| /* |
| * Copyright (c) 2018-2020 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 "src/core/CL/kernels/CLPriorBoxLayerKernel.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/TensorInfo.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "src/core/CL/CLValidate.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| |
| #include "support/StringSupport.h" |
| |
| using namespace arm_compute::misc::shape_calculator; |
| |
| namespace arm_compute |
| { |
| namespace |
| { |
| Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const PriorBoxLayerInfo &info) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input1, input2, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::F32); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input1, input2); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2); |
| |
| // Check variances |
| const int var_size = info.variances().size(); |
| if(var_size > 1) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(var_size != 4, "Must provide 4 variance values"); |
| for(int i = 0; i < var_size; ++i) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(var_size <= 0, "Must be greater than 0"); |
| } |
| } |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.steps()[0] < 0.f, "Step x should be greater or equal to 0"); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.steps()[1] < 0.f, "Step y should be greater or equal to 0"); |
| |
| if(!info.max_sizes().empty()) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.max_sizes().size() != info.min_sizes().size(), "Max and min sizes dimensions should match"); |
| } |
| |
| for(unsigned int i = 0; i < info.max_sizes().size(); ++i) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.max_sizes()[i] < info.min_sizes()[i], "Max size should be greater than min size"); |
| } |
| |
| if(output != nullptr && output->total_size() != 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(1) != 2); |
| } |
| |
| return Status{}; |
| } |
| |
| std::pair<Status, Window> validate_and_configure_window(const ITensorInfo *input1, const ITensorInfo *input2, ITensorInfo *output, const PriorBoxLayerInfo &info, int num_priors) |
| { |
| ARM_COMPUTE_UNUSED(input2); |
| // Output tensor auto initialization if not yet initialized |
| TensorShape output_shape = compute_prior_box_shape(*input1, info); |
| auto_init_if_empty(*output, output_shape, 1, input1->data_type()); |
| |
| const unsigned int num_elems_processed_per_iteration = 4 * num_priors; |
| Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration)); |
| AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); |
| bool window_changed = update_window_and_padding(win, output_access); |
| Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; |
| return std::make_pair(err, win); |
| } |
| } // namespace |
| |
| CLPriorBoxLayerKernel::CLPriorBoxLayerKernel() |
| : _input1(nullptr), _input2(nullptr), _output(nullptr), _info(), _num_priors(), _min(), _max(), _aspect_ratios() |
| { |
| } |
| |
| void CLPriorBoxLayerKernel::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const PriorBoxLayerInfo &info, cl::Buffer *min, cl::Buffer *max, cl::Buffer *aspect_ratios) |
| { |
| configure(CLKernelLibrary::get().get_compile_context(), input1, input2, output, info, min, max, aspect_ratios); |
| } |
| |
| void CLPriorBoxLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, const PriorBoxLayerInfo &info, cl::Buffer *min, |
| cl::Buffer *max, cl::Buffer *aspect_ratios) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); |
| |
| _input1 = input1; |
| _input2 = input2; |
| _output = output; |
| _info = info; |
| _min = min; |
| _max = max; |
| _aspect_ratios = aspect_ratios; |
| |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1->info(), input2->info(), output->info(), info)); |
| |
| // Calculate number of aspect ratios |
| _num_priors = info.aspect_ratios().size() * info.min_sizes().size() + info.max_sizes().size(); |
| |
| const DataLayout data_layout = input1->info()->data_layout(); |
| |
| const int width_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); |
