Port CLWinogradConvolutionLayer with ClWinogradConv2d
Port CLWinogradInputTransformKernel
Port CLWinogradFilterTransformKernel
Port CLWinogradOutputTransformKernel
Resolves: COMPMID-4504
Change-Id: I3177dda0b9c2f56b36cb317027e94abe8d47229e
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5680
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/gpu/cl/kernels/ClWinogradInputTransformKernel.cpp b/src/core/gpu/cl/kernels/ClWinogradInputTransformKernel.cpp
new file mode 100644
index 0000000..17f0eb9
--- /dev/null
+++ b/src/core/gpu/cl/kernels/ClWinogradInputTransformKernel.cpp
@@ -0,0 +1,278 @@
+/*
+ * Copyright (c) 2018-2021 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 "src/core/gpu/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.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "src/core/AccessWindowStatic.h"
+#include "src/core/CL/CLValidate.h"
+#include "src/core/helpers/AutoConfiguration.h"
+#include "src/core/helpers/WindowHelpers.h"
+#include "support/Cast.h"
+#include "support/StringSupport.h"
+
+namespace arm_compute
+{
+namespace opencl
+{
+namespace kernels
+{
+namespace
+{
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const WinogradInfo &winograd_info)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::F16);
+ ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
+
+ const PadStrideInfo conv_info = winograd_info.convolution_info;
+ 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(!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);
+
+ // Validate configured output
+ if(output->total_size() != 0)
+ {
+ const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*input, winograd_info);
+
+ 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 WinogradInfo &winograd_info)
+{
+ ARM_COMPUTE_UNUSED(output);
+ ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+
+ bool window_changed = false;
+ Window win = calculate_max_window(*input, Steps(1, 1));
+
+ if(input->data_layout() == DataLayout::NCHW)
+ {
+ const PadStrideInfo conv_info = winograd_info.convolution_info;
+ const Size2D output_tile_size = winograd_info.output_tile_size;
+ const Size2D kernel_size = winograd_info.kernel_size;
+
+ unsigned int num_elems_read_per_iteration_x = output_tile_size.width + kernel_size.width - 1;
+ unsigned int num_elems_read_per_iteration_y = output_tile_size.height + kernel_size.height - 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);
+ 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), _data_layout(DataLayout::UNKNOWN), _num_tiles_x(0), _num_tiles_y(0), _step_z(1)
+{
+}
+
+BorderSize ClWinogradInputTransformKernel::border_size() const
+{
+ return _border_size;
+}
+
+void ClWinogradInputTransformKernel::configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *dst, const WinogradInfo &winograd_info)
+{
+ ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, winograd_info));
+
+ auto padding_info = get_padding_info({ src, dst });
+
+ const PadStrideInfo conv_info = winograd_info.convolution_info;
+ const Size2D output_tile_size = winograd_info.output_tile_size;
+ const Size2D kernel_size = winograd_info.kernel_size;
+
+ _data_layout = src->data_layout();
+
+ const size_t idx_w = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
+ const size_t idx_h = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::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(src->dimension(idx_w), src->dimension(idx_h)),
+ kernel_size,
+ output_tile_size,
+ conv_info);
+
+ _num_tiles_x = num_tiles.width;
+ _num_tiles_y = num_tiles.height;
+
+ const TensorShape output_shape = misc::shape_calculator::compute_winograd_input_transform_shape(*src, winograd_info);
+
+ // Output auto initialization if not yet initialized
+ auto_init_if_empty(*dst, src->clone()->set_tensor_shape(output_shape));
+
+ ARM_COMPUTE_ERROR_ON(_num_tiles_x * _num_tiles_y != static_cast<int>(dst->dimension(1)));
+ const size_t total_batches = src->tensor_shape().total_size_upper(3);
+
+ CLBuildOptions build_opts;
+ if(_data_layout == DataLayout::NHWC)
+ {
+ build_opts.add_option("-DNHWC");
+ build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(src->dimension(idx_w)));
+ build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(src->dimension(idx_h)));
