xceb, (q15_t)0x154, (q15_t)0xcf8, (q15_t)0x156, (q15_t)0xd04,
+    (q15_t)0x159, (q15_t)0xd10, (q15_t)0x15b, (q15_t)0xd1c, (q15_t)0x15e, (q15_t)0xd29, (q15_t)0x161, (q15_t)0xd35,
+    (q15_t)0x163, (q15_t)0xd41, (q15_t)0x166, (q15_t)0xd4e, (q15_t)0x168, (q15_t)0xd5a, (q15_t)0x16b, (q15_t)0xd66,
+    (q15_t)0x16e, (q15_t)0xd72, (q15_t)0x170, (q15_t)0xd7f, (q15_t)0x173, (q15_t)0xd8b, (q15_t)0x176, (q15_t)0xd97,
+    (q15_t)0x178, (q15_t)0xda4, (q15_t)0x17b, (q15_t)0xdb0, (q15_t)0x17e, (q15_t)0xdbc, (q15_t)0x180, (q15_t)0xdc8,
+    (q15_t)0x183, (q15_t)0xdd5, (q15_t)0x186, (q15_t)0xde1, (q15_t)0x189, (q15_t)0xded, (q15_t)0x18b, (q15_t)0xdf9,
+    (q15_t)0x18e, (q15_t)0xe06, (q15_t)0x191, (q15_t)0xe12, (q15_t)0x194, (q15_t)0xe1e, (q15_t)0x196, (q15_t)0xe2b,
+    (q15_t)0x199, (q15_t)0xe37, (q15_t)0x19c, (q15_t)0xe43, (q15_t)0x19f, (q15_t)0xe4f, (q15_t)0x1a2, (q15_t)0xe5c,
+    (q15_t)0x1a4, (q15_t)0xe68, (q15_t)0x1a7, (q15_t)0xe74, (q15_t)0x1aa, (q15_t)0xe80, (q15_t)0x1ad, (q15_t)0xe8c,
+    (q15_t)0x1b0, (q15_t)0xe99, (q15_t)0x1b3, (q15_t)0xea5, (q15_t)0x1b6, (q15_t)0xeb1, (q15_t)0x1b8, (q15_t)0xebd,
+    (q15_t)0x1bb, (q15_t)0xeca, (q15_t)0x1be, (q15_t)0xed6, (q15_t)0x1c1, (q15_t)0xee2, (q15_t)0x1c4, (q15_t)0xeee,
+    (q15_t)0x1c7, (q15_t)0xefb, (q15_t)0x1ca, (q15_t)0xf07, (q15_t)0x1cd, (q15_t)0xf13, (q15_t)0x1d0, (q15_t)0xf1f,
+    (q15_t)0x1d3, (q15_t)0xf2b, (q15_t)0x1d6, (q15_t)0xf38, (q15_t)0x1d9, (q15_t)0xf44, (q15_t)0x1dc, (q15_t)0xf50,
+    (q15_t)0x1df, (q15_t)0xf5c, (q15_t)0x1e2, (q15_t)0xf68, (q15_t)0x1e5, (q15_t)0xf75, (q15_t)0x1e8, (q15_t)0xf81,
+    (q15_t)0x1eb, (q15_t)0xf8d, (q15_t)0x1ee, (q15_t)0xf99, (q15_t)0x1f1, (q15_t)0xfa5, (q15_t)0x1f4, (q15_t)0xfb2,
+    (q15_t)0x1f7, (q15_t)0xfbe, (q15_t)0x1fa, (q15_t)0xfca, (q15_t)0x1fd, (q15_t)0xfd6, (q15_t)0x201, (q15_t)0xfe2,
+    (q15_t)0x204, (q15_t)0xfee, (q15_t)0x207, (q15_t)0xffb, (q15_t)0x20a, (q15_t)0x1007, (q15_t)0x20d, (q15_t)0x1013,
+    (q15_t)0x210, (q15_t)0x101f, (q15_t)0x213, (q15_t)0x102b, (q15_t)0x217, (q15_t)0x1037, (q15_t)0x21a, (q15_t)0x1044,
+    (q15_t)0x21d, (q15_t)0x1050, (q15_t)0x220, (q15_t)0x105c, (q15_t)0x223, (q15_t)0x1068, (q15_t)0x227, (q15_t)0x1074,
+    (q15_t)0x22a, (q15_t)0x1080, (q15_t)0x22d, (q15_t)0x108c, (q15_t)0x230, (q15_t)0x1099, (q15_t)0x234, (q15_t)0x10a5,
+    (q15_t)0x237, (q15_t)0x10b1, (q15_t)0x23a, (q15_t)0x10bd, (q15_t)0x23e, (q15_t)0x10c9, (q15_t)0x241, (q15_t)0x10d5,
+    (q15_t)0x244, (q15_t)0x10e1, (q15_t)0x247, (q15_t)0x10ed, (q15_t)0x24b, (q15_t)0x10fa, (q15_t)0x24e, (q15_t)0x1106,
+    (q15_t)0x251, (q15_t)0x1112, (q15_t)0x255, (q15_t)0x111e, (q15_t)0x258, (q15_t)0x112a, (q15_t)0x25c, (q15_t)0x1136,
+    (q15_t)0x25f, (q15_t)0x1142, (q15_t)0x262, (q15_t)0x114e, (q15_t)0x266, (q15_t)0x115a, (q15_t)0x269, (q15_t)0x1167,
+    (q15_t)0x26d, (q15_t)0x1173, (q15_t)0x270, (q15_t)0x117f, (q15_t)0x273, (q15_t)0x118b, (q15_t)0x277, (q15_t)0x1197,
+    (q15_t)0x27a, (q15_t)0x11a3, (q15_t)0x27e, (q15_t)0x11af, (q15_t)0x281, (q15_t)0x11bb, (q15_t)0x285, (q15_t)0x11c7,
+    (q15_t)0x288, (q15_t)0x11d3, (q15_t)0x28c, (q15_t)0x11df, (q15_t)0x28f, (q15_t)0x11eb, (q15_t)0x293, (q15_t)0x11f7,
+    (q15_t)0x296, (q15_t)0x1204, (q15_t)0x29a, (q15_t)0x1210, (q15_t)0x29d, (q15_t)0x121c, (q15_t)0x2a1, (q15_t)0x1228,
+    (q15_t)0x2a5, (q15_t)0x1234, (q15_t)0x2a8, (q15_t)0x1240, (q15_t)0x2ac, (q15_t)0x124c, (q15_t)0x2af, (q15_t)0x1258,
+    (q15_t)0x2b3, (q15_t)0x1264, (q15_t)0x2b7, (q15_t)0x1270, (q15_t)0x2ba, (q15_t)0x127c, (q15_t)0x2be, (q15_t)0x1288,
+    (q15_t)0x2c1, (q15_t)0x1294, (q15_t)0x2c5, (q15_t)0x12a0, (q15_t)0x2c9, (q15_t)0x12ac, (q15_t)0x2cc, (q15_t)0x12b8,
+    (q15_t)0x2d0, (q15_t)0x12c4, (q15_t)0x2d4, (q15_t)0x12d0, (q15_t)0x2d8, (q15_t)0x12dc, (q15_t)0x2db, (q15_t)0x12e8,
+    (q15_t)0x2df, (q15_t)0x12f4, (q15_t)0x2e3, (q15_t)0x1300, (q15_t)0x2e6, (q15_t)0x130c, (q15_t)0x2ea, (q15_t)0x1318,
+    (q15_t)0x2ee, (q15_t)0x1324, (q15_t)0x2f2, (q15_t)0x1330, (q15_t)0x2f5, (q15_t)0x133c, (q15_t)0x2f9, (q15_t)0x1348,
+    (q15_t)0x2fd, (q15_t)0x1354, (q15_t)0x301, (q15_t)0x1360, (q15_t)0x305, (q15_t)0x136c, (q15_t)0x308, (q15_t)0x1378,
+    (q15_t)0x30c, (q15_t)0x1384, (q15_t)0x310, (q15_t)0x1390, (q15_t)0x314, (q15_t)0x139c, (q15_t)0x318, (q15_t)0x13a8,
+    (q15_t)0x31c, (q15_t)0x13b4, (q15_t)0x320, (q15_t)0x13c0, (q15_t)0x323, (q15_t)0x13cc, (q15_t)0x327, (q15_t)0x13d8,
+    (q15_t)0x32b, (q15_t)0x13e4, (q15_t)0x32f, (q15_t)0x13f0, (q15_t)0x333, (q15_t)0x13fb, (q15_t)0x337, (q15_t)0x1407,
+    (q15_t)0x33b, (q15_t)0x1413, (q15_t)0x33f, (q15_t)0x141f, (q15_t)0x343, (q15_t)0x142b, (q15_t)0x347, (q15_t)0x1437,
+    (q15_t)0x34b, (q15_t)0x1443, (q15_t)0x34f, (q15_t)0x144f, (q15_t)0x353, (q15_t)0x145b, (q15_t)0x357, (q15_t)0x1467,
+    (q15_t)0x35b, (q15_t)0x1473, (q15_t)0x35f, (q15_t)0x147f, (q15_t)0x363, (q15_t)0x148b, (q15_t)0x367, (q15_t)0x1496,
+    (q15_t)0x36b, (q15_t)0x14a2, (q15_t)0x36f, (q15_t)0x14ae, (q15_t)0x373, (q15_t)0x14ba, (q15_t)0x377, (q15_t)0x14c6,
+    (q15_t)0x37b, (q15_t)0x14d2, (q15_t)0x37f, (q15_t)0x14de, (q15_t)0x383, (q15_t)0x14ea, (q15_t)0x387, (q15_t)0x14f6,
+    (q15_t)0x38c, (q15_t)0x1501, (q15_t)0x390, (q15_t)0x150d, (q15_t)0x394, (q15_t)0x1519, (q15_t)0x398, (q15_t)0x1525,
+    (q15_t)0x39c, (q15_t)0x1531, (q15_t)0x3a0, (q15_t)0x153d, (q15_t)0x3a5, (q15_t)0x1549, (q15_t)0x3a9, (q15_t)0x1554,
+    (q15_t)0x3ad, (q15_t)0x1560, (q15_t)0x3b1, (q15_t)0x156c, (q15_t)0x3b5, (q15_t)0x1578, (q15_t)0x3ba, (q15_t)0x1584,
+    (q15_t)0x3be, (q15_t)0x1590, (q15_t)0x3c2, (q15_t)0x159b, (q15_t)0x3c6, (q15_t)0x15a7, (q15_t)0x3ca, (q15_t)0x15b3,
+    (q15_t)0x3cf, (q15_t)0x15bf, (q15_t)0x3d3, (q15_t)0x15cb, (q15_t)0x3d7, (q15_t)0x15d7, (q15_t)0x3dc, (q15_t)0x15e2,
+    (q15_t)0x3e0, (q15_t)0x15ee, (q15_t)0x3e4, (q15_t)0x15fa, (q15_t)0x3e9, (q15_t)0x1606, (q15_t)0x3ed, (q15_t)0x1612,
+    (q15_t)0x3f1, (q15_t)0x161d, (q15_t)0x3f6, (q15_t)0x1629, (q15_t)0x3fa, (q15_t)0x1635, (q15_t)0x3fe, (q15_t)0x1641,
+    (q15_t)0x403, (q15_t)0x164c, (q15_t)0x407, (q15_t)0x1658, (q15_t)0x40b, (q15_t)0x1664, (q15_t)0x410, (q15_t)0x1670,
+    (q15_t)0x414, (q15_t)0x167c, (q15_t)0x419, (q15_t)0x1687, (q15_t)0x41d, (q15_t)0x1693, (q15_t)0x422, (q15_t)0x169f,
+    (q15_t)0x426, (q15_t)0x16ab, (q15_t)0x42a, (q15_t)0x16b6, (q15_t)0x42f, (q15_t)0x16c2, (q15_t)0x433, (q15_t)0x16ce,
+    (q15_t)0x438, (q15_t)0x16da, (q15_t)0x43c, (q15_t)0x16e5, (q15_t)0x441, (q15_t)0x16f1, (q15_t)0x445, (q15_t)0x16fd,
+    (q15_t)0x44a, (q15_t)0x1709, (q15_t)0x44e, (q15_t)0x1714, (q15_t)0x453, (q15_t)0x1720, (q15_t)0x457, (q15_t)0x172c,
+    (q15_t)0x45c, (q15_t)0x1737, (q15_t)0x461, (q15_t)0x1743, (q15_t)0x465, (q15_t)0x174f, (q15_t)0x46a, (q15_t)0x175b,
+    (q15_t)0x46e, (q15_t)0x1766, (q15_t)0x473, (q15_t)0x1772, (q15_t)0x478, (q15_t)0x177e, (q15_t)0x47c, (q15_t)0x1789,
+    (q15_t)0x481, (q15_t)0x1795, (q15_t)0x485, (q15_t)0x17a1, (q15_t)0x48a, (q15_t)0x17ac, (q15_t)0x48f, (q15_t)0x17b8,
+    (q15_t)0x493, (q15_t)0x17c4, (q15_t)0x498, (q15_t)0x17cf, (q15_t)0x49d, (q15_t)0x17db, (q15_t)0x4a1, (q15_t)0x17e7,
+    (q15_t)0x4a6, (q15_t)0x17f2, (q15_t)0x4ab, (q15_t)0x17fe, (q15_t)0x4b0, (q15_t)0x180a, (q15_t)0x4b4, (q15_t)0x1815,
+    (q15_t)0x4b9, (q15_t)0x1821, (q15_t)0x4be, (q15_t)0x182d, (q15_t)0x4c2, (q15_t)0x1838, (q15_t)0x4c7, (q15_t)0x1844,
+    (q15_t)0x4cc, (q15_t)0x184f, (q15_t)0x4d1, (q15_t)0x185b, (q15_t)0x4d6, (q15_t)0x1867, (q15_t)0x4da, (q15_t)0x1872,
+    (q15_t)0x4df, (q15_t)0x187e, (q15_t)0x4e4, (q15_t)0x1889, (q15_t)0x4e9, (q15_t)0x1895, (q15_t)0x4ee, (q15_t)0x18a1,
+    (q15_t)0x4f2, (q15_t)0x18ac, (q15_t)0x4f7, (q15_t)0x18b8, (q15_t)0x4fc, (q15_t)0x18c3, (q15_t)0x501, (q15_t)0x18cf,
+    (q15_t)0x506, (q15_t)0x18db, (q15_t)0x50b, (q15_t)0x18e6, (q15_t)0x510, (q15_t)0x18f2, (q15_t)0x515, (q15_t)0x18fd,
+    (q15_t)0x51a, (q15_t)0x1909, (q15_t)0x51e, (q15_t)0x1914, (q15_t)0x523, (q15_t)0x1920, (q15_t)0x528, (q15_t)0x192c,
+    (q15_t)0x52d, (q15_t)0x1937, (q15_t)0x532, (q15_t)0x1943, (q15_t)0x537, (q15_t)0x194e, (q15_t)0x53c, (q15_t)0x195a,
+    (q15_t)0x541, (q15_t)0x1965, (q15_t)0x546, (q15_t)0x1971, (q15_t)0x54b, (q15_t)0x197c, (q15_t)0x550, (q15_t)0x1988,
+    (q15_t)0x555, (q15_t)0x1993, (q15_t)0x55a, (q15_t)0x199f, (q15_t)0x55f, (q15_t)0x19aa, (q15_t)0x564, (q15_t)0x19b6,
+    (q15_t)0x569, (q15_t)0x19c1, (q15_t)0x56e, (q15_t)0x19cd, (q15_t)0x573, (q15_t)0x19d8, (q15_t)0x578, (q15_t)0x19e4,
+    (q15_t)0x57e, (q15_t)0x19ef, (q15_t)0x583, (q15_t)0x19fb, (q15_t)0x588, (q15_t)0x1a06, (q15_t)0x58d, (q15_t)0x1a12,
+    (q15_t)0x592, (q15_t)0x1a1d, (q15_t)0x597, (q15_t)0x1a29, (q15_t)0x59c, (q15_t)0x1a34, (q15_t)0x5a1, (q15_t)0x1a40,
+    (q15_t)0x5a7, (q15_t)0x1a4b, (q15_t)0x5ac, (q15_t)0x1a57, (q15_t)0x5b1, (q15_t)0x1a62, (q15_t)0x5b6, (q15_t)0x1a6e,
+    (q15_t)0x5bb, (q15_t)0x1a79, (q15_t)0x5c1, (q15_t)0x1a84, (q15_t)0x5c6, (q15_t)0x1a90, (q15_t)0x5cb, (q15_t)0x1a9b,
+    (q15_t)0x5d0, (q15_t)0x1aa7, (q15_t)0x5d5, (q15_t)0x1ab2, (q15_t)0x5db, (q15_t)0x1abe, (q15_t)0x5e0, (q15_t)0x1ac9,
+    (q15_t)0x5e5, (q15_t)0x1ad4, (q15_t)0x5ea, (q15_t)0x1ae0, (q15_t)0x5f0, (q15_t)0x1aeb, (q15_t)0x5f5, (q15_t)0x1af7,
+    (q15_t)0x5fa, (q15_t)0x1b02, (q15_t)0x600, (q15_t)0x1b0d, (q15_t)0x605, (q15_t)0x1b19, (q15_t)0x60a, (q15_t)0x1b24,
+    (q15_t)0x610, (q15_t)0x1b30, (q15_t)0x615, (q15_t)0x1b3b, (q15_t)0x61a, (q15_t)0x1b46, (q15_t)0x620, (q15_t)0x1b52,
+    (q15_t)0x625, (q15_t)0x1b5d, (q15_t)0x62a, (q15_t)0x1b68, (q15_t)0x630, (q15_t)0x1b74, (q15_t)0x635, (q15_t)0x1b7f,
+    (q15_t)0x63b, (q15_t)0x1b8a, (q15_t)0x640, (q15_t)0x1b96, (q15_t)0x645, (q15_t)0x1ba1, (q15_t)0x64b, (q15_t)0x1bac,
+    (q15_t)0x650, (q15_t)0x1bb8, (q15_t)0x656, (q15_t)0x1bc3, (q15_t)0x65b, (q15_t)0x1bce, (q15_t)0x661, (q15_t)0x1bda,
+    (q15_t)0x666, (q15_t)0x1be5, (q15_t)0x66c, (q15_t)0x1bf0, (q15_t)0x671, (q15_t)0x1bfc, (q15_t)0x677, (q15_t)0x1c07,
+    (q15_t)0x67c, (q15_t)0x1c12, (q15_t)0x682, (q15_t)0x1c1e, (q15_t)0x687, (q15_t)0x1c29, (q15_t)0x68d, (q15_t)0x1c34,
+    (q15_t)0x692, (q15_t)0x1c3f, (q15_t)0x698, (q15_t)0x1c4b, (q15_t)0x69d, (q15_t)0x1c56, (q15_t)0x6a3, (q15_t)0x1c61,
+    (q15_t)0x6a8, (q15_t)0x1c6c, (q15_t)0x6ae, (q15_t)0x1c78, (q15_t)0x6b4, (q15_t)0x1c83, (q15_t)0x6b9, (q15_t)0x1c8e,
+    (q15_t)0x6bf, (q15_t)0x1c99, (q15_t)0x6c5, (q15_t)0x1ca5, (q15_t)0x6ca, (q15_t)0x1cb0, (q15_t)0x6d0, (q15_t)0x1cbb,
+    (q15_t)0x6d5, (q15_t)0x1cc6, (q15_t)0x6db, (q15_t)0x1cd2, (q15_t)0x6e1, (q15_t)0x1cdd, (q15_t)0x6e6, (q15_t)0x1ce8,
+    (q15_t)0x6ec, (q15_t)0x1cf3, (q15_t)0x6f2, (q15_t)0x1cff, (q15_t)0x6f7, (q15_t)0x1d0a, (q15_t)0x6fd, (q15_t)0x1d15,
+    (q15_t)0x703, (q15_t)0x1d20, (q15_t)0x709, (q15_t)0x1d2b, (q15_t)0x70e, (q15_t)0x1d36, (q15_t)0x714, (q15_t)0x1d42,
+    (q15_t)0x71a, (q15_t)0x1d4d, (q15_t)0x720, (q15_t)0x1d58, (q15_t)0x725, (q15_t)0x1d63, (q15_t)0x72b, (q15_t)0x1d6e,
+    (q15_t)0x731, (q15_t)0x1d79, (q15_t)0x737, (q15_t)0x1d85, (q15_t)0x73d, (q15_t)0x1d90, (q15_t)0x742, (q15_t)0x1d9b,
+    (q15_t)0x748, (q15_t)0x1da6, (q15_t)0x74e, (q15_t)0x1db1, (q15_t)0x754, (q15_t)0x1dbc, (q15_t)0x75a, (q15_t)0x1dc7,
+    (q15_t)0x75f, (q15_t)0x1dd3, (q15_t)0x765, (q15_t)0x1dde, (q15_t)0x76b, (q15_t)0x1de9, (q15_t)0x771, (q15_t)0x1df4,
+    (q15_t)0x777, (q15_t)0x1dff, (q15_t)0x77d, (q15_t)0x1e0a, (q15_t)0x783, (q15_t)0x1e15, (q15_t)0x789, (q15_t)0x1e20,
+    (q15_t)0x78f, (q15_t)0x1e2b, (q15_t)0x795, (q15_t)0x1e36, (q15_t)0x79a, (q15_t)0x1e42, (q15_t)0x7a0, (q15_t)0x1e4d,
+    (q15_t)0x7a6, (q15_t)0x1e58, (q15_t)0x7ac, (q15_t)0x1e63, (q15_t)0x7b2, (q15_t)0x1e6e, (q15_t)0x7b8, (q15_t)0x1e79,
+    (q15_t)0x7be, (q15_t)0x1e84, (q15_t)0x7c4, (q15_t)0x1e8f, (q15_t)0x7ca, (q15_t)0x1e9a, (q15_t)0x7d0, (q15_t)0x1ea5,
+    (q15_t)0x7d6, (q15_t)0x1eb0, (q15_t)0x7dc, (q15_t)0x1ebb, (q15_t)0x7e2, (q15_t)0x1ec6, (q15_t)0x7e8, (q15_t)0x1ed1,
+    (q15_t)0x7ee, (q15_t)0x1edc, (q15_t)0x7f5, (q15_t)0x1ee7, (q15_t)0x7fb, (q15_t)0x1ef2, (q15_t)0x801, (q15_t)0x1efd,
+    (q15_t)0x807, (q15_t)0x1f08, (q15_t)0x80d, (q15_t)0x1f13, (q15_t)0x813, (q15_t)0x1f1e, (q15_t)0x819, (q15_t)0x1f29,
+    (q15_t)0x81f, (q15_t)0x1f34, (q15_t)0x825, (q15_t)0x1f3f, (q15_t)0x82b, (q15_t)0x1f4a, (q15_t)0x832, (q15_t)0x1f55,
+    (q15_t)0x838, (q15_t)0x1f60, (q15_t)0x83e, (q15_t)0x1f6b, (q15_t)0x844, (q15_t)0x1f76, (q15_t)0x84a, (q15_t)0x1f81,
+    (q15_t)0x850, (q15_t)0x1f8c, (q15_t)0x857, (q15_t)0x1f97, (q15_t)0x85d, (q15_t)0x1fa2, (q15_t)0x863, (q15_t)0x1fac,
+    (q15_t)0x869, (q15_t)0x1fb7, (q15_t)0x870, (q15_t)0x1fc2, (q15_t)0x876, (q15_t)0x1fcd, (q15_t)0x87c, (q15_t)0x1fd8,
+    (q15_t)0x882, (q15_t)0x1fe3, (q15_t)0x889, (q15_t)0x1fee, (q15_t)0x88f, (q15_t)0x1ff9, (q15_t)0x895, (q15_t)0x2004,
+    (q15_t)0x89b, (q15_t)0x200f, (q15_t)0x8a2, (q15_t)0x2019, (q15_t)0x8a8, (q15_t)0x2024, (q15_t)0x8ae, (q15_t)0x202f,
+    (q15_t)0x8b5, (q15_t)0x203a, (q15_t)0x8bb, (q15_t)0x2045, (q15_t)0x8c1, (q15_t)0x2050, (q15_t)0x8c8, (q15_t)0x205b,
+    (q15_t)0x8ce, (q15_t)0x2065, (q15_t)0x8d4, (q15_t)0x2070, (q15_t)0x8db, (q15_t)0x207b, (q15_t)0x8e1, (q15_t)0x2086,
+    (q15_t)0x8e8, (q15_t)0x2091, (q15_t)0x8ee, (q15_t)0x209b, (q15_t)0x8f4, (q15_t)0x20a6, (q15_t)0x8fb, (q15_t)0x20b1,
+    (q15_t)0x901, (q15_t)0x20bc, (q15_t)0x908, (q15_t)0x20c7, (q15_t)0x90e, (q15_t)0x20d1, (q15_t)0x915, (q15_t)0x20dc,
+    (q15_t)0x91b, (q15_t)0x20e7, (q15_t)0x921, (q15_t)0x20f2, (q15_t)0x928, (q15_t)0x20fd, (q15_t)0x92e, (q15_t)0x2107,
+    (q15_t)0x935, (q15_t)0x2112, (q15_t)0x93b, (q15_t)0x211d, (q15_t)0x942, (q15_t)0x2128, (q15_t)0x948, (q15_t)0x2132,
+    (q15_t)0x94f, (q15_t)0x213d, (q15_t)0x955, (q15_t)0x2148, (q15_t)0x95c, (q15_t)0x2153, (q15_t)0x963, (q15_t)0x215d,
+    (q15_t)0x969, (q15_t)0x2168, (q15_t)0x970, (q15_t)0x2173, (q15_t)0x976, (q15_t)0x217d, (q15_t)0x97d, (q15_t)0x2188,
+    (q15_t)0x983, (q15_t)0x2193, (q15_t)0x98a, (q15_t)0x219e, (q15_t)0x991, (q15_t)0x21a8, (q15_t)0x997, (q15_t)0x21b3,
+    (q15_t)0x99e, (q15_t)0x21be, (q15_t)0x9a4, (q15_t)0x21c8, (q15_t)0x9ab, (q15_t)0x21d3, (q15_t)0x9b2, (q15_t)0x21de,
+    (q15_t)0x9b8, (q15_t)0x21e8, (q15_t)0x9bf, (q15_t)0x21f3, (q15_t)0x9c6, (q15_t)0x21fe, (q15_t)0x9cc, (q15_t)0x2208,
+    (q15_t)0x9d3, (q15_t)0x2213, (q15_t)0x9da, (q15_t)0x221e, (q15_t)0x9e0, (q15_t)0x2228, (q15_t)0x9e7, (q15_t)0x2233,
+    (q15_t)0x9ee, (q15_t)0x223d, (q15_t)0x9f5, (q15_t)0x2248, (q15_t)0x9fb, (q15_t)0x2253, (q15_t)0xa02, (q15_t)0x225d,
+    (q15_t)0xa09, (q15_t)0x2268, (q15_t)0xa10, (q15_t)0x2272, (q15_t)0xa16, (q15_t)0x227d, (q15_t)0xa1d, (q15_t)0x2288,
+    (q15_t)0xa24, (q15_t)0x2292, (q15_t)0xa2b, (q15_t)0x229d, (q15_t)0xa32, (q15_t)0x22a7, (q15_t)0xa38, (q15_t)0x22b2,
+    (q15_t)0xa3f, (q15_t)0x22bc, (q15_t)0xa46, (q15_t)0x22c7, (q15_t)0xa4d, (q15_t)0x22d2, (q15_t)0xa54, (q15_t)0x22dc,
+    (q15_t)0xa5b, (q15_t)0x22e7, (q15_t)0xa61, (q15_t)0x22f1, (q15_t)0xa68, (q15_t)0x22fc, (q15_t)0xa6f, (q15_t)0x2306,
+    (q15_t)0xa76, (q15_t)0x2311, (q15_t)0xa7d, (q15_t)0x231b, (q15_t)0xa84, (q15_t)0x2326, (q15_t)0xa8b, (q15_t)0x2330,
+    (q15_t)0xa92, (q15_t)0x233b, (q15_t)0xa99, (q15_t)0x2345, (q15_t)0xa9f, (q15_t)0x2350, (q15_t)0xaa6, (q15_t)0x235a,
+    (q15_t)0xaad, (q15_t)0x2365, (q15_t)0xab4, (q15_t)0x236f, (q15_t)0xabb, (q15_t)0x237a, (q15_t)0xac2, (q15_t)0x2384,
+    (q15_t)0xac9, (q15_t)0x238e, (q15_t)0xad0, (q15_t)0x2399, (q15_t)0xad7, (q15_t)0x23a3, (q15_t)0xade, (q15_t)0x23ae,
+    (q15_t)0xae5, (q15_t)0x23b8, (q15_t)0xaec, (q15_t)0x23c3, (q15_t)0xaf3, (q15_t)0x23cd, (q15_t)0xafa, (q15_t)0x23d7,
+    (q15_t)0xb01, (q15_t)0x23e2, (q15_t)0xb08, (q15_t)0x23ec, (q15_t)0xb0f, (q15_t)0x23f7, (q15_t)0xb16, (q15_t)0x2401,
+    (q15_t)0xb1e, (q15_t)0x240b, (q15_t)0xb25, (q15_t)0x2416, (q15_t)0xb2c, (q15_t)0x2420, (q15_t)0xb33, (q15_t)0x242b,
+    (q15_t)0xb3a, (q15_t)0x2435, (q15_t)0xb41, (q15_t)0x243f, (q15_t)0xb48, (q15_t)0x244a, (q15_t)0xb4f, (q15_t)0x2454,
+    (q15_t)0xb56, (q15_t)0x245e, (q15_t)0xb5e, (q15_t)0x2469, (q15_t)0xb65, (q15_t)0x2473, (q15_t)0xb6c, (q15_t)0x247d,
+    (q15_t)0xb73, (q15_t)0x2488, (q15_t)0xb7a, (q15_t)0x2492, (q15_t)0xb81, (q15_t)0x249c, (q15_t)0xb89, (q15_t)0x24a7,
+    (q15_t)0xb90, (q15_t)0x24b1, (q15_t)0xb97, (q15_t)0x24bb, (q15_t)0xb9e, (q15_t)0x24c5, (q15_t)0xba5, (q15_t)0x24d0,
+    (q15_t)0xbad, (q15_t)0x24da, (q15_t)0xbb4, (q15_t)0x24e4, (q15_t)0xbbb, (q15_t)0x24ef, (q15_t)0xbc2, (q15_t)0x24f9,
+    (q15_t)0xbca, (q15_t)0x2503, (q15_t)0xbd1, (q15_t)0x250d, (q15_t)0xbd8, (q15_t)0x2518, (q15_t)0xbe0, (q15_t)0x2522,
+    (q15_t)0xbe7, (q15_t)0x252c, (q15_t)0xbee, (q15_t)0x2536, (q15_t)0xbf5, (q15_t)0x2541, (q15_t)0xbfd, (q15_t)0x254b,
+    (q15_t)0xc04, (q15_t)0x2555, (q15_t)0xc0b, (q15_t)0x255f, (q15_t)0xc13, (q15_t)0x2569, (q15_t)0xc1a, (q15_t)0x2574,
+    (q15_t)0xc21, (q15_t)0x257e, (q15_t)0xc29, (q15_t)0x2588, (q15_t)0xc30, (q15_t)0x2592, (q15_t)0xc38, (q15_t)0x259c,
+    (q15_t)0xc3f, (q15_t)0x25a6, (q15_t)0xc46, (q15_t)0x25b1, (q15_t)0xc4e, (q15_t)0x25bb, (q15_t)0xc55, (q15_t)0x25c5,
+    (q15_t)0xc5d, (q15_t)0x25cf, (q15_t)0xc64, (q15_t)0x25d9, (q15_t)0xc6b, (q15_t)0x25e3, (q15_t)0xc73, (q15_t)0x25ed,
+    (q15_t)0xc7a, (q15_t)0x25f8, (q15_t)0xc82, (q15_t)0x2602, (q15_t)0xc89, (q15_t)0x260c, (q15_t)0xc91, (q15_t)0x2616,
+    (q15_t)0xc98, (q15_t)0x2620, (q15_t)0xca0, (q15_t)0x262a, (q15_t)0xca7, (q15_t)0x2634, (q15_t)0xcaf, (q15_t)0x263e,
+    (q15_t)0xcb6, (q15_t)0x2648, (q15_t)0xcbe, (q15_t)0x2652, (q15_t)0xcc5, (q15_t)0x265c, (q15_t)0xccd, (q15_t)0x2666,
+    (q15_t)0xcd4, (q15_t)0x2671, (q15_t)0xcdc, (q15_t)0x267b, (q15_t)0xce3, (q15_t)0x2685, (q15_t)0xceb, (q15_t)0x268f,
+    (q15_t)0xcf3, (q15_t)0x2699, (q15_t)0xcfa, (q15_t)0x26a3, (q15_t)0xd02, (q15_t)0x26ad, (q15_t)0xd09, (q15_t)0x26b7,
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+    (q15_t)0x18a0, (q15_t)0x3274, (q15_t)0x18aa, (q15_t)0x327c, (q15_t)0x18b4, (q15_t)0x3284, (q15_t)0x18be, (q15_t)0x328b,
+    (q15_t)0x18c8, (q15_t)0x3293, (q15_t)0x18d2, (q15_t)0x329b, (q15_t)0x18dc, (q15_t)0x32a3, (q15_t)0x18e6, (q15_t)0x32aa,
+    (q15_t)0x18ef, (q15_t)0x32b2, (q15_t)0x18f9, (q15_t)0x32ba, (q15_t)0x1903, (q15_t)0x32c1, (q15_t)0x190d, (q15_t)0x32c9,
+    (q15_t)0x1917, (q15_t)0x32d0, (q15_t)0x1921, (q15_t)0x32d8, (q15_t)0x192b, (q15_t)0x32e0, (q15_t)0x1935, (q15_t)0x32e7,
+    (q15_t)0x193f, (q15_t)0x32ef, (q15_t)0x1949, (q15_t)0x32f7, (q15_t)0x1953, (q15_t)0x32fe, (q15_t)0x195d, (q15_t)0x3306,
+    (q15_t)0x1967, (q15_t)0x330d, (q15_t)0x1971, (q15_t)0x3315, (q15_t)0x197b, (q15_t)0x331d, (q15_t)0x1985, (q15_t)0x3324,
+    (q15_t)0x198f, (q15_t)0x332c, (q15_t)0x199a, (q15_t)0x3333, (q15_t)0x19a4, (q15_t)0x333b, (q15_t)0x19ae, (q15_t)0x3342,
+    (q15_t)0x19b8, (q15_t)0x334a, (q15_t)0x19c2, (q15_t)0x3351, (q15_t)0x19cc, (q15_t)0x3359, (q15_t)0x19d6, (q15_t)0x3360,
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+    (q15_t)0x1a31, (q15_t)0x33a3, (q15_t)0x1a3b, (q15_t)0x33ab, (q15_t)0x1a45, (q15_t)0x33b2, (q15_t)0x1a4f, (q15_t)0x33ba,
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+    (q15_t)0x263f, (q15_t)0x3a97, (q15_t)0x264a, (q15_t)0x3a9c, (q15_t)0x2656, (q15_t)0x3aa1, (q15_t)0x2661, (q15_t)0x3aa6,
+    (q15_t)0x266d, (q15_t)0x3aab, (q15_t)0x2678, (q15_t)0x3ab0, (q15_t)0x2684, (q15_t)0x3ab5, (q15_t)0x268f, (q15_t)0x3aba,
+    (q15_t)0x269b, (q15_t)0x3abf, (q15_t)0x26a6, (q15_t)0x3ac4, (q15_t)0x26b2, (q15_t)0x3ac9, (q15_t)0x26bd, (q15_t)0x3ace,
+    (q15_t)0x26c9, (q15_t)0x3ad3, (q15_t)0x26d4, (q15_t)0x3ad8, (q15_t)0x26e0, (q15_t)0x3add, (q15_t)0x26ec, (q15_t)0x3ae2,
+    (q15_t)0x26f7, (q15_t)0x3ae6, (q15_t)0x2703, (q15_t)0x3aeb, (q15_t)0x270e, (q15_t)0x3af0, (q15_t)0x271a, (q15_t)0x3af5,
+    (q15_t)0x2725, (q15_t)0x3afa, (q15_t)0x2731, (q15_t)0x3aff, (q15_t)0x273d, (q15_t)0x3b04, (q15_t)0x2748, (q15_t)0x3b09,
+    (q15_t)0x2754, (q15_t)0x3b0e, (q15_t)0x275f, (q15_t)0x3b12, (q15_t)0x276b, (q15_t)0x3b17, (q15_t)0x2777, (q15_t)0x3b1c,
+    (q15_t)0x2782, (q15_t)0x3b21, (q15_t)0x278e, (q15_t)0x3b26, (q15_t)0x2799, (q15_t)0x3b2a, (q15_t)0x27a5, (q15_t)0x3b2f,
+    (q15_t)0x27b1, (q15_t)0x3b34, (q15_t)0x27bc, (q15_t)0x3b39, (q15_t)0x27c8, (q15_t)0x3b3e, (q15_t)0x27d3, (q15_t)0x3b42,
+    (q15_t)0x27df, (q15_t)0x3b47, (q15_t)0x27eb, (q15_t)0x3b4c, (q15_t)0x27f6, (q15_t)0x3b50, (q15_t)0x2802, (q15_t)0x3b55,
+    (q15_t)0x280e, (q15_t)0x3b5a, (q15_t)0x2819, (q15_t)0x3b5f, (q15_t)0x2825, (q15_t)0x3b63, (q15_t)0x2831, (q15_t)0x3b68,
+    (q15_t)0x283c, (q15_t)0x3b6d, (q15_t)0x2848, (q15_t)0x3b71, (q15_t)0x2854, (q15_t)0x3b76, (q15_t)0x285f, (q15_t)0x3b7b,
+    (q15_t)0x286b, (q15_t)0x3b7f, (q15_t)0x2877, (q15_t)0x3b84, (q15_t)0x2882, (q15_t)0x3b88, (q15_t)0x288e, (q15_t)0x3b8d,
+    (q15_t)0x289a, (q15_t)0x3b92, (q15_t)0x28a5, (q15_t)0x3b96, (q15_t)0x28b1, (q15_t)0x3b9b, (q15_t)0x28bd, (q15_t)0x3b9f,
+    (q15_t)0x28c9, (q15_t)0x3ba4, (q15_t)0x28d4, (q15_t)0x3ba9, (q15_t)0x28e0, (q15_t)0x3bad, (q15_t)0x28ec, (q15_t)0x3bb2,
+    (q15_t)0x28f7, (q15_t)0x3bb6, (q15_t)0x2903, (q15_t)0x3bbb, (q15_t)0x290f, (q15_t)0x3bbf, (q15_t)0x291b, (q15_t)0x3bc4,
+    (q15_t)0x2926, (q15_t)0x3bc8, (q15_t)0x2932, (q15_t)0x3bcd, (q15_t)0x293e, (q15_t)0x3bd1, (q15_t)0x294a, (q15_t)0x3bd6,
+    (q15_t)0x2955, (q15_t)0x3bda, (q15_t)0x2961, (q15_t)0x3bde, (q15_t)0x296d, (q15_t)0x3be3, (q15_t)0x2979, (q15_t)0x3be7,
+    (q15_t)0x2984, (q15_t)0x3bec, (q15_t)0x2990, (q15_t)0x3bf0, (q15_t)0x299c, (q15_t)0x3bf5, (q15_t)0x29a8, (q15_t)0x3bf9,
+    (q15_t)0x29b4, (q15_t)0x3bfd, (q15_t)0x29bf, (q15_t)0x3c02, (q15_t)0x29cb, (q15_t)0x3c06, (q15_t)0x29d7, (q15_t)0x3c0a,
+    (q15_t)0x29e3, (q15_t)0x3c0f, (q15_t)0x29ee, (q15_t)0x3c13, (q15_t)0x29fa, (q15_t)0x3c17, (q15_t)0x2a06, (q15_t)0x3c1c,
+    (q15_t)0x2a12, (q15_t)0x3c20, (q15_t)0x2a1e, (q15_t)0x3c24, (q15_t)0x2a29, (q15_t)0x3c29, (q15_t)0x2a35, (q15_t)0x3c2d,
+    (q15_t)0x2a41, (q15_t)0x3c31, (q15_t)0x2a4d, (q15_t)0x3c36, (q15_t)0x2a59, (q15_t)0x3c3a, (q15_t)0x2a65, (q15_t)0x3c3e,
+    (q15_t)0x2a70, (q15_t)0x3c42, (q15_t)0x2a7c, (q15_t)0x3c46, (q15_t)0x2a88, (q15_t)0x3c4b, (q15_t)0x2a94, (q15_t)0x3c4f,
+    (q15_t)0x2aa0, (q15_t)0x3c53, (q15_t)0x2aac, (q15_t)0x3c57, (q15_t)0x2ab7, (q15_t)0x3c5b, (q15_t)0x2ac3, (q15_t)0x3c60,
+    (q15_t)0x2acf, (q15_t)0x3c64, (q15_t)0x2adb, (q15_t)0x3c68, (q15_t)0x2ae7, (q15_t)0x3c6c, (q15_t)0x2af3, (q15_t)0x3c70,
+    (q15_t)0x2aff, (q15_t)0x3c74, (q15_t)0x2b0a, (q15_t)0x3c79, (q15_t)0x2b16, (q15_t)0x3c7d, (q15_t)0x2b22, (q15_t)0x3c81,
+    (q15_t)0x2b2e, (q15_t)0x3c85, (q15_t)0x2b3a, (q15_t)0x3c89, (q15_t)0x2b46, (q15_t)0x3c8d, (q15_t)0x2b52, (q15_t)0x3c91,
+    (q15_t)0x2b5e, (q15_t)0x3c95, (q15_t)0x2b6a, (q15_t)0x3c99, (q15_t)0x2b75, (q15_t)0x3c9d, (q15_t)0x2b81, (q15_t)0x3ca1,
+    (q15_t)0x2b8d, (q15_t)0x3ca5, (q15_t)0x2b99, (q15_t)0x3ca9, (q15_t)0x2ba5, (q15_t)0x3cad, (q15_t)0x2bb1, (q15_t)0x3cb1,
+    (q15_t)0x2bbd, (q15_t)0x3cb5, (q15_t)0x2bc9, (q15_t)0x3cb9, (q15_t)0x2bd5, (q15_t)0x3cbd, (q15_t)0x2be1, (q15_t)0x3cc1,
+    (q15_t)0x2bed, (q15_t)0x3cc5, (q15_t)0x2bf9, (q15_t)0x3cc9, (q15_t)0x2c05, (q15_t)0x3ccd, (q15_t)0x2c10, (q15_t)0x3cd1,
+    (q15_t)0x2c1c, (q15_t)0x3cd5, (q15_t)0x2c28, (q15_t)0x3cd9, (q15_t)0x2c34, (q15_t)0x3cdd, (q15_t)0x2c40, (q15_t)0x3ce0,
+    (q15_t)0x2c4c, (q15_t)0x3ce4, (q15_t)0x2c58, (q15_t)0x3ce8, (q15_t)0x2c64, (q15_t)0x3cec, (q15_t)0x2c70, (q15_t)0x3cf0,
+    (q15_t)0x2c7c, (q15_t)0x3cf4, (q15_t)0x2c88, (q15_t)0x3cf8, (q15_t)0x2c94, (q15_t)0x3cfb, (q15_t)0x2ca0, (q15_t)0x3cff,
+    (q15_t)0x2cac, (q15_t)0x3d03, (q15_t)0x2cb8, (q15_t)0x3d07, (q15_t)0x2cc4, (q15_t)0x3d0b, (q15_t)0x2cd0, (q15_t)0x3d0e,
+    (q15_t)0x2cdc, (q15_t)0x3d12, (q15_t)0x2ce8, (q15_t)0x3d16, (q15_t)0x2cf4, (q15_t)0x3d1a, (q15_t)0x2d00, (q15_t)0x3d1d,
+    (q15_t)0x2d0c, (q15_t)0x3d21, (q15_t)0x2d18, (q15_t)0x3d25, (q15_t)0x2d24, (q15_t)0x3d28, (q15_t)0x2d30, (q15_t)0x3d2c,
+    (q15_t)0x2d3c, (q15_t)0x3d30, (q15_t)0x2d48, (q15_t)0x3d34, (q15_t)0x2d54, (q15_t)0x3d37, (q15_t)0x2d60, (q15_t)0x3d3b,
+    (q15_t)0x2d6c, (q15_t)0x3d3f, (q15_t)0x2d78, (q15_t)0x3d42, (q15_t)0x2d84, (q15_t)0x3d46, (q15_t)0x2d90, (q15_t)0x3d49,
+    (q15_t)0x2d9c, (q15_t)0x3d4d, (q15_t)0x2da8, (q15_t)0x3d51, (q15_t)0x2db4, (q15_t)0x3d54, (q15_t)0x2dc0, (q15_t)0x3d58,
+    (q15_t)0x2dcc, (q15_t)0x3d5b, (q15_t)0x2dd8, (q15_t)0x3d5f, (q15_t)0x2de4, (q15_t)0x3d63, (q15_t)0x2df0, (q15_t)0x3d66,
+    (q15_t)0x2dfc, (q15_t)0x3d6a, (q15_t)0x2e09, (q15_t)0x3d6d, (q15_t)0x2e15, (q15_t)0x3d71, (q15_t)0x2e21, (q15_t)0x3d74,
+    (q15_t)0x2e2d, (q15_t)0x3d78, (q15_t)0x2e39, (q15_t)0x3d7b, (q15_t)0x2e45, (q15_t)0x3d7f, (q15_t)0x2e51, (q15_t)0x3d82,
+    (q15_t)0x2e5d, (q15_t)0x3d86, (q15_t)0x2e69, (q15_t)0x3d89, (q15_t)0x2e75, (q15_t)0x3d8d, (q15_t)0x2e81, (q15_t)0x3d90,
+    (q15_t)0x2e8d, (q15_t)0x3d93, (q15_t)0x2e99, (q15_t)0x3d97, (q15_t)0x2ea6, (q15_t)0x3d9a, (q15_t)0x2eb2, (q15_t)0x3d9e,
+    (q15_t)0x2ebe, (q15_t)0x3da1, (q15_t)0x2eca, (q15_t)0x3da4, (q15_t)0x2ed6, (q15_t)0x3da8, (q15_t)0x2ee2, (q15_t)0x3dab,
+    (q15_t)0x2eee, (q15_t)0x3daf, (q15_t)0x2efa, (q15_t)0x3db2, (q15_t)0x2f06, (q15_t)0x3db5, (q15_t)0x2f13, (q15_t)0x3db9,
+    (q15_t)0x2f1f, (q15_t)0x3dbc, (q15_t)0x2f2b, (q15_t)0x3dbf, (q15_t)0x2f37, (q15_t)0x3dc2, (q15_t)0x2f43, (q15_t)0x3dc6,
+    (q15_t)0x2f4f, (q15_t)0x3dc9, (q15_t)0x2f5b, (q15_t)0x3dcc, (q15_t)0x2f67, (q15_t)0x3dd0, (q15_t)0x2f74, (q15_t)0x3dd3,
+    (q15_t)0x2f80, (q15_t)0x3dd6, (q15_t)0x2f8c, (q15_t)0x3dd9, (q15_t)0x2f98, (q15_t)0x3ddd, (q15_t)0x2fa4, (q15_t)0x3de0,
+    (q15_t)0x2fb0, (q15_t)0x3de3, (q15_t)0x2fbc, (q15_t)0x3de6, (q15_t)0x2fc9, (q15_t)0x3de9, (q15_t)0x2fd5, (q15_t)0x3ded,
+    (q15_t)0x2fe1, (q15_t)0x3df0, (q15_t)0x2fed, (q15_t)0x3df3, (q15_t)0x2ff9, (q15_t)0x3df6, (q15_t)0x3005, (q15_t)0x3df9,
+    (q15_t)0x3012, (q15_t)0x3dfc, (q15_t)0x301e, (q15_t)0x3dff, (q15_t)0x302a, (q15_t)0x3e03, (q15_t)0x3036, (q15_t)0x3e06,
+    (q15_t)0x3042, (q15_t)0x3e09, (q15_t)0x304e, (q15_t)0x3e0c, (q15_t)0x305b, (q15_t)0x3e0f, (q15_t)0x3067, (q15_t)0x3e12,
+    (q15_t)0x3073, (q15_t)0x3e15, (q15_t)0x307f, (q15_t)0x3e18, (q15_t)0x308b, (q15_t)0x3e1b, (q15_t)0x3098, (q15_t)0x3e1e,
+    (q15_t)0x30a4, (q15_t)0x3e21, (q15_t)0x30b0, (q15_t)0x3e24, (q15_t)0x30bc, (q15_t)0x3e27, (q15_t)0x30c8, (q15_t)0x3e2a,
+    (q15_t)0x30d5, (q15_t)0x3e2d, (q15_t)0x30e1, (q15_t)0x3e30, (q15_t)0x30ed, (q15_t)0x3e33, (q15_t)0x30f9, (q15_t)0x3e36,
+    (q15_t)0x3105, (q15_t)0x3e39, (q15_t)0x3112, (q15_t)0x3e3c, (q15_t)0x311e, (q15_t)0x3e3f, (q15_t)0x312a, (q15_t)0x3e42,
+    (q15_t)0x3136, (q15_t)0x3e45, (q15_t)0x3143, (q15_t)0x3e48, (q15_t)0x314f, (q15_t)0x3e4a, (q15_t)0x315b, (q15_t)0x3e4d,
+    (q15_t)0x3167, (q15_t)0x3e50, (q15_t)0x3174, (q15_t)0x3e53, (q15_t)0x3180, (q15_t)0x3e56, (q15_t)0x318c, (q15_t)0x3e59,
+    (q15_t)0x3198, (q15_t)0x3e5c, (q15_t)0x31a4, (q15_t)0x3e5e, (q15_t)0x31b1, (q15_t)0x3e61, (q15_t)0x31bd, (q15_t)0x3e64,
+    (q15_t)0x31c9, (q15_t)0x3e67, (q15_t)0x31d5, (q15_t)0x3e6a, (q15_t)0x31e2, (q15_t)0x3e6c, (q15_t)0x31ee, (q15_t)0x3e6f,
+    (q15_t)0x31fa, (q15_t)0x3e72, (q15_t)0x3207, (q15_t)0x3e75, (q15_t)0x3213, (q15_t)0x3e77, (q15_t)0x321f, (q15_t)0x3e7a,
+    (q15_t)0x322b, (q15_t)0x3e7d, (q15_t)0x3238, (q15_t)0x3e80, (q15_t)0x3244, (q15_t)0x3e82, (q15_t)0x3250, (q15_t)0x3e85,
+    (q15_t)0x325c, (q15_t)0x3e88, (q15_t)0x3269, (q15_t)0x3e8a, (q15_t)0x3275, (q15_t)0x3e8d, (q15_t)0x3281, (q15_t)0x3e90,
+    (q15_t)0x328e, (q15_t)0x3e92, (q15_t)0x329a, (q15_t)0x3e95, (q15_t)0x32a6, (q15_t)0x3e98, (q15_t)0x32b2, (q15_t)0x3e9a,
+    (q15_t)0x32bf, (q15_t)0x3e9d, (q15_t)0x32cb, (q15_t)0x3e9f, (q15_t)0x32d7, (q15_t)0x3ea2, (q15_t)0x32e4, (q15_t)0x3ea5,
+    (q15_t)0x32f0, (q15_t)0x3ea7, (q15_t)0x32fc, (q15_t)0x3eaa, (q15_t)0x3308, (q15_t)0x3eac, (q15_t)0x3315, (q15_t)0x3eaf,
+    (q15_t)0x3321, (q15_t)0x3eb1, (q15_t)0x332d, (q15_t)0x3eb4, (q15_t)0x333a, (q15_t)0x3eb6, (q15_t)0x3346, (q15_t)0x3eb9,
+    (q15_t)0x3352, (q15_t)0x3ebb, (q15_t)0x335f, (q15_t)0x3ebe, (q15_t)0x336b, (q15_t)0x3ec0, (q15_t)0x3377, (q15_t)0x3ec3,
+    (q15_t)0x3384, (q15_t)0x3ec5, (q15_t)0x3390, (q15_t)0x3ec8, (q15_t)0x339c, (q15_t)0x3eca, (q15_t)0x33a9, (q15_t)0x3ecc,
+    (q15_t)0x33b5, (q15_t)0x3ecf, (q15_t)0x33c1, (q15_t)0x3ed1, (q15_t)0x33ce, (q15_t)0x3ed4, (q15_t)0x33da, (q15_t)0x3ed6,
+    (q15_t)0x33e6, (q15_t)0x3ed8, (q15_t)0x33f3, (q15_t)0x3edb, (q15_t)0x33ff, (q15_t)0x3edd, (q15_t)0x340b, (q15_t)0x3ee0,
+    (q15_t)0x3418, (q15_t)0x3ee2, (q15_t)0x3424, (q15_t)0x3ee4, (q15_t)0x3430, (q15_t)0x3ee7, (q15_t)0x343d, (q15_t)0x3ee9,
+    (q15_t)0x3449, (q15_t)0x3eeb, (q15_t)0x3455, (q15_t)0x3eed, (q15_t)0x3462, (q15_t)0x3ef0, (q15_t)0x346e, (q15_t)0x3ef2,
+    (q15_t)0x347b, (q15_t)0x3ef4, (q15_t)0x3487, (q15_t)0x3ef7, (q15_t)0x3493, (q15_t)0x3ef9, (q15_t)0x34a0, (q15_t)0x3efb,
+    (q15_t)0x34ac, (q15_t)0x3efd, (q15_t)0x34b8, (q15_t)0x3f00, (q15_t)0x34c5, (q15_t)0x3f02, (q15_t)0x34d1, (q15_t)0x3f04,
+    (q15_t)0x34dd, (q15_t)0x3f06, (q15_t)0x34ea, (q15_t)0x3f08, (q15_t)0x34f6, (q15_t)0x3f0a, (q15_t)0x3503, (q15_t)0x3f0d,
+    (q15_t)0x350f, (q15_t)0x3f0f, (q15_t)0x351b, (q15_t)0x3f11, (q15_t)0x3528, (q15_t)0x3f13, (q15_t)0x3534, (q15_t)0x3f15,
+    (q15_t)0x3540, (q15_t)0x3f17, (q15_t)0x354d, (q15_t)0x3f19, (q15_t)0x3559, (q15_t)0x3f1c, (q15_t)0x3566, (q15_t)0x3f1e,
+    (q15_t)0x3572, (q15_t)0x3f20, (q15_t)0x357e, (q15_t)0x3f22, (q15_t)0x358b, (q15_t)0x3f24, (q15_t)0x3597, (q15_t)0x3f26,
+    (q15_t)0x35a4, (q15_t)0x3f28, (q15_t)0x35b0, (q15_t)0x3f2a, (q15_t)0x35bc, (q15_t)0x3f2c, (q15_t)0x35c9, (q15_t)0x3f2e,
+    (q15_t)0x35d5, (q15_t)0x3f30, (q15_t)0x35e2, (q15_t)0x3f32, (q15_t)0x35ee, (q15_t)0x3f34, (q15_t)0x35fa, (q15_t)0x3f36,
+    (q15_t)0x3607, (q15_t)0x3f38, (q15_t)0x3613, (q15_t)0x3f3a, (q15_t)0x3620, (q15_t)0x3f3c, (q15_t)0x362c, (q15_t)0x3f3e,
+    (q15_t)0x3639, (q15_t)0x3f40, (q15_t)0x3645, (q15_t)0x3f42, (q15_t)0x3651, (q15_t)0x3f43, (q15_t)0x365e, (q15_t)0x3f45,
+    (q15_t)0x366a, (q15_t)0x3f47, (q15_t)0x3677, (q15_t)0x3f49, (q15_t)0x3683, (q15_t)0x3f4b, (q15_t)0x3690, (q15_t)0x3f4d,
+    (q15_t)0x369c, (q15_t)0x3f4f, (q15_t)0x36a8, (q15_t)0x3f51, (q15_t)0x36b5, (q15_t)0x3f52, (q15_t)0x36c1, (q15_t)0x3f54,
+    (q15_t)0x36ce, (q15_t)0x3f56, (q15_t)0x36da, (q15_t)0x3f58, (q15_t)0x36e7, (q15_t)0x3f5a, (q15_t)0x36f3, (q15_t)0x3f5b,
+    (q15_t)0x36ff, (q15_t)0x3f5d, (q15_t)0x370c, (q15_t)0x3f5f, (q15_t)0x3718, (q15_t)0x3f61, (q15_t)0x3725, (q15_t)0x3f62,
+    (q15_t)0x3731, (q15_t)0x3f64, (q15_t)0x373e, (q15_t)0x3f66, (q15_t)0x374a, (q15_t)0x3f68, (q15_t)0x3757, (q15_t)0x3f69,
+    (q15_t)0x3763, (q15_t)0x3f6b, (q15_t)0x376f, (q15_t)0x3f6d, (q15_t)0x377c, (q15_t)0x3f6e, (q15_t)0x3788, (q15_t)0x3f70,
+    (q15_t)0x3795, (q15_t)0x3f72, (q15_t)0x37a1, (q15_t)0x3f73, (q15_t)0x37ae, (q15_t)0x3f75, (q15_t)0x37ba, (q15_t)0x3f77,
+    (q15_t)0x37c7, (q15_t)0x3f78, (q15_t)0x37d3, (q15_t)0x3f7a, (q15_t)0x37e0, (q15_t)0x3f7b, (q15_t)0x37ec, (q15_t)0x3f7d,
+    (q15_t)0x37f9, (q15_t)0x3f7f, (q15_t)0x3805, (q15_t)0x3f80, (q15_t)0x3811, (q15_t)0x3f82, (q15_t)0x381e, (q15_t)0x3f83,
+    (q15_t)0x382a, (q15_t)0x3f85, (q15_t)0x3837, (q15_t)0x3f86, (q15_t)0x3843, (q15_t)0x3f88, (q15_t)0x3850, (q15_t)0x3f89,
+    (q15_t)0x385c, (q15_t)0x3f8b, (q15_t)0x3869, (q15_t)0x3f8c, (q15_t)0x3875, (q15_t)0x3f8e, (q15_t)0x3882, (q15_t)0x3f8f,
+    (q15_t)0x388e, (q15_t)0x3f91, (q15_t)0x389b, (q15_t)0x3f92, (q15_t)0x38a7, (q15_t)0x3f94, (q15_t)0x38b4, (q15_t)0x3f95,
+    (q15_t)0x38c0, (q15_t)0x3f97, (q15_t)0x38cd, (q15_t)0x3f98, (q15_t)0x38d9, (q15_t)0x3f99, (q15_t)0x38e6, (q15_t)0x3f9b,
+    (q15_t)0x38f2, (q15_t)0x3f9c, (q15_t)0x38ff, (q15_t)0x3f9e, (q15_t)0x390b, (q15_t)0x3f9f, (q15_t)0x3918, (q15_t)0x3fa0,
+    (q15_t)0x3924, (q15_t)0x3fa2, (q15_t)0x3931, (q15_t)0x3fa3, (q15_t)0x393d, (q15_t)0x3fa4, (q15_t)0x394a, (q15_t)0x3fa6,
+    (q15_t)0x3956, (q15_t)0x3fa7, (q15_t)0x3963, (q15_t)0x3fa8, (q15_t)0x396f, (q15_t)0x3faa, (q15_t)0x397c, (q15_t)0x3fab,
+    (q15_t)0x3988, (q15_t)0x3fac, (q15_t)0x3995, (q15_t)0x3fad, (q15_t)0x39a1, (q15_t)0x3faf, (q15_t)0x39ae, (q15_t)0x3fb0,
+    (q15_t)0x39ba, (q15_t)0x3fb1, (q15_t)0x39c7, (q15_t)0x3fb2, (q15_t)0x39d3, (q15_t)0x3fb4, (q15_t)0x39e0, (q15_t)0x3fb5,
+    (q15_t)0x39ec, (q15_t)0x3fb6, (q15_t)0x39f9, (q15_t)0x3fb7, (q15_t)0x3a05, (q15_t)0x3fb8, (q15_t)0x3a12, (q15_t)0x3fb9,
+    (q15_t)0x3a1e, (q15_t)0x3fbb, (q15_t)0x3a2b, (q15_t)0x3fbc, (q15_t)0x3a37, (q15_t)0x3fbd, (q15_t)0x3a44, (q15_t)0x3fbe,
+    (q15_t)0x3a50, (q15_t)0x3fbf, (q15_t)0x3a5d, (q15_t)0x3fc0, (q15_t)0x3a69, (q15_t)0x3fc1, (q15_t)0x3a76, (q15_t)0x3fc3,
+    (q15_t)0x3a82, (q15_t)0x3fc4, (q15_t)0x3a8f, (q15_t)0x3fc5, (q15_t)0x3a9b, (q15_t)0x3fc6, (q15_t)0x3aa8, (q15_t)0x3fc7,
+    (q15_t)0x3ab4, (q15_t)0x3fc8, (q15_t)0x3ac1, (q15_t)0x3fc9, (q15_t)0x3acd, (q15_t)0x3fca, (q15_t)0x3ada, (q15_t)0x3fcb,
+    (q15_t)0x3ae6, (q15_t)0x3fcc, (q15_t)0x3af3, (q15_t)0x3fcd, (q15_t)0x3b00, (q15_t)0x3fce, (q15_t)0x3b0c, (q15_t)0x3fcf,
+    (q15_t)0x3b19, (q15_t)0x3fd0, (q15_t)0x3b25, (q15_t)0x3fd1, (q15_t)0x3b32, (q15_t)0x3fd2, (q15_t)0x3b3e, (q15_t)0x3fd3,
+    (q15_t)0x3b4b, (q15_t)0x3fd4, (q15_t)0x3b57, (q15_t)0x3fd5, (q15_t)0x3b64, (q15_t)0x3fd5, (q15_t)0x3b70, (q15_t)0x3fd6,
+    (q15_t)0x3b7d, (q15_t)0x3fd7, (q15_t)0x3b89, (q15_t)0x3fd8, (q15_t)0x3b96, (q15_t)0x3fd9, (q15_t)0x3ba2, (q15_t)0x3fda,
+    (q15_t)0x3baf, (q15_t)0x3fdb, (q15_t)0x3bbc, (q15_t)0x3fdc, (q15_t)0x3bc8, (q15_t)0x3fdc, (q15_t)0x3bd5, (q15_t)0x3fdd,
+    (q15_t)0x3be1, (q15_t)0x3fde, (q15_t)0x3bee, (q15_t)0x3fdf, (q15_t)0x3bfa, (q15_t)0x3fe0, (q15_t)0x3c07, (q15_t)0x3fe0,
+    (q15_t)0x3c13, (q15_t)0x3fe1, (q15_t)0x3c20, (q15_t)0x3fe2, (q15_t)0x3c2c, (q15_t)0x3fe3, (q15_t)0x3c39, (q15_t)0x3fe3,
+    (q15_t)0x3c45, (q15_t)0x3fe4, (q15_t)0x3c52, (q15_t)0x3fe5, (q15_t)0x3c5f, (q15_t)0x3fe6, (q15_t)0x3c6b, (q15_t)0x3fe6,
+    (q15_t)0x3c78, (q15_t)0x3fe7, (q15_t)0x3c84, (q15_t)0x3fe8, (q15_t)0x3c91, (q15_t)0x3fe8, (q15_t)0x3c9d, (q15_t)0x3fe9,
+    (q15_t)0x3caa, (q15_t)0x3fea, (q15_t)0x3cb6, (q15_t)0x3fea, (q15_t)0x3cc3, (q15_t)0x3feb, (q15_t)0x3cd0, (q15_t)0x3fec,
+    (q15_t)0x3cdc, (q15_t)0x3fec, (q15_t)0x3ce9, (q15_t)0x3fed, (q15_t)0x3cf5, (q15_t)0x3fed, (q15_t)0x3d02, (q15_t)0x3fee,
+    (q15_t)0x3d0e, (q15_t)0x3fef, (q15_t)0x3d1b, (q15_t)0x3fef, (q15_t)0x3d27, (q15_t)0x3ff0, (q15_t)0x3d34, (q15_t)0x3ff0,
+    (q15_t)0x3d40, (q15_t)0x3ff1, (q15_t)0x3d4d, (q15_t)0x3ff1, (q15_t)0x3d5a, (q15_t)0x3ff2, (q15_t)0x3d66, (q15_t)0x3ff2,
+    (q15_t)0x3d73, (q15_t)0x3ff3, (q15_t)0x3d7f, (q15_t)0x3ff3, (q15_t)0x3d8c, (q15_t)0x3ff4, (q15_t)0x3d98, (q15_t)0x3ff4,
+    (q15_t)0x3da5, (q15_t)0x3ff5, (q15_t)0x3db2, (q15_t)0x3ff5, (q15_t)0x3dbe, (q15_t)0x3ff6, (q15_t)0x3dcb, (q15_t)0x3ff6,
+    (q15_t)0x3dd7, (q15_t)0x3ff7, (q15_t)0x3de4, (q15_t)0x3ff7, (q15_t)0x3df0, (q15_t)0x3ff7, (q15_t)0x3dfd, (q15_t)0x3ff8,
+    (q15_t)0x3e09, (q15_t)0x3ff8, (q15_t)0x3e16, (q15_t)0x3ff9, (q15_t)0x3e23, (q15_t)0x3ff9, (q15_t)0x3e2f, (q15_t)0x3ff9,
+    (q15_t)0x3e3c, (q15_t)0x3ffa, (q15_t)0x3e48, (q15_t)0x3ffa, (q15_t)0x3e55, (q15_t)0x3ffa, (q15_t)0x3e61, (q15_t)0x3ffb,
+    (q15_t)0x3e6e, (q15_t)0x3ffb, (q15_t)0x3e7a, (q15_t)0x3ffb, (q15_t)0x3e87, (q15_t)0x3ffc, (q15_t)0x3e94, (q15_t)0x3ffc,
+    (q15_t)0x3ea0, (q15_t)0x3ffc, (q15_t)0x3ead, (q15_t)0x3ffc, (q15_t)0x3eb9, (q15_t)0x3ffd, (q15_t)0x3ec6, (q15_t)0x3ffd,
+    (q15_t)0x3ed2, (q15_t)0x3ffd, (q15_t)0x3edf, (q15_t)0x3ffd, (q15_t)0x3eec, (q15_t)0x3ffe, (q15_t)0x3ef8, (q15_t)0x3ffe,
+    (q15_t)0x3f05, (q15_t)0x3ffe, (q15_t)0x3f11, (q15_t)0x3ffe, (q15_t)0x3f1e, (q15_t)0x3ffe, (q15_t)0x3f2a, (q15_t)0x3fff,
+    (q15_t)0x3f37, (q15_t)0x3fff, (q15_t)0x3f44, (q15_t)0x3fff, (q15_t)0x3f50, (q15_t)0x3fff, (q15_t)0x3f5d, (q15_t)0x3fff,
+    (q15_t)0x3f69, (q15_t)0x3fff, (q15_t)0x3f76, (q15_t)0x3fff, (q15_t)0x3f82, (q15_t)0x4000, (q15_t)0x3f8f, (q15_t)0x4000,
+    (q15_t)0x3f9b, (q15_t)0x4000, (q15_t)0x3fa8, (q15_t)0x4000, (q15_t)0x3fb5, (q15_t)0x4000, (q15_t)0x3fc1, (q15_t)0x4000,
+    (q15_t)0x3fce, (q15_t)0x4000, (q15_t)0x3fda, (q15_t)0x4000, (q15_t)0x3fe7, (q15_t)0x4000, (q15_t)0x3ff3, (q15_t)0x4000,
+};
+
+/**
+* \par
+* Generation of real_CoefB array:
+* \par
+* n = 4096
+* <pre>for (i = 0; i < n; i++)
+*  {
+*    pBTable[2 * i] = 0.5 * (1.0 + sin (2 * PI / (double) (2 * n) * (double) i));
+*    pBTable[2 * i + 1] = 0.5 * (1.0 * cos (2 * PI / (double) (2 * n) * (double) i));
+*  } </pre>
+* \par
+* Convert to fixed point Q15 format
+*       round(pBTable[i] * pow(2, 15))
+*
+*/
+const q15_t ALIGN4 realCoefBQ15[8192] = {
+    (q15_t)0x4000, (q15_t)0x4000, (q15_t)0x400d, (q15_t)0x4000, (q15_t)0x4019, (q15_t)0x4000, (q15_t)0x4026, (q15_t)0x4000,
+    (q15_t)0x4032, (q15_t)0x4000, (q15_t)0x403f, (q15_t)0x4000, (q15_t)0x404b, (q15_t)0x4000, (q15_t)0x4058, (q15_t)0x4000,
+    (q15_t)0x4065, (q15_t)0x4000, (q15_t)0x4071, (q15_t)0x4000, (q15_t)0x407e, (q15_t)0x4000, (q15_t)0x408a, (q15_t)0x3fff,
+    (q15_t)0x4097, (q15_t)0x3fff, (q15_t)0x40a3, (q15_t)0x3fff, (q15_t)0x40b0, (q15_t)0x3fff, (q15_t)0x40bc, (q15_t)0x3fff,
+    (q15_t)0x40c9, (q15_t)0x3fff, (q15_t)0x40d6, (q15_t)0x3fff, (q15_t)0x40e2, (q15_t)0x3ffe, (q15_t)0x40ef, (q15_t)0x3ffe,
+    (q15_t)0x40fb, (q15_t)0x3ffe, (q15_t)0x4108, (q15_t)0x3ffe, (q15_t)0x4114, (q15_t)0x3ffe, (q15_t)0x4121, (q15_t)0x3ffd,
+    (q15_t)0x412e, (q15_t)0x3ffd, (q15_t)0x413a, (q15_t)0x3ffd, (q15_t)0x4147, (q15_t)0x3ffd, (q15_t)0x4153, (q15_t)0x3ffc,
+    (q15_t)0x4160, (q15_t)0x3ffc, (q15_t)0x416c, (q15_t)0x3ffc, (q15_t)0x4179, (q15_t)0x3ffc, (q15_t)0x4186, (q15_t)0x3ffb,
+    (q15_t)0x4192, (q15_t)0x3ffb, (q15_t)0x419f, (q15_t)0x3ffb, (q15_t)0x41ab, (q15_t)0x3ffa, (q15_t)0x41b8, (q15_t)0x3ffa,
+    (q15_t)0x41c4, (q15_t)0x3ffa, (q15_t)0x41d1, (q15_t)0x3ff9, (q15_t)0x41dd, (q15_t)0x3ff9, (q15_t)0x41ea, (q15_t)0x3ff9,
+    (q15_t)0x41f7, (q15_t)0x3ff8, (q15_t)0x4203, (q15_t)0x3ff8, (q15_t)0x4210, (q15_t)0x3ff7, (q15_t)0x421c, (q15_t)0x3ff7,
+    (q15_t)0x4229, (q15_t)0x3ff7, (q15_t)0x4235, (q15_t)0x3ff6, (q15_t)0x4242, (q15_t)0x3ff6, (q15_t)0x424e, (q15_t)0x3ff5,
+    (q15_t)0x425b, (q15_t)0x3ff5, (q15_t)0x4268, (q15_t)0x3ff4, (q15_t)0x4274, (q15_t)0x3ff4, (q15_t)0x4281, (q15_t)0x3ff3,
+    (q15_t)0x428d, (q15_t)0x3ff3, (q15_t)0x429a, (q15_t)0x3ff2, (q15_t)0x42a6, (q15_t)0x3ff2, (q15_t)0x42b3, (q15_t)0x3ff1,
+    (q15_t)0x42c0, (q15_t)0x3ff1, (q15_t)0x42cc, (q15_t)0x3ff0, (q15_t)0x42d9, (q15_t)0x3ff0, (q15_t)0x42e5, (q15_t)0x3fef,
+    (q15_t)0x42f2, (q15_t)0x3fef, (q15_t)0x42fe, (q15_t)0x3fee, (q15_t)0x430b, (q15_t)0x3fed, (q15_t)0x4317, (q15_t)0x3fed,
+    (q15_t)0x4324, (q15_t)0x3fec, (q15_t)0x4330, (q15_t)0x3fec, (q15_t)0x433d, (q15_t)0x3feb, (q15_t)0x434a, (q15_t)0x3fea,
+    (q15_t)0x4356, (q15_t)0x3fea, (q15_t)0x4363, (q15_t)0x3fe9, (q15_t)0x436f, (q15_t)0x3fe8, (q15_t)0x437c, (q15_t)0x3fe8,
+    (q15_t)0x4388, (q15_t)0x3fe7, (q15_t)0x4395, (q15_t)0x3fe6, (q15_t)0x43a1, (q15_t)0x3fe6, (q15_t)0x43ae, (q15_t)0x3fe5,
+    (q15_t)0x43bb, (q15_t)0x3fe4, (q15_t)0x43c7, (q15_t)0x3fe3, (q15_t)0x43d4, (q15_t)0x3fe3, (q15_t)0x43e0, (q15_t)0x3fe2,
+    (q15_t)0x43ed, (q15_t)0x3fe1, (q15_t)0x43f9, (q15_t)0x3fe0, (q15_t)0x4406, (q15_t)0x3fe0, (q15_t)0x4412, (q15_t)0x3fdf,
+    (q15_t)0x441f, (q15_t)0x3fde, (q15_t)0x442b, (q15_t)0x3fdd, (q15_t)0x4438, (q15_t)0x3fdc, (q15_t)0x4444, (q15_t)0x3fdc,
+    (q15_t)0x4451, (q15_t)0x3fdb, (q15_t)0x445e, (q15_t)0x3fda, (q15_t)0x446a, (q15_t)0x3fd9, (q15_t)0x4477, (q15_t)0x3fd8,
+    (q15_t)0x4483, (q15_t)0x3fd7, (q15_t)0x4490, (q15_t)0x3fd6, (q15_t)0x449c, (q15_t)0x3fd5, (q15_t)0x44a9, (q15_t)0x3fd5,
+    (q15_t)0x44b5, (q15_t)0x3fd4, (q15_t)0x44c2, (q15_t)0x3fd3, (q15_t)0x44ce, (q15_t)0x3fd2, (q15_t)0x44db, (q15_t)0x3fd1,
+    (q15_t)0x44e7, (q15_t)0x3fd0, (q15_t)0x44f4, (q15_t)0x3fcf, (q15_t)0x4500, (q15_t)0x3fce, (q15_t)0x450d, (q15_t)0x3fcd,
+    (q15_t)0x451a, (q15_t)0x3fcc, (q15_t)0x4526, (q15_t)0x3fcb, (q15_t)0x4533, (q15_t)0x3fca, (q15_t)0x453f, (q15_t)0x3fc9,
+    (q15_t)0x454c, (q15_t)0x3fc8, (q15_t)0x4558, (q15_t)0x3fc7, (q15_t)0x4565, (q15_t)0x3fc6, (q15_t)0x4571, (q15_t)0x3fc5,
+    (q15_t)0x457e, (q15_t)0x3fc4, (q15_t)0x458a, (q15_t)0x3fc3, (q15_t)0x4597, (q15_t)0x3fc1, (q15_t)0x45a3, (q15_t)0x3fc0,
+    (q15_t)0x45b0, (q15_t)0x3fbf, (q15_t)0x45bc, (q15_t)0x3fbe, (q15_t)0x45c9, (q15_t)0x3fbd, (q15_t)0x45d5, (q15_t)0x3fbc,
+    (q15_t)0x45e2, (q15_t)0x3fbb, (q15_t)0x45ee, (q15_t)0x3fb9, (q15_t)0x45fb, (q15_t)0x3fb8, (q15_t)0x4607, (q15_t)0x3fb7,
+    (q15_t)0x4614, (q15_t)0x3fb6, (q15_t)0x4620, (q15_t)0x3fb5, (q15_t)0x462d, (q15_t)0x3fb4, (q15_t)0x4639, (q15_t)0x3fb2,
+    (q15_t)0x4646, (q15_t)0x3fb1, (q15_t)0x4652, (q15_t)0x3fb0, (q15_t)0x465f, (q15_t)0x3faf, (q15_t)0x466b, (q15_t)0x3fad,
+    (q15_t)0x4678, (q15_t)0x3fac, (q15_t)0x4684, (q15_t)0x3fab, (q15_t)0x4691, (q15_t)0x3faa, (q15_t)0x469d, (q15_t)0x3fa8,
+    (q15_t)0x46aa, (q15_t)0x3fa7, (q15_t)0x46b6, (q15_t)0x3fa6, (q15_t)0x46c3, (q15_t)0x3fa4, (q15_t)0x46cf, (q15_t)0x3fa3,
+    (q15_t)0x46dc, (q15_t)0x3fa2, (q15_t)0x46e8, (q15_t)0x3fa0, (q15_t)0x46f5, (q15_t)0x3f9f, (q15_t)0x4701, (q15_t)0x3f9e,
+    (q15_t)0x470e, (q15_t)0x3f9c, (q15_t)0x471a, (q15_t)0x3f9b, (q15_t)0x4727, (q15_t)0x3f99, (q15_t)0x4733, (q15_t)0x3f98,
+    (q15_t)0x4740, (q15_t)0x3f97, (q15_t)0x474c, (q15_t)0x3f95, (q15_t)0x4759, (q15_t)0x3f94, (q15_t)0x4765, (q15_t)0x3f92,
+    (q15_t)0x4772, (q15_t)0x3f91, (q15_t)0x477e, (q15_t)0x3f8f, (q15_t)0x478b, (q15_t)0x3f8e, (q15_t)0x4797, (q15_t)0x3f8c,
+    (q15_t)0x47a4, (q15_t)0x3f8b, (q15_t)0x47b0, (q15_t)0x3f89, (q15_t)0x47bd, (q15_t)0x3f88, (q15_t)0x47c9, (q15_t)0x3f86,
+    (q15_t)0x47d6, (q15_t)0x3f85, (q15_t)0x47e2, (q15_t)0x3f83, (q15_t)0x47ef, (q15_t)0x3f82, (q15_t)0x47fb, (q15_t)0x3f80,
+    (q15_t)0x4807, (q15_t)0x3f7f, (q15_t)0x4814, (q15_t)0x3f7d, (q15_t)0x4820, (q15_t)0x3f7b, (q15_t)0x482d, (q15_t)0x3f7a,
+    (q15_t)0x4839, (q15_t)0x3f78, (q15_t)0x4846, (q15_t)0x3f77, (q15_t)0x4852, (q15_t)0x3f75, (q15_t)0x485f, (q15_t)0x3f73,
+    (q15_t)0x486b, (q15_t)0x3f72, (q15_t)0x4878, (q15_t)0x3f70, (q15_t)0x4884, (q15_t)0x3f6e, (q15_t)0x4891, (q15_t)0x3f6d,
+    (q15_t)0x489d, (q15_t)0x3f6b, (q15_t)0x48a9, (q15_t)0x3f69, (q15_t)0x48b6, (q15_t)0x3f68, (q15_t)0x48c2, (q15_t)0x3f66,
+    (q15_t)0x48cf, (q15_t)0x3f64, (q15_t)0x48db, (q15_t)0x3f62, (q15_t)0x48e8, (q15_t)0x3f61, (q15_t)0x48f4, (q15_t)0x3f5f,
+    (q15_t)0x4901, (q15_t)0x3f5d, (q15_t)0x490d, (q15_t)0x3f5b, (q15_t)0x4919, (q15_t)0x3f5a, (q15_t)0x4926, (q15_t)0x3f58,
+    (q15_t)0x4932, (q15_t)0x3f56, (q15_t)0x493f, (q15_t)0x3f54, (q15_t)0x494b, (q15_t)0x3f52, (q15_t)0x4958, (q15_t)0x3f51,
+    (q15_t)0x4964, (q15_t)0x3f4f, (q15_t)0x4970, (q15_t)0x3f4d, (q15_t)0x497d, (q15_t)0x3f4b, (q15_t)0x4989, (q15_t)0x3f49,
+    (q15_t)0x4996, (q15_t)0x3f47, (q15_t)0x49a2, (q15_t)0x3f45, (q15_t)0x49af, (q15_t)0x3f43, (q15_t)0x49bb, (q15_t)0x3f42,
+    (q15_t)0x49c7, (q15_t)0x3f40, (q15_t)0x49d4, (q15_t)0x3f3e, (q15_t)0x49e0, (q15_t)0x3f3c, (q15_t)0x49ed, (q15_t)0x3f3a,
+    (q15_t)0x49f9, (q15_t)0x3f38, (q15_t)0x4a06, (q15_t)0x3f36, (q15_t)0x4a12, (q15_t)0x3f34, (q15_t)0x4a1e, (q15_t)0x3f32,
+    (q15_t)0x4a2b, (q15_t)0x3f30, (q15_t)0x4a37, (q15_t)0x3f2e, (q15_t)0x4a44, (q15_t)0x3f2c, (q15_t)0x4a50, (q15_t)0x3f2a,
+    (q15_t)0x4a5c, (q15_t)0x3f28, (q15_t)0x4a69, (q15_t)0x3f26, (q15_t)0x4a75, (q15_t)0x3f24, (q15_t)0x4a82, (q15_t)0x3f22,
+    (q15_t)0x4a8e, (q15_t)0x3f20, (q15_t)0x4a9a, (q15_t)0x3f1e, (q15_t)0x4aa7, (q15_t)0x3f1c, (q15_t)0x4ab3, (q15_t)0x3f19,
+    (q15_t)0x4ac0, (q15_t)0x3f17, (q15_t)0x4acc, (q15_t)0x3f15, (q15_t)0x4ad8, (q15_t)0x3f13, (q15_t)0x4ae5, (q15_t)0x3f11,
+    (q15_t)0x4af1, (q15_t)0x3f0f, (q15_t)0x4afd, (q15_t)0x3f0d, (q15_t)0x4b0a, (q15_t)0x3f0a, (q15_t)0x4b16, (q15_t)0x3f08,
+    (q15_t)0x4b23, (q15_t)0x3f06, (q15_t)0x4b2f, (q15_t)0x3f04, (q15_t)0x4b3b, (q15_t)0x3f02, (q15_t)0x4b48, (q15_t)0x3f00,
+    (q15_t)0x4b54, (q15_t)0x3efd, (q15_t)0x4b60, (q15_t)0x3efb, (q15_t)0x4b6d, (q15_t)0x3ef9, (q15_t)0x4b79, (q15_t)0x3ef7,
+    (q15_t)0x4b85, (q15_t)0x3ef4, (q15_t)0x4b92, (q15_t)0x3ef2, (q15_t)0x4b9e, (q15_t)0x3ef0, (q15_t)0x4bab, (q15_t)0x3eed,
+    (q15_t)0x4bb7, (q15_t)0x3eeb, (q15_t)0x4bc3, (q15_t)0x3ee9, (q15_t)0x4bd0, (q15_t)0x3ee7, (q15_t)0x4bdc, (q15_t)0x3ee4,
+    (q15_t)0x4be8, (q15_t)0x3ee2, (q15_t)0x4bf5, (q15_t)0x3ee0, (q15_t)0x4c01, (q15_t)0x3edd, (q15_t)0x4c0d, (q15_t)0x3edb,
+    (q15_t)0x4c1a, (q15_t)0x3ed8, (q15_t)0x4c26, (q15_t)0x3ed6, (q15_t)0x4c32, (q15_t)0x3ed4, (q15_t)0x4c3f, (q15_t)0x3ed1,
+    (q15_t)0x4c4b, (q15_t)0x3ecf, (q15_t)0x4c57, (q15_t)0x3ecc, (q15_t)0x4c64, (q15_t)0x3eca, (q15_t)0x4c70, (q15_t)0x3ec8,
+    (q15_t)0x4c7c, (q15_t)0x3ec5, (q15_t)0x4c89, (q15_t)0x3ec3, (q15_t)0x4c95, (q15_t)0x3ec0, (q15_t)0x4ca1, (q15_t)0x3ebe,
+    (q15_t)0x4cae, (q15_t)0x3ebb, (q15_t)0x4cba, (q15_t)0x3eb9, (q15_t)0x4cc6, (q15_t)0x3eb6, (q15_t)0x4cd3, (q15_t)0x3eb4,
+    (q15_t)0x4cdf, (q15_t)0x3eb1, (q15_t)0x4ceb, (q15_t)0x3eaf, (q15_t)0x4cf8, (q15_t)0x3eac, (q15_t)0x4d04, (q15_t)0x3eaa,
+    (q15_t)0x4d10, (q15_t)0x3ea7, (q15_t)0x4d1c, (q15_t)0x3ea5, (q15_t)0x4d29, (q15_t)0x3ea2, (q15_t)0x4d35, (q15_t)0x3e9f,
+    (q15_t)0x4d41, (q15_t)0x3e9d, (q15_t)0x4d4e, (q15_t)0x3e9a, (q15_t)0x4d5a, (q15_t)0x3e98, (q15_t)0x4d66, (q15_t)0x3e95,
+    (q15_t)0x4d72, (q15_t)0x3e92, (q15_t)0x4d7f, (q15_t)0x3e90, (q15_t)0x4d8b, (q15_t)0x3e8d, (q15_t)0x4d97, (q15_t)0x3e8a,
+    (q15_t)0x4da4, (q15_t)0x3e88, (q15_t)0x4db0, (q15_t)0x3e85, (q15_t)0x4dbc, (q15_t)0x3e82, (q15_t)0x4dc8, (q15_t)0x3e80,
+    (q15_t)0x4dd5, (q15_t)0x3e7d, (q15_t)0x4de1, (q15_t)0x3e7a, (q15_t)0x4ded, (q15_t)0x3e77, (q15_t)0x4df9, (q15_t)0x3e75,
+    (q15_t)0x4e06, (q15_t)0x3e72, (q15_t)0x4e12, (q15_t)0x3e6f, (q15_t)0x4e1e, (q15_t)0x3e6c, (q15_t)0x4e2b, (q15_t)0x3e6a,
+    (q15_t)0x4e37, (q15_t)0x3e67, (q15_t)0x4e43, (q15_t)0x3e64, (q15_t)0x4e4f, (q15_t)0x3e61, (q15_t)0x4e5c, (q15_t)0x3e5e,
+    (q15_t)0x4e68, (q15_t)0x3e5c, (q15_t)0x4e74, (q15_t)0x3e59, (q15_t)0x4e80, (q15_t)0x3e56, (q15_t)0x4e8c, (q15_t)0x3e53,
+    (q15_t)0x4e99, (q15_t)0x3e50, (q15_t)0x4ea5, (q15_t)0x3e4d, (q15_t)0x4eb1, (q15_t)0x3e4a, (q15_t)0x4ebd, (q15_t)0x3e48,
+    (q15_t)0x4eca, (q15_t)0x3e45, (q15_t)0x4ed6, (q15_t)0x3e42, (q15_t)0x4ee2, (q15_t)0x3e3f, (q15_t)0x4eee, (q15_t)0x3e3c,
+    (q15_t)0x4efb, (q15_t)0x3e39, (q15_t)0x4f07, (q15_t)0x3e36, (q15_t)0x4f13, (q15_t)0x3e33, (q15_t)0x4f1f, (q15_t)0x3e30,
+    (q15_t)0x4f2b, (q15_t)0x3e2d, (q15_t)0x4f38, (q15_t)0x3e2a, (q15_t)0x4f44, (q15_t)0x3e27, (q15_t)0x4f50, (q15_t)0x3e24,
+    (q15_t)0x4f5c, (q15_t)0x3e21, (q15_t)0x4f68, (q15_t)0x3e1e, (q15_t)0x4f75, (q15_t)0x3e1b, (q15_t)0x4f81, (q15_t)0x3e18,
+    (q15_t)0x4f8d, (q15_t)0x3e15, (q15_t)0x4f99, (q15_t)0x3e12, (q15_t)0x4fa5, (q15_t)0x3e0f, (q15_t)0x4fb2, (q15_t)0x3e0c,
+    (q15_t)0x4fbe, (q15_t)0x3e09, (q15_t)0x4fca, (q15_t)0x3e06, (q15_t)0x4fd6, (q15_t)0x3e03, (q15_t)0x4fe2, (q15_t)0x3dff,
+    (q15_t)0x4fee, (q15_t)0x3dfc, (q15_t)0x4ffb, (q15_t)0x3df9, (q15_t)0x5007, (q15_t)0x3df6, (q15_t)0x5013, (q15_t)0x3df3,
+    (q15_t)0x501f, (q15_t)0x3df0, (q15_t)0x502b, (q15_t)0x3ded, (q15_t)0x5037, (q15_t)0x3de9, (q15_t)0x5044, (q15_t)0x3de6,
+    (q15_t)0x5050, (q15_t)0x3de3, (q15_t)0x505c, (q15_t)0x3de0, (q15_t)0x5068, (q15_t)0x3ddd, (q15_t)0x5074, (q15_t)0x3dd9,
+    (q15_t)0x5080, (q15_t)0x3dd6, (q15_t)0x508c, (q15_t)0x3dd3, (q15_t)0x5099, (q15_t)0x3dd0, (q15_t)0x50a5, (q15_t)0x3dcc,
+    (q15_t)0x50b1, (q15_t)0x3dc9, (q15_t)0x50bd, (q15_t)0x3dc6, (q15_t)0x50c9, (q15_t)0x3dc2, (q15_t)0x50d5, (q15_t)0x3dbf,
+    (q15_t)0x50e1, (q15_t)0x3dbc, (q15_t)0x50ed, (q15_t)0x3db9, (q15_t)0x50fa, (q15_t)0x3db5, (q15_t)0x5106, (q15_t)0x3db2,
+    (q15_t)0x5112, (q15_t)0x3daf, (q15_t)0x511e, (q15_t)0x3dab, (q15_t)0x512a, (q15_t)0x3da8, (q15_t)0x5136, (q15_t)0x3da4,
+    (q15_t)0x5142, (q15_t)0x3da1, (q15_t)0x514e, (q15_t)0x3d9e, (q15_t)0x515a, (q15_t)0x3d9a, (q15_t)0x5167, (q15_t)0x3d97,
+    (q15_t)0x5173, (q15_t)0x3d93, (q15_t)0x517f, (q15_t)0x3d90, (q15_t)0x518b, (q15_t)0x3d8d, (q15_t)0x5197, (q15_t)0x3d89,
+    (q15_t)0x51a3, (q15_t)0x3d86, (q15_t)0x51af, (q15_t)0x3d82, (q15_t)0x51bb, (q15_t)0x3d7f, (q15_t)0x51c7, (q15_t)0x3d7b,
+    (q15_t)0x51d3, (q15_t)0x3d78, (q15_t)0x51df, (q15_t)0x3d74, (q15_t)0x51eb, (q15_t)0x3d71, (q15_t)0x51f7, (q15_t)0x3d6d,
+    (q15_t)0x5204, (q15_t)0x3d6a, (q15_t)0x5210, (q15_t)0x3d66, (q15_t)0x521c, (q15_t)0x3d63, (q15_t)0x5228, (q15_t)0x3d5f,
+    (q15_t)0x5234, (q15_t)0x3d5b, (q15_t)0x5240, (q15_t)0x3d58, (q15_t)0x524c, (q15_t)0x3d54, (q15_t)0x5258, (q15_t)0x3d51,
+    (q15_t)0x5264, (q15_t)0x3d4d, (q15_t)0x5270, (q15_t)0x3d49, (q15_t)0x527c, (q15_t)0x3d46, (q15_t)0x5288, (q15_t)0x3d42,
+    (q15_t)0x5294, (q15_t)0x3d3f, (q15_t)0x52a0, (q15_t)0x3d3b, (q15_t)0x52ac, (q15_t)0x3d37, (q15_t)0x52b8, (q15_t)0x3d34,
+    (q15_t)0x52c4, (q15_t)0x3d30, (q15_t)0x52d0, (q15_t)0x3d2c, (q15_t)0x52dc, (q15_t)0x3d28, (q15_t)0x52e8, (q15_t)0x3d25,
+    (q15_t)0x52f4, (q15_t)0x3d21, (q15_t)0x5300, (q15_t)0x3d1d, (q15_t)0x530c, (q15_t)0x3d1a, (q15_t)0x5318, (q15_t)0x3d16,
+    (q15_t)0x5324, (q15_t)0x3d12, (q15_t)0x5330, (q15_t)0x3d0e, (q15_t)0x533c, (q15_t)0x3d0b, (q15_t)0x5348, (q15_t)0x3d07,
+    (q15_t)0x5354, (q15_t)0x3d03, (q15_t)0x5360, (q15_t)0x3cff, (q15_t)0x536c, (q15_t)0x3cfb, (q15_t)0x5378, (q15_t)0x3cf8,
+    (q15_t)0x5384, (q15_t)0x3cf4, (q15_t)0x5390, (q15_t)0x3cf0, (q15_t)0x539c, (q15_t)0x3cec, (q15_t)0x53a8, (q15_t)0x3ce8,
+    (q15_t)0x53b4, (q15_t)0x3ce4, (q15_t)0x53c0, (q15_t)0x3ce0, (q15_t)0x53cc, (q15_t)0x3cdd, (q15_t)0x53d8, (q15_t)0x3cd9,
+    (q15_t)0x53e4, (q15_t)0x3cd5, (q15_t)0x53f0, (q15_t)0x3cd1, (q15_t)0x53fb, (q15_t)0x3ccd, (q15_t)0x5407, (q15_t)0x3cc9,
+    (q15_t)0x5413, (q15_t)0x3cc5, (q15_t)0x541f, (q15_t)0x3cc1, (q15_t)0x542b, (q15_t)0x3cbd, (q15_t)0x5437, (q15_t)0x3cb9,
+    (q15_t)0x5443, (q15_t)0x3cb5, (q15_t)0x544f, (q15_t)0x3cb1, (q15_t)0x545b, (q15_t)0x3cad, (q15_t)0x5467, (q15_t)0x3ca9,
+    (q15_t)0x5473, (q15_t)0x3ca5, (q15_t)0x547f, (q15_t)0x3ca1, (q15_t)0x548b, (q15_t)0x3c9d, (q15_t)0x5496, (q15_t)0x3c99,
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+    (q15_t)0x62e7, (q15_t)0x35a5, (q15_t)0x62f1, (q15_t)0x359f, (q15_t)0x62fc, (q15_t)0x3598, (q15_t)0x6306, (q15_t)0x3591,
+    (q15_t)0x6311, (q15_t)0x358a, (q15_t)0x631b, (q15_t)0x3583, (q15_t)0x6326, (q15_t)0x357c, (q15_t)0x6330, (q15_t)0x3575,
+    (q15_t)0x633b, (q15_t)0x356e, (q15_t)0x6345, (q15_t)0x3567, (q15_t)0x6350, (q15_t)0x3561, (q15_t)0x635a, (q15_t)0x355a,
+    (q15_t)0x6365, (q15_t)0x3553, (q15_t)0x636f, (q15_t)0x354c, (q15_t)0x637a, (q15_t)0x3545, (q15_t)0x6384, (q15_t)0x353e,
+    (q15_t)0x638e, (q15_t)0x3537, (q15_t)0x6399, (q15_t)0x3530, (q15_t)0x63a3, (q15_t)0x3529, (q15_t)0x63ae, (q15_t)0x3522,
+    (q15_t)0x63b8, (q15_t)0x351b, (q15_t)0x63c3, (q15_t)0x3514, (q15_t)0x63cd, (q15_t)0x350d, (q15_t)0x63d7, (q15_t)0x3506,
+    (q15_t)0x63e2, (q15_t)0x34ff, (q15_t)0x63ec, (q15_t)0x34f8, (q15_t)0x63f7, (q15_t)0x34f1, (q15_t)0x6401, (q15_t)0x34ea,
+    (q15_t)0x640b, (q15_t)0x34e2, (q15_t)0x6416, (q15_t)0x34db, (q15_t)0x6420, (q15_t)0x34d4, (q15_t)0x642b, (q15_t)0x34cd,
+    (q15_t)0x6435, (q15_t)0x34c6, (q15_t)0x643f, (q15_t)0x34bf, (q15_t)0x644a, (q15_t)0x34b8, (q15_t)0x6454, (q15_t)0x34b1,
+    (q15_t)0x645e, (q15_t)0x34aa, (q15_t)0x6469, (q15_t)0x34a2, (q15_t)0x6473, (q15_t)0x349b, (q15_t)0x647d, (q15_t)0x3494,
+    (q15_t)0x6488, (q15_t)0x348d, (q15_t)0x6492, (q15_t)0x3486, (q15_t)0x649c, (q15_t)0x347f, (q15_t)0x64a7, (q15_t)0x3477,
+    (q15_t)0x64b1, (q15_t)0x3470, (q15_t)0x64bb, (q15_t)0x3469, (q15_t)0x64c5, (q15_t)0x3462, (q15_t)0x64d0, (q15_t)0x345b,
+    (q15_t)0x64da, (q15_t)0x3453, (q15_t)0x64e4, (q15_t)0x344c, (q15_t)0x64ef, (q15_t)0x3445, (q15_t)0x64f9, (q15_t)0x343e,
+    (q15_t)0x6503, (q15_t)0x3436, (q15_t)0x650d, (q15_t)0x342f, (q15_t)0x6518, (q15_t)0x3428, (q15_t)0x6522, (q15_t)0x3420,
+    (q15_t)0x652c, (q15_t)0x3419, (q15_t)0x6536, (q15_t)0x3412, (q15_t)0x6541, (q15_t)0x340b, (q15_t)0x654b, (q15_t)0x3403,
+    (q15_t)0x6555, (q15_t)0x33fc, (q15_t)0x655f, (q15_t)0x33f5, (q15_t)0x6569, (q15_t)0x33ed, (q15_t)0x6574, (q15_t)0x33e6,
+    (q15_t)0x657e, (q15_t)0x33df, (q15_t)0x6588, (q15_t)0x33d7, (q15_t)0x6592, (q15_t)0x33d0, (q15_t)0x659c, (q15_t)0x33c8,
+    (q15_t)0x65a6, (q15_t)0x33c1, (q15_t)0x65b1, (q15_t)0x33ba, (q15_t)0x65bb, (q15_t)0x33b2, (q15_t)0x65c5, (q15_t)0x33ab,
+    (q15_t)0x65cf, (q15_t)0x33a3, (q15_t)0x65d9, (q15_t)0x339c, (q15_t)0x65e3, (q15_t)0x3395, (q15_t)0x65ed, (q15_t)0x338d,
+    (q15_t)0x65f8, (q15_t)0x3386, (q15_t)0x6602, (q15_t)0x337e, (q15_t)0x660c, (q15_t)0x3377, (q15_t)0x6616, (q15_t)0x336f,
+    (q15_t)0x6620, (q15_t)0x3368, (q15_t)0x662a, (q15_t)0x3360, (q15_t)0x6634, (q15_t)0x3359, (q15_t)0x663e, (q15_t)0x3351,
+    (q15_t)0x6648, (q15_t)0x334a, (q15_t)0x6652, (q15_t)0x3342, (q15_t)0x665c, (q15_t)0x333b, (q15_t)0x6666, (q15_t)0x3333,
+    (q15_t)0x6671, (q15_t)0x332c, (q15_t)0x667b, (q15_t)0x3324, (q15_t)0x6685, (q15_t)0x331d, (q15_t)0x668f, (q15_t)0x3315,
+    (q15_t)0x6699, (q15_t)0x330d, (q15_t)0x66a3, (q15_t)0x3306, (q15_t)0x66ad, (q15_t)0x32fe, (q15_t)0x66b7, (q15_t)0x32f7,
+    (q15_t)0x66c1, (q15_t)0x32ef, (q15_t)0x66cb, (q15_t)0x32e7, (q15_t)0x66d5, (q15_t)0x32e0, (q15_t)0x66df, (q15_t)0x32d8,
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+    (q15_t)0x6711, (q15_t)0x32b2, (q15_t)0x671a, (q15_t)0x32aa, (q15_t)0x6724, (q15_t)0x32a3, (q15_t)0x672e, (q15_t)0x329b,
+    (q15_t)0x6738, (q15_t)0x3293, (q15_t)0x6742, (q15_t)0x328b, (q15_t)0x674c, (q15_t)0x3284, (q15_t)0x6756, (q15_t)0x327c,
+    (q15_t)0x6760, (q15_t)0x3274, (q15_t)0x676a, (q15_t)0x326d, (q15_t)0x6774, (q15_t)0x3265, (q15_t)0x677e, (q15_t)0x325d,
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+    (q15_t)0x6bfd, (q15_t)0x2e7d, (q15_t)0x6c06, (q15_t)0x2e74, (q15_t)0x6c0f, (q15_t)0x2e6b, (q15_t)0x6c18, (q15_t)0x2e63,
+    (q15_t)0x6c21, (q15_t)0x2e5a, (q15_t)0x6c2b, (q15_t)0x2e51, (q15_t)0x6c34, (q15_t)0x2e49, (q15_t)0x6c3d, (q15_t)0x2e40,
+    (q15_t)0x6c46, (q15_t)0x2e37, (q15_t)0x6c4f, (q15_t)0x2e2f, (q15_t)0x6c58, (q15_t)0x2e26, (q15_t)0x6c61, (q15_t)0x2e1d,
+    (q15_t)0x6c6a, (q15_t)0x2e15, (q15_t)0x6c73, (q15_t)0x2e0c, (q15_t)0x6c7c, (q15_t)0x2e03, (q15_t)0x6c85, (q15_t)0x2dfa,
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+    (q15_t)0x6cd6, (q15_t)0x2dab, (q15_t)0x6cdf, (q15_t)0x2da3, (q15_t)0x6ce8, (q15_t)0x2d9a, (q15_t)0x6cf1, (q15_t)0x2d91,
+    (q15_t)0x6cfa, (q15_t)0x2d88, (q15_t)0x6d03, (q15_t)0x2d7f, (q15_t)0x6d0c, (q15_t)0x2d76, (q15_t)0x6d15, (q15_t)0x2d6e,
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+    (q15_t)0x6f06, (q15_t)0x2b6a, (q15_t)0x6f0e, (q15_t)0x2b61, (q15_t)0x6f17, (q15_t)0x2b58, (q15_t)0x6f20, (q15_t)0x2b4e,
+    (q15_t)0x6f28, (q15_t)0x2b45, (q15_t)0x6f30, (q15_t)0x2b3c, (q15_t)0x6f39, (q15_t)0x2b33, (q15_t)0x6f41, (q15_t)0x2b29,
+    (q15_t)0x6f4a, (q15_t)0x2b20, (q15_t)0x6f52, (q15_t)0x2b17, (q15_t)0x6f5b, (q15_t)0x2b0d, (q15_t)0x6f63, (q15_t)0x2b04,
+    (q15_t)0x6f6c, (q15_t)0x2afb, (q15_t)0x6f74, (q15_t)0x2af2, (q15_t)0x6f7d, (q15_t)0x2ae8, (q15_t)0x6f85, (q15_t)0x2adf,
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+    (q15_t)0x70d8, (q15_t)0x295b, (q15_t)0x70e0, (q15_t)0x2951, (q15_t)0x70e8, (q15_t)0x2948, (q15_t)0x70f0, (q15_t)0x293e,
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+    (q15_t)0x7119, (q15_t)0x290e, (q15_t)0x7121, (q15_t)0x2904, (q15_t)0x7129, (q15_t)0x28fb, (q15_t)0x7131, (q15_t)0x28f1,
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+    (q15_t)0x785a, (q15_t)0x1e58, (q15_t)0x7860, (q15_t)0x1e4d, (q15_t)0x7866, (q15_t)0x1e42, (q15_t)0x786b, (q15_t)0x1e36,
+    (q15_t)0x7871, (q15_t)0x1e2b, (q15_t)0x7877, (q15_t)0x1e20, (q15_t)0x787d, (q15_t)0x1e15, (q15_t)0x7883, (q15_t)0x1e0a,
+    (q15_t)0x7889, (q15_t)0x1dff, (q15_t)0x788f, (q15_t)0x1df4, (q15_t)0x7895, (q15_t)0x1de9, (q15_t)0x789b, (q15_t)0x1dde,
+    (q15_t)0x78a1, (q15_t)0x1dd3, (q15_t)0x78a6, (q15_t)0x1dc7, (q15_t)0x78ac, (q15_t)0x1dbc, (q15_t)0x78b2, (q15_t)0x1db1,
+    (q15_t)0x78b8, (q15_t)0x1da6, (q15_t)0x78be, (q15_t)0x1d9b, (q15_t)0x78c3, (q15_t)0x1d90, (q15_t)0x78c9, (q15_t)0x1d85,
+    (q15_t)0x78cf, (q15_t)0x1d79, (q15_t)0x78d5, (q15_t)0x1d6e, (q15_t)0x78db, (q15_t)0x1d63, (q15_t)0x78e0, (q15_t)0x1d58,
+    (q15_t)0x78e6, (q15_t)0x1d4d, (q15_t)0x78ec, (q15_t)0x1d42, (q15_t)0x78f2, (q15_t)0x1d36, (q15_t)0x78f7, (q15_t)0x1d2b,
+    (q15_t)0x78fd, (q15_t)0x1d20, (q15_t)0x7903, (q15_t)0x1d15, (q15_t)0x7909, (q15_t)0x1d0a, (q15_t)0x790e, (q15_t)0x1cff,
+    (q15_t)0x7914, (q15_t)0x1cf3, (q15_t)0x791a, (q15_t)0x1ce8, (q15_t)0x791f, (q15_t)0x1cdd, (q15_t)0x7925, (q15_t)0x1cd2,
+    (q15_t)0x792b, (q15_t)0x1cc6, (q15_t)0x7930, (q15_t)0x1cbb, (q15_t)0x7936, (q15_t)0x1cb0, (q15_t)0x793b, (q15_t)0x1ca5,
+    (q15_t)0x7941, (q15_t)0x1c99, (q15_t)0x7947, (q15_t)0x1c8e, (q15_t)0x794c, (q15_t)0x1c83, (q15_t)0x7952, (q15_t)0x1c78,
+    (q15_t)0x7958, (q15_t)0x1c6c, (q15_t)0x795d, (q15_t)0x1c61, (q15_t)0x7963, (q15_t)0x1c56, (q15_t)0x7968, (q15_t)0x1c4b,
+    (q15_t)0x796e, (q15_t)0x1c3f, (q15_t)0x7973, (q15_t)0x1c34, (q15_t)0x7979, (q15_t)0x1c29, (q15_t)0x797e, (q15_t)0x1c1e,
+    (q15_t)0x7984, (q15_t)0x1c12, (q15_t)0x7989, (q15_t)0x1c07, (q15_t)0x798f, (q15_t)0x1bfc, (q15_t)0x7994, (q15_t)0x1bf0,
+    (q15_t)0x799a, (q15_t)0x1be5, (q15_t)0x799f, (q15_t)0x1bda, (q15_t)0x79a5, (q15_t)0x1bce, (q15_t)0x79aa, (q15_t)0x1bc3,
+    (q15_t)0x79b0, (q15_t)0x1bb8, (q15_t)0x79b5, (q15_t)0x1bac, (q15_t)0x79bb, (q15_t)0x1ba1, (q15_t)0x79c0, (q15_t)0x1b96,
+    (q15_t)0x79c5, (q15_t)0x1b8a, (q15_t)0x79cb, (q15_t)0x1b7f, (q15_t)0x79d0, (q15_t)0x1b74, (q15_t)0x79d6, (q15_t)0x1b68,
+    (q15_t)0x79db, (q15_t)0x1b5d, (q15_t)0x79e0, (q15_t)0x1b52, (q15_t)0x79e6, (q15_t)0x1b46, (q15_t)0x79eb, (q15_t)0x1b3b,
+    (q15_t)0x79f0, (q15_t)0x1b30, (q15_t)0x79f6, (q15_t)0x1b24, (q15_t)0x79fb, (q15_t)0x1b19, (q15_t)0x7a00, (q15_t)0x1b0d,
+    (q15_t)0x7a06, (q15_t)0x1b02, (q15_t)0x7a0b, (q15_t)0x1af7, (q15_t)0x7a10, (q15_t)0x1aeb, (q15_t)0x7a16, (q15_t)0x1ae0,
+    (q15_t)0x7a1b, (q15_t)0x1ad4, (q15_t)0x7a20, (q15_t)0x1ac9, (q15_t)0x7a25, (q15_t)0x1abe, (q15_t)0x7a2b, (q15_t)0x1ab2,
+    (q15_t)0x7a30, (q15_t)0x1aa7, (q15_t)0x7a35, (q15_t)0x1a9b, (q15_t)0x7a3a, (q15_t)0x1a90, (q15_t)0x7a3f, (q15_t)0x1a84,
+    (q15_t)0x7a45, (q15_t)0x1a79, (q15_t)0x7a4a, (q15_t)0x1a6e, (q15_t)0x7a4f, (q15_t)0x1a62, (q15_t)0x7a54, (q15_t)0x1a57,
+    (q15_t)0x7a59, (q15_t)0x1a4b, (q15_t)0x7a5f, (q15_t)0x1a40, (q15_t)0x7a64, (q15_t)0x1a34, (q15_t)0x7a69, (q15_t)0x1a29,
+    (q15_t)0x7a6e, (q15_t)0x1a1d, (q15_t)0x7a73, (q15_t)0x1a12, (q15_t)0x7a78, (q15_t)0x1a06, (q15_t)0x7a7d, (q15_t)0x19fb,
+    (q15_t)0x7a82, (q15_t)0x19ef, (q15_t)0x7a88, (q15_t)0x19e4, (q15_t)0x7a8d, (q15_t)0x19d8, (q15_t)0x7a92, (q15_t)0x19cd,
+    (q15_t)0x7a97, (q15_t)0x19c1, (q15_t)0x7a9c, (q15_t)0x19b6, (q15_t)0x7aa1, (q15_t)0x19aa, (q15_t)0x7aa6, (q15_t)0x199f,
+    (q15_t)0x7aab, (q15_t)0x1993, (q15_t)0x7ab0, (q15_t)0x1988, (q15_t)0x7ab5, (q15_t)0x197c, (q15_t)0x7aba, (q15_t)0x1971,
+    (q15_t)0x7abf, (q15_t)0x1965, (q15_t)0x7ac4, (q15_t)0x195a, (q15_t)0x7ac9, (q15_t)0x194e, (q15_t)0x7ace, (q15_t)0x1943,
+    (q15_t)0x7ad3, (q15_t)0x1937, (q15_t)0x7ad8, (q15_t)0x192c, (q15_t)0x7add, (q15_t)0x1920, (q15_t)0x7ae2, (q15_t)0x1914,
+    (q15_t)0x7ae6, (q15_t)0x1909, (q15_t)0x7aeb, (q15_t)0x18fd, (q15_t)0x7af0, (q15_t)0x18f2, (q15_t)0x7af5, (q15_t)0x18e6,
+    (q15_t)0x7afa, (q15_t)0x18db, (q15_t)0x7aff, (q15_t)0x18cf, (q15_t)0x7b04, (q15_t)0x18c3, (q15_t)0x7b09, (q15_t)0x18b8,
+    (q15_t)0x7b0e, (q15_t)0x18ac, (q15_t)0x7b12, (q15_t)0x18a1, (q15_t)0x7b17, (q15_t)0x1895, (q15_t)0x7b1c, (q15_t)0x1889,
+    (q15_t)0x7b21, (q15_t)0x187e, (q15_t)0x7b26, (q15_t)0x1872, (q15_t)0x7b2a, (q15_t)0x1867, (q15_t)0x7b2f, (q15_t)0x185b,
+    (q15_t)0x7b34, (q15_t)0x184f, (q15_t)0x7b39, (q15_t)0x1844, (q15_t)0x7b3e, (q15_t)0x1838, (q15_t)0x7b42, (q15_t)0x182d,
+    (q15_t)0x7b47, (q15_t)0x1821, (q15_t)0x7b4c, (q15_t)0x1815, (q15_t)0x7b50, (q15_t)0x180a, (q15_t)0x7b55, (q15_t)0x17fe,
+    (q15_t)0x7b5a, (q15_t)0x17f2, (q15_t)0x7b5f, (q15_t)0x17e7, (q15_t)0x7b63, (q15_t)0x17db, (q15_t)0x7b68, (q15_t)0x17cf,
+    (q15_t)0x7b6d, (q15_t)0x17c4, (q15_t)0x7b71, (q15_t)0x17b8, (q15_t)0x7b76, (q15_t)0x17ac, (q15_t)0x7b7b, (q15_t)0x17a1,
+    (q15_t)0x7b7f, (q15_t)0x1795, (q15_t)0x7b84, (q15_t)0x1789, (q15_t)0x7b88, (q15_t)0x177e, (q15_t)0x7b8d, (q15_t)0x1772,
+    (q15_t)0x7b92, (q15_t)0x1766, (q15_t)0x7b96, (q15_t)0x175b, (q15_t)0x7b9b, (q15_t)0x174f, (q15_t)0x7b9f, (q15_t)0x1743,
+    (q15_t)0x7ba4, (q15_t)0x1737, (q15_t)0x7ba9, (q15_t)0x172c, (q15_t)0x7bad, (q15_t)0x1720, (q15_t)0x7bb2, (q15_t)0x1714,
+    (q15_t)0x7bb6, (q15_t)0x1709, (q15_t)0x7bbb, (q15_t)0x16fd, (q15_t)0x7bbf, (q15_t)0x16f1, (q15_t)0x7bc4, (q15_t)0x16e5,
+    (q15_t)0x7bc8, (q15_t)0x16da, (q15_t)0x7bcd, (q15_t)0x16ce, (q15_t)0x7bd1, (q15_t)0x16c2, (q15_t)0x7bd6, (q15_t)0x16b6,
+    (q15_t)0x7bda, (q15_t)0x16ab, (q15_t)0x7bde, (q15_t)0x169f, (q15_t)0x7be3, (q15_t)0x1693, (q15_t)0x7be7, (q15_t)0x1687,
+    (q15_t)0x7bec, (q15_t)0x167c, (q15_t)0x7bf0, (q15_t)0x1670, (q15_t)0x7bf5, (q15_t)0x1664, (q15_t)0x7bf9, (q15_t)0x1658,
+    (q15_t)0x7bfd, (q15_t)0x164c, (q15_t)0x7c02, (q15_t)0x1641, (q15_t)0x7c06, (q15_t)0x1635, (q15_t)0x7c0a, (q15_t)0x1629,
+    (q15_t)0x7c0f, (q15_t)0x161d, (q15_t)0x7c13, (q15_t)0x1612, (q15_t)0x7c17, (q15_t)0x1606, (q15_t)0x7c1c, (q15_t)0x15fa,
+    (q15_t)0x7c20, (q15_t)0x15ee, (q15_t)0x7c24, (q15_t)0x15e2, (q15_t)0x7c29, (q15_t)0x15d7, (q15_t)0x7c2d, (q15_t)0x15cb,
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+    (q15_t)0x7c42, (q15_t)0x1590, (q15_t)0x7c46, (q15_t)0x1584, (q15_t)0x7c4b, (q15_t)0x1578, (q15_t)0x7c4f, (q15_t)0x156c,
+    (q15_t)0x7c53, (q15_t)0x1560, (q15_t)0x7c57, (q15_t)0x1554, (q15_t)0x7c5b, (q15_t)0x1549, (q15_t)0x7c60, (q15_t)0x153d,
+    (q15_t)0x7c64, (q15_t)0x1531, (q15_t)0x7c68, (q15_t)0x1525, (q15_t)0x7c6c, (q15_t)0x1519, (q15_t)0x7c70, (q15_t)0x150d,
+    (q15_t)0x7c74, (q15_t)0x1501, (q15_t)0x7c79, (q15_t)0x14f6, (q15_t)0x7c7d, (q15_t)0x14ea, (q15_t)0x7c81, (q15_t)0x14de,
+    (q15_t)0x7c85, (q15_t)0x14d2, (q15_t)0x7c89, (q15_t)0x14c6, (q15_t)0x7c8d, (q15_t)0x14ba, (q15_t)0x7c91, (q15_t)0x14ae,
+    (q15_t)0x7c95, (q15_t)0x14a2, (q15_t)0x7c99, (q15_t)0x1496, (q15_t)0x7c9d, (q15_t)0x148b, (q15_t)0x7ca1, (q15_t)0x147f,
+    (q15_t)0x7ca5, (q15_t)0x1473, (q15_t)0x7ca9, (q15_t)0x1467, (q15_t)0x7cad, (q15_t)0x145b, (q15_t)0x7cb1, (q15_t)0x144f,
+    (q15_t)0x7cb5, (q15_t)0x1443, (q15_t)0x7cb9, (q15_t)0x1437, (q15_t)0x7cbd, (q15_t)0x142b, (q15_t)0x7cc1, (q15_t)0x141f,
+    (q15_t)0x7cc5, (q15_t)0x1413, (q15_t)0x7cc9, (q15_t)0x1407, (q15_t)0x7ccd, (q15_t)0x13fb, (q15_t)0x7cd1, (q15_t)0x13f0,
+    (q15_t)0x7cd5, (q15_t)0x13e4, (q15_t)0x7cd9, (q15_t)0x13d8, (q15_t)0x7cdd, (q15_t)0x13cc, (q15_t)0x7ce0, (q15_t)0x13c0,
+    (q15_t)0x7ce4, (q15_t)0x13b4, (q15_t)0x7ce8, (q15_t)0x13a8, (q15_t)0x7cec, (q15_t)0x139c, (q15_t)0x7cf0, (q15_t)0x1390,
+    (q15_t)0x7cf4, (q15_t)0x1384, (q15_t)0x7cf8, (q15_t)0x1378, (q15_t)0x7cfb, (q15_t)0x136c, (q15_t)0x7cff, (q15_t)0x1360,
+    (q15_t)0x7d03, (q15_t)0x1354, (q15_t)0x7d07, (q15_t)0x1348, (q15_t)0x7d0b, (q15_t)0x133c, (q15_t)0x7d0e, (q15_t)0x1330,
+    (q15_t)0x7d12, (q15_t)0x1324, (q15_t)0x7d16, (q15_t)0x1318, (q15_t)0x7d1a, (q15_t)0x130c, (q15_t)0x7d1d, (q15_t)0x1300,
+    (q15_t)0x7d21, (q15_t)0x12f4, (q15_t)0x7d25, (q15_t)0x12e8, (q15_t)0x7d28, (q15_t)0x12dc, (q15_t)0x7d2c, (q15_t)0x12d0,
+    (q15_t)0x7d30, (q15_t)0x12c4, (q15_t)0x7d34, (q15_t)0x12b8, (q15_t)0x7d37, (q15_t)0x12ac, (q15_t)0x7d3b, (q15_t)0x12a0,
+    (q15_t)0x7d3f, (q15_t)0x1294, (q15_t)0x7d42, (q15_t)0x1288, (q15_t)0x7d46, (q15_t)0x127c, (q15_t)0x7d49, (q15_t)0x1270,
+    (q15_t)0x7d4d, (q15_t)0x1264, (q15_t)0x7d51, (q15_t)0x1258, (q15_t)0x7d54, (q15_t)0x124c, (q15_t)0x7d58, (q15_t)0x1240,
+    (q15_t)0x7d5b, (q15_t)0x1234, (q15_t)0x7d5f, (q15_t)0x1228, (q15_t)0x7d63, (q15_t)0x121c, (q15_t)0x7d66, (q15_t)0x1210,
+    (q15_t)0x7d6a, (q15_t)0x1204, (q15_t)0x7d6d, (q15_t)0x11f7, (q15_t)0x7d71, (q15_t)0x11eb, (q15_t)0x7d74, (q15_t)0x11df,
+    (q15_t)0x7d78, (q15_t)0x11d3, (q15_t)0x7d7b, (q15_t)0x11c7, (q15_t)0x7d7f, (q15_t)0x11bb, (q15_t)0x7d82, (q15_t)0x11af,
+    (q15_t)0x7d86, (q15_t)0x11a3, (q15_t)0x7d89, (q15_t)0x1197, (q15_t)0x7d8d, (q15_t)0x118b, (q15_t)0x7d90, (q15_t)0x117f,
+    (q15_t)0x7d93, (q15_t)0x1173, (q15_t)0x7d97, (q15_t)0x1167, (q15_t)0x7d9a, (q15_t)0x115a, (q15_t)0x7d9e, (q15_t)0x114e,
+    (q15_t)0x7da1, (q15_t)0x1142, (q15_t)0x7da4, (q15_t)0x1136, (q15_t)0x7da8, (q15_t)0x112a, (q15_t)0x7dab, (q15_t)0x111e,
+    (q15_t)0x7daf, (q15_t)0x1112, (q15_t)0x7db2, (q15_t)0x1106, (q15_t)0x7db5, (q15_t)0x10fa, (q15_t)0x7db9, (q15_t)0x10ed,
+    (q15_t)0x7dbc, (q15_t)0x10e1, (q15_t)0x7dbf, (q15_t)0x10d5, (q15_t)0x7dc2, (q15_t)0x10c9, (q15_t)0x7dc6, (q15_t)0x10bd,
+    (q15_t)0x7dc9, (q15_t)0x10b1, (q15_t)0x7dcc, (q15_t)0x10a5, (q15_t)0x7dd0, (q15_t)0x1099, (q15_t)0x7dd3, (q15_t)0x108c,
+    (q15_t)0x7dd6, (q15_t)0x1080, (q15_t)0x7dd9, (q15_t)0x1074, (q15_t)0x7ddd, (q15_t)0x1068, (q15_t)0x7de0, (q15_t)0x105c,
+    (q15_t)0x7de3, (q15_t)0x1050, (q15_t)0x7de6, (q15_t)0x1044, (q15_t)0x7de9, (q15_t)0x1037, (q15_t)0x7ded, (q15_t)0x102b,
+    (q15_t)0x7df0, (q15_t)0x101f, (q15_t)0x7df3, (q15_t)0x1013, (q15_t)0x7df6, (q15_t)0x1007, (q15_t)0x7df9, (q15_t)0xffb,
+    (q15_t)0x7dfc, (q15_t)0xfee, (q15_t)0x7dff, (q15_t)0xfe2, (q15_t)0x7e03, (q15_t)0xfd6, (q15_t)0x7e06, (q15_t)0xfca,
+    (q15_t)0x7e09, (q15_t)0xfbe, (q15_t)0x7e0c, (q15_t)0xfb2, (q15_t)0x7e0f, (q15_t)0xfa5, (q15_t)0x7e12, (q15_t)0xf99,
+    (q15_t)0x7e15, (q15_t)0xf8d, (q15_t)0x7e18, (q15_t)0xf81, (q15_t)0x7e1b, (q15_t)0xf75, (q15_t)0x7e1e, (q15_t)0xf68,
+    (q15_t)0x7e21, (q15_t)0xf5c, (q15_t)0x7e24, (q15_t)0xf50, (q15_t)0x7e27, (q15_t)0xf44, (q15_t)0x7e2a, (q15_t)0xf38,
+    (q15_t)0x7e2d, (q15_t)0xf2b, (q15_t)0x7e30, (q15_t)0xf1f, (q15_t)0x7e33, (q15_t)0xf13, (q15_t)0x7e36, (q15_t)0xf07,
+    (q15_t)0x7e39, (q15_t)0xefb, (q15_t)0x7e3c, (q15_t)0xeee, (q15_t)0x7e3f, (q15_t)0xee2, (q15_t)0x7e42, (q15_t)0xed6,
+    (q15_t)0x7e45, (q15_t)0xeca, (q15_t)0x7e48, (q15_t)0xebd, (q15_t)0x7e4a, (q15_t)0xeb1, (q15_t)0x7e4d, (q15_t)0xea5,
+    (q15_t)0x7e50, (q15_t)0xe99, (q15_t)0x7e53, (q15_t)0xe8c, (q15_t)0x7e56, (q15_t)0xe80, (q15_t)0x7e59, (q15_t)0xe74,
+    (q15_t)0x7e5c, (q15_t)0xe68, (q15_t)0x7e5e, (q15_t)0xe5c, (q15_t)0x7e61, (q15_t)0xe4f, (q15_t)0x7e64, (q15_t)0xe43,
+    (q15_t)0x7e67, (q15_t)0xe37, (q15_t)0x7e6a, (q15_t)0xe2b, (q15_t)0x7e6c, (q15_t)0xe1e, (q15_t)0x7e6f, (q15_t)0xe12,
+    (q15_t)0x7e72, (q15_t)0xe06, (q15_t)0x7e75, (q15_t)0xdf9, (q15_t)0x7e77, (q15_t)0xded, (q15_t)0x7e7a, (q15_t)0xde1,
+    (q15_t)0x7e7d, (q15_t)0xdd5, (q15_t)0x7e80, (q15_t)0xdc8, (q15_t)0x7e82, (q15_t)0xdbc, (q15_t)0x7e85, (q15_t)0xdb0,
+    (q15_t)0x7e88, (q15_t)0xda4, (q15_t)0x7e8a, (q15_t)0xd97, (q15_t)0x7e8d, (q15_t)0xd8b, (q15_t)0x7e90, (q15_t)0xd7f,
+    (q15_t)0x7e92, (q15_t)0xd72, (q15_t)0x7e95, (q15_t)0xd66, (q15_t)0x7e98, (q15_t)0xd5a, (q15_t)0x7e9a, (q15_t)0xd4e,
+    (q15_t)0x7e9d, (q15_t)0xd41, (q15_t)0x7e9f, (q15_t)0xd35, (q15_t)0x7ea2, (q15_t)0xd29, (q15_t)0x7ea5, (q15_t)0xd1c,
+    (q15_t)0x7ea7, (q15_t)0xd10, (q15_t)0x7eaa, (q15_t)0xd04, (q15_t)0x7eac, (q15_t)0xcf8, (q15_t)0x7eaf, (q15_t)0xceb,
+    (q15_t)0x7eb1, (q15_t)0xcdf, (q15_t)0x7eb4, (q15_t)0xcd3, (q15_t)0x7eb6, (q15_t)0xcc6, (q15_t)0x7eb9, (q15_t)0xcba,
+    (q15_t)0x7ebb, (q15_t)0xcae, (q15_t)0x7ebe, (q15_t)0xca1, (q15_t)0x7ec0, (q15_t)0xc95, (q15_t)0x7ec3, (q15_t)0xc89,
+    (q15_t)0x7ec5, (q15_t)0xc7c, (q15_t)0x7ec8, (q15_t)0xc70, (q15_t)0x7eca, (q15_t)0xc64, (q15_t)0x7ecc, (q15_t)0xc57,
+    (q15_t)0x7ecf, (q15_t)0xc4b, (q15_t)0x7ed1, (q15_t)0xc3f, (q15_t)0x7ed4, (q15_t)0xc32, (q15_t)0x7ed6, (q15_t)0xc26,
+    (q15_t)0x7ed8, (q15_t)0xc1a, (q15_t)0x7edb, (q15_t)0xc0d, (q15_t)0x7edd, (q15_t)0xc01, (q15_t)0x7ee0, (q15_t)0xbf5,
+    (q15_t)0x7ee2, (q15_t)0xbe8, (q15_t)0x7ee4, (q15_t)0xbdc, (q15_t)0x7ee7, (q15_t)0xbd0, (q15_t)0x7ee9, (q15_t)0xbc3,
+    (q15_t)0x7eeb, (q15_t)0xbb7, (q15_t)0x7eed, (q15_t)0xbab, (q15_t)0x7ef0, (q15_t)0xb9e, (q15_t)0x7ef2, (q15_t)0xb92,
+    (q15_t)0x7ef4, (q15_t)0xb85, (q15_t)0x7ef7, (q15_t)0xb79, (q15_t)0x7ef9, (q15_t)0xb6d, (q15_t)0x7efb, (q15_t)0xb60,
+    (q15_t)0x7efd, (q15_t)0xb54, (q15_t)0x7f00, (q15_t)0xb48, (q15_t)0x7f02, (q15_t)0xb3b, (q15_t)0x7f04, (q15_t)0xb2f,
+    (q15_t)0x7f06, (q15_t)0xb23, (q15_t)0x7f08, (q15_t)0xb16, (q15_t)0x7f0a, (q15_t)0xb0a, (q15_t)0x7f0d, (q15_t)0xafd,
+    (q15_t)0x7f0f, (q15_t)0xaf1, (q15_t)0x7f11, (q15_t)0xae5, (q15_t)0x7f13, (q15_t)0xad8, (q15_t)0x7f15, (q15_t)0xacc,
+    (q15_t)0x7f17, (q15_t)0xac0, (q15_t)0x7f19, (q15_t)0xab3, (q15_t)0x7f1c, (q15_t)0xaa7, (q15_t)0x7f1e, (q15_t)0xa9a,
+    (q15_t)0x7f20, (q15_t)0xa8e, (q15_t)0x7f22, (q15_t)0xa82, (q15_t)0x7f24, (q15_t)0xa75, (q15_t)0x7f26, (q15_t)0xa69,
+    (q15_t)0x7f28, (q15_t)0xa5c, (q15_t)0x7f2a, (q15_t)0xa50, (q15_t)0x7f2c, (q15_t)0xa44, (q15_t)0x7f2e, (q15_t)0xa37,
+    (q15_t)0x7f30, (q15_t)0xa2b, (q15_t)0x7f32, (q15_t)0xa1e, (q15_t)0x7f34, (q15_t)0xa12, (q15_t)0x7f36, (q15_t)0xa06,
+    (q15_t)0x7f38, (q15_t)0x9f9, (q15_t)0x7f3a, (q15_t)0x9ed, (q15_t)0x7f3c, (q15_t)0x9e0, (q15_t)0x7f3e, (q15_t)0x9d4,
+    (q15_t)0x7f40, (q15_t)0x9c7, (q15_t)0x7f42, (q15_t)0x9bb, (q15_t)0x7f43, (q15_t)0x9af, (q15_t)0x7f45, (q15_t)0x9a2,
+    (q15_t)0x7f47, (q15_t)0x996, (q15_t)0x7f49, (q15_t)0x989, (q15_t)0x7f4b, (q15_t)0x97d, (q15_t)0x7f4d, (q15_t)0x970,
+    (q15_t)0x7f4f, (q15_t)0x964, (q15_t)0x7f51, (q15_t)0x958, (q15_t)0x7f52, (q15_t)0x94b, (q15_t)0x7f54, (q15_t)0x93f,
+    (q15_t)0x7f56, (q15_t)0x932, (q15_t)0x7f58, (q15_t)0x926, (q15_t)0x7f5a, (q15_t)0x919, (q15_t)0x7f5b, (q15_t)0x90d,
+    (q15_t)0x7f5d, (q15_t)0x901, (q15_t)0x7f5f, (q15_t)0x8f4, (q15_t)0x7f61, (q15_t)0x8e8, (q15_t)0x7f62, (q15_t)0x8db,
+    (q15_t)0x7f64, (q15_t)0x8cf, (q15_t)0x7f66, (q15_t)0x8c2, (q15_t)0x7f68, (q15_t)0x8b6, (q15_t)0x7f69, (q15_t)0x8a9,
+    (q15_t)0x7f6b, (q15_t)0x89d, (q15_t)0x7f6d, (q15_t)0x891, (q15_t)0x7f6e, (q15_t)0x884, (q15_t)0x7f70, (q15_t)0x878,
+    (q15_t)0x7f72, (q15_t)0x86b, (q15_t)0x7f73, (q15_t)0x85f, (q15_t)0x7f75, (q15_t)0x852, (q15_t)0x7f77, (q15_t)0x846,
+    (q15_t)0x7f78, (q15_t)0x839, (q15_t)0x7f7a, (q15_t)0x82d, (q15_t)0x7f7b, (q15_t)0x820, (q15_t)0x7f7d, (q15_t)0x814,
+    (q15_t)0x7f7f, (q15_t)0x807, (q15_t)0x7f80, (q15_t)0x7fb, (q15_t)0x7f82, (q15_t)0x7ef, (q15_t)0x7f83, (q15_t)0x7e2,
+    (q15_t)0x7f85, (q15_t)0x7d6, (q15_t)0x7f86, (q15_t)0x7c9, (q15_t)0x7f88, (q15_t)0x7bd, (q15_t)0x7f89, (q15_t)0x7b0,
+    (q15_t)0x7f8b, (q15_t)0x7a4, (q15_t)0x7f8c, (q15_t)0x797, (q15_t)0x7f8e, (q15_t)0x78b, (q15_t)0x7f8f, (q15_t)0x77e,
+    (q15_t)0x7f91, (q15_t)0x772, (q15_t)0x7f92, (q15_t)0x765, (q15_t)0x7f94, (q15_t)0x759, (q15_t)0x7f95, (q15_t)0x74c,
+    (q15_t)0x7f97, (q15_t)0x740, (q15_t)0x7f98, (q15_t)0x733, (q15_t)0x7f99, (q15_t)0x727, (q15_t)0x7f9b, (q15_t)0x71a,
+    (q15_t)0x7f9c, (q15_t)0x70e, (q15_t)0x7f9e, (q15_t)0x701, (q15_t)0x7f9f, (q15_t)0x6f5, (q15_t)0x7fa0, (q15_t)0x6e8,
+    (q15_t)0x7fa2, (q15_t)0x6dc, (q15_t)0x7fa3, (q15_t)0x6cf, (q15_t)0x7fa4, (q15_t)0x6c3, (q15_t)0x7fa6, (q15_t)0x6b6,
+    (q15_t)0x7fa7, (q15_t)0x6aa, (q15_t)0x7fa8, (q15_t)0x69d, (q15_t)0x7faa, (q15_t)0x691, (q15_t)0x7fab, (q15_t)0x684,
+    (q15_t)0x7fac, (q15_t)0x678, (q15_t)0x7fad, (q15_t)0x66b, (q15_t)0x7faf, (q15_t)0x65f, (q15_t)0x7fb0, (q15_t)0x652,
+    (q15_t)0x7fb1, (q15_t)0x646, (q15_t)0x7fb2, (q15_t)0x639, (q15_t)0x7fb4, (q15_t)0x62d, (q15_t)0x7fb5, (q15_t)0x620,
+    (q15_t)0x7fb6, (q15_t)0x614, (q15_t)0x7fb7, (q15_t)0x607, (q15_t)0x7fb8, (q15_t)0x5fb, (q15_t)0x7fb9, (q15_t)0x5ee,
+    (q15_t)0x7fbb, (q15_t)0x5e2, (q15_t)0x7fbc, (q15_t)0x5d5, (q15_t)0x7fbd, (q15_t)0x5c9, (q15_t)0x7fbe, (q15_t)0x5bc,
+    (q15_t)0x7fbf, (q15_t)0x5b0, (q15_t)0x7fc0, (q15_t)0x5a3, (q15_t)0x7fc1, (q15_t)0x597, (q15_t)0x7fc3, (q15_t)0x58a,
+    (q15_t)0x7fc4, (q15_t)0x57e, (q15_t)0x7fc5, (q15_t)0x571, (q15_t)0x7fc6, (q15_t)0x565, (q15_t)0x7fc7, (q15_t)0x558,
+    (q15_t)0x7fc8, (q15_t)0x54c, (q15_t)0x7fc9, (q15_t)0x53f, (q15_t)0x7fca, (q15_t)0x533, (q15_t)0x7fcb, (q15_t)0x526,
+    (q15_t)0x7fcc, (q15_t)0x51a, (q15_t)0x7fcd, (q15_t)0x50d, (q15_t)0x7fce, (q15_t)0x500, (q15_t)0x7fcf, (q15_t)0x4f4,
+    (q15_t)0x7fd0, (q15_t)0x4e7, (q15_t)0x7fd1, (q15_t)0x4db, (q15_t)0x7fd2, (q15_t)0x4ce, (q15_t)0x7fd3, (q15_t)0x4c2,
+    (q15_t)0x7fd4, (q15_t)0x4b5, (q15_t)0x7fd5, (q15_t)0x4a9, (q15_t)0x7fd5, (q15_t)0x49c, (q15_t)0x7fd6, (q15_t)0x490,
+    (q15_t)0x7fd7, (q15_t)0x483, (q15_t)0x7fd8, (q15_t)0x477, (q15_t)0x7fd9, (q15_t)0x46a, (q15_t)0x7fda, (q15_t)0x45e,
+    (q15_t)0x7fdb, (q15_t)0x451, (q15_t)0x7fdc, (q15_t)0x444, (q15_t)0x7fdc, (q15_t)0x438, (q15_t)0x7fdd, (q15_t)0x42b,
+    (q15_t)0x7fde, (q15_t)0x41f, (q15_t)0x7fdf, (q15_t)0x412, (q15_t)0x7fe0, (q15_t)0x406, (q15_t)0x7fe0, (q15_t)0x3f9,
+    (q15_t)0x7fe1, (q15_t)0x3ed, (q15_t)0x7fe2, (q15_t)0x3e0, (q15_t)0x7fe3, (q15_t)0x3d4, (q15_t)0x7fe3, (q15_t)0x3c7,
+    (q15_t)0x7fe4, (q15_t)0x3bb, (q15_t)0x7fe5, (q15_t)0x3ae, (q15_t)0x7fe6, (q15_t)0x3a1, (q15_t)0x7fe6, (q15_t)0x395,
+    (q15_t)0x7fe7, (q15_t)0x388, (q15_t)0x7fe8, (q15_t)0x37c, (q15_t)0x7fe8, (q15_t)0x36f, (q15_t)0x7fe9, (q15_t)0x363,
+    (q15_t)0x7fea, (q15_t)0x356, (q15_t)0x7fea, (q15_t)0x34a, (q15_t)0x7feb, (q15_t)0x33d, (q15_t)0x7fec, (q15_t)0x330,
+    (q15_t)0x7fec, (q15_t)0x324, (q15_t)0x7fed, (q15_t)0x317, (q15_t)0x7fed, (q15_t)0x30b, (q15_t)0x7fee, (q15_t)0x2fe,
+    (q15_t)0x7fef, (q15_t)0x2f2, (q15_t)0x7fef, (q15_t)0x2e5, (q15_t)0x7ff0, (q15_t)0x2d9, (q15_t)0x7ff0, (q15_t)0x2cc,
+    (q15_t)0x7ff1, (q15_t)0x2c0, (q15_t)0x7ff1, (q15_t)0x2b3, (q15_t)0x7ff2, (q15_t)0x2a6, (q15_t)0x7ff2, (q15_t)0x29a,
+    (q15_t)0x7ff3, (q15_t)0x28d, (q15_t)0x7ff3, (q15_t)0x281, (q15_t)0x7ff4, (q15_t)0x274, (q15_t)0x7ff4, (q15_t)0x268,
+    (q15_t)0x7ff5, (q15_t)0x25b, (q15_t)0x7ff5, (q15_t)0x24e, (q15_t)0x7ff6, (q15_t)0x242, (q15_t)0x7ff6, (q15_t)0x235,
+    (q15_t)0x7ff7, (q15_t)0x229, (q15_t)0x7ff7, (q15_t)0x21c, (q15_t)0x7ff7, (q15_t)0x210, (q15_t)0x7ff8, (q15_t)0x203,
+    (q15_t)0x7ff8, (q15_t)0x1f7, (q15_t)0x7ff9, (q15_t)0x1ea, (q15_t)0x7ff9, (q15_t)0x1dd, (q15_t)0x7ff9, (q15_t)0x1d1,
+    (q15_t)0x7ffa, (q15_t)0x1c4, (q15_t)0x7ffa, (q15_t)0x1b8, (q15_t)0x7ffa, (q15_t)0x1ab, (q15_t)0x7ffb, (q15_t)0x19f,
+    (q15_t)0x7ffb, (q15_t)0x192, (q15_t)0x7ffb, (q15_t)0x186, (q15_t)0x7ffc, (q15_t)0x179, (q15_t)0x7ffc, (q15_t)0x16c,
+    (q15_t)0x7ffc, (q15_t)0x160, (q15_t)0x7ffc, (q15_t)0x153, (q15_t)0x7ffd, (q15_t)0x147, (q15_t)0x7ffd, (q15_t)0x13a,
+    (q15_t)0x7ffd, (q15_t)0x12e, (q15_t)0x7ffd, (q15_t)0x121, (q15_t)0x7ffe, (q15_t)0x114, (q15_t)0x7ffe, (q15_t)0x108,
+    (q15_t)0x7ffe, (q15_t)0xfb, (q15_t)0x7ffe, (q15_t)0xef, (q15_t)0x7ffe, (q15_t)0xe2, (q15_t)0x7fff, (q15_t)0xd6,
+    (q15_t)0x7fff, (q15_t)0xc9, (q15_t)0x7fff, (q15_t)0xbc, (q15_t)0x7fff, (q15_t)0xb0, (q15_t)0x7fff, (q15_t)0xa3,
+    (q15_t)0x7fff, (q15_t)0x97, (q15_t)0x7fff, (q15_t)0x8a, (q15_t)0x7fff, (q15_t)0x7e, (q15_t)0x7fff, (q15_t)0x71,
+    (q15_t)0x7fff, (q15_t)0x65, (q15_t)0x7fff, (q15_t)0x58, (q15_t)0x7fff, (q15_t)0x4b, (q15_t)0x7fff, (q15_t)0x3f,
+    (q15_t)0x7fff, (q15_t)0x32, (q15_t)0x7fff, (q15_t)0x26, (q15_t)0x7fff, (q15_t)0x19, (q15_t)0x7fff, (q15_t)0xd,
+    (q15_t)0x7fff, (q15_t)0x0, (q15_t)0x7fff, (q15_t)0xfff3, (q15_t)0x7fff, (q15_t)0xffe7, (q15_t)0x7fff, (q15_t)0xffda,
+    (q15_t)0x7fff, (q15_t)0xffce, (q15_t)0x7fff, (q15_t)0xffc1, (q15_t)0x7fff, (q15_t)0xffb5, (q15_t)0x7fff, (q15_t)0xffa8,
+    (q15_t)0x7fff, (q15_t)0xff9b, (q15_t)0x7fff, (q15_t)0xff8f, (q15_t)0x7fff, (q15_t)0xff82, (q15_t)0x7fff, (q15_t)0xff76,
+    (q15_t)0x7fff, (q15_t)0xff69, (q15_t)0x7fff, (q15_t)0xff5d, (q15_t)0x7fff, (q15_t)0xff50, (q15_t)0x7fff, (q15_t)0xff44,
+    (q15_t)0x7fff, (q15_t)0xff37, (q15_t)0x7fff, (q15_t)0xff2a, (q15_t)0x7ffe, (q15_t)0xff1e, (q15_t)0x7ffe, (q15_t)0xff11,
+    (q15_t)0x7ffe, (q15_t)0xff05, (q15_t)0x7ffe, (q15_t)0xfef8, (q15_t)0x7ffe, (q15_t)0xfeec, (q15_t)0x7ffd, (q15_t)0xfedf,
+    (q15_t)0x7ffd, (q15_t)0xfed2, (q15_t)0x7ffd, (q15_t)0xfec6, (q15_t)0x7ffd, (q15_t)0xfeb9, (q15_t)0x7ffc, (q15_t)0xfead,
+    (q15_t)0x7ffc, (q15_t)0xfea0, (q15_t)0x7ffc, (q15_t)0xfe94, (q15_t)0x7ffc, (q15_t)0xfe87, (q15_t)0x7ffb, (q15_t)0xfe7a,
+    (q15_t)0x7ffb, (q15_t)0xfe6e, (q15_t)0x7ffb, (q15_t)0xfe61, (q15_t)0x7ffa, (q15_t)0xfe55, (q15_t)0x7ffa, (q15_t)0xfe48,
+    (q15_t)0x7ffa, (q15_t)0xfe3c, (q15_t)0x7ff9, (q15_t)0xfe2f, (q15_t)0x7ff9, (q15_t)0xfe23, (q15_t)0x7ff9, (q15_t)0xfe16,
+    (q15_t)0x7ff8, (q15_t)0xfe09, (q15_t)0x7ff8, (q15_t)0xfdfd, (q15_t)0x7ff7, (q15_t)0xfdf0, (q15_t)0x7ff7, (q15_t)0xfde4,
+    (q15_t)0x7ff7, (q15_t)0xfdd7, (q15_t)0x7ff6, (q15_t)0xfdcb, (q15_t)0x7ff6, (q15_t)0xfdbe, (q15_t)0x7ff5, (q15_t)0xfdb2,
+    (q15_t)0x7ff5, (q15_t)0xfda5, (q15_t)0x7ff4, (q15_t)0xfd98, (q15_t)0x7ff4, (q15_t)0xfd8c, (q15_t)0x7ff3, (q15_t)0xfd7f,
+    (q15_t)0x7ff3, (q15_t)0xfd73, (q15_t)0x7ff2, (q15_t)0xfd66, (q15_t)0x7ff2, (q15_t)0xfd5a, (q15_t)0x7ff1, (q15_t)0xfd4d,
+    (q15_t)0x7ff1, (q15_t)0xfd40, (q15_t)0x7ff0, (q15_t)0xfd34, (q15_t)0x7ff0, (q15_t)0xfd27, (q15_t)0x7fef, (q15_t)0xfd1b,
+    (q15_t)0x7fef, (q15_t)0xfd0e, (q15_t)0x7fee, (q15_t)0xfd02, (q15_t)0x7fed, (q15_t)0xfcf5, (q15_t)0x7fed, (q15_t)0xfce9,
+    (q15_t)0x7fec, (q15_t)0xfcdc, (q15_t)0x7fec, (q15_t)0xfcd0, (q15_t)0x7feb, (q15_t)0xfcc3, (q15_t)0x7fea, (q15_t)0xfcb6,
+    (q15_t)0x7fea, (q15_t)0xfcaa, (q15_t)0x7fe9, (q15_t)0xfc9d, (q15_t)0x7fe8, (q15_t)0xfc91, (q15_t)0x7fe8, (q15_t)0xfc84,
+    (q15_t)0x7fe7, (q15_t)0xfc78, (q15_t)0x7fe6, (q15_t)0xfc6b, (q15_t)0x7fe6, (q15_t)0xfc5f, (q15_t)0x7fe5, (q15_t)0xfc52,
+    (q15_t)0x7fe4, (q15_t)0xfc45, (q15_t)0x7fe3, (q15_t)0xfc39, (q15_t)0x7fe3, (q15_t)0xfc2c, (q15_t)0x7fe2, (q15_t)0xfc20,
+    (q15_t)0x7fe1, (q15_t)0xfc13, (q15_t)0x7fe0, (q15_t)0xfc07, (q15_t)0x7fe0, (q15_t)0xfbfa, (q15_t)0x7fdf, (q15_t)0xfbee,
+    (q15_t)0x7fde, (q15_t)0xfbe1, (q15_t)0x7fdd, (q15_t)0xfbd5, (q15_t)0x7fdc, (q15_t)0xfbc8, (q15_t)0x7fdc, (q15_t)0xfbbc,
+    (q15_t)0x7fdb, (q15_t)0xfbaf, (q15_t)0x7fda, (q15_t)0xfba2, (q15_t)0x7fd9, (q15_t)0xfb96, (q15_t)0x7fd8, (q15_t)0xfb89,
+    (q15_t)0x7fd7, (q15_t)0xfb7d, (q15_t)0x7fd6, (q15_t)0xfb70, (q15_t)0x7fd5, (q15_t)0xfb64, (q15_t)0x7fd5, (q15_t)0xfb57,
+    (q15_t)0x7fd4, (q15_t)0xfb4b, (q15_t)0x7fd3, (q15_t)0xfb3e, (q15_t)0x7fd2, (q15_t)0xfb32, (q15_t)0x7fd1, (q15_t)0xfb25,
+    (q15_t)0x7fd0, (q15_t)0xfb19, (q15_t)0x7fcf, (q15_t)0xfb0c, (q15_t)0x7fce, (q15_t)0xfb00, (q15_t)0x7fcd, (q15_t)0xfaf3,
+    (q15_t)0x7fcc, (q15_t)0xfae6, (q15_t)0x7fcb, (q15_t)0xfada, (q15_t)0x7fca, (q15_t)0xfacd, (q15_t)0x7fc9, (q15_t)0xfac1,
+    (q15_t)0x7fc8, (q15_t)0xfab4, (q15_t)0x7fc7, (q15_t)0xfaa8, (q15_t)0x7fc6, (q15_t)0xfa9b, (q15_t)0x7fc5, (q15_t)0xfa8f,
+    (q15_t)0x7fc4, (q15_t)0xfa82, (q15_t)0x7fc3, (q15_t)0xfa76, (q15_t)0x7fc1, (q15_t)0xfa69, (q15_t)0x7fc0, (q15_t)0xfa5d,
+    (q15_t)0x7fbf, (q15_t)0xfa50, (q15_t)0x7fbe, (q15_t)0xfa44, (q15_t)0x7fbd, (q15_t)0xfa37, (q15_t)0x7fbc, (q15_t)0xfa2b,
+    (q15_t)0x7fbb, (q15_t)0xfa1e, (q15_t)0x7fb9, (q15_t)0xfa12, (q15_t)0x7fb8, (q15_t)0xfa05, (q15_t)0x7fb7, (q15_t)0xf9f9,
+    (q15_t)0x7fb6, (q15_t)0xf9ec, (q15_t)0x7fb5, (q15_t)0xf9e0, (q15_t)0x7fb4, (q15_t)0xf9d3, (q15_t)0x7fb2, (q15_t)0xf9c7,
+    (q15_t)0x7fb1, (q15_t)0xf9ba, (q15_t)0x7fb0, (q15_t)0xf9ae, (q15_t)0x7faf, (q15_t)0xf9a1, (q15_t)0x7fad, (q15_t)0xf995,
+    (q15_t)0x7fac, (q15_t)0xf988, (q15_t)0x7fab, (q15_t)0xf97c, (q15_t)0x7faa, (q15_t)0xf96f, (q15_t)0x7fa8, (q15_t)0xf963,
+    (q15_t)0x7fa7, (q15_t)0xf956, (q15_t)0x7fa6, (q15_t)0xf94a, (q15_t)0x7fa4, (q15_t)0xf93d, (q15_t)0x7fa3, (q15_t)0xf931,
+    (q15_t)0x7fa2, (q15_t)0xf924, (q15_t)0x7fa0, (q15_t)0xf918, (q15_t)0x7f9f, (q15_t)0xf90b, (q15_t)0x7f9e, (q15_t)0xf8ff,
+    (q15_t)0x7f9c, (q15_t)0xf8f2, (q15_t)0x7f9b, (q15_t)0xf8e6, (q15_t)0x7f99, (q15_t)0xf8d9, (q15_t)0x7f98, (q15_t)0xf8cd,
+    (q15_t)0x7f97, (q15_t)0xf8c0, (q15_t)0x7f95, (q15_t)0xf8b4, (q15_t)0x7f94, (q15_t)0xf8a7, (q15_t)0x7f92, (q15_t)0xf89b,
+    (q15_t)0x7f91, (q15_t)0xf88e, (q15_t)0x7f8f, (q15_t)0xf882, (q15_t)0x7f8e, (q15_t)0xf875, (q15_t)0x7f8c, (q15_t)0xf869,
+    (q15_t)0x7f8b, (q15_t)0xf85c, (q15_t)0x7f89, (q15_t)0xf850, (q15_t)0x7f88, (q15_t)0xf843, (q15_t)0x7f86, (q15_t)0xf837,
+    (q15_t)0x7f85, (q15_t)0xf82a, (q15_t)0x7f83, (q15_t)0xf81e, (q15_t)0x7f82, (q15_t)0xf811, (q15_t)0x7f80, (q15_t)0xf805,
+    (q15_t)0x7f7f, (q15_t)0xf7f9, (q15_t)0x7f7d, (q15_t)0xf7ec, (q15_t)0x7f7b, (q15_t)0xf7e0, (q15_t)0x7f7a, (q15_t)0xf7d3,
+    (q15_t)0x7f78, (q15_t)0xf7c7, (q15_t)0x7f77, (q15_t)0xf7ba, (q15_t)0x7f75, (q15_t)0xf7ae, (q15_t)0x7f73, (q15_t)0xf7a1,
+    (q15_t)0x7f72, (q15_t)0xf795, (q15_t)0x7f70, (q15_t)0xf788, (q15_t)0x7f6e, (q15_t)0xf77c, (q15_t)0x7f6d, (q15_t)0xf76f,
+    (q15_t)0x7f6b, (q15_t)0xf763, (q15_t)0x7f69, (q15_t)0xf757, (q15_t)0x7f68, (q15_t)0xf74a, (q15_t)0x7f66, (q15_t)0xf73e,
+    (q15_t)0x7f64, (q15_t)0xf731, (q15_t)0x7f62, (q15_t)0xf725, (q15_t)0x7f61, (q15_t)0xf718, (q15_t)0x7f5f, (q15_t)0xf70c,
+    (q15_t)0x7f5d, (q15_t)0xf6ff, (q15_t)0x7f5b, (q15_t)0xf6f3, (q15_t)0x7f5a, (q15_t)0xf6e7, (q15_t)0x7f58, (q15_t)0xf6da,
+    (q15_t)0x7f56, (q15_t)0xf6ce, (q15_t)0x7f54, (q15_t)0xf6c1, (q15_t)0x7f52, (q15_t)0xf6b5, (q15_t)0x7f51, (q15_t)0xf6a8,
+    (q15_t)0x7f4f, (q15_t)0xf69c, (q15_t)0x7f4d, (q15_t)0xf690, (q15_t)0x7f4b, (q15_t)0xf683, (q15_t)0x7f49, (q15_t)0xf677,
+    (q15_t)0x7f47, (q15_t)0xf66a, (q15_t)0x7f45, (q15_t)0xf65e, (q15_t)0x7f43, (q15_t)0xf651, (q15_t)0x7f42, (q15_t)0xf645,
+    (q15_t)0x7f40, (q15_t)0xf639, (q15_t)0x7f3e, (q15_t)0xf62c, (q15_t)0x7f3c, (q15_t)0xf620, (q15_t)0x7f3a, (q15_t)0xf613,
+    (q15_t)0x7f38, (q15_t)0xf607, (q15_t)0x7f36, (q15_t)0xf5fa, (q15_t)0x7f34, (q15_t)0xf5ee, (q15_t)0x7f32, (q15_t)0xf5e2,
+    (q15_t)0x7f30, (q15_t)0xf5d5, (q15_t)0x7f2e, (q15_t)0xf5c9, (q15_t)0x7f2c, (q15_t)0xf5bc, (q15_t)0x7f2a, (q15_t)0xf5b0,
+    (q15_t)0x7f28, (q15_t)0xf5a4, (q15_t)0x7f26, (q15_t)0xf597, (q15_t)0x7f24, (q15_t)0xf58b, (q15_t)0x7f22, (q15_t)0xf57e,
+    (q15_t)0x7f20, (q15_t)0xf572, (q15_t)0x7f1e, (q15_t)0xf566, (q15_t)0x7f1c, (q15_t)0xf559, (q15_t)0x7f19, (q15_t)0xf54d,
+    (q15_t)0x7f17, (q15_t)0xf540, (q15_t)0x7f15, (q15_t)0xf534, (q15_t)0x7f13, (q15_t)0xf528, (q15_t)0x7f11, (q15_t)0xf51b,
+    (q15_t)0x7f0f, (q15_t)0xf50f, (q15_t)0x7f0d, (q15_t)0xf503, (q15_t)0x7f0a, (q15_t)0xf4f6, (q15_t)0x7f08, (q15_t)0xf4ea,
+    (q15_t)0x7f06, (q15_t)0xf4dd, (q15_t)0x7f04, (q15_t)0xf4d1, (q15_t)0x7f02, (q15_t)0xf4c5, (q15_t)0x7f00, (q15_t)0xf4b8,
+    (q15_t)0x7efd, (q15_t)0xf4ac, (q15_t)0x7efb, (q15_t)0xf4a0, (q15_t)0x7ef9, (q15_t)0xf493, (q15_t)0x7ef7, (q15_t)0xf487,
+    (q15_t)0x7ef4, (q15_t)0xf47b, (q15_t)0x7ef2, (q15_t)0xf46e, (q15_t)0x7ef0, (q15_t)0xf462, (q15_t)0x7eed, (q15_t)0xf455,
+    (q15_t)0x7eeb, (q15_t)0xf449, (q15_t)0x7ee9, (q15_t)0xf43d, (q15_t)0x7ee7, (q15_t)0xf430, (q15_t)0x7ee4, (q15_t)0xf424,
+    (q15_t)0x7ee2, (q15_t)0xf418, (q15_t)0x7ee0, (q15_t)0xf40b, (q15_t)0x7edd, (q15_t)0xf3ff, (q15_t)0x7edb, (q15_t)0xf3f3,
+    (q15_t)0x7ed8, (q15_t)0xf3e6, (q15_t)0x7ed6, (q15_t)0xf3da, (q15_t)0x7ed4, (q15_t)0xf3ce, (q15_t)0x7ed1, (q15_t)0xf3c1,
+    (q15_t)0x7ecf, (q15_t)0xf3b5, (q15_t)0x7ecc, (q15_t)0xf3a9, (q15_t)0x7eca, (q15_t)0xf39c, (q15_t)0x7ec8, (q15_t)0xf390,
+    (q15_t)0x7ec5, (q15_t)0xf384, (q15_t)0x7ec3, (q15_t)0xf377, (q15_t)0x7ec0, (q15_t)0xf36b, (q15_t)0x7ebe, (q15_t)0xf35f,
+    (q15_t)0x7ebb, (q15_t)0xf352, (q15_t)0x7eb9, (q15_t)0xf346, (q15_t)0x7eb6, (q15_t)0xf33a, (q15_t)0x7eb4, (q15_t)0xf32d,
+    (q15_t)0x7eb1, (q15_t)0xf321, (q15_t)0x7eaf, (q15_t)0xf315, (q15_t)0x7eac, (q15_t)0xf308, (q15_t)0x7eaa, (q15_t)0xf2fc,
+    (q15_t)0x7ea7, (q15_t)0xf2f0, (q15_t)0x7ea5, (q15_t)0xf2e4, (q15_t)0x7ea2, (q15_t)0xf2d7, (q15_t)0x7e9f, (q15_t)0xf2cb,
+    (q15_t)0x7e9d, (q15_t)0xf2bf, (q15_t)0x7e9a, (q15_t)0xf2b2, (q15_t)0x7e98, (q15_t)0xf2a6, (q15_t)0x7e95, (q15_t)0xf29a,
+    (q15_t)0x7e92, (q15_t)0xf28e, (q15_t)0x7e90, (q15_t)0xf281, (q15_t)0x7e8d, (q15_t)0xf275, (q15_t)0x7e8a, (q15_t)0xf269,
+    (q15_t)0x7e88, (q15_t)0xf25c, (q15_t)0x7e85, (q15_t)0xf250, (q15_t)0x7e82, (q15_t)0xf244, (q15_t)0x7e80, (q15_t)0xf238,
+    (q15_t)0x7e7d, (q15_t)0xf22b, (q15_t)0x7e7a, (q15_t)0xf21f, (q15_t)0x7e77, (q15_t)0xf213, (q15_t)0x7e75, (q15_t)0xf207,
+    (q15_t)0x7e72, (q15_t)0xf1fa, (q15_t)0x7e6f, (q15_t)0xf1ee, (q15_t)0x7e6c, (q15_t)0xf1e2, (q15_t)0x7e6a, (q15_t)0xf1d5,
+    (q15_t)0x7e67, (q15_t)0xf1c9, (q15_t)0x7e64, (q15_t)0xf1bd, (q15_t)0x7e61, (q15_t)0xf1b1, (q15_t)0x7e5e, (q15_t)0xf1a4,
+    (q15_t)0x7e5c, (q15_t)0xf198, (q15_t)0x7e59, (q15_t)0xf18c, (q15_t)0x7e56, (q15_t)0xf180, (q15_t)0x7e53, (q15_t)0xf174,
+    (q15_t)0x7e50, (q15_t)0xf167, (q15_t)0x7e4d, (q15_t)0xf15b, (q15_t)0x7e4a, (q15_t)0xf14f, (q15_t)0x7e48, (q15_t)0xf143,
+    (q15_t)0x7e45, (q15_t)0xf136, (q15_t)0x7e42, (q15_t)0xf12a, (q15_t)0x7e3f, (q15_t)0xf11e, (q15_t)0x7e3c, (q15_t)0xf112,
+    (q15_t)0x7e39, (q15_t)0xf105, (q15_t)0x7e36, (q15_t)0xf0f9, (q15_t)0x7e33, (q15_t)0xf0ed, (q15_t)0x7e30, (q15_t)0xf0e1,
+    (q15_t)0x7e2d, (q15_t)0xf0d5, (q15_t)0x7e2a, (q15_t)0xf0c8, (q15_t)0x7e27, (q15_t)0xf0bc, (q15_t)0x7e24, (q15_t)0xf0b0,
+    (q15_t)0x7e21, (q15_t)0xf0a4, (q15_t)0x7e1e, (q15_t)0xf098, (q15_t)0x7e1b, (q15_t)0xf08b, (q15_t)0x7e18, (q15_t)0xf07f,
+    (q15_t)0x7e15, (q15_t)0xf073, (q15_t)0x7e12, (q15_t)0xf067, (q15_t)0x7e0f, (q15_t)0xf05b, (q15_t)0x7e0c, (q15_t)0xf04e,
+    (q15_t)0x7e09, (q15_t)0xf042, (q15_t)0x7e06, (q15_t)0xf036, (q15_t)0x7e03, (q15_t)0xf02a, (q15_t)0x7dff, (q15_t)0xf01e,
+    (q15_t)0x7dfc, (q15_t)0xf012, (q15_t)0x7df9, (q15_t)0xf005, (q15_t)0x7df6, (q15_t)0xeff9, (q15_t)0x7df3, (q15_t)0xefed,
+    (q15_t)0x7df0, (q15_t)0xefe1, (q15_t)0x7ded, (q15_t)0xefd5, (q15_t)0x7de9, (q15_t)0xefc9, (q15_t)0x7de6, (q15_t)0xefbc,
+    (q15_t)0x7de3, (q15_t)0xefb0, (q15_t)0x7de0, (q15_t)0xefa4, (q15_t)0x7ddd, (q15_t)0xef98, (q15_t)0x7dd9, (q15_t)0xef8c,
+    (q15_t)0x7dd6, (q15_t)0xef80, (q15_t)0x7dd3, (q15_t)0xef74, (q15_t)0x7dd0, (q15_t)0xef67, (q15_t)0x7dcc, (q15_t)0xef5b,
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+    (q15_t)0x6d88, (q15_t)0xd306, (q15_t)0x6d7f, (q15_t)0xd2fd, (q15_t)0x6d76, (q15_t)0xd2f4, (q15_t)0x6d6e, (q15_t)0xd2eb,
+    (q15_t)0x6d65, (q15_t)0xd2e2, (q15_t)0x6d5c, (q15_t)0xd2d9, (q15_t)0x6d53, (q15_t)0xd2d1, (q15_t)0x6d4a, (q15_t)0xd2c8,
+    (q15_t)0x6d41, (q15_t)0xd2bf, (q15_t)0x6d38, (q15_t)0xd2b6, (q15_t)0x6d2f, (q15_t)0xd2ad, (q15_t)0x6d27, (q15_t)0xd2a4,
+    (q15_t)0x6d1e, (q15_t)0xd29b, (q15_t)0x6d15, (q15_t)0xd292, (q15_t)0x6d0c, (q15_t)0xd28a, (q15_t)0x6d03, (q15_t)0xd281,
+    (q15_t)0x6cfa, (q15_t)0xd278, (q15_t)0x6cf1, (q15_t)0xd26f, (q15_t)0x6ce8, (q15_t)0xd266, (q15_t)0x6cdf, (q15_t)0xd25d,
+    (q15_t)0x6cd6, (q15_t)0xd255, (q15_t)0x6ccd, (q15_t)0xd24c, (q15_t)0x6cc4, (q15_t)0xd243, (q15_t)0x6cbb, (q15_t)0xd23a,
+    (q15_t)0x6cb2, (q15_t)0xd231, (q15_t)0x6ca9, (q15_t)0xd229, (q15_t)0x6ca0, (q15_t)0xd220, (q15_t)0x6c97, (q15_t)0xd217,
+    (q15_t)0x6c8e, (q15_t)0xd20e, (q15_t)0x6c85, (q15_t)0xd206, (q15_t)0x6c7c, (q15_t)0xd1fd, (q15_t)0x6c73, (q15_t)0xd1f4,
+    (q15_t)0x6c6a, (q15_t)0xd1eb, (q15_t)0x6c61, (q15_t)0xd1e3, (q15_t)0x6c58, (q15_t)0xd1da, (q15_t)0x6c4f, (q15_t)0xd1d1,
+    (q15_t)0x6c46, (q15_t)0xd1c9, (q15_t)0x6c3d, (q15_t)0xd1c0, (q15_t)0x6c34, (q15_t)0xd1b7, (q15_t)0x6c2b, (q15_t)0xd1af,
+    (q15_t)0x6c21, (q15_t)0xd1a6, (q15_t)0x6c18, (q15_t)0xd19d, (q15_t)0x6c0f, (q15_t)0xd195, (q15_t)0x6c06, (q15_t)0xd18c,
+    (q15_t)0x6bfd, (q15_t)0xd183, (q15_t)0x6bf4, (q15_t)0xd17b, (q15_t)0x6beb, (q15_t)0xd172, (q15_t)0x6be2, (q15_t)0xd169,
+    (q15_t)0x6bd8, (q15_t)0xd161, (q15_t)0x6bcf, (q15_t)0xd158, (q15_t)0x6bc6, (q15_t)0xd150, (q15_t)0x6bbd, (q15_t)0xd147,
+    (q15_t)0x6bb4, (q15_t)0xd13e, (q15_t)0x6bab, (q15_t)0xd136, (q15_t)0x6ba1, (q15_t)0xd12d, (q15_t)0x6b98, (q15_t)0xd125,
+    (q15_t)0x6b8f, (q15_t)0xd11c, (q15_t)0x6b86, (q15_t)0xd114, (q15_t)0x6b7d, (q15_t)0xd10b, (q15_t)0x6b73, (q15_t)0xd103,
+    (q15_t)0x6b6a, (q15_t)0xd0fa, (q15_t)0x6b61, (q15_t)0xd0f2, (q15_t)0x6b58, (q15_t)0xd0e9, (q15_t)0x6b4e, (q15_t)0xd0e0,
+    (q15_t)0x6b45, (q15_t)0xd0d8, (q15_t)0x6b3c, (q15_t)0xd0d0, (q15_t)0x6b33, (q15_t)0xd0c7, (q15_t)0x6b29, (q15_t)0xd0bf,
+    (q15_t)0x6b20, (q15_t)0xd0b6, (q15_t)0x6b17, (q15_t)0xd0ae, (q15_t)0x6b0d, (q15_t)0xd0a5, (q15_t)0x6b04, (q15_t)0xd09d,
+    (q15_t)0x6afb, (q15_t)0xd094, (q15_t)0x6af2, (q15_t)0xd08c, (q15_t)0x6ae8, (q15_t)0xd083, (q15_t)0x6adf, (q15_t)0xd07b,
+    (q15_t)0x6ad6, (q15_t)0xd073, (q15_t)0x6acc, (q15_t)0xd06a, (q15_t)0x6ac3, (q15_t)0xd062, (q15_t)0x6ab9, (q15_t)0xd059,
+    (q15_t)0x6ab0, (q15_t)0xd051, (q15_t)0x6aa7, (q15_t)0xd049, (q15_t)0x6a9d, (q15_t)0xd040, (q15_t)0x6a94, (q15_t)0xd038,
+    (q15_t)0x6a8b, (q15_t)0xd030, (q15_t)0x6a81, (q15_t)0xd027, (q15_t)0x6a78, (q15_t)0xd01f, (q15_t)0x6a6e, (q15_t)0xd016,
+    (q15_t)0x6a65, (q15_t)0xd00e, (q15_t)0x6a5c, (q15_t)0xd006, (q15_t)0x6a52, (q15_t)0xcffe, (q15_t)0x6a49, (q15_t)0xcff5,
+    (q15_t)0x6a3f, (q15_t)0xcfed, (q15_t)0x6a36, (q15_t)0xcfe5, (q15_t)0x6a2c, (q15_t)0xcfdc, (q15_t)0x6a23, (q15_t)0xcfd4,
+    (q15_t)0x6a1a, (q15_t)0xcfcc, (q15_t)0x6a10, (q15_t)0xcfc4, (q15_t)0x6a07, (q15_t)0xcfbb, (q15_t)0x69fd, (q15_t)0xcfb3,
+    (q15_t)0x69f4, (q15_t)0xcfab, (q15_t)0x69ea, (q15_t)0xcfa3, (q15_t)0x69e1, (q15_t)0xcf9a, (q15_t)0x69d7, (q15_t)0xcf92,
+    (q15_t)0x69ce, (q15_t)0xcf8a, (q15_t)0x69c4, (q15_t)0xcf82, (q15_t)0x69bb, (q15_t)0xcf79, (q15_t)0x69b1, (q15_t)0xcf71,
+    (q15_t)0x69a7, (q15_t)0xcf69, (q15_t)0x699e, (q15_t)0xcf61, (q15_t)0x6994, (q15_t)0xcf59, (q15_t)0x698b, (q15_t)0xcf51,
+    (q15_t)0x6981, (q15_t)0xcf48, (q15_t)0x6978, (q15_t)0xcf40, (q15_t)0x696e, (q15_t)0xcf38, (q15_t)0x6965, (q15_t)0xcf30,
+    (q15_t)0x695b, (q15_t)0xcf28, (q15_t)0x6951, (q15_t)0xcf20, (q15_t)0x6948, (q15_t)0xcf18, (q15_t)0x693e, (q15_t)0xcf10,
+    (q15_t)0x6935, (q15_t)0xcf07, (q15_t)0x692b, (q15_t)0xceff, (q15_t)0x6921, (q15_t)0xcef7, (q15_t)0x6918, (q15_t)0xceef,
+    (q15_t)0x690e, (q15_t)0xcee7, (q15_t)0x6904, (q15_t)0xcedf, (q15_t)0x68fb, (q15_t)0xced7, (q15_t)0x68f1, (q15_t)0xcecf,
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+    (q15_t)0x68c1, (q15_t)0xcea7, (q15_t)0x68b7, (q15_t)0xce9f, (q15_t)0x68ad, (q15_t)0xce97, (q15_t)0x68a4, (q15_t)0xce8f,
+    (q15_t)0x689a, (q15_t)0xce87, (q15_t)0x6890, (q15_t)0xce7f, (q15_t)0x6886, (q15_t)0xce77, (q15_t)0x687d, (q15_t)0xce6f,
+    (q15_t)0x6873, (q15_t)0xce67, (q15_t)0x6869, (q15_t)0xce5f, (q15_t)0x6860, (q15_t)0xce57, (q15_t)0x6856, (q15_t)0xce4f,
+    (q15_t)0x684c, (q15_t)0xce47, (q15_t)0x6842, (q15_t)0xce40, (q15_t)0x6838, (q15_t)0xce38, (q15_t)0x682f, (q15_t)0xce30,
+    (q15_t)0x6825, (q15_t)0xce28, (q15_t)0x681b, (q15_t)0xce20, (q15_t)0x6811, (q15_t)0xce18, (q15_t)0x6808, (q15_t)0xce10,
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+    (q15_t)0x67d6, (q15_t)0xcde9, (q15_t)0x67cd, (q15_t)0xcde1, (q15_t)0x67c3, (q15_t)0xcdd9, (q15_t)0x67b9, (q15_t)0xcdd2,
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+    (q15_t)0x6788, (q15_t)0xcdab, (q15_t)0x677e, (q15_t)0xcda3, (q15_t)0x6774, (q15_t)0xcd9b, (q15_t)0x676a, (q15_t)0xcd93,
+    (q15_t)0x6760, (q15_t)0xcd8c, (q15_t)0x6756, (q15_t)0xcd84, (q15_t)0x674c, (q15_t)0xcd7c, (q15_t)0x6742, (q15_t)0xcd75,
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+    (q15_t)0x6711, (q15_t)0xcd4e, (q15_t)0x6707, (q15_t)0xcd46, (q15_t)0x66fd, (q15_t)0xcd3f, (q15_t)0x66f3, (q15_t)0xcd37,
+    (q15_t)0x66e9, (q15_t)0xcd30, (q15_t)0x66df, (q15_t)0xcd28, (q15_t)0x66d5, (q15_t)0xcd20, (q15_t)0x66cb, (q15_t)0xcd19,
+    (q15_t)0x66c1, (q15_t)0xcd11, (q15_t)0x66b7, (q15_t)0xcd09, (q15_t)0x66ad, (q15_t)0xcd02, (q15_t)0x66a3, (q15_t)0xccfa,
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+    (q15_t)0x657e, (q15_t)0xcc21, (q15_t)0x6574, (q15_t)0xcc1a, (q15_t)0x6569, (q15_t)0xcc13, (q15_t)0x655f, (q15_t)0xcc0b,
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+    (q15_t)0x64da, (q15_t)0xcbad, (q15_t)0x64d0, (q15_t)0xcba5, (q15_t)0x64c5, (q15_t)0xcb9e, (q15_t)0x64bb, (q15_t)0xcb97,
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+    (q15_t)0x6488, (q15_t)0xcb73, (q15_t)0x647d, (q15_t)0xcb6c, (q15_t)0x6473, (q15_t)0xcb65, (q15_t)0x6469, (q15_t)0xcb5e,
+    (q15_t)0x645e, (q15_t)0xcb56, (q15_t)0x6454, (q15_t)0xcb4f, (q15_t)0x644a, (q15_t)0xcb48, (q15_t)0x643f, (q15_t)0xcb41,
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+    (q15_t)0x640b, (q15_t)0xcb1e, (q15_t)0x6401, (q15_t)0xcb16, (q15_t)0x63f7, (q15_t)0xcb0f, (q15_t)0x63ec, (q15_t)0xcb08,
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+    (q15_t)0x63b8, (q15_t)0xcae5, (q15_t)0x63ae, (q15_t)0xcade, (q15_t)0x63a3, (q15_t)0xcad7, (q15_t)0x6399, (q15_t)0xcad0,
+    (q15_t)0x638e, (q15_t)0xcac9, (q15_t)0x6384, (q15_t)0xcac2, (q15_t)0x637a, (q15_t)0xcabb, (q15_t)0x636f, (q15_t)0xcab4,
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+    (q15_t)0x633b, (q15_t)0xca92, (q15_t)0x6330, (q15_t)0xca8b, (q15_t)0x6326, (q15_t)0xca84, (q15_t)0x631b, (q15_t)0xca7d,
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+    (q15_t)0x6292, (q15_t)0xca24, (q15_t)0x6288, (q15_t)0xca1d, (q15_t)0x627d, (q15_t)0xca16, (q15_t)0x6272, (q15_t)0xca10,
+    (q15_t)0x6268, (q15_t)0xca09, (q15_t)0x625d, (q15_t)0xca02, (q15_t)0x6253, (q15_t)0xc9fb, (q15_t)0x6248, (q15_t)0xc9f5,
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+    (q15_t)0x6213, (q15_t)0xc9d3, (q15_t)0x6208, (q15_t)0xc9cc, (q15_t)0x61fe, (q15_t)0xc9c6, (q15_t)0x61f3, (q15_t)0xc9bf,
+    (q15_t)0x61e8, (q15_t)0xc9b8, (q15_t)0x61de, (q15_t)0xc9b2, (q15_t)0x61d3, (q15_t)0xc9ab, (q15_t)0x61c8, (q15_t)0xc9a4,
+    (q15_t)0x61be, (q15_t)0xc99e, (q15_t)0x61b3, (q15_t)0xc997, (q15_t)0x61a8, (q15_t)0xc991, (q15_t)0x619e, (q15_t)0xc98a,
+    (q15_t)0x6193, (q15_t)0xc983, (q15_t)0x6188, (q15_t)0xc97d, (q15_t)0x617d, (q15_t)0xc976, (q15_t)0x6173, (q15_t)0xc970,
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+    (q15_t)0x613d, (q15_t)0xc94f, (q15_t)0x6132, (q15_t)0xc948, (q15_t)0x6128, (q15_t)0xc942, (q15_t)0x611d, (q15_t)0xc93b,
+    (q15_t)0x6112, (q15_t)0xc935, (q15_t)0x6107, (q15_t)0xc92e, (q15_t)0x60fd, (q15_t)0xc928, (q15_t)0x60f2, (q15_t)0xc921,
+    (q15_t)0x60e7, (q15_t)0xc91b, (q15_t)0x60dc, (q15_t)0xc915, (q15_t)0x60d1, (q15_t)0xc90e, (q15_t)0x60c7, (q15_t)0xc908,
+    (q15_t)0x60bc, (q15_t)0xc901, (q15_t)0x60b1, (q15_t)0xc8fb, (q15_t)0x60a6, (q15_t)0xc8f4, (q15_t)0x609b, (q15_t)0xc8ee,
+    (q15_t)0x6091, (q15_t)0xc8e8, (q15_t)0x6086, (q15_t)0xc8e1, (q15_t)0x607b, (q15_t)0xc8db, (q15_t)0x6070, (q15_t)0xc8d4,
+    (q15_t)0x6065, (q15_t)0xc8ce, (q15_t)0x605b, (q15_t)0xc8c8, (q15_t)0x6050, (q15_t)0xc8c1, (q15_t)0x6045, (q15_t)0xc8bb,
+    (q15_t)0x603a, (q15_t)0xc8b5, (q15_t)0x602f, (q15_t)0xc8ae, (q15_t)0x6024, (q15_t)0xc8a8, (q15_t)0x6019, (q15_t)0xc8a2,
+    (q15_t)0x600f, (q15_t)0xc89b, (q15_t)0x6004, (q15_t)0xc895, (q15_t)0x5ff9, (q15_t)0xc88f, (q15_t)0x5fee, (q15_t)0xc889,
+    (q15_t)0x5fe3, (q15_t)0xc882, (q15_t)0x5fd8, (q15_t)0xc87c, (q15_t)0x5fcd, (q15_t)0xc876, (q15_t)0x5fc2, (q15_t)0xc870,
+    (q15_t)0x5fb7, (q15_t)0xc869, (q15_t)0x5fac, (q15_t)0xc863, (q15_t)0x5fa2, (q15_t)0xc85d, (q15_t)0x5f97, (q15_t)0xc857,
+    (q15_t)0x5f8c, (q15_t)0xc850, (q15_t)0x5f81, (q15_t)0xc84a, (q15_t)0x5f76, (q15_t)0xc844, (q15_t)0x5f6b, (q15_t)0xc83e,
+    (q15_t)0x5f60, (q15_t)0xc838, (q15_t)0x5f55, (q15_t)0xc832, (q15_t)0x5f4a, (q15_t)0xc82b, (q15_t)0x5f3f, (q15_t)0xc825,
+    (q15_t)0x5f34, (q15_t)0xc81f, (q15_t)0x5f29, (q15_t)0xc819, (q15_t)0x5f1e, (q15_t)0xc813, (q15_t)0x5f13, (q15_t)0xc80d,
+    (q15_t)0x5f08, (q15_t)0xc807, (q15_t)0x5efd, (q15_t)0xc801, (q15_t)0x5ef2, (q15_t)0xc7fb, (q15_t)0x5ee7, (q15_t)0xc7f5,
+    (q15_t)0x5edc, (q15_t)0xc7ee, (q15_t)0x5ed1, (q15_t)0xc7e8, (q15_t)0x5ec6, (q15_t)0xc7e2, (q15_t)0x5ebb, (q15_t)0xc7dc,
+    (q15_t)0x5eb0, (q15_t)0xc7d6, (q15_t)0x5ea5, (q15_t)0xc7d0, (q15_t)0x5e9a, (q15_t)0xc7ca, (q15_t)0x5e8f, (q15_t)0xc7c4,
+    (q15_t)0x5e84, (q15_t)0xc7be, (q15_t)0x5e79, (q15_t)0xc7b8, (q15_t)0x5e6e, (q15_t)0xc7b2, (q15_t)0x5e63, (q15_t)0xc7ac,
+    (q15_t)0x5e58, (q15_t)0xc7a6, (q15_t)0x5e4d, (q15_t)0xc7a0, (q15_t)0x5e42, (q15_t)0xc79a, (q15_t)0x5e36, (q15_t)0xc795,
+    (q15_t)0x5e2b, (q15_t)0xc78f, (q15_t)0x5e20, (q15_t)0xc789, (q15_t)0x5e15, (q15_t)0xc783, (q15_t)0x5e0a, (q15_t)0xc77d,
+    (q15_t)0x5dff, (q15_t)0xc777, (q15_t)0x5df4, (q15_t)0xc771, (q15_t)0x5de9, (q15_t)0xc76b, (q15_t)0x5dde, (q15_t)0xc765,
+    (q15_t)0x5dd3, (q15_t)0xc75f, (q15_t)0x5dc7, (q15_t)0xc75a, (q15_t)0x5dbc, (q15_t)0xc754, (q15_t)0x5db1, (q15_t)0xc74e,
+    (q15_t)0x5da6, (q15_t)0xc748, (q15_t)0x5d9b, (q15_t)0xc742, (q15_t)0x5d90, (q15_t)0xc73d, (q15_t)0x5d85, (q15_t)0xc737,
+    (q15_t)0x5d79, (q15_t)0xc731, (q15_t)0x5d6e, (q15_t)0xc72b, (q15_t)0x5d63, (q15_t)0xc725, (q15_t)0x5d58, (q15_t)0xc720,
+    (q15_t)0x5d4d, (q15_t)0xc71a, (q15_t)0x5d42, (q15_t)0xc714, (q15_t)0x5d36, (q15_t)0xc70e, (q15_t)0x5d2b, (q15_t)0xc709,
+    (q15_t)0x5d20, (q15_t)0xc703, (q15_t)0x5d15, (q15_t)0xc6fd, (q15_t)0x5d0a, (q15_t)0xc6f7, (q15_t)0x5cff, (q15_t)0xc6f2,
+    (q15_t)0x5cf3, (q15_t)0xc6ec, (q15_t)0x5ce8, (q15_t)0xc6e6, (q15_t)0x5cdd, (q15_t)0xc6e1, (q15_t)0x5cd2, (q15_t)0xc6db,
+    (q15_t)0x5cc6, (q15_t)0xc6d5, (q15_t)0x5cbb, (q15_t)0xc6d0, (q15_t)0x5cb0, (q15_t)0xc6ca, (q15_t)0x5ca5, (q15_t)0xc6c5,
+    (q15_t)0x5c99, (q15_t)0xc6bf, (q15_t)0x5c8e, (q15_t)0xc6b9, (q15_t)0x5c83, (q15_t)0xc6b4, (q15_t)0x5c78, (q15_t)0xc6ae,
+    (q15_t)0x5c6c, (q15_t)0xc6a8, (q15_t)0x5c61, (q15_t)0xc6a3, (q15_t)0x5c56, (q15_t)0xc69d, (q15_t)0x5c4b, (q15_t)0xc698,
+    (q15_t)0x5c3f, (q15_t)0xc692, (q15_t)0x5c34, (q15_t)0xc68d, (q15_t)0x5c29, (q15_t)0xc687, (q15_t)0x5c1e, (q15_t)0xc682,
+    (q15_t)0x5c12, (q15_t)0xc67c, (q15_t)0x5c07, (q15_t)0xc677, (q15_t)0x5bfc, (q15_t)0xc671, (q15_t)0x5bf0, (q15_t)0xc66c,
+    (q15_t)0x5be5, (q15_t)0xc666, (q15_t)0x5bda, (q15_t)0xc661, (q15_t)0x5bce, (q15_t)0xc65b, (q15_t)0x5bc3, (q15_t)0xc656,
+    (q15_t)0x5bb8, (q15_t)0xc650, (q15_t)0x5bac, (q15_t)0xc64b, (q15_t)0x5ba1, (q15_t)0xc645, (q15_t)0x5b96, (q15_t)0xc640,
+    (q15_t)0x5b8a, (q15_t)0xc63b, (q15_t)0x5b7f, (q15_t)0xc635, (q15_t)0x5b74, (q15_t)0xc630, (q15_t)0x5b68, (q15_t)0xc62a,
+    (q15_t)0x5b5d, (q15_t)0xc625, (q15_t)0x5b52, (q15_t)0xc620, (q15_t)0x5b46, (q15_t)0xc61a, (q15_t)0x5b3b, (q15_t)0xc615,
+    (q15_t)0x5b30, (q15_t)0xc610, (q15_t)0x5b24, (q15_t)0xc60a, (q15_t)0x5b19, (q15_t)0xc605, (q15_t)0x5b0d, (q15_t)0xc600,
+    (q15_t)0x5b02, (q15_t)0xc5fa, (q15_t)0x5af7, (q15_t)0xc5f5, (q15_t)0x5aeb, (q15_t)0xc5f0, (q15_t)0x5ae0, (q15_t)0xc5ea,
+    (q15_t)0x5ad4, (q15_t)0xc5e5, (q15_t)0x5ac9, (q15_t)0xc5e0, (q15_t)0x5abe, (q15_t)0xc5db, (q15_t)0x5ab2, (q15_t)0xc5d5,
+    (q15_t)0x5aa7, (q15_t)0xc5d0, (q15_t)0x5a9b, (q15_t)0xc5cb, (q15_t)0x5a90, (q15_t)0xc5c6, (q15_t)0x5a84, (q15_t)0xc5c1,
+    (q15_t)0x5a79, (q15_t)0xc5bb, (q15_t)0x5a6e, (q15_t)0xc5b6, (q15_t)0x5a62, (q15_t)0xc5b1, (q15_t)0x5a57, (q15_t)0xc5ac,
+    (q15_t)0x5a4b, (q15_t)0xc5a7, (q15_t)0x5a40, (q15_t)0xc5a1, (q15_t)0x5a34, (q15_t)0xc59c, (q15_t)0x5a29, (q15_t)0xc597,
+    (q15_t)0x5a1d, (q15_t)0xc592, (q15_t)0x5a12, (q15_t)0xc58d, (q15_t)0x5a06, (q15_t)0xc588, (q15_t)0x59fb, (q15_t)0xc583,
+    (q15_t)0x59ef, (q15_t)0xc57e, (q15_t)0x59e4, (q15_t)0xc578, (q15_t)0x59d8, (q15_t)0xc573, (q15_t)0x59cd, (q15_t)0xc56e,
+    (q15_t)0x59c1, (q15_t)0xc569, (q15_t)0x59b6, (q15_t)0xc564, (q15_t)0x59aa, (q15_t)0xc55f, (q15_t)0x599f, (q15_t)0xc55a,
+    (q15_t)0x5993, (q15_t)0xc555, (q15_t)0x5988, (q15_t)0xc550, (q15_t)0x597c, (q15_t)0xc54b, (q15_t)0x5971, (q15_t)0xc546,
+    (q15_t)0x5965, (q15_t)0xc541, (q15_t)0x595a, (q15_t)0xc53c, (q15_t)0x594e, (q15_t)0xc537, (q15_t)0x5943, (q15_t)0xc532,
+    (q15_t)0x5937, (q15_t)0xc52d, (q15_t)0x592c, (q15_t)0xc528, (q15_t)0x5920, (q15_t)0xc523, (q15_t)0x5914, (q15_t)0xc51e,
+    (q15_t)0x5909, (q15_t)0xc51a, (q15_t)0x58fd, (q15_t)0xc515, (q15_t)0x58f2, (q15_t)0xc510, (q15_t)0x58e6, (q15_t)0xc50b,
+    (q15_t)0x58db, (q15_t)0xc506, (q15_t)0x58cf, (q15_t)0xc501, (q15_t)0x58c3, (q15_t)0xc4fc, (q15_t)0x58b8, (q15_t)0xc4f7,
+    (q15_t)0x58ac, (q15_t)0xc4f2, (q15_t)0x58a1, (q15_t)0xc4ee, (q15_t)0x5895, (q15_t)0xc4e9, (q15_t)0x5889, (q15_t)0xc4e4,
+    (q15_t)0x587e, (q15_t)0xc4df, (q15_t)0x5872, (q15_t)0xc4da, (q15_t)0x5867, (q15_t)0xc4d6, (q15_t)0x585b, (q15_t)0xc4d1,
+    (q15_t)0x584f, (q15_t)0xc4cc, (q15_t)0x5844, (q15_t)0xc4c7, (q15_t)0x5838, (q15_t)0xc4c2, (q15_t)0x582d, (q15_t)0xc4be,
+    (q15_t)0x5821, (q15_t)0xc4b9, (q15_t)0x5815, (q15_t)0xc4b4, (q15_t)0x580a, (q15_t)0xc4b0, (q15_t)0x57fe, (q15_t)0xc4ab,
+    (q15_t)0x57f2, (q15_t)0xc4a6, (q15_t)0x57e7, (q15_t)0xc4a1, (q15_t)0x57db, (q15_t)0xc49d, (q15_t)0x57cf, (q15_t)0xc498,
+    (q15_t)0x57c4, (q15_t)0xc493, (q15_t)0x57b8, (q15_t)0xc48f, (q15_t)0x57ac, (q15_t)0xc48a, (q15_t)0x57a1, (q15_t)0xc485,
+    (q15_t)0x5795, (q15_t)0xc481, (q15_t)0x5789, (q15_t)0xc47c, (q15_t)0x577e, (q15_t)0xc478, (q15_t)0x5772, (q15_t)0xc473,
+    (q15_t)0x5766, (q15_t)0xc46e, (q15_t)0x575b, (q15_t)0xc46a, (q15_t)0x574f, (q15_t)0xc465, (q15_t)0x5743, (q15_t)0xc461,
+    (q15_t)0x5737, (q15_t)0xc45c, (q15_t)0x572c, (q15_t)0xc457, (q15_t)0x5720, (q15_t)0xc453, (q15_t)0x5714, (q15_t)0xc44e,
+    (q15_t)0x5709, (q15_t)0xc44a, (q15_t)0x56fd, (q15_t)0xc445, (q15_t)0x56f1, (q15_t)0xc441, (q15_t)0x56e5, (q15_t)0xc43c,
+    (q15_t)0x56da, (q15_t)0xc438, (q15_t)0x56ce, (q15_t)0xc433, (q15_t)0x56c2, (q15_t)0xc42f, (q15_t)0x56b6, (q15_t)0xc42a,
+    (q15_t)0x56ab, (q15_t)0xc426, (q15_t)0x569f, (q15_t)0xc422, (q15_t)0x5693, (q15_t)0xc41d, (q15_t)0x5687, (q15_t)0xc419,
+    (q15_t)0x567c, (q15_t)0xc414, (q15_t)0x5670, (q15_t)0xc410, (q15_t)0x5664, (q15_t)0xc40b, (q15_t)0x5658, (q15_t)0xc407,
+    (q15_t)0x564c, (q15_t)0xc403, (q15_t)0x5641, (q15_t)0xc3fe, (q15_t)0x5635, (q15_t)0xc3fa, (q15_t)0x5629, (q15_t)0xc3f6,
+    (q15_t)0x561d, (q15_t)0xc3f1, (q15_t)0x5612, (q15_t)0xc3ed, (q15_t)0x5606, (q15_t)0xc3e9, (q15_t)0x55fa, (q15_t)0xc3e4,
+    (q15_t)0x55ee, (q15_t)0xc3e0, (q15_t)0x55e2, (q15_t)0xc3dc, (q15_t)0x55d7, (q15_t)0xc3d7, (q15_t)0x55cb, (q15_t)0xc3d3,
+    (q15_t)0x55bf, (q15_t)0xc3cf, (q15_t)0x55b3, (q15_t)0xc3ca, (q15_t)0x55a7, (q15_t)0xc3c6, (q15_t)0x559b, (q15_t)0xc3c2,
+    (q15_t)0x5590, (q15_t)0xc3be, (q15_t)0x5584, (q15_t)0xc3ba, (q15_t)0x5578, (q15_t)0xc3b5, (q15_t)0x556c, (q15_t)0xc3b1,
+    (q15_t)0x5560, (q15_t)0xc3ad, (q15_t)0x5554, (q15_t)0xc3a9, (q15_t)0x5549, (q15_t)0xc3a5, (q15_t)0x553d, (q15_t)0xc3a0,
+    (q15_t)0x5531, (q15_t)0xc39c, (q15_t)0x5525, (q15_t)0xc398, (q15_t)0x5519, (q15_t)0xc394, (q15_t)0x550d, (q15_t)0xc390,
+    (q15_t)0x5501, (q15_t)0xc38c, (q15_t)0x54f6, (q15_t)0xc387, (q15_t)0x54ea, (q15_t)0xc383, (q15_t)0x54de, (q15_t)0xc37f,
+    (q15_t)0x54d2, (q15_t)0xc37b, (q15_t)0x54c6, (q15_t)0xc377, (q15_t)0x54ba, (q15_t)0xc373, (q15_t)0x54ae, (q15_t)0xc36f,
+    (q15_t)0x54a2, (q15_t)0xc36b, (q15_t)0x5496, (q15_t)0xc367, (q15_t)0x548b, (q15_t)0xc363, (q15_t)0x547f, (q15_t)0xc35f,
+    (q15_t)0x5473, (q15_t)0xc35b, (q15_t)0x5467, (q15_t)0xc357, (q15_t)0x545b, (q15_t)0xc353, (q15_t)0x544f, (q15_t)0xc34f,
+    (q15_t)0x5443, (q15_t)0xc34b, (q15_t)0x5437, (q15_t)0xc347, (q15_t)0x542b, (q15_t)0xc343, (q15_t)0x541f, (q15_t)0xc33f,
+    (q15_t)0x5413, (q15_t)0xc33b, (q15_t)0x5407, (q15_t)0xc337, (q15_t)0x53fb, (q15_t)0xc333, (q15_t)0x53f0, (q15_t)0xc32f,
+    (q15_t)0x53e4, (q15_t)0xc32b, (q15_t)0x53d8, (q15_t)0xc327, (q15_t)0x53cc, (q15_t)0xc323, (q15_t)0x53c0, (q15_t)0xc320,
+    (q15_t)0x53b4, (q15_t)0xc31c, (q15_t)0x53a8, (q15_t)0xc318, (q15_t)0x539c, (q15_t)0xc314, (q15_t)0x5390, (q15_t)0xc310,
+    (q15_t)0x5384, (q15_t)0xc30c, (q15_t)0x5378, (q15_t)0xc308, (q15_t)0x536c, (q15_t)0xc305, (q15_t)0x5360, (q15_t)0xc301,
+    (q15_t)0x5354, (q15_t)0xc2fd, (q15_t)0x5348, (q15_t)0xc2f9, (q15_t)0x533c, (q15_t)0xc2f5, (q15_t)0x5330, (q15_t)0xc2f2,
+    (q15_t)0x5324, (q15_t)0xc2ee, (q15_t)0x5318, (q15_t)0xc2ea, (q15_t)0x530c, (q15_t)0xc2e6, (q15_t)0x5300, (q15_t)0xc2e3,
+    (q15_t)0x52f4, (q15_t)0xc2df, (q15_t)0x52e8, (q15_t)0xc2db, (q15_t)0x52dc, (q15_t)0xc2d8, (q15_t)0x52d0, (q15_t)0xc2d4,
+    (q15_t)0x52c4, (q15_t)0xc2d0, (q15_t)0x52b8, (q15_t)0xc2cc, (q15_t)0x52ac, (q15_t)0xc2c9, (q15_t)0x52a0, (q15_t)0xc2c5,
+    (q15_t)0x5294, (q15_t)0xc2c1, (q15_t)0x5288, (q15_t)0xc2be, (q15_t)0x527c, (q15_t)0xc2ba, (q15_t)0x5270, (q15_t)0xc2b7,
+    (q15_t)0x5264, (q15_t)0xc2b3, (q15_t)0x5258, (q15_t)0xc2af, (q15_t)0x524c, (q15_t)0xc2ac, (q15_t)0x5240, (q15_t)0xc2a8,
+    (q15_t)0x5234, (q15_t)0xc2a5, (q15_t)0x5228, (q15_t)0xc2a1, (q15_t)0x521c, (q15_t)0xc29d, (q15_t)0x5210, (q15_t)0xc29a,
+    (q15_t)0x5204, (q15_t)0xc296, (q15_t)0x51f7, (q15_t)0xc293, (q15_t)0x51eb, (q15_t)0xc28f, (q15_t)0x51df, (q15_t)0xc28c,
+    (q15_t)0x51d3, (q15_t)0xc288, (q15_t)0x51c7, (q15_t)0xc285, (q15_t)0x51bb, (q15_t)0xc281, (q15_t)0x51af, (q15_t)0xc27e,
+    (q15_t)0x51a3, (q15_t)0xc27a, (q15_t)0x5197, (q15_t)0xc277, (q15_t)0x518b, (q15_t)0xc273, (q15_t)0x517f, (q15_t)0xc270,
+    (q15_t)0x5173, (q15_t)0xc26d, (q15_t)0x5167, (q15_t)0xc269, (q15_t)0x515a, (q15_t)0xc266, (q15_t)0x514e, (q15_t)0xc262,
+    (q15_t)0x5142, (q15_t)0xc25f, (q15_t)0x5136, (q15_t)0xc25c, (q15_t)0x512a, (q15_t)0xc258, (q15_t)0x511e, (q15_t)0xc255,
+    (q15_t)0x5112, (q15_t)0xc251, (q15_t)0x5106, (q15_t)0xc24e, (q15_t)0x50fa, (q15_t)0xc24b, (q15_t)0x50ed, (q15_t)0xc247,
+    (q15_t)0x50e1, (q15_t)0xc244, (q15_t)0x50d5, (q15_t)0xc241, (q15_t)0x50c9, (q15_t)0xc23e, (q15_t)0x50bd, (q15_t)0xc23a,
+    (q15_t)0x50b1, (q15_t)0xc237, (q15_t)0x50a5, (q15_t)0xc234, (q15_t)0x5099, (q15_t)0xc230, (q15_t)0x508c, (q15_t)0xc22d,
+    (q15_t)0x5080, (q15_t)0xc22a, (q15_t)0x5074, (q15_t)0xc227, (q15_t)0x5068, (q15_t)0xc223, (q15_t)0x505c, (q15_t)0xc220,
+    (q15_t)0x5050, (q15_t)0xc21d, (q15_t)0x5044, (q15_t)0xc21a, (q15_t)0x5037, (q15_t)0xc217, (q15_t)0x502b, (q15_t)0xc213,
+    (q15_t)0x501f, (q15_t)0xc210, (q15_t)0x5013, (q15_t)0xc20d, (q15_t)0x5007, (q15_t)0xc20a, (q15_t)0x4ffb, (q15_t)0xc207,
+    (q15_t)0x4fee, (q15_t)0xc204, (q15_t)0x4fe2, (q15_t)0xc201, (q15_t)0x4fd6, (q15_t)0xc1fd, (q15_t)0x4fca, (q15_t)0xc1fa,
+    (q15_t)0x4fbe, (q15_t)0xc1f7, (q15_t)0x4fb2, (q15_t)0xc1f4, (q15_t)0x4fa5, (q15_t)0xc1f1, (q15_t)0x4f99, (q15_t)0xc1ee,
+    (q15_t)0x4f8d, (q15_t)0xc1eb, (q15_t)0x4f81, (q15_t)0xc1e8, (q15_t)0x4f75, (q15_t)0xc1e5, (q15_t)0x4f68, (q15_t)0xc1e2,
+    (q15_t)0x4f5c, (q15_t)0xc1df, (q15_t)0x4f50, (q15_t)0xc1dc, (q15_t)0x4f44, (q15_t)0xc1d9, (q15_t)0x4f38, (q15_t)0xc1d6,
+    (q15_t)0x4f2b, (q15_t)0xc1d3, (q15_t)0x4f1f, (q15_t)0xc1d0, (q15_t)0x4f13, (q15_t)0xc1cd, (q15_t)0x4f07, (q15_t)0xc1ca,
+    (q15_t)0x4efb, (q15_t)0xc1c7, (q15_t)0x4eee, (q15_t)0xc1c4, (q15_t)0x4ee2, (q15_t)0xc1c1, (q15_t)0x4ed6, (q15_t)0xc1be,
+    (q15_t)0x4eca, (q15_t)0xc1bb, (q15_t)0x4ebd, (q15_t)0xc1b8, (q15_t)0x4eb1, (q15_t)0xc1b6, (q15_t)0x4ea5, (q15_t)0xc1b3,
+    (q15_t)0x4e99, (q15_t)0xc1b0, (q15_t)0x4e8c, (q15_t)0xc1ad, (q15_t)0x4e80, (q15_t)0xc1aa, (q15_t)0x4e74, (q15_t)0xc1a7,
+    (q15_t)0x4e68, (q15_t)0xc1a4, (q15_t)0x4e5c, (q15_t)0xc1a2, (q15_t)0x4e4f, (q15_t)0xc19f, (q15_t)0x4e43, (q15_t)0xc19c,
+    (q15_t)0x4e37, (q15_t)0xc199, (q15_t)0x4e2b, (q15_t)0xc196, (q15_t)0x4e1e, (q15_t)0xc194, (q15_t)0x4e12, (q15_t)0xc191,
+    (q15_t)0x4e06, (q15_t)0xc18e, (q15_t)0x4df9, (q15_t)0xc18b, (q15_t)0x4ded, (q15_t)0xc189, (q15_t)0x4de1, (q15_t)0xc186,
+    (q15_t)0x4dd5, (q15_t)0xc183, (q15_t)0x4dc8, (q15_t)0xc180, (q15_t)0x4dbc, (q15_t)0xc17e, (q15_t)0x4db0, (q15_t)0xc17b,
+    (q15_t)0x4da4, (q15_t)0xc178, (q15_t)0x4d97, (q15_t)0xc176, (q15_t)0x4d8b, (q15_t)0xc173, (q15_t)0x4d7f, (q15_t)0xc170,
+    (q15_t)0x4d72, (q15_t)0xc16e, (q15_t)0x4d66, (q15_t)0xc16b, (q15_t)0x4d5a, (q15_t)0xc168, (q15_t)0x4d4e, (q15_t)0xc166,
+    (q15_t)0x4d41, (q15_t)0xc163, (q15_t)0x4d35, (q15_t)0xc161, (q15_t)0x4d29, (q15_t)0xc15e, (q15_t)0x4d1c, (q15_t)0xc15b,
+    (q15_t)0x4d10, (q15_t)0xc159, (q15_t)0x4d04, (q15_t)0xc156, (q15_t)0x4cf8, (q15_t)0xc154, (q15_t)0x4ceb, (q15_t)0xc151,
+    (q15_t)0x4cdf, (q15_t)0xc14f, (q15_t)0x4cd3, (q15_t)0xc14c, (q15_t)0x4cc6, (q15_t)0xc14a, (q15_t)0x4cba, (q15_t)0xc147,
+    (q15_t)0x4cae, (q15_t)0xc145, (q15_t)0x4ca1, (q15_t)0xc142, (q15_t)0x4c95, (q15_t)0xc140, (q15_t)0x4c89, (q15_t)0xc13d,
+    (q15_t)0x4c7c, (q15_t)0xc13b, (q15_t)0x4c70, (q15_t)0xc138, (q15_t)0x4c64, (q15_t)0xc136, (q15_t)0x4c57, (q15_t)0xc134,
+    (q15_t)0x4c4b, (q15_t)0xc131, (q15_t)0x4c3f, (q15_t)0xc12f, (q15_t)0x4c32, (q15_t)0xc12c, (q15_t)0x4c26, (q15_t)0xc12a,
+    (q15_t)0x4c1a, (q15_t)0xc128, (q15_t)0x4c0d, (q15_t)0xc125, (q15_t)0x4c01, (q15_t)0xc123, (q15_t)0x4bf5, (q15_t)0xc120,
+    (q15_t)0x4be8, (q15_t)0xc11e, (q15_t)0x4bdc, (q15_t)0xc11c, (q15_t)0x4bd0, (q15_t)0xc119, (q15_t)0x4bc3, (q15_t)0xc117,
+    (q15_t)0x4bb7, (q15_t)0xc115, (q15_t)0x4bab, (q15_t)0xc113, (q15_t)0x4b9e, (q15_t)0xc110, (q15_t)0x4b92, (q15_t)0xc10e,
+    (q15_t)0x4b85, (q15_t)0xc10c, (q15_t)0x4b79, (q15_t)0xc109, (q15_t)0x4b6d, (q15_t)0xc107, (q15_t)0x4b60, (q15_t)0xc105,
+    (q15_t)0x4b54, (q15_t)0xc103, (q15_t)0x4b48, (q15_t)0xc100, (q15_t)0x4b3b, (q15_t)0xc0fe, (q15_t)0x4b2f, (q15_t)0xc0fc,
+    (q15_t)0x4b23, (q15_t)0xc0fa, (q15_t)0x4b16, (q15_t)0xc0f8, (q15_t)0x4b0a, (q15_t)0xc0f6, (q15_t)0x4afd, (q15_t)0xc0f3,
+    (q15_t)0x4af1, (q15_t)0xc0f1, (q15_t)0x4ae5, (q15_t)0xc0ef, (q15_t)0x4ad8, (q15_t)0xc0ed, (q15_t)0x4acc, (q15_t)0xc0eb,
+    (q15_t)0x4ac0, (q15_t)0xc0e9, (q15_t)0x4ab3, (q15_t)0xc0e7, (q15_t)0x4aa7, (q15_t)0xc0e4, (q15_t)0x4a9a, (q15_t)0xc0e2,
+    (q15_t)0x4a8e, (q15_t)0xc0e0, (q15_t)0x4a82, (q15_t)0xc0de, (q15_t)0x4a75, (q15_t)0xc0dc, (q15_t)0x4a69, (q15_t)0xc0da,
+    (q15_t)0x4a5c, (q15_t)0xc0d8, (q15_t)0x4a50, (q15_t)0xc0d6, (q15_t)0x4a44, (q15_t)0xc0d4, (q15_t)0x4a37, (q15_t)0xc0d2,
+    (q15_t)0x4a2b, (q15_t)0xc0d0, (q15_t)0x4a1e, (q15_t)0xc0ce, (q15_t)0x4a12, (q15_t)0xc0cc, (q15_t)0x4a06, (q15_t)0xc0ca,
+    (q15_t)0x49f9, (q15_t)0xc0c8, (q15_t)0x49ed, (q15_t)0xc0c6, (q15_t)0x49e0, (q15_t)0xc0c4, (q15_t)0x49d4, (q15_t)0xc0c2,
+    (q15_t)0x49c7, (q15_t)0xc0c0, (q15_t)0x49bb, (q15_t)0xc0be, (q15_t)0x49af, (q15_t)0xc0bd, (q15_t)0x49a2, (q15_t)0xc0bb,
+    (q15_t)0x4996, (q15_t)0xc0b9, (q15_t)0x4989, (q15_t)0xc0b7, (q15_t)0x497d, (q15_t)0xc0b5, (q15_t)0x4970, (q15_t)0xc0b3,
+    (q15_t)0x4964, (q15_t)0xc0b1, (q15_t)0x4958, (q15_t)0xc0af, (q15_t)0x494b, (q15_t)0xc0ae, (q15_t)0x493f, (q15_t)0xc0ac,
+    (q15_t)0x4932, (q15_t)0xc0aa, (q15_t)0x4926, (q15_t)0xc0a8, (q15_t)0x4919, (q15_t)0xc0a6, (q15_t)0x490d, (q15_t)0xc0a5,
+    (q15_t)0x4901, (q15_t)0xc0a3, (q15_t)0x48f4, (q15_t)0xc0a1, (q15_t)0x48e8, (q15_t)0xc09f, (q15_t)0x48db, (q15_t)0xc09e,
+    (q15_t)0x48cf, (q15_t)0xc09c, (q15_t)0x48c2, (q15_t)0xc09a, (q15_t)0x48b6, (q15_t)0xc098, (q15_t)0x48a9, (q15_t)0xc097,
+    (q15_t)0x489d, (q15_t)0xc095, (q15_t)0x4891, (q15_t)0xc093, (q15_t)0x4884, (q15_t)0xc092, (q15_t)0x4878, (q15_t)0xc090,
+    (q15_t)0x486b, (q15_t)0xc08e, (q15_t)0x485f, (q15_t)0xc08d, (q15_t)0x4852, (q15_t)0xc08b, (q15_t)0x4846, (q15_t)0xc089,
+    (q15_t)0x4839, (q15_t)0xc088, (q15_t)0x482d, (q15_t)0xc086, (q15_t)0x4820, (q15_t)0xc085, (q15_t)0x4814, (q15_t)0xc083,
+    (q15_t)0x4807, (q15_t)0xc081, (q15_t)0x47fb, (q15_t)0xc080, (q15_t)0x47ef, (q15_t)0xc07e, (q15_t)0x47e2, (q15_t)0xc07d,
+    (q15_t)0x47d6, (q15_t)0xc07b, (q15_t)0x47c9, (q15_t)0xc07a, (q15_t)0x47bd, (q15_t)0xc078, (q15_t)0x47b0, (q15_t)0xc077,
+    (q15_t)0x47a4, (q15_t)0xc075, (q15_t)0x4797, (q15_t)0xc074, (q15_t)0x478b, (q15_t)0xc072, (q15_t)0x477e, (q15_t)0xc071,
+    (q15_t)0x4772, (q15_t)0xc06f, (q15_t)0x4765, (q15_t)0xc06e, (q15_t)0x4759, (q15_t)0xc06c, (q15_t)0x474c, (q15_t)0xc06b,
+    (q15_t)0x4740, (q15_t)0xc069, (q15_t)0x4733, (q15_t)0xc068, (q15_t)0x4727, (q15_t)0xc067, (q15_t)0x471a, (q15_t)0xc065,
+    (q15_t)0x470e, (q15_t)0xc064, (q15_t)0x4701, (q15_t)0xc062, (q15_t)0x46f5, (q15_t)0xc061, (q15_t)0x46e8, (q15_t)0xc060,
+    (q15_t)0x46dc, (q15_t)0xc05e, (q15_t)0x46cf, (q15_t)0xc05d, (q15_t)0x46c3, (q15_t)0xc05c, (q15_t)0x46b6, (q15_t)0xc05a,
+    (q15_t)0x46aa, (q15_t)0xc059, (q15_t)0x469d, (q15_t)0xc058, (q15_t)0x4691, (q15_t)0xc056, (q15_t)0x4684, (q15_t)0xc055,
+    (q15_t)0x4678, (q15_t)0xc054, (q15_t)0x466b, (q15_t)0xc053, (q15_t)0x465f, (q15_t)0xc051, (q15_t)0x4652, (q15_t)0xc050,
+    (q15_t)0x4646, (q15_t)0xc04f, (q15_t)0x4639, (q15_t)0xc04e, (q15_t)0x462d, (q15_t)0xc04c, (q15_t)0x4620, (q15_t)0xc04b,
+    (q15_t)0x4614, (q15_t)0xc04a, (q15_t)0x4607, (q15_t)0xc049, (q15_t)0x45fb, (q15_t)0xc048, (q15_t)0x45ee, (q15_t)0xc047,
+    (q15_t)0x45e2, (q15_t)0xc045, (q15_t)0x45d5, (q15_t)0xc044, (q15_t)0x45c9, (q15_t)0xc043, (q15_t)0x45bc, (q15_t)0xc042,
+    (q15_t)0x45b0, (q15_t)0xc041, (q15_t)0x45a3, (q15_t)0xc040, (q15_t)0x4597, (q15_t)0xc03f, (q15_t)0x458a, (q15_t)0xc03d,
+    (q15_t)0x457e, (q15_t)0xc03c, (q15_t)0x4571, (q15_t)0xc03b, (q15_t)0x4565, (q15_t)0xc03a, (q15_t)0x4558, (q15_t)0xc039,
+    (q15_t)0x454c, (q15_t)0xc038, (q15_t)0x453f, (q15_t)0xc037, (q15_t)0x4533, (q15_t)0xc036, (q15_t)0x4526, (q15_t)0xc035,
+    (q15_t)0x451a, (q15_t)0xc034, (q15_t)0x450d, (q15_t)0xc033, (q15_t)0x4500, (q15_t)0xc032, (q15_t)0x44f4, (q15_t)0xc031,
+    (q15_t)0x44e7, (q15_t)0xc030, (q15_t)0x44db, (q15_t)0xc02f, (q15_t)0x44ce, (q15_t)0xc02e, (q15_t)0x44c2, (q15_t)0xc02d,
+    (q15_t)0x44b5, (q15_t)0xc02c, (q15_t)0x44a9, (q15_t)0xc02b, (q15_t)0x449c, (q15_t)0xc02b, (q15_t)0x4490, (q15_t)0xc02a,
+    (q15_t)0x4483, (q15_t)0xc029, (q15_t)0x4477, (q15_t)0xc028, (q15_t)0x446a, (q15_t)0xc027, (q15_t)0x445e, (q15_t)0xc026,
+    (q15_t)0x4451, (q15_t)0xc025, (q15_t)0x4444, (q15_t)0xc024, (q15_t)0x4438, (q15_t)0xc024, (q15_t)0x442b, (q15_t)0xc023,
+    (q15_t)0x441f, (q15_t)0xc022, (q15_t)0x4412, (q15_t)0xc021, (q15_t)0x4406, (q15_t)0xc020, (q15_t)0x43f9, (q15_t)0xc020,
+    (q15_t)0x43ed, (q15_t)0xc01f, (q15_t)0x43e0, (q15_t)0xc01e, (q15_t)0x43d4, (q15_t)0xc01d, (q15_t)0x43c7, (q15_t)0xc01d,
+    (q15_t)0x43bb, (q15_t)0xc01c, (q15_t)0x43ae, (q15_t)0xc01b, (q15_t)0x43a1, (q15_t)0xc01a, (q15_t)0x4395, (q15_t)0xc01a,
+    (q15_t)0x4388, (q15_t)0xc019, (q15_t)0x437c, (q15_t)0xc018, (q15_t)0x436f, (q15_t)0xc018, (q15_t)0x4363, (q15_t)0xc017,
+    (q15_t)0x4356, (q15_t)0xc016, (q15_t)0x434a, (q15_t)0xc016, (q15_t)0x433d, (q15_t)0xc015, (q15_t)0x4330, (q15_t)0xc014,
+    (q15_t)0x4324, (q15_t)0xc014, (q15_t)0x4317, (q15_t)0xc013, (q15_t)0x430b, (q15_t)0xc013, (q15_t)0x42fe, (q15_t)0xc012,
+    (q15_t)0x42f2, (q15_t)0xc011, (q15_t)0x42e5, (q15_t)0xc011, (q15_t)0x42d9, (q15_t)0xc010, (q15_t)0x42cc, (q15_t)0xc010,
+    (q15_t)0x42c0, (q15_t)0xc00f, (q15_t)0x42b3, (q15_t)0xc00f, (q15_t)0x42a6, (q15_t)0xc00e, (q15_t)0x429a, (q15_t)0xc00e,
+    (q15_t)0x428d, (q15_t)0xc00d, (q15_t)0x4281, (q15_t)0xc00d, (q15_t)0x4274, (q15_t)0xc00c, (q15_t)0x4268, (q15_t)0xc00c,
+    (q15_t)0x425b, (q15_t)0xc00b, (q15_t)0x424e, (q15_t)0xc00b, (q15_t)0x4242, (q15_t)0xc00a, (q15_t)0x4235, (q15_t)0xc00a,
+    (q15_t)0x4229, (q15_t)0xc009, (q15_t)0x421c, (q15_t)0xc009, (q15_t)0x4210, (q15_t)0xc009, (q15_t)0x4203, (q15_t)0xc008,
+    (q15_t)0x41f7, (q15_t)0xc008, (q15_t)0x41ea, (q15_t)0xc007, (q15_t)0x41dd, (q15_t)0xc007, (q15_t)0x41d1, (q15_t)0xc007,
+    (q15_t)0x41c4, (q15_t)0xc006, (q15_t)0x41b8, (q15_t)0xc006, (q15_t)0x41ab, (q15_t)0xc006, (q15_t)0x419f, (q15_t)0xc005,
+    (q15_t)0x4192, (q15_t)0xc005, (q15_t)0x4186, (q15_t)0xc005, (q15_t)0x4179, (q15_t)0xc004, (q15_t)0x416c, (q15_t)0xc004,
+    (q15_t)0x4160, (q15_t)0xc004, (q15_t)0x4153, (q15_t)0xc004, (q15_t)0x4147, (q15_t)0xc003, (q15_t)0x413a, (q15_t)0xc003,
+    (q15_t)0x412e, (q15_t)0xc003, (q15_t)0x4121, (q15_t)0xc003, (q15_t)0x4114, (q15_t)0xc002, (q15_t)0x4108, (q15_t)0xc002,
+    (q15_t)0x40fb, (q15_t)0xc002, (q15_t)0x40ef, (q15_t)0xc002, (q15_t)0x40e2, (q15_t)0xc002, (q15_t)0x40d6, (q15_t)0xc001,
+    (q15_t)0x40c9, (q15_t)0xc001, (q15_t)0x40bc, (q15_t)0xc001, (q15_t)0x40b0, (q15_t)0xc001, (q15_t)0x40a3, (q15_t)0xc001,
+    (q15_t)0x4097, (q15_t)0xc001, (q15_t)0x408a, (q15_t)0xc001, (q15_t)0x407e, (q15_t)0xc000, (q15_t)0x4071, (q15_t)0xc000,
+    (q15_t)0x4065, (q15_t)0xc000, (q15_t)0x4058, (q15_t)0xc000, (q15_t)0x404b, (q15_t)0xc000, (q15_t)0x403f, (q15_t)0xc000,
+    (q15_t)0x4032, (q15_t)0xc000, (q15_t)0x4026, (q15_t)0xc000, (q15_t)0x4019, (q15_t)0xc000, (q15_t)0x400d, (q15_t)0xc000,
+};
+
+/**
+* @} end of RealFFT_Table group
+*/
+
+/**
+* @addtogroup RealFFT
+* @{
+*/
+
+/**
+* @brief  Initialization function for the Q15 RFFT/RIFFT.
