/* * 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/CLTileKernel.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/Helpers.h" #include "arm_compute/core/IAccessWindow.h" #include "arm_compute/core/TensorInfo.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" namespace arm_compute { namespace { Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const Multiples &multiples) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_RETURN_ERROR_ON(multiples.size() > 4); ARM_COMPUTE_RETURN_ERROR_ON(multiples.empty()); ARM_COMPUTE_RETURN_ERROR_ON(std::any_of(multiples.begin(), multiples.end(), [](uint32_t e) { return e == 0; })); // Validate output if initialized if(output->total_size() != 0) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(misc::shape_calculator::compute_tiled_shape(input->tensor_shape(), multiples), output->tensor_shape()); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); } return Status{}; } } // namespace CLTileKernel::CLTileKernel() : _input(nullptr), _output(nullptr) { } void CLTileKernel::configure(const ICLTensor *input, ICLTensor *output, const Multiples &multiples) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); // Auto initialize output TensorShape tiled_shape = misc::shape_calculator::compute_tiled_shape(input->info()->tensor_shape(), multiples); auto_init_if_empty(*output->info(), tiled_shape, 1, input->info()->data_type()); // Validate ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), multiples)); _input = input; _output = output; const DataType data_type = input->info()->data_type(); const int vec_size_x = 16 / input->info()->element_size(); const int input_width_x = input->info()->tensor_shape().x(); const unsigned int offset = ceil_to_multiple(input_width_x, vec_size_x) - input_width_x; const bool multi_access_x = (input_width_x / vec_size_x > 0); // Create kernel CLBuildOptions build_opts; build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type)); build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(input_width_x)); build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(input->info()->dimension(1))); build_opts.add_option("-DSRC_DEPTH=" + support::cpp11::to_string(input->info()->dimension(2))); build_opts.add_option("-DSRC_BATCHES=" + support::cpp11::to_string(input->info()->dimension(3))); build_opts.add_option("-DDST_DEPTH=" + support::cpp11::to_string(output->info()->dimension(2))); build_opts.add_option_if(multi_access_x, "-DOFFSET=" + support::cpp11::to_string(offset)); build_opts.add_option_if(multi_access_x, "-DVEC_SIZE=" + support::cpp11::to_string(vec_size_x)); _kernel = static_cast(CLKernelLibrary::get().create_kernel("tile", build_opts.options())); // Configure window without padding Window win = calculate_max_window(*output->info()); if(multi_access_x) { // If multi-access is enabled, no thread should cross the tile boundaries. This means we need // as many threads as those to cover a single tile times multiples[0]. Note that if threads // do not cross the boundaries of the tiles, they won't cross the boundaries of the last tile, and // we don't need to pad the output const unsigned int size_win_x = ceil_to_multiple(input->info()->dimension(0), vec_size_x) * multiples[0]; win.set(Window::DimX, Window::Dimension(win.x().start(), size_win_x, vec_size_x)); } ICLKernel::configure_internal(win); // Set config_id for enabling LWS tuning _config_id = "tile"; _config_id += "_"; _config_id += lower_string(string_from_data_type(input->info()->data_type())); for(unsigned int i = 0; i < multiples.size(); ++i) { _config_id += "_"; _config_id += support::cpp11::to_string(input->info()->dimension(i)); _config_id += "_"; _config_id += support::cpp11::to_string(multiples[i]); } } Status CLTileKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Multiples &multiples) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, multiples)); return Status{}; } void CLTileKernel::run(const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); Window slice = collapsed.first_slice_window_4D(); do { unsigned int idx = 0; add_4D_tensor_argument(idx, _input, slice); add_4D_tensor_argument(idx, _output, slice); enqueue(queue, *this, slice, lws_hint()); } while(collapsed.slide_window_slice_4D(slice)); } } // namespace arm_compute