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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_EXEC_TRAIN_OPTIMIZER_OPTIMIZER_HELPERS_H__
#define __ONERT_EXEC_TRAIN_OPTIMIZER_OPTIMIZER_HELPERS_H__
#include "backend/IPortableTensor.h"
namespace onert
{
namespace exec
{
namespace train
{
namespace optimizer
{
template <typename T, typename L>
void elementwise(const ir::Shape &shape, const backend::ITensor &src, backend::ITensor &dst,
const L &f)
{
ShapeLoop(shape, [&](const ir::Coordinates &coords) {
const T src_val = *reinterpret_cast<const T *>(src.buffer() + src.calcOffset(coords));
T *dst_data = reinterpret_cast<T *>(dst.buffer() + dst.calcOffset(coords));
*dst_data = f(src_val, *dst_data);
});
}
} // namespace optimizer
} // namespace train
} // namespace exec
} // namespace onert
#endif // __ONERT_EXEC_TRAIN_OPTIMIZER_OPTIMIZER_HELPERS_H__
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