text: /*
   * 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/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(PadStrideInfo info, Size2D inner_border)
      : _info(std::move(info)), _inner_border(inner_border)
  {
      _input_edges.resize(3, EmptyEdgeID);
      _outputs.resize(1, NullTensorID);
  }
  
  PadStrideInfo DeconvolutionLayerNode::deconvolution_info() const
  {
      return _info;
  }
  
  Size2D DeconvolutionLayerNode::inner_border() const
  {
      return _inner_border;
  }
  
  TensorDescriptor DeconvolutionLayerNode::compute_output_descriptor(const TensorDescriptor &input_descriptor,
                                                                     const TensorDescriptor &weights_descriptor,
                                                                     const PadStrideInfo    &info,
                                                                     const Size2D           &inner_border)
  {
      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.pad().first, info.pad().second,
                                                                              inner_border.x(), inner_border.y(),
                                                                              info.stride().first, info.stride().second);
  
      TensorDescriptor output_descriptor = input_descriptor;
      output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::WIDTH), output_width);
      output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::HEIGHT), output_height);
      output_descriptor.shape.set(get_dimension_idx(output_descriptor, 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(), _info, _inner_border);
      return output_info;
  }
  
  NodeType DeconvolutionLayerNode::type() const
  {
      return NodeType::DeconvolutionLayer;
  }
  
  void DeconvolutionLayerNode::accept(INodeVisitor &v)
  {
      v.visit(*this);
  }
  } // namespace graph
  } // namespace arm_compute