src/core/CL/kernels/CLWinogradInputTransformKernel.cpp - ml/ComputeLibrary - Gitiles

 /*
  * Copyright (c) 2018-2020 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 "src/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.h"
 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
 #include "src/core/AccessWindowStatic.h"
 #include "src/core/CL/CLValidate.h"
 #include "src/core/helpers/AutoConfiguration.h"
 #include "src/core/helpers/WindowHelpers.h"
 #include "support/StringSupport.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, DataType::F16);
     ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);

     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(!cl_winograd_convolution_layer_supported(output_tile_size, kernel_size, input->data_layout()), "Winograd input transform not supported");

     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);

     bool   window_changed = false;
     Window win            = calculate_max_window(*input, Steps(1, 1));

     if(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;

         unsigned int num_elems_read_per_iteration_x = output_tile_size.width + kernel_size.width - 1;
         unsigned int num_elems_read_per_iteration_y = output_tile_size.height + kernel_size.height - 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);
         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), _data_layout(DataLayout::UNKNOWN), _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)
 {
     configure(CLKernelLibrary::get().get_compile_context(), input, output, winograd_info);
 }

 void CLWinogradInputTransformKernel::configure(const CLCompileContext &compile_context, 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));

     auto padding_info = get_padding_info({ 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;

     _data_layout = input->info()->data_layout();

     const size_t idx_w = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
     const size_t idx_h = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);

     // Compute number of elements to process in the X and Y direction
     const int num_elements_x = input->info()->dimension(idx_w) - (kernel_size.width - 1) + conv_info.pad_left() + conv_info.pad_right();
     const int num_elements_y = input->info()->dimension(idx_h) - (kernel_size.height - 1) + conv_info.pad_top() + conv_info.pad_bottom();

     if(_data_layout == DataLayout::NCHW)
     {
         // Check if we need to extend the right or bottom border
         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);

         _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());
     }
     else
     {
         _border_size = BorderSize();
     }

     // Compute the number of output tiles along the x and y direction of size "output_tile_size"
     const Size2D num_tiles = compute_winograd_convolution_tiles(Size2D(input->info()->dimension(idx_w), input->info()->dimension(idx_h)),
                                                                 kernel_size,
                                                                 output_tile_size,
                                                                 conv_info);

     _input       = input;
     _output      = output;
     _num_tiles_x = num_tiles.width;
     _num_tiles_y = num_tiles.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)));
     const size_t total_batches = input->info()->tensor_shape().total_size_upper(3);

     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()));
     build_opts.add_option("-DOUTPUT_TILE_W=" + support::cpp11::to_string(output_tile_size.width));
     build_opts.add_option("-DOUTPUT_TILE_H=" + support::cpp11::to_string(output_tile_size.height));
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
     build_opts.add_option_if(winograd_info.kernel_size.height == 1, "-DWINOGRAD_INPUT_TRANSFORM_HORIZONTAL");
     build_opts.add_option_if(winograd_info.kernel_size.width == 1, "-DWINOGRAD_INPUT_TRANSFORM_VERTICAL");
     if(_data_layout == DataLayout::NHWC)
     {
         build_opts.add_option_if(total_batches > 1, "-DNUM_TILES_Y=" + support::cpp11::to_string(_num_tiles_y));
         build_opts.add_option("-DSRC_DIM_1=" + support::cpp11::to_string(_input->info()->dimension(1)));
         build_opts.add_option("-DSRC_DIM_2=" + support::cpp11::to_string(_input->info()->dimension(2)));
     }
     else
     {
         build_opts.add_option_if(total_batches > 1, "-DSRC_DEPTH=" + support::cpp11::to_string(_input->info()->dimension(2)));
     }

     // Create kernel
     std::string kernel_name = "winograd_input_transform_" + output_tile_size.to_string() + "_" + kernel_size.to_string();

