Convert.cpp

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/*
 * Copyright (c) 2018 Samsung Electronics Co., Ltd. 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 "Convert.h"
 
namespace tflchef
{
 
tflchef::TensorType as_tflchef_type(const tflite::TensorType type)
{
  switch (type)
  {
    case tflite::TensorType_FLOAT32:
      return tflchef::FLOAT32;
    case tflite::TensorType_INT32:
      return tflchef::INT32;
    case tflite::TensorType_INT64:
      return tflchef::INT64;
    case tflite::TensorType_UINT8:
      return tflchef::UINT8;
    case tflite::TensorType_BOOL:
      return tflchef::BOOL;
    case tflite::TensorType_INT8:
      return tflchef::INT8;
    case tflite::TensorType_INT16:
      return tflchef::INT16;
    case tflite::TensorType_FLOAT16:
      return tflchef::FLOAT16;
    // TODO handle other types
    // TensorType_STRING
    // TensorType_COMPLEX64
    default:
      throw std::runtime_error{"unsupported tensor type"};
  }
}
 
tflchef::Activation as_tflchef_activation(const tflite::ActivationFunctionType type)
{
  switch (type)
  {
    case tflite::ActivationFunctionType_NONE:
      return tflchef::NONE;
    case tflite::ActivationFunctionType_RELU:
      return tflchef::RELU;
    case tflite::ActivationFunctionType_RELU_N1_TO_1:
      return tflchef::RELU_N1_TO_1;
    case tflite::ActivationFunctionType_RELU6:
      return tflchef::RELU6;
    case tflite::ActivationFunctionType_TANH:
      return tflchef::TANH;
    case tflite::ActivationFunctionType_SIGN_BIT:
      return tflchef::SIGN_BIT;
    default:
      throw std::runtime_error{"unsupported activation type"};
  }
}
 
tflchef::Padding as_tflchef_padding(const tflite::Padding padding)
{
  switch (padding)
  {
    case tflite::Padding_SAME:
      return tflchef::SAME;
    case tflite::Padding_VALID:
      return tflchef::VALID;
    default:
      throw std::runtime_error{"unsupported padding"};
  }
}
 
tflchef::MirrorPadMode as_tflchef_mirrorpadmode(const tflite::MirrorPadMode mode)
{
  switch (mode)
  {
    case tflite::MirrorPadMode_REFLECT:
      return tflchef::REFLECT;
    case tflite::MirrorPadMode_SYMMETRIC:
      return tflchef::SYMMETRIC;
    default:
      throw std::runtime_error{"Unknown mirrorpad mode"};
  }
}
 
tflchef::DimensionType as_tflchef_sparse_dim_type(const tflite::DimensionType type)
{
  switch (type)
  {
    case tflite::DimensionType_DENSE:
      return tflchef::DimensionType::DENSE;
    case tflite::DimensionType_SPARSE_CSR:
      return tflchef::DimensionType::SPARSE_CSR;
    default:
      throw std::runtime_error("unsupported sparse dimension type");
  }
}
 
tflchef::SparseIndexVecType as_tflchef_sparse_idx_vec_type(const tflite::SparseIndexVector type)
{
  switch (type)
  {
    case tflite::SparseIndexVector_NONE:
      return tflchef::SparseIndexVecType::SparseIdxVecType_NONE;
    case tflite::SparseIndexVector_Int32Vector:
      return tflchef::SparseIndexVecType::INT32VEC;
    case tflite::SparseIndexVector_Uint16Vector:
      return tflchef::SparseIndexVecType::UINT16VEC;
    case tflite::SparseIndexVector_Uint8Vector:
      return tflchef::SparseIndexVecType::UINT8VEC;
    default:
      throw std::runtime_error("unsupported sparse index vector type");
  }
}
 
} // namespace tflchef