+* @param[in, out] *S             points to an instance of the Q15 RFFT/RIFFT structure.
+* @param[in]      fftLenReal     length of the FFT.
+* @param[in]      ifftFlagR      flag that selects forward (ifftFlagR=0) or inverse (ifftFlagR=1) transform.
+* @param[in]      bitReverseFlag flag that enables (bitReverseFlag=1) or disables (bitReverseFlag=0) bit reversal of output.
+* @return         The function returns ARM_MATH_SUCCESS if initialization is successful or ARM_MATH_ARGUMENT_ERROR if <code>fftLenReal</code> is not a supported value.
+*
+* \par Description:
+* \par
+* The parameter <code>fftLenReal</code>	Specifies length of RFFT/RIFFT Process. Supported FFT Lengths are 32, 64, 128, 256, 512, 1024, 2048, 4096, 8192.
+* \par
+* The parameter <code>ifftFlagR</code> controls whether a forward or inverse transform is computed.
+* Set(=1) ifftFlagR to calculate RIFFT, otherwise RFFT is calculated.
+* \par
+* The parameter <code>bitReverseFlag</code> controls whether output is in normal order or bit reversed order.
+* Set(=1) bitReverseFlag for output to be in normal order otherwise output is in bit reversed order.
+* \par
+* This function also initializes Twiddle factor table.
+*/
+arm_status arm_rfft_init_q15(
+    arm_rfft_instance_q15 * S,
+    uint32_t fftLenReal,
+    uint32_t ifftFlagR,
+    uint32_t bitReverseFlag)
+{
+    /*  Initialise the default arm status */
+    arm_status status = ARM_MATH_SUCCESS;
+
+    /*  Initialize the Real FFT length */
+    S->fftLenReal = (uint16_t) fftLenReal;
+
+    /*  Initialize the Twiddle coefficientA pointer */
+    S->pTwiddleAReal = (q15_t *) realCoefAQ15;
+
+    /*  Initialize the Twiddle coefficientB pointer */
+    S->pTwiddleBReal = (q15_t *) realCoefBQ15;
+
+    /*  Initialize the Flag for selection of RFFT or RIFFT */
+    S->ifftFlagR = (uint8_t) ifftFlagR;
+
+    /*  Initialize the Flag for calculation Bit reversal or not */
+    S->bitReverseFlagR = (uint8_t) bitReverseFlag;
+
+    /*  Initialization of coef modifier depending on the FFT length */
+    switch (S->fftLenReal)
+    {
+    case 8192U:
+        S->twidCoefRModifier = 1U;
+        S->pCfft = &arm_cfft_sR_q15_len4096;
+        break;
+    case 4096U:
+        S->twidCoefRModifier = 2U;
+        S->pCfft = &arm_cfft_sR_q15_len2048;
+        break;
+    case 2048U:
+        S->twidCoefRModifier = 4U;
+        S->pCfft = &arm_cfft_sR_q15_len1024;
+        break;
+    case 1024U:
+        S->twidCoefRModifier = 8U;
+        S->pCfft = &arm_cfft_sR_q15_len512;
+        break;
+    case 512U:
+        S->twidCoefRModifier = 16U;
+        S->pCfft = &arm_cfft_sR_q15_len256;
+        break;
+    case 256U:
+        S->twidCoefRModifier = 32U;
+        S->pCfft = &arm_cfft_sR_q15_len128;
+        break;
+    case 128U:
+        S->twidCoefRModifier = 64U;
+        S->pCfft = &arm_cfft_sR_q15_len64;
+        break;
+    case 64U:
+        S->twidCoefRModifier = 128U;
+        S->pCfft = &arm_cfft_sR_q15_len32;
+        break;
+    case 32U:
+        S->twidCoefRModifier = 256U;
+        S->pCfft = &arm_cfft_sR_q15_len16;
+        break;
+    default:
+        /*  Reporting argument error if rfftSize is not valid value */
+        status = ARM_MATH_ARGUMENT_ERROR;
+        break;
+    }
+
+    /* return the status of RFFT Init function */
+    return (status);
+}
+
+/**
+* @} end of RealFFT group
+*/

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/TransformFunctions/arm_rfft_q15.c
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/experimental/micro/tools/make/downloads/cmsis/CMSIS/DSP/Source/TransformFunctions/arm_rfft_q15.c	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,426 @@
+/* ----------------------------------------------------------------------
+ * Project:      CMSIS DSP Library
+ * Title:        arm_rfft_q15.c
+ * Description:  RFFT & RIFFT Q15 process function
+ *
+ * $Date:        27. January 2017
+ * $Revision:    V.1.5.1
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+/*
+ * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "arm_math.h"
+
+/* ----------------------------------------------------------------------
+ * Internal functions prototypes
+ * -------------------------------------------------------------------- */
+
+void arm_split_rfft_q15(
+    q15_t * pSrc,
+    uint32_t fftLen,
+    q15_t * pATable,
+    q15_t * pBTable,
+    q15_t * pDst,
+    uint32_t modifier);
+
+void arm_split_rifft_q15(
+    q15_t * pSrc,
+    uint32_t fftLen,
+    q15_t * pATable,
+    q15_t * pBTable,
+    q15_t * pDst,
+    uint32_t modifier);
+
+/**
+* @addtogroup RealFFT
+* @{
+*/
+
+/**
+* @brief Processing function for the Q15 RFFT/RIFFT.
+* @param[in]  *S    points to an instance of the Q15 RFFT/RIFFT structure.
+* @param[in]  *pSrc points to the input buffer.
+* @param[out] *pDst points to the output buffer.
+* @return none.
+*
+* \par Input an output formats:
+* \par
+* Internally input is downscaled by 2 for every stage to avoid saturations inside CFFT/CIFFT process.
+* Hence the output format is different for different RFFT sizes.
+* The input and output formats for different RFFT sizes and number of bits to upscale are mentioned in the tables below for RFFT and RIFFT:
+* \par
+* \image html RFFTQ15.gif "Input and Output Formats for Q15 RFFT"
+* \par
+* \image html RIFFTQ15.gif "Input and Output Formats for Q15 RIFFT"
+*/
+
+void arm_rfft_q15(
+    const arm_rfft_instance_q15 * S,
+    q15_t * pSrc,
+    q15_t * pDst)
+{
+    const arm_cfft_instance_q15 *S_CFFT = S->pCfft;
+    uint32_t i;
+    uint32_t L2 = S->fftLenReal >> 1;
+
+    /* Calculation of RIFFT of input */
+    if (S->ifftFlagR == 1U)
+    {
+        /*  Real IFFT core process */
+        arm_split_rifft_q15(pSrc, L2, S->pTwiddleAReal,
+                            S->pTwiddleBReal, pDst, S->twidCoefRModifier);
+
+        /* Complex IFFT process */
+        arm_cfft_q15(S_CFFT, pDst, S->ifftFlagR, S->bitReverseFlagR);
+
+        for(i=0;i<S->fftLenReal;i++)
+        {
+            pDst[i] = pDst[i] << 1;
+        }
+    }
+    else
+    {
+        /* Calculation of RFFT of input */
+
+        /* Complex FFT process */
+        arm_cfft_q15(S_CFFT, pSrc, S->ifftFlagR, S->bitReverseFlagR);
+
+        /*  Real FFT core process */
+        arm_split_rfft_q15(pSrc, L2, S->pTwiddleAReal,
+                            S->pTwiddleBReal, pDst, S->twidCoefRModifier);
+    }
+}
+
+/**
+* @} end of RealFFT group
+*/
+
+/**
+* @brief  Core Real FFT process
+* @param  *pSrc 				points to the input buffer.
+* @param  fftLen  				length of FFT.
+* @param  *pATable 			points to the A twiddle Coef buffer.
+* @param  *pBTable 			points to the B twiddle Coef buffer.
+* @param  *pDst 				points to the output buffer.
+* @param  modifier 	        twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table.
+* @return none.
+* The function implements a Real FFT
+*/
+
+void arm_split_rfft_q15(
+    q15_t * pSrc,
+    uint32_t fftLen,
+    q15_t * pATable,
+    q15_t * pBTable,
+    q15_t * pDst,
+    uint32_t modifier)
+{
+    uint32_t i;                                    /* Loop Counter */
+    q31_t outR, outI;                              /* Temporary variables for output */
+    q15_t *pCoefA, *pCoefB;                        /* Temporary pointers for twiddle factors */
+    q15_t *pSrc1, *pSrc2;
+#if defined (ARM_MATH_DSP)
+    q15_t *pD1, *pD2;
+#endif
+
+    //  pSrc[2U * fftLen] = pSrc[0];
+    //  pSrc[(2U * fftLen) + 1U] = pSrc[1];
+
+    pCoefA = &pATable[modifier * 2U];
+    pCoefB = &pBTable[modifier * 2U];
+
+    pSrc1 = &pSrc[2];
+    pSrc2 = &pSrc[(2U * fftLen) - 2U];
+
+#if defined (ARM_MATH_DSP)
+
+    /* Run the below code for Cortex-M4 and Cortex-M3 */
+    i = 1U;
+    pD1 = pDst + 2;
+    pD2 = pDst + (4U * fftLen) - 2;
+
+    for(i = fftLen - 1; i > 0; i--)
+    {
+        /*
+        outR = (pSrc[2 * i] * pATable[2 * i] - pSrc[2 * i + 1] * pATable[2 * i + 1]
+        + pSrc[2 * n - 2 * i] * pBTable[2 * i] +
+        pSrc[2 * n - 2 * i + 1] * pBTable[2 * i + 1]);
+        */
+
+        /* outI = (pIn[2 * i + 1] * pATable[2 * i] + pIn[2 * i] * pATable[2 * i + 1] +
+        pIn[2 * n - 2 * i] * pBTable[2 * i + 1] -
+        pIn[2 * n - 2 * i + 1] * pBTable[2 * i]); */
+
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+        /* pSrc[2 * i] * pATable[2 * i] - pSrc[2 * i + 1] * pATable[2 * i + 1] */
+        outR = __SMUSD(*__SIMD32(pSrc1), *__SIMD32(pCoefA));
+
+#else
+
+        /* -(pSrc[2 * i + 1] * pATable[2 * i + 1] - pSrc[2 * i] * pATable[2 * i]) */
+        outR = -(__SMUSD(*__SIMD32(pSrc1), *__SIMD32(pCoefA)));
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+        /* pSrc[2 * n - 2 * i] * pBTable[2 * i] +
+        pSrc[2 * n - 2 * i + 1] * pBTable[2 * i + 1]) */
+        outR = __SMLAD(*__SIMD32(pSrc2), *__SIMD32(pCoefB), outR) >> 16U;
+
+        /* pIn[2 * n - 2 * i] * pBTable[2 * i + 1] -
+        pIn[2 * n - 2 * i + 1] * pBTable[2 * i] */
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+        outI = __SMUSDX(*__SIMD32(pSrc2)--, *__SIMD32(pCoefB));
+
+#else
+
+        outI = __SMUSDX(*__SIMD32(pCoefB), *__SIMD32(pSrc2)--);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+        /* (pIn[2 * i + 1] * pATable[2 * i] + pIn[2 * i] * pATable[2 * i + 1] */
+        outI = __SMLADX(*__SIMD32(pSrc1)++, *__SIMD32(pCoefA), outI);
+
+        /* write output */
+        *pD1++ = (q15_t) outR;
+        *pD1++ = outI >> 16U;
+
+        /* write complex conjugate output */
+        pD2[0] = (q15_t) outR;
+        pD2[1] = -(outI >> 16U);
+        pD2 -= 2;
+
+        /* update coefficient pointer */
+        pCoefB = pCoefB + (2U * modifier);
+        pCoefA = pCoefA + (2U * modifier);
+    }
+
+    pDst[2U * fftLen] = (pSrc[0] - pSrc[1]) >> 1;
+    pDst[(2U * fftLen) + 1U] = 0;
+
+    pDst[0] = (pSrc[0] + pSrc[1]) >> 1;
+    pDst[1] = 0;
+
+#else
+
+    /* Run the below code for Cortex-M0 */
+    i = 1U;
+
+    while (i < fftLen)
+    {
+        /*
+        outR = (pSrc[2 * i] * pATable[2 * i] - pSrc[2 * i + 1] * pATable[2 * i + 1]
+        + pSrc[2 * n - 2 * i] * pBTable[2 * i] +
+        pSrc[2 * n - 2 * i + 1] * pBTable[2 * i + 1]);
+        */
+
+        outR = *pSrc1 * *pCoefA;
+        outR = outR - (*(pSrc1 + 1) * *(pCoefA + 1));
+        outR = outR + (*pSrc2 * *pCoefB);
+        outR = (outR + (*(pSrc2 + 1) * *(pCoefB + 1))) >> 16;
+
+
+        /* outI = (pIn[2 * i + 1] * pATable[2 * i] + pIn[2 * i] * pATable[2 * i + 1] +
+        pIn[2 * n - 2 * i] * pBTable[2 * i + 1] -
+        pIn[2 * n - 2 * i + 1] * pBTable[2 * i]);
+        */
+
+        outI = *pSrc2 * *(pCoefB + 1);
+        outI = outI - (*(pSrc2 + 1) * *pCoefB);
+        outI = outI + (*(pSrc1 + 1) * *pCoefA);
+        outI = outI + (*pSrc1 * *(pCoefA + 1));
+
+        /* update input pointers */
+        pSrc1 += 2U;
+        pSrc2 -= 2U;
+
+        /* write output */
+        pDst[2U * i] = (q15_t) outR;
+        pDst[(2U * i) + 1U] = outI >> 16U;
+
+        /* write complex conjugate output */
+        pDst[(4U * fftLen) - (2U * i)] = (q15_t) outR;
+        pDst[((4U * fftLen) - (2U * i)) + 1U] = -(outI >> 16U);
+
+        /* update coefficient pointer */
+        pCoefB = pCoefB + (2U * modifier);
+        pCoefA = pCoefA + (2U * modifier);
+
+        i++;
+    }
+
+    pDst[2U * fftLen] = (pSrc[0] - pSrc[1]) >> 1;
+    pDst[(2U * fftLen) + 1U] = 0;
+
+    pDst[0] = (pSrc[0] + pSrc[1]) >> 1;
+    pDst[1] = 0;
+
+#endif /* #if defined (ARM_MATH_DSP) */
+}
+
+
+/**
+* @brief  Core Real IFFT process
+* @param[in]   *pSrc 				points to the input buffer.
+* @param[in]   fftLen  		    length of FFT.
+* @param[in]   *pATable 			points to the twiddle Coef A buffer.
+* @param[in]   *pBTable 			points to the twiddle Coef B buffer.
+* @param[out]  *pDst 				points to the output buffer.
+* @param[in]   modifier 	        twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table.
+* @return none.
+* The function implements a Real IFFT
+*/
+void arm_split_rifft_q15(
+    q15_t * pSrc,
+    uint32_t fftLen,
+    q15_t * pATable,
+    q15_t * pBTable,
+    q15_t * pDst,
+    uint32_t modifier)
+{
+    uint32_t i;                                    /* Loop Counter */
+    q31_t outR, outI;                              /* Temporary variables for output */
+    q15_t *pCoefA, *pCoefB;                        /* Temporary pointers for twiddle factors */
+    q15_t *pSrc1, *pSrc2;
+    q15_t *pDst1 = &pDst[0];
+
+    pCoefA = &pATable[0];
+    pCoefB = &pBTable[0];
+
+    pSrc1 = &pSrc[0];
+    pSrc2 = &pSrc[2U * fftLen];
+
+#if defined (ARM_MATH_DSP)
+
+    /* Run the below code for Cortex-M4 and Cortex-M3 */
+    i = fftLen;
+
+    while (i > 0U)
+    {
+        /*
+        outR = (pIn[2 * i] * pATable[2 * i] + pIn[2 * i + 1] * pATable[2 * i + 1] +
+        pIn[2 * n - 2 * i] * pBTable[2 * i] -
+        pIn[2 * n - 2 * i + 1] * pBTable[2 * i + 1]);
+
+        outI = (pIn[2 * i + 1] * pATable[2 * i] - pIn[2 * i] * pATable[2 * i + 1] -
+        pIn[2 * n - 2 * i] * pBTable[2 * i + 1] -
+        pIn[2 * n - 2 * i + 1] * pBTable[2 * i]);
+        */
+
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+        /* pIn[2 * n - 2 * i] * pBTable[2 * i] -
+        pIn[2 * n - 2 * i + 1] * pBTable[2 * i + 1]) */
+        outR = __SMUSD(*__SIMD32(pSrc2), *__SIMD32(pCoefB));
+
+#else
+
+        /* -(-pIn[2 * n - 2 * i] * pBTable[2 * i] +
+        pIn[2 * n - 2 * i + 1] * pBTable[2 * i + 1])) */
+        outR = -(__SMUSD(*__SIMD32(pSrc2), *__SIMD32(pCoefB)));
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+        /* pIn[2 * i] * pATable[2 * i] + pIn[2 * i + 1] * pATable[2 * i + 1] +
+        pIn[2 * n - 2 * i] * pBTable[2 * i] */
+        outR = __SMLAD(*__SIMD32(pSrc1), *__SIMD32(pCoefA), outR) >> 16U;
+
+        /*
+        -pIn[2 * n - 2 * i] * pBTable[2 * i + 1] +
+        pIn[2 * n - 2 * i + 1] * pBTable[2 * i] */
+        outI = __SMUADX(*__SIMD32(pSrc2)--, *__SIMD32(pCoefB));
+
+        /* pIn[2 * i + 1] * pATable[2 * i] - pIn[2 * i] * pATable[2 * i + 1] */
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+        outI = __SMLSDX(*__SIMD32(pCoefA), *__SIMD32(pSrc1)++, -outI);
+
+#else
+
+        outI = __SMLSDX(*__SIMD32(pSrc1)++, *__SIMD32(pCoefA), -outI);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+        /* write output */
+
+#ifndef ARM_MATH_BIG_ENDIAN
+
+        *__SIMD32(pDst1)++ = __PKHBT(outR, (outI >> 16U), 16);
+
+#else
+
+        *__SIMD32(pDst1)++ = __PKHBT((outI >> 16U), outR, 16);
+
+#endif /*      #ifndef ARM_MATH_BIG_ENDIAN     */
+
+        /* update coefficient pointer */
+        pCoefB = pCoefB + (2U * modifier);
+        pCoefA = pCoefA + (2U * modifier);
+
+        i--;
+    }
+#else
+    /* Run the below code for Cortex-M0 */
+    i = fftLen;
+
+    while (i > 0U)
+    {
+        /*
+        outR = (pIn[2 * i] * pATable[2 * i] + pIn[2 * i + 1] * pATable[2 * i + 1] +
+        pIn[2 * n - 2 * i] * pBTable[2 * i] -
+        pIn[2 * n - 2 * i + 1] * pBTable[2 * i + 1]);
+        */
+
+        outR = *pSrc2 * *pCoefB;
+        outR = outR - (*(pSrc2 + 1) * *(pCoefB + 1));
+        outR = outR + (*pSrc1 * *pCoefA);
+        outR = (outR + (*(pSrc1 + 1) * *(pCoefA + 1))) >> 16;
+
+        /*
+        outI = (pIn[2 * i + 1] * pATable[2 * i] - pIn[2 * i] * pATable[2 * i + 1] -
+        pIn[2 * n - 2 * i] * pBTable[2 * i + 1] -
+        pIn[2 * n - 2 * i + 1] * pBTable[2 * i]);
+        */
+
+        outI = *(pSrc1 + 1) * *pCoefA;
+        outI = outI - (*pSrc1 * *(pCoefA + 1));
+        outI = outI - (*pSrc2 * *(pCoefB + 1));
+        outI = outI - (*(pSrc2 + 1) * *(pCoefB));
+
+        /* update input pointers */
+        pSrc1 += 2U;
+        pSrc2 -= 2U;
+
+        /* write output */
+        *pDst1++ = (q15_t) outR;
+        *pDst1++ = (q15_t) (outI >> 16);
+
+        /* update coefficient pointer */
+        pCoefB = pCoefB + (2U * modifier);
+        pCoefA = pCoefA + (2U * modifier);
+
+        i--;
+    }
+#endif /* #if defined (ARM_MATH_DSP) */
+}

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/common.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/common.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,715 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_COMMON_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_COMMON_H_
+
+#ifndef ALLOW_SLOW_GENERIC_DEPTHWISECONV_FALLBACK
+#ifdef GEMMLOWP_ALLOW_SLOW_SCALAR_FALLBACK
+#define ALLOW_SLOW_GENERIC_DEPTHWISECONV_FALLBACK
+#endif
+#endif
+
+#include "fixedpoint/fixedpoint.h"
+#include "tensorflow/lite/kernels/internal/optimized/neon_check.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+inline void GetActivationMinMax(FusedActivationFunctionType ac,
+                                float* output_activation_min,
+                                float* output_activation_max) {
+  switch (ac) {
+    case FusedActivationFunctionType::kNone:
+      *output_activation_min = std::numeric_limits<float>::lowest();
+      *output_activation_max = std::numeric_limits<float>::max();
+      break;
+    case FusedActivationFunctionType::kRelu:
+      *output_activation_min = 0.f;
+      *output_activation_max = std::numeric_limits<float>::max();
+      break;
+    case FusedActivationFunctionType::kRelu1:
+      *output_activation_min = -1.f;
+      *output_activation_max = 1.f;
+      break;
+    case FusedActivationFunctionType::kRelu6:
+      *output_activation_min = 0.f;
+      *output_activation_max = 6.f;
+      break;
+  }
+}
+
+inline float ActivationFunctionWithMinMax(float x, float output_activation_min,
+                                          float output_activation_max) {
+  return std::min(std::max(x, output_activation_min), output_activation_max);
+}
+
+// Legacy function, left for compatibility only.
+template <FusedActivationFunctionType Ac>
+float ActivationFunction(float x) {
+  float output_activation_min, output_activation_max;
+  GetActivationMinMax(Ac, &output_activation_min, &output_activation_max);
+  return ActivationFunctionWithMinMax(x, output_activation_min,
+                                      output_activation_max);
+}
+
+inline void BiasAndClamp(float clamp_min, float clamp_max, int bias_size,
+                         const float* bias_data, int array_size,
+                         float* array_data) {
+  // Note: see b/132215220: in May 2019 we thought it would be OK to replace
+  // this with the Eigen one-liner:
+  //   return (array.colwise() + bias).cwiseMin(clamp_max).cwiseMin(clamp_max).
+  // This turned out to severely regress performance: +4ms (i.e. 8%) on
+  // MobileNet v2 / 1.0 / 224. So we keep custom NEON code for now.
+  TFLITE_DCHECK_EQ((array_size % bias_size), 0);
+#ifdef USE_NEON
+  float* array_ptr = array_data;
+  float* array_end_ptr = array_ptr + array_size;
+  const auto clamp_min_vec = vdupq_n_f32(clamp_min);
+  const auto clamp_max_vec = vdupq_n_f32(clamp_max);
+  for (; array_ptr != array_end_ptr; array_ptr += bias_size) {
+    int i = 0;
+    for (; i <= bias_size - 16; i += 16) {
+      auto b0 = vld1q_f32(bias_data + i);
+      auto b1 = vld1q_f32(bias_data + i + 4);
+      auto b2 = vld1q_f32(bias_data + i + 8);
+      auto b3 = vld1q_f32(bias_data + i + 12);
+      auto a0 = vld1q_f32(array_ptr + i);
+      auto a1 = vld1q_f32(array_ptr + i + 4);
+      auto a2 = vld1q_f32(array_ptr + i + 8);
+      auto a3 = vld1q_f32(array_ptr + i + 12);
+      auto x0 = vaddq_f32(a0, b0);
+      auto x1 = vaddq_f32(a1, b1);
+      auto x2 = vaddq_f32(a2, b2);
+      auto x3 = vaddq_f32(a3, b3);
+      x0 = vmaxq_f32(clamp_min_vec, x0);
+      x1 = vmaxq_f32(clamp_min_vec, x1);
+      x2 = vmaxq_f32(clamp_min_vec, x2);
+      x3 = vmaxq_f32(clamp_min_vec, x3);
+      x0 = vminq_f32(clamp_max_vec, x0);
+      x1 = vminq_f32(clamp_max_vec, x1);
+      x2 = vminq_f32(clamp_max_vec, x2);
+      x3 = vminq_f32(clamp_max_vec, x3);
+      vst1q_f32(array_ptr + i, x0);
+      vst1q_f32(array_ptr + i + 4, x1);
+      vst1q_f32(array_ptr + i + 8, x2);
+      vst1q_f32(array_ptr + i + 12, x3);
+    }
+    for (; i <= bias_size - 4; i += 4) {
+      auto b = vld1q_f32(bias_data + i);
+      auto a = vld1q_f32(array_ptr + i);
+      auto x = vaddq_f32(a, b);
+      x = vmaxq_f32(clamp_min_vec, x);
+      x = vminq_f32(clamp_max_vec, x);
+      vst1q_f32(array_ptr + i, x);
+    }
+    for (; i < bias_size; i++) {
+      array_ptr[i] = ActivationFunctionWithMinMax(array_ptr[i] + bias_data[i],
+                                                  clamp_min, clamp_max);
+    }
+  }
+#else  // not NEON
+  for (int array_offset = 0; array_offset < array_size;
+       array_offset += bias_size) {
+    for (int i = 0; i < bias_size; i++) {
+      array_data[array_offset + i] = ActivationFunctionWithMinMax(
+          array_data[array_offset + i] + bias_data[i], clamp_min, clamp_max);
+    }
+  }
+#endif
+}
+
+inline int32 MultiplyByQuantizedMultiplierSmallerThanOneExp(
+    int32 x, int32 quantized_multiplier, int left_shift) {
+  using gemmlowp::RoundingDivideByPOT;
+  using gemmlowp::SaturatingRoundingDoublingHighMul;
+  return RoundingDivideByPOT(
+      SaturatingRoundingDoublingHighMul(x, quantized_multiplier), -left_shift);
+}
+
+inline int32 MultiplyByQuantizedMultiplierGreaterThanOne(
+    int32 x, int32 quantized_multiplier, int left_shift) {
+  using gemmlowp::SaturatingRoundingDoublingHighMul;
+  return SaturatingRoundingDoublingHighMul(x * (1 << left_shift),
+                                           quantized_multiplier);
+}
+
+inline int32 MultiplyByQuantizedMultiplier(int32 x, int32 quantized_multiplier,
+                                           int shift) {
+  using gemmlowp::RoundingDivideByPOT;
+  using gemmlowp::SaturatingRoundingDoublingHighMul;
+  int left_shift = shift > 0 ? shift : 0;
+  int right_shift = shift > 0 ? 0 : -shift;
+  return RoundingDivideByPOT(SaturatingRoundingDoublingHighMul(
+                                 x * (1 << left_shift), quantized_multiplier),
+                             right_shift);
+}
+
+template <typename T>
+int CountLeadingZeros(T integer_input) {
+  static_assert(std::is_unsigned<T>::value,
+                "Only unsigned integer types handled.");
+#if defined(__GNUC__)
+  return integer_input ? __builtin_clz(integer_input)
+                       : std::numeric_limits<T>::digits;
+#else
+  if (integer_input == 0) {
+    return std::numeric_limits<T>::digits;
+  }
+
+  const T one_in_leading_positive = static_cast<T>(1)
+                                    << (std::numeric_limits<T>::digits - 1);
+  int leading_zeros = 0;
+  while (integer_input < one_in_leading_positive) {
+    integer_input <<= 1;
+    ++leading_zeros;
+  }
+  return leading_zeros;
+#endif
+}
+
+template <typename T>
+inline int CountLeadingSignBits(T integer_input) {
+  static_assert(std::is_signed<T>::value, "Only signed integer types handled.");
+#if defined(__GNUC__) && !defined(__clang__)
+  return integer_input ? __builtin_clrsb(integer_input)
+                       : std::numeric_limits<T>::digits;
+#else
+  using U = typename std::make_unsigned<T>::type;
+  return integer_input >= 0
+             ? CountLeadingZeros(static_cast<U>(integer_input)) - 1
+             : integer_input != std::numeric_limits<T>::min()
+                   ? CountLeadingZeros(2 * static_cast<U>(-integer_input) - 1)
+                   : 0;
+#endif
+}
+
+// TODO(b/77858996): Add these to gemmlowp.
+template <typename IntegerType>
+IntegerType SaturatingAddNonGemmlowp(IntegerType a, IntegerType b) {
+  static_assert(std::is_same<IntegerType, void>::value, "unimplemented");
+  return a;
+}
+
+template <>
+inline std::int32_t SaturatingAddNonGemmlowp(std::int32_t a, std::int32_t b) {
+  std::int64_t a64 = a;
+  std::int64_t b64 = b;
+  std::int64_t sum = a64 + b64;
+  return static_cast<std::int32_t>(std::min(
+      static_cast<std::int64_t>(std::numeric_limits<std::int32_t>::max()),
+      std::max(
+          static_cast<std::int64_t>(std::numeric_limits<std::int32_t>::min()),
+          sum)));
+}
+
+template <typename tRawType, int tIntegerBits>
+gemmlowp::FixedPoint<tRawType, tIntegerBits> SaturatingAddNonGemmlowp(
+    gemmlowp::FixedPoint<tRawType, tIntegerBits> a,
+    gemmlowp::FixedPoint<tRawType, tIntegerBits> b) {
+  return gemmlowp::FixedPoint<tRawType, tIntegerBits>::FromRaw(
+      SaturatingAddNonGemmlowp(a.raw(), b.raw()));
+}
+
+template <typename IntegerType>
+IntegerType SaturatingSub(IntegerType a, IntegerType b) {
+  static_assert(std::is_same<IntegerType, void>::value, "unimplemented");
+  return a;
+}
+
+template <>
+inline std::int16_t SaturatingSub(std::int16_t a, std::int16_t b) {
+  std::int32_t a32 = a;
+  std::int32_t b32 = b;
+  std::int32_t diff = a32 - b32;
+  return static_cast<std::int16_t>(
+      std::min(static_cast<int32_t>(32767),
+               std::max(static_cast<int32_t>(-32768), diff)));
+}
+
+template <>
+inline std::int32_t SaturatingSub(std::int32_t a, std::int32_t b) {
+  std::int64_t a64 = a;
+  std::int64_t b64 = b;
+  std::int64_t diff = a64 - b64;
+  return static_cast<std::int32_t>(std::min(
+      static_cast<std::int64_t>(std::numeric_limits<std::int32_t>::max()),
+      std::max(
+          static_cast<std::int64_t>(std::numeric_limits<std::int32_t>::min()),
+          diff)));
+}
+
+template <typename tRawType, int tIntegerBits>
+gemmlowp::FixedPoint<tRawType, tIntegerBits> SaturatingSub(
+    gemmlowp::FixedPoint<tRawType, tIntegerBits> a,
+    gemmlowp::FixedPoint<tRawType, tIntegerBits> b) {
+  return gemmlowp::FixedPoint<tRawType, tIntegerBits>::FromRaw(
+      SaturatingSub(a.raw(), b.raw()));
+}
+// End section to be moved to gemmlowp.
+
+template <typename IntegerType>
+IntegerType SaturatingRoundingMultiplyByPOTParam(IntegerType x, int exponent) {
+  if (exponent == 0) {
+    return x;
+  }
+  using ScalarIntegerType =
+      typename gemmlowp::FixedPointRawTypeTraits<IntegerType>::ScalarRawType;
+  const IntegerType min =
+      gemmlowp::Dup<IntegerType>(std::numeric_limits<ScalarIntegerType>::min());
+  const IntegerType max =
+      gemmlowp::Dup<IntegerType>(std::numeric_limits<ScalarIntegerType>::max());
+  const int ScalarIntegerTypeBits = 8 * sizeof(ScalarIntegerType);
+
+  const std::int32_t threshold =
+      ((1 << (ScalarIntegerTypeBits - 1 - exponent)) - 1);
+  const IntegerType positive_mask =
+      gemmlowp::MaskIfGreaterThan(x, gemmlowp::Dup<IntegerType>(threshold));
+  const IntegerType negative_mask =
+      gemmlowp::MaskIfLessThan(x, gemmlowp::Dup<IntegerType>(-threshold));
+
+  IntegerType result = gemmlowp::ShiftLeft(x, exponent);
+  result = gemmlowp::SelectUsingMask(positive_mask, max, result);
+  result = gemmlowp::SelectUsingMask(negative_mask, min, result);
+  return result;
+}
+
+// If we want to leave IntegerBits fixed, then multiplication
+// by a power of two has to be saturating/rounding, not exact anymore.
+template <typename tRawType, int tIntegerBits>
+gemmlowp::FixedPoint<tRawType, tIntegerBits>
+SaturatingRoundingMultiplyByPOTParam(
+    gemmlowp::FixedPoint<tRawType, tIntegerBits> a, int exponent) {
+  return gemmlowp::FixedPoint<tRawType, tIntegerBits>::FromRaw(
+      SaturatingRoundingMultiplyByPOTParam(a.raw(), exponent));
+}
+
+// Minimum output bits to accommodate log of maximum input range.  It actually
+// does not matter if one considers, say, [-64,64] or [-64,64).
+//
+// For example, run this through Octave:
+// [0:127; ...
+//  ceil(log(abs( log(2.^(0:127))+1 ))/log(2)); ...
+//  ceil(log(abs( log(2.^(0:127))+1 ))/log(2))]
+constexpr int min_log_x_output_bits(int input_bits) {
+  return input_bits > 90
+             ? 7
+             : input_bits > 44
+                   ? 6
+                   : input_bits > 21
+                         ? 5
+                         : input_bits > 10
+                               ? 4
+                               : input_bits > 4 ? 3 : input_bits > 1 ? 2 : 1;
+}
+
+// Although currently the name of this function says that it cannot handle
+// values less than 1, in practice it can handle as low as 1/x_max, where
+// x_max is the largest representable input.  In other words, the output range
+// is symmetric.
+template <int OutputIntegerBits, int InputIntegerBits>
+inline gemmlowp::FixedPoint<int32, OutputIntegerBits>
+log_x_for_x_greater_than_or_equal_to_1_impl(
+    gemmlowp::FixedPoint<int32, InputIntegerBits> input_val) {
+  // assert(__builtin_clz(0u) >= std::numeric_limits<uint32>::digits - 1);
+  // assert(__builtin_clz(0u) <= std::numeric_limits<uint32>::digits);
+  using FixedPoint0 = gemmlowp::FixedPoint<int32, 0>;
+  // The reason for accumulating the result with an extra bit of headroom is
+  // that z_pow_2_adj * log_2 might be saturated, and adding num_scaled *
+  // recip_denom will otherwise introduce an error.
+  static constexpr int kAccumIntegerBits = OutputIntegerBits + 1;
+  using FixedPointAccum = gemmlowp::FixedPoint<int32, kAccumIntegerBits>;
+
+  const FixedPoint0 log_2 = GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(
+      FixedPoint0, 1488522236, std::log(2.0));
+  const FixedPoint0 sqrt_sqrt_half = GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(
+      FixedPoint0, 1805811301, std::sqrt(std::sqrt(0.5)));
+  const FixedPoint0 sqrt_half = GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(
+      FixedPoint0, 1518500250, std::sqrt(0.5));
+  const FixedPoint0 one_quarter =
+      GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(FixedPoint0, 536870912, 1.0 / 4.0);
+
+  const FixedPoint0 alpha_n = GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(
+      FixedPoint0, 117049297, 11.0 / 240.0 * std::sqrt(std::sqrt(2.0)));
+  const FixedPoint0 alpha_d = GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(
+      FixedPoint0, 127690142, 1.0 / 20.0 * std::sqrt(std::sqrt(2.0)));
+  const FixedPoint0 alpha_i = GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(
+      FixedPoint0, 1057819769,
+      2.0 / std::sqrt(std::sqrt(2.0)) - std::sqrt(std::sqrt(2.0)));
+  const FixedPoint0 alpha_f = GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(
+      FixedPoint0, 638450708, 1.0 / 4.0 * std::sqrt(std::sqrt(2.0)));
+
+  const FixedPointAccum shifted_quarter =
+      gemmlowp::Rescale<kAccumIntegerBits>(one_quarter);
+
+  // Reinterpret the input value as Q0.31, because we will figure out the
+  // required shift "ourselves" instead of using, say, Rescale.
+  FixedPoint0 z_a = FixedPoint0::FromRaw(input_val.raw());
+  // z_a_pow_2 = input_integer_bits - z_a_headroom;
+  int z_a_headroom_plus_1 = CountLeadingZeros(static_cast<uint32>(z_a.raw()));
+  FixedPoint0 r_a_tmp =
+      SaturatingRoundingMultiplyByPOTParam(z_a, (z_a_headroom_plus_1 - 1));
+  const int32 r_a_raw =
+      SaturatingRoundingMultiplyByPOTParam((r_a_tmp * sqrt_half).raw(), 1);
+  // z_pow_2_adj = max(z_pow_2_a - 0.75, z_pow_2_b - 0.25);
+  // z_pow_2_adj = max(InputIntegerBits - z_a_headroom_plus_1 + 0.25,
+  //                   InputIntegerBits - z_b_headroom - 0.25);
+  const FixedPointAccum z_a_pow_2_adj = SaturatingAddNonGemmlowp(
+      FixedPointAccum::FromRaw(SaturatingRoundingMultiplyByPOTParam(
+          InputIntegerBits - z_a_headroom_plus_1, 31 - kAccumIntegerBits)),
+      shifted_quarter);
+
+  // z_b is treated like z_a, but premultiplying by sqrt(0.5).
+  FixedPoint0 z_b = z_a * sqrt_half;
+  int z_b_headroom = CountLeadingZeros(static_cast<uint32>(z_b.raw())) - 1;
+  const int32 r_b_raw =
+      SaturatingRoundingMultiplyByPOTParam(z_a.raw(), z_b_headroom);
+  const FixedPointAccum z_b_pow_2_adj = SaturatingSub(
+      FixedPointAccum::FromRaw(SaturatingRoundingMultiplyByPOTParam(
+          InputIntegerBits - z_b_headroom, 31 - kAccumIntegerBits)),
+      shifted_quarter);
+
+  const FixedPoint0 r = FixedPoint0::FromRaw(std::min(r_a_raw, r_b_raw));
+  const FixedPointAccum z_pow_2_adj = FixedPointAccum::FromRaw(
+      std::max(z_a_pow_2_adj.raw(), z_b_pow_2_adj.raw()));
+
+  const FixedPoint0 p = gemmlowp::RoundingHalfSum(r, sqrt_sqrt_half);
+  FixedPoint0 q = r - sqrt_sqrt_half;
+  q = q + q;
+
+  const FixedPoint0 common_sq = q * q;
+  const FixedPoint0 num = q * r + q * common_sq * alpha_n;
+  const FixedPoint0 denom_minus_one_0 =
+      p * (alpha_i + q + alpha_d * common_sq) + alpha_f * q;
+  const FixedPoint0 recip_denom =
+      one_over_one_plus_x_for_x_in_0_1(denom_minus_one_0);
+
+  const FixedPointAccum num_scaled = gemmlowp::Rescale<kAccumIntegerBits>(num);
+  return gemmlowp::Rescale<OutputIntegerBits>(z_pow_2_adj * log_2 +
+                                              num_scaled * recip_denom);
+}
+
+template <int OutputIntegerBits, int InputIntegerBits>
+inline gemmlowp::FixedPoint<int32, OutputIntegerBits>
+log_x_for_x_greater_than_or_equal_to_1(
+    gemmlowp::FixedPoint<int32, InputIntegerBits> input_val) {
+  static_assert(
+      OutputIntegerBits >= min_log_x_output_bits(InputIntegerBits),
+      "Output integer bits must be sufficent to accommodate logs of inputs.");
+  return log_x_for_x_greater_than_or_equal_to_1_impl<OutputIntegerBits,
+                                                     InputIntegerBits>(
+      input_val);
+}
+
+inline int32 GetReciprocal(int32 x, int x_integer_digits,
+                           int* num_bits_over_unit) {
+  int headroom_plus_one = CountLeadingZeros(static_cast<uint32>(x));
+  // This is the number of bits to the left of the binary point above 1.0.
+  // Consider x=1.25.  In that case shifted_scale=0.8 and
+  // no later adjustment will be needed.
+  *num_bits_over_unit = x_integer_digits - headroom_plus_one;
+  const int32 shifted_sum_minus_one =
+      static_cast<int32>((static_cast<uint32>(x) << headroom_plus_one) -
+                         (static_cast<uint32>(1) << 31));
+
+  gemmlowp::FixedPoint<int32, 0> shifted_scale =
+      gemmlowp::one_over_one_plus_x_for_x_in_0_1(
+          gemmlowp::FixedPoint<int32, 0>::FromRaw(shifted_sum_minus_one));
+  return shifted_scale.raw();
+}
+
+inline void GetInvSqrtQuantizedMultiplierExp(int32 input, int reverse_shift,
+                                             int32* output_inv_sqrt,
+                                             int* output_shift) {
+  *output_shift = 11;
+  while (input >= (1 << 29)) {
+    input /= 4;
+    ++*output_shift;
+  }
+  TFLITE_DCHECK_GT(input, 0);
+  const unsigned max_left_shift_bits =
+      CountLeadingZeros(static_cast<uint32>(input)) - 1;
+  const unsigned max_left_shift_bit_pairs = max_left_shift_bits / 2;
+  const unsigned left_shift_bit_pairs = max_left_shift_bit_pairs - 1;
+  *output_shift -= left_shift_bit_pairs;
+  input <<= 2 * left_shift_bit_pairs;
+  TFLITE_DCHECK_GE(input, (1 << 27));
+  TFLITE_DCHECK_LT(input, (1 << 29));
+  using gemmlowp::FixedPoint;
+  using gemmlowp::Rescale;
+  using gemmlowp::SaturatingRoundingMultiplyByPOT;
+  // Using 3 integer bits gives us enough room for the internal arithmetic in
+  // this Newton-Raphson iteration.
+  using F3 = FixedPoint<int32, 3>;
+  using F0 = FixedPoint<int32, 0>;
+  const F3 fixedpoint_input = F3::FromRaw(input >> 1);
+  const F3 fixedpoint_half_input =
+      SaturatingRoundingMultiplyByPOT<-1>(fixedpoint_input);
+  const F3 fixedpoint_half_three =
+      GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(F3, (1 << 28) + (1 << 27), 1.5);
+  // Newton-Raphson iteration
+  // Naive unoptimized starting guess: x = 1
+  F3 x = F3::One();
+  // Naive unoptimized number of iterations: 5
+  for (int i = 0; i < 5; i++) {
+    const F3 x3 = Rescale<3>(x * x * x);
+    x = Rescale<3>(fixedpoint_half_three * x - fixedpoint_half_input * x3);
+  }
+  const F0 fixedpoint_half_sqrt_2 =
+      GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(F0, 1518500250, std::sqrt(2.) / 2.);
+  x = x * fixedpoint_half_sqrt_2;
+  *output_inv_sqrt = x.raw();
+  if (*output_shift < 0) {
+    *output_inv_sqrt <<= -*output_shift;
+    *output_shift = 0;
+  }
+  // Convert right shift (right is positive) to left shift.
+  *output_shift *= reverse_shift;
+}
+
+// DO NOT USE THIS STRUCT FOR NEW FUNCTIONALITY BEYOND IMPLEMENTING
+// BROADCASTING.
+//
+// NdArrayDesc<N> describes the shape and memory layout of an N-dimensional
+// rectangular array of numbers.
+//
+// NdArrayDesc<N> is basically identical to Dims<N> defined in types.h.
+// However, as Dims<N> is to be deprecated, this class exists as an adaptor
+// to enable simple unoptimized implementations of element-wise broadcasting
+// operations.
+template <int N>
+struct NdArrayDesc {
+  // The "extent" of each dimension. Indices along dimension d must be in the
+  // half-open interval [0, extents[d]).
+  int extents[N];
+
+  // The number of *elements* (not bytes) between consecutive indices of each
+  // dimension.
+  int strides[N];
+};
+
+// DO NOT USE THIS FUNCTION FOR NEW FUNCTIONALITY BEYOND IMPLEMENTING
+// BROADCASTING.
+//
+// Same as Offset(), except takes as NdArrayDesc<N> instead of Dims<N>.
+inline int SubscriptToIndex(const NdArrayDesc<4>& desc, int i0, int i1, int i2,
+                            int i3) {
+  TFLITE_DCHECK(i0 >= 0 && i0 < desc.extents[0]);
+  TFLITE_DCHECK(i1 >= 0 && i1 < desc.extents[1]);
+  TFLITE_DCHECK(i2 >= 0 && i2 < desc.extents[2]);
+  TFLITE_DCHECK(i3 >= 0 && i3 < desc.extents[3]);
+  return i0 * desc.strides[0] + i1 * desc.strides[1] + i2 * desc.strides[2] +
+         i3 * desc.strides[3];
+}
+
+// Given the dimensions of the operands for an element-wise binary broadcast,
+// adjusts them so that they can be directly iterated over with simple loops.
+// Returns the adjusted dims as instances of NdArrayDesc in 'desc0_out' and
+// 'desc1_out'. 'desc0_out' and 'desc1_out' cannot be nullptr.
+//
+// This function assumes that the two input shapes are compatible up to
+// broadcasting and the shorter one has already been prepended with 1s to be the
+// same length. E.g., if shape0 is (1, 16, 16, 64) and shape1 is (1, 64),
+// shape1 must already have been prepended to be (1, 1, 1, 64). Recall that
+// Dims<N> refer to shapes in reverse order. In this case, input0_dims will be
+// (64, 16, 16, 1) and input1_dims will be (64, 1, 1, 1).
+//
+// When two shapes are compatible up to broadcasting, for each dimension d,
+// the input extents are either equal, or one of them is 1.
+//
+// This function performs the following for each dimension d:
+// - If the extents are equal, then do nothing since the loop that walks over
+//   both of the input arrays is correct.
+// - Otherwise, one (and only one) of the extents must be 1. Say extent0 is 1
+//   and extent1 is e1. Then set extent0 to e1 and stride0 *to 0*. This allows
+//   array0 to be referenced *at any index* in dimension d and still access the
+//   same slice.
+template <int N>
+inline void NdArrayDescsForElementwiseBroadcast(const Dims<N>& input0_dims,
+                                                const Dims<N>& input1_dims,
+                                                NdArrayDesc<N>* desc0_out,
+                                                NdArrayDesc<N>* desc1_out) {
+  TFLITE_DCHECK(desc0_out != nullptr);
+  TFLITE_DCHECK(desc1_out != nullptr);
+
+  // Copy dims to desc.
+  for (int i = 0; i < N; ++i) {
+    desc0_out->extents[i] = input0_dims.sizes[i];
+    desc0_out->strides[i] = input0_dims.strides[i];
+    desc1_out->extents[i] = input1_dims.sizes[i];
+    desc1_out->strides[i] = input1_dims.strides[i];
+  }
+
+  // Walk over each dimension. If the extents are equal do nothing.
+  // Otherwise, set the desc with extent 1 to have extent equal to the other and
+  // stride 0.
+  for (int i = 0; i < N; ++i) {
+    const int extent0 = ArraySize(input0_dims, i);
+    const int extent1 = ArraySize(input1_dims, i);
+    if (extent0 != extent1) {
+      if (extent0 == 1) {
+        desc0_out->strides[i] = 0;
+        desc0_out->extents[i] = extent1;
+      } else {
+        TFLITE_DCHECK_EQ(extent1, 1);
+        desc1_out->strides[i] = 0;
+        desc1_out->extents[i] = extent0;
+      }
+    }
+  }
+}
+
+template <int N>
+inline void NdArrayDescsForElementwiseBroadcast(
+    const RuntimeShape& input0_shape, const RuntimeShape& input1_shape,
+    NdArrayDesc<N>* desc0_out, NdArrayDesc<N>* desc1_out) {
+  TFLITE_DCHECK(desc0_out != nullptr);
+  TFLITE_DCHECK(desc1_out != nullptr);
+
+  auto extended_input0_shape = RuntimeShape::ExtendedShape(N, input0_shape);
+  auto extended_input1_shape = RuntimeShape::ExtendedShape(N, input1_shape);
+
+  // Copy dims to desc, calculating strides.
+  int desc0_stride = 1;
+  int desc1_stride = 1;
+  for (int i = N - 1; i >= 0; --i) {
+    desc0_out->extents[i] = extended_input0_shape.Dims(i);
+    desc0_out->strides[i] = desc0_stride;
+    desc0_stride *= extended_input0_shape.Dims(i);
+    desc1_out->extents[i] = extended_input1_shape.Dims(i);
+    desc1_out->strides[i] = desc1_stride;
+    desc1_stride *= extended_input1_shape.Dims(i);
+  }
+
+  // Walk over each dimension. If the extents are equal do nothing.
+  // Otherwise, set the desc with extent 1 to have extent equal to the other and
+  // stride 0.
+  for (int i = 0; i < N; ++i) {
+    const int extent0 = extended_input0_shape.Dims(i);
+    const int extent1 = extended_input1_shape.Dims(i);
+    if (extent0 != extent1) {
+      if (extent0 == 1) {
+        desc0_out->strides[i] = 0;
+        desc0_out->extents[i] = extent1;
+      } else {
+        TFLITE_DCHECK_EQ(extent1, 1);
+        desc1_out->strides[i] = 0;
+        desc1_out->extents[i] = extent0;
+      }
+    }
+  }
+}
+
+// Copied from gemmlowp::RoundDown when we dropped direct dependency on
+// gemmlowp.
+//
+// Returns the runtime argument rounded down to the nearest multiple of
+// the fixed Modulus.
+template <unsigned Modulus, typename Integer>
+Integer RoundDown(Integer i) {
+  return i - (i % Modulus);
+}
+
+// Copied from gemmlowp::RoundUp when we dropped direct dependency on
+// gemmlowp.
+//
+// Returns the runtime argument rounded up to the nearest multiple of
+// the fixed Modulus.
+template <unsigned Modulus, typename Integer>
+Integer RoundUp(Integer i) {
+  return RoundDown<Modulus>(i + Modulus - 1);
+}
+
+// Copied from gemmlowp::CeilQuotient when we dropped direct dependency on
+// gemmlowp.
+//
+// Returns the quotient a / b rounded up ('ceil') to the nearest integer.
+template <typename Integer>
+Integer CeilQuotient(Integer a, Integer b) {
+  return (a + b - 1) / b;
+}
+
+// This function is a copy of gemmlowp::HowManyThreads, copied when we dropped
+// the direct dependency of internal/optimized/ on gemmlowp.
+//
+// It computes a reasonable number of threads to use for a GEMM of shape
+// (rows, cols, depth).
+//
+// TODO(b/131910176): get rid of this function by switching each call site
+// to its own more sensible logic for its own workload.
+template <int KernelRows>
+inline int LegacyHowManyThreads(int max_num_threads, int rows, int cols,
+                                int depth) {
+  // Early-exit in the default case where multi-threading is disabled.
+  if (max_num_threads == 1) {
+    return 1;
+  }
+
+  // Ensure that each thread has KernelRows rows to process, if at all possible.
+  int thread_count = std::min(max_num_threads, rows / KernelRows);
+
+  // Limit the number of threads according to the overall size of the problem.
+  if (thread_count > 1) {
+    // Empirically determined value.
+    static constexpr std::uint64_t min_cubic_size_per_thread = 64 * 1024;
+
+    // We can only multiply two out of three sizes without risking overflow
+    const std::uint64_t cubic_size =
+        std::uint64_t(rows) * std::uint64_t(cols) * std::uint64_t(depth);
+
+    thread_count = std::min(
+        thread_count, static_cast<int>(cubic_size / min_cubic_size_per_thread));
+  }
+
+  if (thread_count < 1) {
+    thread_count = 1;
+  }
+
+  assert(thread_count > 0 && thread_count <= max_num_threads);
+  return thread_count;
+}
+
+template <typename T>
+void optimized_ops_preload_l1_stream(const T* ptr) {
+#ifdef __GNUC__
+  // builtin offered by GCC-compatible compilers including clang
+  __builtin_prefetch(ptr, /* 0 means read */ 0, /* 0 means no locality */ 0);
+#else
+  (void)ptr;
+#endif
+}
+
+template <typename T>
+void optimized_ops_preload_l1_keep(const T* ptr) {
+#ifdef __GNUC__
+  // builtin offered by GCC-compatible compilers including clang
+  __builtin_prefetch(ptr, /* 0 means read */ 0, /* 3 means high locality */ 3);
+#else
+  (void)ptr;
+#endif
+}
+
+template <typename T>
+void optimized_ops_prefetch_write_l1_keep(const T* ptr) {
+#ifdef __GNUC__
+  // builtin offered by GCC-compatible compilers including clang
+  __builtin_prefetch(ptr, /* 1 means write */ 1, /* 3 means high locality */ 3);
+#else
+  (void)ptr;
+#endif
+}
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_COMMON_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/compatibility.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/compatibility.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,110 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_COMPATIBILITY_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_COMPATIBILITY_H_
+
+#include <cstdint>
+
+#include "tensorflow/lite/kernels/op_macros.h"
+
+#ifndef TFLITE_DCHECK
+#define TFLITE_DCHECK(condition) (condition) ? (void)0 : TFLITE_ASSERT_FALSE
+#endif
+
+#ifndef TFLITE_DCHECK_EQ
+#define TFLITE_DCHECK_EQ(x, y) ((x) == (y)) ? (void)0 : TFLITE_ASSERT_FALSE
+#endif
+
+#ifndef TFLITE_DCHECK_NE
+#define TFLITE_DCHECK_NE(x, y) ((x) != (y)) ? (void)0 : TFLITE_ASSERT_FALSE
+#endif
+
+#ifndef TFLITE_DCHECK_GE
+#define TFLITE_DCHECK_GE(x, y) ((x) >= (y)) ? (void)0 : TFLITE_ASSERT_FALSE
+#endif
+
+#ifndef TFLITE_DCHECK_GT
+#define TFLITE_DCHECK_GT(x, y) ((x) > (y)) ? (void)0 : TFLITE_ASSERT_FALSE
+#endif
+
+#ifndef TFLITE_DCHECK_LE
+#define TFLITE_DCHECK_LE(x, y) ((x) <= (y)) ? (void)0 : TFLITE_ASSERT_FALSE
+#endif
+
+#ifndef TFLITE_DCHECK_LT
+#define TFLITE_DCHECK_LT(x, y) ((x) < (y)) ? (void)0 : TFLITE_ASSERT_FALSE
+#endif
+
+// TODO(ahentz): Clean up: We should stick to the DCHECK versions.
+#ifndef TFLITE_CHECK
+#define TFLITE_CHECK(condition) (condition) ? (void)0 : TFLITE_ABORT
+#endif
+
+#ifndef TFLITE_CHECK_EQ
+#define TFLITE_CHECK_EQ(x, y) ((x) == (y)) ? (void)0 : TFLITE_ABORT
+#endif
+
+#ifndef TFLITE_CHECK_NE
+#define TFLITE_CHECK_NE(x, y) ((x) != (y)) ? (void)0 : TFLITE_ABORT
+#endif
+
+#ifndef TFLITE_CHECK_GE
+#define TFLITE_CHECK_GE(x, y) ((x) >= (y)) ? (void)0 : TFLITE_ABORT
+#endif
+
+#ifndef TFLITE_CHECK_GT
+#define TFLITE_CHECK_GT(x, y) ((x) > (y)) ? (void)0 : TFLITE_ABORT
+#endif
+
+#ifndef TFLITE_CHECK_LE
+#define TFLITE_CHECK_LE(x, y) ((x) <= (y)) ? (void)0 : TFLITE_ABORT
+#endif
+
+#ifndef TFLITE_CHECK_LT
+#define TFLITE_CHECK_LT(x, y) ((x) < (y)) ? (void)0 : TFLITE_ABORT
+#endif
+
+// TODO(ahentz): Clean up.
+using int8 = std::int8_t;
+using uint8 = std::uint8_t;
+using int16 = std::int16_t;
+using uint16 = std::uint16_t;
+using int32 = std::int32_t;
+using uint32 = std::uint32_t;
+
+// TFLITE_DEPRECATED()
+//
+// Duplicated from absl/base/macros.h to avoid pulling in that library.
+// Marks a deprecated class, struct, enum, function, method and variable
+// declarations. The macro argument is used as a custom diagnostic message (e.g.
+// suggestion of a better alternative).
+//
+// Example:
+//
+//   class TFLITE_DEPRECATED("Use Bar instead") Foo {...};
+//   TFLITE_DEPRECATED("Use Baz instead") void Bar() {...}
+//
+// Every usage of a deprecated entity will trigger a warning when compiled with
+// clang's `-Wdeprecated-declarations` option. This option is turned off by
+// default, but the warnings will be reported by clang-tidy.
+#if defined(__clang__) && __cplusplus >= 201103L
+#define TFLITE_DEPRECATED(message) __attribute__((deprecated(message)))
+#endif
+
+#ifndef TFLITE_DEPRECATED
+#define TFLITE_DEPRECATED(message)
+#endif
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_COMPATIBILITY_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/optimized/neon_check.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/optimized/neon_check.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,46 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_OPTIMIZED_NEON_CHECK_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_OPTIMIZED_NEON_CHECK_H_
+
+#if defined(__ARM_NEON__) || defined(__ARM_NEON)
+#define USE_NEON
+#include <arm_neon.h>
+#endif
+
+#if defined __GNUC__ && defined __SSE4_1__ && !defined TF_LITE_DISABLE_X86_NEON
+#define USE_NEON
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wdeprecated-declarations"
+#pragma GCC diagnostic ignored "-Wattributes"
+#pragma GCC diagnostic ignored "-Wnarrowing"
+#pragma GCC diagnostic ignored "-Wsequence-point"
+#include "NEON_2_SSE.h"
+#pragma GCC diagnostic pop
+#endif
+
+// NEON_OR_PORTABLE(SomeFunc, args) calls NeonSomeFunc(args) if USE_NEON is
+// defined, PortableSomeFunc(args) otherwise.
+#ifdef USE_NEON
+// Always use Neon code
+#define NEON_OR_PORTABLE(funcname, ...) Neon##funcname(__VA_ARGS__)
+
+#else
+// No NEON available: Use Portable code
+#define NEON_OR_PORTABLE(funcname, ...) Portable##funcname(__VA_ARGS__)
+
+#endif  // defined(USE_NEON)
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_OPTIMIZED_NEON_CHECK_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/quantization_util.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/quantization_util.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,394 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include <algorithm>
+#include <cmath>
+#include <limits>
+
+#include "tensorflow/lite/kernels/internal/compatibility.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/round.h"
+
+namespace tflite {
+
+namespace {
+// These constants are used to manipulate the binary representation of doubles.
+// Double-precision binary64 floating point format is:
+// Bit |  63  |  62-52   |   51-0   |
+//     | Sign | Exponent | Fraction |
+// To avoid 64-bit integers as much as possible, I break this into high and
+// low 32-bit chunks. High is:
+// Bit |  31  |  30-20   |      19-0     |
+//     | Sign | Exponent | High Fraction |
+// Low is:
+// Bit |     31-0     |
+//     | Low Fraction |
+// We then access the components through logical bit-wise operations to
+// extract the parts needed, with the positions and masks derived from the
+// layout shown above.
+constexpr uint64_t kSignMask = 0x8000000000000000LL;
+constexpr uint64_t kExponentMask = 0x7ff0000000000000LL;
+constexpr int32_t kExponentShift = 52;
+constexpr int32_t kExponentBias = 1023;
+constexpr uint32_t kExponentIsBadNum = 0x7ff;
+constexpr uint64_t kFractionMask = 0x000fffffffc00000LL;
+constexpr uint32_t kFractionShift = 22;
+constexpr uint32_t kFractionRoundingMask = 0x003fffff;
+constexpr uint32_t kFractionRoundingThreshold = 0x00200000;
+}  // namespace
+
+void QuantizeMultiplier(double double_multiplier, int32_t* quantized_multiplier,
+                        int* shift) {
+  if (double_multiplier == 0.) {
+    *quantized_multiplier = 0;
+    *shift = 0;
+    return;
+  }
+#ifdef TFLITE_EMULATE_FLOAT
+  // If we're trying to avoid the use of floating-point instructions (for
+  // example on microcontrollers) then use an alternative implementation
+  // that only requires integer and bitwise operations. To enable this, you
+  // need to set the define during the build process for your platform.
+  int64_t q_fixed = IntegerFrExp(double_multiplier, shift);
+#else   // TFLITE_EMULATE_FLOAT
+  const double q = std::frexp(double_multiplier, shift);
+  auto q_fixed = static_cast<int64_t>(TfLiteRound(q * (1ll << 31)));
+#endif  // TFLITE_EMULATE_FLOAT
+  TFLITE_CHECK(q_fixed <= (1ll << 31));
+  if (q_fixed == (1ll << 31)) {
+    q_fixed /= 2;
+    ++*shift;
+  }
+  TFLITE_CHECK_LE(q_fixed, std::numeric_limits<int32_t>::max());
+  // A shift amount smaller than -31 would cause all bits to be shifted out
+  // and thus all results would be zero. We implement that instead with
+  // q_fixed==0, so as to avoid hitting issues with right-shift
+  // operations with shift amounts greater than 31. Note that this happens
+  // roughly when abs(double_multiplier) < 2^-31 and the present handling means
+  // that we're effectively flushing tiny double_multiplier's to zero.
+  // We could conceivably handle values in the range (roughly) [32, 63]
+  // as 'denormals' i.e. (shift==0, q_fixed < 2^30). In that point of view
+  // the present handling is just doing 'flush denormals to zero'. We could
+  // reconsider and actually generate nonzero denormals if a need arises.
+  if (*shift < -31) {
+    *shift = 0;
+    q_fixed = 0;
+  }
+  *quantized_multiplier = static_cast<int32_t>(q_fixed);
+}
+
+void QuantizeMultiplierGreaterThanOne(double double_multiplier,
+                                      int32_t* quantized_multiplier,
+                                      int* left_shift) {
+  TFLITE_CHECK_GT(double_multiplier, 1.);
+  QuantizeMultiplier(double_multiplier, quantized_multiplier, left_shift);
+  TFLITE_CHECK_GE(*left_shift, 0);
+}
+
+void QuantizeMultiplierSmallerThanOneExp(double double_multiplier,
+                                         int32_t* quantized_multiplier,
+                                         int* left_shift) {
+  TFLITE_CHECK_LT(double_multiplier, 1.);
+  TFLITE_CHECK_GT(double_multiplier, 0.);
+  int shift;
+  QuantizeMultiplier(double_multiplier, quantized_multiplier, &shift);
+  TFLITE_CHECK_LE(shift, 0);
+  *left_shift = shift;
+}
+
+int64_t IntegerFrExp(double input, int* shift) {
+  // Make sure our assumptions about the double layout hold.
+  TFLITE_CHECK_EQ(8, sizeof(double));
+
+  // We want to access the bits of the input double value directly, which is
+  // tricky to do safely, so use a union to handle the casting.
+  union {
+    double double_value;
+    uint64_t double_as_uint;
+  } cast_union;
+  cast_union.double_value = input;
+  const uint64_t u = cast_union.double_as_uint;
+
+  // If the bitfield is all zeros apart from the sign bit, this is a normalized
+  // zero value, so return standard values for this special case.
+  if ((u & ~kSignMask) == 0) {
+    *shift = 0;
+    return 0;
+  }
+
+  // Deal with NaNs and Infs, which are always indicated with a fixed pattern in
+  // the exponent, and distinguished by whether the fractions are zero or
+  // non-zero.
+  const uint32_t exponent_part = ((u & kExponentMask) >> kExponentShift);
+  if (exponent_part == kExponentIsBadNum) {
+    *shift = std::numeric_limits<int>::max();
+    if (u & kFractionMask) {
+      // NaN, so just return zero (with the exponent set to INT_MAX).
+      return 0;
+    } else {
+      // Infinity, so return +/- INT_MAX.
+      if (u & kSignMask) {
+        return std::numeric_limits<int64_t>::min();
+      } else {
+        return std::numeric_limits<int64_t>::max();
+      }
+    }
+  }
+
+  // The shift is fairly easy to extract from the high bits of the double value,
+  // just by masking it out and applying a bias. The std::frexp() implementation
+  // always returns values between 0.5 and 1.0 though, whereas the exponent
+  // assumes 1.0 to 2.0 is the standard range, so I add on one to match that
+  // interface.
+  *shift = (exponent_part - kExponentBias) + 1;
+
+  // There's an implicit high bit in the double format definition, so make sure
+  // we include that at the top, and then reconstruct the rest of the fractional
+  // value from the remaining fragments.
+  int64_t fraction = 0x40000000 + ((u & kFractionMask) >> kFractionShift);
+
+  // We're cutting off some bits at the bottom, so to exactly match the standard
+  // frexp implementation here we'll apply rounding by adding one to the least
+  // significant bit of the result if the discarded portion is over half of the
+  // maximum.
+  if ((u & kFractionRoundingMask) > kFractionRoundingThreshold) {
+    fraction += 1;
+  }
+  // Negate the fraction if the sign bit was set.
+  if (u & kSignMask) {
+    fraction *= -1;
+  }
+
+  return fraction;
+}
+
+double DoubleFromFractionAndShift(int64_t fraction, int shift) {
+  union {
+    double double_value;
+    uint64_t double_as_uint;
+  } result;
+
+  // Detect NaNs and infinities.
+  if (shift == std::numeric_limits<int>::max()) {
+    if (fraction == 0) {
+      return NAN;
+    } else if (fraction > 0) {
+      return INFINITY;
+    } else {
+      return -INFINITY;
+    }
+  }
+
+  // Return a normalized zero for a zero fraction.
+  if (fraction == 0) {
+    result.double_as_uint = 0;
+    return result.double_value;
+  }
+
+  bool is_negative = (fraction < 0);
+  int64_t encoded_fraction = is_negative ? -fraction : fraction;
+  int64_t encoded_shift = (shift - 1);
+  while (encoded_fraction < 0x40000000) {
+    encoded_fraction *= 2;
+    encoded_shift -= 1;
+  }
+  while (encoded_fraction > 0x80000000) {
+    encoded_fraction /= 2;
+    encoded_shift += 1;
+  }
+  encoded_fraction -= 0x40000000;
+  if (encoded_shift < -1022) {
+    encoded_shift = -1023;
+  } else if (encoded_shift > 1022) {
+    encoded_shift = 1023;
+  }
+  encoded_shift += kExponentBias;
+  uint64_t encoded_sign = is_negative ? kSignMask : 0;
+  result.double_as_uint = encoded_sign | (encoded_shift << kExponentShift) |
+                          (encoded_fraction << kFractionShift);
+  return result.double_value;
+}
+
+double IntegerDoubleMultiply(double a, double b) {
+  int a_shift;
+  const int64_t a_fraction = IntegerFrExp(a, &a_shift);
+  int b_shift;
+  const int64_t b_fraction = IntegerFrExp(b, &b_shift);
+  // Detect NaNs and infinities.
+  if (a_shift == std::numeric_limits<int>::max() ||
+      (b_shift == std::numeric_limits<int>::max())) {
+    return NAN;
+  }
+  const int result_shift = a_shift + b_shift + 1;
+  const int64_t result_fraction = (a_fraction * b_fraction) >> 32;
+  return DoubleFromFractionAndShift(result_fraction, result_shift);
+}
+
+int IntegerDoubleCompare(double a, double b) {
+  int a_shift;
+  const int64_t a_fraction = IntegerFrExp(a, &a_shift);
+  int b_shift;
+  const int64_t b_fraction = IntegerFrExp(b, &b_shift);
+
+  // Detect NaNs and infinities.
+  if (a_shift == std::numeric_limits<int>::max() ||
+      (b_shift == std::numeric_limits<int>::max())) {
+    return 1;
+  }
+
+  if ((a_fraction == 0) && (b_fraction < 0)) {
+    return 1;
+  } else if ((a_fraction < 0) && (b_fraction == 0)) {
+    return -1;
+  } else if (a_shift < b_shift) {
+    return -1;
+  } else if (a_shift > b_shift) {
+    return 1;
+  } else if (a_fraction < b_fraction) {
+    return -1;
+  } else if (a_fraction > b_fraction) {
+    return 1;
+  } else {
+    return 0;
+  }
+}
+
+void PreprocessSoftmaxScaling(double beta, double input_scale,
+                              int input_integer_bits,
+                              int32_t* quantized_multiplier, int* left_shift) {
+  // If the overall multiplier (input and beta) is large, then exp() of an
+  // input difference of 1 scaled by this will be large.  In other words, we
+  // can cap the multiplier and know that, when it is used, the output will be
+  // (round to) zero wherever the input is not at the maximum value.
+
+  // If the overall scale is less than one, and input_integer_bits=0, then the
+  // result is double equivalent of Q0.31 (actually with more precision). Thus
+  // this generates a Q(input_integer_bits).(31-input_integer_bits)
+  // representation.
+#ifdef TFLITE_EMULATE_FLOAT
+  const double input_beta = IntegerDoubleMultiply(beta, input_scale);
+  int shift;
+  int64_t fraction = IntegerFrExp(input_beta, &shift);
+  shift += (31 - input_integer_bits);
+  double input_beta_real_multiplier =
+      DoubleFromFractionAndShift(fraction, shift);
+  if (IntegerDoubleCompare(input_beta_real_multiplier, (1ll << 31) - 1.0) > 0) {
+    input_beta_real_multiplier = (1ll << 31) - 1.0;
+  }
+#else   // TFLITE_EMULATE_FLOAT
+  const double input_beta_real_multiplier = std::min(
+      beta * input_scale * (1 << (31 - input_integer_bits)), (1ll << 31) - 1.0);
+#endif  // TFLITE_EMULATE_FLOAT
+
+  QuantizeMultiplierGreaterThanOne(input_beta_real_multiplier,
+                                   quantized_multiplier, left_shift);
+}
+
+void PreprocessLogSoftmaxScalingExp(double beta, double input_scale,
+                                    int input_integer_bits,
+                                    int32_t* quantized_multiplier,
+                                    int* left_shift,
+                                    int32_t* reverse_scaling_divisor,
+                                    int* reverse_scaling_left_shift) {
+  PreprocessSoftmaxScaling(beta, input_scale, input_integer_bits,
+                           quantized_multiplier, left_shift);
+
+  // Also calculate what amounts to the inverse scaling factor for the input.
+  const double real_reverse_scaling_divisor =
+      (1 << (31 - *left_shift)) / static_cast<double>(*quantized_multiplier);
+  tflite::QuantizeMultiplierSmallerThanOneExp(real_reverse_scaling_divisor,
+                                              reverse_scaling_divisor,
+                                              reverse_scaling_left_shift);
+}
+
+int CalculateInputRadius(int input_integer_bits, int input_left_shift,
+                         int total_signed_bits) {
+#ifdef TFLITE_EMULATE_FLOAT
+  int64_t result = (1 << input_integer_bits) - 1;
+  result <<= (total_signed_bits - input_integer_bits);
+  result >>= input_left_shift;
+  return result;
+#else   // TFLITE_EMULATE_FLOAT
+  const double max_input_rescaled =
+      1.0 * ((1 << input_integer_bits) - 1) *
+      (1ll << (total_signed_bits - input_integer_bits)) /
+      (1ll << input_left_shift);
+  // Tighten bound using floor.  Suppose that we could use the exact value.
+  // After scaling the difference, the result would be at the maximum.  Thus we
+  // must ensure that our value has lower magnitude.
+  return static_cast<int>(std::floor(max_input_rescaled));
+#endif  // TFLITE_EMULATE_FLOAT
+}
+
+void NudgeQuantizationRange(const float min, const float max,
+                            const int quant_min, const int quant_max,
+                            float* nudged_min, float* nudged_max,
+                            float* nudged_scale) {
+  // This code originates from tensorflow/core/kernels/fake_quant_ops_functor.h.
+  const float quant_min_float = static_cast<float>(quant_min);
+  const float quant_max_float = static_cast<float>(quant_max);
+  *nudged_scale = (max - min) / (quant_max_float - quant_min_float);
+  const float zero_point_from_min = quant_min_float - min / *nudged_scale;
+  uint16 nudged_zero_point;
+  if (zero_point_from_min < quant_min_float) {
+    nudged_zero_point = static_cast<uint16>(quant_min);
+  } else if (zero_point_from_min > quant_max_float) {
+    nudged_zero_point = static_cast<uint16>(quant_max);
+  } else {
+    nudged_zero_point = static_cast<uint16>(TfLiteRound(zero_point_from_min));
+  }
+  *nudged_min = (quant_min_float - nudged_zero_point) * (*nudged_scale);
+  *nudged_max = (quant_max_float - nudged_zero_point) * (*nudged_scale);
+}
+
+void FakeQuantizeArray(const float nudged_scale, const float nudged_min,
+                       const float nudged_max, const float* input_data,
+                       float* output_data, const float size) {
+  // This code originates from tensorflow/core/kernels/fake_quant_ops_functor.h.
+  const float inv_nudged_scale = 1.0f / nudged_scale;
+
+  for (int i = 0; i < size; i++) {
+    const float src_val = input_data[i];
+    const float clamped = std::min(nudged_max, std::max(nudged_min, src_val));
+    const float clamped_shifted = clamped - nudged_min;
+    const float dst_val =
+        TfLiteRound(clamped_shifted * inv_nudged_scale) * nudged_scale +
+        nudged_min;
+    output_data[i] = dst_val;
+  }
+}
+
+bool CheckedLog2(const float x, int* log2_result) {
+  // Using TfLiteRound instead of std::round and std::log instead of
+  // std::log2 to work around these fuctions being missing in a toolchain
+  // used in some TensorFlow tests as of May 2018.
+  const float x_log2 = std::log(x) * (1.0f / std::log(2.0f));
+  const float x_log2_rounded = TfLiteRound(x_log2);
+  const float x_log2_fracpart = x_log2 - x_log2_rounded;
+
+  *log2_result = static_cast<int>(x_log2_rounded);
+  return std::abs(x_log2_fracpart) < 1e-3;
+}
+
+void QuantizeMultiplierArray(const double* effective_scales, size_t size,
+                             int32_t* effective_scale_significand,
+                             int* effective_shift) {
+  for (size_t i = 0; i < size; ++i) {
+    QuantizeMultiplier(effective_scales[i], &effective_scale_significand[i],
+                       &effective_shift[i]);
+  }
+}
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/quantization_util.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/quantization_util.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,292 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_QUANTIZATION_UTIL_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_QUANTIZATION_UTIL_H_
+
+#include <cmath>
+#include <cstdint>
+#include <limits>
+
+#include "tensorflow/lite/kernels/internal/compatibility.h"
+#include "tensorflow/lite/kernels/internal/round.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+// Given the min and max values of a float array, return
+// reasonable quantization parameters to use for this array.
+template <typename T>
+QuantizationParams ChooseQuantizationParams(double rmin, double rmax,
+                                            bool narrow_range) {
+  const T qmin = std::numeric_limits<T>::min() + (narrow_range ? 1 : 0);
+  const T qmax = std::numeric_limits<T>::max();
+  const double qmin_double = qmin;
+  const double qmax_double = qmax;
+  // 0 should always be a representable value. Let's assume that the initial
+  // min,max range contains 0.
+  TFLITE_CHECK_LE(rmin, 0.);
+  TFLITE_CHECK_GE(rmax, 0.);
+  if (rmin == rmax) {
+    // Special case where the min,max range is a point. Should be {0}.
+    TFLITE_CHECK_EQ(rmin, 0.);
+    TFLITE_CHECK_EQ(rmax, 0.);
+    QuantizationParams quantization_params;
+    quantization_params.zero_point = 0;
+    quantization_params.scale = 0.;
+    return quantization_params;
+  }
+
+  // General case.
+  //
+  // First determine the scale.
+  const double scale = (rmax - rmin) / (qmax_double - qmin_double);
+
+  // Zero-point computation.
+  // First the initial floating-point computation. The zero-point can be
+  // determined from solving an affine equation for any known pair
+  // (real value, corresponding quantized value).
+  // We know two such pairs: (rmin, qmin) and (rmax, qmax).
+  // The arithmetic error on the zero point computed from either pair
+  // will be roughly machine_epsilon * (sum of absolute values of terms)
+  // so we want to use the variant that adds the smaller terms.
+  const double zero_point_from_min = qmin_double - rmin / scale;
+  const double zero_point_from_max = qmax_double - rmax / scale;
+  const double zero_point_from_min_error =
+      std::abs(qmin_double) + std::abs(rmin / scale);
+  const double zero_point_from_max_error =
+      std::abs(qmax_double) + std::abs(rmax / scale);
+
+  const double zero_point_double =
+      zero_point_from_min_error < zero_point_from_max_error
+          ? zero_point_from_min
+          : zero_point_from_max;
+
+  // Now we need to nudge the zero point to be an integer
+  // (our zero points are integer, and this is motivated by the requirement
+  // to be able to represent the real value "0" exactly as a quantized value,
+  // which is required in multiple places, for example in Im2col with SAME
+  // padding).
+  T nudged_zero_point = 0;
+  if (zero_point_double < qmin_double) {
+    nudged_zero_point = qmin;
+  } else if (zero_point_double > qmax_double) {
+    nudged_zero_point = qmax;
+  } else {
+    nudged_zero_point = static_cast<T>(round(zero_point_double));
+  }
+  // The zero point should always be in the range of quantized value,
+  // [qmin, qmax].
+  TFLITE_CHECK_GE(nudged_zero_point, qmin);
+  TFLITE_CHECK_LE(nudged_zero_point, qmax);
+
+  // Finally, store the result nudged quantization params.
+  QuantizationParams quantization_params;
+  quantization_params.zero_point = nudged_zero_point;
+  quantization_params.scale = scale;
+  return quantization_params;
+}
+
+template <typename T>
+QuantizationParams ChooseQuantizationParams(double rmin, double rmax) {
+  return ChooseQuantizationParams<T>(rmin, rmax, false);
+}
+
+// Converts a floating-point number to an integer. For all inputs x where
+// static_cast<IntOut>(x) is legal according to the C++ standard, the result
+// is identical to that cast (i.e. the result is x with its fractional part
+// truncated whenever that is representable as IntOut).
+//
+// static_cast would cause undefined behavior for the following cases, which
+// have well-defined behavior for this function:
+//
+//  1. If x is NaN, the result is zero.
+//
+//  2. If the truncated form of x is above the representable range of IntOut,
+//     the result is std::numeric_limits<IntOut>::max().
+//
+//  3. If the truncated form of x is below the representable range of IntOut,
+//     the result is std::numeric_limits<IntOut>::min().
+//
+// Note that cases #2 and #3 cover infinities as well as finite numbers.
+//
+// The range of FloatIn must include the range of IntOut, otherwise
+// the results are undefined.
+// TODO(sfeuz): Replace by absl::SafeCast once available.
+template <class IntOut, class FloatIn>
+IntOut SafeCast(FloatIn x) {
+  static_assert(!std::numeric_limits<FloatIn>::is_integer,
+                "FloatIn is integer");
+  static_assert(std::numeric_limits<IntOut>::is_integer,
+                "IntOut is not integer");
+  static_assert(std::numeric_limits<IntOut>::radix == 2, "IntOut is base 2");
+
+  // Special case NaN, for which the logic below doesn't work.
+  if (std::isnan(x)) {
+    return 0;
+  }
+
+  // Negative values all clip to zero for unsigned results.
+  if (!std::numeric_limits<IntOut>::is_signed && x < 0) {
+    return 0;
+  }
+
+  // Handle infinities.
+  if (std::isinf(x)) {
+    return x < 0 ? std::numeric_limits<IntOut>::min()
+                 : std::numeric_limits<IntOut>::max();
+  }
+
+  // Set exp such that x == f * 2^exp for some f with |f| in [0.5, 1.0),
+  // unless x is zero in which case exp == 0. Note that this implies that the
+  // magnitude of x is strictly less than 2^exp.
+  int exp = 0;
+  std::frexp(x, &exp);
+
+  // Let N be the number of non-sign bits in the representation of IntOut. If
+  // the magnitude of x is strictly less than 2^N, the truncated version of x
+  // is representable as IntOut. The only representable integer for which this
+  // is not the case is kMin for signed types (i.e. -2^N), but that is covered
+  // by the fall-through below.
+  if (exp <= std::numeric_limits<IntOut>::digits) {
+    return x;
+  }
+
+  // Handle numbers with magnitude >= 2^N.
+  return x < 0 ? std::numeric_limits<IntOut>::min()
+               : std::numeric_limits<IntOut>::max();
+}
+
+// Decompose a double multiplier into a Q0.31 int32 representation of its
+// significand, and shift representation of NEGATIVE its exponent ---
+// this is intended as a RIGHT-shift.
+//
+// Restricted to the case where the multiplier < 1 (and non-negative).
+void QuantizeMultiplierSmallerThanOneExp(double double_multiplier,
+                                         int32_t* quantized_multiplier,
+                                         int* left_shift);
+
+// Decompose a double multiplier into a Q0.31 int32 representation of its
+// significand, and shift representation of its exponent.
+//
+// Restricted to the case where the multiplier > 1.
+void QuantizeMultiplierGreaterThanOne(double double_multiplier,
+                                      int32_t* quantized_multiplier,
+                                      int* left_shift);
+
+// Decompose a double multiplier into a Q0.31 int32 representation of its
+// significand, and shift representation of its exponent.
+//
+// Handles an arbitrary positive multiplier. The 'shift' output-value is
+// basically the 'floating-point exponent' of the multiplier:
+// Negative for a right-shift (when the multiplier is <1), positive for a
+// left-shift (when the multiplier is >1)
+void QuantizeMultiplier(double double_multiplier, int32_t* quantized_multiplier,
+                        int* shift);
+
+// Splits a double input value into a returned fraction, and a shift value from
+// the exponent, using only bitwise and integer operations to support
+// microcontrollers and other environments without floating-point support.
+//
+// This is designed to be a replacement for how std::frexp() is used within the
+// QuantizeMultiplier() function, and so has a different signature than the
+// standard version, returning a 64-bit integer rather than a double. This
+// result has a maximum value of 1<<31, with the fraction expressed as a
+// proportion of that maximum.
+//
+// std::frexp() returns NaNs and infinities unmodified, but since we're
+// returning integers that can't represent those values, instead we return
+// a shift of std::numeric_limits<int>::max() for all bad numbers, with an int64
+// result of 0 for NaNs, std:numeric_limits<int64_t>::max() for +INFINITY, and
+// std::numeric_limits<int64_t>::min() for -INFINITY. Denormalized inputs will
+// result in return values that end up truncating some bits at the end,
+// reflecting the loss of precision inherent in denormalization.
+int64_t IntegerFrExp(double input, int* shift);
+
+// Converts an integer fraction in the format produced by IntegerFrExp (where
+// 0x40000000 is 1.0) and an exponent shift (between -1022 and +1022) into an
+// IEEE binary64 double format result. The implementation uses only integer and
+// bitwise operators, so no floating point hardware support or emulation is
+// needed. This is here so quantized operations can run non-time-critical
+// preparation calculations on microcontrollers and other platforms without
+// float support.
+double DoubleFromFractionAndShift(int64_t fraction, int shift);
+
+// Performs a multiplication of two numbers in double format, using only integer
+// and bitwise instructions. This is aimed at supporting housekeeping functions
+// for quantized operations on microcontrollers without floating-point hardware.
+double IntegerDoubleMultiply(double a, double b);
+
+// Returns -1 if a is less than b, 0 if a and b are equal, and +1 if a is
+// greater than b. It is implemented using only integer and logical instructions
+// so that it can be easily run on microcontrollers for quantized operations.
+int IntegerDoubleCompare(double a, double b);
+
+// This first creates a multiplier in a double equivalent of
+// Q(input_integer_bits).(31-input_integer_bits) representation, with extra
+// precision in the double's fractional bits.  It then splits the result into
+// significand and exponent.
+void PreprocessSoftmaxScaling(double beta, double input_scale,
+                              int input_integer_bits,
+                              int32_t* quantized_multiplier, int* left_shift);
+// Like PreprocessSoftmaxScaling, but inverse scaling factors also calculated.
+void PreprocessLogSoftmaxScalingExp(double beta, double input_scale,
+                                    int input_integer_bits,
+                                    int32_t* quantized_multiplier,
+                                    int* left_shift,
+                                    int32_t* reverse_scaling_divisor,
+                                    int* reverse_scaling_left_shift);
+// Calculate the largest input that will result in a within-bounds intermediate
+// result within MultiplyByQuantizedMultiplierGreaterThanOne.  In other words,
+// it must not overflow before we reduce the value by multiplication by the
+// input multiplier.  The negative radius is used as the minimum difference in
+// Softmax.
+int CalculateInputRadius(int input_integer_bits, int input_left_shift,
+                         int total_signed_bits = 31);
+
+// Nudges a min/max quantization range to ensure zero is zero.
+// Gymnastics with nudged zero point is to ensure that real zero maps to
+// an integer, which is required for e.g. zero-padding in convolutional layers.
+// Outputs nudged_min, nudged_max, nudged_scale.
+void NudgeQuantizationRange(const float min, const float max,
+                            const int quant_min, const int quant_max,
+                            float* nudged_min, float* nudged_max,
+                            float* nudged_scale);
+
+// Fake quantizes (quantizes and dequantizes) input_data using the scale,
+// nudged_min, and nudged_max from NudgeQuantizationRange. This matches the code
+// in TensorFlow's FakeQuantizeWithMinMaxVarsFunctor.
+void FakeQuantizeArray(const float nudged_scale, const float nudged_min,
+                       const float nudged_max, const float* input_data,
+                       float* output_data, const float size);
+
+// If x is approximately a power of two (with any positive or negative
+// exponent), stores that exponent (i.e. log2(x)) in *log2_result, otherwise
+// returns false.
+bool CheckedLog2(const float x, int* log2_result);
+
+// Decomposes an array of double multipliers into a Q0.31 int32 representation
+// of its significand, and shift representation of its exponent.
+//
+// Handles an arbitrary multiplier. The 'shift' output-value is
+// basically the 'floating-point exponent' of the multiplier:
+// Negative for a right-shift (when the multiplier is <1), positive for a
+// left-shift (when the multiplier is >1)
+void QuantizeMultiplierArray(const double* effective_scales, size_t size,
+                             int32_t* effective_scale_significand,
+                             int* effective_shift);
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_QUANTIZATION_UTIL_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/add.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/add.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,419 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_ADD_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_ADD_H_
+
+#include "fixedpoint/fixedpoint.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+
+namespace tflite {
+
+namespace reference_ops {
+
+template <typename T>
+inline void Add(const ArithmeticParams& params,
+                const RuntimeShape& input1_shape, const T* input1_data,
+                const RuntimeShape& input2_shape, const T* input2_data,
+                const RuntimeShape& output_shape, T* output_data) {
+  const int flat_size =
+      MatchingElementsSize(input1_shape, input2_shape, output_shape);
+  for (int i = 0; i < flat_size; ++i) {
+    output_data[i] = ActivationFunctionWithMinMax(
+        input1_data[i] + input2_data[i], params.quantized_activation_min,
+        params.quantized_activation_max);
+  }
+}
+
+inline void Add(const ArithmeticParams& params,
+                const RuntimeShape& input1_shape, const float* input1_data,
+                const RuntimeShape& input2_shape, const float* input2_data,
+                const RuntimeShape& output_shape, float* output_data) {
+  const int flat_size =
+      MatchingElementsSize(input1_shape, input2_shape, output_shape);
+  for (int i = 0; i < flat_size; i++) {
+    auto x = input1_data[i] + input2_data[i];
+    output_data[i] = ActivationFunctionWithMinMax(
+        x, params.float_activation_min, params.float_activation_max);
+  }
+}
+
+// Element-wise add that can often be used for inner loop of broadcast add as
+// well as the non-broadcast add.
+inline void AddElementwise(int size, const ArithmeticParams& params,
+                           const uint8* input1_data, const uint8* input2_data,
+                           uint8* output_data) {
+  TFLITE_DCHECK_GT(params.input1_offset, -256);
+  TFLITE_DCHECK_GT(params.input2_offset, -256);
+  TFLITE_DCHECK_LT(params.input1_offset, 256);
+  TFLITE_DCHECK_LT(params.input2_offset, 256);
+
+  for (int i = 0; i < size; ++i) {
+    const int32 input1_val = params.input1_offset + input1_data[i];
+    const int32 input2_val = params.input2_offset + input2_data[i];
+    const int32 shifted_input1_val = input1_val * (1 << params.left_shift);
+    const int32 shifted_input2_val = input2_val * (1 << params.left_shift);
+    const int32 scaled_input1_val =
+        MultiplyByQuantizedMultiplierSmallerThanOneExp(
+            shifted_input1_val, params.input1_multiplier, params.input1_shift);
+    const int32 scaled_input2_val =
+        MultiplyByQuantizedMultiplierSmallerThanOneExp(
+            shifted_input2_val, params.input2_multiplier, params.input2_shift);
+    const int32 raw_sum = scaled_input1_val + scaled_input2_val;
+    const int32 raw_output =
+        MultiplyByQuantizedMultiplierSmallerThanOneExp(
+            raw_sum, params.output_multiplier, params.output_shift) +
+        params.output_offset;
+    const int32 clamped_output =
+        std::min(params.quantized_activation_max,
+                 std::max(params.quantized_activation_min, raw_output));
+    output_data[i] = static_cast<uint8>(clamped_output);
+  }
+}
+
+// Scalar-broadcast add that can be used for inner loop of more general
+// broadcast add, so that, for example, scalar-broadcast with batch will still
+// be fast.
+inline void AddScalarBroadcast(int size, const ArithmeticParams& params,
+                               uint8 input1_data, const uint8* input2_data,
+                               uint8* output_data) {
+  TFLITE_DCHECK_GT(params.input1_offset, -256);
+  TFLITE_DCHECK_GT(params.input2_offset, -256);
+  TFLITE_DCHECK_LT(params.input1_offset, 256);
+  TFLITE_DCHECK_LT(params.input2_offset, 256);
+
+  const int32 input1_val = params.input1_offset + input1_data;
+  const int32 shifted_input1_val = input1_val * (1 << params.left_shift);
+  const int32 scaled_input1_val =
+      MultiplyByQuantizedMultiplierSmallerThanOneExp(
+          shifted_input1_val, params.input1_multiplier, params.input1_shift);
+  for (int i = 0; i < size; ++i) {
+    const int32 input2_val = params.input2_offset + input2_data[i];
+    const int32 shifted_input2_val = input2_val * (1 << params.left_shift);
+    const int32 scaled_input2_val =
+        MultiplyByQuantizedMultiplierSmallerThanOneExp(
+            shifted_input2_val, params.input2_multiplier, params.input2_shift);
+    const int32 raw_sum = scaled_input1_val + scaled_input2_val;
+    const int32 raw_output =
+        MultiplyByQuantizedMultiplierSmallerThanOneExp(
+            raw_sum, params.output_multiplier, params.output_shift) +
+        params.output_offset;
+    const int32 clamped_output =
+        std::min(params.quantized_activation_max,
+                 std::max(params.quantized_activation_min, raw_output));
+    output_data[i] = static_cast<uint8>(clamped_output);
+  }
+}
+
+inline void Add(const ArithmeticParams& params,
+                const RuntimeShape& input1_shape, const uint8* input1_data,
+                const RuntimeShape& input2_shape, const uint8* input2_data,
+                const RuntimeShape& output_shape, uint8* output_data) {
+  TFLITE_DCHECK_LE(params.quantized_activation_min,
+                   params.quantized_activation_max);
+  const int flat_size =
+      MatchingElementsSize(input1_shape, input2_shape, output_shape);
+
+  TFLITE_DCHECK_GT(params.input1_offset, -256);
+  TFLITE_DCHECK_GT(params.input2_offset, -256);
+  TFLITE_DCHECK_LT(params.input1_offset, 256);
+  TFLITE_DCHECK_LT(params.input2_offset, 256);
+  AddElementwise(flat_size, params, input1_data, input2_data, output_data);
+}
+
+inline void Add(const ArithmeticParams& params,
+                const RuntimeShape& input1_shape, const int16* input1_data,
+                const RuntimeShape& input2_shape, const int16* input2_data,
+                const RuntimeShape& output_shape, int16* output_data) {
+  TFLITE_DCHECK_LE(params.quantized_activation_min,
+                   params.quantized_activation_max);
+
+  const int input1_shift = params.input1_shift;
+  const int flat_size =
+      MatchingElementsSize(input1_shape, input2_shape, output_shape);
+  const int16 output_activation_min = params.quantized_activation_min;
+  const int16 output_activation_max = params.quantized_activation_max;
+
+  TFLITE_DCHECK(input1_shift == 0 || params.input2_shift == 0);
+  TFLITE_DCHECK_LE(input1_shift, 0);
+  TFLITE_DCHECK_LE(params.input2_shift, 0);
+  const int16* not_shift_input = input1_shift == 0 ? input1_data : input2_data;
+  const int16* shift_input = input1_shift == 0 ? input2_data : input1_data;
+  const int input_right_shift =
+      input1_shift == 0 ? -params.input2_shift : -input1_shift;
+
+  for (int i = 0; i < flat_size; i++) {
+    // F0 uses 0 integer bits, range [-1, 1].
+    using F0 = gemmlowp::FixedPoint<std::int16_t, 0>;
+
+    F0 input_ready_scaled = F0::FromRaw(not_shift_input[i]);
+    F0 scaled_input = F0::FromRaw(
+        gemmlowp::RoundingDivideByPOT(shift_input[i], input_right_shift));
+    F0 result = gemmlowp::SaturatingAdd(scaled_input, input_ready_scaled);
+    const int16 raw_output = result.raw();
+    const int16 clamped_output = std::min(
+        output_activation_max, std::max(output_activation_min, raw_output));
+    output_data[i] = clamped_output;
+  }
+}
+
+// TODO(jiawen): We can implement BroadcastAdd on buffers of arbitrary
+// dimensionality if the runtime code does a single loop over one dimension
+// that handles broadcasting as the base case. The code generator would then
+// generate max(D1, D2) nested for loops.
+// TODO(benoitjacob): BroadcastAdd is intentionally duplicated from
+// reference_ops.h. Once an optimized version is implemented and NdArrayDesc<T>
+// is no longer referenced in this file, move NdArrayDesc<T> from types.h to
+// reference_ops.h.
+inline void BroadcastAdd4DSlow(const ArithmeticParams& params,
+                               const RuntimeShape& input1_shape,
+                               const float* input1_data,
+                               const RuntimeShape& input2_shape,
+                               const float* input2_data,
+                               const RuntimeShape& output_shape,
+                               float* output_data) {
+  NdArrayDesc<4> desc1;
+  NdArrayDesc<4> desc2;
+  NdArrayDescsForElementwiseBroadcast(input1_shape, input2_shape, &desc1,
+                                      &desc2);
+  const RuntimeShape extended_output_shape =
+      RuntimeShape::ExtendedShape(4, output_shape);
+
+  // In Tensorflow, the dimensions are canonically named (batch_number, row,
+  // col, channel), with extents (batches, height, width, depth), with the
+  // trailing dimension changing most rapidly (channels has the smallest stride,
+  // typically 1 element).
+  //
+  // In generated C code, we store arrays with the dimensions reversed. The
+  // first dimension has smallest stride.
+  //
+  // We name our variables by their Tensorflow convention, but generate C code
+  // nesting loops such that the innermost loop has the smallest stride for the
+  // best cache behavior.
+  for (int b = 0; b < extended_output_shape.Dims(0); ++b) {
+    for (int y = 0; y < extended_output_shape.Dims(1); ++y) {
+      for (int x = 0; x < extended_output_shape.Dims(2); ++x) {
+        for (int c = 0; c < extended_output_shape.Dims(3); ++c) {
+          output_data[Offset(extended_output_shape, b, y, x, c)] =
+              ActivationFunctionWithMinMax(
+                  input1_data[SubscriptToIndex(desc1, b, y, x, c)] +
+                      input2_data[SubscriptToIndex(desc2, b, y, x, c)],
+                  params.float_activation_min, params.float_activation_max);
+        }
+      }
+    }
+  }
+}
+
+inline void BroadcastAdd4DSlow(const ArithmeticParams& params,
+                               const RuntimeShape& input1_shape,
+                               const int32* input1_data,
+                               const RuntimeShape& input2_shape,
+                               const int32* input2_data,
+                               const RuntimeShape& output_shape,
+                               int32* output_data) {
+  NdArrayDesc<4> desc1;
+  NdArrayDesc<4> desc2;
+  NdArrayDescsForElementwiseBroadcast(input1_shape, input2_shape, &desc1,
+                                      &desc2);
+  const RuntimeShape extended_output_shape =
+      RuntimeShape::ExtendedShape(4, output_shape);
+
+  // In Tensorflow, the dimensions are canonically named (batch_number, row,
+  // col, channel), with extents (batches, height, width, depth), with the
+  // trailing dimension changing most rapidly (channels has the smallest stride,
+  // typically 1 element).
+  //
+  // In generated C code, we store arrays with the dimensions reversed. The
+  // first dimension has smallest stride.
+  //
+  // We name our variables by their Tensorflow convention, but generate C code
+  // nesting loops such that the innermost loop has the smallest stride for the
+  // best cache behavior.
+  for (int b = 0; b < extended_output_shape.Dims(0); ++b) {
+    for (int y = 0; y < extended_output_shape.Dims(1); ++y) {
+      for (int x = 0; x < extended_output_shape.Dims(2); ++x) {
+        for (int c = 0; c < extended_output_shape.Dims(3); ++c) {
+          output_data[Offset(extended_output_shape, b, y, x, c)] =
+              ActivationFunctionWithMinMax(
+                  input1_data[SubscriptToIndex(desc1, b, y, x, c)] +
+                      input2_data[SubscriptToIndex(desc2, b, y, x, c)],
+                  params.quantized_activation_min,
+                  params.quantized_activation_max);
+        }
+      }
+    }
+  }
+}
+
+inline void BroadcastAdd4DSlow(const ArithmeticParams& params,
+                               const RuntimeShape& input1_shape,
+                               const uint8* input1_data,
+                               const RuntimeShape& input2_shape,
+                               const uint8* input2_data,
+                               const RuntimeShape& output_shape,
+                               uint8* output_data) {
+  NdArrayDesc<4> desc1;
+  NdArrayDesc<4> desc2;
+  NdArrayDescsForElementwiseBroadcast(input1_shape, input2_shape, &desc1,
+                                      &desc2);
+  const RuntimeShape extended_output_shape =
+      RuntimeShape::ExtendedShape(4, output_shape);
+
+  // In Tensorflow, the dimensions are canonically named (batch_number, row,
+  // col, channel), with extents (batches, height, width, depth), with the
+  // trailing dimension changing most rapidly (channels has the smallest stride,
+  // typically 1 element).
+  //
+  // In generated C code, we store arrays with the dimensions reversed. The
+  // first dimension has smallest stride.
+  //
+  // We name our variables by their Tensorflow convention, but generate C code
+  // nesting loops such that the innermost loop has the smallest stride for the
+  // best cache behavior.
+  for (int b = 0; b < extended_output_shape.Dims(0); ++b) {
+    for (int y = 0; y < extended_output_shape.Dims(1); ++y) {
+      for (int x = 0; x < extended_output_shape.Dims(2); ++x) {
+        for (int c = 0; c < extended_output_shape.Dims(3); ++c) {
+          const int32 input1_val =
+              params.input1_offset +
+              input1_data[SubscriptToIndex(desc1, b, y, x, c)];
+          const int32 input2_val =
+              params.input2_offset +
+              input2_data[SubscriptToIndex(desc2, b, y, x, c)];
+          const int32 shifted_input1_val =
+              input1_val * (1 << params.left_shift);
+          const int32 shifted_input2_val =
+              input2_val * (1 << params.left_shift);
+          const int32 scaled_input1_val =
+              MultiplyByQuantizedMultiplierSmallerThanOneExp(
+                  shifted_input1_val, params.input1_multiplier,
+                  params.input1_shift);
+          const int32 scaled_input2_val =
+              MultiplyByQuantizedMultiplierSmallerThanOneExp(
+                  shifted_input2_val, params.input2_multiplier,
+                  params.input2_shift);
+          const int32 raw_sum = scaled_input1_val + scaled_input2_val;
+          const int32 raw_output =
+              MultiplyByQuantizedMultiplierSmallerThanOneExp(
+                  raw_sum, params.output_multiplier, params.output_shift) +
+              params.output_offset;
+          const int32 clamped_output =
+              std::min(params.quantized_activation_max,
+                       std::max(params.quantized_activation_min, raw_output));
+          output_data[Offset(extended_output_shape, b, y, x, c)] =
+              static_cast<uint8>(clamped_output);
+        }
+      }
+    }
+  }
+}
+
+inline void BroadcastAddFivefold(const ArithmeticParams& unswitched_params,
+                                 const RuntimeShape& unswitched_input1_shape,
+                                 const uint8* unswitched_input1_data,
+                                 const RuntimeShape& unswitched_input2_shape,
+                                 const uint8* unswitched_input2_data,
+                                 const RuntimeShape& output_shape,
+                                 uint8* output_data) {
+  ArithmeticParams switched_params = unswitched_params;
+  switched_params.input1_offset = unswitched_params.input2_offset;
+  switched_params.input1_multiplier = unswitched_params.input2_multiplier;
+  switched_params.input1_shift = unswitched_params.input2_shift;
+  switched_params.input2_offset = unswitched_params.input1_offset;
+  switched_params.input2_multiplier = unswitched_params.input1_multiplier;
+  switched_params.input2_shift = unswitched_params.input1_shift;
+
+  const bool use_unswitched =
+      unswitched_params.broadcast_category ==
+      tflite::BroadcastableOpCategory::kFirstInputBroadcastsFast;
+
+  const ArithmeticParams& params =
+      use_unswitched ? unswitched_params : switched_params;
+  const uint8* input1_data =
+      use_unswitched ? unswitched_input1_data : unswitched_input2_data;
+  const uint8* input2_data =
+      use_unswitched ? unswitched_input2_data : unswitched_input1_data;
+
+  // Fivefold nested loops. The second input resets its position for each
+  // iteration of the second loop. The first input resets its position at the
+  // beginning of the fourth loop. The innermost loop is an elementwise add of
+  // sections of the arrays.
+  uint8* output_data_ptr = output_data;
+  const uint8* input1_data_ptr = input1_data;
+  const uint8* input2_data_reset = input2_data;
+  // In the fivefold pattern, y0, y2 and y4 are not broadcast, and so shared
+  // between input shapes. y3 for input 1 is always broadcast, and so the
+  // dimension there is 1, whereas optionally y1 might be broadcast for input 2.
+  // Put another way,
+  // input1.shape.FlatSize = y0 * y1 * y2 * y4,
+  // input2.shape.FlatSize = y0 * y2 * y3 * y4.
+  int y0 = params.broadcast_shape[0];
+  int y1 = params.broadcast_shape[1];
+  int y2 = params.broadcast_shape[2];
+  int y3 = params.broadcast_shape[3];
+  int y4 = params.broadcast_shape[4];
+  if (y4 > 1) {
+    // General fivefold pattern, with y4 > 1 so there is a non-broadcast inner
+    // dimension.
+    for (int i0 = 0; i0 < y0; ++i0) {
+      const uint8* input2_data_ptr;
+      for (int i1 = 0; i1 < y1; ++i1) {
+        input2_data_ptr = input2_data_reset;
+        for (int i2 = 0; i2 < y2; ++i2) {
+          for (int i3 = 0; i3 < y3; ++i3) {
+            AddElementwise(y4, params, input1_data_ptr, input2_data_ptr,
+                           output_data_ptr);
+            input2_data_ptr += y4;
+            output_data_ptr += y4;
+          }
+          // We have broadcast y4 of input1 data y3 times, and now move on.
+          input1_data_ptr += y4;
+        }
+      }
+      // We have broadcast y2*y3*y4 of input2 data y1 times, and now move on.
+      input2_data_reset = input2_data_ptr;
+    }
+  } else {
+    // Special case of y4 == 1, in which the innermost loop is a single element
+    // and can be combined with the next (y3) as an inner broadcast.
+    //
+    // Note that this handles the case of pure scalar broadcast when
+    // y0 == y1 == y2 == 1. With low overhead it handles cases such as scalar
+    // broadcast with batch (as y2 > 1).
+    //
+    // NOTE The process is the same as the above general case except simplified
+    // for y4 == 1 and the loop over y3 is contained within the
+    // AddScalarBroadcast function.
+    for (int i0 = 0; i0 < y0; ++i0) {
+      const uint8* input2_data_ptr;
+      for (int i1 = 0; i1 < y1; ++i1) {
+        input2_data_ptr = input2_data_reset;
+        for (int i2 = 0; i2 < y2; ++i2) {
+          AddScalarBroadcast(y3, params, *input1_data_ptr, input2_data_ptr,
+                             output_data_ptr);
+          input2_data_ptr += y3;
+          output_data_ptr += y3;
+          input1_data_ptr += 1;
+        }
+      }
+      input2_data_reset = input2_data_ptr;
+    }
+  }
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_ADD_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/arg_min_max.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/arg_min_max.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,68 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_ARG_MIN_MAX_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_ARG_MIN_MAX_H_
+
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+namespace reference_ops {
+
+template <typename T1, typename T2, typename T3, typename Cmp>
+void ArgMinMax(const RuntimeShape& input1_shape, const T1* input1_data,
+               const T3* input2_data, const RuntimeShape& output_shape,
+               T2* output_data, const Cmp& cmp) {
+  TFLITE_DCHECK_GT(input1_shape.DimensionsCount(), 0);
+  TFLITE_DCHECK_EQ(input1_shape.DimensionsCount() - 1,
+                   output_shape.DimensionsCount());
+  int axis = input2_data[0];
+  if (axis < 0) {
+    axis += input1_shape.DimensionsCount();
+  }
+  const int axis_size = input1_shape.Dims(axis);
+
+  int outer_size = 1;
+  for (int i = 0; i < axis; ++i) {
+    TFLITE_DCHECK_EQ(input1_shape.Dims(i), output_shape.Dims(i));
+    outer_size *= input1_shape.Dims(i);
+  }
+
+  int inner_size = 1;
+  const int dims_count = input1_shape.DimensionsCount();
+  for (int i = axis + 1; i < dims_count; ++i) {
+    TFLITE_DCHECK_EQ(input1_shape.Dims(i), output_shape.Dims(i - 1));
+    inner_size *= input1_shape.Dims(i);
+  }
+  for (int outer = 0; outer < outer_size; ++outer) {
+    for (int inner = 0; inner < inner_size; ++inner) {
+      auto min_max_value = input1_data[outer * axis_size * inner_size + inner];
+      T2 min_max_index = 0;
+      for (int i = 1; i < axis_size; ++i) {
+        const auto& curr_value =
+            input1_data[(outer * axis_size + i) * inner_size + inner];
+        if (cmp(curr_value, min_max_value)) {
+          min_max_value = curr_value;
+          min_max_index = static_cast<T2>(i);
+        }
+      }
+      output_data[outer * inner_size + inner] = min_max_index;
+    }
+  }
+}
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_ARG_MIN_MAX_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/binary_function.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/binary_function.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,84 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_BINARY_FUNCTION_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_BINARY_FUNCTION_H_
+
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/compatibility.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+namespace reference_ops {
+
+// TODO(ycling): Refactoring. Remove BroadcastLogical and use the more
+// generalized and efficient BroadcastBinaryFunction.
+//
+// Also appears to duplicte MinimumMaximum.
+//
+// R: Result type. T1: Input 1 type. T2: Input 2 type.
+template <typename R, typename T1, typename T2>
+inline void BroadcastBinaryFunction4DSlow(
+    const RuntimeShape& unextended_input1_shape, const T1* input1_data,
+    const RuntimeShape& unextended_input2_shape, const T2* input2_data,
+    const RuntimeShape& unextended_output_shape, R* output_data,
+    R (*func)(T1, T2)) {
+  TFLITE_DCHECK_LE(unextended_input1_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_LE(unextended_input2_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_LE(unextended_output_shape.DimensionsCount(), 4);
+  const RuntimeShape output_shape =
+      RuntimeShape::ExtendedShape(4, unextended_output_shape);
+
+  NdArrayDesc<4> desc1;
+  NdArrayDesc<4> desc2;
+  NdArrayDescsForElementwiseBroadcast(unextended_input1_shape,
+                                      unextended_input2_shape, &desc1, &desc2);
+
+  for (int b = 0; b < output_shape.Dims(0); ++b) {
+    for (int y = 0; y < output_shape.Dims(1); ++y) {
+      for (int x = 0; x < output_shape.Dims(2); ++x) {
+        for (int c = 0; c < output_shape.Dims(3); ++c) {
+          auto out_idx = Offset(output_shape, b, y, x, c);
+          auto in1_idx = SubscriptToIndex(desc1, b, y, x, c);
+          auto in2_idx = SubscriptToIndex(desc2, b, y, x, c);
+          auto in1_val = input1_data[in1_idx];
+          auto in2_val = input2_data[in2_idx];
+          output_data[out_idx] = func(in1_val, in2_val);
+        }
+      }
+    }
+  }
+}
+
+// R: Result type. T1: Input 1 type. T2: Input 2 type.
+// TODO(renjieliu): Refactor other binary functions to use this one.
+template <typename R, typename T1, typename T2>
+inline void BinaryFunction(const RuntimeShape& input1_shape,
+                           const T1* input1_data,
+                           const RuntimeShape& input2_shape,
+                           const T2* input2_data,
+                           const RuntimeShape& output_shape, R* output_data,
+                           R (*func)(T1, T2)) {
+  const int flat_size =
+      MatchingFlatSize(input1_shape, input2_shape, output_shape);
+  for (int i = 0; i < flat_size; ++i) {
+    output_data[i] = func(input1_data[i], input2_data[i]);
+  }
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_BINARY_FUNCTION_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/ceil.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/ceil.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,37 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_CEIL_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_CEIL_H_
+
+#include <cmath>
+
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+namespace reference_ops {
+
+inline void Ceil(const RuntimeShape& input_shape, const float* input_data,
+                 const RuntimeShape& output_shape, float* output_data) {
+  const int flat_size = MatchingFlatSize(input_shape, output_shape);
+
+  for (int i = 0; i < flat_size; ++i) {
+    output_data[i] = std::ceil(input_data[i]);
+  }
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_CEIL_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/comparisons.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/comparisons.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,267 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_COMPARISONS_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_COMPARISONS_H_
+
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+namespace reference_ops {
+
+template <typename T>
+inline bool EqualFn(T lhs, T rhs) {
+  return lhs == rhs;
+}
+
+template <typename T>
+inline bool NotEqualFn(T lhs, T rhs) {
+  return lhs != rhs;
+}
+
+template <typename T>
+inline bool GreaterFn(T lhs, T rhs) {
+  return lhs > rhs;
+}
+template <typename T>
+inline bool GreaterEqualFn(T lhs, T rhs) {
+  return lhs >= rhs;
+}
+template <typename T>
+inline bool LessFn(T lhs, T rhs) {
+  return lhs < rhs;
+}
+template <typename T>
+inline bool LessEqualFn(T lhs, T rhs) {
+  return lhs <= rhs;
+}
+
+template <typename T>
+using ComparisonFn = bool (*)(T, T);
+
+template <typename T, ComparisonFn<T> F>
+inline void ComparisonImpl(
+    const ComparisonParams& op_params, const RuntimeShape& input1_shape,
+    const T* input1_data, const RuntimeShape& input2_shape,
+    const T* input2_data, const RuntimeShape& output_shape, bool* output_data) {
+  const int64_t flatsize =
+      MatchingFlatSize(input1_shape, input2_shape, output_shape);
+  for (int64_t i = 0; i < flatsize; ++i) {
+    output_data[i] = F(input1_data[i], input2_data[i]);
+  }
+}
+
+template <ComparisonFn<float> F>
+inline void Comparison(const ComparisonParams& op_params,
+                       const RuntimeShape& input1_shape,
+                       const float* input1_data,
+                       const RuntimeShape& input2_shape,
+                       const float* input2_data,
+                       const RuntimeShape& output_shape, bool* output_data) {
+  ComparisonImpl<float, F>(op_params, input1_shape, input1_data, input2_shape,
+                           input2_data, output_shape, output_data);
+}
+
+template <typename T, ComparisonFn<int32> F>
+inline void ComparisonWithScaling(
+    const ComparisonParams& op_params, const RuntimeShape& input1_shape,
+    const T* input1_data, const RuntimeShape& input2_shape,
+    const T* input2_data, const RuntimeShape& output_shape, bool* output_data) {
+  int left_shift = op_params.left_shift;
+  int32 input1_offset = op_params.input1_offset;
+  int32 input1_multiplier = op_params.input1_multiplier;
+  int input1_shift = op_params.input1_shift;
+  int32 input2_offset = op_params.input2_offset;
+  int32 input2_multiplier = op_params.input2_multiplier;
+  int input2_shift = op_params.input2_shift;
+
+  const int64_t flatsize =
+      MatchingFlatSize(input1_shape, input2_shape, output_shape);
+  for (int64_t i = 0; i < flatsize; ++i) {
+    const int32 input1_val = input1_offset + input1_data[i];
+    const int32 input2_val = input2_offset + input2_data[i];
+    const int32 shifted_input1_val = input1_val * (1 << left_shift);
+    const int32 shifted_input2_val = input2_val * (1 << left_shift);
+    const int32 scaled_input1_val =
+        MultiplyByQuantizedMultiplierSmallerThanOneExp(
+            shifted_input1_val, input1_multiplier, input1_shift);
+    const int32 scaled_input2_val =
+        MultiplyByQuantizedMultiplierSmallerThanOneExp(
+            shifted_input2_val, input2_multiplier, input2_shift);
+    output_data[i] = F(scaled_input1_val, scaled_input2_val);
+  }
+}
+
+template <typename T, ComparisonFn<T> F>
+inline void BroadcastComparison4DSlowImpl(
+    const ComparisonParams& op_params,
+    const RuntimeShape& unextended_input1_shape, const T* input1_data,
+    const RuntimeShape& unextended_input2_shape, const T* input2_data,
+    const RuntimeShape& unextended_output_shape, bool* output_data) {
+  TFLITE_DCHECK_LE(unextended_input1_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_LE(unextended_input2_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_LE(unextended_output_shape.DimensionsCount(), 4);
+  const RuntimeShape output_shape =
+      RuntimeShape::ExtendedShape(4, unextended_output_shape);
+
+  NdArrayDesc<4> desc1;
+  NdArrayDesc<4> desc2;
+  NdArrayDescsForElementwiseBroadcast(unextended_input1_shape,
+                                      unextended_input2_shape, &desc1, &desc2);
+
+  for (int b = 0; b < output_shape.Dims(0); ++b) {
+    for (int y = 0; y < output_shape.Dims(1); ++y) {
+      for (int x = 0; x < output_shape.Dims(2); ++x) {
+        for (int c = 0; c < output_shape.Dims(3); ++c) {
+          output_data[Offset(output_shape, b, y, x, c)] =
+              F(input1_data[SubscriptToIndex(desc1, b, y, x, c)],
+                input2_data[SubscriptToIndex(desc2, b, y, x, c)]);
+        }
+      }
+    }
+  }
+}
+template <ComparisonFn<float> F>
+inline void BroadcastComparison4DSlow(const ComparisonParams& op_params,
+                                      const RuntimeShape& input1_shape,
+                                      const float* input1_data,
+                                      const RuntimeShape& input2_shape,
+                                      const float* input2_data,
+                                      const RuntimeShape& output_shape,
+                                      bool* output_data) {
+  BroadcastComparison4DSlowImpl<float, F>(op_params, input1_shape, input1_data,
+                                          input2_shape, input2_data,
+                                          output_shape, output_data);
+}
+
+template <typename T, ComparisonFn<int32> F>
+inline void BroadcastComparison4DSlowWithScaling(
+    const ComparisonParams& op_params,
+    const RuntimeShape& unextended_input1_shape, const T* input1_data,
+    const RuntimeShape& unextended_input2_shape, const T* input2_data,
+    const RuntimeShape& unextended_output_shape, bool* output_data) {
+  TFLITE_DCHECK_LE(unextended_input1_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_LE(unextended_input2_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_LE(unextended_output_shape.DimensionsCount(), 4);
+  const RuntimeShape output_shape =
+      RuntimeShape::ExtendedShape(4, unextended_output_shape);
+
+  NdArrayDesc<4> desc1;
+  NdArrayDesc<4> desc2;
+  NdArrayDescsForElementwiseBroadcast(unextended_input1_shape,
+                                      unextended_input2_shape, &desc1, &desc2);
+
+  int left_shift = op_params.left_shift;
+  int32 input1_offset = op_params.input1_offset;
+  int32 input1_multiplier = op_params.input1_multiplier;
+  int input1_shift = op_params.input1_shift;
+  int32 input2_offset = op_params.input2_offset;
+  int32 input2_multiplier = op_params.input2_multiplier;
+  int input2_shift = op_params.input2_shift;
+
+  for (int b = 0; b < output_shape.Dims(0); ++b) {
+    for (int y = 0; y < output_shape.Dims(1); ++y) {
+      for (int x = 0; x < output_shape.Dims(2); ++x) {
+        for (int c = 0; c < output_shape.Dims(3); ++c) {
+          const int32 input1_val =
+              input1_offset + input1_data[SubscriptToIndex(desc1, b, y, x, c)];
+          const int32 input2_val =
+              input2_offset + input2_data[SubscriptToIndex(desc2, b, y, x, c)];
+          const int32 shifted_input1_val = input1_val * (1 << left_shift);
+          const int32 shifted_input2_val = input2_val * (1 << left_shift);
+          const int32 scaled_input1_val =
+              MultiplyByQuantizedMultiplierSmallerThanOneExp(
+                  shifted_input1_val, input1_multiplier, input1_shift);
+          const int32 scaled_input2_val =
+              MultiplyByQuantizedMultiplierSmallerThanOneExp(
+                  shifted_input2_val, input2_multiplier, input2_shift);
+          output_data[Offset(output_shape, b, y, x, c)] =
+              F(scaled_input1_val, scaled_input2_val);
+        }
+      }
+    }
+  }
+}
+
+#define TFLITE_COMPARISON_OP(name)                                             \
+  inline void name(const ComparisonParams& op_params,                          \
+                   const RuntimeShape& input1_shape, const float* input1_data, \
+                   const RuntimeShape& input2_shape, const float* input2_data, \
+                   const RuntimeShape& output_shape, bool* output_data) {      \
+    Comparison<name##Fn>(op_params, input1_shape, input1_data, input2_shape,   \
+                         input2_data, output_shape, output_data);              \
+  }                                                                            \
+  template <typename T>                                                        \
+  inline void name##NoScaling(                                                 \
+      const ComparisonParams& op_params, const RuntimeShape& input1_shape,     \
+      const T* input1_data, const RuntimeShape& input2_shape,                  \
+      const T* input2_data, const RuntimeShape& output_shape,                  \
+      bool* output_data) {                                                     \
+    ComparisonImpl<T, name##Fn>(op_params, input1_shape, input1_data,          \
+                                input2_shape, input2_data, output_shape,       \
+                                output_data);                                  \
+  }                                                                            \
+  template <typename T>                                                        \
+  inline void name##WithScaling(                                               \
+      const ComparisonParams& op_params, const RuntimeShape& input1_shape,     \
+      const T* input1_data, const RuntimeShape& input2_shape,                  \
+      const T* input2_data, const RuntimeShape& output_shape,                  \
+      bool* output_data) {                                                     \
+    ComparisonWithScaling<T, name##Fn>(op_params, input1_shape, input1_data,   \
+                                       input2_shape, input2_data,              \
+                                       output_shape, output_data);             \
+  }                                                                            \
+  template <typename T>                                                        \
+  inline void Broadcast4DSlow##name##NoScaling(                                \
+      const ComparisonParams& op_params, const RuntimeShape& input1_shape,     \
+      const T* input1_data, const RuntimeShape& input2_shape,                  \
+      const T* input2_data, const RuntimeShape& output_shape,                  \
+      bool* output_data) {                                                     \
+    BroadcastComparison4DSlowImpl<T, name##Fn>(                                \
+        op_params, input1_shape, input1_data, input2_shape, input2_data,       \
+        output_shape, output_data);                                            \
+  }                                                                            \
+  inline void Broadcast4DSlow##name(                                           \
+      const ComparisonParams& op_params, const RuntimeShape& input1_shape,     \
+      const float* input1_data, const RuntimeShape& input2_shape,              \
+      const float* input2_data, const RuntimeShape& output_shape,              \
+      bool* output_data) {                                                     \
+    BroadcastComparison4DSlow<name##Fn>(op_params, input1_shape, input1_data,  \
+                                        input2_shape, input2_data,             \
+                                        output_shape, output_data);            \
+  }                                                                            \
+  template <typename T>                                                        \
+  inline void Broadcast4DSlow##name##WithScaling(                              \
+      const ComparisonParams& op_params, const RuntimeShape& input1_shape,     \
+      const T* input1_data, const RuntimeShape& input2_shape,                  \
+      const T* input2_data, const RuntimeShape& output_shape,                  \
+      bool* output_data) {                                                     \
+    BroadcastComparison4DSlowWithScaling<T, name##Fn>(                         \
+        op_params, input1_shape, input1_data, input2_shape, input2_data,       \
+        output_shape, output_data);                                            \
+  }
+TFLITE_COMPARISON_OP(Equal);
+TFLITE_COMPARISON_OP(NotEqual);
+TFLITE_COMPARISON_OP(Greater);
+TFLITE_COMPARISON_OP(GreaterEqual);
+TFLITE_COMPARISON_OP(Less);
+TFLITE_COMPARISON_OP(LessEqual);
+#undef TFLITE_COMPARISON_OP
+
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_COMPARISONS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/conv.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/conv.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,262 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_CONV_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_CONV_H_
+
+#include "tensorflow/lite/kernels/internal/types.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+
+
+
+namespace tflite {
+
+namespace reference_ops {
+
+
+inline void Conv(const ConvParams& params, const RuntimeShape& input_shape,
+                 const float* input_data, const RuntimeShape& filter_shape,
+                 const float* filter_data, const RuntimeShape& bias_shape,
+                 const float* bias_data, const RuntimeShape& output_shape,
+                 float* output_data, const RuntimeShape& im2col_shape,
+                 float* im2col_data) {
+  const int stride_width = params.stride_width;
+  const int stride_height = params.stride_height;
+  const int dilation_width_factor = params.dilation_width_factor;
+  const int dilation_height_factor = params.dilation_height_factor;
+  const int pad_width = params.padding_values.width;
+  const int pad_height = params.padding_values.height;
+  const float output_activation_min = params.float_activation_min;
+  const float output_activation_max = params.float_activation_max;
+  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(filter_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+
+  (void)im2col_data;   // only used in optimized code.
+  (void)im2col_shape;  // only used in optimized code.
+  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+  const int input_depth = MatchingDim(input_shape, 3, filter_shape, 3);
+  const int output_depth = MatchingDim(filter_shape, 0, output_shape, 3);
+  if (bias_data) {
+    TFLITE_DCHECK_EQ(bias_shape.FlatSize(), output_depth);
+  }
+  const int input_height = input_shape.Dims(1);
+  const int input_width = input_shape.Dims(2);
+  const int filter_height = filter_shape.Dims(1);
+  const int filter_width = filter_shape.Dims(2);
+  const int output_height = output_shape.Dims(1);
+  const int output_width = output_shape.Dims(2);
+  for (int batch = 0; batch < batches; ++batch) {
+    for (int out_y = 0; out_y < output_height; ++out_y) {
+      for (int out_x = 0; out_x < output_width; ++out_x) {
+        for (int out_channel = 0; out_channel < output_depth; ++out_channel) {
+          const int in_x_origin = (out_x * stride_width) - pad_width;
+          const int in_y_origin = (out_y * stride_height) - pad_height;
+          float total = 0.f;
+          for (int filter_y = 0; filter_y < filter_height; ++filter_y) {
+            for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
+              for (int in_channel = 0; in_channel < input_depth; ++in_channel) {
+                const int in_x = in_x_origin + dilation_width_factor * filter_x;
+                const int in_y =
+                    in_y_origin + dilation_height_factor * filter_y;
+                // If the location is outside the bounds of the input image,
+                // use zero as a default value.
+                if ((in_x >= 0) && (in_x < input_width) && (in_y >= 0) &&
+                    (in_y < input_height)) {
+                  float input_value = input_data[Offset(
+                      input_shape, batch, in_y, in_x, in_channel)];
+                  float filter_value =
+                      filter_data[Offset(filter_shape, out_channel, filter_y,
+                                         filter_x, in_channel)];
+                  total += (input_value * filter_value);
+                }
+              }
+            }
+          }
+          float bias_value = 0.0f;
+          if (bias_data) {
+            bias_value = bias_data[out_channel];
+          }
+          output_data[Offset(output_shape, batch, out_y, out_x, out_channel)] =
+              ActivationFunctionWithMinMax(total + bias_value,
+                                           output_activation_min,
+                                           output_activation_max);
+        }
+      }
+    }
+  }
+}
+
+inline void Conv(const ConvParams& params, const RuntimeShape& input_shape,
+                 const uint8* input_data, const RuntimeShape& filter_shape,
+                 const uint8* filter_data, const RuntimeShape& bias_shape,
+                 const int32* bias_data, const RuntimeShape& output_shape,
+                 uint8* output_data, const RuntimeShape& im2col_shape,
+                 uint8* im2col_data, void* cpu_backend_context) {
+  (void)cpu_backend_context;  // only used in optimized code.
+  (void)im2col_data;   // only used in optimized code.
+  (void)im2col_shape;  // only used in optimized code.
+  const int stride_width = params.stride_width;
+  const int stride_height = params.stride_height;
+  const int dilation_width_factor = params.dilation_width_factor;
+  const int dilation_height_factor = params.dilation_height_factor;
+  const int pad_width = params.padding_values.width;
+  const int pad_height = params.padding_values.height;
+  const int32 input_offset = params.input_offset;
+  const int32 filter_offset = params.weights_offset;
+  const int32 output_offset = params.output_offset;
+  const int32 output_multiplier = params.output_multiplier;
+  const int output_shift = params.output_shift;
+  const int32 output_activation_min = params.quantized_activation_min;
+  const int32 output_activation_max = params.quantized_activation_max;
+  TFLITE_DCHECK_LE(output_activation_min, output_activation_max);
+
+  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(filter_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+  const int input_depth = MatchingDim(input_shape, 3, filter_shape, 3);
+  const int output_depth = MatchingDim(filter_shape, 0, output_shape, 3);
+  if (bias_data) {
+    TFLITE_DCHECK_EQ(bias_shape.FlatSize(), output_depth);
+  }
+  const int input_height = input_shape.Dims(1);
+  const int input_width = input_shape.Dims(2);
+  const int filter_height = filter_shape.Dims(1);
+  const int filter_width = filter_shape.Dims(2);
+  const int output_height = output_shape.Dims(1);
+  const int output_width = output_shape.Dims(2);
+  for (int batch = 0; batch < batches; ++batch) {
+    for (int out_y = 0; out_y < output_height; ++out_y) {
+      for (int out_x = 0; out_x < output_width; ++out_x) {
+        for (int out_channel = 0; out_channel < output_depth; ++out_channel) {
+          const int in_x_origin = (out_x * stride_width) - pad_width;
+          const int in_y_origin = (out_y * stride_height) - pad_height;
+          int32 acc = 0;
+          for (int filter_y = 0; filter_y < filter_height; ++filter_y) {
+            for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
+              for (int in_channel = 0; in_channel < input_depth; ++in_channel) {
+                const int in_x = in_x_origin + dilation_width_factor * filter_x;
+                const int in_y =
+                    in_y_origin + dilation_height_factor * filter_y;
+                // If the location is outside the bounds of the input image,
+                // use zero as a default value.
+                if ((in_x >= 0) && (in_x < input_width) && (in_y >= 0) &&
+                    (in_y < input_height)) {
+                  int32 input_val = input_data[Offset(input_shape, batch, in_y,
+                                                      in_x, in_channel)];
+                  int32 filter_val =
+                      filter_data[Offset(filter_shape, out_channel, filter_y,
+                                         filter_x, in_channel)];
+                  acc +=
+                      (filter_val + filter_offset) * (input_val + input_offset);
+                }
+              }
+            }
+          }
+          if (bias_data) {
+            acc += bias_data[out_channel];
+          }
+          acc = MultiplyByQuantizedMultiplier(acc, output_multiplier,
+                                              output_shift);
+          acc += output_offset;
+          acc = std::max(acc, output_activation_min);
+          acc = std::min(acc, output_activation_max);
+          output_data[Offset(output_shape, batch, out_y, out_x, out_channel)] =
+              static_cast<uint8>(acc);
+        }
+      }
+    }
+  }
+}
+
+inline void HybridConvPerChannel(
+    const ConvParams& params, float* scaling_factors_ptr,
+    const RuntimeShape& input_shape, const int8_t* input_data,
+    const RuntimeShape& filter_shape, const int8_t* filter_data,
+    const RuntimeShape& bias_shape, const float* bias_data,
+    const RuntimeShape& output_shape, float* output_data,
+    const RuntimeShape& im2col_shape, int8_t* im2col_data,
+    const float* per_channel_scale, int32_t* input_offset) {
+  (void)im2col_data;   // only used in optimized code.
+  (void)im2col_shape;  // only used in optimized code.
+  const int stride_width = params.stride_width;
+  const int stride_height = params.stride_height;
+  const int dilation_width_factor = params.dilation_width_factor;
+  const int dilation_height_factor = params.dilation_height_factor;
+  const int pad_width = params.padding_values.width;
+  const int pad_height = params.padding_values.height;
+  const float output_activation_min = params.float_activation_min;
+  const float output_activation_max = params.float_activation_max;
+  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(filter_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+  const int input_depth = MatchingDim(input_shape, 3, filter_shape, 3);
+  const int output_depth = MatchingDim(filter_shape, 0, output_shape, 3);
+  if (bias_data) {
+    TFLITE_DCHECK_EQ(bias_shape.FlatSize(), output_depth);
+  }
+  const int input_height = input_shape.Dims(1);
+  const int input_width = input_shape.Dims(2);
+  const int filter_height = filter_shape.Dims(1);
+  const int filter_width = filter_shape.Dims(2);
+  const int output_height = output_shape.Dims(1);
+  const int output_width = output_shape.Dims(2);
+  for (int batch = 0; batch < batches; ++batch) {
+    for (int out_y = 0; out_y < output_height; ++out_y) {
+      for (int out_x = 0; out_x < output_width; ++out_x) {
+        for (int out_channel = 0; out_channel < output_depth; ++out_channel) {
+          const int in_x_origin = (out_x * stride_width) - pad_width;
+          const int in_y_origin = (out_y * stride_height) - pad_height;
+          int32 acc = 0;
+          for (int filter_y = 0; filter_y < filter_height; ++filter_y) {
+            for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
+              for (int in_channel = 0; in_channel < input_depth; ++in_channel) {
+                const int in_x = in_x_origin + dilation_width_factor * filter_x;
+                const int in_y =
+                    in_y_origin + dilation_height_factor * filter_y;
+                // If the location is outside the bounds of the input image,
+                // use zero as a default value.
+                if ((in_x >= 0) && (in_x < input_width) && (in_y >= 0) &&
+                    (in_y < input_height)) {
+                  int32 input_val = input_data[Offset(input_shape, batch, in_y,
+                                                      in_x, in_channel)];
+                  int32 filter_val =
+                      filter_data[Offset(filter_shape, out_channel, filter_y,
+                                         filter_x, in_channel)];
+                  acc += filter_val * (input_val - input_offset[batch]);
+                }
+              }
+            }
+          }
+          float acc_float =
+              acc * per_channel_scale[out_channel] * scaling_factors_ptr[batch];
+          if (bias_data) {
+            acc_float += bias_data[out_channel];
+          }
+          output_data[Offset(output_shape, batch, out_y, out_x, out_channel)] =
+              ActivationFunctionWithMinMax(acc_float, output_activation_min,
+                                           output_activation_max);
+        }
+      }
+    }
+  }
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_CONV_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/depthwiseconv_float.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/depthwiseconv_float.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,100 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_DEPTHWISECONV_FLOAT_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_DEPTHWISECONV_FLOAT_H_
+
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/compatibility.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+namespace reference_ops {
+
+inline void DepthwiseConv(
+    const DepthwiseParams& params, const RuntimeShape& input_shape,
+    const float* input_data, const RuntimeShape& filter_shape,
+    const float* filter_data, const RuntimeShape& bias_shape,
+    const float* bias_data, const RuntimeShape& output_shape,
+    float* output_data) {
+  const int stride_width = params.stride_width;
+  const int stride_height = params.stride_height;
+  const int dilation_width_factor = params.dilation_width_factor;
+  const int dilation_height_factor = params.dilation_height_factor;
+  const int pad_width = params.padding_values.width;
+  const int pad_height = params.padding_values.height;
+  const int depth_multiplier = params.depth_multiplier;
+  const float output_activation_min = params.float_activation_min;
+  const float output_activation_max = params.float_activation_max;
+  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(filter_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+
+  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+  const int output_depth = MatchingDim(filter_shape, 3, output_shape, 3);
+  const int input_height = input_shape.Dims(1);
+  const int input_width = input_shape.Dims(2);
+  const int input_depth = input_shape.Dims(3);
+  const int filter_height = filter_shape.Dims(1);
+  const int filter_width = filter_shape.Dims(2);
+  const int output_height = output_shape.Dims(1);
+  const int output_width = output_shape.Dims(2);
+  TFLITE_DCHECK_EQ(output_depth, input_depth * depth_multiplier);
+  TFLITE_DCHECK_EQ(bias_shape.FlatSize(), output_depth);
+
+  for (int b = 0; b < batches; ++b) {
+    for (int out_y = 0; out_y < output_height; ++out_y) {
+      for (int out_x = 0; out_x < output_width; ++out_x) {
+        for (int ic = 0; ic < input_depth; ++ic) {
+          for (int m = 0; m < depth_multiplier; m++) {
+            const int oc = m + ic * depth_multiplier;
+            const int in_x_origin = (out_x * stride_width) - pad_width;
+            const int in_y_origin = (out_y * stride_height) - pad_height;
+            float total = 0.f;
+            for (int filter_y = 0; filter_y < filter_height; ++filter_y) {
+              for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
+                const int in_x = in_x_origin + dilation_width_factor * filter_x;
+                const int in_y =
+                    in_y_origin + dilation_height_factor * filter_y;
+                // If the location is outside the bounds of the input image,
+                // use zero as a default value.
+                if ((in_x >= 0) && (in_x < input_width) && (in_y >= 0) &&
+                    (in_y < input_height)) {
+                  float input_value =
+                      input_data[Offset(input_shape, b, in_y, in_x, ic)];
+                  float filter_value = filter_data[Offset(
+                      filter_shape, 0, filter_y, filter_x, oc)];
+                  total += (input_value * filter_value);
+                }
+              }
+            }
+            float bias_value = 0.0f;
+            if (bias_data) {
+              bias_value = bias_data[oc];
+            }
+            output_data[Offset(output_shape, b, out_y, out_x, oc)] =
+                ActivationFunctionWithMinMax(total + bias_value,
+                                             output_activation_min,
+                                             output_activation_max);
+          }
+        }
+      }
+    }
+  }
+}
+
+}  // end namespace reference_ops
+}  // end namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_DEPTHWISECONV_FLOAT_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/depthwiseconv_uint8.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/depthwiseconv_uint8.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,195 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_DEPTHWISECONV_UINT8_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_DEPTHWISECONV_UINT8_H_
+
+#include <algorithm>
+
+#include "fixedpoint/fixedpoint.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/compatibility.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+// Used in tests and template parameters to control which version of depthwise
+// convolution is called. Primarily for reference code, and specializations
+// forced in tests.
+enum class DepthwiseConvImplementation {
+  // Run all tests against kUseStandardEntry even if also testing another
+  // kernel, since we need to be sure that the main DepthwiseConv() function in
+  // optimized_ops.h dispatches to a correctly-executing kernel.
+  kNone = 0,                 // The "default" option: use the normal
+                             // DepthwiseConv kernel (entry) function.
+  kUseGenericKernel,         // Forced use of generic kernel.
+  kUseNeon3x3,               // 3x3 kernel that uses NEON when available.
+  kUseNeon3x3DotProduct,     // 3x3 kernel that uses dot-product enabled NEON
+                             // when available.
+  kUseCModel3x3DotProduct,   // 3x3 kernel, reference C model that is intended
+                             // to match overall design NEON code.
+  kUseUnwound3x3DotProduct,  // 3x3 kernel, reference C model with unwound loops
+                             // and some arrays.
+  kUseIntrinsics3x3DotProduct,  // 3x3 kernel using NEON intrinsics.
+};
+
+// Category of depthwise convolution output rounding.
+enum class DepthwiseConvOutputRounding {
+  kNone = 0,      // Invalid: specific method must be specified.
+  kAwayFromZero,  // Original method: exact halves rounded away from zero.
+  kUpward,        // Halves towards +infinity: adds 0.5 before truncate.
+  // This is where a future kNearestEven would be placed.
+};
+
+// Category of depthwise convolution depth multiplication.
+enum class DepthwiseConvDepthMultiplication {
+  kNoMultiplication = 0,  // Depth multiplier = 1.
+  kUnitInputDepth,        // Input depth = 1, output depth = depth multiplier.
+};
+
+namespace reference_ops {
+namespace depthwise_conv {
+
+template <DepthwiseConvOutputRounding output_rounding>
+inline int32 DepthwiseConvRound(int32 x, int32 quantized_multiplier,
+                                int shift) {
+  TFLITE_DCHECK_NE(output_rounding, DepthwiseConvOutputRounding::kNone);
+  return MultiplyByQuantizedMultiplier(x, quantized_multiplier, shift);
+}
+
+template <>
+inline int32 DepthwiseConvRound<DepthwiseConvOutputRounding::kAwayFromZero>(
+    int32 x, int32 quantized_multiplier, int shift) {
+  return MultiplyByQuantizedMultiplier(x, quantized_multiplier, shift);
+}
+
+template <>
+inline int32 DepthwiseConvRound<DepthwiseConvOutputRounding::kUpward>(
+    int32 x, int32 quantized_multiplier, int shift) {
+  using gemmlowp::SaturatingRoundingDoublingHighMul;
+  const int left_shift = shift > 0 ? shift : 0;
+  const int right_shift = shift > 0 ? 0 : -shift;
+  const int rounding_offset = right_shift > 0 ? 1 << (right_shift - 1) : 0;
+  return (SaturatingRoundingDoublingHighMul(x * (1 << left_shift),
+                                            quantized_multiplier) +
+          rounding_offset) >>
+         right_shift;
+}
+
+template <DepthwiseConvOutputRounding output_rounding>
+struct DepthwiseConvBasicKernel {
+  static inline void Run(const DepthwiseParams& params,
+                         const RuntimeShape& input_shape,
+                         const uint8* input_data,
+                         const RuntimeShape& filter_shape,
+                         const uint8* filter_data,
+                         const RuntimeShape& bias_shape, const int32* bias_data,
+                         const RuntimeShape& output_shape, uint8* output_data) {
+    const int stride_width = params.stride_width;
+    const int stride_height = params.stride_height;
+    const int dilation_width_factor = params.dilation_width_factor;
+    const int dilation_height_factor = params.dilation_height_factor;
+    const int pad_width = params.padding_values.width;
+    const int pad_height = params.padding_values.height;
+    const int depth_multiplier = params.depth_multiplier;
+    const int32 output_activation_min = params.quantized_activation_min;
+    const int32 output_activation_max = params.quantized_activation_max;
+    const int32 input_offset = params.input_offset;
+    const int32 filter_offset = params.weights_offset;
+    const int32 output_offset = params.output_offset;
+    const int32 output_multiplier = params.output_multiplier;
+    const int output_shift = params.output_shift;
+    TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+    TFLITE_DCHECK_EQ(filter_shape.DimensionsCount(), 4);
+    TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+
+    TFLITE_DCHECK_LE(output_activation_min, output_activation_max);
+    const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+    const int output_depth = MatchingDim(filter_shape, 3, output_shape, 3);
+    const int input_height = input_shape.Dims(1);
+    const int input_width = input_shape.Dims(2);
+    const int input_depth = input_shape.Dims(3);
+    const int filter_height = filter_shape.Dims(1);
+    const int filter_width = filter_shape.Dims(2);
+    const int output_height = output_shape.Dims(1);
+    const int output_width = output_shape.Dims(2);
+    TFLITE_DCHECK_EQ(output_depth, input_depth * depth_multiplier);
+    TFLITE_DCHECK_EQ(bias_shape.FlatSize(), output_depth);
+
+    for (int b = 0; b < batches; ++b) {
+      for (int out_y = 0; out_y < output_height; ++out_y) {
+        for (int out_x = 0; out_x < output_width; ++out_x) {
+          for (int ic = 0; ic < input_depth; ++ic) {
+            for (int m = 0; m < depth_multiplier; m++) {
+              const int oc = m + ic * depth_multiplier;
+              const int in_x_origin = (out_x * stride_width) - pad_width;
+              const int in_y_origin = (out_y * stride_height) - pad_height;
+              int32 acc = 0;
+              for (int filter_y = 0; filter_y < filter_height; ++filter_y) {
+                for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
+                  const int in_x =
+                      in_x_origin + dilation_width_factor * filter_x;
+                  const int in_y =
+                      in_y_origin + dilation_height_factor * filter_y;
+                  // If the location is outside the bounds of the input image,
+                  // use zero as a default value.
+                  if ((in_x >= 0) && (in_x < input_width) && (in_y >= 0) &&
+                      (in_y < input_height)) {
+                    int32 input_val =
+                        input_data[Offset(input_shape, b, in_y, in_x, ic)];
+                    int32 filter_val = filter_data[Offset(
+                        filter_shape, 0, filter_y, filter_x, oc)];
+                    acc += (filter_val + filter_offset) *
+                           (input_val + input_offset);
+                  }
+                }
+              }
+              if (bias_data) {
+                acc += bias_data[oc];
+              }
+              acc = DepthwiseConvRound<output_rounding>(acc, output_multiplier,
+                                                        output_shift);
+              acc += output_offset;
+              acc = std::max(acc, output_activation_min);
+              acc = std::min(acc, output_activation_max);
+              output_data[Offset(output_shape, b, out_y, out_x, oc)] =
+                  static_cast<uint8>(acc);
+            }
+          }
+        }
+      }
+    }
+  }
+};
+
+}  // namespace depthwise_conv
+
+inline void DepthwiseConv(
+    const DepthwiseParams& params, const RuntimeShape& input_shape,
+    const uint8* input_data, const RuntimeShape& filter_shape,
+    const uint8* filter_data, const RuntimeShape& bias_shape,
+    const int32* bias_data, const RuntimeShape& output_shape,
+    uint8* output_data) {
+  return depthwise_conv::DepthwiseConvBasicKernel<
+      DepthwiseConvOutputRounding::kAwayFromZero>::Run(params, input_shape,
+                                                       input_data, filter_shape,
+                                                       filter_data, bias_shape,
+                                                       bias_data, output_shape,
+                                                       output_data);
+}
+
+}  // namespace reference_ops
+}  // end namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_DEPTHWISECONV_UINT8_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/dequantize.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/dequantize.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,43 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_DEQUANTIZE_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_DEQUANTIZE_H_
+
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+namespace reference_ops {
+
+template <typename T>
+inline void Dequantize(const tflite::DequantizationParams& op_params,
+                       const RuntimeShape& input_shape, const T* input_data,
+                       const RuntimeShape& output_shape, float* output_data) {
+  int32 zero_point = op_params.zero_point;
+  const double scale = op_params.scale;
+  const int flat_size = MatchingFlatSize(input_shape, output_shape);
+
+  for (int i = 0; i < flat_size; i++) {
+    const int32 val = input_data[i];
+    const float result = static_cast<float>(scale * (val - zero_point));
+    output_data[i] = result;
+  }
+}
+
+}  // namespace reference_ops
+
+}  // namespace tflite
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_DEQUANTIZE_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/floor.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/floor.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,39 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_FLOOR_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_FLOOR_H_
+
+#include <cmath>
+
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+namespace reference_ops {
+
+inline void Floor(const RuntimeShape& input_shape, const float* input_data,
+                  const RuntimeShape& output_shape, float* output_data) {
+  const int flat_size = MatchingFlatSize(input_shape, output_shape);
+
+  for (int i = 0; i < flat_size; i++) {
+    int offset = i;
+    output_data[offset] = std::floor(input_data[offset]);
+  }
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_FLOOR_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/fully_connected.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/fully_connected.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,321 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_FULLY_CONNECTED_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_FULLY_CONNECTED_H_
+
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/round.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+namespace reference_ops {
+
+const int kReverseShift = -1;
+
+inline void FullyConnected(
+    const FullyConnectedParams& params, const RuntimeShape& input_shape,
+    const float* input_data, const RuntimeShape& weights_shape,
+    const float* weights_data, const RuntimeShape& bias_shape,
+    const float* bias_data, const RuntimeShape& output_shape,
+    float* output_data) {
+  const float output_activation_min = params.float_activation_min;
+  const float output_activation_max = params.float_activation_max;
+  // TODO(benoitjacob): This really should be:
+  //     const int batches = ArraySize(output_dims, 1);
+  // but the current --variable_batch hack consists in overwriting the 3rd
+  // dimension with the runtime batch size, as we don't keep track for each
+  // array of which dimension is the batch dimension in it.
+  const int output_dims_count = output_shape.DimensionsCount();
+  const int weights_dims_count = weights_shape.DimensionsCount();
+  const int batches = FlatSizeSkipDim(output_shape, output_dims_count - 1);
+  const int output_depth = MatchingDim(weights_shape, weights_dims_count - 2,
+                                       output_shape, output_dims_count - 1);
+  const int accum_depth = weights_shape.Dims(weights_dims_count - 1);
+  for (int b = 0; b < batches; ++b) {
+    for (int out_c = 0; out_c < output_depth; ++out_c) {
+      float total = 0.f;
+      for (int d = 0; d < accum_depth; ++d) {
+        total += input_data[b * accum_depth + d] *
+                 weights_data[out_c * accum_depth + d];
+      }
+      float bias_value = 0.0f;
+      if (bias_data) {
+        bias_value = bias_data[out_c];
+      }
+      output_data[out_c + output_depth * b] = ActivationFunctionWithMinMax(
+          total + bias_value, output_activation_min, output_activation_max);
+    }
+  }
+}
+
+inline void FullyConnected(
+    const FullyConnectedParams& params, const RuntimeShape& input_shape,
+    const uint8* input_data, const RuntimeShape& filter_shape,
+    const uint8* filter_data, const RuntimeShape& bias_shape,
+    const int32* bias_data, const RuntimeShape& output_shape,
+    uint8* output_data) {
+  const int32 input_offset = params.input_offset;
+  const int32 filter_offset = params.weights_offset;
+  const int32 output_offset = params.output_offset;
+  const int32 output_multiplier = params.output_multiplier;
+  const int output_shift = params.output_shift;
+  const int32 output_activation_min = params.quantized_activation_min;
+  const int32 output_activation_max = params.quantized_activation_max;
+  TFLITE_DCHECK_GE(filter_shape.DimensionsCount(), 2);
+  TFLITE_DCHECK_GE(output_shape.DimensionsCount(), 1);
+
+  TFLITE_DCHECK_LE(output_activation_min, output_activation_max);
+  // TODO(benoitjacob): This really should be:
+  //     const int batches = ArraySize(output_dims, 1);
+  // but the current --variable_batch hack consists in overwriting the 3rd
+  // dimension with the runtime batch size, as we don't keep track for each
+  // array of which dimension is the batch dimension in it.
+  const int output_dim_count = output_shape.DimensionsCount();
+  const int filter_dim_count = filter_shape.DimensionsCount();
+  const int batches = FlatSizeSkipDim(output_shape, output_dim_count - 1);
+  const int output_depth = MatchingDim(filter_shape, filter_dim_count - 2,
+                                       output_shape, output_dim_count - 1);
+  const int accum_depth = filter_shape.Dims(filter_dim_count - 1);
+  for (int b = 0; b < batches; ++b) {
+    for (int out_c = 0; out_c < output_depth; ++out_c) {
+      int32 acc = 0;
+      for (int d = 0; d < accum_depth; ++d) {
+        int32 input_val = input_data[b * accum_depth + d];
+        int32 filter_val = filter_data[out_c * accum_depth + d];
+        acc += (filter_val + filter_offset) * (input_val + input_offset);
+      }
+      if (bias_data) {
+        acc += bias_data[out_c];
+      }
+      acc = MultiplyByQuantizedMultiplier(acc, output_multiplier, output_shift);
+      acc += output_offset;
+      acc = std::max(acc, output_activation_min);
+      acc = std::min(acc, output_activation_max);
+      output_data[out_c + output_depth * b] = static_cast<uint8>(acc);
+    }
+  }
+}
+
+inline void FullyConnected(
+    const FullyConnectedParams& params, const RuntimeShape& input_shape,
+    const uint8* input_data, const RuntimeShape& filter_shape,
+    const uint8* filter_data, const RuntimeShape& bias_shape,
+    const int32* bias_data, const RuntimeShape& output_shape,
+    int16* output_data) {
+  const int32 input_offset = params.input_offset;
+  const int32 filter_offset = params.weights_offset;
+  const int32 output_offset = params.output_offset;
+  const int32 output_multiplier = params.output_multiplier;
+  const int output_shift = params.output_shift;
+  const int32 output_activation_min = params.quantized_activation_min;
+  const int32 output_activation_max = params.quantized_activation_max;
+
+  TFLITE_DCHECK_LE(output_activation_min, output_activation_max);
+  TFLITE_DCHECK_EQ(output_offset, 0);
+  // TODO(benoitjacob): This really should be:
+  //     const int batches = ArraySize(output_dims, 1);
+  // but the current --variable_batch hack consists in overwriting the 3rd
+  // dimension with the runtime batch size, as we don't keep track for each
+  // array of which dimension is the batch dimension in it.
+  const int output_dim_count = output_shape.DimensionsCount();
+  const int filter_dim_count = filter_shape.DimensionsCount();
+  const int batches = FlatSizeSkipDim(output_shape, output_dim_count - 1);
+  const int output_depth = MatchingDim(filter_shape, filter_dim_count - 2,
+                                       output_shape, output_dim_count - 1);
+  const int accum_depth = filter_shape.Dims(filter_dim_count - 1);
+  for (int b = 0; b < batches; ++b) {
+    for (int out_c = 0; out_c < output_depth; ++out_c) {
+      // Internal accumulation.
+      // Initialize accumulator with the bias-value.
+      int32 accum = bias_data[out_c];
+      // Accumulation loop.
+      for (int d = 0; d < accum_depth; ++d) {
+        int16 input_val = input_data[b * accum_depth + d] + input_offset;
+        int16 filter_val = filter_data[out_c * accum_depth + d] + filter_offset;
+        accum += filter_val * input_val;
+      }
+      // Down-scale the final int32 accumulator to the scale used by our
+      // (16-bit, typically 3 integer bits) fixed-point format. The quantized
+      // multiplier and shift here have been pre-computed offline
+      // (e.g. by toco).
+      accum =
+          MultiplyByQuantizedMultiplier(accum, output_multiplier, output_shift);
+      // Saturate, cast to int16, and store to output array.
+      accum = std::max(accum, output_activation_min - output_offset);
+      accum = std::min(accum, output_activation_max - output_offset);
+      accum += output_offset;
+      output_data[out_c + output_depth * b] = accum;
+    }
+  }
+}
+
+inline void ShuffledFullyConnected(
+    const FullyConnectedParams& params, const RuntimeShape& input_shape,
+    const uint8* input_data, const RuntimeShape& weights_shape,
+    const uint8* shuffled_weights_data, const RuntimeShape& bias_shape,
+    const int32* bias_data, const RuntimeShape& output_shape,
+    int16* output_data, uint8* shuffled_input_workspace_data) {
+  const int32 output_multiplier = params.output_multiplier;
+  const int output_shift = params.output_shift;
+  const int32 output_activation_min = params.quantized_activation_min;
+  const int32 output_activation_max = params.quantized_activation_max;
+  TFLITE_DCHECK_LE(output_activation_min, output_activation_max);
+
+  TFLITE_DCHECK_GE(input_shape.DimensionsCount(), 1);
+  TFLITE_DCHECK_GE(weights_shape.DimensionsCount(), 2);
+  TFLITE_DCHECK_GE(output_shape.DimensionsCount(), 1);
+  // TODO(benoitjacob): This really should be:
+  //     const int batches = ArraySize(output_dims, 1);
+  // but the current --variable_batch hack consists in overwriting the 3rd
+  // dimension with the runtime batch size, as we don't keep track for each
+  // array of which dimension is the batch dimension in it.
+  const int output_dim_count = output_shape.DimensionsCount();
+  const int weights_dim_count = weights_shape.DimensionsCount();
+  const int batches = FlatSizeSkipDim(output_shape, output_dim_count - 1);
+  const int output_depth = MatchingDim(weights_shape, weights_dim_count - 2,
+                                       output_shape, output_dim_count - 1);
+  const int accum_depth = weights_shape.Dims(weights_dim_count - 1);
+  TFLITE_DCHECK((accum_depth % 16) == 0);
+  TFLITE_DCHECK((output_depth % 4) == 0);
+
+  // Shuffling and xoring of input activations into the workspace buffer
+  uint8* shuffled_input_workspace_ptr = shuffled_input_workspace_data;
+  if (batches == 1) {
+    for (int i = 0; i < accum_depth; i++) {
+      shuffled_input_workspace_data[i] = input_data[i] ^ 0x80;
+    }
+  } else if (batches == 4) {
+    for (int c = 0; c < accum_depth; c += 16) {
+      for (int b = 0; b < 4; b++) {
+        const uint8* src_data_ptr = input_data + b * accum_depth + c;
+        for (int j = 0; j < 16; j++) {
+          uint8 src_val = *src_data_ptr++;
+          // Flip the sign bit, so that the kernel will only need to
+          // reinterpret these uint8 values as int8, getting for free the
+          // subtraction of the zero_point value 128.
+          uint8 dst_val = src_val ^ 0x80;
+          *shuffled_input_workspace_ptr++ = dst_val;
+        }
+      }
+    }
+  } else {
+    TFLITE_DCHECK(false);
+    return;
+  }
+
+  // Actual computation
+  if (batches == 1) {
+    int16* output_ptr = output_data;
+    // Shuffled weights have had their sign bit (0x80) pre-flipped (xor'd)
+    // so that just reinterpreting them as int8 values is equivalent to
+    // subtracting 128 from them, thus implementing for free the subtraction of
+    // the zero_point value 128.
+    const int8* shuffled_weights_ptr =
+        reinterpret_cast<const int8*>(shuffled_weights_data);
+    // Likewise, we preshuffled and pre-xored the input data above.
+    const int8* shuffled_input_data =
+        reinterpret_cast<const int8*>(shuffled_input_workspace_data);
+    for (int c = 0; c < output_depth; c += 4) {
+      // Internal accumulation.
+      // Initialize accumulator with the bias-value.
+      int32 accum[4] = {0};
+      // Accumulation loop.
+      for (int d = 0; d < accum_depth; d += 16) {
+        for (int i = 0; i < 4; i++) {
+          for (int j = 0; j < 16; j++) {
+            int8 input_val = shuffled_input_data[d + j];
+            int8 weights_val = *shuffled_weights_ptr++;
+            accum[i] += weights_val * input_val;
+          }
+        }
+      }
+      for (int i = 0; i < 4; i++) {
+        // Add bias value
+        int32 acc = accum[i] + bias_data[c + i];
+        // Down-scale the final int32 accumulator to the scale used by our
+        // (16-bit, typically 3 integer bits) fixed-point format. The quantized
+        // multiplier and shift here have been pre-computed offline
+        // (e.g. by toco).
+        acc =
+            MultiplyByQuantizedMultiplier(acc, output_multiplier, output_shift);
+        // Saturate, cast to int16, and store to output array.
+        acc = std::max(acc, output_activation_min);
+        acc = std::min(acc, output_activation_max);
+        output_ptr[c + i] = acc;
+      }
+    }
+  } else if (batches == 4) {
+    int16* output_ptr = output_data;
+    // Shuffled weights have had their sign bit (0x80) pre-flipped (xor'd)
+    // so that just reinterpreting them as int8 values is equivalent to
+    // subtracting 128 from them, thus implementing for free the subtraction of
+    // the zero_point value 128.
+    const int8* shuffled_weights_ptr =
+        reinterpret_cast<const int8*>(shuffled_weights_data);
+    // Likewise, we preshuffled and pre-xored the input data above.
+    const int8* shuffled_input_data =
+        reinterpret_cast<const int8*>(shuffled_input_workspace_data);
+    for (int c = 0; c < output_depth; c += 4) {
+      const int8* shuffled_input_ptr = shuffled_input_data;
+      // Accumulation loop.
+      // Internal accumulation.
+      // Initialize accumulator with the bias-value.
+      int32 accum[4][4];
+      for (int i = 0; i < 4; i++) {
+        for (int b = 0; b < 4; b++) {
+          accum[i][b] = 0;
+        }
+      }
+      for (int d = 0; d < accum_depth; d += 16) {
+        for (int i = 0; i < 4; i++) {
+          for (int b = 0; b < 4; b++) {
+            for (int j = 0; j < 16; j++) {
+              int8 input_val = shuffled_input_ptr[16 * b + j];
+              int8 weights_val = shuffled_weights_ptr[16 * i + j];
+              accum[i][b] += weights_val * input_val;
+            }
+          }
+        }
+        shuffled_input_ptr += 64;
+        shuffled_weights_ptr += 64;
+      }
+      for (int i = 0; i < 4; i++) {
+        for (int b = 0; b < 4; b++) {
+          // Add bias value
+          int32 acc = accum[i][b] + bias_data[c + i];
+          // Down-scale the final int32 accumulator to the scale used by our
+          // (16-bit, typically 3 integer bits) fixed-point format. The
+          // quantized multiplier and shift here have been pre-computed offline
+          // (e.g. by toco).
+          acc = MultiplyByQuantizedMultiplier(acc, output_multiplier,
+                                              output_shift);
+          // Saturate, cast to int16, and store to output array.
+          acc = std::max(acc, output_activation_min);
+          acc = std::min(acc, output_activation_max);
+          output_ptr[b * output_depth + c + i] = acc;
+        }
+      }
+    }
+  } else {
+    TFLITE_DCHECK(false);
+    return;
+  }
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_FULLY_CONNECTED_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/integer_ops/add.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/integer_ops/add.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,143 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_ADD_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_ADD_H_
+
+#include <limits>
+
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+namespace reference_integer_ops {
+
+// Element-wise add that can often be used for inner loop of broadcast add as
+// well as the non-broadcast add.
+inline void AddElementwise(int size, const ArithmeticParams& params,
+                           const int8_t* input1_data, const int8_t* input2_data,
+                           int8_t* output_data) {
+  const int32_t int8_max_value = std::numeric_limits<int8_t>::max();
+  TFLITE_DCHECK_GE(params.input1_offset, -1 * int8_max_value);
+  TFLITE_DCHECK_GE(params.input2_offset, -1 * int8_max_value);
+  TFLITE_DCHECK_LE(params.input1_offset, int8_max_value);
+  TFLITE_DCHECK_LE(params.input2_offset, int8_max_value);
+
+  for (int i = 0; i < size; ++i) {
+    const int32 input1_val = params.input1_offset + input1_data[i];
+    const int32 input2_val = params.input2_offset + input2_data[i];
+    const int32 shifted_input1_val = input1_val * (1 << params.left_shift);
+    const int32 shifted_input2_val = input2_val * (1 << params.left_shift);
+    const int32 scaled_input1_val =
+        MultiplyByQuantizedMultiplierSmallerThanOneExp(
+            shifted_input1_val, params.input1_multiplier, params.input1_shift);
+    const int32 scaled_input2_val =
+        MultiplyByQuantizedMultiplierSmallerThanOneExp(
+            shifted_input2_val, params.input2_multiplier, params.input2_shift);
+    const int32 raw_sum = scaled_input1_val + scaled_input2_val;
+    const int32 raw_output =
+        MultiplyByQuantizedMultiplierSmallerThanOneExp(
+            raw_sum, params.output_multiplier, params.output_shift) +
+        params.output_offset;
+    const int32 clamped_output =
+        std::min(params.quantized_activation_max,
+                 std::max(params.quantized_activation_min, raw_output));
+    output_data[i] = static_cast<int8_t>(clamped_output);
+  }
+}
+
+inline void Add(const ArithmeticParams& params,
+                const RuntimeShape& input1_shape, const int8_t* input1_data,
+                const RuntimeShape& input2_shape, const int8_t* input2_data,
+                const RuntimeShape& output_shape, int8_t* output_data) {
+  TFLITE_DCHECK_LE(params.quantized_activation_min,
+                   params.quantized_activation_max);
+  const int flat_size =
+      MatchingElementsSize(input1_shape, input2_shape, output_shape);
+
+  const int32_t int8_max_value = std::numeric_limits<int8_t>::max();
+  TFLITE_DCHECK_GE(params.input1_offset, -1 * int8_max_value);
+  TFLITE_DCHECK_GE(params.input2_offset, -1 * int8_max_value);
+  TFLITE_DCHECK_LE(params.input1_offset, int8_max_value);
+  TFLITE_DCHECK_LE(params.input2_offset, int8_max_value);
+  AddElementwise(flat_size, params, input1_data, input2_data, output_data);
+}
+
+inline void BroadcastAdd4DSlow(const ArithmeticParams& params,
+                               const RuntimeShape& input1_shape,
+                               const int8_t* input1_data,
+                               const RuntimeShape& input2_shape,
+                               const int8_t* input2_data,
+                               const RuntimeShape& output_shape,
+                               int8_t* output_data) {
+  NdArrayDesc<4> desc1;
+  NdArrayDesc<4> desc2;
+  NdArrayDescsForElementwiseBroadcast(input1_shape, input2_shape, &desc1,
+                                      &desc2);
+  const RuntimeShape extended_output_shape =
+      RuntimeShape::ExtendedShape(4, output_shape);
+
+  // In Tensorflow, the dimensions are canonically named (batch_number, row,
+  // col, channel), with extents (batches, height, width, depth), with the
+  // trailing dimension changing most rapidly (channels has the smallest stride,
+  // typically 1 element).
+  //
+  // In generated C code, we store arrays with the dimensions reversed. The
+  // first dimension has smallest stride.
+  //
+  // We name our variables by their Tensorflow convention, but generate C code
+  // nesting loops such that the innermost loop has the smallest stride for the
+  // best cache behavior.
+  for (int b = 0; b < extended_output_shape.Dims(0); ++b) {
+    for (int y = 0; y < extended_output_shape.Dims(1); ++y) {
+      for (int x = 0; x < extended_output_shape.Dims(2); ++x) {
+        for (int c = 0; c < extended_output_shape.Dims(3); ++c) {
+          const int32_t input1_val =
+              params.input1_offset +
+              input1_data[SubscriptToIndex(desc1, b, y, x, c)];
+          const int32_t input2_val =
+              params.input2_offset +
+              input2_data[SubscriptToIndex(desc2, b, y, x, c)];
+          const int32_t shifted_input1_val =
+              input1_val * (1 << params.left_shift);
+          const int32_t shifted_input2_val =
+              input2_val * (1 << params.left_shift);
+          const int32_t scaled_input1_val =
+              MultiplyByQuantizedMultiplierSmallerThanOneExp(
+                  shifted_input1_val, params.input1_multiplier,
+                  params.input1_shift);
+          const int32_t scaled_input2_val =
+              MultiplyByQuantizedMultiplierSmallerThanOneExp(
+                  shifted_input2_val, params.input2_multiplier,
+                  params.input2_shift);
+          const int32_t raw_sum = scaled_input1_val + scaled_input2_val;
+          const int32_t raw_output =
+              MultiplyByQuantizedMultiplierSmallerThanOneExp(
+                  raw_sum, params.output_multiplier, params.output_shift) +
+              params.output_offset;
+          const int32_t clamped_output =
+              std::min(params.quantized_activation_max,
+                       std::max(params.quantized_activation_min, raw_output));
+          output_data[Offset(extended_output_shape, b, y, x, c)] =
+              static_cast<int8_t>(clamped_output);
+        }
+      }
+    }
+  }
+}
+
+}  // namespace reference_integer_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_ADD_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/integer_ops/conv.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/integer_ops/conv.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,128 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_CONV_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_CONV_H_
+
+#include "tensorflow/lite/kernels/internal/common.h"
+
+namespace tflite {
+namespace reference_integer_ops {
+
+// Fixed-point per-channel-quantization convolution reference kernel.
+inline void ConvPerChannel(
+    const ConvParams& params, const int32* output_multiplier,
+    const int32* output_shift, const RuntimeShape& input_shape,
+    const int8* input_data, const RuntimeShape& filter_shape,
+    const int8* filter_data, const RuntimeShape& bias_shape,
+    const int32* bias_data, const RuntimeShape& output_shape,
+    int8* output_data) {
+  // Get parameters.
+  const int32 input_offset = params.input_offset;  // r = s(q - Z)
+  const int stride_width = params.stride_width;
+  const int stride_height = params.stride_height;
+  const int dilation_width_factor = params.dilation_width_factor;
+  const int dilation_height_factor = params.dilation_height_factor;
+  const int pad_width = params.padding_values.width;
+  const int pad_height = params.padding_values.height;
+  const int32 output_offset = params.output_offset;
+
+  // Set min and max value of the output.
+  const int32 output_activation_min = std::numeric_limits<int8_t>::min();
+  const int32 output_activation_max = std::numeric_limits<int8_t>::max();
+
+  // Sanity check.
+  TFLITE_DCHECK_LE(output_activation_min, output_activation_max);
+  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(filter_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+  const int input_depth = MatchingDim(input_shape, 3, filter_shape, 3);
+  const int output_depth = MatchingDim(filter_shape, 0, output_shape, 3);
+  if (bias_data) {
+    TFLITE_DCHECK_EQ(bias_shape.FlatSize(), output_depth);
+  }
+
+  // Check dimensions of the tensors.
+  const int input_height = input_shape.Dims(1);
+  const int input_width = input_shape.Dims(2);
+  const int filter_height = filter_shape.Dims(1);
+  const int filter_width = filter_shape.Dims(2);
+  const int output_height = output_shape.Dims(1);
+  const int output_width = output_shape.Dims(2);
+  for (int batch = 0; batch < batches; ++batch) {
+    for (int out_y = 0; out_y < output_height; ++out_y) {
+      for (int out_x = 0; out_x < output_width; ++out_x) {
+        for (int out_channel = 0; out_channel < output_depth; ++out_channel) {
+          const int in_x_origin = (out_x * stride_width) - pad_width;
+          const int in_y_origin = (out_y * stride_height) - pad_height;
+          int32 acc = 0;
+          for (int filter_y = 0; filter_y < filter_height; ++filter_y) {
+            for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
+              for (int in_channel = 0; in_channel < input_depth; ++in_channel) {
+                const int in_x = in_x_origin + dilation_width_factor * filter_x;
+                const int in_y =
+                    in_y_origin + dilation_height_factor * filter_y;
+                // Zero padding by omitting the areas outside the image.
+                const bool is_point_inside_image =
+                    (in_x >= 0) && (in_x < input_width) && (in_y >= 0) &&
+                    (in_y < input_height);
+                if (is_point_inside_image) {
+                  int32 input_val = input_data[Offset(input_shape, batch, in_y,
+                                                      in_x, in_channel)];
+                  int32 filter_val =
+                      filter_data[Offset(filter_shape, out_channel, filter_y,
+                                         filter_x, in_channel)];
+                  // Accumulate with 32 bits accumulator.
+                  // In the nudging process during model quantization, we force
+                  // real value of 0.0 be represented by a quantized value. This
+                  // guarantees that the input_offset is a int8, even though it
+                  // is represented using int32.
+                  // int32 += int8 * (int8 - int8) so the highest value we can
+                  // get from each accumulation is [-127, 127] * ([-128, 127] -
+                  // [-128, 127]), which is [-32512, 32512]. log2(32512)
+                  // = 14.98, which means we can accumulate at least 2^16
+                  // multiplications without overflow. The accumulator is
+                  // applied to a filter so the accumulation logic will hold as
+                  // long as the filter size (filter_y * filter_x * in_channel)
+                  // does not exceed 2^16, which is the case in all the models
+                  // we have seen so far.
+                  // TODO(jianlijianli): Add a check to make sure the
+                  // accumulator depth is smaller than 2^16.
+                  acc += filter_val * (input_val + input_offset);
+                }
+              }
+            }
+          }
+
+          if (bias_data) {
+            acc += bias_data[out_channel];
+          }
+          acc = MultiplyByQuantizedMultiplier(
+              acc, output_multiplier[out_channel], output_shift[out_channel]);
+          acc += output_offset;
+          acc = std::max(acc, output_activation_min);
+          acc = std::min(acc, output_activation_max);
+          output_data[Offset(output_shape, batch, out_y, out_x, out_channel)] =
+              static_cast<int8_t>(acc);
+        }
+      }
+    }
+  }
+}
+
+}  // namespace reference_integer_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_CONV_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/integer_ops/depthwise_conv.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/integer_ops/depthwise_conv.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,124 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_DEPTHWISE_CONV_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_DEPTHWISE_CONV_H_
+
+#include "tensorflow/lite/kernels/internal/common.h"
+
+namespace tflite {
+namespace reference_integer_ops {
+inline void DepthwiseConvPerChannel(
+    const DepthwiseParams& params, const int32* output_multiplier,
+    const int32* output_shift, const RuntimeShape& input_shape,
+    const int8* input_data, const RuntimeShape& filter_shape,
+    const int8* filter_data, const RuntimeShape& bias_shape,
+    const int32* bias_data, const RuntimeShape& output_shape,
+    int8* output_data) {
+  // Get parameters.
+  // TODO(b/141565753): Re-introduce ScopedProfilingLabel on Micro.
+  const int stride_width = params.stride_width;
+  const int stride_height = params.stride_height;
+  const int dilation_width_factor = params.dilation_width_factor;
+  const int dilation_height_factor = params.dilation_height_factor;
+  const int pad_width = params.padding_values.width;
+  const int pad_height = params.padding_values.height;
+  const int depth_multiplier = params.depth_multiplier;
+  const int32 input_offset = params.input_offset;
+  const int32 output_offset = params.output_offset;
+  const int32 output_activation_min = params.quantized_activation_min;
+  const int32 output_activation_max = params.quantized_activation_max;
+
+  // Check dimensions of the tensors.
+  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(filter_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+
+  TFLITE_DCHECK_LE(output_activation_min, output_activation_max);
+  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+  const int output_depth = MatchingDim(filter_shape, 3, output_shape, 3);
+  const int input_height = input_shape.Dims(1);
+  const int input_width = input_shape.Dims(2);
+  const int input_depth = input_shape.Dims(3);
+  const int filter_height = filter_shape.Dims(1);
+  const int filter_width = filter_shape.Dims(2);
+  const int output_height = output_shape.Dims(1);
+  const int output_width = output_shape.Dims(2);
+  TFLITE_DCHECK_EQ(output_depth, input_depth * depth_multiplier);
+  TFLITE_DCHECK_EQ(bias_shape.FlatSize(), output_depth);
+
+  for (int batch = 0; batch < batches; ++batch) {
+    for (int out_y = 0; out_y < output_height; ++out_y) {
+      for (int out_x = 0; out_x < output_width; ++out_x) {
+        for (int in_channel = 0; in_channel < input_depth; ++in_channel) {
+          for (int m = 0; m < depth_multiplier; ++m) {
+            const int output_channel = m + in_channel * depth_multiplier;
+            const int in_x_origin = (out_x * stride_width) - pad_width;
+            const int in_y_origin = (out_y * stride_height) - pad_height;
+            int32 acc = 0;
+            for (int filter_y = 0; filter_y < filter_height; ++filter_y) {
+              for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
+                const int in_x = in_x_origin + dilation_width_factor * filter_x;
+                const int in_y =
+                    in_y_origin + dilation_height_factor * filter_y;
+                // Zero padding by omitting the areas outside the image.
+                const bool is_point_inside_image =
+                    (in_x >= 0) && (in_x < input_width) && (in_y >= 0) &&
+                    (in_y < input_height);
+                if (is_point_inside_image) {
+                  int32 input_val = input_data[Offset(input_shape, batch, in_y,
+                                                      in_x, in_channel)];
+                  int32 filter_val = filter_data[Offset(
+                      filter_shape, 0, filter_y, filter_x, output_channel)];
+                  // Accumulate with 32 bits accumulator.
+                  // In the nudging process during model quantization, we force
+                  // real value of 0.0 be represented by a quantized value. This
+                  // guarentees that the input_offset is a int8, even though it
+                  // is represented using int32.
+                  // int32 += int8 * (int8 - int8) so the highest value we can
+                  // get from each accumulation is [-127, 127] * ([-128, 127] -
+                  // [-128, 127]), which is [-32512, 32512]. log2(32512)
+                  // = 14.98, which means we can accumulate at least 2^16
+                  // multiplications without overflow. The accumulator is
+                  // applied to a filter so the accumulation logic will hold as
+                  // long as the filter size (filter_y * filter_x * in_channel)
+                  // does not exceed 2^16, which is the case in all the models
+                  // we have seen so far.
+                  // TODO(jianlijianli): Add a check to make sure the
+                  // accumulator depth is smaller than 2^16.
+                  acc += filter_val * (input_val + input_offset);
+                }
+              }
+            }
+            if (bias_data) {
+              acc += bias_data[output_channel];
+            }
+            acc = MultiplyByQuantizedMultiplier(
+                acc, output_multiplier[output_channel],
+                output_shift[output_channel]);
+            acc += output_offset;
+            acc = std::max(acc, output_activation_min);
+            acc = std::min(acc, output_activation_max);
+            output_data[Offset(output_shape, batch, out_y, out_x,
+                               output_channel)] = static_cast<int8_t>(acc);
+          }
+        }
+      }
+    }
+  }
+}
+}  // namespace reference_integer_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_DEPTHWISE_CONV_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/integer_ops/fully_connected.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/integer_ops/fully_connected.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,68 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_FULLY_CONNECTED_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_FULLY_CONNECTED_H_
+
+#include "tensorflow/lite/kernels/internal/common.h"
+
+namespace tflite {
+namespace reference_integer_ops {
+
+inline void FullyConnected(
+    const FullyConnectedParams& params, const RuntimeShape& input_shape,
+    const int8_t* input_data, const RuntimeShape& filter_shape,
+    const int8_t* filter_data, const RuntimeShape& bias_shape,
+    const int32* bias_data, const RuntimeShape& output_shape,
+    int8_t* output_data) {
+  const int32 input_offset = params.input_offset;
+  const int32 filter_offset = params.weights_offset;
+  const int32 output_offset = params.output_offset;
+  const int32 output_multiplier = params.output_multiplier;
+  const int output_shift = params.output_shift;
+  const int32 output_activation_min = params.quantized_activation_min;
+  const int32 output_activation_max = params.quantized_activation_max;
+  TFLITE_DCHECK_GE(filter_shape.DimensionsCount(), 2);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 2);
+
+  TFLITE_DCHECK_LE(output_activation_min, output_activation_max);
+  const int filter_dim_count = filter_shape.DimensionsCount();
+  const int batches = output_shape.Dims(0);
+  const int output_depth = output_shape.Dims(1);
+  TFLITE_DCHECK_LE(output_depth, filter_shape.Dims(filter_dim_count - 2));
+  const int accum_depth = filter_shape.Dims(filter_dim_count - 1);
+  for (int b = 0; b < batches; ++b) {
+    for (int out_c = 0; out_c < output_depth; ++out_c) {
+      int32 acc = 0;
+      for (int d = 0; d < accum_depth; ++d) {
+        int32 input_val = input_data[b * accum_depth + d];
+        int32 filter_val = filter_data[out_c * accum_depth + d];
+        acc += (filter_val + filter_offset) * (input_val + input_offset);
+      }
+      if (bias_data) {
+        acc += bias_data[out_c];
+      }
+      acc = MultiplyByQuantizedMultiplier(acc, output_multiplier, output_shift);
+      acc += output_offset;
+      acc = std::max(acc, output_activation_min);
+      acc = std::min(acc, output_activation_max);
+      output_data[out_c + output_depth * b] = static_cast<int8_t>(acc);
+    }
+  }
+}
+
+}  // namespace reference_integer_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_FULLY_CONNECTED_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/integer_ops/pooling.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/integer_ops/pooling.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,141 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_POOLING_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_POOLING_H_
+
+#include <limits>
+#include "tensorflow/lite/kernels/internal/common.h"
+
+namespace tflite {
+namespace reference_integer_ops {
+
+inline void AveragePool(const PoolParams& params,
+                        const RuntimeShape& input_shape, const int8* input_data,
+                        const RuntimeShape& output_shape, int8* output_data) {
+  TFLITE_DCHECK_LE(params.quantized_activation_min,
+                   params.quantized_activation_max);
+  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+  const int depth = MatchingDim(input_shape, 3, output_shape, 3);
+  const int input_height = input_shape.Dims(1);
+  const int input_width = input_shape.Dims(2);
+  const int output_height = output_shape.Dims(1);
+  const int output_width = output_shape.Dims(2);
+  const int stride_height = params.stride_height;
+  const int stride_width = params.stride_width;
+  for (int batch = 0; batch < batches; ++batch) {
+    for (int out_y = 0; out_y < output_height; ++out_y) {
+      for (int out_x = 0; out_x < output_width; ++out_x) {
+        for (int channel = 0; channel < depth; ++channel) {
+          const int in_x_origin =
+              (out_x * stride_width) - params.padding_values.width;
+          const int in_y_origin =
+              (out_y * stride_height) - params.padding_values.height;
+          // Compute the boundaries of the filter region clamped so as to
+          // ensure that the filter window fits in the input array.
+          const int filter_x_start = std::max(0, -in_x_origin);
+          const int filter_x_end =
+              std::min(params.filter_width, input_width - in_x_origin);
+          const int filter_y_start = std::max(0, -in_y_origin);
+          const int filter_y_end =
+              std::min(params.filter_height, input_height - in_y_origin);
+          int32 acc = 0;
+          int filter_count = 0;
+          for (int filter_y = filter_y_start; filter_y < filter_y_end;
+               ++filter_y) {
+            for (int filter_x = filter_x_start; filter_x < filter_x_end;
+                 ++filter_x) {
+              const int in_x = in_x_origin + filter_x;
+              const int in_y = in_y_origin + filter_y;
+              acc +=
+                  input_data[Offset(input_shape, batch, in_y, in_x, channel)];
+              filter_count++;
+            }
+          }
+          // Round to the closest integer value.
+          acc = acc > 0 ? (acc + filter_count / 2) / filter_count
+                        : (acc - filter_count / 2) / filter_count;
+          acc = std::max(acc, params.quantized_activation_min);
+          acc = std::min(acc, params.quantized_activation_max);
+          output_data[Offset(output_shape, batch, out_y, out_x, channel)] =
+              static_cast<int8>(acc);
+        }
+      }
+    }
+  }
+}
+
+inline void MaxPool(const PoolParams& params, const RuntimeShape& input_shape,
+                    const int8* input_data, const RuntimeShape& output_shape,
+                    int8* output_data) {
+  TFLITE_DCHECK_LE(params.quantized_activation_min,
+                   params.quantized_activation_max);
+  TFLITE_DCHECK_GE(params.quantized_activation_min,
+                   std::numeric_limits<int8_t>::min());
+  TFLITE_DCHECK_LE(params.quantized_activation_max,
+                   std::numeric_limits<int8_t>::max());
+  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+  const int depth = MatchingDim(input_shape, 3, output_shape, 3);
+  const int input_height = input_shape.Dims(1);
+  const int input_width = input_shape.Dims(2);
+  const int output_height = output_shape.Dims(1);
+  const int output_width = output_shape.Dims(2);
+  const int stride_height = params.stride_height;
+  const int stride_width = params.stride_width;
+  for (int batch = 0; batch < batches; ++batch) {
+    for (int out_y = 0; out_y < output_height; ++out_y) {
+      for (int out_x = 0; out_x < output_width; ++out_x) {
+        for (int channel = 0; channel < depth; ++channel) {
+          const int in_x_origin =
+              (out_x * stride_width) - params.padding_values.width;
+          const int in_y_origin =
+              (out_y * stride_height) - params.padding_values.height;
+          // Compute the boundaries of the filter region clamped so as to
+          // ensure that the filter window fits in the input array.
+          const int filter_x_start = std::max(0, -in_x_origin);
+          const int filter_x_end =
+              std::min(params.filter_width, input_width - in_x_origin);
+          const int filter_y_start = std::max(0, -in_y_origin);
+          const int filter_y_end =
+              std::min(params.filter_height, input_height - in_y_origin);
+          int8_t max = std::numeric_limits<int8_t>::lowest();
+          for (int filter_y = filter_y_start; filter_y < filter_y_end;
+               ++filter_y) {
+            for (int filter_x = filter_x_start; filter_x < filter_x_end;
+                 ++filter_x) {
+              const int in_x = in_x_origin + filter_x;
+              const int in_y = in_y_origin + filter_y;
+              max = std::max(
+                  max,
+                  input_data[Offset(input_shape, batch, in_y, in_x, channel)]);
+            }
+          }
+          max = std::max<int8_t>(max, params.quantized_activation_min);
+          max = std::min<int8_t>(max, params.quantized_activation_max);
+          output_data[Offset(output_shape, batch, out_y, out_x, channel)] =
+              static_cast<int8_t>(max);
+        }
+      }
+    }
+  }
+}
+
+}  // namespace reference_integer_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_POOLING_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/logistic.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/logistic.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,70 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_LOGISTIC_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_LOGISTIC_H_
+
+#include "fixedpoint/fixedpoint.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/round.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+
+namespace tflite {
+namespace reference_ops {
+
+inline void Logistic(const RuntimeShape& input_shape, const float* input_data,
+                     const RuntimeShape& output_shape, float* output_data) {
+  const int flat_size = MatchingFlatSize(input_shape, output_shape);
+
+  for (int i = 0; i < flat_size; i++) {
+    float val = input_data[i];
+    float result = 1.f / (1.f + std::exp(-val));
+    output_data[i] = result;
+  }
+}
+
+// Convenience version that allows, for example, generated-code calls to be
+// uniform between data types.
+inline void Logistic(const LogisticParams&, const RuntimeShape& input_shape,
+                     const float* input_data, const RuntimeShape& output_shape,
+                     float* output_data) {
+  // Drop params: not needed.
+  Logistic(input_shape, input_data, output_shape, output_data);
+}
+
+inline void Logistic(const LogisticParams& params,
+                     const RuntimeShape& input_shape, const int16* input_data,
+                     const RuntimeShape& output_shape, int16* output_data) {
+  const int flat_size = MatchingFlatSize(input_shape, output_shape);
+
+  for (int i = 0; i < flat_size; i++) {
+    // F0 uses 0 integer bits, range [-1, 1].
+    // This is the return type of math functions such as tanh, logistic,
+    // whose range is in [-1, 1].
+    using F0 = gemmlowp::FixedPoint<std::int16_t, 0>;
+    // F3 uses 3 integer bits, range [-8, 8], the input range expected here.
+    using F3 = gemmlowp::FixedPoint<std::int16_t, 3>;
+
+    const F3 input = F3::FromRaw(input_data[i]);
+    F0 output = gemmlowp::logistic(input);
+    output_data[i] = output.raw();
+  }
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_LOGISTIC_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/maximum_minimum.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/maximum_minimum.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,61 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_MAXIMUM_MINIMUM_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_MAXIMUM_MINIMUM_H_
+
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+namespace reference_ops {
+
+template <typename T, typename Op>
+void MaximumMinimumBroadcast4DSlow(const RuntimeShape& unextended_input1_shape,
+                                   const T* input1_data,
+                                   const RuntimeShape& unextended_input2_shape,
+                                   const T* input2_data,
+                                   const RuntimeShape& unextended_output_shape,
+                                   T* output_data, Op op) {
+  TFLITE_DCHECK_LE(unextended_input1_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_LE(unextended_input2_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_LE(unextended_output_shape.DimensionsCount(), 4);
+  const RuntimeShape output_shape =
+      RuntimeShape::ExtendedShape(4, unextended_output_shape);
+
+  NdArrayDesc<4> desc1;
+  NdArrayDesc<4> desc2;
+  NdArrayDescsForElementwiseBroadcast(unextended_input1_shape,
+                                      unextended_input2_shape, &desc1, &desc2);
+
+  for (int b = 0; b < output_shape.Dims(0); ++b) {
+    for (int y = 0; y < output_shape.Dims(1); ++y) {
+      for (int x = 0; x < output_shape.Dims(2); ++x) {
+        for (int c = 0; c < output_shape.Dims(3); ++c) {
+          auto out_idx = Offset(output_shape, b, y, x, c);
+          auto in1_idx = SubscriptToIndex(desc1, b, y, x, c);
+          auto in2_idx = SubscriptToIndex(desc2, b, y, x, c);
+          auto in1_val = input1_data[in1_idx];
+          auto in2_val = input2_data[in2_idx];
+          output_data[out_idx] = op(in1_val, in2_val);
+        }
+      }
+    }
+  }
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_MAXIMUM_MINIMUM_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/neg.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/neg.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,37 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_NEG_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_NEG_H_
+
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+namespace reference_ops {
+
+template <typename T>
+inline void Negate(const RuntimeShape& input_shape, const T* input_data,
+                   const RuntimeShape& output_shape, T* output_data) {
+  const int flat_size = MatchingFlatSize(input_shape, output_shape);
+
+  for (int i = 0; i < flat_size; ++i) {
+    output_data[i] = -input_data[i];
+  }
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_NEG_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/pooling.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/pooling.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,296 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_POOLING_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_POOLING_H_
+
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/round.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+namespace reference_ops {
+
+inline void AveragePool(const PoolParams& params,
+                        const RuntimeShape& input_shape,
+                        const float* input_data,
+                        const RuntimeShape& output_shape, float* output_data) {
+  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+  const int depth = MatchingDim(input_shape, 3, output_shape, 3);
+  const int input_height = input_shape.Dims(1);
+  const int input_width = input_shape.Dims(2);
+  const int output_height = output_shape.Dims(1);
+  const int output_width = output_shape.Dims(2);
+  const int stride_height = params.stride_height;
+  const int stride_width = params.stride_width;
+  for (int batch = 0; batch < batches; ++batch) {
+    for (int out_y = 0; out_y < output_height; ++out_y) {
+      for (int out_x = 0; out_x < output_width; ++out_x) {
+        for (int channel = 0; channel < depth; ++channel) {
+          const int in_x_origin =
+              (out_x * stride_width) - params.padding_values.width;
+          const int in_y_origin =
+              (out_y * stride_height) - params.padding_values.height;
+          // Compute the boundaries of the filter region clamped so as to
+          // ensure that the filter window fits in the input array.
+          const int filter_x_start = std::max(0, -in_x_origin);
+          const int filter_x_end =
+              std::min(params.filter_width, input_width - in_x_origin);
+          const int filter_y_start = std::max(0, -in_y_origin);
+          const int filter_y_end =
+              std::min(params.filter_height, input_height - in_y_origin);
+          float total = 0.f;
+          float filter_count = 0;
+          for (int filter_y = filter_y_start; filter_y < filter_y_end;
+               ++filter_y) {
+            for (int filter_x = filter_x_start; filter_x < filter_x_end;
+                 ++filter_x) {
+              const int in_x = in_x_origin + filter_x;
+              const int in_y = in_y_origin + filter_y;
+              total +=
+                  input_data[Offset(input_shape, batch, in_y, in_x, channel)];
+              filter_count++;
+            }
+          }
+          const float average = total / filter_count;
+          output_data[Offset(output_shape, batch, out_y, out_x, channel)] =
+              ActivationFunctionWithMinMax(average, params.float_activation_min,
+                                           params.float_activation_max);
+        }
+      }
+    }
+  }
+}
+
+inline void AveragePool(const PoolParams& params,
+                        const RuntimeShape& input_shape,
+                        const uint8* input_data,
+                        const RuntimeShape& output_shape, uint8* output_data) {
+  TFLITE_DCHECK_LE(params.quantized_activation_min,
+                   params.quantized_activation_max);
+  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+  const int depth = MatchingDim(input_shape, 3, output_shape, 3);
+  const int input_height = input_shape.Dims(1);
+  const int input_width = input_shape.Dims(2);
+  const int output_height = output_shape.Dims(1);
+  const int output_width = output_shape.Dims(2);
+  const int stride_height = params.stride_height;
+  const int stride_width = params.stride_width;
+  for (int batch = 0; batch < batches; ++batch) {
+    for (int out_y = 0; out_y < output_height; ++out_y) {
+      for (int out_x = 0; out_x < output_width; ++out_x) {
+        for (int channel = 0; channel < depth; ++channel) {
+          const int in_x_origin =
+              (out_x * stride_width) - params.padding_values.width;
+          const int in_y_origin =
+              (out_y * stride_height) - params.padding_values.height;
+          // Compute the boundaries of the filter region clamped so as to
+          // ensure that the filter window fits in the input array.
+          const int filter_x_start = std::max(0, -in_x_origin);
+          const int filter_x_end =
+              std::min(params.filter_width, input_width - in_x_origin);
+          const int filter_y_start = std::max(0, -in_y_origin);
+          const int filter_y_end =
+              std::min(params.filter_height, input_height - in_y_origin);
+          int32 acc = 0;
+          int filter_count = 0;
+          for (int filter_y = filter_y_start; filter_y < filter_y_end;
+               ++filter_y) {
+            for (int filter_x = filter_x_start; filter_x < filter_x_end;
+                 ++filter_x) {
+              const int in_x = in_x_origin + filter_x;
+              const int in_y = in_y_origin + filter_y;
+              acc +=
+                  input_data[Offset(input_shape, batch, in_y, in_x, channel)];
+              filter_count++;
+            }
+          }
+          acc = (acc + filter_count / 2) / filter_count;
+          acc = std::max(acc, params.quantized_activation_min);
+          acc = std::min(acc, params.quantized_activation_max);
+          output_data[Offset(output_shape, batch, out_y, out_x, channel)] =
+              static_cast<uint8>(acc);
+        }
+      }
+    }
+  }
+}
+
+inline void L2Pool(const PoolParams& params, const RuntimeShape& input_shape,
+                   const float* input_data, const RuntimeShape& output_shape,
+                   float* output_data) {
+  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+  const int depth = MatchingDim(input_shape, 3, output_shape, 3);
+  const int input_height = input_shape.Dims(1);
+  const int input_width = input_shape.Dims(2);
+  const int output_height = output_shape.Dims(1);
+  const int output_width = output_shape.Dims(2);
+  const int stride_height = params.stride_height;
+  const int stride_width = params.stride_width;
+  for (int batch = 0; batch < batches; ++batch) {
+    for (int out_y = 0; out_y < output_height; ++out_y) {
+      for (int out_x = 0; out_x < output_width; ++out_x) {
+        for (int channel = 0; channel < depth; ++channel) {
+          const int in_x_origin =
+              (out_x * stride_width) - params.padding_values.width;
+          const int in_y_origin =
+              (out_y * stride_height) - params.padding_values.height;
+          // Compute the boundaries of the filter region clamped so as to
+          // ensure that the filter window fits in the input array.
