| /* |
| * 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/gpu/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/Cast.h" |
| #include "support/StringSupport.h" |
| |
| using namespace arm_compute::misc::shape_calculator; |
| |
| namespace arm_compute |
| { |
| namespace opencl |
| { |
| namespace kernels |
| { |
| 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<Status, Window> 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() |
| { |
| _type = CLKernelType::WINOGRAD; |
| } |
| |
| void ClWinogradFilterTransformKernel::configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *dst, const WinogradInfo &winograd_info) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); |
| |
| // Output auto initialization if not yet initialized |
| auto_init_if_empty(*dst, src->clone()->set_tensor_shape(compute_winograd_filter_transform_shape(*src, winograd_info))); |
| |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, winograd_info)); |
| auto padding_info = get_padding_info({ src, dst }); |
| |
| // Set build options |
| CLBuildOptions build_opts; |
| build_opts.add_option("-DSRC_DIM_Z=" + support::cpp11::to_string(src->dimension(2))); |
| build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(src->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(src->data_layout())); |
| _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); |
| |
| // Configure kernel window |
| auto win_config = validate_and_configure_window(src, dst); |
| 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 *src, const ITensorInfo *dst, const WinogradInfo &winograd_info) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, dst, winograd_info)); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(src->clone().get(), dst->clone().get()).first); |
| |
| return Status{}; |
| } |
| |
| void ClWinogradFilterTransformKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IClKernel::window(), window); |
| |
| auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC)); |
| auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST)); |
| |
| // Setup output window |
| Window window_out; |
| window_out.use_tensor_dimensions(dst->info()->tensor_shape(), 0); |
| |
| unsigned int idx = 0; |
| add_4D_tensor_argument(idx, src, window); |
| add_3D_tensor_argument(idx, dst, window_out); |
| enqueue(queue, *this, window, lws_hint()); |
| } |
| } // namespace kernels |
| } // namespace opencl |
| } // namespace arm_compute |