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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 <complex>
#include "arm_compute/runtime/CL/functions/CLStackLayer.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
#include "support/ToolchainSupport.h"
using namespace arm_compute;
CLStackLayer::CLStackLayer() // NOLINT
: _input(),
_stack_kernels(),
_num_inputs(0)
{
}
void CLStackLayer::configure(const std::vector<ICLTensor *> &input, int axis, ICLTensor *output)
{
_num_inputs = input.size();
_stack_kernels = arm_compute::support::cpp14::make_unique<CLStackLayerKernel[]>(_num_inputs);
// Wrap around negative values
const unsigned int axis_u = wrap_around(axis, static_cast<int>(input[0]->info()->num_dimensions() + 1));
for(unsigned int i = 0; i < _num_inputs; i++)
{
_stack_kernels[i].configure(input[i], axis_u, i, _num_inputs, output);
}
}
Status CLStackLayer::validate(const std::vector<ITensorInfo *> &input, int axis, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
ARM_COMPUTE_RETURN_ERROR_ON(input.empty());
// Wrap around negative values
const size_t rank = input[0]->num_dimensions();
const unsigned int axis_u = wrap_around(axis, static_cast<int>(rank + 1));
const unsigned int num_inputs = input.size();
for(unsigned int i = 0; i < num_inputs; i++)
{
// All the tensors must have the same rank
ARM_COMPUTE_RETURN_ERROR_ON(input[i]->num_dimensions() != rank);
// Validate Kernel
ARM_COMPUTE_RETURN_ON_ERROR(CLStackLayerKernel::validate(input[i], axis_u, i, num_inputs, output));
}
return Status{};
}
void CLStackLayer::run()
{
for(unsigned i = 0; i < _num_inputs; i++)
{
CLScheduler::get().enqueue(_stack_kernels[i], false);
}
}
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