+          const int filter_x_start = std::max(0, -in_x_origin);
+          const int filter_x_end =
+              std::min(params.filter_width, input_width - in_x_origin);
+          const int filter_y_start = std::max(0, -in_y_origin);
+          const int filter_y_end =
+              std::min(params.filter_height, input_height - in_y_origin);
+          float sum_squares = 0.f;
+          int filter_count = 0;
+          for (int filter_y = filter_y_start; filter_y < filter_y_end;
+               ++filter_y) {
+            for (int filter_x = filter_x_start; filter_x < filter_x_end;
+                 ++filter_x) {
+              const int in_x = in_x_origin + filter_x;
+              const int in_y = in_y_origin + filter_y;
+              const float val =
+                  input_data[Offset(input_shape, batch, in_y, in_x, channel)];
+              sum_squares += val * val;
+              filter_count++;
+            }
+          }
+          const float l2pool_result = std::sqrt(sum_squares / filter_count);
+          output_data[Offset(output_shape, batch, out_y, out_x, channel)] =
+              ActivationFunctionWithMinMax(l2pool_result,
+                                           params.float_activation_min,
+                                           params.float_activation_max);
+        }
+      }
+    }
+  }
+}
+
+inline void MaxPool(const PoolParams& params, const RuntimeShape& input_shape,
+                    const float* input_data, const RuntimeShape& output_shape,
+                    float* output_data) {
+  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+  const int depth = MatchingDim(input_shape, 3, output_shape, 3);
+  const int input_height = input_shape.Dims(1);
+  const int input_width = input_shape.Dims(2);
+  const int output_height = output_shape.Dims(1);
+  const int output_width = output_shape.Dims(2);
+  const int stride_height = params.stride_height;
+  const int stride_width = params.stride_width;
+  for (int batch = 0; batch < batches; ++batch) {
+    for (int out_y = 0; out_y < output_height; ++out_y) {
+      for (int out_x = 0; out_x < output_width; ++out_x) {
+        for (int channel = 0; channel < depth; ++channel) {
+          const int in_x_origin =
+              (out_x * stride_width) - params.padding_values.width;
+          const int in_y_origin =
+              (out_y * stride_height) - params.padding_values.height;
+          // Compute the boundaries of the filter region clamped so as to
+          // ensure that the filter window fits in the input array.
+          const int filter_x_start = std::max(0, -in_x_origin);
+          const int filter_x_end =
+              std::min(params.filter_width, input_width - in_x_origin);
+          const int filter_y_start = std::max(0, -in_y_origin);
+          const int filter_y_end =
+              std::min(params.filter_height, input_height - in_y_origin);
+          float max = std::numeric_limits<float>::lowest();
+          for (int filter_y = filter_y_start; filter_y < filter_y_end;
+               ++filter_y) {
+            for (int filter_x = filter_x_start; filter_x < filter_x_end;
+                 ++filter_x) {
+              const int in_x = in_x_origin + filter_x;
+              const int in_y = in_y_origin + filter_y;
+              max = std::max(
+                  max,
+                  input_data[Offset(input_shape, batch, in_y, in_x, channel)]);
+            }
+          }
+          output_data[Offset(output_shape, batch, out_y, out_x, channel)] =
+              ActivationFunctionWithMinMax(max, params.float_activation_min,
+                                           params.float_activation_max);
+        }
+      }
+    }
+  }
+}
+
+inline void MaxPool(const PoolParams& params, const RuntimeShape& input_shape,
+                    const uint8* input_data, const RuntimeShape& output_shape,
+                    uint8* output_data) {
+  TFLITE_DCHECK_LE(params.quantized_activation_min,
+                   params.quantized_activation_max);
+  TFLITE_DCHECK_GE(params.quantized_activation_min, 0);
+  TFLITE_DCHECK_LE(params.quantized_activation_max, 255);
+  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);
+  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
+  const int depth = MatchingDim(input_shape, 3, output_shape, 3);
+  const int input_height = input_shape.Dims(1);
+  const int input_width = input_shape.Dims(2);
+  const int output_height = output_shape.Dims(1);
+  const int output_width = output_shape.Dims(2);
+  const int stride_height = params.stride_height;
+  const int stride_width = params.stride_width;
+  for (int batch = 0; batch < batches; ++batch) {
+    for (int out_y = 0; out_y < output_height; ++out_y) {
+      for (int out_x = 0; out_x < output_width; ++out_x) {
+        for (int channel = 0; channel < depth; ++channel) {
+          const int in_x_origin =
+              (out_x * stride_width) - params.padding_values.width;
+          const int in_y_origin =
+              (out_y * stride_height) - params.padding_values.height;
+          // Compute the boundaries of the filter region clamped so as to
+          // ensure that the filter window fits in the input array.
+          const int filter_x_start = std::max(0, -in_x_origin);
+          const int filter_x_end =
+              std::min(params.filter_width, input_width - in_x_origin);
+          const int filter_y_start = std::max(0, -in_y_origin);
+          const int filter_y_end =
+              std::min(params.filter_height, input_height - in_y_origin);
+          uint8 max = 0;
+          for (int filter_y = filter_y_start; filter_y < filter_y_end;
+               ++filter_y) {
+            for (int filter_x = filter_x_start; filter_x < filter_x_end;
+                 ++filter_x) {
+              const int in_x = in_x_origin + filter_x;
+              const int in_y = in_y_origin + filter_y;
+              max = std::max(
+                  max,
+                  input_data[Offset(input_shape, batch, in_y, in_x, channel)]);
+            }
+          }
+          max = std::max<uint8>(max, params.quantized_activation_min);
+          max = std::min<uint8>(max, params.quantized_activation_max);
+          output_data[Offset(output_shape, batch, out_y, out_x, channel)] =
+              static_cast<uint8>(max);
+        }
+      }
+    }
+  }
+}
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_POOLING_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/prelu.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/prelu.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,77 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_PRELU_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_PRELU_H_
+
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/compatibility.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+namespace reference_ops {
+
+// Broadcast prelu to output_shape for quantized uint8 data.
+inline void BroadcastPrelu4DSlow(const PreluParams& params,
+                                 const RuntimeShape& input_shape,
+                                 const uint8* input_data,
+                                 const RuntimeShape& alpha_shape,
+                                 const uint8* alpha_data,
+                                 const RuntimeShape& output_shape,
+                                 uint8* output_data) {
+  TFLITE_DCHECK_LE(input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_LE(alpha_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_LE(output_shape.DimensionsCount(), 4);
+  const RuntimeShape extended_output_shape =
+      RuntimeShape::ExtendedShape(4, output_shape);
+  NdArrayDesc<4> desc1;
+  NdArrayDesc<4> desc2;
+  NdArrayDescsForElementwiseBroadcast(input_shape, alpha_shape, &desc1, &desc2);
+
+  for (int b = 0; b < extended_output_shape.Dims(0); ++b) {
+    for (int y = 0; y < extended_output_shape.Dims(1); ++y) {
+      for (int x = 0; x < extended_output_shape.Dims(2); ++x) {
+        for (int c = 0; c < extended_output_shape.Dims(3); ++c) {
+          int output_index = Offset(extended_output_shape, b, y, x, c);
+          int input_index = SubscriptToIndex(desc1, b, y, x, c);
+          const int32 input_value =
+              params.input_offset + input_data[input_index];
+          if (input_value >= 0) {
+            output_data[output_index] = input_data[input_index];
+          } else {
+            auto alpha_index = SubscriptToIndex(desc2, b, y, x, c);
+            const int32 alpha_value =
+                params.alpha_offset + alpha_data[alpha_index];
+            const int32 unclamped_output =
+                params.output_offset +
+                MultiplyByQuantizedMultiplierSmallerThanOneExp(
+                    input_value * alpha_value, params.output_multiplier,
+                    params.output_shift);
+            const int32 quantized_min = std::numeric_limits<uint8_t>::min();
+            const int32 quantized_max = std::numeric_limits<uint8_t>::max();
+            const int32 clamped_output = std::min(
+                quantized_max, std::max(quantized_min, unclamped_output));
+            output_data[output_index] = static_cast<uint8>(clamped_output);
+          }
+        }
+      }
+    }
+  }
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_PRELU_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/process_broadcast_shapes.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/process_broadcast_shapes.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,134 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_PROCESS_BROADCAST_SHAPES_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_PROCESS_BROADCAST_SHAPES_H_
+
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+namespace reference_ops {
+
+// Consolidates dimensions in broadcast inputs, checks for five-fold pattern.
+//
+// For example, if sequence of dimensions of one input is
+// ..., 1, 3, 1, 7, 9, 5,... and the other is ..., 2, 3, 1, 7, 1, 1, ...
+// we can consolidate these as
+// ..., 1, 3*7, 9*5, ... and 2, 3*7, 1.
+//
+// The category is updated in the less-frequent case of shapes that are
+// not suited to a fivefold-loop broadcast.
+//
+// Falls back to generic pattern when it does not know how to process properly.
+//
+// Returns true iff there is some sort of broadcast, which includes five-fold
+// patterns and falling back to generic broadcast.
+inline bool ProcessBroadcastShapes(const RuntimeShape& shape0,
+                                   const RuntimeShape& shape1,
+                                   tflite::ArithmeticParams* params) {
+  const int dims_count =
+      std::max(shape0.DimensionsCount(), shape1.DimensionsCount());
+
+  params->broadcast_category = BroadcastableOpCategory::kGenericBroadcast;
+  RuntimeShape scalar_shape(dims_count, 1);
+
+  auto extended_shape0 = RuntimeShape::ExtendedShape(dims_count, shape0);
+  auto extended_shape1 = RuntimeShape::ExtendedShape(dims_count, shape1);
+
+  // Check for "exact" match, implicitly accepting any scalar shapes.
+  if (extended_shape0 == extended_shape1) {
+    params->broadcast_category = BroadcastableOpCategory::kNonBroadcast;
+    return false;
+  }
+
+  for (int i = dims_count - 1; i >= 0; --i) {
+    if (extended_shape0.Dims(i) == extended_shape1.Dims(i)) {
+      continue;
+    } else if (extended_shape0.Dims(i) == 1) {
+      params->broadcast_category =
+          BroadcastableOpCategory::kFirstInputBroadcastsFast;
+      break;
+    } else if (extended_shape1.Dims(i) == 1) {
+      params->broadcast_category =
+          BroadcastableOpCategory::kSecondInputBroadcastsFast;
+      break;
+    } else {
+      // This case is erroneous: there is a dimension that does not match and
+      // is not a broadcast from one shape to the other.
+      params->broadcast_category = BroadcastableOpCategory::kGenericBroadcast;
+      return true;
+    }
+  }
+
+  if (params->broadcast_category !=
+          BroadcastableOpCategory::kFirstInputBroadcastsFast &&
+      params->broadcast_category !=
+          BroadcastableOpCategory::kSecondInputBroadcastsFast) {
+    return false;
+  }
+
+  // From this point it is assumed contractually that corresponding dimensions
+  // in shape0 and shape1 are either (a) equal or (b) one or other equals 1.
+  const bool swap_inputs = params->broadcast_category ==
+                           BroadcastableOpCategory::kSecondInputBroadcastsFast;
+  const RuntimeShape* shape_a =
+      swap_inputs ? &extended_shape1 : &extended_shape0;
+  const RuntimeShape* shape_b =
+      swap_inputs ? &extended_shape0 : &extended_shape1;
+
+  int i = dims_count - 1;
+  params->broadcast_shape[0] = 1;
+  params->broadcast_shape[1] = 1;
+  params->broadcast_shape[2] = 1;
+  params->broadcast_shape[3] = 1;
+  params->broadcast_shape[4] = 1;
+  // y_0 is greedy: include dims if both or neither equal 1: in other words,
+  // test for equality rather than (shape_a->Dims(i) != 1).
+  while (i >= 0 && shape_a->Dims(i) == shape_b->Dims(i)) {
+    params->broadcast_shape[4] *= shape_b->Dims(i);
+    --i;
+  }
+  // Here either input_a or input_b has dim of 1 (if i >= 0).  If it is input_b
+  // that has the unit dimension, the next two loops are not entered.
+  while (i >= 0 && shape_a->Dims(i) == 1) {
+    params->broadcast_shape[3] *= shape_b->Dims(i);
+    --i;
+  }
+  while (i >= 0 && shape_a->Dims(i) == shape_b->Dims(i)) {
+    params->broadcast_shape[2] *= shape_a->Dims(i);
+    --i;
+  }
+  // Here either input_a or input_b has dim of 1 (if i >= 0).
+  while (i >= 0 && shape_b->Dims(i) == 1) {
+    params->broadcast_shape[1] *= shape_a->Dims(i);
+    --i;
+  }
+  while (i >= 0 && shape_a->Dims(i) == shape_b->Dims(i)) {
+    params->broadcast_shape[0] *= shape_b->Dims(i);
+    --i;
+  }
+
+  // Rarer case is when the broadcast dimensions cannot be handled by a fivefold
+  // loop.
+  if (i >= 0) {
+    params->broadcast_category = BroadcastableOpCategory::kGenericBroadcast;
+  }
+  return true;
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_PROCESS_BROADCAST_SHAPES_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/quantize.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/quantize.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,48 @@
+/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_QUANTIZE_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_QUANTIZE_H_
+
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/round.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+namespace reference_ops {
+
+template <typename T>
+inline void AffineQuantize(const tflite::QuantizationParams& op_params,
+                           const RuntimeShape& input_shape,
+                           const float* input_data,
+                           const RuntimeShape& output_shape, T* output_data) {
+  const int32 zero_point = op_params.zero_point;
+  const double scale = static_cast<double>(op_params.scale);
+  const int flat_size = MatchingFlatSize(input_shape, output_shape);
+  static constexpr int32 min_val = std::numeric_limits<T>::min();
+  static constexpr int32 max_val = std::numeric_limits<T>::max();
+
+  for (int i = 0; i < flat_size; i++) {
+    const float val = input_data[i];
+    int32 unclamped = static_cast<int32>(TfLiteRound(val / scale)) + zero_point;
+    int32 clamped = std::min(std::max(unclamped, min_val), max_val);
+    output_data[i] = clamped;
+  }
+}
+
+}  // namespace reference_ops
+
+}  // namespace tflite
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_QUANTIZE_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/round.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/round.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,51 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_ROUND_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_ROUND_H_
+
+#include <cmath>
+
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+namespace reference_ops {
+
+inline float RoundToNearest(float value) {
+  auto floor_val = std::floor(value);
+  auto diff = value - floor_val;
+  if ((diff < 0.5f) ||
+      ((diff == 0.5f) && (static_cast<int>(floor_val) % 2 == 0))) {
+    return floor_val;
+  } else {
+    return floor_val = floor_val + 1.0f;
+  }
+}
+
+inline void Round(const RuntimeShape& input_shape, const float* input_data,
+                  const RuntimeShape& output_shape, float* output_data) {
+  const int flat_size = MatchingFlatSize(input_shape, output_shape);
+  for (int i = 0; i < flat_size; ++i) {
+    // Note that this implementation matches that of tensorFlow tf.round
+    // and corresponds to the bankers rounding method.
+    // cfenv (for fesetround) is not yet supported universally on Android, so
+    // using a work around.
+    output_data[i] = RoundToNearest(input_data[i]);
+  }
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_ROUND_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/softmax.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/softmax.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,169 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_SOFTMAX_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_SOFTMAX_H_
+
+#include "fixedpoint/fixedpoint.h"
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/round.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+#include "tensorflow/lite/kernels/op_macros.h"
+
+namespace tflite {
+namespace reference_ops {
+
+inline void Softmax(const SoftmaxParams& params,
+                    const RuntimeShape& input_shape, const float* input_data,
+                    const RuntimeShape& output_shape, float* output_data) {
+  const int trailing_dim = input_shape.DimensionsCount() - 1;
+  const int outer_size =
+      MatchingFlatSizeSkipDim(input_shape, trailing_dim, output_shape);
+  const int depth =
+      MatchingDim(input_shape, trailing_dim, output_shape, trailing_dim);
+
+  for (int i = 0; i < outer_size; ++i) {
+    // Find max element value which we'll use to ensure numerical stability
+    // taking advantage of the following equality:
+    // exp(x[i])/sum(exp(x[i])) == exp(x[i]+C)/sum(exp(x[i]+C))
+    float max = std::numeric_limits<float>::lowest();
+    for (int c = 0; c < depth; ++c) {
+      max = std::max(max, input_data[i * depth + c]);
+    }
+
+    // Compute sum.
+    float sum = 0.f;
+    for (int c = 0; c < depth; ++c) {
+      sum += std::exp((input_data[i * depth + c] - max) * params.beta);
+    }
+
+    // Compute result.
+    for (int c = 0; c < depth; ++c) {
+      output_data[i * depth + c] =
+          std::exp((input_data[i * depth + c] - max) * params.beta) / sum;
+    }
+  }
+}
+
+inline void Softmax(const SoftmaxParams& params,
+                    const RuntimeShape& input_shape, const uint8* input_data,
+                    const RuntimeShape& output_shape, uint8* output_data) {
+  const int32 input_beta_multiplier = params.input_multiplier;
+  const int32 input_beta_left_shift = params.input_left_shift;
+  const int diff_min = params.diff_min;
+  // The representation chosen for the input to the exp() function is Q5.26.
+  // We need to leave extra space since values that we skip might be as large as
+  // -32 before multiplying by input_beta_multiplier, and therefore as large as
+  // -16 afterwards.  Note that exp(-8) is definitely not insignificant to
+  // accumulation, but exp(-16) definitely is.
+  static const int kScaledDiffIntegerBits = 5;
+  static const int kAccumulationIntegerBits = 12;
+  using FixedPointScaledDiff =
+      gemmlowp::FixedPoint<int32, kScaledDiffIntegerBits>;
+  using FixedPointAccum = gemmlowp::FixedPoint<int32, kAccumulationIntegerBits>;
+  using FixedPoint0 = gemmlowp::FixedPoint<int32, 0>;
+
+  const int trailing_dim = input_shape.DimensionsCount() - 1;
+  const int outer_size =
+      MatchingFlatSizeSkipDim(input_shape, trailing_dim, output_shape);
+  const int depth =
+      MatchingDim(input_shape, trailing_dim, output_shape, trailing_dim);
+
+  for (int i = 0; i < outer_size; ++i) {
+    uint8 max_in_row = 0;
+    for (int c = 0; c < depth; ++c) {
+      max_in_row = std::max(max_in_row, input_data[i * depth + c]);
+    }
+
+    FixedPointAccum sum_of_exps = FixedPointAccum::Zero();
+    for (int c = 0; c < depth; ++c) {
+      int32 input_diff =
+          static_cast<int32>(input_data[i * depth + c]) - max_in_row;
+      if (input_diff >= diff_min) {
+        const int32 input_diff_rescaled =
+            MultiplyByQuantizedMultiplierGreaterThanOne(
+                input_diff, input_beta_multiplier, input_beta_left_shift);
+        const FixedPointScaledDiff scaled_diff_f8 =
+            FixedPointScaledDiff::FromRaw(input_diff_rescaled);
+        sum_of_exps = sum_of_exps + gemmlowp::Rescale<kAccumulationIntegerBits>(
+                                        exp_on_negative_values(scaled_diff_f8));
+      }
+    }
+
+    int num_bits_over_unit;
+    FixedPoint0 shifted_scale = FixedPoint0::FromRaw(GetReciprocal(
+        sum_of_exps.raw(), kAccumulationIntegerBits, &num_bits_over_unit));
+
+    for (int c = 0; c < depth; ++c) {
+      int32 input_diff =
+          static_cast<int32>(input_data[i * depth + c]) - max_in_row;
+      if (input_diff >= diff_min) {
+        const int32 input_diff_rescaled =
+            MultiplyByQuantizedMultiplierGreaterThanOne(
+                input_diff, input_beta_multiplier, input_beta_left_shift);
+        const FixedPointScaledDiff scaled_diff_f8 =
+            FixedPointScaledDiff::FromRaw(input_diff_rescaled);
+
+        FixedPoint0 exp_in_0 = exp_on_negative_values(scaled_diff_f8);
+        int32 unsat_output = gemmlowp::RoundingDivideByPOT(
+            (shifted_scale * exp_in_0).raw(), num_bits_over_unit + 31 - 8);
+
+        output_data[i * depth + c] = static_cast<uint8>(
+            std::max(std::min(unsat_output, static_cast<int32>(255)),
+                     static_cast<int32>(0)));
+
+      } else {
+        output_data[i * depth + c] = 0;
+      }
+    }
+  }
+}
+
+// Performs softmax along the input of size (input_size * batch_size).
+inline void Softmax(const float* in, const int input_size, const int batch_size,
+                    const float beta, float* out) {
+  //  TF_LITE_ASSERT(input_size > 0);
+
+  // For each batch
+  for (int b = 0; b < batch_size; b++) {
+    // Find the max coeff.
+    float max_coeff = in[0];
+    for (int i = 1; i < input_size; i++) {
+      if (in[i] > max_coeff) max_coeff = in[i];
+    }
+
+    // Compute the normalized sum of exps.
+    float exp_sum = 0.0;
+    for (int i = 0; i < input_size; i++) {
+      out[i] = std::exp((in[i] - max_coeff) * beta);
+      exp_sum += out[i];
+    }
+
+    // Divide by the sum of exps.
+    float reciprocal_sum_exp = 1.f / exp_sum;
+    for (int i = 0; i < input_size; i++) {
+      out[i] *= reciprocal_sum_exp;
+    }
+
+    // Advance in and out pointers for the next batch.
+    in += input_size;
+    out += input_size;
+  }
+}
+
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_SOFTMAX_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/reference/strided_slice.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/reference/strided_slice.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,80 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_STRIDED_SLICE_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_STRIDED_SLICE_H_
+
+#include "tensorflow/lite/kernels/internal/common.h"
+#include "tensorflow/lite/kernels/internal/strided_slice_logic.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+namespace reference_ops {
+template <typename T>
+inline void StridedSlice(const tflite::StridedSliceParams& op_params,
+                         const RuntimeShape& unextended_input_shape,
+                         const T* input_data,
+                         const RuntimeShape& unextended_output_shape,
+                         T* output_data) {
+  // Note that the output_shape is not used herein.
+  tflite::StridedSliceParams params_copy = op_params;
+
+  TFLITE_DCHECK_LE(unextended_input_shape.DimensionsCount(), 4);
+  TFLITE_DCHECK_LE(unextended_output_shape.DimensionsCount(), 4);
+  const RuntimeShape input_shape =
+      RuntimeShape::ExtendedShape(4, unextended_input_shape);
+  const RuntimeShape output_shape =
+      RuntimeShape::ExtendedShape(4, unextended_output_shape);
+
+  // Reverse and pad to 4 dimensions because that is what the runtime code
+  // requires (ie. all shapes must be 4D and are given backwards).
+  strided_slice::StridedSlicePadIndices(&params_copy, 4);
+
+  const int start_b = strided_slice::StartForAxis(params_copy, input_shape, 0);
+  const int stop_b =
+      strided_slice::StopForAxis(params_copy, input_shape, 0, start_b);
+  const int start_h = strided_slice::StartForAxis(params_copy, input_shape, 1);
+  const int stop_h =
+      strided_slice::StopForAxis(params_copy, input_shape, 1, start_h);
+  const int start_w = strided_slice::StartForAxis(params_copy, input_shape, 2);
+  const int stop_w =
+      strided_slice::StopForAxis(params_copy, input_shape, 2, start_w);
+  const int start_d = strided_slice::StartForAxis(params_copy, input_shape, 3);
+  const int stop_d =
+      strided_slice::StopForAxis(params_copy, input_shape, 3, start_d);
+
+  T* out_ptr = output_data;
+  for (int in_b = start_b;
+       !strided_slice::LoopCondition(in_b, stop_b, params_copy.strides[0]);
+       in_b += params_copy.strides[0]) {
+    for (int in_h = start_h;
+         !strided_slice::LoopCondition(in_h, stop_h, params_copy.strides[1]);
+         in_h += params_copy.strides[1]) {
+      for (int in_w = start_w;
+           !strided_slice::LoopCondition(in_w, stop_w, params_copy.strides[2]);
+           in_w += params_copy.strides[2]) {
+        for (int in_d = start_d; !strided_slice::LoopCondition(
+                 in_d, stop_d, params_copy.strides[3]);
+             in_d += params_copy.strides[3]) {
+          *out_ptr++ = input_data[Offset(input_shape, in_b, in_h, in_w, in_d)];
+        }
+      }
+    }
+  }
+}
+}  // namespace reference_ops
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_STRIDED_SLICE_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/round.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/round.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,40 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_ROUND_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_ROUND_H_
+
+#include <cmath>
+
+namespace tflite {
+
+// TODO(aselle): See if we can do this only on jdk. Also mikecase, check
+// if you need this for java host build.
+#if defined(TF_LITE_USE_GLOBAL_ROUND) || \
+    (defined(__ANDROID__) && !defined(__NDK_MAJOR__)) || defined(ARDUINO)
+template <class T>
+inline float TfLiteRound(const float x) {
+  return ::round(x);
+}
+inline double TfLiteRound(const double x) { return ::round(x); }
+#else
+template <class T>
+inline T TfLiteRound(const T x) {
+  return std::round(x);
+}
+#endif
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_ROUND_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/strided_slice_logic.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/strided_slice_logic.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,198 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_STRIDED_SLICE_LOGIC_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_STRIDED_SLICE_LOGIC_H_
+
+#include <limits>
+#include <vector>
+#include "tensorflow/lite/kernels/internal/compatibility.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+namespace strided_slice {
+
+// Use until std::clamp() is available from C++17.
+inline int Clamp(const int v, const int lo, const int hi) {
+  TFLITE_DCHECK(!(hi < lo));
+  if (hi < v) return hi;
+  if (v < lo) return lo;
+  return v;
+}
+
+inline void StridedSlicePadIndices(tflite::StridedSliceParams* p,
+                                   int dim_count) {
+  // Add indices and mask bits to fully include extra dimensions
+  TFLITE_CHECK_LE(dim_count, 4);
+  TFLITE_CHECK_GE(dim_count, p->start_indices_count);
+  TFLITE_CHECK_EQ(p->start_indices_count, p->stop_indices_count);
+  TFLITE_CHECK_EQ(p->stop_indices_count, p->strides_count);
+
+  const int pad_count = dim_count - p->start_indices_count;
+
+  // Pad indices at start, so move arrays by pad_count.
+  for (int i = p->start_indices_count - 1; i >= 0; --i) {
+    p->strides[i + pad_count] = p->strides[i];
+    p->start_indices[i + pad_count] = p->start_indices[i];
+    p->stop_indices[i + pad_count] = p->stop_indices[i];
+  }
+  for (int i = 0; i < pad_count; ++i) {
+    p->start_indices[i] = 0;
+    p->stop_indices[i] = 1;
+    p->strides[i] = 1;
+  }
+
+  // Pad masks with 0s or 1s as required.
+  p->shrink_axis_mask <<= pad_count;
+  p->ellipsis_mask <<= pad_count;
+  p->new_axis_mask <<= pad_count;
+  p->begin_mask <<= pad_count;
+  p->end_mask <<= pad_count;
+  p->begin_mask |= (1 << pad_count) - 1;
+  p->end_mask |= (1 << pad_count) - 1;
+
+  p->start_indices_count = dim_count;
+  p->stop_indices_count = dim_count;
+  p->strides_count = dim_count;
+}
+
+// Return the index for the first element along that axis. This index will be a
+// positive integer between [0, axis_size - 1] that can be used to index
+// directly into the data.
+inline int StartForAxis(const tflite::StridedSliceParams& params,
+                        const RuntimeShape& input_shape, int axis) {
+  const auto begin_mask = params.begin_mask;
+  const auto* start_indices = params.start_indices;
+  const auto* strides = params.strides;
+  // Begin with the specified index.
+  int start = start_indices[axis];
+
+  // begin_mask override
+  if (begin_mask & 1 << axis) {
+    if (strides[axis] > 0) {
+      // Forward iteration - use the first element. These values will get
+      // clamped below (Note: We could have set them to 0 and axis_size-1, but
+      // use lowest() and max() to maintain symmetry with StopForAxis())
+      start = std::numeric_limits<int>::lowest();
+    } else {
+      // Backward iteration - use the last element.
+      start = std::numeric_limits<int>::max();
+    }
+  }
+
+  // Handle negative indices
+  int axis_size = input_shape.Dims(axis);
+  if (start < 0) {
+    start += axis_size;
+  }
+
+  // Clamping
+  start = Clamp(start, 0, axis_size - 1);
+
+  return start;
+}
+
+// Return the "real" index for the end of iteration along that axis. This is an
+// "end" in the traditional C sense, in that it points to one past the last
+// element. ie. So if you were iterating through all elements of a 1D array of
+// size 4, this function would return 4 as the stop, because it is one past the
+// "real" indices of 0, 1, 2 & 3.
+inline int StopForAxis(const tflite::StridedSliceParams& params,
+                       const RuntimeShape& input_shape, int axis,
+                       int start_for_axis) {
+  const auto end_mask = params.end_mask;
+  const auto shrink_axis_mask = params.shrink_axis_mask;
+  const auto* stop_indices = params.stop_indices;
+  const auto* strides = params.strides;
+
+  // Begin with the specified index
+  const bool shrink_axis = shrink_axis_mask & (1 << axis);
+  int stop = stop_indices[axis];
+
+  // When shrinking an axis, the end position does not matter (and can be
+  // incorrect when negative indexing is used, see Issue #19260). Always use
+  // start_for_axis + 1 to generate a length 1 slice, since start_for_axis has
+  // already been adjusted for negative indices.
+  if (shrink_axis) {
+    stop = start_for_axis + 1;
+  }
+
+  // end_mask override
+  if (end_mask & (1 << axis)) {
+    if (strides[axis] > 0) {
+      // Forward iteration - use the last element. These values will get
+      // clamped below
+      stop = std::numeric_limits<int>::max();
+    } else {
+      // Backward iteration - use the first element.
+      stop = std::numeric_limits<int>::lowest();
+    }
+  }
+
+  // Handle negative indices
+  const int axis_size = input_shape.Dims(axis);
+  if (stop < 0) {
+    stop += axis_size;
+  }
+
+  // Clamping
+  // Because the end index points one past the last element, we need slightly
+  // different clamping ranges depending on the direction.
+  if (strides[axis] > 0) {
+    // Forward iteration
+    stop = Clamp(stop, 0, axis_size);
+  } else {
+    // Backward iteration
+    stop = Clamp(stop, -1, axis_size - 1);
+  }
+
+  return stop;
+}
+
+inline bool LoopCondition(int index, int stop, int stride) {
+  // True when we have reached the end of an axis and should loop.
+  return stride > 0 ? index >= stop : index <= stop;
+}
+
+inline tflite::StridedSliceParams BuildStridedSliceParams(
+    int begin_mask, int end_mask, int shrink_axis_mask,
+    const std::vector<int>& start_indices, const std::vector<int>& stop_indices,
+    const std::vector<int>& strides) {
+  tflite::StridedSliceParams op_params;
+  const int dims_count = start_indices.size();
+
+  op_params.start_indices_count = dims_count;
+  op_params.stop_indices_count = dims_count;
+  op_params.strides_count = dims_count;
+  for (int i = 0; i < dims_count; ++i) {
+    op_params.start_indices[i] = start_indices[i];
+    op_params.stop_indices[i] = stop_indices[i];
+    op_params.strides[i] = strides[i];
+  }
+
+  op_params.begin_mask = begin_mask;
+  op_params.ellipsis_mask = 0;
+  op_params.end_mask = end_mask;
+  op_params.new_axis_mask = 0;
+  op_params.shrink_axis_mask = shrink_axis_mask;
+
+  return op_params;
+}
+
+}  // namespace strided_slice
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_STRIDED_SLICE_LOGIC_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/tensor.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/tensor.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,144 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_TENSOR_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_TENSOR_H_
+
+#include <complex>
+#include <vector>
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+#include "tensorflow/lite/string_util.h"
+
+namespace tflite {
+
+inline RuntimeShape GetTensorShape(std::vector<int32_t> data) {
+  return RuntimeShape(data.size(), data.data());
+}
+
+// A list of tensors in a format that can be used by kernels like split and
+// concatenation.
+template <typename T>
+class VectorOfTensors {
+ public:
+  // Build with the tensors in 'tensor_list'.
+  VectorOfTensors(const TfLiteContext& context,
+                  const TfLiteIntArray& tensor_list) {
+    int num_tensors = tensor_list.size;
+
+    all_data_.reserve(num_tensors);
+    all_shape_.reserve(num_tensors);
+    all_shape_ptr_.reserve(num_tensors);
+
+    for (int i = 0; i < num_tensors; ++i) {
+      TfLiteTensor* t = &context.tensors[tensor_list.data[i]];
+      all_data_.push_back(GetTensorData<T>(t));
+      all_shape_.push_back(GetTensorShape(t));
+    }
+
+    // Taking the pointer from inside a std::vector is only OK if the vector is
+    // never modified, so we populate all_shape in the previous loop and then we
+    // are free to grab iterators here.
+    for (int i = 0; i < num_tensors; ++i) {
+      all_shape_ptr_.push_back(&all_shape_[i]);
+    }
+  }
+  // Return a pointer to the data pointers of all tensors in the list. For
+  // example:
+  //   float* const* f = v.data();
+  //   f[0][1] is the second element of the first tensor.
+  T* const* data() const { return all_data_.data(); }
+
+  // Return a pointer the shape pointers of all tensors in the list. For
+  // example:
+  //   const RuntimeShape* const* d = v.dims();
+  //   dims[1] are the dimensions of the second tensor in the list.
+  const RuntimeShape* const* shapes() const { return all_shape_ptr_.data(); }
+
+ private:
+  std::vector<T*> all_data_;
+  std::vector<RuntimeShape> all_shape_;
+  std::vector<RuntimeShape*> all_shape_ptr_;
+};
+
+// A list of quantized tensors in a format that can be used by kernels like
+// split and concatenation.
+class VectorOfQuantizedTensors : public VectorOfTensors<uint8> {
+ public:
+  // Build with the tensors in 'tensor_list'.
+  VectorOfQuantizedTensors(const TfLiteContext& context,
+                           const TfLiteIntArray& tensor_list)
+      : VectorOfTensors<uint8>(context, tensor_list) {
+    for (int i = 0; i < tensor_list.size; ++i) {
+      TfLiteTensor* t = &context.tensors[tensor_list.data[i]];
+      zero_point_.push_back(t->params.zero_point);
+      scale_.push_back(t->params.scale);
+    }
+  }
+
+  const float* scale() const { return scale_.data(); }
+  const int32* zero_point() const { return zero_point_.data(); }
+
+ private:
+  std::vector<int32> zero_point_;
+  std::vector<float> scale_;
+};
+
+// Writes randomly accessed values from `input` sequentially into `output`.
+template <typename T>
+class SequentialTensorWriter {
+ public:
+  SequentialTensorWriter(const TfLiteTensor* input, TfLiteTensor* output) {
+    input_data_ = GetTensorData<T>(input);
+    output_ptr_ = GetTensorData<T>(output);
+  }
+  SequentialTensorWriter(const T* input_data, T* output_data)
+      : input_data_(input_data), output_ptr_(output_data) {}
+
+  void Write(int position) { *output_ptr_++ = input_data_[position]; }
+  void WriteN(int position, int len) {
+    memcpy(output_ptr_, &input_data_[position], sizeof(T) * len);
+    output_ptr_ += len;
+  }
+
+ private:
+  const T* input_data_;
+  T* output_ptr_;
+};
+
+template <>
+class SequentialTensorWriter<string> {
+ public:
+  SequentialTensorWriter(const TfLiteTensor* input, TfLiteTensor* output)
+      : input_(input), output_(output) {}
+  ~SequentialTensorWriter() { buffer_.WriteToTensor(output_, nullptr); }
+
+  void Write(int position) { this->WriteN(position, 1); }
+  void WriteN(int position, int len) {
+    for (int i = 0; i < len; i++) {
+      buffer_.AddString(GetString(input_, position + i));
+    }
+  }
+
+ private:
+  const TfLiteTensor* input_;
+  TfLiteTensor* output_;
+  DynamicBuffer buffer_;
+};
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_TENSOR_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/tensor_ctypes.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/tensor_ctypes.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,47 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_TENSOR_CTYPES_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_TENSOR_CTYPES_H_
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/kernels/internal/types.h"
+
+namespace tflite {
+
+template <typename T>
+inline T* GetTensorData(TfLiteTensor* tensor) {
+  return tensor != nullptr ? reinterpret_cast<T*>(tensor->data.raw) : nullptr;
+}
+
+template <typename T>
+inline const T* GetTensorData(const TfLiteTensor* tensor) {
+  return tensor != nullptr ? reinterpret_cast<const T*>(tensor->data.raw)
+                           : nullptr;
+}
+
+inline RuntimeShape GetTensorShape(const TfLiteTensor* tensor) {
+  if (tensor == nullptr) {
+    return RuntimeShape();
+  }
+
+  TfLiteIntArray* dims = tensor->dims;
+  const int dims_size = dims->size;
+  const int32_t* dims_data = reinterpret_cast<const int32_t*>(dims->data);
+  return RuntimeShape(dims_size, dims_data);
+}
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_TENSOR_CTYPES_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/internal/types.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/internal/types.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,1108 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_TYPES_H_
+#define TENSORFLOW_LITE_KERNELS_INTERNAL_TYPES_H_
+
+#include <algorithm>
+#include <cstdint>
+#include <cstring>
+#include <initializer_list>
+
+#include "tensorflow/lite/kernels/internal/compatibility.h"
+
+namespace tflite {
+
+enum class FusedActivationFunctionType : uint8 { kNone, kRelu6, kRelu1, kRelu };
+enum class PaddingType : uint8 { kNone, kSame, kValid };
+
+struct PaddingValues {
+  int16 width;
+  int16 height;
+  // offset is used for calculating "remaining" padding, for example, `width`
+  // is 1 and `width_offset` is 1, so padding_left is 1 while padding_right is
+  // 1 + 1 = 2.
+  int16 width_offset;
+  // Same as width_offset except it's over the height dimension.
+  int16 height_offset;
+};
+
+// This enumeration allows for non-default formats for the weights array
+// of a fully-connected operator, allowing the use of special optimized
+// runtime paths.
+enum class FullyConnectedWeightsFormat : uint8 {
+  // Default format (flat 2D layout, the inner contiguous dimension
+  // is input_depth, the outer non-contiguous dimension is output_depth)
+  kDefault,
+  // Summary: optimized layout for fast CPU runtime implementation,
+  // aimed specifically at ARM CPUs at the moment, and specialized for
+  // 8-bit quantized layers.
+  //
+  // The use case we're concerned with here is: 8-bit quantization,
+  // large weights matrix that doesn't fit in cache (e.g. 4096x2048 in
+  // a key application that drove this), very small batch size (e.g. 1 -- 4).
+  //
+  // Even with 8-bit quantization of weights, the performance of memory
+  // accesses to the weights can become the dominant issue when
+  // the batch size is small, so each weight value is used in only a few
+  // arithmetic ops, i.e. the fully-connected node has a low arithmetic
+  // intensity. The specific issues that arise are of three kinds:
+  // (1) One may, ideally, max out DRAM bandwidth, i.e. be truly memory
+  //     bound. That's the "good" issue to run into.
+  // (2) One may run into sub-optimal pre-fetching: the data hasn't been
+  //     prefetched into the cache by the time we need it.
+  // (3) One may run into cache aliasing: multiple values that are
+  //     pre-fetched, alias each other in the L1 cache (which typically
+  //     has only 4-way set associativity in ARM CPUs) and thus evict
+  //     each other before we get to using them.
+  //
+  // The point of this shuffling is to avoid issues (2) and (3) so that
+  // we get as fast as possible given only the hard constraint (1).
+  // This is achieved by turning the difficulty into a solution: the
+  // difficulty, that each value loaded from memory is used only in
+  // one kernel iteration, making this operation memory-intensive, hints at
+  // the solution, of shuffling the weights so that they are stored in the
+  // exact order as the kernel needs to load them, so that the memory
+  // accesses made by the kernel are trivial. This solves (2) because the
+  // trivial memory access pattern allows the CPU's automatic prefetching
+  // to perform very well (no need even for preload instructions), and this
+  // solves (3) because the values being loaded concurrently are now
+  // contiguous in the address space, thus don't alias each other in the cache.
+  //
+  // On ARM, we typically want our kernel to process a 4x16 block of weights
+  // at a time, because:
+  //   - 16 is the number of bytes in a NEON register.
+  //   - 4 is how many rows we need to handle concurrently in the kernel in
+  //     order to have sufficient mutual independence of instructions to
+  //     maximize arithmetic throughput.
+  //
+  // Finally, the 'Int8' part in the name refers to the fact that this
+  // weights format has each weights value encoded as a signed int8 value,
+  // even if the data type of the weights buffer is uint8.  This is intended
+  // to save runtime kernels the effort to have to XOR the top bit of these
+  // bytes before using them in signed arithmetic, see this file for more
+  // explanations on the 'signed int8 trick' in matrix multiplication kernels:
+  //
+  //   tensorflow/lite/toco/graph_transformations/ensure_uint8_weights_safe_for_fast_int8_kernels.cc
+  //
+  kShuffled4x16Int8,
+};
+
+// Quantization parameters, determining the mapping of quantized values
+// to real values (i.e. determining how quantized values are mathematically
+// interpreted).
+//
+// The correspondence is as follows:
+//
+//   real_value = scale * (quantized_value - zero_point);
+//
+// In other words, zero_point designates which quantized value corresponds to
+// the real 0 value, and scale designates the difference between the real values
+// corresponding to consecutive quantized values differing by 1.
+struct QuantizationParams {
+  int32 zero_point = 0;
+  double scale = 0.0;
+};
+
+inline bool operator==(const QuantizationParams& qp1,
+                       const QuantizationParams& qp2) {
+  return qp1.zero_point == qp2.zero_point && qp1.scale == qp2.scale;
+}
+
+template <int N>
+struct Dims {
+  int sizes[N];
+  int strides[N];
+};
+
+class RuntimeShape {
+ public:
+  // Shapes with dimensions up to 4 are stored directly in the structure, while
+  // larger shapes are separately allocated.
+  static constexpr int kMaxSmallSize = 4;
+
+  RuntimeShape& operator=(RuntimeShape const&) = delete;
+
+  RuntimeShape() : size_(0) {}
+
+  explicit RuntimeShape(int dimensions_count) : size_(dimensions_count) {
+    if (dimensions_count > kMaxSmallSize) {
+#ifdef TF_LITE_STATIC_MEMORY
+      TFLITE_CHECK(false && "No shape resizing supported on this platform");
+#else   // TF_LITE_STATIC_MEMORY
+      dims_pointer_ = new int32[dimensions_count];
+#endif  // TF_LITE_STATIC_MEMORY
+    }
+  }
+
+  RuntimeShape(int shape_size, int32 value) : size_(0) {
+    Resize(shape_size);
+    for (int i = 0; i < shape_size; ++i) {
+      SetDim(i, value);
+    }
+  }
+
+  RuntimeShape(int dimensions_count, const int32* dims_data) : size_(0) {
+    ReplaceWith(dimensions_count, dims_data);
+  }
+
+  RuntimeShape(const std::initializer_list<int> init_list) : size_(0) {
+    BuildFrom(init_list);
+  }
+
+  // Avoid using this constructor.  We should be able to delete it when C++17
+  // rolls out.
+  RuntimeShape(RuntimeShape const& other) : size_(other.DimensionsCount()) {
+    if (size_ > kMaxSmallSize) {
+      dims_pointer_ = new int32[size_];
+    }
+    std::memcpy(DimsData(), other.DimsData(), sizeof(int32) * size_);
+  }
+
+  bool operator==(const RuntimeShape& comp) const {
+    return this->size_ == comp.size_ &&
+           std::memcmp(DimsData(), comp.DimsData(), size_ * sizeof(int32)) == 0;
+  }
+
+  ~RuntimeShape() {
+    if (size_ > kMaxSmallSize) {
+#ifdef TF_LITE_STATIC_MEMORY
+      TFLITE_CHECK(false && "No shape resizing supported on this platform");
+#else   // TF_LITE_STATIC_MEMORY
+      delete[] dims_pointer_;
+#endif  // TF_LITE_STATIC_MEMORY
+    }
+  }
+
+  inline int32 DimensionsCount() const { return size_; }
+  inline int32 Dims(int i) const {
+    TFLITE_DCHECK_GE(i, 0);
+    TFLITE_DCHECK_LT(i, size_);
+    return size_ > kMaxSmallSize ? dims_pointer_[i] : dims_[i];
+  }
+  inline void SetDim(int i, int32 val) {
+    TFLITE_DCHECK_GE(i, 0);
+    TFLITE_DCHECK_LT(i, size_);
+    if (size_ > kMaxSmallSize) {
+      dims_pointer_[i] = val;
+    } else {
+      dims_[i] = val;
+    }
+  }
+
+  inline int32* DimsData() {
+    return size_ > kMaxSmallSize ? dims_pointer_ : dims_;
+  }
+  inline const int32* DimsData() const {
+    return size_ > kMaxSmallSize ? dims_pointer_ : dims_;
+  }
+  // The caller must ensure that the shape is no bigger than 4-D.
+  inline const int32* DimsDataUpTo4D() const { return dims_; }
+
+  inline void Resize(int dimensions_count) {
+    if (size_ > kMaxSmallSize) {
+#ifdef TF_LITE_STATIC_MEMORY
+      TFLITE_CHECK(false && "No shape resizing supported on this platform");
+#else   // TF_LITE_STATIC_MEMORY
+      delete[] dims_pointer_;
+#endif  // TF_LITE_STATIC_MEMORY
+    }
+    size_ = dimensions_count;
+    if (dimensions_count > kMaxSmallSize) {
+#ifdef TF_LITE_STATIC_MEMORY
+      TFLITE_CHECK(false && "No shape resizing supported on this platform");
+#else   // TF_LITE_STATIC_MEMORY
+      dims_pointer_ = new int32[dimensions_count];
+#endif  // TF_LITE_STATIC_MEMORY
+    }
+  }
+
+  inline void ReplaceWith(int dimensions_count, const int32* dims_data) {
+    Resize(dimensions_count);
+    int32* dst_dims = DimsData();
+    std::memcpy(dst_dims, dims_data, dimensions_count * sizeof(int32));
+  }
+
+  template <typename T>
+  inline void BuildFrom(const T& src_iterable) {
+    const int dimensions_count =
+        std::distance(src_iterable.begin(), src_iterable.end());
+    Resize(dimensions_count);
+    int32* data = DimsData();
+    for (auto it : src_iterable) {
+      *data = it;
+      ++data;
+    }
+  }
+
+  // This will probably be factored out. Old code made substantial use of 4-D
+  // shapes, and so this function is used to extend smaller shapes. Note that
+  // (a) as Dims<4>-dependent code is eliminated, the reliance on this should be
+  // reduced, and (b) some kernels are stricly 4-D, but then the shapes of their
+  // inputs should already be 4-D, so this function should not be needed.
+  inline static RuntimeShape ExtendedShape(int new_shape_size,
+                                           const RuntimeShape& shape) {
+    return RuntimeShape(new_shape_size, shape, 1);
+  }
+
+  inline void BuildFrom(const std::initializer_list<int> init_list) {
+    BuildFrom<const std::initializer_list<int>>(init_list);
+  }
+
+  // Returns the total count of elements, that is the size when flattened into a
+  // vector.
+  inline int FlatSize() const {
+    int buffer_size = 1;
+    const int* dims_data = reinterpret_cast<const int*>(DimsData());
+    for (int i = 0; i < size_; i++) {
+      buffer_size *= dims_data[i];
+    }
+    return buffer_size;
+  }
+
+  bool operator!=(const RuntimeShape& comp) const { return !((*this) == comp); }
+
+ private:
+  // For use only by ExtendedShape(), written to guarantee (return-value) copy
+  // elision in C++17.
+  // This creates a shape padded to the desired size with the specified value.
+  RuntimeShape(int new_shape_size, const RuntimeShape& shape, int pad_value)
+      : size_(0) {
+    // If the following check fails, it is likely because a 4D-only kernel is
+    // being used with an array of larger dimension count.
+    TFLITE_CHECK_GE(new_shape_size, shape.DimensionsCount());
+    Resize(new_shape_size);
+    const int size_increase = new_shape_size - shape.DimensionsCount();
+    for (int i = 0; i < size_increase; ++i) {
+      SetDim(i, pad_value);
+    }
+    std::memcpy(DimsData() + size_increase, shape.DimsData(),
+                sizeof(int32) * shape.DimensionsCount());
+  }
+
+  int32 size_;
+  union {
+    int32 dims_[kMaxSmallSize];
+    int32* dims_pointer_;
+  };
+};
+
+// Converts inference-style shape to legacy tflite::Dims<4>.
+inline tflite::Dims<4> ToRuntimeDims(const tflite::RuntimeShape& array_shape) {
+  tflite::Dims<4> result;
+  const int dimensions_count = array_shape.DimensionsCount();
+  TFLITE_CHECK_LE(dimensions_count, 4);
+  int cum_prod = 1;
+  for (int i = 0; i < 4; i++) {
+    const int new_dim =
+        (i < dimensions_count) ? array_shape.Dims(dimensions_count - 1 - i) : 1;
+    result.sizes[i] = new_dim;
+    result.strides[i] = cum_prod;
+    cum_prod *= new_dim;
+  }
+  return result;
+}
+
+// TODO(b/80418076): Move to legacy ops file, update invocations.
+inline RuntimeShape DimsToShape(const tflite::Dims<4>& dims) {
+  return RuntimeShape(
+      {dims.sizes[3], dims.sizes[2], dims.sizes[1], dims.sizes[0]});
+}
+
+// Gets next index to iterate through a multidimensional array.
+inline bool NextIndex(const int num_dims, const int* dims, int* current) {
+  if (num_dims == 0) {
+    return false;
+  }
+  TFLITE_DCHECK(dims != nullptr);
+  TFLITE_DCHECK(current != nullptr);
+  int carry = 1;
+  for (int idx = num_dims - 1; idx >= 0; --idx) {
+    int current_val = current[idx] + carry;
+    TFLITE_DCHECK_GE(dims[idx], current_val);
+    if (dims[idx] == current_val) {
+      current[idx] = 0;
+    } else {
+      current[idx] = current_val;
+      carry = 0;
+      break;
+    }
+  }
+  return (carry == 0);
+}
+
+// Gets offset of index if reducing on axis. When reducing, the flattened offset
+// will not change, if the input index changes on the given axis. For example,
+// if you have a 3D tensor and you are reducing to 2D by eliminating axis 0,
+// then index (0, 1, 2) and index (1, 1, 2) will map to the same flattened
+// offset.
+// TODO(kanlig): uses Dims to represent dimensions.
+inline size_t ReducedOutputOffset(const int num_dims, const int* dims,
+                                  const int* index, const int num_axis,
+                                  const int* axis) {
+  if (num_dims == 0) {
+    return 0;
+  }
+  TFLITE_DCHECK(dims != nullptr);
+  TFLITE_DCHECK(index != nullptr);
+  size_t offset = 0;
+  for (int idx = 0; idx < num_dims; ++idx) {
+    // if we need to skip this axis
+    bool is_axis = false;
+    if (axis != nullptr) {
+      for (int axis_idx = 0; axis_idx < num_axis; ++axis_idx) {
+        if (idx == axis[axis_idx]) {
+          is_axis = true;
+          break;
+        }
+      }
+    }
+    if (!is_axis) {
+      offset = offset * static_cast<size_t>(dims[idx]) +
+               static_cast<size_t>(index[idx]);
+    }
+  }
+  return offset;
+}
+
+inline int Offset(const RuntimeShape& shape, int i0, int i1, int i2, int i3) {
+  TFLITE_DCHECK_EQ(shape.DimensionsCount(), 4);
+  const int* dims_data = reinterpret_cast<const int*>(shape.DimsDataUpTo4D());
+  TFLITE_DCHECK(i0 >= 0 && i0 < dims_data[0]);
+  TFLITE_DCHECK(i1 >= 0 && i1 < dims_data[1]);
+  TFLITE_DCHECK(i2 >= 0 && i2 < dims_data[2]);
+  TFLITE_DCHECK(i3 >= 0 && i3 < dims_data[3]);
+  return ((i0 * dims_data[1] + i1) * dims_data[2] + i2) * dims_data[3] + i3;
+}
+
+inline int Offset(const Dims<4>& dims, int i0, int i1, int i2, int i3) {
+  TFLITE_DCHECK(i0 >= 0 && i0 < dims.sizes[0]);
+  TFLITE_DCHECK(i1 >= 0 && i1 < dims.sizes[1]);
+  TFLITE_DCHECK(i2 >= 0 && i2 < dims.sizes[2]);
+  TFLITE_DCHECK(i3 >= 0 && i3 < dims.sizes[3]);
+  return i0 * dims.strides[0] + i1 * dims.strides[1] + i2 * dims.strides[2] +
+         i3 * dims.strides[3];
+}
+
+inline int Offset(const Dims<4>& dims, int* index) {
+  return Offset(dims, index[0], index[1], index[2], index[3]);
+}
+
+inline int Offset(const RuntimeShape& shape, int* index) {
+  return Offset(shape, index[0], index[1], index[2], index[3]);
+}
+
+// Get array size, DCHECKing that the dim index is in range.
+//
+// Note that this will be phased out with Dims<4>, since RuntimeShape::Dims()
+// already performs this check.
+template <int N>
+int ArraySize(const Dims<N>& array, int index) {
+  TFLITE_DCHECK(index >= 0 && index < N);
+  return array.sizes[index];
+}
+
+// Get common array size, DCHECKing that they all agree.
+template <typename ArrayType1, typename ArrayType2>
+int MatchingArraySize(const ArrayType1& array1, int index1,
+                      const ArrayType2& array2, int index2) {
+  TFLITE_DCHECK_EQ(ArraySize(array1, index1), ArraySize(array2, index2));
+  return ArraySize(array1, index1);
+}
+
+template <typename ArrayType1, typename ArrayType2, typename... Args>
+int MatchingArraySize(const ArrayType1& array1, int index1,
+                      const ArrayType2& array2, int index2, Args... args) {
+  TFLITE_DCHECK_EQ(ArraySize(array1, index1), ArraySize(array2, index2));
+  return MatchingArraySize(array1, index1, args...);
+}
+
+// Get common shape dim, DCHECKing that they all agree.
+inline int MatchingDim(const RuntimeShape& shape1, int index1,
+                       const RuntimeShape& shape2, int index2) {
+  TFLITE_DCHECK_EQ(shape1.Dims(index1), shape2.Dims(index2));
+  return shape1.Dims(index1);
+}
+
+template <typename... Args>
+int MatchingDim(const RuntimeShape& shape1, int index1,
+                const RuntimeShape& shape2, int index2, Args... args) {
+  TFLITE_DCHECK_EQ(shape1.Dims(index1), shape2.Dims(index2));
+  return MatchingDim(shape1, index1, args...);
+}
+
+// Will be phased out with Dims<4>, replaced by RuntimeShape::FlatSize().
+template <int N>
+inline int FlatSize(const Dims<N>& dims) {
+  int flat_size = 1;
+  for (int i = 0; i < N; ++i) {
+    flat_size *= dims.sizes[i];
+  }
+  return flat_size;
+}
+
+TFLITE_DEPRECATED("Prefer FlatSize.")
+inline int RequiredBufferSizeForDims(const Dims<4>& dims) {
+  return FlatSize(dims);
+}
+
+inline int MatchingElementsSize(const RuntimeShape& shape,
+                                const RuntimeShape& check_shape_0) {
+  const int size_1 = shape.FlatSize();
+  const int size_2 = check_shape_0.FlatSize();
+  TFLITE_CHECK_EQ(size_1, size_2);
+  return size_1;
+}
+
+inline int MatchingElementsSize(const RuntimeShape& shape,
+                                const RuntimeShape& check_shape_0,
+                                const RuntimeShape& check_shape_1) {
+  const int size_1 = shape.FlatSize();
+  const int size_2 = check_shape_0.FlatSize();
+  const int size_3 = check_shape_1.FlatSize();
+  TFLITE_CHECK_EQ(size_1, size_2);
+  TFLITE_CHECK_EQ(size_2, size_3);
+  return size_1;
+}
+
+// Flat size calculation, checking that dimensions match with one or more other
+// arrays.
+inline int MatchingFlatSize(const RuntimeShape& shape,
+                            const RuntimeShape& check_shape_0) {
+  TFLITE_DCHECK_EQ(shape.DimensionsCount(), check_shape_0.DimensionsCount());
+  const int dims_count = shape.DimensionsCount();
+  for (int i = 0; i < dims_count; ++i) {
+    TFLITE_DCHECK_EQ(shape.Dims(i), check_shape_0.Dims(i));
+  }
+  return shape.FlatSize();
+}
+
+inline int MatchingFlatSize(const RuntimeShape& shape,
+                            const RuntimeShape& check_shape_0,
+                            const RuntimeShape& check_shape_1) {
+  TFLITE_DCHECK_EQ(shape.DimensionsCount(), check_shape_0.DimensionsCount());
+  const int dims_count = shape.DimensionsCount();
+  for (int i = 0; i < dims_count; ++i) {
+    TFLITE_DCHECK_EQ(shape.Dims(i), check_shape_0.Dims(i));
+  }
+  return MatchingFlatSize(shape, check_shape_1);
+}
+
+inline int MatchingFlatSize(const RuntimeShape& shape,
+                            const RuntimeShape& check_shape_0,
+                            const RuntimeShape& check_shape_1,
+                            const RuntimeShape& check_shape_2) {
+  TFLITE_DCHECK_EQ(shape.DimensionsCount(), check_shape_0.DimensionsCount());
+  const int dims_count = shape.DimensionsCount();
+  for (int i = 0; i < dims_count; ++i) {
+    TFLITE_DCHECK_EQ(shape.Dims(i), check_shape_0.Dims(i));
+  }
+  return MatchingFlatSize(shape, check_shape_1, check_shape_2);
+}
+
+inline int MatchingFlatSize(const RuntimeShape& shape,
+                            const RuntimeShape& check_shape_0,
+                            const RuntimeShape& check_shape_1,
+                            const RuntimeShape& check_shape_2,
+                            const RuntimeShape& check_shape_3) {
+  TFLITE_DCHECK_EQ(shape.DimensionsCount(), check_shape_0.DimensionsCount());
+  const int dims_count = shape.DimensionsCount();
+  for (int i = 0; i < dims_count; ++i) {
+    TFLITE_DCHECK_EQ(shape.Dims(i), check_shape_0.Dims(i));
+  }
+  return MatchingFlatSize(shape, check_shape_1, check_shape_2, check_shape_3);
+}
+
+// Flat size calculation, checking that dimensions match with one or more other
+// arrays.
+template <int N>
+inline int MatchingFlatSize(const Dims<N>& dims, const Dims<N>& check_dims_0) {
+  for (int i = 0; i < N; ++i) {
+    TFLITE_DCHECK_EQ(ArraySize(dims, i), ArraySize(check_dims_0, i));
+  }
+  return FlatSize(dims);
+}
+
+template <int N>
+inline int MatchingFlatSize(const Dims<N>& dims, const Dims<N>& check_dims_0,
+                            const Dims<N>& check_dims_1) {
+  for (int i = 0; i < N; ++i) {
+    TFLITE_DCHECK_EQ(ArraySize(dims, i), ArraySize(check_dims_0, i));
+  }
+  return MatchingFlatSize(dims, check_dims_1);
+}
+
+template <int N>
+inline int MatchingFlatSize(const Dims<N>& dims, const Dims<N>& check_dims_0,
+                            const Dims<N>& check_dims_1,
+                            const Dims<N>& check_dims_2) {
+  for (int i = 0; i < N; ++i) {
+    TFLITE_DCHECK_EQ(ArraySize(dims, i), ArraySize(check_dims_0, i));
+  }
+  return MatchingFlatSize(dims, check_dims_1, check_dims_2);
+}
+
+template <int N>
+inline int MatchingFlatSize(const Dims<N>& dims, const Dims<N>& check_dims_0,
+                            const Dims<N>& check_dims_1,
+                            const Dims<N>& check_dims_2,
+                            const Dims<N>& check_dims_3) {
+  for (int i = 0; i < N; ++i) {
+    TFLITE_DCHECK_EQ(ArraySize(dims, i), ArraySize(check_dims_0, i));
+  }
+  return MatchingFlatSize(dims, check_dims_1, check_dims_2, check_dims_3);
+}
+
+// Data is required to be contiguous, and so many operators can use either the
+// full array flat size or the flat size with one dimension skipped (commonly
+// the depth).
+template <int N>
+inline int FlatSizeSkipDim(const Dims<N>& dims, int skip_dim) {
+  TFLITE_DCHECK(skip_dim >= 0 && skip_dim < N);
+  int flat_size = 1;
+  for (int i = 0; i < N; ++i) {
+    flat_size *= (i == skip_dim) ? 1 : dims.sizes[i];
+  }
+  return flat_size;
+}
+
+// A combination of MatchingFlatSize() and FlatSizeSkipDim().
+template <int N>
+inline int MatchingFlatSizeSkipDim(const Dims<N>& dims, int skip_dim,
+                                   const Dims<N>& check_dims_0) {
+  for (int i = 0; i < N; ++i) {
+    if (i != skip_dim) {
+      TFLITE_DCHECK_EQ(ArraySize(dims, i), ArraySize(check_dims_0, i));
+    }
+  }
+  return FlatSizeSkipDim(dims, skip_dim);
+}
+
+template <int N>
+inline int MatchingFlatSizeSkipDim(const Dims<N>& dims, int skip_dim,
+                                   const Dims<N>& check_dims_0,
+                                   const Dims<N>& check_dims_1) {
+  for (int i = 0; i < N; ++i) {
+    if (i != skip_dim) {
+      TFLITE_DCHECK_EQ(ArraySize(dims, i), ArraySize(check_dims_0, i));
+    }
+  }
+  return MatchingFlatSizeSkipDim(dims, skip_dim, check_dims_1);
+}
+
+template <int N>
+inline int MatchingFlatSizeSkipDim(const Dims<N>& dims, int skip_dim,
+                                   const Dims<N>& check_dims_0,
+                                   const Dims<N>& check_dims_1,
+                                   const Dims<N>& check_dims_2) {
+  for (int i = 0; i < N; ++i) {
+    if (i != skip_dim) {
+      TFLITE_DCHECK_EQ(ArraySize(dims, i), ArraySize(check_dims_0, i));
+    }
+  }
+  return MatchingFlatSizeSkipDim(dims, skip_dim, check_dims_1, check_dims_2);
+}
+
+template <int N>
+inline int MatchingFlatSizeSkipDim(const Dims<N>& dims, int skip_dim,
+                                   const Dims<N>& check_dims_0,
+                                   const Dims<N>& check_dims_1,
+                                   const Dims<N>& check_dims_2,
+                                   const Dims<N>& check_dims_3) {
+  for (int i = 0; i < N; ++i) {
+    if (i != skip_dim) {
+      TFLITE_DCHECK_EQ(ArraySize(dims, i), ArraySize(check_dims_0, i));
+    }
+  }
+  return MatchingFlatSizeSkipDim(dims, skip_dim, check_dims_1, check_dims_2,
+                                 check_dims_3);
+}
+
+// Data is required to be contiguous, and so many operators can use either the
+// full array flat size or the flat size with one dimension skipped (commonly
+// the depth).
+inline int FlatSizeSkipDim(const RuntimeShape& shape, int skip_dim) {
+  const int dims_count = shape.DimensionsCount();
+  TFLITE_DCHECK(skip_dim >= 0 && skip_dim < dims_count);
+  const auto* dims_data = shape.DimsData();
+  int flat_size = 1;
+  for (int i = 0; i < dims_count; ++i) {
+    flat_size *= (i == skip_dim) ? 1 : dims_data[i];
+  }
+  return flat_size;
+}
+
+// A combination of MatchingFlatSize() and FlatSizeSkipDim().
+inline int MatchingFlatSizeSkipDim(const RuntimeShape& shape, int skip_dim,
+                                   const RuntimeShape& check_shape_0) {
+  const int dims_count = shape.DimensionsCount();
+  for (int i = 0; i < dims_count; ++i) {
+    if (i != skip_dim) {
+      TFLITE_DCHECK_EQ(shape.Dims(i), check_shape_0.Dims(i));
+    }
+  }
+  return FlatSizeSkipDim(shape, skip_dim);
+}
+
+inline int MatchingFlatSizeSkipDim(const RuntimeShape& shape, int skip_dim,
+                                   const RuntimeShape& check_shape_0,
+                                   const RuntimeShape& check_shape_1) {
+  const int dims_count = shape.DimensionsCount();
+  for (int i = 0; i < dims_count; ++i) {
+    if (i != skip_dim) {
+      TFLITE_DCHECK_EQ(shape.Dims(i), check_shape_0.Dims(i));
+    }
+  }
+  return MatchingFlatSizeSkipDim(shape, skip_dim, check_shape_1);
+}
+
+inline int MatchingFlatSizeSkipDim(const RuntimeShape& shape, int skip_dim,
+                                   const RuntimeShape& check_shape_0,
+                                   const RuntimeShape& check_shape_1,
+                                   const RuntimeShape& check_shape_2) {
+  const int dims_count = shape.DimensionsCount();
+  for (int i = 0; i < dims_count; ++i) {
+    if (i != skip_dim) {
+      TFLITE_DCHECK_EQ(shape.Dims(i), check_shape_0.Dims(i));
+    }
+  }
+  return MatchingFlatSizeSkipDim(shape, skip_dim, check_shape_1, check_shape_2);
+}
+
+inline int MatchingFlatSizeSkipDim(const RuntimeShape& shape, int skip_dim,
+                                   const RuntimeShape& check_shape_0,
+                                   const RuntimeShape& check_shape_1,
+                                   const RuntimeShape& check_shape_2,
+                                   const RuntimeShape& check_shape_3) {
+  const int dims_count = shape.DimensionsCount();
+  for (int i = 0; i < dims_count; ++i) {
+    if (i != skip_dim) {
+      TFLITE_DCHECK_EQ(shape.Dims(i), check_shape_0.Dims(i));
+    }
+  }
+  return MatchingFlatSizeSkipDim(shape, skip_dim, check_shape_1, check_shape_2,
+                                 check_shape_3);
+}
+
+template <int N>
+bool IsPackedWithoutStrides(const Dims<N>& dims) {
+  int expected_stride = 1;
+  for (int d = 0; d < N; d++) {
+    if (dims.strides[d] != expected_stride) return false;
+    expected_stride *= dims.sizes[d];
+  }
+  return true;
+}
+
+template <int N>
+void ComputeStrides(Dims<N>* dims) {
+  dims->strides[0] = 1;
+  for (int d = 1; d < N; d++) {
+    dims->strides[d] = dims->strides[d - 1] * dims->sizes[d - 1];
+  }
+}
+
+enum class BroadcastableOpCategory : uint8 {
+  kNone,
+  kNonBroadcast,               // Matching input shapes.
+  kFirstInputBroadcastsFast,   // Fivefold nested loops.
+  kSecondInputBroadcastsFast,  // Fivefold nested loops.
+  kGenericBroadcast,           // Fall-back.
+};
+
+struct MinMax {
+  float min;
+  float max;
+};
+static_assert(sizeof(MinMax) == 8, "");
+
+struct ActivationParams {
+  FusedActivationFunctionType activation_type;
+  // uint8, etc, activation params.
+  int32 quantized_activation_min;
+  int32 quantized_activation_max;
+};
+
+struct ReluParams : public ActivationParams {
+  int32 input_offset;
+  int32 output_offset;
+  int32 output_multiplier;
+  int32 output_shift;
+};
+
+// Styles of resizing op usages. For example, kImageStyle can be used with a Pad
+// op for pattern-specific optimization.
+enum class ResizingCategory : uint8 {
+  kNone,
+  kImageStyle,  // 4D, operating on inner dimensions, say {0, a, b, 0}.
+  kGenericResize,
+};
+
+// For Add, Sub, Mul ops.
+struct ArithmeticParams {
+  // Shape dependent / common to data / op types.
+  BroadcastableOpCategory broadcast_category;
+  // uint8 inference params.
+  int32 input1_offset;
+  int32 input2_offset;
+  int32 output_offset;
+  int32 output_multiplier;
+  int output_shift;
+  // Add / Sub, not Mul, uint8 inference params.
+  int left_shift;
+  int32 input1_multiplier;
+  int input1_shift;
+  int32 input2_multiplier;
+  int input2_shift;
+  // uint8, etc, activation params.
+  int32 quantized_activation_min;
+  int32 quantized_activation_max;
+  // float activation params.
+  float float_activation_min;
+  float float_activation_max;
+
+  // Processed output dimensions.
+  // Let input "a" be the one that broadcasts in the faster-changing dimension.
+  // Then, after coalescing, for shapes {a0, a1, a2, a3, a4} and
+  // {b0, b1, b2, b3, b4},
+  // broadcast_shape[4] = b0 = a0.
+  // broadcast_shape[3] = b1; a1 = 1.
+  // broadcast_shape[2] = b2 = a2.
+  // broadcast_shape[1] = a3; b3 = 1.
+  // broadcast_shape[0] = b4 = a4.
+  int broadcast_shape[5];
+};
+
+struct ConcatenationParams {
+  int8 axis;
+  const int32* input_zeropoint;
+  const float* input_scale;
+  uint16 inputs_count;
+  int32 output_zeropoint;
+  float output_scale;
+};
+
+struct ComparisonParams {
+  // uint8 inference params.
+  int left_shift;
+  int32 input1_offset;
+  int32 input1_multiplier;
+  int input1_shift;
+  int32 input2_offset;
+  int32 input2_multiplier;
+  int input2_shift;
+  // Shape dependent / common to inference types.
+  bool is_broadcast;
+};
+
+struct ConvParams {
+  PaddingType padding_type;
+  PaddingValues padding_values;
+  // TODO(starka): This was just "stride", so check that width+height is OK.
+  int16 stride_width;
+  int16 stride_height;
+  int16 dilation_width_factor;
+  int16 dilation_height_factor;
+  // uint8 inference params.
+  // TODO(b/65838351): Use smaller types if appropriate.
+  int32 input_offset;
+  int32 weights_offset;
+  int32 output_offset;
+  int32 output_multiplier;
+  int output_shift;
+  // uint8, etc, activation params.
+  int32 quantized_activation_min;
+  int32 quantized_activation_max;
+  // float activation params.
+  float float_activation_min;
+  float float_activation_max;
+};
+
+struct DepthToSpaceParams {
+  int32 block_size;
+};
+
+struct DepthwiseParams {
+  PaddingType padding_type;
+  PaddingValues padding_values;
+  int16 stride_width;
+  int16 stride_height;
+  int16 dilation_width_factor;
+  int16 dilation_height_factor;
+  int16 depth_multiplier;
+  // uint8 inference params.
+  // TODO(b/65838351): Use smaller types if appropriate.
+  int32 input_offset;
+  int32 weights_offset;
+  int32 output_offset;
+  int32 output_multiplier;
+  int output_shift;
+  // uint8, etc, activation params.
+  int32 quantized_activation_min;
+  int32 quantized_activation_max;
+  // float activation params.
+  float float_activation_min;
+  float float_activation_max;
+};
+
+struct DequantizationParams {
+  double scale;
+  int32 zero_point;
+};
+
+struct FakeQuantParams {
+  MinMax minmax;
+  int32 num_bits;
+};
+
+struct FullyConnectedParams {
+  // uint8 inference params.
+  // TODO(b/65838351): Use smaller types if appropriate.
+  int32 input_offset;
+  int32 weights_offset;
+  int32 output_offset;
+  int32 output_multiplier;
+  int output_shift;
+  // uint8, etc, activation params.
+  int32 quantized_activation_min;
+  int32 quantized_activation_max;
+  // float activation params.
+  float float_activation_min;
+  float float_activation_max;
+  FullyConnectedWeightsFormat weights_format;
+};
+
+struct GatherParams {
+  int16 axis;
+};
+
+struct L2NormalizationParams {
+  // uint8 inference params.
+  int32 input_zero_point;
+};
+
+struct LocalResponseNormalizationParams {
+  int32 range;
+  double bias;
+  double alpha;
+  double beta;
+};
+
+struct HardSwishParams {
+  // zero_point of the input activations.
+  int16_t input_zero_point;
+  // zero_point of the output activations.
+  int16_t output_zero_point;
+  // 16bit fixed-point component of the multiplier to apply to go from the
+  // "high-res input scale", which is the input scale multiplied by 2^7, to the
+  // "relu-ish scale", which 3.0/32768.
+  // See the implementation of HardSwishPrepare.
+  int16_t reluish_multiplier_fixedpoint_int16;
+  // exponent/bit-shift component of the aforementioned multiplier.
+  int reluish_multiplier_exponent;
+  // 16bit fixed-point component of the multiplier to apply to go from the
+  // "high-res input scale", which is the input scale multiplied by 2^7, to the
+  // output scale.
+  // See the implementation of HardSwishPrepare.
+  int16_t output_multiplier_fixedpoint_int16;
+  // exponent/bit-shift component of the aforementioned multiplier.
+  int output_multiplier_exponent;
+};
+
+struct LogisticParams {
+  // uint8 inference params.
+  int32 input_zero_point;
+  int32 input_range_radius;
+  int32 input_multiplier;
+  int input_left_shift;
+};
+
+struct LstmCellParams {
+  int32 weights_zero_point;
+  int32 accum_multiplier;
+  int accum_shift;
+  int state_integer_bits;
+};
+
+struct MeanParams {
+  int8 axis_count;
+  int16 axis[4];
+};
+
+struct PackParams {
+  int8 axis;
+  const int32* input_zeropoint;
+  const float* input_scale;
+  uint16 inputs_count;
+  int32 output_zeropoint;
+  float output_scale;
+};
+
+struct PadParams {
+  int8 left_padding_count;
+  int32 left_padding[4];
+  int8 right_padding_count;
+  int32 right_padding[4];
+  ResizingCategory resizing_category;
+};
+
+struct PreluParams {
+  int32 input_offset;
+  int32 alpha_offset;
+  int32 output_offset;
+  int32 output_multiplier;
+  int output_shift;
+};
+
+struct PoolParams {
+  FusedActivationFunctionType activation;
+  PaddingType padding_type;
+  PaddingValues padding_values;
+  int stride_height;
+  int stride_width;
+  int filter_height;
+  int filter_width;
+  // uint8, etc, activation params.
+  int32 quantized_activation_min;
+  int32 quantized_activation_max;
+  // float activation params.
+  float float_activation_min;
+  float float_activation_max;
+};
+
+struct ReshapeParams {
+  int8 shape_count;
+  int32 shape[4];
+};
+
+struct ResizeBilinearParams {
+  bool align_corners;
+};
+
+struct ResizeNearestNeighborParams {
+  bool align_corners;
+};
+
+struct SliceParams {
+  int8 begin_count;
+  int32 begin[4];
+  int8 size_count;
+  int32 size[4];
+};
+
+struct SoftmaxParams {
+  // beta is not really used (not a Tensorflow parameter) and not implemented
+  // for LogSoftmax.
+  double beta;
+  // uint8 inference params.  Used even when beta defaults to 1.0.
+  int32 input_multiplier;
+  int32 input_left_shift;
+  // Reverse scaling is only used by LogSoftmax.
+  int32 reverse_scaling_divisor;
+  int32 reverse_scaling_right_shift;
+  int diff_min;
+  int32_t zero_point;
+  float scale;
+  float* table;
+};
+
+struct SpaceToBatchParams {
+  // "Zero" padding for uint8 means padding with the output offset.
+  int32 output_offset;
+};
+
+struct SpaceToDepthParams {
+  int32 block_size;
+};
+
+struct SplitParams {
+  // Graphs that split into, say, 2000 nodes are encountered.  The indices in
+  // OperatorEdges are of type uint16.
+  uint16 num_split;
+  int16 axis;
+};
+
+struct SqueezeParams {
+  int8 squeeze_dims_count;
+  int32 squeeze_dims[4];
+};
+
+struct StridedSliceParams {
+  int8 start_indices_count;
+  int16 start_indices[4];
+  int8 stop_indices_count;
+  int16 stop_indices[4];
+  int8 strides_count;
+  int16 strides[4];
+
+  int16 begin_mask;
+  int16 ellipsis_mask;
+  int16 end_mask;
+  int16 new_axis_mask;
+  int16 shrink_axis_mask;
+};
+
+struct TanhParams {
+  int32 input_zero_point;
+  int32 input_range_radius;
+  int32 input_multiplier;
+  int input_left_shift;
+};
+
+struct TransposeParams {
+  int8 perm_count;
+  int32 perm[4];
+};
+
+struct UnpackParams {
+  uint16 num_split;
+  int16 axis;
+};
+
+struct LeakyReluParams {
+  float alpha;
+  int32 input_offset;
+  int32 alpha_offset;
+  int32 output_offset;
+  int32 output_multiplier;
+  int output_shift;
+};
+
+template <typename P>
+inline void SetActivationParams(float min, float max, P* params) {
+  params->float_activation_min = min;
+  params->float_activation_max = max;
+}
+
+template <typename P>
+inline void SetActivationParams(int32 min, int32 max, P* params) {
+  params->quantized_activation_min = min;
+  params->quantized_activation_max = max;
+}
+
+template <typename P>
+inline void GetActivationParams(const P& params, int32* min, int32* max) {
+  *min = params.quantized_activation_min;
+  *max = params.quantized_activation_max;
+}
+
+template <typename P>
+inline void GetActivationParams(const P& params, float* min, float* max) {
+  *min = params.float_activation_min;
+  *max = params.float_activation_max;
+}
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_TYPES_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/kernel_util.cc
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/kernel_util.cc	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,228 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/lite/kernels/kernel_util.h"
+
+#include <algorithm>
+#include <cmath>
+#include <memory>
+
+#include "tensorflow/lite/kernels/internal/quantization_util.h"
+#include "tensorflow/lite/kernels/internal/round.h"
+
+namespace tflite {
+
+TfLiteStatus PopulateConvolutionQuantizationParams(
+    TfLiteContext* context, const TfLiteTensor* input,
+    const TfLiteTensor* filter, const TfLiteTensor* bias, TfLiteTensor* output,
+    const TfLiteFusedActivation& activation, int32_t* multiplier, int* shift,
+    int32_t* output_activation_min, int32_t* output_activation_max,
+    int32_t* per_channel_multiplier, int* per_channel_shift) {
+  TF_LITE_ENSURE_EQ(context, input->quantization.type,
+                    kTfLiteAffineQuantization);
+  TF_LITE_ENSURE_EQ(context, filter->quantization.type,
+                    kTfLiteAffineQuantization);
+  // TODO(jianlijianli): Enable bias type check and bias scale == input scale
+  // * filter scale for each channel in affine quantization once bias
+  // quantization is properly populated.
+  // TF_LITE_ENSURE_EQ(context, bias->quantization.type,
+  // kTfLiteAffineQuantization);
+
+  // Check data type.
+  const auto* affine_quantization =
+      reinterpret_cast<TfLiteAffineQuantization*>(filter->quantization.params);
+  TF_LITE_ENSURE(context, affine_quantization);
+  TF_LITE_ENSURE(context, affine_quantization->scale);
+  const bool is_per_channel = affine_quantization->scale->size > 1;
+  if (is_per_channel) {
+    //  Currently only Int8 is supported for per channel quantization.
+    TF_LITE_ENSURE_EQ(context, input->type, kTfLiteInt8);
+    TF_LITE_ENSURE_EQ(context, filter->type, kTfLiteInt8);
+    TF_LITE_ENSURE_EQ(
+        context, affine_quantization->scale->size,
+        filter->dims->data[affine_quantization->quantized_dimension]);
+  }
+
+  // Populate multiplier and shift using affine quantization.
+  const int num_channels = affine_quantization->scale->size;
+  const float input_scale = input->params.scale;
+  const float output_scale = output->params.scale;
+  const float* filter_scales = affine_quantization->scale->data;
+  for (int i = 0; i < num_channels; ++i) {
+    const double filter_scale = static_cast<double>(filter_scales[i]);
+    const double effective_output_scale = static_cast<double>(input_scale) *
+                                          filter_scale /
+                                          static_cast<double>(output_scale);
+    int32_t significand;
+    int shift;
+    QuantizeMultiplier(effective_output_scale, &significand, &shift);
+    per_channel_multiplier[i] = significand;
+    per_channel_shift[i] = shift;
+  }
+
+  // Populate scalar quantization parameters.
+  // This check on legacy quantization parameters is kept only for backward
+  // compatibility.
+  if (input->type == kTfLiteUInt8) {
+    // Check bias scale == input scale * filter scale.
+    double real_multiplier = 0.0;
+    TF_LITE_ENSURE_STATUS(GetQuantizedConvolutionMultipler(
+        context, input, filter, bias, output, &real_multiplier));
+    int exponent;
+
+    // Populate quantization parameteters with multiplier and shift.
+    QuantizeMultiplier(real_multiplier, multiplier, &exponent);
+    *shift = -exponent;
+    CalculateActivationRangeUint8(activation, output, output_activation_min,
+                                  output_activation_max);
+  }
+  return kTfLiteOk;
+}
+
+TfLiteStatus GetQuantizedConvolutionMultipler(TfLiteContext* context,
+                                              const TfLiteTensor* input,
+                                              const TfLiteTensor* filter,
+                                              const TfLiteTensor* bias,
+                                              TfLiteTensor* output,
+                                              double* multiplier) {
+  const double input_product_scale = input->params.scale * filter->params.scale;
+  // TODO(ahentz): The following conditions must be guaranteed by the training
+  // pipeline.
+  if (bias) {
+    const double bias_scale = bias->params.scale;
+    TF_LITE_ENSURE(context,
+                   std::abs(input_product_scale - bias_scale) <=
+                       1e-6 * std::min(input_product_scale, bias_scale));
+  }
+  return GetQuantizedConvolutionMultipler(context, input, filter, output,
+                                          multiplier);
+}
+
+TfLiteStatus GetQuantizedConvolutionMultipler(TfLiteContext* context,
+                                              const TfLiteTensor* input,
+                                              const TfLiteTensor* filter,
+                                              TfLiteTensor* output,
+                                              double* multiplier) {
+  const double input_product_scale = input->params.scale * filter->params.scale;
+  TF_LITE_ENSURE(context, input_product_scale >= 0);
+  *multiplier = input_product_scale / output->params.scale;
+
+  return kTfLiteOk;
+}
+
+namespace {
+void CalculateActivationRangeQuantizedImpl(TfLiteFusedActivation activation,
+                                           int32_t qmin, int32_t qmax,
+                                           TfLiteTensor* output,
+                                           int32_t* act_min, int32_t* act_max) {
+  const auto scale = output->params.scale;
+  const auto zero_point = output->params.zero_point;
+
+  auto quantize = [scale, zero_point](float f) {
+    return zero_point + static_cast<int32_t>(TfLiteRound(f / scale));
+  };
+
+  if (activation == kTfLiteActRelu) {
+    *act_min = std::max(qmin, quantize(0.0));
+    *act_max = qmax;
+  } else if (activation == kTfLiteActRelu6) {
+    *act_min = std::max(qmin, quantize(0.0));
+    *act_max = std::min(qmax, quantize(6.0));
+  } else if (activation == kTfLiteActRelu1) {
+    *act_min = std::max(qmin, quantize(-1.0));
+    *act_max = std::min(qmax, quantize(1.0));
+  } else {
+    *act_min = qmin;
+    *act_max = qmax;
+  }
+}
+}  // namespace
+
+TfLiteStatus CalculateActivationRangeQuantized(TfLiteContext* context,
+                                               TfLiteFusedActivation activation,
+                                               TfLiteTensor* output,
+                                               int32_t* act_min,
+                                               int32_t* act_max) {
+  int32_t qmin = 0;
+  int32_t qmax = 0;
+  if (output->type == kTfLiteUInt8) {
+    qmin = std::numeric_limits<uint8_t>::min();
+    qmax = std::numeric_limits<uint8_t>::max();
+  } else if (output->type == kTfLiteInt8) {
+    qmin = std::numeric_limits<int8_t>::min();
+    qmax = std::numeric_limits<int8_t>::max();
+  } else if (output->type == kTfLiteInt16) {
+    qmin = std::numeric_limits<int16_t>::min();
+    qmax = std::numeric_limits<int16_t>::max();
+  } else {
+    TF_LITE_ENSURE(context, false);
+  }
+
+  CalculateActivationRangeQuantizedImpl(activation, qmin, qmax, output, act_min,
+                                        act_max);
+  return kTfLiteOk;
+}
+
+void CalculateActivationRangeUint8(TfLiteFusedActivation activation,
+                                   TfLiteTensor* output, int32_t* act_min,
+                                   int32_t* act_max) {
+  const int32_t qmin = std::numeric_limits<uint8_t>::min();
+  const int32_t qmax = std::numeric_limits<uint8_t>::max();
+
+  CalculateActivationRangeQuantizedImpl(activation, qmin, qmax, output, act_min,
+                                        act_max);
+}
+
+void CalculateActivationRangeInt8(TfLiteFusedActivation activation,
+                                  TfLiteTensor* output, int32_t* act_min,
+                                  int32_t* act_max) {
+  const int32_t qmin = std::numeric_limits<int8_t>::min();
+  const int32_t qmax = std::numeric_limits<int8_t>::max();
+
+  CalculateActivationRangeQuantizedImpl(activation, qmin, qmax, output, act_min,
+                                        act_max);
+}
+
+bool HaveSameShapes(const TfLiteTensor* input1, const TfLiteTensor* input2) {
+  return TfLiteIntArrayEqual(input1->dims, input2->dims);
+}
+
+// TODO(petewarden): Having macros around this is ugly, look at other strategies
+// before replicating this approach elsewhere.
+#ifndef TF_LITE_STATIC_MEMORY
+TfLiteStatus CalculateShapeForBroadcast(TfLiteContext* context,
+                                        const TfLiteTensor* input1,
+                                        const TfLiteTensor* input2,
+                                        TfLiteIntArray** output_shape) {
+  int64_t dims1 = NumDimensions(input1);
+  int64_t dims2 = NumDimensions(input2);
+  int64_t out_dims = std::max(dims1, dims2);
+  if (NumElements(input1) == 0) {
+    *output_shape = TfLiteIntArrayCopy(input1->dims);
+    return kTfLiteOk;
+  }
+  std::unique_ptr<TfLiteIntArray, void (*)(TfLiteIntArray*)> shape(
+      TfLiteIntArrayCreate(out_dims), TfLiteIntArrayFree);
+  for (int i = 0; i < out_dims; ++i) {
+    int64_t d1 = i >= dims1 ? 1 : SizeOfDimension(input1, dims1 - i - 1);
+    int64_t d2 = i >= dims2 ? 1 : SizeOfDimension(input2, dims2 - i - 1);
+    TF_LITE_ENSURE(context, d1 == d2 || d1 == 1 || d2 == 1);
+    shape->data[out_dims - i - 1] = std::max(d1, d2);
+  }
+  *output_shape = shape.release();
+  return kTfLiteOk;
+}
+#endif  // TF_LITE_STATIC_MEMORY
+
+}  // namespace tflite

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/kernel_util.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/kernel_util.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,179 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_KERNEL_UTIL_H_
+#define TENSORFLOW_LITE_KERNELS_KERNEL_UTIL_H_
+
+#include <algorithm>
+#include <limits>
+
+#include "flatbuffers/flatbuffers.h"
+#include "tensorflow/lite/c/builtin_op_data.h"
+#include "tensorflow/lite/c/c_api_internal.h"
+
+namespace tflite {
+
+inline int NumDimensions(const TfLiteTensor* t) { return t->dims->size; }
+inline int SizeOfDimension(const TfLiteTensor* t, int dim) {
+  return t->dims->data[dim];
+}
+inline const TfLiteTensor* GetInput(TfLiteContext* context,
+                                    const TfLiteNode* node, int index) {
+  return &context
+              ->tensors[flatbuffers::EndianScalar(node->inputs->data[index])];
+}
+inline TfLiteTensor* GetVariableInput(TfLiteContext* context,
+                                      const TfLiteNode* node, int index) {
+  TfLiteTensor* tensor =
+      &context->tensors[flatbuffers::EndianScalar(node->inputs->data[index])];
+  return (tensor->is_variable) ? tensor : nullptr;
+}
+inline TfLiteTensor* GetOutput(TfLiteContext* context, const TfLiteNode* node,
+                               int index) {
+  return &context
+              ->tensors[flatbuffers::EndianScalar(node->outputs->data[index])];
+}
+inline TfLiteTensor* GetTemporary(TfLiteContext* context,
+                                  const TfLiteNode* node, int index) {
+  return &context->tensors[flatbuffers::EndianScalar(
+      node->temporaries->data[index])];
+}
+inline const TfLiteTensor* GetIntermediates(TfLiteContext* context,
+                                            const TfLiteNode* node, int index) {
+  return &context->tensors[node->intermediates->data[index]];
+}
+inline int NumInputs(const TfLiteNode* node) { return node->inputs->size; }
+inline int NumOutputs(const TfLiteNode* node) { return node->outputs->size; }
+inline int NumIntermediates(const TfLiteNode* node) {
+  return node->intermediates->size;
+}
+
+inline int64_t NumElements(const TfLiteIntArray* dims) {
+  int64_t count = 1;
+  for (int i = 0; i < dims->size; ++i) {
+    count *= dims->data[i];
+  }
+  return count;
+}
+
+inline int64_t NumElements(const TfLiteTensor* t) {
+  return NumElements(t->dims);
+}
+
+inline const TfLiteTensor* GetOptionalInputTensor(TfLiteContext* context,
+                                                  const TfLiteNode* node,
+                                                  int index) {
+  const bool use_tensor = node->inputs->data[index] != kOptionalTensor;
+  if (use_tensor) {
+    return &context
+                ->tensors[flatbuffers::EndianScalar(node->inputs->data[index])];
+  }
+  return nullptr;
+}
+
+// Determines whether tensor is constant.
+inline bool IsConstantTensor(const TfLiteTensor* tensor) {
+  return tensor->allocation_type == kTfLiteMmapRo;
+}
+
+// Determines whether tensor is dynamic. Note that a tensor can be non-const and
+// not dynamic. This function specifically checks for a dynamic tensor.
+inline bool IsDynamicTensor(const TfLiteTensor* tensor) {
+  return tensor->allocation_type == kTfLiteDynamic;
+}
+
+// Sets tensor to dynamic.
+inline void SetTensorToDynamic(TfLiteTensor* tensor) {
+  if (tensor->allocation_type != kTfLiteDynamic) {
+    tensor->allocation_type = kTfLiteDynamic;
+    tensor->data.raw = nullptr;
+  }
+}
+
+// Determines whether it is a hybrid op - one that has float inputs and
+// quantized weights.
+inline bool IsHybridOp(const TfLiteTensor* input, const TfLiteTensor* weight) {
+  return ((weight->type == kTfLiteUInt8 || weight->type == kTfLiteInt8) &&
+          input->type == kTfLiteFloat32);
+}
+
+// Check dimensionality match and populate OpData for Conv and DepthwiseConv.
+TfLiteStatus PopulateConvolutionQuantizationParams(
+    TfLiteContext* context, const TfLiteTensor* input,
+    const TfLiteTensor* filter, const TfLiteTensor* bias, TfLiteTensor* output,
+    const TfLiteFusedActivation& activation, int32_t* multiplier, int* shift,
+    int32_t* output_activation_min, int32_t* output_activation_max,
+    int32_t* per_channel_multiplier, int* per_channel_shift);
+
+// Calculates the multiplication factor for a quantized convolution (or
+// quantized depthwise convolution) involving the given tensors. Returns an
+// error if the scales of the tensors are not compatible.
+TfLiteStatus GetQuantizedConvolutionMultipler(TfLiteContext* context,
+                                              const TfLiteTensor* input,
+                                              const TfLiteTensor* filter,
+                                              const TfLiteTensor* bias,
+                                              TfLiteTensor* output,
+                                              double* multiplier);
+
+TfLiteStatus GetQuantizedConvolutionMultipler(TfLiteContext* context,
+                                              const TfLiteTensor* input,
+                                              const TfLiteTensor* filter,
+                                              TfLiteTensor* output,
+                                              double* multiplier);
+
+// Calculates the useful quantized range of an activation layer given its
+// activation tensor.
+TfLiteStatus CalculateActivationRangeQuantized(TfLiteContext* context,
+                                               TfLiteFusedActivation activation,
+                                               TfLiteTensor* output,
+                                               int32_t* act_min,
+                                               int32_t* act_max);
+void CalculateActivationRangeUint8(TfLiteFusedActivation activation,
+                                   TfLiteTensor* output, int32_t* act_min,
+                                   int32_t* act_max);
+void CalculateActivationRangeInt8(TfLiteFusedActivation activation,
+                                  TfLiteTensor* output, int32_t* act_min,
+                                  int32_t* act_max);
+// Calculates the useful range of an activation layer given its activation
+// tensor.a
+template <typename T>
+void CalculateActivationRange(TfLiteFusedActivation activation,
+                              T* activation_min, T* activation_max) {
+  if (activation == kTfLiteActRelu) {
+    *activation_min = 0;
+    *activation_max = std::numeric_limits<T>::max();
+  } else if (activation == kTfLiteActRelu6) {
+    *activation_min = 0;
+    *activation_max = 6;
+  } else if (activation == kTfLiteActRelu1) {
+    *activation_min = -1;
+    *activation_max = 1;
+  } else {
+    *activation_min = std::numeric_limits<T>::lowest();
+    *activation_max = std::numeric_limits<T>::max();
+  }
+}
+
+// Return true if the given tensors have the same shape.
+bool HaveSameShapes(const TfLiteTensor* input1, const TfLiteTensor* input2);
+
+// Calculate the output_shape that is necessary for element-wise operations
+// with broadcasting involving the two input tensors.
+TfLiteStatus CalculateShapeForBroadcast(TfLiteContext* context,
+                                        const TfLiteTensor* input1,
+                                        const TfLiteTensor* input2,
+                                        TfLiteIntArray** output_shape);
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_KERNEL_UTIL_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/op_macros.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/op_macros.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,75 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_OP_MACROS_H_
+#define TENSORFLOW_LITE_KERNELS_OP_MACROS_H_
+
+// If we're on a platform without standard IO functions, fall back to a
+// non-portable function.
+#ifdef TF_LITE_MCU_DEBUG_LOG
+
+#include "tensorflow/lite/experimental/micro/micro_error_reporter.h"
+
+#define DEBUG_LOG(x) \
+  do {               \
+    DebugLog(x);     \
+  } while (0)
+
+inline void InfiniteLoop() {
+  DEBUG_LOG("HALTED\n");
+  while (1) {
+  }
+}
+#define TFLITE_ASSERT_FALSE InfiniteLoop();
+#define TFLITE_ABORT InfiniteLoop();
+
+#else  // TF_LITE_MCU_DEBUG_LOG
+
+#include <cassert>
+#include <cstdio>
+#include <cstdlib>
+
+#define DEBUG_LOG(x)            \
+  do {                          \
+    fprintf(stderr, "%s", (x)); \
+  } while (0)
+
+#define TFLITE_ABORT abort()
+
+#ifdef NDEBUG
+#define TFLITE_ASSERT_FALSE (static_cast<void>(0))
+#else
+#define TFLITE_ASSERT_FALSE TFLITE_ABORT
+#endif
+
+#endif  // TF_LITE_MCU_DEBUG_LOG
+
+#define TF_LITE_FATAL(msg)  \
+  do {                      \
+    DEBUG_LOG(msg);         \
+    DEBUG_LOG("\nFATAL\n"); \
+    TFLITE_ABORT;           \
+  } while (0)
+
+#define TF_LITE_ASSERT(x)        \
+  do {                           \
+    if (!(x)) TF_LITE_FATAL(#x); \
+  } while (0)
+
+#define TF_LITE_ASSERT_EQ(x, y)                            \
+  do {                                                     \
+    if ((x) != (y)) TF_LITE_FATAL(#x " didn't equal " #y); \
+  } while (0)
+
+#endif  // TENSORFLOW_LITE_KERNELS_OP_MACROS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/kernels/padding.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/kernels/padding.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,80 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_KERNELS_PADDING_H_
+#define TENSORFLOW_LITE_KERNELS_PADDING_H_
+
+#include "tensorflow/lite/c/builtin_op_data.h"
+
+namespace tflite {
+
+// TODO(renjieliu): Migrate others to use ComputePaddingWithLeftover.
+inline int ComputePadding(int stride, int dilation_rate, int in_size,
+                          int filter_size, int out_size) {
+  int effective_filter_size = (filter_size - 1) * dilation_rate + 1;
+  int padding = ((out_size - 1) * stride + effective_filter_size - in_size) / 2;
+  return padding > 0 ? padding : 0;
+}
+
+// It's not guaranteed that padding is symmetric. It's important to keep
+// offset for algorithms need all paddings.
+inline int ComputePaddingWithOffset(int stride, int dilation_rate, int in_size,
+                                    int filter_size, int out_size,
+                                    int* offset) {
+  int effective_filter_size = (filter_size - 1) * dilation_rate + 1;
+  int total_padding =
+      ((out_size - 1) * stride + effective_filter_size - in_size);
+  total_padding = total_padding > 0 ? total_padding : 0;
+  *offset = total_padding % 2;
+  return total_padding / 2;
+}
+
+// Matching GetWindowedOutputSize in TensorFlow.
+inline int ComputeOutSize(TfLitePadding padding, int image_size,
+                          int filter_size, int stride, int dilation_rate = 1) {
+  int effective_filter_size = (filter_size - 1) * dilation_rate + 1;
+  switch (padding) {
+    case kTfLitePaddingSame:
+      return (image_size + stride - 1) / stride;
+    case kTfLitePaddingValid:
+      return (image_size + stride - effective_filter_size) / stride;
+    default:
+      return 0;
+  }
+}
+
+inline TfLitePaddingValues ComputePaddingHeightWidth(
+    int stride_height, int stride_width, int dilation_rate_height,
+    int dilation_rate_width, int in_height, int in_width, int filter_height,
+    int filter_width, TfLitePadding padding, int* out_height, int* out_width) {
+  *out_width = ComputeOutSize(padding, in_width, filter_width, stride_width,
+                              dilation_rate_width);
+  *out_height = ComputeOutSize(padding, in_height, filter_height, stride_height,
+                               dilation_rate_height);
+
+  TfLitePaddingValues padding_values;
+  int offset = 0;
+  padding_values.height =
+      ComputePaddingWithOffset(stride_height, dilation_rate_height, in_height,
+                               filter_height, *out_height, &offset);
+  padding_values.height_offset = offset;
+  padding_values.width =
+      ComputePaddingWithOffset(stride_width, dilation_rate_width, in_width,
+                               filter_width, *out_width, &offset);
+  padding_values.width_offset = offset;
+  return padding_values;
+}
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_KERNELS_PADDING_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/schema/schema_generated.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/schema/schema_generated.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,14743 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+// automatically generated by the FlatBuffers compiler, do not modify
+
+
+#ifndef FLATBUFFERS_GENERATED_SCHEMA_TFLITE_H_
+#define FLATBUFFERS_GENERATED_SCHEMA_TFLITE_H_
+
+#include "flatbuffers/flatbuffers.h"
+
+namespace tflite {
+
+struct CustomQuantization;
+struct CustomQuantizationT;
+
+struct QuantizationParameters;
+struct QuantizationParametersT;
+
+struct Tensor;
+struct TensorT;
+
+struct Conv2DOptions;
+struct Conv2DOptionsT;
+
+struct Pool2DOptions;
+struct Pool2DOptionsT;
+
+struct DepthwiseConv2DOptions;
+struct DepthwiseConv2DOptionsT;
+
+struct ConcatEmbeddingsOptions;
+struct ConcatEmbeddingsOptionsT;
+
+struct LSHProjectionOptions;
+struct LSHProjectionOptionsT;
+
+struct SVDFOptions;
+struct SVDFOptionsT;
+
+struct RNNOptions;
+struct RNNOptionsT;
+
+struct SequenceRNNOptions;
+struct SequenceRNNOptionsT;
+
+struct BidirectionalSequenceRNNOptions;
+struct BidirectionalSequenceRNNOptionsT;
+
+struct FullyConnectedOptions;
+struct FullyConnectedOptionsT;
+
+struct SoftmaxOptions;
+struct SoftmaxOptionsT;
+
+struct ConcatenationOptions;
+struct ConcatenationOptionsT;
+
+struct AddOptions;
+struct AddOptionsT;
+
+struct MulOptions;
+struct MulOptionsT;
+
+struct L2NormOptions;
+struct L2NormOptionsT;
+
+struct LocalResponseNormalizationOptions;
+struct LocalResponseNormalizationOptionsT;
+
+struct LSTMOptions;
+struct LSTMOptionsT;
+
+struct UnidirectionalSequenceLSTMOptions;
+struct UnidirectionalSequenceLSTMOptionsT;
+
+struct BidirectionalSequenceLSTMOptions;
+struct BidirectionalSequenceLSTMOptionsT;
+
+struct ResizeBilinearOptions;
+struct ResizeBilinearOptionsT;
+
+struct ResizeNearestNeighborOptions;
+struct ResizeNearestNeighborOptionsT;
+
+struct CallOptions;
+struct CallOptionsT;
+
+struct PadOptions;
+struct PadOptionsT;
+
+struct PadV2Options;
+struct PadV2OptionsT;
+
+struct ReshapeOptions;
+struct ReshapeOptionsT;
+
+struct SpaceToBatchNDOptions;
+struct SpaceToBatchNDOptionsT;
+
+struct BatchToSpaceNDOptions;
+struct BatchToSpaceNDOptionsT;
+
+struct SkipGramOptions;
+struct SkipGramOptionsT;
+
+struct SpaceToDepthOptions;
+struct SpaceToDepthOptionsT;
+
+struct DepthToSpaceOptions;
+struct DepthToSpaceOptionsT;
+
+struct SubOptions;
+struct SubOptionsT;
+
+struct DivOptions;
+struct DivOptionsT;
+
+struct TopKV2Options;
+struct TopKV2OptionsT;
+
+struct EmbeddingLookupSparseOptions;
+struct EmbeddingLookupSparseOptionsT;
+
+struct GatherOptions;
+struct GatherOptionsT;
+
+struct TransposeOptions;
+struct TransposeOptionsT;
+
+struct ExpOptions;
+struct ExpOptionsT;
+
+struct CosOptions;
+struct CosOptionsT;
+
+struct ReducerOptions;
+struct ReducerOptionsT;
+
+struct SqueezeOptions;
+struct SqueezeOptionsT;
+
+struct SplitOptions;
+struct SplitOptionsT;
+
+struct SplitVOptions;
+struct SplitVOptionsT;
+
+struct StridedSliceOptions;
+struct StridedSliceOptionsT;
+
+struct LogSoftmaxOptions;
+struct LogSoftmaxOptionsT;
+
+struct CastOptions;
+struct CastOptionsT;
+
+struct DequantizeOptions;
+struct DequantizeOptionsT;
+
+struct MaximumMinimumOptions;
+struct MaximumMinimumOptionsT;
+
+struct TileOptions;
+struct TileOptionsT;
+
+struct ArgMaxOptions;
+struct ArgMaxOptionsT;
+
+struct ArgMinOptions;
+struct ArgMinOptionsT;
+
+struct GreaterOptions;
+struct GreaterOptionsT;
+
+struct GreaterEqualOptions;
+struct GreaterEqualOptionsT;
+
+struct LessOptions;
+struct LessOptionsT;
+
+struct LessEqualOptions;
+struct LessEqualOptionsT;
+
+struct NegOptions;
+struct NegOptionsT;
+
+struct SelectOptions;
+struct SelectOptionsT;
+
+struct SliceOptions;
+struct SliceOptionsT;
+
+struct TransposeConvOptions;
+struct TransposeConvOptionsT;
+
+struct ExpandDimsOptions;
+struct ExpandDimsOptionsT;
+
+struct SparseToDenseOptions;
+struct SparseToDenseOptionsT;
+
+struct EqualOptions;
+struct EqualOptionsT;
+
+struct NotEqualOptions;
+struct NotEqualOptionsT;
+
+struct ShapeOptions;
+struct ShapeOptionsT;
+
+struct RankOptions;
+struct RankOptionsT;
+
+struct PowOptions;
+struct PowOptionsT;
+
+struct FakeQuantOptions;
+struct FakeQuantOptionsT;
+
+struct PackOptions;
+struct PackOptionsT;
+
+struct LogicalOrOptions;
+struct LogicalOrOptionsT;
+
+struct OneHotOptions;
+struct OneHotOptionsT;
+
+struct AbsOptions;
+struct AbsOptionsT;
+
+struct HardSwishOptions;
+struct HardSwishOptionsT;
+
+struct LogicalAndOptions;
+struct LogicalAndOptionsT;
+
+struct LogicalNotOptions;
+struct LogicalNotOptionsT;
+
+struct UnpackOptions;
+struct UnpackOptionsT;
+
+struct FloorDivOptions;
+struct FloorDivOptionsT;
+
+struct SquareOptions;
+struct SquareOptionsT;
+
+struct ZerosLikeOptions;
+struct ZerosLikeOptionsT;
+
+struct FillOptions;
+struct FillOptionsT;
+
+struct FloorModOptions;
+struct FloorModOptionsT;
+
+struct RangeOptions;
+struct RangeOptionsT;
+
+struct LeakyReluOptions;
+struct LeakyReluOptionsT;
+
+struct SquaredDifferenceOptions;
+struct SquaredDifferenceOptionsT;
+
+struct MirrorPadOptions;
+struct MirrorPadOptionsT;
+
+struct UniqueOptions;
+struct UniqueOptionsT;
+
+struct ReverseV2Options;
+struct ReverseV2OptionsT;
+
+struct AddNOptions;
+struct AddNOptionsT;
+
+struct GatherNdOptions;
+struct GatherNdOptionsT;
+
+struct WhereOptions;
+struct WhereOptionsT;
+
+struct ReverseSequenceOptions;
+struct ReverseSequenceOptionsT;
+
+struct MatrixDiagOptions;
+struct MatrixDiagOptionsT;
+
+struct QuantizeOptions;
+struct QuantizeOptionsT;
+
+struct MatrixSetDiagOptions;
+struct MatrixSetDiagOptionsT;
+
+struct IfOptions;
+struct IfOptionsT;
+
+struct WhileOptions;
+struct WhileOptionsT;
+
+struct NonMaxSuppressionV4Options;
+struct NonMaxSuppressionV4OptionsT;
+
+struct NonMaxSuppressionV5Options;
+struct NonMaxSuppressionV5OptionsT;
+
+struct ScatterNdOptions;
+struct ScatterNdOptionsT;
+
+struct OperatorCode;
+struct OperatorCodeT;
+
+struct Operator;
+struct OperatorT;
+
+struct SubGraph;
+struct SubGraphT;
+
+struct Buffer;
+struct BufferT;
+
+struct Metadata;
+struct MetadataT;
+
+struct Model;
+struct ModelT;
+
+enum TensorType {
+  TensorType_FLOAT32 = 0,
+  TensorType_FLOAT16 = 1,
+  TensorType_INT32 = 2,
+  TensorType_UINT8 = 3,
+  TensorType_INT64 = 4,
+  TensorType_STRING = 5,
+  TensorType_BOOL = 6,
+  TensorType_INT16 = 7,
+  TensorType_COMPLEX64 = 8,
+  TensorType_INT8 = 9,
+  TensorType_MIN = TensorType_FLOAT32,
+  TensorType_MAX = TensorType_INT8
+};
+
+inline const TensorType (&EnumValuesTensorType())[10] {
+  static const TensorType values[] = {
+    TensorType_FLOAT32,
+    TensorType_FLOAT16,
+    TensorType_INT32,
+    TensorType_UINT8,
+    TensorType_INT64,
+    TensorType_STRING,
+    TensorType_BOOL,
+    TensorType_INT16,
+    TensorType_COMPLEX64,
+    TensorType_INT8
+  };
+  return values;
+}
+
+inline const char * const *EnumNamesTensorType() {
+  static const char * const names[] = {
+    "FLOAT32",
+    "FLOAT16",
+    "INT32",
+    "UINT8",
+    "INT64",
+    "STRING",
+    "BOOL",
+    "INT16",
+    "COMPLEX64",
+    "INT8",
+    nullptr
+  };
+  return names;
+}
+
+inline const char *EnumNameTensorType(TensorType e) {
+  if (e < TensorType_FLOAT32 || e > TensorType_INT8) return "";
+  const size_t index = static_cast<size_t>(e);
+  return EnumNamesTensorType()[index];
+}
+
+enum QuantizationDetails {
+  QuantizationDetails_NONE = 0,
+  QuantizationDetails_CustomQuantization = 1,
+  QuantizationDetails_MIN = QuantizationDetails_NONE,
+  QuantizationDetails_MAX = QuantizationDetails_CustomQuantization
+};
+
+inline const QuantizationDetails (&EnumValuesQuantizationDetails())[2] {
+  static const QuantizationDetails values[] = {
+    QuantizationDetails_NONE,
+    QuantizationDetails_CustomQuantization
+  };
+  return values;
+}
+
+inline const char * const *EnumNamesQuantizationDetails() {
+  static const char * const names[] = {
+    "NONE",
+    "CustomQuantization",
+    nullptr
+  };
+  return names;
+}
+
+inline const char *EnumNameQuantizationDetails(QuantizationDetails e) {
+  if (e < QuantizationDetails_NONE || e > QuantizationDetails_CustomQuantization) return "";
+  const size_t index = static_cast<size_t>(e);
+  return EnumNamesQuantizationDetails()[index];
+}
+
+template<typename T> struct QuantizationDetailsTraits {
+  static const QuantizationDetails enum_value = QuantizationDetails_NONE;
+};
+
+template<> struct QuantizationDetailsTraits<CustomQuantization> {
+  static const QuantizationDetails enum_value = QuantizationDetails_CustomQuantization;
+};
+
+struct QuantizationDetailsUnion {
+  QuantizationDetails type;
+  void *value;
+
+  QuantizationDetailsUnion() : type(QuantizationDetails_NONE), value(nullptr) {}
+  QuantizationDetailsUnion(QuantizationDetailsUnion&& u) FLATBUFFERS_NOEXCEPT :
+    type(QuantizationDetails_NONE), value(nullptr)
+    { std::swap(type, u.type); std::swap(value, u.value); }
+  QuantizationDetailsUnion(const QuantizationDetailsUnion &) FLATBUFFERS_NOEXCEPT;
+  QuantizationDetailsUnion &operator=(const QuantizationDetailsUnion &u) FLATBUFFERS_NOEXCEPT
+    { QuantizationDetailsUnion t(u); std::swap(type, t.type); std::swap(value, t.value); return *this; }
+  QuantizationDetailsUnion &operator=(QuantizationDetailsUnion &&u) FLATBUFFERS_NOEXCEPT
+    { std::swap(type, u.type); std::swap(value, u.value); return *this; }
+  ~QuantizationDetailsUnion() { Reset(); }
+
+  void Reset();
+
+#ifndef FLATBUFFERS_CPP98_STL
+  template <typename T>
+  void Set(T&& val) {
+    using RT = typename std::remove_reference<T>::type;
+    Reset();
+    type = QuantizationDetailsTraits<typename RT::TableType>::enum_value;
+    if (type != QuantizationDetails_NONE) {
+      value = new RT(std::forward<T>(val));
+    }
+  }
+#endif  // FLATBUFFERS_CPP98_STL
+
+  static void *UnPack(const void *obj, QuantizationDetails type, const flatbuffers::resolver_function_t *resolver);
+  flatbuffers::Offset<void> Pack(flatbuffers::FlatBufferBuilder &_fbb, const flatbuffers::rehasher_function_t *_rehasher = nullptr) const;
+
+  CustomQuantizationT *AsCustomQuantization() {
+    return type == QuantizationDetails_CustomQuantization ?
+      reinterpret_cast<CustomQuantizationT *>(value) : nullptr;
+  }
+  const CustomQuantizationT *AsCustomQuantization() const {
+    return type == QuantizationDetails_CustomQuantization ?
+      reinterpret_cast<const CustomQuantizationT *>(value) : nullptr;
+  }
+};
+
+bool VerifyQuantizationDetails(flatbuffers::Verifier &verifier, const void *obj, QuantizationDetails type);
+bool VerifyQuantizationDetailsVector(flatbuffers::Verifier &verifier, const flatbuffers::Vector<flatbuffers::Offset<void>> *values, const flatbuffers::Vector<uint8_t> *types);
+
+enum BuiltinOperator {
+  BuiltinOperator_ADD = 0,
+  BuiltinOperator_AVERAGE_POOL_2D = 1,
+  BuiltinOperator_CONCATENATION = 2,
+  BuiltinOperator_CONV_2D = 3,
+  BuiltinOperator_DEPTHWISE_CONV_2D = 4,
+  BuiltinOperator_DEPTH_TO_SPACE = 5,
+  BuiltinOperator_DEQUANTIZE = 6,
+  BuiltinOperator_EMBEDDING_LOOKUP = 7,
+  BuiltinOperator_FLOOR = 8,
+  BuiltinOperator_FULLY_CONNECTED = 9,
+  BuiltinOperator_HASHTABLE_LOOKUP = 10,
+  BuiltinOperator_L2_NORMALIZATION = 11,
+  BuiltinOperator_L2_POOL_2D = 12,
+  BuiltinOperator_LOCAL_RESPONSE_NORMALIZATION = 13,
+  BuiltinOperator_LOGISTIC = 14,
+  BuiltinOperator_LSH_PROJECTION = 15,
+  BuiltinOperator_LSTM = 16,
+  BuiltinOperator_MAX_POOL_2D = 17,
+  BuiltinOperator_MUL = 18,
+  BuiltinOperator_RELU = 19,
+  BuiltinOperator_RELU_N1_TO_1 = 20,
+  BuiltinOperator_RELU6 = 21,
+  BuiltinOperator_RESHAPE = 22,
+  BuiltinOperator_RESIZE_BILINEAR = 23,
+  BuiltinOperator_RNN = 24,
+  BuiltinOperator_SOFTMAX = 25,
+  BuiltinOperator_SPACE_TO_DEPTH = 26,
+  BuiltinOperator_SVDF = 27,
+  BuiltinOperator_TANH = 28,
+  BuiltinOperator_CONCAT_EMBEDDINGS = 29,
+  BuiltinOperator_SKIP_GRAM = 30,
+  BuiltinOperator_CALL = 31,
+  BuiltinOperator_CUSTOM = 32,
+  BuiltinOperator_EMBEDDING_LOOKUP_SPARSE = 33,
+  BuiltinOperator_PAD = 34,
+  BuiltinOperator_UNIDIRECTIONAL_SEQUENCE_RNN = 35,
+  BuiltinOperator_GATHER = 36,
+  BuiltinOperator_BATCH_TO_SPACE_ND = 37,
+  BuiltinOperator_SPACE_TO_BATCH_ND = 38,
+  BuiltinOperator_TRANSPOSE = 39,
+  BuiltinOperator_MEAN = 40,
+  BuiltinOperator_SUB = 41,
+  BuiltinOperator_DIV = 42,
+  BuiltinOperator_SQUEEZE = 43,
+  BuiltinOperator_UNIDIRECTIONAL_SEQUENCE_LSTM = 44,
+  BuiltinOperator_STRIDED_SLICE = 45,
+  BuiltinOperator_BIDIRECTIONAL_SEQUENCE_RNN = 46,
+  BuiltinOperator_EXP = 47,
+  BuiltinOperator_TOPK_V2 = 48,
+  BuiltinOperator_SPLIT = 49,
+  BuiltinOperator_LOG_SOFTMAX = 50,
+  BuiltinOperator_DELEGATE = 51,
+  BuiltinOperator_BIDIRECTIONAL_SEQUENCE_LSTM = 52,
+  BuiltinOperator_CAST = 53,
+  BuiltinOperator_PRELU = 54,
+  BuiltinOperator_MAXIMUM = 55,
+  BuiltinOperator_ARG_MAX = 56,
+  BuiltinOperator_MINIMUM = 57,
+  BuiltinOperator_LESS = 58,
+  BuiltinOperator_NEG = 59,
+  BuiltinOperator_PADV2 = 60,
+  BuiltinOperator_GREATER = 61,
+  BuiltinOperator_GREATER_EQUAL = 62,
+  BuiltinOperator_LESS_EQUAL = 63,
+  BuiltinOperator_SELECT = 64,
+  BuiltinOperator_SLICE = 65,
+  BuiltinOperator_SIN = 66,
+  BuiltinOperator_TRANSPOSE_CONV = 67,
+  BuiltinOperator_SPARSE_TO_DENSE = 68,
+  BuiltinOperator_TILE = 69,
+  BuiltinOperator_EXPAND_DIMS = 70,
+  BuiltinOperator_EQUAL = 71,
+  BuiltinOperator_NOT_EQUAL = 72,
+  BuiltinOperator_LOG = 73,
+  BuiltinOperator_SUM = 74,
+  BuiltinOperator_SQRT = 75,
+  BuiltinOperator_RSQRT = 76,
+  BuiltinOperator_SHAPE = 77,
+  BuiltinOperator_POW = 78,
+  BuiltinOperator_ARG_MIN = 79,
+  BuiltinOperator_FAKE_QUANT = 80,
+  BuiltinOperator_REDUCE_PROD = 81,
+  BuiltinOperator_REDUCE_MAX = 82,
+  BuiltinOperator_PACK = 83,
+  BuiltinOperator_LOGICAL_OR = 84,
+  BuiltinOperator_ONE_HOT = 85,
+  BuiltinOperator_LOGICAL_AND = 86,
+  BuiltinOperator_LOGICAL_NOT = 87,
+  BuiltinOperator_UNPACK = 88,
+  BuiltinOperator_REDUCE_MIN = 89,
+  BuiltinOperator_FLOOR_DIV = 90,
+  BuiltinOperator_REDUCE_ANY = 91,
+  BuiltinOperator_SQUARE = 92,
+  BuiltinOperator_ZEROS_LIKE = 93,
+  BuiltinOperator_FILL = 94,
+  BuiltinOperator_FLOOR_MOD = 95,
+  BuiltinOperator_RANGE = 96,
+  BuiltinOperator_RESIZE_NEAREST_NEIGHBOR = 97,
+  BuiltinOperator_LEAKY_RELU = 98,
+  BuiltinOperator_SQUARED_DIFFERENCE = 99,
+  BuiltinOperator_MIRROR_PAD = 100,
+  BuiltinOperator_ABS = 101,
+  BuiltinOperator_SPLIT_V = 102,
+  BuiltinOperator_UNIQUE = 103,
+  BuiltinOperator_CEIL = 104,
+  BuiltinOperator_REVERSE_V2 = 105,
+  BuiltinOperator_ADD_N = 106,
+  BuiltinOperator_GATHER_ND = 107,
+  BuiltinOperator_COS = 108,
+  BuiltinOperator_WHERE = 109,
+  BuiltinOperator_RANK = 110,
+  BuiltinOperator_ELU = 111,
+  BuiltinOperator_REVERSE_SEQUENCE = 112,
+  BuiltinOperator_MATRIX_DIAG = 113,
+  BuiltinOperator_QUANTIZE = 114,
+  BuiltinOperator_MATRIX_SET_DIAG = 115,
+  BuiltinOperator_ROUND = 116,
+  BuiltinOperator_HARD_SWISH = 117,
+  BuiltinOperator_IF = 118,
+  BuiltinOperator_WHILE = 119,
+  BuiltinOperator_NON_MAX_SUPPRESSION_V4 = 120,
+  BuiltinOperator_NON_MAX_SUPPRESSION_V5 = 121,
+  BuiltinOperator_SCATTER_ND = 122,
+  BuiltinOperator_MIN = BuiltinOperator_ADD,
+  BuiltinOperator_MAX = BuiltinOperator_SCATTER_ND
+};
+
+inline const BuiltinOperator (&EnumValuesBuiltinOperator())[123] {
+  static const BuiltinOperator values[] = {
+    BuiltinOperator_ADD,
+    BuiltinOperator_AVERAGE_POOL_2D,
+    BuiltinOperator_CONCATENATION,
+    BuiltinOperator_CONV_2D,
+    BuiltinOperator_DEPTHWISE_CONV_2D,
+    BuiltinOperator_DEPTH_TO_SPACE,
+    BuiltinOperator_DEQUANTIZE,
+    BuiltinOperator_EMBEDDING_LOOKUP,
+    BuiltinOperator_FLOOR,
+    BuiltinOperator_FULLY_CONNECTED,
+    BuiltinOperator_HASHTABLE_LOOKUP,
+    BuiltinOperator_L2_NORMALIZATION,
+    BuiltinOperator_L2_POOL_2D,
+    BuiltinOperator_LOCAL_RESPONSE_NORMALIZATION,
+    BuiltinOperator_LOGISTIC,
+    BuiltinOperator_LSH_PROJECTION,
+    BuiltinOperator_LSTM,
+    BuiltinOperator_MAX_POOL_2D,
+    BuiltinOperator_MUL,
+    BuiltinOperator_RELU,
+    BuiltinOperator_RELU_N1_TO_1,
+    BuiltinOperator_RELU6,
+    BuiltinOperator_RESHAPE,
+    BuiltinOperator_RESIZE_BILINEAR,
+    BuiltinOperator_RNN,
+    BuiltinOperator_SOFTMAX,
+    BuiltinOperator_SPACE_TO_DEPTH,
+    BuiltinOperator_SVDF,
+    BuiltinOperator_TANH,
+    BuiltinOperator_CONCAT_EMBEDDINGS,
+    BuiltinOperator_SKIP_GRAM,
+    BuiltinOperator_CALL,
+    BuiltinOperator_CUSTOM,
+    BuiltinOperator_EMBEDDING_LOOKUP_SPARSE,
+    BuiltinOperator_PAD,
+    BuiltinOperator_UNIDIRECTIONAL_SEQUENCE_RNN,
+    BuiltinOperator_GATHER,
+    BuiltinOperator_BATCH_TO_SPACE_ND,
+    BuiltinOperator_SPACE_TO_BATCH_ND,
+    BuiltinOperator_TRANSPOSE,
+    BuiltinOperator_MEAN,
+    BuiltinOperator_SUB,
+    BuiltinOperator_DIV,
+    BuiltinOperator_SQUEEZE,
+    BuiltinOperator_UNIDIRECTIONAL_SEQUENCE_LSTM,
+    BuiltinOperator_STRIDED_SLICE,
+    BuiltinOperator_BIDIRECTIONAL_SEQUENCE_RNN,
+    BuiltinOperator_EXP,
+    BuiltinOperator_TOPK_V2,
+    BuiltinOperator_SPLIT,
+    BuiltinOperator_LOG_SOFTMAX,
+    BuiltinOperator_DELEGATE,
+    BuiltinOperator_BIDIRECTIONAL_SEQUENCE_LSTM,
+    BuiltinOperator_CAST,
+    BuiltinOperator_PRELU,
+    BuiltinOperator_MAXIMUM,
+    BuiltinOperator_ARG_MAX,
+    BuiltinOperator_MINIMUM,
+    BuiltinOperator_LESS,
+    BuiltinOperator_NEG,
+    BuiltinOperator_PADV2,
+    BuiltinOperator_GREATER,
+    BuiltinOperator_GREATER_EQUAL,
+    BuiltinOperator_LESS_EQUAL,
+    BuiltinOperator_SELECT,
+    BuiltinOperator_SLICE,
+    BuiltinOperator_SIN,
+    BuiltinOperator_TRANSPOSE_CONV,
+    BuiltinOperator_SPARSE_TO_DENSE,
+    BuiltinOperator_TILE,
+    BuiltinOperator_EXPAND_DIMS,
+    BuiltinOperator_EQUAL,
+    BuiltinOperator_NOT_EQUAL,
+    BuiltinOperator_LOG,
+    BuiltinOperator_SUM,
+    BuiltinOperator_SQRT,
+    BuiltinOperator_RSQRT,
+    BuiltinOperator_SHAPE,
+    BuiltinOperator_POW,
+    BuiltinOperator_ARG_MIN,
+    BuiltinOperator_FAKE_QUANT,
+    BuiltinOperator_REDUCE_PROD,
+    BuiltinOperator_REDUCE_MAX,
+    BuiltinOperator_PACK,
+    BuiltinOperator_LOGICAL_OR,
+    BuiltinOperator_ONE_HOT,
+    BuiltinOperator_LOGICAL_AND,
+    BuiltinOperator_LOGICAL_NOT,
+    BuiltinOperator_UNPACK,
+    BuiltinOperator_REDUCE_MIN,
+    BuiltinOperator_FLOOR_DIV,
+    BuiltinOperator_REDUCE_ANY,
+    BuiltinOperator_SQUARE,
+    BuiltinOperator_ZEROS_LIKE,
+    BuiltinOperator_FILL,
+    BuiltinOperator_FLOOR_MOD,
+    BuiltinOperator_RANGE,
+    BuiltinOperator_RESIZE_NEAREST_NEIGHBOR,
+    BuiltinOperator_LEAKY_RELU,
+    BuiltinOperator_SQUARED_DIFFERENCE,
+    BuiltinOperator_MIRROR_PAD,
+    BuiltinOperator_ABS,
+    BuiltinOperator_SPLIT_V,
+    BuiltinOperator_UNIQUE,
+    BuiltinOperator_CEIL,
+    BuiltinOperator_REVERSE_V2,
+    BuiltinOperator_ADD_N,
+    BuiltinOperator_GATHER_ND,
+    BuiltinOperator_COS,
+    BuiltinOperator_WHERE,
+    BuiltinOperator_RANK,
+    BuiltinOperator_ELU,
+    BuiltinOperator_REVERSE_SEQUENCE,
+    BuiltinOperator_MATRIX_DIAG,
+    BuiltinOperator_QUANTIZE,
+    BuiltinOperator_MATRIX_SET_DIAG,
+    BuiltinOperator_ROUND,
+    BuiltinOperator_HARD_SWISH,
+    BuiltinOperator_IF,
+    BuiltinOperator_WHILE,
+    BuiltinOperator_NON_MAX_SUPPRESSION_V4,
+    BuiltinOperator_NON_MAX_SUPPRESSION_V5,
+    BuiltinOperator_SCATTER_ND
+  };
+  return values;
+}
+
+inline const char * const *EnumNamesBuiltinOperator() {
+  static const char * const names[] = {
+    "ADD",
+    "AVERAGE_POOL_2D",
+    "CONCATENATION",
+    "CONV_2D",
+    "DEPTHWISE_CONV_2D",
+    "DEPTH_TO_SPACE",
+    "DEQUANTIZE",
+    "EMBEDDING_LOOKUP",
+    "FLOOR",
+    "FULLY_CONNECTED",
+    "HASHTABLE_LOOKUP",
+    "L2_NORMALIZATION",
+    "L2_POOL_2D",
+    "LOCAL_RESPONSE_NORMALIZATION",
+    "LOGISTIC",
+    "LSH_PROJECTION",
+    "LSTM",
+    "MAX_POOL_2D",
+    "MUL",
+    "RELU",
+    "RELU_N1_TO_1",
+    "RELU6",
+    "RESHAPE",
+    "RESIZE_BILINEAR",
+    "RNN",
+    "SOFTMAX",
+    "SPACE_TO_DEPTH",
+    "SVDF",
+    "TANH",
+    "CONCAT_EMBEDDINGS",
+    "SKIP_GRAM",
+    "CALL",
+    "CUSTOM",
+    "EMBEDDING_LOOKUP_SPARSE",
+    "PAD",
+    "UNIDIRECTIONAL_SEQUENCE_RNN",
+    "GATHER",
+    "BATCH_TO_SPACE_ND",
+    "SPACE_TO_BATCH_ND",
+    "TRANSPOSE",
+    "MEAN",
+    "SUB",
+    "DIV",
+    "SQUEEZE",
+    "UNIDIRECTIONAL_SEQUENCE_LSTM",
+    "STRIDED_SLICE",
+    "BIDIRECTIONAL_SEQUENCE_RNN",
+    "EXP",
+    "TOPK_V2",
+    "SPLIT",
+    "LOG_SOFTMAX",
+    "DELEGATE",
+    "BIDIRECTIONAL_SEQUENCE_LSTM",
+    "CAST",
+    "PRELU",
+    "MAXIMUM",
+    "ARG_MAX",
+    "MINIMUM",
+    "LESS",
+    "NEG",
+    "PADV2",
+    "GREATER",
+    "GREATER_EQUAL",
+    "LESS_EQUAL",
+    "SELECT",
+    "SLICE",
+    "SIN",
+    "TRANSPOSE_CONV",
+    "SPARSE_TO_DENSE",
+    "TILE",
+    "EXPAND_DIMS",
+    "EQUAL",
+    "NOT_EQUAL",
+    "LOG",
+    "SUM",
+    "SQRT",
+    "RSQRT",
+    "SHAPE",
+    "POW",
+    "ARG_MIN",
+    "FAKE_QUANT",
+    "REDUCE_PROD",
+    "REDUCE_MAX",
+    "PACK",
+    "LOGICAL_OR",
+    "ONE_HOT",
+    "LOGICAL_AND",
+    "LOGICAL_NOT",
+    "UNPACK",
+    "REDUCE_MIN",
+    "FLOOR_DIV",
+    "REDUCE_ANY",
+    "SQUARE",
+    "ZEROS_LIKE",
+    "FILL",
+    "FLOOR_MOD",
+    "RANGE",
+    "RESIZE_NEAREST_NEIGHBOR",
+    "LEAKY_RELU",
+    "SQUARED_DIFFERENCE",
+    "MIRROR_PAD",
+    "ABS",
+    "SPLIT_V",
+    "UNIQUE",
+    "CEIL",
+    "REVERSE_V2",
+    "ADD_N",
+    "GATHER_ND",
+    "COS",
+    "WHERE",
+    "RANK",
+    "ELU",
+    "REVERSE_SEQUENCE",
+    "MATRIX_DIAG",
+    "QUANTIZE",
+    "MATRIX_SET_DIAG",
+    "ROUND",
+    "HARD_SWISH",
+    "IF",
+    "WHILE",
+    "NON_MAX_SUPPRESSION_V4",
+    "NON_MAX_SUPPRESSION_V5",
+    "SCATTER_ND",
+    nullptr
+  };
+  return names;
+}
+
+inline const char *EnumNameBuiltinOperator(BuiltinOperator e) {
+  if (e < BuiltinOperator_ADD || e > BuiltinOperator_SCATTER_ND) return "";
+  const size_t index = static_cast<size_t>(e);
+  return EnumNamesBuiltinOperator()[index];
+}
+
+enum BuiltinOptions {
+  BuiltinOptions_NONE = 0,
+  BuiltinOptions_Conv2DOptions = 1,
+  BuiltinOptions_DepthwiseConv2DOptions = 2,
+  BuiltinOptions_ConcatEmbeddingsOptions = 3,
+  BuiltinOptions_LSHProjectionOptions = 4,
+  BuiltinOptions_Pool2DOptions = 5,
+  BuiltinOptions_SVDFOptions = 6,
+  BuiltinOptions_RNNOptions = 7,
+  BuiltinOptions_FullyConnectedOptions = 8,
+  BuiltinOptions_SoftmaxOptions = 9,
+  BuiltinOptions_ConcatenationOptions = 10,
+  BuiltinOptions_AddOptions = 11,
+  BuiltinOptions_L2NormOptions = 12,
+  BuiltinOptions_LocalResponseNormalizationOptions = 13,
+  BuiltinOptions_LSTMOptions = 14,
+  BuiltinOptions_ResizeBilinearOptions = 15,
+  BuiltinOptions_CallOptions = 16,
+  BuiltinOptions_ReshapeOptions = 17,
+  BuiltinOptions_SkipGramOptions = 18,
+  BuiltinOptions_SpaceToDepthOptions = 19,
+  BuiltinOptions_EmbeddingLookupSparseOptions = 20,
+  BuiltinOptions_MulOptions = 21,
+  BuiltinOptions_PadOptions = 22,
+  BuiltinOptions_GatherOptions = 23,
+  BuiltinOptions_BatchToSpaceNDOptions = 24,
+  BuiltinOptions_SpaceToBatchNDOptions = 25,
+  BuiltinOptions_TransposeOptions = 26,
+  BuiltinOptions_ReducerOptions = 27,
+  BuiltinOptions_SubOptions = 28,
+  BuiltinOptions_DivOptions = 29,
+  BuiltinOptions_SqueezeOptions = 30,
+  BuiltinOptions_SequenceRNNOptions = 31,
+  BuiltinOptions_StridedSliceOptions = 32,
+  BuiltinOptions_ExpOptions = 33,
+  BuiltinOptions_TopKV2Options = 34,
+  BuiltinOptions_SplitOptions = 35,
+  BuiltinOptions_LogSoftmaxOptions = 36,
+  BuiltinOptions_CastOptions = 37,
+  BuiltinOptions_DequantizeOptions = 38,
+  BuiltinOptions_MaximumMinimumOptions = 39,
+  BuiltinOptions_ArgMaxOptions = 40,
+  BuiltinOptions_LessOptions = 41,
+  BuiltinOptions_NegOptions = 42,
+  BuiltinOptions_PadV2Options = 43,
+  BuiltinOptions_GreaterOptions = 44,
+  BuiltinOptions_GreaterEqualOptions = 45,
+  BuiltinOptions_LessEqualOptions = 46,
+  BuiltinOptions_SelectOptions = 47,
+  BuiltinOptions_SliceOptions = 48,
+  BuiltinOptions_TransposeConvOptions = 49,
+  BuiltinOptions_SparseToDenseOptions = 50,
+  BuiltinOptions_TileOptions = 51,
+  BuiltinOptions_ExpandDimsOptions = 52,
+  BuiltinOptions_EqualOptions = 53,
+  BuiltinOptions_NotEqualOptions = 54,
+  BuiltinOptions_ShapeOptions = 55,
+  BuiltinOptions_PowOptions = 56,
+  BuiltinOptions_ArgMinOptions = 57,
+  BuiltinOptions_FakeQuantOptions = 58,
+  BuiltinOptions_PackOptions = 59,
+  BuiltinOptions_LogicalOrOptions = 60,
+  BuiltinOptions_OneHotOptions = 61,
+  BuiltinOptions_LogicalAndOptions = 62,
+  BuiltinOptions_LogicalNotOptions = 63,
+  BuiltinOptions_UnpackOptions = 64,
+  BuiltinOptions_FloorDivOptions = 65,
+  BuiltinOptions_SquareOptions = 66,
+  BuiltinOptions_ZerosLikeOptions = 67,
+  BuiltinOptions_FillOptions = 68,
+  BuiltinOptions_BidirectionalSequenceLSTMOptions = 69,
+  BuiltinOptions_BidirectionalSequenceRNNOptions = 70,
+  BuiltinOptions_UnidirectionalSequenceLSTMOptions = 71,
+  BuiltinOptions_FloorModOptions = 72,
+  BuiltinOptions_RangeOptions = 73,
+  BuiltinOptions_ResizeNearestNeighborOptions = 74,
+  BuiltinOptions_LeakyReluOptions = 75,
+  BuiltinOptions_SquaredDifferenceOptions = 76,
+  BuiltinOptions_MirrorPadOptions = 77,
+  BuiltinOptions_AbsOptions = 78,
+  BuiltinOptions_SplitVOptions = 79,
+  BuiltinOptions_UniqueOptions = 80,
+  BuiltinOptions_ReverseV2Options = 81,
+  BuiltinOptions_AddNOptions = 82,
+  BuiltinOptions_GatherNdOptions = 83,
+  BuiltinOptions_CosOptions = 84,
+  BuiltinOptions_WhereOptions = 85,
+  BuiltinOptions_RankOptions = 86,
+  BuiltinOptions_ReverseSequenceOptions = 87,
+  BuiltinOptions_MatrixDiagOptions = 88,
+  BuiltinOptions_QuantizeOptions = 89,
+  BuiltinOptions_MatrixSetDiagOptions = 90,
+  BuiltinOptions_HardSwishOptions = 91,
+  BuiltinOptions_IfOptions = 92,
+  BuiltinOptions_WhileOptions = 93,
+  BuiltinOptions_DepthToSpaceOptions = 94,
+  BuiltinOptions_NonMaxSuppressionV4Options = 95,
+  BuiltinOptions_NonMaxSuppressionV5Options = 96,
+  BuiltinOptions_ScatterNdOptions = 97,
+  BuiltinOptions_MIN = BuiltinOptions_NONE,
+  BuiltinOptions_MAX = BuiltinOptions_ScatterNdOptions
+};
+
+inline const BuiltinOptions (&EnumValuesBuiltinOptions())[98] {
+  static const BuiltinOptions values[] = {
+    BuiltinOptions_NONE,
+    BuiltinOptions_Conv2DOptions,
+    BuiltinOptions_DepthwiseConv2DOptions,
+    BuiltinOptions_ConcatEmbeddingsOptions,
+    BuiltinOptions_LSHProjectionOptions,
+    BuiltinOptions_Pool2DOptions,
+    BuiltinOptions_SVDFOptions,
+    BuiltinOptions_RNNOptions,
+    BuiltinOptions_FullyConnectedOptions,
+    BuiltinOptions_SoftmaxOptions,
+    BuiltinOptions_ConcatenationOptions,
+    BuiltinOptions_AddOptions,
+    BuiltinOptions_L2NormOptions,
+    BuiltinOptions_LocalResponseNormalizationOptions,
+    BuiltinOptions_LSTMOptions,
+    BuiltinOptions_ResizeBilinearOptions,
+    BuiltinOptions_CallOptions,
+    BuiltinOptions_ReshapeOptions,
+    BuiltinOptions_SkipGramOptions,
+    BuiltinOptions_SpaceToDepthOptions,
+    BuiltinOptions_EmbeddingLookupSparseOptions,
+    BuiltinOptions_MulOptions,
+    BuiltinOptions_PadOptions,
+    BuiltinOptions_GatherOptions,
+    BuiltinOptions_BatchToSpaceNDOptions,
+    BuiltinOptions_SpaceToBatchNDOptions,
+    BuiltinOptions_TransposeOptions,
+    BuiltinOptions_ReducerOptions,
+    BuiltinOptions_SubOptions,
+    BuiltinOptions_DivOptions,
+    BuiltinOptions_SqueezeOptions,
+    BuiltinOptions_SequenceRNNOptions,
+    BuiltinOptions_StridedSliceOptions,
+    BuiltinOptions_ExpOptions,
+    BuiltinOptions_TopKV2Options,
+    BuiltinOptions_SplitOptions,
+    BuiltinOptions_LogSoftmaxOptions,
+    BuiltinOptions_CastOptions,
+    BuiltinOptions_DequantizeOptions,
+    BuiltinOptions_MaximumMinimumOptions,
+    BuiltinOptions_ArgMaxOptions,
+    BuiltinOptions_LessOptions,
+    BuiltinOptions_NegOptions,
+    BuiltinOptions_PadV2Options,
+    BuiltinOptions_GreaterOptions,
+    BuiltinOptions_GreaterEqualOptions,
+    BuiltinOptions_LessEqualOptions,
+    BuiltinOptions_SelectOptions,
+    BuiltinOptions_SliceOptions,
+    BuiltinOptions_TransposeConvOptions,
+    BuiltinOptions_SparseToDenseOptions,
+    BuiltinOptions_TileOptions,
+    BuiltinOptions_ExpandDimsOptions,
+    BuiltinOptions_EqualOptions,
+    BuiltinOptions_NotEqualOptions,
+    BuiltinOptions_ShapeOptions,
+    BuiltinOptions_PowOptions,
+    BuiltinOptions_ArgMinOptions,
+    BuiltinOptions_FakeQuantOptions,
+    BuiltinOptions_PackOptions,
+    BuiltinOptions_LogicalOrOptions,
+    BuiltinOptions_OneHotOptions,
+    BuiltinOptions_LogicalAndOptions,
+    BuiltinOptions_LogicalNotOptions,
+    BuiltinOptions_UnpackOptions,
+    BuiltinOptions_FloorDivOptions,
+    BuiltinOptions_SquareOptions,
+    BuiltinOptions_ZerosLikeOptions,
+    BuiltinOptions_FillOptions,
+    BuiltinOptions_BidirectionalSequenceLSTMOptions,
+    BuiltinOptions_BidirectionalSequenceRNNOptions,
+    BuiltinOptions_UnidirectionalSequenceLSTMOptions,
+    BuiltinOptions_FloorModOptions,
+    BuiltinOptions_RangeOptions,
+    BuiltinOptions_ResizeNearestNeighborOptions,
+    BuiltinOptions_LeakyReluOptions,
+    BuiltinOptions_SquaredDifferenceOptions,
+    BuiltinOptions_MirrorPadOptions,
+    BuiltinOptions_AbsOptions,
+    BuiltinOptions_SplitVOptions,
+    BuiltinOptions_UniqueOptions,
+    BuiltinOptions_ReverseV2Options,
+    BuiltinOptions_AddNOptions,
+    BuiltinOptions_GatherNdOptions,
+    BuiltinOptions_CosOptions,
+    BuiltinOptions_WhereOptions,
+    BuiltinOptions_RankOptions,
+    BuiltinOptions_ReverseSequenceOptions,
+    BuiltinOptions_MatrixDiagOptions,
+    BuiltinOptions_QuantizeOptions,
+    BuiltinOptions_MatrixSetDiagOptions,
+    BuiltinOptions_HardSwishOptions,
+    BuiltinOptions_IfOptions,
+    BuiltinOptions_WhileOptions,
+    BuiltinOptions_DepthToSpaceOptions,
+    BuiltinOptions_NonMaxSuppressionV4Options,
+    BuiltinOptions_NonMaxSuppressionV5Options,
+    BuiltinOptions_ScatterNdOptions
+  };
+  return values;
+}
+
+inline const char * const *EnumNamesBuiltinOptions() {
+  static const char * const names[] = {
+    "NONE",
+    "Conv2DOptions",
+    "DepthwiseConv2DOptions",
+    "ConcatEmbeddingsOptions",
+    "LSHProjectionOptions",
+    "Pool2DOptions",
+    "SVDFOptions",
+    "RNNOptions",
+    "FullyConnectedOptions",
+    "SoftmaxOptions",
+    "ConcatenationOptions",
+    "AddOptions",
+    "L2NormOptions",
+    "LocalResponseNormalizationOptions",
+    "LSTMOptions",
+    "ResizeBilinearOptions",
+    "CallOptions",
+    "ReshapeOptions",
+    "SkipGramOptions",
+    "SpaceToDepthOptions",
+    "EmbeddingLookupSparseOptions",
+    "MulOptions",
+    "PadOptions",
+    "GatherOptions",
+    "BatchToSpaceNDOptions",
+    "SpaceToBatchNDOptions",
+    "TransposeOptions",
+    "ReducerOptions",
+    "SubOptions",
+    "DivOptions",
+    "SqueezeOptions",
+    "SequenceRNNOptions",
+    "StridedSliceOptions",
+    "ExpOptions",
+    "TopKV2Options",
+    "SplitOptions",
+    "LogSoftmaxOptions",
+    "CastOptions",
+    "DequantizeOptions",
+    "MaximumMinimumOptions",
+    "ArgMaxOptions",
+    "LessOptions",
+    "NegOptions",
+    "PadV2Options",
+    "GreaterOptions",
+    "GreaterEqualOptions",
+    "LessEqualOptions",
+    "SelectOptions",
+    "SliceOptions",
+    "TransposeConvOptions",
+    "SparseToDenseOptions",
+    "TileOptions",
+    "ExpandDimsOptions",
+    "EqualOptions",
+    "NotEqualOptions",
+    "ShapeOptions",
+    "PowOptions",
+    "ArgMinOptions",
+    "FakeQuantOptions",
+    "PackOptions",
+    "LogicalOrOptions",
+    "OneHotOptions",
+    "LogicalAndOptions",
+    "LogicalNotOptions",
+    "UnpackOptions",
+    "FloorDivOptions",
+    "SquareOptions",
+    "ZerosLikeOptions",
+    "FillOptions",
+    "BidirectionalSequenceLSTMOptions",
+    "BidirectionalSequenceRNNOptions",
+    "UnidirectionalSequenceLSTMOptions",
+    "FloorModOptions",
+    "RangeOptions",
+    "ResizeNearestNeighborOptions",
+    "LeakyReluOptions",
+    "SquaredDifferenceOptions",
+    "MirrorPadOptions",
+    "AbsOptions",
+    "SplitVOptions",
+    "UniqueOptions",
+    "ReverseV2Options",
+    "AddNOptions",
+    "GatherNdOptions",
+    "CosOptions",
+    "WhereOptions",
+    "RankOptions",
+    "ReverseSequenceOptions",
+    "MatrixDiagOptions",
+    "QuantizeOptions",
+    "MatrixSetDiagOptions",
+    "HardSwishOptions",
+    "IfOptions",
+    "WhileOptions",
+    "DepthToSpaceOptions",
+    "NonMaxSuppressionV4Options",
+    "NonMaxSuppressionV5Options",
+    "ScatterNdOptions",
+    nullptr
+  };
+  return names;
+}
+
+inline const char *EnumNameBuiltinOptions(BuiltinOptions e) {
+  if (e < BuiltinOptions_NONE || e > BuiltinOptions_ScatterNdOptions) return "";
+  const size_t index = static_cast<size_t>(e);
+  return EnumNamesBuiltinOptions()[index];
+}
+
+template<typename T> struct BuiltinOptionsTraits {
+  static const BuiltinOptions enum_value = BuiltinOptions_NONE;
+};
+
+template<> struct BuiltinOptionsTraits<Conv2DOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_Conv2DOptions;
+};
+
+template<> struct BuiltinOptionsTraits<DepthwiseConv2DOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_DepthwiseConv2DOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ConcatEmbeddingsOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ConcatEmbeddingsOptions;
+};
+
+template<> struct BuiltinOptionsTraits<LSHProjectionOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_LSHProjectionOptions;
+};
+
+template<> struct BuiltinOptionsTraits<Pool2DOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_Pool2DOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SVDFOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SVDFOptions;
+};
+
+template<> struct BuiltinOptionsTraits<RNNOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_RNNOptions;
+};
+
+template<> struct BuiltinOptionsTraits<FullyConnectedOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_FullyConnectedOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SoftmaxOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SoftmaxOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ConcatenationOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ConcatenationOptions;
+};
+
+template<> struct BuiltinOptionsTraits<AddOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_AddOptions;
+};
+
+template<> struct BuiltinOptionsTraits<L2NormOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_L2NormOptions;
+};
+
+template<> struct BuiltinOptionsTraits<LocalResponseNormalizationOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_LocalResponseNormalizationOptions;
+};
+
+template<> struct BuiltinOptionsTraits<LSTMOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_LSTMOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ResizeBilinearOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ResizeBilinearOptions;
+};
+
+template<> struct BuiltinOptionsTraits<CallOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_CallOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ReshapeOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ReshapeOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SkipGramOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SkipGramOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SpaceToDepthOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SpaceToDepthOptions;
+};
+
+template<> struct BuiltinOptionsTraits<EmbeddingLookupSparseOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_EmbeddingLookupSparseOptions;
+};
+
+template<> struct BuiltinOptionsTraits<MulOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_MulOptions;
+};
+
+template<> struct BuiltinOptionsTraits<PadOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_PadOptions;
+};
+
+template<> struct BuiltinOptionsTraits<GatherOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_GatherOptions;
+};
+
+template<> struct BuiltinOptionsTraits<BatchToSpaceNDOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_BatchToSpaceNDOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SpaceToBatchNDOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SpaceToBatchNDOptions;
+};
+
+template<> struct BuiltinOptionsTraits<TransposeOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_TransposeOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ReducerOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ReducerOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SubOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SubOptions;
+};
+
+template<> struct BuiltinOptionsTraits<DivOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_DivOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SqueezeOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SqueezeOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SequenceRNNOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SequenceRNNOptions;
+};
+
+template<> struct BuiltinOptionsTraits<StridedSliceOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_StridedSliceOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ExpOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ExpOptions;
+};
+
+template<> struct BuiltinOptionsTraits<TopKV2Options> {
+  static const BuiltinOptions enum_value = BuiltinOptions_TopKV2Options;
+};
+
+template<> struct BuiltinOptionsTraits<SplitOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SplitOptions;
+};
+
+template<> struct BuiltinOptionsTraits<LogSoftmaxOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_LogSoftmaxOptions;
+};
+
+template<> struct BuiltinOptionsTraits<CastOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_CastOptions;
+};
+
+template<> struct BuiltinOptionsTraits<DequantizeOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_DequantizeOptions;
+};
+
+template<> struct BuiltinOptionsTraits<MaximumMinimumOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_MaximumMinimumOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ArgMaxOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ArgMaxOptions;
+};
+
+template<> struct BuiltinOptionsTraits<LessOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_LessOptions;
+};
+
+template<> struct BuiltinOptionsTraits<NegOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_NegOptions;
+};
+
+template<> struct BuiltinOptionsTraits<PadV2Options> {
+  static const BuiltinOptions enum_value = BuiltinOptions_PadV2Options;
+};
+
+template<> struct BuiltinOptionsTraits<GreaterOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_GreaterOptions;
+};
+
+template<> struct BuiltinOptionsTraits<GreaterEqualOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_GreaterEqualOptions;
+};
+
+template<> struct BuiltinOptionsTraits<LessEqualOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_LessEqualOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SelectOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SelectOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SliceOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SliceOptions;
+};
+
+template<> struct BuiltinOptionsTraits<TransposeConvOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_TransposeConvOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SparseToDenseOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SparseToDenseOptions;
+};
+
+template<> struct BuiltinOptionsTraits<TileOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_TileOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ExpandDimsOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ExpandDimsOptions;
+};
+
+template<> struct BuiltinOptionsTraits<EqualOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_EqualOptions;
+};
+
+template<> struct BuiltinOptionsTraits<NotEqualOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_NotEqualOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ShapeOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ShapeOptions;
+};
+
+template<> struct BuiltinOptionsTraits<PowOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_PowOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ArgMinOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ArgMinOptions;
+};
+
+template<> struct BuiltinOptionsTraits<FakeQuantOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_FakeQuantOptions;
+};
+
+template<> struct BuiltinOptionsTraits<PackOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_PackOptions;
+};
+
+template<> struct BuiltinOptionsTraits<LogicalOrOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_LogicalOrOptions;
+};
+
+template<> struct BuiltinOptionsTraits<OneHotOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_OneHotOptions;
+};
+
+template<> struct BuiltinOptionsTraits<LogicalAndOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_LogicalAndOptions;
+};
+
+template<> struct BuiltinOptionsTraits<LogicalNotOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_LogicalNotOptions;
+};
+
+template<> struct BuiltinOptionsTraits<UnpackOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_UnpackOptions;
+};
+
+template<> struct BuiltinOptionsTraits<FloorDivOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_FloorDivOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SquareOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SquareOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ZerosLikeOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ZerosLikeOptions;
+};
+
+template<> struct BuiltinOptionsTraits<FillOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_FillOptions;
+};
+
+template<> struct BuiltinOptionsTraits<BidirectionalSequenceLSTMOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_BidirectionalSequenceLSTMOptions;
+};
+
+template<> struct BuiltinOptionsTraits<BidirectionalSequenceRNNOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_BidirectionalSequenceRNNOptions;
+};
+
+template<> struct BuiltinOptionsTraits<UnidirectionalSequenceLSTMOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_UnidirectionalSequenceLSTMOptions;
+};
+
+template<> struct BuiltinOptionsTraits<FloorModOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_FloorModOptions;
+};
+
+template<> struct BuiltinOptionsTraits<RangeOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_RangeOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ResizeNearestNeighborOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ResizeNearestNeighborOptions;
+};
+
+template<> struct BuiltinOptionsTraits<LeakyReluOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_LeakyReluOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SquaredDifferenceOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SquaredDifferenceOptions;
+};
+
+template<> struct BuiltinOptionsTraits<MirrorPadOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_MirrorPadOptions;
+};
+
+template<> struct BuiltinOptionsTraits<AbsOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_AbsOptions;
+};
+
+template<> struct BuiltinOptionsTraits<SplitVOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_SplitVOptions;
+};
+
+template<> struct BuiltinOptionsTraits<UniqueOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_UniqueOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ReverseV2Options> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ReverseV2Options;
+};
+
+template<> struct BuiltinOptionsTraits<AddNOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_AddNOptions;
+};
+
+template<> struct BuiltinOptionsTraits<GatherNdOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_GatherNdOptions;
+};
+
+template<> struct BuiltinOptionsTraits<CosOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_CosOptions;
+};
+
+template<> struct BuiltinOptionsTraits<WhereOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_WhereOptions;
+};
+
+template<> struct BuiltinOptionsTraits<RankOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_RankOptions;
+};
+
+template<> struct BuiltinOptionsTraits<ReverseSequenceOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ReverseSequenceOptions;
+};
+
+template<> struct BuiltinOptionsTraits<MatrixDiagOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_MatrixDiagOptions;
+};
+
+template<> struct BuiltinOptionsTraits<QuantizeOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_QuantizeOptions;
+};
+
+template<> struct BuiltinOptionsTraits<MatrixSetDiagOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_MatrixSetDiagOptions;
+};
+
+template<> struct BuiltinOptionsTraits<HardSwishOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_HardSwishOptions;
+};
+
+template<> struct BuiltinOptionsTraits<IfOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_IfOptions;
+};
+
+template<> struct BuiltinOptionsTraits<WhileOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_WhileOptions;
+};
+
+template<> struct BuiltinOptionsTraits<DepthToSpaceOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_DepthToSpaceOptions;
+};
+
+template<> struct BuiltinOptionsTraits<NonMaxSuppressionV4Options> {
+  static const BuiltinOptions enum_value = BuiltinOptions_NonMaxSuppressionV4Options;
+};
+
+template<> struct BuiltinOptionsTraits<NonMaxSuppressionV5Options> {
+  static const BuiltinOptions enum_value = BuiltinOptions_NonMaxSuppressionV5Options;
+};
+
+template<> struct BuiltinOptionsTraits<ScatterNdOptions> {
+  static const BuiltinOptions enum_value = BuiltinOptions_ScatterNdOptions;
+};
+
+struct BuiltinOptionsUnion {
+  BuiltinOptions type;
+  void *value;
+
+  BuiltinOptionsUnion() : type(BuiltinOptions_NONE), value(nullptr) {}
+  BuiltinOptionsUnion(BuiltinOptionsUnion&& u) FLATBUFFERS_NOEXCEPT :
+    type(BuiltinOptions_NONE), value(nullptr)
+    { std::swap(type, u.type); std::swap(value, u.value); }
+  BuiltinOptionsUnion(const BuiltinOptionsUnion &) FLATBUFFERS_NOEXCEPT;
+  BuiltinOptionsUnion &operator=(const BuiltinOptionsUnion &u) FLATBUFFERS_NOEXCEPT
+    { BuiltinOptionsUnion t(u); std::swap(type, t.type); std::swap(value, t.value); return *this; }
+  BuiltinOptionsUnion &operator=(BuiltinOptionsUnion &&u) FLATBUFFERS_NOEXCEPT
+    { std::swap(type, u.type); std::swap(value, u.value); return *this; }
+  ~BuiltinOptionsUnion() { Reset(); }
+
+  void Reset();
+
+#ifndef FLATBUFFERS_CPP98_STL
+  template <typename T>
+  void Set(T&& val) {
+    using RT = typename std::remove_reference<T>::type;
+    Reset();
+    type = BuiltinOptionsTraits<typename RT::TableType>::enum_value;
+    if (type != BuiltinOptions_NONE) {
+      value = new RT(std::forward<T>(val));
+    }
+  }
+#endif  // FLATBUFFERS_CPP98_STL
+
+  static void *UnPack(const void *obj, BuiltinOptions type, const flatbuffers::resolver_function_t *resolver);
+  flatbuffers::Offset<void> Pack(flatbuffers::FlatBufferBuilder &_fbb, const flatbuffers::rehasher_function_t *_rehasher = nullptr) const;
+
+  Conv2DOptionsT *AsConv2DOptions() {
+    return type == BuiltinOptions_Conv2DOptions ?
+      reinterpret_cast<Conv2DOptionsT *>(value) : nullptr;
+  }
+  const Conv2DOptionsT *AsConv2DOptions() const {
+    return type == BuiltinOptions_Conv2DOptions ?
+      reinterpret_cast<const Conv2DOptionsT *>(value) : nullptr;
+  }
+  DepthwiseConv2DOptionsT *AsDepthwiseConv2DOptions() {
+    return type == BuiltinOptions_DepthwiseConv2DOptions ?
+      reinterpret_cast<DepthwiseConv2DOptionsT *>(value) : nullptr;
+  }
+  const DepthwiseConv2DOptionsT *AsDepthwiseConv2DOptions() const {
+    return type == BuiltinOptions_DepthwiseConv2DOptions ?
+      reinterpret_cast<const DepthwiseConv2DOptionsT *>(value) : nullptr;
+  }
+  ConcatEmbeddingsOptionsT *AsConcatEmbeddingsOptions() {
+    return type == BuiltinOptions_ConcatEmbeddingsOptions ?
+      reinterpret_cast<ConcatEmbeddingsOptionsT *>(value) : nullptr;
+  }
+  const ConcatEmbeddingsOptionsT *AsConcatEmbeddingsOptions() const {
+    return type == BuiltinOptions_ConcatEmbeddingsOptions ?
+      reinterpret_cast<const ConcatEmbeddingsOptionsT *>(value) : nullptr;
+  }
+  LSHProjectionOptionsT *AsLSHProjectionOptions() {
+    return type == BuiltinOptions_LSHProjectionOptions ?
+      reinterpret_cast<LSHProjectionOptionsT *>(value) : nullptr;
+  }
+  const LSHProjectionOptionsT *AsLSHProjectionOptions() const {
+    return type == BuiltinOptions_LSHProjectionOptions ?
+      reinterpret_cast<const LSHProjectionOptionsT *>(value) : nullptr;
+  }
+  Pool2DOptionsT *AsPool2DOptions() {
+    return type == BuiltinOptions_Pool2DOptions ?
+      reinterpret_cast<Pool2DOptionsT *>(value) : nullptr;
+  }
+  const Pool2DOptionsT *AsPool2DOptions() const {
+    return type == BuiltinOptions_Pool2DOptions ?
+      reinterpret_cast<const Pool2DOptionsT *>(value) : nullptr;
+  }
+  SVDFOptionsT *AsSVDFOptions() {
+    return type == BuiltinOptions_SVDFOptions ?
+      reinterpret_cast<SVDFOptionsT *>(value) : nullptr;
+  }
+  const SVDFOptionsT *AsSVDFOptions() const {
+    return type == BuiltinOptions_SVDFOptions ?
+      reinterpret_cast<const SVDFOptionsT *>(value) : nullptr;
+  }
+  RNNOptionsT *AsRNNOptions() {
+    return type == BuiltinOptions_RNNOptions ?
+      reinterpret_cast<RNNOptionsT *>(value) : nullptr;
+  }
+  const RNNOptionsT *AsRNNOptions() const {
+    return type == BuiltinOptions_RNNOptions ?
+      reinterpret_cast<const RNNOptionsT *>(value) : nullptr;
+  }
+  FullyConnectedOptionsT *AsFullyConnectedOptions() {
+    return type == BuiltinOptions_FullyConnectedOptions ?
+      reinterpret_cast<FullyConnectedOptionsT *>(value) : nullptr;
+  }
+  const FullyConnectedOptionsT *AsFullyConnectedOptions() const {
+    return type == BuiltinOptions_FullyConnectedOptions ?
+      reinterpret_cast<const FullyConnectedOptionsT *>(value) : nullptr;
+  }
+  SoftmaxOptionsT *AsSoftmaxOptions() {
+    return type == BuiltinOptions_SoftmaxOptions ?
+      reinterpret_cast<SoftmaxOptionsT *>(value) : nullptr;
+  }
+  const SoftmaxOptionsT *AsSoftmaxOptions() const {
+    return type == BuiltinOptions_SoftmaxOptions ?
+      reinterpret_cast<const SoftmaxOptionsT *>(value) : nullptr;
+  }
+  ConcatenationOptionsT *AsConcatenationOptions() {
+    return type == BuiltinOptions_ConcatenationOptions ?
+      reinterpret_cast<ConcatenationOptionsT *>(value) : nullptr;
+  }
+  const ConcatenationOptionsT *AsConcatenationOptions() const {
+    return type == BuiltinOptions_ConcatenationOptions ?
+      reinterpret_cast<const ConcatenationOptionsT *>(value) : nullptr;
+  }
+  AddOptionsT *AsAddOptions() {
+    return type == BuiltinOptions_AddOptions ?
+      reinterpret_cast<AddOptionsT *>(value) : nullptr;
+  }
+  const AddOptionsT *AsAddOptions() const {
+    return type == BuiltinOptions_AddOptions ?
+      reinterpret_cast<const AddOptionsT *>(value) : nullptr;
+  }
+  L2NormOptionsT *AsL2NormOptions() {
+    return type == BuiltinOptions_L2NormOptions ?
+      reinterpret_cast<L2NormOptionsT *>(value) : nullptr;
+  }
+  const L2NormOptionsT *AsL2NormOptions() const {
+    return type == BuiltinOptions_L2NormOptions ?
+      reinterpret_cast<const L2NormOptionsT *>(value) : nullptr;
+  }
+  LocalResponseNormalizationOptionsT *AsLocalResponseNormalizationOptions() {
+    return type == BuiltinOptions_LocalResponseNormalizationOptions ?
+      reinterpret_cast<LocalResponseNormalizationOptionsT *>(value) : nullptr;
+  }
+  const LocalResponseNormalizationOptionsT *AsLocalResponseNormalizationOptions() const {
+    return type == BuiltinOptions_LocalResponseNormalizationOptions ?
+      reinterpret_cast<const LocalResponseNormalizationOptionsT *>(value) : nullptr;
+  }
+  LSTMOptionsT *AsLSTMOptions() {
+    return type == BuiltinOptions_LSTMOptions ?
+      reinterpret_cast<LSTMOptionsT *>(value) : nullptr;
+  }
+  const LSTMOptionsT *AsLSTMOptions() const {
+    return type == BuiltinOptions_LSTMOptions ?
+      reinterpret_cast<const LSTMOptionsT *>(value) : nullptr;
+  }
+  ResizeBilinearOptionsT *AsResizeBilinearOptions() {
+    return type == BuiltinOptions_ResizeBilinearOptions ?
+      reinterpret_cast<ResizeBilinearOptionsT *>(value) : nullptr;
+  }
+  const ResizeBilinearOptionsT *AsResizeBilinearOptions() const {
+    return type == BuiltinOptions_ResizeBilinearOptions ?
+      reinterpret_cast<const ResizeBilinearOptionsT *>(value) : nullptr;
+  }
+  CallOptionsT *AsCallOptions() {
+    return type == BuiltinOptions_CallOptions ?
+      reinterpret_cast<CallOptionsT *>(value) : nullptr;
+  }
+  const CallOptionsT *AsCallOptions() const {
+    return type == BuiltinOptions_CallOptions ?
+      reinterpret_cast<const CallOptionsT *>(value) : nullptr;
+  }
+  ReshapeOptionsT *AsReshapeOptions() {
+    return type == BuiltinOptions_ReshapeOptions ?
+      reinterpret_cast<ReshapeOptionsT *>(value) : nullptr;
+  }
+  const ReshapeOptionsT *AsReshapeOptions() const {
+    return type == BuiltinOptions_ReshapeOptions ?
+      reinterpret_cast<const ReshapeOptionsT *>(value) : nullptr;
+  }
+  SkipGramOptionsT *AsSkipGramOptions() {
+    return type == BuiltinOptions_SkipGramOptions ?
+      reinterpret_cast<SkipGramOptionsT *>(value) : nullptr;
+  }
+  const SkipGramOptionsT *AsSkipGramOptions() const {
+    return type == BuiltinOptions_SkipGramOptions ?
+      reinterpret_cast<const SkipGramOptionsT *>(value) : nullptr;
+  }
+  SpaceToDepthOptionsT *AsSpaceToDepthOptions() {
+    return type == BuiltinOptions_SpaceToDepthOptions ?
+      reinterpret_cast<SpaceToDepthOptionsT *>(value) : nullptr;
+  }
+  const SpaceToDepthOptionsT *AsSpaceToDepthOptions() const {
+    return type == BuiltinOptions_SpaceToDepthOptions ?
+      reinterpret_cast<const SpaceToDepthOptionsT *>(value) : nullptr;
+  }
+  EmbeddingLookupSparseOptionsT *AsEmbeddingLookupSparseOptions() {
+    return type == BuiltinOptions_EmbeddingLookupSparseOptions ?
+      reinterpret_cast<EmbeddingLookupSparseOptionsT *>(value) : nullptr;
+  }
+  const EmbeddingLookupSparseOptionsT *AsEmbeddingLookupSparseOptions() const {
+    return type == BuiltinOptions_EmbeddingLookupSparseOptions ?
+      reinterpret_cast<const EmbeddingLookupSparseOptionsT *>(value) : nullptr;
+  }
+  MulOptionsT *AsMulOptions() {
+    return type == BuiltinOptions_MulOptions ?
+      reinterpret_cast<MulOptionsT *>(value) : nullptr;
+  }
+  const MulOptionsT *AsMulOptions() const {
+    return type == BuiltinOptions_MulOptions ?
+      reinterpret_cast<const MulOptionsT *>(value) : nullptr;
+  }
+  PadOptionsT *AsPadOptions() {
+    return type == BuiltinOptions_PadOptions ?
+      reinterpret_cast<PadOptionsT *>(value) : nullptr;
+  }
+  const PadOptionsT *AsPadOptions() const {
+    return type == BuiltinOptions_PadOptions ?
+      reinterpret_cast<const PadOptionsT *>(value) : nullptr;
+  }
+  GatherOptionsT *AsGatherOptions() {
+    return type == BuiltinOptions_GatherOptions ?
+      reinterpret_cast<GatherOptionsT *>(value) : nullptr;
+  }
+  const GatherOptionsT *AsGatherOptions() const {
+    return type == BuiltinOptions_GatherOptions ?
+      reinterpret_cast<const GatherOptionsT *>(value) : nullptr;
+  }
+  BatchToSpaceNDOptionsT *AsBatchToSpaceNDOptions() {
+    return type == BuiltinOptions_BatchToSpaceNDOptions ?
+      reinterpret_cast<BatchToSpaceNDOptionsT *>(value) : nullptr;
+  }
+  const BatchToSpaceNDOptionsT *AsBatchToSpaceNDOptions() const {
+    return type == BuiltinOptions_BatchToSpaceNDOptions ?
+      reinterpret_cast<const BatchToSpaceNDOptionsT *>(value) : nullptr;
+  }
+  SpaceToBatchNDOptionsT *AsSpaceToBatchNDOptions() {
+    return type == BuiltinOptions_SpaceToBatchNDOptions ?
+      reinterpret_cast<SpaceToBatchNDOptionsT *>(value) : nullptr;
+  }
+  const SpaceToBatchNDOptionsT *AsSpaceToBatchNDOptions() const {
+    return type == BuiltinOptions_SpaceToBatchNDOptions ?
+      reinterpret_cast<const SpaceToBatchNDOptionsT *>(value) : nullptr;
+  }
+  TransposeOptionsT *AsTransposeOptions() {
+    return type == BuiltinOptions_TransposeOptions ?
+      reinterpret_cast<TransposeOptionsT *>(value) : nullptr;
+  }
+  const TransposeOptionsT *AsTransposeOptions() const {
+    return type == BuiltinOptions_TransposeOptions ?
+      reinterpret_cast<const TransposeOptionsT *>(value) : nullptr;
+  }
+  ReducerOptionsT *AsReducerOptions() {
+    return type == BuiltinOptions_ReducerOptions ?
+      reinterpret_cast<ReducerOptionsT *>(value) : nullptr;
+  }
+  const ReducerOptionsT *AsReducerOptions() const {
+    return type == BuiltinOptions_ReducerOptions ?
+      reinterpret_cast<const ReducerOptionsT *>(value) : nullptr;
+  }
+  SubOptionsT *AsSubOptions() {
+    return type == BuiltinOptions_SubOptions ?
+      reinterpret_cast<SubOptionsT *>(value) : nullptr;
+  }
+  const SubOptionsT *AsSubOptions() const {
+    return type == BuiltinOptions_SubOptions ?
+      reinterpret_cast<const SubOptionsT *>(value) : nullptr;
+  }
+  DivOptionsT *AsDivOptions() {
+    return type == BuiltinOptions_DivOptions ?
+      reinterpret_cast<DivOptionsT *>(value) : nullptr;
+  }
+  const DivOptionsT *AsDivOptions() const {
+    return type == BuiltinOptions_DivOptions ?
+      reinterpret_cast<const DivOptionsT *>(value) : nullptr;
+  }
+  SqueezeOptionsT *AsSqueezeOptions() {
+    return type == BuiltinOptions_SqueezeOptions ?
+      reinterpret_cast<SqueezeOptionsT *>(value) : nullptr;
+  }
+  const SqueezeOptionsT *AsSqueezeOptions() const {
+    return type == BuiltinOptions_SqueezeOptions ?
+      reinterpret_cast<const SqueezeOptionsT *>(value) : nullptr;
+  }
+  SequenceRNNOptionsT *AsSequenceRNNOptions() {
+    return type == BuiltinOptions_SequenceRNNOptions ?
+      reinterpret_cast<SequenceRNNOptionsT *>(value) : nullptr;
+  }
+  const SequenceRNNOptionsT *AsSequenceRNNOptions() const {
+    return type == BuiltinOptions_SequenceRNNOptions ?
+      reinterpret_cast<const SequenceRNNOptionsT *>(value) : nullptr;
+  }
+  StridedSliceOptionsT *AsStridedSliceOptions() {
+    return type == BuiltinOptions_StridedSliceOptions ?
+      reinterpret_cast<StridedSliceOptionsT *>(value) : nullptr;
+  }
+  const StridedSliceOptionsT *AsStridedSliceOptions() const {
+    return type == BuiltinOptions_StridedSliceOptions ?
+      reinterpret_cast<const StridedSliceOptionsT *>(value) : nullptr;
+  }
+  ExpOptionsT *AsExpOptions() {
+    return type == BuiltinOptions_ExpOptions ?
+      reinterpret_cast<ExpOptionsT *>(value) : nullptr;
+  }
+  const ExpOptionsT *AsExpOptions() const {
+    return type == BuiltinOptions_ExpOptions ?
+      reinterpret_cast<const ExpOptionsT *>(value) : nullptr;
+  }
+  TopKV2OptionsT *AsTopKV2Options() {
+    return type == BuiltinOptions_TopKV2Options ?
+      reinterpret_cast<TopKV2OptionsT *>(value) : nullptr;
+  }
+  const TopKV2OptionsT *AsTopKV2Options() const {
+    return type == BuiltinOptions_TopKV2Options ?
+      reinterpret_cast<const TopKV2OptionsT *>(value) : nullptr;
+  }
+  SplitOptionsT *AsSplitOptions() {
+    return type == BuiltinOptions_SplitOptions ?
+      reinterpret_cast<SplitOptionsT *>(value) : nullptr;
+  }
+  const SplitOptionsT *AsSplitOptions() const {
+    return type == BuiltinOptions_SplitOptions ?
+      reinterpret_cast<const SplitOptionsT *>(value) : nullptr;
+  }
+  LogSoftmaxOptionsT *AsLogSoftmaxOptions() {
+    return type == BuiltinOptions_LogSoftmaxOptions ?
+      reinterpret_cast<LogSoftmaxOptionsT *>(value) : nullptr;
+  }
+  const LogSoftmaxOptionsT *AsLogSoftmaxOptions() const {
+    return type == BuiltinOptions_LogSoftmaxOptions ?
+      reinterpret_cast<const LogSoftmaxOptionsT *>(value) : nullptr;
+  }
+  CastOptionsT *AsCastOptions() {
+    return type == BuiltinOptions_CastOptions ?
+      reinterpret_cast<CastOptionsT *>(value) : nullptr;
+  }
+  const CastOptionsT *AsCastOptions() const {
+    return type == BuiltinOptions_CastOptions ?
+      reinterpret_cast<const CastOptionsT *>(value) : nullptr;
+  }
+  DequantizeOptionsT *AsDequantizeOptions() {
+    return type == BuiltinOptions_DequantizeOptions ?
+      reinterpret_cast<DequantizeOptionsT *>(value) : nullptr;
+  }
+  const DequantizeOptionsT *AsDequantizeOptions() const {
+    return type == BuiltinOptions_DequantizeOptions ?
+      reinterpret_cast<const DequantizeOptionsT *>(value) : nullptr;
+  }
+  MaximumMinimumOptionsT *AsMaximumMinimumOptions() {
+    return type == BuiltinOptions_MaximumMinimumOptions ?
+      reinterpret_cast<MaximumMinimumOptionsT *>(value) : nullptr;
+  }
+  const MaximumMinimumOptionsT *AsMaximumMinimumOptions() const {
+    return type == BuiltinOptions_MaximumMinimumOptions ?
+      reinterpret_cast<const MaximumMinimumOptionsT *>(value) : nullptr;
+  }
+  ArgMaxOptionsT *AsArgMaxOptions() {
+    return type == BuiltinOptions_ArgMaxOptions ?
+      reinterpret_cast<ArgMaxOptionsT *>(value) : nullptr;
+  }
+  const ArgMaxOptionsT *AsArgMaxOptions() const {
+    return type == BuiltinOptions_ArgMaxOptions ?
+      reinterpret_cast<const ArgMaxOptionsT *>(value) : nullptr;
+  }
+  LessOptionsT *AsLessOptions() {
+    return type == BuiltinOptions_LessOptions ?
+      reinterpret_cast<LessOptionsT *>(value) : nullptr;
+  }
+  const LessOptionsT *AsLessOptions() const {
+    return type == BuiltinOptions_LessOptions ?
+      reinterpret_cast<const LessOptionsT *>(value) : nullptr;
+  }
+  NegOptionsT *AsNegOptions() {
+    return type == BuiltinOptions_NegOptions ?
+      reinterpret_cast<NegOptionsT *>(value) : nullptr;
+  }
+  const NegOptionsT *AsNegOptions() const {
+    return type == BuiltinOptions_NegOptions ?
+      reinterpret_cast<const NegOptionsT *>(value) : nullptr;
+  }
+  PadV2OptionsT *AsPadV2Options() {
+    return type == BuiltinOptions_PadV2Options ?
+      reinterpret_cast<PadV2OptionsT *>(value) : nullptr;
+  }
+  const PadV2OptionsT *AsPadV2Options() const {
+    return type == BuiltinOptions_PadV2Options ?
+      reinterpret_cast<const PadV2OptionsT *>(value) : nullptr;
+  }
+  GreaterOptionsT *AsGreaterOptions() {
+    return type == BuiltinOptions_GreaterOptions ?
+      reinterpret_cast<GreaterOptionsT *>(value) : nullptr;
+  }
+  const GreaterOptionsT *AsGreaterOptions() const {
+    return type == BuiltinOptions_GreaterOptions ?
+      reinterpret_cast<const GreaterOptionsT *>(value) : nullptr;
+  }
+  GreaterEqualOptionsT *AsGreaterEqualOptions() {
+    return type == BuiltinOptions_GreaterEqualOptions ?
+      reinterpret_cast<GreaterEqualOptionsT *>(value) : nullptr;
+  }
+  const GreaterEqualOptionsT *AsGreaterEqualOptions() const {
+    return type == BuiltinOptions_GreaterEqualOptions ?
+      reinterpret_cast<const GreaterEqualOptionsT *>(value) : nullptr;
+  }
+  LessEqualOptionsT *AsLessEqualOptions() {
+    return type == BuiltinOptions_LessEqualOptions ?
+      reinterpret_cast<LessEqualOptionsT *>(value) : nullptr;
+  }
+  const LessEqualOptionsT *AsLessEqualOptions() const {
+    return type == BuiltinOptions_LessEqualOptions ?
+      reinterpret_cast<const LessEqualOptionsT *>(value) : nullptr;
+  }
+  SelectOptionsT *AsSelectOptions() {
+    return type == BuiltinOptions_SelectOptions ?
+      reinterpret_cast<SelectOptionsT *>(value) : nullptr;
+  }
+  const SelectOptionsT *AsSelectOptions() const {
+    return type == BuiltinOptions_SelectOptions ?
+      reinterpret_cast<const SelectOptionsT *>(value) : nullptr;
+  }
+  SliceOptionsT *AsSliceOptions() {
+    return type == BuiltinOptions_SliceOptions ?
+      reinterpret_cast<SliceOptionsT *>(value) : nullptr;
+  }
+  const SliceOptionsT *AsSliceOptions() const {
+    return type == BuiltinOptions_SliceOptions ?
+      reinterpret_cast<const SliceOptionsT *>(value) : nullptr;
+  }
+  TransposeConvOptionsT *AsTransposeConvOptions() {
+    return type == BuiltinOptions_TransposeConvOptions ?
+      reinterpret_cast<TransposeConvOptionsT *>(value) : nullptr;
+  }
+  const TransposeConvOptionsT *AsTransposeConvOptions() const {
+    return type == BuiltinOptions_TransposeConvOptions ?
+      reinterpret_cast<const TransposeConvOptionsT *>(value) : nullptr;
+  }
+  SparseToDenseOptionsT *AsSparseToDenseOptions() {
+    return type == BuiltinOptions_SparseToDenseOptions ?
+      reinterpret_cast<SparseToDenseOptionsT *>(value) : nullptr;
+  }
+  const SparseToDenseOptionsT *AsSparseToDenseOptions() const {
+    return type == BuiltinOptions_SparseToDenseOptions ?
+      reinterpret_cast<const SparseToDenseOptionsT *>(value) : nullptr;
+  }
+  TileOptionsT *AsTileOptions() {
+    return type == BuiltinOptions_TileOptions ?
+      reinterpret_cast<TileOptionsT *>(value) : nullptr;
+  }
+  const TileOptionsT *AsTileOptions() const {
+    return type == BuiltinOptions_TileOptions ?
+      reinterpret_cast<const TileOptionsT *>(value) : nullptr;
+  }
+  ExpandDimsOptionsT *AsExpandDimsOptions() {
+    return type == BuiltinOptions_ExpandDimsOptions ?
+      reinterpret_cast<ExpandDimsOptionsT *>(value) : nullptr;
+  }
+  const ExpandDimsOptionsT *AsExpandDimsOptions() const {
+    return type == BuiltinOptions_ExpandDimsOptions ?
+      reinterpret_cast<const ExpandDimsOptionsT *>(value) : nullptr;
+  }
+  EqualOptionsT *AsEqualOptions() {
+    return type == BuiltinOptions_EqualOptions ?
+      reinterpret_cast<EqualOptionsT *>(value) : nullptr;
+  }
+  const EqualOptionsT *AsEqualOptions() const {
+    return type == BuiltinOptions_EqualOptions ?
+      reinterpret_cast<const EqualOptionsT *>(value) : nullptr;
+  }
+  NotEqualOptionsT *AsNotEqualOptions() {
+    return type == BuiltinOptions_NotEqualOptions ?
+      reinterpret_cast<NotEqualOptionsT *>(value) : nullptr;
+  }
+  const NotEqualOptionsT *AsNotEqualOptions() const {
+    return type == BuiltinOptions_NotEqualOptions ?
+      reinterpret_cast<const NotEqualOptionsT *>(value) : nullptr;
+  }
+  ShapeOptionsT *AsShapeOptions() {
+    return type == BuiltinOptions_ShapeOptions ?
+      reinterpret_cast<ShapeOptionsT *>(value) : nullptr;
+  }
+  const ShapeOptionsT *AsShapeOptions() const {
+    return type == BuiltinOptions_ShapeOptions ?
+      reinterpret_cast<const ShapeOptionsT *>(value) : nullptr;
+  }
+  PowOptionsT *AsPowOptions() {
+    return type == BuiltinOptions_PowOptions ?
+      reinterpret_cast<PowOptionsT *>(value) : nullptr;
+  }
+  const PowOptionsT *AsPowOptions() const {
+    return type == BuiltinOptions_PowOptions ?
+      reinterpret_cast<const PowOptionsT *>(value) : nullptr;
+  }
+  ArgMinOptionsT *AsArgMinOptions() {
+    return type == BuiltinOptions_ArgMinOptions ?
+      reinterpret_cast<ArgMinOptionsT *>(value) : nullptr;
+  }
+  const ArgMinOptionsT *AsArgMinOptions() const {
+    return type == BuiltinOptions_ArgMinOptions ?
+      reinterpret_cast<const ArgMinOptionsT *>(value) : nullptr;
+  }
+  FakeQuantOptionsT *AsFakeQuantOptions() {
+    return type == BuiltinOptions_FakeQuantOptions ?
+      reinterpret_cast<FakeQuantOptionsT *>(value) : nullptr;
+  }
+  const FakeQuantOptionsT *AsFakeQuantOptions() const {
+    return type == BuiltinOptions_FakeQuantOptions ?
+      reinterpret_cast<const FakeQuantOptionsT *>(value) : nullptr;
+  }
+  PackOptionsT *AsPackOptions() {
+    return type == BuiltinOptions_PackOptions ?
+      reinterpret_cast<PackOptionsT *>(value) : nullptr;
+  }
+  const PackOptionsT *AsPackOptions() const {
+    return type == BuiltinOptions_PackOptions ?
+      reinterpret_cast<const PackOptionsT *>(value) : nullptr;
+  }
+  LogicalOrOptionsT *AsLogicalOrOptions() {
+    return type == BuiltinOptions_LogicalOrOptions ?
+      reinterpret_cast<LogicalOrOptionsT *>(value) : nullptr;
+  }
+  const LogicalOrOptionsT *AsLogicalOrOptions() const {
+    return type == BuiltinOptions_LogicalOrOptions ?
+      reinterpret_cast<const LogicalOrOptionsT *>(value) : nullptr;
+  }
+  OneHotOptionsT *AsOneHotOptions() {
+    return type == BuiltinOptions_OneHotOptions ?
+      reinterpret_cast<OneHotOptionsT *>(value) : nullptr;
+  }
+  const OneHotOptionsT *AsOneHotOptions() const {
+    return type == BuiltinOptions_OneHotOptions ?
+      reinterpret_cast<const OneHotOptionsT *>(value) : nullptr;
+  }
+  LogicalAndOptionsT *AsLogicalAndOptions() {
+    return type == BuiltinOptions_LogicalAndOptions ?
+      reinterpret_cast<LogicalAndOptionsT *>(value) : nullptr;
+  }
+  const LogicalAndOptionsT *AsLogicalAndOptions() const {
+    return type == BuiltinOptions_LogicalAndOptions ?
+      reinterpret_cast<const LogicalAndOptionsT *>(value) : nullptr;
+  }
+  LogicalNotOptionsT *AsLogicalNotOptions() {
+    return type == BuiltinOptions_LogicalNotOptions ?
+      reinterpret_cast<LogicalNotOptionsT *>(value) : nullptr;
+  }
+  const LogicalNotOptionsT *AsLogicalNotOptions() const {
+    return type == BuiltinOptions_LogicalNotOptions ?
+      reinterpret_cast<const LogicalNotOptionsT *>(value) : nullptr;
+  }
+  UnpackOptionsT *AsUnpackOptions() {
+    return type == BuiltinOptions_UnpackOptions ?
+      reinterpret_cast<UnpackOptionsT *>(value) : nullptr;
+  }
+  const UnpackOptionsT *AsUnpackOptions() const {
+    return type == BuiltinOptions_UnpackOptions ?
+      reinterpret_cast<const UnpackOptionsT *>(value) : nullptr;
+  }
+  FloorDivOptionsT *AsFloorDivOptions() {
+    return type == BuiltinOptions_FloorDivOptions ?
+      reinterpret_cast<FloorDivOptionsT *>(value) : nullptr;
+  }
+  const FloorDivOptionsT *AsFloorDivOptions() const {
+    return type == BuiltinOptions_FloorDivOptions ?
+      reinterpret_cast<const FloorDivOptionsT *>(value) : nullptr;
+  }
+  SquareOptionsT *AsSquareOptions() {
+    return type == BuiltinOptions_SquareOptions ?
+      reinterpret_cast<SquareOptionsT *>(value) : nullptr;
+  }
+  const SquareOptionsT *AsSquareOptions() const {
+    return type == BuiltinOptions_SquareOptions ?
+      reinterpret_cast<const SquareOptionsT *>(value) : nullptr;
+  }
+  ZerosLikeOptionsT *AsZerosLikeOptions() {
+    return type == BuiltinOptions_ZerosLikeOptions ?
+      reinterpret_cast<ZerosLikeOptionsT *>(value) : nullptr;
+  }
+  const ZerosLikeOptionsT *AsZerosLikeOptions() const {
+    return type == BuiltinOptions_ZerosLikeOptions ?
+      reinterpret_cast<const ZerosLikeOptionsT *>(value) : nullptr;
+  }
+  FillOptionsT *AsFillOptions() {
+    return type == BuiltinOptions_FillOptions ?
+      reinterpret_cast<FillOptionsT *>(value) : nullptr;
+  }
+  const FillOptionsT *AsFillOptions() const {
+    return type == BuiltinOptions_FillOptions ?
+      reinterpret_cast<const FillOptionsT *>(value) : nullptr;
+  }
+  BidirectionalSequenceLSTMOptionsT *AsBidirectionalSequenceLSTMOptions() {
+    return type == BuiltinOptions_BidirectionalSequenceLSTMOptions ?
+      reinterpret_cast<BidirectionalSequenceLSTMOptionsT *>(value) : nullptr;
+  }
+  const BidirectionalSequenceLSTMOptionsT *AsBidirectionalSequenceLSTMOptions() const {
+    return type == BuiltinOptions_BidirectionalSequenceLSTMOptions ?
+      reinterpret_cast<const BidirectionalSequenceLSTMOptionsT *>(value) : nullptr;
+  }
+  BidirectionalSequenceRNNOptionsT *AsBidirectionalSequenceRNNOptions() {
+    return type == BuiltinOptions_BidirectionalSequenceRNNOptions ?
+      reinterpret_cast<BidirectionalSequenceRNNOptionsT *>(value) : nullptr;
+  }
+  const BidirectionalSequenceRNNOptionsT *AsBidirectionalSequenceRNNOptions() const {
+    return type == BuiltinOptions_BidirectionalSequenceRNNOptions ?
+      reinterpret_cast<const BidirectionalSequenceRNNOptionsT *>(value) : nullptr;
+  }
+  UnidirectionalSequenceLSTMOptionsT *AsUnidirectionalSequenceLSTMOptions() {
+    return type == BuiltinOptions_UnidirectionalSequenceLSTMOptions ?
+      reinterpret_cast<UnidirectionalSequenceLSTMOptionsT *>(value) : nullptr;
+  }
+  const UnidirectionalSequenceLSTMOptionsT *AsUnidirectionalSequenceLSTMOptions() const {
+    return type == BuiltinOptions_UnidirectionalSequenceLSTMOptions ?
+      reinterpret_cast<const UnidirectionalSequenceLSTMOptionsT *>(value) : nullptr;
+  }
+  FloorModOptionsT *AsFloorModOptions() {
+    return type == BuiltinOptions_FloorModOptions ?
+      reinterpret_cast<FloorModOptionsT *>(value) : nullptr;
+  }
+  const FloorModOptionsT *AsFloorModOptions() const {
+    return type == BuiltinOptions_FloorModOptions ?
+      reinterpret_cast<const FloorModOptionsT *>(value) : nullptr;
+  }
+  RangeOptionsT *AsRangeOptions() {
+    return type == BuiltinOptions_RangeOptions ?
+      reinterpret_cast<RangeOptionsT *>(value) : nullptr;
+  }
+  const RangeOptionsT *AsRangeOptions() const {
+    return type == BuiltinOptions_RangeOptions ?
+      reinterpret_cast<const RangeOptionsT *>(value) : nullptr;
+  }
+  ResizeNearestNeighborOptionsT *AsResizeNearestNeighborOptions() {
+    return type == BuiltinOptions_ResizeNearestNeighborOptions ?
+      reinterpret_cast<ResizeNearestNeighborOptionsT *>(value) : nullptr;
+  }
+  const ResizeNearestNeighborOptionsT *AsResizeNearestNeighborOptions() const {
+    return type == BuiltinOptions_ResizeNearestNeighborOptions ?
+      reinterpret_cast<const ResizeNearestNeighborOptionsT *>(value) : nullptr;
+  }
+  LeakyReluOptionsT *AsLeakyReluOptions() {
+    return type == BuiltinOptions_LeakyReluOptions ?
+      reinterpret_cast<LeakyReluOptionsT *>(value) : nullptr;
+  }
+  const LeakyReluOptionsT *AsLeakyReluOptions() const {
+    return type == BuiltinOptions_LeakyReluOptions ?
+      reinterpret_cast<const LeakyReluOptionsT *>(value) : nullptr;
+  }
+  SquaredDifferenceOptionsT *AsSquaredDifferenceOptions() {
+    return type == BuiltinOptions_SquaredDifferenceOptions ?
+      reinterpret_cast<SquaredDifferenceOptionsT *>(value) : nullptr;
+  }
+  const SquaredDifferenceOptionsT *AsSquaredDifferenceOptions() const {
+    return type == BuiltinOptions_SquaredDifferenceOptions ?
+      reinterpret_cast<const SquaredDifferenceOptionsT *>(value) : nullptr;
+  }
+  MirrorPadOptionsT *AsMirrorPadOptions() {
+    return type == BuiltinOptions_MirrorPadOptions ?
+      reinterpret_cast<MirrorPadOptionsT *>(value) : nullptr;
+  }
+  const MirrorPadOptionsT *AsMirrorPadOptions() const {
+    return type == BuiltinOptions_MirrorPadOptions ?
+      reinterpret_cast<const MirrorPadOptionsT *>(value) : nullptr;
+  }
+  AbsOptionsT *AsAbsOptions() {
+    return type == BuiltinOptions_AbsOptions ?
+      reinterpret_cast<AbsOptionsT *>(value) : nullptr;
+  }
+  const AbsOptionsT *AsAbsOptions() const {
+    return type == BuiltinOptions_AbsOptions ?
+      reinterpret_cast<const AbsOptionsT *>(value) : nullptr;
+  }
+  SplitVOptionsT *AsSplitVOptions() {
+    return type == BuiltinOptions_SplitVOptions ?
+      reinterpret_cast<SplitVOptionsT *>(value) : nullptr;
+  }
+  const SplitVOptionsT *AsSplitVOptions() const {
+    return type == BuiltinOptions_SplitVOptions ?
+      reinterpret_cast<const SplitVOptionsT *>(value) : nullptr;
+  }
+  UniqueOptionsT *AsUniqueOptions() {
+    return type == BuiltinOptions_UniqueOptions ?
+      reinterpret_cast<UniqueOptionsT *>(value) : nullptr;
+  }
+  const UniqueOptionsT *AsUniqueOptions() const {
+    return type == BuiltinOptions_UniqueOptions ?
+      reinterpret_cast<const UniqueOptionsT *>(value) : nullptr;
+  }
+  ReverseV2OptionsT *AsReverseV2Options() {
+    return type == BuiltinOptions_ReverseV2Options ?
+      reinterpret_cast<ReverseV2OptionsT *>(value) : nullptr;
+  }
+  const ReverseV2OptionsT *AsReverseV2Options() const {
+    return type == BuiltinOptions_ReverseV2Options ?
+      reinterpret_cast<const ReverseV2OptionsT *>(value) : nullptr;
+  }
+  AddNOptionsT *AsAddNOptions() {
+    return type == BuiltinOptions_AddNOptions ?
+      reinterpret_cast<AddNOptionsT *>(value) : nullptr;
+  }
+  const AddNOptionsT *AsAddNOptions() const {
+    return type == BuiltinOptions_AddNOptions ?
+      reinterpret_cast<const AddNOptionsT *>(value) : nullptr;
+  }
+  GatherNdOptionsT *AsGatherNdOptions() {
+    return type == BuiltinOptions_GatherNdOptions ?
+      reinterpret_cast<GatherNdOptionsT *>(value) : nullptr;
+  }
+  const GatherNdOptionsT *AsGatherNdOptions() const {
+    return type == BuiltinOptions_GatherNdOptions ?
+      reinterpret_cast<const GatherNdOptionsT *>(value) : nullptr;
+  }
+  CosOptionsT *AsCosOptions() {
+    return type == BuiltinOptions_CosOptions ?
+      reinterpret_cast<CosOptionsT *>(value) : nullptr;
+  }
+  const CosOptionsT *AsCosOptions() const {
+    return type == BuiltinOptions_CosOptions ?
+      reinterpret_cast<const CosOptionsT *>(value) : nullptr;
+  }
+  WhereOptionsT *AsWhereOptions() {
+    return type == BuiltinOptions_WhereOptions ?
+      reinterpret_cast<WhereOptionsT *>(value) : nullptr;
+  }
+  const WhereOptionsT *AsWhereOptions() const {
+    return type == BuiltinOptions_WhereOptions ?
+      reinterpret_cast<const WhereOptionsT *>(value) : nullptr;
+  }
+  RankOptionsT *AsRankOptions() {
+    return type == BuiltinOptions_RankOptions ?
+      reinterpret_cast<RankOptionsT *>(value) : nullptr;
+  }
+  const RankOptionsT *AsRankOptions() const {
+    return type == BuiltinOptions_RankOptions ?
+      reinterpret_cast<const RankOptionsT *>(value) : nullptr;
+  }
+  ReverseSequenceOptionsT *AsReverseSequenceOptions() {
+    return type == BuiltinOptions_ReverseSequenceOptions ?
+      reinterpret_cast<ReverseSequenceOptionsT *>(value) : nullptr;
+  }
+  const ReverseSequenceOptionsT *AsReverseSequenceOptions() const {
+    return type == BuiltinOptions_ReverseSequenceOptions ?
+      reinterpret_cast<const ReverseSequenceOptionsT *>(value) : nullptr;
+  }
+  MatrixDiagOptionsT *AsMatrixDiagOptions() {
+    return type == BuiltinOptions_MatrixDiagOptions ?
+      reinterpret_cast<MatrixDiagOptionsT *>(value) : nullptr;
+  }
+  const MatrixDiagOptionsT *AsMatrixDiagOptions() const {
+    return type == BuiltinOptions_MatrixDiagOptions ?
+      reinterpret_cast<const MatrixDiagOptionsT *>(value) : nullptr;
+  }
+  QuantizeOptionsT *AsQuantizeOptions() {
+    return type == BuiltinOptions_QuantizeOptions ?
+      reinterpret_cast<QuantizeOptionsT *>(value) : nullptr;
+  }
+  const QuantizeOptionsT *AsQuantizeOptions() const {
+    return type == BuiltinOptions_QuantizeOptions ?
+      reinterpret_cast<const QuantizeOptionsT *>(value) : nullptr;
+  }
+  MatrixSetDiagOptionsT *AsMatrixSetDiagOptions() {
+    return type == BuiltinOptions_MatrixSetDiagOptions ?
+      reinterpret_cast<MatrixSetDiagOptionsT *>(value) : nullptr;
+  }
+  const MatrixSetDiagOptionsT *AsMatrixSetDiagOptions() const {
+    return type == BuiltinOptions_MatrixSetDiagOptions ?
+      reinterpret_cast<const MatrixSetDiagOptionsT *>(value) : nullptr;
+  }
+  HardSwishOptionsT *AsHardSwishOptions() {
+    return type == BuiltinOptions_HardSwishOptions ?
+      reinterpret_cast<HardSwishOptionsT *>(value) : nullptr;
+  }
+  const HardSwishOptionsT *AsHardSwishOptions() const {
+    return type == BuiltinOptions_HardSwishOptions ?
+      reinterpret_cast<const HardSwishOptionsT *>(value) : nullptr;
+  }
+  IfOptionsT *AsIfOptions() {
+    return type == BuiltinOptions_IfOptions ?
+      reinterpret_cast<IfOptionsT *>(value) : nullptr;
+  }
+  const IfOptionsT *AsIfOptions() const {
+    return type == BuiltinOptions_IfOptions ?
+      reinterpret_cast<const IfOptionsT *>(value) : nullptr;
+  }
+  WhileOptionsT *AsWhileOptions() {
+    return type == BuiltinOptions_WhileOptions ?
+      reinterpret_cast<WhileOptionsT *>(value) : nullptr;
+  }
+  const WhileOptionsT *AsWhileOptions() const {
+    return type == BuiltinOptions_WhileOptions ?
+      reinterpret_cast<const WhileOptionsT *>(value) : nullptr;
+  }
+  DepthToSpaceOptionsT *AsDepthToSpaceOptions() {
+    return type == BuiltinOptions_DepthToSpaceOptions ?
+      reinterpret_cast<DepthToSpaceOptionsT *>(value) : nullptr;
+  }
+  const DepthToSpaceOptionsT *AsDepthToSpaceOptions() const {
+    return type == BuiltinOptions_DepthToSpaceOptions ?
+      reinterpret_cast<const DepthToSpaceOptionsT *>(value) : nullptr;
+  }
+  NonMaxSuppressionV4OptionsT *AsNonMaxSuppressionV4Options() {
+    return type == BuiltinOptions_NonMaxSuppressionV4Options ?
+      reinterpret_cast<NonMaxSuppressionV4OptionsT *>(value) : nullptr;
+  }
+  const NonMaxSuppressionV4OptionsT *AsNonMaxSuppressionV4Options() const {
+    return type == BuiltinOptions_NonMaxSuppressionV4Options ?
+      reinterpret_cast<const NonMaxSuppressionV4OptionsT *>(value) : nullptr;
+  }
+  NonMaxSuppressionV5OptionsT *AsNonMaxSuppressionV5Options() {
+    return type == BuiltinOptions_NonMaxSuppressionV5Options ?
+      reinterpret_cast<NonMaxSuppressionV5OptionsT *>(value) : nullptr;
+  }
+  const NonMaxSuppressionV5OptionsT *AsNonMaxSuppressionV5Options() const {
+    return type == BuiltinOptions_NonMaxSuppressionV5Options ?
+      reinterpret_cast<const NonMaxSuppressionV5OptionsT *>(value) : nullptr;
+  }
+  ScatterNdOptionsT *AsScatterNdOptions() {
+    return type == BuiltinOptions_ScatterNdOptions ?
+      reinterpret_cast<ScatterNdOptionsT *>(value) : nullptr;
+  }
+  const ScatterNdOptionsT *AsScatterNdOptions() const {
+    return type == BuiltinOptions_ScatterNdOptions ?
