ConcatenateLayerNode.cpp

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/*
 * Copyright (c) 2018-2019 Arm Limited.
 *
 * SPDX-License-Identifier: MIT
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 * of this software and associated documentation files (the "Software"), to
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 * 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.
 *
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 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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#include "arm_compute/graph/nodes/ConcatenateLayerNode.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
{
ConcatenateLayerNode::ConcatenateLayerNode(unsigned int total_nodes, descriptors::ConcatLayerDescriptor concat_descriptor)
    : _total_nodes(total_nodes), _concat_descriptor(std::move(concat_descriptor)), _is_enabled(true)
{
    _input_edges.resize(_total_nodes, EmptyEdgeID);
    _outputs.resize(1, NullTensorID);
}
 
void ConcatenateLayerNode::set_enabled(bool is_enabled)
{
    _is_enabled = is_enabled;
}
 
bool ConcatenateLayerNode::is_enabled() const
{
    return _is_enabled;
}
 
DataLayoutDimension ConcatenateLayerNode::concatenation_axis() const
{
    return _concat_descriptor.axis;
}
 
QuantizationInfo ConcatenateLayerNode::output_quantization_info() const
{
    return _concat_descriptor.output_qinfo;
}
 
TensorDescriptor ConcatenateLayerNode::compute_output_descriptor(const std::vector<TensorDescriptor> &input_descriptors,
                                                                 DataLayoutDimension                  axis)
{
    ARM_COMPUTE_ERROR_ON(input_descriptors.size() == 0);
 
    TensorDescriptor output_descriptor = input_descriptors[0];
    const int        axis_idx          = get_dimension_idx(output_descriptor.layout, axis);
    ARM_COMPUTE_ERROR_ON_MSG(axis_idx > 2, "Unsupported concatenation axis!");
 
    // Extract shapes
    std::vector<const TensorShape *> shapes;
    shapes.reserve(input_descriptors.size());
    for(auto &input_descriptor : input_descriptors)
    {
        shapes.emplace_back(&input_descriptor.shape);
    }
 
    output_descriptor.shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(shapes, axis_idx);
 
    return output_descriptor;
}
 
bool ConcatenateLayerNode::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 ConcatenateLayerNode::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, _concat_descriptor.axis);
        if(!_concat_descriptor.output_qinfo.empty())
        {
            output_info.quant_info = _concat_descriptor.output_qinfo;
        }
    }
 
    return output_info;
}
 
NodeType ConcatenateLayerNode::type() const
{
    return NodeType::ConcatenateLayer;
}
 
void ConcatenateLayerNode::accept(INodeVisitor &v)
{
    v.visit(*this);
}
} // namespace graph
} // namespace arm_compute