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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_COMPILER_TRAIN_TRAINING_INFO_H__
#define __ONERT_COMPILER_TRAIN_TRAINING_INFO_H__
#include "ir/Index.h"
#include "exec/train/optimizer/OptimizerCode.h"
#include "ir/operation/Loss.h"
namespace onert
{
namespace compiler
{
namespace train
{
struct LossInfo
{
ir::operation::Loss::Type type;
// TODO Add members for loss
};
struct OptimizerInfo
{
exec::train::optimizer::OptimizerCode optim_code;
float learning_rate;
// TODO Add properties
};
class TrainingInfo
{
public:
TrainingInfo() {}
TrainingInfo(const TrainingInfo &obj) = default;
TrainingInfo(TrainingInfo &&) = default;
TrainingInfo &operator=(const TrainingInfo &) = default;
TrainingInfo &operator=(TrainingInfo &&) = default;
~TrainingInfo() = default;
uint32_t batchSize() const { return _batch_size; }
void setBatchSize(const uint32_t batch_size) { _batch_size = batch_size; }
const LossInfo &lossInfo() const { return _loss_info; }
void setLossInfo(const LossInfo &loss_info) { _loss_info = loss_info; }
const OptimizerInfo &optimizerInfo() const { return _optimizer_info; }
void setOptimizerInfo(const OptimizerInfo &optimizer_info) { _optimizer_info = optimizer_info; }
private:
LossInfo _loss_info;
OptimizerInfo _optimizer_info;
uint32_t _batch_size;
};
} // namespace train
} // namespace compiler
} // namespace onert
#endif // __ONERT_COMPILER_TRAIN_TRAINING_INFO_H__
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