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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// See LICENSE file in the project root for full license information.
//
#include "NormalizationLayer.hpp"
#include "LayerCloneBase.hpp"
#include <armnn/TypesUtils.hpp>
#include <backends/WorkloadData.hpp>
#include <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 Graph& graph, const IWorkloadFactory& factory) const
{
NormalizationQueueDescriptor descriptor;
return factory.CreateNormalization(descriptor, PrepInfoAndDesc(descriptor, graph));
}
NormalizationLayer* NormalizationLayer::Clone(Graph& graph) const
{
return CloneBase<NormalizationLayer>(graph, m_Param, GetName());
}
void NormalizationLayer::ValidateTensorShapesFromInputs()
{
ConditionalThrow<LayerValidationException>(GetInputSlot(0).GetConnection() != nullptr,
"NormalizationLayer: Input slot must be connected.");
const TensorShape& outShape = GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape();
ConditionalThrowIfNotEqual<LayerValidationException>(
"NormalizationLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
GetOutputSlot(0).GetTensorInfo().GetShape(),
outShape);
}
} // namespace armnn
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