+      reinterpret_cast<const ScatterNdOptionsT *>(value) : nullptr;
+  }
+};
+
+bool VerifyBuiltinOptions(flatbuffers::Verifier &verifier, const void *obj, BuiltinOptions type);
+bool VerifyBuiltinOptionsVector(flatbuffers::Verifier &verifier, const flatbuffers::Vector<flatbuffers::Offset<void>> *values, const flatbuffers::Vector<uint8_t> *types);
+
+enum Padding {
+  Padding_SAME = 0,
+  Padding_VALID = 1,
+  Padding_MIN = Padding_SAME,
+  Padding_MAX = Padding_VALID
+};
+
+inline const Padding (&EnumValuesPadding())[2] {
+  static const Padding values[] = {
+    Padding_SAME,
+    Padding_VALID
+  };
+  return values;
+}
+
+inline const char * const *EnumNamesPadding() {
+  static const char * const names[] = {
+    "SAME",
+    "VALID",
+    nullptr
+  };
+  return names;
+}
+
+inline const char *EnumNamePadding(Padding e) {
+  if (e < Padding_SAME || e > Padding_VALID) return "";
+  const size_t index = static_cast<size_t>(e);
+  return EnumNamesPadding()[index];
+}
+
+enum ActivationFunctionType {
+  ActivationFunctionType_NONE = 0,
+  ActivationFunctionType_RELU = 1,
+  ActivationFunctionType_RELU_N1_TO_1 = 2,
+  ActivationFunctionType_RELU6 = 3,
+  ActivationFunctionType_TANH = 4,
+  ActivationFunctionType_SIGN_BIT = 5,
+  ActivationFunctionType_MIN = ActivationFunctionType_NONE,
+  ActivationFunctionType_MAX = ActivationFunctionType_SIGN_BIT
+};
+
+inline const ActivationFunctionType (&EnumValuesActivationFunctionType())[6] {
+  static const ActivationFunctionType values[] = {
+    ActivationFunctionType_NONE,
+    ActivationFunctionType_RELU,
+    ActivationFunctionType_RELU_N1_TO_1,
+    ActivationFunctionType_RELU6,
+    ActivationFunctionType_TANH,
+    ActivationFunctionType_SIGN_BIT
+  };
+  return values;
+}
+
+inline const char * const *EnumNamesActivationFunctionType() {
+  static const char * const names[] = {
+    "NONE",
+    "RELU",
+    "RELU_N1_TO_1",
+    "RELU6",
+    "TANH",
+    "SIGN_BIT",
+    nullptr
+  };
+  return names;
+}
+
+inline const char *EnumNameActivationFunctionType(ActivationFunctionType e) {
+  if (e < ActivationFunctionType_NONE || e > ActivationFunctionType_SIGN_BIT) return "";
+  const size_t index = static_cast<size_t>(e);
+  return EnumNamesActivationFunctionType()[index];
+}
+
+enum LSHProjectionType {
+  LSHProjectionType_UNKNOWN = 0,
+  LSHProjectionType_SPARSE = 1,
+  LSHProjectionType_DENSE = 2,
+  LSHProjectionType_MIN = LSHProjectionType_UNKNOWN,
+  LSHProjectionType_MAX = LSHProjectionType_DENSE
+};
+
+inline const LSHProjectionType (&EnumValuesLSHProjectionType())[3] {
+  static const LSHProjectionType values[] = {
+    LSHProjectionType_UNKNOWN,
+    LSHProjectionType_SPARSE,
+    LSHProjectionType_DENSE
+  };
+  return values;
+}
+
+inline const char * const *EnumNamesLSHProjectionType() {
+  static const char * const names[] = {
+    "UNKNOWN",
+    "SPARSE",
+    "DENSE",
+    nullptr
+  };
+  return names;
+}
+
+inline const char *EnumNameLSHProjectionType(LSHProjectionType e) {
+  if (e < LSHProjectionType_UNKNOWN || e > LSHProjectionType_DENSE) return "";
+  const size_t index = static_cast<size_t>(e);
+  return EnumNamesLSHProjectionType()[index];
+}
+
+enum FullyConnectedOptionsWeightsFormat {
+  FullyConnectedOptionsWeightsFormat_DEFAULT = 0,
+  FullyConnectedOptionsWeightsFormat_SHUFFLED4x16INT8 = 1,
+  FullyConnectedOptionsWeightsFormat_MIN = FullyConnectedOptionsWeightsFormat_DEFAULT,
+  FullyConnectedOptionsWeightsFormat_MAX = FullyConnectedOptionsWeightsFormat_SHUFFLED4x16INT8
+};
+
+inline const FullyConnectedOptionsWeightsFormat (&EnumValuesFullyConnectedOptionsWeightsFormat())[2] {
+  static const FullyConnectedOptionsWeightsFormat values[] = {
+    FullyConnectedOptionsWeightsFormat_DEFAULT,
+    FullyConnectedOptionsWeightsFormat_SHUFFLED4x16INT8
+  };
+  return values;
+}
+
+inline const char * const *EnumNamesFullyConnectedOptionsWeightsFormat() {
+  static const char * const names[] = {
+    "DEFAULT",
+    "SHUFFLED4x16INT8",
+    nullptr
+  };
+  return names;
+}
+
+inline const char *EnumNameFullyConnectedOptionsWeightsFormat(FullyConnectedOptionsWeightsFormat e) {
+  if (e < FullyConnectedOptionsWeightsFormat_DEFAULT || e > FullyConnectedOptionsWeightsFormat_SHUFFLED4x16INT8) return "";
+  const size_t index = static_cast<size_t>(e);
+  return EnumNamesFullyConnectedOptionsWeightsFormat()[index];
+}
+
+enum LSTMKernelType {
+  LSTMKernelType_FULL = 0,
+  LSTMKernelType_BASIC = 1,
+  LSTMKernelType_MIN = LSTMKernelType_FULL,
+  LSTMKernelType_MAX = LSTMKernelType_BASIC
+};
+
+inline const LSTMKernelType (&EnumValuesLSTMKernelType())[2] {
+  static const LSTMKernelType values[] = {
+    LSTMKernelType_FULL,
+    LSTMKernelType_BASIC
+  };
+  return values;
+}
+
+inline const char * const *EnumNamesLSTMKernelType() {
+  static const char * const names[] = {
+    "FULL",
+    "BASIC",
+    nullptr
+  };
+  return names;
+}
+
+inline const char *EnumNameLSTMKernelType(LSTMKernelType e) {
+  if (e < LSTMKernelType_FULL || e > LSTMKernelType_BASIC) return "";
+  const size_t index = static_cast<size_t>(e);
+  return EnumNamesLSTMKernelType()[index];
+}
+
+enum CombinerType {
+  CombinerType_SUM = 0,
+  CombinerType_MEAN = 1,
+  CombinerType_SQRTN = 2,
+  CombinerType_MIN = CombinerType_SUM,
+  CombinerType_MAX = CombinerType_SQRTN
+};
+
+inline const CombinerType (&EnumValuesCombinerType())[3] {
+  static const CombinerType values[] = {
+    CombinerType_SUM,
+    CombinerType_MEAN,
+    CombinerType_SQRTN
+  };
+  return values;
+}
+
+inline const char * const *EnumNamesCombinerType() {
+  static const char * const names[] = {
+    "SUM",
+    "MEAN",
+    "SQRTN",
+    nullptr
+  };
+  return names;
+}
+
+inline const char *EnumNameCombinerType(CombinerType e) {
+  if (e < CombinerType_SUM || e > CombinerType_SQRTN) return "";
+  const size_t index = static_cast<size_t>(e);
+  return EnumNamesCombinerType()[index];
+}
+
+enum MirrorPadMode {
+  MirrorPadMode_REFLECT = 0,
+  MirrorPadMode_SYMMETRIC = 1,
+  MirrorPadMode_MIN = MirrorPadMode_REFLECT,
+  MirrorPadMode_MAX = MirrorPadMode_SYMMETRIC
+};
+
+inline const MirrorPadMode (&EnumValuesMirrorPadMode())[2] {
+  static const MirrorPadMode values[] = {
+    MirrorPadMode_REFLECT,
+    MirrorPadMode_SYMMETRIC
+  };
+  return values;
+}
+
+inline const char * const *EnumNamesMirrorPadMode() {
+  static const char * const names[] = {
+    "REFLECT",
+    "SYMMETRIC",
+    nullptr
+  };
+  return names;
+}
+
+inline const char *EnumNameMirrorPadMode(MirrorPadMode e) {
+  if (e < MirrorPadMode_REFLECT || e > MirrorPadMode_SYMMETRIC) return "";
+  const size_t index = static_cast<size_t>(e);
+  return EnumNamesMirrorPadMode()[index];
+}
+
+enum CustomOptionsFormat {
+  CustomOptionsFormat_FLEXBUFFERS = 0,
+  CustomOptionsFormat_MIN = CustomOptionsFormat_FLEXBUFFERS,
+  CustomOptionsFormat_MAX = CustomOptionsFormat_FLEXBUFFERS
+};
+
+inline const CustomOptionsFormat (&EnumValuesCustomOptionsFormat())[1] {
+  static const CustomOptionsFormat values[] = {
+    CustomOptionsFormat_FLEXBUFFERS
+  };
+  return values;
+}
+
+inline const char * const *EnumNamesCustomOptionsFormat() {
+  static const char * const names[] = {
+    "FLEXBUFFERS",
+    nullptr
+  };
+  return names;
+}
+
+inline const char *EnumNameCustomOptionsFormat(CustomOptionsFormat e) {
+  if (e < CustomOptionsFormat_FLEXBUFFERS || e > CustomOptionsFormat_FLEXBUFFERS) return "";
+  const size_t index = static_cast<size_t>(e);
+  return EnumNamesCustomOptionsFormat()[index];
+}
+
+struct CustomQuantizationT : public flatbuffers::NativeTable {
+  typedef CustomQuantization TableType;
+  std::vector<uint8_t> custom;
+  CustomQuantizationT() {
+  }
+};
+
+struct CustomQuantization FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef CustomQuantizationT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_CUSTOM = 4
+  };
+  const flatbuffers::Vector<uint8_t> *custom() const {
+    return GetPointer<const flatbuffers::Vector<uint8_t> *>(VT_CUSTOM);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyOffset(verifier, VT_CUSTOM) &&
+           verifier.VerifyVector(custom()) &&
+           verifier.EndTable();
+  }
+  CustomQuantizationT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(CustomQuantizationT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<CustomQuantization> Pack(flatbuffers::FlatBufferBuilder &_fbb, const CustomQuantizationT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct CustomQuantizationBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_custom(flatbuffers::Offset<flatbuffers::Vector<uint8_t>> custom) {
+    fbb_.AddOffset(CustomQuantization::VT_CUSTOM, custom);
+  }
+  explicit CustomQuantizationBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  CustomQuantizationBuilder &operator=(const CustomQuantizationBuilder &);
+  flatbuffers::Offset<CustomQuantization> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<CustomQuantization>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<CustomQuantization> CreateCustomQuantization(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    flatbuffers::Offset<flatbuffers::Vector<uint8_t>> custom = 0) {
+  CustomQuantizationBuilder builder_(_fbb);
+  builder_.add_custom(custom);
+  return builder_.Finish();
+}
+
+inline flatbuffers::Offset<CustomQuantization> CreateCustomQuantizationDirect(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    const std::vector<uint8_t> *custom = nullptr) {
+  auto custom__ = custom ? _fbb.CreateVector<uint8_t>(*custom) : 0;
+  return tflite::CreateCustomQuantization(
+      _fbb,
+      custom__);
+}
+
+flatbuffers::Offset<CustomQuantization> CreateCustomQuantization(flatbuffers::FlatBufferBuilder &_fbb, const CustomQuantizationT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct QuantizationParametersT : public flatbuffers::NativeTable {
+  typedef QuantizationParameters TableType;
+  std::vector<float> min;
+  std::vector<float> max;
+  std::vector<float> scale;
+  std::vector<int64_t> zero_point;
+  QuantizationDetailsUnion details;
+  int32_t quantized_dimension;
+  QuantizationParametersT()
+      : quantized_dimension(0) {
+  }
+};
+
+struct QuantizationParameters FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef QuantizationParametersT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_MIN = 4,
+    VT_MAX = 6,
+    VT_SCALE = 8,
+    VT_ZERO_POINT = 10,
+    VT_DETAILS_TYPE = 12,
+    VT_DETAILS = 14,
+    VT_QUANTIZED_DIMENSION = 16
+  };
+  const flatbuffers::Vector<float> *min() const {
+    return GetPointer<const flatbuffers::Vector<float> *>(VT_MIN);
+  }
+  const flatbuffers::Vector<float> *max() const {
+    return GetPointer<const flatbuffers::Vector<float> *>(VT_MAX);
+  }
+  const flatbuffers::Vector<float> *scale() const {
+    return GetPointer<const flatbuffers::Vector<float> *>(VT_SCALE);
+  }
+  const flatbuffers::Vector<int64_t> *zero_point() const {
+    return GetPointer<const flatbuffers::Vector<int64_t> *>(VT_ZERO_POINT);
+  }
+  QuantizationDetails details_type() const {
+    return static_cast<QuantizationDetails>(GetField<uint8_t>(VT_DETAILS_TYPE, 0));
+  }
+  const void *details() const {
+    return GetPointer<const void *>(VT_DETAILS);
+  }
+  template<typename T> const T *details_as() const;
+  const CustomQuantization *details_as_CustomQuantization() const {
+    return details_type() == QuantizationDetails_CustomQuantization ? static_cast<const CustomQuantization *>(details()) : nullptr;
+  }
+  int32_t quantized_dimension() const {
+    return GetField<int32_t>(VT_QUANTIZED_DIMENSION, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyOffset(verifier, VT_MIN) &&
+           verifier.VerifyVector(min()) &&
+           VerifyOffset(verifier, VT_MAX) &&
+           verifier.VerifyVector(max()) &&
+           VerifyOffset(verifier, VT_SCALE) &&
+           verifier.VerifyVector(scale()) &&
+           VerifyOffset(verifier, VT_ZERO_POINT) &&
+           verifier.VerifyVector(zero_point()) &&
+           VerifyField<uint8_t>(verifier, VT_DETAILS_TYPE) &&
+           VerifyOffset(verifier, VT_DETAILS) &&
+           VerifyQuantizationDetails(verifier, details(), details_type()) &&
+           VerifyField<int32_t>(verifier, VT_QUANTIZED_DIMENSION) &&
+           verifier.EndTable();
+  }
+  QuantizationParametersT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(QuantizationParametersT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<QuantizationParameters> Pack(flatbuffers::FlatBufferBuilder &_fbb, const QuantizationParametersT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+template<> inline const CustomQuantization *QuantizationParameters::details_as<CustomQuantization>() const {
+  return details_as_CustomQuantization();
+}
+
+struct QuantizationParametersBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_min(flatbuffers::Offset<flatbuffers::Vector<float>> min) {
+    fbb_.AddOffset(QuantizationParameters::VT_MIN, min);
+  }
+  void add_max(flatbuffers::Offset<flatbuffers::Vector<float>> max) {
+    fbb_.AddOffset(QuantizationParameters::VT_MAX, max);
+  }
+  void add_scale(flatbuffers::Offset<flatbuffers::Vector<float>> scale) {
+    fbb_.AddOffset(QuantizationParameters::VT_SCALE, scale);
+  }
+  void add_zero_point(flatbuffers::Offset<flatbuffers::Vector<int64_t>> zero_point) {
+    fbb_.AddOffset(QuantizationParameters::VT_ZERO_POINT, zero_point);
+  }
+  void add_details_type(QuantizationDetails details_type) {
+    fbb_.AddElement<uint8_t>(QuantizationParameters::VT_DETAILS_TYPE, static_cast<uint8_t>(details_type), 0);
+  }
+  void add_details(flatbuffers::Offset<void> details) {
+    fbb_.AddOffset(QuantizationParameters::VT_DETAILS, details);
+  }
+  void add_quantized_dimension(int32_t quantized_dimension) {
+    fbb_.AddElement<int32_t>(QuantizationParameters::VT_QUANTIZED_DIMENSION, quantized_dimension, 0);
+  }
+  explicit QuantizationParametersBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  QuantizationParametersBuilder &operator=(const QuantizationParametersBuilder &);
+  flatbuffers::Offset<QuantizationParameters> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<QuantizationParameters>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<QuantizationParameters> CreateQuantizationParameters(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    flatbuffers::Offset<flatbuffers::Vector<float>> min = 0,
+    flatbuffers::Offset<flatbuffers::Vector<float>> max = 0,
+    flatbuffers::Offset<flatbuffers::Vector<float>> scale = 0,
+    flatbuffers::Offset<flatbuffers::Vector<int64_t>> zero_point = 0,
+    QuantizationDetails details_type = QuantizationDetails_NONE,
+    flatbuffers::Offset<void> details = 0,
+    int32_t quantized_dimension = 0) {
+  QuantizationParametersBuilder builder_(_fbb);
+  builder_.add_quantized_dimension(quantized_dimension);
+  builder_.add_details(details);
+  builder_.add_zero_point(zero_point);
+  builder_.add_scale(scale);
+  builder_.add_max(max);
+  builder_.add_min(min);
+  builder_.add_details_type(details_type);
+  return builder_.Finish();
+}
+
+inline flatbuffers::Offset<QuantizationParameters> CreateQuantizationParametersDirect(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    const std::vector<float> *min = nullptr,
+    const std::vector<float> *max = nullptr,
+    const std::vector<float> *scale = nullptr,
+    const std::vector<int64_t> *zero_point = nullptr,
+    QuantizationDetails details_type = QuantizationDetails_NONE,
+    flatbuffers::Offset<void> details = 0,
+    int32_t quantized_dimension = 0) {
+  auto min__ = min ? _fbb.CreateVector<float>(*min) : 0;
+  auto max__ = max ? _fbb.CreateVector<float>(*max) : 0;
+  auto scale__ = scale ? _fbb.CreateVector<float>(*scale) : 0;
+  auto zero_point__ = zero_point ? _fbb.CreateVector<int64_t>(*zero_point) : 0;
+  return tflite::CreateQuantizationParameters(
+      _fbb,
+      min__,
+      max__,
+      scale__,
+      zero_point__,
+      details_type,
+      details,
+      quantized_dimension);
+}
+
+flatbuffers::Offset<QuantizationParameters> CreateQuantizationParameters(flatbuffers::FlatBufferBuilder &_fbb, const QuantizationParametersT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct TensorT : public flatbuffers::NativeTable {
+  typedef Tensor TableType;
+  std::vector<int32_t> shape;
+  TensorType type;
+  uint32_t buffer;
+  std::string name;
+  std::unique_ptr<QuantizationParametersT> quantization;
+  bool is_variable;
+  TensorT()
+      : type(TensorType_FLOAT32),
+        buffer(0),
+        is_variable(false) {
+  }
+};
+
+struct Tensor FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef TensorT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_SHAPE = 4,
+    VT_TYPE = 6,
+    VT_BUFFER = 8,
+    VT_NAME = 10,
+    VT_QUANTIZATION = 12,
+    VT_IS_VARIABLE = 14
+  };
+  const flatbuffers::Vector<int32_t> *shape() const {
+    return GetPointer<const flatbuffers::Vector<int32_t> *>(VT_SHAPE);
+  }
+  TensorType type() const {
+    return static_cast<TensorType>(GetField<int8_t>(VT_TYPE, 0));
+  }
+  uint32_t buffer() const {
+    return GetField<uint32_t>(VT_BUFFER, 0);
+  }
+  const flatbuffers::String *name() const {
+    return GetPointer<const flatbuffers::String *>(VT_NAME);
+  }
+  const QuantizationParameters *quantization() const {
+    return GetPointer<const QuantizationParameters *>(VT_QUANTIZATION);
+  }
+  bool is_variable() const {
+    return GetField<uint8_t>(VT_IS_VARIABLE, 0) != 0;
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyOffset(verifier, VT_SHAPE) &&
+           verifier.VerifyVector(shape()) &&
+           VerifyField<int8_t>(verifier, VT_TYPE) &&
+           VerifyField<uint32_t>(verifier, VT_BUFFER) &&
+           VerifyOffset(verifier, VT_NAME) &&
+           verifier.VerifyString(name()) &&
+           VerifyOffset(verifier, VT_QUANTIZATION) &&
+           verifier.VerifyTable(quantization()) &&
+           VerifyField<uint8_t>(verifier, VT_IS_VARIABLE) &&
+           verifier.EndTable();
+  }
+  TensorT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(TensorT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<Tensor> Pack(flatbuffers::FlatBufferBuilder &_fbb, const TensorT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct TensorBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_shape(flatbuffers::Offset<flatbuffers::Vector<int32_t>> shape) {
+    fbb_.AddOffset(Tensor::VT_SHAPE, shape);
+  }
+  void add_type(TensorType type) {
+    fbb_.AddElement<int8_t>(Tensor::VT_TYPE, static_cast<int8_t>(type), 0);
+  }
+  void add_buffer(uint32_t buffer) {
+    fbb_.AddElement<uint32_t>(Tensor::VT_BUFFER, buffer, 0);
+  }
+  void add_name(flatbuffers::Offset<flatbuffers::String> name) {
+    fbb_.AddOffset(Tensor::VT_NAME, name);
+  }
+  void add_quantization(flatbuffers::Offset<QuantizationParameters> quantization) {
+    fbb_.AddOffset(Tensor::VT_QUANTIZATION, quantization);
+  }
+  void add_is_variable(bool is_variable) {
+    fbb_.AddElement<uint8_t>(Tensor::VT_IS_VARIABLE, static_cast<uint8_t>(is_variable), 0);
+  }
+  explicit TensorBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  TensorBuilder &operator=(const TensorBuilder &);
+  flatbuffers::Offset<Tensor> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<Tensor>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<Tensor> CreateTensor(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    flatbuffers::Offset<flatbuffers::Vector<int32_t>> shape = 0,
+    TensorType type = TensorType_FLOAT32,
+    uint32_t buffer = 0,
+    flatbuffers::Offset<flatbuffers::String> name = 0,
+    flatbuffers::Offset<QuantizationParameters> quantization = 0,
+    bool is_variable = false) {
+  TensorBuilder builder_(_fbb);
+  builder_.add_quantization(quantization);
+  builder_.add_name(name);
+  builder_.add_buffer(buffer);
+  builder_.add_shape(shape);
+  builder_.add_is_variable(is_variable);
+  builder_.add_type(type);
+  return builder_.Finish();
+}
+
+inline flatbuffers::Offset<Tensor> CreateTensorDirect(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    const std::vector<int32_t> *shape = nullptr,
+    TensorType type = TensorType_FLOAT32,
+    uint32_t buffer = 0,
+    const char *name = nullptr,
+    flatbuffers::Offset<QuantizationParameters> quantization = 0,
+    bool is_variable = false) {
+  auto shape__ = shape ? _fbb.CreateVector<int32_t>(*shape) : 0;
+  auto name__ = name ? _fbb.CreateString(name) : 0;
+  return tflite::CreateTensor(
+      _fbb,
+      shape__,
+      type,
+      buffer,
+      name__,
+      quantization,
+      is_variable);
+}
+
+flatbuffers::Offset<Tensor> CreateTensor(flatbuffers::FlatBufferBuilder &_fbb, const TensorT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct Conv2DOptionsT : public flatbuffers::NativeTable {
+  typedef Conv2DOptions TableType;
+  Padding padding;
+  int32_t stride_w;
+  int32_t stride_h;
+  ActivationFunctionType fused_activation_function;
+  int32_t dilation_w_factor;
+  int32_t dilation_h_factor;
+  Conv2DOptionsT()
+      : padding(Padding_SAME),
+        stride_w(0),
+        stride_h(0),
+        fused_activation_function(ActivationFunctionType_NONE),
+        dilation_w_factor(1),
+        dilation_h_factor(1) {
+  }
+};
+
+struct Conv2DOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef Conv2DOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_PADDING = 4,
+    VT_STRIDE_W = 6,
+    VT_STRIDE_H = 8,
+    VT_FUSED_ACTIVATION_FUNCTION = 10,
+    VT_DILATION_W_FACTOR = 12,
+    VT_DILATION_H_FACTOR = 14
+  };
+  Padding padding() const {
+    return static_cast<Padding>(GetField<int8_t>(VT_PADDING, 0));
+  }
+  int32_t stride_w() const {
+    return GetField<int32_t>(VT_STRIDE_W, 0);
+  }
+  int32_t stride_h() const {
+    return GetField<int32_t>(VT_STRIDE_H, 0);
+  }
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  int32_t dilation_w_factor() const {
+    return GetField<int32_t>(VT_DILATION_W_FACTOR, 1);
+  }
+  int32_t dilation_h_factor() const {
+    return GetField<int32_t>(VT_DILATION_H_FACTOR, 1);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_PADDING) &&
+           VerifyField<int32_t>(verifier, VT_STRIDE_W) &&
+           VerifyField<int32_t>(verifier, VT_STRIDE_H) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           VerifyField<int32_t>(verifier, VT_DILATION_W_FACTOR) &&
+           VerifyField<int32_t>(verifier, VT_DILATION_H_FACTOR) &&
+           verifier.EndTable();
+  }
+  Conv2DOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(Conv2DOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<Conv2DOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const Conv2DOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct Conv2DOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_padding(Padding padding) {
+    fbb_.AddElement<int8_t>(Conv2DOptions::VT_PADDING, static_cast<int8_t>(padding), 0);
+  }
+  void add_stride_w(int32_t stride_w) {
+    fbb_.AddElement<int32_t>(Conv2DOptions::VT_STRIDE_W, stride_w, 0);
+  }
+  void add_stride_h(int32_t stride_h) {
+    fbb_.AddElement<int32_t>(Conv2DOptions::VT_STRIDE_H, stride_h, 0);
+  }
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(Conv2DOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  void add_dilation_w_factor(int32_t dilation_w_factor) {
+    fbb_.AddElement<int32_t>(Conv2DOptions::VT_DILATION_W_FACTOR, dilation_w_factor, 1);
+  }
+  void add_dilation_h_factor(int32_t dilation_h_factor) {
+    fbb_.AddElement<int32_t>(Conv2DOptions::VT_DILATION_H_FACTOR, dilation_h_factor, 1);
+  }
+  explicit Conv2DOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  Conv2DOptionsBuilder &operator=(const Conv2DOptionsBuilder &);
+  flatbuffers::Offset<Conv2DOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<Conv2DOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<Conv2DOptions> CreateConv2DOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    Padding padding = Padding_SAME,
+    int32_t stride_w = 0,
+    int32_t stride_h = 0,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE,
+    int32_t dilation_w_factor = 1,
+    int32_t dilation_h_factor = 1) {
+  Conv2DOptionsBuilder builder_(_fbb);
+  builder_.add_dilation_h_factor(dilation_h_factor);
+  builder_.add_dilation_w_factor(dilation_w_factor);
+  builder_.add_stride_h(stride_h);
+  builder_.add_stride_w(stride_w);
+  builder_.add_fused_activation_function(fused_activation_function);
+  builder_.add_padding(padding);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<Conv2DOptions> CreateConv2DOptions(flatbuffers::FlatBufferBuilder &_fbb, const Conv2DOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct Pool2DOptionsT : public flatbuffers::NativeTable {
+  typedef Pool2DOptions TableType;
+  Padding padding;
+  int32_t stride_w;
+  int32_t stride_h;
+  int32_t filter_width;
+  int32_t filter_height;
+  ActivationFunctionType fused_activation_function;
+  Pool2DOptionsT()
+      : padding(Padding_SAME),
+        stride_w(0),
+        stride_h(0),
+        filter_width(0),
+        filter_height(0),
+        fused_activation_function(ActivationFunctionType_NONE) {
+  }
+};
+
+struct Pool2DOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef Pool2DOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_PADDING = 4,
+    VT_STRIDE_W = 6,
+    VT_STRIDE_H = 8,
+    VT_FILTER_WIDTH = 10,
+    VT_FILTER_HEIGHT = 12,
+    VT_FUSED_ACTIVATION_FUNCTION = 14
+  };
+  Padding padding() const {
+    return static_cast<Padding>(GetField<int8_t>(VT_PADDING, 0));
+  }
+  int32_t stride_w() const {
+    return GetField<int32_t>(VT_STRIDE_W, 0);
+  }
+  int32_t stride_h() const {
+    return GetField<int32_t>(VT_STRIDE_H, 0);
+  }
+  int32_t filter_width() const {
+    return GetField<int32_t>(VT_FILTER_WIDTH, 0);
+  }
+  int32_t filter_height() const {
+    return GetField<int32_t>(VT_FILTER_HEIGHT, 0);
+  }
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_PADDING) &&
+           VerifyField<int32_t>(verifier, VT_STRIDE_W) &&
+           VerifyField<int32_t>(verifier, VT_STRIDE_H) &&
+           VerifyField<int32_t>(verifier, VT_FILTER_WIDTH) &&
+           VerifyField<int32_t>(verifier, VT_FILTER_HEIGHT) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           verifier.EndTable();
+  }
+  Pool2DOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(Pool2DOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<Pool2DOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const Pool2DOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct Pool2DOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_padding(Padding padding) {
+    fbb_.AddElement<int8_t>(Pool2DOptions::VT_PADDING, static_cast<int8_t>(padding), 0);
+  }
+  void add_stride_w(int32_t stride_w) {
+    fbb_.AddElement<int32_t>(Pool2DOptions::VT_STRIDE_W, stride_w, 0);
+  }
+  void add_stride_h(int32_t stride_h) {
+    fbb_.AddElement<int32_t>(Pool2DOptions::VT_STRIDE_H, stride_h, 0);
+  }
+  void add_filter_width(int32_t filter_width) {
+    fbb_.AddElement<int32_t>(Pool2DOptions::VT_FILTER_WIDTH, filter_width, 0);
+  }
+  void add_filter_height(int32_t filter_height) {
+    fbb_.AddElement<int32_t>(Pool2DOptions::VT_FILTER_HEIGHT, filter_height, 0);
+  }
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(Pool2DOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  explicit Pool2DOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  Pool2DOptionsBuilder &operator=(const Pool2DOptionsBuilder &);
+  flatbuffers::Offset<Pool2DOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<Pool2DOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<Pool2DOptions> CreatePool2DOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    Padding padding = Padding_SAME,
+    int32_t stride_w = 0,
+    int32_t stride_h = 0,
+    int32_t filter_width = 0,
+    int32_t filter_height = 0,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE) {
+  Pool2DOptionsBuilder builder_(_fbb);
+  builder_.add_filter_height(filter_height);
+  builder_.add_filter_width(filter_width);
+  builder_.add_stride_h(stride_h);
+  builder_.add_stride_w(stride_w);
+  builder_.add_fused_activation_function(fused_activation_function);
+  builder_.add_padding(padding);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<Pool2DOptions> CreatePool2DOptions(flatbuffers::FlatBufferBuilder &_fbb, const Pool2DOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct DepthwiseConv2DOptionsT : public flatbuffers::NativeTable {
+  typedef DepthwiseConv2DOptions TableType;
+  Padding padding;
+  int32_t stride_w;
+  int32_t stride_h;
+  int32_t depth_multiplier;
+  ActivationFunctionType fused_activation_function;
+  int32_t dilation_w_factor;
+  int32_t dilation_h_factor;
+  DepthwiseConv2DOptionsT()
+      : padding(Padding_SAME),
+        stride_w(0),
+        stride_h(0),
+        depth_multiplier(0),
+        fused_activation_function(ActivationFunctionType_NONE),
+        dilation_w_factor(1),
+        dilation_h_factor(1) {
+  }
+};
+
+struct DepthwiseConv2DOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef DepthwiseConv2DOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_PADDING = 4,
+    VT_STRIDE_W = 6,
+    VT_STRIDE_H = 8,
+    VT_DEPTH_MULTIPLIER = 10,
+    VT_FUSED_ACTIVATION_FUNCTION = 12,
+    VT_DILATION_W_FACTOR = 14,
+    VT_DILATION_H_FACTOR = 16
+  };
+  Padding padding() const {
+    return static_cast<Padding>(GetField<int8_t>(VT_PADDING, 0));
+  }
+  int32_t stride_w() const {
+    return GetField<int32_t>(VT_STRIDE_W, 0);
+  }
+  int32_t stride_h() const {
+    return GetField<int32_t>(VT_STRIDE_H, 0);
+  }
+  int32_t depth_multiplier() const {
+    return GetField<int32_t>(VT_DEPTH_MULTIPLIER, 0);
+  }
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  int32_t dilation_w_factor() const {
+    return GetField<int32_t>(VT_DILATION_W_FACTOR, 1);
+  }
+  int32_t dilation_h_factor() const {
+    return GetField<int32_t>(VT_DILATION_H_FACTOR, 1);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_PADDING) &&
+           VerifyField<int32_t>(verifier, VT_STRIDE_W) &&
+           VerifyField<int32_t>(verifier, VT_STRIDE_H) &&
+           VerifyField<int32_t>(verifier, VT_DEPTH_MULTIPLIER) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           VerifyField<int32_t>(verifier, VT_DILATION_W_FACTOR) &&
+           VerifyField<int32_t>(verifier, VT_DILATION_H_FACTOR) &&
+           verifier.EndTable();
+  }
+  DepthwiseConv2DOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(DepthwiseConv2DOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<DepthwiseConv2DOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const DepthwiseConv2DOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct DepthwiseConv2DOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_padding(Padding padding) {
+    fbb_.AddElement<int8_t>(DepthwiseConv2DOptions::VT_PADDING, static_cast<int8_t>(padding), 0);
+  }
+  void add_stride_w(int32_t stride_w) {
+    fbb_.AddElement<int32_t>(DepthwiseConv2DOptions::VT_STRIDE_W, stride_w, 0);
+  }
+  void add_stride_h(int32_t stride_h) {
+    fbb_.AddElement<int32_t>(DepthwiseConv2DOptions::VT_STRIDE_H, stride_h, 0);
+  }
+  void add_depth_multiplier(int32_t depth_multiplier) {
+    fbb_.AddElement<int32_t>(DepthwiseConv2DOptions::VT_DEPTH_MULTIPLIER, depth_multiplier, 0);
+  }
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(DepthwiseConv2DOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  void add_dilation_w_factor(int32_t dilation_w_factor) {
+    fbb_.AddElement<int32_t>(DepthwiseConv2DOptions::VT_DILATION_W_FACTOR, dilation_w_factor, 1);
+  }
+  void add_dilation_h_factor(int32_t dilation_h_factor) {
+    fbb_.AddElement<int32_t>(DepthwiseConv2DOptions::VT_DILATION_H_FACTOR, dilation_h_factor, 1);
+  }
+  explicit DepthwiseConv2DOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  DepthwiseConv2DOptionsBuilder &operator=(const DepthwiseConv2DOptionsBuilder &);
+  flatbuffers::Offset<DepthwiseConv2DOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<DepthwiseConv2DOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<DepthwiseConv2DOptions> CreateDepthwiseConv2DOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    Padding padding = Padding_SAME,
+    int32_t stride_w = 0,
+    int32_t stride_h = 0,
+    int32_t depth_multiplier = 0,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE,
+    int32_t dilation_w_factor = 1,
+    int32_t dilation_h_factor = 1) {
+  DepthwiseConv2DOptionsBuilder builder_(_fbb);
+  builder_.add_dilation_h_factor(dilation_h_factor);
+  builder_.add_dilation_w_factor(dilation_w_factor);
+  builder_.add_depth_multiplier(depth_multiplier);
+  builder_.add_stride_h(stride_h);
+  builder_.add_stride_w(stride_w);
+  builder_.add_fused_activation_function(fused_activation_function);
+  builder_.add_padding(padding);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<DepthwiseConv2DOptions> CreateDepthwiseConv2DOptions(flatbuffers::FlatBufferBuilder &_fbb, const DepthwiseConv2DOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ConcatEmbeddingsOptionsT : public flatbuffers::NativeTable {
+  typedef ConcatEmbeddingsOptions TableType;
+  int32_t num_channels;
+  std::vector<int32_t> num_columns_per_channel;
+  std::vector<int32_t> embedding_dim_per_channel;
+  ConcatEmbeddingsOptionsT()
+      : num_channels(0) {
+  }
+};
+
+struct ConcatEmbeddingsOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ConcatEmbeddingsOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_NUM_CHANNELS = 4,
+    VT_NUM_COLUMNS_PER_CHANNEL = 6,
+    VT_EMBEDDING_DIM_PER_CHANNEL = 8
+  };
+  int32_t num_channels() const {
+    return GetField<int32_t>(VT_NUM_CHANNELS, 0);
+  }
+  const flatbuffers::Vector<int32_t> *num_columns_per_channel() const {
+    return GetPointer<const flatbuffers::Vector<int32_t> *>(VT_NUM_COLUMNS_PER_CHANNEL);
+  }
+  const flatbuffers::Vector<int32_t> *embedding_dim_per_channel() const {
+    return GetPointer<const flatbuffers::Vector<int32_t> *>(VT_EMBEDDING_DIM_PER_CHANNEL);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_NUM_CHANNELS) &&
+           VerifyOffset(verifier, VT_NUM_COLUMNS_PER_CHANNEL) &&
+           verifier.VerifyVector(num_columns_per_channel()) &&
+           VerifyOffset(verifier, VT_EMBEDDING_DIM_PER_CHANNEL) &&
+           verifier.VerifyVector(embedding_dim_per_channel()) &&
+           verifier.EndTable();
+  }
+  ConcatEmbeddingsOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ConcatEmbeddingsOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ConcatEmbeddingsOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ConcatEmbeddingsOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ConcatEmbeddingsOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_num_channels(int32_t num_channels) {
+    fbb_.AddElement<int32_t>(ConcatEmbeddingsOptions::VT_NUM_CHANNELS, num_channels, 0);
+  }
+  void add_num_columns_per_channel(flatbuffers::Offset<flatbuffers::Vector<int32_t>> num_columns_per_channel) {
+    fbb_.AddOffset(ConcatEmbeddingsOptions::VT_NUM_COLUMNS_PER_CHANNEL, num_columns_per_channel);
+  }
+  void add_embedding_dim_per_channel(flatbuffers::Offset<flatbuffers::Vector<int32_t>> embedding_dim_per_channel) {
+    fbb_.AddOffset(ConcatEmbeddingsOptions::VT_EMBEDDING_DIM_PER_CHANNEL, embedding_dim_per_channel);
+  }
+  explicit ConcatEmbeddingsOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ConcatEmbeddingsOptionsBuilder &operator=(const ConcatEmbeddingsOptionsBuilder &);
+  flatbuffers::Offset<ConcatEmbeddingsOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ConcatEmbeddingsOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ConcatEmbeddingsOptions> CreateConcatEmbeddingsOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t num_channels = 0,
+    flatbuffers::Offset<flatbuffers::Vector<int32_t>> num_columns_per_channel = 0,
+    flatbuffers::Offset<flatbuffers::Vector<int32_t>> embedding_dim_per_channel = 0) {
+  ConcatEmbeddingsOptionsBuilder builder_(_fbb);
+  builder_.add_embedding_dim_per_channel(embedding_dim_per_channel);
+  builder_.add_num_columns_per_channel(num_columns_per_channel);
+  builder_.add_num_channels(num_channels);
+  return builder_.Finish();
+}
+
+inline flatbuffers::Offset<ConcatEmbeddingsOptions> CreateConcatEmbeddingsOptionsDirect(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t num_channels = 0,
+    const std::vector<int32_t> *num_columns_per_channel = nullptr,
+    const std::vector<int32_t> *embedding_dim_per_channel = nullptr) {
+  auto num_columns_per_channel__ = num_columns_per_channel ? _fbb.CreateVector<int32_t>(*num_columns_per_channel) : 0;
+  auto embedding_dim_per_channel__ = embedding_dim_per_channel ? _fbb.CreateVector<int32_t>(*embedding_dim_per_channel) : 0;
+  return tflite::CreateConcatEmbeddingsOptions(
+      _fbb,
+      num_channels,
+      num_columns_per_channel__,
+      embedding_dim_per_channel__);
+}
+
+flatbuffers::Offset<ConcatEmbeddingsOptions> CreateConcatEmbeddingsOptions(flatbuffers::FlatBufferBuilder &_fbb, const ConcatEmbeddingsOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct LSHProjectionOptionsT : public flatbuffers::NativeTable {
+  typedef LSHProjectionOptions TableType;
+  LSHProjectionType type;
+  LSHProjectionOptionsT()
+      : type(LSHProjectionType_UNKNOWN) {
+  }
+};
+
+struct LSHProjectionOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef LSHProjectionOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_TYPE = 4
+  };
+  LSHProjectionType type() const {
+    return static_cast<LSHProjectionType>(GetField<int8_t>(VT_TYPE, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_TYPE) &&
+           verifier.EndTable();
+  }
+  LSHProjectionOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(LSHProjectionOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<LSHProjectionOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const LSHProjectionOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct LSHProjectionOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_type(LSHProjectionType type) {
+    fbb_.AddElement<int8_t>(LSHProjectionOptions::VT_TYPE, static_cast<int8_t>(type), 0);
+  }
+  explicit LSHProjectionOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  LSHProjectionOptionsBuilder &operator=(const LSHProjectionOptionsBuilder &);
+  flatbuffers::Offset<LSHProjectionOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<LSHProjectionOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<LSHProjectionOptions> CreateLSHProjectionOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    LSHProjectionType type = LSHProjectionType_UNKNOWN) {
+  LSHProjectionOptionsBuilder builder_(_fbb);
+  builder_.add_type(type);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<LSHProjectionOptions> CreateLSHProjectionOptions(flatbuffers::FlatBufferBuilder &_fbb, const LSHProjectionOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SVDFOptionsT : public flatbuffers::NativeTable {
+  typedef SVDFOptions TableType;
+  int32_t rank;
+  ActivationFunctionType fused_activation_function;
+  SVDFOptionsT()
+      : rank(0),
+        fused_activation_function(ActivationFunctionType_NONE) {
+  }
+};
+
+struct SVDFOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SVDFOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_RANK = 4,
+    VT_FUSED_ACTIVATION_FUNCTION = 6
+  };
+  int32_t rank() const {
+    return GetField<int32_t>(VT_RANK, 0);
+  }
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_RANK) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           verifier.EndTable();
+  }
+  SVDFOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SVDFOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SVDFOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SVDFOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SVDFOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_rank(int32_t rank) {
+    fbb_.AddElement<int32_t>(SVDFOptions::VT_RANK, rank, 0);
+  }
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(SVDFOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  explicit SVDFOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SVDFOptionsBuilder &operator=(const SVDFOptionsBuilder &);
+  flatbuffers::Offset<SVDFOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SVDFOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SVDFOptions> CreateSVDFOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t rank = 0,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE) {
+  SVDFOptionsBuilder builder_(_fbb);
+  builder_.add_rank(rank);
+  builder_.add_fused_activation_function(fused_activation_function);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SVDFOptions> CreateSVDFOptions(flatbuffers::FlatBufferBuilder &_fbb, const SVDFOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct RNNOptionsT : public flatbuffers::NativeTable {
+  typedef RNNOptions TableType;
+  ActivationFunctionType fused_activation_function;
+  RNNOptionsT()
+      : fused_activation_function(ActivationFunctionType_NONE) {
+  }
+};
+
+struct RNNOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef RNNOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_FUSED_ACTIVATION_FUNCTION = 4
+  };
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           verifier.EndTable();
+  }
+  RNNOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(RNNOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<RNNOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const RNNOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct RNNOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(RNNOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  explicit RNNOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  RNNOptionsBuilder &operator=(const RNNOptionsBuilder &);
+  flatbuffers::Offset<RNNOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<RNNOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<RNNOptions> CreateRNNOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE) {
+  RNNOptionsBuilder builder_(_fbb);
+  builder_.add_fused_activation_function(fused_activation_function);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<RNNOptions> CreateRNNOptions(flatbuffers::FlatBufferBuilder &_fbb, const RNNOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SequenceRNNOptionsT : public flatbuffers::NativeTable {
+  typedef SequenceRNNOptions TableType;
+  bool time_major;
+  ActivationFunctionType fused_activation_function;
+  SequenceRNNOptionsT()
+      : time_major(false),
+        fused_activation_function(ActivationFunctionType_NONE) {
+  }
+};
+
+struct SequenceRNNOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SequenceRNNOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_TIME_MAJOR = 4,
+    VT_FUSED_ACTIVATION_FUNCTION = 6
+  };
+  bool time_major() const {
+    return GetField<uint8_t>(VT_TIME_MAJOR, 0) != 0;
+  }
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<uint8_t>(verifier, VT_TIME_MAJOR) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           verifier.EndTable();
+  }
+  SequenceRNNOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SequenceRNNOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SequenceRNNOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SequenceRNNOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SequenceRNNOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_time_major(bool time_major) {
+    fbb_.AddElement<uint8_t>(SequenceRNNOptions::VT_TIME_MAJOR, static_cast<uint8_t>(time_major), 0);
+  }
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(SequenceRNNOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  explicit SequenceRNNOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SequenceRNNOptionsBuilder &operator=(const SequenceRNNOptionsBuilder &);
+  flatbuffers::Offset<SequenceRNNOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SequenceRNNOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SequenceRNNOptions> CreateSequenceRNNOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    bool time_major = false,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE) {
+  SequenceRNNOptionsBuilder builder_(_fbb);
+  builder_.add_fused_activation_function(fused_activation_function);
+  builder_.add_time_major(time_major);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SequenceRNNOptions> CreateSequenceRNNOptions(flatbuffers::FlatBufferBuilder &_fbb, const SequenceRNNOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct BidirectionalSequenceRNNOptionsT : public flatbuffers::NativeTable {
+  typedef BidirectionalSequenceRNNOptions TableType;
+  bool time_major;
+  ActivationFunctionType fused_activation_function;
+  bool merge_outputs;
+  BidirectionalSequenceRNNOptionsT()
+      : time_major(false),
+        fused_activation_function(ActivationFunctionType_NONE),
+        merge_outputs(false) {
+  }
+};
+
+struct BidirectionalSequenceRNNOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef BidirectionalSequenceRNNOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_TIME_MAJOR = 4,
+    VT_FUSED_ACTIVATION_FUNCTION = 6,
+    VT_MERGE_OUTPUTS = 8
+  };
+  bool time_major() const {
+    return GetField<uint8_t>(VT_TIME_MAJOR, 0) != 0;
+  }
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  bool merge_outputs() const {
+    return GetField<uint8_t>(VT_MERGE_OUTPUTS, 0) != 0;
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<uint8_t>(verifier, VT_TIME_MAJOR) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           VerifyField<uint8_t>(verifier, VT_MERGE_OUTPUTS) &&
+           verifier.EndTable();
+  }
+  BidirectionalSequenceRNNOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(BidirectionalSequenceRNNOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<BidirectionalSequenceRNNOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const BidirectionalSequenceRNNOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct BidirectionalSequenceRNNOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_time_major(bool time_major) {
+    fbb_.AddElement<uint8_t>(BidirectionalSequenceRNNOptions::VT_TIME_MAJOR, static_cast<uint8_t>(time_major), 0);
+  }
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(BidirectionalSequenceRNNOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  void add_merge_outputs(bool merge_outputs) {
+    fbb_.AddElement<uint8_t>(BidirectionalSequenceRNNOptions::VT_MERGE_OUTPUTS, static_cast<uint8_t>(merge_outputs), 0);
+  }
+  explicit BidirectionalSequenceRNNOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  BidirectionalSequenceRNNOptionsBuilder &operator=(const BidirectionalSequenceRNNOptionsBuilder &);
+  flatbuffers::Offset<BidirectionalSequenceRNNOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<BidirectionalSequenceRNNOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<BidirectionalSequenceRNNOptions> CreateBidirectionalSequenceRNNOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    bool time_major = false,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE,
+    bool merge_outputs = false) {
+  BidirectionalSequenceRNNOptionsBuilder builder_(_fbb);
+  builder_.add_merge_outputs(merge_outputs);
+  builder_.add_fused_activation_function(fused_activation_function);
+  builder_.add_time_major(time_major);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<BidirectionalSequenceRNNOptions> CreateBidirectionalSequenceRNNOptions(flatbuffers::FlatBufferBuilder &_fbb, const BidirectionalSequenceRNNOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct FullyConnectedOptionsT : public flatbuffers::NativeTable {
+  typedef FullyConnectedOptions TableType;
+  ActivationFunctionType fused_activation_function;
+  FullyConnectedOptionsWeightsFormat weights_format;
+  bool keep_num_dims;
+  FullyConnectedOptionsT()
+      : fused_activation_function(ActivationFunctionType_NONE),
+        weights_format(FullyConnectedOptionsWeightsFormat_DEFAULT),
+        keep_num_dims(false) {
+  }
+};
+
+struct FullyConnectedOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef FullyConnectedOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_FUSED_ACTIVATION_FUNCTION = 4,
+    VT_WEIGHTS_FORMAT = 6,
+    VT_KEEP_NUM_DIMS = 8
+  };
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  FullyConnectedOptionsWeightsFormat weights_format() const {
+    return static_cast<FullyConnectedOptionsWeightsFormat>(GetField<int8_t>(VT_WEIGHTS_FORMAT, 0));
+  }
+  bool keep_num_dims() const {
+    return GetField<uint8_t>(VT_KEEP_NUM_DIMS, 0) != 0;
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           VerifyField<int8_t>(verifier, VT_WEIGHTS_FORMAT) &&
+           VerifyField<uint8_t>(verifier, VT_KEEP_NUM_DIMS) &&
+           verifier.EndTable();
+  }
+  FullyConnectedOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(FullyConnectedOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<FullyConnectedOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const FullyConnectedOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct FullyConnectedOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(FullyConnectedOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  void add_weights_format(FullyConnectedOptionsWeightsFormat weights_format) {
+    fbb_.AddElement<int8_t>(FullyConnectedOptions::VT_WEIGHTS_FORMAT, static_cast<int8_t>(weights_format), 0);
+  }
+  void add_keep_num_dims(bool keep_num_dims) {
+    fbb_.AddElement<uint8_t>(FullyConnectedOptions::VT_KEEP_NUM_DIMS, static_cast<uint8_t>(keep_num_dims), 0);
+  }
+  explicit FullyConnectedOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  FullyConnectedOptionsBuilder &operator=(const FullyConnectedOptionsBuilder &);
+  flatbuffers::Offset<FullyConnectedOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<FullyConnectedOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<FullyConnectedOptions> CreateFullyConnectedOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE,
+    FullyConnectedOptionsWeightsFormat weights_format = FullyConnectedOptionsWeightsFormat_DEFAULT,
+    bool keep_num_dims = false) {
+  FullyConnectedOptionsBuilder builder_(_fbb);
+  builder_.add_keep_num_dims(keep_num_dims);
+  builder_.add_weights_format(weights_format);
+  builder_.add_fused_activation_function(fused_activation_function);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<FullyConnectedOptions> CreateFullyConnectedOptions(flatbuffers::FlatBufferBuilder &_fbb, const FullyConnectedOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SoftmaxOptionsT : public flatbuffers::NativeTable {
+  typedef SoftmaxOptions TableType;
+  float beta;
+  SoftmaxOptionsT()
+      : beta(0.0f) {
+  }
+};
+
+struct SoftmaxOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SoftmaxOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_BETA = 4
+  };
+  float beta() const {
+    return GetField<float>(VT_BETA, 0.0f);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<float>(verifier, VT_BETA) &&
+           verifier.EndTable();
+  }
+  SoftmaxOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SoftmaxOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SoftmaxOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SoftmaxOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SoftmaxOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_beta(float beta) {
+    fbb_.AddElement<float>(SoftmaxOptions::VT_BETA, beta, 0.0f);
+  }
+  explicit SoftmaxOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SoftmaxOptionsBuilder &operator=(const SoftmaxOptionsBuilder &);
+  flatbuffers::Offset<SoftmaxOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SoftmaxOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SoftmaxOptions> CreateSoftmaxOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    float beta = 0.0f) {
+  SoftmaxOptionsBuilder builder_(_fbb);
+  builder_.add_beta(beta);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SoftmaxOptions> CreateSoftmaxOptions(flatbuffers::FlatBufferBuilder &_fbb, const SoftmaxOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ConcatenationOptionsT : public flatbuffers::NativeTable {
+  typedef ConcatenationOptions TableType;
+  int32_t axis;
+  ActivationFunctionType fused_activation_function;
+  ConcatenationOptionsT()
+      : axis(0),
+        fused_activation_function(ActivationFunctionType_NONE) {
+  }
+};
+
+struct ConcatenationOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ConcatenationOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_AXIS = 4,
+    VT_FUSED_ACTIVATION_FUNCTION = 6
+  };
+  int32_t axis() const {
+    return GetField<int32_t>(VT_AXIS, 0);
+  }
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_AXIS) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           verifier.EndTable();
+  }
+  ConcatenationOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ConcatenationOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ConcatenationOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ConcatenationOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ConcatenationOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_axis(int32_t axis) {
+    fbb_.AddElement<int32_t>(ConcatenationOptions::VT_AXIS, axis, 0);
+  }
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(ConcatenationOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  explicit ConcatenationOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ConcatenationOptionsBuilder &operator=(const ConcatenationOptionsBuilder &);
+  flatbuffers::Offset<ConcatenationOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ConcatenationOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ConcatenationOptions> CreateConcatenationOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t axis = 0,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE) {
+  ConcatenationOptionsBuilder builder_(_fbb);
+  builder_.add_axis(axis);
+  builder_.add_fused_activation_function(fused_activation_function);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<ConcatenationOptions> CreateConcatenationOptions(flatbuffers::FlatBufferBuilder &_fbb, const ConcatenationOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct AddOptionsT : public flatbuffers::NativeTable {
+  typedef AddOptions TableType;
+  ActivationFunctionType fused_activation_function;
+  AddOptionsT()
+      : fused_activation_function(ActivationFunctionType_NONE) {
+  }
+};
+
+struct AddOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef AddOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_FUSED_ACTIVATION_FUNCTION = 4
+  };
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           verifier.EndTable();
+  }
+  AddOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(AddOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<AddOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const AddOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct AddOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(AddOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  explicit AddOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  AddOptionsBuilder &operator=(const AddOptionsBuilder &);
+  flatbuffers::Offset<AddOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<AddOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<AddOptions> CreateAddOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE) {
+  AddOptionsBuilder builder_(_fbb);
+  builder_.add_fused_activation_function(fused_activation_function);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<AddOptions> CreateAddOptions(flatbuffers::FlatBufferBuilder &_fbb, const AddOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct MulOptionsT : public flatbuffers::NativeTable {
+  typedef MulOptions TableType;
+  ActivationFunctionType fused_activation_function;
+  MulOptionsT()
+      : fused_activation_function(ActivationFunctionType_NONE) {
+  }
+};
+
+struct MulOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef MulOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_FUSED_ACTIVATION_FUNCTION = 4
+  };
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           verifier.EndTable();
+  }
+  MulOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(MulOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<MulOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const MulOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct MulOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(MulOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  explicit MulOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  MulOptionsBuilder &operator=(const MulOptionsBuilder &);
+  flatbuffers::Offset<MulOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<MulOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<MulOptions> CreateMulOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE) {
+  MulOptionsBuilder builder_(_fbb);
+  builder_.add_fused_activation_function(fused_activation_function);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<MulOptions> CreateMulOptions(flatbuffers::FlatBufferBuilder &_fbb, const MulOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct L2NormOptionsT : public flatbuffers::NativeTable {
+  typedef L2NormOptions TableType;
+  ActivationFunctionType fused_activation_function;
+  L2NormOptionsT()
+      : fused_activation_function(ActivationFunctionType_NONE) {
+  }
+};
+
+struct L2NormOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef L2NormOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_FUSED_ACTIVATION_FUNCTION = 4
+  };
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           verifier.EndTable();
+  }
+  L2NormOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(L2NormOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<L2NormOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const L2NormOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct L2NormOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(L2NormOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  explicit L2NormOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  L2NormOptionsBuilder &operator=(const L2NormOptionsBuilder &);
+  flatbuffers::Offset<L2NormOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<L2NormOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<L2NormOptions> CreateL2NormOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE) {
+  L2NormOptionsBuilder builder_(_fbb);
+  builder_.add_fused_activation_function(fused_activation_function);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<L2NormOptions> CreateL2NormOptions(flatbuffers::FlatBufferBuilder &_fbb, const L2NormOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct LocalResponseNormalizationOptionsT : public flatbuffers::NativeTable {
+  typedef LocalResponseNormalizationOptions TableType;
+  int32_t radius;
+  float bias;
+  float alpha;
+  float beta;
+  LocalResponseNormalizationOptionsT()
+      : radius(0),
+        bias(0.0f),
+        alpha(0.0f),
+        beta(0.0f) {
+  }
+};
+
+struct LocalResponseNormalizationOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef LocalResponseNormalizationOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_RADIUS = 4,
+    VT_BIAS = 6,
+    VT_ALPHA = 8,
+    VT_BETA = 10
+  };
+  int32_t radius() const {
+    return GetField<int32_t>(VT_RADIUS, 0);
+  }
+  float bias() const {
+    return GetField<float>(VT_BIAS, 0.0f);
+  }
+  float alpha() const {
+    return GetField<float>(VT_ALPHA, 0.0f);
+  }
+  float beta() const {
+    return GetField<float>(VT_BETA, 0.0f);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_RADIUS) &&
+           VerifyField<float>(verifier, VT_BIAS) &&
+           VerifyField<float>(verifier, VT_ALPHA) &&
+           VerifyField<float>(verifier, VT_BETA) &&
+           verifier.EndTable();
+  }
+  LocalResponseNormalizationOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(LocalResponseNormalizationOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<LocalResponseNormalizationOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const LocalResponseNormalizationOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct LocalResponseNormalizationOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_radius(int32_t radius) {
+    fbb_.AddElement<int32_t>(LocalResponseNormalizationOptions::VT_RADIUS, radius, 0);
+  }
+  void add_bias(float bias) {
+    fbb_.AddElement<float>(LocalResponseNormalizationOptions::VT_BIAS, bias, 0.0f);
+  }
+  void add_alpha(float alpha) {
+    fbb_.AddElement<float>(LocalResponseNormalizationOptions::VT_ALPHA, alpha, 0.0f);
+  }
+  void add_beta(float beta) {
+    fbb_.AddElement<float>(LocalResponseNormalizationOptions::VT_BETA, beta, 0.0f);
+  }
+  explicit LocalResponseNormalizationOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  LocalResponseNormalizationOptionsBuilder &operator=(const LocalResponseNormalizationOptionsBuilder &);
+  flatbuffers::Offset<LocalResponseNormalizationOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<LocalResponseNormalizationOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<LocalResponseNormalizationOptions> CreateLocalResponseNormalizationOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t radius = 0,
+    float bias = 0.0f,
+    float alpha = 0.0f,
+    float beta = 0.0f) {
+  LocalResponseNormalizationOptionsBuilder builder_(_fbb);
+  builder_.add_beta(beta);
+  builder_.add_alpha(alpha);
+  builder_.add_bias(bias);
+  builder_.add_radius(radius);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<LocalResponseNormalizationOptions> CreateLocalResponseNormalizationOptions(flatbuffers::FlatBufferBuilder &_fbb, const LocalResponseNormalizationOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct LSTMOptionsT : public flatbuffers::NativeTable {
+  typedef LSTMOptions TableType;
+  ActivationFunctionType fused_activation_function;
+  float cell_clip;
+  float proj_clip;
+  LSTMKernelType kernel_type;
+  LSTMOptionsT()
+      : fused_activation_function(ActivationFunctionType_NONE),
+        cell_clip(0.0f),
+        proj_clip(0.0f),
+        kernel_type(LSTMKernelType_FULL) {
+  }
+};
+
+struct LSTMOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef LSTMOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_FUSED_ACTIVATION_FUNCTION = 4,
+    VT_CELL_CLIP = 6,
+    VT_PROJ_CLIP = 8,
+    VT_KERNEL_TYPE = 10
+  };
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  float cell_clip() const {
+    return GetField<float>(VT_CELL_CLIP, 0.0f);
+  }
+  float proj_clip() const {
+    return GetField<float>(VT_PROJ_CLIP, 0.0f);
+  }
+  LSTMKernelType kernel_type() const {
+    return static_cast<LSTMKernelType>(GetField<int8_t>(VT_KERNEL_TYPE, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           VerifyField<float>(verifier, VT_CELL_CLIP) &&
+           VerifyField<float>(verifier, VT_PROJ_CLIP) &&
+           VerifyField<int8_t>(verifier, VT_KERNEL_TYPE) &&
+           verifier.EndTable();
+  }
+  LSTMOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(LSTMOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<LSTMOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const LSTMOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct LSTMOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(LSTMOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  void add_cell_clip(float cell_clip) {
+    fbb_.AddElement<float>(LSTMOptions::VT_CELL_CLIP, cell_clip, 0.0f);
+  }
+  void add_proj_clip(float proj_clip) {
+    fbb_.AddElement<float>(LSTMOptions::VT_PROJ_CLIP, proj_clip, 0.0f);
+  }
+  void add_kernel_type(LSTMKernelType kernel_type) {
+    fbb_.AddElement<int8_t>(LSTMOptions::VT_KERNEL_TYPE, static_cast<int8_t>(kernel_type), 0);
+  }
+  explicit LSTMOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  LSTMOptionsBuilder &operator=(const LSTMOptionsBuilder &);
+  flatbuffers::Offset<LSTMOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<LSTMOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<LSTMOptions> CreateLSTMOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE,
+    float cell_clip = 0.0f,
+    float proj_clip = 0.0f,
+    LSTMKernelType kernel_type = LSTMKernelType_FULL) {
+  LSTMOptionsBuilder builder_(_fbb);
+  builder_.add_proj_clip(proj_clip);
+  builder_.add_cell_clip(cell_clip);
+  builder_.add_kernel_type(kernel_type);
+  builder_.add_fused_activation_function(fused_activation_function);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<LSTMOptions> CreateLSTMOptions(flatbuffers::FlatBufferBuilder &_fbb, const LSTMOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct UnidirectionalSequenceLSTMOptionsT : public flatbuffers::NativeTable {
+  typedef UnidirectionalSequenceLSTMOptions TableType;
+  ActivationFunctionType fused_activation_function;
+  float cell_clip;
+  float proj_clip;
+  bool time_major;
+  UnidirectionalSequenceLSTMOptionsT()
+      : fused_activation_function(ActivationFunctionType_NONE),
+        cell_clip(0.0f),
+        proj_clip(0.0f),
+        time_major(false) {
+  }
+};
+
+struct UnidirectionalSequenceLSTMOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef UnidirectionalSequenceLSTMOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_FUSED_ACTIVATION_FUNCTION = 4,
+    VT_CELL_CLIP = 6,
+    VT_PROJ_CLIP = 8,
+    VT_TIME_MAJOR = 10
+  };
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  float cell_clip() const {
+    return GetField<float>(VT_CELL_CLIP, 0.0f);
+  }
+  float proj_clip() const {
+    return GetField<float>(VT_PROJ_CLIP, 0.0f);
+  }
+  bool time_major() const {
+    return GetField<uint8_t>(VT_TIME_MAJOR, 0) != 0;
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           VerifyField<float>(verifier, VT_CELL_CLIP) &&
+           VerifyField<float>(verifier, VT_PROJ_CLIP) &&
+           VerifyField<uint8_t>(verifier, VT_TIME_MAJOR) &&
+           verifier.EndTable();
+  }
+  UnidirectionalSequenceLSTMOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(UnidirectionalSequenceLSTMOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<UnidirectionalSequenceLSTMOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const UnidirectionalSequenceLSTMOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct UnidirectionalSequenceLSTMOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(UnidirectionalSequenceLSTMOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  void add_cell_clip(float cell_clip) {
+    fbb_.AddElement<float>(UnidirectionalSequenceLSTMOptions::VT_CELL_CLIP, cell_clip, 0.0f);
+  }
+  void add_proj_clip(float proj_clip) {
+    fbb_.AddElement<float>(UnidirectionalSequenceLSTMOptions::VT_PROJ_CLIP, proj_clip, 0.0f);
+  }
+  void add_time_major(bool time_major) {
+    fbb_.AddElement<uint8_t>(UnidirectionalSequenceLSTMOptions::VT_TIME_MAJOR, static_cast<uint8_t>(time_major), 0);
+  }
+  explicit UnidirectionalSequenceLSTMOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  UnidirectionalSequenceLSTMOptionsBuilder &operator=(const UnidirectionalSequenceLSTMOptionsBuilder &);
+  flatbuffers::Offset<UnidirectionalSequenceLSTMOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<UnidirectionalSequenceLSTMOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<UnidirectionalSequenceLSTMOptions> CreateUnidirectionalSequenceLSTMOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE,
+    float cell_clip = 0.0f,
+    float proj_clip = 0.0f,
+    bool time_major = false) {
+  UnidirectionalSequenceLSTMOptionsBuilder builder_(_fbb);
+  builder_.add_proj_clip(proj_clip);
+  builder_.add_cell_clip(cell_clip);
+  builder_.add_time_major(time_major);
+  builder_.add_fused_activation_function(fused_activation_function);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<UnidirectionalSequenceLSTMOptions> CreateUnidirectionalSequenceLSTMOptions(flatbuffers::FlatBufferBuilder &_fbb, const UnidirectionalSequenceLSTMOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct BidirectionalSequenceLSTMOptionsT : public flatbuffers::NativeTable {
+  typedef BidirectionalSequenceLSTMOptions TableType;
+  ActivationFunctionType fused_activation_function;
+  float cell_clip;
+  float proj_clip;
+  bool merge_outputs;
+  bool time_major;
+  BidirectionalSequenceLSTMOptionsT()
+      : fused_activation_function(ActivationFunctionType_NONE),
+        cell_clip(0.0f),
+        proj_clip(0.0f),
+        merge_outputs(false),
+        time_major(true) {
+  }
+};
+
+struct BidirectionalSequenceLSTMOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef BidirectionalSequenceLSTMOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_FUSED_ACTIVATION_FUNCTION = 4,
+    VT_CELL_CLIP = 6,
+    VT_PROJ_CLIP = 8,
+    VT_MERGE_OUTPUTS = 10,
+    VT_TIME_MAJOR = 12
+  };
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  float cell_clip() const {
+    return GetField<float>(VT_CELL_CLIP, 0.0f);
+  }
+  float proj_clip() const {
+    return GetField<float>(VT_PROJ_CLIP, 0.0f);
+  }
+  bool merge_outputs() const {
+    return GetField<uint8_t>(VT_MERGE_OUTPUTS, 0) != 0;
+  }
+  bool time_major() const {
+    return GetField<uint8_t>(VT_TIME_MAJOR, 1) != 0;
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           VerifyField<float>(verifier, VT_CELL_CLIP) &&
+           VerifyField<float>(verifier, VT_PROJ_CLIP) &&
+           VerifyField<uint8_t>(verifier, VT_MERGE_OUTPUTS) &&
+           VerifyField<uint8_t>(verifier, VT_TIME_MAJOR) &&
+           verifier.EndTable();
+  }
+  BidirectionalSequenceLSTMOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(BidirectionalSequenceLSTMOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<BidirectionalSequenceLSTMOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const BidirectionalSequenceLSTMOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct BidirectionalSequenceLSTMOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(BidirectionalSequenceLSTMOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  void add_cell_clip(float cell_clip) {
+    fbb_.AddElement<float>(BidirectionalSequenceLSTMOptions::VT_CELL_CLIP, cell_clip, 0.0f);
+  }
+  void add_proj_clip(float proj_clip) {
+    fbb_.AddElement<float>(BidirectionalSequenceLSTMOptions::VT_PROJ_CLIP, proj_clip, 0.0f);
+  }
+  void add_merge_outputs(bool merge_outputs) {
+    fbb_.AddElement<uint8_t>(BidirectionalSequenceLSTMOptions::VT_MERGE_OUTPUTS, static_cast<uint8_t>(merge_outputs), 0);
+  }
+  void add_time_major(bool time_major) {
+    fbb_.AddElement<uint8_t>(BidirectionalSequenceLSTMOptions::VT_TIME_MAJOR, static_cast<uint8_t>(time_major), 1);
+  }
+  explicit BidirectionalSequenceLSTMOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  BidirectionalSequenceLSTMOptionsBuilder &operator=(const BidirectionalSequenceLSTMOptionsBuilder &);
+  flatbuffers::Offset<BidirectionalSequenceLSTMOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<BidirectionalSequenceLSTMOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<BidirectionalSequenceLSTMOptions> CreateBidirectionalSequenceLSTMOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE,
+    float cell_clip = 0.0f,
+    float proj_clip = 0.0f,
+    bool merge_outputs = false,
+    bool time_major = true) {
+  BidirectionalSequenceLSTMOptionsBuilder builder_(_fbb);
+  builder_.add_proj_clip(proj_clip);
+  builder_.add_cell_clip(cell_clip);
+  builder_.add_time_major(time_major);
+  builder_.add_merge_outputs(merge_outputs);
+  builder_.add_fused_activation_function(fused_activation_function);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<BidirectionalSequenceLSTMOptions> CreateBidirectionalSequenceLSTMOptions(flatbuffers::FlatBufferBuilder &_fbb, const BidirectionalSequenceLSTMOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ResizeBilinearOptionsT : public flatbuffers::NativeTable {
+  typedef ResizeBilinearOptions TableType;
+  bool align_corners;
+  ResizeBilinearOptionsT()
+      : align_corners(false) {
+  }
+};
+
+struct ResizeBilinearOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ResizeBilinearOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_ALIGN_CORNERS = 8
+  };
+  bool align_corners() const {
+    return GetField<uint8_t>(VT_ALIGN_CORNERS, 0) != 0;
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<uint8_t>(verifier, VT_ALIGN_CORNERS) &&
+           verifier.EndTable();
+  }
+  ResizeBilinearOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ResizeBilinearOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ResizeBilinearOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ResizeBilinearOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ResizeBilinearOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_align_corners(bool align_corners) {
+    fbb_.AddElement<uint8_t>(ResizeBilinearOptions::VT_ALIGN_CORNERS, static_cast<uint8_t>(align_corners), 0);
+  }
+  explicit ResizeBilinearOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ResizeBilinearOptionsBuilder &operator=(const ResizeBilinearOptionsBuilder &);
+  flatbuffers::Offset<ResizeBilinearOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ResizeBilinearOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ResizeBilinearOptions> CreateResizeBilinearOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    bool align_corners = false) {
+  ResizeBilinearOptionsBuilder builder_(_fbb);
+  builder_.add_align_corners(align_corners);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<ResizeBilinearOptions> CreateResizeBilinearOptions(flatbuffers::FlatBufferBuilder &_fbb, const ResizeBilinearOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ResizeNearestNeighborOptionsT : public flatbuffers::NativeTable {
+  typedef ResizeNearestNeighborOptions TableType;
+  bool align_corners;
+  ResizeNearestNeighborOptionsT()
+      : align_corners(false) {
+  }
+};
+
+struct ResizeNearestNeighborOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ResizeNearestNeighborOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_ALIGN_CORNERS = 4
+  };
+  bool align_corners() const {
+    return GetField<uint8_t>(VT_ALIGN_CORNERS, 0) != 0;
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<uint8_t>(verifier, VT_ALIGN_CORNERS) &&
+           verifier.EndTable();
+  }
+  ResizeNearestNeighborOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ResizeNearestNeighborOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ResizeNearestNeighborOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ResizeNearestNeighborOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ResizeNearestNeighborOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_align_corners(bool align_corners) {
+    fbb_.AddElement<uint8_t>(ResizeNearestNeighborOptions::VT_ALIGN_CORNERS, static_cast<uint8_t>(align_corners), 0);
+  }
+  explicit ResizeNearestNeighborOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ResizeNearestNeighborOptionsBuilder &operator=(const ResizeNearestNeighborOptionsBuilder &);
+  flatbuffers::Offset<ResizeNearestNeighborOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ResizeNearestNeighborOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ResizeNearestNeighborOptions> CreateResizeNearestNeighborOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    bool align_corners = false) {
+  ResizeNearestNeighborOptionsBuilder builder_(_fbb);
+  builder_.add_align_corners(align_corners);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<ResizeNearestNeighborOptions> CreateResizeNearestNeighborOptions(flatbuffers::FlatBufferBuilder &_fbb, const ResizeNearestNeighborOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct CallOptionsT : public flatbuffers::NativeTable {
+  typedef CallOptions TableType;
+  uint32_t subgraph;
+  CallOptionsT()
+      : subgraph(0) {
+  }
+};
+
+struct CallOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef CallOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_SUBGRAPH = 4
+  };
+  uint32_t subgraph() const {
+    return GetField<uint32_t>(VT_SUBGRAPH, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<uint32_t>(verifier, VT_SUBGRAPH) &&
+           verifier.EndTable();
+  }
+  CallOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(CallOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<CallOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const CallOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct CallOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_subgraph(uint32_t subgraph) {
+    fbb_.AddElement<uint32_t>(CallOptions::VT_SUBGRAPH, subgraph, 0);
+  }
+  explicit CallOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  CallOptionsBuilder &operator=(const CallOptionsBuilder &);
+  flatbuffers::Offset<CallOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<CallOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<CallOptions> CreateCallOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    uint32_t subgraph = 0) {
+  CallOptionsBuilder builder_(_fbb);
+  builder_.add_subgraph(subgraph);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<CallOptions> CreateCallOptions(flatbuffers::FlatBufferBuilder &_fbb, const CallOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct PadOptionsT : public flatbuffers::NativeTable {
+  typedef PadOptions TableType;
+  PadOptionsT() {
+  }
+};
+
+struct PadOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef PadOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  PadOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(PadOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<PadOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const PadOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct PadOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit PadOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  PadOptionsBuilder &operator=(const PadOptionsBuilder &);
+  flatbuffers::Offset<PadOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<PadOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<PadOptions> CreatePadOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  PadOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<PadOptions> CreatePadOptions(flatbuffers::FlatBufferBuilder &_fbb, const PadOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct PadV2OptionsT : public flatbuffers::NativeTable {
+  typedef PadV2Options TableType;
+  PadV2OptionsT() {
+  }
+};
+
+struct PadV2Options FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef PadV2OptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  PadV2OptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(PadV2OptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<PadV2Options> Pack(flatbuffers::FlatBufferBuilder &_fbb, const PadV2OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct PadV2OptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit PadV2OptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  PadV2OptionsBuilder &operator=(const PadV2OptionsBuilder &);
+  flatbuffers::Offset<PadV2Options> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<PadV2Options>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<PadV2Options> CreatePadV2Options(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  PadV2OptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<PadV2Options> CreatePadV2Options(flatbuffers::FlatBufferBuilder &_fbb, const PadV2OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ReshapeOptionsT : public flatbuffers::NativeTable {
+  typedef ReshapeOptions TableType;
+  std::vector<int32_t> new_shape;
+  ReshapeOptionsT() {
+  }
+};
+
+struct ReshapeOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ReshapeOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_NEW_SHAPE = 4
+  };
+  const flatbuffers::Vector<int32_t> *new_shape() const {
+    return GetPointer<const flatbuffers::Vector<int32_t> *>(VT_NEW_SHAPE);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyOffset(verifier, VT_NEW_SHAPE) &&
+           verifier.VerifyVector(new_shape()) &&
+           verifier.EndTable();
+  }
+  ReshapeOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ReshapeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ReshapeOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ReshapeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ReshapeOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_new_shape(flatbuffers::Offset<flatbuffers::Vector<int32_t>> new_shape) {
+    fbb_.AddOffset(ReshapeOptions::VT_NEW_SHAPE, new_shape);
+  }
+  explicit ReshapeOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ReshapeOptionsBuilder &operator=(const ReshapeOptionsBuilder &);
+  flatbuffers::Offset<ReshapeOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ReshapeOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ReshapeOptions> CreateReshapeOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    flatbuffers::Offset<flatbuffers::Vector<int32_t>> new_shape = 0) {
+  ReshapeOptionsBuilder builder_(_fbb);
+  builder_.add_new_shape(new_shape);
+  return builder_.Finish();
+}
+
+inline flatbuffers::Offset<ReshapeOptions> CreateReshapeOptionsDirect(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    const std::vector<int32_t> *new_shape = nullptr) {
+  auto new_shape__ = new_shape ? _fbb.CreateVector<int32_t>(*new_shape) : 0;
+  return tflite::CreateReshapeOptions(
+      _fbb,
+      new_shape__);
+}
+
+flatbuffers::Offset<ReshapeOptions> CreateReshapeOptions(flatbuffers::FlatBufferBuilder &_fbb, const ReshapeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SpaceToBatchNDOptionsT : public flatbuffers::NativeTable {
+  typedef SpaceToBatchNDOptions TableType;
+  SpaceToBatchNDOptionsT() {
+  }
+};
+
+struct SpaceToBatchNDOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SpaceToBatchNDOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  SpaceToBatchNDOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SpaceToBatchNDOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SpaceToBatchNDOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SpaceToBatchNDOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SpaceToBatchNDOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit SpaceToBatchNDOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SpaceToBatchNDOptionsBuilder &operator=(const SpaceToBatchNDOptionsBuilder &);
+  flatbuffers::Offset<SpaceToBatchNDOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SpaceToBatchNDOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SpaceToBatchNDOptions> CreateSpaceToBatchNDOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  SpaceToBatchNDOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SpaceToBatchNDOptions> CreateSpaceToBatchNDOptions(flatbuffers::FlatBufferBuilder &_fbb, const SpaceToBatchNDOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct BatchToSpaceNDOptionsT : public flatbuffers::NativeTable {
+  typedef BatchToSpaceNDOptions TableType;
+  BatchToSpaceNDOptionsT() {
+  }
+};
+
+struct BatchToSpaceNDOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef BatchToSpaceNDOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  BatchToSpaceNDOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(BatchToSpaceNDOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<BatchToSpaceNDOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const BatchToSpaceNDOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct BatchToSpaceNDOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit BatchToSpaceNDOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  BatchToSpaceNDOptionsBuilder &operator=(const BatchToSpaceNDOptionsBuilder &);
+  flatbuffers::Offset<BatchToSpaceNDOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<BatchToSpaceNDOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<BatchToSpaceNDOptions> CreateBatchToSpaceNDOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  BatchToSpaceNDOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<BatchToSpaceNDOptions> CreateBatchToSpaceNDOptions(flatbuffers::FlatBufferBuilder &_fbb, const BatchToSpaceNDOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SkipGramOptionsT : public flatbuffers::NativeTable {
+  typedef SkipGramOptions TableType;
+  int32_t ngram_size;
+  int32_t max_skip_size;
+  bool include_all_ngrams;
+  SkipGramOptionsT()
+      : ngram_size(0),
+        max_skip_size(0),
+        include_all_ngrams(false) {
+  }
+};
+
+struct SkipGramOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SkipGramOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_NGRAM_SIZE = 4,
+    VT_MAX_SKIP_SIZE = 6,
+    VT_INCLUDE_ALL_NGRAMS = 8
+  };
+  int32_t ngram_size() const {
+    return GetField<int32_t>(VT_NGRAM_SIZE, 0);
+  }
+  int32_t max_skip_size() const {
+    return GetField<int32_t>(VT_MAX_SKIP_SIZE, 0);
+  }
+  bool include_all_ngrams() const {
+    return GetField<uint8_t>(VT_INCLUDE_ALL_NGRAMS, 0) != 0;
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_NGRAM_SIZE) &&
+           VerifyField<int32_t>(verifier, VT_MAX_SKIP_SIZE) &&
+           VerifyField<uint8_t>(verifier, VT_INCLUDE_ALL_NGRAMS) &&
+           verifier.EndTable();
+  }
+  SkipGramOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SkipGramOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SkipGramOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SkipGramOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SkipGramOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_ngram_size(int32_t ngram_size) {
+    fbb_.AddElement<int32_t>(SkipGramOptions::VT_NGRAM_SIZE, ngram_size, 0);
+  }
+  void add_max_skip_size(int32_t max_skip_size) {
+    fbb_.AddElement<int32_t>(SkipGramOptions::VT_MAX_SKIP_SIZE, max_skip_size, 0);
+  }
+  void add_include_all_ngrams(bool include_all_ngrams) {
+    fbb_.AddElement<uint8_t>(SkipGramOptions::VT_INCLUDE_ALL_NGRAMS, static_cast<uint8_t>(include_all_ngrams), 0);
+  }
+  explicit SkipGramOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SkipGramOptionsBuilder &operator=(const SkipGramOptionsBuilder &);
+  flatbuffers::Offset<SkipGramOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SkipGramOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SkipGramOptions> CreateSkipGramOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t ngram_size = 0,
+    int32_t max_skip_size = 0,
+    bool include_all_ngrams = false) {
+  SkipGramOptionsBuilder builder_(_fbb);
+  builder_.add_max_skip_size(max_skip_size);
+  builder_.add_ngram_size(ngram_size);
+  builder_.add_include_all_ngrams(include_all_ngrams);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SkipGramOptions> CreateSkipGramOptions(flatbuffers::FlatBufferBuilder &_fbb, const SkipGramOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SpaceToDepthOptionsT : public flatbuffers::NativeTable {
+  typedef SpaceToDepthOptions TableType;
+  int32_t block_size;
+  SpaceToDepthOptionsT()
+      : block_size(0) {
+  }
+};
+
+struct SpaceToDepthOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SpaceToDepthOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_BLOCK_SIZE = 4
+  };
+  int32_t block_size() const {
+    return GetField<int32_t>(VT_BLOCK_SIZE, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_BLOCK_SIZE) &&
+           verifier.EndTable();
+  }
+  SpaceToDepthOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SpaceToDepthOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SpaceToDepthOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SpaceToDepthOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SpaceToDepthOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_block_size(int32_t block_size) {
+    fbb_.AddElement<int32_t>(SpaceToDepthOptions::VT_BLOCK_SIZE, block_size, 0);
+  }
+  explicit SpaceToDepthOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SpaceToDepthOptionsBuilder &operator=(const SpaceToDepthOptionsBuilder &);
+  flatbuffers::Offset<SpaceToDepthOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SpaceToDepthOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SpaceToDepthOptions> CreateSpaceToDepthOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t block_size = 0) {
+  SpaceToDepthOptionsBuilder builder_(_fbb);
+  builder_.add_block_size(block_size);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SpaceToDepthOptions> CreateSpaceToDepthOptions(flatbuffers::FlatBufferBuilder &_fbb, const SpaceToDepthOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct DepthToSpaceOptionsT : public flatbuffers::NativeTable {
+  typedef DepthToSpaceOptions TableType;
+  int32_t block_size;
+  DepthToSpaceOptionsT()
+      : block_size(0) {
+  }
+};
+
+struct DepthToSpaceOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef DepthToSpaceOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_BLOCK_SIZE = 4
+  };
+  int32_t block_size() const {
+    return GetField<int32_t>(VT_BLOCK_SIZE, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_BLOCK_SIZE) &&
+           verifier.EndTable();
+  }
+  DepthToSpaceOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(DepthToSpaceOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<DepthToSpaceOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const DepthToSpaceOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct DepthToSpaceOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_block_size(int32_t block_size) {
+    fbb_.AddElement<int32_t>(DepthToSpaceOptions::VT_BLOCK_SIZE, block_size, 0);
+  }
+  explicit DepthToSpaceOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  DepthToSpaceOptionsBuilder &operator=(const DepthToSpaceOptionsBuilder &);
+  flatbuffers::Offset<DepthToSpaceOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<DepthToSpaceOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<DepthToSpaceOptions> CreateDepthToSpaceOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t block_size = 0) {
+  DepthToSpaceOptionsBuilder builder_(_fbb);
+  builder_.add_block_size(block_size);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<DepthToSpaceOptions> CreateDepthToSpaceOptions(flatbuffers::FlatBufferBuilder &_fbb, const DepthToSpaceOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SubOptionsT : public flatbuffers::NativeTable {
+  typedef SubOptions TableType;
+  ActivationFunctionType fused_activation_function;
+  SubOptionsT()
+      : fused_activation_function(ActivationFunctionType_NONE) {
+  }
+};
+
+struct SubOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SubOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_FUSED_ACTIVATION_FUNCTION = 4
+  };
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           verifier.EndTable();
+  }
+  SubOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SubOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SubOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SubOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SubOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(SubOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  explicit SubOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SubOptionsBuilder &operator=(const SubOptionsBuilder &);
+  flatbuffers::Offset<SubOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SubOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SubOptions> CreateSubOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE) {
+  SubOptionsBuilder builder_(_fbb);
+  builder_.add_fused_activation_function(fused_activation_function);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SubOptions> CreateSubOptions(flatbuffers::FlatBufferBuilder &_fbb, const SubOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct DivOptionsT : public flatbuffers::NativeTable {
+  typedef DivOptions TableType;
+  ActivationFunctionType fused_activation_function;
+  DivOptionsT()
+      : fused_activation_function(ActivationFunctionType_NONE) {
+  }
+};
+
+struct DivOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef DivOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_FUSED_ACTIVATION_FUNCTION = 4
+  };
+  ActivationFunctionType fused_activation_function() const {
+    return static_cast<ActivationFunctionType>(GetField<int8_t>(VT_FUSED_ACTIVATION_FUNCTION, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_FUSED_ACTIVATION_FUNCTION) &&
+           verifier.EndTable();
+  }
+  DivOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(DivOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<DivOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const DivOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct DivOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_fused_activation_function(ActivationFunctionType fused_activation_function) {
+    fbb_.AddElement<int8_t>(DivOptions::VT_FUSED_ACTIVATION_FUNCTION, static_cast<int8_t>(fused_activation_function), 0);
+  }
+  explicit DivOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  DivOptionsBuilder &operator=(const DivOptionsBuilder &);
+  flatbuffers::Offset<DivOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<DivOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<DivOptions> CreateDivOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    ActivationFunctionType fused_activation_function = ActivationFunctionType_NONE) {
+  DivOptionsBuilder builder_(_fbb);
+  builder_.add_fused_activation_function(fused_activation_function);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<DivOptions> CreateDivOptions(flatbuffers::FlatBufferBuilder &_fbb, const DivOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct TopKV2OptionsT : public flatbuffers::NativeTable {
+  typedef TopKV2Options TableType;
+  TopKV2OptionsT() {
+  }
+};
+
+struct TopKV2Options FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef TopKV2OptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  TopKV2OptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(TopKV2OptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<TopKV2Options> Pack(flatbuffers::FlatBufferBuilder &_fbb, const TopKV2OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct TopKV2OptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit TopKV2OptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  TopKV2OptionsBuilder &operator=(const TopKV2OptionsBuilder &);
+  flatbuffers::Offset<TopKV2Options> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<TopKV2Options>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<TopKV2Options> CreateTopKV2Options(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  TopKV2OptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<TopKV2Options> CreateTopKV2Options(flatbuffers::FlatBufferBuilder &_fbb, const TopKV2OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct EmbeddingLookupSparseOptionsT : public flatbuffers::NativeTable {
+  typedef EmbeddingLookupSparseOptions TableType;
+  CombinerType combiner;
+  EmbeddingLookupSparseOptionsT()
+      : combiner(CombinerType_SUM) {
+  }
+};
+
+struct EmbeddingLookupSparseOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef EmbeddingLookupSparseOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_COMBINER = 4
+  };
+  CombinerType combiner() const {
+    return static_cast<CombinerType>(GetField<int8_t>(VT_COMBINER, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_COMBINER) &&
+           verifier.EndTable();
+  }
+  EmbeddingLookupSparseOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(EmbeddingLookupSparseOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<EmbeddingLookupSparseOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const EmbeddingLookupSparseOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct EmbeddingLookupSparseOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_combiner(CombinerType combiner) {
+    fbb_.AddElement<int8_t>(EmbeddingLookupSparseOptions::VT_COMBINER, static_cast<int8_t>(combiner), 0);
+  }
+  explicit EmbeddingLookupSparseOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  EmbeddingLookupSparseOptionsBuilder &operator=(const EmbeddingLookupSparseOptionsBuilder &);
+  flatbuffers::Offset<EmbeddingLookupSparseOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<EmbeddingLookupSparseOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<EmbeddingLookupSparseOptions> CreateEmbeddingLookupSparseOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    CombinerType combiner = CombinerType_SUM) {
+  EmbeddingLookupSparseOptionsBuilder builder_(_fbb);
+  builder_.add_combiner(combiner);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<EmbeddingLookupSparseOptions> CreateEmbeddingLookupSparseOptions(flatbuffers::FlatBufferBuilder &_fbb, const EmbeddingLookupSparseOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct GatherOptionsT : public flatbuffers::NativeTable {
+  typedef GatherOptions TableType;
+  int32_t axis;
+  GatherOptionsT()
+      : axis(0) {
+  }
+};
+
+struct GatherOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef GatherOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_AXIS = 4
+  };
+  int32_t axis() const {
+    return GetField<int32_t>(VT_AXIS, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_AXIS) &&
+           verifier.EndTable();
+  }
+  GatherOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(GatherOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<GatherOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const GatherOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct GatherOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_axis(int32_t axis) {
+    fbb_.AddElement<int32_t>(GatherOptions::VT_AXIS, axis, 0);
+  }
+  explicit GatherOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  GatherOptionsBuilder &operator=(const GatherOptionsBuilder &);
+  flatbuffers::Offset<GatherOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<GatherOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<GatherOptions> CreateGatherOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t axis = 0) {
+  GatherOptionsBuilder builder_(_fbb);
+  builder_.add_axis(axis);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<GatherOptions> CreateGatherOptions(flatbuffers::FlatBufferBuilder &_fbb, const GatherOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct TransposeOptionsT : public flatbuffers::NativeTable {
+  typedef TransposeOptions TableType;
+  TransposeOptionsT() {
+  }
+};
+
+struct TransposeOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef TransposeOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  TransposeOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(TransposeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<TransposeOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const TransposeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct TransposeOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit TransposeOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  TransposeOptionsBuilder &operator=(const TransposeOptionsBuilder &);
+  flatbuffers::Offset<TransposeOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<TransposeOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<TransposeOptions> CreateTransposeOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  TransposeOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<TransposeOptions> CreateTransposeOptions(flatbuffers::FlatBufferBuilder &_fbb, const TransposeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ExpOptionsT : public flatbuffers::NativeTable {
+  typedef ExpOptions TableType;
+  ExpOptionsT() {
+  }
+};
+
+struct ExpOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ExpOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  ExpOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ExpOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ExpOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ExpOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ExpOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit ExpOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ExpOptionsBuilder &operator=(const ExpOptionsBuilder &);
+  flatbuffers::Offset<ExpOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ExpOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ExpOptions> CreateExpOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  ExpOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<ExpOptions> CreateExpOptions(flatbuffers::FlatBufferBuilder &_fbb, const ExpOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct CosOptionsT : public flatbuffers::NativeTable {
+  typedef CosOptions TableType;
+  CosOptionsT() {
+  }
+};
+
+struct CosOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef CosOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  CosOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(CosOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<CosOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const CosOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct CosOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit CosOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  CosOptionsBuilder &operator=(const CosOptionsBuilder &);
+  flatbuffers::Offset<CosOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<CosOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<CosOptions> CreateCosOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  CosOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<CosOptions> CreateCosOptions(flatbuffers::FlatBufferBuilder &_fbb, const CosOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ReducerOptionsT : public flatbuffers::NativeTable {
+  typedef ReducerOptions TableType;
+  bool keep_dims;
+  ReducerOptionsT()
+      : keep_dims(false) {
+  }
+};
+
+struct ReducerOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ReducerOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_KEEP_DIMS = 4
+  };
+  bool keep_dims() const {
+    return GetField<uint8_t>(VT_KEEP_DIMS, 0) != 0;
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<uint8_t>(verifier, VT_KEEP_DIMS) &&
+           verifier.EndTable();
+  }
+  ReducerOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ReducerOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ReducerOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ReducerOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ReducerOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_keep_dims(bool keep_dims) {
+    fbb_.AddElement<uint8_t>(ReducerOptions::VT_KEEP_DIMS, static_cast<uint8_t>(keep_dims), 0);
+  }
+  explicit ReducerOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ReducerOptionsBuilder &operator=(const ReducerOptionsBuilder &);
+  flatbuffers::Offset<ReducerOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ReducerOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ReducerOptions> CreateReducerOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    bool keep_dims = false) {
+  ReducerOptionsBuilder builder_(_fbb);
+  builder_.add_keep_dims(keep_dims);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<ReducerOptions> CreateReducerOptions(flatbuffers::FlatBufferBuilder &_fbb, const ReducerOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SqueezeOptionsT : public flatbuffers::NativeTable {
+  typedef SqueezeOptions TableType;
+  std::vector<int32_t> squeeze_dims;
+  SqueezeOptionsT() {
+  }
+};
+
+struct SqueezeOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SqueezeOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_SQUEEZE_DIMS = 4
+  };
+  const flatbuffers::Vector<int32_t> *squeeze_dims() const {
+    return GetPointer<const flatbuffers::Vector<int32_t> *>(VT_SQUEEZE_DIMS);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyOffset(verifier, VT_SQUEEZE_DIMS) &&
+           verifier.VerifyVector(squeeze_dims()) &&
+           verifier.EndTable();
+  }
+  SqueezeOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SqueezeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SqueezeOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SqueezeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SqueezeOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_squeeze_dims(flatbuffers::Offset<flatbuffers::Vector<int32_t>> squeeze_dims) {
+    fbb_.AddOffset(SqueezeOptions::VT_SQUEEZE_DIMS, squeeze_dims);
+  }
+  explicit SqueezeOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SqueezeOptionsBuilder &operator=(const SqueezeOptionsBuilder &);
+  flatbuffers::Offset<SqueezeOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SqueezeOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SqueezeOptions> CreateSqueezeOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    flatbuffers::Offset<flatbuffers::Vector<int32_t>> squeeze_dims = 0) {
+  SqueezeOptionsBuilder builder_(_fbb);
+  builder_.add_squeeze_dims(squeeze_dims);
+  return builder_.Finish();
+}
+
+inline flatbuffers::Offset<SqueezeOptions> CreateSqueezeOptionsDirect(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    const std::vector<int32_t> *squeeze_dims = nullptr) {
+  auto squeeze_dims__ = squeeze_dims ? _fbb.CreateVector<int32_t>(*squeeze_dims) : 0;
+  return tflite::CreateSqueezeOptions(
+      _fbb,
+      squeeze_dims__);
+}
+
+flatbuffers::Offset<SqueezeOptions> CreateSqueezeOptions(flatbuffers::FlatBufferBuilder &_fbb, const SqueezeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SplitOptionsT : public flatbuffers::NativeTable {
+  typedef SplitOptions TableType;
+  int32_t num_splits;
+  SplitOptionsT()
+      : num_splits(0) {
+  }
+};
+
+struct SplitOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SplitOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_NUM_SPLITS = 4
+  };
+  int32_t num_splits() const {
+    return GetField<int32_t>(VT_NUM_SPLITS, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_NUM_SPLITS) &&
+           verifier.EndTable();
+  }
+  SplitOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SplitOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SplitOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SplitOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SplitOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_num_splits(int32_t num_splits) {
+    fbb_.AddElement<int32_t>(SplitOptions::VT_NUM_SPLITS, num_splits, 0);
+  }
+  explicit SplitOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SplitOptionsBuilder &operator=(const SplitOptionsBuilder &);
+  flatbuffers::Offset<SplitOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SplitOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SplitOptions> CreateSplitOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t num_splits = 0) {
+  SplitOptionsBuilder builder_(_fbb);
+  builder_.add_num_splits(num_splits);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SplitOptions> CreateSplitOptions(flatbuffers::FlatBufferBuilder &_fbb, const SplitOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SplitVOptionsT : public flatbuffers::NativeTable {
+  typedef SplitVOptions TableType;
+  int32_t num_splits;
+  SplitVOptionsT()
+      : num_splits(0) {
+  }
+};
+
+struct SplitVOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SplitVOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_NUM_SPLITS = 4
+  };
+  int32_t num_splits() const {
+    return GetField<int32_t>(VT_NUM_SPLITS, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_NUM_SPLITS) &&
+           verifier.EndTable();
+  }
+  SplitVOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SplitVOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SplitVOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SplitVOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SplitVOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_num_splits(int32_t num_splits) {
+    fbb_.AddElement<int32_t>(SplitVOptions::VT_NUM_SPLITS, num_splits, 0);
+  }
+  explicit SplitVOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SplitVOptionsBuilder &operator=(const SplitVOptionsBuilder &);
+  flatbuffers::Offset<SplitVOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SplitVOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SplitVOptions> CreateSplitVOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t num_splits = 0) {
+  SplitVOptionsBuilder builder_(_fbb);
+  builder_.add_num_splits(num_splits);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SplitVOptions> CreateSplitVOptions(flatbuffers::FlatBufferBuilder &_fbb, const SplitVOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct StridedSliceOptionsT : public flatbuffers::NativeTable {
+  typedef StridedSliceOptions TableType;
+  int32_t begin_mask;
+  int32_t end_mask;
+  int32_t ellipsis_mask;
+  int32_t new_axis_mask;
+  int32_t shrink_axis_mask;
+  StridedSliceOptionsT()
+      : begin_mask(0),
+        end_mask(0),
+        ellipsis_mask(0),
+        new_axis_mask(0),
+        shrink_axis_mask(0) {
+  }
+};
+
+struct StridedSliceOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef StridedSliceOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_BEGIN_MASK = 4,
+    VT_END_MASK = 6,
+    VT_ELLIPSIS_MASK = 8,
+    VT_NEW_AXIS_MASK = 10,
+    VT_SHRINK_AXIS_MASK = 12
+  };
+  int32_t begin_mask() const {
+    return GetField<int32_t>(VT_BEGIN_MASK, 0);
+  }
+  int32_t end_mask() const {
+    return GetField<int32_t>(VT_END_MASK, 0);
+  }
+  int32_t ellipsis_mask() const {
+    return GetField<int32_t>(VT_ELLIPSIS_MASK, 0);
+  }
+  int32_t new_axis_mask() const {
+    return GetField<int32_t>(VT_NEW_AXIS_MASK, 0);
+  }
+  int32_t shrink_axis_mask() const {
+    return GetField<int32_t>(VT_SHRINK_AXIS_MASK, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_BEGIN_MASK) &&
+           VerifyField<int32_t>(verifier, VT_END_MASK) &&
+           VerifyField<int32_t>(verifier, VT_ELLIPSIS_MASK) &&
+           VerifyField<int32_t>(verifier, VT_NEW_AXIS_MASK) &&
+           VerifyField<int32_t>(verifier, VT_SHRINK_AXIS_MASK) &&
+           verifier.EndTable();
+  }
+  StridedSliceOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(StridedSliceOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<StridedSliceOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const StridedSliceOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct StridedSliceOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_begin_mask(int32_t begin_mask) {
+    fbb_.AddElement<int32_t>(StridedSliceOptions::VT_BEGIN_MASK, begin_mask, 0);
+  }
+  void add_end_mask(int32_t end_mask) {
+    fbb_.AddElement<int32_t>(StridedSliceOptions::VT_END_MASK, end_mask, 0);
+  }
+  void add_ellipsis_mask(int32_t ellipsis_mask) {
+    fbb_.AddElement<int32_t>(StridedSliceOptions::VT_ELLIPSIS_MASK, ellipsis_mask, 0);
+  }
+  void add_new_axis_mask(int32_t new_axis_mask) {
+    fbb_.AddElement<int32_t>(StridedSliceOptions::VT_NEW_AXIS_MASK, new_axis_mask, 0);
+  }
+  void add_shrink_axis_mask(int32_t shrink_axis_mask) {
+    fbb_.AddElement<int32_t>(StridedSliceOptions::VT_SHRINK_AXIS_MASK, shrink_axis_mask, 0);
+  }
+  explicit StridedSliceOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  StridedSliceOptionsBuilder &operator=(const StridedSliceOptionsBuilder &);
+  flatbuffers::Offset<StridedSliceOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<StridedSliceOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<StridedSliceOptions> CreateStridedSliceOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t begin_mask = 0,
+    int32_t end_mask = 0,
+    int32_t ellipsis_mask = 0,
+    int32_t new_axis_mask = 0,
+    int32_t shrink_axis_mask = 0) {
+  StridedSliceOptionsBuilder builder_(_fbb);
+  builder_.add_shrink_axis_mask(shrink_axis_mask);
+  builder_.add_new_axis_mask(new_axis_mask);
+  builder_.add_ellipsis_mask(ellipsis_mask);
+  builder_.add_end_mask(end_mask);
+  builder_.add_begin_mask(begin_mask);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<StridedSliceOptions> CreateStridedSliceOptions(flatbuffers::FlatBufferBuilder &_fbb, const StridedSliceOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct LogSoftmaxOptionsT : public flatbuffers::NativeTable {
+  typedef LogSoftmaxOptions TableType;
+  LogSoftmaxOptionsT() {
+  }
+};
+
+struct LogSoftmaxOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef LogSoftmaxOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  LogSoftmaxOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(LogSoftmaxOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<LogSoftmaxOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const LogSoftmaxOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct LogSoftmaxOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit LogSoftmaxOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  LogSoftmaxOptionsBuilder &operator=(const LogSoftmaxOptionsBuilder &);
+  flatbuffers::Offset<LogSoftmaxOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<LogSoftmaxOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<LogSoftmaxOptions> CreateLogSoftmaxOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  LogSoftmaxOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<LogSoftmaxOptions> CreateLogSoftmaxOptions(flatbuffers::FlatBufferBuilder &_fbb, const LogSoftmaxOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct CastOptionsT : public flatbuffers::NativeTable {
+  typedef CastOptions TableType;
+  TensorType in_data_type;
+  TensorType out_data_type;
+  CastOptionsT()
+      : in_data_type(TensorType_FLOAT32),
+        out_data_type(TensorType_FLOAT32) {
+  }
+};
+
+struct CastOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef CastOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_IN_DATA_TYPE = 4,
+    VT_OUT_DATA_TYPE = 6
+  };
+  TensorType in_data_type() const {
+    return static_cast<TensorType>(GetField<int8_t>(VT_IN_DATA_TYPE, 0));
+  }
+  TensorType out_data_type() const {
+    return static_cast<TensorType>(GetField<int8_t>(VT_OUT_DATA_TYPE, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_IN_DATA_TYPE) &&
+           VerifyField<int8_t>(verifier, VT_OUT_DATA_TYPE) &&
+           verifier.EndTable();
+  }
+  CastOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(CastOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<CastOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const CastOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct CastOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_in_data_type(TensorType in_data_type) {
+    fbb_.AddElement<int8_t>(CastOptions::VT_IN_DATA_TYPE, static_cast<int8_t>(in_data_type), 0);
+  }
+  void add_out_data_type(TensorType out_data_type) {
+    fbb_.AddElement<int8_t>(CastOptions::VT_OUT_DATA_TYPE, static_cast<int8_t>(out_data_type), 0);
+  }
+  explicit CastOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  CastOptionsBuilder &operator=(const CastOptionsBuilder &);
+  flatbuffers::Offset<CastOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<CastOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<CastOptions> CreateCastOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    TensorType in_data_type = TensorType_FLOAT32,
+    TensorType out_data_type = TensorType_FLOAT32) {
+  CastOptionsBuilder builder_(_fbb);
+  builder_.add_out_data_type(out_data_type);
+  builder_.add_in_data_type(in_data_type);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<CastOptions> CreateCastOptions(flatbuffers::FlatBufferBuilder &_fbb, const CastOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct DequantizeOptionsT : public flatbuffers::NativeTable {
+  typedef DequantizeOptions TableType;
+  DequantizeOptionsT() {
+  }
+};
+
+struct DequantizeOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef DequantizeOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  DequantizeOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(DequantizeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<DequantizeOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const DequantizeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct DequantizeOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit DequantizeOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  DequantizeOptionsBuilder &operator=(const DequantizeOptionsBuilder &);
+  flatbuffers::Offset<DequantizeOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<DequantizeOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<DequantizeOptions> CreateDequantizeOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  DequantizeOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<DequantizeOptions> CreateDequantizeOptions(flatbuffers::FlatBufferBuilder &_fbb, const DequantizeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct MaximumMinimumOptionsT : public flatbuffers::NativeTable {
+  typedef MaximumMinimumOptions TableType;
+  MaximumMinimumOptionsT() {
+  }
+};
+
+struct MaximumMinimumOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef MaximumMinimumOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  MaximumMinimumOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(MaximumMinimumOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<MaximumMinimumOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const MaximumMinimumOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct MaximumMinimumOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit MaximumMinimumOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  MaximumMinimumOptionsBuilder &operator=(const MaximumMinimumOptionsBuilder &);
+  flatbuffers::Offset<MaximumMinimumOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<MaximumMinimumOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<MaximumMinimumOptions> CreateMaximumMinimumOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  MaximumMinimumOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<MaximumMinimumOptions> CreateMaximumMinimumOptions(flatbuffers::FlatBufferBuilder &_fbb, const MaximumMinimumOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct TileOptionsT : public flatbuffers::NativeTable {
+  typedef TileOptions TableType;
+  TileOptionsT() {
+  }
+};
+
+struct TileOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef TileOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  TileOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(TileOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<TileOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const TileOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct TileOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit TileOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  TileOptionsBuilder &operator=(const TileOptionsBuilder &);
+  flatbuffers::Offset<TileOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<TileOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<TileOptions> CreateTileOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  TileOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<TileOptions> CreateTileOptions(flatbuffers::FlatBufferBuilder &_fbb, const TileOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ArgMaxOptionsT : public flatbuffers::NativeTable {
+  typedef ArgMaxOptions TableType;
+  TensorType output_type;
+  ArgMaxOptionsT()
+      : output_type(TensorType_FLOAT32) {
+  }
+};
+
+struct ArgMaxOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ArgMaxOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_OUTPUT_TYPE = 4
+  };
+  TensorType output_type() const {
+    return static_cast<TensorType>(GetField<int8_t>(VT_OUTPUT_TYPE, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_OUTPUT_TYPE) &&
+           verifier.EndTable();
+  }
+  ArgMaxOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ArgMaxOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ArgMaxOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ArgMaxOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ArgMaxOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_output_type(TensorType output_type) {
+    fbb_.AddElement<int8_t>(ArgMaxOptions::VT_OUTPUT_TYPE, static_cast<int8_t>(output_type), 0);
+  }
+  explicit ArgMaxOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ArgMaxOptionsBuilder &operator=(const ArgMaxOptionsBuilder &);
+  flatbuffers::Offset<ArgMaxOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ArgMaxOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ArgMaxOptions> CreateArgMaxOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    TensorType output_type = TensorType_FLOAT32) {
+  ArgMaxOptionsBuilder builder_(_fbb);
+  builder_.add_output_type(output_type);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<ArgMaxOptions> CreateArgMaxOptions(flatbuffers::FlatBufferBuilder &_fbb, const ArgMaxOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ArgMinOptionsT : public flatbuffers::NativeTable {
+  typedef ArgMinOptions TableType;
+  TensorType output_type;
+  ArgMinOptionsT()
+      : output_type(TensorType_FLOAT32) {
+  }
+};
+
+struct ArgMinOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ArgMinOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_OUTPUT_TYPE = 4
+  };
+  TensorType output_type() const {
+    return static_cast<TensorType>(GetField<int8_t>(VT_OUTPUT_TYPE, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_OUTPUT_TYPE) &&
+           verifier.EndTable();
+  }
+  ArgMinOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ArgMinOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ArgMinOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ArgMinOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ArgMinOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_output_type(TensorType output_type) {
+    fbb_.AddElement<int8_t>(ArgMinOptions::VT_OUTPUT_TYPE, static_cast<int8_t>(output_type), 0);
+  }
+  explicit ArgMinOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ArgMinOptionsBuilder &operator=(const ArgMinOptionsBuilder &);
+  flatbuffers::Offset<ArgMinOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ArgMinOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ArgMinOptions> CreateArgMinOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    TensorType output_type = TensorType_FLOAT32) {
+  ArgMinOptionsBuilder builder_(_fbb);
+  builder_.add_output_type(output_type);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<ArgMinOptions> CreateArgMinOptions(flatbuffers::FlatBufferBuilder &_fbb, const ArgMinOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct GreaterOptionsT : public flatbuffers::NativeTable {
+  typedef GreaterOptions TableType;
+  GreaterOptionsT() {
+  }
+};
+
+struct GreaterOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef GreaterOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  GreaterOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(GreaterOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<GreaterOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const GreaterOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct GreaterOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit GreaterOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  GreaterOptionsBuilder &operator=(const GreaterOptionsBuilder &);
+  flatbuffers::Offset<GreaterOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<GreaterOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<GreaterOptions> CreateGreaterOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  GreaterOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<GreaterOptions> CreateGreaterOptions(flatbuffers::FlatBufferBuilder &_fbb, const GreaterOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct GreaterEqualOptionsT : public flatbuffers::NativeTable {
+  typedef GreaterEqualOptions TableType;
+  GreaterEqualOptionsT() {
+  }
+};
+
+struct GreaterEqualOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef GreaterEqualOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  GreaterEqualOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(GreaterEqualOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<GreaterEqualOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const GreaterEqualOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct GreaterEqualOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit GreaterEqualOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  GreaterEqualOptionsBuilder &operator=(const GreaterEqualOptionsBuilder &);
+  flatbuffers::Offset<GreaterEqualOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<GreaterEqualOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<GreaterEqualOptions> CreateGreaterEqualOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  GreaterEqualOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<GreaterEqualOptions> CreateGreaterEqualOptions(flatbuffers::FlatBufferBuilder &_fbb, const GreaterEqualOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct LessOptionsT : public flatbuffers::NativeTable {
+  typedef LessOptions TableType;
+  LessOptionsT() {
+  }
+};
+
+struct LessOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef LessOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  LessOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(LessOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<LessOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const LessOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct LessOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit LessOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  LessOptionsBuilder &operator=(const LessOptionsBuilder &);
+  flatbuffers::Offset<LessOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<LessOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<LessOptions> CreateLessOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  LessOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<LessOptions> CreateLessOptions(flatbuffers::FlatBufferBuilder &_fbb, const LessOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct LessEqualOptionsT : public flatbuffers::NativeTable {
+  typedef LessEqualOptions TableType;
+  LessEqualOptionsT() {
+  }
+};
+
+struct LessEqualOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef LessEqualOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  LessEqualOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(LessEqualOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<LessEqualOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const LessEqualOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct LessEqualOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit LessEqualOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  LessEqualOptionsBuilder &operator=(const LessEqualOptionsBuilder &);
+  flatbuffers::Offset<LessEqualOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<LessEqualOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<LessEqualOptions> CreateLessEqualOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  LessEqualOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<LessEqualOptions> CreateLessEqualOptions(flatbuffers::FlatBufferBuilder &_fbb, const LessEqualOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct NegOptionsT : public flatbuffers::NativeTable {
+  typedef NegOptions TableType;
+  NegOptionsT() {
+  }
+};
+
+struct NegOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef NegOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  NegOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(NegOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<NegOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const NegOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct NegOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit NegOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  NegOptionsBuilder &operator=(const NegOptionsBuilder &);
+  flatbuffers::Offset<NegOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<NegOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<NegOptions> CreateNegOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  NegOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<NegOptions> CreateNegOptions(flatbuffers::FlatBufferBuilder &_fbb, const NegOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SelectOptionsT : public flatbuffers::NativeTable {
+  typedef SelectOptions TableType;
+  SelectOptionsT() {
+  }
+};
+
+struct SelectOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SelectOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  SelectOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SelectOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SelectOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SelectOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SelectOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit SelectOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SelectOptionsBuilder &operator=(const SelectOptionsBuilder &);
+  flatbuffers::Offset<SelectOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SelectOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SelectOptions> CreateSelectOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  SelectOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SelectOptions> CreateSelectOptions(flatbuffers::FlatBufferBuilder &_fbb, const SelectOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SliceOptionsT : public flatbuffers::NativeTable {
+  typedef SliceOptions TableType;
+  SliceOptionsT() {
+  }
+};
+
+struct SliceOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SliceOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  SliceOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SliceOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SliceOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SliceOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SliceOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit SliceOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SliceOptionsBuilder &operator=(const SliceOptionsBuilder &);
+  flatbuffers::Offset<SliceOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SliceOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SliceOptions> CreateSliceOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  SliceOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SliceOptions> CreateSliceOptions(flatbuffers::FlatBufferBuilder &_fbb, const SliceOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct TransposeConvOptionsT : public flatbuffers::NativeTable {
+  typedef TransposeConvOptions TableType;
+  Padding padding;
+  int32_t stride_w;
+  int32_t stride_h;
+  TransposeConvOptionsT()
+      : padding(Padding_SAME),
+        stride_w(0),
+        stride_h(0) {
+  }
+};
+
+struct TransposeConvOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef TransposeConvOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_PADDING = 4,
+    VT_STRIDE_W = 6,
+    VT_STRIDE_H = 8
+  };
+  Padding padding() const {
+    return static_cast<Padding>(GetField<int8_t>(VT_PADDING, 0));
+  }
+  int32_t stride_w() const {
+    return GetField<int32_t>(VT_STRIDE_W, 0);
+  }
+  int32_t stride_h() const {
+    return GetField<int32_t>(VT_STRIDE_H, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_PADDING) &&
+           VerifyField<int32_t>(verifier, VT_STRIDE_W) &&
+           VerifyField<int32_t>(verifier, VT_STRIDE_H) &&
+           verifier.EndTable();
+  }
+  TransposeConvOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(TransposeConvOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<TransposeConvOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const TransposeConvOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct TransposeConvOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_padding(Padding padding) {
+    fbb_.AddElement<int8_t>(TransposeConvOptions::VT_PADDING, static_cast<int8_t>(padding), 0);
+  }
+  void add_stride_w(int32_t stride_w) {
+    fbb_.AddElement<int32_t>(TransposeConvOptions::VT_STRIDE_W, stride_w, 0);
+  }
+  void add_stride_h(int32_t stride_h) {
+    fbb_.AddElement<int32_t>(TransposeConvOptions::VT_STRIDE_H, stride_h, 0);
+  }
+  explicit TransposeConvOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  TransposeConvOptionsBuilder &operator=(const TransposeConvOptionsBuilder &);
+  flatbuffers::Offset<TransposeConvOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<TransposeConvOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<TransposeConvOptions> CreateTransposeConvOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    Padding padding = Padding_SAME,
+    int32_t stride_w = 0,
+    int32_t stride_h = 0) {
+  TransposeConvOptionsBuilder builder_(_fbb);
+  builder_.add_stride_h(stride_h);
+  builder_.add_stride_w(stride_w);
+  builder_.add_padding(padding);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<TransposeConvOptions> CreateTransposeConvOptions(flatbuffers::FlatBufferBuilder &_fbb, const TransposeConvOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ExpandDimsOptionsT : public flatbuffers::NativeTable {
+  typedef ExpandDimsOptions TableType;
+  ExpandDimsOptionsT() {
+  }
+};
+
+struct ExpandDimsOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ExpandDimsOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  ExpandDimsOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ExpandDimsOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ExpandDimsOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ExpandDimsOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ExpandDimsOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit ExpandDimsOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ExpandDimsOptionsBuilder &operator=(const ExpandDimsOptionsBuilder &);
+  flatbuffers::Offset<ExpandDimsOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ExpandDimsOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ExpandDimsOptions> CreateExpandDimsOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  ExpandDimsOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<ExpandDimsOptions> CreateExpandDimsOptions(flatbuffers::FlatBufferBuilder &_fbb, const ExpandDimsOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SparseToDenseOptionsT : public flatbuffers::NativeTable {
+  typedef SparseToDenseOptions TableType;
+  bool validate_indices;
+  SparseToDenseOptionsT()
+      : validate_indices(false) {
+  }
+};
+
+struct SparseToDenseOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SparseToDenseOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_VALIDATE_INDICES = 4
+  };
+  bool validate_indices() const {
+    return GetField<uint8_t>(VT_VALIDATE_INDICES, 0) != 0;
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<uint8_t>(verifier, VT_VALIDATE_INDICES) &&
+           verifier.EndTable();
+  }
+  SparseToDenseOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SparseToDenseOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SparseToDenseOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SparseToDenseOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SparseToDenseOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_validate_indices(bool validate_indices) {
+    fbb_.AddElement<uint8_t>(SparseToDenseOptions::VT_VALIDATE_INDICES, static_cast<uint8_t>(validate_indices), 0);
+  }
+  explicit SparseToDenseOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SparseToDenseOptionsBuilder &operator=(const SparseToDenseOptionsBuilder &);
+  flatbuffers::Offset<SparseToDenseOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SparseToDenseOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SparseToDenseOptions> CreateSparseToDenseOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    bool validate_indices = false) {
+  SparseToDenseOptionsBuilder builder_(_fbb);
+  builder_.add_validate_indices(validate_indices);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SparseToDenseOptions> CreateSparseToDenseOptions(flatbuffers::FlatBufferBuilder &_fbb, const SparseToDenseOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct EqualOptionsT : public flatbuffers::NativeTable {
+  typedef EqualOptions TableType;
+  EqualOptionsT() {
+  }
+};
+
+struct EqualOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef EqualOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  EqualOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(EqualOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<EqualOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const EqualOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct EqualOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit EqualOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  EqualOptionsBuilder &operator=(const EqualOptionsBuilder &);
+  flatbuffers::Offset<EqualOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<EqualOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<EqualOptions> CreateEqualOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  EqualOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<EqualOptions> CreateEqualOptions(flatbuffers::FlatBufferBuilder &_fbb, const EqualOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct NotEqualOptionsT : public flatbuffers::NativeTable {
+  typedef NotEqualOptions TableType;
+  NotEqualOptionsT() {
+  }
+};
+
+struct NotEqualOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef NotEqualOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  NotEqualOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(NotEqualOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<NotEqualOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const NotEqualOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct NotEqualOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit NotEqualOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  NotEqualOptionsBuilder &operator=(const NotEqualOptionsBuilder &);
+  flatbuffers::Offset<NotEqualOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<NotEqualOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<NotEqualOptions> CreateNotEqualOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  NotEqualOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<NotEqualOptions> CreateNotEqualOptions(flatbuffers::FlatBufferBuilder &_fbb, const NotEqualOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ShapeOptionsT : public flatbuffers::NativeTable {
+  typedef ShapeOptions TableType;
+  TensorType out_type;
+  ShapeOptionsT()
+      : out_type(TensorType_FLOAT32) {
+  }
+};
+
+struct ShapeOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ShapeOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_OUT_TYPE = 4
+  };
+  TensorType out_type() const {
+    return static_cast<TensorType>(GetField<int8_t>(VT_OUT_TYPE, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_OUT_TYPE) &&
+           verifier.EndTable();
+  }
+  ShapeOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ShapeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ShapeOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ShapeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ShapeOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_out_type(TensorType out_type) {
+    fbb_.AddElement<int8_t>(ShapeOptions::VT_OUT_TYPE, static_cast<int8_t>(out_type), 0);
+  }
+  explicit ShapeOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ShapeOptionsBuilder &operator=(const ShapeOptionsBuilder &);
+  flatbuffers::Offset<ShapeOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ShapeOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ShapeOptions> CreateShapeOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    TensorType out_type = TensorType_FLOAT32) {
+  ShapeOptionsBuilder builder_(_fbb);
+  builder_.add_out_type(out_type);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<ShapeOptions> CreateShapeOptions(flatbuffers::FlatBufferBuilder &_fbb, const ShapeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct RankOptionsT : public flatbuffers::NativeTable {
+  typedef RankOptions TableType;
+  RankOptionsT() {
+  }
+};
+
+struct RankOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef RankOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  RankOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(RankOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<RankOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const RankOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct RankOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit RankOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  RankOptionsBuilder &operator=(const RankOptionsBuilder &);
+  flatbuffers::Offset<RankOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<RankOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<RankOptions> CreateRankOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  RankOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<RankOptions> CreateRankOptions(flatbuffers::FlatBufferBuilder &_fbb, const RankOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct PowOptionsT : public flatbuffers::NativeTable {
+  typedef PowOptions TableType;
+  PowOptionsT() {
+  }
+};
+
+struct PowOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef PowOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  PowOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(PowOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<PowOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const PowOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct PowOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit PowOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  PowOptionsBuilder &operator=(const PowOptionsBuilder &);
+  flatbuffers::Offset<PowOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<PowOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<PowOptions> CreatePowOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  PowOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<PowOptions> CreatePowOptions(flatbuffers::FlatBufferBuilder &_fbb, const PowOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct FakeQuantOptionsT : public flatbuffers::NativeTable {
+  typedef FakeQuantOptions TableType;
+  float min;
+  float max;
+  int32_t num_bits;
+  bool narrow_range;
+  FakeQuantOptionsT()
+      : min(0.0f),
+        max(0.0f),
+        num_bits(0),
+        narrow_range(false) {
+  }
+};
+
+struct FakeQuantOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef FakeQuantOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_MIN = 4,
+    VT_MAX = 6,
+    VT_NUM_BITS = 8,
+    VT_NARROW_RANGE = 10
+  };
+  float min() const {
+    return GetField<float>(VT_MIN, 0.0f);
+  }
+  float max() const {
+    return GetField<float>(VT_MAX, 0.0f);
+  }
+  int32_t num_bits() const {
+    return GetField<int32_t>(VT_NUM_BITS, 0);
+  }
+  bool narrow_range() const {
+    return GetField<uint8_t>(VT_NARROW_RANGE, 0) != 0;
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<float>(verifier, VT_MIN) &&
+           VerifyField<float>(verifier, VT_MAX) &&
+           VerifyField<int32_t>(verifier, VT_NUM_BITS) &&
+           VerifyField<uint8_t>(verifier, VT_NARROW_RANGE) &&
+           verifier.EndTable();
+  }
+  FakeQuantOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(FakeQuantOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<FakeQuantOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const FakeQuantOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct FakeQuantOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_min(float min) {
+    fbb_.AddElement<float>(FakeQuantOptions::VT_MIN, min, 0.0f);
+  }
+  void add_max(float max) {
+    fbb_.AddElement<float>(FakeQuantOptions::VT_MAX, max, 0.0f);
+  }
+  void add_num_bits(int32_t num_bits) {
+    fbb_.AddElement<int32_t>(FakeQuantOptions::VT_NUM_BITS, num_bits, 0);
+  }
+  void add_narrow_range(bool narrow_range) {
+    fbb_.AddElement<uint8_t>(FakeQuantOptions::VT_NARROW_RANGE, static_cast<uint8_t>(narrow_range), 0);
+  }
+  explicit FakeQuantOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  FakeQuantOptionsBuilder &operator=(const FakeQuantOptionsBuilder &);
+  flatbuffers::Offset<FakeQuantOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<FakeQuantOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<FakeQuantOptions> CreateFakeQuantOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    float min = 0.0f,
+    float max = 0.0f,
+    int32_t num_bits = 0,
+    bool narrow_range = false) {
+  FakeQuantOptionsBuilder builder_(_fbb);
+  builder_.add_num_bits(num_bits);
+  builder_.add_max(max);
+  builder_.add_min(min);
+  builder_.add_narrow_range(narrow_range);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<FakeQuantOptions> CreateFakeQuantOptions(flatbuffers::FlatBufferBuilder &_fbb, const FakeQuantOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct PackOptionsT : public flatbuffers::NativeTable {
+  typedef PackOptions TableType;
+  int32_t values_count;
+  int32_t axis;
+  PackOptionsT()
+      : values_count(0),
+        axis(0) {
+  }
+};
+
+struct PackOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef PackOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_VALUES_COUNT = 4,
+    VT_AXIS = 6
+  };
+  int32_t values_count() const {
+    return GetField<int32_t>(VT_VALUES_COUNT, 0);
+  }
+  int32_t axis() const {
+    return GetField<int32_t>(VT_AXIS, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_VALUES_COUNT) &&
+           VerifyField<int32_t>(verifier, VT_AXIS) &&
+           verifier.EndTable();
+  }
+  PackOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(PackOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<PackOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const PackOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct PackOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_values_count(int32_t values_count) {
+    fbb_.AddElement<int32_t>(PackOptions::VT_VALUES_COUNT, values_count, 0);
+  }
+  void add_axis(int32_t axis) {
+    fbb_.AddElement<int32_t>(PackOptions::VT_AXIS, axis, 0);
+  }
+  explicit PackOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  PackOptionsBuilder &operator=(const PackOptionsBuilder &);
+  flatbuffers::Offset<PackOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<PackOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<PackOptions> CreatePackOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t values_count = 0,
+    int32_t axis = 0) {
+  PackOptionsBuilder builder_(_fbb);
+  builder_.add_axis(axis);
+  builder_.add_values_count(values_count);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<PackOptions> CreatePackOptions(flatbuffers::FlatBufferBuilder &_fbb, const PackOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct LogicalOrOptionsT : public flatbuffers::NativeTable {
+  typedef LogicalOrOptions TableType;
+  LogicalOrOptionsT() {
+  }
+};
+
+struct LogicalOrOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef LogicalOrOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  LogicalOrOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(LogicalOrOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<LogicalOrOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const LogicalOrOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct LogicalOrOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit LogicalOrOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  LogicalOrOptionsBuilder &operator=(const LogicalOrOptionsBuilder &);
+  flatbuffers::Offset<LogicalOrOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<LogicalOrOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<LogicalOrOptions> CreateLogicalOrOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  LogicalOrOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<LogicalOrOptions> CreateLogicalOrOptions(flatbuffers::FlatBufferBuilder &_fbb, const LogicalOrOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct OneHotOptionsT : public flatbuffers::NativeTable {
+  typedef OneHotOptions TableType;
+  int32_t axis;
+  OneHotOptionsT()
+      : axis(0) {
+  }
+};
+
+struct OneHotOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef OneHotOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_AXIS = 4
+  };
+  int32_t axis() const {
+    return GetField<int32_t>(VT_AXIS, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_AXIS) &&
+           verifier.EndTable();
+  }
+  OneHotOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(OneHotOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<OneHotOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const OneHotOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct OneHotOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_axis(int32_t axis) {
+    fbb_.AddElement<int32_t>(OneHotOptions::VT_AXIS, axis, 0);
+  }
+  explicit OneHotOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  OneHotOptionsBuilder &operator=(const OneHotOptionsBuilder &);
+  flatbuffers::Offset<OneHotOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<OneHotOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<OneHotOptions> CreateOneHotOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t axis = 0) {
+  OneHotOptionsBuilder builder_(_fbb);
+  builder_.add_axis(axis);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<OneHotOptions> CreateOneHotOptions(flatbuffers::FlatBufferBuilder &_fbb, const OneHotOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct AbsOptionsT : public flatbuffers::NativeTable {
+  typedef AbsOptions TableType;
+  AbsOptionsT() {
+  }
+};
+
+struct AbsOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef AbsOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  AbsOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(AbsOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<AbsOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const AbsOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct AbsOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit AbsOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  AbsOptionsBuilder &operator=(const AbsOptionsBuilder &);
+  flatbuffers::Offset<AbsOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<AbsOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<AbsOptions> CreateAbsOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  AbsOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<AbsOptions> CreateAbsOptions(flatbuffers::FlatBufferBuilder &_fbb, const AbsOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct HardSwishOptionsT : public flatbuffers::NativeTable {
+  typedef HardSwishOptions TableType;
+  HardSwishOptionsT() {
+  }
+};
+
+struct HardSwishOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef HardSwishOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  HardSwishOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(HardSwishOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<HardSwishOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const HardSwishOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct HardSwishOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit HardSwishOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  HardSwishOptionsBuilder &operator=(const HardSwishOptionsBuilder &);
+  flatbuffers::Offset<HardSwishOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<HardSwishOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<HardSwishOptions> CreateHardSwishOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  HardSwishOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<HardSwishOptions> CreateHardSwishOptions(flatbuffers::FlatBufferBuilder &_fbb, const HardSwishOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct LogicalAndOptionsT : public flatbuffers::NativeTable {
+  typedef LogicalAndOptions TableType;
+  LogicalAndOptionsT() {
+  }
+};
+
+struct LogicalAndOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef LogicalAndOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  LogicalAndOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(LogicalAndOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<LogicalAndOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const LogicalAndOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct LogicalAndOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit LogicalAndOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  LogicalAndOptionsBuilder &operator=(const LogicalAndOptionsBuilder &);
+  flatbuffers::Offset<LogicalAndOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<LogicalAndOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<LogicalAndOptions> CreateLogicalAndOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  LogicalAndOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<LogicalAndOptions> CreateLogicalAndOptions(flatbuffers::FlatBufferBuilder &_fbb, const LogicalAndOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct LogicalNotOptionsT : public flatbuffers::NativeTable {
+  typedef LogicalNotOptions TableType;
+  LogicalNotOptionsT() {
+  }
+};
+
+struct LogicalNotOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef LogicalNotOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  LogicalNotOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(LogicalNotOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<LogicalNotOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const LogicalNotOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct LogicalNotOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit LogicalNotOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  LogicalNotOptionsBuilder &operator=(const LogicalNotOptionsBuilder &);
+  flatbuffers::Offset<LogicalNotOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<LogicalNotOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<LogicalNotOptions> CreateLogicalNotOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  LogicalNotOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<LogicalNotOptions> CreateLogicalNotOptions(flatbuffers::FlatBufferBuilder &_fbb, const LogicalNotOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct UnpackOptionsT : public flatbuffers::NativeTable {
+  typedef UnpackOptions TableType;
+  int32_t num;
+  int32_t axis;
+  UnpackOptionsT()
+      : num(0),
+        axis(0) {
+  }
+};
+
+struct UnpackOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef UnpackOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_NUM = 4,
+    VT_AXIS = 6
+  };
+  int32_t num() const {
+    return GetField<int32_t>(VT_NUM, 0);
+  }
+  int32_t axis() const {
+    return GetField<int32_t>(VT_AXIS, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_NUM) &&
+           VerifyField<int32_t>(verifier, VT_AXIS) &&
+           verifier.EndTable();
+  }
+  UnpackOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(UnpackOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<UnpackOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const UnpackOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct UnpackOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_num(int32_t num) {
+    fbb_.AddElement<int32_t>(UnpackOptions::VT_NUM, num, 0);
+  }
+  void add_axis(int32_t axis) {
+    fbb_.AddElement<int32_t>(UnpackOptions::VT_AXIS, axis, 0);
+  }
+  explicit UnpackOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  UnpackOptionsBuilder &operator=(const UnpackOptionsBuilder &);
+  flatbuffers::Offset<UnpackOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<UnpackOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<UnpackOptions> CreateUnpackOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t num = 0,
+    int32_t axis = 0) {
+  UnpackOptionsBuilder builder_(_fbb);
+  builder_.add_axis(axis);
+  builder_.add_num(num);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<UnpackOptions> CreateUnpackOptions(flatbuffers::FlatBufferBuilder &_fbb, const UnpackOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct FloorDivOptionsT : public flatbuffers::NativeTable {
+  typedef FloorDivOptions TableType;
+  FloorDivOptionsT() {
+  }
+};
+
+struct FloorDivOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef FloorDivOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  FloorDivOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(FloorDivOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<FloorDivOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const FloorDivOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct FloorDivOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit FloorDivOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  FloorDivOptionsBuilder &operator=(const FloorDivOptionsBuilder &);
+  flatbuffers::Offset<FloorDivOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<FloorDivOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<FloorDivOptions> CreateFloorDivOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  FloorDivOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<FloorDivOptions> CreateFloorDivOptions(flatbuffers::FlatBufferBuilder &_fbb, const FloorDivOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SquareOptionsT : public flatbuffers::NativeTable {
+  typedef SquareOptions TableType;
+  SquareOptionsT() {
+  }
+};
+
+struct SquareOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SquareOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  SquareOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SquareOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SquareOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SquareOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SquareOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit SquareOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SquareOptionsBuilder &operator=(const SquareOptionsBuilder &);
+  flatbuffers::Offset<SquareOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SquareOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SquareOptions> CreateSquareOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  SquareOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SquareOptions> CreateSquareOptions(flatbuffers::FlatBufferBuilder &_fbb, const SquareOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ZerosLikeOptionsT : public flatbuffers::NativeTable {
+  typedef ZerosLikeOptions TableType;
+  ZerosLikeOptionsT() {
+  }
+};
+
+struct ZerosLikeOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ZerosLikeOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  ZerosLikeOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ZerosLikeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ZerosLikeOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ZerosLikeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ZerosLikeOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit ZerosLikeOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ZerosLikeOptionsBuilder &operator=(const ZerosLikeOptionsBuilder &);
+  flatbuffers::Offset<ZerosLikeOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ZerosLikeOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ZerosLikeOptions> CreateZerosLikeOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  ZerosLikeOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<ZerosLikeOptions> CreateZerosLikeOptions(flatbuffers::FlatBufferBuilder &_fbb, const ZerosLikeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct FillOptionsT : public flatbuffers::NativeTable {
+  typedef FillOptions TableType;
+  FillOptionsT() {
+  }
+};
+
+struct FillOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef FillOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  FillOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(FillOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<FillOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const FillOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct FillOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit FillOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  FillOptionsBuilder &operator=(const FillOptionsBuilder &);
+  flatbuffers::Offset<FillOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<FillOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<FillOptions> CreateFillOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  FillOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<FillOptions> CreateFillOptions(flatbuffers::FlatBufferBuilder &_fbb, const FillOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct FloorModOptionsT : public flatbuffers::NativeTable {
+  typedef FloorModOptions TableType;
+  FloorModOptionsT() {
+  }
+};
+
+struct FloorModOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef FloorModOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  FloorModOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(FloorModOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<FloorModOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const FloorModOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct FloorModOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit FloorModOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  FloorModOptionsBuilder &operator=(const FloorModOptionsBuilder &);
+  flatbuffers::Offset<FloorModOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<FloorModOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<FloorModOptions> CreateFloorModOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  FloorModOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<FloorModOptions> CreateFloorModOptions(flatbuffers::FlatBufferBuilder &_fbb, const FloorModOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct RangeOptionsT : public flatbuffers::NativeTable {
+  typedef RangeOptions TableType;
+  RangeOptionsT() {
+  }
+};
+
+struct RangeOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef RangeOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  RangeOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(RangeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<RangeOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const RangeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct RangeOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit RangeOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  RangeOptionsBuilder &operator=(const RangeOptionsBuilder &);
+  flatbuffers::Offset<RangeOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<RangeOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<RangeOptions> CreateRangeOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  RangeOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<RangeOptions> CreateRangeOptions(flatbuffers::FlatBufferBuilder &_fbb, const RangeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct LeakyReluOptionsT : public flatbuffers::NativeTable {
+  typedef LeakyReluOptions TableType;
+  float alpha;
+  LeakyReluOptionsT()
+      : alpha(0.0f) {
+  }
+};
+
+struct LeakyReluOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef LeakyReluOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_ALPHA = 4
+  };
+  float alpha() const {
+    return GetField<float>(VT_ALPHA, 0.0f);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<float>(verifier, VT_ALPHA) &&
+           verifier.EndTable();
+  }
+  LeakyReluOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(LeakyReluOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<LeakyReluOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const LeakyReluOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct LeakyReluOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_alpha(float alpha) {
+    fbb_.AddElement<float>(LeakyReluOptions::VT_ALPHA, alpha, 0.0f);
+  }
+  explicit LeakyReluOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  LeakyReluOptionsBuilder &operator=(const LeakyReluOptionsBuilder &);
+  flatbuffers::Offset<LeakyReluOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<LeakyReluOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<LeakyReluOptions> CreateLeakyReluOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    float alpha = 0.0f) {
+  LeakyReluOptionsBuilder builder_(_fbb);
+  builder_.add_alpha(alpha);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<LeakyReluOptions> CreateLeakyReluOptions(flatbuffers::FlatBufferBuilder &_fbb, const LeakyReluOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SquaredDifferenceOptionsT : public flatbuffers::NativeTable {
+  typedef SquaredDifferenceOptions TableType;
+  SquaredDifferenceOptionsT() {
+  }
+};
+
+struct SquaredDifferenceOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SquaredDifferenceOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  SquaredDifferenceOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SquaredDifferenceOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SquaredDifferenceOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SquaredDifferenceOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SquaredDifferenceOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit SquaredDifferenceOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SquaredDifferenceOptionsBuilder &operator=(const SquaredDifferenceOptionsBuilder &);
+  flatbuffers::Offset<SquaredDifferenceOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SquaredDifferenceOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SquaredDifferenceOptions> CreateSquaredDifferenceOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  SquaredDifferenceOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<SquaredDifferenceOptions> CreateSquaredDifferenceOptions(flatbuffers::FlatBufferBuilder &_fbb, const SquaredDifferenceOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct MirrorPadOptionsT : public flatbuffers::NativeTable {
+  typedef MirrorPadOptions TableType;
+  MirrorPadMode mode;
+  MirrorPadOptionsT()
+      : mode(MirrorPadMode_REFLECT) {
+  }
+};
+
+struct MirrorPadOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef MirrorPadOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_MODE = 4
+  };
+  MirrorPadMode mode() const {
+    return static_cast<MirrorPadMode>(GetField<int8_t>(VT_MODE, 0));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_MODE) &&
+           verifier.EndTable();
+  }
+  MirrorPadOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(MirrorPadOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<MirrorPadOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const MirrorPadOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct MirrorPadOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_mode(MirrorPadMode mode) {
+    fbb_.AddElement<int8_t>(MirrorPadOptions::VT_MODE, static_cast<int8_t>(mode), 0);
+  }
+  explicit MirrorPadOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  MirrorPadOptionsBuilder &operator=(const MirrorPadOptionsBuilder &);
+  flatbuffers::Offset<MirrorPadOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<MirrorPadOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<MirrorPadOptions> CreateMirrorPadOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    MirrorPadMode mode = MirrorPadMode_REFLECT) {
+  MirrorPadOptionsBuilder builder_(_fbb);
+  builder_.add_mode(mode);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<MirrorPadOptions> CreateMirrorPadOptions(flatbuffers::FlatBufferBuilder &_fbb, const MirrorPadOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct UniqueOptionsT : public flatbuffers::NativeTable {
+  typedef UniqueOptions TableType;
+  TensorType idx_out_type;
+  UniqueOptionsT()
+      : idx_out_type(TensorType_INT32) {
+  }
+};
+
+struct UniqueOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef UniqueOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_IDX_OUT_TYPE = 4
+  };
+  TensorType idx_out_type() const {
+    return static_cast<TensorType>(GetField<int8_t>(VT_IDX_OUT_TYPE, 2));
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_IDX_OUT_TYPE) &&
+           verifier.EndTable();
+  }
+  UniqueOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(UniqueOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<UniqueOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const UniqueOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct UniqueOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_idx_out_type(TensorType idx_out_type) {
+    fbb_.AddElement<int8_t>(UniqueOptions::VT_IDX_OUT_TYPE, static_cast<int8_t>(idx_out_type), 2);
+  }
+  explicit UniqueOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  UniqueOptionsBuilder &operator=(const UniqueOptionsBuilder &);
+  flatbuffers::Offset<UniqueOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<UniqueOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<UniqueOptions> CreateUniqueOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    TensorType idx_out_type = TensorType_INT32) {
+  UniqueOptionsBuilder builder_(_fbb);
+  builder_.add_idx_out_type(idx_out_type);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<UniqueOptions> CreateUniqueOptions(flatbuffers::FlatBufferBuilder &_fbb, const UniqueOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ReverseV2OptionsT : public flatbuffers::NativeTable {
+  typedef ReverseV2Options TableType;
+  ReverseV2OptionsT() {
+  }
+};
+
+struct ReverseV2Options FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ReverseV2OptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  ReverseV2OptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ReverseV2OptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ReverseV2Options> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ReverseV2OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ReverseV2OptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit ReverseV2OptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ReverseV2OptionsBuilder &operator=(const ReverseV2OptionsBuilder &);
+  flatbuffers::Offset<ReverseV2Options> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ReverseV2Options>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ReverseV2Options> CreateReverseV2Options(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  ReverseV2OptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<ReverseV2Options> CreateReverseV2Options(flatbuffers::FlatBufferBuilder &_fbb, const ReverseV2OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct AddNOptionsT : public flatbuffers::NativeTable {
+  typedef AddNOptions TableType;
+  AddNOptionsT() {
+  }
+};
+
+struct AddNOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef AddNOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  AddNOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(AddNOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<AddNOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const AddNOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct AddNOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit AddNOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  AddNOptionsBuilder &operator=(const AddNOptionsBuilder &);
+  flatbuffers::Offset<AddNOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<AddNOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<AddNOptions> CreateAddNOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  AddNOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<AddNOptions> CreateAddNOptions(flatbuffers::FlatBufferBuilder &_fbb, const AddNOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct GatherNdOptionsT : public flatbuffers::NativeTable {
+  typedef GatherNdOptions TableType;
+  GatherNdOptionsT() {
+  }
+};
+
+struct GatherNdOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef GatherNdOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  GatherNdOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(GatherNdOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<GatherNdOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const GatherNdOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct GatherNdOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit GatherNdOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  GatherNdOptionsBuilder &operator=(const GatherNdOptionsBuilder &);
+  flatbuffers::Offset<GatherNdOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<GatherNdOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<GatherNdOptions> CreateGatherNdOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  GatherNdOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<GatherNdOptions> CreateGatherNdOptions(flatbuffers::FlatBufferBuilder &_fbb, const GatherNdOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct WhereOptionsT : public flatbuffers::NativeTable {
+  typedef WhereOptions TableType;
+  WhereOptionsT() {
+  }
+};
+
+struct WhereOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef WhereOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  WhereOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(WhereOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<WhereOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const WhereOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct WhereOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit WhereOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  WhereOptionsBuilder &operator=(const WhereOptionsBuilder &);
+  flatbuffers::Offset<WhereOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<WhereOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<WhereOptions> CreateWhereOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  WhereOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<WhereOptions> CreateWhereOptions(flatbuffers::FlatBufferBuilder &_fbb, const WhereOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ReverseSequenceOptionsT : public flatbuffers::NativeTable {
+  typedef ReverseSequenceOptions TableType;
+  int32_t seq_dim;
+  int32_t batch_dim;
+  ReverseSequenceOptionsT()
+      : seq_dim(0),
+        batch_dim(0) {
+  }
+};
+
+struct ReverseSequenceOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ReverseSequenceOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_SEQ_DIM = 4,
+    VT_BATCH_DIM = 6
+  };
+  int32_t seq_dim() const {
+    return GetField<int32_t>(VT_SEQ_DIM, 0);
+  }
+  int32_t batch_dim() const {
+    return GetField<int32_t>(VT_BATCH_DIM, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_SEQ_DIM) &&
+           VerifyField<int32_t>(verifier, VT_BATCH_DIM) &&
+           verifier.EndTable();
+  }
+  ReverseSequenceOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ReverseSequenceOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ReverseSequenceOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ReverseSequenceOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ReverseSequenceOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_seq_dim(int32_t seq_dim) {
+    fbb_.AddElement<int32_t>(ReverseSequenceOptions::VT_SEQ_DIM, seq_dim, 0);
+  }
+  void add_batch_dim(int32_t batch_dim) {
+    fbb_.AddElement<int32_t>(ReverseSequenceOptions::VT_BATCH_DIM, batch_dim, 0);
+  }
+  explicit ReverseSequenceOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ReverseSequenceOptionsBuilder &operator=(const ReverseSequenceOptionsBuilder &);
+  flatbuffers::Offset<ReverseSequenceOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ReverseSequenceOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ReverseSequenceOptions> CreateReverseSequenceOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t seq_dim = 0,
+    int32_t batch_dim = 0) {
+  ReverseSequenceOptionsBuilder builder_(_fbb);
+  builder_.add_batch_dim(batch_dim);
+  builder_.add_seq_dim(seq_dim);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<ReverseSequenceOptions> CreateReverseSequenceOptions(flatbuffers::FlatBufferBuilder &_fbb, const ReverseSequenceOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct MatrixDiagOptionsT : public flatbuffers::NativeTable {
+  typedef MatrixDiagOptions TableType;
+  MatrixDiagOptionsT() {
+  }
+};
+
+struct MatrixDiagOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef MatrixDiagOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  MatrixDiagOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(MatrixDiagOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<MatrixDiagOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const MatrixDiagOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct MatrixDiagOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit MatrixDiagOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  MatrixDiagOptionsBuilder &operator=(const MatrixDiagOptionsBuilder &);
+  flatbuffers::Offset<MatrixDiagOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<MatrixDiagOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<MatrixDiagOptions> CreateMatrixDiagOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  MatrixDiagOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<MatrixDiagOptions> CreateMatrixDiagOptions(flatbuffers::FlatBufferBuilder &_fbb, const MatrixDiagOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct QuantizeOptionsT : public flatbuffers::NativeTable {
+  typedef QuantizeOptions TableType;
+  QuantizeOptionsT() {
+  }
+};
+
+struct QuantizeOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef QuantizeOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  QuantizeOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(QuantizeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<QuantizeOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const QuantizeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct QuantizeOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit QuantizeOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  QuantizeOptionsBuilder &operator=(const QuantizeOptionsBuilder &);
+  flatbuffers::Offset<QuantizeOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<QuantizeOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<QuantizeOptions> CreateQuantizeOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  QuantizeOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<QuantizeOptions> CreateQuantizeOptions(flatbuffers::FlatBufferBuilder &_fbb, const QuantizeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct MatrixSetDiagOptionsT : public flatbuffers::NativeTable {
+  typedef MatrixSetDiagOptions TableType;
+  MatrixSetDiagOptionsT() {
+  }
+};
+
+struct MatrixSetDiagOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef MatrixSetDiagOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  MatrixSetDiagOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(MatrixSetDiagOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<MatrixSetDiagOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const MatrixSetDiagOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct MatrixSetDiagOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit MatrixSetDiagOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  MatrixSetDiagOptionsBuilder &operator=(const MatrixSetDiagOptionsBuilder &);
+  flatbuffers::Offset<MatrixSetDiagOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<MatrixSetDiagOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<MatrixSetDiagOptions> CreateMatrixSetDiagOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  MatrixSetDiagOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<MatrixSetDiagOptions> CreateMatrixSetDiagOptions(flatbuffers::FlatBufferBuilder &_fbb, const MatrixSetDiagOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct IfOptionsT : public flatbuffers::NativeTable {
+  typedef IfOptions TableType;
+  int32_t then_subgraph_index;
+  int32_t else_subgraph_index;
+  IfOptionsT()
+      : then_subgraph_index(0),
+        else_subgraph_index(0) {
+  }
+};
+
+struct IfOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef IfOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_THEN_SUBGRAPH_INDEX = 4,
+    VT_ELSE_SUBGRAPH_INDEX = 6
+  };
+  int32_t then_subgraph_index() const {
+    return GetField<int32_t>(VT_THEN_SUBGRAPH_INDEX, 0);
+  }
+  int32_t else_subgraph_index() const {
+    return GetField<int32_t>(VT_ELSE_SUBGRAPH_INDEX, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_THEN_SUBGRAPH_INDEX) &&
+           VerifyField<int32_t>(verifier, VT_ELSE_SUBGRAPH_INDEX) &&
+           verifier.EndTable();
+  }
+  IfOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(IfOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<IfOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const IfOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct IfOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_then_subgraph_index(int32_t then_subgraph_index) {
+    fbb_.AddElement<int32_t>(IfOptions::VT_THEN_SUBGRAPH_INDEX, then_subgraph_index, 0);
+  }
+  void add_else_subgraph_index(int32_t else_subgraph_index) {
+    fbb_.AddElement<int32_t>(IfOptions::VT_ELSE_SUBGRAPH_INDEX, else_subgraph_index, 0);
+  }
+  explicit IfOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  IfOptionsBuilder &operator=(const IfOptionsBuilder &);
+  flatbuffers::Offset<IfOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<IfOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<IfOptions> CreateIfOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t then_subgraph_index = 0,
+    int32_t else_subgraph_index = 0) {
+  IfOptionsBuilder builder_(_fbb);
+  builder_.add_else_subgraph_index(else_subgraph_index);
+  builder_.add_then_subgraph_index(then_subgraph_index);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<IfOptions> CreateIfOptions(flatbuffers::FlatBufferBuilder &_fbb, const IfOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct WhileOptionsT : public flatbuffers::NativeTable {
+  typedef WhileOptions TableType;
+  int32_t cond_subgraph_index;
+  int32_t body_subgraph_index;
+  WhileOptionsT()
+      : cond_subgraph_index(0),
+        body_subgraph_index(0) {
+  }
+};
+
+struct WhileOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef WhileOptionsT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_COND_SUBGRAPH_INDEX = 4,
+    VT_BODY_SUBGRAPH_INDEX = 6
+  };
+  int32_t cond_subgraph_index() const {
+    return GetField<int32_t>(VT_COND_SUBGRAPH_INDEX, 0);
+  }
+  int32_t body_subgraph_index() const {
+    return GetField<int32_t>(VT_BODY_SUBGRAPH_INDEX, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int32_t>(verifier, VT_COND_SUBGRAPH_INDEX) &&
+           VerifyField<int32_t>(verifier, VT_BODY_SUBGRAPH_INDEX) &&
+           verifier.EndTable();
+  }
+  WhileOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(WhileOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<WhileOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const WhileOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct WhileOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_cond_subgraph_index(int32_t cond_subgraph_index) {
+    fbb_.AddElement<int32_t>(WhileOptions::VT_COND_SUBGRAPH_INDEX, cond_subgraph_index, 0);
+  }
+  void add_body_subgraph_index(int32_t body_subgraph_index) {
+    fbb_.AddElement<int32_t>(WhileOptions::VT_BODY_SUBGRAPH_INDEX, body_subgraph_index, 0);
+  }
+  explicit WhileOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  WhileOptionsBuilder &operator=(const WhileOptionsBuilder &);
+  flatbuffers::Offset<WhileOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<WhileOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<WhileOptions> CreateWhileOptions(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    int32_t cond_subgraph_index = 0,
+    int32_t body_subgraph_index = 0) {
+  WhileOptionsBuilder builder_(_fbb);
+  builder_.add_body_subgraph_index(body_subgraph_index);
+  builder_.add_cond_subgraph_index(cond_subgraph_index);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<WhileOptions> CreateWhileOptions(flatbuffers::FlatBufferBuilder &_fbb, const WhileOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct NonMaxSuppressionV4OptionsT : public flatbuffers::NativeTable {
+  typedef NonMaxSuppressionV4Options TableType;
+  NonMaxSuppressionV4OptionsT() {
+  }
+};
+
+struct NonMaxSuppressionV4Options FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef NonMaxSuppressionV4OptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  NonMaxSuppressionV4OptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(NonMaxSuppressionV4OptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<NonMaxSuppressionV4Options> Pack(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV4OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct NonMaxSuppressionV4OptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit NonMaxSuppressionV4OptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  NonMaxSuppressionV4OptionsBuilder &operator=(const NonMaxSuppressionV4OptionsBuilder &);
+  flatbuffers::Offset<NonMaxSuppressionV4Options> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<NonMaxSuppressionV4Options>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<NonMaxSuppressionV4Options> CreateNonMaxSuppressionV4Options(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  NonMaxSuppressionV4OptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<NonMaxSuppressionV4Options> CreateNonMaxSuppressionV4Options(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV4OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct NonMaxSuppressionV5OptionsT : public flatbuffers::NativeTable {
+  typedef NonMaxSuppressionV5Options TableType;
+  NonMaxSuppressionV5OptionsT() {
+  }
+};
+
+struct NonMaxSuppressionV5Options FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef NonMaxSuppressionV5OptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  NonMaxSuppressionV5OptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(NonMaxSuppressionV5OptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<NonMaxSuppressionV5Options> Pack(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV5OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct NonMaxSuppressionV5OptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit NonMaxSuppressionV5OptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  NonMaxSuppressionV5OptionsBuilder &operator=(const NonMaxSuppressionV5OptionsBuilder &);
+  flatbuffers::Offset<NonMaxSuppressionV5Options> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<NonMaxSuppressionV5Options>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<NonMaxSuppressionV5Options> CreateNonMaxSuppressionV5Options(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  NonMaxSuppressionV5OptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<NonMaxSuppressionV5Options> CreateNonMaxSuppressionV5Options(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV5OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ScatterNdOptionsT : public flatbuffers::NativeTable {
+  typedef ScatterNdOptions TableType;
+  ScatterNdOptionsT() {
+  }
+};
+
+struct ScatterNdOptions FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ScatterNdOptionsT NativeTableType;
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           verifier.EndTable();
+  }
+  ScatterNdOptionsT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ScatterNdOptionsT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<ScatterNdOptions> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ScatterNdOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ScatterNdOptionsBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  explicit ScatterNdOptionsBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ScatterNdOptionsBuilder &operator=(const ScatterNdOptionsBuilder &);
+  flatbuffers::Offset<ScatterNdOptions> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<ScatterNdOptions>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<ScatterNdOptions> CreateScatterNdOptions(
+    flatbuffers::FlatBufferBuilder &_fbb) {
+  ScatterNdOptionsBuilder builder_(_fbb);
+  return builder_.Finish();
+}
+
+flatbuffers::Offset<ScatterNdOptions> CreateScatterNdOptions(flatbuffers::FlatBufferBuilder &_fbb, const ScatterNdOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct OperatorCodeT : public flatbuffers::NativeTable {
+  typedef OperatorCode TableType;
+  BuiltinOperator builtin_code;
+  std::string custom_code;
+  int32_t version;
+  OperatorCodeT()
+      : builtin_code(BuiltinOperator_ADD),
+        version(1) {
+  }
+};
+
+struct OperatorCode FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef OperatorCodeT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_BUILTIN_CODE = 4,
+    VT_CUSTOM_CODE = 6,
+    VT_VERSION = 8
+  };
+  BuiltinOperator builtin_code() const {
+    return static_cast<BuiltinOperator>(GetField<int8_t>(VT_BUILTIN_CODE, 0));
+  }
+  const flatbuffers::String *custom_code() const {
+    return GetPointer<const flatbuffers::String *>(VT_CUSTOM_CODE);
+  }
+  int32_t version() const {
+    return GetField<int32_t>(VT_VERSION, 1);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<int8_t>(verifier, VT_BUILTIN_CODE) &&
+           VerifyOffset(verifier, VT_CUSTOM_CODE) &&
+           verifier.VerifyString(custom_code()) &&
+           VerifyField<int32_t>(verifier, VT_VERSION) &&
+           verifier.EndTable();
+  }
+  OperatorCodeT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(OperatorCodeT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<OperatorCode> Pack(flatbuffers::FlatBufferBuilder &_fbb, const OperatorCodeT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct OperatorCodeBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_builtin_code(BuiltinOperator builtin_code) {
+    fbb_.AddElement<int8_t>(OperatorCode::VT_BUILTIN_CODE, static_cast<int8_t>(builtin_code), 0);
+  }
+  void add_custom_code(flatbuffers::Offset<flatbuffers::String> custom_code) {
+    fbb_.AddOffset(OperatorCode::VT_CUSTOM_CODE, custom_code);
+  }
+  void add_version(int32_t version) {
+    fbb_.AddElement<int32_t>(OperatorCode::VT_VERSION, version, 1);
+  }
+  explicit OperatorCodeBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  OperatorCodeBuilder &operator=(const OperatorCodeBuilder &);
+  flatbuffers::Offset<OperatorCode> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<OperatorCode>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<OperatorCode> CreateOperatorCode(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    BuiltinOperator builtin_code = BuiltinOperator_ADD,
+    flatbuffers::Offset<flatbuffers::String> custom_code = 0,
+    int32_t version = 1) {
+  OperatorCodeBuilder builder_(_fbb);
+  builder_.add_version(version);
+  builder_.add_custom_code(custom_code);
+  builder_.add_builtin_code(builtin_code);
+  return builder_.Finish();
+}
+
+inline flatbuffers::Offset<OperatorCode> CreateOperatorCodeDirect(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    BuiltinOperator builtin_code = BuiltinOperator_ADD,
+    const char *custom_code = nullptr,
+    int32_t version = 1) {
+  auto custom_code__ = custom_code ? _fbb.CreateString(custom_code) : 0;
+  return tflite::CreateOperatorCode(
+      _fbb,
+      builtin_code,
+      custom_code__,
+      version);
+}
+
+flatbuffers::Offset<OperatorCode> CreateOperatorCode(flatbuffers::FlatBufferBuilder &_fbb, const OperatorCodeT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct OperatorT : public flatbuffers::NativeTable {
+  typedef Operator TableType;
+  uint32_t opcode_index;
+  std::vector<int32_t> inputs;
+  std::vector<int32_t> outputs;
+  BuiltinOptionsUnion builtin_options;
+  std::vector<uint8_t> custom_options;
+  CustomOptionsFormat custom_options_format;
+  std::vector<bool> mutating_variable_inputs;
+  std::vector<int32_t> intermediates;
+  OperatorT()
+      : opcode_index(0),
+        custom_options_format(CustomOptionsFormat_FLEXBUFFERS) {
+  }
+};
+
+struct Operator FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef OperatorT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_OPCODE_INDEX = 4,
+    VT_INPUTS = 6,
+    VT_OUTPUTS = 8,
+    VT_BUILTIN_OPTIONS_TYPE = 10,
+    VT_BUILTIN_OPTIONS = 12,
+    VT_CUSTOM_OPTIONS = 14,
+    VT_CUSTOM_OPTIONS_FORMAT = 16,
+    VT_MUTATING_VARIABLE_INPUTS = 18,
+    VT_INTERMEDIATES = 20
+  };
+  uint32_t opcode_index() const {
+    return GetField<uint32_t>(VT_OPCODE_INDEX, 0);
+  }
+  const flatbuffers::Vector<int32_t> *inputs() const {
+    return GetPointer<const flatbuffers::Vector<int32_t> *>(VT_INPUTS);
+  }
+  const flatbuffers::Vector<int32_t> *outputs() const {
+    return GetPointer<const flatbuffers::Vector<int32_t> *>(VT_OUTPUTS);
+  }
+  BuiltinOptions builtin_options_type() const {
+    return static_cast<BuiltinOptions>(GetField<uint8_t>(VT_BUILTIN_OPTIONS_TYPE, 0));
+  }
+  const void *builtin_options() const {
+    return GetPointer<const void *>(VT_BUILTIN_OPTIONS);
+  }
+  template<typename T> const T *builtin_options_as() const;
+  const Conv2DOptions *builtin_options_as_Conv2DOptions() const {
+    return builtin_options_type() == BuiltinOptions_Conv2DOptions ? static_cast<const Conv2DOptions *>(builtin_options()) : nullptr;
+  }
+  const DepthwiseConv2DOptions *builtin_options_as_DepthwiseConv2DOptions() const {
+    return builtin_options_type() == BuiltinOptions_DepthwiseConv2DOptions ? static_cast<const DepthwiseConv2DOptions *>(builtin_options()) : nullptr;
+  }
+  const ConcatEmbeddingsOptions *builtin_options_as_ConcatEmbeddingsOptions() const {
+    return builtin_options_type() == BuiltinOptions_ConcatEmbeddingsOptions ? static_cast<const ConcatEmbeddingsOptions *>(builtin_options()) : nullptr;
+  }
+  const LSHProjectionOptions *builtin_options_as_LSHProjectionOptions() const {
+    return builtin_options_type() == BuiltinOptions_LSHProjectionOptions ? static_cast<const LSHProjectionOptions *>(builtin_options()) : nullptr;
+  }
+  const Pool2DOptions *builtin_options_as_Pool2DOptions() const {
+    return builtin_options_type() == BuiltinOptions_Pool2DOptions ? static_cast<const Pool2DOptions *>(builtin_options()) : nullptr;
+  }
+  const SVDFOptions *builtin_options_as_SVDFOptions() const {
+    return builtin_options_type() == BuiltinOptions_SVDFOptions ? static_cast<const SVDFOptions *>(builtin_options()) : nullptr;
+  }
+  const RNNOptions *builtin_options_as_RNNOptions() const {
+    return builtin_options_type() == BuiltinOptions_RNNOptions ? static_cast<const RNNOptions *>(builtin_options()) : nullptr;
+  }
+  const FullyConnectedOptions *builtin_options_as_FullyConnectedOptions() const {
+    return builtin_options_type() == BuiltinOptions_FullyConnectedOptions ? static_cast<const FullyConnectedOptions *>(builtin_options()) : nullptr;
+  }
+  const SoftmaxOptions *builtin_options_as_SoftmaxOptions() const {
+    return builtin_options_type() == BuiltinOptions_SoftmaxOptions ? static_cast<const SoftmaxOptions *>(builtin_options()) : nullptr;
+  }
+  const ConcatenationOptions *builtin_options_as_ConcatenationOptions() const {
+    return builtin_options_type() == BuiltinOptions_ConcatenationOptions ? static_cast<const ConcatenationOptions *>(builtin_options()) : nullptr;
+  }
+  const AddOptions *builtin_options_as_AddOptions() const {
+    return builtin_options_type() == BuiltinOptions_AddOptions ? static_cast<const AddOptions *>(builtin_options()) : nullptr;
+  }
+  const L2NormOptions *builtin_options_as_L2NormOptions() const {
+    return builtin_options_type() == BuiltinOptions_L2NormOptions ? static_cast<const L2NormOptions *>(builtin_options()) : nullptr;
+  }
+  const LocalResponseNormalizationOptions *builtin_options_as_LocalResponseNormalizationOptions() const {
+    return builtin_options_type() == BuiltinOptions_LocalResponseNormalizationOptions ? static_cast<const LocalResponseNormalizationOptions *>(builtin_options()) : nullptr;
+  }
+  const LSTMOptions *builtin_options_as_LSTMOptions() const {
+    return builtin_options_type() == BuiltinOptions_LSTMOptions ? static_cast<const LSTMOptions *>(builtin_options()) : nullptr;
+  }
+  const ResizeBilinearOptions *builtin_options_as_ResizeBilinearOptions() const {
+    return builtin_options_type() == BuiltinOptions_ResizeBilinearOptions ? static_cast<const ResizeBilinearOptions *>(builtin_options()) : nullptr;
+  }
+  const CallOptions *builtin_options_as_CallOptions() const {
+    return builtin_options_type() == BuiltinOptions_CallOptions ? static_cast<const CallOptions *>(builtin_options()) : nullptr;
+  }
+  const ReshapeOptions *builtin_options_as_ReshapeOptions() const {
+    return builtin_options_type() == BuiltinOptions_ReshapeOptions ? static_cast<const ReshapeOptions *>(builtin_options()) : nullptr;
+  }
+  const SkipGramOptions *builtin_options_as_SkipGramOptions() const {
+    return builtin_options_type() == BuiltinOptions_SkipGramOptions ? static_cast<const SkipGramOptions *>(builtin_options()) : nullptr;
+  }
+  const SpaceToDepthOptions *builtin_options_as_SpaceToDepthOptions() const {
+    return builtin_options_type() == BuiltinOptions_SpaceToDepthOptions ? static_cast<const SpaceToDepthOptions *>(builtin_options()) : nullptr;
+  }
+  const EmbeddingLookupSparseOptions *builtin_options_as_EmbeddingLookupSparseOptions() const {
+    return builtin_options_type() == BuiltinOptions_EmbeddingLookupSparseOptions ? static_cast<const EmbeddingLookupSparseOptions *>(builtin_options()) : nullptr;
+  }
+  const MulOptions *builtin_options_as_MulOptions() const {
+    return builtin_options_type() == BuiltinOptions_MulOptions ? static_cast<const MulOptions *>(builtin_options()) : nullptr;
+  }
+  const PadOptions *builtin_options_as_PadOptions() const {
+    return builtin_options_type() == BuiltinOptions_PadOptions ? static_cast<const PadOptions *>(builtin_options()) : nullptr;
+  }
+  const GatherOptions *builtin_options_as_GatherOptions() const {
+    return builtin_options_type() == BuiltinOptions_GatherOptions ? static_cast<const GatherOptions *>(builtin_options()) : nullptr;
+  }
+  const BatchToSpaceNDOptions *builtin_options_as_BatchToSpaceNDOptions() const {
+    return builtin_options_type() == BuiltinOptions_BatchToSpaceNDOptions ? static_cast<const BatchToSpaceNDOptions *>(builtin_options()) : nullptr;
+  }
+  const SpaceToBatchNDOptions *builtin_options_as_SpaceToBatchNDOptions() const {
+    return builtin_options_type() == BuiltinOptions_SpaceToBatchNDOptions ? static_cast<const SpaceToBatchNDOptions *>(builtin_options()) : nullptr;
+  }
+  const TransposeOptions *builtin_options_as_TransposeOptions() const {
+    return builtin_options_type() == BuiltinOptions_TransposeOptions ? static_cast<const TransposeOptions *>(builtin_options()) : nullptr;
+  }
+  const ReducerOptions *builtin_options_as_ReducerOptions() const {
+    return builtin_options_type() == BuiltinOptions_ReducerOptions ? static_cast<const ReducerOptions *>(builtin_options()) : nullptr;
+  }
+  const SubOptions *builtin_options_as_SubOptions() const {
+    return builtin_options_type() == BuiltinOptions_SubOptions ? static_cast<const SubOptions *>(builtin_options()) : nullptr;
+  }
+  const DivOptions *builtin_options_as_DivOptions() const {
+    return builtin_options_type() == BuiltinOptions_DivOptions ? static_cast<const DivOptions *>(builtin_options()) : nullptr;
+  }
+  const SqueezeOptions *builtin_options_as_SqueezeOptions() const {
+    return builtin_options_type() == BuiltinOptions_SqueezeOptions ? static_cast<const SqueezeOptions *>(builtin_options()) : nullptr;
+  }
+  const SequenceRNNOptions *builtin_options_as_SequenceRNNOptions() const {
+    return builtin_options_type() == BuiltinOptions_SequenceRNNOptions ? static_cast<const SequenceRNNOptions *>(builtin_options()) : nullptr;
+  }
+  const StridedSliceOptions *builtin_options_as_StridedSliceOptions() const {
+    return builtin_options_type() == BuiltinOptions_StridedSliceOptions ? static_cast<const StridedSliceOptions *>(builtin_options()) : nullptr;
+  }
+  const ExpOptions *builtin_options_as_ExpOptions() const {
+    return builtin_options_type() == BuiltinOptions_ExpOptions ? static_cast<const ExpOptions *>(builtin_options()) : nullptr;
+  }
+  const TopKV2Options *builtin_options_as_TopKV2Options() const {
+    return builtin_options_type() == BuiltinOptions_TopKV2Options ? static_cast<const TopKV2Options *>(builtin_options()) : nullptr;
+  }
+  const SplitOptions *builtin_options_as_SplitOptions() const {
+    return builtin_options_type() == BuiltinOptions_SplitOptions ? static_cast<const SplitOptions *>(builtin_options()) : nullptr;
+  }
+  const LogSoftmaxOptions *builtin_options_as_LogSoftmaxOptions() const {
+    return builtin_options_type() == BuiltinOptions_LogSoftmaxOptions ? static_cast<const LogSoftmaxOptions *>(builtin_options()) : nullptr;
+  }
+  const CastOptions *builtin_options_as_CastOptions() const {
+    return builtin_options_type() == BuiltinOptions_CastOptions ? static_cast<const CastOptions *>(builtin_options()) : nullptr;
+  }
+  const DequantizeOptions *builtin_options_as_DequantizeOptions() const {
+    return builtin_options_type() == BuiltinOptions_DequantizeOptions ? static_cast<const DequantizeOptions *>(builtin_options()) : nullptr;
+  }
+  const MaximumMinimumOptions *builtin_options_as_MaximumMinimumOptions() const {
+    return builtin_options_type() == BuiltinOptions_MaximumMinimumOptions ? static_cast<const MaximumMinimumOptions *>(builtin_options()) : nullptr;
+  }
+  const ArgMaxOptions *builtin_options_as_ArgMaxOptions() const {
+    return builtin_options_type() == BuiltinOptions_ArgMaxOptions ? static_cast<const ArgMaxOptions *>(builtin_options()) : nullptr;
+  }
+  const LessOptions *builtin_options_as_LessOptions() const {
+    return builtin_options_type() == BuiltinOptions_LessOptions ? static_cast<const LessOptions *>(builtin_options()) : nullptr;
+  }
+  const NegOptions *builtin_options_as_NegOptions() const {
+    return builtin_options_type() == BuiltinOptions_NegOptions ? static_cast<const NegOptions *>(builtin_options()) : nullptr;
+  }
+  const PadV2Options *builtin_options_as_PadV2Options() const {
+    return builtin_options_type() == BuiltinOptions_PadV2Options ? static_cast<const PadV2Options *>(builtin_options()) : nullptr;
+  }
+  const GreaterOptions *builtin_options_as_GreaterOptions() const {
+    return builtin_options_type() == BuiltinOptions_GreaterOptions ? static_cast<const GreaterOptions *>(builtin_options()) : nullptr;
+  }
+  const GreaterEqualOptions *builtin_options_as_GreaterEqualOptions() const {
+    return builtin_options_type() == BuiltinOptions_GreaterEqualOptions ? static_cast<const GreaterEqualOptions *>(builtin_options()) : nullptr;
+  }
+  const LessEqualOptions *builtin_options_as_LessEqualOptions() const {
+    return builtin_options_type() == BuiltinOptions_LessEqualOptions ? static_cast<const LessEqualOptions *>(builtin_options()) : nullptr;
+  }
+  const SelectOptions *builtin_options_as_SelectOptions() const {
+    return builtin_options_type() == BuiltinOptions_SelectOptions ? static_cast<const SelectOptions *>(builtin_options()) : nullptr;
+  }
+  const SliceOptions *builtin_options_as_SliceOptions() const {
+    return builtin_options_type() == BuiltinOptions_SliceOptions ? static_cast<const SliceOptions *>(builtin_options()) : nullptr;
+  }
+  const TransposeConvOptions *builtin_options_as_TransposeConvOptions() const {
+    return builtin_options_type() == BuiltinOptions_TransposeConvOptions ? static_cast<const TransposeConvOptions *>(builtin_options()) : nullptr;
+  }
+  const SparseToDenseOptions *builtin_options_as_SparseToDenseOptions() const {
+    return builtin_options_type() == BuiltinOptions_SparseToDenseOptions ? static_cast<const SparseToDenseOptions *>(builtin_options()) : nullptr;
+  }
+  const TileOptions *builtin_options_as_TileOptions() const {
+    return builtin_options_type() == BuiltinOptions_TileOptions ? static_cast<const TileOptions *>(builtin_options()) : nullptr;
+  }
+  const ExpandDimsOptions *builtin_options_as_ExpandDimsOptions() const {
+    return builtin_options_type() == BuiltinOptions_ExpandDimsOptions ? static_cast<const ExpandDimsOptions *>(builtin_options()) : nullptr;
+  }
+  const EqualOptions *builtin_options_as_EqualOptions() const {
+    return builtin_options_type() == BuiltinOptions_EqualOptions ? static_cast<const EqualOptions *>(builtin_options()) : nullptr;
+  }
+  const NotEqualOptions *builtin_options_as_NotEqualOptions() const {
+    return builtin_options_type() == BuiltinOptions_NotEqualOptions ? static_cast<const NotEqualOptions *>(builtin_options()) : nullptr;
+  }
+  const ShapeOptions *builtin_options_as_ShapeOptions() const {
+    return builtin_options_type() == BuiltinOptions_ShapeOptions ? static_cast<const ShapeOptions *>(builtin_options()) : nullptr;
+  }
+  const PowOptions *builtin_options_as_PowOptions() const {
+    return builtin_options_type() == BuiltinOptions_PowOptions ? static_cast<const PowOptions *>(builtin_options()) : nullptr;
+  }
+  const ArgMinOptions *builtin_options_as_ArgMinOptions() const {
+    return builtin_options_type() == BuiltinOptions_ArgMinOptions ? static_cast<const ArgMinOptions *>(builtin_options()) : nullptr;
+  }
+  const FakeQuantOptions *builtin_options_as_FakeQuantOptions() const {
+    return builtin_options_type() == BuiltinOptions_FakeQuantOptions ? static_cast<const FakeQuantOptions *>(builtin_options()) : nullptr;
+  }
+  const PackOptions *builtin_options_as_PackOptions() const {
+    return builtin_options_type() == BuiltinOptions_PackOptions ? static_cast<const PackOptions *>(builtin_options()) : nullptr;
+  }
+  const LogicalOrOptions *builtin_options_as_LogicalOrOptions() const {
+    return builtin_options_type() == BuiltinOptions_LogicalOrOptions ? static_cast<const LogicalOrOptions *>(builtin_options()) : nullptr;
+  }
+  const OneHotOptions *builtin_options_as_OneHotOptions() const {
+    return builtin_options_type() == BuiltinOptions_OneHotOptions ? static_cast<const OneHotOptions *>(builtin_options()) : nullptr;
+  }
+  const LogicalAndOptions *builtin_options_as_LogicalAndOptions() const {
+    return builtin_options_type() == BuiltinOptions_LogicalAndOptions ? static_cast<const LogicalAndOptions *>(builtin_options()) : nullptr;
+  }
+  const LogicalNotOptions *builtin_options_as_LogicalNotOptions() const {
+    return builtin_options_type() == BuiltinOptions_LogicalNotOptions ? static_cast<const LogicalNotOptions *>(builtin_options()) : nullptr;
+  }
+  const UnpackOptions *builtin_options_as_UnpackOptions() const {
+    return builtin_options_type() == BuiltinOptions_UnpackOptions ? static_cast<const UnpackOptions *>(builtin_options()) : nullptr;
+  }
+  const FloorDivOptions *builtin_options_as_FloorDivOptions() const {
+    return builtin_options_type() == BuiltinOptions_FloorDivOptions ? static_cast<const FloorDivOptions *>(builtin_options()) : nullptr;
+  }
+  const SquareOptions *builtin_options_as_SquareOptions() const {
+    return builtin_options_type() == BuiltinOptions_SquareOptions ? static_cast<const SquareOptions *>(builtin_options()) : nullptr;
+  }
+  const ZerosLikeOptions *builtin_options_as_ZerosLikeOptions() const {
+    return builtin_options_type() == BuiltinOptions_ZerosLikeOptions ? static_cast<const ZerosLikeOptions *>(builtin_options()) : nullptr;
+  }
+  const FillOptions *builtin_options_as_FillOptions() const {
+    return builtin_options_type() == BuiltinOptions_FillOptions ? static_cast<const FillOptions *>(builtin_options()) : nullptr;
+  }
+  const BidirectionalSequenceLSTMOptions *builtin_options_as_BidirectionalSequenceLSTMOptions() const {
+    return builtin_options_type() == BuiltinOptions_BidirectionalSequenceLSTMOptions ? static_cast<const BidirectionalSequenceLSTMOptions *>(builtin_options()) : nullptr;
+  }
+  const BidirectionalSequenceRNNOptions *builtin_options_as_BidirectionalSequenceRNNOptions() const {
+    return builtin_options_type() == BuiltinOptions_BidirectionalSequenceRNNOptions ? static_cast<const BidirectionalSequenceRNNOptions *>(builtin_options()) : nullptr;
+  }
+  const UnidirectionalSequenceLSTMOptions *builtin_options_as_UnidirectionalSequenceLSTMOptions() const {
+    return builtin_options_type() == BuiltinOptions_UnidirectionalSequenceLSTMOptions ? static_cast<const UnidirectionalSequenceLSTMOptions *>(builtin_options()) : nullptr;
+  }
+  const FloorModOptions *builtin_options_as_FloorModOptions() const {
+    return builtin_options_type() == BuiltinOptions_FloorModOptions ? static_cast<const FloorModOptions *>(builtin_options()) : nullptr;
+  }
+  const RangeOptions *builtin_options_as_RangeOptions() const {
+    return builtin_options_type() == BuiltinOptions_RangeOptions ? static_cast<const RangeOptions *>(builtin_options()) : nullptr;
+  }
+  const ResizeNearestNeighborOptions *builtin_options_as_ResizeNearestNeighborOptions() const {
+    return builtin_options_type() == BuiltinOptions_ResizeNearestNeighborOptions ? static_cast<const ResizeNearestNeighborOptions *>(builtin_options()) : nullptr;
+  }
+  const LeakyReluOptions *builtin_options_as_LeakyReluOptions() const {
+    return builtin_options_type() == BuiltinOptions_LeakyReluOptions ? static_cast<const LeakyReluOptions *>(builtin_options()) : nullptr;
+  }
+  const SquaredDifferenceOptions *builtin_options_as_SquaredDifferenceOptions() const {
+    return builtin_options_type() == BuiltinOptions_SquaredDifferenceOptions ? static_cast<const SquaredDifferenceOptions *>(builtin_options()) : nullptr;
+  }
+  const MirrorPadOptions *builtin_options_as_MirrorPadOptions() const {
+    return builtin_options_type() == BuiltinOptions_MirrorPadOptions ? static_cast<const MirrorPadOptions *>(builtin_options()) : nullptr;
+  }
+  const AbsOptions *builtin_options_as_AbsOptions() const {
+    return builtin_options_type() == BuiltinOptions_AbsOptions ? static_cast<const AbsOptions *>(builtin_options()) : nullptr;
+  }
+  const SplitVOptions *builtin_options_as_SplitVOptions() const {
+    return builtin_options_type() == BuiltinOptions_SplitVOptions ? static_cast<const SplitVOptions *>(builtin_options()) : nullptr;
+  }
+  const UniqueOptions *builtin_options_as_UniqueOptions() const {
+    return builtin_options_type() == BuiltinOptions_UniqueOptions ? static_cast<const UniqueOptions *>(builtin_options()) : nullptr;
+  }
+  const ReverseV2Options *builtin_options_as_ReverseV2Options() const {
+    return builtin_options_type() == BuiltinOptions_ReverseV2Options ? static_cast<const ReverseV2Options *>(builtin_options()) : nullptr;
+  }
+  const AddNOptions *builtin_options_as_AddNOptions() const {
+    return builtin_options_type() == BuiltinOptions_AddNOptions ? static_cast<const AddNOptions *>(builtin_options()) : nullptr;
+  }
+  const GatherNdOptions *builtin_options_as_GatherNdOptions() const {
+    return builtin_options_type() == BuiltinOptions_GatherNdOptions ? static_cast<const GatherNdOptions *>(builtin_options()) : nullptr;
+  }
+  const CosOptions *builtin_options_as_CosOptions() const {
+    return builtin_options_type() == BuiltinOptions_CosOptions ? static_cast<const CosOptions *>(builtin_options()) : nullptr;
+  }
+  const WhereOptions *builtin_options_as_WhereOptions() const {
+    return builtin_options_type() == BuiltinOptions_WhereOptions ? static_cast<const WhereOptions *>(builtin_options()) : nullptr;
+  }
+  const RankOptions *builtin_options_as_RankOptions() const {
+    return builtin_options_type() == BuiltinOptions_RankOptions ? static_cast<const RankOptions *>(builtin_options()) : nullptr;
+  }
+  const ReverseSequenceOptions *builtin_options_as_ReverseSequenceOptions() const {
+    return builtin_options_type() == BuiltinOptions_ReverseSequenceOptions ? static_cast<const ReverseSequenceOptions *>(builtin_options()) : nullptr;
+  }
+  const MatrixDiagOptions *builtin_options_as_MatrixDiagOptions() const {
+    return builtin_options_type() == BuiltinOptions_MatrixDiagOptions ? static_cast<const MatrixDiagOptions *>(builtin_options()) : nullptr;
+  }
+  const QuantizeOptions *builtin_options_as_QuantizeOptions() const {
+    return builtin_options_type() == BuiltinOptions_QuantizeOptions ? static_cast<const QuantizeOptions *>(builtin_options()) : nullptr;
+  }
+  const MatrixSetDiagOptions *builtin_options_as_MatrixSetDiagOptions() const {
+    return builtin_options_type() == BuiltinOptions_MatrixSetDiagOptions ? static_cast<const MatrixSetDiagOptions *>(builtin_options()) : nullptr;
+  }
+  const HardSwishOptions *builtin_options_as_HardSwishOptions() const {
+    return builtin_options_type() == BuiltinOptions_HardSwishOptions ? static_cast<const HardSwishOptions *>(builtin_options()) : nullptr;
+  }
+  const IfOptions *builtin_options_as_IfOptions() const {
+    return builtin_options_type() == BuiltinOptions_IfOptions ? static_cast<const IfOptions *>(builtin_options()) : nullptr;
+  }
+  const WhileOptions *builtin_options_as_WhileOptions() const {
+    return builtin_options_type() == BuiltinOptions_WhileOptions ? static_cast<const WhileOptions *>(builtin_options()) : nullptr;
+  }
+  const DepthToSpaceOptions *builtin_options_as_DepthToSpaceOptions() const {
+    return builtin_options_type() == BuiltinOptions_DepthToSpaceOptions ? static_cast<const DepthToSpaceOptions *>(builtin_options()) : nullptr;
+  }
+  const NonMaxSuppressionV4Options *builtin_options_as_NonMaxSuppressionV4Options() const {
+    return builtin_options_type() == BuiltinOptions_NonMaxSuppressionV4Options ? static_cast<const NonMaxSuppressionV4Options *>(builtin_options()) : nullptr;
+  }
+  const NonMaxSuppressionV5Options *builtin_options_as_NonMaxSuppressionV5Options() const {
+    return builtin_options_type() == BuiltinOptions_NonMaxSuppressionV5Options ? static_cast<const NonMaxSuppressionV5Options *>(builtin_options()) : nullptr;
+  }
+  const ScatterNdOptions *builtin_options_as_ScatterNdOptions() const {
+    return builtin_options_type() == BuiltinOptions_ScatterNdOptions ? static_cast<const ScatterNdOptions *>(builtin_options()) : nullptr;
+  }
+  const flatbuffers::Vector<uint8_t> *custom_options() const {
+    return GetPointer<const flatbuffers::Vector<uint8_t> *>(VT_CUSTOM_OPTIONS);
+  }
+  CustomOptionsFormat custom_options_format() const {
+    return static_cast<CustomOptionsFormat>(GetField<int8_t>(VT_CUSTOM_OPTIONS_FORMAT, 0));
+  }
+  const flatbuffers::Vector<uint8_t> *mutating_variable_inputs() const {
+    return GetPointer<const flatbuffers::Vector<uint8_t> *>(VT_MUTATING_VARIABLE_INPUTS);
+  }
+  const flatbuffers::Vector<int32_t> *intermediates() const {
+    return GetPointer<const flatbuffers::Vector<int32_t> *>(VT_INTERMEDIATES);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<uint32_t>(verifier, VT_OPCODE_INDEX) &&
+           VerifyOffset(verifier, VT_INPUTS) &&
+           verifier.VerifyVector(inputs()) &&
+           VerifyOffset(verifier, VT_OUTPUTS) &&
+           verifier.VerifyVector(outputs()) &&
+           VerifyField<uint8_t>(verifier, VT_BUILTIN_OPTIONS_TYPE) &&
+           VerifyOffset(verifier, VT_BUILTIN_OPTIONS) &&
+           VerifyBuiltinOptions(verifier, builtin_options(), builtin_options_type()) &&
+           VerifyOffset(verifier, VT_CUSTOM_OPTIONS) &&
+           verifier.VerifyVector(custom_options()) &&
+           VerifyField<int8_t>(verifier, VT_CUSTOM_OPTIONS_FORMAT) &&
+           VerifyOffset(verifier, VT_MUTATING_VARIABLE_INPUTS) &&
+           verifier.VerifyVector(mutating_variable_inputs()) &&
+           VerifyOffset(verifier, VT_INTERMEDIATES) &&
+           verifier.VerifyVector(intermediates()) &&
+           verifier.EndTable();
+  }
+  OperatorT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(OperatorT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<Operator> Pack(flatbuffers::FlatBufferBuilder &_fbb, const OperatorT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+template<> inline const Conv2DOptions *Operator::builtin_options_as<Conv2DOptions>() const {
+  return builtin_options_as_Conv2DOptions();
+}
+
+template<> inline const DepthwiseConv2DOptions *Operator::builtin_options_as<DepthwiseConv2DOptions>() const {
+  return builtin_options_as_DepthwiseConv2DOptions();
+}
+
+template<> inline const ConcatEmbeddingsOptions *Operator::builtin_options_as<ConcatEmbeddingsOptions>() const {
+  return builtin_options_as_ConcatEmbeddingsOptions();
+}
+
+template<> inline const LSHProjectionOptions *Operator::builtin_options_as<LSHProjectionOptions>() const {
+  return builtin_options_as_LSHProjectionOptions();
+}
+
+template<> inline const Pool2DOptions *Operator::builtin_options_as<Pool2DOptions>() const {
+  return builtin_options_as_Pool2DOptions();
+}
+
+template<> inline const SVDFOptions *Operator::builtin_options_as<SVDFOptions>() const {
+  return builtin_options_as_SVDFOptions();
+}
+
+template<> inline const RNNOptions *Operator::builtin_options_as<RNNOptions>() const {
+  return builtin_options_as_RNNOptions();
+}
+
+template<> inline const FullyConnectedOptions *Operator::builtin_options_as<FullyConnectedOptions>() const {
+  return builtin_options_as_FullyConnectedOptions();
+}
+
+template<> inline const SoftmaxOptions *Operator::builtin_options_as<SoftmaxOptions>() const {
+  return builtin_options_as_SoftmaxOptions();
+}
+
+template<> inline const ConcatenationOptions *Operator::builtin_options_as<ConcatenationOptions>() const {
+  return builtin_options_as_ConcatenationOptions();
+}
+
+template<> inline const AddOptions *Operator::builtin_options_as<AddOptions>() const {
+  return builtin_options_as_AddOptions();
+}
+
+template<> inline const L2NormOptions *Operator::builtin_options_as<L2NormOptions>() const {
+  return builtin_options_as_L2NormOptions();
+}
+
+template<> inline const LocalResponseNormalizationOptions *Operator::builtin_options_as<LocalResponseNormalizationOptions>() const {
+  return builtin_options_as_LocalResponseNormalizationOptions();
+}
+
+template<> inline const LSTMOptions *Operator::builtin_options_as<LSTMOptions>() const {
+  return builtin_options_as_LSTMOptions();
+}
+
+template<> inline const ResizeBilinearOptions *Operator::builtin_options_as<ResizeBilinearOptions>() const {
+  return builtin_options_as_ResizeBilinearOptions();
+}
+
+template<> inline const CallOptions *Operator::builtin_options_as<CallOptions>() const {
+  return builtin_options_as_CallOptions();
+}
+
+template<> inline const ReshapeOptions *Operator::builtin_options_as<ReshapeOptions>() const {
+  return builtin_options_as_ReshapeOptions();
+}
+
+template<> inline const SkipGramOptions *Operator::builtin_options_as<SkipGramOptions>() const {
+  return builtin_options_as_SkipGramOptions();
+}
+
+template<> inline const SpaceToDepthOptions *Operator::builtin_options_as<SpaceToDepthOptions>() const {
+  return builtin_options_as_SpaceToDepthOptions();
+}
+
+template<> inline const EmbeddingLookupSparseOptions *Operator::builtin_options_as<EmbeddingLookupSparseOptions>() const {
+  return builtin_options_as_EmbeddingLookupSparseOptions();
+}
+
+template<> inline const MulOptions *Operator::builtin_options_as<MulOptions>() const {
+  return builtin_options_as_MulOptions();
+}
+
+template<> inline const PadOptions *Operator::builtin_options_as<PadOptions>() const {
+  return builtin_options_as_PadOptions();
+}
+
+template<> inline const GatherOptions *Operator::builtin_options_as<GatherOptions>() const {
+  return builtin_options_as_GatherOptions();
+}
+
+template<> inline const BatchToSpaceNDOptions *Operator::builtin_options_as<BatchToSpaceNDOptions>() const {
+  return builtin_options_as_BatchToSpaceNDOptions();
+}
+
+template<> inline const SpaceToBatchNDOptions *Operator::builtin_options_as<SpaceToBatchNDOptions>() const {
+  return builtin_options_as_SpaceToBatchNDOptions();
+}
+
+template<> inline const TransposeOptions *Operator::builtin_options_as<TransposeOptions>() const {
+  return builtin_options_as_TransposeOptions();
+}
+
+template<> inline const ReducerOptions *Operator::builtin_options_as<ReducerOptions>() const {
+  return builtin_options_as_ReducerOptions();
+}
+
+template<> inline const SubOptions *Operator::builtin_options_as<SubOptions>() const {
+  return builtin_options_as_SubOptions();
+}
+
+template<> inline const DivOptions *Operator::builtin_options_as<DivOptions>() const {
+  return builtin_options_as_DivOptions();
+}
+
+template<> inline const SqueezeOptions *Operator::builtin_options_as<SqueezeOptions>() const {
+  return builtin_options_as_SqueezeOptions();
+}
+
+template<> inline const SequenceRNNOptions *Operator::builtin_options_as<SequenceRNNOptions>() const {
+  return builtin_options_as_SequenceRNNOptions();
+}
+
+template<> inline const StridedSliceOptions *Operator::builtin_options_as<StridedSliceOptions>() const {
+  return builtin_options_as_StridedSliceOptions();
+}
+
+template<> inline const ExpOptions *Operator::builtin_options_as<ExpOptions>() const {
+  return builtin_options_as_ExpOptions();
+}
+
+template<> inline const TopKV2Options *Operator::builtin_options_as<TopKV2Options>() const {
+  return builtin_options_as_TopKV2Options();
+}
+
+template<> inline const SplitOptions *Operator::builtin_options_as<SplitOptions>() const {
+  return builtin_options_as_SplitOptions();
+}
+
+template<> inline const LogSoftmaxOptions *Operator::builtin_options_as<LogSoftmaxOptions>() const {
+  return builtin_options_as_LogSoftmaxOptions();
+}
+
+template<> inline const CastOptions *Operator::builtin_options_as<CastOptions>() const {
+  return builtin_options_as_CastOptions();
+}
+
+template<> inline const DequantizeOptions *Operator::builtin_options_as<DequantizeOptions>() const {
+  return builtin_options_as_DequantizeOptions();
+}
+
+template<> inline const MaximumMinimumOptions *Operator::builtin_options_as<MaximumMinimumOptions>() const {
+  return builtin_options_as_MaximumMinimumOptions();
+}
+
+template<> inline const ArgMaxOptions *Operator::builtin_options_as<ArgMaxOptions>() const {
+  return builtin_options_as_ArgMaxOptions();
+}
+
+template<> inline const LessOptions *Operator::builtin_options_as<LessOptions>() const {
+  return builtin_options_as_LessOptions();
+}
+
+template<> inline const NegOptions *Operator::builtin_options_as<NegOptions>() const {
+  return builtin_options_as_NegOptions();
+}
+
+template<> inline const PadV2Options *Operator::builtin_options_as<PadV2Options>() const {
+  return builtin_options_as_PadV2Options();
+}
+
+template<> inline const GreaterOptions *Operator::builtin_options_as<GreaterOptions>() const {
+  return builtin_options_as_GreaterOptions();
+}
+
+template<> inline const GreaterEqualOptions *Operator::builtin_options_as<GreaterEqualOptions>() const {
+  return builtin_options_as_GreaterEqualOptions();
+}
+
+template<> inline const LessEqualOptions *Operator::builtin_options_as<LessEqualOptions>() const {
+  return builtin_options_as_LessEqualOptions();
+}
+
+template<> inline const SelectOptions *Operator::builtin_options_as<SelectOptions>() const {
+  return builtin_options_as_SelectOptions();
+}
+
+template<> inline const SliceOptions *Operator::builtin_options_as<SliceOptions>() const {
+  return builtin_options_as_SliceOptions();
+}
+
+template<> inline const TransposeConvOptions *Operator::builtin_options_as<TransposeConvOptions>() const {
+  return builtin_options_as_TransposeConvOptions();
+}
+
+template<> inline const SparseToDenseOptions *Operator::builtin_options_as<SparseToDenseOptions>() const {
+  return builtin_options_as_SparseToDenseOptions();
+}
+
+template<> inline const TileOptions *Operator::builtin_options_as<TileOptions>() const {
+  return builtin_options_as_TileOptions();
+}
+
+template<> inline const ExpandDimsOptions *Operator::builtin_options_as<ExpandDimsOptions>() const {
+  return builtin_options_as_ExpandDimsOptions();
+}
+
+template<> inline const EqualOptions *Operator::builtin_options_as<EqualOptions>() const {
+  return builtin_options_as_EqualOptions();
+}
+
+template<> inline const NotEqualOptions *Operator::builtin_options_as<NotEqualOptions>() const {
+  return builtin_options_as_NotEqualOptions();
+}
+
+template<> inline const ShapeOptions *Operator::builtin_options_as<ShapeOptions>() const {
+  return builtin_options_as_ShapeOptions();
+}
+
+template<> inline const PowOptions *Operator::builtin_options_as<PowOptions>() const {
+  return builtin_options_as_PowOptions();
+}
+
+template<> inline const ArgMinOptions *Operator::builtin_options_as<ArgMinOptions>() const {
+  return builtin_options_as_ArgMinOptions();
+}
+
+template<> inline const FakeQuantOptions *Operator::builtin_options_as<FakeQuantOptions>() const {
+  return builtin_options_as_FakeQuantOptions();
+}
+
+template<> inline const PackOptions *Operator::builtin_options_as<PackOptions>() const {
+  return builtin_options_as_PackOptions();
+}
+
+template<> inline const LogicalOrOptions *Operator::builtin_options_as<LogicalOrOptions>() const {
+  return builtin_options_as_LogicalOrOptions();
+}
+
+template<> inline const OneHotOptions *Operator::builtin_options_as<OneHotOptions>() const {
+  return builtin_options_as_OneHotOptions();
+}
+
+template<> inline const LogicalAndOptions *Operator::builtin_options_as<LogicalAndOptions>() const {
+  return builtin_options_as_LogicalAndOptions();
+}
+
+template<> inline const LogicalNotOptions *Operator::builtin_options_as<LogicalNotOptions>() const {
+  return builtin_options_as_LogicalNotOptions();
+}
+
+template<> inline const UnpackOptions *Operator::builtin_options_as<UnpackOptions>() const {
+  return builtin_options_as_UnpackOptions();
+}
+
+template<> inline const FloorDivOptions *Operator::builtin_options_as<FloorDivOptions>() const {
+  return builtin_options_as_FloorDivOptions();
+}
+
+template<> inline const SquareOptions *Operator::builtin_options_as<SquareOptions>() const {
+  return builtin_options_as_SquareOptions();
+}
+
+template<> inline const ZerosLikeOptions *Operator::builtin_options_as<ZerosLikeOptions>() const {
+  return builtin_options_as_ZerosLikeOptions();
+}
+
+template<> inline const FillOptions *Operator::builtin_options_as<FillOptions>() const {
+  return builtin_options_as_FillOptions();
+}
+
+template<> inline const BidirectionalSequenceLSTMOptions *Operator::builtin_options_as<BidirectionalSequenceLSTMOptions>() const {
+  return builtin_options_as_BidirectionalSequenceLSTMOptions();
+}
+
+template<> inline const BidirectionalSequenceRNNOptions *Operator::builtin_options_as<BidirectionalSequenceRNNOptions>() const {
+  return builtin_options_as_BidirectionalSequenceRNNOptions();
+}
+
+template<> inline const UnidirectionalSequenceLSTMOptions *Operator::builtin_options_as<UnidirectionalSequenceLSTMOptions>() const {
+  return builtin_options_as_UnidirectionalSequenceLSTMOptions();
+}
+
+template<> inline const FloorModOptions *Operator::builtin_options_as<FloorModOptions>() const {
+  return builtin_options_as_FloorModOptions();
+}
+
+template<> inline const RangeOptions *Operator::builtin_options_as<RangeOptions>() const {
+  return builtin_options_as_RangeOptions();
+}
+
+template<> inline const ResizeNearestNeighborOptions *Operator::builtin_options_as<ResizeNearestNeighborOptions>() const {
+  return builtin_options_as_ResizeNearestNeighborOptions();
+}
+
+template<> inline const LeakyReluOptions *Operator::builtin_options_as<LeakyReluOptions>() const {
+  return builtin_options_as_LeakyReluOptions();
+}
+
+template<> inline const SquaredDifferenceOptions *Operator::builtin_options_as<SquaredDifferenceOptions>() const {
+  return builtin_options_as_SquaredDifferenceOptions();
+}
+
+template<> inline const MirrorPadOptions *Operator::builtin_options_as<MirrorPadOptions>() const {
+  return builtin_options_as_MirrorPadOptions();
+}
+
+template<> inline const AbsOptions *Operator::builtin_options_as<AbsOptions>() const {
+  return builtin_options_as_AbsOptions();
+}
+
+template<> inline const SplitVOptions *Operator::builtin_options_as<SplitVOptions>() const {
+  return builtin_options_as_SplitVOptions();
+}
+
+template<> inline const UniqueOptions *Operator::builtin_options_as<UniqueOptions>() const {
+  return builtin_options_as_UniqueOptions();
+}
+
+template<> inline const ReverseV2Options *Operator::builtin_options_as<ReverseV2Options>() const {
+  return builtin_options_as_ReverseV2Options();
+}
+
+template<> inline const AddNOptions *Operator::builtin_options_as<AddNOptions>() const {
+  return builtin_options_as_AddNOptions();
+}
+
+template<> inline const GatherNdOptions *Operator::builtin_options_as<GatherNdOptions>() const {
+  return builtin_options_as_GatherNdOptions();
+}
+
+template<> inline const CosOptions *Operator::builtin_options_as<CosOptions>() const {
+  return builtin_options_as_CosOptions();
+}
+
+template<> inline const WhereOptions *Operator::builtin_options_as<WhereOptions>() const {
+  return builtin_options_as_WhereOptions();
+}
+
+template<> inline const RankOptions *Operator::builtin_options_as<RankOptions>() const {
+  return builtin_options_as_RankOptions();
+}
+
+template<> inline const ReverseSequenceOptions *Operator::builtin_options_as<ReverseSequenceOptions>() const {
+  return builtin_options_as_ReverseSequenceOptions();
+}
+
+template<> inline const MatrixDiagOptions *Operator::builtin_options_as<MatrixDiagOptions>() const {
+  return builtin_options_as_MatrixDiagOptions();
+}
+
+template<> inline const QuantizeOptions *Operator::builtin_options_as<QuantizeOptions>() const {
+  return builtin_options_as_QuantizeOptions();
+}
+
+template<> inline const MatrixSetDiagOptions *Operator::builtin_options_as<MatrixSetDiagOptions>() const {
+  return builtin_options_as_MatrixSetDiagOptions();
+}
+
+template<> inline const HardSwishOptions *Operator::builtin_options_as<HardSwishOptions>() const {
+  return builtin_options_as_HardSwishOptions();
+}
+
+template<> inline const IfOptions *Operator::builtin_options_as<IfOptions>() const {
+  return builtin_options_as_IfOptions();
+}
+
+template<> inline const WhileOptions *Operator::builtin_options_as<WhileOptions>() const {
+  return builtin_options_as_WhileOptions();
+}
+
+template<> inline const DepthToSpaceOptions *Operator::builtin_options_as<DepthToSpaceOptions>() const {
+  return builtin_options_as_DepthToSpaceOptions();
+}
+
+template<> inline const NonMaxSuppressionV4Options *Operator::builtin_options_as<NonMaxSuppressionV4Options>() const {
+  return builtin_options_as_NonMaxSuppressionV4Options();
+}
+
+template<> inline const NonMaxSuppressionV5Options *Operator::builtin_options_as<NonMaxSuppressionV5Options>() const {
+  return builtin_options_as_NonMaxSuppressionV5Options();
+}
+
+template<> inline const ScatterNdOptions *Operator::builtin_options_as<ScatterNdOptions>() const {
+  return builtin_options_as_ScatterNdOptions();
+}
+
+struct OperatorBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_opcode_index(uint32_t opcode_index) {
+    fbb_.AddElement<uint32_t>(Operator::VT_OPCODE_INDEX, opcode_index, 0);
+  }
+  void add_inputs(flatbuffers::Offset<flatbuffers::Vector<int32_t>> inputs) {
+    fbb_.AddOffset(Operator::VT_INPUTS, inputs);
+  }
+  void add_outputs(flatbuffers::Offset<flatbuffers::Vector<int32_t>> outputs) {
+    fbb_.AddOffset(Operator::VT_OUTPUTS, outputs);
+  }
+  void add_builtin_options_type(BuiltinOptions builtin_options_type) {
+    fbb_.AddElement<uint8_t>(Operator::VT_BUILTIN_OPTIONS_TYPE, static_cast<uint8_t>(builtin_options_type), 0);
+  }
+  void add_builtin_options(flatbuffers::Offset<void> builtin_options) {
+    fbb_.AddOffset(Operator::VT_BUILTIN_OPTIONS, builtin_options);
+  }
+  void add_custom_options(flatbuffers::Offset<flatbuffers::Vector<uint8_t>> custom_options) {
+    fbb_.AddOffset(Operator::VT_CUSTOM_OPTIONS, custom_options);
+  }
+  void add_custom_options_format(CustomOptionsFormat custom_options_format) {
+    fbb_.AddElement<int8_t>(Operator::VT_CUSTOM_OPTIONS_FORMAT, static_cast<int8_t>(custom_options_format), 0);
+  }
+  void add_mutating_variable_inputs(flatbuffers::Offset<flatbuffers::Vector<uint8_t>> mutating_variable_inputs) {
+    fbb_.AddOffset(Operator::VT_MUTATING_VARIABLE_INPUTS, mutating_variable_inputs);
+  }
+  void add_intermediates(flatbuffers::Offset<flatbuffers::Vector<int32_t>> intermediates) {
+    fbb_.AddOffset(Operator::VT_INTERMEDIATES, intermediates);
+  }
+  explicit OperatorBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  OperatorBuilder &operator=(const OperatorBuilder &);
+  flatbuffers::Offset<Operator> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<Operator>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<Operator> CreateOperator(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    uint32_t opcode_index = 0,
+    flatbuffers::Offset<flatbuffers::Vector<int32_t>> inputs = 0,
+    flatbuffers::Offset<flatbuffers::Vector<int32_t>> outputs = 0,
+    BuiltinOptions builtin_options_type = BuiltinOptions_NONE,
+    flatbuffers::Offset<void> builtin_options = 0,
+    flatbuffers::Offset<flatbuffers::Vector<uint8_t>> custom_options = 0,
+    CustomOptionsFormat custom_options_format = CustomOptionsFormat_FLEXBUFFERS,
+    flatbuffers::Offset<flatbuffers::Vector<uint8_t>> mutating_variable_inputs = 0,
+    flatbuffers::Offset<flatbuffers::Vector<int32_t>> intermediates = 0) {
+  OperatorBuilder builder_(_fbb);
+  builder_.add_intermediates(intermediates);
+  builder_.add_mutating_variable_inputs(mutating_variable_inputs);
+  builder_.add_custom_options(custom_options);
+  builder_.add_builtin_options(builtin_options);
+  builder_.add_outputs(outputs);
+  builder_.add_inputs(inputs);
+  builder_.add_opcode_index(opcode_index);
+  builder_.add_custom_options_format(custom_options_format);
+  builder_.add_builtin_options_type(builtin_options_type);
+  return builder_.Finish();
+}
+
+inline flatbuffers::Offset<Operator> CreateOperatorDirect(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    uint32_t opcode_index = 0,
+    const std::vector<int32_t> *inputs = nullptr,
+    const std::vector<int32_t> *outputs = nullptr,
+    BuiltinOptions builtin_options_type = BuiltinOptions_NONE,
+    flatbuffers::Offset<void> builtin_options = 0,
+    const std::vector<uint8_t> *custom_options = nullptr,
+    CustomOptionsFormat custom_options_format = CustomOptionsFormat_FLEXBUFFERS,
+    const std::vector<uint8_t> *mutating_variable_inputs = nullptr,
+    const std::vector<int32_t> *intermediates = nullptr) {
+  auto inputs__ = inputs ? _fbb.CreateVector<int32_t>(*inputs) : 0;
+  auto outputs__ = outputs ? _fbb.CreateVector<int32_t>(*outputs) : 0;
+  auto custom_options__ = custom_options ? _fbb.CreateVector<uint8_t>(*custom_options) : 0;
+  auto mutating_variable_inputs__ = mutating_variable_inputs ? _fbb.CreateVector<uint8_t>(*mutating_variable_inputs) : 0;
+  auto intermediates__ = intermediates ? _fbb.CreateVector<int32_t>(*intermediates) : 0;
+  return tflite::CreateOperator(
+      _fbb,
+      opcode_index,
+      inputs__,
+      outputs__,
+      builtin_options_type,
+      builtin_options,
+      custom_options__,
+      custom_options_format,
+      mutating_variable_inputs__,
+      intermediates__);
+}
+
+flatbuffers::Offset<Operator> CreateOperator(flatbuffers::FlatBufferBuilder &_fbb, const OperatorT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct SubGraphT : public flatbuffers::NativeTable {
+  typedef SubGraph TableType;
+  std::vector<std::unique_ptr<TensorT>> tensors;
+  std::vector<int32_t> inputs;
+  std::vector<int32_t> outputs;
+  std::vector<std::unique_ptr<OperatorT>> operators;
+  std::string name;
+  SubGraphT() {
+  }
+};
+
+struct SubGraph FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef SubGraphT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_TENSORS = 4,
+    VT_INPUTS = 6,
+    VT_OUTPUTS = 8,
+    VT_OPERATORS = 10,
+    VT_NAME = 12
+  };
+  const flatbuffers::Vector<flatbuffers::Offset<Tensor>> *tensors() const {
+    return GetPointer<const flatbuffers::Vector<flatbuffers::Offset<Tensor>> *>(VT_TENSORS);
+  }
+  const flatbuffers::Vector<int32_t> *inputs() const {
+    return GetPointer<const flatbuffers::Vector<int32_t> *>(VT_INPUTS);
+  }
+  const flatbuffers::Vector<int32_t> *outputs() const {
+    return GetPointer<const flatbuffers::Vector<int32_t> *>(VT_OUTPUTS);
+  }
+  const flatbuffers::Vector<flatbuffers::Offset<Operator>> *operators() const {
+    return GetPointer<const flatbuffers::Vector<flatbuffers::Offset<Operator>> *>(VT_OPERATORS);
+  }
+  const flatbuffers::String *name() const {
+    return GetPointer<const flatbuffers::String *>(VT_NAME);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyOffset(verifier, VT_TENSORS) &&
+           verifier.VerifyVector(tensors()) &&
+           verifier.VerifyVectorOfTables(tensors()) &&
+           VerifyOffset(verifier, VT_INPUTS) &&
+           verifier.VerifyVector(inputs()) &&
+           VerifyOffset(verifier, VT_OUTPUTS) &&
+           verifier.VerifyVector(outputs()) &&
+           VerifyOffset(verifier, VT_OPERATORS) &&
+           verifier.VerifyVector(operators()) &&
+           verifier.VerifyVectorOfTables(operators()) &&
+           VerifyOffset(verifier, VT_NAME) &&
+           verifier.VerifyString(name()) &&
+           verifier.EndTable();
+  }
+  SubGraphT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(SubGraphT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<SubGraph> Pack(flatbuffers::FlatBufferBuilder &_fbb, const SubGraphT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct SubGraphBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_tensors(flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<Tensor>>> tensors) {
+    fbb_.AddOffset(SubGraph::VT_TENSORS, tensors);
+  }
+  void add_inputs(flatbuffers::Offset<flatbuffers::Vector<int32_t>> inputs) {
+    fbb_.AddOffset(SubGraph::VT_INPUTS, inputs);
+  }
+  void add_outputs(flatbuffers::Offset<flatbuffers::Vector<int32_t>> outputs) {
+    fbb_.AddOffset(SubGraph::VT_OUTPUTS, outputs);
+  }
+  void add_operators(flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<Operator>>> operators) {
+    fbb_.AddOffset(SubGraph::VT_OPERATORS, operators);
+  }
+  void add_name(flatbuffers::Offset<flatbuffers::String> name) {
+    fbb_.AddOffset(SubGraph::VT_NAME, name);
+  }
+  explicit SubGraphBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  SubGraphBuilder &operator=(const SubGraphBuilder &);
+  flatbuffers::Offset<SubGraph> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<SubGraph>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<SubGraph> CreateSubGraph(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<Tensor>>> tensors = 0,
+    flatbuffers::Offset<flatbuffers::Vector<int32_t>> inputs = 0,
+    flatbuffers::Offset<flatbuffers::Vector<int32_t>> outputs = 0,
+    flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<Operator>>> operators = 0,
+    flatbuffers::Offset<flatbuffers::String> name = 0) {
+  SubGraphBuilder builder_(_fbb);
+  builder_.add_name(name);
+  builder_.add_operators(operators);
+  builder_.add_outputs(outputs);
+  builder_.add_inputs(inputs);
+  builder_.add_tensors(tensors);
+  return builder_.Finish();
