#include <PreluLayer.hpp>

Inheritance diagram for PreluLayer:

Collaboration diagram for PreluLayer:

Public Member Functions
virtual std::unique_ptr< IWorkload >	CreateWorkload (const IWorkloadFactory &factory) const override
	Makes a workload for the PReLU type.

PreluLayer *	Clone (Graph &graph) const override
	Creates a dynamically-allocated copy of this layer.

std::vector< TensorShape >	InferOutputShapes (const std::vector< TensorShape > &inputShapes) const override
	By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties.

void	ValidateTensorShapesFromInputs () override
	Check if the input tensor shape(s) will lead to a valid configuration of PreluLayer.

void	ExecuteStrategy (IStrategy &strategy) const override
	Apply a visitor to this layer.

Public Member Functions inherited from Layer
	Layer (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char *name)

	Layer (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, DataLayout layout, const char *name)

const std::string &	GetNameStr () const

const OutputHandler &	GetOutputHandler (unsigned int i=0) const

OutputHandler &	GetOutputHandler (unsigned int i=0)

ShapeInferenceMethod	GetShapeInferenceMethod () const

bool	GetAllowExpandedDims () const

const std::vector< InputSlot > &	GetInputSlots () const

const std::vector< OutputSlot > &	GetOutputSlots () const

std::vector< InputSlot >::iterator	BeginInputSlots ()

std::vector< InputSlot >::iterator	EndInputSlots ()

std::vector< OutputSlot >::iterator	BeginOutputSlots ()

std::vector< OutputSlot >::iterator	EndOutputSlots ()

bool	IsOutputUnconnected ()

void	ResetPriority () const

LayerPriority	GetPriority () const

LayerType	GetType () const override
	Returns the armnn::LayerType of this layer.

DataType	GetDataType () const

const BackendId &	GetBackendId () const

void	SetBackendId (const BackendId &id) override
	Set the backend of the IConnectableLayer.

virtual void	CreateTensorHandles (const TensorHandleFactoryRegistry &registry, const IWorkloadFactory &factory, const bool IsMemoryManaged=true)

void	VerifyLayerConnections (unsigned int expectedConnections, const CheckLocation &location) const

virtual void	SerializeLayerParameters (ParameterStringifyFunction &fn) const
	Helper to serialize the layer parameters to string.

virtual void	ReleaseConstantData ()

template<typename Op >
void	OperateOnConstantTensors (Op op)

const char *	GetName () const override
	Returns the name of the layer.

unsigned int	GetNumInputSlots () const override
	Returns the number of connectable input slots.

unsigned int	GetNumOutputSlots () const override
	Returns the number of connectable output slots.

const InputSlot &	GetInputSlot (unsigned int index) const override
	Get a const input slot handle by slot index.

InputSlot &	GetInputSlot (unsigned int index) override
	Get the input slot handle by slot index.

const OutputSlot &	GetOutputSlot (unsigned int index=0) const override
	Get the const output slot handle by slot index.

OutputSlot &	GetOutputSlot (unsigned int index=0) override
	Get the output slot handle by slot index.

void	SetGuid (LayerGuid guid)

LayerGuid	GetGuid () const final
	Returns the unique id of the layer.

void	AddRelatedLayerName (const std::string layerName)

const std::list< std::string > &	GetRelatedLayerNames ()

virtual void	Reparent (Graph &dest, std::list< Layer * >::const_iterator iterator)=0

void	BackendSelectionHint (Optional< BackendId > backend) final
	Provide a hint for the optimizer as to which backend to prefer for this layer.

Optional< BackendId >	GetBackendHint () const

void	SetShapeInferenceMethod (ShapeInferenceMethod shapeInferenceMethod)

void	SetAllowExpandedDims (bool allowExpandedDims)

template<typename T >
std::shared_ptr< T >	GetAdditionalInformation () const

void	SetAdditionalInfoForObject (const AdditionalInfoObjectPtr &additionalInfo)

virtual const BaseDescriptor &	GetParameters () const override
	If the layer has a descriptor return it.

Protected Member Functions
	PreluLayer (const char *name)
	Constructor to create a PreluLayer.

