From c6f4ec377027b21a67061efd21b65609079f98f9 Mon Sep 17 00:00:00 2001 From: Manuel Bottini Date: Tue, 18 May 2021 18:41:56 +0100 Subject: Port CLWinogradConvolutionLayer with ClWinogradConv2d Port CLWinogradInputTransformKernel Port CLWinogradFilterTransformKernel Port CLWinogradOutputTransformKernel Resolves: COMPMID-4504 Change-Id: I3177dda0b9c2f56b36cb317027e94abe8d47229e Signed-off-by: Manuel Bottini Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5680 Reviewed-by: Georgios Pinitas Tested-by: Arm Jenkins Comments-Addressed: Arm Jenkins --- .../CL/kernels/CLWinogradFilterTransformKernel.cpp | 155 ------------ .../CL/kernels/CLWinogradFilterTransformKernel.h | 115 --------- .../CL/kernels/CLWinogradInputTransformKernel.cpp | 275 --------------------- .../CL/kernels/CLWinogradInputTransformKernel.h | 121 --------- .../CL/kernels/CLWinogradOutputTransformKernel.cpp | 267 -------------------- .../CL/kernels/CLWinogradOutputTransformKernel.h | 127 ---------- 6 files changed, 1060 deletions(-) delete mode 100644 src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp delete mode 100644 src/core/CL/kernels/CLWinogradFilterTransformKernel.h delete mode 100644 src/core/CL/kernels/CLWinogradInputTransformKernel.cpp delete mode 100644 src/core/CL/kernels/CLWinogradInputTransformKernel.h delete mode 100644 src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp delete mode 100644 src/core/CL/kernels/CLWinogradOutputTransformKernel.h (limited to 'src/core/CL/kernels') diff --git a/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp b/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp deleted file mode 100644 index 138f4cf947..0000000000 --- a/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp +++ /dev/null @@ -1,155 +0,0 @@ -/* - * Copyright (c) 2018-2021 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/CLWinogradFilterTransformKernel.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/Helpers.h" -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/core/Utils.h" -#include "arm_compute/core/Validate.h" -#include "arm_compute/core/Window.h" -#include "arm_compute/core/utils/misc/ShapeCalculator.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::misc::shape_calculator; - -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 Size2D kernel_size = winograd_info.kernel_size; - const Size2D output_tile_size = winograd_info.output_tile_size; - - const size_t idx_w = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH); - const size_t idx_h = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(!cl_winograd_convolution_layer_supported(output_tile_size, kernel_size, input->data_layout()), "Winograd filter transform not supported"); - ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(idx_w) != kernel_size.width || input->dimension(idx_h) != kernel_size.height); - ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4); - - // Checks performed when output is configured - if(output->total_size() != 0) - { - const TensorInfo tensor_info_output = input->clone()->set_tensor_shape(compute_winograd_filter_transform_shape(*input, winograd_info)); - - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &tensor_info_output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - } - - return Status{}; -} - -std::pair validate_and_configure_window(ITensorInfo *input, ITensorInfo *output) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_UNUSED(output); - - const unsigned int num_elems_processed_per_iteration_x = input->data_layout() == DataLayout::NCHW ? input->dimension(0) : 1; - const unsigned int num_elems_processed_per_iteration_y = input->dimension(1); - const unsigned int num_elems_read_per_iteration_z = input->data_layout() == DataLayout::NCHW ? 1 : input->dimension(2); - - Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y, num_elems_read_per_iteration_z)); - Window win_collapsed = win.collapse(win, Window::DimZ); - return std::make_pair(Status{}, win_collapsed); -} -} // namespace - -CLWinogradFilterTransformKernel::CLWinogradFilterTransformKernel() - : _input(nullptr), _output(nullptr) -{ -} - -void CLWinogradFilterTransformKernel::configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info) -{ - configure(CLKernelLibrary::get().get_compile_context(), input, output, winograd_info); -} - -void CLWinogradFilterTransformKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - - // Output auto initialization if not yet initialized - auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_winograd_filter_transform_shape(*input->info(), winograd_info))); - - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), winograd_info)); - auto padding_info = get_padding_info({ input, output }); - - // Set build options - CLBuildOptions build_opts; - build_opts.add_option("-DSRC_DIM_Z=" + support::cpp11::to_string(input->info()->dimension(2))); - 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_FILTER_TRANSFORM_HORIZONTAL"); - build_opts.add_option_if(winograd_info.kernel_size.width == 1, "-DWINOGRAD_FILTER_TRANSFORM_VERTICAL"); - const Size2D kernel_size = winograd_info.kernel_size; - const Size2D output_tile_size = winograd_info.output_tile_size; - - // Create kernel - std::string kernel_name = "winograd_filter_transform_" + output_tile_size.to_string() + "_" + kernel_size.to_string() + "_" + lower_string(string_from_data_layout(input->info()->data_layout())); - _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); - - _input = input; - _output = output; - - // Configure kernel window - auto win_config = validate_and_configure_window(input->info(), output->info()); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - ICLKernel::configure_internal(win_config.second); - ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); -} - -Status CLWinogradFilterTransformKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info) -{ - 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()).first); - - return Status{}; -} - -void CLWinogradFilterTransformKernel::run(const Window &window, cl::CommandQueue &queue) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); - - // Setup output window - Window window_out; - window_out.use_tensor_dimensions(_output->info()->tensor_shape(), 0); - - unsigned int idx = 0; - add_4D_tensor_argument(idx, _input, window); - add_3D_tensor_argument(idx, _output, window_out); - enqueue(queue, *this, window, lws_hint()); -} -} // namespace arm_compute \ No newline at end of file diff --git a/src/core/CL/kernels/CLWinogradFilterTransformKernel.h b/src/core/CL/kernels/CLWinogradFilterTransformKernel.h deleted file mode 100644 index d22fedebcd..0000000000 --- a/src/core/CL/kernels/CLWinogradFilterTransformKernel.h +++ /dev/null @@ -1,115 +0,0 @@ -/* - * 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. - */ -#ifndef ARM_COMPUTE_CLWINOGRADFILTERTRANSFORMKERNEL_H -#define ARM_COMPUTE_CLWINOGRADFILTERTRANSFORMKERNEL_H - -#include "src/core/CL/ICLKernel.h" - -namespace arm_compute -{ -class ICLTensor; - -/** Interface for the Winograd filter transform kernel. */ -class CLWinogradFilterTransformKernel : public ICLKernel -{ -public: - /** Default constructor */ - CLWinogradFilterTransformKernel(); - /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLWinogradFilterTransformKernel(const CLWinogradFilterTransformKernel &) = delete; - /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLWinogradFilterTransformKernel &operator=(const CLWinogradFilterTransformKernel &) = delete; - /** Allow instances of this class to be moved */ - CLWinogradFilterTransformKernel(CLWinogradFilterTransformKernel &&) = default; - /** Allow instances of this class to be moved */ - CLWinogradFilterTransformKernel &operator=(CLWinogradFilterTransformKernel &&) = default; - /** Default destructor */ - ~CLWinogradFilterTransformKernel() = default; - /** Set the input and output tensor. - * - * @note Winograd filter transform supports the following configurations for NCWH data layout - * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), - * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * @note Winograd filter transform supports the following configurations for NHWC data layout - * F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * Strides: only unit strides - * - * @param[in] input Source tensor. The input is a 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] (NCHW data layout) or [IFM, kernel_x, kernel_y, OFM] (NHWC data layout). Data types supported: F16/F32. - * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_filter_transform_shape. Data types supported: Same as @p input - * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo - */ - void configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info); - /** Set the input and output tensor. - * - * @note Winograd filter transform supports the following configurations for NCWH data layout - * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), - * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * @note Winograd filter transform supports the following configurations for NHWC data layout - * F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * Strides: only unit strides - * - * @param[in] compile_context The compile context to be used. - * @param[in] input Source tensor. The input is a 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] (NCHW data layout) or [IFM, kernel_x, kernel_y, OFM] (NHWC data layout). Data types supported: F16/F32. - * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_filter_transform_shape. Data types supported: Same as @p input - * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo - */ - void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info); - /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradFilterTransformKernel - * - * @note Winograd filter transform supports the following configurations for NCWH data layout - * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), - * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * @note Winograd filter transform supports the following configurations for NHWC data layout - * F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * Strides: only unit strides - * - * @param[in] input Source tensor. The input is a 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] (NCHW data layout) or [IFM, kernel_x, kernel_y, OFM] (NHWC data layout). Data types supported: F16/F32. - * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_filter_transform_shape. Data types supported: Same as @p input - * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo - * - * @return a status - */ - static Status