/* * Copyright (c) 2019-2020 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/CLGenerateProposalsLayerKernel.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/CLValidate.h" #include "arm_compute/core/CL/ICLArray.h" #include "arm_compute/core/CL/ICLTensor.h" #include "arm_compute/core/CL/OpenCL.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Window.h" #include "support/StringSupport.h" namespace arm_compute { namespace { Status validate_arguments(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(anchors, all_anchors); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(anchors); ARM_COMPUTE_RETURN_ERROR_ON(anchors->dimension(0) != info.values_per_roi()); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(anchors, DataType::QSYMM16, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON(anchors->num_dimensions() > 2); if(all_anchors->total_size() > 0) { size_t feature_height = info.feat_height(); size_t feature_width = info.feat_width(); size_t num_anchors = anchors->dimension(1); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(all_anchors, anchors); ARM_COMPUTE_RETURN_ERROR_ON(all_anchors->num_dimensions() > 2); ARM_COMPUTE_RETURN_ERROR_ON(all_anchors->dimension(0) != info.values_per_roi()); ARM_COMPUTE_RETURN_ERROR_ON(all_anchors->dimension(1) != feature_height * feature_width * num_anchors); if(is_data_type_quantized(anchors->data_type())) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(anchors, all_anchors); } } return Status{}; } } // namespace CLComputeAllAnchorsKernel::CLComputeAllAnchorsKernel() : _anchors(nullptr), _all_anchors(nullptr) { } void CLComputeAllAnchorsKernel::configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info) { configure(CLKernelLibrary::get().get_compile_context(), anchors, all_anchors, info); } void CLComputeAllAnchorsKernel::configure(const CLCompileContext &compile_context, const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info) { ARM_COMPUTE_ERROR_ON_NULLPTR(anchors, all_anchors); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(anchors->info(), all_anchors->info(), info)); // Metadata const size_t num_anchors = anchors->info()->dimension(1); const DataType data_type = anchors->info()->data_type(); const float width = info.feat_width(); const float height = info.feat_height(); // Initialize the output if empty const TensorShape output_shape(info.values_per_roi(), width * height * num_anchors); auto_init_if_empty(*all_anchors->info(), TensorInfo(output_shape, 1, data_type, anchors->info()->quantization_info())); // Set instance variables _anchors = anchors; _all_anchors = all_anchors; const bool is_quantized = is_data_type_quantized(anchors->info()->data_type()); // Set build options CLBuildOptions build_opts; build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type)); build_opts.add_option("-DWIDTH=" + float_to_string_with_full_precision(width)); build_opts.add_option("-DHEIGHT=" + float_to_string_with_full_precision(height)); build_opts.add_option("-DSTRIDE=" + float_to_string_with_full_precision(1.f / info.spatial_scale())); build_opts.add_option("-DNUM_ANCHORS=" + support::cpp11::to_string(num_anchors)); build_opts.add_option("-DNUM_ROI_FIELDS=" + support::cpp11::to_string(info.values_per_roi())); if(is_quantized) { const UniformQuantizationInfo qinfo = anchors->info()->quantization_info().uniform(); build_opts.add_option("-DSCALE=" + float_to_string_with_full_precision(qinfo.scale)); build_opts.add_option("-DOFFSET=" + float_to_string_with_full_precision(qinfo.offset)); } // Create kernel const std::string kernel_name = (is_quantized) ? "generate_proposals_compute_all_anchors_quantized" : "generate_proposals_compute_all_anchors"; _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); // The tensor all_anchors can be interpreted as an array of structs (each structs has values_per_roi fields). // This means we don't need to pad on the X dimension, as we know in advance how many fields // compose the struct. Window win = calculate_max_window(*all_anchors->info(), Steps(info.values_per_roi())); ICLKernel::configure_internal(win); } Status CLComputeAllAnchorsKernel::validate(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(anchors, all_anchors, info)); return Status{}; } void CLComputeAllAnchorsKernel::run(const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); // Collapse everything on the first dimension Window collapsed = window.collapse(ICLKernel::window(), Window::DimX); // Set arguments unsigned int idx = 0; add_1D_tensor_argument(idx, _anchors, collapsed); add_1D_tensor_argument(idx, _all_anchors, collapsed); // Note that we don't need to loop over the slices, as we are launching exactly // as many threads as all the anchors generated enqueue(queue, *this, collapsed, lws_hint()); } } // namespace arm_compute