SpaceToDepthLayer.cpp

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//
// Copyright © 2019-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
 
#include "SpaceToDepthLayer.hpp"
#include "LayerCloneBase.hpp"
 
#include <armnn/TypesUtils.hpp>
#include <armnn/utility/IgnoreUnused.hpp>
#include <armnnUtils/DataLayoutIndexed.hpp>
 
#include <armnn/backends/WorkloadData.hpp>
#include <armnn/backends/WorkloadFactory.hpp>
 
#include <numeric>
 
using namespace armnnUtils;
 
namespace armnn
{
 
SpaceToDepthLayer::SpaceToDepthLayer(const SpaceToDepthDescriptor param, const char* name)
    : LayerWithParameters(1, 1, LayerType::SpaceToDepth, param, name)
{}
 
std::unique_ptr<IWorkload> SpaceToDepthLayer::CreateWorkload(const IWorkloadFactory& factory) const
{
    SpaceToDepthQueueDescriptor descriptor;
    descriptor.m_Parameters.m_BlockSize  = m_Param.m_BlockSize;
    descriptor.m_Parameters.m_DataLayout = m_Param.m_DataLayout;
 
    SetAdditionalInfo(descriptor);
 
    return factory.CreateWorkload(LayerType::SpaceToDepth, descriptor, PrepInfoAndDesc(descriptor));
}
 
SpaceToDepthLayer* SpaceToDepthLayer::Clone(Graph& graph) const
{
    IgnoreUnused(graph);
    return CloneBase<SpaceToDepthLayer>(graph, m_Param, GetName());
}
 
std::vector<TensorShape> SpaceToDepthLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
{
    if (inputShapes.size() != 1)
    {
        throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
                               "\" - should be \"1\".");
    }
 
    TensorShape inputShape = inputShapes[0];
    TensorShape outputShape(inputShape);
 
    DataLayoutIndexed dimensionIndices{m_Param.m_DataLayout};
    unsigned int hIndex = dimensionIndices.GetHeightIndex();
    unsigned int wIndex = dimensionIndices.GetWidthIndex();
    unsigned int cIndex = dimensionIndices.GetChannelsIndex();
 
    outputShape[hIndex] = inputShape[hIndex] / m_Param.m_BlockSize;
    outputShape[wIndex] = inputShape[wIndex] / m_Param.m_BlockSize;
 
    outputShape[cIndex] = inputShape[cIndex] * m_Param.m_BlockSize * m_Param.m_BlockSize;
 
    return std::vector<TensorShape>({ outputShape });
}
 
void SpaceToDepthLayer::ValidateTensorShapesFromInputs()
{
    VerifyLayerConnections(1, CHECK_LOCATION());
 
    const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
 
    VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
 
    std::vector<TensorShape> inferredShapes = InferOutputShapes({
        GetInputSlot(0).GetTensorInfo().GetShape() });
 
    if (inferredShapes.size() != 1)
    {
        throw armnn::LayerValidationException("inferredShapes has "
                                              + std::to_string(inferredShapes.size()) +
                                              " elements - should only have 1.");
    }
 
    ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "SpaceToDepthLayer");
}
 
void SpaceToDepthLayer::ExecuteStrategy(IStrategy& strategy) const
{
    strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
}
 
} // namespace armnn