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/*
* Copyright (c) 2019-2020 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "DepthToSpaceLayer.h"
#include "tests/validation/Helpers.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace reference
{
// Batch to Space
template <typename T>
SimpleTensor<T> depth_to_space(const SimpleTensor<T> &src, const TensorShape &dst_shape, int32_t block_shape)
{
ARM_COMPUTE_ERROR_ON(block_shape <= 0);
SimpleTensor<T> result(dst_shape, src.data_type());
const auto width_in = static_cast<int>(src.shape()[0]);
const auto height_in = static_cast<int>(src.shape()[1]);
const auto channel_in = static_cast<int>(src.shape()[2]);
const auto batch_in = static_cast<int>(src.shape()[3]);
const int r = channel_in / (block_shape * block_shape);
#if defined(_OPENMP)
#pragma omp parallel for collapse(4)
#endif /* _OPENMP */
for(int b = 0; b < batch_in; ++b)
{
for(int z = 0; z < channel_in; ++z)
{
for(int y = 0; y < height_in; ++y)
{
for(int x = 0; x < width_in; ++x)
{
const int out_x = (block_shape * x + (z / r) % block_shape);
const int out_y = (block_shape * y + (z / r) / block_shape);
const int out_pos = out_x + dst_shape[0] * out_y + (z % r) * dst_shape[0] * dst_shape[1] + b * dst_shape[0] * dst_shape[1] * dst_shape[2];
const int in_pos = x + width_in * y + z * width_in * height_in + b * width_in * height_in * channel_in;
result[out_pos] = src[in_pos];
}
}
}
}
return result;
}
template SimpleTensor<float> depth_to_space(const SimpleTensor<float> &src, const TensorShape &dst_shape, int32_t block_shape);
template SimpleTensor<half> depth_to_space(const SimpleTensor<half> &src, const TensorShape &dst_shape, int32_t block_shape);
} // namespace reference
} // namespace validation
} // namespace test
} // namespace arm_compute
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