validate(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info); - - // Inherited methods overridden: - void run(const Window &window, cl::CommandQueue &queue) override; - -private: - const ICLTensor *_input; - ICLTensor *_output; -}; -} // namespace arm_compute -#endif /*ARM_COMPUTE_CLWINOGRADFILTERTRANSFORMKERNEL_H */ diff --git a/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp b/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp deleted file mode 100644 index 3399f47d5f..0000000000 --- a/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp +++ /dev/null @@ -1,275 +0,0 @@ -/* - * Copyright (c) 2018-2021 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 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 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(output->info()->dimension(1))); - const size_t total_batches = input->info()->tensor_shape().total_size_upper(3); - - CLBuildOptions build_opts; - if(_data_layout == DataLayout::NHWC) - { - build_opts.add_option("-DNHWC"); - build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(input->info()->dimension(idx_w))); - build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(input->info()->dimension(idx_h))); - build_opts.add_option("-DNUM_TILES_X=" + support::cpp11::to_string(_num_tiles_x)); - build_opts.add_option("-DNUM_TILES_Y=" + support::cpp11::to_string(_num_tiles_y)); - 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"); - } - else - { - 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"); - 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)); - - _border_size = BorderSize(_input->info()->padding()); - - 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); - - if(_data_layout == DataLayout::NHWC) - { - Window slice = window_collapsed.first_slice_window_3D(); - slice.set(1, Window::Dimension(0, _num_tiles_x * _num_tiles_y, 1)); - slice.set(2, Window::Dimension(0, total_batches, 1)); - - unsigned int idx = 0; - add_4D_tensor_argument(idx, _input, slice); - add_4D_tensor_argument(idx, _output, slice); - enqueue(queue, *this, slice, lws_hint()); - } - else - { - 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)); - - 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(idx++, static_cast(_input->info()->strides_in_bytes()[3])); - _kernel.setArg(idx++, static_cast(_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)); - } -} diff --git a/src/core/CL/kernels/CLWinogradInputTransformKernel.h b/src/core/CL/kernels/CLWinogradInputTransformKernel.h deleted file mode 100644 index 25301877e6..0000000000 --- a/src/core/CL/kernels/CLWinogradInputTransformKernel.h +++ /dev/null @@ -1,121 +0,0 @@ -/* - * 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. - */ -#ifndef ARM_COMPUTE_CLWINOGRADINPUTTRANSFORMKERNEL_H -#define ARM_COMPUTE_CLWINOGRADINPUTTRANSFORMKERNEL_H - -#include "src/core/CL/ICLKernel.h" - -namespace arm_compute -{ -class ICLTensor; - -/** OpenCL kernel to perform Winograd input transform.*/ -class CLWinogradInputTransformKernel : public ICLKernel -{ -public: - /** Default constructor */ - CLWinogradInputTransformKernel(); - /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLWinogradInputTransformKernel(const CLWinogradInputTransformKernel &) = delete; - /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLWinogradInputTransformKernel &operator=(const CLWinogradInputTransformKernel &) = delete; - /** Allow instances of this class to be moved */ - CLWinogradInputTransformKernel(CLWinogradInputTransformKernel &&) = default; - /** Allow instances of this class to be moved */ - CLWinogradInputTransformKernel &operator=(CLWinogradInputTransformKernel &&) = default; - /** Set the input and output of the kernel. - * - * @note Winograd input transform supports the following configurations for NCWH data layout - * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), - * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * @note Winograd input transform supports the following configurations for NHWC data layout - * F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * Strides: only unit strides - * - * @param[in] input The input tensor to transform. Data types supported: F16/F32 - * @param[in] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_transform_shape. Data types supported: Same as @p input - * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo. - */ - void configure(const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info); - /** Set the input and output of the kernel. - * - * @note Winograd input transform supports the following configurations for NCWH data layout - * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), - * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * @note Winograd input transform supports the following configurations for NHWC data layout - * F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * Strides: only unit strides - * - * @param[in] compile_context The compile context to be used. - * @param[in] input The input tensor to transform. Data types supported: F16/F32 - * @param[in] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_transform_shape. Data types supported: Same as @p input - * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo. - */ - void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info); - /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradInputTransformKernel - * - * @note Winograd input transform supports the following configurations for NCWH data layout - * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), - * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * @note Winograd input transform supports the following configurations for NHWC data layout - * F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * Strides: only unit strides - * - * @param[in] input The input tensor to transform. Data types supported: F16/F32 - * @param[in] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_input_transform_shape. Data types supported: Same as @p input - * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo. - * - * @return a status - */ - static Status validate(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info); - - // Inherited methods overridden: - void run(const Window &window, cl::CommandQueue &queue) override; - BorderSize border_size() const override; - -private: - using WinogradKey = std::pair, std::pair>; - - BorderSize _border_size; - const ICLTensor *_input; - ICLTensor *_output; - DataLayout _data_layout; - int _num_tiles_x; - int _num_tiles_y; - unsigned int _step_z; -}; -} // arm_compute -#endif /*ARM_COMPUTE_CLWINOGRADINPUTTRANSFORMKERNEL_H */ diff --git a/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp b/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp deleted file mode 100644 index 965bf9df77..0000000000 --- a/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp +++ /dev/null @@ -1,267 +0,0 @@ -/* - * Copyright (c) 2018-2021 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/CLWinogradOutputTransformKernel.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/Helpers.h" -#include "arm_compute/core/IAccessWindow.h" -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/core/Utils.h" -#include "arm_compute/core/Validate.h" -#include "arm_compute/core/Window.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" - -#include - -namespace arm_compute -{ -using namespace arm_compute::misc::shape_calculator; - -namespace -{ -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_UNUSED(act_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); - - ARM_COMPUTE_RETURN_ERROR_ON(output->data_layout() != winograd_info.output_data_layout); - - 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 Size2D input_dimensions = winograd_info.input_dimensions; - const unsigned int num_channels = (winograd_info.kernel_size.width + winograd_info.output_tile_size.width - 1) * (winograd_info.kernel_size.height + winograd_info.output_tile_size.height - 1); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(!cl_winograd_convolution_layer_supported(output_tile_size, kernel_size, winograd_info.output_data_layout), "Winograd output transform not supported"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->dimension(2) != num_channels, "Wrong number of channels"); - - // Compute number of elements to process in the X and Y direction - // 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(input_dimensions, - kernel_size, - output_tile_size, - conv_info); - - ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(1) != static_cast((num_tiles.area()))); - - if(bias != nullptr) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias); - ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(0) != bias->dimension(0)); - } - - // Checks performed when output is configured - if(output->total_size() != 0) - { - const TensorInfo tensor_info_output = input->clone()->set_tensor_shape(compute_winograd_output_transform_shape(*input, winograd_info)); - - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &tensor_info_output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - } - - return Status{}; -} - -std::pair validate_and_configure_window(ITensorInfo *input, ITensorInfo *bias, ITensorInfo *output, const Size2D &output_tile_size) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_UNUSED(bias); - - constexpr unsigned int num_elems_processed_per_iteration = 1; - - Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); - bool window_changed = false; - - if(output->data_layout() == DataLayout::NCHW) - { - const int output_static_window_end_x = ceil_to_multiple(output->dimension(0), output_tile_size.width); - const int output_static_window_end_y = ceil_to_multiple(output->dimension(1), output_tile_size.height); - - AccessWindowRectangle input_access(input, 0, 0, num_elems_processed_per_iteration, num_elems_processed_per_iteration); - AccessWindowStatic output_access(output, 0, 0, output_static_window_end_x, output_static_window_end_y); - window_changed = update_window_and_padding(win, input_access, output_access); - } - - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_pair(err, win); -} -} // namespace - -CLWinogradOutputTransformKernel::CLWinogradOutputTransformKernel() - : _input(nullptr), _bias(nullptr), _output(nullptr), _is_nhwc(false) -{ -} - -void CLWinogradOutputTransformKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info) -{ - configure(CLKernelLibrary::get().get_compile_context(), input, bias, output, winograd_info, act_info); -} - -void CLWinogradOutputTransformKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info, - const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - - // Output