+}
+
+inline flatbuffers::Offset<SubGraph> CreateSubGraphDirect(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    const std::vector<flatbuffers::Offset<Tensor>> *tensors = nullptr,
+    const std::vector<int32_t> *inputs = nullptr,
+    const std::vector<int32_t> *outputs = nullptr,
+    const std::vector<flatbuffers::Offset<Operator>> *operators = nullptr,
+    const char *name = nullptr) {
+  auto tensors__ = tensors ? _fbb.CreateVector<flatbuffers::Offset<Tensor>>(*tensors) : 0;
+  auto inputs__ = inputs ? _fbb.CreateVector<int32_t>(*inputs) : 0;
+  auto outputs__ = outputs ? _fbb.CreateVector<int32_t>(*outputs) : 0;
+  auto operators__ = operators ? _fbb.CreateVector<flatbuffers::Offset<Operator>>(*operators) : 0;
+  auto name__ = name ? _fbb.CreateString(name) : 0;
+  return tflite::CreateSubGraph(
+      _fbb,
+      tensors__,
+      inputs__,
+      outputs__,
+      operators__,
+      name__);
+}
+
+flatbuffers::Offset<SubGraph> CreateSubGraph(flatbuffers::FlatBufferBuilder &_fbb, const SubGraphT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct BufferT : public flatbuffers::NativeTable {
+  typedef Buffer TableType;
+  std::vector<uint8_t> data;
+  BufferT() {
+  }
+};
+
+struct Buffer FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef BufferT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_DATA = 4
+  };
+  const flatbuffers::Vector<uint8_t> *data() const {
+    return GetPointer<const flatbuffers::Vector<uint8_t> *>(VT_DATA);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyOffset(verifier, VT_DATA) &&
+           verifier.VerifyVector(data()) &&
+           verifier.EndTable();
+  }
+  BufferT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(BufferT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<Buffer> Pack(flatbuffers::FlatBufferBuilder &_fbb, const BufferT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct BufferBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_data(flatbuffers::Offset<flatbuffers::Vector<uint8_t>> data) {
+    fbb_.AddOffset(Buffer::VT_DATA, data);
+  }
+  explicit BufferBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  BufferBuilder &operator=(const BufferBuilder &);
+  flatbuffers::Offset<Buffer> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<Buffer>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<Buffer> CreateBuffer(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    flatbuffers::Offset<flatbuffers::Vector<uint8_t>> data = 0) {
+  BufferBuilder builder_(_fbb);
+  builder_.add_data(data);
+  return builder_.Finish();
+}
+
+inline flatbuffers::Offset<Buffer> CreateBufferDirect(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    const std::vector<uint8_t> *data = nullptr) {
+  auto data__ = data ? _fbb.CreateVector<uint8_t>(*data) : 0;
+  return tflite::CreateBuffer(
+      _fbb,
+      data__);
+}
+
+flatbuffers::Offset<Buffer> CreateBuffer(flatbuffers::FlatBufferBuilder &_fbb, const BufferT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct MetadataT : public flatbuffers::NativeTable {
+  typedef Metadata TableType;
+  std::string name;
+  uint32_t buffer;
+  MetadataT()
+      : buffer(0) {
+  }
+};
+
+struct Metadata FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef MetadataT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_NAME = 4,
+    VT_BUFFER = 6
+  };
+  const flatbuffers::String *name() const {
+    return GetPointer<const flatbuffers::String *>(VT_NAME);
+  }
+  uint32_t buffer() const {
+    return GetField<uint32_t>(VT_BUFFER, 0);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyOffset(verifier, VT_NAME) &&
+           verifier.VerifyString(name()) &&
+           VerifyField<uint32_t>(verifier, VT_BUFFER) &&
+           verifier.EndTable();
+  }
+  MetadataT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(MetadataT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<Metadata> Pack(flatbuffers::FlatBufferBuilder &_fbb, const MetadataT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct MetadataBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_name(flatbuffers::Offset<flatbuffers::String> name) {
+    fbb_.AddOffset(Metadata::VT_NAME, name);
+  }
+  void add_buffer(uint32_t buffer) {
+    fbb_.AddElement<uint32_t>(Metadata::VT_BUFFER, buffer, 0);
+  }
+  explicit MetadataBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  MetadataBuilder &operator=(const MetadataBuilder &);
+  flatbuffers::Offset<Metadata> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<Metadata>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<Metadata> CreateMetadata(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    flatbuffers::Offset<flatbuffers::String> name = 0,
+    uint32_t buffer = 0) {
+  MetadataBuilder builder_(_fbb);
+  builder_.add_buffer(buffer);
+  builder_.add_name(name);
+  return builder_.Finish();
+}
+
+inline flatbuffers::Offset<Metadata> CreateMetadataDirect(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    const char *name = nullptr,
+    uint32_t buffer = 0) {
+  auto name__ = name ? _fbb.CreateString(name) : 0;
+  return tflite::CreateMetadata(
+      _fbb,
+      name__,
+      buffer);
+}
+
+flatbuffers::Offset<Metadata> CreateMetadata(flatbuffers::FlatBufferBuilder &_fbb, const MetadataT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+struct ModelT : public flatbuffers::NativeTable {
+  typedef Model TableType;
+  uint32_t version;
+  std::vector<std::unique_ptr<OperatorCodeT>> operator_codes;
+  std::vector<std::unique_ptr<SubGraphT>> subgraphs;
+  std::string description;
+  std::vector<std::unique_ptr<BufferT>> buffers;
+  std::vector<int32_t> metadata_buffer;
+  std::vector<std::unique_ptr<MetadataT>> metadata;
+  ModelT()
+      : version(0) {
+  }
+};
+
+struct Model FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table {
+  typedef ModelT NativeTableType;
+  enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE {
+    VT_VERSION = 4,
+    VT_OPERATOR_CODES = 6,
+    VT_SUBGRAPHS = 8,
+    VT_DESCRIPTION = 10,
+    VT_BUFFERS = 12,
+    VT_METADATA_BUFFER = 14,
+    VT_METADATA = 16
+  };
+  uint32_t version() const {
+    return GetField<uint32_t>(VT_VERSION, 0);
+  }
+  const flatbuffers::Vector<flatbuffers::Offset<OperatorCode>> *operator_codes() const {
+    return GetPointer<const flatbuffers::Vector<flatbuffers::Offset<OperatorCode>> *>(VT_OPERATOR_CODES);
+  }
+  const flatbuffers::Vector<flatbuffers::Offset<SubGraph>> *subgraphs() const {
+    return GetPointer<const flatbuffers::Vector<flatbuffers::Offset<SubGraph>> *>(VT_SUBGRAPHS);
+  }
+  const flatbuffers::String *description() const {
+    return GetPointer<const flatbuffers::String *>(VT_DESCRIPTION);
+  }
+  const flatbuffers::Vector<flatbuffers::Offset<Buffer>> *buffers() const {
+    return GetPointer<const flatbuffers::Vector<flatbuffers::Offset<Buffer>> *>(VT_BUFFERS);
+  }
+  const flatbuffers::Vector<int32_t> *metadata_buffer() const {
+    return GetPointer<const flatbuffers::Vector<int32_t> *>(VT_METADATA_BUFFER);
+  }
+  const flatbuffers::Vector<flatbuffers::Offset<Metadata>> *metadata() const {
+    return GetPointer<const flatbuffers::Vector<flatbuffers::Offset<Metadata>> *>(VT_METADATA);
+  }
+  bool Verify(flatbuffers::Verifier &verifier) const {
+    return VerifyTableStart(verifier) &&
+           VerifyField<uint32_t>(verifier, VT_VERSION) &&
+           VerifyOffset(verifier, VT_OPERATOR_CODES) &&
+           verifier.VerifyVector(operator_codes()) &&
+           verifier.VerifyVectorOfTables(operator_codes()) &&
+           VerifyOffset(verifier, VT_SUBGRAPHS) &&
+           verifier.VerifyVector(subgraphs()) &&
+           verifier.VerifyVectorOfTables(subgraphs()) &&
+           VerifyOffset(verifier, VT_DESCRIPTION) &&
+           verifier.VerifyString(description()) &&
+           VerifyOffset(verifier, VT_BUFFERS) &&
+           verifier.VerifyVector(buffers()) &&
+           verifier.VerifyVectorOfTables(buffers()) &&
+           VerifyOffset(verifier, VT_METADATA_BUFFER) &&
+           verifier.VerifyVector(metadata_buffer()) &&
+           VerifyOffset(verifier, VT_METADATA) &&
+           verifier.VerifyVector(metadata()) &&
+           verifier.VerifyVectorOfTables(metadata()) &&
+           verifier.EndTable();
+  }
+  ModelT *UnPack(const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  void UnPackTo(ModelT *_o, const flatbuffers::resolver_function_t *_resolver = nullptr) const;
+  static flatbuffers::Offset<Model> Pack(flatbuffers::FlatBufferBuilder &_fbb, const ModelT* _o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+};
+
+struct ModelBuilder {
+  flatbuffers::FlatBufferBuilder &fbb_;
+  flatbuffers::uoffset_t start_;
+  void add_version(uint32_t version) {
+    fbb_.AddElement<uint32_t>(Model::VT_VERSION, version, 0);
+  }
+  void add_operator_codes(flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<OperatorCode>>> operator_codes) {
+    fbb_.AddOffset(Model::VT_OPERATOR_CODES, operator_codes);
+  }
+  void add_subgraphs(flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<SubGraph>>> subgraphs) {
+    fbb_.AddOffset(Model::VT_SUBGRAPHS, subgraphs);
+  }
+  void add_description(flatbuffers::Offset<flatbuffers::String> description) {
+    fbb_.AddOffset(Model::VT_DESCRIPTION, description);
+  }
+  void add_buffers(flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<Buffer>>> buffers) {
+    fbb_.AddOffset(Model::VT_BUFFERS, buffers);
+  }
+  void add_metadata_buffer(flatbuffers::Offset<flatbuffers::Vector<int32_t>> metadata_buffer) {
+    fbb_.AddOffset(Model::VT_METADATA_BUFFER, metadata_buffer);
+  }
+  void add_metadata(flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<Metadata>>> metadata) {
+    fbb_.AddOffset(Model::VT_METADATA, metadata);
+  }
+  explicit ModelBuilder(flatbuffers::FlatBufferBuilder &_fbb)
+        : fbb_(_fbb) {
+    start_ = fbb_.StartTable();
+  }
+  ModelBuilder &operator=(const ModelBuilder &);
+  flatbuffers::Offset<Model> Finish() {
+    const auto end = fbb_.EndTable(start_);
+    auto o = flatbuffers::Offset<Model>(end);
+    return o;
+  }
+};
+
+inline flatbuffers::Offset<Model> CreateModel(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    uint32_t version = 0,
+    flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<OperatorCode>>> operator_codes = 0,
+    flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<SubGraph>>> subgraphs = 0,
+    flatbuffers::Offset<flatbuffers::String> description = 0,
+    flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<Buffer>>> buffers = 0,
+    flatbuffers::Offset<flatbuffers::Vector<int32_t>> metadata_buffer = 0,
+    flatbuffers::Offset<flatbuffers::Vector<flatbuffers::Offset<Metadata>>> metadata = 0) {
+  ModelBuilder builder_(_fbb);
+  builder_.add_metadata(metadata);
+  builder_.add_metadata_buffer(metadata_buffer);
+  builder_.add_buffers(buffers);
+  builder_.add_description(description);
+  builder_.add_subgraphs(subgraphs);
+  builder_.add_operator_codes(operator_codes);
+  builder_.add_version(version);
+  return builder_.Finish();
+}
+
+inline flatbuffers::Offset<Model> CreateModelDirect(
+    flatbuffers::FlatBufferBuilder &_fbb,
+    uint32_t version = 0,
+    const std::vector<flatbuffers::Offset<OperatorCode>> *operator_codes = nullptr,
+    const std::vector<flatbuffers::Offset<SubGraph>> *subgraphs = nullptr,
+    const char *description = nullptr,
+    const std::vector<flatbuffers::Offset<Buffer>> *buffers = nullptr,
+    const std::vector<int32_t> *metadata_buffer = nullptr,
+    const std::vector<flatbuffers::Offset<Metadata>> *metadata = nullptr) {
+  auto operator_codes__ = operator_codes ? _fbb.CreateVector<flatbuffers::Offset<OperatorCode>>(*operator_codes) : 0;
+  auto subgraphs__ = subgraphs ? _fbb.CreateVector<flatbuffers::Offset<SubGraph>>(*subgraphs) : 0;
+  auto description__ = description ? _fbb.CreateString(description) : 0;
+  auto buffers__ = buffers ? _fbb.CreateVector<flatbuffers::Offset<Buffer>>(*buffers) : 0;
+  auto metadata_buffer__ = metadata_buffer ? _fbb.CreateVector<int32_t>(*metadata_buffer) : 0;
+  auto metadata__ = metadata ? _fbb.CreateVector<flatbuffers::Offset<Metadata>>(*metadata) : 0;
+  return tflite::CreateModel(
+      _fbb,
+      version,
+      operator_codes__,
+      subgraphs__,
+      description__,
+      buffers__,
+      metadata_buffer__,
+      metadata__);
+}
+
+flatbuffers::Offset<Model> CreateModel(flatbuffers::FlatBufferBuilder &_fbb, const ModelT *_o, const flatbuffers::rehasher_function_t *_rehasher = nullptr);
+
+inline CustomQuantizationT *CustomQuantization::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new CustomQuantizationT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void CustomQuantization::UnPackTo(CustomQuantizationT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = custom(); if (_e) { _o->custom.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->custom[_i] = _e->Get(_i); } } };
+}
+
+inline flatbuffers::Offset<CustomQuantization> CustomQuantization::Pack(flatbuffers::FlatBufferBuilder &_fbb, const CustomQuantizationT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateCustomQuantization(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<CustomQuantization> CreateCustomQuantization(flatbuffers::FlatBufferBuilder &_fbb, const CustomQuantizationT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const CustomQuantizationT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _custom = _o->custom.size() ? _fbb.CreateVector(_o->custom) : 0;
+  return tflite::CreateCustomQuantization(
+      _fbb,
+      _custom);
+}
+
+inline QuantizationParametersT *QuantizationParameters::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new QuantizationParametersT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void QuantizationParameters::UnPackTo(QuantizationParametersT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = min(); if (_e) { _o->min.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->min[_i] = _e->Get(_i); } } };
+  { auto _e = max(); if (_e) { _o->max.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->max[_i] = _e->Get(_i); } } };
+  { auto _e = scale(); if (_e) { _o->scale.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->scale[_i] = _e->Get(_i); } } };
+  { auto _e = zero_point(); if (_e) { _o->zero_point.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->zero_point[_i] = _e->Get(_i); } } };
+  { auto _e = details_type(); _o->details.type = _e; };
+  { auto _e = details(); if (_e) _o->details.value = QuantizationDetailsUnion::UnPack(_e, details_type(), _resolver); };
+  { auto _e = quantized_dimension(); _o->quantized_dimension = _e; };
+}
+
+inline flatbuffers::Offset<QuantizationParameters> QuantizationParameters::Pack(flatbuffers::FlatBufferBuilder &_fbb, const QuantizationParametersT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateQuantizationParameters(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<QuantizationParameters> CreateQuantizationParameters(flatbuffers::FlatBufferBuilder &_fbb, const QuantizationParametersT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const QuantizationParametersT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _min = _o->min.size() ? _fbb.CreateVector(_o->min) : 0;
+  auto _max = _o->max.size() ? _fbb.CreateVector(_o->max) : 0;
+  auto _scale = _o->scale.size() ? _fbb.CreateVector(_o->scale) : 0;
+  auto _zero_point = _o->zero_point.size() ? _fbb.CreateVector(_o->zero_point) : 0;
+  auto _details_type = _o->details.type;
+  auto _details = _o->details.Pack(_fbb);
+  auto _quantized_dimension = _o->quantized_dimension;
+  return tflite::CreateQuantizationParameters(
+      _fbb,
+      _min,
+      _max,
+      _scale,
+      _zero_point,
+      _details_type,
+      _details,
+      _quantized_dimension);
+}
+
+inline TensorT *Tensor::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new TensorT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void Tensor::UnPackTo(TensorT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = shape(); if (_e) { _o->shape.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->shape[_i] = _e->Get(_i); } } };
+  { auto _e = type(); _o->type = _e; };
+  { auto _e = buffer(); _o->buffer = _e; };
+  { auto _e = name(); if (_e) _o->name = _e->str(); };
+  { auto _e = quantization(); if (_e) _o->quantization = std::unique_ptr<QuantizationParametersT>(_e->UnPack(_resolver)); };
+  { auto _e = is_variable(); _o->is_variable = _e; };
+}
+
+inline flatbuffers::Offset<Tensor> Tensor::Pack(flatbuffers::FlatBufferBuilder &_fbb, const TensorT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateTensor(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<Tensor> CreateTensor(flatbuffers::FlatBufferBuilder &_fbb, const TensorT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const TensorT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _shape = _o->shape.size() ? _fbb.CreateVector(_o->shape) : 0;
+  auto _type = _o->type;
+  auto _buffer = _o->buffer;
+  auto _name = _o->name.empty() ? 0 : _fbb.CreateString(_o->name);
+  auto _quantization = _o->quantization ? CreateQuantizationParameters(_fbb, _o->quantization.get(), _rehasher) : 0;
+  auto _is_variable = _o->is_variable;
+  return tflite::CreateTensor(
+      _fbb,
+      _shape,
+      _type,
+      _buffer,
+      _name,
+      _quantization,
+      _is_variable);
+}
+
+inline Conv2DOptionsT *Conv2DOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new Conv2DOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void Conv2DOptions::UnPackTo(Conv2DOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = padding(); _o->padding = _e; };
+  { auto _e = stride_w(); _o->stride_w = _e; };
+  { auto _e = stride_h(); _o->stride_h = _e; };
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+  { auto _e = dilation_w_factor(); _o->dilation_w_factor = _e; };
+  { auto _e = dilation_h_factor(); _o->dilation_h_factor = _e; };
+}
+
+inline flatbuffers::Offset<Conv2DOptions> Conv2DOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const Conv2DOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateConv2DOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<Conv2DOptions> CreateConv2DOptions(flatbuffers::FlatBufferBuilder &_fbb, const Conv2DOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const Conv2DOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _padding = _o->padding;
+  auto _stride_w = _o->stride_w;
+  auto _stride_h = _o->stride_h;
+  auto _fused_activation_function = _o->fused_activation_function;
+  auto _dilation_w_factor = _o->dilation_w_factor;
+  auto _dilation_h_factor = _o->dilation_h_factor;
+  return tflite::CreateConv2DOptions(
+      _fbb,
+      _padding,
+      _stride_w,
+      _stride_h,
+      _fused_activation_function,
+      _dilation_w_factor,
+      _dilation_h_factor);
+}
+
+inline Pool2DOptionsT *Pool2DOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new Pool2DOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void Pool2DOptions::UnPackTo(Pool2DOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = padding(); _o->padding = _e; };
+  { auto _e = stride_w(); _o->stride_w = _e; };
+  { auto _e = stride_h(); _o->stride_h = _e; };
+  { auto _e = filter_width(); _o->filter_width = _e; };
+  { auto _e = filter_height(); _o->filter_height = _e; };
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+}
+
+inline flatbuffers::Offset<Pool2DOptions> Pool2DOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const Pool2DOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreatePool2DOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<Pool2DOptions> CreatePool2DOptions(flatbuffers::FlatBufferBuilder &_fbb, const Pool2DOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const Pool2DOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _padding = _o->padding;
+  auto _stride_w = _o->stride_w;
+  auto _stride_h = _o->stride_h;
+  auto _filter_width = _o->filter_width;
+  auto _filter_height = _o->filter_height;
+  auto _fused_activation_function = _o->fused_activation_function;
+  return tflite::CreatePool2DOptions(
+      _fbb,
+      _padding,
+      _stride_w,
+      _stride_h,
+      _filter_width,
+      _filter_height,
+      _fused_activation_function);
+}
+
+inline DepthwiseConv2DOptionsT *DepthwiseConv2DOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new DepthwiseConv2DOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void DepthwiseConv2DOptions::UnPackTo(DepthwiseConv2DOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = padding(); _o->padding = _e; };
+  { auto _e = stride_w(); _o->stride_w = _e; };
+  { auto _e = stride_h(); _o->stride_h = _e; };
+  { auto _e = depth_multiplier(); _o->depth_multiplier = _e; };
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+  { auto _e = dilation_w_factor(); _o->dilation_w_factor = _e; };
+  { auto _e = dilation_h_factor(); _o->dilation_h_factor = _e; };
+}
+
+inline flatbuffers::Offset<DepthwiseConv2DOptions> DepthwiseConv2DOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const DepthwiseConv2DOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateDepthwiseConv2DOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<DepthwiseConv2DOptions> CreateDepthwiseConv2DOptions(flatbuffers::FlatBufferBuilder &_fbb, const DepthwiseConv2DOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const DepthwiseConv2DOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _padding = _o->padding;
+  auto _stride_w = _o->stride_w;
+  auto _stride_h = _o->stride_h;
+  auto _depth_multiplier = _o->depth_multiplier;
+  auto _fused_activation_function = _o->fused_activation_function;
+  auto _dilation_w_factor = _o->dilation_w_factor;
+  auto _dilation_h_factor = _o->dilation_h_factor;
+  return tflite::CreateDepthwiseConv2DOptions(
+      _fbb,
+      _padding,
+      _stride_w,
+      _stride_h,
+      _depth_multiplier,
+      _fused_activation_function,
+      _dilation_w_factor,
+      _dilation_h_factor);
+}
+
+inline ConcatEmbeddingsOptionsT *ConcatEmbeddingsOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ConcatEmbeddingsOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ConcatEmbeddingsOptions::UnPackTo(ConcatEmbeddingsOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = num_channels(); _o->num_channels = _e; };
+  { auto _e = num_columns_per_channel(); if (_e) { _o->num_columns_per_channel.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->num_columns_per_channel[_i] = _e->Get(_i); } } };
+  { auto _e = embedding_dim_per_channel(); if (_e) { _o->embedding_dim_per_channel.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->embedding_dim_per_channel[_i] = _e->Get(_i); } } };
+}
+
+inline flatbuffers::Offset<ConcatEmbeddingsOptions> ConcatEmbeddingsOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ConcatEmbeddingsOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateConcatEmbeddingsOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ConcatEmbeddingsOptions> CreateConcatEmbeddingsOptions(flatbuffers::FlatBufferBuilder &_fbb, const ConcatEmbeddingsOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ConcatEmbeddingsOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _num_channels = _o->num_channels;
+  auto _num_columns_per_channel = _o->num_columns_per_channel.size() ? _fbb.CreateVector(_o->num_columns_per_channel) : 0;
+  auto _embedding_dim_per_channel = _o->embedding_dim_per_channel.size() ? _fbb.CreateVector(_o->embedding_dim_per_channel) : 0;
+  return tflite::CreateConcatEmbeddingsOptions(
+      _fbb,
+      _num_channels,
+      _num_columns_per_channel,
+      _embedding_dim_per_channel);
+}
+
+inline LSHProjectionOptionsT *LSHProjectionOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new LSHProjectionOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void LSHProjectionOptions::UnPackTo(LSHProjectionOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = type(); _o->type = _e; };
+}
+
+inline flatbuffers::Offset<LSHProjectionOptions> LSHProjectionOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const LSHProjectionOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateLSHProjectionOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<LSHProjectionOptions> CreateLSHProjectionOptions(flatbuffers::FlatBufferBuilder &_fbb, const LSHProjectionOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const LSHProjectionOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _type = _o->type;
+  return tflite::CreateLSHProjectionOptions(
+      _fbb,
+      _type);
+}
+
+inline SVDFOptionsT *SVDFOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SVDFOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SVDFOptions::UnPackTo(SVDFOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = rank(); _o->rank = _e; };
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+}
+
+inline flatbuffers::Offset<SVDFOptions> SVDFOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SVDFOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSVDFOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SVDFOptions> CreateSVDFOptions(flatbuffers::FlatBufferBuilder &_fbb, const SVDFOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SVDFOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _rank = _o->rank;
+  auto _fused_activation_function = _o->fused_activation_function;
+  return tflite::CreateSVDFOptions(
+      _fbb,
+      _rank,
+      _fused_activation_function);
+}
+
+inline RNNOptionsT *RNNOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new RNNOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void RNNOptions::UnPackTo(RNNOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+}
+
+inline flatbuffers::Offset<RNNOptions> RNNOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const RNNOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateRNNOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<RNNOptions> CreateRNNOptions(flatbuffers::FlatBufferBuilder &_fbb, const RNNOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const RNNOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _fused_activation_function = _o->fused_activation_function;
+  return tflite::CreateRNNOptions(
+      _fbb,
+      _fused_activation_function);
+}
+
+inline SequenceRNNOptionsT *SequenceRNNOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SequenceRNNOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SequenceRNNOptions::UnPackTo(SequenceRNNOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = time_major(); _o->time_major = _e; };
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+}
+
+inline flatbuffers::Offset<SequenceRNNOptions> SequenceRNNOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SequenceRNNOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSequenceRNNOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SequenceRNNOptions> CreateSequenceRNNOptions(flatbuffers::FlatBufferBuilder &_fbb, const SequenceRNNOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SequenceRNNOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _time_major = _o->time_major;
+  auto _fused_activation_function = _o->fused_activation_function;
+  return tflite::CreateSequenceRNNOptions(
+      _fbb,
+      _time_major,
+      _fused_activation_function);
+}
+
+inline BidirectionalSequenceRNNOptionsT *BidirectionalSequenceRNNOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new BidirectionalSequenceRNNOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void BidirectionalSequenceRNNOptions::UnPackTo(BidirectionalSequenceRNNOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = time_major(); _o->time_major = _e; };
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+  { auto _e = merge_outputs(); _o->merge_outputs = _e; };
+}
+
+inline flatbuffers::Offset<BidirectionalSequenceRNNOptions> BidirectionalSequenceRNNOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const BidirectionalSequenceRNNOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateBidirectionalSequenceRNNOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<BidirectionalSequenceRNNOptions> CreateBidirectionalSequenceRNNOptions(flatbuffers::FlatBufferBuilder &_fbb, const BidirectionalSequenceRNNOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const BidirectionalSequenceRNNOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _time_major = _o->time_major;
+  auto _fused_activation_function = _o->fused_activation_function;
+  auto _merge_outputs = _o->merge_outputs;
+  return tflite::CreateBidirectionalSequenceRNNOptions(
+      _fbb,
+      _time_major,
+      _fused_activation_function,
+      _merge_outputs);
+}
+
+inline FullyConnectedOptionsT *FullyConnectedOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new FullyConnectedOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void FullyConnectedOptions::UnPackTo(FullyConnectedOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+  { auto _e = weights_format(); _o->weights_format = _e; };
+  { auto _e = keep_num_dims(); _o->keep_num_dims = _e; };
+}
+
+inline flatbuffers::Offset<FullyConnectedOptions> FullyConnectedOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const FullyConnectedOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateFullyConnectedOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<FullyConnectedOptions> CreateFullyConnectedOptions(flatbuffers::FlatBufferBuilder &_fbb, const FullyConnectedOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const FullyConnectedOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _fused_activation_function = _o->fused_activation_function;
+  auto _weights_format = _o->weights_format;
+  auto _keep_num_dims = _o->keep_num_dims;
+  return tflite::CreateFullyConnectedOptions(
+      _fbb,
+      _fused_activation_function,
+      _weights_format,
+      _keep_num_dims);
+}
+
+inline SoftmaxOptionsT *SoftmaxOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SoftmaxOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SoftmaxOptions::UnPackTo(SoftmaxOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = beta(); _o->beta = _e; };
+}
+
+inline flatbuffers::Offset<SoftmaxOptions> SoftmaxOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SoftmaxOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSoftmaxOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SoftmaxOptions> CreateSoftmaxOptions(flatbuffers::FlatBufferBuilder &_fbb, const SoftmaxOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SoftmaxOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _beta = _o->beta;
+  return tflite::CreateSoftmaxOptions(
+      _fbb,
+      _beta);
+}
+
+inline ConcatenationOptionsT *ConcatenationOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ConcatenationOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ConcatenationOptions::UnPackTo(ConcatenationOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = axis(); _o->axis = _e; };
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+}
+
+inline flatbuffers::Offset<ConcatenationOptions> ConcatenationOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ConcatenationOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateConcatenationOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ConcatenationOptions> CreateConcatenationOptions(flatbuffers::FlatBufferBuilder &_fbb, const ConcatenationOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ConcatenationOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _axis = _o->axis;
+  auto _fused_activation_function = _o->fused_activation_function;
+  return tflite::CreateConcatenationOptions(
+      _fbb,
+      _axis,
+      _fused_activation_function);
+}
+
+inline AddOptionsT *AddOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new AddOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void AddOptions::UnPackTo(AddOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+}
+
+inline flatbuffers::Offset<AddOptions> AddOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const AddOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateAddOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<AddOptions> CreateAddOptions(flatbuffers::FlatBufferBuilder &_fbb, const AddOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const AddOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _fused_activation_function = _o->fused_activation_function;
+  return tflite::CreateAddOptions(
+      _fbb,
+      _fused_activation_function);
+}
+
+inline MulOptionsT *MulOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new MulOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void MulOptions::UnPackTo(MulOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+}
+
+inline flatbuffers::Offset<MulOptions> MulOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const MulOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateMulOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<MulOptions> CreateMulOptions(flatbuffers::FlatBufferBuilder &_fbb, const MulOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const MulOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _fused_activation_function = _o->fused_activation_function;
+  return tflite::CreateMulOptions(
+      _fbb,
+      _fused_activation_function);
+}
+
+inline L2NormOptionsT *L2NormOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new L2NormOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void L2NormOptions::UnPackTo(L2NormOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+}
+
+inline flatbuffers::Offset<L2NormOptions> L2NormOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const L2NormOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateL2NormOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<L2NormOptions> CreateL2NormOptions(flatbuffers::FlatBufferBuilder &_fbb, const L2NormOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const L2NormOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _fused_activation_function = _o->fused_activation_function;
+  return tflite::CreateL2NormOptions(
+      _fbb,
+      _fused_activation_function);
+}
+
+inline LocalResponseNormalizationOptionsT *LocalResponseNormalizationOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new LocalResponseNormalizationOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void LocalResponseNormalizationOptions::UnPackTo(LocalResponseNormalizationOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = radius(); _o->radius = _e; };
+  { auto _e = bias(); _o->bias = _e; };
+  { auto _e = alpha(); _o->alpha = _e; };
+  { auto _e = beta(); _o->beta = _e; };
+}
+
+inline flatbuffers::Offset<LocalResponseNormalizationOptions> LocalResponseNormalizationOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const LocalResponseNormalizationOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateLocalResponseNormalizationOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<LocalResponseNormalizationOptions> CreateLocalResponseNormalizationOptions(flatbuffers::FlatBufferBuilder &_fbb, const LocalResponseNormalizationOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const LocalResponseNormalizationOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _radius = _o->radius;
+  auto _bias = _o->bias;
+  auto _alpha = _o->alpha;
+  auto _beta = _o->beta;
+  return tflite::CreateLocalResponseNormalizationOptions(
+      _fbb,
+      _radius,
+      _bias,
+      _alpha,
+      _beta);
+}
+
+inline LSTMOptionsT *LSTMOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new LSTMOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void LSTMOptions::UnPackTo(LSTMOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+  { auto _e = cell_clip(); _o->cell_clip = _e; };
+  { auto _e = proj_clip(); _o->proj_clip = _e; };
+  { auto _e = kernel_type(); _o->kernel_type = _e; };
+}
+
+inline flatbuffers::Offset<LSTMOptions> LSTMOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const LSTMOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateLSTMOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<LSTMOptions> CreateLSTMOptions(flatbuffers::FlatBufferBuilder &_fbb, const LSTMOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const LSTMOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _fused_activation_function = _o->fused_activation_function;
+  auto _cell_clip = _o->cell_clip;
+  auto _proj_clip = _o->proj_clip;
+  auto _kernel_type = _o->kernel_type;
+  return tflite::CreateLSTMOptions(
+      _fbb,
+      _fused_activation_function,
+      _cell_clip,
+      _proj_clip,
+      _kernel_type);
+}
+
+inline UnidirectionalSequenceLSTMOptionsT *UnidirectionalSequenceLSTMOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new UnidirectionalSequenceLSTMOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void UnidirectionalSequenceLSTMOptions::UnPackTo(UnidirectionalSequenceLSTMOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+  { auto _e = cell_clip(); _o->cell_clip = _e; };
+  { auto _e = proj_clip(); _o->proj_clip = _e; };
+  { auto _e = time_major(); _o->time_major = _e; };
+}
+
+inline flatbuffers::Offset<UnidirectionalSequenceLSTMOptions> UnidirectionalSequenceLSTMOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const UnidirectionalSequenceLSTMOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateUnidirectionalSequenceLSTMOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<UnidirectionalSequenceLSTMOptions> CreateUnidirectionalSequenceLSTMOptions(flatbuffers::FlatBufferBuilder &_fbb, const UnidirectionalSequenceLSTMOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const UnidirectionalSequenceLSTMOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _fused_activation_function = _o->fused_activation_function;
+  auto _cell_clip = _o->cell_clip;
+  auto _proj_clip = _o->proj_clip;
+  auto _time_major = _o->time_major;
+  return tflite::CreateUnidirectionalSequenceLSTMOptions(
+      _fbb,
+      _fused_activation_function,
+      _cell_clip,
+      _proj_clip,
+      _time_major);
+}
+
+inline BidirectionalSequenceLSTMOptionsT *BidirectionalSequenceLSTMOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new BidirectionalSequenceLSTMOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void BidirectionalSequenceLSTMOptions::UnPackTo(BidirectionalSequenceLSTMOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+  { auto _e = cell_clip(); _o->cell_clip = _e; };
+  { auto _e = proj_clip(); _o->proj_clip = _e; };
+  { auto _e = merge_outputs(); _o->merge_outputs = _e; };
+  { auto _e = time_major(); _o->time_major = _e; };
+}
+
+inline flatbuffers::Offset<BidirectionalSequenceLSTMOptions> BidirectionalSequenceLSTMOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const BidirectionalSequenceLSTMOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateBidirectionalSequenceLSTMOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<BidirectionalSequenceLSTMOptions> CreateBidirectionalSequenceLSTMOptions(flatbuffers::FlatBufferBuilder &_fbb, const BidirectionalSequenceLSTMOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const BidirectionalSequenceLSTMOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _fused_activation_function = _o->fused_activation_function;
+  auto _cell_clip = _o->cell_clip;
+  auto _proj_clip = _o->proj_clip;
+  auto _merge_outputs = _o->merge_outputs;
+  auto _time_major = _o->time_major;
+  return tflite::CreateBidirectionalSequenceLSTMOptions(
+      _fbb,
+      _fused_activation_function,
+      _cell_clip,
+      _proj_clip,
+      _merge_outputs,
+      _time_major);
+}
+
+inline ResizeBilinearOptionsT *ResizeBilinearOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ResizeBilinearOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ResizeBilinearOptions::UnPackTo(ResizeBilinearOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = align_corners(); _o->align_corners = _e; };
+}
+
+inline flatbuffers::Offset<ResizeBilinearOptions> ResizeBilinearOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ResizeBilinearOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateResizeBilinearOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ResizeBilinearOptions> CreateResizeBilinearOptions(flatbuffers::FlatBufferBuilder &_fbb, const ResizeBilinearOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ResizeBilinearOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _align_corners = _o->align_corners;
+  return tflite::CreateResizeBilinearOptions(
+      _fbb,
+      _align_corners);
+}
+
+inline ResizeNearestNeighborOptionsT *ResizeNearestNeighborOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ResizeNearestNeighborOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ResizeNearestNeighborOptions::UnPackTo(ResizeNearestNeighborOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = align_corners(); _o->align_corners = _e; };
+}
+
+inline flatbuffers::Offset<ResizeNearestNeighborOptions> ResizeNearestNeighborOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ResizeNearestNeighborOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateResizeNearestNeighborOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ResizeNearestNeighborOptions> CreateResizeNearestNeighborOptions(flatbuffers::FlatBufferBuilder &_fbb, const ResizeNearestNeighborOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ResizeNearestNeighborOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _align_corners = _o->align_corners;
+  return tflite::CreateResizeNearestNeighborOptions(
+      _fbb,
+      _align_corners);
+}
+
+inline CallOptionsT *CallOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new CallOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void CallOptions::UnPackTo(CallOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = subgraph(); _o->subgraph = _e; };
+}
+
+inline flatbuffers::Offset<CallOptions> CallOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const CallOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateCallOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<CallOptions> CreateCallOptions(flatbuffers::FlatBufferBuilder &_fbb, const CallOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const CallOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _subgraph = _o->subgraph;
+  return tflite::CreateCallOptions(
+      _fbb,
+      _subgraph);
+}
+
+inline PadOptionsT *PadOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new PadOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void PadOptions::UnPackTo(PadOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<PadOptions> PadOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const PadOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreatePadOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<PadOptions> CreatePadOptions(flatbuffers::FlatBufferBuilder &_fbb, const PadOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const PadOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreatePadOptions(
+      _fbb);
+}
+
+inline PadV2OptionsT *PadV2Options::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new PadV2OptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void PadV2Options::UnPackTo(PadV2OptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<PadV2Options> PadV2Options::Pack(flatbuffers::FlatBufferBuilder &_fbb, const PadV2OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreatePadV2Options(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<PadV2Options> CreatePadV2Options(flatbuffers::FlatBufferBuilder &_fbb, const PadV2OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const PadV2OptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreatePadV2Options(
+      _fbb);
+}
+
+inline ReshapeOptionsT *ReshapeOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ReshapeOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ReshapeOptions::UnPackTo(ReshapeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = new_shape(); if (_e) { _o->new_shape.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->new_shape[_i] = _e->Get(_i); } } };
+}
+
+inline flatbuffers::Offset<ReshapeOptions> ReshapeOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ReshapeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateReshapeOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ReshapeOptions> CreateReshapeOptions(flatbuffers::FlatBufferBuilder &_fbb, const ReshapeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ReshapeOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _new_shape = _o->new_shape.size() ? _fbb.CreateVector(_o->new_shape) : 0;
+  return tflite::CreateReshapeOptions(
+      _fbb,
+      _new_shape);
+}
+
+inline SpaceToBatchNDOptionsT *SpaceToBatchNDOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SpaceToBatchNDOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SpaceToBatchNDOptions::UnPackTo(SpaceToBatchNDOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<SpaceToBatchNDOptions> SpaceToBatchNDOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SpaceToBatchNDOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSpaceToBatchNDOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SpaceToBatchNDOptions> CreateSpaceToBatchNDOptions(flatbuffers::FlatBufferBuilder &_fbb, const SpaceToBatchNDOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SpaceToBatchNDOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateSpaceToBatchNDOptions(
+      _fbb);
+}
+
+inline BatchToSpaceNDOptionsT *BatchToSpaceNDOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new BatchToSpaceNDOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void BatchToSpaceNDOptions::UnPackTo(BatchToSpaceNDOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<BatchToSpaceNDOptions> BatchToSpaceNDOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const BatchToSpaceNDOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateBatchToSpaceNDOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<BatchToSpaceNDOptions> CreateBatchToSpaceNDOptions(flatbuffers::FlatBufferBuilder &_fbb, const BatchToSpaceNDOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const BatchToSpaceNDOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateBatchToSpaceNDOptions(
+      _fbb);
+}
+
+inline SkipGramOptionsT *SkipGramOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SkipGramOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SkipGramOptions::UnPackTo(SkipGramOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = ngram_size(); _o->ngram_size = _e; };
+  { auto _e = max_skip_size(); _o->max_skip_size = _e; };
+  { auto _e = include_all_ngrams(); _o->include_all_ngrams = _e; };
+}
+
+inline flatbuffers::Offset<SkipGramOptions> SkipGramOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SkipGramOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSkipGramOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SkipGramOptions> CreateSkipGramOptions(flatbuffers::FlatBufferBuilder &_fbb, const SkipGramOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SkipGramOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _ngram_size = _o->ngram_size;
+  auto _max_skip_size = _o->max_skip_size;
+  auto _include_all_ngrams = _o->include_all_ngrams;
+  return tflite::CreateSkipGramOptions(
+      _fbb,
+      _ngram_size,
+      _max_skip_size,
+      _include_all_ngrams);
+}
+
+inline SpaceToDepthOptionsT *SpaceToDepthOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SpaceToDepthOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SpaceToDepthOptions::UnPackTo(SpaceToDepthOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = block_size(); _o->block_size = _e; };
+}
+
+inline flatbuffers::Offset<SpaceToDepthOptions> SpaceToDepthOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SpaceToDepthOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSpaceToDepthOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SpaceToDepthOptions> CreateSpaceToDepthOptions(flatbuffers::FlatBufferBuilder &_fbb, const SpaceToDepthOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SpaceToDepthOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _block_size = _o->block_size;
+  return tflite::CreateSpaceToDepthOptions(
+      _fbb,
+      _block_size);
+}
+
+inline DepthToSpaceOptionsT *DepthToSpaceOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new DepthToSpaceOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void DepthToSpaceOptions::UnPackTo(DepthToSpaceOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = block_size(); _o->block_size = _e; };
+}
+
+inline flatbuffers::Offset<DepthToSpaceOptions> DepthToSpaceOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const DepthToSpaceOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateDepthToSpaceOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<DepthToSpaceOptions> CreateDepthToSpaceOptions(flatbuffers::FlatBufferBuilder &_fbb, const DepthToSpaceOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const DepthToSpaceOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _block_size = _o->block_size;
+  return tflite::CreateDepthToSpaceOptions(
+      _fbb,
+      _block_size);
+}
+
+inline SubOptionsT *SubOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SubOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SubOptions::UnPackTo(SubOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+}
+
+inline flatbuffers::Offset<SubOptions> SubOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SubOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSubOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SubOptions> CreateSubOptions(flatbuffers::FlatBufferBuilder &_fbb, const SubOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SubOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _fused_activation_function = _o->fused_activation_function;
+  return tflite::CreateSubOptions(
+      _fbb,
+      _fused_activation_function);
+}
+
+inline DivOptionsT *DivOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new DivOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void DivOptions::UnPackTo(DivOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = fused_activation_function(); _o->fused_activation_function = _e; };
+}
+
+inline flatbuffers::Offset<DivOptions> DivOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const DivOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateDivOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<DivOptions> CreateDivOptions(flatbuffers::FlatBufferBuilder &_fbb, const DivOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const DivOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _fused_activation_function = _o->fused_activation_function;
+  return tflite::CreateDivOptions(
+      _fbb,
+      _fused_activation_function);
+}
+
+inline TopKV2OptionsT *TopKV2Options::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new TopKV2OptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void TopKV2Options::UnPackTo(TopKV2OptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<TopKV2Options> TopKV2Options::Pack(flatbuffers::FlatBufferBuilder &_fbb, const TopKV2OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateTopKV2Options(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<TopKV2Options> CreateTopKV2Options(flatbuffers::FlatBufferBuilder &_fbb, const TopKV2OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const TopKV2OptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateTopKV2Options(
+      _fbb);
+}
+
+inline EmbeddingLookupSparseOptionsT *EmbeddingLookupSparseOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new EmbeddingLookupSparseOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void EmbeddingLookupSparseOptions::UnPackTo(EmbeddingLookupSparseOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = combiner(); _o->combiner = _e; };
+}
+
+inline flatbuffers::Offset<EmbeddingLookupSparseOptions> EmbeddingLookupSparseOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const EmbeddingLookupSparseOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateEmbeddingLookupSparseOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<EmbeddingLookupSparseOptions> CreateEmbeddingLookupSparseOptions(flatbuffers::FlatBufferBuilder &_fbb, const EmbeddingLookupSparseOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const EmbeddingLookupSparseOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _combiner = _o->combiner;
+  return tflite::CreateEmbeddingLookupSparseOptions(
+      _fbb,
+      _combiner);
+}
+
+inline GatherOptionsT *GatherOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new GatherOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void GatherOptions::UnPackTo(GatherOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = axis(); _o->axis = _e; };
+}
+
+inline flatbuffers::Offset<GatherOptions> GatherOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const GatherOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateGatherOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<GatherOptions> CreateGatherOptions(flatbuffers::FlatBufferBuilder &_fbb, const GatherOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const GatherOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _axis = _o->axis;
+  return tflite::CreateGatherOptions(
+      _fbb,
+      _axis);
+}
+
+inline TransposeOptionsT *TransposeOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new TransposeOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void TransposeOptions::UnPackTo(TransposeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<TransposeOptions> TransposeOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const TransposeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateTransposeOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<TransposeOptions> CreateTransposeOptions(flatbuffers::FlatBufferBuilder &_fbb, const TransposeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const TransposeOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateTransposeOptions(
+      _fbb);
+}
+
+inline ExpOptionsT *ExpOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ExpOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ExpOptions::UnPackTo(ExpOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<ExpOptions> ExpOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ExpOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateExpOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ExpOptions> CreateExpOptions(flatbuffers::FlatBufferBuilder &_fbb, const ExpOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ExpOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateExpOptions(
+      _fbb);
+}
+
+inline CosOptionsT *CosOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new CosOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void CosOptions::UnPackTo(CosOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<CosOptions> CosOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const CosOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateCosOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<CosOptions> CreateCosOptions(flatbuffers::FlatBufferBuilder &_fbb, const CosOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const CosOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateCosOptions(
+      _fbb);
+}
+
+inline ReducerOptionsT *ReducerOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ReducerOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ReducerOptions::UnPackTo(ReducerOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = keep_dims(); _o->keep_dims = _e; };
+}
+
+inline flatbuffers::Offset<ReducerOptions> ReducerOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ReducerOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateReducerOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ReducerOptions> CreateReducerOptions(flatbuffers::FlatBufferBuilder &_fbb, const ReducerOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ReducerOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _keep_dims = _o->keep_dims;
+  return tflite::CreateReducerOptions(
+      _fbb,
+      _keep_dims);
+}
+
+inline SqueezeOptionsT *SqueezeOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SqueezeOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SqueezeOptions::UnPackTo(SqueezeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = squeeze_dims(); if (_e) { _o->squeeze_dims.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->squeeze_dims[_i] = _e->Get(_i); } } };
+}
+
+inline flatbuffers::Offset<SqueezeOptions> SqueezeOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SqueezeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSqueezeOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SqueezeOptions> CreateSqueezeOptions(flatbuffers::FlatBufferBuilder &_fbb, const SqueezeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SqueezeOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _squeeze_dims = _o->squeeze_dims.size() ? _fbb.CreateVector(_o->squeeze_dims) : 0;
+  return tflite::CreateSqueezeOptions(
+      _fbb,
+      _squeeze_dims);
+}
+
+inline SplitOptionsT *SplitOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SplitOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SplitOptions::UnPackTo(SplitOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = num_splits(); _o->num_splits = _e; };
+}
+
+inline flatbuffers::Offset<SplitOptions> SplitOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SplitOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSplitOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SplitOptions> CreateSplitOptions(flatbuffers::FlatBufferBuilder &_fbb, const SplitOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SplitOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _num_splits = _o->num_splits;
+  return tflite::CreateSplitOptions(
+      _fbb,
+      _num_splits);
+}
+
+inline SplitVOptionsT *SplitVOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SplitVOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SplitVOptions::UnPackTo(SplitVOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = num_splits(); _o->num_splits = _e; };
+}
+
+inline flatbuffers::Offset<SplitVOptions> SplitVOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SplitVOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSplitVOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SplitVOptions> CreateSplitVOptions(flatbuffers::FlatBufferBuilder &_fbb, const SplitVOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SplitVOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _num_splits = _o->num_splits;
+  return tflite::CreateSplitVOptions(
+      _fbb,
+      _num_splits);
+}
+
+inline StridedSliceOptionsT *StridedSliceOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new StridedSliceOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void StridedSliceOptions::UnPackTo(StridedSliceOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = begin_mask(); _o->begin_mask = _e; };
+  { auto _e = end_mask(); _o->end_mask = _e; };
+  { auto _e = ellipsis_mask(); _o->ellipsis_mask = _e; };
+  { auto _e = new_axis_mask(); _o->new_axis_mask = _e; };
+  { auto _e = shrink_axis_mask(); _o->shrink_axis_mask = _e; };
+}
+
+inline flatbuffers::Offset<StridedSliceOptions> StridedSliceOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const StridedSliceOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateStridedSliceOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<StridedSliceOptions> CreateStridedSliceOptions(flatbuffers::FlatBufferBuilder &_fbb, const StridedSliceOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const StridedSliceOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _begin_mask = _o->begin_mask;
+  auto _end_mask = _o->end_mask;
+  auto _ellipsis_mask = _o->ellipsis_mask;
+  auto _new_axis_mask = _o->new_axis_mask;
+  auto _shrink_axis_mask = _o->shrink_axis_mask;
+  return tflite::CreateStridedSliceOptions(
+      _fbb,
+      _begin_mask,
+      _end_mask,
+      _ellipsis_mask,
+      _new_axis_mask,
+      _shrink_axis_mask);
+}
+
+inline LogSoftmaxOptionsT *LogSoftmaxOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new LogSoftmaxOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void LogSoftmaxOptions::UnPackTo(LogSoftmaxOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<LogSoftmaxOptions> LogSoftmaxOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const LogSoftmaxOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateLogSoftmaxOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<LogSoftmaxOptions> CreateLogSoftmaxOptions(flatbuffers::FlatBufferBuilder &_fbb, const LogSoftmaxOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const LogSoftmaxOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateLogSoftmaxOptions(
+      _fbb);
+}
+
+inline CastOptionsT *CastOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new CastOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void CastOptions::UnPackTo(CastOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = in_data_type(); _o->in_data_type = _e; };
+  { auto _e = out_data_type(); _o->out_data_type = _e; };
+}
+
+inline flatbuffers::Offset<CastOptions> CastOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const CastOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateCastOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<CastOptions> CreateCastOptions(flatbuffers::FlatBufferBuilder &_fbb, const CastOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const CastOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _in_data_type = _o->in_data_type;
+  auto _out_data_type = _o->out_data_type;
+  return tflite::CreateCastOptions(
+      _fbb,
+      _in_data_type,
+      _out_data_type);
+}
+
+inline DequantizeOptionsT *DequantizeOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new DequantizeOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void DequantizeOptions::UnPackTo(DequantizeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<DequantizeOptions> DequantizeOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const DequantizeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateDequantizeOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<DequantizeOptions> CreateDequantizeOptions(flatbuffers::FlatBufferBuilder &_fbb, const DequantizeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const DequantizeOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateDequantizeOptions(
+      _fbb);
+}
+
+inline MaximumMinimumOptionsT *MaximumMinimumOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new MaximumMinimumOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void MaximumMinimumOptions::UnPackTo(MaximumMinimumOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<MaximumMinimumOptions> MaximumMinimumOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const MaximumMinimumOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateMaximumMinimumOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<MaximumMinimumOptions> CreateMaximumMinimumOptions(flatbuffers::FlatBufferBuilder &_fbb, const MaximumMinimumOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const MaximumMinimumOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateMaximumMinimumOptions(
+      _fbb);
+}
+
+inline TileOptionsT *TileOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new TileOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void TileOptions::UnPackTo(TileOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<TileOptions> TileOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const TileOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateTileOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<TileOptions> CreateTileOptions(flatbuffers::FlatBufferBuilder &_fbb, const TileOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const TileOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateTileOptions(
+      _fbb);
+}
+
+inline ArgMaxOptionsT *ArgMaxOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ArgMaxOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ArgMaxOptions::UnPackTo(ArgMaxOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = output_type(); _o->output_type = _e; };
+}
+
+inline flatbuffers::Offset<ArgMaxOptions> ArgMaxOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ArgMaxOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateArgMaxOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ArgMaxOptions> CreateArgMaxOptions(flatbuffers::FlatBufferBuilder &_fbb, const ArgMaxOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ArgMaxOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _output_type = _o->output_type;
+  return tflite::CreateArgMaxOptions(
+      _fbb,
+      _output_type);
+}
+
+inline ArgMinOptionsT *ArgMinOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ArgMinOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ArgMinOptions::UnPackTo(ArgMinOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = output_type(); _o->output_type = _e; };
+}
+
+inline flatbuffers::Offset<ArgMinOptions> ArgMinOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ArgMinOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateArgMinOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ArgMinOptions> CreateArgMinOptions(flatbuffers::FlatBufferBuilder &_fbb, const ArgMinOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ArgMinOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _output_type = _o->output_type;
+  return tflite::CreateArgMinOptions(
+      _fbb,
+      _output_type);
+}
+
+inline GreaterOptionsT *GreaterOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new GreaterOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void GreaterOptions::UnPackTo(GreaterOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<GreaterOptions> GreaterOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const GreaterOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateGreaterOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<GreaterOptions> CreateGreaterOptions(flatbuffers::FlatBufferBuilder &_fbb, const GreaterOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const GreaterOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateGreaterOptions(
+      _fbb);
+}
+
+inline GreaterEqualOptionsT *GreaterEqualOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new GreaterEqualOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void GreaterEqualOptions::UnPackTo(GreaterEqualOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<GreaterEqualOptions> GreaterEqualOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const GreaterEqualOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateGreaterEqualOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<GreaterEqualOptions> CreateGreaterEqualOptions(flatbuffers::FlatBufferBuilder &_fbb, const GreaterEqualOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const GreaterEqualOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateGreaterEqualOptions(
+      _fbb);
+}
+
+inline LessOptionsT *LessOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new LessOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void LessOptions::UnPackTo(LessOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<LessOptions> LessOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const LessOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateLessOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<LessOptions> CreateLessOptions(flatbuffers::FlatBufferBuilder &_fbb, const LessOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const LessOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateLessOptions(
+      _fbb);
+}
+
+inline LessEqualOptionsT *LessEqualOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new LessEqualOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void LessEqualOptions::UnPackTo(LessEqualOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<LessEqualOptions> LessEqualOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const LessEqualOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateLessEqualOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<LessEqualOptions> CreateLessEqualOptions(flatbuffers::FlatBufferBuilder &_fbb, const LessEqualOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const LessEqualOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateLessEqualOptions(
+      _fbb);
+}
+
+inline NegOptionsT *NegOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new NegOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void NegOptions::UnPackTo(NegOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<NegOptions> NegOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const NegOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateNegOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<NegOptions> CreateNegOptions(flatbuffers::FlatBufferBuilder &_fbb, const NegOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const NegOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateNegOptions(
+      _fbb);
+}
+
+inline SelectOptionsT *SelectOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SelectOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SelectOptions::UnPackTo(SelectOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<SelectOptions> SelectOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SelectOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSelectOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SelectOptions> CreateSelectOptions(flatbuffers::FlatBufferBuilder &_fbb, const SelectOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SelectOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateSelectOptions(
+      _fbb);
+}
+
+inline SliceOptionsT *SliceOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SliceOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SliceOptions::UnPackTo(SliceOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<SliceOptions> SliceOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SliceOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSliceOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SliceOptions> CreateSliceOptions(flatbuffers::FlatBufferBuilder &_fbb, const SliceOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SliceOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateSliceOptions(
+      _fbb);
+}
+
+inline TransposeConvOptionsT *TransposeConvOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new TransposeConvOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void TransposeConvOptions::UnPackTo(TransposeConvOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = padding(); _o->padding = _e; };
+  { auto _e = stride_w(); _o->stride_w = _e; };
+  { auto _e = stride_h(); _o->stride_h = _e; };
+}
+
+inline flatbuffers::Offset<TransposeConvOptions> TransposeConvOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const TransposeConvOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateTransposeConvOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<TransposeConvOptions> CreateTransposeConvOptions(flatbuffers::FlatBufferBuilder &_fbb, const TransposeConvOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const TransposeConvOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _padding = _o->padding;
+  auto _stride_w = _o->stride_w;
+  auto _stride_h = _o->stride_h;
+  return tflite::CreateTransposeConvOptions(
+      _fbb,
+      _padding,
+      _stride_w,
+      _stride_h);
+}
+
+inline ExpandDimsOptionsT *ExpandDimsOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ExpandDimsOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ExpandDimsOptions::UnPackTo(ExpandDimsOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<ExpandDimsOptions> ExpandDimsOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ExpandDimsOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateExpandDimsOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ExpandDimsOptions> CreateExpandDimsOptions(flatbuffers::FlatBufferBuilder &_fbb, const ExpandDimsOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ExpandDimsOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateExpandDimsOptions(
+      _fbb);
+}
+
+inline SparseToDenseOptionsT *SparseToDenseOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SparseToDenseOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SparseToDenseOptions::UnPackTo(SparseToDenseOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = validate_indices(); _o->validate_indices = _e; };
+}
+
+inline flatbuffers::Offset<SparseToDenseOptions> SparseToDenseOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SparseToDenseOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSparseToDenseOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SparseToDenseOptions> CreateSparseToDenseOptions(flatbuffers::FlatBufferBuilder &_fbb, const SparseToDenseOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SparseToDenseOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _validate_indices = _o->validate_indices;
+  return tflite::CreateSparseToDenseOptions(
+      _fbb,
+      _validate_indices);
+}
+
+inline EqualOptionsT *EqualOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new EqualOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void EqualOptions::UnPackTo(EqualOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<EqualOptions> EqualOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const EqualOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateEqualOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<EqualOptions> CreateEqualOptions(flatbuffers::FlatBufferBuilder &_fbb, const EqualOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const EqualOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateEqualOptions(
+      _fbb);
+}
+
+inline NotEqualOptionsT *NotEqualOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new NotEqualOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void NotEqualOptions::UnPackTo(NotEqualOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<NotEqualOptions> NotEqualOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const NotEqualOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateNotEqualOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<NotEqualOptions> CreateNotEqualOptions(flatbuffers::FlatBufferBuilder &_fbb, const NotEqualOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const NotEqualOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateNotEqualOptions(
+      _fbb);
+}
+
+inline ShapeOptionsT *ShapeOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ShapeOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ShapeOptions::UnPackTo(ShapeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = out_type(); _o->out_type = _e; };
+}
+
+inline flatbuffers::Offset<ShapeOptions> ShapeOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ShapeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateShapeOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ShapeOptions> CreateShapeOptions(flatbuffers::FlatBufferBuilder &_fbb, const ShapeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ShapeOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _out_type = _o->out_type;
+  return tflite::CreateShapeOptions(
+      _fbb,
+      _out_type);
+}
+
+inline RankOptionsT *RankOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new RankOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void RankOptions::UnPackTo(RankOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<RankOptions> RankOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const RankOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateRankOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<RankOptions> CreateRankOptions(flatbuffers::FlatBufferBuilder &_fbb, const RankOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const RankOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateRankOptions(
+      _fbb);
+}
+
+inline PowOptionsT *PowOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new PowOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void PowOptions::UnPackTo(PowOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<PowOptions> PowOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const PowOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreatePowOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<PowOptions> CreatePowOptions(flatbuffers::FlatBufferBuilder &_fbb, const PowOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const PowOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreatePowOptions(
+      _fbb);
+}
+
+inline FakeQuantOptionsT *FakeQuantOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new FakeQuantOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void FakeQuantOptions::UnPackTo(FakeQuantOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = min(); _o->min = _e; };
+  { auto _e = max(); _o->max = _e; };
+  { auto _e = num_bits(); _o->num_bits = _e; };
+  { auto _e = narrow_range(); _o->narrow_range = _e; };
+}
+
+inline flatbuffers::Offset<FakeQuantOptions> FakeQuantOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const FakeQuantOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateFakeQuantOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<FakeQuantOptions> CreateFakeQuantOptions(flatbuffers::FlatBufferBuilder &_fbb, const FakeQuantOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const FakeQuantOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _min = _o->min;
+  auto _max = _o->max;
+  auto _num_bits = _o->num_bits;
+  auto _narrow_range = _o->narrow_range;
+  return tflite::CreateFakeQuantOptions(
+      _fbb,
+      _min,
+      _max,
+      _num_bits,
+      _narrow_range);
+}
+
+inline PackOptionsT *PackOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new PackOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void PackOptions::UnPackTo(PackOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = values_count(); _o->values_count = _e; };
+  { auto _e = axis(); _o->axis = _e; };
+}
+
+inline flatbuffers::Offset<PackOptions> PackOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const PackOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreatePackOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<PackOptions> CreatePackOptions(flatbuffers::FlatBufferBuilder &_fbb, const PackOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const PackOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _values_count = _o->values_count;
+  auto _axis = _o->axis;
+  return tflite::CreatePackOptions(
+      _fbb,
+      _values_count,
+      _axis);
+}
+
+inline LogicalOrOptionsT *LogicalOrOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new LogicalOrOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void LogicalOrOptions::UnPackTo(LogicalOrOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<LogicalOrOptions> LogicalOrOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const LogicalOrOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateLogicalOrOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<LogicalOrOptions> CreateLogicalOrOptions(flatbuffers::FlatBufferBuilder &_fbb, const LogicalOrOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const LogicalOrOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateLogicalOrOptions(
+      _fbb);
+}
+
+inline OneHotOptionsT *OneHotOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new OneHotOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void OneHotOptions::UnPackTo(OneHotOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = axis(); _o->axis = _e; };
+}
+
+inline flatbuffers::Offset<OneHotOptions> OneHotOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const OneHotOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateOneHotOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<OneHotOptions> CreateOneHotOptions(flatbuffers::FlatBufferBuilder &_fbb, const OneHotOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const OneHotOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _axis = _o->axis;
+  return tflite::CreateOneHotOptions(
+      _fbb,
+      _axis);
+}
+
+inline AbsOptionsT *AbsOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new AbsOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void AbsOptions::UnPackTo(AbsOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<AbsOptions> AbsOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const AbsOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateAbsOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<AbsOptions> CreateAbsOptions(flatbuffers::FlatBufferBuilder &_fbb, const AbsOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const AbsOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateAbsOptions(
+      _fbb);
+}
+
+inline HardSwishOptionsT *HardSwishOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new HardSwishOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void HardSwishOptions::UnPackTo(HardSwishOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<HardSwishOptions> HardSwishOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const HardSwishOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateHardSwishOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<HardSwishOptions> CreateHardSwishOptions(flatbuffers::FlatBufferBuilder &_fbb, const HardSwishOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const HardSwishOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateHardSwishOptions(
+      _fbb);
+}
+
+inline LogicalAndOptionsT *LogicalAndOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new LogicalAndOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void LogicalAndOptions::UnPackTo(LogicalAndOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<LogicalAndOptions> LogicalAndOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const LogicalAndOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateLogicalAndOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<LogicalAndOptions> CreateLogicalAndOptions(flatbuffers::FlatBufferBuilder &_fbb, const LogicalAndOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const LogicalAndOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateLogicalAndOptions(
+      _fbb);
+}
+
+inline LogicalNotOptionsT *LogicalNotOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new LogicalNotOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void LogicalNotOptions::UnPackTo(LogicalNotOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<LogicalNotOptions> LogicalNotOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const LogicalNotOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateLogicalNotOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<LogicalNotOptions> CreateLogicalNotOptions(flatbuffers::FlatBufferBuilder &_fbb, const LogicalNotOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const LogicalNotOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateLogicalNotOptions(
+      _fbb);
+}
+
+inline UnpackOptionsT *UnpackOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new UnpackOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void UnpackOptions::UnPackTo(UnpackOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = num(); _o->num = _e; };
+  { auto _e = axis(); _o->axis = _e; };
+}
+
+inline flatbuffers::Offset<UnpackOptions> UnpackOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const UnpackOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateUnpackOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<UnpackOptions> CreateUnpackOptions(flatbuffers::FlatBufferBuilder &_fbb, const UnpackOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const UnpackOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _num = _o->num;
+  auto _axis = _o->axis;
+  return tflite::CreateUnpackOptions(
+      _fbb,
+      _num,
+      _axis);
+}
+
+inline FloorDivOptionsT *FloorDivOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new FloorDivOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void FloorDivOptions::UnPackTo(FloorDivOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<FloorDivOptions> FloorDivOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const FloorDivOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateFloorDivOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<FloorDivOptions> CreateFloorDivOptions(flatbuffers::FlatBufferBuilder &_fbb, const FloorDivOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const FloorDivOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateFloorDivOptions(
+      _fbb);
+}
+
+inline SquareOptionsT *SquareOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SquareOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SquareOptions::UnPackTo(SquareOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<SquareOptions> SquareOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SquareOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSquareOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SquareOptions> CreateSquareOptions(flatbuffers::FlatBufferBuilder &_fbb, const SquareOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SquareOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateSquareOptions(
+      _fbb);
+}
+
+inline ZerosLikeOptionsT *ZerosLikeOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ZerosLikeOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ZerosLikeOptions::UnPackTo(ZerosLikeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<ZerosLikeOptions> ZerosLikeOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ZerosLikeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateZerosLikeOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ZerosLikeOptions> CreateZerosLikeOptions(flatbuffers::FlatBufferBuilder &_fbb, const ZerosLikeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ZerosLikeOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateZerosLikeOptions(
+      _fbb);
+}
+
+inline FillOptionsT *FillOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new FillOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void FillOptions::UnPackTo(FillOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<FillOptions> FillOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const FillOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateFillOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<FillOptions> CreateFillOptions(flatbuffers::FlatBufferBuilder &_fbb, const FillOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const FillOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateFillOptions(
+      _fbb);
+}
+
+inline FloorModOptionsT *FloorModOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new FloorModOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void FloorModOptions::UnPackTo(FloorModOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<FloorModOptions> FloorModOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const FloorModOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateFloorModOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<FloorModOptions> CreateFloorModOptions(flatbuffers::FlatBufferBuilder &_fbb, const FloorModOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const FloorModOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateFloorModOptions(
+      _fbb);
+}
+
+inline RangeOptionsT *RangeOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new RangeOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void RangeOptions::UnPackTo(RangeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<RangeOptions> RangeOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const RangeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateRangeOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<RangeOptions> CreateRangeOptions(flatbuffers::FlatBufferBuilder &_fbb, const RangeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const RangeOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateRangeOptions(
+      _fbb);
+}
+
+inline LeakyReluOptionsT *LeakyReluOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new LeakyReluOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void LeakyReluOptions::UnPackTo(LeakyReluOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = alpha(); _o->alpha = _e; };
+}
+
+inline flatbuffers::Offset<LeakyReluOptions> LeakyReluOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const LeakyReluOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateLeakyReluOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<LeakyReluOptions> CreateLeakyReluOptions(flatbuffers::FlatBufferBuilder &_fbb, const LeakyReluOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const LeakyReluOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _alpha = _o->alpha;
+  return tflite::CreateLeakyReluOptions(
+      _fbb,
+      _alpha);
+}
+
+inline SquaredDifferenceOptionsT *SquaredDifferenceOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SquaredDifferenceOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SquaredDifferenceOptions::UnPackTo(SquaredDifferenceOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<SquaredDifferenceOptions> SquaredDifferenceOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SquaredDifferenceOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSquaredDifferenceOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SquaredDifferenceOptions> CreateSquaredDifferenceOptions(flatbuffers::FlatBufferBuilder &_fbb, const SquaredDifferenceOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SquaredDifferenceOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateSquaredDifferenceOptions(
+      _fbb);
+}
+
+inline MirrorPadOptionsT *MirrorPadOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new MirrorPadOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void MirrorPadOptions::UnPackTo(MirrorPadOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = mode(); _o->mode = _e; };
+}
+
+inline flatbuffers::Offset<MirrorPadOptions> MirrorPadOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const MirrorPadOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateMirrorPadOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<MirrorPadOptions> CreateMirrorPadOptions(flatbuffers::FlatBufferBuilder &_fbb, const MirrorPadOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const MirrorPadOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _mode = _o->mode;
+  return tflite::CreateMirrorPadOptions(
+      _fbb,
+      _mode);
+}
+
+inline UniqueOptionsT *UniqueOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new UniqueOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void UniqueOptions::UnPackTo(UniqueOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = idx_out_type(); _o->idx_out_type = _e; };
+}
+
+inline flatbuffers::Offset<UniqueOptions> UniqueOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const UniqueOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateUniqueOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<UniqueOptions> CreateUniqueOptions(flatbuffers::FlatBufferBuilder &_fbb, const UniqueOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const UniqueOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _idx_out_type = _o->idx_out_type;
+  return tflite::CreateUniqueOptions(
+      _fbb,
+      _idx_out_type);
+}
+
+inline ReverseV2OptionsT *ReverseV2Options::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ReverseV2OptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ReverseV2Options::UnPackTo(ReverseV2OptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<ReverseV2Options> ReverseV2Options::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ReverseV2OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateReverseV2Options(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ReverseV2Options> CreateReverseV2Options(flatbuffers::FlatBufferBuilder &_fbb, const ReverseV2OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ReverseV2OptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateReverseV2Options(
+      _fbb);
+}
+
+inline AddNOptionsT *AddNOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new AddNOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void AddNOptions::UnPackTo(AddNOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<AddNOptions> AddNOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const AddNOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateAddNOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<AddNOptions> CreateAddNOptions(flatbuffers::FlatBufferBuilder &_fbb, const AddNOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const AddNOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateAddNOptions(
+      _fbb);
+}
+
+inline GatherNdOptionsT *GatherNdOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new GatherNdOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void GatherNdOptions::UnPackTo(GatherNdOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<GatherNdOptions> GatherNdOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const GatherNdOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateGatherNdOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<GatherNdOptions> CreateGatherNdOptions(flatbuffers::FlatBufferBuilder &_fbb, const GatherNdOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const GatherNdOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateGatherNdOptions(
+      _fbb);
+}
+
+inline WhereOptionsT *WhereOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new WhereOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void WhereOptions::UnPackTo(WhereOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<WhereOptions> WhereOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const WhereOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateWhereOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<WhereOptions> CreateWhereOptions(flatbuffers::FlatBufferBuilder &_fbb, const WhereOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const WhereOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateWhereOptions(
+      _fbb);
+}
+
+inline ReverseSequenceOptionsT *ReverseSequenceOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ReverseSequenceOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ReverseSequenceOptions::UnPackTo(ReverseSequenceOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = seq_dim(); _o->seq_dim = _e; };
+  { auto _e = batch_dim(); _o->batch_dim = _e; };
+}
+
+inline flatbuffers::Offset<ReverseSequenceOptions> ReverseSequenceOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ReverseSequenceOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateReverseSequenceOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ReverseSequenceOptions> CreateReverseSequenceOptions(flatbuffers::FlatBufferBuilder &_fbb, const ReverseSequenceOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ReverseSequenceOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _seq_dim = _o->seq_dim;
+  auto _batch_dim = _o->batch_dim;
+  return tflite::CreateReverseSequenceOptions(
+      _fbb,
+      _seq_dim,
+      _batch_dim);
+}
+
+inline MatrixDiagOptionsT *MatrixDiagOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new MatrixDiagOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void MatrixDiagOptions::UnPackTo(MatrixDiagOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<MatrixDiagOptions> MatrixDiagOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const MatrixDiagOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateMatrixDiagOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<MatrixDiagOptions> CreateMatrixDiagOptions(flatbuffers::FlatBufferBuilder &_fbb, const MatrixDiagOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const MatrixDiagOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateMatrixDiagOptions(
+      _fbb);
+}
+
+inline QuantizeOptionsT *QuantizeOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new QuantizeOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void QuantizeOptions::UnPackTo(QuantizeOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<QuantizeOptions> QuantizeOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const QuantizeOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateQuantizeOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<QuantizeOptions> CreateQuantizeOptions(flatbuffers::FlatBufferBuilder &_fbb, const QuantizeOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const QuantizeOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateQuantizeOptions(
+      _fbb);
+}
+
+inline MatrixSetDiagOptionsT *MatrixSetDiagOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new MatrixSetDiagOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void MatrixSetDiagOptions::UnPackTo(MatrixSetDiagOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<MatrixSetDiagOptions> MatrixSetDiagOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const MatrixSetDiagOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateMatrixSetDiagOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<MatrixSetDiagOptions> CreateMatrixSetDiagOptions(flatbuffers::FlatBufferBuilder &_fbb, const MatrixSetDiagOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const MatrixSetDiagOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateMatrixSetDiagOptions(
+      _fbb);
+}
+
+inline IfOptionsT *IfOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new IfOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void IfOptions::UnPackTo(IfOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = then_subgraph_index(); _o->then_subgraph_index = _e; };
+  { auto _e = else_subgraph_index(); _o->else_subgraph_index = _e; };
+}
+
+inline flatbuffers::Offset<IfOptions> IfOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const IfOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateIfOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<IfOptions> CreateIfOptions(flatbuffers::FlatBufferBuilder &_fbb, const IfOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const IfOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _then_subgraph_index = _o->then_subgraph_index;
+  auto _else_subgraph_index = _o->else_subgraph_index;
+  return tflite::CreateIfOptions(
+      _fbb,
+      _then_subgraph_index,
+      _else_subgraph_index);
+}
+
+inline WhileOptionsT *WhileOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new WhileOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void WhileOptions::UnPackTo(WhileOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = cond_subgraph_index(); _o->cond_subgraph_index = _e; };
+  { auto _e = body_subgraph_index(); _o->body_subgraph_index = _e; };
+}
+
+inline flatbuffers::Offset<WhileOptions> WhileOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const WhileOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateWhileOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<WhileOptions> CreateWhileOptions(flatbuffers::FlatBufferBuilder &_fbb, const WhileOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const WhileOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _cond_subgraph_index = _o->cond_subgraph_index;
+  auto _body_subgraph_index = _o->body_subgraph_index;
+  return tflite::CreateWhileOptions(
+      _fbb,
+      _cond_subgraph_index,
+      _body_subgraph_index);
+}
+
+inline NonMaxSuppressionV4OptionsT *NonMaxSuppressionV4Options::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new NonMaxSuppressionV4OptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void NonMaxSuppressionV4Options::UnPackTo(NonMaxSuppressionV4OptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<NonMaxSuppressionV4Options> NonMaxSuppressionV4Options::Pack(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV4OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateNonMaxSuppressionV4Options(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<NonMaxSuppressionV4Options> CreateNonMaxSuppressionV4Options(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV4OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const NonMaxSuppressionV4OptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateNonMaxSuppressionV4Options(
+      _fbb);
+}
+
+inline NonMaxSuppressionV5OptionsT *NonMaxSuppressionV5Options::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new NonMaxSuppressionV5OptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void NonMaxSuppressionV5Options::UnPackTo(NonMaxSuppressionV5OptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<NonMaxSuppressionV5Options> NonMaxSuppressionV5Options::Pack(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV5OptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateNonMaxSuppressionV5Options(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<NonMaxSuppressionV5Options> CreateNonMaxSuppressionV5Options(flatbuffers::FlatBufferBuilder &_fbb, const NonMaxSuppressionV5OptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const NonMaxSuppressionV5OptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateNonMaxSuppressionV5Options(
+      _fbb);
+}
+
+inline ScatterNdOptionsT *ScatterNdOptions::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ScatterNdOptionsT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void ScatterNdOptions::UnPackTo(ScatterNdOptionsT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+}
+
+inline flatbuffers::Offset<ScatterNdOptions> ScatterNdOptions::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ScatterNdOptionsT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateScatterNdOptions(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<ScatterNdOptions> CreateScatterNdOptions(flatbuffers::FlatBufferBuilder &_fbb, const ScatterNdOptionsT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ScatterNdOptionsT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  return tflite::CreateScatterNdOptions(
+      _fbb);
+}
+
+inline OperatorCodeT *OperatorCode::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new OperatorCodeT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void OperatorCode::UnPackTo(OperatorCodeT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = builtin_code(); _o->builtin_code = _e; };
+  { auto _e = custom_code(); if (_e) _o->custom_code = _e->str(); };
+  { auto _e = version(); _o->version = _e; };
+}
+
+inline flatbuffers::Offset<OperatorCode> OperatorCode::Pack(flatbuffers::FlatBufferBuilder &_fbb, const OperatorCodeT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateOperatorCode(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<OperatorCode> CreateOperatorCode(flatbuffers::FlatBufferBuilder &_fbb, const OperatorCodeT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const OperatorCodeT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _builtin_code = _o->builtin_code;
+  auto _custom_code = _o->custom_code.empty() ? 0 : _fbb.CreateString(_o->custom_code);
+  auto _version = _o->version;
+  return tflite::CreateOperatorCode(
+      _fbb,
+      _builtin_code,
+      _custom_code,
+      _version);
+}
+
+inline OperatorT *Operator::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new OperatorT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void Operator::UnPackTo(OperatorT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = opcode_index(); _o->opcode_index = _e; };
+  { auto _e = inputs(); if (_e) { _o->inputs.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->inputs[_i] = _e->Get(_i); } } };
+  { auto _e = outputs(); if (_e) { _o->outputs.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->outputs[_i] = _e->Get(_i); } } };
+  { auto _e = builtin_options_type(); _o->builtin_options.type = _e; };
+  { auto _e = builtin_options(); if (_e) _o->builtin_options.value = BuiltinOptionsUnion::UnPack(_e, builtin_options_type(), _resolver); };
+  { auto _e = custom_options(); if (_e) { _o->custom_options.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->custom_options[_i] = _e->Get(_i); } } };
+  { auto _e = custom_options_format(); _o->custom_options_format = _e; };
+  { auto _e = mutating_variable_inputs(); if (_e) { _o->mutating_variable_inputs.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->mutating_variable_inputs[_i] = _e->Get(_i) != 0; } } };
+  { auto _e = intermediates(); if (_e) { _o->intermediates.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->intermediates[_i] = _e->Get(_i); } } };
+}
+
+inline flatbuffers::Offset<Operator> Operator::Pack(flatbuffers::FlatBufferBuilder &_fbb, const OperatorT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateOperator(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<Operator> CreateOperator(flatbuffers::FlatBufferBuilder &_fbb, const OperatorT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const OperatorT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _opcode_index = _o->opcode_index;
+  auto _inputs = _o->inputs.size() ? _fbb.CreateVector(_o->inputs) : 0;
+  auto _outputs = _o->outputs.size() ? _fbb.CreateVector(_o->outputs) : 0;
+  auto _builtin_options_type = _o->builtin_options.type;
+  auto _builtin_options = _o->builtin_options.Pack(_fbb);
+  auto _custom_options = _o->custom_options.size() ? _fbb.CreateVector(_o->custom_options) : 0;
+  auto _custom_options_format = _o->custom_options_format;
+  auto _mutating_variable_inputs = _o->mutating_variable_inputs.size() ? _fbb.CreateVector(_o->mutating_variable_inputs) : 0;
+  auto _intermediates = _o->intermediates.size() ? _fbb.CreateVector(_o->intermediates) : 0;
+  return tflite::CreateOperator(
+      _fbb,
+      _opcode_index,
+      _inputs,
+      _outputs,
+      _builtin_options_type,
+      _builtin_options,
+      _custom_options,
+      _custom_options_format,
+      _mutating_variable_inputs,
+      _intermediates);
+}
+
+inline SubGraphT *SubGraph::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new SubGraphT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void SubGraph::UnPackTo(SubGraphT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = tensors(); if (_e) { _o->tensors.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->tensors[_i] = std::unique_ptr<TensorT>(_e->Get(_i)->UnPack(_resolver)); } } };
+  { auto _e = inputs(); if (_e) { _o->inputs.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->inputs[_i] = _e->Get(_i); } } };
+  { auto _e = outputs(); if (_e) { _o->outputs.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->outputs[_i] = _e->Get(_i); } } };
+  { auto _e = operators(); if (_e) { _o->operators.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->operators[_i] = std::unique_ptr<OperatorT>(_e->Get(_i)->UnPack(_resolver)); } } };
+  { auto _e = name(); if (_e) _o->name = _e->str(); };
+}
+
+inline flatbuffers::Offset<SubGraph> SubGraph::Pack(flatbuffers::FlatBufferBuilder &_fbb, const SubGraphT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateSubGraph(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<SubGraph> CreateSubGraph(flatbuffers::FlatBufferBuilder &_fbb, const SubGraphT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const SubGraphT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _tensors = _o->tensors.size() ? _fbb.CreateVector<flatbuffers::Offset<Tensor>> (_o->tensors.size(), [](size_t i, _VectorArgs *__va) { return CreateTensor(*__va->__fbb, __va->__o->tensors[i].get(), __va->__rehasher); }, &_va ) : 0;
+  auto _inputs = _o->inputs.size() ? _fbb.CreateVector(_o->inputs) : 0;
+  auto _outputs = _o->outputs.size() ? _fbb.CreateVector(_o->outputs) : 0;
+  auto _operators = _o->operators.size() ? _fbb.CreateVector<flatbuffers::Offset<Operator>> (_o->operators.size(), [](size_t i, _VectorArgs *__va) { return CreateOperator(*__va->__fbb, __va->__o->operators[i].get(), __va->__rehasher); }, &_va ) : 0;
+  auto _name = _o->name.empty() ? 0 : _fbb.CreateString(_o->name);
+  return tflite::CreateSubGraph(
+      _fbb,
+      _tensors,
+      _inputs,
+      _outputs,
+      _operators,
+      _name);
+}
+
+inline BufferT *Buffer::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new BufferT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void Buffer::UnPackTo(BufferT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = data(); if (_e) { _o->data.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->data[_i] = _e->Get(_i); } } };
+}
+
+inline flatbuffers::Offset<Buffer> Buffer::Pack(flatbuffers::FlatBufferBuilder &_fbb, const BufferT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateBuffer(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<Buffer> CreateBuffer(flatbuffers::FlatBufferBuilder &_fbb, const BufferT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const BufferT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _data = _o->data.size() ? _fbb.CreateVector(_o->data) : 0;
+  return tflite::CreateBuffer(
+      _fbb,
+      _data);
+}
+
+inline MetadataT *Metadata::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new MetadataT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void Metadata::UnPackTo(MetadataT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = name(); if (_e) _o->name = _e->str(); };
+  { auto _e = buffer(); _o->buffer = _e; };
+}
+
+inline flatbuffers::Offset<Metadata> Metadata::Pack(flatbuffers::FlatBufferBuilder &_fbb, const MetadataT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateMetadata(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<Metadata> CreateMetadata(flatbuffers::FlatBufferBuilder &_fbb, const MetadataT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const MetadataT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _name = _o->name.empty() ? 0 : _fbb.CreateString(_o->name);
+  auto _buffer = _o->buffer;
+  return tflite::CreateMetadata(
+      _fbb,
+      _name,
+      _buffer);
+}
+
+inline ModelT *Model::UnPack(const flatbuffers::resolver_function_t *_resolver) const {
+  auto _o = new ModelT();
+  UnPackTo(_o, _resolver);
+  return _o;
+}
+
+inline void Model::UnPackTo(ModelT *_o, const flatbuffers::resolver_function_t *_resolver) const {
+  (void)_o;
+  (void)_resolver;
+  { auto _e = version(); _o->version = _e; };
+  { auto _e = operator_codes(); if (_e) { _o->operator_codes.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->operator_codes[_i] = std::unique_ptr<OperatorCodeT>(_e->Get(_i)->UnPack(_resolver)); } } };
+  { auto _e = subgraphs(); if (_e) { _o->subgraphs.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->subgraphs[_i] = std::unique_ptr<SubGraphT>(_e->Get(_i)->UnPack(_resolver)); } } };
+  { auto _e = description(); if (_e) _o->description = _e->str(); };
+  { auto _e = buffers(); if (_e) { _o->buffers.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->buffers[_i] = std::unique_ptr<BufferT>(_e->Get(_i)->UnPack(_resolver)); } } };
+  { auto _e = metadata_buffer(); if (_e) { _o->metadata_buffer.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->metadata_buffer[_i] = _e->Get(_i); } } };
+  { auto _e = metadata(); if (_e) { _o->metadata.resize(_e->size()); for (flatbuffers::uoffset_t _i = 0; _i < _e->size(); _i++) { _o->metadata[_i] = std::unique_ptr<MetadataT>(_e->Get(_i)->UnPack(_resolver)); } } };
+}
+
+inline flatbuffers::Offset<Model> Model::Pack(flatbuffers::FlatBufferBuilder &_fbb, const ModelT* _o, const flatbuffers::rehasher_function_t *_rehasher) {
+  return CreateModel(_fbb, _o, _rehasher);
+}
+
+inline flatbuffers::Offset<Model> CreateModel(flatbuffers::FlatBufferBuilder &_fbb, const ModelT *_o, const flatbuffers::rehasher_function_t *_rehasher) {
+  (void)_rehasher;
+  (void)_o;
+  struct _VectorArgs { flatbuffers::FlatBufferBuilder *__fbb; const ModelT* __o; const flatbuffers::rehasher_function_t *__rehasher; } _va = { &_fbb, _o, _rehasher}; (void)_va;
+  auto _version = _o->version;
+  auto _operator_codes = _o->operator_codes.size() ? _fbb.CreateVector<flatbuffers::Offset<OperatorCode>> (_o->operator_codes.size(), [](size_t i, _VectorArgs *__va) { return CreateOperatorCode(*__va->__fbb, __va->__o->operator_codes[i].get(), __va->__rehasher); }, &_va ) : 0;
+  auto _subgraphs = _o->subgraphs.size() ? _fbb.CreateVector<flatbuffers::Offset<SubGraph>> (_o->subgraphs.size(), [](size_t i, _VectorArgs *__va) { return CreateSubGraph(*__va->__fbb, __va->__o->subgraphs[i].get(), __va->__rehasher); }, &_va ) : 0;
+  auto _description = _o->description.empty() ? 0 : _fbb.CreateString(_o->description);
+  auto _buffers = _o->buffers.size() ? _fbb.CreateVector<flatbuffers::Offset<Buffer>> (_o->buffers.size(), [](size_t i, _VectorArgs *__va) { return CreateBuffer(*__va->__fbb, __va->__o->buffers[i].get(), __va->__rehasher); }, &_va ) : 0;
+  auto _metadata_buffer = _o->metadata_buffer.size() ? _fbb.CreateVector(_o->metadata_buffer) : 0;
+  auto _metadata = _o->metadata.size() ? _fbb.CreateVector<flatbuffers::Offset<Metadata>> (_o->metadata.size(), [](size_t i, _VectorArgs *__va) { return CreateMetadata(*__va->__fbb, __va->__o->metadata[i].get(), __va->__rehasher); }, &_va ) : 0;
+  return tflite::CreateModel(
+      _fbb,
+      _version,
+      _operator_codes,
+      _subgraphs,
+      _description,
+      _buffers,
+      _metadata_buffer,
+      _metadata);
+}
+
+inline bool VerifyQuantizationDetails(flatbuffers::Verifier &verifier, const void *obj, QuantizationDetails type) {
+  switch (type) {
+    case QuantizationDetails_NONE: {
+      return true;
+    }
+    case QuantizationDetails_CustomQuantization: {
+      auto ptr = reinterpret_cast<const CustomQuantization *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    default: return false;
+  }
+}
+
+inline bool VerifyQuantizationDetailsVector(flatbuffers::Verifier &verifier, const flatbuffers::Vector<flatbuffers::Offset<void>> *values, const flatbuffers::Vector<uint8_t> *types) {
+  if (!values || !types) return !values && !types;
+  if (values->size() != types->size()) return false;
+  for (flatbuffers::uoffset_t i = 0; i < values->size(); ++i) {
+    if (!VerifyQuantizationDetails(
+        verifier,  values->Get(i), types->GetEnum<QuantizationDetails>(i))) {
+      return false;
+    }
+  }
+  return true;
+}
+
+inline void *QuantizationDetailsUnion::UnPack(const void *obj, QuantizationDetails type, const flatbuffers::resolver_function_t *resolver) {
+  switch (type) {
+    case QuantizationDetails_CustomQuantization: {
+      auto ptr = reinterpret_cast<const CustomQuantization *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    default: return nullptr;
+  }
+}
+
+inline flatbuffers::Offset<void> QuantizationDetailsUnion::Pack(flatbuffers::FlatBufferBuilder &_fbb, const flatbuffers::rehasher_function_t *_rehasher) const {
+  switch (type) {
+    case QuantizationDetails_CustomQuantization: {
+      auto ptr = reinterpret_cast<const CustomQuantizationT *>(value);
+      return CreateCustomQuantization(_fbb, ptr, _rehasher).Union();
+    }
+    default: return 0;
+  }
+}
+
+inline QuantizationDetailsUnion::QuantizationDetailsUnion(const QuantizationDetailsUnion &u) FLATBUFFERS_NOEXCEPT : type(u.type), value(nullptr) {
+  switch (type) {
+    case QuantizationDetails_CustomQuantization: {
+      value = new CustomQuantizationT(*reinterpret_cast<CustomQuantizationT *>(u.value));
+      break;
+    }
+    default:
+      break;
+  }
+}
+
+inline void QuantizationDetailsUnion::Reset() {
+  switch (type) {
+    case QuantizationDetails_CustomQuantization: {
+      auto ptr = reinterpret_cast<CustomQuantizationT *>(value);
+      delete ptr;
+      break;
+    }
+    default: break;
+  }
+  value = nullptr;
+  type = QuantizationDetails_NONE;
+}
+
+inline bool VerifyBuiltinOptions(flatbuffers::Verifier &verifier, const void *obj, BuiltinOptions type) {
+  switch (type) {
+    case BuiltinOptions_NONE: {
+      return true;
+    }
+    case BuiltinOptions_Conv2DOptions: {
+      auto ptr = reinterpret_cast<const Conv2DOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_DepthwiseConv2DOptions: {
+      auto ptr = reinterpret_cast<const DepthwiseConv2DOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ConcatEmbeddingsOptions: {
+      auto ptr = reinterpret_cast<const ConcatEmbeddingsOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_LSHProjectionOptions: {
+      auto ptr = reinterpret_cast<const LSHProjectionOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_Pool2DOptions: {
+      auto ptr = reinterpret_cast<const Pool2DOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SVDFOptions: {
+      auto ptr = reinterpret_cast<const SVDFOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_RNNOptions: {
+      auto ptr = reinterpret_cast<const RNNOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_FullyConnectedOptions: {
+      auto ptr = reinterpret_cast<const FullyConnectedOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SoftmaxOptions: {
+      auto ptr = reinterpret_cast<const SoftmaxOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ConcatenationOptions: {
+      auto ptr = reinterpret_cast<const ConcatenationOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_AddOptions: {
+      auto ptr = reinterpret_cast<const AddOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_L2NormOptions: {
+      auto ptr = reinterpret_cast<const L2NormOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_LocalResponseNormalizationOptions: {
+      auto ptr = reinterpret_cast<const LocalResponseNormalizationOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_LSTMOptions: {
+      auto ptr = reinterpret_cast<const LSTMOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ResizeBilinearOptions: {
+      auto ptr = reinterpret_cast<const ResizeBilinearOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_CallOptions: {
+      auto ptr = reinterpret_cast<const CallOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ReshapeOptions: {
+      auto ptr = reinterpret_cast<const ReshapeOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SkipGramOptions: {
+      auto ptr = reinterpret_cast<const SkipGramOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SpaceToDepthOptions: {
+      auto ptr = reinterpret_cast<const SpaceToDepthOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_EmbeddingLookupSparseOptions: {
+      auto ptr = reinterpret_cast<const EmbeddingLookupSparseOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_MulOptions: {
+      auto ptr = reinterpret_cast<const MulOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_PadOptions: {
+      auto ptr = reinterpret_cast<const PadOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_GatherOptions: {
+      auto ptr = reinterpret_cast<const GatherOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_BatchToSpaceNDOptions: {
+      auto ptr = reinterpret_cast<const BatchToSpaceNDOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SpaceToBatchNDOptions: {
+      auto ptr = reinterpret_cast<const SpaceToBatchNDOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_TransposeOptions: {
+      auto ptr = reinterpret_cast<const TransposeOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ReducerOptions: {
+      auto ptr = reinterpret_cast<const ReducerOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SubOptions: {
+      auto ptr = reinterpret_cast<const SubOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_DivOptions: {
+      auto ptr = reinterpret_cast<const DivOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SqueezeOptions: {
+      auto ptr = reinterpret_cast<const SqueezeOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SequenceRNNOptions: {
+      auto ptr = reinterpret_cast<const SequenceRNNOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_StridedSliceOptions: {
+      auto ptr = reinterpret_cast<const StridedSliceOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ExpOptions: {
+      auto ptr = reinterpret_cast<const ExpOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_TopKV2Options: {
+      auto ptr = reinterpret_cast<const TopKV2Options *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SplitOptions: {
+      auto ptr = reinterpret_cast<const SplitOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_LogSoftmaxOptions: {
+      auto ptr = reinterpret_cast<const LogSoftmaxOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_CastOptions: {
+      auto ptr = reinterpret_cast<const CastOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_DequantizeOptions: {
+      auto ptr = reinterpret_cast<const DequantizeOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_MaximumMinimumOptions: {
+      auto ptr = reinterpret_cast<const MaximumMinimumOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ArgMaxOptions: {
+      auto ptr = reinterpret_cast<const ArgMaxOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_LessOptions: {
+      auto ptr = reinterpret_cast<const LessOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_NegOptions: {
+      auto ptr = reinterpret_cast<const NegOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_PadV2Options: {
+      auto ptr = reinterpret_cast<const PadV2Options *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_GreaterOptions: {
+      auto ptr = reinterpret_cast<const GreaterOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_GreaterEqualOptions: {
+      auto ptr = reinterpret_cast<const GreaterEqualOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_LessEqualOptions: {
+      auto ptr = reinterpret_cast<const LessEqualOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SelectOptions: {
+      auto ptr = reinterpret_cast<const SelectOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SliceOptions: {
+      auto ptr = reinterpret_cast<const SliceOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_TransposeConvOptions: {
+      auto ptr = reinterpret_cast<const TransposeConvOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SparseToDenseOptions: {
+      auto ptr = reinterpret_cast<const SparseToDenseOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_TileOptions: {
+      auto ptr = reinterpret_cast<const TileOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ExpandDimsOptions: {
+      auto ptr = reinterpret_cast<const ExpandDimsOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_EqualOptions: {
+      auto ptr = reinterpret_cast<const EqualOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_NotEqualOptions: {
+      auto ptr = reinterpret_cast<const NotEqualOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ShapeOptions: {
+      auto ptr = reinterpret_cast<const ShapeOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_PowOptions: {
+      auto ptr = reinterpret_cast<const PowOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ArgMinOptions: {
+      auto ptr = reinterpret_cast<const ArgMinOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_FakeQuantOptions: {
+      auto ptr = reinterpret_cast<const FakeQuantOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_PackOptions: {
+      auto ptr = reinterpret_cast<const PackOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_LogicalOrOptions: {
+      auto ptr = reinterpret_cast<const LogicalOrOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_OneHotOptions: {
+      auto ptr = reinterpret_cast<const OneHotOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_LogicalAndOptions: {
+      auto ptr = reinterpret_cast<const LogicalAndOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_LogicalNotOptions: {
+      auto ptr = reinterpret_cast<const LogicalNotOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_UnpackOptions: {
+      auto ptr = reinterpret_cast<const UnpackOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_FloorDivOptions: {
+      auto ptr = reinterpret_cast<const FloorDivOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SquareOptions: {
+      auto ptr = reinterpret_cast<const SquareOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ZerosLikeOptions: {
+      auto ptr = reinterpret_cast<const ZerosLikeOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_FillOptions: {
+      auto ptr = reinterpret_cast<const FillOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_BidirectionalSequenceLSTMOptions: {
+      auto ptr = reinterpret_cast<const BidirectionalSequenceLSTMOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_BidirectionalSequenceRNNOptions: {
+      auto ptr = reinterpret_cast<const BidirectionalSequenceRNNOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_UnidirectionalSequenceLSTMOptions: {
+      auto ptr = reinterpret_cast<const UnidirectionalSequenceLSTMOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_FloorModOptions: {
+      auto ptr = reinterpret_cast<const FloorModOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_RangeOptions: {
+      auto ptr = reinterpret_cast<const RangeOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ResizeNearestNeighborOptions: {
+      auto ptr = reinterpret_cast<const ResizeNearestNeighborOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_LeakyReluOptions: {
+      auto ptr = reinterpret_cast<const LeakyReluOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SquaredDifferenceOptions: {
+      auto ptr = reinterpret_cast<const SquaredDifferenceOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_MirrorPadOptions: {
+      auto ptr = reinterpret_cast<const MirrorPadOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_AbsOptions: {
+      auto ptr = reinterpret_cast<const AbsOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_SplitVOptions: {
+      auto ptr = reinterpret_cast<const SplitVOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_UniqueOptions: {
+      auto ptr = reinterpret_cast<const UniqueOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ReverseV2Options: {
+      auto ptr = reinterpret_cast<const ReverseV2Options *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_AddNOptions: {
+      auto ptr = reinterpret_cast<const AddNOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_GatherNdOptions: {
+      auto ptr = reinterpret_cast<const GatherNdOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_CosOptions: {
+      auto ptr = reinterpret_cast<const CosOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_WhereOptions: {
+      auto ptr = reinterpret_cast<const WhereOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_RankOptions: {
+      auto ptr = reinterpret_cast<const RankOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ReverseSequenceOptions: {
+      auto ptr = reinterpret_cast<const ReverseSequenceOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_MatrixDiagOptions: {
+      auto ptr = reinterpret_cast<const MatrixDiagOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_QuantizeOptions: {
+      auto ptr = reinterpret_cast<const QuantizeOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_MatrixSetDiagOptions: {
+      auto ptr = reinterpret_cast<const MatrixSetDiagOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_HardSwishOptions: {
+      auto ptr = reinterpret_cast<const HardSwishOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_IfOptions: {
+      auto ptr = reinterpret_cast<const IfOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_WhileOptions: {
+      auto ptr = reinterpret_cast<const WhileOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_DepthToSpaceOptions: {
+      auto ptr = reinterpret_cast<const DepthToSpaceOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_NonMaxSuppressionV4Options: {
+      auto ptr = reinterpret_cast<const NonMaxSuppressionV4Options *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_NonMaxSuppressionV5Options: {
+      auto ptr = reinterpret_cast<const NonMaxSuppressionV5Options *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    case BuiltinOptions_ScatterNdOptions: {
+      auto ptr = reinterpret_cast<const ScatterNdOptions *>(obj);
+      return verifier.VerifyTable(ptr);
+    }
+    default: return false;
+  }
+}
+
+inline bool VerifyBuiltinOptionsVector(flatbuffers::Verifier &verifier, const flatbuffers::Vector<flatbuffers::Offset<void>> *values, const flatbuffers::Vector<uint8_t> *types) {
+  if (!values || !types) return !values && !types;
+  if (values->size() != types->size()) return false;
+  for (flatbuffers::uoffset_t i = 0; i < values->size(); ++i) {
+    if (!VerifyBuiltinOptions(
+        verifier,  values->Get(i), types->GetEnum<BuiltinOptions>(i))) {
+      return false;
+    }
+  }
+  return true;
+}
+
+inline void *BuiltinOptionsUnion::UnPack(const void *obj, BuiltinOptions type, const flatbuffers::resolver_function_t *resolver) {
+  switch (type) {
+    case BuiltinOptions_Conv2DOptions: {
+      auto ptr = reinterpret_cast<const Conv2DOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_DepthwiseConv2DOptions: {
+      auto ptr = reinterpret_cast<const DepthwiseConv2DOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ConcatEmbeddingsOptions: {
+      auto ptr = reinterpret_cast<const ConcatEmbeddingsOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_LSHProjectionOptions: {
+      auto ptr = reinterpret_cast<const LSHProjectionOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_Pool2DOptions: {
+      auto ptr = reinterpret_cast<const Pool2DOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SVDFOptions: {
+      auto ptr = reinterpret_cast<const SVDFOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_RNNOptions: {
+      auto ptr = reinterpret_cast<const RNNOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_FullyConnectedOptions: {
+      auto ptr = reinterpret_cast<const FullyConnectedOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SoftmaxOptions: {
+      auto ptr = reinterpret_cast<const SoftmaxOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ConcatenationOptions: {
+      auto ptr = reinterpret_cast<const ConcatenationOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_AddOptions: {
+      auto ptr = reinterpret_cast<const AddOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_L2NormOptions: {
+      auto ptr = reinterpret_cast<const L2NormOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_LocalResponseNormalizationOptions: {
+      auto ptr = reinterpret_cast<const LocalResponseNormalizationOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_LSTMOptions: {
+      auto ptr = reinterpret_cast<const LSTMOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ResizeBilinearOptions: {
+      auto ptr = reinterpret_cast<const ResizeBilinearOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_CallOptions: {
+      auto ptr = reinterpret_cast<const CallOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ReshapeOptions: {
+      auto ptr = reinterpret_cast<const ReshapeOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SkipGramOptions: {
+      auto ptr = reinterpret_cast<const SkipGramOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SpaceToDepthOptions: {
+      auto ptr = reinterpret_cast<const SpaceToDepthOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_EmbeddingLookupSparseOptions: {
+      auto ptr = reinterpret_cast<const EmbeddingLookupSparseOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_MulOptions: {
+      auto ptr = reinterpret_cast<const MulOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_PadOptions: {
+      auto ptr = reinterpret_cast<const PadOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_GatherOptions: {
+      auto ptr = reinterpret_cast<const GatherOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_BatchToSpaceNDOptions: {
+      auto ptr = reinterpret_cast<const BatchToSpaceNDOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SpaceToBatchNDOptions: {
+      auto ptr = reinterpret_cast<const SpaceToBatchNDOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_TransposeOptions: {
+      auto ptr = reinterpret_cast<const TransposeOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ReducerOptions: {
+      auto ptr = reinterpret_cast<const ReducerOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SubOptions: {
+      auto ptr = reinterpret_cast<const SubOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_DivOptions: {
+      auto ptr = reinterpret_cast<const DivOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SqueezeOptions: {
+      auto ptr = reinterpret_cast<const SqueezeOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SequenceRNNOptions: {
+      auto ptr = reinterpret_cast<const SequenceRNNOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_StridedSliceOptions: {
+      auto ptr = reinterpret_cast<const StridedSliceOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ExpOptions: {
+      auto ptr = reinterpret_cast<const ExpOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_TopKV2Options: {
+      auto ptr = reinterpret_cast<const TopKV2Options *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SplitOptions: {
+      auto ptr = reinterpret_cast<const SplitOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_LogSoftmaxOptions: {
+      auto ptr = reinterpret_cast<const LogSoftmaxOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_CastOptions: {
+      auto ptr = reinterpret_cast<const CastOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_DequantizeOptions: {
+      auto ptr = reinterpret_cast<const DequantizeOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_MaximumMinimumOptions: {
+      auto ptr = reinterpret_cast<const MaximumMinimumOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ArgMaxOptions: {
+      auto ptr = reinterpret_cast<const ArgMaxOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_LessOptions: {
+      auto ptr = reinterpret_cast<const LessOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_NegOptions: {
+      auto ptr = reinterpret_cast<const NegOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_PadV2Options: {
+      auto ptr = reinterpret_cast<const PadV2Options *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_GreaterOptions: {
+      auto ptr = reinterpret_cast<const GreaterOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_GreaterEqualOptions: {
+      auto ptr = reinterpret_cast<const GreaterEqualOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_LessEqualOptions: {
+      auto ptr = reinterpret_cast<const LessEqualOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SelectOptions: {
+      auto ptr = reinterpret_cast<const SelectOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SliceOptions: {
+      auto ptr = reinterpret_cast<const SliceOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_TransposeConvOptions: {
+      auto ptr = reinterpret_cast<const TransposeConvOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SparseToDenseOptions: {
+      auto ptr = reinterpret_cast<const SparseToDenseOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_TileOptions: {
+      auto ptr = reinterpret_cast<const TileOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ExpandDimsOptions: {
+      auto ptr = reinterpret_cast<const ExpandDimsOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_EqualOptions: {
+      auto ptr = reinterpret_cast<const EqualOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_NotEqualOptions: {
+      auto ptr = reinterpret_cast<const NotEqualOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ShapeOptions: {
+      auto ptr = reinterpret_cast<const ShapeOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_PowOptions: {
+      auto ptr = reinterpret_cast<const PowOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ArgMinOptions: {
+      auto ptr = reinterpret_cast<const ArgMinOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_FakeQuantOptions: {
+      auto ptr = reinterpret_cast<const FakeQuantOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_PackOptions: {
+      auto ptr = reinterpret_cast<const PackOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_LogicalOrOptions: {
+      auto ptr = reinterpret_cast<const LogicalOrOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_OneHotOptions: {
+      auto ptr = reinterpret_cast<const OneHotOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_LogicalAndOptions: {
+      auto ptr = reinterpret_cast<const LogicalAndOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_LogicalNotOptions: {
+      auto ptr = reinterpret_cast<const LogicalNotOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_UnpackOptions: {
+      auto ptr = reinterpret_cast<const UnpackOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_FloorDivOptions: {
+      auto ptr = reinterpret_cast<const FloorDivOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SquareOptions: {
+      auto ptr = reinterpret_cast<const SquareOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ZerosLikeOptions: {
+      auto ptr = reinterpret_cast<const ZerosLikeOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_FillOptions: {
+      auto ptr = reinterpret_cast<const FillOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_BidirectionalSequenceLSTMOptions: {
+      auto ptr = reinterpret_cast<const BidirectionalSequenceLSTMOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_BidirectionalSequenceRNNOptions: {
+      auto ptr = reinterpret_cast<const BidirectionalSequenceRNNOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_UnidirectionalSequenceLSTMOptions: {
+      auto ptr = reinterpret_cast<const UnidirectionalSequenceLSTMOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_FloorModOptions: {
+      auto ptr = reinterpret_cast<const FloorModOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_RangeOptions: {
+      auto ptr = reinterpret_cast<const RangeOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ResizeNearestNeighborOptions: {
+      auto ptr = reinterpret_cast<const ResizeNearestNeighborOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_LeakyReluOptions: {
+      auto ptr = reinterpret_cast<const LeakyReluOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SquaredDifferenceOptions: {
+      auto ptr = reinterpret_cast<const SquaredDifferenceOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_MirrorPadOptions: {
+      auto ptr = reinterpret_cast<const MirrorPadOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_AbsOptions: {
+      auto ptr = reinterpret_cast<const AbsOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_SplitVOptions: {
+      auto ptr = reinterpret_cast<const SplitVOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_UniqueOptions: {
+      auto ptr = reinterpret_cast<const UniqueOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ReverseV2Options: {
+      auto ptr = reinterpret_cast<const ReverseV2Options *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_AddNOptions: {
+      auto ptr = reinterpret_cast<const AddNOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_GatherNdOptions: {
+      auto ptr = reinterpret_cast<const GatherNdOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_CosOptions: {
+      auto ptr = reinterpret_cast<const CosOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_WhereOptions: {
+      auto ptr = reinterpret_cast<const WhereOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_RankOptions: {
+      auto ptr = reinterpret_cast<const RankOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ReverseSequenceOptions: {
+      auto ptr = reinterpret_cast<const ReverseSequenceOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_MatrixDiagOptions: {
+      auto ptr = reinterpret_cast<const MatrixDiagOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_QuantizeOptions: {
+      auto ptr = reinterpret_cast<const QuantizeOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_MatrixSetDiagOptions: {
+      auto ptr = reinterpret_cast<const MatrixSetDiagOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_HardSwishOptions: {
+      auto ptr = reinterpret_cast<const HardSwishOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_IfOptions: {
+      auto ptr = reinterpret_cast<const IfOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_WhileOptions: {
+      auto ptr = reinterpret_cast<const WhileOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_DepthToSpaceOptions: {
+      auto ptr = reinterpret_cast<const DepthToSpaceOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_NonMaxSuppressionV4Options: {
+      auto ptr = reinterpret_cast<const NonMaxSuppressionV4Options *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_NonMaxSuppressionV5Options: {
+      auto ptr = reinterpret_cast<const NonMaxSuppressionV5Options *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    case BuiltinOptions_ScatterNdOptions: {
+      auto ptr = reinterpret_cast<const ScatterNdOptions *>(obj);
+      return ptr->UnPack(resolver);
+    }
+    default: return nullptr;
+  }
+}
+
+inline flatbuffers::Offset<void> BuiltinOptionsUnion::Pack(flatbuffers::FlatBufferBuilder &_fbb, const flatbuffers::rehasher_function_t *_rehasher) const {
+  switch (type) {
+    case BuiltinOptions_Conv2DOptions: {
+      auto ptr = reinterpret_cast<const Conv2DOptionsT *>(value);
+      return CreateConv2DOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_DepthwiseConv2DOptions: {
+      auto ptr = reinterpret_cast<const DepthwiseConv2DOptionsT *>(value);
+      return CreateDepthwiseConv2DOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ConcatEmbeddingsOptions: {
+      auto ptr = reinterpret_cast<const ConcatEmbeddingsOptionsT *>(value);
+      return CreateConcatEmbeddingsOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_LSHProjectionOptions: {
+      auto ptr = reinterpret_cast<const LSHProjectionOptionsT *>(value);
+      return CreateLSHProjectionOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_Pool2DOptions: {
+      auto ptr = reinterpret_cast<const Pool2DOptionsT *>(value);
+      return CreatePool2DOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SVDFOptions: {
+      auto ptr = reinterpret_cast<const SVDFOptionsT *>(value);
+      return CreateSVDFOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_RNNOptions: {
+      auto ptr = reinterpret_cast<const RNNOptionsT *>(value);
+      return CreateRNNOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_FullyConnectedOptions: {
+      auto ptr = reinterpret_cast<const FullyConnectedOptionsT *>(value);
+      return CreateFullyConnectedOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SoftmaxOptions: {
+      auto ptr = reinterpret_cast<const SoftmaxOptionsT *>(value);
+      return CreateSoftmaxOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ConcatenationOptions: {
+      auto ptr = reinterpret_cast<const ConcatenationOptionsT *>(value);
+      return CreateConcatenationOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_AddOptions: {
+      auto ptr = reinterpret_cast<const AddOptionsT *>(value);
+      return CreateAddOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_L2NormOptions: {
+      auto ptr = reinterpret_cast<const L2NormOptionsT *>(value);
+      return CreateL2NormOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_LocalResponseNormalizationOptions: {
+      auto ptr = reinterpret_cast<const LocalResponseNormalizationOptionsT *>(value);
+      return CreateLocalResponseNormalizationOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_LSTMOptions: {
+      auto ptr = reinterpret_cast<const LSTMOptionsT *>(value);
+      return CreateLSTMOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ResizeBilinearOptions: {
+      auto ptr = reinterpret_cast<const ResizeBilinearOptionsT *>(value);
+      return CreateResizeBilinearOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_CallOptions: {
+      auto ptr = reinterpret_cast<const CallOptionsT *>(value);
+      return CreateCallOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ReshapeOptions: {
+      auto ptr = reinterpret_cast<const ReshapeOptionsT *>(value);
+      return CreateReshapeOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SkipGramOptions: {
+      auto ptr = reinterpret_cast<const SkipGramOptionsT *>(value);
+      return CreateSkipGramOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SpaceToDepthOptions: {
+      auto ptr = reinterpret_cast<const SpaceToDepthOptionsT *>(value);
+      return CreateSpaceToDepthOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_EmbeddingLookupSparseOptions: {
+      auto ptr = reinterpret_cast<const EmbeddingLookupSparseOptionsT *>(value);
+      return CreateEmbeddingLookupSparseOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_MulOptions: {
+      auto ptr = reinterpret_cast<const MulOptionsT *>(value);
+      return CreateMulOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_PadOptions: {
+      auto ptr = reinterpret_cast<const PadOptionsT *>(value);
+      return CreatePadOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_GatherOptions: {
+      auto ptr = reinterpret_cast<const GatherOptionsT *>(value);
+      return CreateGatherOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_BatchToSpaceNDOptions: {
+      auto ptr = reinterpret_cast<const BatchToSpaceNDOptionsT *>(value);
+      return CreateBatchToSpaceNDOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SpaceToBatchNDOptions: {
+      auto ptr = reinterpret_cast<const SpaceToBatchNDOptionsT *>(value);
+      return CreateSpaceToBatchNDOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_TransposeOptions: {
+      auto ptr = reinterpret_cast<const TransposeOptionsT *>(value);
+      return CreateTransposeOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ReducerOptions: {
+      auto ptr = reinterpret_cast<const ReducerOptionsT *>(value);
+      return CreateReducerOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SubOptions: {
+      auto ptr = reinterpret_cast<const SubOptionsT *>(value);
+      return CreateSubOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_DivOptions: {
+      auto ptr = reinterpret_cast<const DivOptionsT *>(value);
+      return CreateDivOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SqueezeOptions: {
+      auto ptr = reinterpret_cast<const SqueezeOptionsT *>(value);
+      return CreateSqueezeOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SequenceRNNOptions: {
+      auto ptr = reinterpret_cast<const SequenceRNNOptionsT *>(value);
+      return CreateSequenceRNNOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_StridedSliceOptions: {
+      auto ptr = reinterpret_cast<const StridedSliceOptionsT *>(value);
+      return CreateStridedSliceOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ExpOptions: {
+      auto ptr = reinterpret_cast<const ExpOptionsT *>(value);
+      return CreateExpOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_TopKV2Options: {
+      auto ptr = reinterpret_cast<const TopKV2OptionsT *>(value);
+      return CreateTopKV2Options(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SplitOptions: {
+      auto ptr = reinterpret_cast<const SplitOptionsT *>(value);
+      return CreateSplitOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_LogSoftmaxOptions: {
+      auto ptr = reinterpret_cast<const LogSoftmaxOptionsT *>(value);
+      return CreateLogSoftmaxOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_CastOptions: {
+      auto ptr = reinterpret_cast<const CastOptionsT *>(value);
+      return CreateCastOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_DequantizeOptions: {
+      auto ptr = reinterpret_cast<const DequantizeOptionsT *>(value);
+      return CreateDequantizeOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_MaximumMinimumOptions: {
+      auto ptr = reinterpret_cast<const MaximumMinimumOptionsT *>(value);
+      return CreateMaximumMinimumOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ArgMaxOptions: {
+      auto ptr = reinterpret_cast<const ArgMaxOptionsT *>(value);
+      return CreateArgMaxOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_LessOptions: {
+      auto ptr = reinterpret_cast<const LessOptionsT *>(value);
+      return CreateLessOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_NegOptions: {
+      auto ptr = reinterpret_cast<const NegOptionsT *>(value);
+      return CreateNegOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_PadV2Options: {
+      auto ptr = reinterpret_cast<const PadV2OptionsT *>(value);
+      return CreatePadV2Options(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_GreaterOptions: {
+      auto ptr = reinterpret_cast<const GreaterOptionsT *>(value);
+      return CreateGreaterOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_GreaterEqualOptions: {
+      auto ptr = reinterpret_cast<const GreaterEqualOptionsT *>(value);
+      return CreateGreaterEqualOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_LessEqualOptions: {
+      auto ptr = reinterpret_cast<const LessEqualOptionsT *>(value);
+      return CreateLessEqualOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SelectOptions: {
+      auto ptr = reinterpret_cast<const SelectOptionsT *>(value);
+      return CreateSelectOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SliceOptions: {
+      auto ptr = reinterpret_cast<const SliceOptionsT *>(value);
+      return CreateSliceOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_TransposeConvOptions: {
+      auto ptr = reinterpret_cast<const TransposeConvOptionsT *>(value);
+      return CreateTransposeConvOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SparseToDenseOptions: {
+      auto ptr = reinterpret_cast<const SparseToDenseOptionsT *>(value);
+      return CreateSparseToDenseOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_TileOptions: {
+      auto ptr = reinterpret_cast<const TileOptionsT *>(value);
+      return CreateTileOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ExpandDimsOptions: {
+      auto ptr = reinterpret_cast<const ExpandDimsOptionsT *>(value);
+      return CreateExpandDimsOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_EqualOptions: {
+      auto ptr = reinterpret_cast<const EqualOptionsT *>(value);
+      return CreateEqualOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_NotEqualOptions: {
+      auto ptr = reinterpret_cast<const NotEqualOptionsT *>(value);
+      return CreateNotEqualOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ShapeOptions: {
+      auto ptr = reinterpret_cast<const ShapeOptionsT *>(value);
+      return CreateShapeOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_PowOptions: {
+      auto ptr = reinterpret_cast<const PowOptionsT *>(value);
+      return CreatePowOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ArgMinOptions: {
+      auto ptr = reinterpret_cast<const ArgMinOptionsT *>(value);
+      return CreateArgMinOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_FakeQuantOptions: {
+      auto ptr = reinterpret_cast<const FakeQuantOptionsT *>(value);
+      return CreateFakeQuantOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_PackOptions: {
+      auto ptr = reinterpret_cast<const PackOptionsT *>(value);
+      return CreatePackOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_LogicalOrOptions: {
+      auto ptr = reinterpret_cast<const LogicalOrOptionsT *>(value);
+      return CreateLogicalOrOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_OneHotOptions: {
+      auto ptr = reinterpret_cast<const OneHotOptionsT *>(value);
+      return CreateOneHotOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_LogicalAndOptions: {
+      auto ptr = reinterpret_cast<const LogicalAndOptionsT *>(value);
+      return CreateLogicalAndOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_LogicalNotOptions: {
+      auto ptr = reinterpret_cast<const LogicalNotOptionsT *>(value);
+      return CreateLogicalNotOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_UnpackOptions: {
+      auto ptr = reinterpret_cast<const UnpackOptionsT *>(value);
+      return CreateUnpackOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_FloorDivOptions: {
+      auto ptr = reinterpret_cast<const FloorDivOptionsT *>(value);
+      return CreateFloorDivOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SquareOptions: {
+      auto ptr = reinterpret_cast<const SquareOptionsT *>(value);
+      return CreateSquareOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ZerosLikeOptions: {
+      auto ptr = reinterpret_cast<const ZerosLikeOptionsT *>(value);
+      return CreateZerosLikeOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_FillOptions: {
+      auto ptr = reinterpret_cast<const FillOptionsT *>(value);
+      return CreateFillOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_BidirectionalSequenceLSTMOptions: {
+      auto ptr = reinterpret_cast<const BidirectionalSequenceLSTMOptionsT *>(value);
+      return CreateBidirectionalSequenceLSTMOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_BidirectionalSequenceRNNOptions: {
+      auto ptr = reinterpret_cast<const BidirectionalSequenceRNNOptionsT *>(value);
+      return CreateBidirectionalSequenceRNNOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_UnidirectionalSequenceLSTMOptions: {
+      auto ptr = reinterpret_cast<const UnidirectionalSequenceLSTMOptionsT *>(value);
+      return CreateUnidirectionalSequenceLSTMOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_FloorModOptions: {
+      auto ptr = reinterpret_cast<const FloorModOptionsT *>(value);
+      return CreateFloorModOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_RangeOptions: {
+      auto ptr = reinterpret_cast<const RangeOptionsT *>(value);
+      return CreateRangeOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ResizeNearestNeighborOptions: {
+      auto ptr = reinterpret_cast<const ResizeNearestNeighborOptionsT *>(value);
+      return CreateResizeNearestNeighborOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_LeakyReluOptions: {
+      auto ptr = reinterpret_cast<const LeakyReluOptionsT *>(value);
+      return CreateLeakyReluOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SquaredDifferenceOptions: {
+      auto ptr = reinterpret_cast<const SquaredDifferenceOptionsT *>(value);
+      return CreateSquaredDifferenceOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_MirrorPadOptions: {
+      auto ptr = reinterpret_cast<const MirrorPadOptionsT *>(value);
+      return CreateMirrorPadOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_AbsOptions: {
+      auto ptr = reinterpret_cast<const AbsOptionsT *>(value);
+      return CreateAbsOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_SplitVOptions: {
+      auto ptr = reinterpret_cast<const SplitVOptionsT *>(value);
+      return CreateSplitVOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_UniqueOptions: {
+      auto ptr = reinterpret_cast<const UniqueOptionsT *>(value);
+      return CreateUniqueOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ReverseV2Options: {
+      auto ptr = reinterpret_cast<const ReverseV2OptionsT *>(value);
+      return CreateReverseV2Options(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_AddNOptions: {
+      auto ptr = reinterpret_cast<const AddNOptionsT *>(value);
+      return CreateAddNOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_GatherNdOptions: {
+      auto ptr = reinterpret_cast<const GatherNdOptionsT *>(value);
+      return CreateGatherNdOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_CosOptions: {
+      auto ptr = reinterpret_cast<const CosOptionsT *>(value);
+      return CreateCosOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_WhereOptions: {
+      auto ptr = reinterpret_cast<const WhereOptionsT *>(value);
+      return CreateWhereOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_RankOptions: {
+      auto ptr = reinterpret_cast<const RankOptionsT *>(value);
+      return CreateRankOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ReverseSequenceOptions: {
+      auto ptr = reinterpret_cast<const ReverseSequenceOptionsT *>(value);
+      return CreateReverseSequenceOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_MatrixDiagOptions: {
+      auto ptr = reinterpret_cast<const MatrixDiagOptionsT *>(value);
+      return CreateMatrixDiagOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_QuantizeOptions: {
+      auto ptr = reinterpret_cast<const QuantizeOptionsT *>(value);
+      return CreateQuantizeOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_MatrixSetDiagOptions: {
+      auto ptr = reinterpret_cast<const MatrixSetDiagOptionsT *>(value);
+      return CreateMatrixSetDiagOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_HardSwishOptions: {
+      auto ptr = reinterpret_cast<const HardSwishOptionsT *>(value);
+      return CreateHardSwishOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_IfOptions: {
+      auto ptr = reinterpret_cast<const IfOptionsT *>(value);
+      return CreateIfOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_WhileOptions: {
+      auto ptr = reinterpret_cast<const WhileOptionsT *>(value);
+      return CreateWhileOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_DepthToSpaceOptions: {
+      auto ptr = reinterpret_cast<const DepthToSpaceOptionsT *>(value);
+      return CreateDepthToSpaceOptions(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_NonMaxSuppressionV4Options: {
+      auto ptr = reinterpret_cast<const NonMaxSuppressionV4OptionsT *>(value);
+      return CreateNonMaxSuppressionV4Options(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_NonMaxSuppressionV5Options: {
+      auto ptr = reinterpret_cast<const NonMaxSuppressionV5OptionsT *>(value);
+      return CreateNonMaxSuppressionV5Options(_fbb, ptr, _rehasher).Union();
+    }
+    case BuiltinOptions_ScatterNdOptions: {
+      auto ptr = reinterpret_cast<const ScatterNdOptionsT *>(value);
+      return CreateScatterNdOptions(_fbb, ptr, _rehasher).Union();
+    }
+    default: return 0;
+  }
+}
+
+inline BuiltinOptionsUnion::BuiltinOptionsUnion(const BuiltinOptionsUnion &u) FLATBUFFERS_NOEXCEPT : type(u.type), value(nullptr) {
+  switch (type) {
+    case BuiltinOptions_Conv2DOptions: {
+      value = new Conv2DOptionsT(*reinterpret_cast<Conv2DOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_DepthwiseConv2DOptions: {
+      value = new DepthwiseConv2DOptionsT(*reinterpret_cast<DepthwiseConv2DOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ConcatEmbeddingsOptions: {
+      value = new ConcatEmbeddingsOptionsT(*reinterpret_cast<ConcatEmbeddingsOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_LSHProjectionOptions: {
+      value = new LSHProjectionOptionsT(*reinterpret_cast<LSHProjectionOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_Pool2DOptions: {
+      value = new Pool2DOptionsT(*reinterpret_cast<Pool2DOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SVDFOptions: {
+      value = new SVDFOptionsT(*reinterpret_cast<SVDFOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_RNNOptions: {
+      value = new RNNOptionsT(*reinterpret_cast<RNNOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_FullyConnectedOptions: {
+      value = new FullyConnectedOptionsT(*reinterpret_cast<FullyConnectedOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SoftmaxOptions: {
+      value = new SoftmaxOptionsT(*reinterpret_cast<SoftmaxOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ConcatenationOptions: {
+      value = new ConcatenationOptionsT(*reinterpret_cast<ConcatenationOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_AddOptions: {
+      value = new AddOptionsT(*reinterpret_cast<AddOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_L2NormOptions: {
+      value = new L2NormOptionsT(*reinterpret_cast<L2NormOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_LocalResponseNormalizationOptions: {
+      value = new LocalResponseNormalizationOptionsT(*reinterpret_cast<LocalResponseNormalizationOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_LSTMOptions: {
+      value = new LSTMOptionsT(*reinterpret_cast<LSTMOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ResizeBilinearOptions: {
+      value = new ResizeBilinearOptionsT(*reinterpret_cast<ResizeBilinearOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_CallOptions: {
+      value = new CallOptionsT(*reinterpret_cast<CallOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ReshapeOptions: {
+      value = new ReshapeOptionsT(*reinterpret_cast<ReshapeOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SkipGramOptions: {
+      value = new SkipGramOptionsT(*reinterpret_cast<SkipGramOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SpaceToDepthOptions: {
+      value = new SpaceToDepthOptionsT(*reinterpret_cast<SpaceToDepthOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_EmbeddingLookupSparseOptions: {
+      value = new EmbeddingLookupSparseOptionsT(*reinterpret_cast<EmbeddingLookupSparseOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_MulOptions: {
+      value = new MulOptionsT(*reinterpret_cast<MulOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_PadOptions: {
+      value = new PadOptionsT(*reinterpret_cast<PadOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_GatherOptions: {
+      value = new GatherOptionsT(*reinterpret_cast<GatherOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_BatchToSpaceNDOptions: {
+      value = new BatchToSpaceNDOptionsT(*reinterpret_cast<BatchToSpaceNDOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SpaceToBatchNDOptions: {
+      value = new SpaceToBatchNDOptionsT(*reinterpret_cast<SpaceToBatchNDOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_TransposeOptions: {
+      value = new TransposeOptionsT(*reinterpret_cast<TransposeOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ReducerOptions: {
+      value = new ReducerOptionsT(*reinterpret_cast<ReducerOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SubOptions: {
+      value = new SubOptionsT(*reinterpret_cast<SubOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_DivOptions: {
+      value = new DivOptionsT(*reinterpret_cast<DivOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SqueezeOptions: {
+      value = new SqueezeOptionsT(*reinterpret_cast<SqueezeOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SequenceRNNOptions: {
+      value = new SequenceRNNOptionsT(*reinterpret_cast<SequenceRNNOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_StridedSliceOptions: {
+      value = new StridedSliceOptionsT(*reinterpret_cast<StridedSliceOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ExpOptions: {
+      value = new ExpOptionsT(*reinterpret_cast<ExpOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_TopKV2Options: {
+      value = new TopKV2OptionsT(*reinterpret_cast<TopKV2OptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SplitOptions: {
+      value = new SplitOptionsT(*reinterpret_cast<SplitOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_LogSoftmaxOptions: {
+      value = new LogSoftmaxOptionsT(*reinterpret_cast<LogSoftmaxOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_CastOptions: {
+      value = new CastOptionsT(*reinterpret_cast<CastOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_DequantizeOptions: {
+      value = new DequantizeOptionsT(*reinterpret_cast<DequantizeOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_MaximumMinimumOptions: {
+      value = new MaximumMinimumOptionsT(*reinterpret_cast<MaximumMinimumOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ArgMaxOptions: {
+      value = new ArgMaxOptionsT(*reinterpret_cast<ArgMaxOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_LessOptions: {
+      value = new LessOptionsT(*reinterpret_cast<LessOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_NegOptions: {
+      value = new NegOptionsT(*reinterpret_cast<NegOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_PadV2Options: {
+      value = new PadV2OptionsT(*reinterpret_cast<PadV2OptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_GreaterOptions: {
+      value = new GreaterOptionsT(*reinterpret_cast<GreaterOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_GreaterEqualOptions: {
+      value = new GreaterEqualOptionsT(*reinterpret_cast<GreaterEqualOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_LessEqualOptions: {
+      value = new LessEqualOptionsT(*reinterpret_cast<LessEqualOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SelectOptions: {
+      value = new SelectOptionsT(*reinterpret_cast<SelectOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SliceOptions: {
+      value = new SliceOptionsT(*reinterpret_cast<SliceOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_TransposeConvOptions: {
+      value = new TransposeConvOptionsT(*reinterpret_cast<TransposeConvOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SparseToDenseOptions: {
+      value = new SparseToDenseOptionsT(*reinterpret_cast<SparseToDenseOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_TileOptions: {
+      value = new TileOptionsT(*reinterpret_cast<TileOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ExpandDimsOptions: {
+      value = new ExpandDimsOptionsT(*reinterpret_cast<ExpandDimsOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_EqualOptions: {
+      value = new EqualOptionsT(*reinterpret_cast<EqualOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_NotEqualOptions: {
+      value = new NotEqualOptionsT(*reinterpret_cast<NotEqualOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ShapeOptions: {
+      value = new ShapeOptionsT(*reinterpret_cast<ShapeOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_PowOptions: {
+      value = new PowOptionsT(*reinterpret_cast<PowOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ArgMinOptions: {
+      value = new ArgMinOptionsT(*reinterpret_cast<ArgMinOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_FakeQuantOptions: {
+      value = new FakeQuantOptionsT(*reinterpret_cast<FakeQuantOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_PackOptions: {
+      value = new PackOptionsT(*reinterpret_cast<PackOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_LogicalOrOptions: {
+      value = new LogicalOrOptionsT(*reinterpret_cast<LogicalOrOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_OneHotOptions: {
+      value = new OneHotOptionsT(*reinterpret_cast<OneHotOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_LogicalAndOptions: {
+      value = new LogicalAndOptionsT(*reinterpret_cast<LogicalAndOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_LogicalNotOptions: {
+      value = new LogicalNotOptionsT(*reinterpret_cast<LogicalNotOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_UnpackOptions: {
+      value = new UnpackOptionsT(*reinterpret_cast<UnpackOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_FloorDivOptions: {
+      value = new FloorDivOptionsT(*reinterpret_cast<FloorDivOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SquareOptions: {
+      value = new SquareOptionsT(*reinterpret_cast<SquareOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ZerosLikeOptions: {
+      value = new ZerosLikeOptionsT(*reinterpret_cast<ZerosLikeOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_FillOptions: {
+      value = new FillOptionsT(*reinterpret_cast<FillOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_BidirectionalSequenceLSTMOptions: {
+      value = new BidirectionalSequenceLSTMOptionsT(*reinterpret_cast<BidirectionalSequenceLSTMOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_BidirectionalSequenceRNNOptions: {
+      value = new BidirectionalSequenceRNNOptionsT(*reinterpret_cast<BidirectionalSequenceRNNOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_UnidirectionalSequenceLSTMOptions: {
+      value = new UnidirectionalSequenceLSTMOptionsT(*reinterpret_cast<UnidirectionalSequenceLSTMOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_FloorModOptions: {
+      value = new FloorModOptionsT(*reinterpret_cast<FloorModOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_RangeOptions: {
+      value = new RangeOptionsT(*reinterpret_cast<RangeOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ResizeNearestNeighborOptions: {
+      value = new ResizeNearestNeighborOptionsT(*reinterpret_cast<ResizeNearestNeighborOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_LeakyReluOptions: {
+      value = new LeakyReluOptionsT(*reinterpret_cast<LeakyReluOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SquaredDifferenceOptions: {
+      value = new SquaredDifferenceOptionsT(*reinterpret_cast<SquaredDifferenceOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_MirrorPadOptions: {
+      value = new MirrorPadOptionsT(*reinterpret_cast<MirrorPadOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_AbsOptions: {
+      value = new AbsOptionsT(*reinterpret_cast<AbsOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_SplitVOptions: {
+      value = new SplitVOptionsT(*reinterpret_cast<SplitVOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_UniqueOptions: {
+      value = new UniqueOptionsT(*reinterpret_cast<UniqueOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ReverseV2Options: {
+      value = new ReverseV2OptionsT(*reinterpret_cast<ReverseV2OptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_AddNOptions: {
+      value = new AddNOptionsT(*reinterpret_cast<AddNOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_GatherNdOptions: {
+      value = new GatherNdOptionsT(*reinterpret_cast<GatherNdOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_CosOptions: {
+      value = new CosOptionsT(*reinterpret_cast<CosOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_WhereOptions: {
+      value = new WhereOptionsT(*reinterpret_cast<WhereOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_RankOptions: {
+      value = new RankOptionsT(*reinterpret_cast<RankOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ReverseSequenceOptions: {
+      value = new ReverseSequenceOptionsT(*reinterpret_cast<ReverseSequenceOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_MatrixDiagOptions: {
+      value = new MatrixDiagOptionsT(*reinterpret_cast<MatrixDiagOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_QuantizeOptions: {
+      value = new QuantizeOptionsT(*reinterpret_cast<QuantizeOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_MatrixSetDiagOptions: {
+      value = new MatrixSetDiagOptionsT(*reinterpret_cast<MatrixSetDiagOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_HardSwishOptions: {
+      value = new HardSwishOptionsT(*reinterpret_cast<HardSwishOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_IfOptions: {
+      value = new IfOptionsT(*reinterpret_cast<IfOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_WhileOptions: {
+      value = new WhileOptionsT(*reinterpret_cast<WhileOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_DepthToSpaceOptions: {
+      value = new DepthToSpaceOptionsT(*reinterpret_cast<DepthToSpaceOptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_NonMaxSuppressionV4Options: {
+      value = new NonMaxSuppressionV4OptionsT(*reinterpret_cast<NonMaxSuppressionV4OptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_NonMaxSuppressionV5Options: {
+      value = new NonMaxSuppressionV5OptionsT(*reinterpret_cast<NonMaxSuppressionV5OptionsT *>(u.value));
+      break;
+    }
+    case BuiltinOptions_ScatterNdOptions: {
+      value = new ScatterNdOptionsT(*reinterpret_cast<ScatterNdOptionsT *>(u.value));
+      break;
+    }
+    default:
+      break;
+  }
+}
+
+inline void BuiltinOptionsUnion::Reset() {
+  switch (type) {
+    case BuiltinOptions_Conv2DOptions: {
+      auto ptr = reinterpret_cast<Conv2DOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_DepthwiseConv2DOptions: {
+      auto ptr = reinterpret_cast<DepthwiseConv2DOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ConcatEmbeddingsOptions: {
+      auto ptr = reinterpret_cast<ConcatEmbeddingsOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_LSHProjectionOptions: {
+      auto ptr = reinterpret_cast<LSHProjectionOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_Pool2DOptions: {
+      auto ptr = reinterpret_cast<Pool2DOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SVDFOptions: {
+      auto ptr = reinterpret_cast<SVDFOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_RNNOptions: {
+      auto ptr = reinterpret_cast<RNNOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_FullyConnectedOptions: {
+      auto ptr = reinterpret_cast<FullyConnectedOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SoftmaxOptions: {
+      auto ptr = reinterpret_cast<SoftmaxOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ConcatenationOptions: {
+      auto ptr = reinterpret_cast<ConcatenationOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_AddOptions: {
+      auto ptr = reinterpret_cast<AddOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_L2NormOptions: {
+      auto ptr = reinterpret_cast<L2NormOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_LocalResponseNormalizationOptions: {
+      auto ptr = reinterpret_cast<LocalResponseNormalizationOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_LSTMOptions: {
+      auto ptr = reinterpret_cast<LSTMOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ResizeBilinearOptions: {
+      auto ptr = reinterpret_cast<ResizeBilinearOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_CallOptions: {
+      auto ptr = reinterpret_cast<CallOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ReshapeOptions: {
+      auto ptr = reinterpret_cast<ReshapeOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SkipGramOptions: {
+      auto ptr = reinterpret_cast<SkipGramOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SpaceToDepthOptions: {
+      auto ptr = reinterpret_cast<SpaceToDepthOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_EmbeddingLookupSparseOptions: {
+      auto ptr = reinterpret_cast<EmbeddingLookupSparseOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_MulOptions: {
+      auto ptr = reinterpret_cast<MulOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_PadOptions: {
+      auto ptr = reinterpret_cast<PadOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_GatherOptions: {
+      auto ptr = reinterpret_cast<GatherOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_BatchToSpaceNDOptions: {
+      auto ptr = reinterpret_cast<BatchToSpaceNDOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SpaceToBatchNDOptions: {
+      auto ptr = reinterpret_cast<SpaceToBatchNDOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_TransposeOptions: {
+      auto ptr = reinterpret_cast<TransposeOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ReducerOptions: {
+      auto ptr = reinterpret_cast<ReducerOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SubOptions: {
+      auto ptr = reinterpret_cast<SubOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_DivOptions: {
+      auto ptr = reinterpret_cast<DivOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SqueezeOptions: {
+      auto ptr = reinterpret_cast<SqueezeOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SequenceRNNOptions: {
+      auto ptr = reinterpret_cast<SequenceRNNOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_StridedSliceOptions: {
+      auto ptr = reinterpret_cast<StridedSliceOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ExpOptions: {
+      auto ptr = reinterpret_cast<ExpOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_TopKV2Options: {
+      auto ptr = reinterpret_cast<TopKV2OptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SplitOptions: {
+      auto ptr = reinterpret_cast<SplitOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_LogSoftmaxOptions: {
+      auto ptr = reinterpret_cast<LogSoftmaxOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_CastOptions: {
+      auto ptr = reinterpret_cast<CastOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_DequantizeOptions: {
+      auto ptr = reinterpret_cast<DequantizeOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_MaximumMinimumOptions: {
+      auto ptr = reinterpret_cast<MaximumMinimumOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ArgMaxOptions: {
+      auto ptr = reinterpret_cast<ArgMaxOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_LessOptions: {
+      auto ptr = reinterpret_cast<LessOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_NegOptions: {
+      auto ptr = reinterpret_cast<NegOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_PadV2Options: {
+      auto ptr = reinterpret_cast<PadV2OptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_GreaterOptions: {
+      auto ptr = reinterpret_cast<GreaterOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_GreaterEqualOptions: {
+      auto ptr = reinterpret_cast<GreaterEqualOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_LessEqualOptions: {
+      auto ptr = reinterpret_cast<LessEqualOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SelectOptions: {
+      auto ptr = reinterpret_cast<SelectOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SliceOptions: {
+      auto ptr = reinterpret_cast<SliceOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_TransposeConvOptions: {
+      auto ptr = reinterpret_cast<TransposeConvOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SparseToDenseOptions: {
+      auto ptr = reinterpret_cast<SparseToDenseOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_TileOptions: {
+      auto ptr = reinterpret_cast<TileOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ExpandDimsOptions: {
+      auto ptr = reinterpret_cast<ExpandDimsOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_EqualOptions: {
+      auto ptr = reinterpret_cast<EqualOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_NotEqualOptions: {
+      auto ptr = reinterpret_cast<NotEqualOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ShapeOptions: {
+      auto ptr = reinterpret_cast<ShapeOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_PowOptions: {
+      auto ptr = reinterpret_cast<PowOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ArgMinOptions: {
+      auto ptr = reinterpret_cast<ArgMinOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_FakeQuantOptions: {
+      auto ptr = reinterpret_cast<FakeQuantOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_PackOptions: {
+      auto ptr = reinterpret_cast<PackOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_LogicalOrOptions: {
+      auto ptr = reinterpret_cast<LogicalOrOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_OneHotOptions: {
+      auto ptr = reinterpret_cast<OneHotOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_LogicalAndOptions: {
+      auto ptr = reinterpret_cast<LogicalAndOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_LogicalNotOptions: {
+      auto ptr = reinterpret_cast<LogicalNotOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_UnpackOptions: {
+      auto ptr = reinterpret_cast<UnpackOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_FloorDivOptions: {
+      auto ptr = reinterpret_cast<FloorDivOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SquareOptions: {
+      auto ptr = reinterpret_cast<SquareOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ZerosLikeOptions: {
+      auto ptr = reinterpret_cast<ZerosLikeOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_FillOptions: {
+      auto ptr = reinterpret_cast<FillOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_BidirectionalSequenceLSTMOptions: {
+      auto ptr = reinterpret_cast<BidirectionalSequenceLSTMOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_BidirectionalSequenceRNNOptions: {
+      auto ptr = reinterpret_cast<BidirectionalSequenceRNNOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_UnidirectionalSequenceLSTMOptions: {
+      auto ptr = reinterpret_cast<UnidirectionalSequenceLSTMOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_FloorModOptions: {
+      auto ptr = reinterpret_cast<FloorModOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_RangeOptions: {
+      auto ptr = reinterpret_cast<RangeOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ResizeNearestNeighborOptions: {
+      auto ptr = reinterpret_cast<ResizeNearestNeighborOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_LeakyReluOptions: {
+      auto ptr = reinterpret_cast<LeakyReluOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SquaredDifferenceOptions: {
+      auto ptr = reinterpret_cast<SquaredDifferenceOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_MirrorPadOptions: {
+      auto ptr = reinterpret_cast<MirrorPadOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_AbsOptions: {
+      auto ptr = reinterpret_cast<AbsOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_SplitVOptions: {
+      auto ptr = reinterpret_cast<SplitVOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_UniqueOptions: {
+      auto ptr = reinterpret_cast<UniqueOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ReverseV2Options: {
+      auto ptr = reinterpret_cast<ReverseV2OptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_AddNOptions: {
+      auto ptr = reinterpret_cast<AddNOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_GatherNdOptions: {
+      auto ptr = reinterpret_cast<GatherNdOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_CosOptions: {
+      auto ptr = reinterpret_cast<CosOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_WhereOptions: {
+      auto ptr = reinterpret_cast<WhereOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_RankOptions: {
+      auto ptr = reinterpret_cast<RankOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ReverseSequenceOptions: {
+      auto ptr = reinterpret_cast<ReverseSequenceOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_MatrixDiagOptions: {
+      auto ptr = reinterpret_cast<MatrixDiagOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_QuantizeOptions: {
+      auto ptr = reinterpret_cast<QuantizeOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_MatrixSetDiagOptions: {
+      auto ptr = reinterpret_cast<MatrixSetDiagOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_HardSwishOptions: {
+      auto ptr = reinterpret_cast<HardSwishOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_IfOptions: {
+      auto ptr = reinterpret_cast<IfOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_WhileOptions: {
+      auto ptr = reinterpret_cast<WhileOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_DepthToSpaceOptions: {
+      auto ptr = reinterpret_cast<DepthToSpaceOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_NonMaxSuppressionV4Options: {
+      auto ptr = reinterpret_cast<NonMaxSuppressionV4OptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_NonMaxSuppressionV5Options: {
+      auto ptr = reinterpret_cast<NonMaxSuppressionV5OptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    case BuiltinOptions_ScatterNdOptions: {
+      auto ptr = reinterpret_cast<ScatterNdOptionsT *>(value);
+      delete ptr;
+      break;
+    }
+    default: break;
+  }
+  value = nullptr;
+  type = BuiltinOptions_NONE;
+}
+
+inline const tflite::Model *GetModel(const void *buf) {
+  return flatbuffers::GetRoot<tflite::Model>(buf);
+}
+
+inline const tflite::Model *GetSizePrefixedModel(const void *buf) {
+  return flatbuffers::GetSizePrefixedRoot<tflite::Model>(buf);
+}
+
+inline const char *ModelIdentifier() {
+  return "TFL3";
+}
+
+inline bool ModelBufferHasIdentifier(const void *buf) {
+  return flatbuffers::BufferHasIdentifier(
+      buf, ModelIdentifier());
+}
+
+inline bool VerifyModelBuffer(
+    flatbuffers::Verifier &verifier) {
+  return verifier.VerifyBuffer<tflite::Model>(ModelIdentifier());
+}
+
+inline bool VerifySizePrefixedModelBuffer(
+    flatbuffers::Verifier &verifier) {
+  return verifier.VerifySizePrefixedBuffer<tflite::Model>(ModelIdentifier());
+}
+
+inline const char *ModelExtension() {
+  return "tflite";
+}
+
+inline void FinishModelBuffer(
+    flatbuffers::FlatBufferBuilder &fbb,
+    flatbuffers::Offset<tflite::Model> root) {
+  fbb.Finish(root, ModelIdentifier());
+}
+
+inline void FinishSizePrefixedModelBuffer(
+    flatbuffers::FlatBufferBuilder &fbb,
+    flatbuffers::Offset<tflite::Model> root) {
+  fbb.FinishSizePrefixed(root, ModelIdentifier());
+}
+
+inline std::unique_ptr<ModelT> UnPackModel(
+    const void *buf,
+    const flatbuffers::resolver_function_t *res = nullptr) {
+  return std::unique_ptr<ModelT>(GetModel(buf)->UnPack(res));
+}
+
+}  // namespace tflite
+
+#endif  // FLATBUFFERS_GENERATED_SCHEMA_TFLITE_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/string_type.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/string_type.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,27 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+// Abstract string. We don't want even absl at this level.
+#ifndef TENSORFLOW_LITE_STRING_TYPE_H_
+#define TENSORFLOW_LITE_STRING_TYPE_H_
+
+#include <string>
+
+namespace tflite {
+
+using std::string;
+
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_STRING_TYPE_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/string_util.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/string_util.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,103 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+// Util methods to read and write String tensors.
+// String tensors are considered to be char tensor with protocol.
+//   [0, 3] 4 bytes: N, num of strings in the tensor in little endian.
+//   [(i+1)*4, (i+1)*4+3] 4 bytes: offset of i-th string in little endian.
+//   [(N+2)*4, (N+2)*4+3] 4 bytes: length of the whole char buffer.
+//   [offset(i), offset(i+1) - 1] : content of i-th string.
+// Example of a string tensor:
+// [
+//   2, 0, 0, 0,     # 2 strings.
+//   16, 0, 0, 0,    # 0-th string starts from index 12.
+//   18, 0, 0, 0,    # 1-st string starts from index 18.
+//   18, 0, 0, 0,    # total length of array.
+//   'A', 'B',       # 0-th string [16..17]: "AB"
+// ]                 # 1-th string, empty
+//
+// A typical usage:
+// In op.Eval(context, node):
+//   DynamicBuffer buf;
+//   # Add string "AB" to tensor, string is stored in dynamic buffer.
+//   buf.AddString("AB", 2);
+//   # Write content of DynamicBuffer to tensor in format of string tensor
+//   # described above.
+//   buf.WriteToTensor(tensor, nullptr)
+
+#ifndef TENSORFLOW_LITE_STRING_UTIL_H_
+#define TENSORFLOW_LITE_STRING_UTIL_H_
+
+#include <vector>
+
+#include "tensorflow/lite/c/c_api_internal.h"
+#include "tensorflow/lite/string_type.h"
+
+namespace tflite {
+
+// Convenient structure to store string pointer and length.
+typedef struct {
+  const char* str;
+  int len;
+} StringRef;
+
+// DynamicBuffer holds temporary buffer that will be used to create a dynamic
+// tensor. A typical usage is to initialize a DynamicBuffer object, fill in
+// content and call CreateStringTensor in op.Eval().
+class DynamicBuffer {
+ public:
+  DynamicBuffer() : offset_({0}) {}
+
+  // Add string to dynamic buffer by resizing the buffer and copying the data.
+  void AddString(const StringRef& string);
+
+  // Add string to dynamic buffer by resizing the buffer and copying the data.
+  void AddString(const char* str, size_t len);
+
+  // Join a list of string with separator, and add as a single string to the
+  // buffer.
+  void AddJoinedString(const std::vector<StringRef>& strings, char separator);
+
+  // Fill content into a buffer and returns the number of bytes stored.
+  // The function allocates space for the buffer but does NOT take ownership.
+  int WriteToBuffer(char** buffer);
+
+  // Fill content into a string tensor, with the given new_shape. The new shape
+  // must match the number of strings in this object. Caller relinquishes
+  // ownership of new_shape. If 'new_shape' is nullptr, keep the tensor's
+  // existing shape.
+  void WriteToTensor(TfLiteTensor* tensor, TfLiteIntArray* new_shape);
+
+  // Fill content into a string tensor. Set shape to {num_strings}.
+  void WriteToTensorAsVector(TfLiteTensor* tensor);
+
+ private:
+  // Data buffer to store contents of strings, not including headers.
+  std::vector<char> data_;
+  // Offset of the starting index of each string in data buffer.
+  std::vector<int32_t> offset_;
+};
+
+// Return num of strings in a String tensor.
+int GetStringCount(const void* raw_buffer);
+int GetStringCount(const TfLiteTensor* tensor);
+
+// Get String pointer and length of index-th string in tensor.
+// NOTE: This will not create a copy of string data.
+StringRef GetString(const void* raw_buffer, int string_index);
+StringRef GetString(const TfLiteTensor* tensor, int string_index);
+}  // namespace tflite
+
+#endif  // TENSORFLOW_LITE_STRING_UTIL_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/tensorflow/lite/version.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/tensorflow/lite/version.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,29 @@
+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#ifndef TENSORFLOW_LITE_VERSION_H_
+#define TENSORFLOW_LITE_VERSION_H_
+
+#include "tensorflow/core/public/version.h"
+
+// The version number of the Schema. Ideally all changes will be backward
+// compatible. If that ever changes, we must ensure that version is the first
+// entry in the new tflite root so that we can see that version is not 1.
+#define TFLITE_SCHEMA_VERSION (3)
+
+// TensorFlow Lite Runtime version.
+// This value is currently shared with that of TensorFlow.
+#define TFLITE_VERSION_STRING TF_VERSION_STRING
+
+#endif  // TENSORFLOW_LITE_VERSION_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/cmsis/CMSIS/Core/Include/cmsis_compiler.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/cmsis/CMSIS/Core/Include/cmsis_compiler.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,266 @@
+/**************************************************************************//**
+ * @file     cmsis_compiler.h
+ * @brief    CMSIS compiler generic header file
+ * @version  V5.0.4
+ * @date     10. January 2018
+ ******************************************************************************/
+/*
+ * Copyright (c) 2009-2018 Arm Limited. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef __CMSIS_COMPILER_H
+#define __CMSIS_COMPILER_H
+
+#include <stdint.h>
+
+/*
+ * Arm Compiler 4/5
+ */
+#if   defined ( __CC_ARM )
+  #include "cmsis_armcc.h"
+
+
+/*
+ * Arm Compiler 6 (armclang)
+ */
+#elif defined (__ARMCC_VERSION) && (__ARMCC_VERSION >= 6010050)
+  #include "cmsis_armclang.h"
+
+
+/*
+ * GNU Compiler
+ */
+#elif defined ( __GNUC__ )
+  #include "cmsis_gcc.h"
+
+
+/*
+ * IAR Compiler
+ */
+#elif defined ( __ICCARM__ )
+  #include <cmsis_iccarm.h>
+
+
+/*
+ * TI Arm Compiler
+ */
+#elif defined ( __TI_ARM__ )
+  #include <cmsis_ccs.h>
+
+  #ifndef   __ASM
+    #define __ASM                                  __asm
+  #endif
+  #ifndef   __INLINE
+    #define __INLINE                               inline
+  #endif
+  #ifndef   __STATIC_INLINE
+    #define __STATIC_INLINE                        static inline
+  #endif
+  #ifndef   __STATIC_FORCEINLINE
+    #define __STATIC_FORCEINLINE                   __STATIC_INLINE
+  #endif
+  #ifndef   __NO_RETURN
+    #define __NO_RETURN                            __attribute__((noreturn))
+  #endif
+  #ifndef   __USED
+    #define __USED                                 __attribute__((used))
+  #endif
+  #ifndef   __WEAK
+    #define __WEAK                                 __attribute__((weak))
+  #endif
+  #ifndef   __PACKED
+    #define __PACKED                               __attribute__((packed))
+  #endif
+  #ifndef   __PACKED_STRUCT
+    #define __PACKED_STRUCT                        struct __attribute__((packed))
+  #endif
+  #ifndef   __PACKED_UNION
+    #define __PACKED_UNION                         union __attribute__((packed))
+  #endif
+  #ifndef   __UNALIGNED_UINT32        /* deprecated */
+    struct __attribute__((packed)) T_UINT32 { uint32_t v; };
+    #define __UNALIGNED_UINT32(x)                  (((struct T_UINT32 *)(x))->v)
+  #endif
+  #ifndef   __UNALIGNED_UINT16_WRITE
+    __PACKED_STRUCT T_UINT16_WRITE { uint16_t v; };
+    #define __UNALIGNED_UINT16_WRITE(addr, val)    (void)((((struct T_UINT16_WRITE *)(void*)(addr))->v) = (val))
+  #endif
+  #ifndef   __UNALIGNED_UINT16_READ
+    __PACKED_STRUCT T_UINT16_READ { uint16_t v; };
+    #define __UNALIGNED_UINT16_READ(addr)          (((const struct T_UINT16_READ *)(const void *)(addr))->v)
+  #endif
+  #ifndef   __UNALIGNED_UINT32_WRITE
+    __PACKED_STRUCT T_UINT32_WRITE { uint32_t v; };
+    #define __UNALIGNED_UINT32_WRITE(addr, val)    (void)((((struct T_UINT32_WRITE *)(void *)(addr))->v) = (val))
+  #endif
+  #ifndef   __UNALIGNED_UINT32_READ
+    __PACKED_STRUCT T_UINT32_READ { uint32_t v; };
+    #define __UNALIGNED_UINT32_READ(addr)          (((const struct T_UINT32_READ *)(const void *)(addr))->v)
+  #endif
+  #ifndef   __ALIGNED
+    #define __ALIGNED(x)                           __attribute__((aligned(x)))
+  #endif
+  #ifndef   __RESTRICT
+    #warning No compiler specific solution for __RESTRICT. __RESTRICT is ignored.
+    #define __RESTRICT
+  #endif
+
+
+/*
+ * TASKING Compiler
+ */
+#elif defined ( __TASKING__ )
+  /*
+   * The CMSIS functions have been implemented as intrinsics in the compiler.
+   * Please use "carm -?i" to get an up to date list of all intrinsics,
+   * Including the CMSIS ones.
+   */
+
+  #ifndef   __ASM
+    #define __ASM                                  __asm
+  #endif
+  #ifndef   __INLINE
+    #define __INLINE                               inline
+  #endif
+  #ifndef   __STATIC_INLINE
+    #define __STATIC_INLINE                        static inline
+  #endif
+  #ifndef   __STATIC_FORCEINLINE
+    #define __STATIC_FORCEINLINE                   __STATIC_INLINE
+  #endif
+  #ifndef   __NO_RETURN
+    #define __NO_RETURN                            __attribute__((noreturn))
+  #endif
+  #ifndef   __USED
+    #define __USED                                 __attribute__((used))
+  #endif
+  #ifndef   __WEAK
+    #define __WEAK                                 __attribute__((weak))
+  #endif
+  #ifndef   __PACKED
+    #define __PACKED                               __packed__
+  #endif
+  #ifndef   __PACKED_STRUCT
+    #define __PACKED_STRUCT                        struct __packed__
+  #endif
+  #ifndef   __PACKED_UNION
+    #define __PACKED_UNION                         union __packed__
+  #endif
+  #ifndef   __UNALIGNED_UINT32        /* deprecated */
+    struct __packed__ T_UINT32 { uint32_t v; };
+    #define __UNALIGNED_UINT32(x)                  (((struct T_UINT32 *)(x))->v)
+  #endif
+  #ifndef   __UNALIGNED_UINT16_WRITE
+    __PACKED_STRUCT T_UINT16_WRITE { uint16_t v; };
+    #define __UNALIGNED_UINT16_WRITE(addr, val)    (void)((((struct T_UINT16_WRITE *)(void *)(addr))->v) = (val))
+  #endif
+  #ifndef   __UNALIGNED_UINT16_READ
+    __PACKED_STRUCT T_UINT16_READ { uint16_t v; };
+    #define __UNALIGNED_UINT16_READ(addr)          (((const struct T_UINT16_READ *)(const void *)(addr))->v)
+  #endif
+  #ifndef   __UNALIGNED_UINT32_WRITE
+    __PACKED_STRUCT T_UINT32_WRITE { uint32_t v; };
+    #define __UNALIGNED_UINT32_WRITE(addr, val)    (void)((((struct T_UINT32_WRITE *)(void *)(addr))->v) = (val))
+  #endif
+  #ifndef   __UNALIGNED_UINT32_READ
+    __PACKED_STRUCT T_UINT32_READ { uint32_t v; };
+    #define __UNALIGNED_UINT32_READ(addr)          (((const struct T_UINT32_READ *)(const void *)(addr))->v)
+  #endif
+  #ifndef   __ALIGNED
+    #define __ALIGNED(x)              __align(x)
+  #endif
+  #ifndef   __RESTRICT
+    #warning No compiler specific solution for __RESTRICT. __RESTRICT is ignored.
+    #define __RESTRICT
+  #endif
+
+
+/*
+ * COSMIC Compiler
+ */
+#elif defined ( __CSMC__ )
+   #include <cmsis_csm.h>
+
+ #ifndef   __ASM
+    #define __ASM                                  _asm
+  #endif
+  #ifndef   __INLINE
+    #define __INLINE                               inline
+  #endif
+  #ifndef   __STATIC_INLINE
+    #define __STATIC_INLINE                        static inline
+  #endif
+  #ifndef   __STATIC_FORCEINLINE
+    #define __STATIC_FORCEINLINE                   __STATIC_INLINE
+  #endif
+  #ifndef   __NO_RETURN
+    // NO RETURN is automatically detected hence no warning here
+    #define __NO_RETURN
+  #endif
+  #ifndef   __USED
+    #warning No compiler specific solution for __USED. __USED is ignored.
+    #define __USED
+  #endif
+  #ifndef   __WEAK
+    #define __WEAK                                 __weak
+  #endif
+  #ifndef   __PACKED
+    #define __PACKED                               @packed
+  #endif
+  #ifndef   __PACKED_STRUCT
+    #define __PACKED_STRUCT                        @packed struct
+  #endif
+  #ifndef   __PACKED_UNION
+    #define __PACKED_UNION                         @packed union
+  #endif
+  #ifndef   __UNALIGNED_UINT32        /* deprecated */
+    @packed struct T_UINT32 { uint32_t v; };
+    #define __UNALIGNED_UINT32(x)                  (((struct T_UINT32 *)(x))->v)
+  #endif
+  #ifndef   __UNALIGNED_UINT16_WRITE
+    __PACKED_STRUCT T_UINT16_WRITE { uint16_t v; };
+    #define __UNALIGNED_UINT16_WRITE(addr, val)    (void)((((struct T_UINT16_WRITE *)(void *)(addr))->v) = (val))
+  #endif
+  #ifndef   __UNALIGNED_UINT16_READ
+    __PACKED_STRUCT T_UINT16_READ { uint16_t v; };
+    #define __UNALIGNED_UINT16_READ(addr)          (((const struct T_UINT16_READ *)(const void *)(addr))->v)
+  #endif
+  #ifndef   __UNALIGNED_UINT32_WRITE
+    __PACKED_STRUCT T_UINT32_WRITE { uint32_t v; };
+    #define __UNALIGNED_UINT32_WRITE(addr, val)    (void)((((struct T_UINT32_WRITE *)(void *)(addr))->v) = (val))
+  #endif
+  #ifndef   __UNALIGNED_UINT32_READ
+    __PACKED_STRUCT T_UINT32_READ { uint32_t v; };
+    #define __UNALIGNED_UINT32_READ(addr)          (((const struct T_UINT32_READ *)(const void *)(addr))->v)
+  #endif
+  #ifndef   __ALIGNED
+    #warning No compiler specific solution for __ALIGNED. __ALIGNED is ignored.
+    #define __ALIGNED(x)
+  #endif
+  #ifndef   __RESTRICT
+    #warning No compiler specific solution for __RESTRICT. __RESTRICT is ignored.
+    #define __RESTRICT
+  #endif
+
+
+#else
+  #error Unknown compiler.
+#endif
+
+
+#endif /* __CMSIS_COMPILER_H */
+

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/cmsis/CMSIS/Core/Include/cmsis_gcc.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/cmsis/CMSIS/Core/Include/cmsis_gcc.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,2085 @@
+/**************************************************************************//**
+ * @file     cmsis_gcc.h
+ * @brief    CMSIS compiler GCC header file
+ * @version  V5.0.4
+ * @date     09. April 2018
+ ******************************************************************************/
+/*
+ * Copyright (c) 2009-2018 Arm Limited. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef __CMSIS_GCC_H
+#define __CMSIS_GCC_H
+
+/* ignore some GCC warnings */
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wsign-conversion"
+#pragma GCC diagnostic ignored "-Wconversion"
+#pragma GCC diagnostic ignored "-Wunused-parameter"
+
+/* Fallback for __has_builtin */
+#ifndef __has_builtin
+  #define __has_builtin(x) (0)
+#endif
+
+/* CMSIS compiler specific defines */
+#ifndef   __ASM
+  #define __ASM                                  __asm
+#endif
+#ifndef   __INLINE
+  #define __INLINE                               inline
+#endif
+#ifndef   __STATIC_INLINE
+  #define __STATIC_INLINE                        static inline
+#endif
+#ifndef   __STATIC_FORCEINLINE                 
+  #define __STATIC_FORCEINLINE                   __attribute__((always_inline)) static inline
+#endif                                           
+#ifndef   __NO_RETURN
+  #define __NO_RETURN                            __attribute__((__noreturn__))
+#endif
+#ifndef   __USED
+  #define __USED                                 __attribute__((used))
+#endif
+#ifndef   __WEAK
+  #define __WEAK                                 __attribute__((weak))
+#endif
+#ifndef   __PACKED
+  #define __PACKED                               __attribute__((packed, aligned(1)))
+#endif
+#ifndef   __PACKED_STRUCT
+  #define __PACKED_STRUCT                        struct __attribute__((packed, aligned(1)))
+#endif
+#ifndef   __PACKED_UNION
+  #define __PACKED_UNION                         union __attribute__((packed, aligned(1)))
+#endif
+#ifndef   __UNALIGNED_UINT32        /* deprecated */
+  #pragma GCC diagnostic push
+  #pragma GCC diagnostic ignored "-Wpacked"
+  #pragma GCC diagnostic ignored "-Wattributes"
+  struct __attribute__((packed)) T_UINT32 { uint32_t v; };
+  #pragma GCC diagnostic pop
+  #define __UNALIGNED_UINT32(x)                  (((struct T_UINT32 *)(x))->v)
+#endif
+#ifndef   __UNALIGNED_UINT16_WRITE
+  #pragma GCC diagnostic push
+  #pragma GCC diagnostic ignored "-Wpacked"
+  #pragma GCC diagnostic ignored "-Wattributes"
+  __PACKED_STRUCT T_UINT16_WRITE { uint16_t v; };
+  #pragma GCC diagnostic pop
+  #define __UNALIGNED_UINT16_WRITE(addr, val)    (void)((((struct T_UINT16_WRITE *)(void *)(addr))->v) = (val))
+#endif
+#ifndef   __UNALIGNED_UINT16_READ
+  #pragma GCC diagnostic push
+  #pragma GCC diagnostic ignored "-Wpacked"
+  #pragma GCC diagnostic ignored "-Wattributes"
+  __PACKED_STRUCT T_UINT16_READ { uint16_t v; };
+  #pragma GCC diagnostic pop
+  #define __UNALIGNED_UINT16_READ(addr)          (((const struct T_UINT16_READ *)(const void *)(addr))->v)
+#endif
+#ifndef   __UNALIGNED_UINT32_WRITE
+  #pragma GCC diagnostic push
+  #pragma GCC diagnostic ignored "-Wpacked"
+  #pragma GCC diagnostic ignored "-Wattributes"
+  __PACKED_STRUCT T_UINT32_WRITE { uint32_t v; };
+  #pragma GCC diagnostic pop
+  #define __UNALIGNED_UINT32_WRITE(addr, val)    (void)((((struct T_UINT32_WRITE *)(void *)(addr))->v) = (val))
+#endif
+#ifndef   __UNALIGNED_UINT32_READ
+  #pragma GCC diagnostic push
+  #pragma GCC diagnostic ignored "-Wpacked"
+  #pragma GCC diagnostic ignored "-Wattributes"
+  __PACKED_STRUCT T_UINT32_READ { uint32_t v; };
+  #pragma GCC diagnostic pop
+  #define __UNALIGNED_UINT32_READ(addr)          (((const struct T_UINT32_READ *)(const void *)(addr))->v)
+#endif
+#ifndef   __ALIGNED
+  #define __ALIGNED(x)                           __attribute__((aligned(x)))
+#endif
+#ifndef   __RESTRICT
+  #define __RESTRICT                             __restrict
+#endif
+
+
+/* ###########################  Core Function Access  ########################### */
+/** \ingroup  CMSIS_Core_FunctionInterface
+    \defgroup CMSIS_Core_RegAccFunctions CMSIS Core Register Access Functions
+  @{
+ */
+
+/**
+  \brief   Enable IRQ Interrupts
+  \details Enables IRQ interrupts by clearing the I-bit in the CPSR.
+           Can only be executed in Privileged modes.
+ */
+__STATIC_FORCEINLINE void __enable_irq(void)
+{
+  __ASM volatile ("cpsie i" : : : "memory");
+}
+
+
+/**
+  \brief   Disable IRQ Interrupts
+  \details Disables IRQ interrupts by setting the I-bit in the CPSR.
+           Can only be executed in Privileged modes.
+ */
+__STATIC_FORCEINLINE void __disable_irq(void)
+{
+  __ASM volatile ("cpsid i" : : : "memory");
+}
+
+
+/**
+  \brief   Get Control Register
+  \details Returns the content of the Control Register.
+  \return               Control Register value
+ */
+__STATIC_FORCEINLINE uint32_t __get_CONTROL(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, control" : "=r" (result) );
+  return(result);
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE ) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Get Control Register (non-secure)
+  \details Returns the content of the non-secure Control Register when in secure mode.
+  \return               non-secure Control Register value
+ */
+__STATIC_FORCEINLINE uint32_t __TZ_get_CONTROL_NS(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, control_ns" : "=r" (result) );
+  return(result);
+}
+#endif
+
+
+/**
+  \brief   Set Control Register
+  \details Writes the given value to the Control Register.
+  \param [in]    control  Control Register value to set
+ */
+__STATIC_FORCEINLINE void __set_CONTROL(uint32_t control)
+{
+  __ASM volatile ("MSR control, %0" : : "r" (control) : "memory");
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE ) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Set Control Register (non-secure)
+  \details Writes the given value to the non-secure Control Register when in secure state.
+  \param [in]    control  Control Register value to set
+ */
+__STATIC_FORCEINLINE void __TZ_set_CONTROL_NS(uint32_t control)
+{
+  __ASM volatile ("MSR control_ns, %0" : : "r" (control) : "memory");
+}
+#endif
+
+
+/**
+  \brief   Get IPSR Register
+  \details Returns the content of the IPSR Register.
+  \return               IPSR Register value
+ */
+__STATIC_FORCEINLINE uint32_t __get_IPSR(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, ipsr" : "=r" (result) );
+  return(result);
+}
+
+
+/**
+  \brief   Get APSR Register
+  \details Returns the content of the APSR Register.
+  \return               APSR Register value
+ */
+__STATIC_FORCEINLINE uint32_t __get_APSR(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, apsr" : "=r" (result) );
+  return(result);
+}
+
+
+/**
+  \brief   Get xPSR Register
+  \details Returns the content of the xPSR Register.
+  \return               xPSR Register value
+ */
+__STATIC_FORCEINLINE uint32_t __get_xPSR(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, xpsr" : "=r" (result) );
+  return(result);
+}
+
+
+/**
+  \brief   Get Process Stack Pointer
+  \details Returns the current value of the Process Stack Pointer (PSP).
+  \return               PSP Register value
+ */
+__STATIC_FORCEINLINE uint32_t __get_PSP(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, psp"  : "=r" (result) );
+  return(result);
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE ) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Get Process Stack Pointer (non-secure)
+  \details Returns the current value of the non-secure Process Stack Pointer (PSP) when in secure state.
+  \return               PSP Register value
+ */
+__STATIC_FORCEINLINE uint32_t __TZ_get_PSP_NS(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, psp_ns"  : "=r" (result) );
+  return(result);
+}
+#endif
+
+
+/**
+  \brief   Set Process Stack Pointer
+  \details Assigns the given value to the Process Stack Pointer (PSP).
+  \param [in]    topOfProcStack  Process Stack Pointer value to set
+ */
+__STATIC_FORCEINLINE void __set_PSP(uint32_t topOfProcStack)
+{
+  __ASM volatile ("MSR psp, %0" : : "r" (topOfProcStack) : );
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE ) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Set Process Stack Pointer (non-secure)
+  \details Assigns the given value to the non-secure Process Stack Pointer (PSP) when in secure state.
+  \param [in]    topOfProcStack  Process Stack Pointer value to set
+ */
+__STATIC_FORCEINLINE void __TZ_set_PSP_NS(uint32_t topOfProcStack)
+{
+  __ASM volatile ("MSR psp_ns, %0" : : "r" (topOfProcStack) : );
+}
+#endif
+
+
+/**
+  \brief   Get Main Stack Pointer
+  \details Returns the current value of the Main Stack Pointer (MSP).
+  \return               MSP Register value
+ */
+__STATIC_FORCEINLINE uint32_t __get_MSP(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, msp" : "=r" (result) );
+  return(result);
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE ) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Get Main Stack Pointer (non-secure)
+  \details Returns the current value of the non-secure Main Stack Pointer (MSP) when in secure state.
+  \return               MSP Register value
+ */
+__STATIC_FORCEINLINE uint32_t __TZ_get_MSP_NS(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, msp_ns" : "=r" (result) );
+  return(result);
+}
+#endif
+
+
+/**
+  \brief   Set Main Stack Pointer
+  \details Assigns the given value to the Main Stack Pointer (MSP).
+  \param [in]    topOfMainStack  Main Stack Pointer value to set
+ */
+__STATIC_FORCEINLINE void __set_MSP(uint32_t topOfMainStack)
+{
+  __ASM volatile ("MSR msp, %0" : : "r" (topOfMainStack) : );
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE ) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Set Main Stack Pointer (non-secure)
+  \details Assigns the given value to the non-secure Main Stack Pointer (MSP) when in secure state.
+  \param [in]    topOfMainStack  Main Stack Pointer value to set
+ */
+__STATIC_FORCEINLINE void __TZ_set_MSP_NS(uint32_t topOfMainStack)
+{
+  __ASM volatile ("MSR msp_ns, %0" : : "r" (topOfMainStack) : );
+}
+#endif
+
+
+#if (defined (__ARM_FEATURE_CMSE ) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Get Stack Pointer (non-secure)
+  \details Returns the current value of the non-secure Stack Pointer (SP) when in secure state.
+  \return               SP Register value
+ */
+__STATIC_FORCEINLINE uint32_t __TZ_get_SP_NS(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, sp_ns" : "=r" (result) );
+  return(result);
+}
+
+
+/**
+  \brief   Set Stack Pointer (non-secure)
+  \details Assigns the given value to the non-secure Stack Pointer (SP) when in secure state.
+  \param [in]    topOfStack  Stack Pointer value to set
+ */
+__STATIC_FORCEINLINE void __TZ_set_SP_NS(uint32_t topOfStack)
+{
+  __ASM volatile ("MSR sp_ns, %0" : : "r" (topOfStack) : );
+}
+#endif
+
+
+/**
+  \brief   Get Priority Mask
+  \details Returns the current state of the priority mask bit from the Priority Mask Register.
+  \return               Priority Mask value
+ */
+__STATIC_FORCEINLINE uint32_t __get_PRIMASK(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, primask" : "=r" (result) :: "memory");
+  return(result);
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE ) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Get Priority Mask (non-secure)
+  \details Returns the current state of the non-secure priority mask bit from the Priority Mask Register when in secure state.
+  \return               Priority Mask value
+ */
+__STATIC_FORCEINLINE uint32_t __TZ_get_PRIMASK_NS(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, primask_ns" : "=r" (result) :: "memory");
+  return(result);
+}
+#endif
+
+
+/**
+  \brief   Set Priority Mask
+  \details Assigns the given value to the Priority Mask Register.
+  \param [in]    priMask  Priority Mask
+ */
+__STATIC_FORCEINLINE void __set_PRIMASK(uint32_t priMask)
+{
+  __ASM volatile ("MSR primask, %0" : : "r" (priMask) : "memory");
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE ) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Set Priority Mask (non-secure)
+  \details Assigns the given value to the non-secure Priority Mask Register when in secure state.
+  \param [in]    priMask  Priority Mask
+ */
+__STATIC_FORCEINLINE void __TZ_set_PRIMASK_NS(uint32_t priMask)
+{
+  __ASM volatile ("MSR primask_ns, %0" : : "r" (priMask) : "memory");
+}
+#endif
+
+
+#if ((defined (__ARM_ARCH_7M__      ) && (__ARM_ARCH_7M__      == 1)) || \
+     (defined (__ARM_ARCH_7EM__     ) && (__ARM_ARCH_7EM__     == 1)) || \
+     (defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1))    )
+/**
+  \brief   Enable FIQ
+  \details Enables FIQ interrupts by clearing the F-bit in the CPSR.
+           Can only be executed in Privileged modes.
+ */
+__STATIC_FORCEINLINE void __enable_fault_irq(void)
+{
+  __ASM volatile ("cpsie f" : : : "memory");
+}
+
+
+/**
+  \brief   Disable FIQ
+  \details Disables FIQ interrupts by setting the F-bit in the CPSR.
+           Can only be executed in Privileged modes.
+ */
+__STATIC_FORCEINLINE void __disable_fault_irq(void)
+{
+  __ASM volatile ("cpsid f" : : : "memory");
+}
+
+
+/**
+  \brief   Get Base Priority
+  \details Returns the current value of the Base Priority register.
+  \return               Base Priority register value
+ */
+__STATIC_FORCEINLINE uint32_t __get_BASEPRI(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, basepri" : "=r" (result) );
+  return(result);
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE ) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Get Base Priority (non-secure)
+  \details Returns the current value of the non-secure Base Priority register when in secure state.
+  \return               Base Priority register value
+ */
+__STATIC_FORCEINLINE uint32_t __TZ_get_BASEPRI_NS(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, basepri_ns" : "=r" (result) );
+  return(result);
+}
+#endif
+
+
+/**
+  \brief   Set Base Priority
+  \details Assigns the given value to the Base Priority register.
+  \param [in]    basePri  Base Priority value to set
+ */
+__STATIC_FORCEINLINE void __set_BASEPRI(uint32_t basePri)
+{
+  __ASM volatile ("MSR basepri, %0" : : "r" (basePri) : "memory");
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE ) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Set Base Priority (non-secure)
+  \details Assigns the given value to the non-secure Base Priority register when in secure state.
+  \param [in]    basePri  Base Priority value to set
+ */
+__STATIC_FORCEINLINE void __TZ_set_BASEPRI_NS(uint32_t basePri)
+{
+  __ASM volatile ("MSR basepri_ns, %0" : : "r" (basePri) : "memory");
+}
+#endif
+
+
+/**
+  \brief   Set Base Priority with condition
+  \details Assigns the given value to the Base Priority register only if BASEPRI masking is disabled,
+           or the new value increases the BASEPRI priority level.
+  \param [in]    basePri  Base Priority value to set
+ */
+__STATIC_FORCEINLINE void __set_BASEPRI_MAX(uint32_t basePri)
+{
+  __ASM volatile ("MSR basepri_max, %0" : : "r" (basePri) : "memory");
+}
+
+
+/**
+  \brief   Get Fault Mask
+  \details Returns the current value of the Fault Mask register.
+  \return               Fault Mask register value
+ */
+__STATIC_FORCEINLINE uint32_t __get_FAULTMASK(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, faultmask" : "=r" (result) );
+  return(result);
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE ) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Get Fault Mask (non-secure)
+  \details Returns the current value of the non-secure Fault Mask register when in secure state.
+  \return               Fault Mask register value
+ */
+__STATIC_FORCEINLINE uint32_t __TZ_get_FAULTMASK_NS(void)
+{
+  uint32_t result;
+
+  __ASM volatile ("MRS %0, faultmask_ns" : "=r" (result) );
+  return(result);
+}
+#endif
+
+
+/**
+  \brief   Set Fault Mask
+  \details Assigns the given value to the Fault Mask register.
+  \param [in]    faultMask  Fault Mask value to set
+ */
+__STATIC_FORCEINLINE void __set_FAULTMASK(uint32_t faultMask)
+{
+  __ASM volatile ("MSR faultmask, %0" : : "r" (faultMask) : "memory");
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE ) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Set Fault Mask (non-secure)
+  \details Assigns the given value to the non-secure Fault Mask register when in secure state.
+  \param [in]    faultMask  Fault Mask value to set
+ */
+__STATIC_FORCEINLINE void __TZ_set_FAULTMASK_NS(uint32_t faultMask)
+{
+  __ASM volatile ("MSR faultmask_ns, %0" : : "r" (faultMask) : "memory");
+}
+#endif
+
+#endif /* ((defined (__ARM_ARCH_7M__      ) && (__ARM_ARCH_7M__      == 1)) || \
+           (defined (__ARM_ARCH_7EM__     ) && (__ARM_ARCH_7EM__     == 1)) || \
+           (defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1))    ) */
+
+
+#if ((defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)) || \
+     (defined (__ARM_ARCH_8M_BASE__ ) && (__ARM_ARCH_8M_BASE__ == 1))    )
+
+/**
+  \brief   Get Process Stack Pointer Limit
+  Devices without ARMv8-M Main Extensions (i.e. Cortex-M23) lack the non-secure
+  Stack Pointer Limit register hence zero is returned always in non-secure
+  mode.
+  
+  \details Returns the current value of the Process Stack Pointer Limit (PSPLIM).
+  \return               PSPLIM Register value
+ */
+__STATIC_FORCEINLINE uint32_t __get_PSPLIM(void)
+{
+#if (!(defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)) && \
+    (!defined (__ARM_FEATURE_CMSE) || (__ARM_FEATURE_CMSE < 3)))
+    // without main extensions, the non-secure PSPLIM is RAZ/WI
+  return 0U;
+#else
+  uint32_t result;
+  __ASM volatile ("MRS %0, psplim"  : "=r" (result) );
+  return result;
+#endif
+}
+
+#if (defined (__ARM_FEATURE_CMSE) && (__ARM_FEATURE_CMSE == 3))
+/**
+  \brief   Get Process Stack Pointer Limit (non-secure)
+  Devices without ARMv8-M Main Extensions (i.e. Cortex-M23) lack the non-secure
+  Stack Pointer Limit register hence zero is returned always.
+
+  \details Returns the current value of the non-secure Process Stack Pointer Limit (PSPLIM) when in secure state.
+  \return               PSPLIM Register value
+ */
+__STATIC_FORCEINLINE uint32_t __TZ_get_PSPLIM_NS(void)
+{
+#if (!(defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)))
+  // without main extensions, the non-secure PSPLIM is RAZ/WI
+  return 0U;
+#else
+  uint32_t result;
+  __ASM volatile ("MRS %0, psplim_ns"  : "=r" (result) );
+  return result;
+#endif
+}
+#endif
+
+
+/**
+  \brief   Set Process Stack Pointer Limit
+  Devices without ARMv8-M Main Extensions (i.e. Cortex-M23) lack the non-secure
+  Stack Pointer Limit register hence the write is silently ignored in non-secure
+  mode.
+  
+  \details Assigns the given value to the Process Stack Pointer Limit (PSPLIM).
+  \param [in]    ProcStackPtrLimit  Process Stack Pointer Limit value to set
+ */
+__STATIC_FORCEINLINE void __set_PSPLIM(uint32_t ProcStackPtrLimit)
+{
+#if (!(defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)) && \
+    (!defined (__ARM_FEATURE_CMSE) || (__ARM_FEATURE_CMSE < 3)))
+  // without main extensions, the non-secure PSPLIM is RAZ/WI
+  (void)ProcStackPtrLimit;
+#else
+  __ASM volatile ("MSR psplim, %0" : : "r" (ProcStackPtrLimit));
+#endif
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE  ) && (__ARM_FEATURE_CMSE   == 3))
+/**
+  \brief   Set Process Stack Pointer (non-secure)
+  Devices without ARMv8-M Main Extensions (i.e. Cortex-M23) lack the non-secure
+  Stack Pointer Limit register hence the write is silently ignored.
+
+  \details Assigns the given value to the non-secure Process Stack Pointer Limit (PSPLIM) when in secure state.
+  \param [in]    ProcStackPtrLimit  Process Stack Pointer Limit value to set
+ */
+__STATIC_FORCEINLINE void __TZ_set_PSPLIM_NS(uint32_t ProcStackPtrLimit)
+{
+#if (!(defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)))
+  // without main extensions, the non-secure PSPLIM is RAZ/WI
+  (void)ProcStackPtrLimit;
+#else
+  __ASM volatile ("MSR psplim_ns, %0\n" : : "r" (ProcStackPtrLimit));
+#endif
+}
+#endif
+
+
+/**
+  \brief   Get Main Stack Pointer Limit
+  Devices without ARMv8-M Main Extensions (i.e. Cortex-M23) lack the non-secure
+  Stack Pointer Limit register hence zero is returned always in non-secure
+  mode.
+
+  \details Returns the current value of the Main Stack Pointer Limit (MSPLIM).
+  \return               MSPLIM Register value
+ */
+__STATIC_FORCEINLINE uint32_t __get_MSPLIM(void)
+{
+#if (!(defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)) && \
+    (!defined (__ARM_FEATURE_CMSE) || (__ARM_FEATURE_CMSE < 3)))
+  // without main extensions, the non-secure MSPLIM is RAZ/WI
+  return 0U;
+#else
+  uint32_t result;
+  __ASM volatile ("MRS %0, msplim" : "=r" (result) );
+  return result;
+#endif
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE  ) && (__ARM_FEATURE_CMSE   == 3))
+/**
+  \brief   Get Main Stack Pointer Limit (non-secure)
+  Devices without ARMv8-M Main Extensions (i.e. Cortex-M23) lack the non-secure
+  Stack Pointer Limit register hence zero is returned always.
+
+  \details Returns the current value of the non-secure Main Stack Pointer Limit(MSPLIM) when in secure state.
+  \return               MSPLIM Register value
+ */
+__STATIC_FORCEINLINE uint32_t __TZ_get_MSPLIM_NS(void)
+{
+#if (!(defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)))
+  // without main extensions, the non-secure MSPLIM is RAZ/WI
+  return 0U;
+#else
+  uint32_t result;
+  __ASM volatile ("MRS %0, msplim_ns" : "=r" (result) );
+  return result;
+#endif
+}
+#endif
+
+
+/**
+  \brief   Set Main Stack Pointer Limit
+  Devices without ARMv8-M Main Extensions (i.e. Cortex-M23) lack the non-secure
+  Stack Pointer Limit register hence the write is silently ignored in non-secure
+  mode.
+
+  \details Assigns the given value to the Main Stack Pointer Limit (MSPLIM).
+  \param [in]    MainStackPtrLimit  Main Stack Pointer Limit value to set
+ */
+__STATIC_FORCEINLINE void __set_MSPLIM(uint32_t MainStackPtrLimit)
+{
+#if (!(defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)) && \
+    (!defined (__ARM_FEATURE_CMSE) || (__ARM_FEATURE_CMSE < 3)))
+  // without main extensions, the non-secure MSPLIM is RAZ/WI
+  (void)MainStackPtrLimit;
+#else
+  __ASM volatile ("MSR msplim, %0" : : "r" (MainStackPtrLimit));
+#endif
+}
+
+
+#if (defined (__ARM_FEATURE_CMSE  ) && (__ARM_FEATURE_CMSE   == 3))
+/**
+  \brief   Set Main Stack Pointer Limit (non-secure)
+  Devices without ARMv8-M Main Extensions (i.e. Cortex-M23) lack the non-secure
+  Stack Pointer Limit register hence the write is silently ignored.
+
+  \details Assigns the given value to the non-secure Main Stack Pointer Limit (MSPLIM) when in secure state.
+  \param [in]    MainStackPtrLimit  Main Stack Pointer value to set
+ */
+__STATIC_FORCEINLINE void __TZ_set_MSPLIM_NS(uint32_t MainStackPtrLimit)
+{
+#if (!(defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)))
+  // without main extensions, the non-secure MSPLIM is RAZ/WI
+  (void)MainStackPtrLimit;
+#else
+  __ASM volatile ("MSR msplim_ns, %0" : : "r" (MainStackPtrLimit));
+#endif
+}
+#endif
+
+#endif /* ((defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)) || \
+           (defined (__ARM_ARCH_8M_BASE__ ) && (__ARM_ARCH_8M_BASE__ == 1))    ) */
+
+
+/**
+  \brief   Get FPSCR
+  \details Returns the current value of the Floating Point Status/Control register.
+  \return               Floating Point Status/Control register value
+ */
+__STATIC_FORCEINLINE uint32_t __get_FPSCR(void)
+{
+#if ((defined (__FPU_PRESENT) && (__FPU_PRESENT == 1U)) && \
+     (defined (__FPU_USED   ) && (__FPU_USED    == 1U))     )
+#if __has_builtin(__builtin_arm_get_fpscr) 
+// Re-enable using built-in when GCC has been fixed
+// || (__GNUC__ > 7) || (__GNUC__ == 7 && __GNUC_MINOR__ >= 2)
+  /* see https://gcc.gnu.org/ml/gcc-patches/2017-04/msg00443.html */
+  return __builtin_arm_get_fpscr();
+#else
+  uint32_t result;
+
+  __ASM volatile ("VMRS %0, fpscr" : "=r" (result) );
+  return(result);
+#endif
+#else
+  return(0U);
+#endif
+}
+
+
+/**
+  \brief   Set FPSCR
+  \details Assigns the given value to the Floating Point Status/Control register.
+  \param [in]    fpscr  Floating Point Status/Control value to set
+ */
+__STATIC_FORCEINLINE void __set_FPSCR(uint32_t fpscr)
+{
+#if ((defined (__FPU_PRESENT) && (__FPU_PRESENT == 1U)) && \
+     (defined (__FPU_USED   ) && (__FPU_USED    == 1U))     )
+#if __has_builtin(__builtin_arm_set_fpscr)
+// Re-enable using built-in when GCC has been fixed
+// || (__GNUC__ > 7) || (__GNUC__ == 7 && __GNUC_MINOR__ >= 2)
+  /* see https://gcc.gnu.org/ml/gcc-patches/2017-04/msg00443.html */
+  __builtin_arm_set_fpscr(fpscr);
+#else
+  __ASM volatile ("VMSR fpscr, %0" : : "r" (fpscr) : "vfpcc", "memory");
+#endif
+#else
+  (void)fpscr;
+#endif
+}
+
+
+/*@} end of CMSIS_Core_RegAccFunctions */
+
+
+/* ##########################  Core Instruction Access  ######################### */
+/** \defgroup CMSIS_Core_InstructionInterface CMSIS Core Instruction Interface
+  Access to dedicated instructions
+  @{
+*/
+
+/* Define macros for porting to both thumb1 and thumb2.
+ * For thumb1, use low register (r0-r7), specified by constraint "l"
+ * Otherwise, use general registers, specified by constraint "r" */
+#if defined (__thumb__) && !defined (__thumb2__)
+#define __CMSIS_GCC_OUT_REG(r) "=l" (r)
+#define __CMSIS_GCC_RW_REG(r) "+l" (r)
+#define __CMSIS_GCC_USE_REG(r) "l" (r)
+#else
+#define __CMSIS_GCC_OUT_REG(r) "=r" (r)
+#define __CMSIS_GCC_RW_REG(r) "+r" (r)
+#define __CMSIS_GCC_USE_REG(r) "r" (r)
+#endif
+
+/**
+  \brief   No Operation
+  \details No Operation does nothing. This instruction can be used for code alignment purposes.
+ */
+#define __NOP()                             __ASM volatile ("nop")
+
+/**
+  \brief   Wait For Interrupt
+  \details Wait For Interrupt is a hint instruction that suspends execution until one of a number of events occurs.
+ */
+#define __WFI()                             __ASM volatile ("wfi")
+
+
+/**
+  \brief   Wait For Event
+  \details Wait For Event is a hint instruction that permits the processor to enter
+           a low-power state until one of a number of events occurs.
+ */
+#define __WFE()                             __ASM volatile ("wfe")
+
+
+/**
+  \brief   Send Event
+  \details Send Event is a hint instruction. It causes an event to be signaled to the CPU.
+ */
+#define __SEV()                             __ASM volatile ("sev")
+
+
+/**
+  \brief   Instruction Synchronization Barrier
+  \details Instruction Synchronization Barrier flushes the pipeline in the processor,
+           so that all instructions following the ISB are fetched from cache or memory,
+           after the instruction has been completed.
+ */
+__STATIC_FORCEINLINE void __ISB(void)
+{
+  __ASM volatile ("isb 0xF":::"memory");
+}
+
+
+/**
+  \brief   Data Synchronization Barrier
+  \details Acts as a special kind of Data Memory Barrier.
+           It completes when all explicit memory accesses before this instruction complete.
+ */
+__STATIC_FORCEINLINE void __DSB(void)
+{
+  __ASM volatile ("dsb 0xF":::"memory");
+}
+
+
+/**
+  \brief   Data Memory Barrier
+  \details Ensures the apparent order of the explicit memory operations before
+           and after the instruction, without ensuring their completion.
+ */
+__STATIC_FORCEINLINE void __DMB(void)
+{
+  __ASM volatile ("dmb 0xF":::"memory");
+}
+
+
+/**
+  \brief   Reverse byte order (32 bit)
+  \details Reverses the byte order in unsigned integer value. For example, 0x12345678 becomes 0x78563412.
+  \param [in]    value  Value to reverse
+  \return               Reversed value
+ */
+__STATIC_FORCEINLINE uint32_t __REV(uint32_t value)
+{
+#if (__GNUC__ > 4) || (__GNUC__ == 4 && __GNUC_MINOR__ >= 5)
+  return __builtin_bswap32(value);
+#else
+  uint32_t result;
+
+  __ASM volatile ("rev %0, %1" : __CMSIS_GCC_OUT_REG (result) : __CMSIS_GCC_USE_REG (value) );
+  return result;
+#endif
+}
+
+
+/**
+  \brief   Reverse byte order (16 bit)
+  \details Reverses the byte order within each halfword of a word. For example, 0x12345678 becomes 0x34127856.
+  \param [in]    value  Value to reverse
+  \return               Reversed value
+ */
+__STATIC_FORCEINLINE uint32_t __REV16(uint32_t value)
+{
+  uint32_t result;
+
+  __ASM volatile ("rev16 %0, %1" : __CMSIS_GCC_OUT_REG (result) : __CMSIS_GCC_USE_REG (value) );
+  return result;
+}
+
+
+/**
+  \brief   Reverse byte order (16 bit)
+  \details Reverses the byte order in a 16-bit value and returns the signed 16-bit result. For example, 0x0080 becomes 0x8000.
+  \param [in]    value  Value to reverse
+  \return               Reversed value
+ */
+__STATIC_FORCEINLINE int16_t __REVSH(int16_t value)
+{
+#if (__GNUC__ > 4) || (__GNUC__ == 4 && __GNUC_MINOR__ >= 8)
+  return (int16_t)__builtin_bswap16(value);
+#else
+  int16_t result;
+
+  __ASM volatile ("revsh %0, %1" : __CMSIS_GCC_OUT_REG (result) : __CMSIS_GCC_USE_REG (value) );
+  return result;
+#endif
+}
+
+
+/**
+  \brief   Rotate Right in unsigned value (32 bit)
+  \details Rotate Right (immediate) provides the value of the contents of a register rotated by a variable number of bits.
+  \param [in]    op1  Value to rotate
+  \param [in]    op2  Number of Bits to rotate
+  \return               Rotated value
+ */
+__STATIC_FORCEINLINE uint32_t __ROR(uint32_t op1, uint32_t op2)
+{
+  op2 %= 32U;
+  if (op2 == 0U)
+  {
+    return op1;
+  }
+  return (op1 >> op2) | (op1 << (32U - op2));
+}
+
+
+/**
+  \brief   Breakpoint
+  \details Causes the processor to enter Debug state.
+           Debug tools can use this to investigate system state when the instruction at a particular address is reached.
+  \param [in]    value  is ignored by the processor.
+                 If required, a debugger can use it to store additional information about the breakpoint.
+ */
+#define __BKPT(value)                       __ASM volatile ("bkpt "#value)
+
+
+/**
+  \brief   Reverse bit order of value
+  \details Reverses the bit order of the given value.
+  \param [in]    value  Value to reverse
+  \return               Reversed value
+ */
+__STATIC_FORCEINLINE uint32_t __RBIT(uint32_t value)
+{
+  uint32_t result;
+
+#if ((defined (__ARM_ARCH_7M__      ) && (__ARM_ARCH_7M__      == 1)) || \
+     (defined (__ARM_ARCH_7EM__     ) && (__ARM_ARCH_7EM__     == 1)) || \
+     (defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1))    )
+   __ASM volatile ("rbit %0, %1" : "=r" (result) : "r" (value) );
+#else
+  uint32_t s = (4U /*sizeof(v)*/ * 8U) - 1U; /* extra shift needed at end */
+
+  result = value;                      /* r will be reversed bits of v; first get LSB of v */
+  for (value >>= 1U; value != 0U; value >>= 1U)
+  {
+    result <<= 1U;
+    result |= value & 1U;
+    s--;
+  }
+  result <<= s;                        /* shift when v's highest bits are zero */
+#endif
+  return result;
+}
+
+
+/**
+  \brief   Count leading zeros
+  \details Counts the number of leading zeros of a data value.
+  \param [in]  value  Value to count the leading zeros
+  \return             number of leading zeros in value
+ */
+#define __CLZ             (uint8_t)__builtin_clz
+
+
+#if ((defined (__ARM_ARCH_7M__      ) && (__ARM_ARCH_7M__      == 1)) || \
+     (defined (__ARM_ARCH_7EM__     ) && (__ARM_ARCH_7EM__     == 1)) || \
+     (defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)) || \
+     (defined (__ARM_ARCH_8M_BASE__ ) && (__ARM_ARCH_8M_BASE__ == 1))    )
+/**
+  \brief   LDR Exclusive (8 bit)
+  \details Executes a exclusive LDR instruction for 8 bit value.
+  \param [in]    ptr  Pointer to data
+  \return             value of type uint8_t at (*ptr)
+ */
+__STATIC_FORCEINLINE uint8_t __LDREXB(volatile uint8_t *addr)
+{
+    uint32_t result;
+
+#if (__GNUC__ > 4) || (__GNUC__ == 4 && __GNUC_MINOR__ >= 8)
+   __ASM volatile ("ldrexb %0, %1" : "=r" (result) : "Q" (*addr) );
+#else
+    /* Prior to GCC 4.8, "Q" will be expanded to [rx, #0] which is not
+       accepted by assembler. So has to use following less efficient pattern.
+    */
+   __ASM volatile ("ldrexb %0, [%1]" : "=r" (result) : "r" (addr) : "memory" );
+#endif
+   return ((uint8_t) result);    /* Add explicit type cast here */
+}
+
+
+/**
+  \brief   LDR Exclusive (16 bit)
+  \details Executes a exclusive LDR instruction for 16 bit values.
+  \param [in]    ptr  Pointer to data
+  \return        value of type uint16_t at (*ptr)
+ */
+__STATIC_FORCEINLINE uint16_t __LDREXH(volatile uint16_t *addr)
+{
+    uint32_t result;
+
+#if (__GNUC__ > 4) || (__GNUC__ == 4 && __GNUC_MINOR__ >= 8)
+   __ASM volatile ("ldrexh %0, %1" : "=r" (result) : "Q" (*addr) );
+#else
+    /* Prior to GCC 4.8, "Q" will be expanded to [rx, #0] which is not
+       accepted by assembler. So has to use following less efficient pattern.
+    */
+   __ASM volatile ("ldrexh %0, [%1]" : "=r" (result) : "r" (addr) : "memory" );
+#endif
+   return ((uint16_t) result);    /* Add explicit type cast here */
+}
+
+
+/**
+  \brief   LDR Exclusive (32 bit)
+  \details Executes a exclusive LDR instruction for 32 bit values.
+  \param [in]    ptr  Pointer to data
+  \return        value of type uint32_t at (*ptr)
+ */
+__STATIC_FORCEINLINE uint32_t __LDREXW(volatile uint32_t *addr)
+{
+    uint32_t result;
+
+   __ASM volatile ("ldrex %0, %1" : "=r" (result) : "Q" (*addr) );
+   return(result);
+}
+
+
+/**
+  \brief   STR Exclusive (8 bit)
+  \details Executes a exclusive STR instruction for 8 bit values.
+  \param [in]  value  Value to store
+  \param [in]    ptr  Pointer to location
+  \return          0  Function succeeded
+  \return          1  Function failed
+ */
+__STATIC_FORCEINLINE uint32_t __STREXB(uint8_t value, volatile uint8_t *addr)
+{
+   uint32_t result;
+
+   __ASM volatile ("strexb %0, %2, %1" : "=&r" (result), "=Q" (*addr) : "r" ((uint32_t)value) );
+   return(result);
+}
+
+
+/**
+  \brief   STR Exclusive (16 bit)
+  \details Executes a exclusive STR instruction for 16 bit values.
+  \param [in]  value  Value to store
+  \param [in]    ptr  Pointer to location
+  \return          0  Function succeeded
+  \return          1  Function failed
+ */
+__STATIC_FORCEINLINE uint32_t __STREXH(uint16_t value, volatile uint16_t *addr)
+{
+   uint32_t result;
+
+   __ASM volatile ("strexh %0, %2, %1" : "=&r" (result), "=Q" (*addr) : "r" ((uint32_t)value) );
+   return(result);
+}
+
+
+/**
+  \brief   STR Exclusive (32 bit)
+  \details Executes a exclusive STR instruction for 32 bit values.
+  \param [in]  value  Value to store
+  \param [in]    ptr  Pointer to location
+  \return          0  Function succeeded
+  \return          1  Function failed
+ */
+__STATIC_FORCEINLINE uint32_t __STREXW(uint32_t value, volatile uint32_t *addr)
+{
+   uint32_t result;
+
+   __ASM volatile ("strex %0, %2, %1" : "=&r" (result), "=Q" (*addr) : "r" (value) );
+   return(result);
+}
+
+
+/**
+  \brief   Remove the exclusive lock
+  \details Removes the exclusive lock which is created by LDREX.
+ */
+__STATIC_FORCEINLINE void __CLREX(void)
+{
+  __ASM volatile ("clrex" ::: "memory");
+}
+
+#endif /* ((defined (__ARM_ARCH_7M__      ) && (__ARM_ARCH_7M__      == 1)) || \
+           (defined (__ARM_ARCH_7EM__     ) && (__ARM_ARCH_7EM__     == 1)) || \
+           (defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)) || \
+           (defined (__ARM_ARCH_8M_BASE__ ) && (__ARM_ARCH_8M_BASE__ == 1))    ) */
+
+
+#if ((defined (__ARM_ARCH_7M__      ) && (__ARM_ARCH_7M__      == 1)) || \
+     (defined (__ARM_ARCH_7EM__     ) && (__ARM_ARCH_7EM__     == 1)) || \
+     (defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1))    )
+/**
+  \brief   Signed Saturate
+  \details Saturates a signed value.
+  \param [in]  ARG1  Value to be saturated
+  \param [in]  ARG2  Bit position to saturate to (1..32)
+  \return             Saturated value
+ */
+#define __SSAT(ARG1,ARG2) \
+__extension__ \
+({                          \
+  int32_t __RES, __ARG1 = (ARG1); \
+  __ASM ("ssat %0, %1, %2" : "=r" (__RES) :  "I" (ARG2), "r" (__ARG1) ); \
+  __RES; \
+ })
+
+
+/**
+  \brief   Unsigned Saturate
+  \details Saturates an unsigned value.
+  \param [in]  ARG1  Value to be saturated
+  \param [in]  ARG2  Bit position to saturate to (0..31)
+  \return             Saturated value
+ */
+#define __USAT(ARG1,ARG2) \
+ __extension__ \
+({                          \
+  uint32_t __RES, __ARG1 = (ARG1); \
+  __ASM ("usat %0, %1, %2" : "=r" (__RES) :  "I" (ARG2), "r" (__ARG1) ); \
+  __RES; \
+ })
+
+
+/**
+  \brief   Rotate Right with Extend (32 bit)
+  \details Moves each bit of a bitstring right by one bit.
+           The carry input is shifted in at the left end of the bitstring.
+  \param [in]    value  Value to rotate
+  \return               Rotated value
+ */
+__STATIC_FORCEINLINE uint32_t __RRX(uint32_t value)
+{
+  uint32_t result;
+
+  __ASM volatile ("rrx %0, %1" : __CMSIS_GCC_OUT_REG (result) : __CMSIS_GCC_USE_REG (value) );
+  return(result);
+}
+
+
+/**
+  \brief   LDRT Unprivileged (8 bit)
+  \details Executes a Unprivileged LDRT instruction for 8 bit value.
+  \param [in]    ptr  Pointer to data
+  \return             value of type uint8_t at (*ptr)
+ */
+__STATIC_FORCEINLINE uint8_t __LDRBT(volatile uint8_t *ptr)
+{
+    uint32_t result;
+
+#if (__GNUC__ > 4) || (__GNUC__ == 4 && __GNUC_MINOR__ >= 8)
+   __ASM volatile ("ldrbt %0, %1" : "=r" (result) : "Q" (*ptr) );
+#else
+    /* Prior to GCC 4.8, "Q" will be expanded to [rx, #0] which is not
+       accepted by assembler. So has to use following less efficient pattern.
+    */
+   __ASM volatile ("ldrbt %0, [%1]" : "=r" (result) : "r" (ptr) : "memory" );
+#endif
+   return ((uint8_t) result);    /* Add explicit type cast here */
+}
+
+
+/**
+  \brief   LDRT Unprivileged (16 bit)
+  \details Executes a Unprivileged LDRT instruction for 16 bit values.
+  \param [in]    ptr  Pointer to data
+  \return        value of type uint16_t at (*ptr)
+ */
+__STATIC_FORCEINLINE uint16_t __LDRHT(volatile uint16_t *ptr)
+{
+    uint32_t result;
+
+#if (__GNUC__ > 4) || (__GNUC__ == 4 && __GNUC_MINOR__ >= 8)
+   __ASM volatile ("ldrht %0, %1" : "=r" (result) : "Q" (*ptr) );
+#else
+    /* Prior to GCC 4.8, "Q" will be expanded to [rx, #0] which is not
+       accepted by assembler. So has to use following less efficient pattern.
+    */
+   __ASM volatile ("ldrht %0, [%1]" : "=r" (result) : "r" (ptr) : "memory" );
+#endif
+   return ((uint16_t) result);    /* Add explicit type cast here */
+}
+
+
+/**
+  \brief   LDRT Unprivileged (32 bit)
+  \details Executes a Unprivileged LDRT instruction for 32 bit values.
+  \param [in]    ptr  Pointer to data
+  \return        value of type uint32_t at (*ptr)
+ */
+__STATIC_FORCEINLINE uint32_t __LDRT(volatile uint32_t *ptr)
+{
+    uint32_t result;
+
+   __ASM volatile ("ldrt %0, %1" : "=r" (result) : "Q" (*ptr) );
+   return(result);
+}
+
+
+/**
+  \brief   STRT Unprivileged (8 bit)
+  \details Executes a Unprivileged STRT instruction for 8 bit values.
+  \param [in]  value  Value to store
+  \param [in]    ptr  Pointer to location
+ */
+__STATIC_FORCEINLINE void __STRBT(uint8_t value, volatile uint8_t *ptr)
+{
+   __ASM volatile ("strbt %1, %0" : "=Q" (*ptr) : "r" ((uint32_t)value) );
+}
+
+
+/**
+  \brief   STRT Unprivileged (16 bit)
+  \details Executes a Unprivileged STRT instruction for 16 bit values.
+  \param [in]  value  Value to store
+  \param [in]    ptr  Pointer to location
+ */
+__STATIC_FORCEINLINE void __STRHT(uint16_t value, volatile uint16_t *ptr)
+{
+   __ASM volatile ("strht %1, %0" : "=Q" (*ptr) : "r" ((uint32_t)value) );
+}
+
+
+/**
+  \brief   STRT Unprivileged (32 bit)
+  \details Executes a Unprivileged STRT instruction for 32 bit values.
