/* * 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/NEON/kernels/NEDepthwiseIm2ColKernel.h" #include "arm_compute/core/Coordinates.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/ITensor.h" #include "arm_compute/core/NEON/INEKernel.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/TensorShape.h" #include "arm_compute/core/Types.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" using namespace arm_compute; namespace { Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier, const Size2D &dilation) { ARM_COMPUTE_UNUSED(conv_info); //Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input) is not needed here as this kernel doesn't use NEON FP16 instructions. ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_asymmetric(input->data_type()) && has_bias); ARM_COMPUTE_RETURN_ERROR_ON((input->dimension(2) * depth_multiplier) != output->dimension(2)); ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(0) != (kernel_dims.width * kernel_dims.height + ((has_bias) ? 1 : 0))); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output); ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || dilation.y() < 1); return Status{}; } } // namespace template void NEDepthwiseIm2ColKernel::run_generic(const Window &window) { const int input_w = _input->info()->dimension(0); const int input_h = _input->info()->dimension(1); const int input_stride_x = _input->info()->strides_in_bytes().x(); const int input_stride_y = _input->info()->strides_in_bytes().y(); const int input_stride_z = _input->info()->strides_in_bytes().z(); const int stride_x = _conv_info.stride().first; const int stride_y = _conv_info.stride().second; const int pad_left = _conv_info.pad_left(); const int pad_right = _conv_info.pad_right(); const int pad_top = _conv_info.pad_top(); Window window_in(window); // The first three dimensions of the input are increased by the inner loops window_in.set(Window::DimX, Window::Dimension(0, 0, 0)); window_in.set(Window::DimY, Window::Dimension(0, 0, 0)); window_in.set(Window::DimZ, Window::Dimension(0, 0, 0)); // Setup output window Window window_out(window); window_out.set(Window::DimX, Window::Dimension(0, _output->info()->dimension(0), _output->info()->dimension(0))); window_out.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), 1)); window_out.set(Window::DimZ, Window::Dimension(0, _output->info()->dimension(2), 1)); Iterator in(_input, window_in); Iterator out(_output, window_out); const int full_length = input_w + pad_left + pad_right; const int max_initial_x = stride_x * (((full_length - (_kernel_dims.width + (_kernel_dims.width - 1) * (_dilation.x() - 1))) / stride_x) + 1); // Define pad value auto zero = static_cast(0); if(std::is_same::value) { zero = _input->info()->quantization_info().uniform().offset; } execute_window_loop(window_out, [&](const Coordinates & id) { const int src_pixel_linear = id.y() * stride_x; const int src_x = -pad_left + src_pixel_linear % max_initial_x; const int src_y = -pad_top + src_pixel_linear / max_initial_x * stride_y; // Get pointers const uint8_t *const input_ptr = in.ptr() + id.z() / _depth_multiplier * input_stride_z; auto output_ptr = reinterpret_cast(out.ptr()); const int height = src_y + (_kernel_dims.height + (_kernel_dims.height - 1) * (_dilation.y() - 1)); const int width = src_x + (_kernel_dims.width + (_kernel_dims.width - 1) * (_dilation.x() - 1)); for(int y = src_y; y < height; y += _dilation.y()) { for(int x = src_x; x < width; x += _dilation.x(), ++output_ptr) { if(x < 0 || x >= input_w || y < 0 || y >= input_h) { *output_ptr = zero; } else { *output_ptr = *(reinterpret_cast(input_ptr + x * input_stride_x + y * input_stride_y)); } } } if(_has_bias) { *output_ptr = static_cast(1); } }, in, out); } NEDepthwiseIm2ColKernel::NEDepthwiseIm2ColKernel() : _func(nullptr), _input(nullptr), _output(nullptr), _kernel_dims(), _conv_info(), _has_bias(), _depth_multiplier(1), _dilation() { } void NEDepthwiseIm2ColKernel::configure(const ITensor *input, ITensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier, const Size2D &dilation) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), kernel_dims, conv_info, has_bias, depth_multiplier, dilation)); _input = input; _output = output; _kernel_dims = kernel_dims; _conv_info = conv_info; _has_bias = has_bias; _depth_multiplier = depth_multiplier; _dilation = dilation; // Configure kernel window Window win = calculate_max_window(*input->info(), Steps()); // Set appropriate function to run switch(input->info()->data_type()) { case DataType::QASYMM8: _func = &NEDepthwiseIm2ColKernel::run_generic; break; case DataType::F16: _func = &NEDepthwiseIm2ColKernel::run_generic; break; case DataType::F32: _func = &NEDepthwiseIm2ColKernel::run_generic; break; default: ARM_COMPUTE_ERROR("Unsupported data type"); } // The NEDepthwiseIm2ColKernel doesn't need padding so update_window_and_padding() can be skipped output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape())); INEKernel::configure(win); } Status NEDepthwiseIm2ColKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier, const Size2D &dilation) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, kernel_dims, conv_info, has_bias, depth_multiplier, dilation)); return Status{}; } void NEDepthwiseIm2ColKernel::run(const Window &window, const ThreadInfo &info) { ARM_COMPUTE_UNUSED(info); ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); if(_func != nullptr) { (this->*_func)(window); } }