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/*
* Copyright (c) 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/CLWinogradInputTransformKernel.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/CL/OpenCL.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "support/ToolchainSupport.h"
using namespace arm_compute;
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() != DataLayout::NCHW);
const PadStrideInfo conv_info = winograd_info.convolution_info;
const Size2D output_tile_size = winograd_info.output_tile_size;
const Size2D kernel_size = winograd_info.kernel_size;
ARM_COMPUTE_RETURN_ERROR_ON_MSG(conv_info.stride().first != 1 || conv_info.stride().second != 1, "Winograd input transform only supports unit strides");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(kernel_size != Size2D(3U, 3U) && kernel_size != Size2D(5U, 5U), "Winograd input transform only supports 3x3 and 5x5 kernels");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(kernel_size == Size2D(3U, 3U) && output_tile_size != Size2D(2U, 2U), "Winograd input transform only supports 2x2 output tile for 3x3 kernels");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(kernel_size == Size2D(5U, 5U) && output_tile_size != Size2D(4U, 4U), "Winograd input transform only supports 4x4 output tile for 5x5 kernels");
ARM_COMPUTE_UNUSED(conv_info);
ARM_COMPUTE_UNUSED(output_tile_size);
ARM_COMPUTE_UNUSED(kernel_size);
// Validate configured output
if(output->total_size() != 0)
{
const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*input, winograd_info);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
}
return Status{};
}
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const WinogradInfo &winograd_info)
{
ARM_COMPUTE_UNUSED(output);
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
const PadStrideInfo conv_info = winograd_info.convolution_info;
const Size2D output_tile_size = winograd_info.output_tile_size;
const Size2D kernel_size = winograd_info.kernel_size;
const unsigned int num_elems_read_per_iteration_x = output_tile_size.width + kernel_size.width - 1;
const unsigned int num_elems_read_per_iteration_y = output_tile_size.height + kernel_size.height - 1;
Window win = calculate_max_window(*input, Steps(1, 1));
AccessWindowRectangle input_access(input, -conv_info.pad_left(), -conv_info.pad_top(), num_elems_read_per_iteration_x, num_elems_read_per_iteration_y);
bool window_changed = update_window_and_padding(win, input_access);
Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
return std::make_pair(err, win);
}
} // namespace
CLWinogradInputTransformKernel::CLWinogradInputTransformKernel()
: _border_size(0), _input(nullptr), _output(nullptr), _num_tiles_x(0), _num_tiles_y(0), _step_z(1)
{
}
BorderSize CLWinogradInputTransformKernel::border_size() const
{
return _border_size;
}
void CLWinogradInputTransformKernel::configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), winograd_info));
const PadStrideInfo conv_info = winograd_info.convolution_info;
const Size2D output_tile_size = winograd_info.output_tile_size;
const Size2D kernel_size = winograd_info.kernel_size;
// Compute number of elements to process in the X and Y direction
const int num_elements_x = input->info()->dimension(0) - (kernel_size.width - 1) + conv_info.pad_left() + conv_info.pad_right();
const int num_elements_y = input->info()->dimension(1) - (kernel_size.height - 1) + conv_info.pad_top() + conv_info.pad_bottom();
// Check if we need to extend the right or bottom border
// FIXME: This actually is not needed. Added just for validating the result;
const unsigned int extra_border_right = ((num_elements_x % output_tile_size.width) == 0) ? 0u : static_cast<unsigned int>(output_tile_size.width - 1);
const unsigned int extra_border_bottom = ((num_elements_y % output_tile_size.height) == 0) ? 0u : static_cast<unsigned int>(output_tile_size.height - 1);
_input = input;
_output = output;
_border_size = BorderSize(conv_info.pad_top(), conv_info.pad_right() + extra_border_right, conv_info.pad_bottom() + extra_border_bottom, conv_info.pad_left());
_num_tiles_x = std::ceil(num_elements_x / static_cast<float>(output_tile_size.width));
_num_tiles_y = std::ceil(num_elements_y / static_cast<float>(output_tile_size.height));
const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*input->info(), winograd_info);
// Output auto initialization if not yet initialized
auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape));
ARM_COMPUTE_ERROR_ON(_num_tiles_x * _num_tiles_y != static_cast<int>(output->info()->dimension(1)));
CLBuildOptions build_opts;
build_opts.add_option("-DNUM_TILES_X=" + support::cpp11::to_string(_num_tiles_x));
build_opts.add_option("-DPAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left()));
build_opts.add_option("-DPAD_TOP=" + support::cpp11::to_string(conv_info.pad_top()));
// Create kernel
std::string kernel_name = "winograd_input_transform_" + output_tile_size.to_string() + "_" + kernel_size.to_string();
// Check optimized kernel if output_dims == 2x2
if(output_tile_size.width == 2 && output_tile_size.height == 2)
{
if((_input->info()->dimension(2) % 2) != 0)
{
_step_z = 1;
}
else
{
_step_z = 2;
_lws_hint = cl::NDRange(1, 1, 8);
}
}
// Append stepz and data layout
kernel_name += "_stepz";
kernel_name += support::cpp11::to_string(_step_z);
kernel_name += "_nchw";
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
// Create window and update padding
auto win_config = validate_and_configure_window(input->info(), output->info(), winograd_info);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure(win_config.second);
_config_id = kernel_name;
_config_id += support::cpp11::to_string(input->info()->dimension(0));
_config_id += "_";
_config_id += support::cpp11::to_string(input->info()->dimension(1));
_config_id += "_";
_config_id += support::cpp11::to_string(input->info()->dimension(2));
_config_id += "_";
_config_id += support::cpp11::to_string(conv_info.pad_left());
_config_id += "_";
_config_id += support::cpp11::to_string(conv_info.pad_top());
}
Status CLWinogradInputTransformKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, winograd_info));
ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), winograd_info).first);
return Status{};
}
void CLWinogradInputTransformKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
Window slice = window.first_slice_window_3D();
slice.set(Window::DimX, Window::Dimension(0, _num_tiles_x, 1));
slice.set(Window::DimY, Window::Dimension(0, _num_tiles_y, 1));
ARM_COMPUTE_ERROR_ON(((slice.z().end() - slice.z().start()) % _step_z) != 0);
slice.set(Window::DimZ, Window::Dimension(slice.z().start(), slice.z().end(), _step_z));
do
{
unsigned int idx = 0;
add_3D_tensor_argument(idx, _input, slice);
add_3D_tensor_argument(idx, _output, slice);
enqueue(queue, *this, slice, _lws_hint);
}
while(window.slide_window_slice_3D(slice));
}
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