ResizeLayer.cpp

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//
// Copyright © 2019-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
 
#include "ResizeLayer.hpp"
#include "LayerCloneBase.hpp"
 
#include <armnn/TypesUtils.hpp>
 
#include <armnnUtils/DataLayoutIndexed.hpp>
 
#include <armnn/backends/WorkloadData.hpp>
#include <armnn/backends/WorkloadFactory.hpp>
 
using namespace armnnUtils;
 
namespace armnn
{
 
ResizeLayer::ResizeLayer(const ResizeDescriptor& param, const char* name)
    : LayerWithParameters(1, 1, LayerType::Resize, param, name)
{
}
 
std::unique_ptr<IWorkload> ResizeLayer::CreateWorkload(const IWorkloadFactory& factory) const
{
    ResizeQueueDescriptor descriptor;
    SetAdditionalInfo(descriptor);
 
    return factory.CreateWorkload(LayerType::Resize, descriptor, PrepInfoAndDesc(descriptor));
}
 
ResizeLayer* ResizeLayer::Clone(Graph& graph) const
{
    return CloneBase<ResizeLayer>(graph, m_Param, GetName());
}
 
std::vector<TensorShape> ResizeLayer::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\".");
    }
 
    const TensorShape& inputShape = inputShapes[0];
    const DataLayoutIndexed dimensionIndices = m_Param.m_DataLayout;
 
    unsigned int outWidth = m_Param.m_TargetWidth;
    unsigned int outHeight = m_Param.m_TargetHeight;
    unsigned int outChannels = inputShape[dimensionIndices.GetChannelsIndex()];
    unsigned int outBatch = inputShape[0];
 
    TensorShape tensorShape = m_Param.m_DataLayout == armnn::DataLayout::NHWC ?
        TensorShape( { outBatch, outHeight, outWidth, outChannels } ) :
        TensorShape( { outBatch, outChannels, outHeight, outWidth });
 
    if (m_Param.m_HalfPixelCenters && m_Param.m_AlignCorners)
    {
        throw LayerValidationException("ResizeLayer: AlignCorners cannot be true when HalfPixelCenters is true");
    }
 
    return std::vector<TensorShape>({ tensorShape });
}
 
void ResizeLayer::ValidateTensorShapesFromInputs()
{
    VerifyLayerConnections(1, CHECK_LOCATION());
 
    const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
 
    VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
 
    auto 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, "ResizeLayer");
}
 
void ResizeLayer::ExecuteStrategy(IStrategy& strategy) const
{
    strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
}
 
} // namespace armnn