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/*
* Copyright (c) 2017-2018 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 "arm_compute/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.h"
#include "arm_compute/core/CL/CLHelpers.h"
#include "arm_compute/core/CL/CLKernelLibrary.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
using namespace arm_compute;
CLDeconvolutionLayerUpsampleKernel::CLDeconvolutionLayerUpsampleKernel()
: _input(nullptr), _output(nullptr), _inner_border(), _info()
{
}
Status CLDeconvolutionLayerUpsampleKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const BorderSize &inner_border,
const PadStrideInfo &info)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(0) == 0);
ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(1) == 0);
ARM_COMPUTE_RETURN_ERROR_ON(!info.padding_is_symmetric());
for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i)
{
ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(i) != output->dimension(i));
}
ARM_COMPUTE_RETURN_ERROR_ON_MSG(inner_border.right > info.stride().first - 1, "inner_border_right must be smaller that stride_x");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(inner_border.top > info.stride().second - 1, "inner_border_top must be smaller that stride_y");
return Status{};
}
void CLDeconvolutionLayerUpsampleKernel::configure(const ICLTensor *input, ICLTensor *output, const BorderSize &inner_border,
const PadStrideInfo &info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
_input = input;
_output = output;
_inner_border = inner_border;
_info = info;
// Perform validation step
ARM_COMPUTE_ERROR_THROW_ON(CLDeconvolutionLayerUpsampleKernel::validate(input->info(), output->info(), inner_border, info));
// Create kernel
CLBuildOptions build_opts;
build_opts.add_option(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())));
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("deconvolution_upsample", build_opts.options()));
constexpr unsigned int num_elems_processed_per_iteration = 1;
// Configure kernel window
Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration));
AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape()));
ICLKernel::configure(win);
}
void CLDeconvolutionLayerUpsampleKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
const int out_start_x = _info.pad().first;
const int out_end_x = _output->info()->dimension(0) - _inner_border.right - _info.pad().first + _info.stride().first - 1;
const int out_step_x = _info.stride().first;
const int out_start_y = _inner_border.top + _info.pad().second;
const int out_end_y = _output->info()->dimension(1) - _info.pad().second + _info.stride().second - 1;
const int out_step_y = _info.stride().second;
Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
Window slice_out = collapsed.first_slice_window_3D();
slice_out.set(Window::DimX, Window::Dimension(out_start_x, out_end_x, out_step_x));
slice_out.set(Window::DimY, Window::Dimension(out_start_y, out_end_y, out_step_y));
Window slice_in = collapsed.first_slice_window_3D();
do
{
unsigned int idx = 0;
add_3D_tensor_argument(idx, _input, slice_in);
add_3D_tensor_argument(idx, _output, slice_out);
enqueue(queue, *this, slice_out);
}
while(collapsed.slide_window_slice_3D(slice_in) && collapsed.slide_window_slice_3D(slice_out));
}
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