+  \param [in]  value  Value to store
+  \param [in]    ptr  Pointer to location
+ */
+__STATIC_FORCEINLINE void __STRT(uint32_t value, volatile uint32_t *ptr)
+{
+   __ASM volatile ("strt %1, %0" : "=Q" (*ptr) : "r" (value) );
+}
+
+#else  /* ((defined (__ARM_ARCH_7M__      ) && (__ARM_ARCH_7M__      == 1)) || \
+           (defined (__ARM_ARCH_7EM__     ) && (__ARM_ARCH_7EM__     == 1)) || \
+           (defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1))    ) */
+
+/**
+  \brief   Signed Saturate
+  \details Saturates a signed value.
+  \param [in]  value  Value to be saturated
+  \param [in]    sat  Bit position to saturate to (1..32)
+  \return             Saturated value
+ */
+__STATIC_FORCEINLINE int32_t __SSAT(int32_t val, uint32_t sat)
+{
+  if ((sat >= 1U) && (sat <= 32U))
+  {
+    const int32_t max = (int32_t)((1U << (sat - 1U)) - 1U);
+    const int32_t min = -1 - max ;
+    if (val > max)
+    {
+      return max;
+    }
+    else if (val < min)
+    {
+      return min;
+    }
+  }
+  return val;
+}
+
+/**
+  \brief   Unsigned Saturate
+  \details Saturates an unsigned value.
+  \param [in]  value  Value to be saturated
+  \param [in]    sat  Bit position to saturate to (0..31)
+  \return             Saturated value
+ */
+__STATIC_FORCEINLINE uint32_t __USAT(int32_t val, uint32_t sat)
+{
+  if (sat <= 31U)
+  {
+    const uint32_t max = ((1U << sat) - 1U);
+    if (val > (int32_t)max)
+    {
+      return max;
+    }
+    else if (val < 0)
+    {
+      return 0U;
+    }
+  }
+  return (uint32_t)val;
+}
+
+#endif /* ((defined (__ARM_ARCH_7M__      ) && (__ARM_ARCH_7M__      == 1)) || \
+           (defined (__ARM_ARCH_7EM__     ) && (__ARM_ARCH_7EM__     == 1)) || \
+           (defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1))    ) */
+
+
+#if ((defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)) || \
+     (defined (__ARM_ARCH_8M_BASE__ ) && (__ARM_ARCH_8M_BASE__ == 1))    )
+/**
+  \brief   Load-Acquire (8 bit)
+  \details Executes a LDAB instruction for 8 bit value.
+  \param [in]    ptr  Pointer to data
+  \return             value of type uint8_t at (*ptr)
+ */
+__STATIC_FORCEINLINE uint8_t __LDAB(volatile uint8_t *ptr)
+{
+    uint32_t result;
+
+   __ASM volatile ("ldab %0, %1" : "=r" (result) : "Q" (*ptr) );
+   return ((uint8_t) result);
+}
+
+
+/**
+  \brief   Load-Acquire (16 bit)
+  \details Executes a LDAH instruction for 16 bit values.
+  \param [in]    ptr  Pointer to data
+  \return        value of type uint16_t at (*ptr)
+ */
+__STATIC_FORCEINLINE uint16_t __LDAH(volatile uint16_t *ptr)
+{
+    uint32_t result;
+
+   __ASM volatile ("ldah %0, %1" : "=r" (result) : "Q" (*ptr) );
+   return ((uint16_t) result);
+}
+
+
+/**
+  \brief   Load-Acquire (32 bit)
+  \details Executes a LDA instruction for 32 bit values.
+  \param [in]    ptr  Pointer to data
+  \return        value of type uint32_t at (*ptr)
+ */
+__STATIC_FORCEINLINE uint32_t __LDA(volatile uint32_t *ptr)
+{
+    uint32_t result;
+
+   __ASM volatile ("lda %0, %1" : "=r" (result) : "Q" (*ptr) );
+   return(result);
+}
+
+
+/**
+  \brief   Store-Release (8 bit)
+  \details Executes a STLB instruction for 8 bit values.
+  \param [in]  value  Value to store
+  \param [in]    ptr  Pointer to location
+ */
+__STATIC_FORCEINLINE void __STLB(uint8_t value, volatile uint8_t *ptr)
+{
+   __ASM volatile ("stlb %1, %0" : "=Q" (*ptr) : "r" ((uint32_t)value) );
+}
+
+
+/**
+  \brief   Store-Release (16 bit)
+  \details Executes a STLH instruction for 16 bit values.
+  \param [in]  value  Value to store
+  \param [in]    ptr  Pointer to location
+ */
+__STATIC_FORCEINLINE void __STLH(uint16_t value, volatile uint16_t *ptr)
+{
+   __ASM volatile ("stlh %1, %0" : "=Q" (*ptr) : "r" ((uint32_t)value) );
+}
+
+
+/**
+  \brief   Store-Release (32 bit)
+  \details Executes a STL instruction for 32 bit values.
+  \param [in]  value  Value to store
+  \param [in]    ptr  Pointer to location
+ */
+__STATIC_FORCEINLINE void __STL(uint32_t value, volatile uint32_t *ptr)
+{
+   __ASM volatile ("stl %1, %0" : "=Q" (*ptr) : "r" ((uint32_t)value) );
+}
+
+
+/**
+  \brief   Load-Acquire Exclusive (8 bit)
+  \details Executes a LDAB exclusive instruction for 8 bit value.
+  \param [in]    ptr  Pointer to data
+  \return             value of type uint8_t at (*ptr)
+ */
+__STATIC_FORCEINLINE uint8_t __LDAEXB(volatile uint8_t *ptr)
+{
+    uint32_t result;
+
+   __ASM volatile ("ldaexb %0, %1" : "=r" (result) : "Q" (*ptr) );
+   return ((uint8_t) result);
+}
+
+
+/**
+  \brief   Load-Acquire Exclusive (16 bit)
+  \details Executes a LDAH exclusive instruction for 16 bit values.
+  \param [in]    ptr  Pointer to data
+  \return        value of type uint16_t at (*ptr)
+ */
+__STATIC_FORCEINLINE uint16_t __LDAEXH(volatile uint16_t *ptr)
+{
+    uint32_t result;
+
+   __ASM volatile ("ldaexh %0, %1" : "=r" (result) : "Q" (*ptr) );
+   return ((uint16_t) result);
+}
+
+
+/**
+  \brief   Load-Acquire Exclusive (32 bit)
+  \details Executes a LDA exclusive instruction for 32 bit values.
+  \param [in]    ptr  Pointer to data
+  \return        value of type uint32_t at (*ptr)
+ */
+__STATIC_FORCEINLINE uint32_t __LDAEX(volatile uint32_t *ptr)
+{
+    uint32_t result;
+
+   __ASM volatile ("ldaex %0, %1" : "=r" (result) : "Q" (*ptr) );
+   return(result);
+}
+
+
+/**
+  \brief   Store-Release Exclusive (8 bit)
+  \details Executes a STLB exclusive instruction for 8 bit values.
+  \param [in]  value  Value to store
+  \param [in]    ptr  Pointer to location
+  \return          0  Function succeeded
+  \return          1  Function failed
+ */
+__STATIC_FORCEINLINE uint32_t __STLEXB(uint8_t value, volatile uint8_t *ptr)
+{
+   uint32_t result;
+
+   __ASM volatile ("stlexb %0, %2, %1" : "=&r" (result), "=Q" (*ptr) : "r" ((uint32_t)value) );
+   return(result);
+}
+
+
+/**
+  \brief   Store-Release Exclusive (16 bit)
+  \details Executes a STLH exclusive instruction for 16 bit values.
+  \param [in]  value  Value to store
+  \param [in]    ptr  Pointer to location
+  \return          0  Function succeeded
+  \return          1  Function failed
+ */
+__STATIC_FORCEINLINE uint32_t __STLEXH(uint16_t value, volatile uint16_t *ptr)
+{
+   uint32_t result;
+
+   __ASM volatile ("stlexh %0, %2, %1" : "=&r" (result), "=Q" (*ptr) : "r" ((uint32_t)value) );
+   return(result);
+}
+
+
+/**
+  \brief   Store-Release Exclusive (32 bit)
+  \details Executes a STL exclusive instruction for 32 bit values.
+  \param [in]  value  Value to store
+  \param [in]    ptr  Pointer to location
+  \return          0  Function succeeded
+  \return          1  Function failed
+ */
+__STATIC_FORCEINLINE uint32_t __STLEX(uint32_t value, volatile uint32_t *ptr)
+{
+   uint32_t result;
+
+   __ASM volatile ("stlex %0, %2, %1" : "=&r" (result), "=Q" (*ptr) : "r" ((uint32_t)value) );
+   return(result);
+}
+
+#endif /* ((defined (__ARM_ARCH_8M_MAIN__ ) && (__ARM_ARCH_8M_MAIN__ == 1)) || \
+           (defined (__ARM_ARCH_8M_BASE__ ) && (__ARM_ARCH_8M_BASE__ == 1))    ) */
+
+/*@}*/ /* end of group CMSIS_Core_InstructionInterface */
+
+
+/* ###################  Compiler specific Intrinsics  ########################### */
+/** \defgroup CMSIS_SIMD_intrinsics CMSIS SIMD Intrinsics
+  Access to dedicated SIMD instructions
+  @{
+*/
+
+#if (defined (__ARM_FEATURE_DSP) && (__ARM_FEATURE_DSP == 1))
+
+__STATIC_FORCEINLINE uint32_t __SADD8(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("sadd8 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __QADD8(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("qadd8 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SHADD8(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("shadd8 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UADD8(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uadd8 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UQADD8(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uqadd8 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UHADD8(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uhadd8 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+
+__STATIC_FORCEINLINE uint32_t __SSUB8(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("ssub8 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __QSUB8(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("qsub8 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SHSUB8(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("shsub8 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __USUB8(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("usub8 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UQSUB8(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uqsub8 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UHSUB8(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uhsub8 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+
+__STATIC_FORCEINLINE uint32_t __SADD16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("sadd16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __QADD16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("qadd16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SHADD16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("shadd16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UADD16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uadd16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UQADD16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uqadd16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UHADD16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uhadd16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SSUB16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("ssub16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __QSUB16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("qsub16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SHSUB16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("shsub16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __USUB16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("usub16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UQSUB16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uqsub16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UHSUB16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uhsub16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SASX(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("sasx %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __QASX(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("qasx %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SHASX(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("shasx %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UASX(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uasx %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UQASX(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uqasx %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UHASX(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uhasx %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SSAX(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("ssax %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __QSAX(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("qsax %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SHSAX(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("shsax %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __USAX(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("usax %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UQSAX(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uqsax %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UHSAX(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uhsax %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __USAD8(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("usad8 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __USADA8(uint32_t op1, uint32_t op2, uint32_t op3)
+{
+  uint32_t result;
+
+  __ASM volatile ("usada8 %0, %1, %2, %3" : "=r" (result) : "r" (op1), "r" (op2), "r" (op3) );
+  return(result);
+}
+
+#define __SSAT16(ARG1,ARG2) \
+({                          \
+  int32_t __RES, __ARG1 = (ARG1); \
+  __ASM ("ssat16 %0, %1, %2" : "=r" (__RES) :  "I" (ARG2), "r" (__ARG1) ); \
+  __RES; \
+ })
+
+#define __USAT16(ARG1,ARG2) \
+({                          \
+  uint32_t __RES, __ARG1 = (ARG1); \
+  __ASM ("usat16 %0, %1, %2" : "=r" (__RES) :  "I" (ARG2), "r" (__ARG1) ); \
+  __RES; \
+ })
+
+__STATIC_FORCEINLINE uint32_t __UXTB16(uint32_t op1)
+{
+  uint32_t result;
+
+  __ASM volatile ("uxtb16 %0, %1" : "=r" (result) : "r" (op1));
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __UXTAB16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("uxtab16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SXTB16(uint32_t op1)
+{
+  uint32_t result;
+
+  __ASM volatile ("sxtb16 %0, %1" : "=r" (result) : "r" (op1));
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SXTAB16(uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("sxtab16 %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SMUAD  (uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("smuad %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SMUADX (uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("smuadx %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SMLAD (uint32_t op1, uint32_t op2, uint32_t op3)
+{
+  uint32_t result;
+
+  __ASM volatile ("smlad %0, %1, %2, %3" : "=r" (result) : "r" (op1), "r" (op2), "r" (op3) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SMLADX (uint32_t op1, uint32_t op2, uint32_t op3)
+{
+  uint32_t result;
+
+  __ASM volatile ("smladx %0, %1, %2, %3" : "=r" (result) : "r" (op1), "r" (op2), "r" (op3) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint64_t __SMLALD (uint32_t op1, uint32_t op2, uint64_t acc)
+{
+  union llreg_u{
+    uint32_t w32[2];
+    uint64_t w64;
+  } llr;
+  llr.w64 = acc;
+
+#ifndef __ARMEB__   /* Little endian */
+  __ASM volatile ("smlald %0, %1, %2, %3" : "=r" (llr.w32[0]), "=r" (llr.w32[1]): "r" (op1), "r" (op2) , "0" (llr.w32[0]), "1" (llr.w32[1]) );
+#else               /* Big endian */
+  __ASM volatile ("smlald %0, %1, %2, %3" : "=r" (llr.w32[1]), "=r" (llr.w32[0]): "r" (op1), "r" (op2) , "0" (llr.w32[1]), "1" (llr.w32[0]) );
+#endif
+
+  return(llr.w64);
+}
+
+__STATIC_FORCEINLINE uint64_t __SMLALDX (uint32_t op1, uint32_t op2, uint64_t acc)
+{
+  union llreg_u{
+    uint32_t w32[2];
+    uint64_t w64;
+  } llr;
+  llr.w64 = acc;
+
+#ifndef __ARMEB__   /* Little endian */
+  __ASM volatile ("smlaldx %0, %1, %2, %3" : "=r" (llr.w32[0]), "=r" (llr.w32[1]): "r" (op1), "r" (op2) , "0" (llr.w32[0]), "1" (llr.w32[1]) );
+#else               /* Big endian */
+  __ASM volatile ("smlaldx %0, %1, %2, %3" : "=r" (llr.w32[1]), "=r" (llr.w32[0]): "r" (op1), "r" (op2) , "0" (llr.w32[1]), "1" (llr.w32[0]) );
+#endif
+
+  return(llr.w64);
+}
+
+__STATIC_FORCEINLINE uint32_t __SMUSD  (uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("smusd %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SMUSDX (uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("smusdx %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SMLSD (uint32_t op1, uint32_t op2, uint32_t op3)
+{
+  uint32_t result;
+
+  __ASM volatile ("smlsd %0, %1, %2, %3" : "=r" (result) : "r" (op1), "r" (op2), "r" (op3) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint32_t __SMLSDX (uint32_t op1, uint32_t op2, uint32_t op3)
+{
+  uint32_t result;
+
+  __ASM volatile ("smlsdx %0, %1, %2, %3" : "=r" (result) : "r" (op1), "r" (op2), "r" (op3) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE uint64_t __SMLSLD (uint32_t op1, uint32_t op2, uint64_t acc)
+{
+  union llreg_u{
+    uint32_t w32[2];
+    uint64_t w64;
+  } llr;
+  llr.w64 = acc;
+
+#ifndef __ARMEB__   /* Little endian */
+  __ASM volatile ("smlsld %0, %1, %2, %3" : "=r" (llr.w32[0]), "=r" (llr.w32[1]): "r" (op1), "r" (op2) , "0" (llr.w32[0]), "1" (llr.w32[1]) );
+#else               /* Big endian */
+  __ASM volatile ("smlsld %0, %1, %2, %3" : "=r" (llr.w32[1]), "=r" (llr.w32[0]): "r" (op1), "r" (op2) , "0" (llr.w32[1]), "1" (llr.w32[0]) );
+#endif
+
+  return(llr.w64);
+}
+
+__STATIC_FORCEINLINE uint64_t __SMLSLDX (uint32_t op1, uint32_t op2, uint64_t acc)
+{
+  union llreg_u{
+    uint32_t w32[2];
+    uint64_t w64;
+  } llr;
+  llr.w64 = acc;
+
+#ifndef __ARMEB__   /* Little endian */
+  __ASM volatile ("smlsldx %0, %1, %2, %3" : "=r" (llr.w32[0]), "=r" (llr.w32[1]): "r" (op1), "r" (op2) , "0" (llr.w32[0]), "1" (llr.w32[1]) );
+#else               /* Big endian */
+  __ASM volatile ("smlsldx %0, %1, %2, %3" : "=r" (llr.w32[1]), "=r" (llr.w32[0]): "r" (op1), "r" (op2) , "0" (llr.w32[1]), "1" (llr.w32[0]) );
+#endif
+
+  return(llr.w64);
+}
+
+__STATIC_FORCEINLINE uint32_t __SEL  (uint32_t op1, uint32_t op2)
+{
+  uint32_t result;
+
+  __ASM volatile ("sel %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE  int32_t __QADD( int32_t op1,  int32_t op2)
+{
+  int32_t result;
+
+  __ASM volatile ("qadd %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+__STATIC_FORCEINLINE  int32_t __QSUB( int32_t op1,  int32_t op2)
+{
+  int32_t result;
+
+  __ASM volatile ("qsub %0, %1, %2" : "=r" (result) : "r" (op1), "r" (op2) );
+  return(result);
+}
+
+#if 0
+#define __PKHBT(ARG1,ARG2,ARG3) \
+({                          \
+  uint32_t __RES, __ARG1 = (ARG1), __ARG2 = (ARG2); \
+  __ASM ("pkhbt %0, %1, %2, lsl %3" : "=r" (__RES) :  "r" (__ARG1), "r" (__ARG2), "I" (ARG3)  ); \
+  __RES; \
+ })
+
+#define __PKHTB(ARG1,ARG2,ARG3) \
+({                          \
+  uint32_t __RES, __ARG1 = (ARG1), __ARG2 = (ARG2); \
+  if (ARG3 == 0) \
+    __ASM ("pkhtb %0, %1, %2" : "=r" (__RES) :  "r" (__ARG1), "r" (__ARG2)  ); \
+  else \
+    __ASM ("pkhtb %0, %1, %2, asr %3" : "=r" (__RES) :  "r" (__ARG1), "r" (__ARG2), "I" (ARG3)  ); \
+  __RES; \
+ })
+#endif
+
+#define __PKHBT(ARG1,ARG2,ARG3)          ( ((((uint32_t)(ARG1))          ) & 0x0000FFFFUL) |  \
+                                           ((((uint32_t)(ARG2)) << (ARG3)) & 0xFFFF0000UL)  )
+
+#define __PKHTB(ARG1,ARG2,ARG3)          ( ((((uint32_t)(ARG1))          ) & 0xFFFF0000UL) |  \
+                                           ((((uint32_t)(ARG2)) >> (ARG3)) & 0x0000FFFFUL)  )
+
+__STATIC_FORCEINLINE int32_t __SMMLA (int32_t op1, int32_t op2, int32_t op3)
+{
+ int32_t result;
+
+ __ASM volatile ("smmla %0, %1, %2, %3" : "=r" (result): "r"  (op1), "r" (op2), "r" (op3) );
+ return(result);
+}
+
+#endif /* (__ARM_FEATURE_DSP == 1) */
+/*@} end of group CMSIS_SIMD_intrinsics */
+
+
+#pragma GCC diagnostic pop
+
+#endif /* __CMSIS_GCC_H */

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/cmsis/CMSIS/Core/Include/cmsis_version.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/cmsis/CMSIS/Core/Include/cmsis_version.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,39 @@
+/**************************************************************************//**
+ * @file     cmsis_version.h
+ * @brief    CMSIS Core(M) Version definitions
+ * @version  V5.0.2
+ * @date     19. April 2017
+ ******************************************************************************/
+/*
+ * Copyright (c) 2009-2017 ARM Limited. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#if   defined ( __ICCARM__ )
+  #pragma system_include         /* treat file as system include file for MISRA check */
+#elif defined (__clang__)
+  #pragma clang system_header   /* treat file as system include file */
+#endif
+
+#ifndef __CMSIS_VERSION_H
+#define __CMSIS_VERSION_H
+
+/*  CMSIS Version definitions */
+#define __CM_CMSIS_VERSION_MAIN  ( 5U)                                      /*!< [31:16] CMSIS Core(M) main version */
+#define __CM_CMSIS_VERSION_SUB   ( 1U)                                      /*!< [15:0]  CMSIS Core(M) sub version */
+#define __CM_CMSIS_VERSION       ((__CM_CMSIS_VERSION_MAIN << 16U) | \
+                                   __CM_CMSIS_VERSION_SUB           )       /*!< CMSIS Core(M) version number */
+#endif

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/cmsis/CMSIS/Core/Include/core_cm3.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/cmsis/CMSIS/Core/Include/core_cm3.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,1941 @@
+/**************************************************************************//**
+ * @file     core_cm3.h
+ * @brief    CMSIS Cortex-M3 Core Peripheral Access Layer Header File
+ * @version  V5.0.8
+ * @date     04. June 2018
+ ******************************************************************************/
+/*
+ * Copyright (c) 2009-2018 Arm Limited. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#if   defined ( __ICCARM__ )
+  #pragma system_include         /* treat file as system include file for MISRA check */
+#elif defined (__clang__)
+  #pragma clang system_header   /* treat file as system include file */
+#endif
+
+#ifndef __CORE_CM3_H_GENERIC
+#define __CORE_CM3_H_GENERIC
+
+#include <stdint.h>
+
+#ifdef __cplusplus
+ extern "C" {
+#endif
+
+/**
+  \page CMSIS_MISRA_Exceptions  MISRA-C:2004 Compliance Exceptions
+  CMSIS violates the following MISRA-C:2004 rules:
+
+   \li Required Rule 8.5, object/function definition in header file.<br>
+     Function definitions in header files are used to allow 'inlining'.
+
+   \li Required Rule 18.4, declaration of union type or object of union type: '{...}'.<br>
+     Unions are used for effective representation of core registers.
+
+   \li Advisory Rule 19.7, Function-like macro defined.<br>
+     Function-like macros are used to allow more efficient code.
+ */
+
+
+/*******************************************************************************
+ *                 CMSIS definitions
+ ******************************************************************************/
+/**
+  \ingroup Cortex_M3
+  @{
+ */
+
+#include "cmsis_version.h"
+
+/*  CMSIS CM3 definitions */
+#define __CM3_CMSIS_VERSION_MAIN  (__CM_CMSIS_VERSION_MAIN)              /*!< \deprecated [31:16] CMSIS HAL main version */
+#define __CM3_CMSIS_VERSION_SUB   (__CM_CMSIS_VERSION_SUB)               /*!< \deprecated [15:0]  CMSIS HAL sub version */
+#define __CM3_CMSIS_VERSION       ((__CM3_CMSIS_VERSION_MAIN << 16U) | \
+                                    __CM3_CMSIS_VERSION_SUB           )  /*!< \deprecated CMSIS HAL version number */
+
+#define __CORTEX_M                (3U)                                   /*!< Cortex-M Core */
+
+/** __FPU_USED indicates whether an FPU is used or not.
+    This core does not support an FPU at all
+*/
+#define __FPU_USED       0U
+
+#if defined ( __CC_ARM )
+  #if defined __TARGET_FPU_VFP
+    #error "Compiler generates FPU instructions for a device without an FPU (check __FPU_PRESENT)"
+  #endif
+
+#elif defined (__ARMCC_VERSION) && (__ARMCC_VERSION >= 6010050)
+  #if defined __ARM_PCS_VFP
+    #error "Compiler generates FPU instructions for a device without an FPU (check __FPU_PRESENT)"
+  #endif
+
+#elif defined ( __GNUC__ )
+  #if defined (__VFP_FP__) && !defined(__SOFTFP__)
+    #error "Compiler generates FPU instructions for a device without an FPU (check __FPU_PRESENT)"
+  #endif
+
+#elif defined ( __ICCARM__ )
+  #if defined __ARMVFP__
+    #error "Compiler generates FPU instructions for a device without an FPU (check __FPU_PRESENT)"
+  #endif
+
+#elif defined ( __TI_ARM__ )
+  #if defined __TI_VFP_SUPPORT__
+    #error "Compiler generates FPU instructions for a device without an FPU (check __FPU_PRESENT)"
+  #endif
+
+#elif defined ( __TASKING__ )
+  #if defined __FPU_VFP__
+    #error "Compiler generates FPU instructions for a device without an FPU (check __FPU_PRESENT)"
+  #endif
+
+#elif defined ( __CSMC__ )
+  #if ( __CSMC__ & 0x400U)
+    #error "Compiler generates FPU instructions for a device without an FPU (check __FPU_PRESENT)"
+  #endif
+
+#endif
+
+#include "cmsis_compiler.h"               /* CMSIS compiler specific defines */
+
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif /* __CORE_CM3_H_GENERIC */
+
+#ifndef __CMSIS_GENERIC
+
+#ifndef __CORE_CM3_H_DEPENDANT
+#define __CORE_CM3_H_DEPENDANT
+
+#ifdef __cplusplus
+ extern "C" {
+#endif
+
+/* check device defines and use defaults */
+#if defined __CHECK_DEVICE_DEFINES
+  #ifndef __CM3_REV
+    #define __CM3_REV               0x0200U
+    #warning "__CM3_REV not defined in device header file; using default!"
+  #endif
+
+  #ifndef __MPU_PRESENT
+    #define __MPU_PRESENT             0U
+    #warning "__MPU_PRESENT not defined in device header file; using default!"
+  #endif
+
+  #ifndef __NVIC_PRIO_BITS
+    #define __NVIC_PRIO_BITS          3U
+    #warning "__NVIC_PRIO_BITS not defined in device header file; using default!"
+  #endif
+
+  #ifndef __Vendor_SysTickConfig
+    #define __Vendor_SysTickConfig    0U
+    #warning "__Vendor_SysTickConfig not defined in device header file; using default!"
+  #endif
+#endif
+
+/* IO definitions (access restrictions to peripheral registers) */
+/**
+    \defgroup CMSIS_glob_defs CMSIS Global Defines
+
+    <strong>IO Type Qualifiers</strong> are used
+    \li to specify the access to peripheral variables.
+    \li for automatic generation of peripheral register debug information.
+*/
+#ifdef __cplusplus
+  #define   __I     volatile             /*!< Defines 'read only' permissions */
+#else
+  #define   __I     volatile const       /*!< Defines 'read only' permissions */
+#endif
+#define     __O     volatile             /*!< Defines 'write only' permissions */
+#define     __IO    volatile             /*!< Defines 'read / write' permissions */
+
+/* following defines should be used for structure members */
+#define     __IM     volatile const      /*! Defines 'read only' structure member permissions */
+#define     __OM     volatile            /*! Defines 'write only' structure member permissions */
+#define     __IOM    volatile            /*! Defines 'read / write' structure member permissions */
+
+/*@} end of group Cortex_M3 */
+
+
+
+/*******************************************************************************
+ *                 Register Abstraction
+  Core Register contain:
+  - Core Register
+  - Core NVIC Register
+  - Core SCB Register
+  - Core SysTick Register
+  - Core Debug Register
+  - Core MPU Register
+ ******************************************************************************/
+/**
+  \defgroup CMSIS_core_register Defines and Type Definitions
+  \brief Type definitions and defines for Cortex-M processor based devices.
+*/
+
+/**
+  \ingroup    CMSIS_core_register
+  \defgroup   CMSIS_CORE  Status and Control Registers
+  \brief      Core Register type definitions.
+  @{
+ */
+
+/**
+  \brief  Union type to access the Application Program Status Register (APSR).
+ */
+typedef union
+{
+  struct
+  {
+    uint32_t _reserved0:27;              /*!< bit:  0..26  Reserved */
+    uint32_t Q:1;                        /*!< bit:     27  Saturation condition flag */
+    uint32_t V:1;                        /*!< bit:     28  Overflow condition code flag */
+    uint32_t C:1;                        /*!< bit:     29  Carry condition code flag */
+    uint32_t Z:1;                        /*!< bit:     30  Zero condition code flag */
+    uint32_t N:1;                        /*!< bit:     31  Negative condition code flag */
+  } b;                                   /*!< Structure used for bit  access */
+  uint32_t w;                            /*!< Type      used for word access */
+} APSR_Type;
+
+/* APSR Register Definitions */
+#define APSR_N_Pos                         31U                                            /*!< APSR: N Position */
+#define APSR_N_Msk                         (1UL << APSR_N_Pos)                            /*!< APSR: N Mask */
+
+#define APSR_Z_Pos                         30U                                            /*!< APSR: Z Position */
+#define APSR_Z_Msk                         (1UL << APSR_Z_Pos)                            /*!< APSR: Z Mask */
+
+#define APSR_C_Pos                         29U                                            /*!< APSR: C Position */
+#define APSR_C_Msk                         (1UL << APSR_C_Pos)                            /*!< APSR: C Mask */
+
+#define APSR_V_Pos                         28U                                            /*!< APSR: V Position */
+#define APSR_V_Msk                         (1UL << APSR_V_Pos)                            /*!< APSR: V Mask */
+
+#define APSR_Q_Pos                         27U                                            /*!< APSR: Q Position */
+#define APSR_Q_Msk                         (1UL << APSR_Q_Pos)                            /*!< APSR: Q Mask */
+
+
+/**
+  \brief  Union type to access the Interrupt Program Status Register (IPSR).
+ */
+typedef union
+{
+  struct
+  {
+    uint32_t ISR:9;                      /*!< bit:  0.. 8  Exception number */
+    uint32_t _reserved0:23;              /*!< bit:  9..31  Reserved */
+  } b;                                   /*!< Structure used for bit  access */
+  uint32_t w;                            /*!< Type      used for word access */
+} IPSR_Type;
+
+/* IPSR Register Definitions */
+#define IPSR_ISR_Pos                        0U                                            /*!< IPSR: ISR Position */
+#define IPSR_ISR_Msk                       (0x1FFUL /*<< IPSR_ISR_Pos*/)                  /*!< IPSR: ISR Mask */
+
+
+/**
+  \brief  Union type to access the Special-Purpose Program Status Registers (xPSR).
+ */
+typedef union
+{
+  struct
+  {
+    uint32_t ISR:9;                      /*!< bit:  0.. 8  Exception number */
+    uint32_t _reserved0:1;               /*!< bit:      9  Reserved */
+    uint32_t ICI_IT_1:6;                 /*!< bit: 10..15  ICI/IT part 1 */
+    uint32_t _reserved1:8;               /*!< bit: 16..23  Reserved */
+    uint32_t T:1;                        /*!< bit:     24  Thumb bit */
+    uint32_t ICI_IT_2:2;                 /*!< bit: 25..26  ICI/IT part 2 */
+    uint32_t Q:1;                        /*!< bit:     27  Saturation condition flag */
+    uint32_t V:1;                        /*!< bit:     28  Overflow condition code flag */
+    uint32_t C:1;                        /*!< bit:     29  Carry condition code flag */
+    uint32_t Z:1;                        /*!< bit:     30  Zero condition code flag */
+    uint32_t N:1;                        /*!< bit:     31  Negative condition code flag */
+  } b;                                   /*!< Structure used for bit  access */
+  uint32_t w;                            /*!< Type      used for word access */
+} xPSR_Type;
+
+/* xPSR Register Definitions */
+#define xPSR_N_Pos                         31U                                            /*!< xPSR: N Position */
+#define xPSR_N_Msk                         (1UL << xPSR_N_Pos)                            /*!< xPSR: N Mask */
+
+#define xPSR_Z_Pos                         30U                                            /*!< xPSR: Z Position */
+#define xPSR_Z_Msk                         (1UL << xPSR_Z_Pos)                            /*!< xPSR: Z Mask */
+
+#define xPSR_C_Pos                         29U                                            /*!< xPSR: C Position */
+#define xPSR_C_Msk                         (1UL << xPSR_C_Pos)                            /*!< xPSR: C Mask */
+
+#define xPSR_V_Pos                         28U                                            /*!< xPSR: V Position */
+#define xPSR_V_Msk                         (1UL << xPSR_V_Pos)                            /*!< xPSR: V Mask */
+
+#define xPSR_Q_Pos                         27U                                            /*!< xPSR: Q Position */
+#define xPSR_Q_Msk                         (1UL << xPSR_Q_Pos)                            /*!< xPSR: Q Mask */
+
+#define xPSR_ICI_IT_2_Pos                  25U                                            /*!< xPSR: ICI/IT part 2 Position */
+#define xPSR_ICI_IT_2_Msk                  (3UL << xPSR_ICI_IT_2_Pos)                     /*!< xPSR: ICI/IT part 2 Mask */
+
+#define xPSR_T_Pos                         24U                                            /*!< xPSR: T Position */
+#define xPSR_T_Msk                         (1UL << xPSR_T_Pos)                            /*!< xPSR: T Mask */
+
+#define xPSR_ICI_IT_1_Pos                  10U                                            /*!< xPSR: ICI/IT part 1 Position */
+#define xPSR_ICI_IT_1_Msk                  (0x3FUL << xPSR_ICI_IT_1_Pos)                  /*!< xPSR: ICI/IT part 1 Mask */
+
+#define xPSR_ISR_Pos                        0U                                            /*!< xPSR: ISR Position */
+#define xPSR_ISR_Msk                       (0x1FFUL /*<< xPSR_ISR_Pos*/)                  /*!< xPSR: ISR Mask */
+
+
+/**
+  \brief  Union type to access the Control Registers (CONTROL).
+ */
+typedef union
+{
+  struct
+  {
+    uint32_t nPRIV:1;                    /*!< bit:      0  Execution privilege in Thread mode */
+    uint32_t SPSEL:1;                    /*!< bit:      1  Stack to be used */
+    uint32_t _reserved1:30;              /*!< bit:  2..31  Reserved */
+  } b;                                   /*!< Structure used for bit  access */
+  uint32_t w;                            /*!< Type      used for word access */
+} CONTROL_Type;
+
+/* CONTROL Register Definitions */
+#define CONTROL_SPSEL_Pos                   1U                                            /*!< CONTROL: SPSEL Position */
+#define CONTROL_SPSEL_Msk                  (1UL << CONTROL_SPSEL_Pos)                     /*!< CONTROL: SPSEL Mask */
+
+#define CONTROL_nPRIV_Pos                   0U                                            /*!< CONTROL: nPRIV Position */
+#define CONTROL_nPRIV_Msk                  (1UL /*<< CONTROL_nPRIV_Pos*/)                 /*!< CONTROL: nPRIV Mask */
+
+/*@} end of group CMSIS_CORE */
+
+
+/**
+  \ingroup    CMSIS_core_register
+  \defgroup   CMSIS_NVIC  Nested Vectored Interrupt Controller (NVIC)
+  \brief      Type definitions for the NVIC Registers
+  @{
+ */
+
+/**
+  \brief  Structure type to access the Nested Vectored Interrupt Controller (NVIC).
+ */
+typedef struct
+{
+  __IOM uint32_t ISER[8U];               /*!< Offset: 0x000 (R/W)  Interrupt Set Enable Register */
+        uint32_t RESERVED0[24U];
+  __IOM uint32_t ICER[8U];               /*!< Offset: 0x080 (R/W)  Interrupt Clear Enable Register */
+        uint32_t RSERVED1[24U];
+  __IOM uint32_t ISPR[8U];               /*!< Offset: 0x100 (R/W)  Interrupt Set Pending Register */
+        uint32_t RESERVED2[24U];
+  __IOM uint32_t ICPR[8U];               /*!< Offset: 0x180 (R/W)  Interrupt Clear Pending Register */
+        uint32_t RESERVED3[24U];
+  __IOM uint32_t IABR[8U];               /*!< Offset: 0x200 (R/W)  Interrupt Active bit Register */
+        uint32_t RESERVED4[56U];
+  __IOM uint8_t  IP[240U];               /*!< Offset: 0x300 (R/W)  Interrupt Priority Register (8Bit wide) */
+        uint32_t RESERVED5[644U];
+  __OM  uint32_t STIR;                   /*!< Offset: 0xE00 ( /W)  Software Trigger Interrupt Register */
+}  NVIC_Type;
+
+/* Software Triggered Interrupt Register Definitions */
+#define NVIC_STIR_INTID_Pos                 0U                                         /*!< STIR: INTLINESNUM Position */
+#define NVIC_STIR_INTID_Msk                (0x1FFUL /*<< NVIC_STIR_INTID_Pos*/)        /*!< STIR: INTLINESNUM Mask */
+
+/*@} end of group CMSIS_NVIC */
+
+
+/**
+  \ingroup  CMSIS_core_register
+  \defgroup CMSIS_SCB     System Control Block (SCB)
+  \brief    Type definitions for the System Control Block Registers
+  @{
+ */
+
+/**
+  \brief  Structure type to access the System Control Block (SCB).
+ */
+typedef struct
+{
+  __IM  uint32_t CPUID;                  /*!< Offset: 0x000 (R/ )  CPUID Base Register */
+  __IOM uint32_t ICSR;                   /*!< Offset: 0x004 (R/W)  Interrupt Control and State Register */
+  __IOM uint32_t VTOR;                   /*!< Offset: 0x008 (R/W)  Vector Table Offset Register */
+  __IOM uint32_t AIRCR;                  /*!< Offset: 0x00C (R/W)  Application Interrupt and Reset Control Register */
+  __IOM uint32_t SCR;                    /*!< Offset: 0x010 (R/W)  System Control Register */
+  __IOM uint32_t CCR;                    /*!< Offset: 0x014 (R/W)  Configuration Control Register */
+  __IOM uint8_t  SHP[12U];               /*!< Offset: 0x018 (R/W)  System Handlers Priority Registers (4-7, 8-11, 12-15) */
+  __IOM uint32_t SHCSR;                  /*!< Offset: 0x024 (R/W)  System Handler Control and State Register */
+  __IOM uint32_t CFSR;                   /*!< Offset: 0x028 (R/W)  Configurable Fault Status Register */
+  __IOM uint32_t HFSR;                   /*!< Offset: 0x02C (R/W)  HardFault Status Register */
+  __IOM uint32_t DFSR;                   /*!< Offset: 0x030 (R/W)  Debug Fault Status Register */
+  __IOM uint32_t MMFAR;                  /*!< Offset: 0x034 (R/W)  MemManage Fault Address Register */
+  __IOM uint32_t BFAR;                   /*!< Offset: 0x038 (R/W)  BusFault Address Register */
+  __IOM uint32_t AFSR;                   /*!< Offset: 0x03C (R/W)  Auxiliary Fault Status Register */
+  __IM  uint32_t PFR[2U];                /*!< Offset: 0x040 (R/ )  Processor Feature Register */
+  __IM  uint32_t DFR;                    /*!< Offset: 0x048 (R/ )  Debug Feature Register */
+  __IM  uint32_t ADR;                    /*!< Offset: 0x04C (R/ )  Auxiliary Feature Register */
+  __IM  uint32_t MMFR[4U];               /*!< Offset: 0x050 (R/ )  Memory Model Feature Register */
+  __IM  uint32_t ISAR[5U];               /*!< Offset: 0x060 (R/ )  Instruction Set Attributes Register */
+        uint32_t RESERVED0[5U];
+  __IOM uint32_t CPACR;                  /*!< Offset: 0x088 (R/W)  Coprocessor Access Control Register */
+} SCB_Type;
+
+/* SCB CPUID Register Definitions */
+#define SCB_CPUID_IMPLEMENTER_Pos          24U                                            /*!< SCB CPUID: IMPLEMENTER Position */
+#define SCB_CPUID_IMPLEMENTER_Msk          (0xFFUL << SCB_CPUID_IMPLEMENTER_Pos)          /*!< SCB CPUID: IMPLEMENTER Mask */
+
+#define SCB_CPUID_VARIANT_Pos              20U                                            /*!< SCB CPUID: VARIANT Position */
+#define SCB_CPUID_VARIANT_Msk              (0xFUL << SCB_CPUID_VARIANT_Pos)               /*!< SCB CPUID: VARIANT Mask */
+
+#define SCB_CPUID_ARCHITECTURE_Pos         16U                                            /*!< SCB CPUID: ARCHITECTURE Position */
+#define SCB_CPUID_ARCHITECTURE_Msk         (0xFUL << SCB_CPUID_ARCHITECTURE_Pos)          /*!< SCB CPUID: ARCHITECTURE Mask */
+
+#define SCB_CPUID_PARTNO_Pos                4U                                            /*!< SCB CPUID: PARTNO Position */
+#define SCB_CPUID_PARTNO_Msk               (0xFFFUL << SCB_CPUID_PARTNO_Pos)              /*!< SCB CPUID: PARTNO Mask */
+
+#define SCB_CPUID_REVISION_Pos              0U                                            /*!< SCB CPUID: REVISION Position */
+#define SCB_CPUID_REVISION_Msk             (0xFUL /*<< SCB_CPUID_REVISION_Pos*/)          /*!< SCB CPUID: REVISION Mask */
+
+/* SCB Interrupt Control State Register Definitions */
+#define SCB_ICSR_NMIPENDSET_Pos            31U                                            /*!< SCB ICSR: NMIPENDSET Position */
+#define SCB_ICSR_NMIPENDSET_Msk            (1UL << SCB_ICSR_NMIPENDSET_Pos)               /*!< SCB ICSR: NMIPENDSET Mask */
+
+#define SCB_ICSR_PENDSVSET_Pos             28U                                            /*!< SCB ICSR: PENDSVSET Position */
+#define SCB_ICSR_PENDSVSET_Msk             (1UL << SCB_ICSR_PENDSVSET_Pos)                /*!< SCB ICSR: PENDSVSET Mask */
+
+#define SCB_ICSR_PENDSVCLR_Pos             27U                                            /*!< SCB ICSR: PENDSVCLR Position */
+#define SCB_ICSR_PENDSVCLR_Msk             (1UL << SCB_ICSR_PENDSVCLR_Pos)                /*!< SCB ICSR: PENDSVCLR Mask */
+
+#define SCB_ICSR_PENDSTSET_Pos             26U                                            /*!< SCB ICSR: PENDSTSET Position */
+#define SCB_ICSR_PENDSTSET_Msk             (1UL << SCB_ICSR_PENDSTSET_Pos)                /*!< SCB ICSR: PENDSTSET Mask */
+
+#define SCB_ICSR_PENDSTCLR_Pos             25U                                            /*!< SCB ICSR: PENDSTCLR Position */
+#define SCB_ICSR_PENDSTCLR_Msk             (1UL << SCB_ICSR_PENDSTCLR_Pos)                /*!< SCB ICSR: PENDSTCLR Mask */
+
+#define SCB_ICSR_ISRPREEMPT_Pos            23U                                            /*!< SCB ICSR: ISRPREEMPT Position */
+#define SCB_ICSR_ISRPREEMPT_Msk            (1UL << SCB_ICSR_ISRPREEMPT_Pos)               /*!< SCB ICSR: ISRPREEMPT Mask */
+
+#define SCB_ICSR_ISRPENDING_Pos            22U                                            /*!< SCB ICSR: ISRPENDING Position */
+#define SCB_ICSR_ISRPENDING_Msk            (1UL << SCB_ICSR_ISRPENDING_Pos)               /*!< SCB ICSR: ISRPENDING Mask */
+
+#define SCB_ICSR_VECTPENDING_Pos           12U                                            /*!< SCB ICSR: VECTPENDING Position */
+#define SCB_ICSR_VECTPENDING_Msk           (0x1FFUL << SCB_ICSR_VECTPENDING_Pos)          /*!< SCB ICSR: VECTPENDING Mask */
+
+#define SCB_ICSR_RETTOBASE_Pos             11U                                            /*!< SCB ICSR: RETTOBASE Position */
+#define SCB_ICSR_RETTOBASE_Msk             (1UL << SCB_ICSR_RETTOBASE_Pos)                /*!< SCB ICSR: RETTOBASE Mask */
+
+#define SCB_ICSR_VECTACTIVE_Pos             0U                                            /*!< SCB ICSR: VECTACTIVE Position */
+#define SCB_ICSR_VECTACTIVE_Msk            (0x1FFUL /*<< SCB_ICSR_VECTACTIVE_Pos*/)       /*!< SCB ICSR: VECTACTIVE Mask */
+
+/* SCB Vector Table Offset Register Definitions */
+#if defined (__CM3_REV) && (__CM3_REV < 0x0201U)                   /* core r2p1 */
+#define SCB_VTOR_TBLBASE_Pos               29U                                            /*!< SCB VTOR: TBLBASE Position */
+#define SCB_VTOR_TBLBASE_Msk               (1UL << SCB_VTOR_TBLBASE_Pos)                  /*!< SCB VTOR: TBLBASE Mask */
+
+#define SCB_VTOR_TBLOFF_Pos                 7U                                            /*!< SCB VTOR: TBLOFF Position */
+#define SCB_VTOR_TBLOFF_Msk                (0x3FFFFFUL << SCB_VTOR_TBLOFF_Pos)            /*!< SCB VTOR: TBLOFF Mask */
+#else
+#define SCB_VTOR_TBLOFF_Pos                 7U                                            /*!< SCB VTOR: TBLOFF Position */
+#define SCB_VTOR_TBLOFF_Msk                (0x1FFFFFFUL << SCB_VTOR_TBLOFF_Pos)           /*!< SCB VTOR: TBLOFF Mask */
+#endif
+
+/* SCB Application Interrupt and Reset Control Register Definitions */
+#define SCB_AIRCR_VECTKEY_Pos              16U                                            /*!< SCB AIRCR: VECTKEY Position */
+#define SCB_AIRCR_VECTKEY_Msk              (0xFFFFUL << SCB_AIRCR_VECTKEY_Pos)            /*!< SCB AIRCR: VECTKEY Mask */
+
+#define SCB_AIRCR_VECTKEYSTAT_Pos          16U                                            /*!< SCB AIRCR: VECTKEYSTAT Position */
+#define SCB_AIRCR_VECTKEYSTAT_Msk          (0xFFFFUL << SCB_AIRCR_VECTKEYSTAT_Pos)        /*!< SCB AIRCR: VECTKEYSTAT Mask */
+
+#define SCB_AIRCR_ENDIANESS_Pos            15U                                            /*!< SCB AIRCR: ENDIANESS Position */
+#define SCB_AIRCR_ENDIANESS_Msk            (1UL << SCB_AIRCR_ENDIANESS_Pos)               /*!< SCB AIRCR: ENDIANESS Mask */
+
+#define SCB_AIRCR_PRIGROUP_Pos              8U                                            /*!< SCB AIRCR: PRIGROUP Position */
+#define SCB_AIRCR_PRIGROUP_Msk             (7UL << SCB_AIRCR_PRIGROUP_Pos)                /*!< SCB AIRCR: PRIGROUP Mask */
+
+#define SCB_AIRCR_SYSRESETREQ_Pos           2U                                            /*!< SCB AIRCR: SYSRESETREQ Position */
+#define SCB_AIRCR_SYSRESETREQ_Msk          (1UL << SCB_AIRCR_SYSRESETREQ_Pos)             /*!< SCB AIRCR: SYSRESETREQ Mask */
+
+#define SCB_AIRCR_VECTCLRACTIVE_Pos         1U                                            /*!< SCB AIRCR: VECTCLRACTIVE Position */
+#define SCB_AIRCR_VECTCLRACTIVE_Msk        (1UL << SCB_AIRCR_VECTCLRACTIVE_Pos)           /*!< SCB AIRCR: VECTCLRACTIVE Mask */
+
+#define SCB_AIRCR_VECTRESET_Pos             0U                                            /*!< SCB AIRCR: VECTRESET Position */
+#define SCB_AIRCR_VECTRESET_Msk            (1UL /*<< SCB_AIRCR_VECTRESET_Pos*/)           /*!< SCB AIRCR: VECTRESET Mask */
+
+/* SCB System Control Register Definitions */
+#define SCB_SCR_SEVONPEND_Pos               4U                                            /*!< SCB SCR: SEVONPEND Position */
+#define SCB_SCR_SEVONPEND_Msk              (1UL << SCB_SCR_SEVONPEND_Pos)                 /*!< SCB SCR: SEVONPEND Mask */
+
+#define SCB_SCR_SLEEPDEEP_Pos               2U                                            /*!< SCB SCR: SLEEPDEEP Position */
+#define SCB_SCR_SLEEPDEEP_Msk              (1UL << SCB_SCR_SLEEPDEEP_Pos)                 /*!< SCB SCR: SLEEPDEEP Mask */
+
+#define SCB_SCR_SLEEPONEXIT_Pos             1U                                            /*!< SCB SCR: SLEEPONEXIT Position */
+#define SCB_SCR_SLEEPONEXIT_Msk            (1UL << SCB_SCR_SLEEPONEXIT_Pos)               /*!< SCB SCR: SLEEPONEXIT Mask */
+
+/* SCB Configuration Control Register Definitions */
+#define SCB_CCR_STKALIGN_Pos                9U                                            /*!< SCB CCR: STKALIGN Position */
+#define SCB_CCR_STKALIGN_Msk               (1UL << SCB_CCR_STKALIGN_Pos)                  /*!< SCB CCR: STKALIGN Mask */
+
+#define SCB_CCR_BFHFNMIGN_Pos               8U                                            /*!< SCB CCR: BFHFNMIGN Position */
+#define SCB_CCR_BFHFNMIGN_Msk              (1UL << SCB_CCR_BFHFNMIGN_Pos)                 /*!< SCB CCR: BFHFNMIGN Mask */
+
+#define SCB_CCR_DIV_0_TRP_Pos               4U                                            /*!< SCB CCR: DIV_0_TRP Position */
+#define SCB_CCR_DIV_0_TRP_Msk              (1UL << SCB_CCR_DIV_0_TRP_Pos)                 /*!< SCB CCR: DIV_0_TRP Mask */
+
+#define SCB_CCR_UNALIGN_TRP_Pos             3U                                            /*!< SCB CCR: UNALIGN_TRP Position */
+#define SCB_CCR_UNALIGN_TRP_Msk            (1UL << SCB_CCR_UNALIGN_TRP_Pos)               /*!< SCB CCR: UNALIGN_TRP Mask */
+
+#define SCB_CCR_USERSETMPEND_Pos            1U                                            /*!< SCB CCR: USERSETMPEND Position */
+#define SCB_CCR_USERSETMPEND_Msk           (1UL << SCB_CCR_USERSETMPEND_Pos)              /*!< SCB CCR: USERSETMPEND Mask */
+
+#define SCB_CCR_NONBASETHRDENA_Pos          0U                                            /*!< SCB CCR: NONBASETHRDENA Position */
+#define SCB_CCR_NONBASETHRDENA_Msk         (1UL /*<< SCB_CCR_NONBASETHRDENA_Pos*/)        /*!< SCB CCR: NONBASETHRDENA Mask */
+
+/* SCB System Handler Control and State Register Definitions */
+#define SCB_SHCSR_USGFAULTENA_Pos          18U                                            /*!< SCB SHCSR: USGFAULTENA Position */
+#define SCB_SHCSR_USGFAULTENA_Msk          (1UL << SCB_SHCSR_USGFAULTENA_Pos)             /*!< SCB SHCSR: USGFAULTENA Mask */
+
+#define SCB_SHCSR_BUSFAULTENA_Pos          17U                                            /*!< SCB SHCSR: BUSFAULTENA Position */
+#define SCB_SHCSR_BUSFAULTENA_Msk          (1UL << SCB_SHCSR_BUSFAULTENA_Pos)             /*!< SCB SHCSR: BUSFAULTENA Mask */
+
+#define SCB_SHCSR_MEMFAULTENA_Pos          16U                                            /*!< SCB SHCSR: MEMFAULTENA Position */
+#define SCB_SHCSR_MEMFAULTENA_Msk          (1UL << SCB_SHCSR_MEMFAULTENA_Pos)             /*!< SCB SHCSR: MEMFAULTENA Mask */
+
+#define SCB_SHCSR_SVCALLPENDED_Pos         15U                                            /*!< SCB SHCSR: SVCALLPENDED Position */
+#define SCB_SHCSR_SVCALLPENDED_Msk         (1UL << SCB_SHCSR_SVCALLPENDED_Pos)            /*!< SCB SHCSR: SVCALLPENDED Mask */
+
+#define SCB_SHCSR_BUSFAULTPENDED_Pos       14U                                            /*!< SCB SHCSR: BUSFAULTPENDED Position */
+#define SCB_SHCSR_BUSFAULTPENDED_Msk       (1UL << SCB_SHCSR_BUSFAULTPENDED_Pos)          /*!< SCB SHCSR: BUSFAULTPENDED Mask */
+
+#define SCB_SHCSR_MEMFAULTPENDED_Pos       13U                                            /*!< SCB SHCSR: MEMFAULTPENDED Position */
+#define SCB_SHCSR_MEMFAULTPENDED_Msk       (1UL << SCB_SHCSR_MEMFAULTPENDED_Pos)          /*!< SCB SHCSR: MEMFAULTPENDED Mask */
+
+#define SCB_SHCSR_USGFAULTPENDED_Pos       12U                                            /*!< SCB SHCSR: USGFAULTPENDED Position */
+#define SCB_SHCSR_USGFAULTPENDED_Msk       (1UL << SCB_SHCSR_USGFAULTPENDED_Pos)          /*!< SCB SHCSR: USGFAULTPENDED Mask */
+
+#define SCB_SHCSR_SYSTICKACT_Pos           11U                                            /*!< SCB SHCSR: SYSTICKACT Position */
+#define SCB_SHCSR_SYSTICKACT_Msk           (1UL << SCB_SHCSR_SYSTICKACT_Pos)              /*!< SCB SHCSR: SYSTICKACT Mask */
+
+#define SCB_SHCSR_PENDSVACT_Pos            10U                                            /*!< SCB SHCSR: PENDSVACT Position */
+#define SCB_SHCSR_PENDSVACT_Msk            (1UL << SCB_SHCSR_PENDSVACT_Pos)               /*!< SCB SHCSR: PENDSVACT Mask */
+
+#define SCB_SHCSR_MONITORACT_Pos            8U                                            /*!< SCB SHCSR: MONITORACT Position */
+#define SCB_SHCSR_MONITORACT_Msk           (1UL << SCB_SHCSR_MONITORACT_Pos)              /*!< SCB SHCSR: MONITORACT Mask */
+
+#define SCB_SHCSR_SVCALLACT_Pos             7U                                            /*!< SCB SHCSR: SVCALLACT Position */
+#define SCB_SHCSR_SVCALLACT_Msk            (1UL << SCB_SHCSR_SVCALLACT_Pos)               /*!< SCB SHCSR: SVCALLACT Mask */
+
+#define SCB_SHCSR_USGFAULTACT_Pos           3U                                            /*!< SCB SHCSR: USGFAULTACT Position */
+#define SCB_SHCSR_USGFAULTACT_Msk          (1UL << SCB_SHCSR_USGFAULTACT_Pos)             /*!< SCB SHCSR: USGFAULTACT Mask */
+
+#define SCB_SHCSR_BUSFAULTACT_Pos           1U                                            /*!< SCB SHCSR: BUSFAULTACT Position */
+#define SCB_SHCSR_BUSFAULTACT_Msk          (1UL << SCB_SHCSR_BUSFAULTACT_Pos)             /*!< SCB SHCSR: BUSFAULTACT Mask */
+
+#define SCB_SHCSR_MEMFAULTACT_Pos           0U                                            /*!< SCB SHCSR: MEMFAULTACT Position */
+#define SCB_SHCSR_MEMFAULTACT_Msk          (1UL /*<< SCB_SHCSR_MEMFAULTACT_Pos*/)         /*!< SCB SHCSR: MEMFAULTACT Mask */
+
+/* SCB Configurable Fault Status Register Definitions */
+#define SCB_CFSR_USGFAULTSR_Pos            16U                                            /*!< SCB CFSR: Usage Fault Status Register Position */
+#define SCB_CFSR_USGFAULTSR_Msk            (0xFFFFUL << SCB_CFSR_USGFAULTSR_Pos)          /*!< SCB CFSR: Usage Fault Status Register Mask */
+
+#define SCB_CFSR_BUSFAULTSR_Pos             8U                                            /*!< SCB CFSR: Bus Fault Status Register Position */
+#define SCB_CFSR_BUSFAULTSR_Msk            (0xFFUL << SCB_CFSR_BUSFAULTSR_Pos)            /*!< SCB CFSR: Bus Fault Status Register Mask */
+
+#define SCB_CFSR_MEMFAULTSR_Pos             0U                                            /*!< SCB CFSR: Memory Manage Fault Status Register Position */
+#define SCB_CFSR_MEMFAULTSR_Msk            (0xFFUL /*<< SCB_CFSR_MEMFAULTSR_Pos*/)        /*!< SCB CFSR: Memory Manage Fault Status Register Mask */
+
+/* MemManage Fault Status Register (part of SCB Configurable Fault Status Register) */
+#define SCB_CFSR_MMARVALID_Pos             (SCB_SHCSR_MEMFAULTACT_Pos + 7U)               /*!< SCB CFSR (MMFSR): MMARVALID Position */
+#define SCB_CFSR_MMARVALID_Msk             (1UL << SCB_CFSR_MMARVALID_Pos)                /*!< SCB CFSR (MMFSR): MMARVALID Mask */
+
+#define SCB_CFSR_MSTKERR_Pos               (SCB_SHCSR_MEMFAULTACT_Pos + 4U)               /*!< SCB CFSR (MMFSR): MSTKERR Position */
+#define SCB_CFSR_MSTKERR_Msk               (1UL << SCB_CFSR_MSTKERR_Pos)                  /*!< SCB CFSR (MMFSR): MSTKERR Mask */
+
+#define SCB_CFSR_MUNSTKERR_Pos             (SCB_SHCSR_MEMFAULTACT_Pos + 3U)               /*!< SCB CFSR (MMFSR): MUNSTKERR Position */
+#define SCB_CFSR_MUNSTKERR_Msk             (1UL << SCB_CFSR_MUNSTKERR_Pos)                /*!< SCB CFSR (MMFSR): MUNSTKERR Mask */
+
+#define SCB_CFSR_DACCVIOL_Pos              (SCB_SHCSR_MEMFAULTACT_Pos + 1U)               /*!< SCB CFSR (MMFSR): DACCVIOL Position */
+#define SCB_CFSR_DACCVIOL_Msk              (1UL << SCB_CFSR_DACCVIOL_Pos)                 /*!< SCB CFSR (MMFSR): DACCVIOL Mask */
+
+#define SCB_CFSR_IACCVIOL_Pos              (SCB_SHCSR_MEMFAULTACT_Pos + 0U)               /*!< SCB CFSR (MMFSR): IACCVIOL Position */
+#define SCB_CFSR_IACCVIOL_Msk              (1UL /*<< SCB_CFSR_IACCVIOL_Pos*/)             /*!< SCB CFSR (MMFSR): IACCVIOL Mask */
+
+/* BusFault Status Register (part of SCB Configurable Fault Status Register) */
+#define SCB_CFSR_BFARVALID_Pos            (SCB_CFSR_BUSFAULTSR_Pos + 7U)                  /*!< SCB CFSR (BFSR): BFARVALID Position */
+#define SCB_CFSR_BFARVALID_Msk            (1UL << SCB_CFSR_BFARVALID_Pos)                 /*!< SCB CFSR (BFSR): BFARVALID Mask */
+
+#define SCB_CFSR_STKERR_Pos               (SCB_CFSR_BUSFAULTSR_Pos + 4U)                  /*!< SCB CFSR (BFSR): STKERR Position */
+#define SCB_CFSR_STKERR_Msk               (1UL << SCB_CFSR_STKERR_Pos)                    /*!< SCB CFSR (BFSR): STKERR Mask */
+
+#define SCB_CFSR_UNSTKERR_Pos             (SCB_CFSR_BUSFAULTSR_Pos + 3U)                  /*!< SCB CFSR (BFSR): UNSTKERR Position */
+#define SCB_CFSR_UNSTKERR_Msk             (1UL << SCB_CFSR_UNSTKERR_Pos)                  /*!< SCB CFSR (BFSR): UNSTKERR Mask */
+
+#define SCB_CFSR_IMPRECISERR_Pos          (SCB_CFSR_BUSFAULTSR_Pos + 2U)                  /*!< SCB CFSR (BFSR): IMPRECISERR Position */
+#define SCB_CFSR_IMPRECISERR_Msk          (1UL << SCB_CFSR_IMPRECISERR_Pos)               /*!< SCB CFSR (BFSR): IMPRECISERR Mask */
+
+#define SCB_CFSR_PRECISERR_Pos            (SCB_CFSR_BUSFAULTSR_Pos + 1U)                  /*!< SCB CFSR (BFSR): PRECISERR Position */
+#define SCB_CFSR_PRECISERR_Msk            (1UL << SCB_CFSR_PRECISERR_Pos)                 /*!< SCB CFSR (BFSR): PRECISERR Mask */
+
+#define SCB_CFSR_IBUSERR_Pos              (SCB_CFSR_BUSFAULTSR_Pos + 0U)                  /*!< SCB CFSR (BFSR): IBUSERR Position */
+#define SCB_CFSR_IBUSERR_Msk              (1UL << SCB_CFSR_IBUSERR_Pos)                   /*!< SCB CFSR (BFSR): IBUSERR Mask */
+
+/* UsageFault Status Register (part of SCB Configurable Fault Status Register) */
+#define SCB_CFSR_DIVBYZERO_Pos            (SCB_CFSR_USGFAULTSR_Pos + 9U)                  /*!< SCB CFSR (UFSR): DIVBYZERO Position */
+#define SCB_CFSR_DIVBYZERO_Msk            (1UL << SCB_CFSR_DIVBYZERO_Pos)                 /*!< SCB CFSR (UFSR): DIVBYZERO Mask */
+
+#define SCB_CFSR_UNALIGNED_Pos            (SCB_CFSR_USGFAULTSR_Pos + 8U)                  /*!< SCB CFSR (UFSR): UNALIGNED Position */
+#define SCB_CFSR_UNALIGNED_Msk            (1UL << SCB_CFSR_UNALIGNED_Pos)                 /*!< SCB CFSR (UFSR): UNALIGNED Mask */
+
+#define SCB_CFSR_NOCP_Pos                 (SCB_CFSR_USGFAULTSR_Pos + 3U)                  /*!< SCB CFSR (UFSR): NOCP Position */
+#define SCB_CFSR_NOCP_Msk                 (1UL << SCB_CFSR_NOCP_Pos)                      /*!< SCB CFSR (UFSR): NOCP Mask */
+
+#define SCB_CFSR_INVPC_Pos                (SCB_CFSR_USGFAULTSR_Pos + 2U)                  /*!< SCB CFSR (UFSR): INVPC Position */
+#define SCB_CFSR_INVPC_Msk                (1UL << SCB_CFSR_INVPC_Pos)                     /*!< SCB CFSR (UFSR): INVPC Mask */
+
+#define SCB_CFSR_INVSTATE_Pos             (SCB_CFSR_USGFAULTSR_Pos + 1U)                  /*!< SCB CFSR (UFSR): INVSTATE Position */
+#define SCB_CFSR_INVSTATE_Msk             (1UL << SCB_CFSR_INVSTATE_Pos)                  /*!< SCB CFSR (UFSR): INVSTATE Mask */
+
+#define SCB_CFSR_UNDEFINSTR_Pos           (SCB_CFSR_USGFAULTSR_Pos + 0U)                  /*!< SCB CFSR (UFSR): UNDEFINSTR Position */
+#define SCB_CFSR_UNDEFINSTR_Msk           (1UL << SCB_CFSR_UNDEFINSTR_Pos)                /*!< SCB CFSR (UFSR): UNDEFINSTR Mask */
+
+/* SCB Hard Fault Status Register Definitions */
+#define SCB_HFSR_DEBUGEVT_Pos              31U                                            /*!< SCB HFSR: DEBUGEVT Position */
+#define SCB_HFSR_DEBUGEVT_Msk              (1UL << SCB_HFSR_DEBUGEVT_Pos)                 /*!< SCB HFSR: DEBUGEVT Mask */
+
+#define SCB_HFSR_FORCED_Pos                30U                                            /*!< SCB HFSR: FORCED Position */
+#define SCB_HFSR_FORCED_Msk                (1UL << SCB_HFSR_FORCED_Pos)                   /*!< SCB HFSR: FORCED Mask */
+
+#define SCB_HFSR_VECTTBL_Pos                1U                                            /*!< SCB HFSR: VECTTBL Position */
+#define SCB_HFSR_VECTTBL_Msk               (1UL << SCB_HFSR_VECTTBL_Pos)                  /*!< SCB HFSR: VECTTBL Mask */
+
+/* SCB Debug Fault Status Register Definitions */
+#define SCB_DFSR_EXTERNAL_Pos               4U                                            /*!< SCB DFSR: EXTERNAL Position */
+#define SCB_DFSR_EXTERNAL_Msk              (1UL << SCB_DFSR_EXTERNAL_Pos)                 /*!< SCB DFSR: EXTERNAL Mask */
+
+#define SCB_DFSR_VCATCH_Pos                 3U                                            /*!< SCB DFSR: VCATCH Position */
+#define SCB_DFSR_VCATCH_Msk                (1UL << SCB_DFSR_VCATCH_Pos)                   /*!< SCB DFSR: VCATCH Mask */
+
+#define SCB_DFSR_DWTTRAP_Pos                2U                                            /*!< SCB DFSR: DWTTRAP Position */
+#define SCB_DFSR_DWTTRAP_Msk               (1UL << SCB_DFSR_DWTTRAP_Pos)                  /*!< SCB DFSR: DWTTRAP Mask */
+
+#define SCB_DFSR_BKPT_Pos                   1U                                            /*!< SCB DFSR: BKPT Position */
+#define SCB_DFSR_BKPT_Msk                  (1UL << SCB_DFSR_BKPT_Pos)                     /*!< SCB DFSR: BKPT Mask */
+
+#define SCB_DFSR_HALTED_Pos                 0U                                            /*!< SCB DFSR: HALTED Position */
+#define SCB_DFSR_HALTED_Msk                (1UL /*<< SCB_DFSR_HALTED_Pos*/)               /*!< SCB DFSR: HALTED Mask */
+
+/*@} end of group CMSIS_SCB */
+
+
+/**
+  \ingroup  CMSIS_core_register
+  \defgroup CMSIS_SCnSCB System Controls not in SCB (SCnSCB)
+  \brief    Type definitions for the System Control and ID Register not in the SCB
+  @{
+ */
+
+/**
+  \brief  Structure type to access the System Control and ID Register not in the SCB.
+ */
+typedef struct
+{
+        uint32_t RESERVED0[1U];
+  __IM  uint32_t ICTR;                   /*!< Offset: 0x004 (R/ )  Interrupt Controller Type Register */
+#if defined (__CM3_REV) && (__CM3_REV >= 0x200U)
+  __IOM uint32_t ACTLR;                  /*!< Offset: 0x008 (R/W)  Auxiliary Control Register */
+#else
+        uint32_t RESERVED1[1U];
+#endif
+} SCnSCB_Type;
+
+/* Interrupt Controller Type Register Definitions */
+#define SCnSCB_ICTR_INTLINESNUM_Pos         0U                                         /*!< ICTR: INTLINESNUM Position */
+#define SCnSCB_ICTR_INTLINESNUM_Msk        (0xFUL /*<< SCnSCB_ICTR_INTLINESNUM_Pos*/)  /*!< ICTR: INTLINESNUM Mask */
+
+/* Auxiliary Control Register Definitions */
+
+#define SCnSCB_ACTLR_DISFOLD_Pos            2U                                         /*!< ACTLR: DISFOLD Position */
+#define SCnSCB_ACTLR_DISFOLD_Msk           (1UL << SCnSCB_ACTLR_DISFOLD_Pos)           /*!< ACTLR: DISFOLD Mask */
+
+#define SCnSCB_ACTLR_DISDEFWBUF_Pos         1U                                         /*!< ACTLR: DISDEFWBUF Position */
+#define SCnSCB_ACTLR_DISDEFWBUF_Msk        (1UL << SCnSCB_ACTLR_DISDEFWBUF_Pos)        /*!< ACTLR: DISDEFWBUF Mask */
+
+#define SCnSCB_ACTLR_DISMCYCINT_Pos         0U                                         /*!< ACTLR: DISMCYCINT Position */
+#define SCnSCB_ACTLR_DISMCYCINT_Msk        (1UL /*<< SCnSCB_ACTLR_DISMCYCINT_Pos*/)    /*!< ACTLR: DISMCYCINT Mask */
+
+/*@} end of group CMSIS_SCnotSCB */
+
+
+/**
+  \ingroup  CMSIS_core_register
+  \defgroup CMSIS_SysTick     System Tick Timer (SysTick)
+  \brief    Type definitions for the System Timer Registers.
+  @{
+ */
+
+/**
+  \brief  Structure type to access the System Timer (SysTick).
+ */
+typedef struct
+{
+  __IOM uint32_t CTRL;                   /*!< Offset: 0x000 (R/W)  SysTick Control and Status Register */
+  __IOM uint32_t LOAD;                   /*!< Offset: 0x004 (R/W)  SysTick Reload Value Register */
+  __IOM uint32_t VAL;                    /*!< Offset: 0x008 (R/W)  SysTick Current Value Register */
+  __IM  uint32_t CALIB;                  /*!< Offset: 0x00C (R/ )  SysTick Calibration Register */
+} SysTick_Type;
+
+/* SysTick Control / Status Register Definitions */
+#define SysTick_CTRL_COUNTFLAG_Pos         16U                                            /*!< SysTick CTRL: COUNTFLAG Position */
+#define SysTick_CTRL_COUNTFLAG_Msk         (1UL << SysTick_CTRL_COUNTFLAG_Pos)            /*!< SysTick CTRL: COUNTFLAG Mask */
+
+#define SysTick_CTRL_CLKSOURCE_Pos          2U                                            /*!< SysTick CTRL: CLKSOURCE Position */
+#define SysTick_CTRL_CLKSOURCE_Msk         (1UL << SysTick_CTRL_CLKSOURCE_Pos)            /*!< SysTick CTRL: CLKSOURCE Mask */
+
+#define SysTick_CTRL_TICKINT_Pos            1U                                            /*!< SysTick CTRL: TICKINT Position */
+#define SysTick_CTRL_TICKINT_Msk           (1UL << SysTick_CTRL_TICKINT_Pos)              /*!< SysTick CTRL: TICKINT Mask */
+
+#define SysTick_CTRL_ENABLE_Pos             0U                                            /*!< SysTick CTRL: ENABLE Position */
+#define SysTick_CTRL_ENABLE_Msk            (1UL /*<< SysTick_CTRL_ENABLE_Pos*/)           /*!< SysTick CTRL: ENABLE Mask */
+
+/* SysTick Reload Register Definitions */
+#define SysTick_LOAD_RELOAD_Pos             0U                                            /*!< SysTick LOAD: RELOAD Position */
+#define SysTick_LOAD_RELOAD_Msk            (0xFFFFFFUL /*<< SysTick_LOAD_RELOAD_Pos*/)    /*!< SysTick LOAD: RELOAD Mask */
+
+/* SysTick Current Register Definitions */
+#define SysTick_VAL_CURRENT_Pos             0U                                            /*!< SysTick VAL: CURRENT Position */
+#define SysTick_VAL_CURRENT_Msk            (0xFFFFFFUL /*<< SysTick_VAL_CURRENT_Pos*/)    /*!< SysTick VAL: CURRENT Mask */
+
+/* SysTick Calibration Register Definitions */
+#define SysTick_CALIB_NOREF_Pos            31U                                            /*!< SysTick CALIB: NOREF Position */
+#define SysTick_CALIB_NOREF_Msk            (1UL << SysTick_CALIB_NOREF_Pos)               /*!< SysTick CALIB: NOREF Mask */
+
+#define SysTick_CALIB_SKEW_Pos             30U                                            /*!< SysTick CALIB: SKEW Position */
+#define SysTick_CALIB_SKEW_Msk             (1UL << SysTick_CALIB_SKEW_Pos)                /*!< SysTick CALIB: SKEW Mask */
+
+#define SysTick_CALIB_TENMS_Pos             0U                                            /*!< SysTick CALIB: TENMS Position */
+#define SysTick_CALIB_TENMS_Msk            (0xFFFFFFUL /*<< SysTick_CALIB_TENMS_Pos*/)    /*!< SysTick CALIB: TENMS Mask */
+
+/*@} end of group CMSIS_SysTick */
+
+
+/**
+  \ingroup  CMSIS_core_register
+  \defgroup CMSIS_ITM     Instrumentation Trace Macrocell (ITM)
+  \brief    Type definitions for the Instrumentation Trace Macrocell (ITM)
+  @{
+ */
+
+/**
+  \brief  Structure type to access the Instrumentation Trace Macrocell Register (ITM).
+ */
+typedef struct
+{
+  __OM  union
+  {
+    __OM  uint8_t    u8;                 /*!< Offset: 0x000 ( /W)  ITM Stimulus Port 8-bit */
+    __OM  uint16_t   u16;                /*!< Offset: 0x000 ( /W)  ITM Stimulus Port 16-bit */
+    __OM  uint32_t   u32;                /*!< Offset: 0x000 ( /W)  ITM Stimulus Port 32-bit */
+  }  PORT [32U];                         /*!< Offset: 0x000 ( /W)  ITM Stimulus Port Registers */
+        uint32_t RESERVED0[864U];
+  __IOM uint32_t TER;                    /*!< Offset: 0xE00 (R/W)  ITM Trace Enable Register */
+        uint32_t RESERVED1[15U];
+  __IOM uint32_t TPR;                    /*!< Offset: 0xE40 (R/W)  ITM Trace Privilege Register */
+        uint32_t RESERVED2[15U];
+  __IOM uint32_t TCR;                    /*!< Offset: 0xE80 (R/W)  ITM Trace Control Register */
+        uint32_t RESERVED3[29U];
+  __OM  uint32_t IWR;                    /*!< Offset: 0xEF8 ( /W)  ITM Integration Write Register */
+  __IM  uint32_t IRR;                    /*!< Offset: 0xEFC (R/ )  ITM Integration Read Register */
+  __IOM uint32_t IMCR;                   /*!< Offset: 0xF00 (R/W)  ITM Integration Mode Control Register */
+        uint32_t RESERVED4[43U];
+  __OM  uint32_t LAR;                    /*!< Offset: 0xFB0 ( /W)  ITM Lock Access Register */
+  __IM  uint32_t LSR;                    /*!< Offset: 0xFB4 (R/ )  ITM Lock Status Register */
+        uint32_t RESERVED5[6U];
+  __IM  uint32_t PID4;                   /*!< Offset: 0xFD0 (R/ )  ITM Peripheral Identification Register #4 */
+  __IM  uint32_t PID5;                   /*!< Offset: 0xFD4 (R/ )  ITM Peripheral Identification Register #5 */
+  __IM  uint32_t PID6;                   /*!< Offset: 0xFD8 (R/ )  ITM Peripheral Identification Register #6 */
+  __IM  uint32_t PID7;                   /*!< Offset: 0xFDC (R/ )  ITM Peripheral Identification Register #7 */
+  __IM  uint32_t PID0;                   /*!< Offset: 0xFE0 (R/ )  ITM Peripheral Identification Register #0 */
+  __IM  uint32_t PID1;                   /*!< Offset: 0xFE4 (R/ )  ITM Peripheral Identification Register #1 */
+  __IM  uint32_t PID2;                   /*!< Offset: 0xFE8 (R/ )  ITM Peripheral Identification Register #2 */
+  __IM  uint32_t PID3;                   /*!< Offset: 0xFEC (R/ )  ITM Peripheral Identification Register #3 */
+  __IM  uint32_t CID0;                   /*!< Offset: 0xFF0 (R/ )  ITM Component  Identification Register #0 */
+  __IM  uint32_t CID1;                   /*!< Offset: 0xFF4 (R/ )  ITM Component  Identification Register #1 */
+  __IM  uint32_t CID2;                   /*!< Offset: 0xFF8 (R/ )  ITM Component  Identification Register #2 */
+  __IM  uint32_t CID3;                   /*!< Offset: 0xFFC (R/ )  ITM Component  Identification Register #3 */
+} ITM_Type;
+
+/* ITM Trace Privilege Register Definitions */
+#define ITM_TPR_PRIVMASK_Pos                0U                                            /*!< ITM TPR: PRIVMASK Position */
+#define ITM_TPR_PRIVMASK_Msk               (0xFFFFFFFFUL /*<< ITM_TPR_PRIVMASK_Pos*/)     /*!< ITM TPR: PRIVMASK Mask */
+
+/* ITM Trace Control Register Definitions */
+#define ITM_TCR_BUSY_Pos                   23U                                            /*!< ITM TCR: BUSY Position */
+#define ITM_TCR_BUSY_Msk                   (1UL << ITM_TCR_BUSY_Pos)                      /*!< ITM TCR: BUSY Mask */
+
+#define ITM_TCR_TraceBusID_Pos             16U                                            /*!< ITM TCR: ATBID Position */
+#define ITM_TCR_TraceBusID_Msk             (0x7FUL << ITM_TCR_TraceBusID_Pos)             /*!< ITM TCR: ATBID Mask */
+
+#define ITM_TCR_GTSFREQ_Pos                10U                                            /*!< ITM TCR: Global timestamp frequency Position */
+#define ITM_TCR_GTSFREQ_Msk                (3UL << ITM_TCR_GTSFREQ_Pos)                   /*!< ITM TCR: Global timestamp frequency Mask */
+
+#define ITM_TCR_TSPrescale_Pos              8U                                            /*!< ITM TCR: TSPrescale Position */
+#define ITM_TCR_TSPrescale_Msk             (3UL << ITM_TCR_TSPrescale_Pos)                /*!< ITM TCR: TSPrescale Mask */
+
+#define ITM_TCR_SWOENA_Pos                  4U                                            /*!< ITM TCR: SWOENA Position */
+#define ITM_TCR_SWOENA_Msk                 (1UL << ITM_TCR_SWOENA_Pos)                    /*!< ITM TCR: SWOENA Mask */
+
+#define ITM_TCR_DWTENA_Pos                  3U                                            /*!< ITM TCR: DWTENA Position */
+#define ITM_TCR_DWTENA_Msk                 (1UL << ITM_TCR_DWTENA_Pos)                    /*!< ITM TCR: DWTENA Mask */
+
+#define ITM_TCR_SYNCENA_Pos                 2U                                            /*!< ITM TCR: SYNCENA Position */
+#define ITM_TCR_SYNCENA_Msk                (1UL << ITM_TCR_SYNCENA_Pos)                   /*!< ITM TCR: SYNCENA Mask */
+
+#define ITM_TCR_TSENA_Pos                   1U                                            /*!< ITM TCR: TSENA Position */
+#define ITM_TCR_TSENA_Msk                  (1UL << ITM_TCR_TSENA_Pos)                     /*!< ITM TCR: TSENA Mask */
+
+#define ITM_TCR_ITMENA_Pos                  0U                                            /*!< ITM TCR: ITM Enable bit Position */
+#define ITM_TCR_ITMENA_Msk                 (1UL /*<< ITM_TCR_ITMENA_Pos*/)                /*!< ITM TCR: ITM Enable bit Mask */
+
+/* ITM Integration Write Register Definitions */
+#define ITM_IWR_ATVALIDM_Pos                0U                                            /*!< ITM IWR: ATVALIDM Position */
+#define ITM_IWR_ATVALIDM_Msk               (1UL /*<< ITM_IWR_ATVALIDM_Pos*/)              /*!< ITM IWR: ATVALIDM Mask */
+
+/* ITM Integration Read Register Definitions */
+#define ITM_IRR_ATREADYM_Pos                0U                                            /*!< ITM IRR: ATREADYM Position */
+#define ITM_IRR_ATREADYM_Msk               (1UL /*<< ITM_IRR_ATREADYM_Pos*/)              /*!< ITM IRR: ATREADYM Mask */
+
+/* ITM Integration Mode Control Register Definitions */
+#define ITM_IMCR_INTEGRATION_Pos            0U                                            /*!< ITM IMCR: INTEGRATION Position */
+#define ITM_IMCR_INTEGRATION_Msk           (1UL /*<< ITM_IMCR_INTEGRATION_Pos*/)          /*!< ITM IMCR: INTEGRATION Mask */
+
+/* ITM Lock Status Register Definitions */
+#define ITM_LSR_ByteAcc_Pos                 2U                                            /*!< ITM LSR: ByteAcc Position */
+#define ITM_LSR_ByteAcc_Msk                (1UL << ITM_LSR_ByteAcc_Pos)                   /*!< ITM LSR: ByteAcc Mask */
+
+#define ITM_LSR_Access_Pos                  1U                                            /*!< ITM LSR: Access Position */
+#define ITM_LSR_Access_Msk                 (1UL << ITM_LSR_Access_Pos)                    /*!< ITM LSR: Access Mask */
+
+#define ITM_LSR_Present_Pos                 0U                                            /*!< ITM LSR: Present Position */
+#define ITM_LSR_Present_Msk                (1UL /*<< ITM_LSR_Present_Pos*/)               /*!< ITM LSR: Present Mask */
+
+/*@}*/ /* end of group CMSIS_ITM */
+
+
+/**
+  \ingroup  CMSIS_core_register
+  \defgroup CMSIS_DWT     Data Watchpoint and Trace (DWT)
+  \brief    Type definitions for the Data Watchpoint and Trace (DWT)
+  @{
+ */
+
+/**
+  \brief  Structure type to access the Data Watchpoint and Trace Register (DWT).
+ */
+typedef struct
+{
+  __IOM uint32_t CTRL;                   /*!< Offset: 0x000 (R/W)  Control Register */
+  __IOM uint32_t CYCCNT;                 /*!< Offset: 0x004 (R/W)  Cycle Count Register */
+  __IOM uint32_t CPICNT;                 /*!< Offset: 0x008 (R/W)  CPI Count Register */
+  __IOM uint32_t EXCCNT;                 /*!< Offset: 0x00C (R/W)  Exception Overhead Count Register */
+  __IOM uint32_t SLEEPCNT;               /*!< Offset: 0x010 (R/W)  Sleep Count Register */
+  __IOM uint32_t LSUCNT;                 /*!< Offset: 0x014 (R/W)  LSU Count Register */
+  __IOM uint32_t FOLDCNT;                /*!< Offset: 0x018 (R/W)  Folded-instruction Count Register */
+  __IM  uint32_t PCSR;                   /*!< Offset: 0x01C (R/ )  Program Counter Sample Register */
+  __IOM uint32_t COMP0;                  /*!< Offset: 0x020 (R/W)  Comparator Register 0 */
+  __IOM uint32_t MASK0;                  /*!< Offset: 0x024 (R/W)  Mask Register 0 */
+  __IOM uint32_t FUNCTION0;              /*!< Offset: 0x028 (R/W)  Function Register 0 */
+        uint32_t RESERVED0[1U];
+  __IOM uint32_t COMP1;                  /*!< Offset: 0x030 (R/W)  Comparator Register 1 */
+  __IOM uint32_t MASK1;                  /*!< Offset: 0x034 (R/W)  Mask Register 1 */
+  __IOM uint32_t FUNCTION1;              /*!< Offset: 0x038 (R/W)  Function Register 1 */
+        uint32_t RESERVED1[1U];
+  __IOM uint32_t COMP2;                  /*!< Offset: 0x040 (R/W)  Comparator Register 2 */
+  __IOM uint32_t MASK2;                  /*!< Offset: 0x044 (R/W)  Mask Register 2 */
+  __IOM uint32_t FUNCTION2;              /*!< Offset: 0x048 (R/W)  Function Register 2 */
+        uint32_t RESERVED2[1U];
+  __IOM uint32_t COMP3;                  /*!< Offset: 0x050 (R/W)  Comparator Register 3 */
+  __IOM uint32_t MASK3;                  /*!< Offset: 0x054 (R/W)  Mask Register 3 */
+  __IOM uint32_t FUNCTION3;              /*!< Offset: 0x058 (R/W)  Function Register 3 */
+} DWT_Type;
+
+/* DWT Control Register Definitions */
+#define DWT_CTRL_NUMCOMP_Pos               28U                                         /*!< DWT CTRL: NUMCOMP Position */
+#define DWT_CTRL_NUMCOMP_Msk               (0xFUL << DWT_CTRL_NUMCOMP_Pos)             /*!< DWT CTRL: NUMCOMP Mask */
+
+#define DWT_CTRL_NOTRCPKT_Pos              27U                                         /*!< DWT CTRL: NOTRCPKT Position */
+#define DWT_CTRL_NOTRCPKT_Msk              (0x1UL << DWT_CTRL_NOTRCPKT_Pos)            /*!< DWT CTRL: NOTRCPKT Mask */
+
+#define DWT_CTRL_NOEXTTRIG_Pos             26U                                         /*!< DWT CTRL: NOEXTTRIG Position */
+#define DWT_CTRL_NOEXTTRIG_Msk             (0x1UL << DWT_CTRL_NOEXTTRIG_Pos)           /*!< DWT CTRL: NOEXTTRIG Mask */
+
+#define DWT_CTRL_NOCYCCNT_Pos              25U                                         /*!< DWT CTRL: NOCYCCNT Position */
+#define DWT_CTRL_NOCYCCNT_Msk              (0x1UL << DWT_CTRL_NOCYCCNT_Pos)            /*!< DWT CTRL: NOCYCCNT Mask */
+
+#define DWT_CTRL_NOPRFCNT_Pos              24U                                         /*!< DWT CTRL: NOPRFCNT Position */
+#define DWT_CTRL_NOPRFCNT_Msk              (0x1UL << DWT_CTRL_NOPRFCNT_Pos)            /*!< DWT CTRL: NOPRFCNT Mask */
+
+#define DWT_CTRL_CYCEVTENA_Pos             22U                                         /*!< DWT CTRL: CYCEVTENA Position */
+#define DWT_CTRL_CYCEVTENA_Msk             (0x1UL << DWT_CTRL_CYCEVTENA_Pos)           /*!< DWT CTRL: CYCEVTENA Mask */
+
+#define DWT_CTRL_FOLDEVTENA_Pos            21U                                         /*!< DWT CTRL: FOLDEVTENA Position */
+#define DWT_CTRL_FOLDEVTENA_Msk            (0x1UL << DWT_CTRL_FOLDEVTENA_Pos)          /*!< DWT CTRL: FOLDEVTENA Mask */
+
+#define DWT_CTRL_LSUEVTENA_Pos             20U                                         /*!< DWT CTRL: LSUEVTENA Position */
+#define DWT_CTRL_LSUEVTENA_Msk             (0x1UL << DWT_CTRL_LSUEVTENA_Pos)           /*!< DWT CTRL: LSUEVTENA Mask */
+
+#define DWT_CTRL_SLEEPEVTENA_Pos           19U                                         /*!< DWT CTRL: SLEEPEVTENA Position */
+#define DWT_CTRL_SLEEPEVTENA_Msk           (0x1UL << DWT_CTRL_SLEEPEVTENA_Pos)         /*!< DWT CTRL: SLEEPEVTENA Mask */
+
+#define DWT_CTRL_EXCEVTENA_Pos             18U                                         /*!< DWT CTRL: EXCEVTENA Position */
+#define DWT_CTRL_EXCEVTENA_Msk             (0x1UL << DWT_CTRL_EXCEVTENA_Pos)           /*!< DWT CTRL: EXCEVTENA Mask */
+
+#define DWT_CTRL_CPIEVTENA_Pos             17U                                         /*!< DWT CTRL: CPIEVTENA Position */
+#define DWT_CTRL_CPIEVTENA_Msk             (0x1UL << DWT_CTRL_CPIEVTENA_Pos)           /*!< DWT CTRL: CPIEVTENA Mask */
+
+#define DWT_CTRL_EXCTRCENA_Pos             16U                                         /*!< DWT CTRL: EXCTRCENA Position */
+#define DWT_CTRL_EXCTRCENA_Msk             (0x1UL << DWT_CTRL_EXCTRCENA_Pos)           /*!< DWT CTRL: EXCTRCENA Mask */
+
+#define DWT_CTRL_PCSAMPLENA_Pos            12U                                         /*!< DWT CTRL: PCSAMPLENA Position */
+#define DWT_CTRL_PCSAMPLENA_Msk            (0x1UL << DWT_CTRL_PCSAMPLENA_Pos)          /*!< DWT CTRL: PCSAMPLENA Mask */
+
+#define DWT_CTRL_SYNCTAP_Pos               10U                                         /*!< DWT CTRL: SYNCTAP Position */
+#define DWT_CTRL_SYNCTAP_Msk               (0x3UL << DWT_CTRL_SYNCTAP_Pos)             /*!< DWT CTRL: SYNCTAP Mask */
+
+#define DWT_CTRL_CYCTAP_Pos                 9U                                         /*!< DWT CTRL: CYCTAP Position */
+#define DWT_CTRL_CYCTAP_Msk                (0x1UL << DWT_CTRL_CYCTAP_Pos)              /*!< DWT CTRL: CYCTAP Mask */
+
+#define DWT_CTRL_POSTINIT_Pos               5U                                         /*!< DWT CTRL: POSTINIT Position */
+#define DWT_CTRL_POSTINIT_Msk              (0xFUL << DWT_CTRL_POSTINIT_Pos)            /*!< DWT CTRL: POSTINIT Mask */
+
+#define DWT_CTRL_POSTPRESET_Pos             1U                                         /*!< DWT CTRL: POSTPRESET Position */
+#define DWT_CTRL_POSTPRESET_Msk            (0xFUL << DWT_CTRL_POSTPRESET_Pos)          /*!< DWT CTRL: POSTPRESET Mask */
+
+#define DWT_CTRL_CYCCNTENA_Pos              0U                                         /*!< DWT CTRL: CYCCNTENA Position */
+#define DWT_CTRL_CYCCNTENA_Msk             (0x1UL /*<< DWT_CTRL_CYCCNTENA_Pos*/)       /*!< DWT CTRL: CYCCNTENA Mask */
+
+/* DWT CPI Count Register Definitions */
+#define DWT_CPICNT_CPICNT_Pos               0U                                         /*!< DWT CPICNT: CPICNT Position */
+#define DWT_CPICNT_CPICNT_Msk              (0xFFUL /*<< DWT_CPICNT_CPICNT_Pos*/)       /*!< DWT CPICNT: CPICNT Mask */
+
+/* DWT Exception Overhead Count Register Definitions */
+#define DWT_EXCCNT_EXCCNT_Pos               0U                                         /*!< DWT EXCCNT: EXCCNT Position */
+#define DWT_EXCCNT_EXCCNT_Msk              (0xFFUL /*<< DWT_EXCCNT_EXCCNT_Pos*/)       /*!< DWT EXCCNT: EXCCNT Mask */
+
+/* DWT Sleep Count Register Definitions */
+#define DWT_SLEEPCNT_SLEEPCNT_Pos           0U                                         /*!< DWT SLEEPCNT: SLEEPCNT Position */
+#define DWT_SLEEPCNT_SLEEPCNT_Msk          (0xFFUL /*<< DWT_SLEEPCNT_SLEEPCNT_Pos*/)   /*!< DWT SLEEPCNT: SLEEPCNT Mask */
+
+/* DWT LSU Count Register Definitions */
+#define DWT_LSUCNT_LSUCNT_Pos               0U                                         /*!< DWT LSUCNT: LSUCNT Position */
+#define DWT_LSUCNT_LSUCNT_Msk              (0xFFUL /*<< DWT_LSUCNT_LSUCNT_Pos*/)       /*!< DWT LSUCNT: LSUCNT Mask */
+
+/* DWT Folded-instruction Count Register Definitions */
+#define DWT_FOLDCNT_FOLDCNT_Pos             0U                                         /*!< DWT FOLDCNT: FOLDCNT Position */
+#define DWT_FOLDCNT_FOLDCNT_Msk            (0xFFUL /*<< DWT_FOLDCNT_FOLDCNT_Pos*/)     /*!< DWT FOLDCNT: FOLDCNT Mask */
+
+/* DWT Comparator Mask Register Definitions */
+#define DWT_MASK_MASK_Pos                   0U                                         /*!< DWT MASK: MASK Position */
+#define DWT_MASK_MASK_Msk                  (0x1FUL /*<< DWT_MASK_MASK_Pos*/)           /*!< DWT MASK: MASK Mask */
+
+/* DWT Comparator Function Register Definitions */
+#define DWT_FUNCTION_MATCHED_Pos           24U                                         /*!< DWT FUNCTION: MATCHED Position */
+#define DWT_FUNCTION_MATCHED_Msk           (0x1UL << DWT_FUNCTION_MATCHED_Pos)         /*!< DWT FUNCTION: MATCHED Mask */
+
+#define DWT_FUNCTION_DATAVADDR1_Pos        16U                                         /*!< DWT FUNCTION: DATAVADDR1 Position */
+#define DWT_FUNCTION_DATAVADDR1_Msk        (0xFUL << DWT_FUNCTION_DATAVADDR1_Pos)      /*!< DWT FUNCTION: DATAVADDR1 Mask */
+
+#define DWT_FUNCTION_DATAVADDR0_Pos        12U                                         /*!< DWT FUNCTION: DATAVADDR0 Position */
+#define DWT_FUNCTION_DATAVADDR0_Msk        (0xFUL << DWT_FUNCTION_DATAVADDR0_Pos)      /*!< DWT FUNCTION: DATAVADDR0 Mask */
+
+#define DWT_FUNCTION_DATAVSIZE_Pos         10U                                         /*!< DWT FUNCTION: DATAVSIZE Position */
+#define DWT_FUNCTION_DATAVSIZE_Msk         (0x3UL << DWT_FUNCTION_DATAVSIZE_Pos)       /*!< DWT FUNCTION: DATAVSIZE Mask */
+
+#define DWT_FUNCTION_LNK1ENA_Pos            9U                                         /*!< DWT FUNCTION: LNK1ENA Position */
+#define DWT_FUNCTION_LNK1ENA_Msk           (0x1UL << DWT_FUNCTION_LNK1ENA_Pos)         /*!< DWT FUNCTION: LNK1ENA Mask */
+
+#define DWT_FUNCTION_DATAVMATCH_Pos         8U                                         /*!< DWT FUNCTION: DATAVMATCH Position */
+#define DWT_FUNCTION_DATAVMATCH_Msk        (0x1UL << DWT_FUNCTION_DATAVMATCH_Pos)      /*!< DWT FUNCTION: DATAVMATCH Mask */
+
+#define DWT_FUNCTION_CYCMATCH_Pos           7U                                         /*!< DWT FUNCTION: CYCMATCH Position */
+#define DWT_FUNCTION_CYCMATCH_Msk          (0x1UL << DWT_FUNCTION_CYCMATCH_Pos)        /*!< DWT FUNCTION: CYCMATCH Mask */
+
+#define DWT_FUNCTION_EMITRANGE_Pos          5U                                         /*!< DWT FUNCTION: EMITRANGE Position */
+#define DWT_FUNCTION_EMITRANGE_Msk         (0x1UL << DWT_FUNCTION_EMITRANGE_Pos)       /*!< DWT FUNCTION: EMITRANGE Mask */
+
+#define DWT_FUNCTION_FUNCTION_Pos           0U                                         /*!< DWT FUNCTION: FUNCTION Position */
+#define DWT_FUNCTION_FUNCTION_Msk          (0xFUL /*<< DWT_FUNCTION_FUNCTION_Pos*/)    /*!< DWT FUNCTION: FUNCTION Mask */
+
+/*@}*/ /* end of group CMSIS_DWT */
+
+
+/**
+  \ingroup  CMSIS_core_register
+  \defgroup CMSIS_TPI     Trace Port Interface (TPI)
+  \brief    Type definitions for the Trace Port Interface (TPI)
+  @{
+ */
+
+/**
+  \brief  Structure type to access the Trace Port Interface Register (TPI).
+ */
+typedef struct
+{
+  __IM  uint32_t SSPSR;                  /*!< Offset: 0x000 (R/ )  Supported Parallel Port Size Register */
+  __IOM uint32_t CSPSR;                  /*!< Offset: 0x004 (R/W)  Current Parallel Port Size Register */
+        uint32_t RESERVED0[2U];
+  __IOM uint32_t ACPR;                   /*!< Offset: 0x010 (R/W)  Asynchronous Clock Prescaler Register */
+        uint32_t RESERVED1[55U];
+  __IOM uint32_t SPPR;                   /*!< Offset: 0x0F0 (R/W)  Selected Pin Protocol Register */
+        uint32_t RESERVED2[131U];
+  __IM  uint32_t FFSR;                   /*!< Offset: 0x300 (R/ )  Formatter and Flush Status Register */
+  __IOM uint32_t FFCR;                   /*!< Offset: 0x304 (R/W)  Formatter and Flush Control Register */
+  __IM  uint32_t FSCR;                   /*!< Offset: 0x308 (R/ )  Formatter Synchronization Counter Register */
+        uint32_t RESERVED3[759U];
+  __IM  uint32_t TRIGGER;                /*!< Offset: 0xEE8 (R/ )  TRIGGER Register */
+  __IM  uint32_t FIFO0;                  /*!< Offset: 0xEEC (R/ )  Integration ETM Data */
+  __IM  uint32_t ITATBCTR2;              /*!< Offset: 0xEF0 (R/ )  ITATBCTR2 */
+        uint32_t RESERVED4[1U];
+  __IM  uint32_t ITATBCTR0;              /*!< Offset: 0xEF8 (R/ )  ITATBCTR0 */
+  __IM  uint32_t FIFO1;                  /*!< Offset: 0xEFC (R/ )  Integration ITM Data */
+  __IOM uint32_t ITCTRL;                 /*!< Offset: 0xF00 (R/W)  Integration Mode Control */
+        uint32_t RESERVED5[39U];
+  __IOM uint32_t CLAIMSET;               /*!< Offset: 0xFA0 (R/W)  Claim tag set */
+  __IOM uint32_t CLAIMCLR;               /*!< Offset: 0xFA4 (R/W)  Claim tag clear */
+        uint32_t RESERVED7[8U];
+  __IM  uint32_t DEVID;                  /*!< Offset: 0xFC8 (R/ )  TPIU_DEVID */
+  __IM  uint32_t DEVTYPE;                /*!< Offset: 0xFCC (R/ )  TPIU_DEVTYPE */
+} TPI_Type;
+
+/* TPI Asynchronous Clock Prescaler Register Definitions */
+#define TPI_ACPR_PRESCALER_Pos              0U                                         /*!< TPI ACPR: PRESCALER Position */
+#define TPI_ACPR_PRESCALER_Msk             (0x1FFFUL /*<< TPI_ACPR_PRESCALER_Pos*/)    /*!< TPI ACPR: PRESCALER Mask */
+
+/* TPI Selected Pin Protocol Register Definitions */
+#define TPI_SPPR_TXMODE_Pos                 0U                                         /*!< TPI SPPR: TXMODE Position */
+#define TPI_SPPR_TXMODE_Msk                (0x3UL /*<< TPI_SPPR_TXMODE_Pos*/)          /*!< TPI SPPR: TXMODE Mask */
+
+/* TPI Formatter and Flush Status Register Definitions */
+#define TPI_FFSR_FtNonStop_Pos              3U                                         /*!< TPI FFSR: FtNonStop Position */
+#define TPI_FFSR_FtNonStop_Msk             (0x1UL << TPI_FFSR_FtNonStop_Pos)           /*!< TPI FFSR: FtNonStop Mask */
+
+#define TPI_FFSR_TCPresent_Pos              2U                                         /*!< TPI FFSR: TCPresent Position */
+#define TPI_FFSR_TCPresent_Msk             (0x1UL << TPI_FFSR_TCPresent_Pos)           /*!< TPI FFSR: TCPresent Mask */
+
+#define TPI_FFSR_FtStopped_Pos              1U                                         /*!< TPI FFSR: FtStopped Position */
+#define TPI_FFSR_FtStopped_Msk             (0x1UL << TPI_FFSR_FtStopped_Pos)           /*!< TPI FFSR: FtStopped Mask */
+
+#define TPI_FFSR_FlInProg_Pos               0U                                         /*!< TPI FFSR: FlInProg Position */
+#define TPI_FFSR_FlInProg_Msk              (0x1UL /*<< TPI_FFSR_FlInProg_Pos*/)        /*!< TPI FFSR: FlInProg Mask */
+
+/* TPI Formatter and Flush Control Register Definitions */
+#define TPI_FFCR_TrigIn_Pos                 8U                                         /*!< TPI FFCR: TrigIn Position */
+#define TPI_FFCR_TrigIn_Msk                (0x1UL << TPI_FFCR_TrigIn_Pos)              /*!< TPI FFCR: TrigIn Mask */
+
+#define TPI_FFCR_EnFCont_Pos                1U                                         /*!< TPI FFCR: EnFCont Position */
+#define TPI_FFCR_EnFCont_Msk               (0x1UL << TPI_FFCR_EnFCont_Pos)             /*!< TPI FFCR: EnFCont Mask */
+
+/* TPI TRIGGER Register Definitions */
+#define TPI_TRIGGER_TRIGGER_Pos             0U                                         /*!< TPI TRIGGER: TRIGGER Position */
+#define TPI_TRIGGER_TRIGGER_Msk            (0x1UL /*<< TPI_TRIGGER_TRIGGER_Pos*/)      /*!< TPI TRIGGER: TRIGGER Mask */
+
+/* TPI Integration ETM Data Register Definitions (FIFO0) */
+#define TPI_FIFO0_ITM_ATVALID_Pos          29U                                         /*!< TPI FIFO0: ITM_ATVALID Position */
+#define TPI_FIFO0_ITM_ATVALID_Msk          (0x3UL << TPI_FIFO0_ITM_ATVALID_Pos)        /*!< TPI FIFO0: ITM_ATVALID Mask */
+
+#define TPI_FIFO0_ITM_bytecount_Pos        27U                                         /*!< TPI FIFO0: ITM_bytecount Position */
+#define TPI_FIFO0_ITM_bytecount_Msk        (0x3UL << TPI_FIFO0_ITM_bytecount_Pos)      /*!< TPI FIFO0: ITM_bytecount Mask */
+
+#define TPI_FIFO0_ETM_ATVALID_Pos          26U                                         /*!< TPI FIFO0: ETM_ATVALID Position */
+#define TPI_FIFO0_ETM_ATVALID_Msk          (0x3UL << TPI_FIFO0_ETM_ATVALID_Pos)        /*!< TPI FIFO0: ETM_ATVALID Mask */
+
+#define TPI_FIFO0_ETM_bytecount_Pos        24U                                         /*!< TPI FIFO0: ETM_bytecount Position */
+#define TPI_FIFO0_ETM_bytecount_Msk        (0x3UL << TPI_FIFO0_ETM_bytecount_Pos)      /*!< TPI FIFO0: ETM_bytecount Mask */
+
+#define TPI_FIFO0_ETM2_Pos                 16U                                         /*!< TPI FIFO0: ETM2 Position */
+#define TPI_FIFO0_ETM2_Msk                 (0xFFUL << TPI_FIFO0_ETM2_Pos)              /*!< TPI FIFO0: ETM2 Mask */
+
+#define TPI_FIFO0_ETM1_Pos                  8U                                         /*!< TPI FIFO0: ETM1 Position */
+#define TPI_FIFO0_ETM1_Msk                 (0xFFUL << TPI_FIFO0_ETM1_Pos)              /*!< TPI FIFO0: ETM1 Mask */
+
+#define TPI_FIFO0_ETM0_Pos                  0U                                         /*!< TPI FIFO0: ETM0 Position */
+#define TPI_FIFO0_ETM0_Msk                 (0xFFUL /*<< TPI_FIFO0_ETM0_Pos*/)          /*!< TPI FIFO0: ETM0 Mask */
+
+/* TPI ITATBCTR2 Register Definitions */
+#define TPI_ITATBCTR2_ATREADY2_Pos          0U                                         /*!< TPI ITATBCTR2: ATREADY2 Position */
+#define TPI_ITATBCTR2_ATREADY2_Msk         (0x1UL /*<< TPI_ITATBCTR2_ATREADY2_Pos*/)   /*!< TPI ITATBCTR2: ATREADY2 Mask */
+
+#define TPI_ITATBCTR2_ATREADY1_Pos          0U                                         /*!< TPI ITATBCTR2: ATREADY1 Position */
+#define TPI_ITATBCTR2_ATREADY1_Msk         (0x1UL /*<< TPI_ITATBCTR2_ATREADY1_Pos*/)   /*!< TPI ITATBCTR2: ATREADY1 Mask */
+
+/* TPI Integration ITM Data Register Definitions (FIFO1) */
+#define TPI_FIFO1_ITM_ATVALID_Pos          29U                                         /*!< TPI FIFO1: ITM_ATVALID Position */
+#define TPI_FIFO1_ITM_ATVALID_Msk          (0x3UL << TPI_FIFO1_ITM_ATVALID_Pos)        /*!< TPI FIFO1: ITM_ATVALID Mask */
+
+#define TPI_FIFO1_ITM_bytecount_Pos        27U                                         /*!< TPI FIFO1: ITM_bytecount Position */
+#define TPI_FIFO1_ITM_bytecount_Msk        (0x3UL << TPI_FIFO1_ITM_bytecount_Pos)      /*!< TPI FIFO1: ITM_bytecount Mask */
+
+#define TPI_FIFO1_ETM_ATVALID_Pos          26U                                         /*!< TPI FIFO1: ETM_ATVALID Position */
+#define TPI_FIFO1_ETM_ATVALID_Msk          (0x3UL << TPI_FIFO1_ETM_ATVALID_Pos)        /*!< TPI FIFO1: ETM_ATVALID Mask */
+
+#define TPI_FIFO1_ETM_bytecount_Pos        24U                                         /*!< TPI FIFO1: ETM_bytecount Position */
+#define TPI_FIFO1_ETM_bytecount_Msk        (0x3UL << TPI_FIFO1_ETM_bytecount_Pos)      /*!< TPI FIFO1: ETM_bytecount Mask */
+
+#define TPI_FIFO1_ITM2_Pos                 16U                                         /*!< TPI FIFO1: ITM2 Position */
+#define TPI_FIFO1_ITM2_Msk                 (0xFFUL << TPI_FIFO1_ITM2_Pos)              /*!< TPI FIFO1: ITM2 Mask */
+
+#define TPI_FIFO1_ITM1_Pos                  8U                                         /*!< TPI FIFO1: ITM1 Position */
+#define TPI_FIFO1_ITM1_Msk                 (0xFFUL << TPI_FIFO1_ITM1_Pos)              /*!< TPI FIFO1: ITM1 Mask */
+
+#define TPI_FIFO1_ITM0_Pos                  0U                                         /*!< TPI FIFO1: ITM0 Position */
+#define TPI_FIFO1_ITM0_Msk                 (0xFFUL /*<< TPI_FIFO1_ITM0_Pos*/)          /*!< TPI FIFO1: ITM0 Mask */
+
+/* TPI ITATBCTR0 Register Definitions */
+#define TPI_ITATBCTR0_ATREADY2_Pos          0U                                         /*!< TPI ITATBCTR0: ATREADY2 Position */
+#define TPI_ITATBCTR0_ATREADY2_Msk         (0x1UL /*<< TPI_ITATBCTR0_ATREADY2_Pos*/)   /*!< TPI ITATBCTR0: ATREADY2 Mask */
+
+#define TPI_ITATBCTR0_ATREADY1_Pos          0U                                         /*!< TPI ITATBCTR0: ATREADY1 Position */
+#define TPI_ITATBCTR0_ATREADY1_Msk         (0x1UL /*<< TPI_ITATBCTR0_ATREADY1_Pos*/)   /*!< TPI ITATBCTR0: ATREADY1 Mask */
+
+/* TPI Integration Mode Control Register Definitions */
+#define TPI_ITCTRL_Mode_Pos                 0U                                         /*!< TPI ITCTRL: Mode Position */
+#define TPI_ITCTRL_Mode_Msk                (0x3UL /*<< TPI_ITCTRL_Mode_Pos*/)          /*!< TPI ITCTRL: Mode Mask */
+
+/* TPI DEVID Register Definitions */
+#define TPI_DEVID_NRZVALID_Pos             11U                                         /*!< TPI DEVID: NRZVALID Position */
+#define TPI_DEVID_NRZVALID_Msk             (0x1UL << TPI_DEVID_NRZVALID_Pos)           /*!< TPI DEVID: NRZVALID Mask */
+
+#define TPI_DEVID_MANCVALID_Pos            10U                                         /*!< TPI DEVID: MANCVALID Position */
+#define TPI_DEVID_MANCVALID_Msk            (0x1UL << TPI_DEVID_MANCVALID_Pos)          /*!< TPI DEVID: MANCVALID Mask */
+
+#define TPI_DEVID_PTINVALID_Pos             9U                                         /*!< TPI DEVID: PTINVALID Position */
+#define TPI_DEVID_PTINVALID_Msk            (0x1UL << TPI_DEVID_PTINVALID_Pos)          /*!< TPI DEVID: PTINVALID Mask */
+
+#define TPI_DEVID_MinBufSz_Pos              6U                                         /*!< TPI DEVID: MinBufSz Position */
+#define TPI_DEVID_MinBufSz_Msk             (0x7UL << TPI_DEVID_MinBufSz_Pos)           /*!< TPI DEVID: MinBufSz Mask */
+
+#define TPI_DEVID_AsynClkIn_Pos             5U                                         /*!< TPI DEVID: AsynClkIn Position */
+#define TPI_DEVID_AsynClkIn_Msk            (0x1UL << TPI_DEVID_AsynClkIn_Pos)          /*!< TPI DEVID: AsynClkIn Mask */
+
+#define TPI_DEVID_NrTraceInput_Pos          0U                                         /*!< TPI DEVID: NrTraceInput Position */
+#define TPI_DEVID_NrTraceInput_Msk         (0x1FUL /*<< TPI_DEVID_NrTraceInput_Pos*/)  /*!< TPI DEVID: NrTraceInput Mask */
+
+/* TPI DEVTYPE Register Definitions */
+#define TPI_DEVTYPE_SubType_Pos             4U                                         /*!< TPI DEVTYPE: SubType Position */
+#define TPI_DEVTYPE_SubType_Msk            (0xFUL /*<< TPI_DEVTYPE_SubType_Pos*/)      /*!< TPI DEVTYPE: SubType Mask */
+
+#define TPI_DEVTYPE_MajorType_Pos           0U                                         /*!< TPI DEVTYPE: MajorType Position */
+#define TPI_DEVTYPE_MajorType_Msk          (0xFUL << TPI_DEVTYPE_MajorType_Pos)        /*!< TPI DEVTYPE: MajorType Mask */
+
+/*@}*/ /* end of group CMSIS_TPI */
+
+
+#if defined (__MPU_PRESENT) && (__MPU_PRESENT == 1U)
+/**
+  \ingroup  CMSIS_core_register
+  \defgroup CMSIS_MPU     Memory Protection Unit (MPU)
+  \brief    Type definitions for the Memory Protection Unit (MPU)
+  @{
+ */
+
+/**
+  \brief  Structure type to access the Memory Protection Unit (MPU).
+ */
+typedef struct
+{
+  __IM  uint32_t TYPE;                   /*!< Offset: 0x000 (R/ )  MPU Type Register */
+  __IOM uint32_t CTRL;                   /*!< Offset: 0x004 (R/W)  MPU Control Register */
+  __IOM uint32_t RNR;                    /*!< Offset: 0x008 (R/W)  MPU Region RNRber Register */
+  __IOM uint32_t RBAR;                   /*!< Offset: 0x00C (R/W)  MPU Region Base Address Register */
+  __IOM uint32_t RASR;                   /*!< Offset: 0x010 (R/W)  MPU Region Attribute and Size Register */
+  __IOM uint32_t RBAR_A1;                /*!< Offset: 0x014 (R/W)  MPU Alias 1 Region Base Address Register */
+  __IOM uint32_t RASR_A1;                /*!< Offset: 0x018 (R/W)  MPU Alias 1 Region Attribute and Size Register */
+  __IOM uint32_t RBAR_A2;                /*!< Offset: 0x01C (R/W)  MPU Alias 2 Region Base Address Register */
+  __IOM uint32_t RASR_A2;                /*!< Offset: 0x020 (R/W)  MPU Alias 2 Region Attribute and Size Register */
+  __IOM uint32_t RBAR_A3;                /*!< Offset: 0x024 (R/W)  MPU Alias 3 Region Base Address Register */
+  __IOM uint32_t RASR_A3;                /*!< Offset: 0x028 (R/W)  MPU Alias 3 Region Attribute and Size Register */
+} MPU_Type;
+
+#define MPU_TYPE_RALIASES                  4U
+
+/* MPU Type Register Definitions */
+#define MPU_TYPE_IREGION_Pos               16U                                            /*!< MPU TYPE: IREGION Position */
+#define MPU_TYPE_IREGION_Msk               (0xFFUL << MPU_TYPE_IREGION_Pos)               /*!< MPU TYPE: IREGION Mask */
+
+#define MPU_TYPE_DREGION_Pos                8U                                            /*!< MPU TYPE: DREGION Position */
+#define MPU_TYPE_DREGION_Msk               (0xFFUL << MPU_TYPE_DREGION_Pos)               /*!< MPU TYPE: DREGION Mask */
+
+#define MPU_TYPE_SEPARATE_Pos               0U                                            /*!< MPU TYPE: SEPARATE Position */
+#define MPU_TYPE_SEPARATE_Msk              (1UL /*<< MPU_TYPE_SEPARATE_Pos*/)             /*!< MPU TYPE: SEPARATE Mask */
+
+/* MPU Control Register Definitions */
+#define MPU_CTRL_PRIVDEFENA_Pos             2U                                            /*!< MPU CTRL: PRIVDEFENA Position */
+#define MPU_CTRL_PRIVDEFENA_Msk            (1UL << MPU_CTRL_PRIVDEFENA_Pos)               /*!< MPU CTRL: PRIVDEFENA Mask */
+
+#define MPU_CTRL_HFNMIENA_Pos               1U                                            /*!< MPU CTRL: HFNMIENA Position */
+#define MPU_CTRL_HFNMIENA_Msk              (1UL << MPU_CTRL_HFNMIENA_Pos)                 /*!< MPU CTRL: HFNMIENA Mask */
+
+#define MPU_CTRL_ENABLE_Pos                 0U                                            /*!< MPU CTRL: ENABLE Position */
+#define MPU_CTRL_ENABLE_Msk                (1UL /*<< MPU_CTRL_ENABLE_Pos*/)               /*!< MPU CTRL: ENABLE Mask */
+
+/* MPU Region Number Register Definitions */
+#define MPU_RNR_REGION_Pos                  0U                                            /*!< MPU RNR: REGION Position */
+#define MPU_RNR_REGION_Msk                 (0xFFUL /*<< MPU_RNR_REGION_Pos*/)             /*!< MPU RNR: REGION Mask */
+
+/* MPU Region Base Address Register Definitions */
+#define MPU_RBAR_ADDR_Pos                   5U                                            /*!< MPU RBAR: ADDR Position */
+#define MPU_RBAR_ADDR_Msk                  (0x7FFFFFFUL << MPU_RBAR_ADDR_Pos)             /*!< MPU RBAR: ADDR Mask */
+
+#define MPU_RBAR_VALID_Pos                  4U                                            /*!< MPU RBAR: VALID Position */
+#define MPU_RBAR_VALID_Msk                 (1UL << MPU_RBAR_VALID_Pos)                    /*!< MPU RBAR: VALID Mask */
+
+#define MPU_RBAR_REGION_Pos                 0U                                            /*!< MPU RBAR: REGION Position */
+#define MPU_RBAR_REGION_Msk                (0xFUL /*<< MPU_RBAR_REGION_Pos*/)             /*!< MPU RBAR: REGION Mask */
+
+/* MPU Region Attribute and Size Register Definitions */
+#define MPU_RASR_ATTRS_Pos                 16U                                            /*!< MPU RASR: MPU Region Attribute field Position */
+#define MPU_RASR_ATTRS_Msk                 (0xFFFFUL << MPU_RASR_ATTRS_Pos)               /*!< MPU RASR: MPU Region Attribute field Mask */
+
+#define MPU_RASR_XN_Pos                    28U                                            /*!< MPU RASR: ATTRS.XN Position */
+#define MPU_RASR_XN_Msk                    (1UL << MPU_RASR_XN_Pos)                       /*!< MPU RASR: ATTRS.XN Mask */
+
+#define MPU_RASR_AP_Pos                    24U                                            /*!< MPU RASR: ATTRS.AP Position */
+#define MPU_RASR_AP_Msk                    (0x7UL << MPU_RASR_AP_Pos)                     /*!< MPU RASR: ATTRS.AP Mask */
+
+#define MPU_RASR_TEX_Pos                   19U                                            /*!< MPU RASR: ATTRS.TEX Position */
+#define MPU_RASR_TEX_Msk                   (0x7UL << MPU_RASR_TEX_Pos)                    /*!< MPU RASR: ATTRS.TEX Mask */
+
+#define MPU_RASR_S_Pos                     18U                                            /*!< MPU RASR: ATTRS.S Position */
+#define MPU_RASR_S_Msk                     (1UL << MPU_RASR_S_Pos)                        /*!< MPU RASR: ATTRS.S Mask */
+
+#define MPU_RASR_C_Pos                     17U                                            /*!< MPU RASR: ATTRS.C Position */
+#define MPU_RASR_C_Msk                     (1UL << MPU_RASR_C_Pos)                        /*!< MPU RASR: ATTRS.C Mask */
+
+#define MPU_RASR_B_Pos                     16U                                            /*!< MPU RASR: ATTRS.B Position */
+#define MPU_RASR_B_Msk                     (1UL << MPU_RASR_B_Pos)                        /*!< MPU RASR: ATTRS.B Mask */
+
+#define MPU_RASR_SRD_Pos                    8U                                            /*!< MPU RASR: Sub-Region Disable Position */
+#define MPU_RASR_SRD_Msk                   (0xFFUL << MPU_RASR_SRD_Pos)                   /*!< MPU RASR: Sub-Region Disable Mask */
+
+#define MPU_RASR_SIZE_Pos                   1U                                            /*!< MPU RASR: Region Size Field Position */
+#define MPU_RASR_SIZE_Msk                  (0x1FUL << MPU_RASR_SIZE_Pos)                  /*!< MPU RASR: Region Size Field Mask */
+
+#define MPU_RASR_ENABLE_Pos                 0U                                            /*!< MPU RASR: Region enable bit Position */
+#define MPU_RASR_ENABLE_Msk                (1UL /*<< MPU_RASR_ENABLE_Pos*/)               /*!< MPU RASR: Region enable bit Disable Mask */
+
+/*@} end of group CMSIS_MPU */
+#endif
+
+
+/**
+  \ingroup  CMSIS_core_register
+  \defgroup CMSIS_CoreDebug       Core Debug Registers (CoreDebug)
+  \brief    Type definitions for the Core Debug Registers
+  @{
+ */
+
+/**
+  \brief  Structure type to access the Core Debug Register (CoreDebug).
+ */
+typedef struct
+{
+  __IOM uint32_t DHCSR;                  /*!< Offset: 0x000 (R/W)  Debug Halting Control and Status Register */
+  __OM  uint32_t DCRSR;                  /*!< Offset: 0x004 ( /W)  Debug Core Register Selector Register */
+  __IOM uint32_t DCRDR;                  /*!< Offset: 0x008 (R/W)  Debug Core Register Data Register */
+  __IOM uint32_t DEMCR;                  /*!< Offset: 0x00C (R/W)  Debug Exception and Monitor Control Register */
+} CoreDebug_Type;
+
+/* Debug Halting Control and Status Register Definitions */
+#define CoreDebug_DHCSR_DBGKEY_Pos         16U                                            /*!< CoreDebug DHCSR: DBGKEY Position */
+#define CoreDebug_DHCSR_DBGKEY_Msk         (0xFFFFUL << CoreDebug_DHCSR_DBGKEY_Pos)       /*!< CoreDebug DHCSR: DBGKEY Mask */
+
+#define CoreDebug_DHCSR_S_RESET_ST_Pos     25U                                            /*!< CoreDebug DHCSR: S_RESET_ST Position */
+#define CoreDebug_DHCSR_S_RESET_ST_Msk     (1UL << CoreDebug_DHCSR_S_RESET_ST_Pos)        /*!< CoreDebug DHCSR: S_RESET_ST Mask */
+
+#define CoreDebug_DHCSR_S_RETIRE_ST_Pos    24U                                            /*!< CoreDebug DHCSR: S_RETIRE_ST Position */
+#define CoreDebug_DHCSR_S_RETIRE_ST_Msk    (1UL << CoreDebug_DHCSR_S_RETIRE_ST_Pos)       /*!< CoreDebug DHCSR: S_RETIRE_ST Mask */
+
+#define CoreDebug_DHCSR_S_LOCKUP_Pos       19U                                            /*!< CoreDebug DHCSR: S_LOCKUP Position */
+#define CoreDebug_DHCSR_S_LOCKUP_Msk       (1UL << CoreDebug_DHCSR_S_LOCKUP_Pos)          /*!< CoreDebug DHCSR: S_LOCKUP Mask */
+
+#define CoreDebug_DHCSR_S_SLEEP_Pos        18U                                            /*!< CoreDebug DHCSR: S_SLEEP Position */
+#define CoreDebug_DHCSR_S_SLEEP_Msk        (1UL << CoreDebug_DHCSR_S_SLEEP_Pos)           /*!< CoreDebug DHCSR: S_SLEEP Mask */
+
+#define CoreDebug_DHCSR_S_HALT_Pos         17U                                            /*!< CoreDebug DHCSR: S_HALT Position */
+#define CoreDebug_DHCSR_S_HALT_Msk         (1UL << CoreDebug_DHCSR_S_HALT_Pos)            /*!< CoreDebug DHCSR: S_HALT Mask */
+
+#define CoreDebug_DHCSR_S_REGRDY_Pos       16U                                            /*!< CoreDebug DHCSR: S_REGRDY Position */
+#define CoreDebug_DHCSR_S_REGRDY_Msk       (1UL << CoreDebug_DHCSR_S_REGRDY_Pos)          /*!< CoreDebug DHCSR: S_REGRDY Mask */
+
+#define CoreDebug_DHCSR_C_SNAPSTALL_Pos     5U                                            /*!< CoreDebug DHCSR: C_SNAPSTALL Position */
+#define CoreDebug_DHCSR_C_SNAPSTALL_Msk    (1UL << CoreDebug_DHCSR_C_SNAPSTALL_Pos)       /*!< CoreDebug DHCSR: C_SNAPSTALL Mask */
+
+#define CoreDebug_DHCSR_C_MASKINTS_Pos      3U                                            /*!< CoreDebug DHCSR: C_MASKINTS Position */
+#define CoreDebug_DHCSR_C_MASKINTS_Msk     (1UL << CoreDebug_DHCSR_C_MASKINTS_Pos)        /*!< CoreDebug DHCSR: C_MASKINTS Mask */
+
+#define CoreDebug_DHCSR_C_STEP_Pos          2U                                            /*!< CoreDebug DHCSR: C_STEP Position */
+#define CoreDebug_DHCSR_C_STEP_Msk         (1UL << CoreDebug_DHCSR_C_STEP_Pos)            /*!< CoreDebug DHCSR: C_STEP Mask */
+
+#define CoreDebug_DHCSR_C_HALT_Pos          1U                                            /*!< CoreDebug DHCSR: C_HALT Position */
+#define CoreDebug_DHCSR_C_HALT_Msk         (1UL << CoreDebug_DHCSR_C_HALT_Pos)            /*!< CoreDebug DHCSR: C_HALT Mask */
+
+#define CoreDebug_DHCSR_C_DEBUGEN_Pos       0U                                            /*!< CoreDebug DHCSR: C_DEBUGEN Position */
+#define CoreDebug_DHCSR_C_DEBUGEN_Msk      (1UL /*<< CoreDebug_DHCSR_C_DEBUGEN_Pos*/)     /*!< CoreDebug DHCSR: C_DEBUGEN Mask */
+
+/* Debug Core Register Selector Register Definitions */
+#define CoreDebug_DCRSR_REGWnR_Pos         16U                                            /*!< CoreDebug DCRSR: REGWnR Position */
+#define CoreDebug_DCRSR_REGWnR_Msk         (1UL << CoreDebug_DCRSR_REGWnR_Pos)            /*!< CoreDebug DCRSR: REGWnR Mask */
+
+#define CoreDebug_DCRSR_REGSEL_Pos          0U                                            /*!< CoreDebug DCRSR: REGSEL Position */
+#define CoreDebug_DCRSR_REGSEL_Msk         (0x1FUL /*<< CoreDebug_DCRSR_REGSEL_Pos*/)     /*!< CoreDebug DCRSR: REGSEL Mask */
+
+/* Debug Exception and Monitor Control Register Definitions */
+#define CoreDebug_DEMCR_TRCENA_Pos         24U                                            /*!< CoreDebug DEMCR: TRCENA Position */
+#define CoreDebug_DEMCR_TRCENA_Msk         (1UL << CoreDebug_DEMCR_TRCENA_Pos)            /*!< CoreDebug DEMCR: TRCENA Mask */
+
+#define CoreDebug_DEMCR_MON_REQ_Pos        19U                                            /*!< CoreDebug DEMCR: MON_REQ Position */
+#define CoreDebug_DEMCR_MON_REQ_Msk        (1UL << CoreDebug_DEMCR_MON_REQ_Pos)           /*!< CoreDebug DEMCR: MON_REQ Mask */
+
+#define CoreDebug_DEMCR_MON_STEP_Pos       18U                                            /*!< CoreDebug DEMCR: MON_STEP Position */
+#define CoreDebug_DEMCR_MON_STEP_Msk       (1UL << CoreDebug_DEMCR_MON_STEP_Pos)          /*!< CoreDebug DEMCR: MON_STEP Mask */
+
+#define CoreDebug_DEMCR_MON_PEND_Pos       17U                                            /*!< CoreDebug DEMCR: MON_PEND Position */
+#define CoreDebug_DEMCR_MON_PEND_Msk       (1UL << CoreDebug_DEMCR_MON_PEND_Pos)          /*!< CoreDebug DEMCR: MON_PEND Mask */
+
+#define CoreDebug_DEMCR_MON_EN_Pos         16U                                            /*!< CoreDebug DEMCR: MON_EN Position */
+#define CoreDebug_DEMCR_MON_EN_Msk         (1UL << CoreDebug_DEMCR_MON_EN_Pos)            /*!< CoreDebug DEMCR: MON_EN Mask */
+
+#define CoreDebug_DEMCR_VC_HARDERR_Pos     10U                                            /*!< CoreDebug DEMCR: VC_HARDERR Position */
+#define CoreDebug_DEMCR_VC_HARDERR_Msk     (1UL << CoreDebug_DEMCR_VC_HARDERR_Pos)        /*!< CoreDebug DEMCR: VC_HARDERR Mask */
+
+#define CoreDebug_DEMCR_VC_INTERR_Pos       9U                                            /*!< CoreDebug DEMCR: VC_INTERR Position */
+#define CoreDebug_DEMCR_VC_INTERR_Msk      (1UL << CoreDebug_DEMCR_VC_INTERR_Pos)         /*!< CoreDebug DEMCR: VC_INTERR Mask */
+
+#define CoreDebug_DEMCR_VC_BUSERR_Pos       8U                                            /*!< CoreDebug DEMCR: VC_BUSERR Position */
+#define CoreDebug_DEMCR_VC_BUSERR_Msk      (1UL << CoreDebug_DEMCR_VC_BUSERR_Pos)         /*!< CoreDebug DEMCR: VC_BUSERR Mask */
+
+#define CoreDebug_DEMCR_VC_STATERR_Pos      7U                                            /*!< CoreDebug DEMCR: VC_STATERR Position */
+#define CoreDebug_DEMCR_VC_STATERR_Msk     (1UL << CoreDebug_DEMCR_VC_STATERR_Pos)        /*!< CoreDebug DEMCR: VC_STATERR Mask */
+
+#define CoreDebug_DEMCR_VC_CHKERR_Pos       6U                                            /*!< CoreDebug DEMCR: VC_CHKERR Position */
+#define CoreDebug_DEMCR_VC_CHKERR_Msk      (1UL << CoreDebug_DEMCR_VC_CHKERR_Pos)         /*!< CoreDebug DEMCR: VC_CHKERR Mask */
+
+#define CoreDebug_DEMCR_VC_NOCPERR_Pos      5U                                            /*!< CoreDebug DEMCR: VC_NOCPERR Position */
+#define CoreDebug_DEMCR_VC_NOCPERR_Msk     (1UL << CoreDebug_DEMCR_VC_NOCPERR_Pos)        /*!< CoreDebug DEMCR: VC_NOCPERR Mask */
+
+#define CoreDebug_DEMCR_VC_MMERR_Pos        4U                                            /*!< CoreDebug DEMCR: VC_MMERR Position */
+#define CoreDebug_DEMCR_VC_MMERR_Msk       (1UL << CoreDebug_DEMCR_VC_MMERR_Pos)          /*!< CoreDebug DEMCR: VC_MMERR Mask */
+
+#define CoreDebug_DEMCR_VC_CORERESET_Pos    0U                                            /*!< CoreDebug DEMCR: VC_CORERESET Position */
+#define CoreDebug_DEMCR_VC_CORERESET_Msk   (1UL /*<< CoreDebug_DEMCR_VC_CORERESET_Pos*/)  /*!< CoreDebug DEMCR: VC_CORERESET Mask */
+
+/*@} end of group CMSIS_CoreDebug */
+
+
+/**
+  \ingroup    CMSIS_core_register
+  \defgroup   CMSIS_core_bitfield     Core register bit field macros
+  \brief      Macros for use with bit field definitions (xxx_Pos, xxx_Msk).
+  @{
+ */
+
+/**
+  \brief   Mask and shift a bit field value for use in a register bit range.
+  \param[in] field  Name of the register bit field.
+  \param[in] value  Value of the bit field. This parameter is interpreted as an uint32_t type.
+  \return           Masked and shifted value.
+*/
+#define _VAL2FLD(field, value)    (((uint32_t)(value) << field ## _Pos) & field ## _Msk)
+
+/**
+  \brief     Mask and shift a register value to extract a bit filed value.
+  \param[in] field  Name of the register bit field.
+  \param[in] value  Value of register. This parameter is interpreted as an uint32_t type.
+  \return           Masked and shifted bit field value.
+*/
+#define _FLD2VAL(field, value)    (((uint32_t)(value) & field ## _Msk) >> field ## _Pos)
+
+/*@} end of group CMSIS_core_bitfield */
+
+
+/**
+  \ingroup    CMSIS_core_register
+  \defgroup   CMSIS_core_base     Core Definitions
+  \brief      Definitions for base addresses, unions, and structures.
+  @{
+ */
+
+/* Memory mapping of Core Hardware */
+#define SCS_BASE            (0xE000E000UL)                            /*!< System Control Space Base Address */
+#define ITM_BASE            (0xE0000000UL)                            /*!< ITM Base Address */
+#define DWT_BASE            (0xE0001000UL)                            /*!< DWT Base Address */
+#define TPI_BASE            (0xE0040000UL)                            /*!< TPI Base Address */
+#define CoreDebug_BASE      (0xE000EDF0UL)                            /*!< Core Debug Base Address */
+#define SysTick_BASE        (SCS_BASE +  0x0010UL)                    /*!< SysTick Base Address */
+#define NVIC_BASE           (SCS_BASE +  0x0100UL)                    /*!< NVIC Base Address */
+#define SCB_BASE            (SCS_BASE +  0x0D00UL)                    /*!< System Control Block Base Address */
+
+#define SCnSCB              ((SCnSCB_Type    *)     SCS_BASE      )   /*!< System control Register not in SCB */
+#define SCB                 ((SCB_Type       *)     SCB_BASE      )   /*!< SCB configuration struct */
+#define SysTick             ((SysTick_Type   *)     SysTick_BASE  )   /*!< SysTick configuration struct */
+#define NVIC                ((NVIC_Type      *)     NVIC_BASE     )   /*!< NVIC configuration struct */
+#define ITM                 ((ITM_Type       *)     ITM_BASE      )   /*!< ITM configuration struct */
+#define DWT                 ((DWT_Type       *)     DWT_BASE      )   /*!< DWT configuration struct */
+#define TPI                 ((TPI_Type       *)     TPI_BASE      )   /*!< TPI configuration struct */
+#define CoreDebug           ((CoreDebug_Type *)     CoreDebug_BASE)   /*!< Core Debug configuration struct */
+
+#if defined (__MPU_PRESENT) && (__MPU_PRESENT == 1U)
+  #define MPU_BASE          (SCS_BASE +  0x0D90UL)                    /*!< Memory Protection Unit */
+  #define MPU               ((MPU_Type       *)     MPU_BASE      )   /*!< Memory Protection Unit */
+#endif
+
+/*@} */
+
+
+
+/*******************************************************************************
+ *                Hardware Abstraction Layer
+  Core Function Interface contains:
+  - Core NVIC Functions
+  - Core SysTick Functions
+  - Core Debug Functions
+  - Core Register Access Functions
+ ******************************************************************************/
+/**
+  \defgroup CMSIS_Core_FunctionInterface Functions and Instructions Reference
+*/
+
+
+
+/* ##########################   NVIC functions  #################################### */
+/**
+  \ingroup  CMSIS_Core_FunctionInterface
+  \defgroup CMSIS_Core_NVICFunctions NVIC Functions
+  \brief    Functions that manage interrupts and exceptions via the NVIC.
+  @{
+ */
+
+#ifdef CMSIS_NVIC_VIRTUAL
+  #ifndef CMSIS_NVIC_VIRTUAL_HEADER_FILE
+    #define CMSIS_NVIC_VIRTUAL_HEADER_FILE "cmsis_nvic_virtual.h"
+  #endif
+  #include CMSIS_NVIC_VIRTUAL_HEADER_FILE
+#else
+  #define NVIC_SetPriorityGrouping    __NVIC_SetPriorityGrouping
+  #define NVIC_GetPriorityGrouping    __NVIC_GetPriorityGrouping
+  #define NVIC_EnableIRQ              __NVIC_EnableIRQ
+  #define NVIC_GetEnableIRQ           __NVIC_GetEnableIRQ
+  #define NVIC_DisableIRQ             __NVIC_DisableIRQ
+  #define NVIC_GetPendingIRQ          __NVIC_GetPendingIRQ
+  #define NVIC_SetPendingIRQ          __NVIC_SetPendingIRQ
+  #define NVIC_ClearPendingIRQ        __NVIC_ClearPendingIRQ
+  #define NVIC_GetActive              __NVIC_GetActive
+  #define NVIC_SetPriority            __NVIC_SetPriority
+  #define NVIC_GetPriority            __NVIC_GetPriority
+  #define NVIC_SystemReset            __NVIC_SystemReset
+#endif /* CMSIS_NVIC_VIRTUAL */
+
+#ifdef CMSIS_VECTAB_VIRTUAL
+  #ifndef CMSIS_VECTAB_VIRTUAL_HEADER_FILE
+   #define CMSIS_VECTAB_VIRTUAL_HEADER_FILE "cmsis_vectab_virtual.h"
+  #endif
+  #include CMSIS_VECTAB_VIRTUAL_HEADER_FILE
+#else
+  #define NVIC_SetVector              __NVIC_SetVector
+  #define NVIC_GetVector              __NVIC_GetVector
+#endif  /* (CMSIS_VECTAB_VIRTUAL) */
+
+#define NVIC_USER_IRQ_OFFSET          16
+
+
+/* The following EXC_RETURN values are saved the LR on exception entry */
+#define EXC_RETURN_HANDLER         (0xFFFFFFF1UL)     /* return to Handler mode, uses MSP after return                               */
+#define EXC_RETURN_THREAD_MSP      (0xFFFFFFF9UL)     /* return to Thread mode, uses MSP after return                                */
+#define EXC_RETURN_THREAD_PSP      (0xFFFFFFFDUL)     /* return to Thread mode, uses PSP after return                                */
+
+
+/**
+  \brief   Set Priority Grouping
+  \details Sets the priority grouping field using the required unlock sequence.
+           The parameter PriorityGroup is assigned to the field SCB->AIRCR [10:8] PRIGROUP field.
+           Only values from 0..7 are used.
+           In case of a conflict between priority grouping and available
+           priority bits (__NVIC_PRIO_BITS), the smallest possible priority group is set.
+  \param [in]      PriorityGroup  Priority grouping field.
+ */
+__STATIC_INLINE void __NVIC_SetPriorityGrouping(uint32_t PriorityGroup)
+{
+  uint32_t reg_value;
+  uint32_t PriorityGroupTmp = (PriorityGroup & (uint32_t)0x07UL);             /* only values 0..7 are used          */
+
+  reg_value  =  SCB->AIRCR;                                                   /* read old register configuration    */
+  reg_value &= ~((uint32_t)(SCB_AIRCR_VECTKEY_Msk | SCB_AIRCR_PRIGROUP_Msk)); /* clear bits to change               */
+  reg_value  =  (reg_value                                   |
+                ((uint32_t)0x5FAUL << SCB_AIRCR_VECTKEY_Pos) |
+                (PriorityGroupTmp << SCB_AIRCR_PRIGROUP_Pos) );               /* Insert write key and priority group */
+  SCB->AIRCR =  reg_value;
+}
+
+
+/**
+  \brief   Get Priority Grouping
+  \details Reads the priority grouping field from the NVIC Interrupt Controller.
+  \return                Priority grouping field (SCB->AIRCR [10:8] PRIGROUP field).
+ */
+__STATIC_INLINE uint32_t __NVIC_GetPriorityGrouping(void)
+{
+  return ((uint32_t)((SCB->AIRCR & SCB_AIRCR_PRIGROUP_Msk) >> SCB_AIRCR_PRIGROUP_Pos));
+}
+
+
+/**
+  \brief   Enable Interrupt
+  \details Enables a device specific interrupt in the NVIC interrupt controller.
+  \param [in]      IRQn  Device specific interrupt number.
+  \note    IRQn must not be negative.
+ */
+__STATIC_INLINE void __NVIC_EnableIRQ(IRQn_Type IRQn)
+{
+  if ((int32_t)(IRQn) >= 0)
+  {
+    NVIC->ISER[(((uint32_t)IRQn) >> 5UL)] = (uint32_t)(1UL << (((uint32_t)IRQn) & 0x1FUL));
+  }
+}
+
+
+/**
+  \brief   Get Interrupt Enable status
+  \details Returns a device specific interrupt enable status from the NVIC interrupt controller.
+  \param [in]      IRQn  Device specific interrupt number.
+  \return             0  Interrupt is not enabled.
+  \return             1  Interrupt is enabled.
+  \note    IRQn must not be negative.
+ */
+__STATIC_INLINE uint32_t __NVIC_GetEnableIRQ(IRQn_Type IRQn)
+{
+  if ((int32_t)(IRQn) >= 0)
+  {
+    return((uint32_t)(((NVIC->ISER[(((uint32_t)IRQn) >> 5UL)] & (1UL << (((uint32_t)IRQn) & 0x1FUL))) != 0UL) ? 1UL : 0UL));
+  }
+  else
+  {
+    return(0U);
+  }
+}
+
+
+/**
+  \brief   Disable Interrupt
+  \details Disables a device specific interrupt in the NVIC interrupt controller.
+  \param [in]      IRQn  Device specific interrupt number.
+  \note    IRQn must not be negative.
+ */
+__STATIC_INLINE void __NVIC_DisableIRQ(IRQn_Type IRQn)
+{
+  if ((int32_t)(IRQn) >= 0)
+  {
+    NVIC->ICER[(((uint32_t)IRQn) >> 5UL)] = (uint32_t)(1UL << (((uint32_t)IRQn) & 0x1FUL));
+    __DSB();
+    __ISB();
+  }
+}
+
+
+/**
+  \brief   Get Pending Interrupt
+  \details Reads the NVIC pending register and returns the pending bit for the specified device specific interrupt.
+  \param [in]      IRQn  Device specific interrupt number.
+  \return             0  Interrupt status is not pending.
+  \return             1  Interrupt status is pending.
+  \note    IRQn must not be negative.
+ */
+__STATIC_INLINE uint32_t __NVIC_GetPendingIRQ(IRQn_Type IRQn)
+{
+  if ((int32_t)(IRQn) >= 0)
+  {
+    return((uint32_t)(((NVIC->ISPR[(((uint32_t)IRQn) >> 5UL)] & (1UL << (((uint32_t)IRQn) & 0x1FUL))) != 0UL) ? 1UL : 0UL));
+  }
+  else
+  {
+    return(0U);
+  }
+}
+
+
+/**
+  \brief   Set Pending Interrupt
+  \details Sets the pending bit of a device specific interrupt in the NVIC pending register.
+  \param [in]      IRQn  Device specific interrupt number.
+  \note    IRQn must not be negative.
+ */
+__STATIC_INLINE void __NVIC_SetPendingIRQ(IRQn_Type IRQn)
+{
+  if ((int32_t)(IRQn) >= 0)
+  {
+    NVIC->ISPR[(((uint32_t)IRQn) >> 5UL)] = (uint32_t)(1UL << (((uint32_t)IRQn) & 0x1FUL));
+  }
+}
+
+
+/**
+  \brief   Clear Pending Interrupt
+  \details Clears the pending bit of a device specific interrupt in the NVIC pending register.
+  \param [in]      IRQn  Device specific interrupt number.
+  \note    IRQn must not be negative.
+ */
+__STATIC_INLINE void __NVIC_ClearPendingIRQ(IRQn_Type IRQn)
+{
+  if ((int32_t)(IRQn) >= 0)
+  {
+    NVIC->ICPR[(((uint32_t)IRQn) >> 5UL)] = (uint32_t)(1UL << (((uint32_t)IRQn) & 0x1FUL));
+  }
+}
+
+
+/**
+  \brief   Get Active Interrupt
+  \details Reads the active register in the NVIC and returns the active bit for the device specific interrupt.
+  \param [in]      IRQn  Device specific interrupt number.
+  \return             0  Interrupt status is not active.
+  \return             1  Interrupt status is active.
+  \note    IRQn must not be negative.
+ */
+__STATIC_INLINE uint32_t __NVIC_GetActive(IRQn_Type IRQn)
+{
+  if ((int32_t)(IRQn) >= 0)
+  {
+    return((uint32_t)(((NVIC->IABR[(((uint32_t)IRQn) >> 5UL)] & (1UL << (((uint32_t)IRQn) & 0x1FUL))) != 0UL) ? 1UL : 0UL));
+  }
+  else
+  {
+    return(0U);
+  }
+}
+
+
+/**
+  \brief   Set Interrupt Priority
+  \details Sets the priority of a device specific interrupt or a processor exception.
+           The interrupt number can be positive to specify a device specific interrupt,
+           or negative to specify a processor exception.
+  \param [in]      IRQn  Interrupt number.
+  \param [in]  priority  Priority to set.
+  \note    The priority cannot be set for every processor exception.
+ */
+__STATIC_INLINE void __NVIC_SetPriority(IRQn_Type IRQn, uint32_t priority)
+{
+  if ((int32_t)(IRQn) >= 0)
+  {
+    NVIC->IP[((uint32_t)IRQn)]               = (uint8_t)((priority << (8U - __NVIC_PRIO_BITS)) & (uint32_t)0xFFUL);
+  }
+  else
+  {
+    SCB->SHP[(((uint32_t)IRQn) & 0xFUL)-4UL] = (uint8_t)((priority << (8U - __NVIC_PRIO_BITS)) & (uint32_t)0xFFUL);
+  }
+}
+
+
+/**
+  \brief   Get Interrupt Priority
+  \details Reads the priority of a device specific interrupt or a processor exception.
+           The interrupt number can be positive to specify a device specific interrupt,
+           or negative to specify a processor exception.
+  \param [in]   IRQn  Interrupt number.
+  \return             Interrupt Priority.
+                      Value is aligned automatically to the implemented priority bits of the microcontroller.
+ */
+__STATIC_INLINE uint32_t __NVIC_GetPriority(IRQn_Type IRQn)
+{
+
+  if ((int32_t)(IRQn) >= 0)
+  {
+    return(((uint32_t)NVIC->IP[((uint32_t)IRQn)]               >> (8U - __NVIC_PRIO_BITS)));
+  }
+  else
+  {
+    return(((uint32_t)SCB->SHP[(((uint32_t)IRQn) & 0xFUL)-4UL] >> (8U - __NVIC_PRIO_BITS)));
+  }
+}
+
+
+/**
+  \brief   Encode Priority
+  \details Encodes the priority for an interrupt with the given priority group,
+           preemptive priority value, and subpriority value.
+           In case of a conflict between priority grouping and available
+           priority bits (__NVIC_PRIO_BITS), the smallest possible priority group is set.
+  \param [in]     PriorityGroup  Used priority group.
+  \param [in]   PreemptPriority  Preemptive priority value (starting from 0).
+  \param [in]       SubPriority  Subpriority value (starting from 0).
+  \return                        Encoded priority. Value can be used in the function \ref NVIC_SetPriority().
+ */
+__STATIC_INLINE uint32_t NVIC_EncodePriority (uint32_t PriorityGroup, uint32_t PreemptPriority, uint32_t SubPriority)
+{
+  uint32_t PriorityGroupTmp = (PriorityGroup & (uint32_t)0x07UL);   /* only values 0..7 are used          */
+  uint32_t PreemptPriorityBits;
+  uint32_t SubPriorityBits;
+
+  PreemptPriorityBits = ((7UL - PriorityGroupTmp) > (uint32_t)(__NVIC_PRIO_BITS)) ? (uint32_t)(__NVIC_PRIO_BITS) : (uint32_t)(7UL - PriorityGroupTmp);
+  SubPriorityBits     = ((PriorityGroupTmp + (uint32_t)(__NVIC_PRIO_BITS)) < (uint32_t)7UL) ? (uint32_t)0UL : (uint32_t)((PriorityGroupTmp - 7UL) + (uint32_t)(__NVIC_PRIO_BITS));
+
+  return (
+           ((PreemptPriority & (uint32_t)((1UL << (PreemptPriorityBits)) - 1UL)) << SubPriorityBits) |
+           ((SubPriority     & (uint32_t)((1UL << (SubPriorityBits    )) - 1UL)))
+         );
+}
+
+
+/**
+  \brief   Decode Priority
+  \details Decodes an interrupt priority value with a given priority group to
+           preemptive priority value and subpriority value.
+           In case of a conflict between priority grouping and available
+           priority bits (__NVIC_PRIO_BITS) the smallest possible priority group is set.
+  \param [in]         Priority   Priority value, which can be retrieved with the function \ref NVIC_GetPriority().
+  \param [in]     PriorityGroup  Used priority group.
+  \param [out] pPreemptPriority  Preemptive priority value (starting from 0).
+  \param [out]     pSubPriority  Subpriority value (starting from 0).
+ */
+__STATIC_INLINE void NVIC_DecodePriority (uint32_t Priority, uint32_t PriorityGroup, uint32_t* const pPreemptPriority, uint32_t* const pSubPriority)
+{
+  uint32_t PriorityGroupTmp = (PriorityGroup & (uint32_t)0x07UL);   /* only values 0..7 are used          */
+  uint32_t PreemptPriorityBits;
+  uint32_t SubPriorityBits;
+
+  PreemptPriorityBits = ((7UL - PriorityGroupTmp) > (uint32_t)(__NVIC_PRIO_BITS)) ? (uint32_t)(__NVIC_PRIO_BITS) : (uint32_t)(7UL - PriorityGroupTmp);
+  SubPriorityBits     = ((PriorityGroupTmp + (uint32_t)(__NVIC_PRIO_BITS)) < (uint32_t)7UL) ? (uint32_t)0UL : (uint32_t)((PriorityGroupTmp - 7UL) + (uint32_t)(__NVIC_PRIO_BITS));
+
+  *pPreemptPriority = (Priority >> SubPriorityBits) & (uint32_t)((1UL << (PreemptPriorityBits)) - 1UL);
+  *pSubPriority     = (Priority                   ) & (uint32_t)((1UL << (SubPriorityBits    )) - 1UL);
+}
+
+
+/**
+  \brief   Set Interrupt Vector
+  \details Sets an interrupt vector in SRAM based interrupt vector table.
+           The interrupt number can be positive to specify a device specific interrupt,
+           or negative to specify a processor exception.
+           VTOR must been relocated to SRAM before.
+  \param [in]   IRQn      Interrupt number
+  \param [in]   vector    Address of interrupt handler function
+ */
+__STATIC_INLINE void __NVIC_SetVector(IRQn_Type IRQn, uint32_t vector)
+{
+  uint32_t *vectors = (uint32_t *)SCB->VTOR;
+  vectors[(int32_t)IRQn + NVIC_USER_IRQ_OFFSET] = vector;
+}
+
+
+/**
+  \brief   Get Interrupt Vector
+  \details Reads an interrupt vector from interrupt vector table.
+           The interrupt number can be positive to specify a device specific interrupt,
+           or negative to specify a processor exception.
+  \param [in]   IRQn      Interrupt number.
+  \return                 Address of interrupt handler function
+ */
+__STATIC_INLINE uint32_t __NVIC_GetVector(IRQn_Type IRQn)
+{
+  uint32_t *vectors = (uint32_t *)SCB->VTOR;
+  return vectors[(int32_t)IRQn + NVIC_USER_IRQ_OFFSET];
+}
+
+
+/**
+  \brief   System Reset
+  \details Initiates a system reset request to reset the MCU.
+ */
+__NO_RETURN __STATIC_INLINE void __NVIC_SystemReset(void)
+{
+  __DSB();                                                          /* Ensure all outstanding memory accesses included
+                                                                       buffered write are completed before reset */
+  SCB->AIRCR  = (uint32_t)((0x5FAUL << SCB_AIRCR_VECTKEY_Pos)    |
+                           (SCB->AIRCR & SCB_AIRCR_PRIGROUP_Msk) |
+                            SCB_AIRCR_SYSRESETREQ_Msk    );         /* Keep priority group unchanged */
+  __DSB();                                                          /* Ensure completion of memory access */
+
+  for(;;)                                                           /* wait until reset */
+  {
+    __NOP();
+  }
+}
+
+/*@} end of CMSIS_Core_NVICFunctions */
+
+/* ##########################  MPU functions  #################################### */
+
+#if defined (__MPU_PRESENT) && (__MPU_PRESENT == 1U)
+
+#include "mpu_armv7.h"
+
+#endif
+
+/* ##########################  FPU functions  #################################### */
+/**
+  \ingroup  CMSIS_Core_FunctionInterface
+  \defgroup CMSIS_Core_FpuFunctions FPU Functions
+  \brief    Function that provides FPU type.
+  @{
+ */
+
+/**
+  \brief   get FPU type
+  \details returns the FPU type
+  \returns
+   - \b  0: No FPU
+   - \b  1: Single precision FPU
+   - \b  2: Double + Single precision FPU
+ */
+__STATIC_INLINE uint32_t SCB_GetFPUType(void)
+{
+    return 0U;           /* No FPU */
+}
+
+
+/*@} end of CMSIS_Core_FpuFunctions */
+
+
+
+/* ##################################    SysTick function  ############################################ */
+/**
+  \ingroup  CMSIS_Core_FunctionInterface
+  \defgroup CMSIS_Core_SysTickFunctions SysTick Functions
+  \brief    Functions that configure the System.
+  @{
+ */
+
+#if defined (__Vendor_SysTickConfig) && (__Vendor_SysTickConfig == 0U)
+
+/**
+  \brief   System Tick Configuration
+  \details Initializes the System Timer and its interrupt, and starts the System Tick Timer.
+           Counter is in free running mode to generate periodic interrupts.
+  \param [in]  ticks  Number of ticks between two interrupts.
+  \return          0  Function succeeded.
+  \return          1  Function failed.
+  \note    When the variable <b>__Vendor_SysTickConfig</b> is set to 1, then the
+           function <b>SysTick_Config</b> is not included. In this case, the file <b><i>device</i>.h</b>
+           must contain a vendor-specific implementation of this function.
+ */
+__STATIC_INLINE uint32_t SysTick_Config(uint32_t ticks)
+{
+  if ((ticks - 1UL) > SysTick_LOAD_RELOAD_Msk)
+  {
+    return (1UL);                                                   /* Reload value impossible */
+  }
+
+  SysTick->LOAD  = (uint32_t)(ticks - 1UL);                         /* set reload register */
+  NVIC_SetPriority (SysTick_IRQn, (1UL << __NVIC_PRIO_BITS) - 1UL); /* set Priority for Systick Interrupt */
+  SysTick->VAL   = 0UL;                                             /* Load the SysTick Counter Value */
+  SysTick->CTRL  = SysTick_CTRL_CLKSOURCE_Msk |
+                   SysTick_CTRL_TICKINT_Msk   |
+                   SysTick_CTRL_ENABLE_Msk;                         /* Enable SysTick IRQ and SysTick Timer */
+  return (0UL);                                                     /* Function successful */
+}
+
+#endif
+
+/*@} end of CMSIS_Core_SysTickFunctions */
+
+
+
+/* ##################################### Debug In/Output function ########################################### */
+/**
+  \ingroup  CMSIS_Core_FunctionInterface
+  \defgroup CMSIS_core_DebugFunctions ITM Functions
+  \brief    Functions that access the ITM debug interface.
+  @{
+ */
+
+extern volatile int32_t ITM_RxBuffer;                              /*!< External variable to receive characters. */
+#define                 ITM_RXBUFFER_EMPTY  ((int32_t)0x5AA55AA5U) /*!< Value identifying \ref ITM_RxBuffer is ready for next character. */
+
+
+/**
+  \brief   ITM Send Character
+  \details Transmits a character via the ITM channel 0, and
+           \li Just returns when no debugger is connected that has booked the output.
+           \li Is blocking when a debugger is connected, but the previous character sent has not been transmitted.
+  \param [in]     ch  Character to transmit.
+  \returns            Character to transmit.
+ */
+__STATIC_INLINE uint32_t ITM_SendChar (uint32_t ch)
+{
+  if (((ITM->TCR & ITM_TCR_ITMENA_Msk) != 0UL) &&      /* ITM enabled */
+      ((ITM->TER & 1UL               ) != 0UL)   )     /* ITM Port #0 enabled */
+  {
+    while (ITM->PORT[0U].u32 == 0UL)
+    {
+      __NOP();
+    }
+    ITM->PORT[0U].u8 = (uint8_t)ch;
+  }
+  return (ch);
+}
+
+
+/**
+  \brief   ITM Receive Character
+  \details Inputs a character via the external variable \ref ITM_RxBuffer.
+  \return             Received character.
+  \return         -1  No character pending.
+ */
+__STATIC_INLINE int32_t ITM_ReceiveChar (void)
+{
+  int32_t ch = -1;                           /* no character available */
+
+  if (ITM_RxBuffer != ITM_RXBUFFER_EMPTY)
+  {
+    ch = ITM_RxBuffer;
+    ITM_RxBuffer = ITM_RXBUFFER_EMPTY;       /* ready for next character */
+  }
+
+  return (ch);
+}
+
+
+/**
+  \brief   ITM Check Character
+  \details Checks whether a character is pending for reading in the variable \ref ITM_RxBuffer.
+  \return          0  No character available.
+  \return          1  Character available.
+ */
+__STATIC_INLINE int32_t ITM_CheckChar (void)
+{
+
+  if (ITM_RxBuffer == ITM_RXBUFFER_EMPTY)
+  {
+    return (0);                              /* no character available */
+  }
+  else
+  {
+    return (1);                              /*    character available */
+  }
+}
+
+/*@} end of CMSIS_core_DebugFunctions */
+
+
+
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif /* __CORE_CM3_H_DEPENDANT */
+
+#endif /* __CMSIS_GENERIC */

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/cmsis/CMSIS/DSP/Include/arm_common_tables.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/cmsis/CMSIS/DSP/Include/arm_common_tables.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,121 @@
+/* ----------------------------------------------------------------------
+ * Project:      CMSIS DSP Library
+ * Title:        arm_common_tables.h
+ * Description:  Extern declaration for common tables
+ *
+ * $Date:        27. January 2017
+ * $Revision:    V.1.5.1
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+/*
+ * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef _ARM_COMMON_TABLES_H
+#define _ARM_COMMON_TABLES_H
+
+#include "arm_math.h"
+
+extern const uint16_t armBitRevTable[1024];
+extern const q15_t armRecipTableQ15[64];
+extern const q31_t armRecipTableQ31[64];
+extern const float32_t twiddleCoef_16[32];
+extern const float32_t twiddleCoef_32[64];
+extern const float32_t twiddleCoef_64[128];
+extern const float32_t twiddleCoef_128[256];
+extern const float32_t twiddleCoef_256[512];
+extern const float32_t twiddleCoef_512[1024];
+extern const float32_t twiddleCoef_1024[2048];
+extern const float32_t twiddleCoef_2048[4096];
+extern const float32_t twiddleCoef_4096[8192];
+#define twiddleCoef twiddleCoef_4096
+extern const q31_t twiddleCoef_16_q31[24];
+extern const q31_t twiddleCoef_32_q31[48];
+extern const q31_t twiddleCoef_64_q31[96];
+extern const q31_t twiddleCoef_128_q31[192];
+extern const q31_t twiddleCoef_256_q31[384];
+extern const q31_t twiddleCoef_512_q31[768];
+extern const q31_t twiddleCoef_1024_q31[1536];
+extern const q31_t twiddleCoef_2048_q31[3072];
+extern const q31_t twiddleCoef_4096_q31[6144];
+extern const q15_t twiddleCoef_16_q15[24];
+extern const q15_t twiddleCoef_32_q15[48];
+extern const q15_t twiddleCoef_64_q15[96];
+extern const q15_t twiddleCoef_128_q15[192];
+extern const q15_t twiddleCoef_256_q15[384];
+extern const q15_t twiddleCoef_512_q15[768];
+extern const q15_t twiddleCoef_1024_q15[1536];
+extern const q15_t twiddleCoef_2048_q15[3072];
+extern const q15_t twiddleCoef_4096_q15[6144];
+extern const float32_t twiddleCoef_rfft_32[32];
+extern const float32_t twiddleCoef_rfft_64[64];
+extern const float32_t twiddleCoef_rfft_128[128];
+extern const float32_t twiddleCoef_rfft_256[256];
+extern const float32_t twiddleCoef_rfft_512[512];
+extern const float32_t twiddleCoef_rfft_1024[1024];
+extern const float32_t twiddleCoef_rfft_2048[2048];
+extern const float32_t twiddleCoef_rfft_4096[4096];
+
+/* floating-point bit reversal tables */
+#define ARMBITREVINDEXTABLE_16_TABLE_LENGTH ((uint16_t)20)
+#define ARMBITREVINDEXTABLE_32_TABLE_LENGTH ((uint16_t)48)
+#define ARMBITREVINDEXTABLE_64_TABLE_LENGTH ((uint16_t)56)
+#define ARMBITREVINDEXTABLE_128_TABLE_LENGTH ((uint16_t)208)
+#define ARMBITREVINDEXTABLE_256_TABLE_LENGTH ((uint16_t)440)
+#define ARMBITREVINDEXTABLE_512_TABLE_LENGTH ((uint16_t)448)
+#define ARMBITREVINDEXTABLE_1024_TABLE_LENGTH ((uint16_t)1800)
+#define ARMBITREVINDEXTABLE_2048_TABLE_LENGTH ((uint16_t)3808)
+#define ARMBITREVINDEXTABLE_4096_TABLE_LENGTH ((uint16_t)4032)
+
+extern const uint16_t armBitRevIndexTable16[ARMBITREVINDEXTABLE_16_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable32[ARMBITREVINDEXTABLE_32_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable64[ARMBITREVINDEXTABLE_64_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable128[ARMBITREVINDEXTABLE_128_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable256[ARMBITREVINDEXTABLE_256_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable512[ARMBITREVINDEXTABLE_512_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable1024[ARMBITREVINDEXTABLE_1024_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable2048[ARMBITREVINDEXTABLE_2048_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable4096[ARMBITREVINDEXTABLE_4096_TABLE_LENGTH];
+
+/* fixed-point bit reversal tables */
+#define ARMBITREVINDEXTABLE_FIXED_16_TABLE_LENGTH ((uint16_t)12)
+#define ARMBITREVINDEXTABLE_FIXED_32_TABLE_LENGTH ((uint16_t)24)
+#define ARMBITREVINDEXTABLE_FIXED_64_TABLE_LENGTH ((uint16_t)56)
+#define ARMBITREVINDEXTABLE_FIXED_128_TABLE_LENGTH ((uint16_t)112)
+#define ARMBITREVINDEXTABLE_FIXED_256_TABLE_LENGTH ((uint16_t)240)
+#define ARMBITREVINDEXTABLE_FIXED_512_TABLE_LENGTH ((uint16_t)480)
+#define ARMBITREVINDEXTABLE_FIXED_1024_TABLE_LENGTH ((uint16_t)992)
+#define ARMBITREVINDEXTABLE_FIXED_2048_TABLE_LENGTH ((uint16_t)1984)
+#define ARMBITREVINDEXTABLE_FIXED_4096_TABLE_LENGTH ((uint16_t)4032)
+
+extern const uint16_t armBitRevIndexTable_fixed_16[ARMBITREVINDEXTABLE_FIXED_16_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable_fixed_32[ARMBITREVINDEXTABLE_FIXED_32_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable_fixed_64[ARMBITREVINDEXTABLE_FIXED_64_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable_fixed_128[ARMBITREVINDEXTABLE_FIXED_128_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable_fixed_256[ARMBITREVINDEXTABLE_FIXED_256_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable_fixed_512[ARMBITREVINDEXTABLE_FIXED_512_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable_fixed_1024[ARMBITREVINDEXTABLE_FIXED_1024_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable_fixed_2048[ARMBITREVINDEXTABLE_FIXED_2048_TABLE_LENGTH];
+extern const uint16_t armBitRevIndexTable_fixed_4096[ARMBITREVINDEXTABLE_FIXED_4096_TABLE_LENGTH];
+
+/* Tables for Fast Math Sine and Cosine */
+extern const float32_t sinTable_f32[FAST_MATH_TABLE_SIZE + 1];
+extern const q31_t sinTable_q31[FAST_MATH_TABLE_SIZE + 1];
+extern const q15_t sinTable_q15[FAST_MATH_TABLE_SIZE + 1];
+
+#endif /*  ARM_COMMON_TABLES_H */

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/cmsis/CMSIS/DSP/Include/arm_const_structs.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/cmsis/CMSIS/DSP/Include/arm_const_structs.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,66 @@
+/* ----------------------------------------------------------------------
+ * Project:      CMSIS DSP Library
+ * Title:        arm_const_structs.h
+ * Description:  Constant structs that are initialized for user convenience.
+ *               For example, some can be given as arguments to the arm_cfft_f32() function.
+ *
+ * $Date:        27. January 2017
+ * $Revision:    V.1.5.1
+ *
+ * Target Processor: Cortex-M cores
+ * -------------------------------------------------------------------- */
+/*
+ * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef _ARM_CONST_STRUCTS_H
+#define _ARM_CONST_STRUCTS_H
+
+#include "arm_math.h"
+#include "arm_common_tables.h"
+
+   extern const arm_cfft_instance_f32 arm_cfft_sR_f32_len16;
+   extern const arm_cfft_instance_f32 arm_cfft_sR_f32_len32;
+   extern const arm_cfft_instance_f32 arm_cfft_sR_f32_len64;
+   extern const arm_cfft_instance_f32 arm_cfft_sR_f32_len128;
+   extern const arm_cfft_instance_f32 arm_cfft_sR_f32_len256;
+   extern const arm_cfft_instance_f32 arm_cfft_sR_f32_len512;
+   extern const arm_cfft_instance_f32 arm_cfft_sR_f32_len1024;
+   extern const arm_cfft_instance_f32 arm_cfft_sR_f32_len2048;
+   extern const arm_cfft_instance_f32 arm_cfft_sR_f32_len4096;
+
+   extern const arm_cfft_instance_q31 arm_cfft_sR_q31_len16;
+   extern const arm_cfft_instance_q31 arm_cfft_sR_q31_len32;
+   extern const arm_cfft_instance_q31 arm_cfft_sR_q31_len64;
+   extern const arm_cfft_instance_q31 arm_cfft_sR_q31_len128;
+   extern const arm_cfft_instance_q31 arm_cfft_sR_q31_len256;
+   extern const arm_cfft_instance_q31 arm_cfft_sR_q31_len512;
+   extern const arm_cfft_instance_q31 arm_cfft_sR_q31_len1024;
+   extern const arm_cfft_instance_q31 arm_cfft_sR_q31_len2048;
+   extern const arm_cfft_instance_q31 arm_cfft_sR_q31_len4096;
+
+   extern const arm_cfft_instance_q15 arm_cfft_sR_q15_len16;
+   extern const arm_cfft_instance_q15 arm_cfft_sR_q15_len32;
+   extern const arm_cfft_instance_q15 arm_cfft_sR_q15_len64;
+   extern const arm_cfft_instance_q15 arm_cfft_sR_q15_len128;
+   extern const arm_cfft_instance_q15 arm_cfft_sR_q15_len256;
+   extern const arm_cfft_instance_q15 arm_cfft_sR_q15_len512;
+   extern const arm_cfft_instance_q15 arm_cfft_sR_q15_len1024;
+   extern const arm_cfft_instance_q15 arm_cfft_sR_q15_len2048;
+   extern const arm_cfft_instance_q15 arm_cfft_sR_q15_len4096;
+
+#endif

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/cmsis/CMSIS/DSP/Include/arm_math.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/cmsis/CMSIS/DSP/Include/arm_math.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,7157 @@
+/******************************************************************************
+ * @file     arm_math.h
+ * @brief    Public header file for CMSIS DSP LibraryU
+ * @version  V1.5.3
+ * @date     10. January 2018
+ ******************************************************************************/
+/*
+ * Copyright (c) 2010-2018 Arm Limited or its affiliates. All rights reserved.
+ *
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the License); you may
+ * not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an AS IS BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+/**
+   \mainpage CMSIS DSP Software Library
+   *
+   * Introduction
+   * ------------
+   *
+   * This user manual describes the CMSIS DSP software library,
+   * a suite of common signal processing functions for use on Cortex-M processor based devices.
+   *
+   * The library is divided into a number of functions each covering a specific category:
+   * - Basic math functions
+   * - Fast math functions
+   * - Complex math functions
+   * - Filters
+   * - Matrix functions
+   * - Transforms
+   * - Motor control functions
+   * - Statistical functions
+   * - Support functions
+   * - Interpolation functions
+   *
+   * The library has separate functions for operating on 8-bit integers, 16-bit integers,
+   * 32-bit integer and 32-bit floating-point values.
+   *
+   * Using the Library
+   * ------------
+   *
+   * The library installer contains prebuilt versions of the libraries in the <code>Lib</code> folder.
+   * - arm_cortexM7lfdp_math.lib (Cortex-M7, Little endian, Double Precision Floating Point Unit)
+   * - arm_cortexM7bfdp_math.lib (Cortex-M7, Big endian, Double Precision Floating Point Unit)
+   * - arm_cortexM7lfsp_math.lib (Cortex-M7, Little endian, Single Precision Floating Point Unit)
+   * - arm_cortexM7bfsp_math.lib (Cortex-M7, Big endian and Single Precision Floating Point Unit on)
+   * - arm_cortexM7l_math.lib (Cortex-M7, Little endian)
+   * - arm_cortexM7b_math.lib (Cortex-M7, Big endian)
+   * - arm_cortexM4lf_math.lib (Cortex-M4, Little endian, Floating Point Unit)
+   * - arm_cortexM4bf_math.lib (Cortex-M4, Big endian, Floating Point Unit)
+   * - arm_cortexM4l_math.lib (Cortex-M4, Little endian)
+   * - arm_cortexM4b_math.lib (Cortex-M4, Big endian)
+   * - arm_cortexM3l_math.lib (Cortex-M3, Little endian)
+   * - arm_cortexM3b_math.lib (Cortex-M3, Big endian)
+   * - arm_cortexM0l_math.lib (Cortex-M0 / Cortex-M0+, Little endian)
+   * - arm_cortexM0b_math.lib (Cortex-M0 / Cortex-M0+, Big endian)
+   * - arm_ARMv8MBLl_math.lib (Armv8-M Baseline, Little endian)
+   * - arm_ARMv8MMLl_math.lib (Armv8-M Mainline, Little endian)
+   * - arm_ARMv8MMLlfsp_math.lib (Armv8-M Mainline, Little endian, Single Precision Floating Point Unit)
+   * - arm_ARMv8MMLld_math.lib (Armv8-M Mainline, Little endian, DSP instructions)
+   * - arm_ARMv8MMLldfsp_math.lib (Armv8-M Mainline, Little endian, DSP instructions, Single Precision Floating Point Unit)
+   *
+   * The library functions are declared in the public file <code>arm_math.h</code> which is placed in the <code>Include</code> folder.
+   * Simply include this file and link the appropriate library in the application and begin calling the library functions. The Library supports single
+   * public header file <code> arm_math.h</code> for Cortex-M cores with little endian and big endian. Same header file will be used for floating point unit(FPU) variants.
+   * Define the appropriate preprocessor macro ARM_MATH_CM7 or ARM_MATH_CM4 or ARM_MATH_CM3 or
+   * ARM_MATH_CM0 or ARM_MATH_CM0PLUS depending on the target processor in the application.
+   * For Armv8-M cores define preprocessor macro ARM_MATH_ARMV8MBL or ARM_MATH_ARMV8MML.
+   * Set preprocessor macro __DSP_PRESENT if Armv8-M Mainline core supports DSP instructions.
+   * 
+   *
+   * Examples
+   * --------
+   *
+   * The library ships with a number of examples which demonstrate how to use the library functions.
+   *
+   * Toolchain Support
+   * ------------
+   *
+   * The library has been developed and tested with MDK version 5.14.0.0
+   * The library is being tested in GCC and IAR toolchains and updates on this activity will be made available shortly.
+   *
+   * Building the Library
+   * ------------
+   *
+   * The library installer contains a project file to rebuild libraries on MDK toolchain in the <code>CMSIS\\DSP_Lib\\Source\\ARM</code> folder.
+   * - arm_cortexM_math.uvprojx
+   *
+   *
+   * The libraries can be built by opening the arm_cortexM_math.uvprojx project in MDK-ARM, selecting a specific target, and defining the optional preprocessor macros detailed above.
+   *
+   * Preprocessor Macros
+   * ------------
+   *
+   * Each library project have different preprocessor macros.
+   *
+   * - UNALIGNED_SUPPORT_DISABLE:
+   *
+   * Define macro UNALIGNED_SUPPORT_DISABLE, If the silicon does not support unaligned memory access
+   *
+   * - ARM_MATH_BIG_ENDIAN:
+   *
+   * Define macro ARM_MATH_BIG_ENDIAN to build the library for big endian targets. By default library builds for little endian targets.
+   *
+   * - ARM_MATH_MATRIX_CHECK:
+   *
+   * Define macro ARM_MATH_MATRIX_CHECK for checking on the input and output sizes of matrices
+   *
+   * - ARM_MATH_ROUNDING:
+   *
+   * Define macro ARM_MATH_ROUNDING for rounding on support functions
+   *
+   * - ARM_MATH_CMx:
+   *
+   * Define macro ARM_MATH_CM4 for building the library on Cortex-M4 target, ARM_MATH_CM3 for building library on Cortex-M3 target
+   * and ARM_MATH_CM0 for building library on Cortex-M0 target, ARM_MATH_CM0PLUS for building library on Cortex-M0+ target, and
+   * ARM_MATH_CM7 for building the library on cortex-M7.
+   *
+   * - ARM_MATH_ARMV8MxL:
+   *
+   * Define macro ARM_MATH_ARMV8MBL for building the library on Armv8-M Baseline target, ARM_MATH_ARMV8MML for building library
+   * on Armv8-M Mainline target.
+   *
+   * - __FPU_PRESENT:
+   *
+   * Initialize macro __FPU_PRESENT = 1 when building on FPU supported Targets. Enable this macro for floating point libraries.
+   *
+   * - __DSP_PRESENT:
+   *
+   * Initialize macro __DSP_PRESENT = 1 when Armv8-M Mainline core supports DSP instructions.
+   *
+   * <hr>
+   * CMSIS-DSP in ARM::CMSIS Pack
+   * -----------------------------
+   *
+   * The following files relevant to CMSIS-DSP are present in the <b>ARM::CMSIS</b> Pack directories:
+   * |File/Folder                   |Content                                                                 |
+   * |------------------------------|------------------------------------------------------------------------|
+   * |\b CMSIS\\Documentation\\DSP  | This documentation                                                     |
+   * |\b CMSIS\\DSP_Lib             | Software license agreement (license.txt)                               |
+   * |\b CMSIS\\DSP_Lib\\Examples   | Example projects demonstrating the usage of the library functions      |
+   * |\b CMSIS\\DSP_Lib\\Source     | Source files for rebuilding the library                                |
+   *
+   * <hr>
+   * Revision History of CMSIS-DSP
+   * ------------
+   * Please refer to \ref ChangeLog_pg.
+   *
+   * Copyright Notice
+   * ------------
+   *
+   * Copyright (C) 2010-2015 Arm Limited. All rights reserved.
+   */
+
+
+/**
+ * @defgroup groupMath Basic Math Functions
+ */
+
+/**
+ * @defgroup groupFastMath Fast Math Functions
+ * This set of functions provides a fast approximation to sine, cosine, and square root.
+ * As compared to most of the other functions in the CMSIS math library, the fast math functions
+ * operate on individual values and not arrays.
+ * There are separate functions for Q15, Q31, and floating-point data.
+ *
+ */
+
+/**
+ * @defgroup groupCmplxMath Complex Math Functions
+ * This set of functions operates on complex data vectors.
+ * The data in the complex arrays is stored in an interleaved fashion
+ * (real, imag, real, imag, ...).
+ * In the API functions, the number of samples in a complex array refers
+ * to the number of complex values; the array contains twice this number of
+ * real values.
+ */
+
+/**
+ * @defgroup groupFilters Filtering Functions
+ */
+
+/**
+ * @defgroup groupMatrix Matrix Functions
+ *
+ * This set of functions provides basic matrix math operations.
+ * The functions operate on matrix data structures.  For example,
+ * the type
+ * definition for the floating-point matrix structure is shown
+ * below:
+ * <pre>
+ *     typedef struct
+ *     {
+ *       uint16_t numRows;     // number of rows of the matrix.
+ *       uint16_t numCols;     // number of columns of the matrix.
+ *       float32_t *pData;     // points to the data of the matrix.
+ *     } arm_matrix_instance_f32;
+ * </pre>
+ * There are similar definitions for Q15 and Q31 data types.
+ *
+ * The structure specifies the size of the matrix and then points to
+ * an array of data.  The array is of size <code>numRows X numCols</code>
+ * and the values are arranged in row order.  That is, the
+ * matrix element (i, j) is stored at:
+ * <pre>
+ *     pData[i*numCols + j]
+ * </pre>
+ *
+ * \par Init Functions
+ * There is an associated initialization function for each type of matrix
+ * data structure.
+ * The initialization function sets the values of the internal structure fields.
+ * Refer to the function <code>arm_mat_init_f32()</code>, <code>arm_mat_init_q31()</code>
+ * and <code>arm_mat_init_q15()</code> for floating-point, Q31 and Q15 types,  respectively.
+ *
+ * \par
+ * Use of the initialization function is optional. However, if initialization function is used
+ * then the instance structure cannot be placed into a const data section.
+ * To place the instance structure in a const data
+ * section, manually initialize the data structure.  For example:
+ * <pre>
+ * <code>arm_matrix_instance_f32 S = {nRows, nColumns, pData};</code>
+ * <code>arm_matrix_instance_q31 S = {nRows, nColumns, pData};</code>
+ * <code>arm_matrix_instance_q15 S = {nRows, nColumns, pData};</code>
+ * </pre>
+ * where <code>nRows</code> specifies the number of rows, <code>nColumns</code>
+ * specifies the number of columns, and <code>pData</code> points to the
+ * data array.
+ *
+ * \par Size Checking
+ * By default all of the matrix functions perform size checking on the input and
+ * output matrices. For example, the matrix addition function verifies that the
+ * two input matrices and the output matrix all have the same number of rows and
+ * columns. If the size check fails the functions return:
+ * <pre>
+ *     ARM_MATH_SIZE_MISMATCH
+ * </pre>
+ * Otherwise the functions return
+ * <pre>
+ *     ARM_MATH_SUCCESS
+ * </pre>
+ * There is some overhead associated with this matrix size checking.
+ * The matrix size checking is enabled via the \#define
+ * <pre>
+ *     ARM_MATH_MATRIX_CHECK
+ * </pre>
+ * within the library project settings.  By default this macro is defined
+ * and size checking is enabled. By changing the project settings and
+ * undefining this macro size checking is eliminated and the functions
+ * run a bit faster. With size checking disabled the functions always
+ * return <code>ARM_MATH_SUCCESS</code>.
+ */
+
+/**
+ * @defgroup groupTransforms Transform Functions
+ */
+
+/**
+ * @defgroup groupController Controller Functions
+ */
+
+/**
+ * @defgroup groupStats Statistics Functions
+ */
+/**
+ * @defgroup groupSupport Support Functions
+ */
+
+/**
+ * @defgroup groupInterpolation Interpolation Functions
+ * These functions perform 1- and 2-dimensional interpolation of data.
+ * Linear interpolation is used for 1-dimensional data and
+ * bilinear interpolation is used for 2-dimensional data.
+ */
+
+/**
+ * @defgroup groupExamples Examples
+ */
+#ifndef _ARM_MATH_H
+#define _ARM_MATH_H
+
+/* Compiler specific diagnostic adjustment */
+#if   defined ( __CC_ARM )
+
+#elif defined ( __ARMCC_VERSION ) && ( __ARMCC_VERSION >= 6010050 )
+
+#elif defined ( __GNUC__ )
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wsign-conversion"
+#pragma GCC diagnostic ignored "-Wconversion"
+#pragma GCC diagnostic ignored "-Wunused-parameter"
+
+#elif defined ( __ICCARM__ )
+
+#elif defined ( __TI_ARM__ )
+
+#elif defined ( __CSMC__ )
+
+#elif defined ( __TASKING__ )
+
+#else
+  #error Unknown compiler
+#endif
+
+
+#define __CMSIS_GENERIC         /* disable NVIC and Systick functions */
+
+#if defined(ARM_MATH_CM7)
+  #include "core_cm7.h"
+  #define ARM_MATH_DSP
+#elif defined (ARM_MATH_CM4)
+  #include "core_cm4.h"
+  #define ARM_MATH_DSP
+#elif defined (ARM_MATH_CM3)
+  #include "core_cm3.h"
+#elif defined (ARM_MATH_CM0)
+  #include "core_cm0.h"
+  #define ARM_MATH_CM0_FAMILY
+#elif defined (ARM_MATH_CM0PLUS)
+  #include "core_cm0plus.h"
+  #define ARM_MATH_CM0_FAMILY
+#elif defined (ARM_MATH_ARMV8MBL)
+  #include "core_armv8mbl.h"
+  #define ARM_MATH_CM0_FAMILY
+#elif defined (ARM_MATH_ARMV8MML)
+  #include "core_armv8mml.h"
+  #if (defined (__DSP_PRESENT) && (__DSP_PRESENT == 1))
+    #define ARM_MATH_DSP
+  #endif
+#else
+  #error "Define according the used Cortex core ARM_MATH_CM7, ARM_MATH_CM4, ARM_MATH_CM3, ARM_MATH_CM0PLUS, ARM_MATH_CM0, ARM_MATH_ARMV8MBL, ARM_MATH_ARMV8MML"
+#endif
+
+#undef  __CMSIS_GENERIC         /* enable NVIC and Systick functions */
+#include "string.h"
+#include "math.h"
+#ifdef   __cplusplus
+extern "C"
+{
+#endif
+
+
+  /**
+   * @brief Macros required for reciprocal calculation in Normalized LMS
+   */
+
+#define DELTA_Q31          (0x100)
+#define DELTA_Q15          0x5
+#define INDEX_MASK         0x0000003F
+#ifndef PI
+  #define PI               3.14159265358979f
+#endif
+
+  /**
+   * @brief Macros required for SINE and COSINE Fast math approximations
+   */
+
+#define FAST_MATH_TABLE_SIZE  512
+#define FAST_MATH_Q31_SHIFT   (32 - 10)
+#define FAST_MATH_Q15_SHIFT   (16 - 10)
+#define CONTROLLER_Q31_SHIFT  (32 - 9)
+#define TABLE_SPACING_Q31     0x400000
+#define TABLE_SPACING_Q15     0x80
+
+  /**
+   * @brief Macros required for SINE and COSINE Controller functions
+   */
+  /* 1.31(q31) Fixed value of 2/360 */
+  /* -1 to +1 is divided into 360 values so total spacing is (2/360) */
+#define INPUT_SPACING         0xB60B61
+
+  /**
+   * @brief Macro for Unaligned Support
+   */
+#ifndef UNALIGNED_SUPPORT_DISABLE
+    #define ALIGN4
+#else
+  #if defined  (__GNUC__)
+    #define ALIGN4 __attribute__((aligned(4)))
+  #else
+    #define ALIGN4 __align(4)
+  #endif
+#endif   /* #ifndef UNALIGNED_SUPPORT_DISABLE */
+
+  /**
+   * @brief Error status returned by some functions in the library.
+   */
+
+  typedef enum
+  {
+    ARM_MATH_SUCCESS = 0,                /**< No error */
+    ARM_MATH_ARGUMENT_ERROR = -1,        /**< One or more arguments are incorrect */
+    ARM_MATH_LENGTH_ERROR = -2,          /**< Length of data buffer is incorrect */
+    ARM_MATH_SIZE_MISMATCH = -3,         /**< Size of matrices is not compatible with the operation. */
+    ARM_MATH_NANINF = -4,                /**< Not-a-number (NaN) or infinity is generated */
+    ARM_MATH_SINGULAR = -5,              /**< Generated by matrix inversion if the input matrix is singular and cannot be inverted. */
+    ARM_MATH_TEST_FAILURE = -6           /**< Test Failed  */
+  } arm_status;
+
+  /**
+   * @brief 8-bit fractional data type in 1.7 format.
+   */
+  typedef int8_t q7_t;
+
+  /**
+   * @brief 16-bit fractional data type in 1.15 format.
+   */
+  typedef int16_t q15_t;
+
+  /**
+   * @brief 32-bit fractional data type in 1.31 format.
+   */
+  typedef int32_t q31_t;
+
+  /**
+   * @brief 64-bit fractional data type in 1.63 format.
+   */
+  typedef int64_t q63_t;
+
+  /**
+   * @brief 32-bit floating-point type definition.
+   */
+  typedef float float32_t;
+
+  /**
+   * @brief 64-bit floating-point type definition.
+   */
+  typedef double float64_t;
+
+  /**
+   * @brief definition to read/write two 16 bit values.
+   */
+#if   defined ( __CC_ARM )
+  #define __SIMD32_TYPE int32_t __packed
+  #define CMSIS_UNUSED __attribute__((unused))
+  #define CMSIS_INLINE __attribute__((always_inline))
+
+#elif defined ( __ARMCC_VERSION ) && ( __ARMCC_VERSION >= 6010050 )
+  #define __SIMD32_TYPE int32_t
+  #define CMSIS_UNUSED __attribute__((unused))
+  #define CMSIS_INLINE __attribute__((always_inline))
+
+#elif defined ( __GNUC__ )
+  #define __SIMD32_TYPE int32_t
+  #define CMSIS_UNUSED __attribute__((unused))
+  #define CMSIS_INLINE __attribute__((always_inline))
+
+#elif defined ( __ICCARM__ )
+  #define __SIMD32_TYPE int32_t __packed
+  #define CMSIS_UNUSED
+  #define CMSIS_INLINE
+
+#elif defined ( __TI_ARM__ )
+  #define __SIMD32_TYPE int32_t
+  #define CMSIS_UNUSED __attribute__((unused))
+  #define CMSIS_INLINE
+
+#elif defined ( __CSMC__ )
+  #define __SIMD32_TYPE int32_t
+  #define CMSIS_UNUSED
+  #define CMSIS_INLINE
+
+#elif defined ( __TASKING__ )
+  #define __SIMD32_TYPE __unaligned int32_t
+  #define CMSIS_UNUSED
+  #define CMSIS_INLINE
+
+#else
+  #error Unknown compiler
+#endif
+
+#define __SIMD32(addr)        (*(__SIMD32_TYPE **) & (addr))
+#define __SIMD32_CONST(addr)  ((__SIMD32_TYPE *)(addr))
+#define _SIMD32_OFFSET(addr)  (*(__SIMD32_TYPE *)  (addr))
+#define __SIMD64(addr)        (*(int64_t **) & (addr))
+
+#if !defined (ARM_MATH_DSP)
+  /**
+   * @brief definition to pack two 16 bit values.
+   */
+#define __PKHBT(ARG1, ARG2, ARG3) ( (((int32_t)(ARG1) <<    0) & (int32_t)0x0000FFFF) | \
+                                    (((int32_t)(ARG2) << ARG3) & (int32_t)0xFFFF0000)  )
+#define __PKHTB(ARG1, ARG2, ARG3) ( (((int32_t)(ARG1) <<    0) & (int32_t)0xFFFF0000) | \
+                                    (((int32_t)(ARG2) >> ARG3) & (int32_t)0x0000FFFF)  )
+
+#endif /* !defined (ARM_MATH_DSP) */
+
+   /**
+   * @brief definition to pack four 8 bit values.
+   */
+#ifndef ARM_MATH_BIG_ENDIAN
+
+#define __PACKq7(v0,v1,v2,v3) ( (((int32_t)(v0) <<  0) & (int32_t)0x000000FF) | \
+                                (((int32_t)(v1) <<  8) & (int32_t)0x0000FF00) | \
+                                (((int32_t)(v2) << 16) & (int32_t)0x00FF0000) | \
+                                (((int32_t)(v3) << 24) & (int32_t)0xFF000000)  )
+#else
+
+#define __PACKq7(v0,v1,v2,v3) ( (((int32_t)(v3) <<  0) & (int32_t)0x000000FF) | \
+                                (((int32_t)(v2) <<  8) & (int32_t)0x0000FF00) | \
+                                (((int32_t)(v1) << 16) & (int32_t)0x00FF0000) | \
+                                (((int32_t)(v0) << 24) & (int32_t)0xFF000000)  )
+
+#endif
+
+
+  /**
+   * @brief Clips Q63 to Q31 values.
+   */
+  CMSIS_INLINE __STATIC_INLINE q31_t clip_q63_to_q31(
+  q63_t x)
+  {
+    return ((q31_t) (x >> 32) != ((q31_t) x >> 31)) ?
+      ((0x7FFFFFFF ^ ((q31_t) (x >> 63)))) : (q31_t) x;
+  }
+
+  /**
+   * @brief Clips Q63 to Q15 values.
+   */
+  CMSIS_INLINE __STATIC_INLINE q15_t clip_q63_to_q15(
+  q63_t x)
+  {
+    return ((q31_t) (x >> 32) != ((q31_t) x >> 31)) ?
+      ((0x7FFF ^ ((q15_t) (x >> 63)))) : (q15_t) (x >> 15);
+  }
+
+  /**
+   * @brief Clips Q31 to Q7 values.
+   */
+  CMSIS_INLINE __STATIC_INLINE q7_t clip_q31_to_q7(
+  q31_t x)
+  {
+    return ((q31_t) (x >> 24) != ((q31_t) x >> 23)) ?
+      ((0x7F ^ ((q7_t) (x >> 31)))) : (q7_t) x;
+  }
+
+  /**
+   * @brief Clips Q31 to Q15 values.
+   */
+  CMSIS_INLINE __STATIC_INLINE q15_t clip_q31_to_q15(
+  q31_t x)
+  {
+    return ((q31_t) (x >> 16) != ((q31_t) x >> 15)) ?
+      ((0x7FFF ^ ((q15_t) (x >> 31)))) : (q15_t) x;
+  }
+
+  /**
+   * @brief Multiplies 32 X 64 and returns 32 bit result in 2.30 format.
+   */
+
+  CMSIS_INLINE __STATIC_INLINE q63_t mult32x64(
+  q63_t x,
+  q31_t y)
+  {
+    return ((((q63_t) (x & 0x00000000FFFFFFFF) * y) >> 32) +
+            (((q63_t) (x >> 32) * y)));
+  }
+
+  /**
+   * @brief Function to Calculates 1/in (reciprocal) value of Q31 Data type.
+   */
+
+  CMSIS_INLINE __STATIC_INLINE uint32_t arm_recip_q31(
+  q31_t in,
+  q31_t * dst,
+  q31_t * pRecipTable)
+  {
+    q31_t out;
+    uint32_t tempVal;
+    uint32_t index, i;
+    uint32_t signBits;
+
+    if (in > 0)
+    {
+      signBits = ((uint32_t) (__CLZ( in) - 1));
+    }
+    else
+    {
+      signBits = ((uint32_t) (__CLZ(-in) - 1));
+    }
+
+    /* Convert input sample to 1.31 format */
+    in = (in << signBits);
+
+    /* calculation of index for initial approximated Val */
+    index = (uint32_t)(in >> 24);
+    index = (index & INDEX_MASK);
+
+    /* 1.31 with exp 1 */
+    out = pRecipTable[index];
+
+    /* calculation of reciprocal value */
+    /* running approximation for two iterations */
+    for (i = 0U; i < 2U; i++)
+    {
+      tempVal = (uint32_t) (((q63_t) in * out) >> 31);
+      tempVal = 0x7FFFFFFFu - tempVal;
+      /*      1.31 with exp 1 */
+      /* out = (q31_t) (((q63_t) out * tempVal) >> 30); */
+      out = clip_q63_to_q31(((q63_t) out * tempVal) >> 30);
+    }
+
+    /* write output */
+    *dst = out;
+
+    /* return num of signbits of out = 1/in value */
+    return (signBits + 1U);
+  }
+
+
+  /**
+   * @brief Function to Calculates 1/in (reciprocal) value of Q15 Data type.
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t arm_recip_q15(
+  q15_t in,
+  q15_t * dst,
+  q15_t * pRecipTable)
+  {
+    q15_t out = 0;
+    uint32_t tempVal = 0;
+    uint32_t index = 0, i = 0;
+    uint32_t signBits = 0;
+
+    if (in > 0)
+    {
+      signBits = ((uint32_t)(__CLZ( in) - 17));
+    }
+    else
+    {
+      signBits = ((uint32_t)(__CLZ(-in) - 17));
+    }
+
+    /* Convert input sample to 1.15 format */
+    in = (in << signBits);
+
+    /* calculation of index for initial approximated Val */
+    index = (uint32_t)(in >>  8);
+    index = (index & INDEX_MASK);
+
+    /*      1.15 with exp 1  */
+    out = pRecipTable[index];
+
+    /* calculation of reciprocal value */
+    /* running approximation for two iterations */
+    for (i = 0U; i < 2U; i++)
+    {
+      tempVal = (uint32_t) (((q31_t) in * out) >> 15);
+      tempVal = 0x7FFFu - tempVal;
+      /*      1.15 with exp 1 */
+      out = (q15_t) (((q31_t) out * tempVal) >> 14);
+      /* out = clip_q31_to_q15(((q31_t) out * tempVal) >> 14); */
+    }
+
+    /* write output */
+    *dst = out;
+
+    /* return num of signbits of out = 1/in value */
+    return (signBits + 1);
+  }
+
+
+/*
+ * @brief C custom defined intrinsic function for M3 and M0 processors
+ */
+#if !defined (ARM_MATH_DSP)
+
+  /*
+   * @brief C custom defined QADD8 for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __QADD8(
+  uint32_t x,
+  uint32_t y)
+  {
+    q31_t r, s, t, u;
+
+    r = __SSAT(((((q31_t)x << 24) >> 24) + (((q31_t)y << 24) >> 24)), 8) & (int32_t)0x000000FF;
+    s = __SSAT(((((q31_t)x << 16) >> 24) + (((q31_t)y << 16) >> 24)), 8) & (int32_t)0x000000FF;
+    t = __SSAT(((((q31_t)x <<  8) >> 24) + (((q31_t)y <<  8) >> 24)), 8) & (int32_t)0x000000FF;
+    u = __SSAT(((((q31_t)x      ) >> 24) + (((q31_t)y      ) >> 24)), 8) & (int32_t)0x000000FF;
+
+    return ((uint32_t)((u << 24) | (t << 16) | (s <<  8) | (r      )));
+  }
+
+
+  /*
+   * @brief C custom defined QSUB8 for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __QSUB8(
+  uint32_t x,
+  uint32_t y)
+  {
+    q31_t r, s, t, u;
+
+    r = __SSAT(((((q31_t)x << 24) >> 24) - (((q31_t)y << 24) >> 24)), 8) & (int32_t)0x000000FF;
+    s = __SSAT(((((q31_t)x << 16) >> 24) - (((q31_t)y << 16) >> 24)), 8) & (int32_t)0x000000FF;
+    t = __SSAT(((((q31_t)x <<  8) >> 24) - (((q31_t)y <<  8) >> 24)), 8) & (int32_t)0x000000FF;
+    u = __SSAT(((((q31_t)x      ) >> 24) - (((q31_t)y      ) >> 24)), 8) & (int32_t)0x000000FF;
+
+    return ((uint32_t)((u << 24) | (t << 16) | (s <<  8) | (r      )));
+  }
+
+
+  /*
+   * @brief C custom defined QADD16 for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __QADD16(
+  uint32_t x,
+  uint32_t y)
+  {
+/*  q31_t r,     s;  without initialisation 'arm_offset_q15 test' fails  but 'intrinsic' tests pass! for armCC */
+    q31_t r = 0, s = 0;
+
+    r = __SSAT(((((q31_t)x << 16) >> 16) + (((q31_t)y << 16) >> 16)), 16) & (int32_t)0x0000FFFF;
+    s = __SSAT(((((q31_t)x      ) >> 16) + (((q31_t)y      ) >> 16)), 16) & (int32_t)0x0000FFFF;
+
+    return ((uint32_t)((s << 16) | (r      )));
+  }
+
+
+  /*
+   * @brief C custom defined SHADD16 for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __SHADD16(
+  uint32_t x,
+  uint32_t y)
+  {
+    q31_t r, s;
+
+    r = (((((q31_t)x << 16) >> 16) + (((q31_t)y << 16) >> 16)) >> 1) & (int32_t)0x0000FFFF;
+    s = (((((q31_t)x      ) >> 16) + (((q31_t)y      ) >> 16)) >> 1) & (int32_t)0x0000FFFF;
+
+    return ((uint32_t)((s << 16) | (r      )));
+  }
+
+
+  /*
+   * @brief C custom defined QSUB16 for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __QSUB16(
+  uint32_t x,
+  uint32_t y)
+  {
+    q31_t r, s;
+
+    r = __SSAT(((((q31_t)x << 16) >> 16) - (((q31_t)y << 16) >> 16)), 16) & (int32_t)0x0000FFFF;
+    s = __SSAT(((((q31_t)x      ) >> 16) - (((q31_t)y      ) >> 16)), 16) & (int32_t)0x0000FFFF;
+
+    return ((uint32_t)((s << 16) | (r      )));
+  }
+
+
+  /*
+   * @brief C custom defined SHSUB16 for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __SHSUB16(
+  uint32_t x,
+  uint32_t y)
+  {
+    q31_t r, s;
+
+    r = (((((q31_t)x << 16) >> 16) - (((q31_t)y << 16) >> 16)) >> 1) & (int32_t)0x0000FFFF;
+    s = (((((q31_t)x      ) >> 16) - (((q31_t)y      ) >> 16)) >> 1) & (int32_t)0x0000FFFF;
+
+    return ((uint32_t)((s << 16) | (r      )));
+  }
+
+
+  /*
+   * @brief C custom defined QASX for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __QASX(
+  uint32_t x,
+  uint32_t y)
+  {
+    q31_t r, s;
+
+    r = __SSAT(((((q31_t)x << 16) >> 16) - (((q31_t)y      ) >> 16)), 16) & (int32_t)0x0000FFFF;
+    s = __SSAT(((((q31_t)x      ) >> 16) + (((q31_t)y << 16) >> 16)), 16) & (int32_t)0x0000FFFF;
+
+    return ((uint32_t)((s << 16) | (r      )));
+  }
+
+
+  /*
+   * @brief C custom defined SHASX for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __SHASX(
+  uint32_t x,
+  uint32_t y)
+  {
+    q31_t r, s;
+
+    r = (((((q31_t)x << 16) >> 16) - (((q31_t)y      ) >> 16)) >> 1) & (int32_t)0x0000FFFF;
+    s = (((((q31_t)x      ) >> 16) + (((q31_t)y << 16) >> 16)) >> 1) & (int32_t)0x0000FFFF;
+
+    return ((uint32_t)((s << 16) | (r      )));
+  }
+
+
+  /*
+   * @brief C custom defined QSAX for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __QSAX(
+  uint32_t x,
+  uint32_t y)
+  {
+    q31_t r, s;
+
+    r = __SSAT(((((q31_t)x << 16) >> 16) + (((q31_t)y      ) >> 16)), 16) & (int32_t)0x0000FFFF;
+    s = __SSAT(((((q31_t)x      ) >> 16) - (((q31_t)y << 16) >> 16)), 16) & (int32_t)0x0000FFFF;
+
+    return ((uint32_t)((s << 16) | (r      )));
+  }
+
+
+  /*
+   * @brief C custom defined SHSAX for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __SHSAX(
+  uint32_t x,
+  uint32_t y)
+  {
+    q31_t r, s;
+
+    r = (((((q31_t)x << 16) >> 16) + (((q31_t)y      ) >> 16)) >> 1) & (int32_t)0x0000FFFF;
+    s = (((((q31_t)x      ) >> 16) - (((q31_t)y << 16) >> 16)) >> 1) & (int32_t)0x0000FFFF;
+
+    return ((uint32_t)((s << 16) | (r      )));
+  }
+
+
+  /*
+   * @brief C custom defined SMUSDX for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __SMUSDX(
+  uint32_t x,
+  uint32_t y)
+  {
+    return ((uint32_t)(((((q31_t)x << 16) >> 16) * (((q31_t)y      ) >> 16)) -
+                       ((((q31_t)x      ) >> 16) * (((q31_t)y << 16) >> 16))   ));
+  }
+
+  /*
+   * @brief C custom defined SMUADX for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __SMUADX(
+  uint32_t x,
+  uint32_t y)
+  {
+    return ((uint32_t)(((((q31_t)x << 16) >> 16) * (((q31_t)y      ) >> 16)) +
+                       ((((q31_t)x      ) >> 16) * (((q31_t)y << 16) >> 16))   ));
+  }
+
+
+  /*
+   * @brief C custom defined QADD for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE int32_t __QADD(
+  int32_t x,
+  int32_t y)
+  {
+    return ((int32_t)(clip_q63_to_q31((q63_t)x + (q31_t)y)));
+  }
+
+
+  /*
+   * @brief C custom defined QSUB for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE int32_t __QSUB(
+  int32_t x,
+  int32_t y)
+  {
+    return ((int32_t)(clip_q63_to_q31((q63_t)x - (q31_t)y)));
+  }
+
+
+  /*
+   * @brief C custom defined SMLAD for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __SMLAD(
+  uint32_t x,
+  uint32_t y,
+  uint32_t sum)
+  {
+    return ((uint32_t)(((((q31_t)x << 16) >> 16) * (((q31_t)y << 16) >> 16)) +
+                       ((((q31_t)x      ) >> 16) * (((q31_t)y      ) >> 16)) +
+                       ( ((q31_t)sum    )                                  )   ));
+  }
+
+
+  /*
+   * @brief C custom defined SMLADX for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __SMLADX(
+  uint32_t x,
+  uint32_t y,
+  uint32_t sum)
+  {
+    return ((uint32_t)(((((q31_t)x << 16) >> 16) * (((q31_t)y      ) >> 16)) +
+                       ((((q31_t)x      ) >> 16) * (((q31_t)y << 16) >> 16)) +
+                       ( ((q31_t)sum    )                                  )   ));
+  }
+
+
+  /*
+   * @brief C custom defined SMLSDX for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __SMLSDX(
+  uint32_t x,
+  uint32_t y,
+  uint32_t sum)
+  {
+    return ((uint32_t)(((((q31_t)x << 16) >> 16) * (((q31_t)y      ) >> 16)) -
+                       ((((q31_t)x      ) >> 16) * (((q31_t)y << 16) >> 16)) +
+                       ( ((q31_t)sum    )                                  )   ));
+  }
+
+
+  /*
+   * @brief C custom defined SMLALD for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint64_t __SMLALD(
+  uint32_t x,
+  uint32_t y,
+  uint64_t sum)
+  {
+/*  return (sum + ((q15_t) (x >> 16) * (q15_t) (y >> 16)) + ((q15_t) x * (q15_t) y)); */
+    return ((uint64_t)(((((q31_t)x << 16) >> 16) * (((q31_t)y << 16) >> 16)) +
+                       ((((q31_t)x      ) >> 16) * (((q31_t)y      ) >> 16)) +
+                       ( ((q63_t)sum    )                                  )   ));
+  }
+
+
+  /*
+   * @brief C custom defined SMLALDX for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint64_t __SMLALDX(
+  uint32_t x,
+  uint32_t y,
+  uint64_t sum)
+  {
+/*  return (sum + ((q15_t) (x >> 16) * (q15_t) y)) + ((q15_t) x * (q15_t) (y >> 16)); */
+    return ((uint64_t)(((((q31_t)x << 16) >> 16) * (((q31_t)y      ) >> 16)) +
+                       ((((q31_t)x      ) >> 16) * (((q31_t)y << 16) >> 16)) +
+                       ( ((q63_t)sum    )                                  )   ));
+  }
+
+
+  /*
+   * @brief C custom defined SMUAD for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __SMUAD(
+  uint32_t x,
+  uint32_t y)
+  {
+    return ((uint32_t)(((((q31_t)x << 16) >> 16) * (((q31_t)y << 16) >> 16)) +
+                       ((((q31_t)x      ) >> 16) * (((q31_t)y      ) >> 16))   ));
+  }
+
+
+  /*
+   * @brief C custom defined SMUSD for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __SMUSD(
+  uint32_t x,
+  uint32_t y)
+  {
+    return ((uint32_t)(((((q31_t)x << 16) >> 16) * (((q31_t)y << 16) >> 16)) -
+                       ((((q31_t)x      ) >> 16) * (((q31_t)y      ) >> 16))   ));
+  }
+
+
+  /*
+   * @brief C custom defined SXTB16 for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE uint32_t __SXTB16(
+  uint32_t x)
+  {
+    return ((uint32_t)(((((q31_t)x << 24) >> 24) & (q31_t)0x0000FFFF) |
+                       ((((q31_t)x <<  8) >>  8) & (q31_t)0xFFFF0000)  ));
+  }
+
+  /*
+   * @brief C custom defined SMMLA for M3 and M0 processors
+   */
+  CMSIS_INLINE __STATIC_INLINE int32_t __SMMLA(
+  int32_t x,
+  int32_t y,
+  int32_t sum)
+  {
+    return (sum + (int32_t) (((int64_t) x * y) >> 32));
+  }
+
+#endif /* !defined (ARM_MATH_DSP) */
+
+
+  /**
+   * @brief Instance structure for the Q7 FIR filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;        /**< number of filter coefficients in the filter. */
+    q7_t *pState;            /**< points to the state variable array. The array is of length numTaps+blockSize-1. */
+    q7_t *pCoeffs;           /**< points to the coefficient array. The array is of length numTaps.*/
+  } arm_fir_instance_q7;
+
+  /**
+   * @brief Instance structure for the Q15 FIR filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;         /**< number of filter coefficients in the filter. */
+    q15_t *pState;            /**< points to the state variable array. The array is of length numTaps+blockSize-1. */
+    q15_t *pCoeffs;           /**< points to the coefficient array. The array is of length numTaps.*/
+  } arm_fir_instance_q15;
+
+  /**
+   * @brief Instance structure for the Q31 FIR filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;         /**< number of filter coefficients in the filter. */
+    q31_t *pState;            /**< points to the state variable array. The array is of length numTaps+blockSize-1. */
+    q31_t *pCoeffs;           /**< points to the coefficient array. The array is of length numTaps. */
+  } arm_fir_instance_q31;
+
+  /**
+   * @brief Instance structure for the floating-point FIR filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;     /**< number of filter coefficients in the filter. */
+    float32_t *pState;    /**< points to the state variable array. The array is of length numTaps+blockSize-1. */
+    float32_t *pCoeffs;   /**< points to the coefficient array. The array is of length numTaps. */
+  } arm_fir_instance_f32;
+
+
+  /**
+   * @brief Processing function for the Q7 FIR filter.