	~PreluLayer ()=default
	Default destructor.

Protected Member Functions inherited from Layer
virtual	~Layer ()=default

template<typename QueueDescriptor >
void	CollectQueueDescriptorInputs (QueueDescriptor &descriptor, WorkloadInfo &info) const

template<typename QueueDescriptor >
void	CollectQueueDescriptorOutputs (QueueDescriptor &descriptor, WorkloadInfo &info) const

void	ValidateAndCopyShape (const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)

void	VerifyShapeInferenceType (const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)

template<typename QueueDescriptor >
WorkloadInfo	PrepInfoAndDesc (QueueDescriptor &descriptor) const
	Helper function to reduce duplication in *LayerCreateWorkload.

template<typename LayerType , typename ... Params>
LayerType *	CloneBase (Graph &graph, Params &&... params) const

virtual ConstantTensors	GetConstantTensorsByRef () override final

virtual ImmutableConstantTensors	GetConstantTensorsByRef () const override

void	SetAdditionalInfo (QueueDescriptor &descriptor) const

Protected Member Functions inherited from IConnectableLayer
	~IConnectableLayer ()
	Objects are not deletable via the handle.

Additional Inherited Members
Public Types inherited from IConnectableLayer
using	ConstantTensors = std::vector<std::reference_wrapper<std::shared_ptr<ConstTensorHandle>>>

using	ImmutableConstantTensors = std::vector<std::reference_wrapper<const std::shared_ptr<ConstTensorHandle>>>

Protected Attributes inherited from Layer
AdditionalInfoObjectPtr	m_AdditionalInfoObject

std::vector< OutputHandler >	m_OutputHandlers

ShapeInferenceMethod	m_ShapeInferenceMethod

Detailed Description

Definition at line 14 of file PreluLayer.hpp.

Constructor & Destructor Documentation

◆ PreluLayer()

PreluLayer ( const char * name )

protected

Constructor to create a PreluLayer.

Parameters

[in] name Optional name for the layer.

Definition at line 19 of file PreluLayer.cpp.

20 : Layer(2, 1, LayerType::Prelu, name)

21{}

armnn::Layer::Layer

Layer(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char *name)

Definition Layer.cpp:260

armnn::LayerType::Prelu

@ Prelu

◆ ~PreluLayer()

~PreluLayer ( )

protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

PreluLayer * Clone ( Graph & graph ) const

overridevirtual

Creates a dynamically-allocated copy of this layer.

Parameters

[in] graph The graph into which this layer is being cloned.

Implements Layer.

Definition at line 31 of file PreluLayer.cpp.

{
    auto layer = CloneBase<PreluLayer>(graph, GetName());
 
    return std::move(layer);
}

References Layer::GetName().

◆ CreateWorkload()

std::unique_ptr< IWorkload > CreateWorkload ( const IWorkloadFactory & factory ) const

overridevirtual

Makes a workload for the PReLU type.

Parameters

[in]	graph	The graph where this layer can be found.
[in]	factory	The workload factory which will create the workload.

Returns: A pointer to the created workload, or nullptr if not created.

Implements Layer.

Definition at line 23 of file PreluLayer.cpp.

{
    PreluQueueDescriptor descriptor;
    SetAdditionalInfo(descriptor);
 
    return factory.CreateWorkload(LayerType::Prelu, descriptor, PrepInfoAndDesc(descriptor));
}

References IWorkloadFactory::CreateWorkload(), armnn::Prelu, Layer::PrepInfoAndDesc(), and Layer::SetAdditionalInfo().

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy & strategy ) const

overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 138 of file PreluLayer.cpp.

{
    strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
}

References IStrategy::ExecuteStrategy(), Layer::GetName(), and Layer::GetParameters().

◆ InferOutputShapes()

std::vector< TensorShape > InferOutputShapes ( const std::vector< TensorShape > & inputShapes ) const

overridevirtual

By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties.

Parameters

[in] inputShapes The input shapes layer has.

Returns: A vector to the inferred output shape.

Reimplemented from Layer.

Definition at line 38 of file PreluLayer.cpp.

