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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// See LICENSE file in the project root for full license information.
//
#include "L2NormalizationLayer.hpp"
#include "LayerCloneBase.hpp"
#include <armnn/TypesUtils.hpp>
#include <backends/WorkloadData.hpp>
#include <backends/WorkloadFactory.hpp>
namespace armnn
{
L2NormalizationLayer::L2NormalizationLayer(const char* name)
: Layer(1, 1, LayerType::L2Normalization, name)
{
}
std::unique_ptr<IWorkload> L2NormalizationLayer::CreateWorkload(const Graph& graph,
const IWorkloadFactory& factory) const
{
L2NormalizationQueueDescriptor descriptor;
return factory.CreateL2Normalization(descriptor, PrepInfoAndDesc(descriptor, graph));
}
L2NormalizationLayer* L2NormalizationLayer::Clone(Graph& graph) const
{
return CloneBase<L2NormalizationLayer>(graph, GetName());
}
void L2NormalizationLayer::ValidateTensorShapesFromInputs()
{
ConditionalThrow<LayerValidationException>(GetInputSlot(0).GetConnection() != nullptr,
"L2NormalizationLayer: InputSlot must be connected to an OutputSlot");
ConditionalThrow<LayerValidationException>(GetInputSlot(0).GetConnection()->IsTensorInfoSet(),
"L2NormalizationLayer: TensorInfo must be set on connected OutputSlot.");
IOutputSlot* input = GetInputSlot(0).GetConnection();
// input and output shapes are the same
TensorShape const& outShape = input->GetTensorInfo().GetShape();
ConditionalThrowIfNotEqual<LayerValidationException>(
"L2NormalizationLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
GetOutputSlot(0).GetTensorInfo().GetShape(),
outShape);
}
} // namespace armnn
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