+   * @param[in]  S          points to an instance of the Q7 FIR filter structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_fir_q7(
+  const arm_fir_instance_q7 * S,
+  q7_t * pSrc,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the Q7 FIR filter.
+   * @param[in,out] S          points to an instance of the Q7 FIR structure.
+   * @param[in]     numTaps    Number of filter coefficients in the filter.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     blockSize  number of samples that are processed.
+   */
+  void arm_fir_init_q7(
+  arm_fir_instance_q7 * S,
+  uint16_t numTaps,
+  q7_t * pCoeffs,
+  q7_t * pState,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the Q15 FIR filter.
+   * @param[in]  S          points to an instance of the Q15 FIR structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_fir_q15(
+  const arm_fir_instance_q15 * S,
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the fast Q15 FIR filter for Cortex-M3 and Cortex-M4.
+   * @param[in]  S          points to an instance of the Q15 FIR filter structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_fir_fast_q15(
+  const arm_fir_instance_q15 * S,
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the Q15 FIR filter.
+   * @param[in,out] S          points to an instance of the Q15 FIR filter structure.
+   * @param[in]     numTaps    Number of filter coefficients in the filter. Must be even and greater than or equal to 4.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     blockSize  number of samples that are processed at a time.
+   * @return The function returns ARM_MATH_SUCCESS if initialization was successful or ARM_MATH_ARGUMENT_ERROR if
+   * <code>numTaps</code> is not a supported value.
+   */
+  arm_status arm_fir_init_q15(
+  arm_fir_instance_q15 * S,
+  uint16_t numTaps,
+  q15_t * pCoeffs,
+  q15_t * pState,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the Q31 FIR filter.
+   * @param[in]  S          points to an instance of the Q31 FIR filter structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_fir_q31(
+  const arm_fir_instance_q31 * S,
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the fast Q31 FIR filter for Cortex-M3 and Cortex-M4.
+   * @param[in]  S          points to an instance of the Q31 FIR structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_fir_fast_q31(
+  const arm_fir_instance_q31 * S,
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the Q31 FIR filter.
+   * @param[in,out] S          points to an instance of the Q31 FIR structure.
+   * @param[in]     numTaps    Number of filter coefficients in the filter.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     blockSize  number of samples that are processed at a time.
+   */
+  void arm_fir_init_q31(
+  arm_fir_instance_q31 * S,
+  uint16_t numTaps,
+  q31_t * pCoeffs,
+  q31_t * pState,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the floating-point FIR filter.
+   * @param[in]  S          points to an instance of the floating-point FIR structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_fir_f32(
+  const arm_fir_instance_f32 * S,
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the floating-point FIR filter.
+   * @param[in,out] S          points to an instance of the floating-point FIR filter structure.
+   * @param[in]     numTaps    Number of filter coefficients in the filter.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     blockSize  number of samples that are processed at a time.
+   */
+  void arm_fir_init_f32(
+  arm_fir_instance_f32 * S,
+  uint16_t numTaps,
+  float32_t * pCoeffs,
+  float32_t * pState,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Instance structure for the Q15 Biquad cascade filter.
+   */
+  typedef struct
+  {
+    int8_t numStages;        /**< number of 2nd order stages in the filter.  Overall order is 2*numStages. */
+    q15_t *pState;           /**< Points to the array of state coefficients.  The array is of length 4*numStages. */
+    q15_t *pCoeffs;          /**< Points to the array of coefficients.  The array is of length 5*numStages. */
+    int8_t postShift;        /**< Additional shift, in bits, applied to each output sample. */
+  } arm_biquad_casd_df1_inst_q15;
+
+  /**
+   * @brief Instance structure for the Q31 Biquad cascade filter.
+   */
+  typedef struct
+  {
+    uint32_t numStages;      /**< number of 2nd order stages in the filter.  Overall order is 2*numStages. */
+    q31_t *pState;           /**< Points to the array of state coefficients.  The array is of length 4*numStages. */
+    q31_t *pCoeffs;          /**< Points to the array of coefficients.  The array is of length 5*numStages. */
+    uint8_t postShift;       /**< Additional shift, in bits, applied to each output sample. */
+  } arm_biquad_casd_df1_inst_q31;
+
+  /**
+   * @brief Instance structure for the floating-point Biquad cascade filter.
+   */
+  typedef struct
+  {
+    uint32_t numStages;      /**< number of 2nd order stages in the filter.  Overall order is 2*numStages. */
+    float32_t *pState;       /**< Points to the array of state coefficients.  The array is of length 4*numStages. */
+    float32_t *pCoeffs;      /**< Points to the array of coefficients.  The array is of length 5*numStages. */
+  } arm_biquad_casd_df1_inst_f32;
+
+
+  /**
+   * @brief Processing function for the Q15 Biquad cascade filter.
+   * @param[in]  S          points to an instance of the Q15 Biquad cascade structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_biquad_cascade_df1_q15(
+  const arm_biquad_casd_df1_inst_q15 * S,
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the Q15 Biquad cascade filter.
+   * @param[in,out] S          points to an instance of the Q15 Biquad cascade structure.
+   * @param[in]     numStages  number of 2nd order stages in the filter.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     postShift  Shift to be applied to the output. Varies according to the coefficients format
+   */
+  void arm_biquad_cascade_df1_init_q15(
+  arm_biquad_casd_df1_inst_q15 * S,
+  uint8_t numStages,
+  q15_t * pCoeffs,
+  q15_t * pState,
+  int8_t postShift);
+
+
+  /**
+   * @brief Fast but less precise processing function for the Q15 Biquad cascade filter for Cortex-M3 and Cortex-M4.
+   * @param[in]  S          points to an instance of the Q15 Biquad cascade structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_biquad_cascade_df1_fast_q15(
+  const arm_biquad_casd_df1_inst_q15 * S,
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the Q31 Biquad cascade filter
+   * @param[in]  S          points to an instance of the Q31 Biquad cascade structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_biquad_cascade_df1_q31(
+  const arm_biquad_casd_df1_inst_q31 * S,
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Fast but less precise processing function for the Q31 Biquad cascade filter for Cortex-M3 and Cortex-M4.
+   * @param[in]  S          points to an instance of the Q31 Biquad cascade structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_biquad_cascade_df1_fast_q31(
+  const arm_biquad_casd_df1_inst_q31 * S,
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the Q31 Biquad cascade filter.
+   * @param[in,out] S          points to an instance of the Q31 Biquad cascade structure.
+   * @param[in]     numStages  number of 2nd order stages in the filter.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     postShift  Shift to be applied to the output. Varies according to the coefficients format
+   */
+  void arm_biquad_cascade_df1_init_q31(
+  arm_biquad_casd_df1_inst_q31 * S,
+  uint8_t numStages,
+  q31_t * pCoeffs,
+  q31_t * pState,
+  int8_t postShift);
+
+
+  /**
+   * @brief Processing function for the floating-point Biquad cascade filter.
+   * @param[in]  S          points to an instance of the floating-point Biquad cascade structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_biquad_cascade_df1_f32(
+  const arm_biquad_casd_df1_inst_f32 * S,
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the floating-point Biquad cascade filter.
+   * @param[in,out] S          points to an instance of the floating-point Biquad cascade structure.
+   * @param[in]     numStages  number of 2nd order stages in the filter.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   */
+  void arm_biquad_cascade_df1_init_f32(
+  arm_biquad_casd_df1_inst_f32 * S,
+  uint8_t numStages,
+  float32_t * pCoeffs,
+  float32_t * pState);
+
+
+  /**
+   * @brief Instance structure for the floating-point matrix structure.
+   */
+  typedef struct
+  {
+    uint16_t numRows;     /**< number of rows of the matrix.     */
+    uint16_t numCols;     /**< number of columns of the matrix.  */
+    float32_t *pData;     /**< points to the data of the matrix. */
+  } arm_matrix_instance_f32;
+
+
+  /**
+   * @brief Instance structure for the floating-point matrix structure.
+   */
+  typedef struct
+  {
+    uint16_t numRows;     /**< number of rows of the matrix.     */
+    uint16_t numCols;     /**< number of columns of the matrix.  */
+    float64_t *pData;     /**< points to the data of the matrix. */
+  } arm_matrix_instance_f64;
+
+  /**
+   * @brief Instance structure for the Q15 matrix structure.
+   */
+  typedef struct
+  {
+    uint16_t numRows;     /**< number of rows of the matrix.     */
+    uint16_t numCols;     /**< number of columns of the matrix.  */
+    q15_t *pData;         /**< points to the data of the matrix. */
+  } arm_matrix_instance_q15;
+
+  /**
+   * @brief Instance structure for the Q31 matrix structure.
+   */
+  typedef struct
+  {
+    uint16_t numRows;     /**< number of rows of the matrix.     */
+    uint16_t numCols;     /**< number of columns of the matrix.  */
+    q31_t *pData;         /**< points to the data of the matrix. */
+  } arm_matrix_instance_q31;
+
+
+  /**
+   * @brief Floating-point matrix addition.
+   * @param[in]  pSrcA  points to the first input matrix structure
+   * @param[in]  pSrcB  points to the second input matrix structure
+   * @param[out] pDst   points to output matrix structure
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_add_f32(
+  const arm_matrix_instance_f32 * pSrcA,
+  const arm_matrix_instance_f32 * pSrcB,
+  arm_matrix_instance_f32 * pDst);
+
+
+  /**
+   * @brief Q15 matrix addition.
+   * @param[in]   pSrcA  points to the first input matrix structure
+   * @param[in]   pSrcB  points to the second input matrix structure
+   * @param[out]  pDst   points to output matrix structure
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_add_q15(
+  const arm_matrix_instance_q15 * pSrcA,
+  const arm_matrix_instance_q15 * pSrcB,
+  arm_matrix_instance_q15 * pDst);
+
+
+  /**
+   * @brief Q31 matrix addition.
+   * @param[in]  pSrcA  points to the first input matrix structure
+   * @param[in]  pSrcB  points to the second input matrix structure
+   * @param[out] pDst   points to output matrix structure
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_add_q31(
+  const arm_matrix_instance_q31 * pSrcA,
+  const arm_matrix_instance_q31 * pSrcB,
+  arm_matrix_instance_q31 * pDst);
+
+
+  /**
+   * @brief Floating-point, complex, matrix multiplication.
+   * @param[in]  pSrcA  points to the first input matrix structure
+   * @param[in]  pSrcB  points to the second input matrix structure
+   * @param[out] pDst   points to output matrix structure
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_cmplx_mult_f32(
+  const arm_matrix_instance_f32 * pSrcA,
+  const arm_matrix_instance_f32 * pSrcB,
+  arm_matrix_instance_f32 * pDst);
+
+
+  /**
+   * @brief Q15, complex,  matrix multiplication.
+   * @param[in]  pSrcA  points to the first input matrix structure
+   * @param[in]  pSrcB  points to the second input matrix structure
+   * @param[out] pDst   points to output matrix structure
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_cmplx_mult_q15(
+  const arm_matrix_instance_q15 * pSrcA,
+  const arm_matrix_instance_q15 * pSrcB,
+  arm_matrix_instance_q15 * pDst,
+  q15_t * pScratch);
+
+
+  /**
+   * @brief Q31, complex, matrix multiplication.
+   * @param[in]  pSrcA  points to the first input matrix structure
+   * @param[in]  pSrcB  points to the second input matrix structure
+   * @param[out] pDst   points to output matrix structure
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_cmplx_mult_q31(
+  const arm_matrix_instance_q31 * pSrcA,
+  const arm_matrix_instance_q31 * pSrcB,
+  arm_matrix_instance_q31 * pDst);
+
+
+  /**
+   * @brief Floating-point matrix transpose.
+   * @param[in]  pSrc  points to the input matrix
+   * @param[out] pDst  points to the output matrix
+   * @return    The function returns either  <code>ARM_MATH_SIZE_MISMATCH</code>
+   * or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_trans_f32(
+  const arm_matrix_instance_f32 * pSrc,
+  arm_matrix_instance_f32 * pDst);
+
+
+  /**
+   * @brief Q15 matrix transpose.
+   * @param[in]  pSrc  points to the input matrix
+   * @param[out] pDst  points to the output matrix
+   * @return    The function returns either  <code>ARM_MATH_SIZE_MISMATCH</code>
+   * or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_trans_q15(
+  const arm_matrix_instance_q15 * pSrc,
+  arm_matrix_instance_q15 * pDst);
+
+
+  /**
+   * @brief Q31 matrix transpose.
+   * @param[in]  pSrc  points to the input matrix
+   * @param[out] pDst  points to the output matrix
+   * @return    The function returns either  <code>ARM_MATH_SIZE_MISMATCH</code>
+   * or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_trans_q31(
+  const arm_matrix_instance_q31 * pSrc,
+  arm_matrix_instance_q31 * pDst);
+
+
+  /**
+   * @brief Floating-point matrix multiplication
+   * @param[in]  pSrcA  points to the first input matrix structure
+   * @param[in]  pSrcB  points to the second input matrix structure
+   * @param[out] pDst   points to output matrix structure
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_mult_f32(
+  const arm_matrix_instance_f32 * pSrcA,
+  const arm_matrix_instance_f32 * pSrcB,
+  arm_matrix_instance_f32 * pDst);
+
+
+  /**
+   * @brief Q15 matrix multiplication
+   * @param[in]  pSrcA   points to the first input matrix structure
+   * @param[in]  pSrcB   points to the second input matrix structure
+   * @param[out] pDst    points to output matrix structure
+   * @param[in]  pState  points to the array for storing intermediate results
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_mult_q15(
+  const arm_matrix_instance_q15 * pSrcA,
+  const arm_matrix_instance_q15 * pSrcB,
+  arm_matrix_instance_q15 * pDst,
+  q15_t * pState);
+
+
+  /**
+   * @brief Q15 matrix multiplication (fast variant) for Cortex-M3 and Cortex-M4
+   * @param[in]  pSrcA   points to the first input matrix structure
+   * @param[in]  pSrcB   points to the second input matrix structure
+   * @param[out] pDst    points to output matrix structure
+   * @param[in]  pState  points to the array for storing intermediate results
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_mult_fast_q15(
+  const arm_matrix_instance_q15 * pSrcA,
+  const arm_matrix_instance_q15 * pSrcB,
+  arm_matrix_instance_q15 * pDst,
+  q15_t * pState);
+
+
+  /**
+   * @brief Q31 matrix multiplication
+   * @param[in]  pSrcA  points to the first input matrix structure
+   * @param[in]  pSrcB  points to the second input matrix structure
+   * @param[out] pDst   points to output matrix structure
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_mult_q31(
+  const arm_matrix_instance_q31 * pSrcA,
+  const arm_matrix_instance_q31 * pSrcB,
+  arm_matrix_instance_q31 * pDst);
+
+
+  /**
+   * @brief Q31 matrix multiplication (fast variant) for Cortex-M3 and Cortex-M4
+   * @param[in]  pSrcA  points to the first input matrix structure
+   * @param[in]  pSrcB  points to the second input matrix structure
+   * @param[out] pDst   points to output matrix structure
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_mult_fast_q31(
+  const arm_matrix_instance_q31 * pSrcA,
+  const arm_matrix_instance_q31 * pSrcB,
+  arm_matrix_instance_q31 * pDst);
+
+
+  /**
+   * @brief Floating-point matrix subtraction
+   * @param[in]  pSrcA  points to the first input matrix structure
+   * @param[in]  pSrcB  points to the second input matrix structure
+   * @param[out] pDst   points to output matrix structure
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_sub_f32(
+  const arm_matrix_instance_f32 * pSrcA,
+  const arm_matrix_instance_f32 * pSrcB,
+  arm_matrix_instance_f32 * pDst);
+
+
+  /**
+   * @brief Q15 matrix subtraction
+   * @param[in]  pSrcA  points to the first input matrix structure
+   * @param[in]  pSrcB  points to the second input matrix structure
+   * @param[out] pDst   points to output matrix structure
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_sub_q15(
+  const arm_matrix_instance_q15 * pSrcA,
+  const arm_matrix_instance_q15 * pSrcB,
+  arm_matrix_instance_q15 * pDst);
+
+
+  /**
+   * @brief Q31 matrix subtraction
+   * @param[in]  pSrcA  points to the first input matrix structure
+   * @param[in]  pSrcB  points to the second input matrix structure
+   * @param[out] pDst   points to output matrix structure
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_sub_q31(
+  const arm_matrix_instance_q31 * pSrcA,
+  const arm_matrix_instance_q31 * pSrcB,
+  arm_matrix_instance_q31 * pDst);
+
+
+  /**
+   * @brief Floating-point matrix scaling.
+   * @param[in]  pSrc   points to the input matrix
+   * @param[in]  scale  scale factor
+   * @param[out] pDst   points to the output matrix
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_scale_f32(
+  const arm_matrix_instance_f32 * pSrc,
+  float32_t scale,
+  arm_matrix_instance_f32 * pDst);
+
+
+  /**
+   * @brief Q15 matrix scaling.
+   * @param[in]  pSrc        points to input matrix
+   * @param[in]  scaleFract  fractional portion of the scale factor
+   * @param[in]  shift       number of bits to shift the result by
+   * @param[out] pDst        points to output matrix
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_scale_q15(
+  const arm_matrix_instance_q15 * pSrc,
+  q15_t scaleFract,
+  int32_t shift,
+  arm_matrix_instance_q15 * pDst);
+
+
+  /**
+   * @brief Q31 matrix scaling.
+   * @param[in]  pSrc        points to input matrix
+   * @param[in]  scaleFract  fractional portion of the scale factor
+   * @param[in]  shift       number of bits to shift the result by
+   * @param[out] pDst        points to output matrix structure
+   * @return     The function returns either
+   * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
+   */
+  arm_status arm_mat_scale_q31(
+  const arm_matrix_instance_q31 * pSrc,
+  q31_t scaleFract,
+  int32_t shift,
+  arm_matrix_instance_q31 * pDst);
+
+
+  /**
+   * @brief  Q31 matrix initialization.
+   * @param[in,out] S         points to an instance of the floating-point matrix structure.
+   * @param[in]     nRows     number of rows in the matrix.
+   * @param[in]     nColumns  number of columns in the matrix.
+   * @param[in]     pData     points to the matrix data array.
+   */
+  void arm_mat_init_q31(
+  arm_matrix_instance_q31 * S,
+  uint16_t nRows,
+  uint16_t nColumns,
+  q31_t * pData);
+
+
+  /**
+   * @brief  Q15 matrix initialization.
+   * @param[in,out] S         points to an instance of the floating-point matrix structure.
+   * @param[in]     nRows     number of rows in the matrix.
+   * @param[in]     nColumns  number of columns in the matrix.
+   * @param[in]     pData     points to the matrix data array.
+   */
+  void arm_mat_init_q15(
+  arm_matrix_instance_q15 * S,
+  uint16_t nRows,
+  uint16_t nColumns,
+  q15_t * pData);
+
+
+  /**
+   * @brief  Floating-point matrix initialization.
+   * @param[in,out] S         points to an instance of the floating-point matrix structure.
+   * @param[in]     nRows     number of rows in the matrix.
+   * @param[in]     nColumns  number of columns in the matrix.
+   * @param[in]     pData     points to the matrix data array.
+   */
+  void arm_mat_init_f32(
+  arm_matrix_instance_f32 * S,
+  uint16_t nRows,
+  uint16_t nColumns,
+  float32_t * pData);
+
+
+
+  /**
+   * @brief Instance structure for the Q15 PID Control.
+   */
+  typedef struct
+  {
+    q15_t A0;           /**< The derived gain, A0 = Kp + Ki + Kd . */
+#if !defined (ARM_MATH_DSP)
+    q15_t A1;
+    q15_t A2;
+#else
+    q31_t A1;           /**< The derived gain A1 = -Kp - 2Kd | Kd.*/
+#endif
+    q15_t state[3];     /**< The state array of length 3. */
+    q15_t Kp;           /**< The proportional gain. */
+    q15_t Ki;           /**< The integral gain. */
+    q15_t Kd;           /**< The derivative gain. */
+  } arm_pid_instance_q15;
+
+  /**
+   * @brief Instance structure for the Q31 PID Control.
+   */
+  typedef struct
+  {
+    q31_t A0;            /**< The derived gain, A0 = Kp + Ki + Kd . */
+    q31_t A1;            /**< The derived gain, A1 = -Kp - 2Kd. */
+    q31_t A2;            /**< The derived gain, A2 = Kd . */
+    q31_t state[3];      /**< The state array of length 3. */
+    q31_t Kp;            /**< The proportional gain. */
+    q31_t Ki;            /**< The integral gain. */
+    q31_t Kd;            /**< The derivative gain. */
+  } arm_pid_instance_q31;
+
+  /**
+   * @brief Instance structure for the floating-point PID Control.
+   */
+  typedef struct
+  {
+    float32_t A0;          /**< The derived gain, A0 = Kp + Ki + Kd . */
+    float32_t A1;          /**< The derived gain, A1 = -Kp - 2Kd. */
+    float32_t A2;          /**< The derived gain, A2 = Kd . */
+    float32_t state[3];    /**< The state array of length 3. */
+    float32_t Kp;          /**< The proportional gain. */
+    float32_t Ki;          /**< The integral gain. */
+    float32_t Kd;          /**< The derivative gain. */
+  } arm_pid_instance_f32;
+
+
+
+  /**
+   * @brief  Initialization function for the floating-point PID Control.
+   * @param[in,out] S               points to an instance of the PID structure.
+   * @param[in]     resetStateFlag  flag to reset the state. 0 = no change in state 1 = reset the state.
+   */
+  void arm_pid_init_f32(
+  arm_pid_instance_f32 * S,
+  int32_t resetStateFlag);
+
+
+  /**
+   * @brief  Reset function for the floating-point PID Control.
+   * @param[in,out] S  is an instance of the floating-point PID Control structure
+   */
+  void arm_pid_reset_f32(
+  arm_pid_instance_f32 * S);
+
+
+  /**
+   * @brief  Initialization function for the Q31 PID Control.
+   * @param[in,out] S               points to an instance of the Q15 PID structure.
+   * @param[in]     resetStateFlag  flag to reset the state. 0 = no change in state 1 = reset the state.
+   */
+  void arm_pid_init_q31(
+  arm_pid_instance_q31 * S,
+  int32_t resetStateFlag);
+
+
+  /**
+   * @brief  Reset function for the Q31 PID Control.
+   * @param[in,out] S   points to an instance of the Q31 PID Control structure
+   */
+
+  void arm_pid_reset_q31(
+  arm_pid_instance_q31 * S);
+
+
+  /**
+   * @brief  Initialization function for the Q15 PID Control.
+   * @param[in,out] S               points to an instance of the Q15 PID structure.
+   * @param[in]     resetStateFlag  flag to reset the state. 0 = no change in state 1 = reset the state.
+   */
+  void arm_pid_init_q15(
+  arm_pid_instance_q15 * S,
+  int32_t resetStateFlag);
+
+
+  /**
+   * @brief  Reset function for the Q15 PID Control.
+   * @param[in,out] S  points to an instance of the q15 PID Control structure
+   */
+  void arm_pid_reset_q15(
+  arm_pid_instance_q15 * S);
+
+
+  /**
+   * @brief Instance structure for the floating-point Linear Interpolate function.
+   */
+  typedef struct
+  {
+    uint32_t nValues;           /**< nValues */
+    float32_t x1;               /**< x1 */
+    float32_t xSpacing;         /**< xSpacing */
+    float32_t *pYData;          /**< pointer to the table of Y values */
+  } arm_linear_interp_instance_f32;
+
+  /**
+   * @brief Instance structure for the floating-point bilinear interpolation function.
+   */
+  typedef struct
+  {
+    uint16_t numRows;   /**< number of rows in the data table. */
+    uint16_t numCols;   /**< number of columns in the data table. */
+    float32_t *pData;   /**< points to the data table. */
+  } arm_bilinear_interp_instance_f32;
+
+   /**
+   * @brief Instance structure for the Q31 bilinear interpolation function.
+   */
+  typedef struct
+  {
+    uint16_t numRows;   /**< number of rows in the data table. */
+    uint16_t numCols;   /**< number of columns in the data table. */
+    q31_t *pData;       /**< points to the data table. */
+  } arm_bilinear_interp_instance_q31;
+
+   /**
+   * @brief Instance structure for the Q15 bilinear interpolation function.
+   */
+  typedef struct
+  {
+    uint16_t numRows;   /**< number of rows in the data table. */
+    uint16_t numCols;   /**< number of columns in the data table. */
+    q15_t *pData;       /**< points to the data table. */
+  } arm_bilinear_interp_instance_q15;
+
+   /**
+   * @brief Instance structure for the Q15 bilinear interpolation function.
+   */
+  typedef struct
+  {
+    uint16_t numRows;   /**< number of rows in the data table. */
+    uint16_t numCols;   /**< number of columns in the data table. */
+    q7_t *pData;        /**< points to the data table. */
+  } arm_bilinear_interp_instance_q7;
+
+
+  /**
+   * @brief Q7 vector multiplication.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_mult_q7(
+  q7_t * pSrcA,
+  q7_t * pSrcB,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Q15 vector multiplication.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_mult_q15(
+  q15_t * pSrcA,
+  q15_t * pSrcB,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Q31 vector multiplication.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_mult_q31(
+  q31_t * pSrcA,
+  q31_t * pSrcB,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Floating-point vector multiplication.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_mult_f32(
+  float32_t * pSrcA,
+  float32_t * pSrcB,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Instance structure for the Q15 CFFT/CIFFT function.
+   */
+  typedef struct
+  {
+    uint16_t fftLen;                 /**< length of the FFT. */
+    uint8_t ifftFlag;                /**< flag that selects forward (ifftFlag=0) or inverse (ifftFlag=1) transform. */
+    uint8_t bitReverseFlag;          /**< flag that enables (bitReverseFlag=1) or disables (bitReverseFlag=0) bit reversal of output. */
+    q15_t *pTwiddle;                 /**< points to the Sin twiddle factor table. */
+    uint16_t *pBitRevTable;          /**< points to the bit reversal table. */
+    uint16_t twidCoefModifier;       /**< twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table. */
+    uint16_t bitRevFactor;           /**< bit reversal modifier that supports different size FFTs with the same bit reversal table. */
+  } arm_cfft_radix2_instance_q15;
+
+/* Deprecated */
+  arm_status arm_cfft_radix2_init_q15(
+  arm_cfft_radix2_instance_q15 * S,
+  uint16_t fftLen,
+  uint8_t ifftFlag,
+  uint8_t bitReverseFlag);
+
+/* Deprecated */
+  void arm_cfft_radix2_q15(
+  const arm_cfft_radix2_instance_q15 * S,
+  q15_t * pSrc);
+
+
+  /**
+   * @brief Instance structure for the Q15 CFFT/CIFFT function.
+   */
+  typedef struct
+  {
+    uint16_t fftLen;                 /**< length of the FFT. */
+    uint8_t ifftFlag;                /**< flag that selects forward (ifftFlag=0) or inverse (ifftFlag=1) transform. */
+    uint8_t bitReverseFlag;          /**< flag that enables (bitReverseFlag=1) or disables (bitReverseFlag=0) bit reversal of output. */
+    q15_t *pTwiddle;                 /**< points to the twiddle factor table. */
+    uint16_t *pBitRevTable;          /**< points to the bit reversal table. */
+    uint16_t twidCoefModifier;       /**< twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table. */
+    uint16_t bitRevFactor;           /**< bit reversal modifier that supports different size FFTs with the same bit reversal table. */
+  } arm_cfft_radix4_instance_q15;
+
+/* Deprecated */
+  arm_status arm_cfft_radix4_init_q15(
+  arm_cfft_radix4_instance_q15 * S,
+  uint16_t fftLen,
+  uint8_t ifftFlag,
+  uint8_t bitReverseFlag);
+
+/* Deprecated */
+  void arm_cfft_radix4_q15(
+  const arm_cfft_radix4_instance_q15 * S,
+  q15_t * pSrc);
+
+  /**
+   * @brief Instance structure for the Radix-2 Q31 CFFT/CIFFT function.
+   */
+  typedef struct
+  {
+    uint16_t fftLen;                 /**< length of the FFT. */
+    uint8_t ifftFlag;                /**< flag that selects forward (ifftFlag=0) or inverse (ifftFlag=1) transform. */
+    uint8_t bitReverseFlag;          /**< flag that enables (bitReverseFlag=1) or disables (bitReverseFlag=0) bit reversal of output. */
+    q31_t *pTwiddle;                 /**< points to the Twiddle factor table. */
+    uint16_t *pBitRevTable;          /**< points to the bit reversal table. */
+    uint16_t twidCoefModifier;       /**< twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table. */
+    uint16_t bitRevFactor;           /**< bit reversal modifier that supports different size FFTs with the same bit reversal table. */
+  } arm_cfft_radix2_instance_q31;
+
+/* Deprecated */
+  arm_status arm_cfft_radix2_init_q31(
+  arm_cfft_radix2_instance_q31 * S,
+  uint16_t fftLen,
+  uint8_t ifftFlag,
+  uint8_t bitReverseFlag);
+
+/* Deprecated */
+  void arm_cfft_radix2_q31(
+  const arm_cfft_radix2_instance_q31 * S,
+  q31_t * pSrc);
+
+  /**
+   * @brief Instance structure for the Q31 CFFT/CIFFT function.
+   */
+  typedef struct
+  {
+    uint16_t fftLen;                 /**< length of the FFT. */
+    uint8_t ifftFlag;                /**< flag that selects forward (ifftFlag=0) or inverse (ifftFlag=1) transform. */
+    uint8_t bitReverseFlag;          /**< flag that enables (bitReverseFlag=1) or disables (bitReverseFlag=0) bit reversal of output. */
+    q31_t *pTwiddle;                 /**< points to the twiddle factor table. */
+    uint16_t *pBitRevTable;          /**< points to the bit reversal table. */
+    uint16_t twidCoefModifier;       /**< twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table. */
+    uint16_t bitRevFactor;           /**< bit reversal modifier that supports different size FFTs with the same bit reversal table. */
+  } arm_cfft_radix4_instance_q31;
+
+/* Deprecated */
+  void arm_cfft_radix4_q31(
+  const arm_cfft_radix4_instance_q31 * S,
+  q31_t * pSrc);
+
+/* Deprecated */
+  arm_status arm_cfft_radix4_init_q31(
+  arm_cfft_radix4_instance_q31 * S,
+  uint16_t fftLen,
+  uint8_t ifftFlag,
+  uint8_t bitReverseFlag);
+
+  /**
+   * @brief Instance structure for the floating-point CFFT/CIFFT function.
+   */
+  typedef struct
+  {
+    uint16_t fftLen;                   /**< length of the FFT. */
+    uint8_t ifftFlag;                  /**< flag that selects forward (ifftFlag=0) or inverse (ifftFlag=1) transform. */
+    uint8_t bitReverseFlag;            /**< flag that enables (bitReverseFlag=1) or disables (bitReverseFlag=0) bit reversal of output. */
+    float32_t *pTwiddle;               /**< points to the Twiddle factor table. */
+    uint16_t *pBitRevTable;            /**< points to the bit reversal table. */
+    uint16_t twidCoefModifier;         /**< twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table. */
+    uint16_t bitRevFactor;             /**< bit reversal modifier that supports different size FFTs with the same bit reversal table. */
+    float32_t onebyfftLen;             /**< value of 1/fftLen. */
+  } arm_cfft_radix2_instance_f32;
+
+/* Deprecated */
+  arm_status arm_cfft_radix2_init_f32(
+  arm_cfft_radix2_instance_f32 * S,
+  uint16_t fftLen,
+  uint8_t ifftFlag,
+  uint8_t bitReverseFlag);
+
+/* Deprecated */
+  void arm_cfft_radix2_f32(
+  const arm_cfft_radix2_instance_f32 * S,
+  float32_t * pSrc);
+
+  /**
+   * @brief Instance structure for the floating-point CFFT/CIFFT function.
+   */
+  typedef struct
+  {
+    uint16_t fftLen;                   /**< length of the FFT. */
+    uint8_t ifftFlag;                  /**< flag that selects forward (ifftFlag=0) or inverse (ifftFlag=1) transform. */
+    uint8_t bitReverseFlag;            /**< flag that enables (bitReverseFlag=1) or disables (bitReverseFlag=0) bit reversal of output. */
+    float32_t *pTwiddle;               /**< points to the Twiddle factor table. */
+    uint16_t *pBitRevTable;            /**< points to the bit reversal table. */
+    uint16_t twidCoefModifier;         /**< twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table. */
+    uint16_t bitRevFactor;             /**< bit reversal modifier that supports different size FFTs with the same bit reversal table. */
+    float32_t onebyfftLen;             /**< value of 1/fftLen. */
+  } arm_cfft_radix4_instance_f32;
+
+/* Deprecated */
+  arm_status arm_cfft_radix4_init_f32(
+  arm_cfft_radix4_instance_f32 * S,
+  uint16_t fftLen,
+  uint8_t ifftFlag,
+  uint8_t bitReverseFlag);
+
+/* Deprecated */
+  void arm_cfft_radix4_f32(
+  const arm_cfft_radix4_instance_f32 * S,
+  float32_t * pSrc);
+
+  /**
+   * @brief Instance structure for the fixed-point CFFT/CIFFT function.
+   */
+  typedef struct
+  {
+    uint16_t fftLen;                   /**< length of the FFT. */
+    const q15_t *pTwiddle;             /**< points to the Twiddle factor table. */
+    const uint16_t *pBitRevTable;      /**< points to the bit reversal table. */
+    uint16_t bitRevLength;             /**< bit reversal table length. */
+  } arm_cfft_instance_q15;
+
+void arm_cfft_q15(
+    const arm_cfft_instance_q15 * S,
+    q15_t * p1,
+    uint8_t ifftFlag,
+    uint8_t bitReverseFlag);
+
+  /**
+   * @brief Instance structure for the fixed-point CFFT/CIFFT function.
+   */
+  typedef struct
+  {
+    uint16_t fftLen;                   /**< length of the FFT. */
+    const q31_t *pTwiddle;             /**< points to the Twiddle factor table. */
+    const uint16_t *pBitRevTable;      /**< points to the bit reversal table. */
+    uint16_t bitRevLength;             /**< bit reversal table length. */
+  } arm_cfft_instance_q31;
+
+void arm_cfft_q31(
+    const arm_cfft_instance_q31 * S,
+    q31_t * p1,
+    uint8_t ifftFlag,
+    uint8_t bitReverseFlag);
+
+  /**
+   * @brief Instance structure for the floating-point CFFT/CIFFT function.
+   */
+  typedef struct
+  {
+    uint16_t fftLen;                   /**< length of the FFT. */
+    const float32_t *pTwiddle;         /**< points to the Twiddle factor table. */
+    const uint16_t *pBitRevTable;      /**< points to the bit reversal table. */
+    uint16_t bitRevLength;             /**< bit reversal table length. */
+  } arm_cfft_instance_f32;
+
+  void arm_cfft_f32(
+  const arm_cfft_instance_f32 * S,
+  float32_t * p1,
+  uint8_t ifftFlag,
+  uint8_t bitReverseFlag);
+
+  /**
+   * @brief Instance structure for the Q15 RFFT/RIFFT function.
+   */
+  typedef struct
+  {
+    uint32_t fftLenReal;                      /**< length of the real FFT. */
+    uint8_t ifftFlagR;                        /**< flag that selects forward (ifftFlagR=0) or inverse (ifftFlagR=1) transform. */
+    uint8_t bitReverseFlagR;                  /**< flag that enables (bitReverseFlagR=1) or disables (bitReverseFlagR=0) bit reversal of output. */
+    uint32_t twidCoefRModifier;               /**< twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table. */
+    q15_t *pTwiddleAReal;                     /**< points to the real twiddle factor table. */
+    q15_t *pTwiddleBReal;                     /**< points to the imag twiddle factor table. */
+    const arm_cfft_instance_q15 *pCfft;       /**< points to the complex FFT instance. */
+  } arm_rfft_instance_q15;
+
+  arm_status arm_rfft_init_q15(
+  arm_rfft_instance_q15 * S,
+  uint32_t fftLenReal,
+  uint32_t ifftFlagR,
+  uint32_t bitReverseFlag);
+
+  void arm_rfft_q15(
+  const arm_rfft_instance_q15 * S,
+  q15_t * pSrc,
+  q15_t * pDst);
+
+  /**
+   * @brief Instance structure for the Q31 RFFT/RIFFT function.
+   */
+  typedef struct
+  {
+    uint32_t fftLenReal;                        /**< length of the real FFT. */
+    uint8_t ifftFlagR;                          /**< flag that selects forward (ifftFlagR=0) or inverse (ifftFlagR=1) transform. */
+    uint8_t bitReverseFlagR;                    /**< flag that enables (bitReverseFlagR=1) or disables (bitReverseFlagR=0) bit reversal of output. */
+    uint32_t twidCoefRModifier;                 /**< twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table. */
+    q31_t *pTwiddleAReal;                       /**< points to the real twiddle factor table. */
+    q31_t *pTwiddleBReal;                       /**< points to the imag twiddle factor table. */
+    const arm_cfft_instance_q31 *pCfft;         /**< points to the complex FFT instance. */
+  } arm_rfft_instance_q31;
+
+  arm_status arm_rfft_init_q31(
+  arm_rfft_instance_q31 * S,
+  uint32_t fftLenReal,
+  uint32_t ifftFlagR,
+  uint32_t bitReverseFlag);
+
+  void arm_rfft_q31(
+  const arm_rfft_instance_q31 * S,
+  q31_t * pSrc,
+  q31_t * pDst);
+
+  /**
+   * @brief Instance structure for the floating-point RFFT/RIFFT function.
+   */
+  typedef struct
+  {
+    uint32_t fftLenReal;                        /**< length of the real FFT. */
+    uint16_t fftLenBy2;                         /**< length of the complex FFT. */
+    uint8_t ifftFlagR;                          /**< flag that selects forward (ifftFlagR=0) or inverse (ifftFlagR=1) transform. */
+    uint8_t bitReverseFlagR;                    /**< flag that enables (bitReverseFlagR=1) or disables (bitReverseFlagR=0) bit reversal of output. */
+    uint32_t twidCoefRModifier;                     /**< twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table. */
+    float32_t *pTwiddleAReal;                   /**< points to the real twiddle factor table. */
+    float32_t *pTwiddleBReal;                   /**< points to the imag twiddle factor table. */
+    arm_cfft_radix4_instance_f32 *pCfft;        /**< points to the complex FFT instance. */
+  } arm_rfft_instance_f32;
+
+  arm_status arm_rfft_init_f32(
+  arm_rfft_instance_f32 * S,
+  arm_cfft_radix4_instance_f32 * S_CFFT,
+  uint32_t fftLenReal,
+  uint32_t ifftFlagR,
+  uint32_t bitReverseFlag);
+
+  void arm_rfft_f32(
+  const arm_rfft_instance_f32 * S,
+  float32_t * pSrc,
+  float32_t * pDst);
+
+  /**
+   * @brief Instance structure for the floating-point RFFT/RIFFT function.
+   */
+typedef struct
+  {
+    arm_cfft_instance_f32 Sint;      /**< Internal CFFT structure. */
+    uint16_t fftLenRFFT;             /**< length of the real sequence */
+    float32_t * pTwiddleRFFT;        /**< Twiddle factors real stage  */
+  } arm_rfft_fast_instance_f32 ;
+
+arm_status arm_rfft_fast_init_f32 (
+   arm_rfft_fast_instance_f32 * S,
+   uint16_t fftLen);
+
+void arm_rfft_fast_f32(
+  arm_rfft_fast_instance_f32 * S,
+  float32_t * p, float32_t * pOut,
+  uint8_t ifftFlag);
+
+  /**
+   * @brief Instance structure for the floating-point DCT4/IDCT4 function.
+   */
+  typedef struct
+  {
+    uint16_t N;                          /**< length of the DCT4. */
+    uint16_t Nby2;                       /**< half of the length of the DCT4. */
+    float32_t normalize;                 /**< normalizing factor. */
+    float32_t *pTwiddle;                 /**< points to the twiddle factor table. */
+    float32_t *pCosFactor;               /**< points to the cosFactor table. */
+    arm_rfft_instance_f32 *pRfft;        /**< points to the real FFT instance. */
+    arm_cfft_radix4_instance_f32 *pCfft; /**< points to the complex FFT instance. */
+  } arm_dct4_instance_f32;
+
+
+  /**
+   * @brief  Initialization function for the floating-point DCT4/IDCT4.
+   * @param[in,out] S          points to an instance of floating-point DCT4/IDCT4 structure.
+   * @param[in]     S_RFFT     points to an instance of floating-point RFFT/RIFFT structure.
+   * @param[in]     S_CFFT     points to an instance of floating-point CFFT/CIFFT structure.
+   * @param[in]     N          length of the DCT4.
+   * @param[in]     Nby2       half of the length of the DCT4.
+   * @param[in]     normalize  normalizing factor.
+   * @return      arm_status function returns ARM_MATH_SUCCESS if initialization is successful or ARM_MATH_ARGUMENT_ERROR if <code>fftLenReal</code> is not a supported transform length.
+   */
+  arm_status arm_dct4_init_f32(
+  arm_dct4_instance_f32 * S,
+  arm_rfft_instance_f32 * S_RFFT,
+  arm_cfft_radix4_instance_f32 * S_CFFT,
+  uint16_t N,
+  uint16_t Nby2,
+  float32_t normalize);
+
+
+  /**
+   * @brief Processing function for the floating-point DCT4/IDCT4.
+   * @param[in]     S              points to an instance of the floating-point DCT4/IDCT4 structure.
+   * @param[in]     pState         points to state buffer.
+   * @param[in,out] pInlineBuffer  points to the in-place input and output buffer.
+   */
+  void arm_dct4_f32(
+  const arm_dct4_instance_f32 * S,
+  float32_t * pState,
+  float32_t * pInlineBuffer);
+
+
+  /**
+   * @brief Instance structure for the Q31 DCT4/IDCT4 function.
+   */
+  typedef struct
+  {
+    uint16_t N;                          /**< length of the DCT4. */
+    uint16_t Nby2;                       /**< half of the length of the DCT4. */
+    q31_t normalize;                     /**< normalizing factor. */
+    q31_t *pTwiddle;                     /**< points to the twiddle factor table. */
+    q31_t *pCosFactor;                   /**< points to the cosFactor table. */
+    arm_rfft_instance_q31 *pRfft;        /**< points to the real FFT instance. */
+    arm_cfft_radix4_instance_q31 *pCfft; /**< points to the complex FFT instance. */
+  } arm_dct4_instance_q31;
+
+
+  /**
+   * @brief  Initialization function for the Q31 DCT4/IDCT4.
+   * @param[in,out] S          points to an instance of Q31 DCT4/IDCT4 structure.
+   * @param[in]     S_RFFT     points to an instance of Q31 RFFT/RIFFT structure
+   * @param[in]     S_CFFT     points to an instance of Q31 CFFT/CIFFT structure
+   * @param[in]     N          length of the DCT4.
+   * @param[in]     Nby2       half of the length of the DCT4.
+   * @param[in]     normalize  normalizing factor.
+   * @return      arm_status function returns ARM_MATH_SUCCESS if initialization is successful or ARM_MATH_ARGUMENT_ERROR if <code>N</code> is not a supported transform length.
+   */
+  arm_status arm_dct4_init_q31(
+  arm_dct4_instance_q31 * S,
+  arm_rfft_instance_q31 * S_RFFT,
+  arm_cfft_radix4_instance_q31 * S_CFFT,
+  uint16_t N,
+  uint16_t Nby2,
+  q31_t normalize);
+
+
+  /**
+   * @brief Processing function for the Q31 DCT4/IDCT4.
+   * @param[in]     S              points to an instance of the Q31 DCT4 structure.
+   * @param[in]     pState         points to state buffer.
+   * @param[in,out] pInlineBuffer  points to the in-place input and output buffer.
+   */
+  void arm_dct4_q31(
+  const arm_dct4_instance_q31 * S,
+  q31_t * pState,
+  q31_t * pInlineBuffer);
+
+
+  /**
+   * @brief Instance structure for the Q15 DCT4/IDCT4 function.
+   */
+  typedef struct
+  {
+    uint16_t N;                          /**< length of the DCT4. */
+    uint16_t Nby2;                       /**< half of the length of the DCT4. */
+    q15_t normalize;                     /**< normalizing factor. */
+    q15_t *pTwiddle;                     /**< points to the twiddle factor table. */
+    q15_t *pCosFactor;                   /**< points to the cosFactor table. */
+    arm_rfft_instance_q15 *pRfft;        /**< points to the real FFT instance. */
+    arm_cfft_radix4_instance_q15 *pCfft; /**< points to the complex FFT instance. */
+  } arm_dct4_instance_q15;
+
+
+  /**
+   * @brief  Initialization function for the Q15 DCT4/IDCT4.
+   * @param[in,out] S          points to an instance of Q15 DCT4/IDCT4 structure.
+   * @param[in]     S_RFFT     points to an instance of Q15 RFFT/RIFFT structure.
+   * @param[in]     S_CFFT     points to an instance of Q15 CFFT/CIFFT structure.
+   * @param[in]     N          length of the DCT4.
+   * @param[in]     Nby2       half of the length of the DCT4.
+   * @param[in]     normalize  normalizing factor.
+   * @return      arm_status function returns ARM_MATH_SUCCESS if initialization is successful or ARM_MATH_ARGUMENT_ERROR if <code>N</code> is not a supported transform length.
+   */
+  arm_status arm_dct4_init_q15(
+  arm_dct4_instance_q15 * S,
+  arm_rfft_instance_q15 * S_RFFT,
+  arm_cfft_radix4_instance_q15 * S_CFFT,
+  uint16_t N,
+  uint16_t Nby2,
+  q15_t normalize);
+
+
+  /**
+   * @brief Processing function for the Q15 DCT4/IDCT4.
+   * @param[in]     S              points to an instance of the Q15 DCT4 structure.
+   * @param[in]     pState         points to state buffer.
+   * @param[in,out] pInlineBuffer  points to the in-place input and output buffer.
+   */
+  void arm_dct4_q15(
+  const arm_dct4_instance_q15 * S,
+  q15_t * pState,
+  q15_t * pInlineBuffer);
+
+
+  /**
+   * @brief Floating-point vector addition.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_add_f32(
+  float32_t * pSrcA,
+  float32_t * pSrcB,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Q7 vector addition.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_add_q7(
+  q7_t * pSrcA,
+  q7_t * pSrcB,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Q15 vector addition.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_add_q15(
+  q15_t * pSrcA,
+  q15_t * pSrcB,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Q31 vector addition.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_add_q31(
+  q31_t * pSrcA,
+  q31_t * pSrcB,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Floating-point vector subtraction.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_sub_f32(
+  float32_t * pSrcA,
+  float32_t * pSrcB,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Q7 vector subtraction.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_sub_q7(
+  q7_t * pSrcA,
+  q7_t * pSrcB,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Q15 vector subtraction.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_sub_q15(
+  q15_t * pSrcA,
+  q15_t * pSrcB,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Q31 vector subtraction.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_sub_q31(
+  q31_t * pSrcA,
+  q31_t * pSrcB,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Multiplies a floating-point vector by a scalar.
+   * @param[in]  pSrc       points to the input vector
+   * @param[in]  scale      scale factor to be applied
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in the vector
+   */
+  void arm_scale_f32(
+  float32_t * pSrc,
+  float32_t scale,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Multiplies a Q7 vector by a scalar.
+   * @param[in]  pSrc        points to the input vector
+   * @param[in]  scaleFract  fractional portion of the scale value
+   * @param[in]  shift       number of bits to shift the result by
+   * @param[out] pDst        points to the output vector
+   * @param[in]  blockSize   number of samples in the vector
+   */
+  void arm_scale_q7(
+  q7_t * pSrc,
+  q7_t scaleFract,
+  int8_t shift,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Multiplies a Q15 vector by a scalar.
+   * @param[in]  pSrc        points to the input vector
+   * @param[in]  scaleFract  fractional portion of the scale value
+   * @param[in]  shift       number of bits to shift the result by
+   * @param[out] pDst        points to the output vector
+   * @param[in]  blockSize   number of samples in the vector
+   */
+  void arm_scale_q15(
+  q15_t * pSrc,
+  q15_t scaleFract,
+  int8_t shift,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Multiplies a Q31 vector by a scalar.
+   * @param[in]  pSrc        points to the input vector
+   * @param[in]  scaleFract  fractional portion of the scale value
+   * @param[in]  shift       number of bits to shift the result by
+   * @param[out] pDst        points to the output vector
+   * @param[in]  blockSize   number of samples in the vector
+   */
+  void arm_scale_q31(
+  q31_t * pSrc,
+  q31_t scaleFract,
+  int8_t shift,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Q7 vector absolute value.
+   * @param[in]  pSrc       points to the input buffer
+   * @param[out] pDst       points to the output buffer
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_abs_q7(
+  q7_t * pSrc,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Floating-point vector absolute value.
+   * @param[in]  pSrc       points to the input buffer
+   * @param[out] pDst       points to the output buffer
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_abs_f32(
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Q15 vector absolute value.
+   * @param[in]  pSrc       points to the input buffer
+   * @param[out] pDst       points to the output buffer
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_abs_q15(
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Q31 vector absolute value.
+   * @param[in]  pSrc       points to the input buffer
+   * @param[out] pDst       points to the output buffer
+   * @param[in]  blockSize  number of samples in each vector
+   */
+  void arm_abs_q31(
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Dot product of floating-point vectors.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[in]  blockSize  number of samples in each vector
+   * @param[out] result     output result returned here
+   */
+  void arm_dot_prod_f32(
+  float32_t * pSrcA,
+  float32_t * pSrcB,
+  uint32_t blockSize,
+  float32_t * result);
+
+
+  /**
+   * @brief Dot product of Q7 vectors.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[in]  blockSize  number of samples in each vector
+   * @param[out] result     output result returned here
+   */
+  void arm_dot_prod_q7(
+  q7_t * pSrcA,
+  q7_t * pSrcB,
+  uint32_t blockSize,
+  q31_t * result);
+
+
+  /**
+   * @brief Dot product of Q15 vectors.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[in]  blockSize  number of samples in each vector
+   * @param[out] result     output result returned here
+   */
+  void arm_dot_prod_q15(
+  q15_t * pSrcA,
+  q15_t * pSrcB,
+  uint32_t blockSize,
+  q63_t * result);
+
+
+  /**
+   * @brief Dot product of Q31 vectors.
+   * @param[in]  pSrcA      points to the first input vector
+   * @param[in]  pSrcB      points to the second input vector
+   * @param[in]  blockSize  number of samples in each vector
+   * @param[out] result     output result returned here
+   */
+  void arm_dot_prod_q31(
+  q31_t * pSrcA,
+  q31_t * pSrcB,
+  uint32_t blockSize,
+  q63_t * result);
+
+
+  /**
+   * @brief  Shifts the elements of a Q7 vector a specified number of bits.
+   * @param[in]  pSrc       points to the input vector
+   * @param[in]  shiftBits  number of bits to shift.  A positive value shifts left; a negative value shifts right.
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in the vector
+   */
+  void arm_shift_q7(
+  q7_t * pSrc,
+  int8_t shiftBits,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Shifts the elements of a Q15 vector a specified number of bits.
+   * @param[in]  pSrc       points to the input vector
+   * @param[in]  shiftBits  number of bits to shift.  A positive value shifts left; a negative value shifts right.
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in the vector
+   */
+  void arm_shift_q15(
+  q15_t * pSrc,
+  int8_t shiftBits,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Shifts the elements of a Q31 vector a specified number of bits.
+   * @param[in]  pSrc       points to the input vector
+   * @param[in]  shiftBits  number of bits to shift.  A positive value shifts left; a negative value shifts right.
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in the vector
+   */
+  void arm_shift_q31(
+  q31_t * pSrc,
+  int8_t shiftBits,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Adds a constant offset to a floating-point vector.
+   * @param[in]  pSrc       points to the input vector
+   * @param[in]  offset     is the offset to be added
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in the vector
+   */
+  void arm_offset_f32(
+  float32_t * pSrc,
+  float32_t offset,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Adds a constant offset to a Q7 vector.
+   * @param[in]  pSrc       points to the input vector
+   * @param[in]  offset     is the offset to be added
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in the vector
+   */
+  void arm_offset_q7(
+  q7_t * pSrc,
+  q7_t offset,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Adds a constant offset to a Q15 vector.
+   * @param[in]  pSrc       points to the input vector
+   * @param[in]  offset     is the offset to be added
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in the vector
+   */
+  void arm_offset_q15(
+  q15_t * pSrc,
+  q15_t offset,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Adds a constant offset to a Q31 vector.
+   * @param[in]  pSrc       points to the input vector
+   * @param[in]  offset     is the offset to be added
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in the vector
+   */
+  void arm_offset_q31(
+  q31_t * pSrc,
+  q31_t offset,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Negates the elements of a floating-point vector.
+   * @param[in]  pSrc       points to the input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in the vector
+   */
+  void arm_negate_f32(
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Negates the elements of a Q7 vector.
+   * @param[in]  pSrc       points to the input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in the vector
+   */
+  void arm_negate_q7(
+  q7_t * pSrc,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Negates the elements of a Q15 vector.
+   * @param[in]  pSrc       points to the input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in the vector
+   */
+  void arm_negate_q15(
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Negates the elements of a Q31 vector.
+   * @param[in]  pSrc       points to the input vector
+   * @param[out] pDst       points to the output vector
+   * @param[in]  blockSize  number of samples in the vector
+   */
+  void arm_negate_q31(
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Copies the elements of a floating-point vector.
+   * @param[in]  pSrc       input pointer
+   * @param[out] pDst       output pointer
+   * @param[in]  blockSize  number of samples to process
+   */
+  void arm_copy_f32(
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Copies the elements of a Q7 vector.
+   * @param[in]  pSrc       input pointer
+   * @param[out] pDst       output pointer
+   * @param[in]  blockSize  number of samples to process
+   */
+  void arm_copy_q7(
+  q7_t * pSrc,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Copies the elements of a Q15 vector.
+   * @param[in]  pSrc       input pointer
+   * @param[out] pDst       output pointer
+   * @param[in]  blockSize  number of samples to process
+   */
+  void arm_copy_q15(
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Copies the elements of a Q31 vector.
+   * @param[in]  pSrc       input pointer
+   * @param[out] pDst       output pointer
+   * @param[in]  blockSize  number of samples to process
+   */
+  void arm_copy_q31(
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Fills a constant value into a floating-point vector.
+   * @param[in]  value      input value to be filled
+   * @param[out] pDst       output pointer
+   * @param[in]  blockSize  number of samples to process
+   */
+  void arm_fill_f32(
+  float32_t value,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Fills a constant value into a Q7 vector.
+   * @param[in]  value      input value to be filled
+   * @param[out] pDst       output pointer
+   * @param[in]  blockSize  number of samples to process
+   */
+  void arm_fill_q7(
+  q7_t value,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Fills a constant value into a Q15 vector.
+   * @param[in]  value      input value to be filled
+   * @param[out] pDst       output pointer
+   * @param[in]  blockSize  number of samples to process
+   */
+  void arm_fill_q15(
+  q15_t value,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Fills a constant value into a Q31 vector.
+   * @param[in]  value      input value to be filled
+   * @param[out] pDst       output pointer
+   * @param[in]  blockSize  number of samples to process
+   */
+  void arm_fill_q31(
+  q31_t value,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+/**
+ * @brief Convolution of floating-point sequences.
+ * @param[in]  pSrcA    points to the first input sequence.
+ * @param[in]  srcALen  length of the first input sequence.
+ * @param[in]  pSrcB    points to the second input sequence.
+ * @param[in]  srcBLen  length of the second input sequence.
+ * @param[out] pDst     points to the location where the output result is written.  Length srcALen+srcBLen-1.
+ */
+  void arm_conv_f32(
+  float32_t * pSrcA,
+  uint32_t srcALen,
+  float32_t * pSrcB,
+  uint32_t srcBLen,
+  float32_t * pDst);
+
+
+  /**
+   * @brief Convolution of Q15 sequences.
+   * @param[in]  pSrcA      points to the first input sequence.
+   * @param[in]  srcALen    length of the first input sequence.
+   * @param[in]  pSrcB      points to the second input sequence.
+   * @param[in]  srcBLen    length of the second input sequence.
+   * @param[out] pDst       points to the block of output data  Length srcALen+srcBLen-1.
+   * @param[in]  pScratch1  points to scratch buffer of size max(srcALen, srcBLen) + 2*min(srcALen, srcBLen) - 2.
+   * @param[in]  pScratch2  points to scratch buffer of size min(srcALen, srcBLen).
+   */
+  void arm_conv_opt_q15(
+  q15_t * pSrcA,
+  uint32_t srcALen,
+  q15_t * pSrcB,
+  uint32_t srcBLen,
+  q15_t * pDst,
+  q15_t * pScratch1,
+  q15_t * pScratch2);
+
+
+/**
+ * @brief Convolution of Q15 sequences.
+ * @param[in]  pSrcA    points to the first input sequence.
+ * @param[in]  srcALen  length of the first input sequence.
+ * @param[in]  pSrcB    points to the second input sequence.
+ * @param[in]  srcBLen  length of the second input sequence.
+ * @param[out] pDst     points to the location where the output result is written.  Length srcALen+srcBLen-1.
+ */
+  void arm_conv_q15(
+  q15_t * pSrcA,
+  uint32_t srcALen,
+  q15_t * pSrcB,
+  uint32_t srcBLen,
+  q15_t * pDst);
+
+
+  /**
+   * @brief Convolution of Q15 sequences (fast version) for Cortex-M3 and Cortex-M4
+   * @param[in]  pSrcA    points to the first input sequence.
+   * @param[in]  srcALen  length of the first input sequence.
+   * @param[in]  pSrcB    points to the second input sequence.
+   * @param[in]  srcBLen  length of the second input sequence.
+   * @param[out] pDst     points to the block of output data  Length srcALen+srcBLen-1.
+   */
+  void arm_conv_fast_q15(
+          q15_t * pSrcA,
+          uint32_t srcALen,
+          q15_t * pSrcB,
+          uint32_t srcBLen,
+          q15_t * pDst);
+
+
+  /**
+   * @brief Convolution of Q15 sequences (fast version) for Cortex-M3 and Cortex-M4
+   * @param[in]  pSrcA      points to the first input sequence.
+   * @param[in]  srcALen    length of the first input sequence.
+   * @param[in]  pSrcB      points to the second input sequence.
+   * @param[in]  srcBLen    length of the second input sequence.
+   * @param[out] pDst       points to the block of output data  Length srcALen+srcBLen-1.
+   * @param[in]  pScratch1  points to scratch buffer of size max(srcALen, srcBLen) + 2*min(srcALen, srcBLen) - 2.
+   * @param[in]  pScratch2  points to scratch buffer of size min(srcALen, srcBLen).
+   */
+  void arm_conv_fast_opt_q15(
+  q15_t * pSrcA,
+  uint32_t srcALen,
+  q15_t * pSrcB,
+  uint32_t srcBLen,
+  q15_t * pDst,
+  q15_t * pScratch1,
+  q15_t * pScratch2);
+
+
+  /**
+   * @brief Convolution of Q31 sequences.
+   * @param[in]  pSrcA    points to the first input sequence.
+   * @param[in]  srcALen  length of the first input sequence.
+   * @param[in]  pSrcB    points to the second input sequence.
+   * @param[in]  srcBLen  length of the second input sequence.
+   * @param[out] pDst     points to the block of output data  Length srcALen+srcBLen-1.
+   */
+  void arm_conv_q31(
+  q31_t * pSrcA,
+  uint32_t srcALen,
+  q31_t * pSrcB,
+  uint32_t srcBLen,
+  q31_t * pDst);
+
+
+  /**
+   * @brief Convolution of Q31 sequences (fast version) for Cortex-M3 and Cortex-M4
+   * @param[in]  pSrcA    points to the first input sequence.
+   * @param[in]  srcALen  length of the first input sequence.
+   * @param[in]  pSrcB    points to the second input sequence.
+   * @param[in]  srcBLen  length of the second input sequence.
+   * @param[out] pDst     points to the block of output data  Length srcALen+srcBLen-1.
+   */
+  void arm_conv_fast_q31(
+  q31_t * pSrcA,
+  uint32_t srcALen,
+  q31_t * pSrcB,
+  uint32_t srcBLen,
+  q31_t * pDst);
+
+
+    /**
+   * @brief Convolution of Q7 sequences.
+   * @param[in]  pSrcA      points to the first input sequence.
+   * @param[in]  srcALen    length of the first input sequence.
+   * @param[in]  pSrcB      points to the second input sequence.
+   * @param[in]  srcBLen    length of the second input sequence.
+   * @param[out] pDst       points to the block of output data  Length srcALen+srcBLen-1.
+   * @param[in]  pScratch1  points to scratch buffer(of type q15_t) of size max(srcALen, srcBLen) + 2*min(srcALen, srcBLen) - 2.
+   * @param[in]  pScratch2  points to scratch buffer (of type q15_t) of size min(srcALen, srcBLen).
+   */
+  void arm_conv_opt_q7(
+  q7_t * pSrcA,
+  uint32_t srcALen,
+  q7_t * pSrcB,
+  uint32_t srcBLen,
+  q7_t * pDst,
+  q15_t * pScratch1,
+  q15_t * pScratch2);
+
+
+  /**
+   * @brief Convolution of Q7 sequences.
+   * @param[in]  pSrcA    points to the first input sequence.
+   * @param[in]  srcALen  length of the first input sequence.
+   * @param[in]  pSrcB    points to the second input sequence.
+   * @param[in]  srcBLen  length of the second input sequence.
+   * @param[out] pDst     points to the block of output data  Length srcALen+srcBLen-1.
+   */
+  void arm_conv_q7(
+  q7_t * pSrcA,
+  uint32_t srcALen,
+  q7_t * pSrcB,
+  uint32_t srcBLen,
+  q7_t * pDst);
+
+
+  /**
+   * @brief Partial convolution of floating-point sequences.
+   * @param[in]  pSrcA       points to the first input sequence.
+   * @param[in]  srcALen     length of the first input sequence.
+   * @param[in]  pSrcB       points to the second input sequence.
+   * @param[in]  srcBLen     length of the second input sequence.
+   * @param[out] pDst        points to the block of output data
+   * @param[in]  firstIndex  is the first output sample to start with.
+   * @param[in]  numPoints   is the number of output points to be computed.
+   * @return  Returns either ARM_MATH_SUCCESS if the function completed correctly or ARM_MATH_ARGUMENT_ERROR if the requested subset is not in the range [0 srcALen+srcBLen-2].
+   */
+  arm_status arm_conv_partial_f32(
+  float32_t * pSrcA,
+  uint32_t srcALen,
+  float32_t * pSrcB,
+  uint32_t srcBLen,
+  float32_t * pDst,
+  uint32_t firstIndex,
+  uint32_t numPoints);
+
+
+  /**
+   * @brief Partial convolution of Q15 sequences.
+   * @param[in]  pSrcA       points to the first input sequence.
+   * @param[in]  srcALen     length of the first input sequence.
+   * @param[in]  pSrcB       points to the second input sequence.
+   * @param[in]  srcBLen     length of the second input sequence.
+   * @param[out] pDst        points to the block of output data
+   * @param[in]  firstIndex  is the first output sample to start with.
+   * @param[in]  numPoints   is the number of output points to be computed.
+   * @param[in]  pScratch1   points to scratch buffer of size max(srcALen, srcBLen) + 2*min(srcALen, srcBLen) - 2.
+   * @param[in]  pScratch2   points to scratch buffer of size min(srcALen, srcBLen).
+   * @return  Returns either ARM_MATH_SUCCESS if the function completed correctly or ARM_MATH_ARGUMENT_ERROR if the requested subset is not in the range [0 srcALen+srcBLen-2].
+   */
+  arm_status arm_conv_partial_opt_q15(
+  q15_t * pSrcA,
+  uint32_t srcALen,
+  q15_t * pSrcB,
+  uint32_t srcBLen,
+  q15_t * pDst,
+  uint32_t firstIndex,
+  uint32_t numPoints,
+  q15_t * pScratch1,
+  q15_t * pScratch2);
+
+
+  /**
+   * @brief Partial convolution of Q15 sequences.
+   * @param[in]  pSrcA       points to the first input sequence.
+   * @param[in]  srcALen     length of the first input sequence.
+   * @param[in]  pSrcB       points to the second input sequence.
+   * @param[in]  srcBLen     length of the second input sequence.
+   * @param[out] pDst        points to the block of output data
+   * @param[in]  firstIndex  is the first output sample to start with.
+   * @param[in]  numPoints   is the number of output points to be computed.
+   * @return  Returns either ARM_MATH_SUCCESS if the function completed correctly or ARM_MATH_ARGUMENT_ERROR if the requested subset is not in the range [0 srcALen+srcBLen-2].
+   */
+  arm_status arm_conv_partial_q15(
+  q15_t * pSrcA,
+  uint32_t srcALen,
+  q15_t * pSrcB,
+  uint32_t srcBLen,
+  q15_t * pDst,
+  uint32_t firstIndex,
+  uint32_t numPoints);
+
+
+  /**
+   * @brief Partial convolution of Q15 sequences (fast version) for Cortex-M3 and Cortex-M4
+   * @param[in]  pSrcA       points to the first input sequence.
+   * @param[in]  srcALen     length of the first input sequence.
+   * @param[in]  pSrcB       points to the second input sequence.
+   * @param[in]  srcBLen     length of the second input sequence.
+   * @param[out] pDst        points to the block of output data
+   * @param[in]  firstIndex  is the first output sample to start with.
+   * @param[in]  numPoints   is the number of output points to be computed.
+   * @return  Returns either ARM_MATH_SUCCESS if the function completed correctly or ARM_MATH_ARGUMENT_ERROR if the requested subset is not in the range [0 srcALen+srcBLen-2].
+   */
+  arm_status arm_conv_partial_fast_q15(
+  q15_t * pSrcA,
+  uint32_t srcALen,
+  q15_t * pSrcB,
+  uint32_t srcBLen,
+  q15_t * pDst,
+  uint32_t firstIndex,
+  uint32_t numPoints);
+
+
+  /**
+   * @brief Partial convolution of Q15 sequences (fast version) for Cortex-M3 and Cortex-M4
+   * @param[in]  pSrcA       points to the first input sequence.
+   * @param[in]  srcALen     length of the first input sequence.
+   * @param[in]  pSrcB       points to the second input sequence.
+   * @param[in]  srcBLen     length of the second input sequence.
+   * @param[out] pDst        points to the block of output data
+   * @param[in]  firstIndex  is the first output sample to start with.
+   * @param[in]  numPoints   is the number of output points to be computed.
+   * @param[in]  pScratch1   points to scratch buffer of size max(srcALen, srcBLen) + 2*min(srcALen, srcBLen) - 2.
+   * @param[in]  pScratch2   points to scratch buffer of size min(srcALen, srcBLen).
+   * @return  Returns either ARM_MATH_SUCCESS if the function completed correctly or ARM_MATH_ARGUMENT_ERROR if the requested subset is not in the range [0 srcALen+srcBLen-2].
+   */
+  arm_status arm_conv_partial_fast_opt_q15(
+  q15_t * pSrcA,
+  uint32_t srcALen,
+  q15_t * pSrcB,
+  uint32_t srcBLen,
+  q15_t * pDst,
+  uint32_t firstIndex,
+  uint32_t numPoints,
+  q15_t * pScratch1,
+  q15_t * pScratch2);
+
+
+  /**
+   * @brief Partial convolution of Q31 sequences.
+   * @param[in]  pSrcA       points to the first input sequence.
+   * @param[in]  srcALen     length of the first input sequence.
+   * @param[in]  pSrcB       points to the second input sequence.
+   * @param[in]  srcBLen     length of the second input sequence.
+   * @param[out] pDst        points to the block of output data
+   * @param[in]  firstIndex  is the first output sample to start with.
+   * @param[in]  numPoints   is the number of output points to be computed.
+   * @return  Returns either ARM_MATH_SUCCESS if the function completed correctly or ARM_MATH_ARGUMENT_ERROR if the requested subset is not in the range [0 srcALen+srcBLen-2].
+   */
+  arm_status arm_conv_partial_q31(
+  q31_t * pSrcA,
+  uint32_t srcALen,
+  q31_t * pSrcB,
+  uint32_t srcBLen,
+  q31_t * pDst,
+  uint32_t firstIndex,
+  uint32_t numPoints);
+
+
+  /**
+   * @brief Partial convolution of Q31 sequences (fast version) for Cortex-M3 and Cortex-M4
+   * @param[in]  pSrcA       points to the first input sequence.
+   * @param[in]  srcALen     length of the first input sequence.
+   * @param[in]  pSrcB       points to the second input sequence.
+   * @param[in]  srcBLen     length of the second input sequence.
+   * @param[out] pDst        points to the block of output data
+   * @param[in]  firstIndex  is the first output sample to start with.
+   * @param[in]  numPoints   is the number of output points to be computed.
+   * @return  Returns either ARM_MATH_SUCCESS if the function completed correctly or ARM_MATH_ARGUMENT_ERROR if the requested subset is not in the range [0 srcALen+srcBLen-2].
+   */
+  arm_status arm_conv_partial_fast_q31(
+  q31_t * pSrcA,
+  uint32_t srcALen,
+  q31_t * pSrcB,
+  uint32_t srcBLen,
+  q31_t * pDst,
+  uint32_t firstIndex,
+  uint32_t numPoints);
+
+
+  /**
+   * @brief Partial convolution of Q7 sequences
+   * @param[in]  pSrcA       points to the first input sequence.
+   * @param[in]  srcALen     length of the first input sequence.
+   * @param[in]  pSrcB       points to the second input sequence.
+   * @param[in]  srcBLen     length of the second input sequence.
+   * @param[out] pDst        points to the block of output data
+   * @param[in]  firstIndex  is the first output sample to start with.
+   * @param[in]  numPoints   is the number of output points to be computed.
+   * @param[in]  pScratch1   points to scratch buffer(of type q15_t) of size max(srcALen, srcBLen) + 2*min(srcALen, srcBLen) - 2.
+   * @param[in]  pScratch2   points to scratch buffer (of type q15_t) of size min(srcALen, srcBLen).
+   * @return  Returns either ARM_MATH_SUCCESS if the function completed correctly or ARM_MATH_ARGUMENT_ERROR if the requested subset is not in the range [0 srcALen+srcBLen-2].
+   */
+  arm_status arm_conv_partial_opt_q7(
+  q7_t * pSrcA,
+  uint32_t srcALen,
+  q7_t * pSrcB,
+  uint32_t srcBLen,
+  q7_t * pDst,
+  uint32_t firstIndex,
+  uint32_t numPoints,
+  q15_t * pScratch1,
+  q15_t * pScratch2);
+
+
+/**
+   * @brief Partial convolution of Q7 sequences.
+   * @param[in]  pSrcA       points to the first input sequence.
+   * @param[in]  srcALen     length of the first input sequence.
+   * @param[in]  pSrcB       points to the second input sequence.
+   * @param[in]  srcBLen     length of the second input sequence.
+   * @param[out] pDst        points to the block of output data
+   * @param[in]  firstIndex  is the first output sample to start with.
+   * @param[in]  numPoints   is the number of output points to be computed.
+   * @return  Returns either ARM_MATH_SUCCESS if the function completed correctly or ARM_MATH_ARGUMENT_ERROR if the requested subset is not in the range [0 srcALen+srcBLen-2].
+   */
+  arm_status arm_conv_partial_q7(
+  q7_t * pSrcA,
+  uint32_t srcALen,
+  q7_t * pSrcB,
+  uint32_t srcBLen,
+  q7_t * pDst,
+  uint32_t firstIndex,
+  uint32_t numPoints);
+
+
+  /**
+   * @brief Instance structure for the Q15 FIR decimator.
+   */
+  typedef struct
+  {
+    uint8_t M;                  /**< decimation factor. */
+    uint16_t numTaps;           /**< number of coefficients in the filter. */
+    q15_t *pCoeffs;             /**< points to the coefficient array. The array is of length numTaps.*/
+    q15_t *pState;              /**< points to the state variable array. The array is of length numTaps+blockSize-1. */
+  } arm_fir_decimate_instance_q15;
+
+  /**
+   * @brief Instance structure for the Q31 FIR decimator.
+   */
+  typedef struct
+  {
+    uint8_t M;                  /**< decimation factor. */
+    uint16_t numTaps;           /**< number of coefficients in the filter. */
+    q31_t *pCoeffs;             /**< points to the coefficient array. The array is of length numTaps.*/
+    q31_t *pState;              /**< points to the state variable array. The array is of length numTaps+blockSize-1. */
+  } arm_fir_decimate_instance_q31;
+
+  /**
+   * @brief Instance structure for the floating-point FIR decimator.
+   */
+  typedef struct
+  {
+    uint8_t M;                  /**< decimation factor. */
+    uint16_t numTaps;           /**< number of coefficients in the filter. */
+    float32_t *pCoeffs;         /**< points to the coefficient array. The array is of length numTaps.*/
+    float32_t *pState;          /**< points to the state variable array. The array is of length numTaps+blockSize-1. */
+  } arm_fir_decimate_instance_f32;
+
+
+  /**
+   * @brief Processing function for the floating-point FIR decimator.
+   * @param[in]  S          points to an instance of the floating-point FIR decimator structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data
+   * @param[in]  blockSize  number of input samples to process per call.
+   */
+  void arm_fir_decimate_f32(
+  const arm_fir_decimate_instance_f32 * S,
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the floating-point FIR decimator.
+   * @param[in,out] S          points to an instance of the floating-point FIR decimator structure.
+   * @param[in]     numTaps    number of coefficients in the filter.
+   * @param[in]     M          decimation factor.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     blockSize  number of input samples to process per call.
+   * @return    The function returns ARM_MATH_SUCCESS if initialization is successful or ARM_MATH_LENGTH_ERROR if
+   * <code>blockSize</code> is not a multiple of <code>M</code>.
+   */
+  arm_status arm_fir_decimate_init_f32(
+  arm_fir_decimate_instance_f32 * S,
+  uint16_t numTaps,
+  uint8_t M,
+  float32_t * pCoeffs,
+  float32_t * pState,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the Q15 FIR decimator.
+   * @param[in]  S          points to an instance of the Q15 FIR decimator structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data
+   * @param[in]  blockSize  number of input samples to process per call.
+   */
+  void arm_fir_decimate_q15(
+  const arm_fir_decimate_instance_q15 * S,
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the Q15 FIR decimator (fast variant) for Cortex-M3 and Cortex-M4.
+   * @param[in]  S          points to an instance of the Q15 FIR decimator structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data
+   * @param[in]  blockSize  number of input samples to process per call.
+   */
+  void arm_fir_decimate_fast_q15(
+  const arm_fir_decimate_instance_q15 * S,
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the Q15 FIR decimator.
+   * @param[in,out] S          points to an instance of the Q15 FIR decimator structure.
+   * @param[in]     numTaps    number of coefficients in the filter.
+   * @param[in]     M          decimation factor.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     blockSize  number of input samples to process per call.
+   * @return    The function returns ARM_MATH_SUCCESS if initialization is successful or ARM_MATH_LENGTH_ERROR if
+   * <code>blockSize</code> is not a multiple of <code>M</code>.
+   */
+  arm_status arm_fir_decimate_init_q15(
+  arm_fir_decimate_instance_q15 * S,
+  uint16_t numTaps,
+  uint8_t M,
+  q15_t * pCoeffs,
+  q15_t * pState,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the Q31 FIR decimator.
+   * @param[in]  S     points to an instance of the Q31 FIR decimator structure.
+   * @param[in]  pSrc  points to the block of input data.
+   * @param[out] pDst  points to the block of output data
+   * @param[in] blockSize number of input samples to process per call.
+   */
+  void arm_fir_decimate_q31(
+  const arm_fir_decimate_instance_q31 * S,
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+  /**
+   * @brief Processing function for the Q31 FIR decimator (fast variant) for Cortex-M3 and Cortex-M4.
+   * @param[in]  S          points to an instance of the Q31 FIR decimator structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data
+   * @param[in]  blockSize  number of input samples to process per call.
+   */
+  void arm_fir_decimate_fast_q31(
+  arm_fir_decimate_instance_q31 * S,
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the Q31 FIR decimator.
+   * @param[in,out] S          points to an instance of the Q31 FIR decimator structure.
+   * @param[in]     numTaps    number of coefficients in the filter.
+   * @param[in]     M          decimation factor.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     blockSize  number of input samples to process per call.
+   * @return    The function returns ARM_MATH_SUCCESS if initialization is successful or ARM_MATH_LENGTH_ERROR if
+   * <code>blockSize</code> is not a multiple of <code>M</code>.
+   */
+  arm_status arm_fir_decimate_init_q31(
+  arm_fir_decimate_instance_q31 * S,
+  uint16_t numTaps,
+  uint8_t M,
+  q31_t * pCoeffs,
+  q31_t * pState,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Instance structure for the Q15 FIR interpolator.
+   */
+  typedef struct
+  {
+    uint8_t L;                      /**< upsample factor. */
+    uint16_t phaseLength;           /**< length of each polyphase filter component. */
+    q15_t *pCoeffs;                 /**< points to the coefficient array. The array is of length L*phaseLength. */
+    q15_t *pState;                  /**< points to the state variable array. The array is of length blockSize+phaseLength-1. */
+  } arm_fir_interpolate_instance_q15;
+
+  /**
+   * @brief Instance structure for the Q31 FIR interpolator.
+   */
+  typedef struct
+  {
+    uint8_t L;                      /**< upsample factor. */
+    uint16_t phaseLength;           /**< length of each polyphase filter component. */
+    q31_t *pCoeffs;                 /**< points to the coefficient array. The array is of length L*phaseLength. */
+    q31_t *pState;                  /**< points to the state variable array. The array is of length blockSize+phaseLength-1. */
+  } arm_fir_interpolate_instance_q31;
+
+  /**
+   * @brief Instance structure for the floating-point FIR interpolator.
+   */
+  typedef struct
+  {
+    uint8_t L;                     /**< upsample factor. */
+    uint16_t phaseLength;          /**< length of each polyphase filter component. */
+    float32_t *pCoeffs;            /**< points to the coefficient array. The array is of length L*phaseLength. */
+    float32_t *pState;             /**< points to the state variable array. The array is of length phaseLength+numTaps-1. */
+  } arm_fir_interpolate_instance_f32;
+
+
+  /**
+   * @brief Processing function for the Q15 FIR interpolator.
+   * @param[in]  S          points to an instance of the Q15 FIR interpolator structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of input samples to process per call.
+   */
+  void arm_fir_interpolate_q15(
+  const arm_fir_interpolate_instance_q15 * S,
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the Q15 FIR interpolator.
+   * @param[in,out] S          points to an instance of the Q15 FIR interpolator structure.
+   * @param[in]     L          upsample factor.
+   * @param[in]     numTaps    number of filter coefficients in the filter.
+   * @param[in]     pCoeffs    points to the filter coefficient buffer.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     blockSize  number of input samples to process per call.
+   * @return        The function returns ARM_MATH_SUCCESS if initialization is successful or ARM_MATH_LENGTH_ERROR if
+   * the filter length <code>numTaps</code> is not a multiple of the interpolation factor <code>L</code>.
+   */
+  arm_status arm_fir_interpolate_init_q15(
+  arm_fir_interpolate_instance_q15 * S,
+  uint8_t L,
+  uint16_t numTaps,
+  q15_t * pCoeffs,
+  q15_t * pState,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the Q31 FIR interpolator.
+   * @param[in]  S          points to an instance of the Q15 FIR interpolator structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of input samples to process per call.
+   */
+  void arm_fir_interpolate_q31(
+  const arm_fir_interpolate_instance_q31 * S,
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the Q31 FIR interpolator.
+   * @param[in,out] S          points to an instance of the Q31 FIR interpolator structure.
+   * @param[in]     L          upsample factor.
+   * @param[in]     numTaps    number of filter coefficients in the filter.
+   * @param[in]     pCoeffs    points to the filter coefficient buffer.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     blockSize  number of input samples to process per call.
+   * @return        The function returns ARM_MATH_SUCCESS if initialization is successful or ARM_MATH_LENGTH_ERROR if
+   * the filter length <code>numTaps</code> is not a multiple of the interpolation factor <code>L</code>.
+   */
+  arm_status arm_fir_interpolate_init_q31(
+  arm_fir_interpolate_instance_q31 * S,
+  uint8_t L,
+  uint16_t numTaps,
+  q31_t * pCoeffs,
+  q31_t * pState,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the floating-point FIR interpolator.
+   * @param[in]  S          points to an instance of the floating-point FIR interpolator structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of input samples to process per call.
+   */
+  void arm_fir_interpolate_f32(
+  const arm_fir_interpolate_instance_f32 * S,
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the floating-point FIR interpolator.
+   * @param[in,out] S          points to an instance of the floating-point FIR interpolator structure.
+   * @param[in]     L          upsample factor.
+   * @param[in]     numTaps    number of filter coefficients in the filter.
+   * @param[in]     pCoeffs    points to the filter coefficient buffer.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     blockSize  number of input samples to process per call.
+   * @return        The function returns ARM_MATH_SUCCESS if initialization is successful or ARM_MATH_LENGTH_ERROR if
+   * the filter length <code>numTaps</code> is not a multiple of the interpolation factor <code>L</code>.
+   */
+  arm_status arm_fir_interpolate_init_f32(
+  arm_fir_interpolate_instance_f32 * S,
+  uint8_t L,
+  uint16_t numTaps,
+  float32_t * pCoeffs,
+  float32_t * pState,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Instance structure for the high precision Q31 Biquad cascade filter.
+   */
+  typedef struct
+  {
+    uint8_t numStages;       /**< number of 2nd order stages in the filter.  Overall order is 2*numStages. */
+    q63_t *pState;           /**< points to the array of state coefficients.  The array is of length 4*numStages. */
+    q31_t *pCoeffs;          /**< points to the array of coefficients.  The array is of length 5*numStages. */
+    uint8_t postShift;       /**< additional shift, in bits, applied to each output sample. */
+  } arm_biquad_cas_df1_32x64_ins_q31;
+
+
+  /**
+   * @param[in]  S          points to an instance of the high precision Q31 Biquad cascade filter structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_biquad_cas_df1_32x64_q31(
+  const arm_biquad_cas_df1_32x64_ins_q31 * S,
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @param[in,out] S          points to an instance of the high precision Q31 Biquad cascade filter structure.
+   * @param[in]     numStages  number of 2nd order stages in the filter.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     postShift  shift to be applied to the output. Varies according to the coefficients format
+   */
+  void arm_biquad_cas_df1_32x64_init_q31(
+  arm_biquad_cas_df1_32x64_ins_q31 * S,
+  uint8_t numStages,
+  q31_t * pCoeffs,
+  q63_t * pState,
+  uint8_t postShift);
+
+
+  /**
+   * @brief Instance structure for the floating-point transposed direct form II Biquad cascade filter.
+   */
+  typedef struct
+  {
+    uint8_t numStages;         /**< number of 2nd order stages in the filter.  Overall order is 2*numStages. */
+    float32_t *pState;         /**< points to the array of state coefficients.  The array is of length 2*numStages. */
+    float32_t *pCoeffs;        /**< points to the array of coefficients.  The array is of length 5*numStages. */
+  } arm_biquad_cascade_df2T_instance_f32;
+
+  /**
+   * @brief Instance structure for the floating-point transposed direct form II Biquad cascade filter.
+   */
+  typedef struct
+  {
+    uint8_t numStages;         /**< number of 2nd order stages in the filter.  Overall order is 2*numStages. */
+    float32_t *pState;         /**< points to the array of state coefficients.  The array is of length 4*numStages. */
+    float32_t *pCoeffs;        /**< points to the array of coefficients.  The array is of length 5*numStages. */
+  } arm_biquad_cascade_stereo_df2T_instance_f32;
+
+  /**
+   * @brief Instance structure for the floating-point transposed direct form II Biquad cascade filter.
+   */
+  typedef struct
+  {
+    uint8_t numStages;         /**< number of 2nd order stages in the filter.  Overall order is 2*numStages. */
+    float64_t *pState;         /**< points to the array of state coefficients.  The array is of length 2*numStages. */
+    float64_t *pCoeffs;        /**< points to the array of coefficients.  The array is of length 5*numStages. */
+  } arm_biquad_cascade_df2T_instance_f64;
+
+
+  /**
+   * @brief Processing function for the floating-point transposed direct form II Biquad cascade filter.
+   * @param[in]  S          points to an instance of the filter data structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_biquad_cascade_df2T_f32(
+  const arm_biquad_cascade_df2T_instance_f32 * S,
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the floating-point transposed direct form II Biquad cascade filter. 2 channels
+   * @param[in]  S          points to an instance of the filter data structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_biquad_cascade_stereo_df2T_f32(
+  const arm_biquad_cascade_stereo_df2T_instance_f32 * S,
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the floating-point transposed direct form II Biquad cascade filter.
+   * @param[in]  S          points to an instance of the filter data structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_biquad_cascade_df2T_f64(
+  const arm_biquad_cascade_df2T_instance_f64 * S,
+  float64_t * pSrc,
+  float64_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the floating-point transposed direct form II Biquad cascade filter.
+   * @param[in,out] S          points to an instance of the filter data structure.
+   * @param[in]     numStages  number of 2nd order stages in the filter.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   */
+  void arm_biquad_cascade_df2T_init_f32(
+  arm_biquad_cascade_df2T_instance_f32 * S,
+  uint8_t numStages,
+  float32_t * pCoeffs,
+  float32_t * pState);
+
+
+  /**
+   * @brief  Initialization function for the floating-point transposed direct form II Biquad cascade filter.
+   * @param[in,out] S          points to an instance of the filter data structure.
+   * @param[in]     numStages  number of 2nd order stages in the filter.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   */
+  void arm_biquad_cascade_stereo_df2T_init_f32(
+  arm_biquad_cascade_stereo_df2T_instance_f32 * S,
+  uint8_t numStages,
+  float32_t * pCoeffs,
+  float32_t * pState);
+
+
+  /**
+   * @brief  Initialization function for the floating-point transposed direct form II Biquad cascade filter.
+   * @param[in,out] S          points to an instance of the filter data structure.
+   * @param[in]     numStages  number of 2nd order stages in the filter.
+   * @param[in]     pCoeffs    points to the filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   */
+  void arm_biquad_cascade_df2T_init_f64(
+  arm_biquad_cascade_df2T_instance_f64 * S,
+  uint8_t numStages,
+  float64_t * pCoeffs,
+  float64_t * pState);
+
+
+  /**
+   * @brief Instance structure for the Q15 FIR lattice filter.
+   */
+  typedef struct
+  {
+    uint16_t numStages;                  /**< number of filter stages. */
+    q15_t *pState;                       /**< points to the state variable array. The array is of length numStages. */
+    q15_t *pCoeffs;                      /**< points to the coefficient array. The array is of length numStages. */
+  } arm_fir_lattice_instance_q15;
+
+  /**
+   * @brief Instance structure for the Q31 FIR lattice filter.
+   */
+  typedef struct
+  {
+    uint16_t numStages;                  /**< number of filter stages. */
+    q31_t *pState;                       /**< points to the state variable array. The array is of length numStages. */
+    q31_t *pCoeffs;                      /**< points to the coefficient array. The array is of length numStages. */
+  } arm_fir_lattice_instance_q31;
+
+  /**
+   * @brief Instance structure for the floating-point FIR lattice filter.
+   */
+  typedef struct
+  {
+    uint16_t numStages;                  /**< number of filter stages. */
+    float32_t *pState;                   /**< points to the state variable array. The array is of length numStages. */
+    float32_t *pCoeffs;                  /**< points to the coefficient array. The array is of length numStages. */
+  } arm_fir_lattice_instance_f32;
+
+
+  /**
+   * @brief Initialization function for the Q15 FIR lattice filter.
+   * @param[in] S          points to an instance of the Q15 FIR lattice structure.
+   * @param[in] numStages  number of filter stages.
+   * @param[in] pCoeffs    points to the coefficient buffer.  The array is of length numStages.
+   * @param[in] pState     points to the state buffer.  The array is of length numStages.
+   */
+  void arm_fir_lattice_init_q15(
+  arm_fir_lattice_instance_q15 * S,
+  uint16_t numStages,
+  q15_t * pCoeffs,
+  q15_t * pState);
+
+
+  /**
+   * @brief Processing function for the Q15 FIR lattice filter.
+   * @param[in]  S          points to an instance of the Q15 FIR lattice structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_fir_lattice_q15(
+  const arm_fir_lattice_instance_q15 * S,
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Initialization function for the Q31 FIR lattice filter.
+   * @param[in] S          points to an instance of the Q31 FIR lattice structure.
+   * @param[in] numStages  number of filter stages.
+   * @param[in] pCoeffs    points to the coefficient buffer.  The array is of length numStages.
+   * @param[in] pState     points to the state buffer.   The array is of length numStages.
+   */
+  void arm_fir_lattice_init_q31(
+  arm_fir_lattice_instance_q31 * S,
+  uint16_t numStages,
+  q31_t * pCoeffs,
+  q31_t * pState);
+
+
+  /**
+   * @brief Processing function for the Q31 FIR lattice filter.
+   * @param[in]  S          points to an instance of the Q31 FIR lattice structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_fir_lattice_q31(
+  const arm_fir_lattice_instance_q31 * S,
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+/**
+ * @brief Initialization function for the floating-point FIR lattice filter.
+ * @param[in] S          points to an instance of the floating-point FIR lattice structure.
+ * @param[in] numStages  number of filter stages.
+ * @param[in] pCoeffs    points to the coefficient buffer.  The array is of length numStages.
+ * @param[in] pState     points to the state buffer.  The array is of length numStages.
+ */
+  void arm_fir_lattice_init_f32(
+  arm_fir_lattice_instance_f32 * S,
+  uint16_t numStages,
+  float32_t * pCoeffs,
+  float32_t * pState);
+
+
+  /**
+   * @brief Processing function for the floating-point FIR lattice filter.
+   * @param[in]  S          points to an instance of the floating-point FIR lattice structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_fir_lattice_f32(
+  const arm_fir_lattice_instance_f32 * S,
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Instance structure for the Q15 IIR lattice filter.
+   */
+  typedef struct
+  {
+    uint16_t numStages;                  /**< number of stages in the filter. */
+    q15_t *pState;                       /**< points to the state variable array. The array is of length numStages+blockSize. */
+    q15_t *pkCoeffs;                     /**< points to the reflection coefficient array. The array is of length numStages. */
+    q15_t *pvCoeffs;                     /**< points to the ladder coefficient array. The array is of length numStages+1. */
+  } arm_iir_lattice_instance_q15;
+
+  /**
+   * @brief Instance structure for the Q31 IIR lattice filter.
+   */
+  typedef struct
+  {
+    uint16_t numStages;                  /**< number of stages in the filter. */
+    q31_t *pState;                       /**< points to the state variable array. The array is of length numStages+blockSize. */
+    q31_t *pkCoeffs;                     /**< points to the reflection coefficient array. The array is of length numStages. */
+    q31_t *pvCoeffs;                     /**< points to the ladder coefficient array. The array is of length numStages+1. */
+  } arm_iir_lattice_instance_q31;
+
+  /**
+   * @brief Instance structure for the floating-point IIR lattice filter.
+   */
+  typedef struct
+  {
+    uint16_t numStages;                  /**< number of stages in the filter. */
+    float32_t *pState;                   /**< points to the state variable array. The array is of length numStages+blockSize. */
+    float32_t *pkCoeffs;                 /**< points to the reflection coefficient array. The array is of length numStages. */
+    float32_t *pvCoeffs;                 /**< points to the ladder coefficient array. The array is of length numStages+1. */
+  } arm_iir_lattice_instance_f32;
+
+
+  /**
+   * @brief Processing function for the floating-point IIR lattice filter.
+   * @param[in]  S          points to an instance of the floating-point IIR lattice structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_iir_lattice_f32(
+  const arm_iir_lattice_instance_f32 * S,
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Initialization function for the floating-point IIR lattice filter.
+   * @param[in] S          points to an instance of the floating-point IIR lattice structure.
+   * @param[in] numStages  number of stages in the filter.
+   * @param[in] pkCoeffs   points to the reflection coefficient buffer.  The array is of length numStages.
+   * @param[in] pvCoeffs   points to the ladder coefficient buffer.  The array is of length numStages+1.
+   * @param[in] pState     points to the state buffer.  The array is of length numStages+blockSize-1.
+   * @param[in] blockSize  number of samples to process.
+   */
+  void arm_iir_lattice_init_f32(
+  arm_iir_lattice_instance_f32 * S,
+  uint16_t numStages,
+  float32_t * pkCoeffs,
+  float32_t * pvCoeffs,
+  float32_t * pState,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the Q31 IIR lattice filter.
+   * @param[in]  S          points to an instance of the Q31 IIR lattice structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_iir_lattice_q31(
+  const arm_iir_lattice_instance_q31 * S,
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Initialization function for the Q31 IIR lattice filter.
+   * @param[in] S          points to an instance of the Q31 IIR lattice structure.
+   * @param[in] numStages  number of stages in the filter.
+   * @param[in] pkCoeffs   points to the reflection coefficient buffer.  The array is of length numStages.
+   * @param[in] pvCoeffs   points to the ladder coefficient buffer.  The array is of length numStages+1.
+   * @param[in] pState     points to the state buffer.  The array is of length numStages+blockSize.
+   * @param[in] blockSize  number of samples to process.
+   */
+  void arm_iir_lattice_init_q31(
+  arm_iir_lattice_instance_q31 * S,
+  uint16_t numStages,
+  q31_t * pkCoeffs,
+  q31_t * pvCoeffs,
+  q31_t * pState,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the Q15 IIR lattice filter.
+   * @param[in]  S          points to an instance of the Q15 IIR lattice structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[out] pDst       points to the block of output data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_iir_lattice_q15(
+  const arm_iir_lattice_instance_q15 * S,
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+/**
+ * @brief Initialization function for the Q15 IIR lattice filter.
+ * @param[in] S          points to an instance of the fixed-point Q15 IIR lattice structure.
+ * @param[in] numStages  number of stages in the filter.
+ * @param[in] pkCoeffs   points to reflection coefficient buffer.  The array is of length numStages.
+ * @param[in] pvCoeffs   points to ladder coefficient buffer.  The array is of length numStages+1.
+ * @param[in] pState     points to state buffer.  The array is of length numStages+blockSize.
+ * @param[in] blockSize  number of samples to process per call.
+ */
+  void arm_iir_lattice_init_q15(
+  arm_iir_lattice_instance_q15 * S,
+  uint16_t numStages,
+  q15_t * pkCoeffs,
+  q15_t * pvCoeffs,
+  q15_t * pState,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Instance structure for the floating-point LMS filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;    /**< number of coefficients in the filter. */
+    float32_t *pState;   /**< points to the state variable array. The array is of length numTaps+blockSize-1. */
+    float32_t *pCoeffs;  /**< points to the coefficient array. The array is of length numTaps. */
+    float32_t mu;        /**< step size that controls filter coefficient updates. */
+  } arm_lms_instance_f32;
+
+
+  /**
+   * @brief Processing function for floating-point LMS filter.
+   * @param[in]  S          points to an instance of the floating-point LMS filter structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[in]  pRef       points to the block of reference data.
+   * @param[out] pOut       points to the block of output data.
+   * @param[out] pErr       points to the block of error data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_lms_f32(
+  const arm_lms_instance_f32 * S,
+  float32_t * pSrc,
+  float32_t * pRef,
+  float32_t * pOut,
+  float32_t * pErr,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Initialization function for floating-point LMS filter.
+   * @param[in] S          points to an instance of the floating-point LMS filter structure.
+   * @param[in] numTaps    number of filter coefficients.
+   * @param[in] pCoeffs    points to the coefficient buffer.
+   * @param[in] pState     points to state buffer.
+   * @param[in] mu         step size that controls filter coefficient updates.
+   * @param[in] blockSize  number of samples to process.
+   */
+  void arm_lms_init_f32(
+  arm_lms_instance_f32 * S,
+  uint16_t numTaps,
+  float32_t * pCoeffs,
+  float32_t * pState,
+  float32_t mu,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Instance structure for the Q15 LMS filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;    /**< number of coefficients in the filter. */
+    q15_t *pState;       /**< points to the state variable array. The array is of length numTaps+blockSize-1. */
+    q15_t *pCoeffs;      /**< points to the coefficient array. The array is of length numTaps. */
+    q15_t mu;            /**< step size that controls filter coefficient updates. */
+    uint32_t postShift;  /**< bit shift applied to coefficients. */
+  } arm_lms_instance_q15;
+
+
+  /**
+   * @brief Initialization function for the Q15 LMS filter.
+   * @param[in] S          points to an instance of the Q15 LMS filter structure.
+   * @param[in] numTaps    number of filter coefficients.
+   * @param[in] pCoeffs    points to the coefficient buffer.
+   * @param[in] pState     points to the state buffer.
+   * @param[in] mu         step size that controls filter coefficient updates.
+   * @param[in] blockSize  number of samples to process.
+   * @param[in] postShift  bit shift applied to coefficients.
+   */
+  void arm_lms_init_q15(
+  arm_lms_instance_q15 * S,
+  uint16_t numTaps,
+  q15_t * pCoeffs,
+  q15_t * pState,
+  q15_t mu,
+  uint32_t blockSize,
+  uint32_t postShift);
+
+
+  /**
+   * @brief Processing function for Q15 LMS filter.
+   * @param[in]  S          points to an instance of the Q15 LMS filter structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[in]  pRef       points to the block of reference data.
+   * @param[out] pOut       points to the block of output data.
+   * @param[out] pErr       points to the block of error data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_lms_q15(
+  const arm_lms_instance_q15 * S,
+  q15_t * pSrc,
+  q15_t * pRef,
+  q15_t * pOut,
+  q15_t * pErr,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Instance structure for the Q31 LMS filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;    /**< number of coefficients in the filter. */
+    q31_t *pState;       /**< points to the state variable array. The array is of length numTaps+blockSize-1. */
+    q31_t *pCoeffs;      /**< points to the coefficient array. The array is of length numTaps. */
+    q31_t mu;            /**< step size that controls filter coefficient updates. */
+    uint32_t postShift;  /**< bit shift applied to coefficients. */
+  } arm_lms_instance_q31;
+
+
+  /**
+   * @brief Processing function for Q31 LMS filter.
+   * @param[in]  S          points to an instance of the Q15 LMS filter structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[in]  pRef       points to the block of reference data.
+   * @param[out] pOut       points to the block of output data.
+   * @param[out] pErr       points to the block of error data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_lms_q31(
+  const arm_lms_instance_q31 * S,
+  q31_t * pSrc,
+  q31_t * pRef,
+  q31_t * pOut,
+  q31_t * pErr,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Initialization function for Q31 LMS filter.
+   * @param[in] S          points to an instance of the Q31 LMS filter structure.
+   * @param[in] numTaps    number of filter coefficients.
+   * @param[in] pCoeffs    points to coefficient buffer.
+   * @param[in] pState     points to state buffer.
+   * @param[in] mu         step size that controls filter coefficient updates.
+   * @param[in] blockSize  number of samples to process.
+   * @param[in] postShift  bit shift applied to coefficients.
+   */
+  void arm_lms_init_q31(
+  arm_lms_instance_q31 * S,
+  uint16_t numTaps,
+  q31_t * pCoeffs,
+  q31_t * pState,
+  q31_t mu,
+  uint32_t blockSize,
+  uint32_t postShift);
+
+
+  /**
+   * @brief Instance structure for the floating-point normalized LMS filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;     /**< number of coefficients in the filter. */
+    float32_t *pState;    /**< points to the state variable array. The array is of length numTaps+blockSize-1. */
+    float32_t *pCoeffs;   /**< points to the coefficient array. The array is of length numTaps. */
+    float32_t mu;         /**< step size that control filter coefficient updates. */
+    float32_t energy;     /**< saves previous frame energy. */
+    float32_t x0;         /**< saves previous input sample. */
+  } arm_lms_norm_instance_f32;
+
+
+  /**
+   * @brief Processing function for floating-point normalized LMS filter.
+   * @param[in]  S          points to an instance of the floating-point normalized LMS filter structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[in]  pRef       points to the block of reference data.
+   * @param[out] pOut       points to the block of output data.
+   * @param[out] pErr       points to the block of error data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_lms_norm_f32(
+  arm_lms_norm_instance_f32 * S,
+  float32_t * pSrc,
+  float32_t * pRef,
+  float32_t * pOut,
+  float32_t * pErr,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Initialization function for floating-point normalized LMS filter.
+   * @param[in] S          points to an instance of the floating-point LMS filter structure.
+   * @param[in] numTaps    number of filter coefficients.
+   * @param[in] pCoeffs    points to coefficient buffer.
+   * @param[in] pState     points to state buffer.
+   * @param[in] mu         step size that controls filter coefficient updates.
+   * @param[in] blockSize  number of samples to process.
+   */
+  void arm_lms_norm_init_f32(
+  arm_lms_norm_instance_f32 * S,
+  uint16_t numTaps,
+  float32_t * pCoeffs,
+  float32_t * pState,
+  float32_t mu,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Instance structure for the Q31 normalized LMS filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;     /**< number of coefficients in the filter. */
+    q31_t *pState;        /**< points to the state variable array. The array is of length numTaps+blockSize-1. */
+    q31_t *pCoeffs;       /**< points to the coefficient array. The array is of length numTaps. */
+    q31_t mu;             /**< step size that controls filter coefficient updates. */
+    uint8_t postShift;    /**< bit shift applied to coefficients. */
+    q31_t *recipTable;    /**< points to the reciprocal initial value table. */
+    q31_t energy;         /**< saves previous frame energy. */
+    q31_t x0;             /**< saves previous input sample. */
+  } arm_lms_norm_instance_q31;
+
+
+  /**
+   * @brief Processing function for Q31 normalized LMS filter.
+   * @param[in]  S          points to an instance of the Q31 normalized LMS filter structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[in]  pRef       points to the block of reference data.
+   * @param[out] pOut       points to the block of output data.
+   * @param[out] pErr       points to the block of error data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_lms_norm_q31(
+  arm_lms_norm_instance_q31 * S,
+  q31_t * pSrc,
+  q31_t * pRef,
+  q31_t * pOut,
+  q31_t * pErr,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Initialization function for Q31 normalized LMS filter.
+   * @param[in] S          points to an instance of the Q31 normalized LMS filter structure.
+   * @param[in] numTaps    number of filter coefficients.
+   * @param[in] pCoeffs    points to coefficient buffer.
+   * @param[in] pState     points to state buffer.
+   * @param[in] mu         step size that controls filter coefficient updates.
+   * @param[in] blockSize  number of samples to process.
+   * @param[in] postShift  bit shift applied to coefficients.
+   */
+  void arm_lms_norm_init_q31(
+  arm_lms_norm_instance_q31 * S,
+  uint16_t numTaps,
+  q31_t * pCoeffs,
+  q31_t * pState,
+  q31_t mu,
+  uint32_t blockSize,
+  uint8_t postShift);
+
+
+  /**
+   * @brief Instance structure for the Q15 normalized LMS filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;     /**< Number of coefficients in the filter. */
+    q15_t *pState;        /**< points to the state variable array. The array is of length numTaps+blockSize-1. */
+    q15_t *pCoeffs;       /**< points to the coefficient array. The array is of length numTaps. */
+    q15_t mu;             /**< step size that controls filter coefficient updates. */
+    uint8_t postShift;    /**< bit shift applied to coefficients. */
+    q15_t *recipTable;    /**< Points to the reciprocal initial value table. */
+    q15_t energy;         /**< saves previous frame energy. */
+    q15_t x0;             /**< saves previous input sample. */
+  } arm_lms_norm_instance_q15;
+
+
+  /**
+   * @brief Processing function for Q15 normalized LMS filter.
+   * @param[in]  S          points to an instance of the Q15 normalized LMS filter structure.
+   * @param[in]  pSrc       points to the block of input data.
+   * @param[in]  pRef       points to the block of reference data.
+   * @param[out] pOut       points to the block of output data.
+   * @param[out] pErr       points to the block of error data.
+   * @param[in]  blockSize  number of samples to process.
+   */
+  void arm_lms_norm_q15(
+  arm_lms_norm_instance_q15 * S,
+  q15_t * pSrc,
+  q15_t * pRef,
+  q15_t * pOut,
+  q15_t * pErr,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Initialization function for Q15 normalized LMS filter.
+   * @param[in] S          points to an instance of the Q15 normalized LMS filter structure.
+   * @param[in] numTaps    number of filter coefficients.
+   * @param[in] pCoeffs    points to coefficient buffer.
+   * @param[in] pState     points to state buffer.
+   * @param[in] mu         step size that controls filter coefficient updates.
+   * @param[in] blockSize  number of samples to process.
+   * @param[in] postShift  bit shift applied to coefficients.
+   */
+  void arm_lms_norm_init_q15(
+  arm_lms_norm_instance_q15 * S,
+  uint16_t numTaps,
+  q15_t * pCoeffs,
+  q15_t * pState,
+  q15_t mu,
+  uint32_t blockSize,
+  uint8_t postShift);
+
+
+  /**
+   * @brief Correlation of floating-point sequences.
+   * @param[in]  pSrcA    points to the first input sequence.
+   * @param[in]  srcALen  length of the first input sequence.
+   * @param[in]  pSrcB    points to the second input sequence.
+   * @param[in]  srcBLen  length of the second input sequence.
+   * @param[out] pDst     points to the block of output data  Length 2 * max(srcALen, srcBLen) - 1.
+   */
+  void arm_correlate_f32(
+  float32_t * pSrcA,
+  uint32_t srcALen,
+  float32_t * pSrcB,
+  uint32_t srcBLen,
+  float32_t * pDst);
+
+
+   /**
+   * @brief Correlation of Q15 sequences
+   * @param[in]  pSrcA     points to the first input sequence.
+   * @param[in]  srcALen   length of the first input sequence.
+   * @param[in]  pSrcB     points to the second input sequence.
+   * @param[in]  srcBLen   length of the second input sequence.
+   * @param[out] pDst      points to the block of output data  Length 2 * max(srcALen, srcBLen) - 1.
+   * @param[in]  pScratch  points to scratch buffer of size max(srcALen, srcBLen) + 2*min(srcALen, srcBLen) - 2.
+   */
+  void arm_correlate_opt_q15(
+  q15_t * pSrcA,
+  uint32_t srcALen,
+  q15_t * pSrcB,
+  uint32_t srcBLen,
+  q15_t * pDst,
+  q15_t * pScratch);
+
+
+  /**
+   * @brief Correlation of Q15 sequences.
+   * @param[in]  pSrcA    points to the first input sequence.
+   * @param[in]  srcALen  length of the first input sequence.
+   * @param[in]  pSrcB    points to the second input sequence.
+   * @param[in]  srcBLen  length of the second input sequence.
+   * @param[out] pDst     points to the block of output data  Length 2 * max(srcALen, srcBLen) - 1.
+   */
+
+  void arm_correlate_q15(
+  q15_t * pSrcA,
+  uint32_t srcALen,
+  q15_t * pSrcB,
+  uint32_t srcBLen,
+  q15_t * pDst);
+
+
+  /**
+   * @brief Correlation of Q15 sequences (fast version) for Cortex-M3 and Cortex-M4.
+   * @param[in]  pSrcA    points to the first input sequence.
+   * @param[in]  srcALen  length of the first input sequence.
+   * @param[in]  pSrcB    points to the second input sequence.
+   * @param[in]  srcBLen  length of the second input sequence.
+   * @param[out] pDst     points to the block of output data  Length 2 * max(srcALen, srcBLen) - 1.
+   */
+
+  void arm_correlate_fast_q15(
+  q15_t * pSrcA,
+  uint32_t srcALen,
+  q15_t * pSrcB,
+  uint32_t srcBLen,
+  q15_t * pDst);
+
+
+  /**
+   * @brief Correlation of Q15 sequences (fast version) for Cortex-M3 and Cortex-M4.
+   * @param[in]  pSrcA     points to the first input sequence.
+   * @param[in]  srcALen   length of the first input sequence.
+   * @param[in]  pSrcB     points to the second input sequence.
+   * @param[in]  srcBLen   length of the second input sequence.
+   * @param[out] pDst      points to the block of output data  Length 2 * max(srcALen, srcBLen) - 1.
+   * @param[in]  pScratch  points to scratch buffer of size max(srcALen, srcBLen) + 2*min(srcALen, srcBLen) - 2.
+   */
+  void arm_correlate_fast_opt_q15(
+  q15_t * pSrcA,
+  uint32_t srcALen,
+  q15_t * pSrcB,
+  uint32_t srcBLen,
+  q15_t * pDst,
+  q15_t * pScratch);
+
+
+  /**
+   * @brief Correlation of Q31 sequences.
+   * @param[in]  pSrcA    points to the first input sequence.
+   * @param[in]  srcALen  length of the first input sequence.
+   * @param[in]  pSrcB    points to the second input sequence.
+   * @param[in]  srcBLen  length of the second input sequence.
+   * @param[out] pDst     points to the block of output data  Length 2 * max(srcALen, srcBLen) - 1.
+   */
+  void arm_correlate_q31(
+  q31_t * pSrcA,
+  uint32_t srcALen,
+  q31_t * pSrcB,
+  uint32_t srcBLen,
+  q31_t * pDst);
+
+
+  /**
+   * @brief Correlation of Q31 sequences (fast version) for Cortex-M3 and Cortex-M4
+   * @param[in]  pSrcA    points to the first input sequence.
+   * @param[in]  srcALen  length of the first input sequence.
+   * @param[in]  pSrcB    points to the second input sequence.
+   * @param[in]  srcBLen  length of the second input sequence.
+   * @param[out] pDst     points to the block of output data  Length 2 * max(srcALen, srcBLen) - 1.
+   */
+  void arm_correlate_fast_q31(
+  q31_t * pSrcA,
+  uint32_t srcALen,
+  q31_t * pSrcB,
+  uint32_t srcBLen,
+  q31_t * pDst);
+
+
+ /**
+   * @brief Correlation of Q7 sequences.
+   * @param[in]  pSrcA      points to the first input sequence.
+   * @param[in]  srcALen    length of the first input sequence.
+   * @param[in]  pSrcB      points to the second input sequence.
+   * @param[in]  srcBLen    length of the second input sequence.
+   * @param[out] pDst       points to the block of output data  Length 2 * max(srcALen, srcBLen) - 1.
+   * @param[in]  pScratch1  points to scratch buffer(of type q15_t) of size max(srcALen, srcBLen) + 2*min(srcALen, srcBLen) - 2.
+   * @param[in]  pScratch2  points to scratch buffer (of type q15_t) of size min(srcALen, srcBLen).
+   */
+  void arm_correlate_opt_q7(
+  q7_t * pSrcA,
+  uint32_t srcALen,
+  q7_t * pSrcB,
+  uint32_t srcBLen,
+  q7_t * pDst,
+  q15_t * pScratch1,
+  q15_t * pScratch2);
+
+
+  /**
+   * @brief Correlation of Q7 sequences.
+   * @param[in]  pSrcA    points to the first input sequence.
+   * @param[in]  srcALen  length of the first input sequence.
+   * @param[in]  pSrcB    points to the second input sequence.
+   * @param[in]  srcBLen  length of the second input sequence.
+   * @param[out] pDst     points to the block of output data  Length 2 * max(srcALen, srcBLen) - 1.
+   */
+  void arm_correlate_q7(
+  q7_t * pSrcA,
+  uint32_t srcALen,
+  q7_t * pSrcB,
+  uint32_t srcBLen,
+  q7_t * pDst);
+
+
+  /**
+   * @brief Instance structure for the floating-point sparse FIR filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;             /**< number of coefficients in the filter. */
+    uint16_t stateIndex;          /**< state buffer index.  Points to the oldest sample in the state buffer. */
+    float32_t *pState;            /**< points to the state buffer array. The array is of length maxDelay+blockSize-1. */
+    float32_t *pCoeffs;           /**< points to the coefficient array. The array is of length numTaps.*/
+    uint16_t maxDelay;            /**< maximum offset specified by the pTapDelay array. */
+    int32_t *pTapDelay;           /**< points to the array of delay values.  The array is of length numTaps. */
+  } arm_fir_sparse_instance_f32;
+
+  /**
+   * @brief Instance structure for the Q31 sparse FIR filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;             /**< number of coefficients in the filter. */
+    uint16_t stateIndex;          /**< state buffer index.  Points to the oldest sample in the state buffer. */
+    q31_t *pState;                /**< points to the state buffer array. The array is of length maxDelay+blockSize-1. */
+    q31_t *pCoeffs;               /**< points to the coefficient array. The array is of length numTaps.*/
+    uint16_t maxDelay;            /**< maximum offset specified by the pTapDelay array. */
+    int32_t *pTapDelay;           /**< points to the array of delay values.  The array is of length numTaps. */
+  } arm_fir_sparse_instance_q31;
+
+  /**
+   * @brief Instance structure for the Q15 sparse FIR filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;             /**< number of coefficients in the filter. */
+    uint16_t stateIndex;          /**< state buffer index.  Points to the oldest sample in the state buffer. */
+    q15_t *pState;                /**< points to the state buffer array. The array is of length maxDelay+blockSize-1. */
+    q15_t *pCoeffs;               /**< points to the coefficient array. The array is of length numTaps.*/
+    uint16_t maxDelay;            /**< maximum offset specified by the pTapDelay array. */
+    int32_t *pTapDelay;           /**< points to the array of delay values.  The array is of length numTaps. */
+  } arm_fir_sparse_instance_q15;
+
+  /**
+   * @brief Instance structure for the Q7 sparse FIR filter.
+   */
+  typedef struct
+  {
+    uint16_t numTaps;             /**< number of coefficients in the filter. */
+    uint16_t stateIndex;          /**< state buffer index.  Points to the oldest sample in the state buffer. */
+    q7_t *pState;                 /**< points to the state buffer array. The array is of length maxDelay+blockSize-1. */
+    q7_t *pCoeffs;                /**< points to the coefficient array. The array is of length numTaps.*/
+    uint16_t maxDelay;            /**< maximum offset specified by the pTapDelay array. */
+    int32_t *pTapDelay;           /**< points to the array of delay values.  The array is of length numTaps. */
+  } arm_fir_sparse_instance_q7;
+
+
+  /**
+   * @brief Processing function for the floating-point sparse FIR filter.
+   * @param[in]  S           points to an instance of the floating-point sparse FIR structure.
+   * @param[in]  pSrc        points to the block of input data.
+   * @param[out] pDst        points to the block of output data
+   * @param[in]  pScratchIn  points to a temporary buffer of size blockSize.
+   * @param[in]  blockSize   number of input samples to process per call.
+   */
+  void arm_fir_sparse_f32(
+  arm_fir_sparse_instance_f32 * S,
+  float32_t * pSrc,
+  float32_t * pDst,
+  float32_t * pScratchIn,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the floating-point sparse FIR filter.
+   * @param[in,out] S          points to an instance of the floating-point sparse FIR structure.
+   * @param[in]     numTaps    number of nonzero coefficients in the filter.
+   * @param[in]     pCoeffs    points to the array of filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     pTapDelay  points to the array of offset times.
+   * @param[in]     maxDelay   maximum offset time supported.
+   * @param[in]     blockSize  number of samples that will be processed per block.
+   */
+  void arm_fir_sparse_init_f32(
+  arm_fir_sparse_instance_f32 * S,
+  uint16_t numTaps,
+  float32_t * pCoeffs,
+  float32_t * pState,
+  int32_t * pTapDelay,
+  uint16_t maxDelay,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the Q31 sparse FIR filter.
+   * @param[in]  S           points to an instance of the Q31 sparse FIR structure.
+   * @param[in]  pSrc        points to the block of input data.
+   * @param[out] pDst        points to the block of output data
+   * @param[in]  pScratchIn  points to a temporary buffer of size blockSize.
+   * @param[in]  blockSize   number of input samples to process per call.
+   */
+  void arm_fir_sparse_q31(
+  arm_fir_sparse_instance_q31 * S,
+  q31_t * pSrc,
+  q31_t * pDst,
+  q31_t * pScratchIn,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the Q31 sparse FIR filter.
+   * @param[in,out] S          points to an instance of the Q31 sparse FIR structure.
+   * @param[in]     numTaps    number of nonzero coefficients in the filter.
+   * @param[in]     pCoeffs    points to the array of filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     pTapDelay  points to the array of offset times.
+   * @param[in]     maxDelay   maximum offset time supported.
+   * @param[in]     blockSize  number of samples that will be processed per block.
+   */
+  void arm_fir_sparse_init_q31(
+  arm_fir_sparse_instance_q31 * S,
+  uint16_t numTaps,
+  q31_t * pCoeffs,
+  q31_t * pState,
+  int32_t * pTapDelay,
+  uint16_t maxDelay,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the Q15 sparse FIR filter.
+   * @param[in]  S            points to an instance of the Q15 sparse FIR structure.
+   * @param[in]  pSrc         points to the block of input data.
+   * @param[out] pDst         points to the block of output data
+   * @param[in]  pScratchIn   points to a temporary buffer of size blockSize.
+   * @param[in]  pScratchOut  points to a temporary buffer of size blockSize.
+   * @param[in]  blockSize    number of input samples to process per call.
+   */
+  void arm_fir_sparse_q15(
+  arm_fir_sparse_instance_q15 * S,
+  q15_t * pSrc,
+  q15_t * pDst,
+  q15_t * pScratchIn,
+  q31_t * pScratchOut,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the Q15 sparse FIR filter.
+   * @param[in,out] S          points to an instance of the Q15 sparse FIR structure.
+   * @param[in]     numTaps    number of nonzero coefficients in the filter.
+   * @param[in]     pCoeffs    points to the array of filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     pTapDelay  points to the array of offset times.
+   * @param[in]     maxDelay   maximum offset time supported.
+   * @param[in]     blockSize  number of samples that will be processed per block.
+   */
+  void arm_fir_sparse_init_q15(
+  arm_fir_sparse_instance_q15 * S,
+  uint16_t numTaps,
+  q15_t * pCoeffs,
+  q15_t * pState,
+  int32_t * pTapDelay,
+  uint16_t maxDelay,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Processing function for the Q7 sparse FIR filter.
+   * @param[in]  S            points to an instance of the Q7 sparse FIR structure.
+   * @param[in]  pSrc         points to the block of input data.
+   * @param[out] pDst         points to the block of output data
+   * @param[in]  pScratchIn   points to a temporary buffer of size blockSize.
+   * @param[in]  pScratchOut  points to a temporary buffer of size blockSize.
+   * @param[in]  blockSize    number of input samples to process per call.
+   */
+  void arm_fir_sparse_q7(
+  arm_fir_sparse_instance_q7 * S,
+  q7_t * pSrc,
+  q7_t * pDst,
+  q7_t * pScratchIn,
+  q31_t * pScratchOut,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Initialization function for the Q7 sparse FIR filter.
+   * @param[in,out] S          points to an instance of the Q7 sparse FIR structure.
+   * @param[in]     numTaps    number of nonzero coefficients in the filter.
+   * @param[in]     pCoeffs    points to the array of filter coefficients.
+   * @param[in]     pState     points to the state buffer.
+   * @param[in]     pTapDelay  points to the array of offset times.
+   * @param[in]     maxDelay   maximum offset time supported.
+   * @param[in]     blockSize  number of samples that will be processed per block.
+   */
+  void arm_fir_sparse_init_q7(
+  arm_fir_sparse_instance_q7 * S,
+  uint16_t numTaps,
+  q7_t * pCoeffs,
+  q7_t * pState,
+  int32_t * pTapDelay,
+  uint16_t maxDelay,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Floating-point sin_cos function.
+   * @param[in]  theta   input value in degrees
+   * @param[out] pSinVal  points to the processed sine output.
+   * @param[out] pCosVal  points to the processed cos output.
+   */
+  void arm_sin_cos_f32(
+  float32_t theta,
+  float32_t * pSinVal,
+  float32_t * pCosVal);
+
+
+  /**
+   * @brief  Q31 sin_cos function.
+   * @param[in]  theta    scaled input value in degrees
+   * @param[out] pSinVal  points to the processed sine output.
+   * @param[out] pCosVal  points to the processed cosine output.
+   */
+  void arm_sin_cos_q31(
+  q31_t theta,
+  q31_t * pSinVal,
+  q31_t * pCosVal);
+
+
+  /**
+   * @brief  Floating-point complex conjugate.
+   * @param[in]  pSrc        points to the input vector
+   * @param[out] pDst        points to the output vector
+   * @param[in]  numSamples  number of complex samples in each vector
+   */
+  void arm_cmplx_conj_f32(
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t numSamples);
+
+  /**
+   * @brief  Q31 complex conjugate.
+   * @param[in]  pSrc        points to the input vector
+   * @param[out] pDst        points to the output vector
+   * @param[in]  numSamples  number of complex samples in each vector
+   */
+  void arm_cmplx_conj_q31(
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t numSamples);
+
+
+  /**
+   * @brief  Q15 complex conjugate.
+   * @param[in]  pSrc        points to the input vector
+   * @param[out] pDst        points to the output vector
+   * @param[in]  numSamples  number of complex samples in each vector
+   */
+  void arm_cmplx_conj_q15(
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t numSamples);
+
+
+  /**
+   * @brief  Floating-point complex magnitude squared
+   * @param[in]  pSrc        points to the complex input vector
+   * @param[out] pDst        points to the real output vector
+   * @param[in]  numSamples  number of complex samples in the input vector
+   */
+  void arm_cmplx_mag_squared_f32(
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t numSamples);
+
+
+  /**
+   * @brief  Q31 complex magnitude squared
+   * @param[in]  pSrc        points to the complex input vector
+   * @param[out] pDst        points to the real output vector
+   * @param[in]  numSamples  number of complex samples in the input vector
+   */
+  void arm_cmplx_mag_squared_q31(
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t numSamples);
+
+
+  /**
+   * @brief  Q15 complex magnitude squared
+   * @param[in]  pSrc        points to the complex input vector
+   * @param[out] pDst        points to the real output vector
+   * @param[in]  numSamples  number of complex samples in the input vector
+   */
+  void arm_cmplx_mag_squared_q15(
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t numSamples);
+
+
+ /**
+   * @ingroup groupController
+   */
+
+  /**
+   * @defgroup PID PID Motor Control
+   *
+   * A Proportional Integral Derivative (PID) controller is a generic feedback control
+   * loop mechanism widely used in industrial control systems.
+   * A PID controller is the most commonly used type of feedback controller.
+   *
+   * This set of functions implements (PID) controllers
+   * for Q15, Q31, and floating-point data types.  The functions operate on a single sample
+   * of data and each call to the function returns a single processed value.
+   * <code>S</code> points to an instance of the PID control data structure.  <code>in</code>
+   * is the input sample value. The functions return the output value.
+   *
+   * \par Algorithm:
+   * <pre>
+   *    y[n] = y[n-1] + A0 * x[n] + A1 * x[n-1] + A2 * x[n-2]
+   *    A0 = Kp + Ki + Kd
+   *    A1 = (-Kp ) - (2 * Kd )
+   *    A2 = Kd  </pre>
+   *
+   * \par
+   * where \c Kp is proportional constant, \c Ki is Integral constant and \c Kd is Derivative constant
+   *
+   * \par
+   * \image html PID.gif "Proportional Integral Derivative Controller"
+   *
+   * \par
+   * The PID controller calculates an "error" value as the difference between
+   * the measured output and the reference input.
+   * The controller attempts to minimize the error by adjusting the process control inputs.
+   * The proportional value determines the reaction to the current error,
+   * the integral value determines the reaction based on the sum of recent errors,
+   * and the derivative value determines the reaction based on the rate at which the error has been changing.
+   *
+   * \par Instance Structure
+   * The Gains A0, A1, A2 and state variables for a PID controller are stored together in an instance data structure.
+   * A separate instance structure must be defined for each PID Controller.
+   * There are separate instance structure declarations for each of the 3 supported data types.
+   *
+   * \par Reset Functions
+   * There is also an associated reset function for each data type which clears the state array.
+   *
+   * \par Initialization Functions
+   * There is also an associated initialization function for each data type.
+   * The initialization function performs the following operations:
+   * - Initializes the Gains A0, A1, A2 from Kp,Ki, Kd gains.
+   * - Zeros out the values in the state buffer.
+   *
+   * \par
+   * Instance structure cannot be placed into a const data section and it is recommended to use the initialization function.
+   *
+   * \par Fixed-Point Behavior
+   * Care must be taken when using the fixed-point versions of the PID Controller functions.
+   * In particular, the overflow and saturation behavior of the accumulator used in each function must be considered.
+   * Refer to the function specific documentation below for usage guidelines.
+   */
+
+  /**
+   * @addtogroup PID
+   * @{
+   */
+
+  /**
+   * @brief  Process function for the floating-point PID Control.
+   * @param[in,out] S   is an instance of the floating-point PID Control structure
+   * @param[in]     in  input sample to process
+   * @return out processed output sample.
+   */
+  CMSIS_INLINE __STATIC_INLINE float32_t arm_pid_f32(
+  arm_pid_instance_f32 * S,
+  float32_t in)
+  {
+    float32_t out;
+
+    /* y[n] = y[n-1] + A0 * x[n] + A1 * x[n-1] + A2 * x[n-2]  */
+    out = (S->A0 * in) +
+      (S->A1 * S->state[0]) + (S->A2 * S->state[1]) + (S->state[2]);
+
+    /* Update state */
+    S->state[1] = S->state[0];
+    S->state[0] = in;
+    S->state[2] = out;
+
+    /* return to application */
+    return (out);
+
+  }
+
+  /**
+   * @brief  Process function for the Q31 PID Control.
+   * @param[in,out] S  points to an instance of the Q31 PID Control structure
+   * @param[in]     in  input sample to process
+   * @return out processed output sample.
+   *
+   * <b>Scaling and Overflow Behavior:</b>
+   * \par
+   * The function is implemented using an internal 64-bit accumulator.
+   * The accumulator has a 2.62 format and maintains full precision of the intermediate multiplication results but provides only a single guard bit.
+   * Thus, if the accumulator result overflows it wraps around rather than clip.
+   * In order to avoid overflows completely the input signal must be scaled down by 2 bits as there are four additions.
+   * After all multiply-accumulates are performed, the 2.62 accumulator is truncated to 1.32 format and then saturated to 1.31 format.
+   */
+  CMSIS_INLINE __STATIC_INLINE q31_t arm_pid_q31(
+  arm_pid_instance_q31 * S,
+  q31_t in)
+  {
+    q63_t acc;
+    q31_t out;
+
+    /* acc = A0 * x[n]  */
+    acc = (q63_t) S->A0 * in;
+
+    /* acc += A1 * x[n-1] */
+    acc += (q63_t) S->A1 * S->state[0];
+
+    /* acc += A2 * x[n-2]  */
+    acc += (q63_t) S->A2 * S->state[1];
+
+    /* convert output to 1.31 format to add y[n-1] */
+    out = (q31_t) (acc >> 31U);
+
+    /* out += y[n-1] */
+    out += S->state[2];
+
+    /* Update state */
+    S->state[1] = S->state[0];
+    S->state[0] = in;
+    S->state[2] = out;
+
+    /* return to application */
+    return (out);
+  }
+
+
+  /**
+   * @brief  Process function for the Q15 PID Control.
+   * @param[in,out] S   points to an instance of the Q15 PID Control structure
+   * @param[in]     in  input sample to process
+   * @return out processed output sample.
+   *
+   * <b>Scaling and Overflow Behavior:</b>
+   * \par
+   * The function is implemented using a 64-bit internal accumulator.
+   * Both Gains and state variables are represented in 1.15 format and multiplications yield a 2.30 result.
+   * The 2.30 intermediate results are accumulated in a 64-bit accumulator in 34.30 format.
+   * There is no risk of internal overflow with this approach and the full precision of intermediate multiplications is preserved.
+   * After all additions have been performed, the accumulator is truncated to 34.15 format by discarding low 15 bits.
+   * Lastly, the accumulator is saturated to yield a result in 1.15 format.
+   */
+  CMSIS_INLINE __STATIC_INLINE q15_t arm_pid_q15(
+  arm_pid_instance_q15 * S,
+  q15_t in)
+  {
+    q63_t acc;
+    q15_t out;
+
+#if defined (ARM_MATH_DSP)
+    __SIMD32_TYPE *vstate;
+
+    /* Implementation of PID controller */
+
+    /* acc = A0 * x[n]  */
+    acc = (q31_t) __SMUAD((uint32_t)S->A0, (uint32_t)in);
+
+    /* acc += A1 * x[n-1] + A2 * x[n-2]  */
+    vstate = __SIMD32_CONST(S->state);
+    acc = (q63_t)__SMLALD((uint32_t)S->A1, (uint32_t)*vstate, (uint64_t)acc);
+#else
+    /* acc = A0 * x[n]  */
+    acc = ((q31_t) S->A0) * in;
+
+    /* acc += A1 * x[n-1] + A2 * x[n-2]  */
+    acc += (q31_t) S->A1 * S->state[0];
+    acc += (q31_t) S->A2 * S->state[1];
+#endif
+
+    /* acc += y[n-1] */
+    acc += (q31_t) S->state[2] << 15;
+
+    /* saturate the output */
+    out = (q15_t) (__SSAT((acc >> 15), 16));
+
+    /* Update state */
+    S->state[1] = S->state[0];
+    S->state[0] = in;
+    S->state[2] = out;
+
+    /* return to application */
+    return (out);
+  }
+
+  /**
+   * @} end of PID group
+   */
+
+
+  /**
+   * @brief Floating-point matrix inverse.
+   * @param[in]  src   points to the instance of the input floating-point matrix structure.
+   * @param[out] dst   points to the instance of the output floating-point matrix structure.
+   * @return The function returns ARM_MATH_SIZE_MISMATCH, if the dimensions do not match.
+   * If the input matrix is singular (does not have an inverse), then the algorithm terminates and returns error status ARM_MATH_SINGULAR.
+   */
+  arm_status arm_mat_inverse_f32(
+  const arm_matrix_instance_f32 * src,
+  arm_matrix_instance_f32 * dst);
+
+
+  /**
+   * @brief Floating-point matrix inverse.
+   * @param[in]  src   points to the instance of the input floating-point matrix structure.
+   * @param[out] dst   points to the instance of the output floating-point matrix structure.
+   * @return The function returns ARM_MATH_SIZE_MISMATCH, if the dimensions do not match.
+   * If the input matrix is singular (does not have an inverse), then the algorithm terminates and returns error status ARM_MATH_SINGULAR.
+   */
+  arm_status arm_mat_inverse_f64(
+  const arm_matrix_instance_f64 * src,
+  arm_matrix_instance_f64 * dst);
+
+
+
+  /**
+   * @ingroup groupController
+   */
+
+  /**
+   * @defgroup clarke Vector Clarke Transform
+   * Forward Clarke transform converts the instantaneous stator phases into a two-coordinate time invariant vector.
+   * Generally the Clarke transform uses three-phase currents <code>Ia, Ib and Ic</code> to calculate currents
+   * in the two-phase orthogonal stator axis <code>Ialpha</code> and <code>Ibeta</code>.
+   * When <code>Ialpha</code> is superposed with <code>Ia</code> as shown in the figure below
+   * \image html clarke.gif Stator current space vector and its components in (a,b).
+   * and <code>Ia + Ib + Ic = 0</code>, in this condition <code>Ialpha</code> and <code>Ibeta</code>
+   * can be calculated using only <code>Ia</code> and <code>Ib</code>.
+   *
+   * The function operates on a single sample of data and each call to the function returns the processed output.
+   * The library provides separate functions for Q31 and floating-point data types.
+   * \par Algorithm
+   * \image html clarkeFormula.gif
+   * where <code>Ia</code> and <code>Ib</code> are the instantaneous stator phases and
+   * <code>pIalpha</code> and <code>pIbeta</code> are the two coordinates of time invariant vector.
+   * \par Fixed-Point Behavior
+   * Care must be taken when using the Q31 version of the Clarke transform.
+   * In particular, the overflow and saturation behavior of the accumulator used must be considered.
+   * Refer to the function specific documentation below for usage guidelines.
+   */
+
+  /**
+   * @addtogroup clarke
+   * @{
+   */
+
+  /**
+   *
+   * @brief  Floating-point Clarke transform
+   * @param[in]  Ia       input three-phase coordinate <code>a</code>
+   * @param[in]  Ib       input three-phase coordinate <code>b</code>
+   * @param[out] pIalpha  points to output two-phase orthogonal vector axis alpha
+   * @param[out] pIbeta   points to output two-phase orthogonal vector axis beta
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_clarke_f32(
+  float32_t Ia,
+  float32_t Ib,
+  float32_t * pIalpha,
+  float32_t * pIbeta)
+  {
+    /* Calculate pIalpha using the equation, pIalpha = Ia */
+    *pIalpha = Ia;
+
+    /* Calculate pIbeta using the equation, pIbeta = (1/sqrt(3)) * Ia + (2/sqrt(3)) * Ib */
+    *pIbeta = ((float32_t) 0.57735026919 * Ia + (float32_t) 1.15470053838 * Ib);
+  }
+
+
+  /**
+   * @brief  Clarke transform for Q31 version
+   * @param[in]  Ia       input three-phase coordinate <code>a</code>
+   * @param[in]  Ib       input three-phase coordinate <code>b</code>
+   * @param[out] pIalpha  points to output two-phase orthogonal vector axis alpha
+   * @param[out] pIbeta   points to output two-phase orthogonal vector axis beta
+   *
+   * <b>Scaling and Overflow Behavior:</b>
+   * \par
+   * The function is implemented using an internal 32-bit accumulator.
+   * The accumulator maintains 1.31 format by truncating lower 31 bits of the intermediate multiplication in 2.62 format.
+   * There is saturation on the addition, hence there is no risk of overflow.
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_clarke_q31(
+  q31_t Ia,
+  q31_t Ib,
+  q31_t * pIalpha,
+  q31_t * pIbeta)
+  {
+    q31_t product1, product2;                    /* Temporary variables used to store intermediate results */
+
+    /* Calculating pIalpha from Ia by equation pIalpha = Ia */
+    *pIalpha = Ia;
+
+    /* Intermediate product is calculated by (1/(sqrt(3)) * Ia) */
+    product1 = (q31_t) (((q63_t) Ia * 0x24F34E8B) >> 30);
+
+    /* Intermediate product is calculated by (2/sqrt(3) * Ib) */
+    product2 = (q31_t) (((q63_t) Ib * 0x49E69D16) >> 30);
+
+    /* pIbeta is calculated by adding the intermediate products */
+    *pIbeta = __QADD(product1, product2);
+  }
+
+  /**
+   * @} end of clarke group
+   */
+
+  /**
+   * @brief  Converts the elements of the Q7 vector to Q31 vector.
+   * @param[in]  pSrc       input pointer
+   * @param[out] pDst       output pointer
+   * @param[in]  blockSize  number of samples to process
+   */
+  void arm_q7_to_q31(
+  q7_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+
+  /**
+   * @ingroup groupController
+   */
+
+  /**
+   * @defgroup inv_clarke Vector Inverse Clarke Transform
+   * Inverse Clarke transform converts the two-coordinate time invariant vector into instantaneous stator phases.
+   *
+   * The function operates on a single sample of data and each call to the function returns the processed output.
+   * The library provides separate functions for Q31 and floating-point data types.
+   * \par Algorithm
+   * \image html clarkeInvFormula.gif
+   * where <code>pIa</code> and <code>pIb</code> are the instantaneous stator phases and
+   * <code>Ialpha</code> and <code>Ibeta</code> are the two coordinates of time invariant vector.
+   * \par Fixed-Point Behavior
+   * Care must be taken when using the Q31 version of the Clarke transform.
+   * In particular, the overflow and saturation behavior of the accumulator used must be considered.
+   * Refer to the function specific documentation below for usage guidelines.
+   */
+
+  /**
+   * @addtogroup inv_clarke
+   * @{
+   */
+
+   /**
+   * @brief  Floating-point Inverse Clarke transform
+   * @param[in]  Ialpha  input two-phase orthogonal vector axis alpha
+   * @param[in]  Ibeta   input two-phase orthogonal vector axis beta
+   * @param[out] pIa     points to output three-phase coordinate <code>a</code>
+   * @param[out] pIb     points to output three-phase coordinate <code>b</code>
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_inv_clarke_f32(
+  float32_t Ialpha,
+  float32_t Ibeta,
+  float32_t * pIa,
+  float32_t * pIb)
+  {
+    /* Calculating pIa from Ialpha by equation pIa = Ialpha */
+    *pIa = Ialpha;
+
+    /* Calculating pIb from Ialpha and Ibeta by equation pIb = -(1/2) * Ialpha + (sqrt(3)/2) * Ibeta */
+    *pIb = -0.5f * Ialpha + 0.8660254039f * Ibeta;
+  }
+
+
+  /**
+   * @brief  Inverse Clarke transform for Q31 version
+   * @param[in]  Ialpha  input two-phase orthogonal vector axis alpha
+   * @param[in]  Ibeta   input two-phase orthogonal vector axis beta
+   * @param[out] pIa     points to output three-phase coordinate <code>a</code>
+   * @param[out] pIb     points to output three-phase coordinate <code>b</code>
+   *
+   * <b>Scaling and Overflow Behavior:</b>
+   * \par
+   * The function is implemented using an internal 32-bit accumulator.
+   * The accumulator maintains 1.31 format by truncating lower 31 bits of the intermediate multiplication in 2.62 format.
+   * There is saturation on the subtraction, hence there is no risk of overflow.
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_inv_clarke_q31(
+  q31_t Ialpha,
+  q31_t Ibeta,
+  q31_t * pIa,
+  q31_t * pIb)
+  {
+    q31_t product1, product2;                    /* Temporary variables used to store intermediate results */
+
+    /* Calculating pIa from Ialpha by equation pIa = Ialpha */
+    *pIa = Ialpha;
+
+    /* Intermediate product is calculated by (1/(2*sqrt(3)) * Ia) */
+    product1 = (q31_t) (((q63_t) (Ialpha) * (0x40000000)) >> 31);
+
+    /* Intermediate product is calculated by (1/sqrt(3) * pIb) */
+    product2 = (q31_t) (((q63_t) (Ibeta) * (0x6ED9EBA1)) >> 31);
+
+    /* pIb is calculated by subtracting the products */
+    *pIb = __QSUB(product2, product1);
+  }
+
+  /**
+   * @} end of inv_clarke group
+   */
+
+  /**
+   * @brief  Converts the elements of the Q7 vector to Q15 vector.
+   * @param[in]  pSrc       input pointer
+   * @param[out] pDst       output pointer
+   * @param[in]  blockSize  number of samples to process
+   */
+  void arm_q7_to_q15(
+  q7_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+
+  /**
+   * @ingroup groupController
+   */
+
+  /**
+   * @defgroup park Vector Park Transform
+   *
+   * Forward Park transform converts the input two-coordinate vector to flux and torque components.
+   * The Park transform can be used to realize the transformation of the <code>Ialpha</code> and the <code>Ibeta</code> currents
+   * from the stationary to the moving reference frame and control the spatial relationship between
+   * the stator vector current and rotor flux vector.
+   * If we consider the d axis aligned with the rotor flux, the diagram below shows the
+   * current vector and the relationship from the two reference frames:
+   * \image html park.gif "Stator current space vector and its component in (a,b) and in the d,q rotating reference frame"
+   *
+   * The function operates on a single sample of data and each call to the function returns the processed output.
+   * The library provides separate functions for Q31 and floating-point data types.
+   * \par Algorithm
+   * \image html parkFormula.gif
+   * where <code>Ialpha</code> and <code>Ibeta</code> are the stator vector components,
+   * <code>pId</code> and <code>pIq</code> are rotor vector components and <code>cosVal</code> and <code>sinVal</code> are the
+   * cosine and sine values of theta (rotor flux position).
+   * \par Fixed-Point Behavior
+   * Care must be taken when using the Q31 version of the Park transform.
+   * In particular, the overflow and saturation behavior of the accumulator used must be considered.
+   * Refer to the function specific documentation below for usage guidelines.
+   */
+
+  /**
+   * @addtogroup park
+   * @{
+   */
+
+  /**
+   * @brief Floating-point Park transform
+   * @param[in]  Ialpha  input two-phase vector coordinate alpha
+   * @param[in]  Ibeta   input two-phase vector coordinate beta
+   * @param[out] pId     points to output   rotor reference frame d
+   * @param[out] pIq     points to output   rotor reference frame q
+   * @param[in]  sinVal  sine value of rotation angle theta
+   * @param[in]  cosVal  cosine value of rotation angle theta
+   *
+   * The function implements the forward Park transform.
+   *
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_park_f32(
+  float32_t Ialpha,
+  float32_t Ibeta,
+  float32_t * pId,
+  float32_t * pIq,
+  float32_t sinVal,
+  float32_t cosVal)
+  {
+    /* Calculate pId using the equation, pId = Ialpha * cosVal + Ibeta * sinVal */
+    *pId = Ialpha * cosVal + Ibeta * sinVal;
+
+    /* Calculate pIq using the equation, pIq = - Ialpha * sinVal + Ibeta * cosVal */
+    *pIq = -Ialpha * sinVal + Ibeta * cosVal;
+  }
+
+
+  /**
+   * @brief  Park transform for Q31 version
+   * @param[in]  Ialpha  input two-phase vector coordinate alpha
+   * @param[in]  Ibeta   input two-phase vector coordinate beta
+   * @param[out] pId     points to output rotor reference frame d
+   * @param[out] pIq     points to output rotor reference frame q
+   * @param[in]  sinVal  sine value of rotation angle theta
+   * @param[in]  cosVal  cosine value of rotation angle theta
+   *
+   * <b>Scaling and Overflow Behavior:</b>
+   * \par
+   * The function is implemented using an internal 32-bit accumulator.
+   * The accumulator maintains 1.31 format by truncating lower 31 bits of the intermediate multiplication in 2.62 format.
+   * There is saturation on the addition and subtraction, hence there is no risk of overflow.
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_park_q31(
+  q31_t Ialpha,
+  q31_t Ibeta,
+  q31_t * pId,
+  q31_t * pIq,
+  q31_t sinVal,
+  q31_t cosVal)
+  {
+    q31_t product1, product2;                    /* Temporary variables used to store intermediate results */
+    q31_t product3, product4;                    /* Temporary variables used to store intermediate results */
+
+    /* Intermediate product is calculated by (Ialpha * cosVal) */
+    product1 = (q31_t) (((q63_t) (Ialpha) * (cosVal)) >> 31);
+
+    /* Intermediate product is calculated by (Ibeta * sinVal) */
+    product2 = (q31_t) (((q63_t) (Ibeta) * (sinVal)) >> 31);
+
+
+    /* Intermediate product is calculated by (Ialpha * sinVal) */
+    product3 = (q31_t) (((q63_t) (Ialpha) * (sinVal)) >> 31);
+
+    /* Intermediate product is calculated by (Ibeta * cosVal) */
+    product4 = (q31_t) (((q63_t) (Ibeta) * (cosVal)) >> 31);
+
+    /* Calculate pId by adding the two intermediate products 1 and 2 */
+    *pId = __QADD(product1, product2);
+
+    /* Calculate pIq by subtracting the two intermediate products 3 from 4 */
+    *pIq = __QSUB(product4, product3);
+  }
+
+  /**
+   * @} end of park group
+   */
+
+  /**
+   * @brief  Converts the elements of the Q7 vector to floating-point vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[out] pDst       is output pointer
+   * @param[in]  blockSize  is the number of samples to process
+   */
+  void arm_q7_to_float(
+  q7_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @ingroup groupController
+   */
+
+  /**
+   * @defgroup inv_park Vector Inverse Park transform
+   * Inverse Park transform converts the input flux and torque components to two-coordinate vector.
+   *
+   * The function operates on a single sample of data and each call to the function returns the processed output.
+   * The library provides separate functions for Q31 and floating-point data types.
+   * \par Algorithm
+   * \image html parkInvFormula.gif
+   * where <code>pIalpha</code> and <code>pIbeta</code> are the stator vector components,
+   * <code>Id</code> and <code>Iq</code> are rotor vector components and <code>cosVal</code> and <code>sinVal</code> are the
+   * cosine and sine values of theta (rotor flux position).
+   * \par Fixed-Point Behavior
+   * Care must be taken when using the Q31 version of the Park transform.
+   * In particular, the overflow and saturation behavior of the accumulator used must be considered.
+   * Refer to the function specific documentation below for usage guidelines.
+   */
+
+  /**
+   * @addtogroup inv_park
+   * @{
+   */
+
+   /**
+   * @brief  Floating-point Inverse Park transform
+   * @param[in]  Id       input coordinate of rotor reference frame d
+   * @param[in]  Iq       input coordinate of rotor reference frame q
+   * @param[out] pIalpha  points to output two-phase orthogonal vector axis alpha
+   * @param[out] pIbeta   points to output two-phase orthogonal vector axis beta
+   * @param[in]  sinVal   sine value of rotation angle theta
+   * @param[in]  cosVal   cosine value of rotation angle theta
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_inv_park_f32(
+  float32_t Id,
+  float32_t Iq,
+  float32_t * pIalpha,
+  float32_t * pIbeta,
+  float32_t sinVal,
+  float32_t cosVal)
+  {
+    /* Calculate pIalpha using the equation, pIalpha = Id * cosVal - Iq * sinVal */
+    *pIalpha = Id * cosVal - Iq * sinVal;
+
+    /* Calculate pIbeta using the equation, pIbeta = Id * sinVal + Iq * cosVal */
+    *pIbeta = Id * sinVal + Iq * cosVal;
+  }
+
+
+  /**
+   * @brief  Inverse Park transform for   Q31 version
+   * @param[in]  Id       input coordinate of rotor reference frame d
+   * @param[in]  Iq       input coordinate of rotor reference frame q
+   * @param[out] pIalpha  points to output two-phase orthogonal vector axis alpha
+   * @param[out] pIbeta   points to output two-phase orthogonal vector axis beta
+   * @param[in]  sinVal   sine value of rotation angle theta
+   * @param[in]  cosVal   cosine value of rotation angle theta
+   *
+   * <b>Scaling and Overflow Behavior:</b>
+   * \par
+   * The function is implemented using an internal 32-bit accumulator.
+   * The accumulator maintains 1.31 format by truncating lower 31 bits of the intermediate multiplication in 2.62 format.
+   * There is saturation on the addition, hence there is no risk of overflow.
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_inv_park_q31(
+  q31_t Id,
+  q31_t Iq,
+  q31_t * pIalpha,
+  q31_t * pIbeta,
+  q31_t sinVal,
+  q31_t cosVal)
+  {
+    q31_t product1, product2;                    /* Temporary variables used to store intermediate results */
+    q31_t product3, product4;                    /* Temporary variables used to store intermediate results */
+
+    /* Intermediate product is calculated by (Id * cosVal) */
+    product1 = (q31_t) (((q63_t) (Id) * (cosVal)) >> 31);
+
+    /* Intermediate product is calculated by (Iq * sinVal) */
+    product2 = (q31_t) (((q63_t) (Iq) * (sinVal)) >> 31);
+
+
+    /* Intermediate product is calculated by (Id * sinVal) */
+    product3 = (q31_t) (((q63_t) (Id) * (sinVal)) >> 31);
+
+    /* Intermediate product is calculated by (Iq * cosVal) */
+    product4 = (q31_t) (((q63_t) (Iq) * (cosVal)) >> 31);
+
+    /* Calculate pIalpha by using the two intermediate products 1 and 2 */
+    *pIalpha = __QSUB(product1, product2);
+
+    /* Calculate pIbeta by using the two intermediate products 3 and 4 */
+    *pIbeta = __QADD(product4, product3);
+  }
+
+  /**
+   * @} end of Inverse park group
+   */
+
+
+  /**
+   * @brief  Converts the elements of the Q31 vector to floating-point vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[out] pDst       is output pointer
+   * @param[in]  blockSize  is the number of samples to process
+   */
+  void arm_q31_to_float(
+  q31_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+  /**
+   * @ingroup groupInterpolation
+   */
+
+  /**
+   * @defgroup LinearInterpolate Linear Interpolation
+   *
+   * Linear interpolation is a method of curve fitting using linear polynomials.
+   * Linear interpolation works by effectively drawing a straight line between two neighboring samples and returning the appropriate point along that line
+   *
+   * \par
+   * \image html LinearInterp.gif "Linear interpolation"
+   *
+   * \par
+   * A  Linear Interpolate function calculates an output value(y), for the input(x)
+   * using linear interpolation of the input values x0, x1( nearest input values) and the output values y0 and y1(nearest output values)
+   *
+   * \par Algorithm:
+   * <pre>
+   *       y = y0 + (x - x0) * ((y1 - y0)/(x1-x0))
+   *       where x0, x1 are nearest values of input x
+   *             y0, y1 are nearest values to output y
+   * </pre>
+   *
+   * \par
+   * This set of functions implements Linear interpolation process
+   * for Q7, Q15, Q31, and floating-point data types.  The functions operate on a single
+   * sample of data and each call to the function returns a single processed value.
+   * <code>S</code> points to an instance of the Linear Interpolate function data structure.
+   * <code>x</code> is the input sample value. The functions returns the output value.
+   *
+   * \par
+   * if x is outside of the table boundary, Linear interpolation returns first value of the table
+   * if x is below input range and returns last value of table if x is above range.
+   */
+
+  /**
+   * @addtogroup LinearInterpolate
+   * @{
+   */
+
+  /**
+   * @brief  Process function for the floating-point Linear Interpolation Function.
+   * @param[in,out] S  is an instance of the floating-point Linear Interpolation structure
+   * @param[in]     x  input sample to process
+   * @return y processed output sample.
+   *
+   */
+  CMSIS_INLINE __STATIC_INLINE float32_t arm_linear_interp_f32(
+  arm_linear_interp_instance_f32 * S,
+  float32_t x)
+  {
+    float32_t y;
+    float32_t x0, x1;                            /* Nearest input values */
+    float32_t y0, y1;                            /* Nearest output values */
+    float32_t xSpacing = S->xSpacing;            /* spacing between input values */
+    int32_t i;                                   /* Index variable */
+    float32_t *pYData = S->pYData;               /* pointer to output table */
+
+    /* Calculation of index */
+    i = (int32_t) ((x - S->x1) / xSpacing);
+
+    if (i < 0)
+    {
+      /* Iniatilize output for below specified range as least output value of table */
+      y = pYData[0];
+    }
+    else if ((uint32_t)i >= S->nValues)
+    {
+      /* Iniatilize output for above specified range as last output value of table */
+      y = pYData[S->nValues - 1];
+    }
+    else
+    {
+      /* Calculation of nearest input values */
+      x0 = S->x1 +  i      * xSpacing;
+      x1 = S->x1 + (i + 1) * xSpacing;
+
+      /* Read of nearest output values */
+      y0 = pYData[i];
+      y1 = pYData[i + 1];
+
+      /* Calculation of output */
+      y = y0 + (x - x0) * ((y1 - y0) / (x1 - x0));
+
+    }
+
+    /* returns output value */
+    return (y);
+  }
+
+
+   /**
+   *
+   * @brief  Process function for the Q31 Linear Interpolation Function.
+   * @param[in] pYData   pointer to Q31 Linear Interpolation table
+   * @param[in] x        input sample to process
+   * @param[in] nValues  number of table values
+   * @return y processed output sample.
+   *
+   * \par
+   * Input sample <code>x</code> is in 12.20 format which contains 12 bits for table index and 20 bits for fractional part.
+   * This function can support maximum of table size 2^12.
+   *
+   */
+  CMSIS_INLINE __STATIC_INLINE q31_t arm_linear_interp_q31(
+  q31_t * pYData,
+  q31_t x,
+  uint32_t nValues)
+  {
+    q31_t y;                                     /* output */
+    q31_t y0, y1;                                /* Nearest output values */
+    q31_t fract;                                 /* fractional part */
+    int32_t index;                               /* Index to read nearest output values */
+
+    /* Input is in 12.20 format */
+    /* 12 bits for the table index */
+    /* Index value calculation */
+    index = ((x & (q31_t)0xFFF00000) >> 20);
+
+    if (index >= (int32_t)(nValues - 1))
+    {
+      return (pYData[nValues - 1]);
+    }
+    else if (index < 0)
+    {
+      return (pYData[0]);
+    }
+    else
+    {
+      /* 20 bits for the fractional part */
+      /* shift left by 11 to keep fract in 1.31 format */
+      fract = (x & 0x000FFFFF) << 11;
+
+      /* Read two nearest output values from the index in 1.31(q31) format */
+      y0 = pYData[index];
+      y1 = pYData[index + 1];
+
+      /* Calculation of y0 * (1-fract) and y is in 2.30 format */
+      y = ((q31_t) ((q63_t) y0 * (0x7FFFFFFF - fract) >> 32));
+
+      /* Calculation of y0 * (1-fract) + y1 *fract and y is in 2.30 format */
+      y += ((q31_t) (((q63_t) y1 * fract) >> 32));
+
+      /* Convert y to 1.31 format */
+      return (y << 1U);
+    }
+  }
+
+
+  /**
+   *
+   * @brief  Process function for the Q15 Linear Interpolation Function.
+   * @param[in] pYData   pointer to Q15 Linear Interpolation table
+   * @param[in] x        input sample to process
+   * @param[in] nValues  number of table values
+   * @return y processed output sample.
+   *
+   * \par
+   * Input sample <code>x</code> is in 12.20 format which contains 12 bits for table index and 20 bits for fractional part.
+   * This function can support maximum of table size 2^12.
+   *
+   */
+  CMSIS_INLINE __STATIC_INLINE q15_t arm_linear_interp_q15(
+  q15_t * pYData,
+  q31_t x,
+  uint32_t nValues)
+  {
+    q63_t y;                                     /* output */
+    q15_t y0, y1;                                /* Nearest output values */
+    q31_t fract;                                 /* fractional part */
+    int32_t index;                               /* Index to read nearest output values */
+
+    /* Input is in 12.20 format */
+    /* 12 bits for the table index */
+    /* Index value calculation */
+    index = ((x & (int32_t)0xFFF00000) >> 20);
+
+    if (index >= (int32_t)(nValues - 1))
+    {
+      return (pYData[nValues - 1]);
+    }
+    else if (index < 0)
+    {
+      return (pYData[0]);
+    }
+    else
+    {
+      /* 20 bits for the fractional part */
+      /* fract is in 12.20 format */
+      fract = (x & 0x000FFFFF);
+
+      /* Read two nearest output values from the index */
+      y0 = pYData[index];
+      y1 = pYData[index + 1];
+
+      /* Calculation of y0 * (1-fract) and y is in 13.35 format */
+      y = ((q63_t) y0 * (0xFFFFF - fract));
+
+      /* Calculation of (y0 * (1-fract) + y1 * fract) and y is in 13.35 format */
+      y += ((q63_t) y1 * (fract));
+
+      /* convert y to 1.15 format */
+      return (q15_t) (y >> 20);
+    }
+  }
+
+
+  /**
+   *
+   * @brief  Process function for the Q7 Linear Interpolation Function.
+   * @param[in] pYData   pointer to Q7 Linear Interpolation table
+   * @param[in] x        input sample to process
+   * @param[in] nValues  number of table values
+   * @return y processed output sample.
+   *
+   * \par
+   * Input sample <code>x</code> is in 12.20 format which contains 12 bits for table index and 20 bits for fractional part.
+   * This function can support maximum of table size 2^12.
+   */
+  CMSIS_INLINE __STATIC_INLINE q7_t arm_linear_interp_q7(
+  q7_t * pYData,
+  q31_t x,
+  uint32_t nValues)
+  {
+    q31_t y;                                     /* output */
+    q7_t y0, y1;                                 /* Nearest output values */
+    q31_t fract;                                 /* fractional part */
+    uint32_t index;                              /* Index to read nearest output values */
+
+    /* Input is in 12.20 format */
+    /* 12 bits for the table index */
+    /* Index value calculation */
+    if (x < 0)
+    {
+      return (pYData[0]);
+    }
+    index = (x >> 20) & 0xfff;
+
+    if (index >= (nValues - 1))
+    {
+      return (pYData[nValues - 1]);
+    }
+    else
+    {
+      /* 20 bits for the fractional part */
+      /* fract is in 12.20 format */
+      fract = (x & 0x000FFFFF);
+
+      /* Read two nearest output values from the index and are in 1.7(q7) format */
+      y0 = pYData[index];
+      y1 = pYData[index + 1];
+
+      /* Calculation of y0 * (1-fract ) and y is in 13.27(q27) format */
+      y = ((y0 * (0xFFFFF - fract)));
+
+      /* Calculation of y1 * fract + y0 * (1-fract) and y is in 13.27(q27) format */
+      y += (y1 * fract);
+
+      /* convert y to 1.7(q7) format */
+      return (q7_t) (y >> 20);
+     }
+  }
+
+  /**
+   * @} end of LinearInterpolate group
+   */
+
+  /**
+   * @brief  Fast approximation to the trigonometric sine function for floating-point data.
+   * @param[in] x  input value in radians.
+   * @return  sin(x).
+   */
+  float32_t arm_sin_f32(
+  float32_t x);
+
+
+  /**
+   * @brief  Fast approximation to the trigonometric sine function for Q31 data.
+   * @param[in] x  Scaled input value in radians.
+   * @return  sin(x).
+   */
+  q31_t arm_sin_q31(
+  q31_t x);
+
+
+  /**
+   * @brief  Fast approximation to the trigonometric sine function for Q15 data.
+   * @param[in] x  Scaled input value in radians.
+   * @return  sin(x).
+   */
+  q15_t arm_sin_q15(
+  q15_t x);
+
+
+  /**
+   * @brief  Fast approximation to the trigonometric cosine function for floating-point data.
+   * @param[in] x  input value in radians.
+   * @return  cos(x).
+   */
+  float32_t arm_cos_f32(
+  float32_t x);
+
+
+  /**
+   * @brief Fast approximation to the trigonometric cosine function for Q31 data.
+   * @param[in] x  Scaled input value in radians.
+   * @return  cos(x).
+   */
+  q31_t arm_cos_q31(
+  q31_t x);
+
+
+  /**
+   * @brief  Fast approximation to the trigonometric cosine function for Q15 data.
+   * @param[in] x  Scaled input value in radians.
+   * @return  cos(x).
+   */
+  q15_t arm_cos_q15(
+  q15_t x);
+
+
+  /**
+   * @ingroup groupFastMath
+   */
+
+
+  /**
+   * @defgroup SQRT Square Root
+   *
+   * Computes the square root of a number.
+   * There are separate functions for Q15, Q31, and floating-point data types.
+   * The square root function is computed using the Newton-Raphson algorithm.
+   * This is an iterative algorithm of the form:
+   * <pre>
+   *      x1 = x0 - f(x0)/f'(x0)
+   * </pre>
+   * where <code>x1</code> is the current estimate,
+   * <code>x0</code> is the previous estimate, and
+   * <code>f'(x0)</code> is the derivative of <code>f()</code> evaluated at <code>x0</code>.
+   * For the square root function, the algorithm reduces to:
+   * <pre>
+   *     x0 = in/2                         [initial guess]
+   *     x1 = 1/2 * ( x0 + in / x0)        [each iteration]
+   * </pre>
+   */
+
+
+  /**
+   * @addtogroup SQRT
+   * @{
+   */
+
+  /**
+   * @brief  Floating-point square root function.
+   * @param[in]  in    input value.
+   * @param[out] pOut  square root of input value.
+   * @return The function returns ARM_MATH_SUCCESS if input value is positive value or ARM_MATH_ARGUMENT_ERROR if
+   * <code>in</code> is negative value and returns zero output for negative values.
+   */
+  CMSIS_INLINE __STATIC_INLINE arm_status arm_sqrt_f32(
+  float32_t in,
+  float32_t * pOut)
+  {
+    if (in >= 0.0f)
+    {
+
+#if   (__FPU_USED == 1) && defined ( __CC_ARM   )
+      *pOut = __sqrtf(in);
+#elif (__FPU_USED == 1) && (defined(__ARMCC_VERSION) && (__ARMCC_VERSION >= 6010050))
+      *pOut = __builtin_sqrtf(in);
+#elif (__FPU_USED == 1) && defined(__GNUC__)
+      *pOut = __builtin_sqrtf(in);
+#elif (__FPU_USED == 1) && defined ( __ICCARM__ ) && (__VER__ >= 6040000)
+      __ASM("VSQRT.F32 %0,%1" : "=t"(*pOut) : "t"(in));
+#else
+      *pOut = sqrtf(in);
+#endif
+
+      return (ARM_MATH_SUCCESS);
+    }
+    else
+    {
+      *pOut = 0.0f;
+      return (ARM_MATH_ARGUMENT_ERROR);
+    }
+  }
+
+
+  /**
+   * @brief Q31 square root function.
+   * @param[in]  in    input value.  The range of the input value is [0 +1) or 0x00000000 to 0x7FFFFFFF.
+   * @param[out] pOut  square root of input value.
+   * @return The function returns ARM_MATH_SUCCESS if input value is positive value or ARM_MATH_ARGUMENT_ERROR if
+   * <code>in</code> is negative value and returns zero output for negative values.
+   */
+  arm_status arm_sqrt_q31(
+  q31_t in,
+  q31_t * pOut);
+
+
+  /**
+   * @brief  Q15 square root function.
+   * @param[in]  in    input value.  The range of the input value is [0 +1) or 0x0000 to 0x7FFF.
+   * @param[out] pOut  square root of input value.
+   * @return The function returns ARM_MATH_SUCCESS if input value is positive value or ARM_MATH_ARGUMENT_ERROR if
+   * <code>in</code> is negative value and returns zero output for negative values.
+   */
+  arm_status arm_sqrt_q15(
+  q15_t in,
+  q15_t * pOut);
+
+  /**
+   * @} end of SQRT group
+   */
+
+
+  /**
+   * @brief floating-point Circular write function.
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_circularWrite_f32(
+  int32_t * circBuffer,
+  int32_t L,
+  uint16_t * writeOffset,
+  int32_t bufferInc,
+  const int32_t * src,
+  int32_t srcInc,
+  uint32_t blockSize)
+  {
+    uint32_t i = 0U;
+    int32_t wOffset;
+
+    /* Copy the value of Index pointer that points
+     * to the current location where the input samples to be copied */
+    wOffset = *writeOffset;
+
+    /* Loop over the blockSize */
+    i = blockSize;
+
+    while (i > 0U)
+    {
+      /* copy the input sample to the circular buffer */
+      circBuffer[wOffset] = *src;
+
+      /* Update the input pointer */
+      src += srcInc;
+
+      /* Circularly update wOffset.  Watch out for positive and negative value */
+      wOffset += bufferInc;
+      if (wOffset >= L)
+        wOffset -= L;
+
+      /* Decrement the loop counter */
+      i--;
+    }
+
+    /* Update the index pointer */
+    *writeOffset = (uint16_t)wOffset;
+  }
+
+
+
+  /**
+   * @brief floating-point Circular Read function.
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_circularRead_f32(
+  int32_t * circBuffer,
+  int32_t L,
+  int32_t * readOffset,
+  int32_t bufferInc,
+  int32_t * dst,
+  int32_t * dst_base,
+  int32_t dst_length,
+  int32_t dstInc,
+  uint32_t blockSize)
+  {
+    uint32_t i = 0U;
+    int32_t rOffset, dst_end;
+
+    /* Copy the value of Index pointer that points
+     * to the current location from where the input samples to be read */
+    rOffset = *readOffset;
+    dst_end = (int32_t) (dst_base + dst_length);
+
+    /* Loop over the blockSize */
+    i = blockSize;
+
+    while (i > 0U)
+    {
+      /* copy the sample from the circular buffer to the destination buffer */
+      *dst = circBuffer[rOffset];
+
+      /* Update the input pointer */
+      dst += dstInc;
+
+      if (dst == (int32_t *) dst_end)
+      {
+        dst = dst_base;
+      }
+
+      /* Circularly update rOffset.  Watch out for positive and negative value  */
+      rOffset += bufferInc;
+
+      if (rOffset >= L)
+      {
+        rOffset -= L;
+      }
+
+      /* Decrement the loop counter */
+      i--;
+    }
+
+    /* Update the index pointer */
+    *readOffset = rOffset;
+  }
+
+
+  /**
+   * @brief Q15 Circular write function.
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_circularWrite_q15(
+  q15_t * circBuffer,
+  int32_t L,
+  uint16_t * writeOffset,
+  int32_t bufferInc,
+  const q15_t * src,
+  int32_t srcInc,
+  uint32_t blockSize)
+  {
+    uint32_t i = 0U;
+    int32_t wOffset;
+
+    /* Copy the value of Index pointer that points
+     * to the current location where the input samples to be copied */
+    wOffset = *writeOffset;
+
+    /* Loop over the blockSize */
+    i = blockSize;
+
+    while (i > 0U)
+    {
+      /* copy the input sample to the circular buffer */
+      circBuffer[wOffset] = *src;
+
+      /* Update the input pointer */
+      src += srcInc;
+
+      /* Circularly update wOffset.  Watch out for positive and negative value */
+      wOffset += bufferInc;
+      if (wOffset >= L)
+        wOffset -= L;
+
+      /* Decrement the loop counter */
+      i--;
+    }
+
+    /* Update the index pointer */
+    *writeOffset = (uint16_t)wOffset;
+  }
+
+
+  /**
+   * @brief Q15 Circular Read function.
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_circularRead_q15(
+  q15_t * circBuffer,
+  int32_t L,
+  int32_t * readOffset,
+  int32_t bufferInc,
+  q15_t * dst,
+  q15_t * dst_base,
+  int32_t dst_length,
+  int32_t dstInc,
+  uint32_t blockSize)
+  {
+    uint32_t i = 0;
+    int32_t rOffset, dst_end;
+
+    /* Copy the value of Index pointer that points
+     * to the current location from where the input samples to be read */
+    rOffset = *readOffset;
+
+    dst_end = (int32_t) (dst_base + dst_length);
+
+    /* Loop over the blockSize */
+    i = blockSize;
+
+    while (i > 0U)
+    {
+      /* copy the sample from the circular buffer to the destination buffer */
+      *dst = circBuffer[rOffset];
+
+      /* Update the input pointer */
+      dst += dstInc;
+
+      if (dst == (q15_t *) dst_end)
+      {
+        dst = dst_base;
+      }
+
+      /* Circularly update wOffset.  Watch out for positive and negative value */
+      rOffset += bufferInc;
+
+      if (rOffset >= L)
+      {
+        rOffset -= L;
+      }
+
+      /* Decrement the loop counter */
+      i--;
+    }
+
+    /* Update the index pointer */
+    *readOffset = rOffset;
+  }
+
+
+  /**
+   * @brief Q7 Circular write function.
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_circularWrite_q7(
+  q7_t * circBuffer,
+  int32_t L,
+  uint16_t * writeOffset,
+  int32_t bufferInc,
+  const q7_t * src,
+  int32_t srcInc,
+  uint32_t blockSize)
+  {
+    uint32_t i = 0U;
+    int32_t wOffset;
+
+    /* Copy the value of Index pointer that points
+     * to the current location where the input samples to be copied */
+    wOffset = *writeOffset;
+
+    /* Loop over the blockSize */
+    i = blockSize;
+
+    while (i > 0U)
+    {
+      /* copy the input sample to the circular buffer */
+      circBuffer[wOffset] = *src;
+
+      /* Update the input pointer */
+      src += srcInc;
+
+      /* Circularly update wOffset.  Watch out for positive and negative value */
+      wOffset += bufferInc;
+      if (wOffset >= L)
+        wOffset -= L;
+
+      /* Decrement the loop counter */
+      i--;
+    }
+
+    /* Update the index pointer */
+    *writeOffset = (uint16_t)wOffset;
+  }
+
+
+  /**
+   * @brief Q7 Circular Read function.
+   */
+  CMSIS_INLINE __STATIC_INLINE void arm_circularRead_q7(
+  q7_t * circBuffer,
+  int32_t L,
+  int32_t * readOffset,
+  int32_t bufferInc,
+  q7_t * dst,
+  q7_t * dst_base,
+  int32_t dst_length,
+  int32_t dstInc,
+  uint32_t blockSize)
+  {
+    uint32_t i = 0;
+    int32_t rOffset, dst_end;
+
+    /* Copy the value of Index pointer that points
+     * to the current location from where the input samples to be read */
+    rOffset = *readOffset;
+
+    dst_end = (int32_t) (dst_base + dst_length);
+
+    /* Loop over the blockSize */
+    i = blockSize;
+
+    while (i > 0U)
+    {
+      /* copy the sample from the circular buffer to the destination buffer */
+      *dst = circBuffer[rOffset];
+
+      /* Update the input pointer */
+      dst += dstInc;
+
+      if (dst == (q7_t *) dst_end)
+      {
+        dst = dst_base;
+      }
+
+      /* Circularly update rOffset.  Watch out for positive and negative value */
+      rOffset += bufferInc;
+
+      if (rOffset >= L)
+      {
+        rOffset -= L;
+      }
+
+      /* Decrement the loop counter */
+      i--;
+    }
+
+    /* Update the index pointer */
+    *readOffset = rOffset;
+  }
+
+
+  /**
+   * @brief  Sum of the squares of the elements of a Q31 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_power_q31(
+  q31_t * pSrc,
+  uint32_t blockSize,
+  q63_t * pResult);
+
+
+  /**
+   * @brief  Sum of the squares of the elements of a floating-point vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_power_f32(
+  float32_t * pSrc,
+  uint32_t blockSize,
+  float32_t * pResult);
+
+
+  /**
+   * @brief  Sum of the squares of the elements of a Q15 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_power_q15(
+  q15_t * pSrc,
+  uint32_t blockSize,
+  q63_t * pResult);
+
+
+  /**
+   * @brief  Sum of the squares of the elements of a Q7 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_power_q7(
+  q7_t * pSrc,
+  uint32_t blockSize,
+  q31_t * pResult);
+
+
+  /**
+   * @brief  Mean value of a Q7 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_mean_q7(
+  q7_t * pSrc,
+  uint32_t blockSize,
+  q7_t * pResult);
+
+
+  /**
+   * @brief  Mean value of a Q15 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_mean_q15(
+  q15_t * pSrc,
+  uint32_t blockSize,
+  q15_t * pResult);
+
+
+  /**
+   * @brief  Mean value of a Q31 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_mean_q31(
+  q31_t * pSrc,
+  uint32_t blockSize,
+  q31_t * pResult);
+
+
+  /**
+   * @brief  Mean value of a floating-point vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_mean_f32(
+  float32_t * pSrc,
+  uint32_t blockSize,
+  float32_t * pResult);
+
+
+  /**
+   * @brief  Variance of the elements of a floating-point vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_var_f32(
+  float32_t * pSrc,
+  uint32_t blockSize,
+  float32_t * pResult);
+
+
+  /**
+   * @brief  Variance of the elements of a Q31 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_var_q31(
+  q31_t * pSrc,
+  uint32_t blockSize,
+  q31_t * pResult);
+
+
+  /**
+   * @brief  Variance of the elements of a Q15 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_var_q15(
+  q15_t * pSrc,
+  uint32_t blockSize,
+  q15_t * pResult);
+
+
+  /**
+   * @brief  Root Mean Square of the elements of a floating-point vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_rms_f32(
+  float32_t * pSrc,
+  uint32_t blockSize,
+  float32_t * pResult);
+
+
+  /**
+   * @brief  Root Mean Square of the elements of a Q31 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_rms_q31(
+  q31_t * pSrc,
+  uint32_t blockSize,
+  q31_t * pResult);
+
+
+  /**
+   * @brief  Root Mean Square of the elements of a Q15 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_rms_q15(
+  q15_t * pSrc,
+  uint32_t blockSize,
+  q15_t * pResult);
+
+
+  /**
+   * @brief  Standard deviation of the elements of a floating-point vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_std_f32(
+  float32_t * pSrc,
+  uint32_t blockSize,
+  float32_t * pResult);
+
+
+  /**
+   * @brief  Standard deviation of the elements of a Q31 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_std_q31(
+  q31_t * pSrc,
+  uint32_t blockSize,
+  q31_t * pResult);
+
+
+  /**
+   * @brief  Standard deviation of the elements of a Q15 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output value.
+   */
+  void arm_std_q15(
+  q15_t * pSrc,
+  uint32_t blockSize,
+  q15_t * pResult);
+
+
+  /**
+   * @brief  Floating-point complex magnitude
+   * @param[in]  pSrc        points to the complex input vector
+   * @param[out] pDst        points to the real output vector
+   * @param[in]  numSamples  number of complex samples in the input vector
+   */
+  void arm_cmplx_mag_f32(
+  float32_t * pSrc,
+  float32_t * pDst,
+  uint32_t numSamples);
+
+
+  /**
+   * @brief  Q31 complex magnitude
+   * @param[in]  pSrc        points to the complex input vector
+   * @param[out] pDst        points to the real output vector
+   * @param[in]  numSamples  number of complex samples in the input vector
+   */
+  void arm_cmplx_mag_q31(
+  q31_t * pSrc,
+  q31_t * pDst,
+  uint32_t numSamples);
+
+
+  /**
+   * @brief  Q15 complex magnitude
+   * @param[in]  pSrc        points to the complex input vector
+   * @param[out] pDst        points to the real output vector
+   * @param[in]  numSamples  number of complex samples in the input vector
+   */
+  void arm_cmplx_mag_q15(
+  q15_t * pSrc,
+  q15_t * pDst,
+  uint32_t numSamples);
+
+
+  /**
+   * @brief  Q15 complex dot product
+   * @param[in]  pSrcA       points to the first input vector
+   * @param[in]  pSrcB       points to the second input vector
+   * @param[in]  numSamples  number of complex samples in each vector
+   * @param[out] realResult  real part of the result returned here
+   * @param[out] imagResult  imaginary part of the result returned here
+   */
+  void arm_cmplx_dot_prod_q15(
+  q15_t * pSrcA,
+  q15_t * pSrcB,
+  uint32_t numSamples,
+  q31_t * realResult,
+  q31_t * imagResult);
+
+
+  /**
+   * @brief  Q31 complex dot product
+   * @param[in]  pSrcA       points to the first input vector
+   * @param[in]  pSrcB       points to the second input vector
+   * @param[in]  numSamples  number of complex samples in each vector
+   * @param[out] realResult  real part of the result returned here
+   * @param[out] imagResult  imaginary part of the result returned here
+   */
+  void arm_cmplx_dot_prod_q31(
+  q31_t * pSrcA,
+  q31_t * pSrcB,
+  uint32_t numSamples,
+  q63_t * realResult,
+  q63_t * imagResult);
+
+
+  /**
+   * @brief  Floating-point complex dot product
+   * @param[in]  pSrcA       points to the first input vector
+   * @param[in]  pSrcB       points to the second input vector
+   * @param[in]  numSamples  number of complex samples in each vector
+   * @param[out] realResult  real part of the result returned here
+   * @param[out] imagResult  imaginary part of the result returned here
+   */
+  void arm_cmplx_dot_prod_f32(
+  float32_t * pSrcA,
+  float32_t * pSrcB,
+  uint32_t numSamples,
+  float32_t * realResult,
+  float32_t * imagResult);
+
+
+  /**
+   * @brief  Q15 complex-by-real multiplication
+   * @param[in]  pSrcCmplx   points to the complex input vector
+   * @param[in]  pSrcReal    points to the real input vector
+   * @param[out] pCmplxDst   points to the complex output vector
+   * @param[in]  numSamples  number of samples in each vector
+   */
+  void arm_cmplx_mult_real_q15(
+  q15_t * pSrcCmplx,
+  q15_t * pSrcReal,
+  q15_t * pCmplxDst,
+  uint32_t numSamples);
+
+
+  /**
+   * @brief  Q31 complex-by-real multiplication
+   * @param[in]  pSrcCmplx   points to the complex input vector
+   * @param[in]  pSrcReal    points to the real input vector
+   * @param[out] pCmplxDst   points to the complex output vector
+   * @param[in]  numSamples  number of samples in each vector
+   */
+  void arm_cmplx_mult_real_q31(
+  q31_t * pSrcCmplx,
+  q31_t * pSrcReal,
+  q31_t * pCmplxDst,
+  uint32_t numSamples);
+
+
+  /**
+   * @brief  Floating-point complex-by-real multiplication
+   * @param[in]  pSrcCmplx   points to the complex input vector
+   * @param[in]  pSrcReal    points to the real input vector
+   * @param[out] pCmplxDst   points to the complex output vector
+   * @param[in]  numSamples  number of samples in each vector
+   */
+  void arm_cmplx_mult_real_f32(
+  float32_t * pSrcCmplx,
+  float32_t * pSrcReal,
+  float32_t * pCmplxDst,
+  uint32_t numSamples);
+
+
+  /**
+   * @brief  Minimum value of a Q7 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] result     is output pointer
+   * @param[in]  index      is the array index of the minimum value in the input buffer.
+   */
+  void arm_min_q7(
+  q7_t * pSrc,
+  uint32_t blockSize,
+  q7_t * result,
+  uint32_t * index);
+
+
+  /**
+   * @brief  Minimum value of a Q15 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output pointer
+   * @param[in]  pIndex     is the array index of the minimum value in the input buffer.
+   */
+  void arm_min_q15(
+  q15_t * pSrc,
+  uint32_t blockSize,
+  q15_t * pResult,
+  uint32_t * pIndex);
+
+
+  /**
+   * @brief  Minimum value of a Q31 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output pointer
+   * @param[out] pIndex     is the array index of the minimum value in the input buffer.
+   */
+  void arm_min_q31(
+  q31_t * pSrc,
+  uint32_t blockSize,
+  q31_t * pResult,
+  uint32_t * pIndex);
+
+
+  /**
+   * @brief  Minimum value of a floating-point vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[in]  blockSize  is the number of samples to process
+   * @param[out] pResult    is output pointer
+   * @param[out] pIndex     is the array index of the minimum value in the input buffer.
+   */
+  void arm_min_f32(
+  float32_t * pSrc,
+  uint32_t blockSize,
+  float32_t * pResult,
+  uint32_t * pIndex);
+
+
+/**
+ * @brief Maximum value of a Q7 vector.
+ * @param[in]  pSrc       points to the input buffer
+ * @param[in]  blockSize  length of the input vector
+ * @param[out] pResult    maximum value returned here
+ * @param[out] pIndex     index of maximum value returned here
+ */
+  void arm_max_q7(
+  q7_t * pSrc,
+  uint32_t blockSize,
+  q7_t * pResult,
+  uint32_t * pIndex);
+
+
+/**
+ * @brief Maximum value of a Q15 vector.
+ * @param[in]  pSrc       points to the input buffer
+ * @param[in]  blockSize  length of the input vector
+ * @param[out] pResult    maximum value returned here
+ * @param[out] pIndex     index of maximum value returned here
+ */
+  void arm_max_q15(
+  q15_t * pSrc,
+  uint32_t blockSize,
+  q15_t * pResult,
+  uint32_t * pIndex);
+
+
+/**
+ * @brief Maximum value of a Q31 vector.
+ * @param[in]  pSrc       points to the input buffer
+ * @param[in]  blockSize  length of the input vector
+ * @param[out] pResult    maximum value returned here
+ * @param[out] pIndex     index of maximum value returned here
+ */
+  void arm_max_q31(
+  q31_t * pSrc,
+  uint32_t blockSize,
+  q31_t * pResult,
+  uint32_t * pIndex);
+
+
+/**
+ * @brief Maximum value of a floating-point vector.
+ * @param[in]  pSrc       points to the input buffer
+ * @param[in]  blockSize  length of the input vector
+ * @param[out] pResult    maximum value returned here
+ * @param[out] pIndex     index of maximum value returned here
+ */
+  void arm_max_f32(
+  float32_t * pSrc,
+  uint32_t blockSize,
+  float32_t * pResult,
+  uint32_t * pIndex);
+
+
+  /**
+   * @brief  Q15 complex-by-complex multiplication
+   * @param[in]  pSrcA       points to the first input vector
+   * @param[in]  pSrcB       points to the second input vector
+   * @param[out] pDst        points to the output vector
+   * @param[in]  numSamples  number of complex samples in each vector
+   */
+  void arm_cmplx_mult_cmplx_q15(
+  q15_t * pSrcA,
+  q15_t * pSrcB,
+  q15_t * pDst,
+  uint32_t numSamples);
+
+
+  /**
+   * @brief  Q31 complex-by-complex multiplication
+   * @param[in]  pSrcA       points to the first input vector
+   * @param[in]  pSrcB       points to the second input vector
+   * @param[out] pDst        points to the output vector
+   * @param[in]  numSamples  number of complex samples in each vector
+   */
+  void arm_cmplx_mult_cmplx_q31(
+  q31_t * pSrcA,
+  q31_t * pSrcB,
+  q31_t * pDst,
+  uint32_t numSamples);
+
+
+  /**
+   * @brief  Floating-point complex-by-complex multiplication
+   * @param[in]  pSrcA       points to the first input vector
+   * @param[in]  pSrcB       points to the second input vector
+   * @param[out] pDst        points to the output vector
+   * @param[in]  numSamples  number of complex samples in each vector
+   */
+  void arm_cmplx_mult_cmplx_f32(
+  float32_t * pSrcA,
+  float32_t * pSrcB,
+  float32_t * pDst,
+  uint32_t numSamples);
+
+
+  /**
+   * @brief Converts the elements of the floating-point vector to Q31 vector.
+   * @param[in]  pSrc       points to the floating-point input vector
+   * @param[out] pDst       points to the Q31 output vector
+   * @param[in]  blockSize  length of the input vector
+   */
+  void arm_float_to_q31(
+  float32_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Converts the elements of the floating-point vector to Q15 vector.
+   * @param[in]  pSrc       points to the floating-point input vector
+   * @param[out] pDst       points to the Q15 output vector
+   * @param[in]  blockSize  length of the input vector
+   */
+  void arm_float_to_q15(
+  float32_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief Converts the elements of the floating-point vector to Q7 vector.
+   * @param[in]  pSrc       points to the floating-point input vector
+   * @param[out] pDst       points to the Q7 output vector
+   * @param[in]  blockSize  length of the input vector
+   */
+  void arm_float_to_q7(
+  float32_t * pSrc,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Converts the elements of the Q31 vector to Q15 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[out] pDst       is output pointer
+   * @param[in]  blockSize  is the number of samples to process
+   */
+  void arm_q31_to_q15(
+  q31_t * pSrc,
+  q15_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Converts the elements of the Q31 vector to Q7 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[out] pDst       is output pointer
+   * @param[in]  blockSize  is the number of samples to process
+   */
+  void arm_q31_to_q7(
+  q31_t * pSrc,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Converts the elements of the Q15 vector to floating-point vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[out] pDst       is output pointer
+   * @param[in]  blockSize  is the number of samples to process
+   */
+  void arm_q15_to_float(
+  q15_t * pSrc,
+  float32_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Converts the elements of the Q15 vector to Q31 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[out] pDst       is output pointer
+   * @param[in]  blockSize  is the number of samples to process
+   */
+  void arm_q15_to_q31(
+  q15_t * pSrc,
+  q31_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @brief  Converts the elements of the Q15 vector to Q7 vector.
+   * @param[in]  pSrc       is input pointer
+   * @param[out] pDst       is output pointer
+   * @param[in]  blockSize  is the number of samples to process
+   */
+  void arm_q15_to_q7(
+  q15_t * pSrc,
+  q7_t * pDst,
+  uint32_t blockSize);
+
+
+  /**
+   * @ingroup groupInterpolation
+   */
+
+  /**
+   * @defgroup BilinearInterpolate Bilinear Interpolation
+   *
+   * Bilinear interpolation is an extension of linear interpolation applied to a two dimensional grid.
+   * The underlying function <code>f(x, y)</code> is sampled on a regular grid and the interpolation process
+   * determines values between the grid points.
+   * Bilinear interpolation is equivalent to two step linear interpolation, first in the x-dimension and then in the y-dimension.
+   * Bilinear interpolation is often used in image processing to rescale images.
+   * The CMSIS DSP library provides bilinear interpolation functions for Q7, Q15, Q31, and floating-point data types.
+   *
+   * <b>Algorithm</b>
+   * \par
+   * The instance structure used by the bilinear interpolation functions describes a two dimensional data table.
+   * For floating-point, the instance structure is defined as:
+   * <pre>
+   *   typedef struct
+   *   {
+   *     uint16_t numRows;
+   *     uint16_t numCols;
+   *     float32_t *pData;
+   * } arm_bilinear_interp_instance_f32;
+   * </pre>
+   *
+   * \par
+   * where <code>numRows</code> specifies the number of rows in the table;
+   * <code>numCols</code> specifies the number of columns in the table;
+   * and <code>pData</code> points to an array of size <code>numRows*numCols</code> values.
+   * The data table <code>pTable</code> is organized in row order and the supplied data values fall on integer indexes.
+   * That is, table element (x,y) is located at <code>pTable[x + y*numCols]</code> where x and y are integers.
+   *
+   * \par
+   * Let <code>(x, y)</code> specify the desired interpolation point.  Then define:
+   * <pre>
+   *     XF = floor(x)
+   *     YF = floor(y)
+   * </pre>
+   * \par
+   * The interpolated output point is computed as:
+   * <pre>
+   *  f(x, y) = f(XF, YF) * (1-(x-XF)) * (1-(y-YF))
+   *           + f(XF+1, YF) * (x-XF)*(1-(y-YF))
+   *           + f(XF, YF+1) * (1-(x-XF))*(y-YF)
+   *           + f(XF+1, YF+1) * (x-XF)*(y-YF)
+   * </pre>
+   * Note that the coordinates (x, y) contain integer and fractional components.
+   * The integer components specify which portion of the table to use while the
+   * fractional components control the interpolation processor.
+   *
+   * \par
+   * if (x,y) are outside of the table boundary, Bilinear interpolation returns zero output.
+   */
+
+  /**
+   * @addtogroup BilinearInterpolate
+   * @{
+   */
+
+
+  /**
+  *
+  * @brief  Floating-point bilinear interpolation.
+  * @param[in,out] S  points to an instance of the interpolation structure.
+  * @param[in]     X  interpolation coordinate.
+  * @param[in]     Y  interpolation coordinate.
+  * @return out interpolated value.
+  */
+  CMSIS_INLINE __STATIC_INLINE float32_t arm_bilinear_interp_f32(
+  const arm_bilinear_interp_instance_f32 * S,
+  float32_t X,
+  float32_t Y)
+  {
+    float32_t out;
+    float32_t f00, f01, f10, f11;
+    float32_t *pData = S->pData;
+    int32_t xIndex, yIndex, index;
+    float32_t xdiff, ydiff;
+    float32_t b1, b2, b3, b4;
+
+    xIndex = (int32_t) X;
+    yIndex = (int32_t) Y;
+
+    /* Care taken for table outside boundary */
+    /* Returns zero output when values are outside table boundary */
+    if (xIndex < 0 || xIndex > (S->numRows - 1) || yIndex < 0 || yIndex > (S->numCols - 1))
+    {
+      return (0);
+    }
+
+    /* Calculation of index for two nearest points in X-direction */
+    index = (xIndex - 1) + (yIndex - 1) * S->numCols;
+
+
+    /* Read two nearest points in X-direction */
+    f00 = pData[index];
+    f01 = pData[index + 1];
+
+    /* Calculation of index for two nearest points in Y-direction */
+    index = (xIndex - 1) + (yIndex) * S->numCols;
+
+
+    /* Read two nearest points in Y-direction */
+    f10 = pData[index];
+    f11 = pData[index + 1];
+
+    /* Calculation of intermediate values */
+    b1 = f00;
+    b2 = f01 - f00;
+    b3 = f10 - f00;
+    b4 = f00 - f01 - f10 + f11;
+
+    /* Calculation of fractional part in X */
+    xdiff = X - xIndex;
+
+    /* Calculation of fractional part in Y */
+    ydiff = Y - yIndex;
+
+    /* Calculation of bi-linear interpolated output */
+    out = b1 + b2 * xdiff + b3 * ydiff + b4 * xdiff * ydiff;
+
+    /* return to application */
+    return (out);
+  }
+
+
+  /**
+  *
+  * @brief  Q31 bilinear interpolation.
+  * @param[in,out] S  points to an instance of the interpolation structure.
+  * @param[in]     X  interpolation coordinate in 12.20 format.
+  * @param[in]     Y  interpolation coordinate in 12.20 format.
+  * @return out interpolated value.
+  */
+  CMSIS_INLINE __STATIC_INLINE q31_t arm_bilinear_interp_q31(
+  arm_bilinear_interp_instance_q31 * S,
+  q31_t X,
+  q31_t Y)
+  {
+    q31_t out;                                   /* Temporary output */
+    q31_t acc = 0;                               /* output */
+    q31_t xfract, yfract;                        /* X, Y fractional parts */
+    q31_t x1, x2, y1, y2;                        /* Nearest output values */
+    int32_t rI, cI;                              /* Row and column indices */
+    q31_t *pYData = S->pData;                    /* pointer to output table values */
+    uint32_t nCols = S->numCols;                 /* num of rows */
+
+    /* Input is in 12.20 format */
+    /* 12 bits for the table index */
+    /* Index value calculation */
+    rI = ((X & (q31_t)0xFFF00000) >> 20);
+
+    /* Input is in 12.20 format */
+    /* 12 bits for the table index */
+    /* Index value calculation */
+    cI = ((Y & (q31_t)0xFFF00000) >> 20);
+
+    /* Care taken for table outside boundary */
+    /* Returns zero output when values are outside table boundary */
+    if (rI < 0 || rI > (S->numRows - 1) || cI < 0 || cI > (S->numCols - 1))
+    {
+      return (0);
+    }
+
+    /* 20 bits for the fractional part */
+    /* shift left xfract by 11 to keep 1.31 format */
+    xfract = (X & 0x000FFFFF) << 11U;
+
+    /* Read two nearest output values from the index */
+    x1 = pYData[(rI) + (int32_t)nCols * (cI)    ];
+    x2 = pYData[(rI) + (int32_t)nCols * (cI) + 1];
+
+    /* 20 bits for the fractional part */
+    /* shift left yfract by 11 to keep 1.31 format */
+    yfract = (Y & 0x000FFFFF) << 11U;
+
+    /* Read two nearest output values from the index */
+    y1 = pYData[(rI) + (int32_t)nCols * (cI + 1)    ];
+    y2 = pYData[(rI) + (int32_t)nCols * (cI + 1) + 1];
+
+    /* Calculation of x1 * (1-xfract ) * (1-yfract) and acc is in 3.29(q29) format */
+    out = ((q31_t) (((q63_t) x1  * (0x7FFFFFFF - xfract)) >> 32));
+    acc = ((q31_t) (((q63_t) out * (0x7FFFFFFF - yfract)) >> 32));
+
+    /* x2 * (xfract) * (1-yfract)  in 3.29(q29) and adding to acc */
+    out = ((q31_t) ((q63_t) x2 * (0x7FFFFFFF - yfract) >> 32));
+    acc += ((q31_t) ((q63_t) out * (xfract) >> 32));
+
+    /* y1 * (1 - xfract) * (yfract)  in 3.29(q29) and adding to acc */
+    out = ((q31_t) ((q63_t) y1 * (0x7FFFFFFF - xfract) >> 32));
+    acc += ((q31_t) ((q63_t) out * (yfract) >> 32));
+
+    /* y2 * (xfract) * (yfract)  in 3.29(q29) and adding to acc */
+    out = ((q31_t) ((q63_t) y2 * (xfract) >> 32));
+    acc += ((q31_t) ((q63_t) out * (yfract) >> 32));
+
+    /* Convert acc to 1.31(q31) format */
+    return ((q31_t)(acc << 2));
+  }
+
+
+  /**
+  * @brief  Q15 bilinear interpolation.
+  * @param[in,out] S  points to an instance of the interpolation structure.
+  * @param[in]     X  interpolation coordinate in 12.20 format.
+  * @param[in]     Y  interpolation coordinate in 12.20 format.
+  * @return out interpolated value.
+  */
+  CMSIS_INLINE __STATIC_INLINE q15_t arm_bilinear_interp_q15(
+  arm_bilinear_interp_instance_q15 * S,
+  q31_t X,
+  q31_t Y)
+  {
+    q63_t acc = 0;                               /* output */
+    q31_t out;                                   /* Temporary output */
+    q15_t x1, x2, y1, y2;                        /* Nearest output values */
+    q31_t xfract, yfract;                        /* X, Y fractional parts */
+    int32_t rI, cI;                              /* Row and column indices */
+    q15_t *pYData = S->pData;                    /* pointer to output table values */
+    uint32_t nCols = S->numCols;                 /* num of rows */
+
+    /* Input is in 12.20 format */
+    /* 12 bits for the table index */
+    /* Index value calculation */
+    rI = ((X & (q31_t)0xFFF00000) >> 20);
+
+    /* Input is in 12.20 format */
+    /* 12 bits for the table index */
+    /* Index value calculation */
+    cI = ((Y & (q31_t)0xFFF00000) >> 20);
+
+    /* Care taken for table outside boundary */
+    /* Returns zero output when values are outside table boundary */
+    if (rI < 0 || rI > (S->numRows - 1) || cI < 0 || cI > (S->numCols - 1))
+    {
+      return (0);
+    }
+
+    /* 20 bits for the fractional part */
+    /* xfract should be in 12.20 format */
+    xfract = (X & 0x000FFFFF);
+
+    /* Read two nearest output values from the index */
+    x1 = pYData[((uint32_t)rI) + nCols * ((uint32_t)cI)    ];
+    x2 = pYData[((uint32_t)rI) + nCols * ((uint32_t)cI) + 1];
+
+    /* 20 bits for the fractional part */
+    /* yfract should be in 12.20 format */
+    yfract = (Y & 0x000FFFFF);
+
+    /* Read two nearest output values from the index */
+    y1 = pYData[((uint32_t)rI) + nCols * ((uint32_t)cI + 1)    ];
+    y2 = pYData[((uint32_t)rI) + nCols * ((uint32_t)cI + 1) + 1];
+
+    /* Calculation of x1 * (1-xfract ) * (1-yfract) and acc is in 13.51 format */
+
+    /* x1 is in 1.15(q15), xfract in 12.20 format and out is in 13.35 format */
+    /* convert 13.35 to 13.31 by right shifting  and out is in 1.31 */
+    out = (q31_t) (((q63_t) x1 * (0xFFFFF - xfract)) >> 4U);
+    acc = ((q63_t) out * (0xFFFFF - yfract));
+
+    /* x2 * (xfract) * (1-yfract)  in 1.51 and adding to acc */
+    out = (q31_t) (((q63_t) x2 * (0xFFFFF - yfract)) >> 4U);
+    acc += ((q63_t) out * (xfract));
+
+    /* y1 * (1 - xfract) * (yfract)  in 1.51 and adding to acc */
+    out = (q31_t) (((q63_t) y1 * (0xFFFFF - xfract)) >> 4U);
+    acc += ((q63_t) out * (yfract));
+
+    /* y2 * (xfract) * (yfract)  in 1.51 and adding to acc */
+    out = (q31_t) (((q63_t) y2 * (xfract)) >> 4U);
+    acc += ((q63_t) out * (yfract));
+
+    /* acc is in 13.51 format and down shift acc by 36 times */
+    /* Convert out to 1.15 format */
+    return ((q15_t)(acc >> 36));
+  }
+
+
+  /**
+  * @brief  Q7 bilinear interpolation.
+  * @param[in,out] S  points to an instance of the interpolation structure.
+  * @param[in]     X  interpolation coordinate in 12.20 format.
+  * @param[in]     Y  interpolation coordinate in 12.20 format.
+  * @return out interpolated value.
+  */
+  CMSIS_INLINE __STATIC_INLINE q7_t arm_bilinear_interp_q7(
+  arm_bilinear_interp_instance_q7 * S,
+  q31_t X,
+  q31_t Y)
+  {
+    q63_t acc = 0;                               /* output */
+    q31_t out;                                   /* Temporary output */
+    q31_t xfract, yfract;                        /* X, Y fractional parts */
+    q7_t x1, x2, y1, y2;                         /* Nearest output values */
+    int32_t rI, cI;                              /* Row and column indices */
+    q7_t *pYData = S->pData;                     /* pointer to output table values */
+    uint32_t nCols = S->numCols;                 /* num of rows */
+
+    /* Input is in 12.20 format */
+    /* 12 bits for the table index */
+    /* Index value calculation */
+    rI = ((X & (q31_t)0xFFF00000) >> 20);
+
+    /* Input is in 12.20 format */
+    /* 12 bits for the table index */
+    /* Index value calculation */
+    cI = ((Y & (q31_t)0xFFF00000) >> 20);
+
+    /* Care taken for table outside boundary */
+    /* Returns zero output when values are outside table boundary */
+    if (rI < 0 || rI > (S->numRows - 1) || cI < 0 || cI > (S->numCols - 1))
+    {
+      return (0);
+    }
+
+    /* 20 bits for the fractional part */
+    /* xfract should be in 12.20 format */
+    xfract = (X & (q31_t)0x000FFFFF);
+
+    /* Read two nearest output values from the index */
+    x1 = pYData[((uint32_t)rI) + nCols * ((uint32_t)cI)    ];
+    x2 = pYData[((uint32_t)rI) + nCols * ((uint32_t)cI) + 1];
+
+    /* 20 bits for the fractional part */
+    /* yfract should be in 12.20 format */
+    yfract = (Y & (q31_t)0x000FFFFF);
+
+    /* Read two nearest output values from the index */
+    y1 = pYData[((uint32_t)rI) + nCols * ((uint32_t)cI + 1)    ];
+    y2 = pYData[((uint32_t)rI) + nCols * ((uint32_t)cI + 1) + 1];
+
+    /* Calculation of x1 * (1-xfract ) * (1-yfract) and acc is in 16.47 format */
+    out = ((x1 * (0xFFFFF - xfract)));
+    acc = (((q63_t) out * (0xFFFFF - yfract)));
+
+    /* x2 * (xfract) * (1-yfract)  in 2.22 and adding to acc */
+    out = ((x2 * (0xFFFFF - yfract)));
+    acc += (((q63_t) out * (xfract)));
+
+    /* y1 * (1 - xfract) * (yfract)  in 2.22 and adding to acc */
+    out = ((y1 * (0xFFFFF - xfract)));
+    acc += (((q63_t) out * (yfract)));
+
+    /* y2 * (xfract) * (yfract)  in 2.22 and adding to acc */
+    out = ((y2 * (yfract)));
+    acc += (((q63_t) out * (xfract)));
+
+    /* acc in 16.47 format and down shift by 40 to convert to 1.7 format */
+    return ((q7_t)(acc >> 40));
+  }
+
+  /**
+   * @} end of BilinearInterpolate group
+   */
+
+
+/* SMMLAR */
+#define multAcc_32x32_keep32_R(a, x, y) \
+    a = (q31_t) (((((q63_t) a) << 32) + ((q63_t) x * y) + 0x80000000LL ) >> 32)
+
+/* SMMLSR */
+#define multSub_32x32_keep32_R(a, x, y) \
+    a = (q31_t) (((((q63_t) a) << 32) - ((q63_t) x * y) + 0x80000000LL ) >> 32)
+
+/* SMMULR */
+#define mult_32x32_keep32_R(a, x, y) \
+    a = (q31_t) (((q63_t) x * y + 0x80000000LL ) >> 32)
+
+/* SMMLA */
+#define multAcc_32x32_keep32(a, x, y) \
+    a += (q31_t) (((q63_t) x * y) >> 32)
+
+/* SMMLS */
+#define multSub_32x32_keep32(a, x, y) \
+    a -= (q31_t) (((q63_t) x * y) >> 32)
+
+/* SMMUL */
+#define mult_32x32_keep32(a, x, y) \
+    a = (q31_t) (((q63_t) x * y ) >> 32)
+
+
+#if   defined ( __CC_ARM )
+  /* Enter low optimization region - place directly above function definition */
+  #if defined( ARM_MATH_CM4 ) || defined( ARM_MATH_CM7)
+    #define LOW_OPTIMIZATION_ENTER \
+       _Pragma ("push")         \
+       _Pragma ("O1")
+  #else
+    #define LOW_OPTIMIZATION_ENTER
+  #endif
+
+  /* Exit low optimization region - place directly after end of function definition */
+  #if defined ( ARM_MATH_CM4 ) || defined ( ARM_MATH_CM7 )
+    #define LOW_OPTIMIZATION_EXIT \
+       _Pragma ("pop")
+  #else
+    #define LOW_OPTIMIZATION_EXIT
+  #endif
+
+  /* Enter low optimization region - place directly above function definition */
+  #define IAR_ONLY_LOW_OPTIMIZATION_ENTER
+
+  /* Exit low optimization region - place directly after end of function definition */
+  #define IAR_ONLY_LOW_OPTIMIZATION_EXIT
+
+#elif defined (__ARMCC_VERSION ) && ( __ARMCC_VERSION >= 6010050 )
+  #define LOW_OPTIMIZATION_ENTER
+  #define LOW_OPTIMIZATION_EXIT
+  #define IAR_ONLY_LOW_OPTIMIZATION_ENTER
+  #define IAR_ONLY_LOW_OPTIMIZATION_EXIT
+
+#elif defined ( __GNUC__ )
+  #define LOW_OPTIMIZATION_ENTER \
+       __attribute__(( optimize("-O1") ))
+  #define LOW_OPTIMIZATION_EXIT
+  #define IAR_ONLY_LOW_OPTIMIZATION_ENTER
+  #define IAR_ONLY_LOW_OPTIMIZATION_EXIT
+
+#elif defined ( __ICCARM__ )
+  /* Enter low optimization region - place directly above function definition */
+  #if defined ( ARM_MATH_CM4 ) || defined ( ARM_MATH_CM7 )
+    #define LOW_OPTIMIZATION_ENTER \
+       _Pragma ("optimize=low")
+  #else
+    #define LOW_OPTIMIZATION_ENTER
+  #endif
+
+  /* Exit low optimization region - place directly after end of function definition */
+  #define LOW_OPTIMIZATION_EXIT
+
+  /* Enter low optimization region - place directly above function definition */
+  #if defined ( ARM_MATH_CM4 ) || defined ( ARM_MATH_CM7 )
+    #define IAR_ONLY_LOW_OPTIMIZATION_ENTER \
+       _Pragma ("optimize=low")
+  #else
+    #define IAR_ONLY_LOW_OPTIMIZATION_ENTER
+  #endif
+
+  /* Exit low optimization region - place directly after end of function definition */
+  #define IAR_ONLY_LOW_OPTIMIZATION_EXIT
+
+#elif defined ( __TI_ARM__ )
+  #define LOW_OPTIMIZATION_ENTER
+  #define LOW_OPTIMIZATION_EXIT
+  #define IAR_ONLY_LOW_OPTIMIZATION_ENTER
+  #define IAR_ONLY_LOW_OPTIMIZATION_EXIT
+
+#elif defined ( __CSMC__ )
+  #define LOW_OPTIMIZATION_ENTER
+  #define LOW_OPTIMIZATION_EXIT
+  #define IAR_ONLY_LOW_OPTIMIZATION_ENTER
+  #define IAR_ONLY_LOW_OPTIMIZATION_EXIT
+
+#elif defined ( __TASKING__ )
+  #define LOW_OPTIMIZATION_ENTER
+  #define LOW_OPTIMIZATION_EXIT
+  #define IAR_ONLY_LOW_OPTIMIZATION_ENTER
+  #define IAR_ONLY_LOW_OPTIMIZATION_EXIT
+
+#endif
+
+
+#ifdef   __cplusplus
+}
+#endif
+
+/* Compiler specific diagnostic adjustment */
+#if   defined ( __CC_ARM )
+
+#elif defined ( __ARMCC_VERSION ) && ( __ARMCC_VERSION >= 6010050 )
+
+#elif defined ( __GNUC__ )
+#pragma GCC diagnostic pop
+
+#elif defined ( __ICCARM__ )
+
+#elif defined ( __TI_ARM__ )
+
+#elif defined ( __CSMC__ )
+
+#elif defined ( __TASKING__ )
+
+#else
+  #error Unknown compiler
+#endif
+
+#endif /* _ARM_MATH_H */
+
+/**
+ *
+ * End of file.