+ build_opts.add_option("-DNUM_TILES_X=" + support::cpp11::to_string(_num_tiles_x));
+ build_opts.add_option("-DNUM_TILES_Y=" + support::cpp11::to_string(_num_tiles_y));
+ 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("-DDATA_TYPE=" + get_cl_type_from_data_type(src->data_type()));
+ 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");
+ }
+ else
+ {
+ 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("-DDATA_TYPE=" + get_cl_type_from_data_type(src->data_type()));
+ 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");
+ build_opts.add_option_if(total_batches > 1, "-DSRC_DEPTH=" + support::cpp11::to_string(src->dimension(2)));
+ }
+
+ // 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((tile_max_dim == 2) && (_data_layout == DataLayout::NCHW))
+ {
+ _step_z = (src->dimension(2) % 2) != 0 ? 1 : 2;
+ }
+
+ // Append stepz and data layout
+ kernel_name += "_stepz";
+ kernel_name += support::cpp11::to_string(_step_z);
+ kernel_name += "_" + lower_string(string_from_data_layout(_data_layout));
+
+ _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
+
+ // Create window and update padding
+ auto win_config = validate_and_configure_window(src, dst, winograd_info);
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+ IClKernel::configure_internal(win_config.second, cl::NDRange(1, 1, 8));
+
+ _border_size = BorderSize(src->padding());
+
+ ARM_COMPUTE_ERROR_ON((src->data_layout() == DataLayout::NHWC) && has_padding_changed(padding_info));
+
+ _config_id = kernel_name;
+ _config_id += support::cpp11::to_string(src->dimension(0));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(src->dimension(1));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(src->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());
+ _config_id += "_";
+ _config_id += lower_string(string_from_data_layout(_data_layout));
+}
+
+Status ClWinogradInputTransformKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const WinogradInfo &winograd_info)
+{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, dst, winograd_info));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(src->clone().get(), dst->clone().get(), winograd_info).first);
+ return Status{};
+}
+
+void ClWinogradInputTransformKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
+
+ auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC));
+ auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
+
+ const size_t idx_w = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
+ const size_t idx_h = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
+ const size_t idx_c = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL);
+ const size_t total_batches = window.shape().total_size_upper(3);
+
+ // Collapse window
+ Window window_collapsed = window.collapse_if_possible(IClKernel::window(), Window::DimZ);
+
+ if(_data_layout == DataLayout::NHWC)
+ {
+ Window slice = window_collapsed.first_slice_window_3D();
+ slice.set(1, Window::Dimension(0, _num_tiles_x * _num_tiles_y, 1));
+ slice.set(2, Window::Dimension(0, total_batches, 1));
+
+ unsigned int idx = 0;
+ add_4D_tensor_argument(idx, src, slice);
+ add_4D_tensor_argument(idx, dst, slice);
+ enqueue(queue, *this, slice, lws_hint());
+ }
+ else
+ {
+ Window slice = window_collapsed.first_slice_window_3D();
+ slice.set(idx_w, Window::Dimension(0, _num_tiles_x, 1));
+ slice.set(idx_h, Window::Dimension(0, _num_tiles_y, 1));
+
+ ARM_COMPUTE_ERROR_ON(((slice[idx_c].end() - slice[idx_c].start()) % _step_z) != 0);
+ slice.set(idx_c, Window::Dimension(slice[idx_c].start(), slice[idx_c].end(), _step_z));
+
+ unsigned int idx = 2 * num_arguments_per_3D_tensor();
+ _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(src->info()->strides_in_bytes()[3]));
+ _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(dst->info()->strides_in_bytes()[3]));
+
+ do
+ {
+ unsigned int idx = 0;
+ add_3D_tensor_argument(idx, src, slice);
+ add_3D_tensor_argument(idx, dst, slice);
+
+ enqueue(queue, *this, slice, lws_hint());
+ }
+ while(window_collapsed.slide_window_slice_3D(slice));
+ }
+}
+} // namespace kernels
+} // namespace opencl
+} // namespace arm_compute
\ No newline at end of file