ConvolutionLayer.h

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/*
 * Copyright (c) 2023 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.
 */
 
#ifndef __ONERT_BACKEND_TRAIN_OPS_CONVOLUTIONLAYER_H__
#define __ONERT_BACKEND_TRAIN_OPS_CONVOLUTIONLAYER_H__
 
#include <ops/ConvolutionLayer.h>
 
#include "../Tensor.h"
#include <exec/train/ITrainableFunction.h>
 
namespace onert::backend::train::ops
{
 
class ConvolutionLayer : public ::onert::exec::train::ITrainableFunction,
                         public cpu::ops::ConvolutionLayer
{
public:
  ConvolutionLayer();
  ~ConvolutionLayer();
 
  void configureBackward(const IPortableTensor *weights, IPortableTensor *back_prop_input,
                         IPortableTensor *grad_weights, IPortableTensor *grad_bias,
                         const IPortableTensor *back_prop_output, const ir::Activation activation);
  void forward(bool training) override;
  void backward() override;
 
private:
  void backwardFloat32();
 
private:
  IPortableTensor *_grad_weights;
  IPortableTensor *_grad_bias;
  IPortableTensor *_back_prop_input;
  const IPortableTensor *_back_prop_output;
 
  // TODO Consider if these tensors should be built in TensorBuilder
  std::unique_ptr<Tensor> _transposed_weights;
  std::unique_ptr<BackPropTensor> _conv_back_prop_output;
  std::unique_ptr<BackPropTensor> _act_back_prop_output;
  std::unique_ptr<GradientTensor> _transposed_grad_weights;
};
class ConvolutionLayer : public ::onert::exec::train::ITrainableFunction, {…};
 
} // namespace onert::backend::train::ops
 
#endif // __ONERT_BACKEND_TRAIN_OPS_CONVOLUTIONLAYER_H__