/* * 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 "arm_compute/graph/nodes/DeconvolutionLayerNode.h" #include "arm_compute/core/Utils.h" #include "arm_compute/graph/Graph.h" #include "arm_compute/graph/INodeVisitor.h" #include "arm_compute/graph/Utils.h" namespace arm_compute { namespace graph { DeconvolutionLayerNode::DeconvolutionLayerNode(const descriptors::DeconvolutionLayerDescriptor &descriptor) : descriptor(std::move(descriptor)) { _input_edges.resize(3, EmptyEdgeID); _outputs.resize(1, NullTensorID); } PadStrideInfo DeconvolutionLayerNode::deconvolution_info() const { return descriptor.info; } TensorDescriptor DeconvolutionLayerNode::compute_output_descriptor(const TensorDescriptor &input_descriptor, const TensorDescriptor &weights_descriptor, const PadStrideInfo &info) { unsigned int output_width = 0; unsigned int output_height = 0; const unsigned int input_width = get_dimension_size(input_descriptor, DataLayoutDimension::WIDTH); const unsigned int input_height = get_dimension_size(input_descriptor, DataLayoutDimension::HEIGHT); const unsigned int kernel_width = get_dimension_size(weights_descriptor, DataLayoutDimension::WIDTH); const unsigned int kernel_height = get_dimension_size(weights_descriptor, DataLayoutDimension::HEIGHT); std::tie(output_width, output_height) = deconvolution_output_dimensions(input_width, input_height, kernel_width, kernel_height, info); const DataLayout data_layout = input_descriptor.layout; TensorDescriptor output_descriptor = input_descriptor; output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::WIDTH), output_width); output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::HEIGHT), output_height); output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::CHANNEL), weights_descriptor.shape[3]); return output_descriptor; } bool DeconvolutionLayerNode::forward_descriptors() { if((input_id(0) != NullTensorID) && (input_id(1) != NullTensorID) && (output_id(0) != NullTensorID)) { Tensor *dst = output(0); ARM_COMPUTE_ERROR_ON(dst == nullptr); dst->desc() = configure_output(0); return true; } return false; } TensorDescriptor DeconvolutionLayerNode::configure_output(size_t idx) const { ARM_COMPUTE_UNUSED(idx); const Tensor *src = input(0); const Tensor *weights = input(1); ARM_COMPUTE_ERROR_ON(src == nullptr || weights == nullptr); TensorDescriptor output_info = compute_output_descriptor(src->desc(), weights->desc(), descriptor.info); if(!descriptor.out_quant_info.empty()) { output_info.set_quantization_info(descriptor.out_quant_info); } return output_info; } NodeType DeconvolutionLayerNode::type() const { return NodeType::DeconvolutionLayer; } void DeconvolutionLayerNode::accept(INodeVisitor &v) { v.visit(*this); } } // namespace graph } // namespace arm_compute