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/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
* Copyright 2018 The TensorFlow Authors. 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 __NNFW_CKER_ELEMENTWISE_H__
#define __NNFW_CKER_ELEMENTWISE_H__
#include "cker/eigen/Utils.h"
#include "cker/Shape.h"
#include "cker/Types.h"
#include <Eigen/Core>
namespace nnfw
{
namespace cker
{
inline void Sin(const Shape &input_shape, const float *input_data, const Shape &output_shape,
float *output_data)
{
const int size = MatchingFlatSize(input_shape, output_shape);
for (int i = 0; i < size; i++)
{
output_data[i] = std::sin(input_data[i]);
}
}
inline void Cos(const Shape &input_shape, const float *input_data, const Shape &output_shape,
float *output_data)
{
const int size = MatchingFlatSize(input_shape, output_shape);
for (int i = 0; i < size; i++)
{
output_data[i] = std::cos(input_data[i]);
}
}
inline void Abs(const Shape &input_shape, const float *input_data, const Shape &output_shape,
float *output_data)
{
auto input_map = MapAsVector(input_data, input_shape);
auto output_map = MapAsVector(output_data, output_shape);
output_map.array() = input_map.array().abs();
}
inline void Rsqrt(const Shape &input_shape, const float *input_data, const Shape &output_shape,
float *output_data)
{
const int size = MatchingFlatSize(input_shape, output_shape);
for (int i = 0; i < size; i++)
{
output_data[i] = 1.f / std::sqrt(input_data[i]);
}
}
inline void Neg(const Shape &input_shape, const float *input_data, const Shape &output_shape,
float *output_data)
{
const int size = MatchingFlatSize(input_shape, output_shape);
for (int i = 0; i < size; i++)
{
output_data[i] = -input_data[i];
}
}
inline void Log(const Shape &input_shape, const float *input_data, const Shape &output_shape,
float *output_data)
{
const int size = MatchingFlatSize(input_shape, output_shape);
for (int i = 0; i < size; i++)
{
output_data[i] = std::log(input_data[i]);
}
}
} // namespace cker
} // namespace nnfw
#endif // __NNFW_CKER_ELEMENTWISE_H__
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