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//
// Copyright © 2019-2024 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "LogSoftmaxLayer.hpp"
#include "LayerCloneBase.hpp"
#include <armnn/TypesUtils.hpp>
#include <armnn/backends/WorkloadData.hpp>
#include <armnn/backends/WorkloadFactory.hpp>
namespace armnn
{
LogSoftmaxLayer::LogSoftmaxLayer(const LogSoftmaxDescriptor ¶m, const char* name)
: LayerWithParameters(1, 1, LayerType::LogSoftmax, param, name) {}
std::unique_ptr<IWorkload> LogSoftmaxLayer::CreateWorkload(const IWorkloadFactory& factory) const
{
LogSoftmaxQueueDescriptor descriptor;
SetAdditionalInfo(descriptor);
return factory.CreateWorkload(LayerType::LogSoftmax, descriptor, PrepInfoAndDesc(descriptor));
}
LogSoftmaxLayer* LogSoftmaxLayer::Clone(Graph& graph) const
{
return CloneBase<LogSoftmaxLayer>(graph, m_Param, GetName());
}
void LogSoftmaxLayer::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, "LogSoftmaxLayer");
}
void LogSoftmaxLayer::ExecuteStrategy(IStrategy& strategy) const
{
strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
}
} // namespace armnn
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