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/*
* Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
* Copyright 2017 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_GATHER_H__
#define __NNFW_CKER_GATHER_H__
#include "cker/Shape.h"
#include "cker/Types.h"
#include "cker/Utils.h"
namespace nnfw
{
namespace cker
{
template <typename T, typename CoordsT = int32_t>
inline void Gather(const GatherParams &op_params, const Shape &input_shape, const T *input_data,
const Shape &coords_shape, const CoordsT *coords_data, const Shape &,
T *output_data)
{
int axis = op_params.axis;
if (axis < 0)
{
axis += input_shape.DimensionsCount();
}
assert(axis >= 0);
assert(axis < input_shape.DimensionsCount());
const int axis_size = input_shape.Dims(axis);
const int coords_count = coords_shape.FlatSize();
int outer_size = 1;
for (int i = 0; i < axis; ++i)
{
outer_size *= input_shape.Dims(i);
}
int inner_size = 1;
for (int i = axis + 1; i < input_shape.DimensionsCount(); ++i)
{
inner_size *= input_shape.Dims(i);
}
for (int outer = 0; outer < outer_size; ++outer)
{
for (int i = 0; i < coords_count; ++i)
{
assert(coords_data[i] >= 0);
assert(coords_data[i] < axis_size);
std::memcpy(output_data + (outer * coords_count + i) * inner_size,
input_data + (outer * axis_size + coords_data[i]) * inner_size,
sizeof(T) * inner_size);
}
}
}
} // namespace cker
} // namespace nnfw
#endif // __NNFW_CKER_GATHER_H__
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