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author | Gian Marco Iodice <gianmarco.iodice@arm.com> | 2018-03-02 11:18:12 +0000 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:49:16 +0000 |
commit | d2fab7315bac3a586f2f1b1c8d64f2441f89ca64 (patch) | |
tree | 33572f0fea29d24546850f3835703f9869726122 /src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp | |
parent | 27c08abe6947b1ee5b266799f2bb2bf0a05d0def (diff) | |
download | ComputeLibrary-d2fab7315bac3a586f2f1b1c8d64f2441f89ca64.tar.gz |
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 <georgios.pinitas@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp')
-rw-r--r-- | src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp | 188 |
1 files changed, 188 insertions, 0 deletions
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 <cmath> + +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<unsigned int>(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<Status, Window> 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<cl::Kernel>(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)); +}
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