/* * 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/CLMinMaxLayerKernel.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/Helpers.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include using namespace arm_compute; using namespace arm_compute::misc::shape_calculator; namespace { Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() < 3); if(output->tensor_shape().total_size() > 0) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); TensorShape output_shape = compute_min_max_shape(input); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); } return Status{}; } std::tuple validate_and_configure_window(ITensorInfo *input, ITensorInfo *output) { TensorShape output_shape = compute_min_max_shape(input); // Output auto initialization if not yet initialized auto_init_if_empty(*output, output_shape, 1, input->data_type()); const unsigned int num_elems_processed_per_iteration = 1; // Configure kernel window Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); AccessWindowStatic output_access(output, 0, 0, 2, output->dimension(1)); bool window_changed = update_window_and_padding(win, input_access, output_access); output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; return std::make_tuple(err, win); } } // namespace CLMinMaxLayerKernel::CLMinMaxLayerKernel() : _input(nullptr), _output(nullptr) { } void CLMinMaxLayerKernel::configure(const ICLTensor *input, ICLTensor *output) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info())); _input = input; _output = output; std::set build_opts; build_opts.emplace("-DWIDTH=" + support::cpp11::to_string(input->info()->dimension(0))); build_opts.emplace("-DHEIGHT=" + support::cpp11::to_string(input->info()->dimension(1))); build_opts.emplace("-DDEPTH=" + support::cpp11::to_string(input->info()->dimension(2))); // Create kernel _kernel = static_cast(CLKernelLibrary::get().create_kernel("minmax_layer", build_opts)); auto win_config = validate_and_configure_window(input->info(), output->info()); ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config)); ICLKernel::configure_internal(std::get<1>(win_config)); } Status CLMinMaxLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output)); ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get()))); return Status{}; } void CLMinMaxLayerKernel::reset(cl::CommandQueue &queue) { _output->map(queue, true); Window window_output; window_output.use_tensor_dimensions(_output->info()->tensor_shape()); window_output.set(Window::DimX, Window::Dimension(0, 1, 1)); Iterator output(_output, window_output); // Reset output execute_window_loop(window_output, [&](const Coordinates & id) { auto *ptr = reinterpret_cast(output.ptr()); ptr[0] = std::numeric_limits::max(); ptr[1] = std::numeric_limits::min(); }, output); _output->unmap(queue); } void CLMinMaxLayerKernel::run(const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), 3); Window slice = window_collapsed.first_slice_window_3D(); slice.set(Window::DimX, Window::Dimension(0, 1, 1)); slice.set(Window::DimY, Window::Dimension(0, 1, 1)); slice.set(Window::DimZ, Window::Dimension(0, 1, 1)); do { Window output_slice = slice.shift_dimensions(2); unsigned int idx = 0; // Set inputs add_3D_tensor_argument(idx, _input, slice); add_1D_tensor_argument(idx, _output, output_slice); enqueue(queue, *this, slice); } while(window_collapsed.slide_window_slice_3D(slice)); }