From a046e164b96a8441b2fa14ef578f7db46a0e97da Mon Sep 17 00:00:00 2001 From: Michele Di Giorgio Date: Tue, 8 Oct 2019 09:36:26 +0100 Subject: COMPMID-2600: Implement a new and generic depthwise convolution for CL QASYMM8 NHWC The NCHW case is supported at function level by permuting the inputs/outputs to NHWC. This patch also removes CLDirectConvolutionLayerOutputStageKernel which is deprecated and some kernels which were only used in the generic case of depthwise convolution. Change-Id: I91e0f02d0a2f4a4a352e08c248e648944137fe68 Signed-off-by: Michele Di Giorgio Reviewed-on: https://review.mlplatform.org/c/2056 Reviewed-by: Giorgio Arena Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins Reviewed-by: Gian Marco Iodice --- .../CL/kernels/CLDepthwiseVectorToTensorKernel.cpp | 125 --------------------- 1 file changed, 125 deletions(-) delete mode 100644 src/core/CL/kernels/CLDepthwiseVectorToTensorKernel.cpp (limited to 'src/core/CL/kernels/CLDepthwiseVectorToTensorKernel.cpp') diff --git a/src/core/CL/kernels/CLDepthwiseVectorToTensorKernel.cpp b/src/core/CL/kernels/CLDepthwiseVectorToTensorKernel.cpp deleted file mode 100644 index 0f029fda74..0000000000 --- a/src/core/CL/kernels/CLDepthwiseVectorToTensorKernel.cpp +++ /dev/null @@ -1,125 +0,0 @@ -/* - * Copyright (c) 2017-2019 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/CLDepthwiseVectorToTensorKernel.h" - -#include "arm_compute/core/CL/CLHelpers.h" -#include "arm_compute/core/CL/CLKernelLibrary.h" -#include "arm_compute/core/CL/CLValidate.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; -using namespace arm_compute::misc::shape_calculator; - -namespace -{ -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, size_t conv_w, size_t conv_h) -{ - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::S32, DataType::F16, DataType::F32); - - if(output->total_size() != 0) - { - TensorShape output_shape = compute_vector_to_tensor_output_shape(input->tensor_shape(), conv_w, conv_h, output->data_layout()); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output); - } - - return Status{}; -} -} // namespace - -CLDepthwiseVectorToTensorKernel::CLDepthwiseVectorToTensorKernel() - : _input(nullptr), _output(nullptr) -{ -} - -void CLDepthwiseVectorToTensorKernel::configure(const ICLTensor *input, ICLTensor *output, size_t conv_w, size_t conv_h) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - - // Output auto inizialitation if not yet initialized - TensorShape output_shape = compute_vector_to_tensor_output_shape(input->info()->tensor_shape(), conv_w, conv_h, output->info()->data_layout()); - auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape)); - - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), conv_w, conv_h)); - - _input = input; - _output = output; - - // Create kernel - CLBuildOptions build_opts; - build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); - build_opts.add_option("-DCONV_WIDTH=" + support::cpp11::to_string(conv_w)); - build_opts.add_option("-DCONV_HEIGHT=" + support::cpp11::to_string(conv_h)); - build_opts.add_option("-D" + string_from_data_layout(output->info()->data_layout())); - - _kernel = static_cast(CLKernelLibrary::get().create_kernel("depthwise_vector_to_tensor", build_opts.options())); - - // Configure kernel window - Window win = calculate_max_window(*input->info(), Steps()); - // The CLDepthwisevectorToTensorKernel doesn't need padding so update_window_and_padding() can be skipped - output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape())); - - ICLKernel::configure_internal(win); -} - -Status CLDepthwiseVectorToTensorKernel::validate(const ITensorInfo *input, const ITensorInfo *output, size_t conv_w, size_t conv_h) -{ - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, conv_w, conv_h)); - return Status{}; -} - -void CLDepthwiseVectorToTensorKernel::run(const Window &window, cl::CommandQueue &queue) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(ICLKernel::window(), window); - - Window slice = window.first_slice_window_1D(); - Window slice_out = window.first_slice_window_3D(); - - // Setup slice - slice.set(Window::DimX, Window::Dimension(0, _input->info()->dimension(0), 1)); - - // Setup output slice - // The first three dimensions of the output are increased by the inner loops - slice_out.set(Window::DimX, Window::Dimension(0, 0, 0)); - slice_out.set(Window::DimY, Window::Dimension(0, 0, 0)); - slice_out.set(Window::DimZ, Window::Dimension(0, 0, 0)); - - do - { - unsigned int idx = 0; - add_1D_tensor_argument(idx, _input, slice); - add_3D_tensor_argument(idx, _output, slice_out); - enqueue(queue, *this, slice, lws_hint()); - } - while(window.slide_window_slice_1D(slice) && window.slide_window_slice_3D(slice_out)); -} -- cgit v1.2.1