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>
diff --git a/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp b/src/core/CL/kernels/CLWinogradOutputTransformKernel.cpp
new file mode 100644
index 0000000..c982327
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+++ 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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