From d2fab7315bac3a586f2f1b1c8d64f2441f89ca64 Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Fri, 2 Mar 2018 11:18:12 +0000 Subject: COMPMID-935 - Implementing Convolution with Winograd on OpenCL (part 4) Implemented Winograd Output Transform (2x2,3x3) on OpenCL Implemented CLWinogradConvolutionLayer on OpenCL Change-Id: I6a113fc5f052ca07f878d2b800d2ab003f84af65 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/125148 Reviewed-by: Georgios Pinitas Tested-by: Jenkins --- src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp | 21 ++- src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp | 7 +- .../CL/kernels/CLWinogradFilterTransformKernel.cpp | 2 +- .../CL/kernels/CLWinogradInputTransformKernel.cpp | 7 +- .../CL/kernels/CLWinogradOutputTransformKernel.cpp | 188 +++++++++++++++++++++ 5 files changed, 211 insertions(+), 14 deletions(-) create mode 100644 src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp (limited to 'src/core/CL/kernels') diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp index 9c69800928..7b785bb8da 100644 --- a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp +++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp @@ -55,6 +55,7 @@ inline Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *i ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, input1); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->num_dimensions() > 3, "The number of dimensions for the matrix B must be <= 3"); if(!is_interleaved_transposed) { @@ -174,7 +175,7 @@ inline std::pair validate_and_configure_window(ITensorInfo *inpu } // namespace CLGEMMMatrixMultiplyKernel::CLGEMMMatrixMultiplyKernel() - : _input0(nullptr), _input1(nullptr), _output(nullptr) + : _input0(nullptr), _input1(nullptr), _output(nullptr), _slide_matrix_b(true) { } @@ -192,9 +193,10 @@ void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTen // Perform validate step ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info(), is_interleaved_transposed, reshape_info)); - _input0 = input0; - _input1 = input1; - _output = output; + _input0 = input0; + _input1 = input1; + _output = output; + _slide_matrix_b = _input1->info()->num_dimensions() >= _input0->info()->num_dimensions(); const DataType data_type = input0->info()->data_type(); const int fp_pos = input0->info()->fixed_point_position(); @@ -257,6 +259,9 @@ void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTen "-DALPHA=" + float_to_string_with_full_precision(alpha)); } + // Do not slide matrix B if _slide_matrix_b = false + build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(input1->info()->dimension(2))); + std::string kernel_name; if(is_interleaved_transposed) { @@ -365,7 +370,7 @@ void CLGEMMMatrixMultiplyKernel::run(const Window &window, cl::CommandQueue &que Window slice_b = slice; // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2 // This scenario can happen when the matrix multiplication is used to perform a convolution operation - if(_input1->info()->num_dimensions() < 3) + if(!_slide_matrix_b) { slice_b = slice_matrix_b; } @@ -374,9 +379,9 @@ void CLGEMMMatrixMultiplyKernel::run(const Window &window, cl::CommandQueue &que add_2D_tensor_argument(idx, _input0, slice); add_2D_tensor_argument(idx, _input1, slice_b); add_2D_tensor_argument(idx, _output, slice); - _kernel.setArg(idx++, static_cast(_input0->info()->strides_in_bytes()[3])); - _kernel.setArg(idx++, static_cast(_input1->info()->strides_in_bytes()[3])); - _kernel.setArg(idx++, static_cast(_output->info()->strides_in_bytes()[3])); + _kernel.setArg(idx++, static_cast(_input0->info()->strides_in_bytes()[2])); + _kernel.setArg(idx++, static_cast(_input1->info()->strides_in_bytes()[2])); + _kernel.setArg(idx++, static_cast(_output->info()->strides_in_bytes()[2])); enqueue(queue, *this, slice, _lws_hint); } while(window.slide_window_slice_3D(slice)); diff --git a/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp b/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp index 5489fde818..f69a39e4ad 100644 --- a/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp +++ b/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp @@ -76,15 +76,18 @@ std::pair validate_and_configure_window(ITensorInfo *input, ITen } AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); - window_changed = window_changed || update_window_and_padding(win, input_access); // Configure window in case of configured output if(output->total_size() != 0) { AccessWindowTranspose output_access(output, 0, 0, num_elems_processed_per_iteration, 1, scale_x, 1.f / scale_x); - window_changed = window_changed || update_window_and_padding(win, output_access); + window_changed = window_changed || update_window_and_padding(win, input_access, output_access); output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), input->tensor_shape())); } + else + { + window_changed = window_changed || update_window_and_padding(win, input_access); + } // Collapse along the Z direction Window collapsed = win.collapse(win, Window::DimZ); diff --git a/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp b/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp index 3dbbe157b2..655b82bf66 100644 --- a/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp +++ b/src/core/CL/kernels/CLWinogradFilterTransformKernel.cpp @@ -76,7 +76,7 @@ std::pair validate_and_configure_window(ITensorInfo *input, ITen AccessWindowRectangle input_access(input, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y); AccessWindowStatic output_access(output, 0, 0, output->dimension(0), output->dimension(1)); window_changed = update_window_and_padding(win, input_access, output_access); - output_access.set_valid_region(win, input->valid_region()); + output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->tensor_shape())); Window win_collapsed = win.collapse(win, Window::DimZ); diff --git a/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp b/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp index 72adb5f358..3b9350f9ba 100644 --- a/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp +++ b/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp @@ -44,11 +44,11 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c ARM_COMPUTE_RETURN_ERROR_ON_MSG(kernel_dims.width != 3 || kernel_dims.height != 3, "Winograd input transform only supports 3x3 kernels"); ARM_COMPUTE_UNUSED(kernel_dims); - const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*input, conv_info, Size2D(3U, 3U)); - // Validate configured output if(output->total_size() != 0) { + const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*input, conv_info, kernel_dims); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); } @@ -151,7 +151,8 @@ void CLWinogradInputTransformKernel::configure(const ICLTensor *input, ICLTensor Status CLWinogradInputTransformKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const PadStrideInfo &conv_info, const Size2D &kernel_dims) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_RETURN_ERROR_ON(validate_arguments(input, output, conv_info, kernel_dims)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, conv_info, kernel_dims)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), conv_info, kernel_dims).first); return Status{}; } diff --git a/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp b/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp new file mode 100644 index 0000000000..c9823275eb --- /dev/null +++ b/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp @@ -0,0 +1,188 @@ +/* + * Copyright (c) 2018 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 "arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h" + +#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" +#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 "support/ToolchainSupport.h" + +#include + +using namespace arm_compute; +using namespace arm_compute::misc::shape_calculator; + +namespace +{ +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const Size2D &kernel_dims, const Size2D &output_convolved_dims, const Size2D &num_tiles) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(1) != num_tiles.area()); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(kernel_dims.width != 3 || kernel_dims.height != 3, "Only 3x3 kernels are supported"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(static_cast(std::sqrt(input->dimension(2))) != 4, "Only 2x2 output tile is supported"); + ARM_COMPUTE_UNUSED(kernel_dims); + + 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, output_convolved_dims, DataLayout::NCHW)); + + 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) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + + 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; + + AccessWindowRectangle input_access(input, 0, 0, num_elems_processed_per_iteration, num_elems_processed_per_iteration); + AccessWindowStatic output_access(output, 0, 0, ceil_to_multiple(output->dimension(0), 2), ceil_to_multiple(output->dimension(1), 2)); + + if(bias != nullptr) + { + AccessWindowStatic bias_access(bias, 0, 0, bias->dimension(0), bias->dimension(1)); + window_changed = update_window_and_padding(win, input_access, bias_access, output_access); + } + else + { + window_changed = update_window_and_padding(win, input_access, output_access); + } + output->set_valid_region(ValidRegion(Coordinates(), output->tensor_shape())); + + 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) +{ +} + +void CLWinogradOutputTransformKernel::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const Size2D &kernel_dims, const Size2D &output_convolved_dims, + const Size2D &num_tiles) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_UNUSED(kernel_dims); + + // 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(), output_convolved_dims, DataLayout::NCHW))); + + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias != nullptr ? bias->info() : nullptr), output->info(), kernel_dims, output_convolved_dims, num_tiles)); + + _input = input; + _bias = bias; + _output = output; + + // 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.width)); + + // Create kernel + _kernel = static_cast(CLKernelLibrary::get().create_kernel("winograd_output_transform_2x2_3x3_nchw", build_opts.options())); + + // Configure kernel window + auto win_config = validate_and_configure_window(input->info(), (bias != nullptr ? bias->info() : nullptr), output->info()); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure(win_config.second); + + // Set config_id for enabling LWS tuning + _config_id = "winograd_output_transform_2x2_3x3"; + _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)); +} + +Status CLWinogradOutputTransformKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const Size2D &kernel_dims, const Size2D &output_convolved_dims, + const Size2D &num_tiles) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, (bias != nullptr ? bias->clone().get() : nullptr), output, kernel_dims, output_convolved_dims, num_tiles)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), (bias != nullptr ? bias->clone().get() : nullptr), output->clone().get()).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); + + // Get initial windows + Window slice = window.first_slice_window_3D(); + 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_3D_tensor(); + Window slice_biases; + slice_biases.use_tensor_dimensions(_bias->info()->tensor_shape()); + add_1D_tensor_argument(idx1, _bias, slice_biases); + } + + do + { + unsigned int idx = 0; + add_3D_tensor_argument(idx, _input, slice); + add_3D_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)); +} \ No newline at end of file -- cgit v1.2.1