/*
 * 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__