TensorContext.cpp

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/*
 * Copyright (c) 2019 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 "nnkit/support/tf/TensorContext.h"
#include "nnkit/support/tftestinfo/ParsedTensor.h"
 
#include <nncc/core/ADT/tensor/LexicalLayout.h>
#include <nncc/core/ADT/tensor/Overlay.h>
 
namespace nnkit
{
namespace support
{
namespace tf
{
 
using nnkit::support::tftestinfo::ParsedTensor;
 
void TensorContext::getMutableFloatTensor(uint32_t n,
                                          const nnkit::TensorContext::TypedAccessor<float> &f)
{ // for input
  using nncc::core::ADT::tensor::LexicalLayout;
  using nncc::core::ADT::tensor::make_overlay;
 
  const ParsedTensor *parsed_tensor = _tensors.at(n).get();
  float *data = reinterpret_cast<float *>(_data_map.data(parsed_tensor));
  auto overlay = make_overlay<float, LexicalLayout>(shape(n), data);
 
  f(*this, n, overlay);
}
 
void TensorContext::getConstFloatTensor(uint32_t n,
                                        const nnkit::TensorContext::TypedReader<float> &f) const
{ // for output
  using nncc::core::ADT::tensor::LexicalLayout;
  using nncc::core::ADT::tensor::make_overlay;
 
  const ParsedTensor *parsed_tensor = _tensors.at(n).get();
  float *data = reinterpret_cast<float *>(_data_map.data(parsed_tensor));
  auto overlay = make_overlay<float, LexicalLayout>(shape(n), data);
 
  f(*this, n, overlay);
}
 
} // namespace tf
} // namespace support
} // namespace nnkit