+ */

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/flatbuffers/include/flatbuffers/base.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/flatbuffers/include/flatbuffers/base.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,379 @@
+#ifndef FLATBUFFERS_BASE_H_
+#define FLATBUFFERS_BASE_H_
+
+// clang-format off
+
+// If activate should be declared and included first.
+#if defined(FLATBUFFERS_MEMORY_LEAK_TRACKING) && \
+    defined(_MSC_VER) && defined(_DEBUG)
+  // The _CRTDBG_MAP_ALLOC inside <crtdbg.h> will replace
+  // calloc/free (etc) to its debug version using #define directives.
+  #define _CRTDBG_MAP_ALLOC
+  #include <stdlib.h>
+  #include <crtdbg.h>
+  // Replace operator new by trace-enabled version.
+  #define DEBUG_NEW new(_NORMAL_BLOCK, __FILE__, __LINE__)
+  #define new DEBUG_NEW
+#endif
+
+#if !defined(FLATBUFFERS_ASSERT)
+#include <assert.h>
+#define FLATBUFFERS_ASSERT assert
+#elif defined(FLATBUFFERS_ASSERT_INCLUDE)
+// Include file with forward declaration
+#include FLATBUFFERS_ASSERT_INCLUDE
+#endif
+
+#ifndef ARDUINO
+#include <cstdint>
+#endif
+
+#include <cstddef>
+#include <cstdlib>
+#include <cstring>
+
+#if defined(ARDUINO) && !defined(ARDUINOSTL_M_H)
+  #include <utility.h>
+#else
+  #include <utility>
+#endif
+
+#include <string>
+#include <type_traits>
+#include <vector>
+#include <set>
+#include <algorithm>
+#include <iterator>
+#include <memory>
+
+#ifdef _STLPORT_VERSION
+  #define FLATBUFFERS_CPP98_STL
+#endif
+#ifndef FLATBUFFERS_CPP98_STL
+  #include <functional>
+#endif
+
+#include "flatbuffers/stl_emulation.h"
+
+// Note the __clang__ check is needed, because clang presents itself
+// as an older GNUC compiler (4.2).
+// Clang 3.3 and later implement all of the ISO C++ 2011 standard.
+// Clang 3.4 and later implement all of the ISO C++ 2014 standard.
+// http://clang.llvm.org/cxx_status.html
+
+// Note the MSVC value '__cplusplus' may be incorrect:
+// The '__cplusplus' predefined macro in the MSVC stuck at the value 199711L,
+// indicating (erroneously!) that the compiler conformed to the C++98 Standard.
+// This value should be correct starting from MSVC2017-15.7-Preview-3.
+// The '__cplusplus' will be valid only if MSVC2017-15.7-P3 and the `/Zc:__cplusplus` switch is set.
+// Workaround (for details see MSDN):
+// Use the _MSC_VER and _MSVC_LANG definition instead of the __cplusplus  for compatibility.
+// The _MSVC_LANG macro reports the Standard version regardless of the '/Zc:__cplusplus' switch.
+
+#if defined(__GNUC__) && !defined(__clang__)
+  #define FLATBUFFERS_GCC (__GNUC__ * 10000 + __GNUC_MINOR__ * 100 + __GNUC_PATCHLEVEL__)
+#else
+  #define FLATBUFFERS_GCC 0
+#endif
+
+#if defined(__clang__)
+  #define FLATBUFFERS_CLANG (__clang_major__ * 10000 + __clang_minor__ * 100 + __clang_patchlevel__)
+#else
+  #define FLATBUFFERS_CLANG 0
+#endif
+
+/// @cond FLATBUFFERS_INTERNAL
+#if __cplusplus <= 199711L && \
+    (!defined(_MSC_VER) || _MSC_VER < 1600) && \
+    (!defined(__GNUC__) || \
+      (__GNUC__ * 10000 + __GNUC_MINOR__ * 100 + __GNUC_PATCHLEVEL__ < 40400))
+  #error A C++11 compatible compiler with support for the auto typing is \
+         required for FlatBuffers.
+  #error __cplusplus _MSC_VER __GNUC__  __GNUC_MINOR__  __GNUC_PATCHLEVEL__
+#endif
+
+#if !defined(__clang__) && \
+    defined(__GNUC__) && \
+    (__GNUC__ * 10000 + __GNUC_MINOR__ * 100 + __GNUC_PATCHLEVEL__ < 40600)
+  // Backwards compatability for g++ 4.4, and 4.5 which don't have the nullptr
+  // and constexpr keywords. Note the __clang__ check is needed, because clang
+  // presents itself as an older GNUC compiler.
+  #ifndef nullptr_t
+    const class nullptr_t {
+    public:
+      template<class T> inline operator T*() const { return 0; }
+    private:
+      void operator&() const;
+    } nullptr = {};
+  #endif
+  #ifndef constexpr
+    #define constexpr const
+  #endif
+#endif
+
+// The wire format uses a little endian encoding (since that's efficient for
+// the common platforms).
+#if defined(__s390x__)
+  #define FLATBUFFERS_LITTLEENDIAN 0
+#endif // __s390x__
+#if !defined(FLATBUFFERS_LITTLEENDIAN)
+  #if defined(__GNUC__) || defined(__clang__)
+    #if (defined(__BIG_ENDIAN__) || \
+         (defined(__BYTE_ORDER__) && __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__))
+      #define FLATBUFFERS_LITTLEENDIAN 0
+    #else
+      #define FLATBUFFERS_LITTLEENDIAN 1
+    #endif // __BIG_ENDIAN__
+  #elif defined(_MSC_VER)
+    #if defined(_M_PPC)
+      #define FLATBUFFERS_LITTLEENDIAN 0
+    #else
+      #define FLATBUFFERS_LITTLEENDIAN 1
+    #endif
+  #else
+    #error Unable to determine endianness, define FLATBUFFERS_LITTLEENDIAN.
+  #endif
+#endif // !defined(FLATBUFFERS_LITTLEENDIAN)
+
+#define FLATBUFFERS_VERSION_MAJOR 1
+#define FLATBUFFERS_VERSION_MINOR 11
+#define FLATBUFFERS_VERSION_REVISION 0
+#define FLATBUFFERS_STRING_EXPAND(X) #X
+#define FLATBUFFERS_STRING(X) FLATBUFFERS_STRING_EXPAND(X)
+
+#if (!defined(_MSC_VER) || _MSC_VER > 1600) && \
+    (!defined(__GNUC__) || (__GNUC__ * 100 + __GNUC_MINOR__ >= 407)) || \
+    defined(__clang__)
+  #define FLATBUFFERS_FINAL_CLASS final
+  #define FLATBUFFERS_OVERRIDE override
+  #define FLATBUFFERS_VTABLE_UNDERLYING_TYPE : flatbuffers::voffset_t
+#else
+  #define FLATBUFFERS_FINAL_CLASS
+  #define FLATBUFFERS_OVERRIDE
+  #define FLATBUFFERS_VTABLE_UNDERLYING_TYPE
+#endif
+
+#if (!defined(_MSC_VER) || _MSC_VER >= 1900) && \
+    (!defined(__GNUC__) || (__GNUC__ * 100 + __GNUC_MINOR__ >= 406)) || \
+    (defined(__cpp_constexpr) && __cpp_constexpr >= 200704)
+  #define FLATBUFFERS_CONSTEXPR constexpr
+#else
+  #define FLATBUFFERS_CONSTEXPR const
+#endif
+
+#if (defined(__cplusplus) && __cplusplus >= 201402L) || \
+    (defined(__cpp_constexpr) && __cpp_constexpr >= 201304)
+  #define FLATBUFFERS_CONSTEXPR_CPP14 FLATBUFFERS_CONSTEXPR
+#else
+  #define FLATBUFFERS_CONSTEXPR_CPP14
+#endif
+
+#if (defined(__GXX_EXPERIMENTAL_CXX0X__) && (__GNUC__ * 100 + __GNUC_MINOR__ >= 406)) || \
+    (defined(_MSC_FULL_VER) && (_MSC_FULL_VER >= 190023026)) || \
+    defined(__clang__)
+  #define FLATBUFFERS_NOEXCEPT noexcept
+#else
+  #define FLATBUFFERS_NOEXCEPT
+#endif
+
+// NOTE: the FLATBUFFERS_DELETE_FUNC macro may change the access mode to
+// private, so be sure to put it at the end or reset access mode explicitly.
+#if (!defined(_MSC_VER) || _MSC_FULL_VER >= 180020827) && \
+    (!defined(__GNUC__) || (__GNUC__ * 100 + __GNUC_MINOR__ >= 404)) || \
+    defined(__clang__)
+  #define FLATBUFFERS_DELETE_FUNC(func) func = delete;
+#else
+  #define FLATBUFFERS_DELETE_FUNC(func) private: func;
+#endif
+
+#ifndef FLATBUFFERS_HAS_STRING_VIEW
+  // Only provide flatbuffers::string_view if __has_include can be used
+  // to detect a header that provides an implementation
+  #if defined(__has_include)
+    // Check for std::string_view (in c++17)
+    #if __has_include(<string_view>) && (__cplusplus >= 201606 || _HAS_CXX17)
+      #include <string_view>
+      namespace flatbuffers {
+        typedef std::string_view string_view;
+      }
+      #define FLATBUFFERS_HAS_STRING_VIEW 1
+    // Check for std::experimental::string_view (in c++14, compiler-dependent)
+    #elif __has_include(<experimental/string_view>) && (__cplusplus >= 201411)
+      #include <experimental/string_view>
+      namespace flatbuffers {
+        typedef std::experimental::string_view string_view;
+      }
+      #define FLATBUFFERS_HAS_STRING_VIEW 1
+    #endif
+  #endif // __has_include
+#endif // !FLATBUFFERS_HAS_STRING_VIEW
+
+#ifndef FLATBUFFERS_HAS_NEW_STRTOD
+  // Modern (C++11) strtod and strtof functions are available for use.
+  // 1) nan/inf strings as argument of strtod;
+  // 2) hex-float  as argument of  strtod/strtof.
+  #if (defined(_MSC_VER) && _MSC_VER >= 1900) || \
+      (defined(__GNUC__) && (__GNUC__ * 100 + __GNUC_MINOR__ >= 409)) || \
+      (defined(__clang__))
+    #define FLATBUFFERS_HAS_NEW_STRTOD 1
+  #endif
+#endif // !FLATBUFFERS_HAS_NEW_STRTOD
+
+#ifndef FLATBUFFERS_LOCALE_INDEPENDENT
+  // Enable locale independent functions {strtof_l, strtod_l,strtoll_l, strtoull_l}.
+  // They are part of the POSIX-2008 but not part of the C/C++ standard.
+  // GCC/Clang have definition (_XOPEN_SOURCE>=700) if POSIX-2008.
+  #if ((defined(_MSC_VER) && _MSC_VER >= 1800)            || \
+       (defined(_XOPEN_SOURCE) && (_XOPEN_SOURCE>=700)))
+    #define FLATBUFFERS_LOCALE_INDEPENDENT 1
+  #else
+    #define FLATBUFFERS_LOCALE_INDEPENDENT 0
+  #endif
+#endif  // !FLATBUFFERS_LOCALE_INDEPENDENT
+
+// Suppress Undefined Behavior Sanitizer (recoverable only). Usage:
+// - __supress_ubsan__("undefined")
+// - __supress_ubsan__("signed-integer-overflow")
+#if defined(__clang__)
+  #define __supress_ubsan__(type) __attribute__((no_sanitize(type)))
+#elif defined(__GNUC__) && (__GNUC__ * 100 + __GNUC_MINOR__ >= 409)
+  #define __supress_ubsan__(type) __attribute__((no_sanitize_undefined))
+#else
+  #define __supress_ubsan__(type)
+#endif
+
+// This is constexpr function used for checking compile-time constants.
+// Avoid `#pragma warning(disable: 4127) // C4127: expression is constant`.
+template<typename T> FLATBUFFERS_CONSTEXPR inline bool IsConstTrue(T t) {
+  return !!t;
+}
+
+// Enable C++ attribute [[]] if std:c++17 or higher.
+#if ((__cplusplus >= 201703L) \
+    || (defined(_MSVC_LANG) &&  (_MSVC_LANG >= 201703L)))
+  // All attributes unknown to an implementation are ignored without causing an error.
+  #define FLATBUFFERS_ATTRIBUTE(attr) [[attr]]
+
+  #define FLATBUFFERS_FALLTHROUGH() [[fallthrough]]
+#else
+  #define FLATBUFFERS_ATTRIBUTE(attr)
+
+  #if FLATBUFFERS_CLANG >= 30800
+    #define FLATBUFFERS_FALLTHROUGH() [[clang::fallthrough]]
+  #elif FLATBUFFERS_GCC >= 70300
+    #define FLATBUFFERS_FALLTHROUGH() [[gnu::fallthrough]]
+  #else
+    #define FLATBUFFERS_FALLTHROUGH()
+  #endif
+#endif
+
+/// @endcond
+
+/// @file
+namespace flatbuffers {
+
+/// @cond FLATBUFFERS_INTERNAL
+// Our default offset / size type, 32bit on purpose on 64bit systems.
+// Also, using a consistent offset type maintains compatibility of serialized
+// offset values between 32bit and 64bit systems.
+typedef uint32_t uoffset_t;
+
+// Signed offsets for references that can go in both directions.
+typedef int32_t soffset_t;
+
+// Offset/index used in v-tables, can be changed to uint8_t in
+// format forks to save a bit of space if desired.
+typedef uint16_t voffset_t;
+
+typedef uintmax_t largest_scalar_t;
+
+// In 32bits, this evaluates to 2GB - 1
+#define FLATBUFFERS_MAX_BUFFER_SIZE ((1ULL << (sizeof(soffset_t) * 8 - 1)) - 1)
+
+// We support aligning the contents of buffers up to this size.
+#define FLATBUFFERS_MAX_ALIGNMENT 16
+
+#if defined(_MSC_VER)
+  #pragma warning(push)
+  #pragma warning(disable: 4127) // C4127: conditional expression is constant
+#endif
+
+template<typename T> T EndianSwap(T t) {
+  #if defined(_MSC_VER)
+    #define FLATBUFFERS_BYTESWAP16 _byteswap_ushort
+    #define FLATBUFFERS_BYTESWAP32 _byteswap_ulong
+    #define FLATBUFFERS_BYTESWAP64 _byteswap_uint64
+  #else
+    #if defined(__GNUC__) && __GNUC__ * 100 + __GNUC_MINOR__ < 408 && !defined(__clang__)
+      // __builtin_bswap16 was missing prior to GCC 4.8.
+      #define FLATBUFFERS_BYTESWAP16(x) \
+        static_cast<uint16_t>(__builtin_bswap32(static_cast<uint32_t>(x) << 16))
+    #else
+      #define FLATBUFFERS_BYTESWAP16 __builtin_bswap16
+    #endif
+    #define FLATBUFFERS_BYTESWAP32 __builtin_bswap32
+    #define FLATBUFFERS_BYTESWAP64 __builtin_bswap64
+  #endif
+  if (sizeof(T) == 1) {   // Compile-time if-then's.
+    return t;
+  } else if (sizeof(T) == 2) {
+    union { T t; uint16_t i; } u;
+    u.t = t;
+    u.i = FLATBUFFERS_BYTESWAP16(u.i);
+    return u.t;
+  } else if (sizeof(T) == 4) {
+    union { T t; uint32_t i; } u;
+    u.t = t;
+    u.i = FLATBUFFERS_BYTESWAP32(u.i);
+    return u.t;
+  } else if (sizeof(T) == 8) {
+    union { T t; uint64_t i; } u;
+    u.t = t;
+    u.i = FLATBUFFERS_BYTESWAP64(u.i);
+    return u.t;
+  } else {
+    FLATBUFFERS_ASSERT(0);
+  }
+}
+
+#if defined(_MSC_VER)
+  #pragma warning(pop)
+#endif
+
+
+template<typename T> T EndianScalar(T t) {
+  #if FLATBUFFERS_LITTLEENDIAN
+    return t;
+  #else
+    return EndianSwap(t);
+  #endif
+}
+
+template<typename T>
+// UBSAN: C++ aliasing type rules, see std::bit_cast<> for details.
+__supress_ubsan__("alignment")
+T ReadScalar(const void *p) {
+  return EndianScalar(*reinterpret_cast<const T *>(p));
+}
+
+template<typename T>
+// UBSAN: C++ aliasing type rules, see std::bit_cast<> for details.
+__supress_ubsan__("alignment")
+void WriteScalar(void *p, T t) {
+  *reinterpret_cast<T *>(p) = EndianScalar(t);
+}
+
+template<typename T> struct Offset;
+template<typename T> __supress_ubsan__("alignment") void WriteScalar(void *p, Offset<T> t) {
+  *reinterpret_cast<uoffset_t *>(p) = EndianScalar(t.o);
+}
+
+// Computes how many bytes you'd have to pad to be able to write an
+// "scalar_size" scalar if the buffer had grown to "buf_size" (downwards in
+// memory).
+inline size_t PaddingBytes(size_t buf_size, size_t scalar_size) {
+  return ((~buf_size) + 1) & (scalar_size - 1);
+}
+
+}  // namespace flatbuffers
+#endif  // FLATBUFFERS_BASE_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/flatbuffers/include/flatbuffers/flatbuffers.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/flatbuffers/include/flatbuffers/flatbuffers.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,2613 @@
+/*
+ * Copyright 2014 Google Inc. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef FLATBUFFERS_H_
+#define FLATBUFFERS_H_
+
+#include "flatbuffers/base.h"
+
+#if defined(FLATBUFFERS_NAN_DEFAULTS)
+#include <cmath>
+#endif
+
+namespace flatbuffers {
+// Generic 'operator==' with conditional specialisations.
+template<typename T> inline bool IsTheSameAs(T e, T def) { return e == def; }
+
+#if defined(FLATBUFFERS_NAN_DEFAULTS) && \
+    (!defined(_MSC_VER) || _MSC_VER >= 1800)
+// Like `operator==(e, def)` with weak NaN if T=(float|double).
+template<> inline bool IsTheSameAs<float>(float e, float def) {
+  return (e == def) || (std::isnan(def) && std::isnan(e));
+}
+template<> inline bool IsTheSameAs<double>(double e, double def) {
+  return (e == def) || (std::isnan(def) && std::isnan(e));
+}
+#endif
+
+// Wrapper for uoffset_t to allow safe template specialization.
+// Value is allowed to be 0 to indicate a null object (see e.g. AddOffset).
+template<typename T> struct Offset {
+  uoffset_t o;
+  Offset() : o(0) {}
+  Offset(uoffset_t _o) : o(_o) {}
+  Offset<void> Union() const { return Offset<void>(o); }
+  bool IsNull() const { return !o; }
+};
+
+inline void EndianCheck() {
+  int endiantest = 1;
+  // If this fails, see FLATBUFFERS_LITTLEENDIAN above.
+  FLATBUFFERS_ASSERT(*reinterpret_cast<char *>(&endiantest) ==
+                     FLATBUFFERS_LITTLEENDIAN);
+  (void)endiantest;
+}
+
+template<typename T> FLATBUFFERS_CONSTEXPR size_t AlignOf() {
+  // clang-format off
+  #ifdef _MSC_VER
+    return __alignof(T);
+  #else
+    #ifndef alignof
+      return __alignof__(T);
+    #else
+      return alignof(T);
+    #endif
+  #endif
+  // clang-format on
+}
+
+// When we read serialized data from memory, in the case of most scalars,
+// we want to just read T, but in the case of Offset, we want to actually
+// perform the indirection and return a pointer.
+// The template specialization below does just that.
+// It is wrapped in a struct since function templates can't overload on the
+// return type like this.
+// The typedef is for the convenience of callers of this function
+// (avoiding the need for a trailing return decltype)
+template<typename T> struct IndirectHelper {
+  typedef T return_type;
+  typedef T mutable_return_type;
+  static const size_t element_stride = sizeof(T);
+  static return_type Read(const uint8_t *p, uoffset_t i) {
+    return EndianScalar((reinterpret_cast<const T *>(p))[i]);
+  }
+};
+template<typename T> struct IndirectHelper<Offset<T>> {
+  typedef const T *return_type;
+  typedef T *mutable_return_type;
+  static const size_t element_stride = sizeof(uoffset_t);
+  static return_type Read(const uint8_t *p, uoffset_t i) {
+    p += i * sizeof(uoffset_t);
+    return reinterpret_cast<return_type>(p + ReadScalar<uoffset_t>(p));
+  }
+};
+template<typename T> struct IndirectHelper<const T *> {
+  typedef const T *return_type;
+  typedef T *mutable_return_type;
+  static const size_t element_stride = sizeof(T);
+  static return_type Read(const uint8_t *p, uoffset_t i) {
+    return reinterpret_cast<const T *>(p + i * sizeof(T));
+  }
+};
+
+// An STL compatible iterator implementation for Vector below, effectively
+// calling Get() for every element.
+template<typename T, typename IT> struct VectorIterator {
+  typedef std::random_access_iterator_tag iterator_category;
+  typedef IT value_type;
+  typedef ptrdiff_t difference_type;
+  typedef IT *pointer;
+  typedef IT &reference;
+
+  VectorIterator(const uint8_t *data, uoffset_t i)
+      : data_(data + IndirectHelper<T>::element_stride * i) {}
+  VectorIterator(const VectorIterator &other) : data_(other.data_) {}
+  VectorIterator() : data_(nullptr) {}
+
+  VectorIterator &operator=(const VectorIterator &other) {
+    data_ = other.data_;
+    return *this;
+  }
+
+  // clang-format off
+  #if !defined(FLATBUFFERS_CPP98_STL)
+  VectorIterator &operator=(VectorIterator &&other) {
+    data_ = other.data_;
+    return *this;
+  }
+  #endif  // !defined(FLATBUFFERS_CPP98_STL)
+  // clang-format on
+
+  bool operator==(const VectorIterator &other) const {
+    return data_ == other.data_;
+  }
+
+  bool operator<(const VectorIterator &other) const {
+    return data_ < other.data_;
+  }
+
+  bool operator!=(const VectorIterator &other) const {
+    return data_ != other.data_;
+  }
+
+  difference_type operator-(const VectorIterator &other) const {
+    return (data_ - other.data_) / IndirectHelper<T>::element_stride;
+  }
+
+  IT operator*() const { return IndirectHelper<T>::Read(data_, 0); }
+
+  IT operator->() const { return IndirectHelper<T>::Read(data_, 0); }
+
+  VectorIterator &operator++() {
+    data_ += IndirectHelper<T>::element_stride;
+    return *this;
+  }
+
+  VectorIterator operator++(int) {
+    VectorIterator temp(data_, 0);
+    data_ += IndirectHelper<T>::element_stride;
+    return temp;
+  }
+
+  VectorIterator operator+(const uoffset_t &offset) const {
+    return VectorIterator(data_ + offset * IndirectHelper<T>::element_stride,
+                          0);
+  }
+
+  VectorIterator &operator+=(const uoffset_t &offset) {
+    data_ += offset * IndirectHelper<T>::element_stride;
+    return *this;
+  }
+
+  VectorIterator &operator--() {
+    data_ -= IndirectHelper<T>::element_stride;
+    return *this;
+  }
+
+  VectorIterator operator--(int) {
+    VectorIterator temp(data_, 0);
+    data_ -= IndirectHelper<T>::element_stride;
+    return temp;
+  }
+
+  VectorIterator operator-(const uoffset_t &offset) const {
+    return VectorIterator(data_ - offset * IndirectHelper<T>::element_stride,
+                          0);
+  }
+
+  VectorIterator &operator-=(const uoffset_t &offset) {
+    data_ -= offset * IndirectHelper<T>::element_stride;
+    return *this;
+  }
+
+ private:
+  const uint8_t *data_;
+};
+
+template<typename Iterator> struct VectorReverseIterator :
+  public std::reverse_iterator<Iterator> {
+
+  explicit VectorReverseIterator(Iterator iter) : iter_(iter) {}
+
+  typename Iterator::value_type operator*() const { return *(iter_ - 1); }
+
+  typename Iterator::value_type operator->() const { return *(iter_ - 1); }
+
+ private:
+  Iterator iter_;
+};
+
+struct String;
+
+// This is used as a helper type for accessing vectors.
+// Vector::data() assumes the vector elements start after the length field.
+template<typename T> class Vector {
+ public:
+  typedef VectorIterator<T, typename IndirectHelper<T>::mutable_return_type>
+      iterator;
+  typedef VectorIterator<T, typename IndirectHelper<T>::return_type>
+      const_iterator;
+  typedef VectorReverseIterator<iterator> reverse_iterator;
+  typedef VectorReverseIterator<const_iterator> const_reverse_iterator;
+
+  uoffset_t size() const { return EndianScalar(length_); }
+
+  // Deprecated: use size(). Here for backwards compatibility.
+  FLATBUFFERS_ATTRIBUTE(deprecated("use size() instead"))
+  uoffset_t Length() const { return size(); }
+
+  typedef typename IndirectHelper<T>::return_type return_type;
+  typedef typename IndirectHelper<T>::mutable_return_type mutable_return_type;
+
+  return_type Get(uoffset_t i) const {
+    FLATBUFFERS_ASSERT(i < size());
+    return IndirectHelper<T>::Read(Data(), i);
+  }
+
+  return_type operator[](uoffset_t i) const { return Get(i); }
+
+  // If this is a Vector of enums, T will be its storage type, not the enum
+  // type. This function makes it convenient to retrieve value with enum
+  // type E.
+  template<typename E> E GetEnum(uoffset_t i) const {
+    return static_cast<E>(Get(i));
+  }
+
+  // If this a vector of unions, this does the cast for you. There's no check
+  // to make sure this is the right type!
+  template<typename U> const U *GetAs(uoffset_t i) const {
+    return reinterpret_cast<const U *>(Get(i));
+  }
+
+  // If this a vector of unions, this does the cast for you. There's no check
+  // to make sure this is actually a string!
+  const String *GetAsString(uoffset_t i) const {
+    return reinterpret_cast<const String *>(Get(i));
+  }
+
+  const void *GetStructFromOffset(size_t o) const {
+    return reinterpret_cast<const void *>(Data() + o);
+  }
+
+  iterator begin() { return iterator(Data(), 0); }
+  const_iterator begin() const { return const_iterator(Data(), 0); }
+
+  iterator end() { return iterator(Data(), size()); }
+  const_iterator end() const { return const_iterator(Data(), size()); }
+
+  reverse_iterator rbegin() { return reverse_iterator(end()); }
+  const_reverse_iterator rbegin() const { return const_reverse_iterator(end()); }
+
+  reverse_iterator rend() { return reverse_iterator(end()); }
+  const_reverse_iterator rend() const { return const_reverse_iterator(end()); }
+
+  const_iterator cbegin() const { return begin(); }
+
+  const_iterator cend() const { return end(); }
+
+  const_reverse_iterator crbegin() const { return rbegin(); }
+
+  const_reverse_iterator crend() const { return rend(); }
+
+  // Change elements if you have a non-const pointer to this object.
+  // Scalars only. See reflection.h, and the documentation.
+  void Mutate(uoffset_t i, const T &val) {
+    FLATBUFFERS_ASSERT(i < size());
+    WriteScalar(data() + i, val);
+  }
+
+  // Change an element of a vector of tables (or strings).
+  // "val" points to the new table/string, as you can obtain from
+  // e.g. reflection::AddFlatBuffer().
+  void MutateOffset(uoffset_t i, const uint8_t *val) {
+    FLATBUFFERS_ASSERT(i < size());
+    static_assert(sizeof(T) == sizeof(uoffset_t), "Unrelated types");
+    WriteScalar(data() + i,
+                static_cast<uoffset_t>(val - (Data() + i * sizeof(uoffset_t))));
+  }
+
+  // Get a mutable pointer to tables/strings inside this vector.
+  mutable_return_type GetMutableObject(uoffset_t i) const {
+    FLATBUFFERS_ASSERT(i < size());
+    return const_cast<mutable_return_type>(IndirectHelper<T>::Read(Data(), i));
+  }
+
+  // The raw data in little endian format. Use with care.
+  const uint8_t *Data() const {
+    return reinterpret_cast<const uint8_t *>(&length_ + 1);
+  }
+
+  uint8_t *Data() { return reinterpret_cast<uint8_t *>(&length_ + 1); }
+
+  // Similarly, but typed, much like std::vector::data
+  const T *data() const { return reinterpret_cast<const T *>(Data()); }
+  T *data() { return reinterpret_cast<T *>(Data()); }
+
+  template<typename K> return_type LookupByKey(K key) const {
+    void *search_result = std::bsearch(
+        &key, Data(), size(), IndirectHelper<T>::element_stride, KeyCompare<K>);
+
+    if (!search_result) {
+      return nullptr;  // Key not found.
+    }
+
+    const uint8_t *element = reinterpret_cast<const uint8_t *>(search_result);
+
+    return IndirectHelper<T>::Read(element, 0);
+  }
+
+ protected:
+  // This class is only used to access pre-existing data. Don't ever
+  // try to construct these manually.
+  Vector();
+
+  uoffset_t length_;
+
+ private:
+  // This class is a pointer. Copying will therefore create an invalid object.
+  // Private and unimplemented copy constructor.
+  Vector(const Vector &);
+
+  template<typename K> static int KeyCompare(const void *ap, const void *bp) {
+    const K *key = reinterpret_cast<const K *>(ap);
+    const uint8_t *data = reinterpret_cast<const uint8_t *>(bp);
+    auto table = IndirectHelper<T>::Read(data, 0);
+
+    // std::bsearch compares with the operands transposed, so we negate the
+    // result here.
+    return -table->KeyCompareWithValue(*key);
+  }
+};
+
+// Represent a vector much like the template above, but in this case we
+// don't know what the element types are (used with reflection.h).
+class VectorOfAny {
+ public:
+  uoffset_t size() const { return EndianScalar(length_); }
+
+  const uint8_t *Data() const {
+    return reinterpret_cast<const uint8_t *>(&length_ + 1);
+  }
+  uint8_t *Data() { return reinterpret_cast<uint8_t *>(&length_ + 1); }
+
+ protected:
+  VectorOfAny();
+
+  uoffset_t length_;
+
+ private:
+  VectorOfAny(const VectorOfAny &);
+};
+
+#ifndef FLATBUFFERS_CPP98_STL
+template<typename T, typename U>
+Vector<Offset<T>> *VectorCast(Vector<Offset<U>> *ptr) {
+  static_assert(std::is_base_of<T, U>::value, "Unrelated types");
+  return reinterpret_cast<Vector<Offset<T>> *>(ptr);
+}
+
+template<typename T, typename U>
+const Vector<Offset<T>> *VectorCast(const Vector<Offset<U>> *ptr) {
+  static_assert(std::is_base_of<T, U>::value, "Unrelated types");
+  return reinterpret_cast<const Vector<Offset<T>> *>(ptr);
+}
+#endif
+
+// Convenient helper function to get the length of any vector, regardless
+// of whether it is null or not (the field is not set).
+template<typename T> static inline size_t VectorLength(const Vector<T> *v) {
+  return v ? v->size() : 0;
+}
+
+// Lexicographically compare two strings (possibly containing nulls), and
+// return true if the first is less than the second.
+static inline bool StringLessThan(const char *a_data, uoffset_t a_size,
+                                  const char *b_data, uoffset_t b_size) {
+  const auto cmp = memcmp(a_data, b_data, (std::min)(a_size, b_size));
+  return cmp == 0 ? a_size < b_size : cmp < 0;
+}
+
+struct String : public Vector<char> {
+  const char *c_str() const { return reinterpret_cast<const char *>(Data()); }
+  std::string str() const { return std::string(c_str(), size()); }
+
+  // clang-format off
+  #ifdef FLATBUFFERS_HAS_STRING_VIEW
+  flatbuffers::string_view string_view() const {
+    return flatbuffers::string_view(c_str(), size());
+  }
+  #endif // FLATBUFFERS_HAS_STRING_VIEW
+  // clang-format on
+
+  bool operator<(const String &o) const {
+    return StringLessThan(this->data(), this->size(), o.data(), o.size());
+  }
+};
+
+// Convenience function to get std::string from a String returning an empty
+// string on null pointer.
+static inline std::string GetString(const String * str) {
+  return str ? str->str() : "";
+}
+
+// Convenience function to get char* from a String returning an empty string on
+// null pointer.
+static inline const char * GetCstring(const String * str) {
+  return str ? str->c_str() : "";
+}
+
+// Allocator interface. This is flatbuffers-specific and meant only for
+// `vector_downward` usage.
+class Allocator {
+ public:
+  virtual ~Allocator() {}
+
+  // Allocate `size` bytes of memory.
+  virtual uint8_t *allocate(size_t size) = 0;
+
+  // Deallocate `size` bytes of memory at `p` allocated by this allocator.
+  virtual void deallocate(uint8_t *p, size_t size) = 0;
+
+  // Reallocate `new_size` bytes of memory, replacing the old region of size
+  // `old_size` at `p`. In contrast to a normal realloc, this grows downwards,
+  // and is intended specifcally for `vector_downward` use.
+  // `in_use_back` and `in_use_front` indicate how much of `old_size` is
+  // actually in use at each end, and needs to be copied.
+  virtual uint8_t *reallocate_downward(uint8_t *old_p, size_t old_size,
+                                       size_t new_size, size_t in_use_back,
+                                       size_t in_use_front) {
+    FLATBUFFERS_ASSERT(new_size > old_size);  // vector_downward only grows
+    uint8_t *new_p = allocate(new_size);
+    memcpy_downward(old_p, old_size, new_p, new_size, in_use_back,
+                    in_use_front);
+    deallocate(old_p, old_size);
+    return new_p;
+  }
+
+ protected:
+  // Called by `reallocate_downward` to copy memory from `old_p` of `old_size`
+  // to `new_p` of `new_size`. Only memory of size `in_use_front` and
+  // `in_use_back` will be copied from the front and back of the old memory
+  // allocation.
+  void memcpy_downward(uint8_t *old_p, size_t old_size,
+                       uint8_t *new_p, size_t new_size,
+                       size_t in_use_back, size_t in_use_front) {
+    memcpy(new_p + new_size - in_use_back, old_p + old_size - in_use_back,
+           in_use_back);
+    memcpy(new_p, old_p, in_use_front);
+  }
+};
+
+// DefaultAllocator uses new/delete to allocate memory regions
+class DefaultAllocator : public Allocator {
+ public:
+  uint8_t *allocate(size_t size) FLATBUFFERS_OVERRIDE {
+    return new uint8_t[size];
+  }
+
+  void deallocate(uint8_t *p, size_t) FLATBUFFERS_OVERRIDE {
+    delete[] p;
+  }
+
+  static void dealloc(void *p, size_t) {
+    delete[] static_cast<uint8_t *>(p);
+  }
+};
+
+// These functions allow for a null allocator to mean use the default allocator,
+// as used by DetachedBuffer and vector_downward below.
+// This is to avoid having a statically or dynamically allocated default
+// allocator, or having to move it between the classes that may own it.
+inline uint8_t *Allocate(Allocator *allocator, size_t size) {
+  return allocator ? allocator->allocate(size)
+                   : DefaultAllocator().allocate(size);
+}
+
+inline void Deallocate(Allocator *allocator, uint8_t *p, size_t size) {
+  if (allocator) allocator->deallocate(p, size);
+  else DefaultAllocator().deallocate(p, size);
+}
+
+inline uint8_t *ReallocateDownward(Allocator *allocator, uint8_t *old_p,
+                                   size_t old_size, size_t new_size,
+                                   size_t in_use_back, size_t in_use_front) {
+  return allocator
+      ? allocator->reallocate_downward(old_p, old_size, new_size,
+                                       in_use_back, in_use_front)
+      : DefaultAllocator().reallocate_downward(old_p, old_size, new_size,
+                                               in_use_back, in_use_front);
+}
+
+// DetachedBuffer is a finished flatbuffer memory region, detached from its
+// builder. The original memory region and allocator are also stored so that
+// the DetachedBuffer can manage the memory lifetime.
+class DetachedBuffer {
+ public:
+  DetachedBuffer()
+      : allocator_(nullptr),
+        own_allocator_(false),
+        buf_(nullptr),
+        reserved_(0),
+        cur_(nullptr),
+        size_(0) {}
+
+  DetachedBuffer(Allocator *allocator, bool own_allocator, uint8_t *buf,
+                 size_t reserved, uint8_t *cur, size_t sz)
+      : allocator_(allocator),
+        own_allocator_(own_allocator),
+        buf_(buf),
+        reserved_(reserved),
+        cur_(cur),
+        size_(sz) {}
+
+  // clang-format off
+  #if !defined(FLATBUFFERS_CPP98_STL)
+  // clang-format on
+  DetachedBuffer(DetachedBuffer &&other)
+      : allocator_(other.allocator_),
+        own_allocator_(other.own_allocator_),
+        buf_(other.buf_),
+        reserved_(other.reserved_),
+        cur_(other.cur_),
+        size_(other.size_) {
+    other.reset();
+  }
+  // clang-format off
+  #endif  // !defined(FLATBUFFERS_CPP98_STL)
+  // clang-format on
+
+  // clang-format off
+  #if !defined(FLATBUFFERS_CPP98_STL)
+  // clang-format on
+  DetachedBuffer &operator=(DetachedBuffer &&other) {
+    destroy();
+
+    allocator_ = other.allocator_;
+    own_allocator_ = other.own_allocator_;
+    buf_ = other.buf_;
+    reserved_ = other.reserved_;
+    cur_ = other.cur_;
+    size_ = other.size_;
+
+    other.reset();
+
+    return *this;
+  }
+  // clang-format off
+  #endif  // !defined(FLATBUFFERS_CPP98_STL)
+  // clang-format on
+
+  ~DetachedBuffer() { destroy(); }
+
+  const uint8_t *data() const { return cur_; }
+
+  uint8_t *data() { return cur_; }
+
+  size_t size() const { return size_; }
+
+  // clang-format off
+  #if 0  // disabled for now due to the ordering of classes in this header
+  template <class T>
+  bool Verify() const {
+    Verifier verifier(data(), size());
+    return verifier.Verify<T>(nullptr);
+  }
+
+  template <class T>
+  const T* GetRoot() const {
+    return flatbuffers::GetRoot<T>(data());
+  }
+
+  template <class T>
+  T* GetRoot() {
+    return flatbuffers::GetRoot<T>(data());
+  }
+  #endif
+  // clang-format on
+
+  // clang-format off
+  #if !defined(FLATBUFFERS_CPP98_STL)
+  // clang-format on
+  // These may change access mode, leave these at end of public section
+  FLATBUFFERS_DELETE_FUNC(DetachedBuffer(const DetachedBuffer &other))
+  FLATBUFFERS_DELETE_FUNC(
+      DetachedBuffer &operator=(const DetachedBuffer &other))
+  // clang-format off
+  #endif  // !defined(FLATBUFFERS_CPP98_STL)
+  // clang-format on
+
+protected:
+  Allocator *allocator_;
+  bool own_allocator_;
+  uint8_t *buf_;
+  size_t reserved_;
+  uint8_t *cur_;
+  size_t size_;
+
+  inline void destroy() {
+    if (buf_) Deallocate(allocator_, buf_, reserved_);
+    if (own_allocator_ && allocator_) { delete allocator_; }
+    reset();
+  }
+
+  inline void reset() {
+    allocator_ = nullptr;
+    own_allocator_ = false;
+    buf_ = nullptr;
+    reserved_ = 0;
+    cur_ = nullptr;
+    size_ = 0;
+  }
+};
+
+// This is a minimal replication of std::vector<uint8_t> functionality,
+// except growing from higher to lower addresses. i.e push_back() inserts data
+// in the lowest address in the vector.
+// Since this vector leaves the lower part unused, we support a "scratch-pad"
+// that can be stored there for temporary data, to share the allocated space.
+// Essentially, this supports 2 std::vectors in a single buffer.
+class vector_downward {
+ public:
+  explicit vector_downward(size_t initial_size,
+                           Allocator *allocator,
+                           bool own_allocator,
+                           size_t buffer_minalign)
+      : allocator_(allocator),
+        own_allocator_(own_allocator),
+        initial_size_(initial_size),
+        buffer_minalign_(buffer_minalign),
+        reserved_(0),
+        buf_(nullptr),
+        cur_(nullptr),
+        scratch_(nullptr) {}
+
+  // clang-format off
+  #if !defined(FLATBUFFERS_CPP98_STL)
+  vector_downward(vector_downward &&other)
+  #else
+  vector_downward(vector_downward &other)
+  #endif  // defined(FLATBUFFERS_CPP98_STL)
+  // clang-format on
+    : allocator_(other.allocator_),
+      own_allocator_(other.own_allocator_),
+      initial_size_(other.initial_size_),
+      buffer_minalign_(other.buffer_minalign_),
+      reserved_(other.reserved_),
+      buf_(other.buf_),
+      cur_(other.cur_),
+      scratch_(other.scratch_) {
+    // No change in other.allocator_
+    // No change in other.initial_size_
+    // No change in other.buffer_minalign_
+    other.own_allocator_ = false;
+    other.reserved_ = 0;
+    other.buf_ = nullptr;
+    other.cur_ = nullptr;
+    other.scratch_ = nullptr;
+  }
+
+  // clang-format off
+  #if !defined(FLATBUFFERS_CPP98_STL)
+  // clang-format on
+  vector_downward &operator=(vector_downward &&other) {
+    // Move construct a temporary and swap idiom
+    vector_downward temp(std::move(other));
+    swap(temp);
+    return *this;
+  }
+  // clang-format off
+  #endif  // defined(FLATBUFFERS_CPP98_STL)
+  // clang-format on
+
+  ~vector_downward() {
+    clear_buffer();
+    clear_allocator();
+  }
+
+  void reset() {
+    clear_buffer();
+    clear();
+  }
+
+  void clear() {
+    if (buf_) {
+      cur_ = buf_ + reserved_;
+    } else {
+      reserved_ = 0;
+      cur_ = nullptr;
+    }
+    clear_scratch();
+  }
+
+  void clear_scratch() {
+    scratch_ = buf_;
+  }
+
+  void clear_allocator() {
+    if (own_allocator_ && allocator_) { delete allocator_; }
+    allocator_ = nullptr;
+    own_allocator_ = false;
+  }
+
+  void clear_buffer() {
+    if (buf_) Deallocate(allocator_, buf_, reserved_);
+    buf_ = nullptr;
+  }
+
+  // Relinquish the pointer to the caller.
+  uint8_t *release_raw(size_t &allocated_bytes, size_t &offset) {
+    auto *buf = buf_;
+    allocated_bytes = reserved_;
+    offset = static_cast<size_t>(cur_ - buf_);
+
+    // release_raw only relinquishes the buffer ownership.
+    // Does not deallocate or reset the allocator. Destructor will do that.
+    buf_ = nullptr;
+    clear();
+    return buf;
+  }
+
+  // Relinquish the pointer to the caller.
+  DetachedBuffer release() {
+    // allocator ownership (if any) is transferred to DetachedBuffer.
+    DetachedBuffer fb(allocator_, own_allocator_, buf_, reserved_, cur_,
+                      size());
+    if (own_allocator_) {
+      allocator_ = nullptr;
+      own_allocator_ = false;
+    }
+    buf_ = nullptr;
+    clear();
+    return fb;
+  }
+
+  size_t ensure_space(size_t len) {
+    FLATBUFFERS_ASSERT(cur_ >= scratch_ && scratch_ >= buf_);
+    if (len > static_cast<size_t>(cur_ - scratch_)) { reallocate(len); }
+    // Beyond this, signed offsets may not have enough range:
+    // (FlatBuffers > 2GB not supported).
+    FLATBUFFERS_ASSERT(size() < FLATBUFFERS_MAX_BUFFER_SIZE);
+    return len;
+  }
+
+  inline uint8_t *make_space(size_t len) {
+    size_t space = ensure_space(len);
+    cur_ -= space;
+    return cur_;
+  }
+
+  // Returns nullptr if using the DefaultAllocator.
+  Allocator *get_custom_allocator() { return allocator_; }
+
+  uoffset_t size() const {
+    return static_cast<uoffset_t>(reserved_ - (cur_ - buf_));
+  }
+
+  uoffset_t scratch_size() const {
+    return static_cast<uoffset_t>(scratch_ - buf_);
+  }
+
+  size_t capacity() const { return reserved_; }
+
+  uint8_t *data() const {
+    FLATBUFFERS_ASSERT(cur_);
+    return cur_;
+  }
+
+  uint8_t *scratch_data() const {
+    FLATBUFFERS_ASSERT(buf_);
+    return buf_;
+  }
+
+  uint8_t *scratch_end() const {
+    FLATBUFFERS_ASSERT(scratch_);
+    return scratch_;
+  }
+
+  uint8_t *data_at(size_t offset) const { return buf_ + reserved_ - offset; }
+
+  void push(const uint8_t *bytes, size_t num) {
+    memcpy(make_space(num), bytes, num);
+  }
+
+  // Specialized version of push() that avoids memcpy call for small data.
+  template<typename T> void push_small(const T &little_endian_t) {
+    make_space(sizeof(T));
+    *reinterpret_cast<T *>(cur_) = little_endian_t;
+  }
+
+  template<typename T> void scratch_push_small(const T &t) {
+    ensure_space(sizeof(T));
+    *reinterpret_cast<T *>(scratch_) = t;
+    scratch_ += sizeof(T);
+  }
+
+  // fill() is most frequently called with small byte counts (<= 4),
+  // which is why we're using loops rather than calling memset.
+  void fill(size_t zero_pad_bytes) {
+    make_space(zero_pad_bytes);
+    for (size_t i = 0; i < zero_pad_bytes; i++) cur_[i] = 0;
+  }
+
+  // Version for when we know the size is larger.
+  void fill_big(size_t zero_pad_bytes) {
+    memset(make_space(zero_pad_bytes), 0, zero_pad_bytes);
+  }
+
+  void pop(size_t bytes_to_remove) { cur_ += bytes_to_remove; }
+  void scratch_pop(size_t bytes_to_remove) { scratch_ -= bytes_to_remove; }
+
+  void swap(vector_downward &other) {
+    using std::swap;
+    swap(allocator_, other.allocator_);
+    swap(own_allocator_, other.own_allocator_);
+    swap(initial_size_, other.initial_size_);
+    swap(buffer_minalign_, other.buffer_minalign_);
+    swap(reserved_, other.reserved_);
+    swap(buf_, other.buf_);
+    swap(cur_, other.cur_);
+    swap(scratch_, other.scratch_);
+  }
+
+  void swap_allocator(vector_downward &other) {
+    using std::swap;
+    swap(allocator_, other.allocator_);
+    swap(own_allocator_, other.own_allocator_);
+  }
+
+ private:
+  // You shouldn't really be copying instances of this class.
+  FLATBUFFERS_DELETE_FUNC(vector_downward(const vector_downward &))
+  FLATBUFFERS_DELETE_FUNC(vector_downward &operator=(const vector_downward &))
+
+  Allocator *allocator_;
+  bool own_allocator_;
+  size_t initial_size_;
+  size_t buffer_minalign_;
+  size_t reserved_;
+  uint8_t *buf_;
+  uint8_t *cur_;  // Points at location between empty (below) and used (above).
+  uint8_t *scratch_;  // Points to the end of the scratchpad in use.
+
+  void reallocate(size_t len) {
+    auto old_reserved = reserved_;
+    auto old_size = size();
+    auto old_scratch_size = scratch_size();
+    reserved_ += (std::max)(len,
+                            old_reserved ? old_reserved / 2 : initial_size_);
+    reserved_ = (reserved_ + buffer_minalign_ - 1) & ~(buffer_minalign_ - 1);
+    if (buf_) {
+      buf_ = ReallocateDownward(allocator_, buf_, old_reserved, reserved_,
+                                old_size, old_scratch_size);
+    } else {
+      buf_ = Allocate(allocator_, reserved_);
+    }
+    cur_ = buf_ + reserved_ - old_size;
+    scratch_ = buf_ + old_scratch_size;
+  }
+};
+
+// Converts a Field ID to a virtual table offset.
+inline voffset_t FieldIndexToOffset(voffset_t field_id) {
+  // Should correspond to what EndTable() below builds up.
+  const int fixed_fields = 2;  // Vtable size and Object Size.
+  return static_cast<voffset_t>((field_id + fixed_fields) * sizeof(voffset_t));
+}
+
+template<typename T, typename Alloc>
+const T *data(const std::vector<T, Alloc> &v) {
+  return v.empty() ? nullptr : &v.front();
+}
+template<typename T, typename Alloc> T *data(std::vector<T, Alloc> &v) {
+  return v.empty() ? nullptr : &v.front();
+}
+
+/// @endcond
+
+/// @addtogroup flatbuffers_cpp_api
+/// @{
+/// @class FlatBufferBuilder
+/// @brief Helper class to hold data needed in creation of a FlatBuffer.
+/// To serialize data, you typically call one of the `Create*()` functions in
+/// the generated code, which in turn call a sequence of `StartTable`/
+/// `PushElement`/`AddElement`/`EndTable`, or the builtin `CreateString`/
+/// `CreateVector` functions. Do this is depth-first order to build up a tree to
+/// the root. `Finish()` wraps up the buffer ready for transport.
+class FlatBufferBuilder {
+ public:
+  /// @brief Default constructor for FlatBufferBuilder.
+  /// @param[in] initial_size The initial size of the buffer, in bytes. Defaults
+  /// to `1024`.
+  /// @param[in] allocator An `Allocator` to use. If null will use
+  /// `DefaultAllocator`.
+  /// @param[in] own_allocator Whether the builder/vector should own the
+  /// allocator. Defaults to / `false`.
+  /// @param[in] buffer_minalign Force the buffer to be aligned to the given
+  /// minimum alignment upon reallocation. Only needed if you intend to store
+  /// types with custom alignment AND you wish to read the buffer in-place
+  /// directly after creation.
+  explicit FlatBufferBuilder(size_t initial_size = 1024,
+                             Allocator *allocator = nullptr,
+                             bool own_allocator = false,
+                             size_t buffer_minalign =
+                                 AlignOf<largest_scalar_t>())
+      : buf_(initial_size, allocator, own_allocator, buffer_minalign),
+        num_field_loc(0),
+        max_voffset_(0),
+        nested(false),
+        finished(false),
+        minalign_(1),
+        force_defaults_(false),
+        dedup_vtables_(true),
+        string_pool(nullptr) {
+    EndianCheck();
+  }
+
+  // clang-format off
+  /// @brief Move constructor for FlatBufferBuilder.
+  #if !defined(FLATBUFFERS_CPP98_STL)
+  FlatBufferBuilder(FlatBufferBuilder &&other)
+  #else
+  FlatBufferBuilder(FlatBufferBuilder &other)
+  #endif  // #if !defined(FLATBUFFERS_CPP98_STL)
+    : buf_(1024, nullptr, false, AlignOf<largest_scalar_t>()),
+      num_field_loc(0),
+      max_voffset_(0),
+      nested(false),
+      finished(false),
+      minalign_(1),
+      force_defaults_(false),
+      dedup_vtables_(true),
+      string_pool(nullptr) {
+    EndianCheck();
+    // Default construct and swap idiom.
+    // Lack of delegating constructors in vs2010 makes it more verbose than needed.
+    Swap(other);
+  }
+  // clang-format on
+
+  // clang-format off
+  #if !defined(FLATBUFFERS_CPP98_STL)
+  // clang-format on
+  /// @brief Move assignment operator for FlatBufferBuilder.
+  FlatBufferBuilder &operator=(FlatBufferBuilder &&other) {
+    // Move construct a temporary and swap idiom
+    FlatBufferBuilder temp(std::move(other));
+    Swap(temp);
+    return *this;
+  }
+  // clang-format off
+  #endif  // defined(FLATBUFFERS_CPP98_STL)
+  // clang-format on
+
+  void Swap(FlatBufferBuilder &other) {
+    using std::swap;
+    buf_.swap(other.buf_);
+    swap(num_field_loc, other.num_field_loc);
+    swap(max_voffset_, other.max_voffset_);
+    swap(nested, other.nested);
+    swap(finished, other.finished);
+    swap(minalign_, other.minalign_);
+    swap(force_defaults_, other.force_defaults_);
+    swap(dedup_vtables_, other.dedup_vtables_);
+    swap(string_pool, other.string_pool);
+  }
+
+  ~FlatBufferBuilder() {
+    if (string_pool) delete string_pool;
+  }
+
+  void Reset() {
+    Clear();       // clear builder state
+    buf_.reset();  // deallocate buffer
+  }
+
+  /// @brief Reset all the state in this FlatBufferBuilder so it can be reused
+  /// to construct another buffer.
+  void Clear() {
+    ClearOffsets();
+    buf_.clear();
+    nested = false;
+    finished = false;
+    minalign_ = 1;
+    if (string_pool) string_pool->clear();
+  }
+
+  /// @brief The current size of the serialized buffer, counting from the end.
+  /// @return Returns an `uoffset_t` with the current size of the buffer.
+  uoffset_t GetSize() const { return buf_.size(); }
+
+  /// @brief Get the serialized buffer (after you call `Finish()`).
+  /// @return Returns an `uint8_t` pointer to the FlatBuffer data inside the
+  /// buffer.
+  uint8_t *GetBufferPointer() const {
+    Finished();
+    return buf_.data();
+  }
+
+  /// @brief Get a pointer to an unfinished buffer.
+  /// @return Returns a `uint8_t` pointer to the unfinished buffer.
+  uint8_t *GetCurrentBufferPointer() const { return buf_.data(); }
+
+  /// @brief Get the released pointer to the serialized buffer.
+  /// @warning Do NOT attempt to use this FlatBufferBuilder afterwards!
+  /// @return A `FlatBuffer` that owns the buffer and its allocator and
+  /// behaves similar to a `unique_ptr` with a deleter.
+  FLATBUFFERS_ATTRIBUTE(deprecated("use Release() instead")) DetachedBuffer
+  ReleaseBufferPointer() {
+    Finished();
+    return buf_.release();
+  }
+
+  /// @brief Get the released DetachedBuffer.
+  /// @return A `DetachedBuffer` that owns the buffer and its allocator.
+  DetachedBuffer Release() {
+    Finished();
+    return buf_.release();
+  }
+
+  /// @brief Get the released pointer to the serialized buffer.
+  /// @param The size of the memory block containing
+  /// the serialized `FlatBuffer`.
+  /// @param The offset from the released pointer where the finished
+  /// `FlatBuffer` starts.
+  /// @return A raw pointer to the start of the memory block containing
+  /// the serialized `FlatBuffer`.
+  /// @remark If the allocator is owned, it gets deleted when the destructor is called..
+  uint8_t *ReleaseRaw(size_t &size, size_t &offset) {
+    Finished();
+    return buf_.release_raw(size, offset);
+  }
+
+  /// @brief get the minimum alignment this buffer needs to be accessed
+  /// properly. This is only known once all elements have been written (after
+  /// you call Finish()). You can use this information if you need to embed
+  /// a FlatBuffer in some other buffer, such that you can later read it
+  /// without first having to copy it into its own buffer.
+  size_t GetBufferMinAlignment() {
+    Finished();
+    return minalign_;
+  }
+
+  /// @cond FLATBUFFERS_INTERNAL
+  void Finished() const {
+    // If you get this assert, you're attempting to get access a buffer
+    // which hasn't been finished yet. Be sure to call
+    // FlatBufferBuilder::Finish with your root table.
+    // If you really need to access an unfinished buffer, call
+    // GetCurrentBufferPointer instead.
+    FLATBUFFERS_ASSERT(finished);
+  }
+  /// @endcond
+
+  /// @brief In order to save space, fields that are set to their default value
+  /// don't get serialized into the buffer.
+  /// @param[in] bool fd When set to `true`, always serializes default values that are set.
+  /// Optional fields which are not set explicitly, will still not be serialized.
+  void ForceDefaults(bool fd) { force_defaults_ = fd; }
+
+  /// @brief By default vtables are deduped in order to save space.
+  /// @param[in] bool dedup When set to `true`, dedup vtables.
+  void DedupVtables(bool dedup) { dedup_vtables_ = dedup; }
+
+  /// @cond FLATBUFFERS_INTERNAL
+  void Pad(size_t num_bytes) { buf_.fill(num_bytes); }
+
+  void TrackMinAlign(size_t elem_size) {
+    if (elem_size > minalign_) minalign_ = elem_size;
+  }
+
+  void Align(size_t elem_size) {
+    TrackMinAlign(elem_size);
+    buf_.fill(PaddingBytes(buf_.size(), elem_size));
+  }
+
+  void PushFlatBuffer(const uint8_t *bytes, size_t size) {
+    PushBytes(bytes, size);
+    finished = true;
+  }
+
+  void PushBytes(const uint8_t *bytes, size_t size) { buf_.push(bytes, size); }
+
+  void PopBytes(size_t amount) { buf_.pop(amount); }
+
+  template<typename T> void AssertScalarT() {
+    // The code assumes power of 2 sizes and endian-swap-ability.
+    static_assert(flatbuffers::is_scalar<T>::value, "T must be a scalar type");
+  }
+
+  // Write a single aligned scalar to the buffer
+  template<typename T> uoffset_t PushElement(T element) {
+    AssertScalarT<T>();
+    T litle_endian_element = EndianScalar(element);
+    Align(sizeof(T));
+    buf_.push_small(litle_endian_element);
+    return GetSize();
+  }
+
+  template<typename T> uoffset_t PushElement(Offset<T> off) {
+    // Special case for offsets: see ReferTo below.
+    return PushElement(ReferTo(off.o));
+  }
+
+  // When writing fields, we track where they are, so we can create correct
+  // vtables later.
+  void TrackField(voffset_t field, uoffset_t off) {
+    FieldLoc fl = { off, field };
+    buf_.scratch_push_small(fl);
+    num_field_loc++;
+    max_voffset_ = (std::max)(max_voffset_, field);
+  }
+
+  // Like PushElement, but additionally tracks the field this represents.
+  template<typename T> void AddElement(voffset_t field, T e, T def) {
+    // We don't serialize values equal to the default.
+    if (IsTheSameAs(e, def) && !force_defaults_) return;
+    auto off = PushElement(e);
+    TrackField(field, off);
+  }
+
+  template<typename T> void AddOffset(voffset_t field, Offset<T> off) {
+    if (off.IsNull()) return;  // Don't store.
+    AddElement(field, ReferTo(off.o), static_cast<uoffset_t>(0));
+  }
+
+  template<typename T> void AddStruct(voffset_t field, const T *structptr) {
+    if (!structptr) return;  // Default, don't store.
+    Align(AlignOf<T>());
+    buf_.push_small(*structptr);
+    TrackField(field, GetSize());
+  }
+
+  void AddStructOffset(voffset_t field, uoffset_t off) {
+    TrackField(field, off);
+  }
+
+  // Offsets initially are relative to the end of the buffer (downwards).
+  // This function converts them to be relative to the current location
+  // in the buffer (when stored here), pointing upwards.
+  uoffset_t ReferTo(uoffset_t off) {
+    // Align to ensure GetSize() below is correct.
+    Align(sizeof(uoffset_t));
+    // Offset must refer to something already in buffer.
+    FLATBUFFERS_ASSERT(off && off <= GetSize());
+    return GetSize() - off + static_cast<uoffset_t>(sizeof(uoffset_t));
+  }
+
+  void NotNested() {
+    // If you hit this, you're trying to construct a Table/Vector/String
+    // during the construction of its parent table (between the MyTableBuilder
+    // and table.Finish().
+    // Move the creation of these sub-objects to above the MyTableBuilder to
+    // not get this assert.
+    // Ignoring this assert may appear to work in simple cases, but the reason
+    // it is here is that storing objects in-line may cause vtable offsets
+    // to not fit anymore. It also leads to vtable duplication.
+    FLATBUFFERS_ASSERT(!nested);
+    // If you hit this, fields were added outside the scope of a table.
+    FLATBUFFERS_ASSERT(!num_field_loc);
+  }
+
+  // From generated code (or from the parser), we call StartTable/EndTable
+  // with a sequence of AddElement calls in between.
+  uoffset_t StartTable() {
+    NotNested();
+    nested = true;
+    return GetSize();
+  }
+
+  // This finishes one serialized object by generating the vtable if it's a
+  // table, comparing it against existing vtables, and writing the
+  // resulting vtable offset.
+  uoffset_t EndTable(uoffset_t start) {
+    // If you get this assert, a corresponding StartTable wasn't called.
+    FLATBUFFERS_ASSERT(nested);
+    // Write the vtable offset, which is the start of any Table.
+    // We fill it's value later.
+    auto vtableoffsetloc = PushElement<soffset_t>(0);
+    // Write a vtable, which consists entirely of voffset_t elements.
+    // It starts with the number of offsets, followed by a type id, followed
+    // by the offsets themselves. In reverse:
+    // Include space for the last offset and ensure empty tables have a
+    // minimum size.
+    max_voffset_ =
+        (std::max)(static_cast<voffset_t>(max_voffset_ + sizeof(voffset_t)),
+                   FieldIndexToOffset(0));
+    buf_.fill_big(max_voffset_);
+    auto table_object_size = vtableoffsetloc - start;
+    // Vtable use 16bit offsets.
+    FLATBUFFERS_ASSERT(table_object_size < 0x10000);
+    WriteScalar<voffset_t>(buf_.data() + sizeof(voffset_t),
+                           static_cast<voffset_t>(table_object_size));
+    WriteScalar<voffset_t>(buf_.data(), max_voffset_);
+    // Write the offsets into the table
+    for (auto it = buf_.scratch_end() - num_field_loc * sizeof(FieldLoc);
+         it < buf_.scratch_end(); it += sizeof(FieldLoc)) {
+      auto field_location = reinterpret_cast<FieldLoc *>(it);
+      auto pos = static_cast<voffset_t>(vtableoffsetloc - field_location->off);
+      // If this asserts, it means you've set a field twice.
+      FLATBUFFERS_ASSERT(
+          !ReadScalar<voffset_t>(buf_.data() + field_location->id));
+      WriteScalar<voffset_t>(buf_.data() + field_location->id, pos);
+    }
+    ClearOffsets();
+    auto vt1 = reinterpret_cast<voffset_t *>(buf_.data());
+    auto vt1_size = ReadScalar<voffset_t>(vt1);
+    auto vt_use = GetSize();
+    // See if we already have generated a vtable with this exact same
+    // layout before. If so, make it point to the old one, remove this one.
+    if (dedup_vtables_) {
+      for (auto it = buf_.scratch_data(); it < buf_.scratch_end();
+           it += sizeof(uoffset_t)) {
+        auto vt_offset_ptr = reinterpret_cast<uoffset_t *>(it);
+        auto vt2 = reinterpret_cast<voffset_t *>(buf_.data_at(*vt_offset_ptr));
+        auto vt2_size = *vt2;
+        if (vt1_size != vt2_size || 0 != memcmp(vt2, vt1, vt1_size)) continue;
+        vt_use = *vt_offset_ptr;
+        buf_.pop(GetSize() - vtableoffsetloc);
+        break;
+      }
+    }
+    // If this is a new vtable, remember it.
+    if (vt_use == GetSize()) { buf_.scratch_push_small(vt_use); }
+    // Fill the vtable offset we created above.
+    // The offset points from the beginning of the object to where the
+    // vtable is stored.
+    // Offsets default direction is downward in memory for future format
+    // flexibility (storing all vtables at the start of the file).
+    WriteScalar(buf_.data_at(vtableoffsetloc),
+                static_cast<soffset_t>(vt_use) -
+                    static_cast<soffset_t>(vtableoffsetloc));
+
+    nested = false;
+    return vtableoffsetloc;
+  }
+
+  FLATBUFFERS_ATTRIBUTE(deprecated("call the version above instead"))
+  uoffset_t EndTable(uoffset_t start, voffset_t /*numfields*/) {
+    return EndTable(start);
+  }
+
+  // This checks a required field has been set in a given table that has
+  // just been constructed.
+  template<typename T> void Required(Offset<T> table, voffset_t field);
+
+  uoffset_t StartStruct(size_t alignment) {
+    Align(alignment);
+    return GetSize();
+  }
+
+  uoffset_t EndStruct() { return GetSize(); }
+
+  void ClearOffsets() {
+    buf_.scratch_pop(num_field_loc * sizeof(FieldLoc));
+    num_field_loc = 0;
+    max_voffset_ = 0;
+  }
+
+  // Aligns such that when "len" bytes are written, an object can be written
+  // after it with "alignment" without padding.
+  void PreAlign(size_t len, size_t alignment) {
+    TrackMinAlign(alignment);
+    buf_.fill(PaddingBytes(GetSize() + len, alignment));
+  }
+  template<typename T> void PreAlign(size_t len) {
+    AssertScalarT<T>();
+    PreAlign(len, sizeof(T));
+  }
+  /// @endcond
+
+  /// @brief Store a string in the buffer, which can contain any binary data.
+  /// @param[in] str A const char pointer to the data to be stored as a string.
+  /// @param[in] len The number of bytes that should be stored from `str`.
+  /// @return Returns the offset in the buffer where the string starts.
+  Offset<String> CreateString(const char *str, size_t len) {
+    NotNested();
+    PreAlign<uoffset_t>(len + 1);  // Always 0-terminated.
+    buf_.fill(1);
+    PushBytes(reinterpret_cast<const uint8_t *>(str), len);
+    PushElement(static_cast<uoffset_t>(len));
+    return Offset<String>(GetSize());
+  }
+
+  /// @brief Store a string in the buffer, which is null-terminated.
+  /// @param[in] str A const char pointer to a C-string to add to the buffer.
+  /// @return Returns the offset in the buffer where the string starts.
+  Offset<String> CreateString(const char *str) {
+    return CreateString(str, strlen(str));
+  }
+
+  /// @brief Store a string in the buffer, which is null-terminated.
+  /// @param[in] str A char pointer to a C-string to add to the buffer.
+  /// @return Returns the offset in the buffer where the string starts.
+  Offset<String> CreateString(char *str) {
+    return CreateString(str, strlen(str));
+  }
+
+  /// @brief Store a string in the buffer, which can contain any binary data.
+  /// @param[in] str A const reference to a std::string to store in the buffer.
+  /// @return Returns the offset in the buffer where the string starts.
+  Offset<String> CreateString(const std::string &str) {
+    return CreateString(str.c_str(), str.length());
+  }
+
+  // clang-format off
+  #ifdef FLATBUFFERS_HAS_STRING_VIEW
+  /// @brief Store a string in the buffer, which can contain any binary data.
+  /// @param[in] str A const string_view to copy in to the buffer.
+  /// @return Returns the offset in the buffer where the string starts.
+  Offset<String> CreateString(flatbuffers::string_view str) {
+    return CreateString(str.data(), str.size());
+  }
+  #endif // FLATBUFFERS_HAS_STRING_VIEW
+  // clang-format on
+
+  /// @brief Store a string in the buffer, which can contain any binary data.
+  /// @param[in] str A const pointer to a `String` struct to add to the buffer.
+  /// @return Returns the offset in the buffer where the string starts
+  Offset<String> CreateString(const String *str) {
+    return str ? CreateString(str->c_str(), str->size()) : 0;
+  }
+
+  /// @brief Store a string in the buffer, which can contain any binary data.
+  /// @param[in] str A const reference to a std::string like type with support
+  /// of T::c_str() and T::length() to store in the buffer.
+  /// @return Returns the offset in the buffer where the string starts.
+  template<typename T> Offset<String> CreateString(const T &str) {
+    return CreateString(str.c_str(), str.length());
+  }
+
+  /// @brief Store a string in the buffer, which can contain any binary data.
+  /// If a string with this exact contents has already been serialized before,
+  /// instead simply returns the offset of the existing string.
+  /// @param[in] str A const char pointer to the data to be stored as a string.
+  /// @param[in] len The number of bytes that should be stored from `str`.
+  /// @return Returns the offset in the buffer where the string starts.
+  Offset<String> CreateSharedString(const char *str, size_t len) {
+    if (!string_pool)
+      string_pool = new StringOffsetMap(StringOffsetCompare(buf_));
+    auto size_before_string = buf_.size();
+    // Must first serialize the string, since the set is all offsets into
+    // buffer.
+    auto off = CreateString(str, len);
+    auto it = string_pool->find(off);
+    // If it exists we reuse existing serialized data!
+    if (it != string_pool->end()) {
+      // We can remove the string we serialized.
+      buf_.pop(buf_.size() - size_before_string);
+      return *it;
+    }
+    // Record this string for future use.
+    string_pool->insert(off);
+    return off;
+  }
+
+  /// @brief Store a string in the buffer, which null-terminated.
+  /// If a string with this exact contents has already been serialized before,
+  /// instead simply returns the offset of the existing string.
+  /// @param[in] str A const char pointer to a C-string to add to the buffer.
+  /// @return Returns the offset in the buffer where the string starts.
+  Offset<String> CreateSharedString(const char *str) {
+    return CreateSharedString(str, strlen(str));
+  }
+
+  /// @brief Store a string in the buffer, which can contain any binary data.
+  /// If a string with this exact contents has already been serialized before,
+  /// instead simply returns the offset of the existing string.
+  /// @param[in] str A const reference to a std::string to store in the buffer.
+  /// @return Returns the offset in the buffer where the string starts.
+  Offset<String> CreateSharedString(const std::string &str) {
+    return CreateSharedString(str.c_str(), str.length());
+  }
+
+  /// @brief Store a string in the buffer, which can contain any binary data.
+  /// If a string with this exact contents has already been serialized before,
+  /// instead simply returns the offset of the existing string.
+  /// @param[in] str A const pointer to a `String` struct to add to the buffer.
+  /// @return Returns the offset in the buffer where the string starts
+  Offset<String> CreateSharedString(const String *str) {
+    return CreateSharedString(str->c_str(), str->size());
+  }
+
+  /// @cond FLATBUFFERS_INTERNAL
+  uoffset_t EndVector(size_t len) {
+    FLATBUFFERS_ASSERT(nested);  // Hit if no corresponding StartVector.
+    nested = false;
+    return PushElement(static_cast<uoffset_t>(len));
+  }
+
+  void StartVector(size_t len, size_t elemsize) {
+    NotNested();
+    nested = true;
+    PreAlign<uoffset_t>(len * elemsize);
+    PreAlign(len * elemsize, elemsize);  // Just in case elemsize > uoffset_t.
+  }
+
+  // Call this right before StartVector/CreateVector if you want to force the
+  // alignment to be something different than what the element size would
+  // normally dictate.
+  // This is useful when storing a nested_flatbuffer in a vector of bytes,
+  // or when storing SIMD floats, etc.
+  void ForceVectorAlignment(size_t len, size_t elemsize, size_t alignment) {
+    PreAlign(len * elemsize, alignment);
+  }
+
+  // Similar to ForceVectorAlignment but for String fields.
+  void ForceStringAlignment(size_t len, size_t alignment) {
+    PreAlign((len + 1) * sizeof(char), alignment);
+  }
+
+  /// @endcond
+
+  /// @brief Serialize an array into a FlatBuffer `vector`.
+  /// @tparam T The data type of the array elements.
+  /// @param[in] v A pointer to the array of type `T` to serialize into the
+  /// buffer as a `vector`.
+  /// @param[in] len The number of elements to serialize.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T> Offset<Vector<T>> CreateVector(const T *v, size_t len) {
+    // If this assert hits, you're specifying a template argument that is
+    // causing the wrong overload to be selected, remove it.
+    AssertScalarT<T>();
+    StartVector(len, sizeof(T));
+    // clang-format off
+    #if FLATBUFFERS_LITTLEENDIAN
+      PushBytes(reinterpret_cast<const uint8_t *>(v), len * sizeof(T));
+    #else
+      if (sizeof(T) == 1) {
+        PushBytes(reinterpret_cast<const uint8_t *>(v), len);
+      } else {
+        for (auto i = len; i > 0; ) {
+          PushElement(v[--i]);
+        }
+      }
+    #endif
+    // clang-format on
+    return Offset<Vector<T>>(EndVector(len));
+  }
+
+  template<typename T>
+  Offset<Vector<Offset<T>>> CreateVector(const Offset<T> *v, size_t len) {
+    StartVector(len, sizeof(Offset<T>));
+    for (auto i = len; i > 0;) { PushElement(v[--i]); }
+    return Offset<Vector<Offset<T>>>(EndVector(len));
+  }
+
+  /// @brief Serialize a `std::vector` into a FlatBuffer `vector`.
+  /// @tparam T The data type of the `std::vector` elements.
+  /// @param v A const reference to the `std::vector` to serialize into the
+  /// buffer as a `vector`.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T> Offset<Vector<T>> CreateVector(const std::vector<T> &v) {
+    return CreateVector(data(v), v.size());
+  }
+
+  // vector<bool> may be implemented using a bit-set, so we can't access it as
+  // an array. Instead, read elements manually.
+  // Background: https://isocpp.org/blog/2012/11/on-vectorbool
+  Offset<Vector<uint8_t>> CreateVector(const std::vector<bool> &v) {
+    StartVector(v.size(), sizeof(uint8_t));
+    for (auto i = v.size(); i > 0;) {
+      PushElement(static_cast<uint8_t>(v[--i]));
+    }
+    return Offset<Vector<uint8_t>>(EndVector(v.size()));
+  }
+
+  // clang-format off
+  #ifndef FLATBUFFERS_CPP98_STL
+  /// @brief Serialize values returned by a function into a FlatBuffer `vector`.
+  /// This is a convenience function that takes care of iteration for you.
+  /// @tparam T The data type of the `std::vector` elements.
+  /// @param f A function that takes the current iteration 0..vector_size-1 and
+  /// returns any type that you can construct a FlatBuffers vector out of.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T> Offset<Vector<T>> CreateVector(size_t vector_size,
+      const std::function<T (size_t i)> &f) {
+    std::vector<T> elems(vector_size);
+    for (size_t i = 0; i < vector_size; i++) elems[i] = f(i);
+    return CreateVector(elems);
+  }
+  #endif
+  // clang-format on
+
+  /// @brief Serialize values returned by a function into a FlatBuffer `vector`.
+  /// This is a convenience function that takes care of iteration for you.
+  /// @tparam T The data type of the `std::vector` elements.
+  /// @param f A function that takes the current iteration 0..vector_size-1,
+  /// and the state parameter returning any type that you can construct a
+  /// FlatBuffers vector out of.
+  /// @param state State passed to f.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T, typename F, typename S>
+  Offset<Vector<T>> CreateVector(size_t vector_size, F f, S *state) {
+    std::vector<T> elems(vector_size);
+    for (size_t i = 0; i < vector_size; i++) elems[i] = f(i, state);
+    return CreateVector(elems);
+  }
+
+  /// @brief Serialize a `std::vector<std::string>` into a FlatBuffer `vector`.
+  /// This is a convenience function for a common case.
+  /// @param v A const reference to the `std::vector` to serialize into the
+  /// buffer as a `vector`.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  Offset<Vector<Offset<String>>> CreateVectorOfStrings(
+      const std::vector<std::string> &v) {
+    std::vector<Offset<String>> offsets(v.size());
+    for (size_t i = 0; i < v.size(); i++) offsets[i] = CreateString(v[i]);
+    return CreateVector(offsets);
+  }
+
+  /// @brief Serialize an array of structs into a FlatBuffer `vector`.
+  /// @tparam T The data type of the struct array elements.
+  /// @param[in] v A pointer to the array of type `T` to serialize into the
+  /// buffer as a `vector`.
+  /// @param[in] len The number of elements to serialize.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T>
+  Offset<Vector<const T *>> CreateVectorOfStructs(const T *v, size_t len) {
+    StartVector(len * sizeof(T) / AlignOf<T>(), AlignOf<T>());
+    PushBytes(reinterpret_cast<const uint8_t *>(v), sizeof(T) * len);
+    return Offset<Vector<const T *>>(EndVector(len));
+  }
+
+  /// @brief Serialize an array of native structs into a FlatBuffer `vector`.
+  /// @tparam T The data type of the struct array elements.
+  /// @tparam S The data type of the native struct array elements.
+  /// @param[in] v A pointer to the array of type `S` to serialize into the
+  /// buffer as a `vector`.
+  /// @param[in] len The number of elements to serialize.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T, typename S>
+  Offset<Vector<const T *>> CreateVectorOfNativeStructs(const S *v,
+                                                        size_t len) {
+    extern T Pack(const S &);
+    typedef T (*Pack_t)(const S &);
+    std::vector<T> vv(len);
+    std::transform(v, v + len, vv.begin(), static_cast<Pack_t&>(Pack));
+    return CreateVectorOfStructs<T>(vv.data(), vv.size());
+  }
+
+  // clang-format off
+  #ifndef FLATBUFFERS_CPP98_STL
+  /// @brief Serialize an array of structs into a FlatBuffer `vector`.
+  /// @tparam T The data type of the struct array elements.
+  /// @param[in] f A function that takes the current iteration 0..vector_size-1
+  /// and a pointer to the struct that must be filled.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  /// This is mostly useful when flatbuffers are generated with mutation
+  /// accessors.
+  template<typename T> Offset<Vector<const T *>> CreateVectorOfStructs(
+      size_t vector_size, const std::function<void(size_t i, T *)> &filler) {
+    T* structs = StartVectorOfStructs<T>(vector_size);
+    for (size_t i = 0; i < vector_size; i++) {
+      filler(i, structs);
+      structs++;
+    }
+    return EndVectorOfStructs<T>(vector_size);
+  }
+  #endif
+  // clang-format on
+
+  /// @brief Serialize an array of structs into a FlatBuffer `vector`.
+  /// @tparam T The data type of the struct array elements.
+  /// @param[in] f A function that takes the current iteration 0..vector_size-1,
+  /// a pointer to the struct that must be filled and the state argument.
+  /// @param[in] state Arbitrary state to pass to f.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  /// This is mostly useful when flatbuffers are generated with mutation
+  /// accessors.
+  template<typename T, typename F, typename S>
+  Offset<Vector<const T *>> CreateVectorOfStructs(size_t vector_size, F f,
+                                                  S *state) {
+    T *structs = StartVectorOfStructs<T>(vector_size);
+    for (size_t i = 0; i < vector_size; i++) {
+      f(i, structs, state);
+      structs++;
+    }
+    return EndVectorOfStructs<T>(vector_size);
+  }
+
+  /// @brief Serialize a `std::vector` of structs into a FlatBuffer `vector`.
+  /// @tparam T The data type of the `std::vector` struct elements.
+  /// @param[in]] v A const reference to the `std::vector` of structs to
+  /// serialize into the buffer as a `vector`.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T, typename Alloc>
+  Offset<Vector<const T *>> CreateVectorOfStructs(
+      const std::vector<T, Alloc> &v) {
+    return CreateVectorOfStructs(data(v), v.size());
+  }
+
+  /// @brief Serialize a `std::vector` of native structs into a FlatBuffer
+  /// `vector`.
+  /// @tparam T The data type of the `std::vector` struct elements.
+  /// @tparam S The data type of the `std::vector` native struct elements.
+  /// @param[in]] v A const reference to the `std::vector` of structs to
+  /// serialize into the buffer as a `vector`.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T, typename S>
+  Offset<Vector<const T *>> CreateVectorOfNativeStructs(
+      const std::vector<S> &v) {
+    return CreateVectorOfNativeStructs<T, S>(data(v), v.size());
+  }
+
+  /// @cond FLATBUFFERS_INTERNAL
+  template<typename T> struct StructKeyComparator {
+    bool operator()(const T &a, const T &b) const {
+      return a.KeyCompareLessThan(&b);
+    }
+
+   private:
+    StructKeyComparator &operator=(const StructKeyComparator &);
+  };
+  /// @endcond
+
+  /// @brief Serialize a `std::vector` of structs into a FlatBuffer `vector`
+  /// in sorted order.
+  /// @tparam T The data type of the `std::vector` struct elements.
+  /// @param[in]] v A const reference to the `std::vector` of structs to
+  /// serialize into the buffer as a `vector`.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T>
+  Offset<Vector<const T *>> CreateVectorOfSortedStructs(std::vector<T> *v) {
+    return CreateVectorOfSortedStructs(data(*v), v->size());
+  }
+
+  /// @brief Serialize a `std::vector` of native structs into a FlatBuffer
+  /// `vector` in sorted order.
+  /// @tparam T The data type of the `std::vector` struct elements.
+  /// @tparam S The data type of the `std::vector` native struct elements.
+  /// @param[in]] v A const reference to the `std::vector` of structs to
+  /// serialize into the buffer as a `vector`.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T, typename S>
+  Offset<Vector<const T *>> CreateVectorOfSortedNativeStructs(
+      std::vector<S> *v) {
+    return CreateVectorOfSortedNativeStructs<T, S>(data(*v), v->size());
+  }
+
+  /// @brief Serialize an array of structs into a FlatBuffer `vector` in sorted
+  /// order.
+  /// @tparam T The data type of the struct array elements.
+  /// @param[in] v A pointer to the array of type `T` to serialize into the
+  /// buffer as a `vector`.
+  /// @param[in] len The number of elements to serialize.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T>
+  Offset<Vector<const T *>> CreateVectorOfSortedStructs(T *v, size_t len) {
+    std::sort(v, v + len, StructKeyComparator<T>());
+    return CreateVectorOfStructs(v, len);
+  }
+
+  /// @brief Serialize an array of native structs into a FlatBuffer `vector` in
+  /// sorted order.
+  /// @tparam T The data type of the struct array elements.
+  /// @tparam S The data type of the native struct array elements.
+  /// @param[in] v A pointer to the array of type `S` to serialize into the
+  /// buffer as a `vector`.
+  /// @param[in] len The number of elements to serialize.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T, typename S>
+  Offset<Vector<const T *>> CreateVectorOfSortedNativeStructs(S *v,
+                                                              size_t len) {
+    extern T Pack(const S &);
+    typedef T (*Pack_t)(const S &);
+    std::vector<T> vv(len);
+    std::transform(v, v + len, vv.begin(), static_cast<Pack_t&>(Pack));
+    return CreateVectorOfSortedStructs<T>(vv, len);
+  }
+
+  /// @cond FLATBUFFERS_INTERNAL
+  template<typename T> struct TableKeyComparator {
+    TableKeyComparator(vector_downward &buf) : buf_(buf) {}
+    bool operator()(const Offset<T> &a, const Offset<T> &b) const {
+      auto table_a = reinterpret_cast<T *>(buf_.data_at(a.o));
+      auto table_b = reinterpret_cast<T *>(buf_.data_at(b.o));
+      return table_a->KeyCompareLessThan(table_b);
+    }
+    vector_downward &buf_;
+
+   private:
+    TableKeyComparator &operator=(const TableKeyComparator &);
+  };
+  /// @endcond
+
+  /// @brief Serialize an array of `table` offsets as a `vector` in the buffer
+  /// in sorted order.
+  /// @tparam T The data type that the offset refers to.
+  /// @param[in] v An array of type `Offset<T>` that contains the `table`
+  /// offsets to store in the buffer in sorted order.
+  /// @param[in] len The number of elements to store in the `vector`.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T>
+  Offset<Vector<Offset<T>>> CreateVectorOfSortedTables(Offset<T> *v,
+                                                       size_t len) {
+    std::sort(v, v + len, TableKeyComparator<T>(buf_));
+    return CreateVector(v, len);
+  }
+
+  /// @brief Serialize an array of `table` offsets as a `vector` in the buffer
+  /// in sorted order.
+  /// @tparam T The data type that the offset refers to.
+  /// @param[in] v An array of type `Offset<T>` that contains the `table`
+  /// offsets to store in the buffer in sorted order.
+  /// @return Returns a typed `Offset` into the serialized data indicating
+  /// where the vector is stored.
+  template<typename T>
+  Offset<Vector<Offset<T>>> CreateVectorOfSortedTables(
+      std::vector<Offset<T>> *v) {
+    return CreateVectorOfSortedTables(data(*v), v->size());
+  }
+
+  /// @brief Specialized version of `CreateVector` for non-copying use cases.
+  /// Write the data any time later to the returned buffer pointer `buf`.
+  /// @param[in] len The number of elements to store in the `vector`.
+  /// @param[in] elemsize The size of each element in the `vector`.
+  /// @param[out] buf A pointer to a `uint8_t` pointer that can be
+  /// written to at a later time to serialize the data into a `vector`
+  /// in the buffer.
+  uoffset_t CreateUninitializedVector(size_t len, size_t elemsize,
+                                      uint8_t **buf) {
+    NotNested();
+    StartVector(len, elemsize);
+    buf_.make_space(len * elemsize);
+    auto vec_start = GetSize();
+    auto vec_end = EndVector(len);
+    *buf = buf_.data_at(vec_start);
+    return vec_end;
+  }
+
+  /// @brief Specialized version of `CreateVector` for non-copying use cases.
+  /// Write the data any time later to the returned buffer pointer `buf`.
+  /// @tparam T The data type of the data that will be stored in the buffer
+  /// as a `vector`.
+  /// @param[in] len The number of elements to store in the `vector`.
+  /// @param[out] buf A pointer to a pointer of type `T` that can be
+  /// written to at a later time to serialize the data into a `vector`
+  /// in the buffer.
+  template<typename T>
+  Offset<Vector<T>> CreateUninitializedVector(size_t len, T **buf) {
+    AssertScalarT<T>();
+    return CreateUninitializedVector(len, sizeof(T),
+                                     reinterpret_cast<uint8_t **>(buf));
+  }
+
+  template<typename T>
+  Offset<Vector<const T*>> CreateUninitializedVectorOfStructs(size_t len, T **buf) {
+    return CreateUninitializedVector(len, sizeof(T),
+                                     reinterpret_cast<uint8_t **>(buf));
+  }
+
+
+  // @brief Create a vector of scalar type T given as input a vector of scalar
+  // type U, useful with e.g. pre "enum class" enums, or any existing scalar
+  // data of the wrong type.
+  template<typename T, typename U>
+  Offset<Vector<T>> CreateVectorScalarCast(const U *v, size_t len) {
+    AssertScalarT<T>();
+    AssertScalarT<U>();
+    StartVector(len, sizeof(T));
+    for (auto i = len; i > 0;) { PushElement(static_cast<T>(v[--i])); }
+    return Offset<Vector<T>>(EndVector(len));
+  }
+
+  /// @brief Write a struct by itself, typically to be part of a union.
+  template<typename T> Offset<const T *> CreateStruct(const T &structobj) {
+    NotNested();
+    Align(AlignOf<T>());
+    buf_.push_small(structobj);
+    return Offset<const T *>(GetSize());
+  }
+
+  /// @brief The length of a FlatBuffer file header.
+  static const size_t kFileIdentifierLength = 4;
+
+  /// @brief Finish serializing a buffer by writing the root offset.
+  /// @param[in] file_identifier If a `file_identifier` is given, the buffer
+  /// will be prefixed with a standard FlatBuffers file header.
+  template<typename T>
+  void Finish(Offset<T> root, const char *file_identifier = nullptr) {
+    Finish(root.o, file_identifier, false);
+  }
+
+  /// @brief Finish a buffer with a 32 bit size field pre-fixed (size of the
+  /// buffer following the size field). These buffers are NOT compatible
+  /// with standard buffers created by Finish, i.e. you can't call GetRoot
+  /// on them, you have to use GetSizePrefixedRoot instead.
+  /// All >32 bit quantities in this buffer will be aligned when the whole
+  /// size pre-fixed buffer is aligned.
+  /// These kinds of buffers are useful for creating a stream of FlatBuffers.
+  template<typename T>
+  void FinishSizePrefixed(Offset<T> root,
+                          const char *file_identifier = nullptr) {
+    Finish(root.o, file_identifier, true);
+  }
+
+  void SwapBufAllocator(FlatBufferBuilder &other) {
+    buf_.swap_allocator(other.buf_);
+  }
+
+protected:
+
+  // You shouldn't really be copying instances of this class.
+  FlatBufferBuilder(const FlatBufferBuilder &);
+  FlatBufferBuilder &operator=(const FlatBufferBuilder &);
+
+  void Finish(uoffset_t root, const char *file_identifier, bool size_prefix) {
+    NotNested();
+    buf_.clear_scratch();
+    // This will cause the whole buffer to be aligned.
+    PreAlign((size_prefix ? sizeof(uoffset_t) : 0) + sizeof(uoffset_t) +
+                 (file_identifier ? kFileIdentifierLength : 0),
+             minalign_);
+    if (file_identifier) {
+      FLATBUFFERS_ASSERT(strlen(file_identifier) == kFileIdentifierLength);
+      PushBytes(reinterpret_cast<const uint8_t *>(file_identifier),
+                kFileIdentifierLength);
+    }
+    PushElement(ReferTo(root));  // Location of root.
+    if (size_prefix) { PushElement(GetSize()); }
+    finished = true;
+  }
+
+  struct FieldLoc {
+    uoffset_t off;
+    voffset_t id;
+  };
+
+  vector_downward buf_;
+
+  // Accumulating offsets of table members while it is being built.
+  // We store these in the scratch pad of buf_, after the vtable offsets.
+  uoffset_t num_field_loc;
+  // Track how much of the vtable is in use, so we can output the most compact
+  // possible vtable.
+  voffset_t max_voffset_;
+
+  // Ensure objects are not nested.
+  bool nested;
+
+  // Ensure the buffer is finished before it is being accessed.
+  bool finished;
+
+  size_t minalign_;
+
+  bool force_defaults_;  // Serialize values equal to their defaults anyway.
+
+  bool dedup_vtables_;
+
+  struct StringOffsetCompare {
+    StringOffsetCompare(const vector_downward &buf) : buf_(&buf) {}
+    bool operator()(const Offset<String> &a, const Offset<String> &b) const {
+      auto stra = reinterpret_cast<const String *>(buf_->data_at(a.o));
+      auto strb = reinterpret_cast<const String *>(buf_->data_at(b.o));
+      return StringLessThan(stra->data(), stra->size(),
+                            strb->data(), strb->size());
+    }
+    const vector_downward *buf_;
+  };
+
+  // For use with CreateSharedString. Instantiated on first use only.
+  typedef std::set<Offset<String>, StringOffsetCompare> StringOffsetMap;
+  StringOffsetMap *string_pool;
+
+ private:
+  // Allocates space for a vector of structures.
+  // Must be completed with EndVectorOfStructs().
+  template<typename T> T *StartVectorOfStructs(size_t vector_size) {
+    StartVector(vector_size * sizeof(T) / AlignOf<T>(), AlignOf<T>());
+    return reinterpret_cast<T *>(buf_.make_space(vector_size * sizeof(T)));
+  }
+
+  // End the vector of structues in the flatbuffers.
+  // Vector should have previously be started with StartVectorOfStructs().
+  template<typename T>
+  Offset<Vector<const T *>> EndVectorOfStructs(size_t vector_size) {
+    return Offset<Vector<const T *>>(EndVector(vector_size));
+  }
+};
+/// @}
+
+/// @cond FLATBUFFERS_INTERNAL
+// Helpers to get a typed pointer to the root object contained in the buffer.
+template<typename T> T *GetMutableRoot(void *buf) {
+  EndianCheck();
+  return reinterpret_cast<T *>(
+      reinterpret_cast<uint8_t *>(buf) +
+      EndianScalar(*reinterpret_cast<uoffset_t *>(buf)));
+}
+
+template<typename T> const T *GetRoot(const void *buf) {
+  return GetMutableRoot<T>(const_cast<void *>(buf));
+}
+
+template<typename T> const T *GetSizePrefixedRoot(const void *buf) {
+  return GetRoot<T>(reinterpret_cast<const uint8_t *>(buf) + sizeof(uoffset_t));
+}
+
+/// Helpers to get a typed pointer to objects that are currently being built.
+/// @warning Creating new objects will lead to reallocations and invalidates
+/// the pointer!
+template<typename T>
+T *GetMutableTemporaryPointer(FlatBufferBuilder &fbb, Offset<T> offset) {
+  return reinterpret_cast<T *>(fbb.GetCurrentBufferPointer() + fbb.GetSize() -
+                               offset.o);
+}
+
+template<typename T>
+const T *GetTemporaryPointer(FlatBufferBuilder &fbb, Offset<T> offset) {
+  return GetMutableTemporaryPointer<T>(fbb, offset);
+}
+
+/// @brief Get a pointer to the the file_identifier section of the buffer.
+/// @return Returns a const char pointer to the start of the file_identifier
+/// characters in the buffer.  The returned char * has length
+/// 'flatbuffers::FlatBufferBuilder::kFileIdentifierLength'.
+/// This function is UNDEFINED for FlatBuffers whose schema does not include
+/// a file_identifier (likely points at padding or the start of a the root
+/// vtable).
+inline const char *GetBufferIdentifier(const void *buf, bool size_prefixed = false) {
+  return reinterpret_cast<const char *>(buf) +
+         ((size_prefixed) ? 2 * sizeof(uoffset_t) : sizeof(uoffset_t));
+}
+
+// Helper to see if the identifier in a buffer has the expected value.
+inline bool BufferHasIdentifier(const void *buf, const char *identifier, bool size_prefixed = false) {
+  return strncmp(GetBufferIdentifier(buf, size_prefixed), identifier,
+                 FlatBufferBuilder::kFileIdentifierLength) == 0;
+}
+
+// Helper class to verify the integrity of a FlatBuffer
+class Verifier FLATBUFFERS_FINAL_CLASS {
+ public:
+  Verifier(const uint8_t *buf, size_t buf_len, uoffset_t _max_depth = 64,
+           uoffset_t _max_tables = 1000000, bool _check_alignment = true)
+      : buf_(buf),
+        size_(buf_len),
+        depth_(0),
+        max_depth_(_max_depth),
+        num_tables_(0),
+        max_tables_(_max_tables),
+        upper_bound_(0),
+        check_alignment_(_check_alignment)
+  {
+    FLATBUFFERS_ASSERT(size_ < FLATBUFFERS_MAX_BUFFER_SIZE);
+  }
+
+  // Central location where any verification failures register.
+  bool Check(bool ok) const {
+    // clang-format off
+    #ifdef FLATBUFFERS_DEBUG_VERIFICATION_FAILURE
+      FLATBUFFERS_ASSERT(ok);
+    #endif
+    #ifdef FLATBUFFERS_TRACK_VERIFIER_BUFFER_SIZE
+      if (!ok)
+        upper_bound_ = 0;
+    #endif
+    // clang-format on
+    return ok;
+  }
+
+  // Verify any range within the buffer.
+  bool Verify(size_t elem, size_t elem_len) const {
+    // clang-format off
+    #ifdef FLATBUFFERS_TRACK_VERIFIER_BUFFER_SIZE
+      auto upper_bound = elem + elem_len;
+      if (upper_bound_ < upper_bound)
+        upper_bound_ =  upper_bound;
+    #endif
+    // clang-format on
+    return Check(elem_len < size_ && elem <= size_ - elem_len);
+  }
+
+  template<typename T> bool VerifyAlignment(size_t elem) const {
+    return (elem & (sizeof(T) - 1)) == 0 || !check_alignment_;
+  }
+
+  // Verify a range indicated by sizeof(T).
+  template<typename T> bool Verify(size_t elem) const {
+    return VerifyAlignment<T>(elem) && Verify(elem, sizeof(T));
+  }
+
+  // Verify relative to a known-good base pointer.
+  bool Verify(const uint8_t *base, voffset_t elem_off, size_t elem_len) const {
+    return Verify(static_cast<size_t>(base - buf_) + elem_off, elem_len);
+  }
+
+  template<typename T> bool Verify(const uint8_t *base, voffset_t elem_off)
+      const {
+    return Verify(static_cast<size_t>(base - buf_) + elem_off, sizeof(T));
+  }
+
+  // Verify a pointer (may be NULL) of a table type.
+  template<typename T> bool VerifyTable(const T *table) {
+    return !table || table->Verify(*this);
+  }
+
+  // Verify a pointer (may be NULL) of any vector type.
+  template<typename T> bool VerifyVector(const Vector<T> *vec) const {
+    return !vec || VerifyVectorOrString(reinterpret_cast<const uint8_t *>(vec),
+                                        sizeof(T));
+  }
+
+  // Verify a pointer (may be NULL) of a vector to struct.
+  template<typename T> bool VerifyVector(const Vector<const T *> *vec) const {
+    return VerifyVector(reinterpret_cast<const Vector<T> *>(vec));
+  }
+
+  // Verify a pointer (may be NULL) to string.
+  bool VerifyString(const String *str) const {
+    size_t end;
+    return !str ||
+           (VerifyVectorOrString(reinterpret_cast<const uint8_t *>(str),
+                                 1, &end) &&
+            Verify(end, 1) &&      // Must have terminator
+            Check(buf_[end] == '\0'));  // Terminating byte must be 0.
+  }
+
+  // Common code between vectors and strings.
+  bool VerifyVectorOrString(const uint8_t *vec, size_t elem_size,
+                    size_t *end = nullptr) const {
+    auto veco = static_cast<size_t>(vec - buf_);
+    // Check we can read the size field.
+    if (!Verify<uoffset_t>(veco)) return false;
+    // Check the whole array. If this is a string, the byte past the array
+    // must be 0.
+    auto size = ReadScalar<uoffset_t>(vec);
+    auto max_elems = FLATBUFFERS_MAX_BUFFER_SIZE / elem_size;
+    if (!Check(size < max_elems))
+      return false;  // Protect against byte_size overflowing.
+    auto byte_size = sizeof(size) + elem_size * size;
+    if (end) *end = veco + byte_size;
+    return Verify(veco, byte_size);
+  }
+
+  // Special case for string contents, after the above has been called.
+  bool VerifyVectorOfStrings(const Vector<Offset<String>> *vec) const {
+    if (vec) {
+      for (uoffset_t i = 0; i < vec->size(); i++) {
+        if (!VerifyString(vec->Get(i))) return false;
+      }
+    }
+    return true;
+  }
+
+  // Special case for table contents, after the above has been called.
+  template<typename T> bool VerifyVectorOfTables(const Vector<Offset<T>> *vec) {
+    if (vec) {
+      for (uoffset_t i = 0; i < vec->size(); i++) {
+        if (!vec->Get(i)->Verify(*this)) return false;
+      }
+    }
+    return true;
+  }
+
+  bool VerifyTableStart(const uint8_t *table) {
+    // Check the vtable offset.
+    auto tableo = static_cast<size_t>(table - buf_);
+    if (!Verify<soffset_t>(tableo)) return false;
+    // This offset may be signed, but doing the substraction unsigned always
+    // gives the result we want.
+    auto vtableo = tableo - static_cast<size_t>(ReadScalar<soffset_t>(table));
+    // Check the vtable size field, then check vtable fits in its entirety.
+    return VerifyComplexity() && Verify<voffset_t>(vtableo) &&
+           VerifyAlignment<voffset_t>(ReadScalar<voffset_t>(buf_ + vtableo)) &&
+           Verify(vtableo, ReadScalar<voffset_t>(buf_ + vtableo));
+  }
+
+  template<typename T>
+  bool VerifyBufferFromStart(const char *identifier, size_t start) {
+    if (identifier &&
+        (size_ < 2 * sizeof(flatbuffers::uoffset_t) ||
+         !BufferHasIdentifier(buf_ + start, identifier))) {
+      return false;
+    }
+
+    // Call T::Verify, which must be in the generated code for this type.
+    auto o = VerifyOffset(start);
+    return o && reinterpret_cast<const T *>(buf_ + start + o)->Verify(*this)
+    // clang-format off
+    #ifdef FLATBUFFERS_TRACK_VERIFIER_BUFFER_SIZE
+           && GetComputedSize()
+    #endif
+        ;
+    // clang-format on
+  }
+
+  // Verify this whole buffer, starting with root type T.
+  template<typename T> bool VerifyBuffer() { return VerifyBuffer<T>(nullptr); }
+
+  template<typename T> bool VerifyBuffer(const char *identifier) {
+    return VerifyBufferFromStart<T>(identifier, 0);
+  }
+
+  template<typename T> bool VerifySizePrefixedBuffer(const char *identifier) {
+    return Verify<uoffset_t>(0U) &&
+           ReadScalar<uoffset_t>(buf_) == size_ - sizeof(uoffset_t) &&
+           VerifyBufferFromStart<T>(identifier, sizeof(uoffset_t));
+  }
+
+  uoffset_t VerifyOffset(size_t start) const {
+    if (!Verify<uoffset_t>(start)) return 0;
+    auto o = ReadScalar<uoffset_t>(buf_ + start);
+    // May not point to itself.
+    if (!Check(o != 0)) return 0;
+    // Can't wrap around / buffers are max 2GB.
+    if (!Check(static_cast<soffset_t>(o) >= 0)) return 0;
+    // Must be inside the buffer to create a pointer from it (pointer outside
+    // buffer is UB).
+    if (!Verify(start + o, 1)) return 0;
+    return o;
+  }
+
+  uoffset_t VerifyOffset(const uint8_t *base, voffset_t start) const {
+    return VerifyOffset(static_cast<size_t>(base - buf_) + start);
+  }
+
+  // Called at the start of a table to increase counters measuring data
+  // structure depth and amount, and possibly bails out with false if
+  // limits set by the constructor have been hit. Needs to be balanced
+  // with EndTable().
+  bool VerifyComplexity() {
+    depth_++;
+    num_tables_++;
+    return Check(depth_ <= max_depth_ && num_tables_ <= max_tables_);
+  }
+
+  // Called at the end of a table to pop the depth count.
+  bool EndTable() {
+    depth_--;
+    return true;
+  }
+
+  // Returns the message size in bytes
+  size_t GetComputedSize() const {
+    // clang-format off
+    #ifdef FLATBUFFERS_TRACK_VERIFIER_BUFFER_SIZE
+      uintptr_t size = upper_bound_;
+      // Align the size to uoffset_t
+      size = (size - 1 + sizeof(uoffset_t)) & ~(sizeof(uoffset_t) - 1);
+      return (size > size_) ?  0 : size;
+    #else
+      // Must turn on FLATBUFFERS_TRACK_VERIFIER_BUFFER_SIZE for this to work.
+      (void)upper_bound_;
+      FLATBUFFERS_ASSERT(false);
+      return 0;
+    #endif
+    // clang-format on
+  }
+
+ private:
+  const uint8_t *buf_;
+  size_t size_;
+  uoffset_t depth_;
+  uoffset_t max_depth_;
+  uoffset_t num_tables_;
+  uoffset_t max_tables_;
+  mutable size_t upper_bound_;
+  bool check_alignment_;
+};
+
+// Convenient way to bundle a buffer and its length, to pass it around
+// typed by its root.
+// A BufferRef does not own its buffer.
+struct BufferRefBase {};  // for std::is_base_of
+template<typename T> struct BufferRef : BufferRefBase {
+  BufferRef() : buf(nullptr), len(0), must_free(false) {}
+  BufferRef(uint8_t *_buf, uoffset_t _len)
+      : buf(_buf), len(_len), must_free(false) {}
+
+  ~BufferRef() {
+    if (must_free) free(buf);
+  }
+
+  const T *GetRoot() const { return flatbuffers::GetRoot<T>(buf); }
+
+  bool Verify() {
+    Verifier verifier(buf, len);
+    return verifier.VerifyBuffer<T>(nullptr);
+  }
+
+  uint8_t *buf;
+  uoffset_t len;
+  bool must_free;
+};
+
+// "structs" are flat structures that do not have an offset table, thus
+// always have all members present and do not support forwards/backwards
+// compatible extensions.
+
+class Struct FLATBUFFERS_FINAL_CLASS {
+ public:
+  template<typename T> T GetField(uoffset_t o) const {
+    return ReadScalar<T>(&data_[o]);
+  }
+
+  template<typename T> T GetStruct(uoffset_t o) const {
+    return reinterpret_cast<T>(&data_[o]);
+  }
+
+  const uint8_t *GetAddressOf(uoffset_t o) const { return &data_[o]; }
+  uint8_t *GetAddressOf(uoffset_t o) { return &data_[o]; }
+
+ private:
+  uint8_t data_[1];
+};
+
+// "tables" use an offset table (possibly shared) that allows fields to be
+// omitted and added at will, but uses an extra indirection to read.
+class Table {
+ public:
+  const uint8_t *GetVTable() const {
+    return data_ - ReadScalar<soffset_t>(data_);
+  }
+
+  // This gets the field offset for any of the functions below it, or 0
+  // if the field was not present.
+  voffset_t GetOptionalFieldOffset(voffset_t field) const {
+    // The vtable offset is always at the start.
+    auto vtable = GetVTable();
+    // The first element is the size of the vtable (fields + type id + itself).
+    auto vtsize = ReadScalar<voffset_t>(vtable);
+    // If the field we're accessing is outside the vtable, we're reading older
+    // data, so it's the same as if the offset was 0 (not present).
+    return field < vtsize ? ReadScalar<voffset_t>(vtable + field) : 0;
+  }
+
+  template<typename T> T GetField(voffset_t field, T defaultval) const {
+    auto field_offset = GetOptionalFieldOffset(field);
+    return field_offset ? ReadScalar<T>(data_ + field_offset) : defaultval;
+  }
+
+  template<typename P> P GetPointer(voffset_t field) {
+    auto field_offset = GetOptionalFieldOffset(field);
+    auto p = data_ + field_offset;
+    return field_offset ? reinterpret_cast<P>(p + ReadScalar<uoffset_t>(p))
+                        : nullptr;
+  }
+  template<typename P> P GetPointer(voffset_t field) const {
+    return const_cast<Table *>(this)->GetPointer<P>(field);
+  }
+
+  template<typename P> P GetStruct(voffset_t field) const {
+    auto field_offset = GetOptionalFieldOffset(field);
+    auto p = const_cast<uint8_t *>(data_ + field_offset);
+    return field_offset ? reinterpret_cast<P>(p) : nullptr;
+  }
+
+  template<typename T> bool SetField(voffset_t field, T val, T def) {
+    auto field_offset = GetOptionalFieldOffset(field);
+    if (!field_offset) return IsTheSameAs(val, def);
+    WriteScalar(data_ + field_offset, val);
+    return true;
+  }
+
+  bool SetPointer(voffset_t field, const uint8_t *val) {
+    auto field_offset = GetOptionalFieldOffset(field);
+    if (!field_offset) return false;
+    WriteScalar(data_ + field_offset,
+                static_cast<uoffset_t>(val - (data_ + field_offset)));
+    return true;
+  }
+
+  uint8_t *GetAddressOf(voffset_t field) {
+    auto field_offset = GetOptionalFieldOffset(field);
+    return field_offset ? data_ + field_offset : nullptr;
+  }
+  const uint8_t *GetAddressOf(voffset_t field) const {
+    return const_cast<Table *>(this)->GetAddressOf(field);
+  }
+
+  bool CheckField(voffset_t field) const {
+    return GetOptionalFieldOffset(field) != 0;
+  }
+
+  // Verify the vtable of this table.
+  // Call this once per table, followed by VerifyField once per field.
+  bool VerifyTableStart(Verifier &verifier) const {
+    return verifier.VerifyTableStart(data_);
+  }
+
+  // Verify a particular field.
+  template<typename T>
+  bool VerifyField(const Verifier &verifier, voffset_t field) const {
+    // Calling GetOptionalFieldOffset should be safe now thanks to
+    // VerifyTable().
+    auto field_offset = GetOptionalFieldOffset(field);
+    // Check the actual field.
+    return !field_offset || verifier.Verify<T>(data_, field_offset);
+  }
+
+  // VerifyField for required fields.
+  template<typename T>
+  bool VerifyFieldRequired(const Verifier &verifier, voffset_t field) const {
+    auto field_offset = GetOptionalFieldOffset(field);
+    return verifier.Check(field_offset != 0) &&
+           verifier.Verify<T>(data_, field_offset);
+  }
+
+  // Versions for offsets.
+  bool VerifyOffset(const Verifier &verifier, voffset_t field) const {
+    auto field_offset = GetOptionalFieldOffset(field);
+    return !field_offset || verifier.VerifyOffset(data_, field_offset);
+  }
+
+  bool VerifyOffsetRequired(const Verifier &verifier, voffset_t field) const {
+    auto field_offset = GetOptionalFieldOffset(field);
+    return verifier.Check(field_offset != 0) &&
+           verifier.VerifyOffset(data_, field_offset);
+  }
+
+ private:
+  // private constructor & copy constructor: you obtain instances of this
+  // class by pointing to existing data only
+  Table();
+  Table(const Table &other);
+
+  uint8_t data_[1];
+};
+
+template<typename T> void FlatBufferBuilder::Required(Offset<T> table,
+                                                      voffset_t field) {
+  auto table_ptr = reinterpret_cast<const Table *>(buf_.data_at(table.o));
+  bool ok = table_ptr->GetOptionalFieldOffset(field) != 0;
+  // If this fails, the caller will show what field needs to be set.
+  FLATBUFFERS_ASSERT(ok);
+  (void)ok;
+}
+
+/// @brief This can compute the start of a FlatBuffer from a root pointer, i.e.
+/// it is the opposite transformation of GetRoot().
+/// This may be useful if you want to pass on a root and have the recipient
+/// delete the buffer afterwards.
+inline const uint8_t *GetBufferStartFromRootPointer(const void *root) {
+  auto table = reinterpret_cast<const Table *>(root);
+  auto vtable = table->GetVTable();
+  // Either the vtable is before the root or after the root.
+  auto start = (std::min)(vtable, reinterpret_cast<const uint8_t *>(root));
+  // Align to at least sizeof(uoffset_t).
+  start = reinterpret_cast<const uint8_t *>(reinterpret_cast<uintptr_t>(start) &
+                                            ~(sizeof(uoffset_t) - 1));
+  // Additionally, there may be a file_identifier in the buffer, and the root
+  // offset. The buffer may have been aligned to any size between
+  // sizeof(uoffset_t) and FLATBUFFERS_MAX_ALIGNMENT (see "force_align").
+  // Sadly, the exact alignment is only known when constructing the buffer,
+  // since it depends on the presence of values with said alignment properties.
+  // So instead, we simply look at the next uoffset_t values (root,
+  // file_identifier, and alignment padding) to see which points to the root.
+  // None of the other values can "impersonate" the root since they will either
+  // be 0 or four ASCII characters.
+  static_assert(FlatBufferBuilder::kFileIdentifierLength == sizeof(uoffset_t),
+                "file_identifier is assumed to be the same size as uoffset_t");
+  for (auto possible_roots = FLATBUFFERS_MAX_ALIGNMENT / sizeof(uoffset_t) + 1;
+       possible_roots; possible_roots--) {
+    start -= sizeof(uoffset_t);
+    if (ReadScalar<uoffset_t>(start) + start ==
+        reinterpret_cast<const uint8_t *>(root))
+      return start;
+  }
+  // We didn't find the root, either the "root" passed isn't really a root,
+  // or the buffer is corrupt.
+  // Assert, because calling this function with bad data may cause reads
+  // outside of buffer boundaries.
+  FLATBUFFERS_ASSERT(false);
+  return nullptr;
+}
+
+/// @brief This return the prefixed size of a FlatBuffer.
+inline uoffset_t GetPrefixedSize(const uint8_t* buf){ return ReadScalar<uoffset_t>(buf); }
+
+// Base class for native objects (FlatBuffer data de-serialized into native
+// C++ data structures).
+// Contains no functionality, purely documentative.
+struct NativeTable {};
+
+/// @brief Function types to be used with resolving hashes into objects and
+/// back again. The resolver gets a pointer to a field inside an object API
+/// object that is of the type specified in the schema using the attribute
+/// `cpp_type` (it is thus important whatever you write to this address
+/// matches that type). The value of this field is initially null, so you
+/// may choose to implement a delayed binding lookup using this function
+/// if you wish. The resolver does the opposite lookup, for when the object
+/// is being serialized again.
+typedef uint64_t hash_value_t;
+// clang-format off
+#ifdef FLATBUFFERS_CPP98_STL
+  typedef void (*resolver_function_t)(void **pointer_adr, hash_value_t hash);
+  typedef hash_value_t (*rehasher_function_t)(void *pointer);
+#else
+  typedef std::function<void (void **pointer_adr, hash_value_t hash)>
+          resolver_function_t;
+  typedef std::function<hash_value_t (void *pointer)> rehasher_function_t;
+#endif
+// clang-format on
+
+// Helper function to test if a field is present, using any of the field
+// enums in the generated code.
+// `table` must be a generated table type. Since this is a template parameter,
+// this is not typechecked to be a subclass of Table, so beware!
+// Note: this function will return false for fields equal to the default
+// value, since they're not stored in the buffer (unless force_defaults was
+// used).
+template<typename T>
+bool IsFieldPresent(const T *table, typename T::FlatBuffersVTableOffset field) {
+  // Cast, since Table is a private baseclass of any table types.
+  return reinterpret_cast<const Table *>(table)->CheckField(
+      static_cast<voffset_t>(field));
+}
+
+// Utility function for reverse lookups on the EnumNames*() functions
+// (in the generated C++ code)
+// names must be NULL terminated.
+inline int LookupEnum(const char **names, const char *name) {
+  for (const char **p = names; *p; p++)
+    if (!strcmp(*p, name)) return static_cast<int>(p - names);
+  return -1;
+}
+
+// These macros allow us to layout a struct with a guarantee that they'll end
+// up looking the same on different compilers and platforms.
+// It does this by disallowing the compiler to do any padding, and then
+// does padding itself by inserting extra padding fields that make every
+// element aligned to its own size.
+// Additionally, it manually sets the alignment of the struct as a whole,
+// which is typically its largest element, or a custom size set in the schema
+// by the force_align attribute.
+// These are used in the generated code only.
+
+// clang-format off
+#if defined(_MSC_VER)
+  #define FLATBUFFERS_MANUALLY_ALIGNED_STRUCT(alignment) \
+    __pragma(pack(1)) \
+    struct __declspec(align(alignment))
+  #define FLATBUFFERS_STRUCT_END(name, size) \
+    __pragma(pack()) \
+    static_assert(sizeof(name) == size, "compiler breaks packing rules")
+#elif defined(__GNUC__) || defined(__clang__)
+  #define FLATBUFFERS_MANUALLY_ALIGNED_STRUCT(alignment) \
+    _Pragma("pack(1)") \
+    struct __attribute__((aligned(alignment)))
+  #define FLATBUFFERS_STRUCT_END(name, size) \
+    _Pragma("pack()") \
+    static_assert(sizeof(name) == size, "compiler breaks packing rules")
+#else
+  #error Unknown compiler, please define structure alignment macros
+#endif
+// clang-format on
+
+// Minimal reflection via code generation.
+// Besides full-fat reflection (see reflection.h) and parsing/printing by
+// loading schemas (see idl.h), we can also have code generation for mimimal
+// reflection data which allows pretty-printing and other uses without needing
+// a schema or a parser.
+// Generate code with --reflect-types (types only) or --reflect-names (names
+// also) to enable.
+// See minireflect.h for utilities using this functionality.
+
+// These types are organized slightly differently as the ones in idl.h.
+enum SequenceType { ST_TABLE, ST_STRUCT, ST_UNION, ST_ENUM };
+
+// Scalars have the same order as in idl.h
+// clang-format off
+#define FLATBUFFERS_GEN_ELEMENTARY_TYPES(ET) \
+  ET(ET_UTYPE) \
+  ET(ET_BOOL) \
+  ET(ET_CHAR) \
+  ET(ET_UCHAR) \
+  ET(ET_SHORT) \
+  ET(ET_USHORT) \
+  ET(ET_INT) \
+  ET(ET_UINT) \
+  ET(ET_LONG) \
+  ET(ET_ULONG) \
+  ET(ET_FLOAT) \
+  ET(ET_DOUBLE) \
+  ET(ET_STRING) \
+  ET(ET_SEQUENCE)  // See SequenceType.
+
+enum ElementaryType {
+  #define FLATBUFFERS_ET(E) E,
+    FLATBUFFERS_GEN_ELEMENTARY_TYPES(FLATBUFFERS_ET)
+  #undef FLATBUFFERS_ET
+};
+
+inline const char * const *ElementaryTypeNames() {
+  static const char * const names[] = {
+    #define FLATBUFFERS_ET(E) #E,
+      FLATBUFFERS_GEN_ELEMENTARY_TYPES(FLATBUFFERS_ET)
+    #undef FLATBUFFERS_ET
+  };
+  return names;
+}
+// clang-format on
+
+// Basic type info cost just 16bits per field!
+struct TypeCode {
+  uint16_t base_type : 4;  // ElementaryType
+  uint16_t is_vector : 1;
+  int16_t sequence_ref : 11;  // Index into type_refs below, or -1 for none.
+};
+
+static_assert(sizeof(TypeCode) == 2, "TypeCode");
+
+struct TypeTable;
+
+// Signature of the static method present in each type.
+typedef const TypeTable *(*TypeFunction)();
+
+struct TypeTable {
+  SequenceType st;
+  size_t num_elems;  // of type_codes, values, names (but not type_refs).
+  const TypeCode *type_codes;  // num_elems count
+  const TypeFunction *type_refs;  // less than num_elems entries (see TypeCode).
+  const int64_t *values;  // Only set for non-consecutive enum/union or structs.
+  const char * const *names;     // Only set if compiled with --reflect-names.
+};
+
+// String which identifies the current version of FlatBuffers.
+// flatbuffer_version_string is used by Google developers to identify which
+// applications uploaded to Google Play are using this library.  This allows
+// the development team at Google to determine the popularity of the library.
+// How it works: Applications that are uploaded to the Google Play Store are
+// scanned for this version string.  We track which applications are using it
+// to measure popularity.  You are free to remove it (of course) but we would
+// appreciate if you left it in.
+
+// Weak linkage is culled by VS & doesn't work on cygwin.
+// clang-format off
+#if !defined(_WIN32) && !defined(__CYGWIN__)
+
+extern volatile __attribute__((weak)) const char *flatbuffer_version_string;
+volatile __attribute__((weak)) const char *flatbuffer_version_string =
+  "FlatBuffers "
+  FLATBUFFERS_STRING(FLATBUFFERS_VERSION_MAJOR) "."
+  FLATBUFFERS_STRING(FLATBUFFERS_VERSION_MINOR) "."
+  FLATBUFFERS_STRING(FLATBUFFERS_VERSION_REVISION);
+
+#endif  // !defined(_WIN32) && !defined(__CYGWIN__)
+
+#define FLATBUFFERS_DEFINE_BITMASK_OPERATORS(E, T)\
+    inline E operator | (E lhs, E rhs){\
+        return E(T(lhs) | T(rhs));\
+    }\
+    inline E operator & (E lhs, E rhs){\
+        return E(T(lhs) & T(rhs));\
+    }\
+    inline E operator ^ (E lhs, E rhs){\
+        return E(T(lhs) ^ T(rhs));\
+    }\
+    inline E operator ~ (E lhs){\
+        return E(~T(lhs));\
+    }\
+    inline E operator |= (E &lhs, E rhs){\
+        lhs = lhs | rhs;\
+        return lhs;\
+    }\
+    inline E operator &= (E &lhs, E rhs){\
+        lhs = lhs & rhs;\
+        return lhs;\
+    }\
+    inline E operator ^= (E &lhs, E rhs){\
+        lhs = lhs ^ rhs;\
+        return lhs;\
+    }\
+    inline bool operator !(E rhs) \
+    {\
+        return !bool(T(rhs)); \
+    }
+/// @endcond
+}  // namespace flatbuffers
+
+// clang-format on
+
+#endif  // FLATBUFFERS_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/flatbuffers/include/flatbuffers/stl_emulation.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/flatbuffers/include/flatbuffers/stl_emulation.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,275 @@
+/*
+ * Copyright 2017 Google Inc. All rights reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef FLATBUFFERS_STL_EMULATION_H_
+#define FLATBUFFERS_STL_EMULATION_H_
+
+// clang-format off
+
+#include <string>
+#include <type_traits>
+#include <vector>
+#include <memory>
+#include <limits>
+
+#if defined(_STLPORT_VERSION) && !defined(FLATBUFFERS_CPP98_STL)
+  #define FLATBUFFERS_CPP98_STL
+#endif  // defined(_STLPORT_VERSION) && !defined(FLATBUFFERS_CPP98_STL)
+
+#if defined(FLATBUFFERS_CPP98_STL)
+  #include <cctype>
+#endif  // defined(FLATBUFFERS_CPP98_STL)
+
+// Check if we can use template aliases
+// Not possible if Microsoft Compiler before 2012
+// Possible is the language feature __cpp_alias_templates is defined well
+// Or possible if the C++ std is C+11 or newer
+#if (defined(_MSC_VER) && _MSC_VER > 1700 /* MSVC2012 */) \
+    || (defined(__cpp_alias_templates) && __cpp_alias_templates >= 200704) \
+    || (defined(__cplusplus) && __cplusplus >= 201103L)
+  #define FLATBUFFERS_TEMPLATES_ALIASES
+#endif
+
+// This header provides backwards compatibility for C++98 STLs like stlport.
+namespace flatbuffers {
+
+// Retrieve ::back() from a string in a way that is compatible with pre C++11
+// STLs (e.g stlport).
+inline char& string_back(std::string &value) {
+  return value[value.length() - 1];
+}
+
+inline char string_back(const std::string &value) {
+  return value[value.length() - 1];
+}
+
+// Helper method that retrieves ::data() from a vector in a way that is
+// compatible with pre C++11 STLs (e.g stlport).
+template <typename T> inline T *vector_data(std::vector<T> &vector) {
+  // In some debug environments, operator[] does bounds checking, so &vector[0]
+  // can't be used.
+  return vector.empty() ? nullptr : &vector[0];
+}
+
+template <typename T> inline const T *vector_data(
+    const std::vector<T> &vector) {
+  return vector.empty() ? nullptr : &vector[0];
+}
+
+template <typename T, typename V>
+inline void vector_emplace_back(std::vector<T> *vector, V &&data) {
+  #if defined(FLATBUFFERS_CPP98_STL)
+    vector->push_back(data);
+  #else
+    vector->emplace_back(std::forward<V>(data));
+  #endif  // defined(FLATBUFFERS_CPP98_STL)
+}
+
+#ifndef FLATBUFFERS_CPP98_STL
+  #if defined(FLATBUFFERS_TEMPLATES_ALIASES)
+    template <typename T>
+    using numeric_limits = std::numeric_limits<T>;
+  #else
+    template <typename T> class numeric_limits :
+      public std::numeric_limits<T> {};
+  #endif  // defined(FLATBUFFERS_TEMPLATES_ALIASES)
+#else
+  template <typename T> class numeric_limits :
+      public std::numeric_limits<T> {
+    public:
+      // Android NDK fix.
+      static T lowest() {
+        return std::numeric_limits<T>::min();
+      }
+  };
+
+  template <> class numeric_limits<float> : 
+      public std::numeric_limits<float> {
+    public:
+      static float lowest() { return -FLT_MAX; }
+  };
+
+  template <> class numeric_limits<double> : 
+      public std::numeric_limits<double> {
+    public:
+      static double lowest() { return -DBL_MAX; }
+  };
+
+  template <> class numeric_limits<unsigned long long> {
+   public:
+    static unsigned long long min() { return 0ULL; }
+    static unsigned long long max() { return ~0ULL; }
+    static unsigned long long lowest() {
+      return numeric_limits<unsigned long long>::min();
+    }
+  };
+
+  template <> class numeric_limits<long long> {
+   public:
+    static long long min() {
+      return static_cast<long long>(1ULL << ((sizeof(long long) << 3) - 1));
+    }
+    static long long max() {
+      return static_cast<long long>(
+          (1ULL << ((sizeof(long long) << 3) - 1)) - 1);
+    }
+    static long long lowest() {
+      return numeric_limits<long long>::min();
+    }
+  };
+#endif  // FLATBUFFERS_CPP98_STL
+
+#if defined(FLATBUFFERS_TEMPLATES_ALIASES)
+  #ifndef FLATBUFFERS_CPP98_STL
+    template <typename T> using is_scalar = std::is_scalar<T>;
+    template <typename T, typename U> using is_same = std::is_same<T,U>;
+    template <typename T> using is_floating_point = std::is_floating_point<T>;
+    template <typename T> using is_unsigned = std::is_unsigned<T>;
+    template <typename T> using make_unsigned = std::make_unsigned<T>;
+  #else
+    // Map C++ TR1 templates defined by stlport.
+    template <typename T> using is_scalar = std::tr1::is_scalar<T>;
+    template <typename T, typename U> using is_same = std::tr1::is_same<T,U>;
+    template <typename T> using is_floating_point =
+        std::tr1::is_floating_point<T>;
+    template <typename T> using is_unsigned = std::tr1::is_unsigned<T>;
+    // Android NDK doesn't have std::make_unsigned or std::tr1::make_unsigned.
+    template<typename T> struct make_unsigned {
+      static_assert(is_unsigned<T>::value, "Specialization not implemented!");
+      using type = T;
+    };
+    template<> struct make_unsigned<char> { using type = unsigned char; };
+    template<> struct make_unsigned<short> { using type = unsigned short; };
+    template<> struct make_unsigned<int> { using type = unsigned int; };
+    template<> struct make_unsigned<long> { using type = unsigned long; };
+    template<>
+    struct make_unsigned<long long> { using type = unsigned long long; };
+  #endif  // !FLATBUFFERS_CPP98_STL
+#else
+  // MSVC 2010 doesn't support C++11 aliases.
+  template <typename T> struct is_scalar : public std::is_scalar<T> {};
+  template <typename T, typename U> struct is_same : public std::is_same<T,U> {};
+  template <typename T> struct is_floating_point :
+        public std::is_floating_point<T> {};
+  template <typename T> struct is_unsigned : public std::is_unsigned<T> {};
+  template <typename T> struct make_unsigned : public std::make_unsigned<T> {};
+#endif  // defined(FLATBUFFERS_TEMPLATES_ALIASES)
+
+#ifndef FLATBUFFERS_CPP98_STL
+  #if defined(FLATBUFFERS_TEMPLATES_ALIASES)
+    template <class T> using unique_ptr = std::unique_ptr<T>;
+  #else
+    // MSVC 2010 doesn't support C++11 aliases.
+    // We're manually "aliasing" the class here as we want to bring unique_ptr
+    // into the flatbuffers namespace.  We have unique_ptr in the flatbuffers
+    // namespace we have a completely independent implemenation (see below)
+    // for C++98 STL implementations.
+    template <class T> class unique_ptr : public std::unique_ptr<T> {
+     public:
+      unique_ptr() {}
+      explicit unique_ptr(T* p) : std::unique_ptr<T>(p) {}
+      unique_ptr(std::unique_ptr<T>&& u) { *this = std::move(u); }
+      unique_ptr(unique_ptr&& u) { *this = std::move(u); }
+      unique_ptr& operator=(std::unique_ptr<T>&& u) {
+        std::unique_ptr<T>::reset(u.release());
+        return *this;
+      }
+      unique_ptr& operator=(unique_ptr&& u) {
+        std::unique_ptr<T>::reset(u.release());
+        return *this;
+      }
+      unique_ptr& operator=(T* p) {
+        return std::unique_ptr<T>::operator=(p);
+      }
+    };
+  #endif  // defined(FLATBUFFERS_TEMPLATES_ALIASES)
+#else
+  // Very limited implementation of unique_ptr.
+  // This is provided simply to allow the C++ code generated from the default
+  // settings to function in C++98 environments with no modifications.
+  template <class T> class unique_ptr {
+   public:
+    typedef T element_type;
+
+    unique_ptr() : ptr_(nullptr) {}
+    explicit unique_ptr(T* p) : ptr_(p) {}
+    unique_ptr(unique_ptr&& u) : ptr_(nullptr) { reset(u.release()); }
+    unique_ptr(const unique_ptr& u) : ptr_(nullptr) {
+      reset(const_cast<unique_ptr*>(&u)->release());
+    }
+    ~unique_ptr() { reset(); }
+
+    unique_ptr& operator=(const unique_ptr& u) {
+      reset(const_cast<unique_ptr*>(&u)->release());
+      return *this;
+    }
+
+    unique_ptr& operator=(unique_ptr&& u) {
+      reset(u.release());
+      return *this;
+    }
+
+    unique_ptr& operator=(T* p) {
+      reset(p);
+      return *this;
+    }
+
+    const T& operator*() const { return *ptr_; }
+    T* operator->() const { return ptr_; }
+    T* get() const noexcept { return ptr_; }
+    explicit operator bool() const { return ptr_ != nullptr; }
+
+    // modifiers
+    T* release() {
+      T* value = ptr_;
+      ptr_ = nullptr;
+      return value;
+    }
+
+    void reset(T* p = nullptr) {
+      T* value = ptr_;
+      ptr_ = p;
+      if (value) delete value;
+    }
+
+    void swap(unique_ptr& u) {
+      T* temp_ptr = ptr_;
+      ptr_ = u.ptr_;
+      u.ptr_ = temp_ptr;
+    }
+
+   private:
+    T* ptr_;
+  };
+
+  template <class T> bool operator==(const unique_ptr<T>& x,
+                                     const unique_ptr<T>& y) {
+    return x.get() == y.get();
+  }
+
+  template <class T, class D> bool operator==(const unique_ptr<T>& x,
+                                              const D* y) {
+    return static_cast<D*>(x.get()) == y;
+  }
+
+  template <class T> bool operator==(const unique_ptr<T>& x, intptr_t y) {
+    return reinterpret_cast<intptr_t>(x.get()) == y;
+  }
+#endif  // !FLATBUFFERS_CPP98_STL
+
+}  // namespace flatbuffers
+
+#endif  // FLATBUFFERS_STL_EMULATION_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/gemmlowp/fixedpoint/fixedpoint.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/gemmlowp/fixedpoint/fixedpoint.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,900 @@
+// Copyright 2015 The Gemmlowp Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+// fixedpoint.h: fixed-point arithmetic, with basic operations and
+// a few math functions such as tanh.
+
+#ifndef GEMMLOWP_INTERNAL_FIXEDPOINT_H_
+#define GEMMLOWP_INTERNAL_FIXEDPOINT_H_
+
+#include <algorithm>
+#include <cassert>
+#include <cmath>
+#include <cstdint>
+#include <limits>
+
+#include "../internal/detect_platform.h"
+
+namespace gemmlowp {
+
+// Part 1: Low-level integer-arithmetic primitives.
+// The implementations here are generic implementations valid for
+// scalar types (e.g. std::int32_t). Architecture-specific SIMD types
+// (e.g. NEON int32x4_t) may be supported by providing
+// specializations for them in separate files.
+//
+// The purpose of these primitives is two-fold:
+//  - They will be used to implement higher-level fixed-point
+//    abstractions, namely the FixedPoint class and its arithmetic
+//    operators.
+//  - They will be directly used to implement some more involved
+//    fixed-point computations, e.g. the fixed-point implementation
+//    of math functions such as tanh.
+
+// Some compile-time traits around raw types to handle SIMD aspects:
+// number of lanes, underlying scalar type.
+template <typename tIntegerType>
+struct FixedPointRawTypeTraits {};
+
+template <>
+struct FixedPointRawTypeTraits<std::int32_t> {
+  typedef std::int32_t ScalarRawType;
+  static constexpr int kLanes = 1;
+};
+
+template <>
+struct FixedPointRawTypeTraits<std::int16_t> {
+  typedef std::int16_t ScalarRawType;
+  static constexpr int kLanes = 1;
+};
+
+// Returns a SIMD value duplicating a scalar value across all lanes.
+template <typename tRawType>
+tRawType Dup(typename FixedPointRawTypeTraits<tRawType>::ScalarRawType x) {
+  return x;
+}
+
+// Plain bit-wise AND
+template <typename tIntegerType>
+tIntegerType BitAnd(tIntegerType a, tIntegerType b) {
+  return a & b;
+}
+
+// Plain bit-wise OR
+template <typename tIntegerType>
+tIntegerType BitOr(tIntegerType a, tIntegerType b) {
+  return a | b;
+}
+
+// Plain bit-wise XOR
+template <typename tIntegerType>
+tIntegerType BitXor(tIntegerType a, tIntegerType b) {
+  return a ^ b;
+}
+
+// Plain bit-wise NOT
+template <typename tIntegerType>
+tIntegerType BitNot(tIntegerType a) {
+  return ~a;
+}
+
+// Integer addition. Not saturating. Overflow is undefined behavior.
+template <typename tIntegerType>
+tIntegerType Add(tIntegerType a, tIntegerType b) {
+  return a + b;
+}
+
+// Integer subtraction. Not saturating. Overflow is undefined behavior.
+template <typename tIntegerType>
+tIntegerType Mul(tIntegerType a, tIntegerType b) {
+  return a * b;
+}
+
+template <typename tIntegerType>
+tIntegerType Sub(tIntegerType a, tIntegerType b) {
+  return a - b;
+}
+
+// Integer unary negative. Not saturating. Overflow is undefined behavior.
+template <typename tIntegerType>
+tIntegerType Neg(tIntegerType a) {
+  return -a;
+}
+
+// Integer arithmetic left-shift, equivalent to multiplying with a power of two.
+// Negative values are OK. In case of overflow, no Undefined
+// Behavior, but the results are implementation-defined (in practice,
+// they currently are saturated, but we make no commitment to that). The idea
+// is that the caller will want to implement the overflowing cases with
+// saturation with compare-and-mask, so we don't care about the results
+// in the overflow case, we just want to avoid undefined behavior.
+//
+// tIntegerType may be int32 or any narrower signed type.
+template <typename tIntegerType>
+tIntegerType ShiftLeft(tIntegerType a, int offset) {
+  const std::int64_t wide_a = static_cast<std::int64_t>(a);
+  const std::int64_t wide_shifted = wide_a * (1 << offset);
+  const auto min = std::numeric_limits<tIntegerType>::min();
+  const auto max = std::numeric_limits<tIntegerType>::max();
+  return wide_shifted < min
+             ? min
+             : wide_shifted > max ? max
+                                  : static_cast<tIntegerType>(wide_shifted);
+}
+
+// Integer arithmetic right-shift. Not rounding.
+// Relying on implementation-defined, but in-practice-consistent,
+// C++ compiler behavior.
+template <typename tIntegerType>
+tIntegerType ShiftRight(tIntegerType a, int offset) {
+  return a >> offset;
+}
+
+// Each bit of the result is set to the corresponding bit of either then_val or
+// else_val depending on whether the corresponding bit of if_mask is set.
+// Equivalent to the VBSL instruction in ARM NEON.
+template <typename tIntegerType>
+tIntegerType SelectUsingMask(tIntegerType if_mask, tIntegerType then_val,
+                             tIntegerType else_val) {
+  return BitXor(BitAnd(if_mask, then_val), BitAnd(BitNot(if_mask), else_val));
+}
+
+// For each input scalar, the corresponding bits of the result are set if the
+// input scalar is non-zero.
+template <typename tIntegerType>
+tIntegerType MaskIfNonZero(tIntegerType a) {
+  static constexpr tIntegerType zero = 0;
+  return a ? BitNot(zero) : zero;
+}
+
+// For each input scalar, the corresponding bits of the result are set if the
+// input scalar is zero.
+template <typename tIntegerType>
+tIntegerType MaskIfZero(tIntegerType a) {
+  return MaskIfNonZero<tIntegerType>(!a);
+}
+
+// For each pair of input scalars, the corresponding bits of the result are
+// set if the input scalars are equal.
+template <typename tIntegerType>
+tIntegerType MaskIfEqual(tIntegerType a, tIntegerType b) {
+  return MaskIfNonZero<tIntegerType>(a == b);
+}
+
+// For each pair of input scalars, the corresponding bits of the result are
+// set if the input scalars are not equal.
+template <typename tIntegerType>
+tIntegerType MaskIfNotEqual(tIntegerType a, tIntegerType b) {
+  return MaskIfNonZero<tIntegerType>(a != b);
+}
+
+// For each pair of input scalars, the corresponding bits of the result are
+// set if the input scalars a, b satisfy a > b.
+template <typename tIntegerType>
+tIntegerType MaskIfGreaterThan(tIntegerType a, tIntegerType b) {
+  return MaskIfNonZero<tIntegerType>(a > b);
+}
+
+// For each pair of input scalars, the corresponding bits of the result are
+// set if the input scalars a, b satisfy a >= b.
+template <typename tIntegerType>
+tIntegerType MaskIfGreaterThanOrEqual(tIntegerType a, tIntegerType b) {
+  return MaskIfNonZero<tIntegerType>(a >= b);
+}
+
+// For each pair of input scalars, the corresponding bits of the result are
+// set if the input scalars a, b satisfy a < b.
+template <typename tIntegerType>
+tIntegerType MaskIfLessThan(tIntegerType a, tIntegerType b) {
+  return MaskIfNonZero<tIntegerType>(a < b);
+}
+
+// For each pair of input scalars, the corresponding bits of the result are
+// set if the input scalars a, b satisfy a <= b.
+template <typename tIntegerType>
+tIntegerType MaskIfLessThanOrEqual(tIntegerType a, tIntegerType b) {
+  return MaskIfNonZero<tIntegerType>(a <= b);
+}
+
+// Returns true if all of the input scalars are nonzero.
+// This function may currently assume that each of the input scalars has either
+// all or none of its bits set. Otherwise, its behavior is currently undefined.
+template <typename tIntegerType>
+bool All(tIntegerType a) {
+  return a;
+}
+
+// Returns true if any of the input scalars are nonzero.
+// This function may currently assume that each of the input scalars has either
+// all or none of its bits set. Otherwise, its behavior is currently undefined.
+template <typename tIntegerType>
+bool Any(tIntegerType a) {
+  return a;
+}
+
+// Returns (a+b)/2, rounded to the nearest integer.
+// Equivalent to VRHADD in the ARM NEON instruction set.
+template <typename IntegerType>
+IntegerType RoundingHalfSum(IntegerType a, IntegerType b) {
+  static_assert(std::is_same<IntegerType, void>::value, "unimplemented");
+  (void)b;
+  return a;
+}
+
+template <>
+inline std::int32_t RoundingHalfSum(std::int32_t a, std::int32_t b) {
+  std::int64_t a64 = a;
+  std::int64_t b64 = b;
+  std::int64_t sum = a64 + b64;
+  std::int64_t sign = sum >= 0 ? 1 : -1;
+  return static_cast<std::int32_t>((sum + sign) / 2);
+}
+
+template <>
+inline std::int16_t RoundingHalfSum(std::int16_t a, std::int16_t b) {
+  std::int32_t a32 = a;
+  std::int32_t b32 = b;
+  std::int32_t sum = a32 + b32;
+  std::int32_t sign = sum >= 0 ? 1 : -1;
+  return static_cast<std::int16_t>((sum + sign) / 2);
+}
+
+template <typename IntegerType>
+IntegerType SaturatingAdd(IntegerType a, IntegerType b) {
+  static_assert(std::is_same<IntegerType, void>::value, "unimplemented");
+  (void)b;
+  return a;
+}
+
+// So far this is only needed for int16.
+template <>
+inline std::int16_t SaturatingAdd(std::int16_t a, std::int16_t b) {
+  std::int32_t a32 = a;
+  std::int32_t b32 = b;
+  std::int32_t sum = a32 + b32;
+  return static_cast<std::int16_t>(
+      std::min(static_cast<std::int32_t>(32767),
+               std::max(static_cast<std::int32_t>(-32768), sum)));
+}
+
+// Returns a+b, saturating if the integers are 16bit or narrower,
+// otherwise just a plain addition.
+template <typename IntegerType, bool Is16Bit>
+struct AddSaturatingIf16BitImpl {
+  static IntegerType Run(IntegerType a, IntegerType b) { return Add(a, b); }
+};
+template <typename IntegerType>
+struct AddSaturatingIf16BitImpl<IntegerType, true> {
+  static IntegerType Run(IntegerType a, IntegerType b) {
+    return SaturatingAdd(a, b);
+  }
+};
+template <typename IntegerType>
+IntegerType AddSaturatingIf16Bit(IntegerType a, IntegerType b) {
+  using ScalarType =
+      typename FixedPointRawTypeTraits<IntegerType>::ScalarRawType;
+  return AddSaturatingIf16BitImpl<IntegerType, sizeof(ScalarType) == 2>::Run(a,
+                                                                             b);
+}
+
+// Returns the integer that represents the product of two fixed-point
+// numbers, interpreting all integers as fixed-point values in the
+// interval [-1, 1), rounding to the nearest value, and saturating
+// -1 * -1 to the maximum value (since 1 is not in the half-open
+// interval [-1, 1)).
+//
+// [The explanation below specializes to std::int32_t for example purpose.]
+//
+// The mapping between IntegerType and the interval [-1, 1) is unique and
+// implied by IntegerType, which is assumed to be signed. For example,
+// for IntegerType==std::int32_t, the mapping is
+//   real_value = integer_value / 2^31.
+// So in this case, and leaving aside rounding and saturating, this
+// function computes ((a / 2^31) * (b / 2^31)) * 2^31, which simplifies to
+//   (a * b) / 2^31.
+//
+// The 'doubling' part in the name of this function comes from the fact that
+// this operation is very close to a "multiply-high" operation, keeping only
+// the top half bits, except that that would be effectively computing
+//   (a * b) / 2^32,
+// so here we are computing 2x that, since
+//   1/2^31 = 2 * 1/2^32.
+// The idea is to use all of the available 32 bits in the destination int32
+// value.
+//
+// [End of the explanation specializing to int32.]
+//
+// This is equivalent to the VQRDMULH instruction in ARM NEON.
+template <typename IntegerType>
+IntegerType SaturatingRoundingDoublingHighMul(IntegerType a, IntegerType b) {
+  static_assert(std::is_same<IntegerType, void>::value, "unimplemented");
+  (void)b;
+  return a;
+}
+
+// This function implements the same computation as the ARMv7 NEON VQRDMULH
+// instruction.
+template <>
+inline std::int32_t SaturatingRoundingDoublingHighMul(std::int32_t a,
+                                                      std::int32_t b) {
+  bool overflow = a == b && a == std::numeric_limits<std::int32_t>::min();
+  std::int64_t a_64(a);
+  std::int64_t b_64(b);
+  std::int64_t ab_64 = a_64 * b_64;
+  std::int32_t nudge = ab_64 >= 0 ? (1 << 30) : (1 - (1 << 30));
+  std::int32_t ab_x2_high32 =
+      static_cast<std::int32_t>((ab_64 + nudge) / (1ll << 31));
+  return overflow ? std::numeric_limits<std::int32_t>::max() : ab_x2_high32;
+}
+
+template <>
+inline std::int16_t SaturatingRoundingDoublingHighMul(std::int16_t a,
+                                                      std::int16_t b) {
+  bool overflow = a == b && a == std::numeric_limits<std::int16_t>::min();
+  std::int32_t a_32(a);
+  std::int32_t b_32(b);
+  std::int32_t ab_32 = a_32 * b_32;
+  std::int16_t nudge = ab_32 >= 0 ? (1 << 14) : (1 - (1 << 14));
+  std::int16_t ab_x2_high16 =
+      static_cast<std::int16_t>((ab_32 + nudge) / (1 << 15));
+  return overflow ? std::numeric_limits<std::int16_t>::max() : ab_x2_high16;
+}
+
+// Correctly-rounded-to-nearest division by a power-of-two.
+// Also known as a rounding arithmetic right shift.
+template <typename IntegerType>
+inline IntegerType RoundingDivideByPOT(IntegerType x, int exponent) {
+  assert(exponent >= 0);
+  assert(exponent <= 31);
+  const IntegerType mask = Dup<IntegerType>((1ll << exponent) - 1);
+  const IntegerType zero = Dup<IntegerType>(0);
+  const IntegerType one = Dup<IntegerType>(1);
+  const IntegerType remainder = BitAnd(x, mask);
+  const IntegerType threshold =
+      Add(ShiftRight(mask, 1), BitAnd(MaskIfLessThan(x, zero), one));
+  return Add(ShiftRight(x, exponent),
+             BitAnd(MaskIfGreaterThan(remainder, threshold), one));
+}
+
+// Returns the product of a run-time integer value by a compile-time power
+// of two, with either a positive exponent (equivalent to an arithmetic
+// left shift, saturating) or a negative exponent (equivalent to an arithmetic
+// right shift, rounding to nearest).
+template <int Exponent, typename IntegerType,
+          int ExponentSign = (Exponent > 0 ? 1 : Exponent < 0 ? -1 : 0)>
+struct ImplSaturatingRoundingMultiplyByPOT {};
+
+template <int Exponent, typename IntegerType>
+struct ImplSaturatingRoundingMultiplyByPOT<Exponent, IntegerType, 0> {
+  static IntegerType eval(IntegerType x) { return x; }
+};
+
+template <int Exponent, typename IntegerType>
+struct ImplSaturatingRoundingMultiplyByPOT<Exponent, IntegerType, 1> {
+  static IntegerType eval(IntegerType x) {
+    using ScalarIntegerType =
+        typename FixedPointRawTypeTraits<IntegerType>::ScalarRawType;
+    const IntegerType min =
+        Dup<IntegerType>(std::numeric_limits<ScalarIntegerType>::min());
+    const IntegerType max =
+        Dup<IntegerType>(std::numeric_limits<ScalarIntegerType>::max());
+    const int ScalarIntegerTypeBits = 8 * sizeof(ScalarIntegerType);
+
+    const std::int32_t threshold =
+        ((1 << (ScalarIntegerTypeBits - 1 - Exponent)) - 1);
+    const IntegerType positive_mask =
+        MaskIfGreaterThan(x, Dup<IntegerType>(threshold));
+    const IntegerType negative_mask =
+        MaskIfLessThan(x, Dup<IntegerType>(-threshold));
+
+    IntegerType result = ShiftLeft(x, Exponent);
+    result = SelectUsingMask(positive_mask, max, result);
+    result = SelectUsingMask(negative_mask, min, result);
+    return result;
+  }
+};
+
+template <int Exponent, typename IntegerType>
+struct ImplSaturatingRoundingMultiplyByPOT<Exponent, IntegerType, -1> {
+  static IntegerType eval(IntegerType x) {
+    return RoundingDivideByPOT<IntegerType>(x, -Exponent);
+  }
+};
+
+template <int Exponent, typename IntegerType>
+IntegerType SaturatingRoundingMultiplyByPOT(IntegerType x) {
+  return ImplSaturatingRoundingMultiplyByPOT<Exponent, IntegerType>::eval(x);
+}
+
+// Part 2: the FixedPoint class.
+
+// A FixedPoint object represents a fixed-point value stored in the underlying
+// integer type tRawType, if tRawType is a plain scalar integer type.
+// Alternatively, tRawType may be a SIMD type (e.g. NEON int32x4_t) in which
+// case a FixedPoint object represents a corresponding SIMD vector of fixed
+// point values.
+//
+// tIntegerBits describes the range of the fixed-point format: if
+// tIntegerBits == m then the range of representable values is the half-open
+// interval [-2^m; 2^m) where the open boundary on the right side means that
+// 2^m is not representable (how close the maximum representable value is to
+// it, depends on bit-depth of tRawType).
+//
+// In "Q format notation",
+//   https://en.wikipedia.org/wiki/Q_(number_format)
+// we are describing the format
+//   Qm.n
+// where
+//   m = tIntegerBits
+// and
+//   n = NumberOfBits(tRawType) - (m + 1)
+// Note that the (m + 1) in the above line is because we adopt the convention
+// that we count the integer bits exclusively of the sign bit; so (m + 1) is
+// the total number of integer bits inclusive of the sign bit.
+//
+// Accordingly, the number of integral representable values in our range
+//   [-2^m ; 2^m)
+// is equal to 2^(m+1).
+template <typename tRawType, int tIntegerBits>
+class FixedPoint {
+ public:
+  typedef tRawType RawType;
+
+  typedef FixedPointRawTypeTraits<RawType> RawTypeTraits;
+  typedef typename RawTypeTraits::ScalarRawType ScalarRawType;
+
+  static constexpr int kTotalBits = 8 * sizeof(ScalarRawType);
+  static constexpr int kIntegerBits = tIntegerBits;
+  static constexpr int kFractionalBits = kTotalBits - 1 - kIntegerBits;
+  static_assert(kIntegerBits >= 0 && kIntegerBits < kTotalBits,
+                "bad IntegerBits");
+
+  typedef FixedPoint<ScalarRawType, kIntegerBits> ScalarFixedPointType;
+
+  static const ScalarRawType ScalarRawMin() {
+    return std::numeric_limits<ScalarRawType>::min();
+  }
+
+  static const ScalarRawType ScalarRawMax() {
+    return std::numeric_limits<ScalarRawType>::max();
+  }
+
+  static const ScalarRawType RawMin() {
+    return VectorFromScalar(ScalarRawMin());
+  }
+
+  static const ScalarRawType RawMax() {
+    return VectorFromScalar(ScalarRawMax());
+  }
+
+  static FixedPoint FromRaw(RawType x) {
+    FixedPoint retval;
+    retval.raw() = x;
+    return retval;
+  }
+
+  static FixedPoint FromScalarRaw(ScalarRawType x) {
+    FixedPoint retval;
+    retval.raw() = Dup<RawType>(x);
+    return retval;
+  }
+
+  static FixedPoint FromScalarFixedPoint(ScalarFixedPointType x) {
+    return FromScalarRaw(x.raw());
+  }
+
+  template <int Exponent>
+  static FixedPoint ConstantPOT() {
+    static constexpr int kOffset = kFractionalBits + Exponent;
+    static_assert(
+        kOffset < 31,
+        "Constant not exactly representable in this fixed-point format");
+    return FromScalarRaw(ScalarRawType(1) << kOffset);
+  }
+
+  static FixedPoint Zero() { return FromScalarRaw(0); }
+
+  static FixedPoint One() {
+    return FromScalarRaw(
+        kIntegerBits == 0
+            ? ScalarRawMax()
+            : (ScalarRawType(1) << (kIntegerBits == 0 ? 0 : kFractionalBits)));
+  }
+
+  static FixedPoint FromDouble(double x) {
+    const double min_bound = static_cast<double>(ScalarRawMin());
+    const double max_bound = static_cast<double>(ScalarRawMax());
+    return FromScalarRaw(static_cast<ScalarRawType>(std::min(
+        std::max(round(x * static_cast<double>(1ll << kFractionalBits)),
+                 min_bound),
+        max_bound)));
+  }
+
+  RawType raw() const { return i_; }
+  RawType& raw() { return i_; }
+
+ private:
+  RawType i_;
+};
+
+// Part 3: implementation of arithmetic operators for the
+// FixedPoint class, and a few related functions.
+
+// A FixedPoint multiplication is just a
+// SaturatingRoundingDoublingHighMul operation on the underlying
+// raw integer values. The IntegerBits simply add up, as is obvious
+// from the fact that the range is [-2^IntegerBits, 2^IntegerBits).
+template <typename tRawType, int tIntegerBits_a, int tIntegerBits_b>
+FixedPoint<tRawType, tIntegerBits_a + tIntegerBits_b> operator*(
+    FixedPoint<tRawType, tIntegerBits_a> a,
+    FixedPoint<tRawType, tIntegerBits_b> b) {
+  FixedPoint<tRawType, tIntegerBits_a + tIntegerBits_b> c;
+  c.raw() = SaturatingRoundingDoublingHighMul(a.raw(), b.raw());
+  return c;
+}
+
+// Tweaking IntegerBits gives exact multiplication by a power of two.
+template <int tExponent, typename tRawType, int tIntegerBits>
+FixedPoint<tRawType, tExponent + tIntegerBits> ExactMulByPot(
+    FixedPoint<tRawType, tIntegerBits> a) {
+  FixedPoint<tRawType, tExponent + tIntegerBits> c;
+  c.raw() = a.raw();
+  return c;
+}
+
+// If we want to leave IntegerBits fixed, then multiplication
+// by a power of two has to be saturating/rounding, not exact anymore.
+template <int tExponent, typename tRawType, int tIntegerBits>
+FixedPoint<tRawType, tIntegerBits> SaturatingRoundingMultiplyByPOT(
+    FixedPoint<tRawType, tIntegerBits> a) {
+  return FixedPoint<tRawType, tIntegerBits>::FromRaw(
+      SaturatingRoundingMultiplyByPOT<tExponent>(a.raw()));
+}
+
+// Generic arithmetic operators.
+
+#define MAKE_FIXEDPOINT_UNARY_FUNC(FuncName, ImplFuncName)                     \
+  template <typename tRawType, int tIntegerBits>                               \
+  FixedPoint<tRawType, tIntegerBits> FuncName(                                 \
+      FixedPoint<tRawType, tIntegerBits> a) {                                  \
+    return FixedPoint<tRawType, tIntegerBits>::FromRaw(ImplFuncName(a.raw())); \
+  }
+
+#define MAKE_FIXEDPOINT_BINARY_FUNC(FuncName, ImplFuncName) \
+  template <typename tRawType, int tIntegerBits>            \
+  FixedPoint<tRawType, tIntegerBits> FuncName(              \
+      FixedPoint<tRawType, tIntegerBits> a,                 \
+      FixedPoint<tRawType, tIntegerBits> b) {               \
+    return FixedPoint<tRawType, tIntegerBits>::FromRaw(     \
+        ImplFuncName(a.raw(), b.raw()));                    \
+  }
+
+MAKE_FIXEDPOINT_UNARY_FUNC(operator-, Neg)
+MAKE_FIXEDPOINT_UNARY_FUNC(operator~, BitNot)
+MAKE_FIXEDPOINT_BINARY_FUNC(operator+, Add)
+MAKE_FIXEDPOINT_BINARY_FUNC(operator-, Sub)
+MAKE_FIXEDPOINT_BINARY_FUNC(operator&, BitAnd)
+MAKE_FIXEDPOINT_BINARY_FUNC(operator^, BitXor)
+MAKE_FIXEDPOINT_BINARY_FUNC(operator|, BitOr)
+MAKE_FIXEDPOINT_BINARY_FUNC(RoundingHalfSum, RoundingHalfSum)
+
+#undef MAKE_FIXEDPOINT_UNARY_FUNC
+#undef MAKE_FIXEDPOINT_BINARY_FUNC
+
+#define MAKE_FIXEDPOINT_UNARY_FUNC_RETURNING_RAW(FuncName)  \
+  template <typename tRawType, int tIntegerBits>            \
+  tRawType FuncName(FixedPoint<tRawType, tIntegerBits> a) { \
+    return FuncName(a.raw());                               \
+  }
+
+#define MAKE_FIXEDPOINT_BINARY_FUNC_RETURNING_RAW(FuncName) \
+  template <typename tRawType, int tIntegerBits>            \
+  tRawType FuncName(FixedPoint<tRawType, tIntegerBits> a,   \
+                    FixedPoint<tRawType, tIntegerBits> b) { \
+    return FuncName(a.raw(), b.raw());                      \
+  }
+
+MAKE_FIXEDPOINT_UNARY_FUNC_RETURNING_RAW(MaskIfZero)
+MAKE_FIXEDPOINT_UNARY_FUNC_RETURNING_RAW(MaskIfNonZero)
+MAKE_FIXEDPOINT_BINARY_FUNC_RETURNING_RAW(MaskIfEqual)
+MAKE_FIXEDPOINT_BINARY_FUNC_RETURNING_RAW(MaskIfNotEqual)
+MAKE_FIXEDPOINT_BINARY_FUNC_RETURNING_RAW(MaskIfGreaterThan)
+MAKE_FIXEDPOINT_BINARY_FUNC_RETURNING_RAW(MaskIfGreaterThanOrEqual)
+MAKE_FIXEDPOINT_BINARY_FUNC_RETURNING_RAW(MaskIfLessThan)
+MAKE_FIXEDPOINT_BINARY_FUNC_RETURNING_RAW(MaskIfLessThanOrEqual)
+
+#undef MAKE_FIXEDPOINT_UNARY_FUNC_RETURNING_RAW
+#undef MAKE_FIXEDPOINT_BINARY_FUNC_RETURNING_RAW
+
+template <typename tRawType, int tIntegerBits>
+FixedPoint<tRawType, tIntegerBits> SelectUsingMask(
+    tRawType if_mask, FixedPoint<tRawType, tIntegerBits> then_val,
+    FixedPoint<tRawType, tIntegerBits> else_val) {
+  return FixedPoint<tRawType, tIntegerBits>::FromRaw(
+      SelectUsingMask(if_mask, then_val.raw(), else_val.raw()));
+}
+
+template <typename tRawType, int tIntegerBits>
+bool operator==(FixedPoint<tRawType, tIntegerBits> a,
+                FixedPoint<tRawType, tIntegerBits> b) {
+  return All(MaskIfEqual(a.raw(), b.raw()));
+}
+
+template <typename tRawType, int tIntegerBits>
+bool operator!=(FixedPoint<tRawType, tIntegerBits> a,
+                FixedPoint<tRawType, tIntegerBits> b) {
+  return !(a == b);
+}
+
+template <typename tRawType, int tIntegerBits>
+FixedPoint<tRawType, tIntegerBits> SaturatingAdd(
+    FixedPoint<tRawType, tIntegerBits> a,
+    FixedPoint<tRawType, tIntegerBits> b) {
+  return FixedPoint<tRawType, tIntegerBits>::FromRaw(
+      SaturatingAdd(a.raw(), b.raw()));
+}
+
+template <typename tRawType, int tIntegerBits>
+FixedPoint<tRawType, tIntegerBits> AddSaturatingIf16Bit(
+    FixedPoint<tRawType, tIntegerBits> a,
+    FixedPoint<tRawType, tIntegerBits> b) {
+  return FixedPoint<tRawType, tIntegerBits>::FromRaw(
+      AddSaturatingIf16Bit(a.raw(), b.raw()));
+}
+
+// Conversion to floating-point.
+template <typename tRawType, int tIntegerBits>
+double ToDouble(FixedPoint<tRawType, tIntegerBits> x) {
+  static_assert(FixedPointRawTypeTraits<tRawType>::kLanes == 1,
+                "not applicable to SIMD types");
+  typedef FixedPoint<tRawType, tIntegerBits> F;
+  return x.raw() / static_cast<double>(1ll << F::kFractionalBits);
+}
+
+// Rescale changes the number of IntegerBits and updates the underlying
+// raw integer value accordingly.
+template <int tIntegerBitsDst, typename tRawType, int tIntegerBitsSrc>
+FixedPoint<tRawType, tIntegerBitsDst> Rescale(
+    FixedPoint<tRawType, tIntegerBitsSrc> x) {
+  static constexpr int kExponent = tIntegerBitsSrc - tIntegerBitsDst;
+  FixedPoint<tRawType, tIntegerBitsDst> result;
+  result.raw() = SaturatingRoundingMultiplyByPOT<kExponent>(x.raw());
+  return result;
+}
+
+// CheckedFixedPointConstant allows to specify fixed-point constants
+// initialized as real numbers, in a way that does not compile floating-point
+// arithmetic in production code, yet still checks agreement with the
+// floating-point expressions when asserts are enabled.
+//
+// The raw integer value provided is always a int32, encoding a 32-bit
+// fixed-point value, regardless of the actual Scalar type. This allows
+// writing generic code that applies just as well to the 32-bit and 16-bit
+// cases. In the 16-bit case, the raw integer value is internally
+// rounding-shifted by 16 bits to the right.
+template <typename FixedPointType>
+inline typename FixedPointType::ScalarRawType RescaleConstantInitializer(
+    std::int32_t int32_value) {
+  typedef typename FixedPointType::ScalarRawType ScalarRawType;
+  static constexpr int ScalarTypeBits = 8 * sizeof(ScalarRawType);
+  return static_cast<ScalarRawType>(
+      RoundingDivideByPOT<std::int32_t>(int32_value, 32 - ScalarTypeBits));
+}
+#ifdef GEMMLOWP_ENABLE_FIXEDPOINT_CONSTANTS_CHECKS
+template <typename FixedPointType>
+FixedPointType CheckedFixedPointConstant(std::int32_t raw_value,
+                                         double double_value) {
+  const FixedPointType result = FixedPointType::FromScalarRaw(raw_value);
+  assert(result == FixedPointType::FromDouble(double_value));
+  return result;
+}
+#define GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(FixedPointType,                   \
+                                             ScalarRawInt32Value, DoubleValue) \
+  (gemmlowp::CheckedFixedPointConstant<FixedPointType>(                        \
+      gemmlowp::RescaleConstantInitializer<FixedPointType>(                    \
+          ScalarRawInt32Value),                                                \
+      DoubleValue))
+
+#else
+#define GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(FixedPointType,                   \
+                                             ScalarRawInt32Value, DoubleValue) \
+  (FixedPointType::FromScalarRaw(                                              \
+      gemmlowp::RescaleConstantInitializer<FixedPointType>(                    \
+          ScalarRawInt32Value)))
+#endif
+
+// Implementation of exponential function.
+
+// Returns exp(x) for x in [-1/4, 0).
+template <typename tRawType>
+FixedPoint<tRawType, 0> exp_on_interval_between_negative_one_quarter_and_0_excl(
+    FixedPoint<tRawType, 0> a) {
+  typedef FixedPoint<tRawType, 0> F;
+  const F constant_term =
+      GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(F, 1895147668, std::exp(-1.0 / 8.0));
+  const F constant_1_over_3 =
+      GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(F, 715827883, 1.0 / 3.0);
+  // We're evaluating a Taylor expansion around -1/8, so we do the change of
+  // variable: x = a + 1/8.
+  // In fixed-point with 0 integer bits, 1/8 is represented by 1 << 28.
+  F x = a + F::template ConstantPOT<-3>();
+  F x2 = x * x;
+  F x3 = x2 * x;
+  F x4 = x2 * x2;
+  F x4_over_4 = SaturatingRoundingMultiplyByPOT<-2>(x4);
+  F x4_over_24_plus_x3_over_6_plus_x2_over_2 =
+      SaturatingRoundingMultiplyByPOT<-1>(
+          ((x4_over_4 + x3) * constant_1_over_3) + x2);
+  return AddSaturatingIf16Bit(
+      constant_term,
+      constant_term * (x + x4_over_24_plus_x3_over_6_plus_x2_over_2));
+}
+
+// Returns exp(x) for x < 0.
+template <typename tRawType, int tIntegerBits>
+FixedPoint<tRawType, 0> exp_on_negative_values(
+    FixedPoint<tRawType, tIntegerBits> a) {
+  typedef FixedPoint<tRawType, tIntegerBits> InputF;
+  typedef FixedPoint<tRawType, 0> ResultF;
+  static constexpr int kFractionalBits = InputF::kFractionalBits;
+  static constexpr int kIntegerBits = InputF::kIntegerBits;
+  const InputF kOneQuarter = InputF::template ConstantPOT<-2>();
+  InputF mask = kOneQuarter - InputF::FromScalarRaw(1);
+  InputF a_mod_quarter_minus_one_quarter = (a & mask) - kOneQuarter;
+  ResultF result = exp_on_interval_between_negative_one_quarter_and_0_excl(
+      Rescale<0>(a_mod_quarter_minus_one_quarter));
+  tRawType remainder = (a_mod_quarter_minus_one_quarter - a).raw();
+
+#define GEMMLOWP_EXP_BARREL_SHIFTER(Exponent, FixedPointMultiplier)         \
+  if (kIntegerBits > Exponent) {                                            \
+    const ResultF kMultiplier = GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(       \
+        ResultF, FixedPointMultiplier, std::exp(-std::pow(2.0, Exponent))); \
+    static constexpr int kShiftAmount =                                     \
+        kIntegerBits > Exponent ? kFractionalBits + Exponent : 0;           \
+    result = SelectUsingMask(                                               \
+        MaskIfNonZero(BitAnd(remainder, Dup<tRawType>(1 << kShiftAmount))), \
+        result * kMultiplier, result);                                      \
+  }
+
+  GEMMLOWP_EXP_BARREL_SHIFTER(-2, 1672461947);
+  GEMMLOWP_EXP_BARREL_SHIFTER(-1, 1302514674);
+  GEMMLOWP_EXP_BARREL_SHIFTER(+0, 790015084);
+  GEMMLOWP_EXP_BARREL_SHIFTER(+1, 290630308);
+  GEMMLOWP_EXP_BARREL_SHIFTER(+2, 39332535);
+  GEMMLOWP_EXP_BARREL_SHIFTER(+3, 720401);
+  GEMMLOWP_EXP_BARREL_SHIFTER(+4, 242);
+
+#undef GEMMLOWP_EXP_BARREL_SHIFTER
+
+  static constexpr int clampB = kIntegerBits > 5 ? 36 - kIntegerBits : 0;
+  if (kIntegerBits > 5) {
+    const InputF clamp =
+        GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(InputF, -(1 << clampB), -32.0);
+    result = SelectUsingMask(MaskIfLessThan(a, clamp), ResultF::Zero(), result);
+  }
+
+  result = SelectUsingMask(MaskIfZero(a), ResultF::One(), result);
+  return result;
+}
+
+// Implementation of tanh: (1 - exp(-2x)) / (1 + exp(-2x)).
+
+// Returns (1 - x) / (1 + x) for x in (0, 1).
+template <typename tRawType>
+FixedPoint<tRawType, 0> one_minus_x_over_one_plus_x_for_x_in_0_1(
+    FixedPoint<tRawType, 0> a) {
+  typedef FixedPoint<tRawType, 0> F0;
+  typedef FixedPoint<tRawType, 2> F2;
+  F0 half_denominator = RoundingHalfSum(a, F0::One());
+  // Newton-Raphson division
+  // https://en.wikipedia.org/wiki/Division_algorithm#Newton.E2.80.93Raphson_division
+  // Refer to that page for the logic behind the 48/17 and 32/17 constants.
+  const F2 constant_48_over_17 =
+      GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(F2, 1515870810, 48.0 / 17.0);
+  const F2 constant_neg_32_over_17 =
+      GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(F2, -1010580540, -32.0 / 17.0);
+  F2 x = constant_48_over_17 + half_denominator * constant_neg_32_over_17;
+  for (int i = 0; i < 3; i++) {
+    F2 half_denominator_times_x = half_denominator * x;
+    F2 one_minus_half_denominator_times_x =
+        F2::One() - half_denominator_times_x;
+    x = x + Rescale<2>(x * one_minus_half_denominator_times_x);
+  }
+  return Rescale<0>(x - F2::One());
+}
+
+// Returns -tanh(x) for x < 0.
+template <typename tRawType, int tIntegerBits>
+FixedPoint<tRawType, 0> neg_tanh_on_negative_values(
+    FixedPoint<tRawType, tIntegerBits> a) {
+  return one_minus_x_over_one_plus_x_for_x_in_0_1(
+      exp_on_negative_values(ExactMulByPot<1>(a)));
+}
+
+// Returns tanh(x) for any x.
+template <typename tRawType, int tIntegerBits>
+FixedPoint<tRawType, 0> tanh(FixedPoint<tRawType, tIntegerBits> a) {
+  typedef FixedPoint<tRawType, tIntegerBits> InputF;
+  typedef FixedPoint<tRawType, 0> ResultF;
+  tRawType mask_if_negative = MaskIfLessThan(a, InputF::Zero());
+  tRawType mask_if_zero = MaskIfZero(a);
+  InputF n = SelectUsingMask(mask_if_negative, a, -a);
+  ResultF t = neg_tanh_on_negative_values(n);
+  return SelectUsingMask(mask_if_zero, ResultF::Zero(),
+                         SelectUsingMask(mask_if_negative, -t, t));
+}
+
+// Implementation of logistic function.
+
+// Returns 1 / (1 + x) for x in (0, 1).
+template <typename tRawType>
+FixedPoint<tRawType, 0> one_over_one_plus_x_for_x_in_0_1(
+    FixedPoint<tRawType, 0> a) {
+  typedef FixedPoint<tRawType, 0> F0;
+  typedef FixedPoint<tRawType, 2> F2;
+  F0 half_denominator = RoundingHalfSum(a, F0::One());
+  // Newton-Raphson division
+  // https://en.wikipedia.org/wiki/Division_algorithm#Newton.E2.80.93Raphson_division
+  // Refer to that page for the logic behind the 48/17 and 32/17 constants.
+  const F2 constant_48_over_17 =
+      GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(F2, 1515870810, 48.0 / 17.0);
+  const F2 constant_neg_32_over_17 =
+      GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(F2, -1010580540, -32.0 / 17.0);
+  F2 x = constant_48_over_17 + half_denominator * constant_neg_32_over_17;
+  for (int i = 0; i < 3; i++) {
+    F2 half_denominator_times_x = half_denominator * x;
+    F2 one_minus_half_denominator_times_x =
+        F2::One() - half_denominator_times_x;
+    x = x + Rescale<2>(x * one_minus_half_denominator_times_x);
+  }
+  return Rescale<0>(ExactMulByPot<-1>(x));
+}
+
+// Returns logistic(x) = 1 / (1 + exp(-x)) for x > 0.
+template <typename tRawType, int tIntegerBits>
+FixedPoint<tRawType, 0> logistic_on_positive_values(
+    FixedPoint<tRawType, tIntegerBits> a) {
+  return one_over_one_plus_x_for_x_in_0_1(exp_on_negative_values(-a));
+}
+
+// Returns logistic(x) = 1 / (1 + exp(-x)) for any x.
+template <typename tRawType, int tIntegerBits>
+FixedPoint<tRawType, 0> logistic(FixedPoint<tRawType, tIntegerBits> a) {
+  typedef FixedPoint<tRawType, tIntegerBits> InputF;
+  typedef FixedPoint<tRawType, 0> ResultF;
+  tRawType mask_if_positive = MaskIfGreaterThan(a, InputF::Zero());
+  tRawType mask_if_zero = MaskIfZero(a);
+  InputF abs_input = SelectUsingMask(mask_if_positive, a, -a);
+  ResultF result_if_positive = logistic_on_positive_values(abs_input);
+  ResultF result_if_negative = ResultF::One() - result_if_positive;
+  const ResultF one_half =
+      GEMMLOWP_CHECKED_FIXEDPOINT_CONSTANT(ResultF, 1 << 30, 0.5);
+  return SelectUsingMask(mask_if_zero, one_half,
+                         SelectUsingMask(mask_if_positive, result_if_positive,
+                                         result_if_negative));
+}
+
+}  // end namespace gemmlowp
+
+#ifdef GEMMLOWP_NEON
+#include "./fixedpoint_neon.h"
+#elif defined(GEMMLOWP_AVX2)
+#include "./fixedpoint_avx.h"
+#elif defined(GEMMLOWP_SSE4)
+#include "./fixedpoint_sse.h"
+#elif defined(GEMMLOWP_MSA)
+#include "./fixedpoint_msa.h"
+#endif
+
+#endif  // GEMMLOWP_INTERNAL_FIXEDPOINT_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/gemmlowp/fixedpoint/fixedpoint_sse.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/gemmlowp/fixedpoint/fixedpoint_sse.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,384 @@
+// Copyright 2015 Google Inc. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+// fixedpoint_SSE.h: optimized SSE specializations of the templates
+// in fixedpoint.h.
+
+#ifndef GEMMLOWP_INTERNAL_FIXEDPOINT_SSE_H_
+#define GEMMLOWP_INTERNAL_FIXEDPOINT_SSE_H_
+
+#include <smmintrin.h>
+#include "fixedpoint.h"
+
+namespace gemmlowp {
+
+// SSE intrinsics are not finely typed: there is a single __m128i vector
+// type that does not distinguish between "int32x4" and "int16x8" use
+// cases, unlike the NEON equivalents. Because we had initially focused
+// on int32x4, we did not pay attention and specialized these fixedpoint
+// templates directly for __m128i hardcoding the int32x4 semantics,
+// not leaving room for int16x8 semantics. Amending that by adding a separate
+// data type, int16x8_m128i, that wraps __m128i while being a separate
+// type.
+struct int16x8_m128i {
+  int16x8_m128i() {}
+  explicit int16x8_m128i(__m128i w) : v(w) {}
+  ~int16x8_m128i() {}
+
+  __m128i v;
+};
+
+template <>
+struct FixedPointRawTypeTraits<__m128i> {
+  typedef std::int32_t ScalarRawType;
+  static constexpr int kLanes = 4;
+};
+
+template <>
+struct FixedPointRawTypeTraits<int16x8_m128i> {
+  typedef std::int16_t ScalarRawType;
+  static constexpr int kLanes = 8;
+};
+
+template <>
+inline __m128i BitAnd(__m128i a, __m128i b) {
+  return _mm_and_si128(a, b);
+}
+
+template <>
+inline int16x8_m128i BitAnd(int16x8_m128i a, int16x8_m128i b) {
+  return int16x8_m128i(_mm_and_si128(a.v, b.v));
+}
+
+template <>
+inline __m128i BitOr(__m128i a, __m128i b) {
+  return _mm_or_si128(a, b);
+}
+
+template <>
+inline int16x8_m128i BitOr(int16x8_m128i a, int16x8_m128i b) {
+  return int16x8_m128i(_mm_or_si128(a.v, b.v));
+}
+
+template <>
+inline __m128i BitXor(__m128i a, __m128i b) {
+  return _mm_xor_si128(a, b);
+}
+
+template <>
+inline int16x8_m128i BitXor(int16x8_m128i a, int16x8_m128i b) {
+  return int16x8_m128i(_mm_xor_si128(a.v, b.v));
+}
+
+template <>
+inline __m128i BitNot(__m128i a) {
+  return _mm_andnot_si128(a, _mm_set1_epi32(-1));
+}
+
+template <>
+inline int16x8_m128i BitNot(int16x8_m128i a) {
+  return int16x8_m128i(_mm_andnot_si128(a.v, _mm_set1_epi16(-1)));
+}
+
+template <>
+inline __m128i Add(__m128i a, __m128i b) {
+  return _mm_add_epi32(a, b);
+}
+
+template <>
+inline int16x8_m128i Add(int16x8_m128i a, int16x8_m128i b) {
+  return int16x8_m128i(_mm_add_epi16(a.v, b.v));
+}
+
+template <>
+inline __m128i Mul(__m128i a, __m128i b) {
+  return _mm_mullo_epi32(a, b);
+}
+
+template <>
+inline int16x8_m128i Mul(int16x8_m128i a, int16x8_m128i b) {
+  return int16x8_m128i(_mm_mullo_epi16(a.v, b.v));
+}
+
+template <>
+inline __m128i Sub(__m128i a, __m128i b) {
+  return _mm_sub_epi32(a, b);
+}
+
+template <>
+inline int16x8_m128i Sub(int16x8_m128i a, int16x8_m128i b) {
+  return int16x8_m128i(_mm_sub_epi16(a.v, b.v));
+}
+
+template <>
+inline __m128i Neg(__m128i a) {
+  return _mm_sign_epi32(a, _mm_set1_epi32(-1));
+}
+
+template <>
+inline int16x8_m128i Neg(int16x8_m128i a) {
+  return int16x8_m128i(_mm_sign_epi16(a.v, _mm_set1_epi16(-1)));
+}
+
+template <>
+inline __m128i ShiftLeft(__m128i a, int offset) {
+  return _mm_slli_epi32(a, offset);
+}
+
+template <>
+inline int16x8_m128i ShiftLeft(int16x8_m128i a, int offset) {
+  return int16x8_m128i(_mm_slli_epi16(a.v, offset));
+}
+
+template <>
+inline __m128i ShiftRight(__m128i a, int offset) {
+  return _mm_srai_epi32(a, offset);
+}
+
+template <>
+inline int16x8_m128i ShiftRight(int16x8_m128i a, int offset) {
+  return int16x8_m128i(_mm_srai_epi16(a.v, offset));
+}
+
+template <>
+inline __m128i SelectUsingMask(__m128i if_mask, __m128i then_val,
+                               __m128i else_val) {
+  // borrowed from Intel's arm_neon_sse.h header.
+  return _mm_or_si128(_mm_and_si128(if_mask, then_val),
+                      _mm_andnot_si128(if_mask, else_val));
+}
+
+template <>
+inline int16x8_m128i SelectUsingMask(int16x8_m128i if_mask,
+                                     int16x8_m128i then_val,
+                                     int16x8_m128i else_val) {
+  // borrowed from Intel's arm_neon_sse.h header.
+  return int16x8_m128i(SelectUsingMask(if_mask.v, then_val.v, else_val.v));
+}
+
+template <>
+inline __m128i MaskIfEqual(__m128i a, __m128i b) {
+  return _mm_cmpeq_epi32(a, b);
+}
+
+template <>
+inline int16x8_m128i MaskIfEqual(int16x8_m128i a, int16x8_m128i b) {
+  return int16x8_m128i(_mm_cmpeq_epi16(a.v, b.v));
+}
+
+template <>
+inline __m128i MaskIfNotEqual(__m128i a, __m128i b) {
+  return BitNot(MaskIfEqual(a, b));
+}
+
+template <>
+inline int16x8_m128i MaskIfNotEqual(int16x8_m128i a, int16x8_m128i b) {
+  return BitNot(MaskIfEqual(a, b));
+}
+
+template <>
+inline __m128i MaskIfZero(__m128i a) {
+  return MaskIfEqual(a, _mm_set1_epi32(0));
+}
+
+template <>
+inline int16x8_m128i MaskIfZero(int16x8_m128i a) {
+  return MaskIfEqual(a, int16x8_m128i(_mm_set1_epi16(0)));
+}
+
+template <>
+inline __m128i MaskIfNonZero(__m128i a) {
+  return MaskIfNotEqual(a, _mm_set1_epi32(0));
+}
+
+template <>
+inline int16x8_m128i MaskIfNonZero(int16x8_m128i a) {
+  return MaskIfNotEqual(a, int16x8_m128i(_mm_set1_epi16(0)));
+}
+
+template <>
+inline __m128i MaskIfGreaterThan(__m128i a, __m128i b) {
+  return _mm_cmpgt_epi32(a, b);
+}
+
+template <>
+inline int16x8_m128i MaskIfGreaterThan(int16x8_m128i a, int16x8_m128i b) {
+  return int16x8_m128i(_mm_cmpgt_epi16(a.v, b.v));
+}
+
+template <>
+inline __m128i MaskIfLessThan(__m128i a, __m128i b) {
+  return _mm_cmplt_epi32(a, b);
+}
+
+template <>
+inline int16x8_m128i MaskIfLessThan(int16x8_m128i a, int16x8_m128i b) {
+  return int16x8_m128i(_mm_cmplt_epi16(a.v, b.v));
+}
+
+template <>
+inline __m128i MaskIfGreaterThanOrEqual(__m128i a, __m128i b) {
+  return BitNot(MaskIfLessThan(a, b));
+}
+
+template <>
+inline int16x8_m128i MaskIfGreaterThanOrEqual(int16x8_m128i a,
+                                              int16x8_m128i b) {
+  return BitNot(MaskIfLessThan(a, b));
+}
+
+template <>
+inline __m128i MaskIfLessThanOrEqual(__m128i a, __m128i b) {
+  return BitNot(MaskIfGreaterThan(a, b));
+}
+
+template <>
+inline int16x8_m128i MaskIfLessThanOrEqual(int16x8_m128i a, int16x8_m128i b) {
+  return BitNot(MaskIfGreaterThan(a, b));
+}
+
+/* Assumptions:
+   - All and Any are used on masks.
+   - masks are all_ones for true lanes, all_zeroes otherwise.
+Hence, All means all 128bits set, and Any means any bit set.
+*/
+
+template <>
+inline bool All(__m128i a) {
+  return _mm_testc_si128(a, a);
+}
+
+template <>
+inline bool All(int16x8_m128i a) {
+  return _mm_testc_si128(a.v, a.v);
+}
+
+template <>
+inline bool Any(__m128i a) {
+  return !_mm_testz_si128(a, a);
+}
+
+template <>
+inline bool Any(int16x8_m128i a) {
+  return !_mm_testz_si128(a.v, a.v);
+}
+
+template <>
+inline __m128i RoundingHalfSum(__m128i a, __m128i b) {
+  /* __m128i round_bit_mask, a_over_2, b_over_2, round_bit, sum; */
+  /* We divide the inputs before the add to avoid the overflow and costly test
+   */
+  /* of checking if an overflow occured on signed add */
+  /* round_bit_mask = _mm_set1_epi32(1); */
+  /* a_over_2 = _mm_srai_epi32(a, 1); */
+  /* b_over_2 = _mm_srai_epi32(b, 1); */
+  /* sum = Add(a_over_2, b_over_2); */
+  /* round_bit = _mm_sign_epi32(BitAnd(BitOr(a,b), round_bit_mask), sum); */
+  /* return Add(sum, round_bit); */
+
+  /* Other possibility detecting overflow and xor the sign if an overflow
+   * happened*/
+  __m128i one, sign_bit_mask, sum, rounded_half_sum, overflow, result;
+  one = _mm_set1_epi32(1);
+  sign_bit_mask = _mm_set1_epi32(0x80000000);
+  sum = Add(a, b);
+  rounded_half_sum = _mm_srai_epi32(Add(sum, one), 1);
+  overflow =
+      BitAnd(BitAnd(BitXor(a, rounded_half_sum), BitXor(b, rounded_half_sum)),
+             sign_bit_mask);
+  result = BitXor(rounded_half_sum, overflow);
+  return result;
+}
+
+template <>
+inline int16x8_m128i RoundingHalfSum(int16x8_m128i a, int16x8_m128i b) {
+  // Idea: go to unsigned to use _mm_avg_epu16,
+  // borrowed from Intel's arm_neon_sse.h header.
+  __m128i constant_neg_32768 = _mm_set1_epi16(-32768);
+  __m128i a_unsigned = _mm_sub_epi16(a.v, constant_neg_32768);
+  __m128i b_unsigned = _mm_sub_epi16(b.v, constant_neg_32768);
+  __m128i avg_unsigned = _mm_avg_epu16(a_unsigned, b_unsigned);
+  __m128i avg = _mm_add_epi16(avg_unsigned, constant_neg_32768);
+  return int16x8_m128i(avg);
+}
+
+template <>
+inline __m128i SaturatingRoundingDoublingHighMul(__m128i a, __m128i b) {
+  __m128i min, saturation_mask, a0_a2, a1_a3, b0_b2, b1_b3;
+  __m128i a0b0_a2b2, a1b1_a3b3, a0b0_a2b2_rounded, a1b1_a3b3_rounded;
+  __m128i a0b0_a2b2_rounded_2x, a1b1_a3b3_rounded_2x, result;
+  __m128i nudge;
+
+  // saturation only happen if a == b == INT_MIN
+  min = _mm_set1_epi32(std::numeric_limits<std::int32_t>::min());
+  saturation_mask = BitAnd(MaskIfEqual(a, b), MaskIfEqual(a, min));
+
+  // a = a0 | a1 | a2 | a3
+  // b = b0 | b1 | b2 | b3
+  a0_a2 = a;
+  a1_a3 = _mm_srli_si128(a, 4);
+  b0_b2 = b;
+  b1_b3 = _mm_srli_si128(b, 4);
+
+  a0b0_a2b2 = _mm_mul_epi32(a0_a2, b0_b2);
+  a1b1_a3b3 = _mm_mul_epi32(a1_a3, b1_b3);
+
+  // do the rounding and take into account that it will be doubled
+  nudge = _mm_set1_epi64x(1 << 30);
+  a0b0_a2b2_rounded = _mm_add_epi64(a0b0_a2b2, nudge);
+  a1b1_a3b3_rounded = _mm_add_epi64(a1b1_a3b3, nudge);
+
+  // do the doubling
+  a0b0_a2b2_rounded_2x = _mm_slli_epi64(a0b0_a2b2_rounded, 1);
+  a1b1_a3b3_rounded_2x = _mm_slli_epi64(a1b1_a3b3_rounded, 1);
+
+  // get the high part of the products
+  result = _mm_blend_epi16(_mm_srli_si128(a0b0_a2b2_rounded_2x, 4),
+                           a1b1_a3b3_rounded_2x, 0xcc);
+
+  // saturate those which overflowed
+  return SelectUsingMask(saturation_mask, min, result);
+}
+
+template <>
+inline int16x8_m128i SaturatingRoundingDoublingHighMul(int16x8_m128i a,
+                                                       int16x8_m128i b) {
+  // Idea: use _mm_mulhrs_epi16 then saturate with a bit-operation,
+  // borrowed from Intel's arm_neon_sse.h header.
+  __m128i result_unsaturated = _mm_mulhrs_epi16(a.v, b.v);
+  __m128i saturation_mask =
+      _mm_cmpeq_epi16(result_unsaturated, _mm_set1_epi16(0x8000));
+  __m128i result = _mm_xor_si128(result_unsaturated, saturation_mask);
+  return int16x8_m128i(result);
+}
+
+template <>
+inline __m128i Dup<__m128i>(std::int32_t x) {
+  return _mm_set1_epi32(x);
+}
+
+template <>
+inline int16x8_m128i Dup<int16x8_m128i>(std::int16_t x) {
+  return int16x8_m128i(_mm_set1_epi16(x));
+}
+
+// So far this is only needed for int16.
+template <>
+inline int16x8_m128i SaturatingAdd(int16x8_m128i a, int16x8_m128i b) {
+  return int16x8_m128i(_mm_adds_epi16(a.v, b.v));
+}
+
+}  // end namespace gemmlowp
+
+#endif  // GEMMLOWP_INTERNAL_FIXEDPOINT_SSE_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/gemmlowp/internal/detect_platform.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/gemmlowp/internal/detect_platform.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,166 @@
+// Copyright 2018 The Gemmlowp Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+// detect_platform.h: Sets up macros that control architecture-specific
+// features of gemmlowp's implementation.
+
+#ifndef GEMMLOWP_INTERNAL_DETECT_PLATFORM_H_
+#define GEMMLOWP_INTERNAL_DETECT_PLATFORM_H_
+
+// Our inline assembly path assume GCC/Clang syntax.
+// Native Client doesn't seem to support inline assembly(?).
+#if defined(__GNUC__) && !defined(__native_client__)
+#define GEMMLOWP_ALLOW_INLINE_ASM
+#endif
+
+// Define macro statement that avoids inlining for GCC.
+// For non-GCC, define as empty macro.
+#if defined(__GNUC__)
+#define GEMMLOWP_NOINLINE __attribute__((noinline))
+#else
+#define GEMMLOWP_NOINLINE
+#endif
+
+// Detect ARM, 32-bit or 64-bit
+#ifdef __arm__
+#define GEMMLOWP_ARM_32
+#endif
+
+#ifdef __aarch64__
+#define GEMMLOWP_ARM_64
+#endif
+
+#if defined(GEMMLOWP_ARM_32) || defined(GEMMLOWP_ARM_64)
+#define GEMMLOWP_ARM
+#endif
+
+// Detect MIPS, 32-bit or 64-bit
+#if defined(__mips) && !defined(__LP64__)
+#define GEMMLOWP_MIPS_32
+#endif
+
+#if defined(__mips) && defined(__LP64__)
+#define GEMMLOWP_MIPS_64
+#endif
+
+#if defined(GEMMLOWP_MIPS_32) || defined(GEMMLOWP_MIPS_64)
+#define GEMMLOWP_MIPS
+#endif
+
+// Detect x86, 32-bit or 64-bit
+#if defined(__i386__) || defined(_M_IX86) || defined(_X86_) || defined(__i386)
+#define GEMMLOWP_X86_32
+#endif
+
+#if defined(__x86_64__) || defined(_M_X64) || defined(__amd64)
+#define GEMMLOWP_X86_64
+#endif
+
+#if defined(GEMMLOWP_X86_32) || defined(GEMMLOWP_X86_64)
+#define GEMMLOWP_X86
+#endif
+
+// Some of our optimized paths use inline assembly and for
+// now we don't bother enabling some other optimized paths using intrinddics
+// where we can't use inline assembly paths.
+#ifdef GEMMLOWP_ALLOW_INLINE_ASM
+
+// Detect NEON. It's important to check for both tokens.
+#if (defined __ARM_NEON) || (defined __ARM_NEON__)
+#define GEMMLOWP_NEON
+#endif
+
+// Convenience NEON tokens for 32-bit or 64-bit
+#if defined(GEMMLOWP_NEON) && defined(GEMMLOWP_ARM_32)
+#define GEMMLOWP_NEON_32
+#endif
+
+#if defined(GEMMLOWP_NEON) && defined(GEMMLOWP_ARM_64)
+#define GEMMLOWP_NEON_64
+#endif
+
+// Detect MIPS MSA.
+// Limit MSA optimizations to little-endian CPUs for now.
+// TODO: Perhaps, eventually support MSA optimizations on big-endian CPUs?
+#if defined(GEMMLOWP_MIPS) && (__mips_isa_rev >= 5) && defined(__mips_msa) && \
+    defined(__BYTE_ORDER__) && (__BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__)
+#define GEMMLOWP_MSA
+#endif
+
+// Convenience MIPS MSA tokens for 32-bit or 64-bit.
+#if defined(GEMMLOWP_MSA) && defined(GEMMLOWP_MIPS_32)
+#define GEMMLOWP_MSA_32
+#endif
+
+#if defined(GEMMLOWP_MSA) && defined(GEMMLOWP_MIPS_64)
+#define GEMMLOWP_MSA_64
+#endif
+
+// compiler define for AVX2 -D GEMMLOWP_ENABLE_AVX2
+// Detect AVX2
+#if defined(__AVX2__) && defined(GEMMLOWP_ENABLE_AVX2)
+#define GEMMLOWP_AVX2
+// Detect SSE4.
+// MSVC does not have __SSE4_1__ macro, but will enable SSE4
+// when AVX is turned on.
+#elif defined(__SSE4_1__) || (defined(_MSC_VER) && defined(__AVX__))
+#define GEMMLOWP_SSE4
+// Detect SSE3.
+#elif defined(__SSE3__)
+#define GEMMLOWP_SSE3
+#endif
+
+// Convenience SSE4 tokens for 32-bit or 64-bit
+#if defined(GEMMLOWP_SSE4) && defined(GEMMLOWP_X86_32) && \
+    !defined(GEMMLOWP_DISABLE_SSE4)
+#define GEMMLOWP_SSE4_32
+#endif
+
+#if defined(GEMMLOWP_SSE3) && defined(GEMMLOWP_X86_32)
+#define GEMMLOWP_SSE3_32
+#endif
+
+#if defined(GEMMLOWP_SSE4) && defined(GEMMLOWP_X86_64) && \
+    !defined(GEMMLOWP_DISABLE_SSE4)
+#define GEMMLOWP_SSE4_64
+#endif
+
+#if defined(GEMMLOWP_SSE3) && defined(GEMMLOWP_X86_64)
+#define GEMMLOWP_SSE3_64
+#endif
+
+#if defined(GEMMLOWP_AVX2) && defined(GEMMLOWP_X86_64)
+#define GEMMLOWP_AVX2_64
+#endif
+
+#if defined(__has_feature)
+#if __has_feature(memory_sanitizer)
+#include <sanitizer/msan_interface.h>
+#define GEMMLOWP_MARK_MEMORY_AS_INITIALIZED __msan_unpoison
+#elif __has_feature(address_sanitizer)
+#include <sanitizer/asan_interface.h>
+#define GEMMLOWP_MARK_MEMORY_AS_INITIALIZED __asan_unpoison_memory_region
+#endif
+#endif
+
+#endif  // GEMMLOWP_ALLOW_INLINE_ASM
+
+// Detect Android. Don't conflate with ARM - we care about tuning
+// for non-ARM Android devices too. This can be used in conjunction
+// with x86 to tune differently for mobile x86 CPUs (Atom) vs. desktop x86 CPUs.
+#if defined(__ANDROID__) || defined(ANDROID)
+#define GEMMLOWP_ANDROID
+#endif
+
+#endif  // GEMMLOWP_INTERNAL_DETECT_PLATFORM_H_

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/kissfft/_kiss_fft_guts.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/kissfft/_kiss_fft_guts.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,164 @@
+/*
+Copyright (c) 2003-2010, Mark Borgerding
+
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
+
+    * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
+    * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
+    * Neither the author nor the names of any contributors may be used to endorse or promote products derived from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+*/
+
+/* kiss_fft.h
+   defines kiss_fft_scalar as either short or a float type
+   and defines
+   typedef struct { kiss_fft_scalar r; kiss_fft_scalar i; }kiss_fft_cpx; */
+#include "kiss_fft.h"
+#include <limits.h>
+
+#define MAXFACTORS 32
+/* e.g. an fft of length 128 has 4 factors 
+ as far as kissfft is concerned
+ 4*4*4*2
+ */
+
+struct kiss_fft_state{
+    int nfft;
+    int inverse;
+    int factors[2*MAXFACTORS];
+    kiss_fft_cpx twiddles[1];
+};
+
+/*
+  Explanation of macros dealing with complex math:
+
+   C_MUL(m,a,b)         : m = a*b
+   C_FIXDIV( c , div )  : if a fixed point impl., c /= div. noop otherwise
+   C_SUB( res, a,b)     : res = a - b
+   C_SUBFROM( res , a)  : res -= a
+   C_ADDTO( res , a)    : res += a
+ * */
+#ifdef FIXED_POINT
+#if (FIXED_POINT==32)
+# define FRACBITS 31
+# define SAMPPROD int64_t
+#define SAMP_MAX 2147483647
+#else
+# define FRACBITS 15
+# define SAMPPROD int32_t 
+#define SAMP_MAX 32767
+#endif
+
+#define SAMP_MIN -SAMP_MAX
+
+#if defined(CHECK_OVERFLOW)
+#  define CHECK_OVERFLOW_OP(a,op,b)  \
+	if ( (SAMPPROD)(a) op (SAMPPROD)(b) > SAMP_MAX || (SAMPPROD)(a) op (SAMPPROD)(b) < SAMP_MIN ) { \
+		fprintf(stderr,"WARNING:overflow @ " __FILE__ "(%d): (%d " #op" %d) = %ld\n",__LINE__,(a),(b),(SAMPPROD)(a) op (SAMPPROD)(b) );  }
+#endif
+
+
+#   define smul(a,b) ( (SAMPPROD)(a)*(b) )
+#   define sround( x )  (kiss_fft_scalar)( ( (x) + (1<<(FRACBITS-1)) ) >> FRACBITS )
+
+#   define S_MUL(a,b) sround( smul(a,b) )
+
+#   define C_MUL(m,a,b) \
+      do{ (m).r = sround( smul((a).r,(b).r) - smul((a).i,(b).i) ); \
+          (m).i = sround( smul((a).r,(b).i) + smul((a).i,(b).r) ); }while(0)
+
+#   define DIVSCALAR(x,k) \
+	(x) = sround( smul(  x, SAMP_MAX/k ) )
+
+#   define C_FIXDIV(c,div) \
+	do {    DIVSCALAR( (c).r , div);  \
+		DIVSCALAR( (c).i  , div); }while (0)
+
+#   define C_MULBYSCALAR( c, s ) \
+    do{ (c).r =  sround( smul( (c).r , s ) ) ;\
+        (c).i =  sround( smul( (c).i , s ) ) ; }while(0)
+
+#else  /* not FIXED_POINT*/
+
+#   define S_MUL(a,b) ( (a)*(b) )
+#define C_MUL(m,a,b) \
+    do{ (m).r = (a).r*(b).r - (a).i*(b).i;\
+        (m).i = (a).r*(b).i + (a).i*(b).r; }while(0)
+#   define C_FIXDIV(c,div) /* NOOP */
+#   define C_MULBYSCALAR( c, s ) \
+    do{ (c).r *= (s);\
+        (c).i *= (s); }while(0)
+#endif
+
+#ifndef CHECK_OVERFLOW_OP
+#  define CHECK_OVERFLOW_OP(a,op,b) /* noop */
+#endif
+
+#define  C_ADD( res, a,b)\
+    do { \
+	    CHECK_OVERFLOW_OP((a).r,+,(b).r)\
+	    CHECK_OVERFLOW_OP((a).i,+,(b).i)\
+	    (res).r=(a).r+(b).r;  (res).i=(a).i+(b).i; \
+    }while(0)
+#define  C_SUB( res, a,b)\
+    do { \
+	    CHECK_OVERFLOW_OP((a).r,-,(b).r)\
+	    CHECK_OVERFLOW_OP((a).i,-,(b).i)\
+	    (res).r=(a).r-(b).r;  (res).i=(a).i-(b).i; \
+    }while(0)
+#define C_ADDTO( res , a)\
+    do { \
+	    CHECK_OVERFLOW_OP((res).r,+,(a).r)\
+	    CHECK_OVERFLOW_OP((res).i,+,(a).i)\
+	    (res).r += (a).r;  (res).i += (a).i;\
+    }while(0)
+
+#define C_SUBFROM( res , a)\
+    do {\
+	    CHECK_OVERFLOW_OP((res).r,-,(a).r)\
+	    CHECK_OVERFLOW_OP((res).i,-,(a).i)\
+	    (res).r -= (a).r;  (res).i -= (a).i; \
+    }while(0)
+
+
+#ifdef FIXED_POINT
+#  define KISS_FFT_COS(phase)  floor(.5+SAMP_MAX * cos (phase))
+#  define KISS_FFT_SIN(phase)  floor(.5+SAMP_MAX * sin (phase))
+#  define HALF_OF(x) ((x)>>1)
+#elif defined(USE_SIMD)
+#  define KISS_FFT_COS(phase) _mm_set1_ps( cos(phase) )
+#  define KISS_FFT_SIN(phase) _mm_set1_ps( sin(phase) )
+#  define HALF_OF(x) ((x)*_mm_set1_ps(.5))
+#else
+#  define KISS_FFT_COS(phase) (kiss_fft_scalar) cos(phase)
+#  define KISS_FFT_SIN(phase) (kiss_fft_scalar) sin(phase)
+#  define HALF_OF(x) ((x)*.5)
+#endif
+
+#define  kf_cexp(x,phase) \
+	do{ \
+		(x)->r = KISS_FFT_COS(phase);\
+		(x)->i = KISS_FFT_SIN(phase);\
+	}while(0)
+
+
+/* a debugging function */
+#define pcpx(c)\
+    fprintf(stderr,"%g + %gi\n",(double)((c)->r),(double)((c)->i) )
+
+
+#ifdef KISS_FFT_USE_ALLOCA
+// define this to allow use of alloca instead of malloc for temporary buffers
+// Temporary buffers are used in two case: 
+// 1. FFT sizes that have "bad" factors. i.e. not 2,3 and 5
+// 2. "in-place" FFTs.  Notice the quotes, since kissfft does not really do an in-place transform.
+#include <alloca.h>
+#define  KISS_FFT_TMP_ALLOC(nbytes) alloca(nbytes)
+#define  KISS_FFT_TMP_FREE(ptr) 
+#else
+#define  KISS_FFT_TMP_ALLOC(nbytes) KISS_FFT_MALLOC(nbytes)
+#define  KISS_FFT_TMP_FREE(ptr) KISS_FFT_FREE(ptr)
+#endif

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/kissfft/kiss_fft.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/kissfft/kiss_fft.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,130 @@
+#ifndef KISS_FFT_H
+#define KISS_FFT_H
+
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+#include <string.h>
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/*
+ ATTENTION!
+ If you would like a :
+ -- a utility that will handle the caching of fft objects
+ -- real-only (no imaginary time component ) FFT
+ -- a multi-dimensional FFT
+ -- a command-line utility to perform ffts
+ -- a command-line utility to perform fast-convolution filtering
+
+ Then see kfc.h kiss_fftr.h kiss_fftnd.h fftutil.c kiss_fastfir.c
+  in the tools/ directory.
+*/
+
+#ifdef USE_SIMD
+# include <xmmintrin.h>
+# define kiss_fft_scalar __m128
+#define KISS_FFT_MALLOC(nbytes) _mm_malloc(nbytes,16)
+#define KISS_FFT_FREE _mm_free
+#else	
+#define KISS_FFT_MALLOC(X) (void*)(0) /* Patched. */
+#define KISS_FFT_FREE(X) /* Patched. */
+#endif	
+
+
+// Patched automatically by download_dependencies.sh so default is 16 bit.
+#ifndef FIXED_POINT
+#define FIXED_POINT (16)
+#endif
+// End patch.
+
+#ifdef FIXED_POINT
+#include <sys/types.h>	
+# if (FIXED_POINT == 32)
+#  define kiss_fft_scalar int32_t
+# else	
+#  define kiss_fft_scalar int16_t
+# endif
+#else
+# ifndef kiss_fft_scalar
+/*  default is float */
+#   define kiss_fft_scalar float
+# endif
+#endif
+
+typedef struct {
+    kiss_fft_scalar r;
+    kiss_fft_scalar i;
+}kiss_fft_cpx;
+
+typedef struct kiss_fft_state* kiss_fft_cfg;
+
+/* 
+ *  kiss_fft_alloc
+ *  
+ *  Initialize a FFT (or IFFT) algorithm's cfg/state buffer.
+ *
+ *  typical usage:      kiss_fft_cfg mycfg=kiss_fft_alloc(1024,0,NULL,NULL);
+ *
+ *  The return value from fft_alloc is a cfg buffer used internally
+ *  by the fft routine or NULL.
+ *
+ *  If lenmem is NULL, then kiss_fft_alloc will allocate a cfg buffer using malloc.
+ *  The returned value should be free()d when done to avoid memory leaks.
+ *  
+ *  The state can be placed in a user supplied buffer 'mem':
+ *  If lenmem is not NULL and mem is not NULL and *lenmem is large enough,
+ *      then the function places the cfg in mem and the size used in *lenmem
+ *      and returns mem.
+ *  
+ *  If lenmem is not NULL and ( mem is NULL or *lenmem is not large enough),
+ *      then the function returns NULL and places the minimum cfg 
+ *      buffer size in *lenmem.
+ * */
+
+kiss_fft_cfg kiss_fft_alloc(int nfft,int inverse_fft,void * mem,size_t * lenmem); 
+
+/*
+ * kiss_fft(cfg,in_out_buf)
+ *
+ * Perform an FFT on a complex input buffer.
+ * for a forward FFT,
+ * fin should be  f[0] , f[1] , ... ,f[nfft-1]
+ * fout will be   F[0] , F[1] , ... ,F[nfft-1]
+ * Note that each element is complex and can be accessed like
+    f[k].r and f[k].i
+ * */
+void kiss_fft(kiss_fft_cfg cfg,const kiss_fft_cpx *fin,kiss_fft_cpx *fout);
+
+/*
+ A more generic version of the above function. It reads its input from every Nth sample.
+ * */
+void kiss_fft_stride(kiss_fft_cfg cfg,const kiss_fft_cpx *fin,kiss_fft_cpx *fout,int fin_stride);
+
+/* If kiss_fft_alloc allocated a buffer, it is one contiguous 
+   buffer and can be simply free()d when no longer needed*/
+#define kiss_fft_free free
+
+/*
+ Cleans up some memory that gets managed internally. Not necessary to call, but it might clean up 
+ your compiler output to call this before you exit.
+*/
+void kiss_fft_cleanup(void);
+	
+
+/*
+ * Returns the smallest integer k, such that k>=n and k has only "fast" factors (2,3,5)
+ */
+int kiss_fft_next_fast_size(int n);
+
+/* for real ffts, we need an even size */
+#define kiss_fftr_next_fast_size_real(n) \
+        (kiss_fft_next_fast_size( ((n)+1)>>1)<<1)
+
+#ifdef __cplusplus
+} 
+#endif
+
+#endif

diff -r 000000000000 -r 49cb9a5a60f3 MNIST_example/third_party/kissfft/tools/kiss_fftr.h
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MNIST_example/third_party/kissfft/tools/kiss_fftr.h	Wed Apr 15 07:09:26 2020 +0000
@@ -0,0 +1,46 @@
+#ifndef KISS_FTR_H
+#define KISS_FTR_H
+
+#include "kiss_fft.h"
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+    
+/* 
+ 
+ Real optimized version can save about 45% cpu time vs. complex fft of a real seq.
+
+ 
+ 
+ */
+
+typedef struct kiss_fftr_state *kiss_fftr_cfg;
+
+
+kiss_fftr_cfg kiss_fftr_alloc(int nfft,int inverse_fft,void * mem, size_t * lenmem);
+/*
+ nfft must be even
+
+ If you don't care to allocate space, use mem = lenmem = NULL 
+*/
+
+
+void kiss_fftr(kiss_fftr_cfg cfg,const kiss_fft_scalar *timedata,kiss_fft_cpx *freqdata);
+/*
+ input timedata has nfft scalar points
+ output freqdata has nfft/2+1 complex points
+*/
+
+void kiss_fftri(kiss_fftr_cfg cfg,const kiss_fft_cpx *freqdata,kiss_fft_scalar *timedata);
+/*
+ input freqdata has  nfft/2+1 complex points
+ output timedata has nfft scalar points
+*/
+
+#define kiss_fftr_free free
+
+#ifdef __cplusplus
+}
+#endif
+#endif