tensor auto initialization if not yet initialized - auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_winograd_output_transform_shape(*input->info(), winograd_info))); - - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr ? bias->info() : nullptr), output->info(), winograd_info, act_info)); - - // Configure kernel window - auto win_config = validate_and_configure_window(input->info(), (bias != nullptr ? bias->info() : nullptr), output->info(), winograd_info.output_tile_size); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - ICLKernel::configure_internal(win_config.second); - - auto padding_info = get_padding_info({ input, bias, output }); - - _input = input; - _bias = bias; - _output = output; - _is_nhwc = winograd_info.output_data_layout == DataLayout::NHWC; - - // Compute num_tiles_x - const Size2D input_dimensions = winograd_info.input_dimensions; - const Size2D kernel_size = winograd_info.kernel_size; - const Size2D output_tile_size = winograd_info.output_tile_size; - const PadStrideInfo conv_info = winograd_info.convolution_info; - const int idx_width = get_data_layout_dimension_index(winograd_info.output_data_layout, DataLayoutDimension::WIDTH); - const int idx_height = get_data_layout_dimension_index(winograd_info.output_data_layout, DataLayoutDimension::HEIGHT); - - // 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(input_dimensions, - kernel_size, - output_tile_size, - conv_info); - const size_t total_batches = output->info()->tensor_shape().total_size_upper(3); - - // Set build options - CLBuildOptions build_opts; - build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_info.activation()))); - build_opts.add_option_if(act_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(act_info.a())); - build_opts.add_option_if(act_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(act_info.b())); - - if((output_tile_size.x() == 2) || (output_tile_size.x() == 1 && output_tile_size.y() == 2)) - { - build_opts.add_option("-DVEC_SIZE=2"); - } - else if((output_tile_size.x() == 4) || (output_tile_size.x() == 1 && output_tile_size.y() == 4)) - { - build_opts.add_option("-DVEC_SIZE=4"); - } - - build_opts.add_option_if(_bias != nullptr, std::string("-DHAS_BIAS")); - build_opts.add_option("-cl-fast-relaxed-math"); - build_opts.add_option("-DN0=" + support::cpp11::to_string(win_config.second.x().step())); - build_opts.add_option("-DNUM_TILES_X=" + support::cpp11::to_string(num_tiles.width)); - 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("-DSRC_HEIGHT=" + support::cpp11::to_string(_input->info()->dimension(1))); - build_opts.add_option("-DDST_WIDTH=" + support::cpp11::to_string(_output->info()->dimension(idx_width))); - build_opts.add_option("-DDST_HEIGHT=" + support::cpp11::to_string(_output->info()->dimension(idx_height))); - build_opts.add_option_if(total_batches > 1, "-DSRC_DEPTH=" + support::cpp11::to_string(_input->info()->dimension(2))); - build_opts.add_option_if(winograd_info.kernel_size.height == 1, "-DWINOGRAD_OUTPUT_TRANSFORM_HORIZONTAL"); - build_opts.add_option_if(winograd_info.kernel_size.width == 1, "-DWINOGRAD_OUTPUT_TRANSFORM_VERTICAL"); - - // Create kernel - std::string kernel_name = "winograd_output_transform_" + output_tile_size.to_string() + "_" + kernel_size.to_string() + "_" + lower_string(string_from_data_layout(winograd_info.output_data_layout)); - _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); - - // Set config_id for enabling LWS tuning - _config_id = kernel_name; - _config_id += "_"; - _config_id += lower_string(string_from_data_type(input->info()->data_type())); - _config_id += "_"; - _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(output->info()->dimension(0)); - _config_id += "_"; - _config_id += support::cpp11::to_string(output->info()->dimension(1)); - _config_id += "_"; - _config_id += lower_string(string_from_data_layout(winograd_info.output_data_layout)); - - ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info) && _is_nhwc); -} - -Status CLWinogradOutputTransformKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info) -{ - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, (bias != nullptr ? bias->clone().get() : nullptr), output, winograd_info, act_info)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), (bias != nullptr ? bias->clone().get() : nullptr), output->clone().get(), winograd_info.output_tile_size).first); - - return Status{}; -} - -void CLWinogradOutputTransformKernel::run(const Window &window, cl::CommandQueue &queue) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); - - // Collapse window - Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); - - // Get initial windows - Window slice = window_collapsed.first_slice_window_4D(); - slice.set(Window::DimZ, Window::Dimension(0, 1, 1)); - - // Setup output slice - Window slice_out(slice); - slice_out.set(Window::DimX, Window::Dimension(0, 0, 0)); - slice_out.set(Window::DimY, Window::Dimension(0, 0, 0)); - - if(_bias != nullptr) - { - unsigned int idx1 = 2 * num_arguments_per_4D_tensor(); - Window slice_biases; - slice_biases.use_tensor_dimensions(_bias->info()->tensor_shape()); - add_1D_tensor_argument(idx1, _bias, slice_biases); - } - - if(_is_nhwc) - { - unsigned int idx2 = 2 * num_arguments_per_4D_tensor() + ((_bias != nullptr) ? num_arguments_per_1D_tensor() : 0); - _kernel.setArg(idx2, static_cast(_output->info()->total_size() - _output->info()->strides_in_bytes().y())); - } - - do - { - unsigned int idx = 0; - add_4D_tensor_argument(idx, _input, slice); - add_4D_tensor_argument(idx, _output, slice_out); - enqueue(queue, *this, slice, lws_hint()); - } - while(window.slide_window_slice_3D(slice) && window.slide_window_slice_3D(slice_out)); -} -} // namespace arm_compute diff --git a/src/core/CL/kernels/CLWinogradOutputTransformKernel.h b/src/core/CL/kernels/CLWinogradOutputTransformKernel.h deleted file mode 100644 index 632a5629d9..0000000000 --- a/src/core/CL/kernels/CLWinogradOutputTransformKernel.h +++ /dev/null @@ -1,127 +0,0 @@ -/* - * 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. - */ -#ifndef ARM_COMPUTE_CLWINOGRADOUTPUTTRANSFORMKERNEL_H -#define ARM_COMPUTE_CLWINOGRADOUTPUTTRANSFORMKERNEL_H - -#include "src/core/CL/ICLKernel.h" - -namespace arm_compute -{ -class ICLTensor; - -/** Interface for the Winograd output transform kernel. */ -class CLWinogradOutputTransformKernel : public ICLKernel -{ -public: - /** Default constructor */ - CLWinogradOutputTransformKernel(); - /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLWinogradOutputTransformKernel(const CLWinogradOutputTransformKernel &) = delete; - /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLWinogradOutputTransformKernel &operator=(const CLWinogradOutputTransformKernel &) = delete; - /** Allow instances of this class to be moved */ - CLWinogradOutputTransformKernel(CLWinogradOutputTransformKernel &&) = default; - /** Allow instances of this class to be moved */ - CLWinogradOutputTransformKernel &operator=(CLWinogradOutputTransformKernel &&) = default; - /** Default destructor */ - ~CLWinogradOutputTransformKernel() = default; - /** Set the input and output tensor. - * - * @note Winograd output transform supports the following configurations for NCWH data layout - * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), - * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * @note Winograd output transform supports the following configurations for NHWC data layout - * F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * Strides: only unit strides - * - * @param[in] input Source tensor with shape [C, N, K, batches]. Data types supported: F16/F32. - * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p input - * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_output_transform_shape. Data types supported: Same as @p input - * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. - */ - void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info = ActivationLayerInfo()); - /** Set the input and output tensor. - * - * @note Winograd output transform supports the following configurations for NCWH data layout - * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), - * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * @note Winograd output transform supports the following configurations for NHWC data layout - * F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * Strides: only unit strides - * - * @param[in] compile_context The compile context to be used. - * @param[in] input Source tensor with shape [C, N, K, batches]. Data types supported: F16/F32. - * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p input - * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_output_transform_shape. Data types supported: Same as @p input - * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. - */ - void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info, - const ActivationLayerInfo &act_info = ActivationLayerInfo()); - - /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradOutputTransformKernel - * - * @note Winograd output transform supports the following configurations for NCWH data layout - * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), - * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * @note Winograd output transform supports the following configurations for NHWC data layout - * F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), - * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) - * - * Strides: only unit strides - * - * @param[in] input Source tensor with shape [C, N, K, batches]. Data types supported: F16/F32. - * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p input - * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_output_transform_shape. Data types supported: Same as @p input - * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo - * @param[in] act_info (Optional) Activation layer information in case of a fused activation @ref ActivationLayerInfo. Only RELU, BOUNDED_RELU, LU_BOUNDED_RELU, LEAKY_RELU and SOFT_RELU supported. - * - * @return a status - */ - static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info = ActivationLayerInfo()); - - // Inherited methods overridden: - void run(const Window &window, cl::CommandQueue &queue) override; - -private: - using WinogradKey = std::pair, std::pair>; - - const ICLTensor *_input; - const ICLTensor *_bias; - ICLTensor *_output; - bool _is_nhwc; -}; -} // namespace arm_compute -#endif /*ARM_COMPUTE_CLWINOGRADOUTPUTTRANSFORMKERNEL_H */ -- cgit v1.2.1