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author | Giorgio Arena <gioare01@e108627-lin.cambridge.arm.com> | 2018-03-01 11:13:45 +0000 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:49:16 +0000 |
commit | 1f9ca1d7737846c74053d68ee0844b448bae298b (patch) | |
tree | c8f8c6850b59899a01efcde3b0a2e294af40c5b5 /src/core/CL/kernels/CLWinogradInputTransformKernel.cpp | |
parent | a9676118fd2a0e5bc916969af83ecee049bae76b (diff) | |
download | ComputeLibrary-1f9ca1d7737846c74053d68ee0844b448bae298b.tar.gz |
COMPMID-935 Implementing Convolution with Winograd on OpenCL (part 3)
Change-Id: I51f92f30602fb0a02314f344fa67061f448694bf
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/122793
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Diffstat (limited to 'src/core/CL/kernels/CLWinogradInputTransformKernel.cpp')
-rw-r--r-- | src/core/CL/kernels/CLWinogradInputTransformKernel.cpp | 180 |
1 files changed, 180 insertions, 0 deletions
diff --git a/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp b/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp new file mode 100644 index 0000000000..72adb5f358 --- /dev/null +++ b/src/core/CL/kernels/CLWinogradInputTransformKernel.cpp @@ -0,0 +1,180 @@ +/* + * 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/CLWinogradInputTransformKernel.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/CL/OpenCL.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "support/ToolchainSupport.h" + +using namespace arm_compute; + +namespace +{ +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const PadStrideInfo &conv_info, const Size2D &kernel_dims) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); + 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_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) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + } + + return Status{}; +} + +std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, const PadStrideInfo &conv_info, const Size2D &kernel_dims) +{ + ARM_COMPUTE_UNUSED(output); + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_ERROR_ON(kernel_dims.width != 3 || kernel_dims.height != 3); + ARM_COMPUTE_UNUSED(kernel_dims); + + constexpr unsigned int num_elems_read_per_iteration_x = 4u; + constexpr unsigned int num_elems_read_per_iteration_y = 4u; + + Window win = calculate_max_window(*input, Steps(1, 1)); + + AccessWindowRectangle input_access(input, -conv_info.pad_left(), -conv_info.pad_top(), num_elems_read_per_iteration_x, num_elems_read_per_iteration_y); + + bool window_changed = update_window_and_padding(win, input_access); + + Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; + return std::make_pair(err, win); +} +} // namespace + +CLWinogradInputTransformKernel::CLWinogradInputTransformKernel() + : _border_size(0), _input(nullptr), _output(nullptr), _num_tiles_x(0), _num_tiles_y(0), _step_z(1) +{ +} + +BorderSize CLWinogradInputTransformKernel::border_size() const +{ + return _border_size; +} + +void CLWinogradInputTransformKernel::configure(const ICLTensor *input, ICLTensor *output, const PadStrideInfo &conv_info, const Size2D &kernel_dims) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), conv_info, kernel_dims)); + + // Compute number of elements to process in the X and Y direction + const int num_elements_x = input->info()->dimension(0) - 2 + conv_info.pad_left() + conv_info.pad_right(); + const int num_elements_y = input->info()->dimension(1) - 2 + conv_info.pad_top() + conv_info.pad_bottom(); + + // Check if we need to extend the right or bottom border + const unsigned int extra_border_right = (num_elements_x % 2 == 0) ? 0u : 1u; + const unsigned int extra_border_bottom = (num_elements_y % 2 == 0) ? 0u : 1u; + + _input = input; + _output = output; + _border_size = BorderSize(conv_info.pad_top(), conv_info.pad_right() + extra_border_right, conv_info.pad_bottom() + extra_border_bottom, conv_info.pad_left()); + _num_tiles_x = std::ceil(num_elements_x / 2.0f); + _num_tiles_y = std::ceil(num_elements_y / 2.0f); + + const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*input->info(), conv_info, Size2D(3U, 3U)); + + // Output auto inizialitation if not yet initialized + auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape)); + + ARM_COMPUTE_ERROR_ON(_num_tiles_x * _num_tiles_y != static_cast<int>(output->info()->dimension(1))); + + CLBuildOptions build_opts; + 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())); + + // Create kernel + if((_input->info()->dimension(2) % 2) != 0) + { + _step_z = 1; + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("winograd_input_transform_2x2_3x3_stepz1_nchw", build_opts.options())); + } + else + { + _step_z = 2; + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("winograd_input_transform_2x2_3x3_stepz2_nchw", build_opts.options())); + _lws_hint = cl::NDRange(1, 1, 8); + } + + // Create window and update padding + auto win_config = validate_and_configure_window(input->info(), output->info(), conv_info, kernel_dims); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure(win_config.second); + + _config_id = "winograd_transform_input_2x2_3x3_"; + _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(input->info()->dimension(2)); + _config_id += "_"; + _config_id += support::cpp11::to_string(conv_info.pad_left()); + _config_id += "_"; + _config_id += support::cpp11::to_string(conv_info.pad_top()); +} + +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)); + + return Status{}; +} + +void CLWinogradInputTransformKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); + + Window slice = window.first_slice_window_3D(); + slice.set(Window::DimX, Window::Dimension(0, _num_tiles_x, 1)); + slice.set(Window::DimY, Window::Dimension(0, _num_tiles_y, 1)); + + ARM_COMPUTE_ERROR_ON(((slice.z().end() - slice.z().start()) % _step_z) != 0); + slice.set(Window::DimZ, Window::Dimension(slice.z().start(), slice.z().end(), _step_z)); + + do + { + unsigned int idx = 0; + add_3D_tensor_argument(idx, _input, slice); + add_3D_tensor_argument(idx, _output, slice); + + enqueue(queue, *this, slice, _lws_hint); + } + while(window.slide_window_slice_3D(slice)); +} |