/* * Copyright (c) 2018-2019 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/CLCopyKernel.h" #include "arm_compute/core/AccessWindowStatic.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/Error.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Window.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" namespace arm_compute { namespace { Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const PaddingList &padding = PaddingList(), Window *output_window = nullptr) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_ERROR_ON(!padding.empty() && output_window != nullptr); ARM_COMPUTE_RETURN_ERROR_ON(padding.size() > 4); // Validate output if initialized if(output->total_size() != 0) { if(output_window == nullptr) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(misc::shape_calculator::compute_padded_shape(input->tensor_shape(), padding), output->tensor_shape()); } else { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(input->tensor_shape(), output_window->shape()); } ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); } return Status{}; } std::pair validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, Window *output_window) { // Output auto inizialitation if not yet initialized auto_init_if_empty(*output, *input); // Configure window const unsigned int vec_size_x = 16 / input->element_size(); if(output_window == nullptr) { // Create and update the window (if needed) Window win = calculate_max_window(*input, Steps(vec_size_x)); AccessWindowHorizontal input_access(input, 0, vec_size_x); AccessWindowHorizontal output_access(output, 0, vec_size_x); bool window_changed = update_window_and_padding(win, input_access, output_access); Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; return std::make_pair(err, win); } else { Window win = calculate_max_window(*input); return std::make_pair(Status{}, win); } } std::pair validate_and_configure_window_with_padding(ITensorInfo *input, ITensorInfo *output, const PaddingList &padding) { TensorShape input_shape = input->tensor_shape(); TensorShape padded_shape = misc::shape_calculator::compute_padded_shape(input_shape, padding); auto_init_if_empty(*output, input->clone()->set_tensor_shape(padded_shape)); // Configure window const unsigned int num_elems_processed_per_iteration = 16 / input->element_size(); Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); // Pad on the x dimension accounting for the padding offset along the same dimension AccessWindowHorizontal output_access(output, padding[0].first, num_elems_processed_per_iteration); AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); bool window_changed = update_window_and_padding(win, input_access, output_access); Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; return std::make_pair(err, win); } /** Generate the string "-DPAD= @p dim @p index @p padding" * * @param[in] dim The dimension index * @param[in] index Can be 0 for the start dimension and 1 for the end dimension * @param[in] padding The value to pad for that index/dimension pair * * @return The correct concatenated string */ std::string generate_pad_string(const size_t dim, const size_t index, const size_t padding) { return "-DPAD" + support::cpp11::to_string(dim) + support::cpp11::to_string(index) + "=" + support::cpp11::to_string(padding); } /** Pass the padding as build option to the kernel. * * @param[in] tensor The padded tensor * @param[in] padding The list of the padding for each dimension * @param[out] build_opts The build option to which adding the padding */ void add_padding_as_build_options(const PaddingList &padding, CLBuildOptions &build_opts) { size_t dim = 0; for(dim = 0; dim < padding.size(); dim++) { build_opts.add_option(generate_pad_string(dim, 0, padding[dim].first)); build_opts.add_option(generate_pad_string(dim, 1, padding[dim].second)); } while(dim < TensorShape::num_max_dimensions) { build_opts.add_option(generate_pad_string(dim, 0, 0)); build_opts.add_option(generate_pad_string(dim, 1, 0)); dim++; } } } // namespace CLCopyKernel::CLCopyKernel() : _input(nullptr), _output(nullptr), _output_window(), _has_output_window(false) { } void CLCopyKernel::configure(const ICLTensor *input, ICLTensor *output, const PaddingList &padding, Window *output_window) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), padding, output_window)); _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())); std::pair win_config; const unsigned int vec_size_x = 16 / input->info()->element_size(); if(padding.empty()) { // Configure window win_config = validate_and_configure_window(input->info(), output->info(), output_window); if(output_window != nullptr) { _has_output_window = true; _output_window = Window(*output_window); const int width_x = output_window->num_iterations(0); const bool multi_access_x = width_x >= static_cast(vec_size_x); const bool remainder_x = width_x % vec_size_x > 0; if(multi_access_x) { _output_window.set(Window::DimX, Window::Dimension(output_window->x().start(), ceil_to_multiple(output_window->x().end(), vec_size_x), vec_size_x)); win_config.second.set(Window::DimX, Window::Dimension(win_config.second.x().start(), ceil_to_multiple(win_config.second.x().end(), vec_size_x), vec_size_x)); } build_opts.add_option_if(multi_access_x, "-DVEC_SIZE=" + support::cpp11::to_string(vec_size_x)); build_opts.add_option_if(multi_access_x && remainder_x, "-DLAST_ACCESSED_X=" + support::cpp11::to_string(std::max(width_x - vec_size_x, 0))); } else { build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(vec_size_x)); } // Build kernel _kernel = static_cast(CLKernelLibrary::get().create_kernel("copy_tensor", build_opts.options())); } else { build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(vec_size_x)); // Add compile time options add_padding_as_build_options(padding, build_opts); // If we are padding in the fourth dimension the kernel needs to know the depth of the // different cubes if(padding.size() == 4) { const size_t depth = input->info()->tensor_shape()[2]; build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(depth)); } // Build kernel _kernel = static_cast(CLKernelLibrary::get().create_kernel("copy_pad_tensor", build_opts.options())); // Configure window win_config = validate_and_configure_window_with_padding(input->info(), output->info(), padding); } // Validate and set the window ARM_COMPUTE_ERROR_THROW_ON(win_config.first); ICLKernel::configure_internal(win_config.second); } Status CLCopyKernel::validate(const arm_compute::ITensorInfo *input, const arm_compute::ITensorInfo *output, const PaddingList &padding, Window *output_window) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, padding, output_window)); if(padding.empty()) { ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), output_window).first); } else { ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_with_padding(input->clone().get(), output->clone().get(), padding).first); } return Status{}; } void CLCopyKernel::run(const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); Window slice; if(_has_output_window) { slice = window.first_slice_window_3D(); Window out_slice = _output_window.first_slice_window_3D(); do { unsigned int idx = 0; add_3D_tensor_argument(idx, _input, slice); add_3D_tensor_argument(idx, _output, out_slice); enqueue(queue, *this, slice, lws_hint()); } while(window.slide_window_slice_3D(slice) && _output_window.slide_window_slice_3D(out_slice)); } else { Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); slice = collapsed.first_slice_window_3D(); 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(collapsed.slide_window_slice_3D(slice)); } } } // namespace arm_compute