| const int height_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); |
| |
| const int layer_width = input1->info()->dimension(width_idx); |
| const int layer_height = input1->info()->dimension(height_idx); |
| |
| int img_width = info.img_size().x; |
| int img_height = info.img_size().y; |
| if(img_width == 0 || img_height == 0) |
| { |
| img_width = input2->info()->dimension(width_idx); |
| img_height = input2->info()->dimension(height_idx); |
| } |
| |
| float step_x = info.steps()[0]; |
| float step_y = info.steps()[0]; |
| if(step_x == 0.f || step_y == 0.f) |
| { |
| step_x = static_cast<float>(img_width) / layer_width; |
| step_y = static_cast<float>(img_height) / layer_height; |
| } |
| |
| // Set build options |
| CLBuildOptions build_opts; |
| build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input1->info()->data_type())); |
| build_opts.add_option("-DWIDTH=" + support::cpp11::to_string(img_width)); |
| build_opts.add_option("-DHEIGHT=" + support::cpp11::to_string(img_height)); |
| build_opts.add_option("-DLAYER_WIDTH=" + support::cpp11::to_string(layer_width)); |
| build_opts.add_option("-DLAYER_HEIGHT=" + support::cpp11::to_string(layer_height)); |
| build_opts.add_option("-DSTEP_X=" + support::cpp11::to_string(step_x)); |
| build_opts.add_option("-DSTEP_Y=" + support::cpp11::to_string(step_y)); |
| build_opts.add_option("-DNUM_PRIORS=" + support::cpp11::to_string(_num_priors)); |
| build_opts.add_option("-DOFFSET=" + support::cpp11::to_string(info.offset())); |
| build_opts.add_option_if(info.clip(), "-DIN_PLACE"); |
| |
| if(info.variances().size() > 1) |
| { |
| for(unsigned int i = 0; i < info.variances().size(); ++i) |
| { |
| build_opts.add_option("-DVARIANCE_" + support::cpp11::to_string(i) + "=" + support::cpp11::to_string(info.variances().at(i))); |
| } |
| } |
| else |
| { |
| for(unsigned int i = 0; i < 4; ++i) |
| { |
| build_opts.add_option("-DVARIANCE_" + support::cpp11::to_string(i) + "=" + support::cpp11::to_string(info.variances().at(0))); |
| } |
| } |
| |
| unsigned int idx = num_arguments_per_2D_tensor(); |
| _kernel = create_kernel(compile_context, "prior_box_layer_nchw", build_opts.options()); |
| |
| _kernel.setArg(idx++, *_min); |
| _kernel.setArg(idx++, *_max); |
| _kernel.setArg(idx++, *_aspect_ratios); |
| _kernel.setArg<unsigned int>(idx++, info.min_sizes().size()); |
| _kernel.setArg<unsigned int>(idx++, info.max_sizes().size()); |
| _kernel.setArg<unsigned int>(idx++, info.aspect_ratios().size()); |
| |
| // Configure kernel window |
| auto win_config = validate_and_configure_window(input1->info(), input2->info(), output->info(), info, _num_priors); |
| |
| ARM_COMPUTE_ERROR_THROW_ON(win_config.first); |
| ICLKernel::configure_internal(win_config.second); |
| } |
| |
| Status CLPriorBoxLayerKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, const PriorBoxLayerInfo &info) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, output, info)); |
| const int num_priors = info.aspect_ratios().size() * info.min_sizes().size() + info.max_sizes().size(); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input1->clone().get(), input2->clone().get(), output->clone().get(), info, num_priors) |
| .first); |
| |
| return Status{}; |
| } |
| |
| void CLPriorBoxLayerKernel::run(const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); |
| |
| queue.enqueueWriteBuffer(*_min, CL_TRUE, 0, _info.min_sizes().size() * sizeof(float), _info.min_sizes().data()); |
| queue.enqueueWriteBuffer(*_aspect_ratios, CL_TRUE, 0, _info.aspect_ratios().size() * sizeof(float), _info.aspect_ratios().data()); |
| if(!_info.max_sizes().empty()) |
| { |
| queue.enqueueWriteBuffer(*_max, CL_TRUE, 0, _info.max_sizes().size() * sizeof(float), _info.max_sizes().data()); |
| } |
| |
| Window slice = window.first_slice_window_2D(); |
| slice.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), 2)); |
| |
| unsigned int idx = 0; |
| add_2D_tensor_argument(idx, _output, slice); |
| enqueue(queue, *this, slice, lws_hint()); |
| } |
| } // namespace arm_compute |