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/* 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 THIRD_PARTY_TENSORFLOW_CONTRIB_LITE_BUILTIN_OP_DATA_H_
#define THIRD_PARTY_TENSORFLOW_CONTRIB_LITE_BUILTIN_OP_DATA_H_

#include <stdint.h>

#ifdef __cplusplus
extern "C" {
#endif  // __cplusplus

// TODO(aselle): Consider using "if this then that" for testing.

// Possible padding types (for convolutions)
typedef enum {
  kTfLitePaddingUnknown = 0,
  kTfLitePaddingSame,
  kTfLitePaddingValid,
} TfLitePadding;

typedef struct {
  int width;
  int height;
} TfLitePaddingValues;

// Possible fused activation functions.
// TODO(aselle): rename to TfLiteActivation
typedef enum {
  kTfLiteActNone = 0,
  kTfLiteActRelu,
  kTfLiteActRelu1,
  kTfLiteActRelu6,
  kTfLiteActTanh,
  kTfLiteActSignBit,
  kTfLiteActSigmoid,
} TfLiteFusedActivation;

typedef struct {
  TfLitePadding padding;
  int stride_width;
  int stride_height;
  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 {
  TfLitePadding padding;
  int stride_width;
  int stride_height;
  int depth_multiplier;
  TfLiteFusedActivation activation;
} TfLiteDepthwiseConvParams;

typedef struct {
  int rank;
  TfLiteFusedActivation activation;
} TfLiteSVDFParams;

typedef struct {
  TfLiteFusedActivation activation;
} TfLiteRNNParams;

typedef struct { TfLiteFusedActivation activation; } 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 {
  TfLiteFusedActivation activation;
} TfLiteMulParams;

typedef struct {
  TfLiteFusedActivation activation;
} TfLiteL2NormParams;

typedef struct {
  int radius;
  float bias;
  float alpha;
  float beta;
} TfLiteLocalResponseNormParams;

typedef struct {
  TfLiteFusedActivation activation;
  float cell_clip;
  float proj_clip;
} TfLiteLSTMParams;

typedef struct {
  int new_height;
  int new_width;
} TfLiteResizeBilinearParams;

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 before_padding[8];
  int after_padding[8];
  int num_dimensions;
} TfLitePadParams;

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 enum {
  kTfLiteCombinerTypeSum = 0,
  kTfLiteCombinerTypeMean = 1,
  kTfLiteCombinerTypeSqrtn = 2,
} TfLiteCombinerType;

typedef struct {
  TfLiteCombinerType combiner;
} TfLiteEmbeddingLookupSparseParams;

#ifdef __cplusplus
}  // extern "C"
#endif  // __cplusplus

#endif  // THIRD_PARTY_TENSORFLOW_CONTRIB_LITE_BUILTIN_OP_DATA_H_