FullyConnectedLayer.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_FULLYCONNECTEDLAYER_H__
#define __ONERT_BACKEND_TRAIN_OPS_FULLYCONNECTEDLAYER_H__
 
#include "../ExternalContext.h"
#include "../Tensor.h"
 
#include <exec/train/ITrainableFunction.h>
#include <ops/FullyConnectedLayer.h>
 
namespace onert
{
namespace backend
{
namespace train
{
namespace ops
{
 
class FullyConnectedLayer : public exec::train::ITrainableFunction,
                            public cpu::ops::FullyConnectedLayer
{
public:
  FullyConnectedLayer();
  ~FullyConnectedLayer();
 
public:
  void configureBackward(const IPortableTensor *input, const IPortableTensor *weights,
                         IPortableTensor *output, IPortableTensor *back_prop_input,
                         IPortableTensor *grad_weights, IPortableTensor *grad_bias,
                         const IPortableTensor *back_prop_output, ir::Activation activation,
                         ir::FullyConnectedWeightsFormat weights_format);
 
  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 Optimize memory
  std::unique_ptr<Tensor> _transposed_weights;
  std::unique_ptr<Tensor> _transposed_input;
  std::unique_ptr<Tensor> _transposed_back_prop_output;
  std::unique_ptr<Tensor> _act_back_prop_output;
};
 
} // namespace ops
} // namespace train
} // namespace backend
} // namespace onert
 
#endif // __ONERT_BACKEND_TRAIN_OPS_FULLYCONNECTEDLAYER_H__