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/*
* Copyright (c) 2018-2019 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 "StackLayer.h"
#include "arm_compute/core/Types.h"
#include "tests/validation/Helpers.h"
#include <vector>
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace reference
{
template <typename T>
SimpleTensor<T> stack_layer(const std::vector<SimpleTensor<T>> &in, const TensorShape &output_shape, DataType data_type, unsigned int axis)
{
ARM_COMPUTE_ERROR_ON(output_shape.num_dimensions() > 5);
ARM_COMPUTE_ERROR_ON(in.size() < 2);
ARM_COMPUTE_ERROR_ON(axis > in[0].shape().num_dimensions());
SimpleTensor<T> out{ output_shape, data_type };
const int width = in[0].shape()[0];
const int height = in[0].shape()[1];
const int depth = in[0].shape()[2];
const int batch_size = in[0].shape()[3];
const int num_tensors = in.size();
// Array to store the input coordinates
// i_coordinates[0] = xi, i_coordinates[1] = yi, i_coordinates[2] = zi
// i_coordinates[3] = bi, i_coordinates[4] = i, i_coordinates[5] = 0
// i_coordinates[5] will be always zero and used for not incrementing the output when the input has less than 4 dimensions
std::array<int, 6> i_coordinates{ 0 };
// Array of pointers used to map the output coordinates to the input ones accordingly with the axis
// This array is initialized with &i_coordinates[5] since this will be always zero
std::array<int *, 5> o_coordinates = { &i_coordinates[5], &i_coordinates[5], &i_coordinates[5], &i_coordinates[5], &i_coordinates[5] };
// Set the axis coordinate
o_coordinates[axis] = &i_coordinates[4];
unsigned int k_shift = 0;
// Map the output coordinates
for(unsigned int k = 0; k < in[0].shape().num_dimensions(); ++k)
{
if(k == axis)
{
k_shift++;
}
o_coordinates[k + k_shift] = &i_coordinates[k];
}
// Use alias for the input coordinates
int &xi = i_coordinates[0];
int &yi = i_coordinates[1];
int &zi = i_coordinates[2];
int &bi = i_coordinates[3];
int &i = i_coordinates[4];
// Use alias for the output coordinates
int &xo = *(o_coordinates[0]);
int &yo = *(o_coordinates[1]);
int &zo = *(o_coordinates[2]);
int &bo = *(o_coordinates[3]);
int &wo = *(o_coordinates[4]);
// Stack tensors
for(; i < num_tensors; ++(i))
{
bi = 0;
for(; bi < batch_size; ++(bi))
{
zi = 0;
for(; zi < depth; ++(zi))
{
yi = 0;
for(; yi < height; ++(yi))
{
xi = 0;
for(; xi < width; ++(xi))
{
*(reinterpret_cast<T *>(out(Coordinates(xo, yo, zo, bo, wo)))) = *(reinterpret_cast<const T *>(in[i](Coordinates(xi, yi, zi, bi))));
}
}
}
}
}
return out;
}
template SimpleTensor<int> stack_layer(const std::vector<SimpleTensor<int>> &in, const TensorShape &output_shape, DataType data_type, unsigned int axis);
template SimpleTensor<short> stack_layer(const std::vector<SimpleTensor<short>> &in, const TensorShape &output_shape, DataType data_type, unsigned int axis);
template SimpleTensor<char> stack_layer(const std::vector<SimpleTensor<char>> &in, const TensorShape &output_shape, DataType data_type, unsigned int axis);
} // namespace reference
} // namespace validation
} // namespace test
} // namespace arm_compute