/* * Copyright (c) 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/graph/nodes/DepthwiseConvolutionLayerNode.h" #include "arm_compute/core/Utils.h" #include "arm_compute/graph/Graph.h" #include "arm_compute/graph/INodeVisitor.h" namespace arm_compute { namespace graph { DepthwiseConvolutionLayerNode::DepthwiseConvolutionLayerNode(PadStrideInfo info, DepthwiseConvolutionMethod method) : _info(std::move(info)), _method(method) { _input_edges.resize(3, EmptyEdgeID); _outputs.resize(1, NullTensorID); } void DepthwiseConvolutionLayerNode::set_depthwise_convolution_method(DepthwiseConvolutionMethod method) { _method = method; } DepthwiseConvolutionMethod DepthwiseConvolutionLayerNode::depthwise_convolution_method() const { return _method; } PadStrideInfo DepthwiseConvolutionLayerNode::convolution_info() const { return _info; } TensorShape DepthwiseConvolutionLayerNode::compute_output_shape(TensorShape input_shape, TensorShape weights_shape, PadStrideInfo info) { unsigned int output_width = 0; unsigned int output_height = 0; std::tie(output_width, output_height) = scaled_dimensions(input_shape.x(), input_shape.y(), weights_shape.x(), weights_shape.y(), info); TensorShape output_shape{ input_shape }; output_shape.set(0, output_width); output_shape.set(1, output_height); return output_shape; } bool DepthwiseConvolutionLayerNode::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 DepthwiseConvolutionLayerNode::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 = src->desc(); TensorShape output_shape = compute_output_shape(src->desc().shape, weights->desc().shape, _info); output_info.shape = output_shape; return output_info; } Status DepthwiseConvolutionLayerNode::validate() { return Status{}; } NodeType DepthwiseConvolutionLayerNode::type() const { return NodeType::DepthwiseConvolutionLayer; } void DepthwiseConvolutionLayerNode::accept(INodeVisitor &v) { v.visit(*this); } } // namespace graph } // namespace arm_compute