     // Get the maximum dimension from the tile size
     const unsigned int tile_max_dim = std::max(output_tile_size.width, output_tile_size.height);

     // Check optimized kernel if output_dims == 2x2
     if((tile_max_dim == 2) && (_data_layout == DataLayout::NCHW))
     {
         _step_z = (_input->info()->dimension(2) % 2) != 0 ? 1 : 2;
     }

     // Append stepz and data layout
     kernel_name += "_stepz";
     kernel_name += support::cpp11::to_string(_step_z);
     kernel_name += "_" + lower_string(string_from_data_layout(_data_layout));

     _kernel = create_kernel(compile_context, 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_internal(win_config.second, cl::NDRange(1, 1, 8));

     ARM_COMPUTE_ERROR_ON((input->info()->data_layout() == DataLayout::NHWC) && has_padding_changed(padding_info));

     _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());
     _config_id += "_";
     _config_id += lower_string(string_from_data_layout(_data_layout));
 }

 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);

     const size_t idx_w         = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
     const size_t idx_h         = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
     const size_t idx_c         = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL);
     const size_t total_batches = window.shape().total_size_upper(3);

     // Collapse window
     Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);

     Window slice = window_collapsed.first_slice_window_3D();
     slice.set(idx_w, Window::Dimension(0, _num_tiles_x, 1));
     slice.set(idx_h, Window::Dimension(0, _num_tiles_y, 1));
     if(_data_layout == DataLayout::NHWC)
     {
         slice.set(idx_h, Window::Dimension(0, _num_tiles_y * total_batches, 1));
     }

     ARM_COMPUTE_ERROR_ON(((slice[idx_c].end() - slice[idx_c].start()) % _step_z) != 0);
     slice.set(idx_c, Window::Dimension(slice[idx_c].start(), slice[idx_c].end(), _step_z));

     unsigned int idx = 2 * num_arguments_per_3D_tensor();
     _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input->info()->strides_in_bytes()[3]));
     _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[3]));

     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_collapsed.slide_window_slice_3D(slice));
 }
	/*
	* Copyright (c) 2018-2020 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 "src/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.h"
	#include "arm_compute/core/utils/misc/ShapeCalculator.h"
	#include "src/core/AccessWindowStatic.h"
	#include "src/core/CL/CLValidate.h"
	#include "src/core/helpers/AutoConfiguration.h"
	#include "src/core/helpers/WindowHelpers.h"
	#include "support/StringSupport.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, DataType::F16);
	ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);

	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(!cl_winograd_convolution_layer_supported(output_tile_size, kernel_size, input->data_layout()), "Winograd input transform not supported");

	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);

	bool window_changed = false;
	Window win = calculate_max_window(*input, Steps(1, 1));

	if(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;

	unsigned int num_elems_read_per_iteration_x = output_tile_size.width + kernel_size.width - 1;
	unsigned int num_elems_read_per_iteration_y = output_tile_size.height + kernel_size.height - 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);
	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), _data_layout(DataLayout::UNKNOWN), _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)
	{
	configure(CLKernelLibrary::get().get_compile_context(), input, output, winograd_info);
	}

	void CLWinogradInputTransformKernel::configure(const CLCompileContext &compile_context, 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));

	auto padding_info = get_padding_info({ 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;

	_data_layout = input->info()->data_layout();

	const size_t idx_w = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
	const size_t idx_h = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);

	// Compute number of elements to process in the X and Y direction
	const int num_elements_x = input->info()->dimension(idx_w) - (kernel_size.width - 1) + conv_info.pad_left() + conv_info.pad_right();
	const int num_elements_y = input->info()->dimension(idx_h) - (kernel_size.height - 1) + conv_info.pad_top() + conv_info.pad_bottom();

	if(_data_layout == DataLayout::NCHW)
	{
	// Check if we need to extend the right or bottom border
	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);

	_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());
	}
	else
	{
	_border_size = BorderSize();
	}

