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author | Gian Marco Iodice <gianmarco.iodice@arm.com> | 2018-06-13 14:05:54 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:53:57 +0000 |
commit | f1c2bf0971dd1c996da149faf3dd669d566074c7 (patch) | |
tree | 802b3ce5198c3209d77fc6b603c209023fe45650 /src/core/CL/kernels | |
parent | 89a2b571cfc0ea87c26ba8b1ed1ab87d13244f0e (diff) | |
download | ComputeLibrary-f1c2bf0971dd1c996da149faf3dd669d566074c7.tar.gz |
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 <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Diffstat (limited to 'src/core/CL/kernels')
3 files changed, 49 insertions, 31 deletions
diff --git a/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp b/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp index 779df637f6..e6c713e5e7 100644 --- a/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp +++ b/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/AccessWindowStatic.h" #include "arm_compute/core/CL/CLHelpers.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" @@ -54,12 +53,7 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c 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(kernel_size != Size2D(3U, 3U) && kernel_size != Size2D(5U, 5U), "Winograd filter 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 filter 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 filter 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 filter 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 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); @@ -115,6 +109,8 @@ void CLWinogradFilterTransformKernel::configure(const ICLTensor *input, ICLTenso // 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_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; 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<float>(output_tile_size.width)); - _num_tiles_y = std::ceil(num_elements_y / static_cast<float>(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) diff --git a/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp b/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp index 980498c4d1..40d5f6588f 100644 --- a/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp +++ b/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp @@ -55,20 +55,19 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, con 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(kernel_size != Size2D(3U, 3U) && kernel_size != Size2D(5U, 5U), "Only 3x3 and 5x5 kernels are supported"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_layout() == DataLayout::NHWC && output_tile_size != Size2D(4U, 4U), "Only 4x4 output tile supported for NHWC data layout"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(kernel_size == Size2D(3U, 3U) && output_tile_size == Size2D(2U, 2U) && input->dimension(2) != 16, "Wrong number of batches"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(kernel_size == Size2D(3U, 3U) && output_tile_size == Size2D(4U, 4U) && input->dimension(2) != 36, "Wrong number of batches"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(kernel_size == Size2D(5U, 5U) && output_tile_size == Size2D(4U, 4U) && input->dimension(2) != 64, "Wrong number of batches"); + 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 - const int num_elements_x = input_dimensions.width - (kernel_size.width - 1) + conv_info.pad_left() + conv_info.pad_right(); - const int num_elements_y = input_dimensions.height - (kernel_size.height - 1) + conv_info.pad_top() + conv_info.pad_bottom(); - const int num_tiles_x = std::ceil(num_elements_x / static_cast<float>(output_tile_size.width)); - const int num_tiles_y = std::ceil(num_elements_y / static_cast<float>(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(input_dimensions, + kernel_size, + output_tile_size, + conv_info); - ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(1) != static_cast<unsigned int>((num_tiles_x * num_tiles_y))); + ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(1) != static_cast<unsigned int>((num_tiles.area()))); if(bias != nullptr) { @@ -150,13 +149,21 @@ void CLWinogradOutputTransformKernel::configure(const ICLTensor *input, const IC 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 num_elements_x = input_dimensions.width - (kernel_size.width - 1) + conv_info.pad_left() + conv_info.pad_right(); - const int num_tiles_x = std::ceil(num_elements_x / static_cast<float>(output_tile_size.width)); + + // 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); // Set build options CLBuildOptions build_opts; build_opts.add_option_if(_bias != nullptr, std::string("-DHAS_BIAS")); - build_opts.add_option("-DNUM_TILES_X=" + support::cpp11::to_string(num_tiles_x)); + 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_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)); @@ -179,6 +186,8 @@ void CLWinogradOutputTransformKernel::configure(const ICLTensor *input, const IC _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)); } Status CLWinogradOutputTransformKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const WinogradInfo &winograd_info) |