/* * Copyright (c) 2016, 2017 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/CLScaleKernel.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/ICLKernel.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/TensorInfo.h" #include "arm_compute/core/Validate.h" #include #include using namespace arm_compute; BorderSize CLScaleKernel::border_size() const { return BorderSize(1); } void CLScaleKernel::configure(const ICLTensor *input, ICLTensor *output, InterpolationPolicy policy, bool border_undefined) { ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S16); ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::S16); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); _input = input; _output = output; /* Compute the ratio between source width/height and destination width/height */ const auto wr = static_cast(input->info()->dimension(0)) / static_cast(output->info()->dimension(0)); const auto hr = static_cast(input->info()->dimension(1)) / static_cast(output->info()->dimension(1)); /* Area interpolation behaves as Nearest Neighbour in case of up-sampling */ if(policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) { policy = InterpolationPolicy::NEAREST_NEIGHBOR; } else { ARM_COMPUTE_ERROR_ON(policy == InterpolationPolicy::AREA); } // Create kernel std::set build_opts = { ("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())) }; std::string interpolation_name = string_from_interpolation_policy(policy); std::transform(interpolation_name.begin(), interpolation_name.end(), interpolation_name.begin(), ::tolower); std::string kernel_name = "scale_" + interpolation_name; _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name, build_opts)); // Configure kernel window constexpr unsigned int num_elems_processed_per_iteration = 4; Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration)); const ValidRegion &input_valid_region = input->info()->valid_region(); // Reads can occur within the valid region of the input AccessWindowStatic input_access(input->info(), input_valid_region.anchor[0] - border_size().left, input_valid_region.anchor[1] - border_size().top, input_valid_region.anchor[0] + input_valid_region.shape[0] + border_size().right, input_valid_region.anchor[1] + input_valid_region.shape[1] + border_size().bottom); 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, calculate_valid_region_scale(*(input->info()), output->info()->tensor_shape(), policy, border_size(), border_undefined)); ICLKernel::configure(win); // Set static kernel arguments unsigned int idx = 2 * num_arguments_per_2D_tensor(); //Skip the input and output parameters _kernel.setArg(idx++, input->info()->dimension(0)); _kernel.setArg(idx++, input->info()->dimension(1)); _kernel.setArg(idx++, output->info()->dimension(0)); _kernel.setArg(idx++, output->info()->dimension(1)); }