src/armnn/layers/NormalizationLayer.cpp

//
// Copyright © 2017-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "NormalizationLayer.hpp"

#include "LayerCloneBase.hpp"

#include <armnn/TypesUtils.hpp>
#include <armnn/backends/WorkloadData.hpp>
#include <armnn/backends/WorkloadFactory.hpp>

namespace armnn
{

NormalizationLayer::NormalizationLayer(const NormalizationDescriptor& param, const char* name)
    : LayerWithParameters(1, 1, LayerType::Normalization, param, name)
{
}

std::unique_ptr<IWorkload> NormalizationLayer::CreateWorkload(const IWorkloadFactory& factory) const
{
    NormalizationQueueDescriptor descriptor;
    SetAdditionalInfo(descriptor);

    return factory.CreateWorkload(LayerType::Normalization, descriptor, PrepInfoAndDesc(descriptor));
}

NormalizationLayer* NormalizationLayer::Clone(Graph& graph) const
{
    return CloneBase<NormalizationLayer>(graph, m_Param, GetName());
}

void NormalizationLayer::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, "NormalizationLayer");
}

void NormalizationLayer::ExecuteStrategy(IStrategy& strategy) const
{
    strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
}

} // namespace armnn