{
    if (inputShapes.size() != 2)
    {
        throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
                               "\" - should be \"2\".");
    }
 
    const TensorShape& inputShape = inputShapes[0];
    const TensorShape& alphaShape = inputShapes[1];
 
    const unsigned int inputShapeDimensions = inputShape.GetNumDimensions();
    const unsigned int alphaShapeDimensions = alphaShape.GetNumDimensions();
 
    if (inputShapeDimensions == 0)
    {
        throw armnn::Exception("inputShapeDimensions must be greater than 0.");
    }
 
    if (alphaShapeDimensions == 0)
    {
       throw armnn::Exception("alphaShapeDimensions must be not be zero (\""
                              + std::to_string(alphaShapeDimensions) + "\")");
    }
 
    // The size of the output is the maximum size along each dimension of the input operands,
    // it starts with the trailing dimensions, and works its way forward
 
    unsigned int outputDimensions = std::max(inputShapeDimensions, alphaShapeDimensions);
 
    TensorShape outputShape(outputDimensions);
 
    int inputShapeIndex = armnn::numeric_cast<int>(inputShapeDimensions) - 1;
    int alphaShapeIndex = armnn::numeric_cast<int>(alphaShapeDimensions) - 1;
    unsigned int outputShapeIndex = outputDimensions - 1;
 
    // Loop backwards through the common part of the shapes
    while (inputShapeIndex >= 0 && alphaShapeIndex >= 0)
    {
        unsigned int inputDimension = inputShape[armnn::numeric_cast<unsigned int>(inputShapeIndex)];
        unsigned int alphaDimension = alphaShape[armnn::numeric_cast<unsigned int>(alphaShapeIndex)];
 
        // Check that the inputs are broadcast compatible
        if (inputDimension != alphaDimension && inputDimension != 1 && alphaDimension != 1)
        {
            throw armnn::Exception("PreluLayer: Dimensions should either match or one should be of size 1");
        }
 
        outputShape[outputShapeIndex] = std::max(inputDimension, alphaDimension);
 
        inputShapeIndex--;
        alphaShapeIndex--;
        outputShapeIndex--;
    }
 
    // Loop backwards through the remaing part of the input shape (if any)
    while (inputShapeIndex >= 0)
    {
        outputShape[outputShapeIndex] = inputShape[armnn::numeric_cast<unsigned int>(inputShapeIndex)];
 
        inputShapeIndex--;
        outputShapeIndex--;
    }
 
    // Loop backwards through the remaing part of the alpha shape (if any)
    while (alphaShapeIndex >= 0)
    {
        outputShape[outputShapeIndex] = alphaShape[armnn::numeric_cast<unsigned int>(alphaShapeIndex)];
 
        alphaShapeIndex--;
        outputShapeIndex--;
    }
 
    return { outputShape };
}

References TensorShape::GetNumDimensions().

Referenced by PreluLayer::ValidateTensorShapesFromInputs().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )

overridevirtual

Check if the input tensor shape(s) will lead to a valid configuration of PreluLayer.

Parameters

[in] shapeInferenceMethod Indicates if output shape shall be overwritten or just validated.

Implements Layer.

Definition at line 114 of file PreluLayer.cpp.

{
    VerifyLayerConnections(2, CHECK_LOCATION());
 
    const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
 
    VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
 
    std::vector<TensorShape> inferredShapes = InferOutputShapes(
    {
        GetInputSlot(0).GetTensorInfo().GetShape(),
        GetInputSlot(1).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, "PreluLayer");
}

References CHECK_LOCATION, Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), InputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), PreluLayer::InferOutputShapes(), Layer::m_ShapeInferenceMethod, Layer::ValidateAndCopyShape(), Layer::VerifyLayerConnections(), and Layer::VerifyShapeInferenceType().

The documentation for this class was generated from the following files:

src/armnn/layers/PreluLayer.hpp
src/armnn/layers/PreluLayer.cpp

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ PreluLayer()

◆ ~PreluLayer()

Member Function Documentation

◆ Clone()

◆ CreateWorkload()

◆ ExecuteStrategy()

◆ InferOutputShapes()

◆ ValidateTensorShapesFromInputs()