LogSoftmaxLayer.cpp

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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 &param, 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