/* * Copyright (c) 2017-2019 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/runtime/NEON/functions/NEDepthConcatenateLayer.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/ITensor.h" #include "arm_compute/core/PixelValue.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Types.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "support/ToolchainSupport.h" using namespace arm_compute; NEDepthConcatenateLayer::NEDepthConcatenateLayer() // NOLINT : _inputs_vector(), _concat_kernels_vector(), _border_handlers_vector(), _num_inputs(0) { } void NEDepthConcatenateLayer::configure(const std::vector &inputs_vector, ITensor *output) // NOLINT { _num_inputs = inputs_vector.size(); std::vector inputs_vector_info; for(unsigned int i = 0; i < _num_inputs; i++) { inputs_vector_info.emplace_back(inputs_vector.at(i)->info()); } TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector_info, Window::DimZ); // Output auto inizialitation if not yet initialized auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type()); ARM_COMPUTE_ERROR_THROW_ON(NEDepthConcatenateLayer::validate(inputs_vector_info, output->info())); unsigned int depth_offset = 0; _concat_kernels_vector.reserve(_num_inputs); _border_handlers_vector.reserve(_num_inputs); for(unsigned int i = 0; i < _num_inputs; ++i) { auto concat_kernel = support::cpp14::make_unique(); auto border_kernel = support::cpp14::make_unique(); concat_kernel->configure(inputs_vector.at(i), depth_offset, output); border_kernel->configure(inputs_vector.at(i), concat_kernel->border_size(), BorderMode::CONSTANT, PixelValue(static_cast(0.f))); _border_handlers_vector.emplace_back(std::move(border_kernel)); _concat_kernels_vector.emplace_back(std::move(concat_kernel)); depth_offset += inputs_vector.at(i)->info()->dimension(2); } // Set valid region from shape output->info()->set_valid_region(ValidRegion(Coordinates(), output_shape)); } Status NEDepthConcatenateLayer::validate(const std::vector &inputs_vector, const ITensorInfo *output) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); ARM_COMPUTE_RETURN_ERROR_ON(inputs_vector.size() < 2); // Output auto inizialitation if not yet initialized TensorInfo tmp_output_info = *output->clone(); TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimZ); auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type()); unsigned int depth_offset = 0; for(const auto &input : inputs_vector) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); ARM_COMPUTE_RETURN_ON_ERROR(NEDepthConcatenateLayerKernel::validate(input, depth_offset, &tmp_output_info)); depth_offset += input->dimension(2); } return Status{}; } void NEDepthConcatenateLayer::run() { for(unsigned i = 0; i < _num_inputs; ++i) { NEScheduler::get().schedule(_border_handlers_vector[i].get(), Window::DimX); NEScheduler::get().schedule(_concat_kernels_vector[i].get(), Window::DimX); } }