From f1c2bf0971dd1c996da149faf3dd669d566074c7 Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Wed, 13 Jun 2018 14:05:54 +0100 Subject: COMPMID-1201 - Implementing Winograd Convolution Layer 1x3 and 3x1 kernels on OpenCL Change-Id: I39667bab49daa4da009694163274a59fd3574c73 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/137595 Tested-by: Jenkins Reviewed-by: Giorgio Arena Reviewed-by: Georgios Pinitas --- .../CL/kernels/CLWinogradInputTransformKernel.cpp | 35 +++++++++++++++------- 1 file changed, 24 insertions(+), 11 deletions(-) (limited to 'src/core/CL/kernels/CLWinogradInputTransformKernel.cpp') diff --git a/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp b/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp index 274c9e7c3d..bb484afafb 100644 --- a/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp +++ b/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp @@ -30,6 +30,7 @@ #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 "support/ToolchainSupport.h" @@ -45,12 +46,8 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c 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(input->data_layout() == DataLayout::NHWC && output_tile_size != Size2D(4U, 4U), "Winograd input transform only supports 4x4 output tile for NHWC data layout"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(kernel_size == Size2D(3U, 3U) && output_tile_size != Size2D(2U, 2U) - && output_tile_size != Size2D(4U, 4U), - "Winograd input transform only supports 2x2 or 4x4 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_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); @@ -131,8 +128,6 @@ void CLWinogradInputTransformKernel::configure(const ICLTensor *input, ICLTensor 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(); - _input = input; - _output = output; if(input->info()->data_layout() == DataLayout::NCHW) { // Check if we need to extend the right or bottom border @@ -145,8 +140,17 @@ void CLWinogradInputTransformKernel::configure(const ICLTensor *input, ICLTensor { _border_size = BorderSize(1U, 0U, 1U, 0); } - _num_tiles_x = std::ceil(num_elements_x / static_cast(output_tile_size.width)); - _num_tiles_y = std::ceil(num_elements_y / static_cast(output_tile_size.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); @@ -159,6 +163,10 @@ void CLWinogradInputTransformKernel::configure(const ICLTensor *input, ICLTensor 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_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(input->info()->data_layout() == DataLayout::NHWC) { @@ -169,8 +177,11 @@ void CLWinogradInputTransformKernel::configure(const ICLTensor *input, ICLTensor // 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(output_tile_size == Size2D(2U, 2U)) + if(tile_max_dim == 2) { _step_z = (_input->info()->dimension(2) % 2) != 0 ? 1 : 2; } @@ -199,6 +210,8 @@ void CLWinogradInputTransformKernel::configure(const ICLTensor *input, ICLTensor _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(input->info()->data_layout())); } Status CLWinogradInputTransformKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info) -- cgit v1.2.1