	// Compute the number of output tiles along the x and y direction of size "output_tile_size"
	const Size2D num_tiles = compute_winograd_convolution_tiles(Size2D(input->info()->dimension(idx_w), input->info()->dimension(idx_h)),
	kernel_size,
	output_tile_size,
	conv_info);

	_input = input;
	_output = output;
	_num_tiles_x = num_tiles.width;
	_num_tiles_y = num_tiles.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)));
	const size_t total_batches = input->info()->tensor_shape().total_size_upper(3);

	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()));
	build_opts.add_option("-DOUTPUT_TILE_W=" + support::cpp11::to_string(output_tile_size.width));
	build_opts.add_option("-DOUTPUT_TILE_H=" + support::cpp11::to_string(output_tile_size.height));
	build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
	build_opts.add_option_if(winograd_info.kernel_size.height == 1, "-DWINOGRAD_INPUT_TRANSFORM_HORIZONTAL");
	build_opts.add_option_if(winograd_info.kernel_size.width == 1, "-DWINOGRAD_INPUT_TRANSFORM_VERTICAL");
	if(_data_layout == DataLayout::NHWC)
	{
	build_opts.add_option_if(total_batches > 1, "-DNUM_TILES_Y=" + support::cpp11::to_string(_num_tiles_y));
	build_opts.add_option("-DSRC_DIM_1=" + support::cpp11::to_string(_input->info()->dimension(1)));
	build_opts.add_option("-DSRC_DIM_2=" + support::cpp11::to_string(_input->info()->dimension(2)));
	}
	else
	{
	build_opts.add_option_if(total_batches > 1, "-DSRC_DEPTH=" + support::cpp11::to_string(_input->info()->dimension(2)));
	}

	// Create kernel
	std::string kernel_name = "winograd_input_transform_" + output_tile_size.to_string() + "_" + kernel_size.to_string();

	// Get the maximum dimension from the tile size
	const unsigned int tile_max_dim = std::max(output_tile_size.width, output_tile_size.height);

	// Check optimized kernel if output_dims == 2x2
	if((tile_max_dim == 2) && (_data_layout == DataLayout::NCHW))
	{
	_step_z = (_input->info()->dimension(2) % 2) != 0 ? 1 : 2;
	}

	// Append stepz and data layout
	kernel_name += "_stepz";
	kernel_name += support::cpp11::to_string(_step_z);
	kernel_name += "_" + lower_string(string_from_data_layout(_data_layout));

	_kernel = create_kernel(compile_context, 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_internal(win_config.second, cl::NDRange(1, 1, 8));

	ARM_COMPUTE_ERROR_ON((input->info()->data_layout() == DataLayout::NHWC) && has_padding_changed(padding_info));

	_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());
	_config_id += "_";
	_config_id += lower_string(string_from_data_layout(_data_layout));
	}

	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);

	const size_t idx_w = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
	const size_t idx_h = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
	const size_t idx_c = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL);
	const size_t total_batches = window.shape().total_size_upper(3);

	// Collapse window
	Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);

	Window slice = window_collapsed.first_slice_window_3D();
	slice.set(idx_w, Window::Dimension(0, _num_tiles_x, 1));
	slice.set(idx_h, Window::Dimension(0, _num_tiles_y, 1));
	if(_data_layout == DataLayout::NHWC)
	{
	slice.set(idx_h, Window::Dimension(0, _num_tiles_y * total_batches, 1));
	}

	ARM_COMPUTE_ERROR_ON(((slice[idx_c].end() - slice[idx_c].start()) % _step_z) != 0);
	slice.set(idx_c, Window::Dimension(slice[idx_c].start(), slice[idx_c].end(), _step_z));

	unsigned int idx = 2 * num_arguments_per_3D_tensor();
	_kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input->info()->strides_in_bytes()[3]));
	_kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[3]));

	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_collapsed.slide_window_slice_3D(slice));
	}