/* * Copyright (c) 2017, 2018 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/CLDepthConcatenateLayerKernel.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/IAccessWindow.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Window.h" #include "support/ToolchainSupport.h" #include using namespace arm_compute; CLDepthConcatenateLayerKernel::CLDepthConcatenateLayerKernel() : _input(nullptr), _output(nullptr), _top_bottom(0), _left_right(0), _depth_offset(0) { } BorderSize CLDepthConcatenateLayerKernel::border_size() const { return BorderSize(_top_bottom, _left_right); } void CLDepthConcatenateLayerKernel::configure(const ICLTensor *input, unsigned int depth_offset, ICLTensor *output) { static std::map> configs_map = { { 1, { "uchar", 16 } }, { 2, { "ushort", 8 } }, { 4, { "uint", 4 } }, { 8, { "ulong", 2 } }, }; ARM_COMPUTE_ERROR_ON_F16_UNSUPPORTED(input); ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT_POSITION(input, output); ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) + depth_offset > output->info()->dimension(2)); ARM_COMPUTE_ERROR_ON(input->info()->dimension(0) > output->info()->dimension(0)); ARM_COMPUTE_ERROR_ON(input->info()->dimension(1) > output->info()->dimension(1)); ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(3, input, output); ARM_COMPUTE_ERROR_ON(configs_map.find(input->info()->element_size()) == configs_map.end()); // The gaps between the two lowest dimensions of input and output need to be divisible by 2 // Otherwise it is not clear how the padding should be added onto the input tensor ARM_COMPUTE_ERROR_ON((output->info()->dimension(0) - input->info()->dimension(0)) % 2); ARM_COMPUTE_ERROR_ON((output->info()->dimension(1) - input->info()->dimension(1)) % 2); _input = input; _output = output; _depth_offset = depth_offset; // Add build options auto config = configs_map.find(static_cast(input->info()->element_size())); std::set build_opts; build_opts.emplace(("-DDATA_TYPE=" + config->second.first)); build_opts.emplace(("-DVEC_SIZE=" + support::cpp11::to_string(config->second.second))); // Create kernel _kernel = static_cast(CLKernelLibrary::get().create_kernel("concatenate_depth", build_opts)); // Configure kernel window _left_right = (output->info()->dimension(0) - input->info()->dimension(0)) / 2; _top_bottom = (output->info()->dimension(1) - input->info()->dimension(1)) / 2; const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size(); const unsigned int num_elems_read_per_iteration = 16 / input->info()->element_size(); const unsigned int num_rows_read_per_iteration = 1; // The window needs to be based on input as we copy all the depths of input Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration)); win.set(Window::DimZ, Window::Dimension(0, input->info()->tensor_shape().z(), 1)); AccessWindowRectangle input_access(input->info(), -_left_right, -_top_bottom, num_elems_read_per_iteration, num_rows_read_per_iteration); AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); update_window_and_padding(win, input_access, output_access); output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); ICLKernel::configure(win); } void CLDepthConcatenateLayerKernel::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 = window.first_slice_window_3D(); const int offset_to_first_elements_in_bytes = _depth_offset * _output->info()->strides_in_bytes()[2]; unsigned int idx = 2 * num_arguments_per_3D_tensor(); // Skip the input and output parameters const cl_int3 offsets = { { static_cast(_left_right), static_cast(_top_bottom), static_cast(offset_to_first_elements_in_bytes), } }; _kernel.setArg(idx, offsets); do { unsigned int idx = 0; add_3D_tensor_argument(idx, _input, slice); add_3D_tensor_argument(idx, _output, slice); enqueue(queue, *this, slice); } while(window.slide_window_slice_3D(slice)); }