text: /*
   * Copyright (c) 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/graph/nodes/StackLayerNode.h"
  
  #include "arm_compute/core/TensorInfo.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"
  
  #include "arm_compute/core/utils/misc/ShapeCalculator.h"
  
  namespace arm_compute
  {
  namespace graph
  {
  StackLayerNode::StackLayerNode(unsigned int total_nodes, int axis)
      : _total_nodes(total_nodes), _axis(axis)
  {
      _input_edges.resize(_total_nodes, EmptyEdgeID);
      _outputs.resize(1, NullTensorID);
  }
  
  int StackLayerNode::axis() const
  {
      return _axis;
  }
  
  TensorDescriptor StackLayerNode::compute_output_descriptor(const std::vector<TensorDescriptor> &input_descriptors,
                                                             int                                  axis)
  {
      ARM_COMPUTE_ERROR_ON(input_descriptors.size() == 0);
  
      TensorDescriptor output_descriptor = input_descriptors[0];
  
      const TensorInfo   input_info(input_descriptors[0].shape, 1, input_descriptors[0].data_type);
      const unsigned int num_tensors = input_descriptors.size();
  
      output_descriptor.shape = arm_compute::misc::shape_calculator::compute_stack_shape(input_info, axis, num_tensors);
  
      return output_descriptor;
  }
  
  bool StackLayerNode::forward_descriptors()
  {
      if(_outputs[0] != NullTensorID)
      {
          Tensor *dst = output(0);
          ARM_COMPUTE_ERROR_ON(dst == nullptr);
          dst->desc() = configure_output(0);
          return true;
      }
      return false;
  }
  
  TensorDescriptor StackLayerNode::configure_output(size_t idx) const
  {
      ARM_COMPUTE_UNUSED(idx);
      ARM_COMPUTE_ERROR_ON(idx >= _outputs.size());
  
      // Check if all input tensors are set
      bool are_all_inputs_set = std::all_of(std::begin(_input_edges), std::end(_input_edges), [](const EdgeID & eid)
      {
          return eid != EmptyEdgeID;
      });
  
      TensorDescriptor output_info = {};
  
      if(are_all_inputs_set)
      {
          std::vector<TensorDescriptor> inputs_descriptors;
          for(unsigned int i = 0; i < _input_edges.size(); ++i)
          {
              const Tensor *t = _graph->tensor(input_id(i));
              ARM_COMPUTE_ERROR_ON(t == nullptr);
              inputs_descriptors.push_back(t->desc());
          }
          output_info = compute_output_descriptor(inputs_descriptors, _axis);
      }
  
      return output_info;
  }
  
  NodeType StackLayerNode::type() const
  {
      return NodeType::StackLayer;
  }
  
  void StackLayerNode::accept(INodeVisitor &v)
  {
      v.visit(*this);
  }
  } // namespace graph
  } // namespace arm_compute
  