This layer represents a mean operation. More...

#include <MeanLayer.hpp>

Inheritance diagram for MeanLayer:

Collaboration diagram for MeanLayer:

Public Member Functions
virtual std::unique_ptr< IWorkload >	CreateWorkload (const IWorkloadFactory &factory) const override
	Makes a workload for the Mean type.
MeanLayer *	Clone (Graph &graph) const override
	Creates a dynamically-allocated copy of this layer.
void	ValidateTensorShapesFromInputs () override
	Check if the input tensor shape(s) will lead to a valid configuration of MeanLayer.
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	ExecuteStrategy (IStrategy &strategy) const override
	Apply a visitor to this layer.
Public Member Functions inherited from LayerWithParameters< MeanDescriptor >
const MeanDescriptor &	GetParameters () const override
	If the layer has a descriptor return it.
void	SerializeLayerParameters (ParameterStringifyFunction &fn) const override
	Helper to serialize the layer parameters to string (currently used in DotSerializer and company).
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	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)

Protected Member Functions
	MeanLayer (const MeanDescriptor &param, const char *name)
	Constructor to create a MeanLayer.
	~MeanLayer ()=default
	Default destructor.
Protected Member Functions inherited from LayerWithParameters< MeanDescriptor >
	LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const MeanDescriptor &param, const char *name)
	~LayerWithParameters ()=default
WorkloadInfo	PrepInfoAndDesc (QueueDescriptor &descriptor) const
	Helper function to reduce duplication in *LayerCreateWorkload.
Layer::ImmutableConstantTensors	GetConnectedConstantAsInputTensors () const
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 LayerWithParameters< MeanDescriptor >
using	DescriptorType
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 LayerWithParameters< MeanDescriptor >
MeanDescriptor	m_Param
	The parameters for the layer (not including tensor-valued weights etc.).
Protected Attributes inherited from Layer
AdditionalInfoObjectPtr	m_AdditionalInfoObject
std::vector< OutputHandler >	m_OutputHandlers
ShapeInferenceMethod	m_ShapeInferenceMethod

Detailed Description

This layer represents a mean operation.

Definition at line 14 of file MeanLayer.hpp.

Constructor & Destructor Documentation

◆ MeanLayer()

MeanLayer	(	const MeanDescriptor &	param,
		const char *	name )

protected

Constructor to create a MeanLayer.

Parameters

[in]	param	MeanDescriptor to configure the mean operation.
[in]	name	Optional name for the layer.

Definition at line 20 of file MeanLayer.cpp.

21 : LayerWithParameters(1, 1, LayerType::Mean, param, name)

22{}

References LayerWithParameters< MeanDescriptor >::LayerWithParameters(), and armnn::Mean.

Referenced by Clone().

◆ ~MeanLayer()

~MeanLayer ( )

protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

MeanLayer * 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 34 of file MeanLayer.cpp.

{
    auto layer = CloneBase<MeanLayer>(graph, m_Param, GetName());
 
    layer->m_Param.m_Axis = m_Param.m_Axis;
    layer->m_Param.m_KeepDims = m_Param.m_KeepDims;
 
    return std::move(layer);
}

References Layer::CloneBase(), Layer::GetName(), LayerWithParameters< MeanDescriptor >::m_Param, and MeanLayer().

◆ CreateWorkload()

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

overridevirtual

Makes a workload for the Mean 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 24 of file MeanLayer.cpp.

{
    MeanQueueDescriptor descriptor;
    descriptor.m_Parameters.m_Axis = m_Param.m_Axis;
    descriptor.m_Parameters.m_KeepDims = m_Param.m_KeepDims;
    SetAdditionalInfo(descriptor);
 
    return factory.CreateWorkload(LayerType::Mean, descriptor, PrepInfoAndDesc(descriptor));
}

References IWorkloadFactory::CreateWorkload(), MeanDescriptor::m_Axis, MeanDescriptor::m_KeepDims, LayerWithParameters< MeanDescriptor >::m_Param, QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters, armnn::Mean, LayerWithParameters< MeanDescriptor >::PrepInfoAndDesc(), and Layer::SetAdditionalInfo().

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy & strategy ) const

overridevirtual

Apply a visitor to this layer.

Reimplemented from LayerWithParameters< MeanDescriptor >.

Definition at line 133 of file MeanLayer.cpp.

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

References IStrategy::ExecuteStrategy(), Layer::GetName(), and LayerWithParameters< MeanDescriptor >::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 70 of file MeanLayer.cpp.

{
    if (inputShapes.size() != 1)
    {
        throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
                               "\" - should be \"1\".");
    }
 
    const TensorShape& input = inputShapes[0];
 
    auto inputDims = input.GetNumDimensions();
    if (inputDims < 1 || inputDims > 4)
    {
        throw armnn::Exception("ReduceLayer: Reduce supports up to 4D input.");
    }
 
    unsigned int rank = input.GetNumDimensions();
    unsigned int outputRank = 0;
 
    // Calculate output dimension
    if (m_Param.m_KeepDims)
    {
        outputRank = rank;
    }
    else if (m_Param.m_Axis.empty())
    {
        outputRank = 1;
    }
    else if (m_Param.m_Axis.size() > input.GetNumDimensions())
    {
        throw LayerValidationException("MeanLayer: Dimensions to reduce can not be bigger than input dimensions");
    }
    else
    {
        outputRank = input.GetNumDimensions() - armnn::numeric_cast<unsigned int>(m_Param.m_Axis.size());
        if (outputRank == 0)
        {
            outputRank = 1;
        }
    }
 
    std::vector<unsigned int> dimSizes(outputRank, 1);
    if (!m_Param.m_Axis.empty())
    {
        // Skip the dimension that has been reduced unless keepDims is true.
        unsigned int outputIndex = 0;
        for (unsigned int i = 0; i < input.GetNumDimensions(); ++i)
        {
            if (std::find(m_Param.m_Axis.begin(), m_Param.m_Axis.end(), i) == m_Param.m_Axis.end())
            {
                dimSizes[outputIndex] = armnn::numeric_cast<unsigned int>(input[i]);
                ++outputIndex;
            }
            else if (m_Param.m_KeepDims)
            {
                dimSizes[outputIndex] = 1;
                ++outputIndex;
            }
        }
    }
    return std::vector<TensorShape>({ TensorShape(outputRank, dimSizes.data()) });
}

References TensorShape::GetNumDimensions(), LayerWithParameters< MeanDescriptor >::m_Param, and armnn::numeric_cast().

Referenced by ValidateTensorShapesFromInputs().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )

overridevirtual

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

Parameters

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

Implements Layer.

Definition at line 44 of file MeanLayer.cpp.

{
    VerifyLayerConnections(1, CHECK_LOCATION());
 
    const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
 
    VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
 
    std::vector<TensorShape> 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.");
    }
 
    if (inferredShapes[0].GetDimensionality() != Dimensionality::Specified)
    {
        throw armnn::LayerValidationException("inferredShapes' dimensionality has not been specified.");
    }
 
    ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "MeanLayer");
}

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

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

src/armnn/layers/MeanLayer.hpp
src/armnn/layers/MeanLayer.cpp

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ MeanLayer()

◆ ~MeanLayer()

Member Function Documentation

◆ Clone()

◆ CreateWorkload()

◆ ExecuteStrategy()

◆ InferOutputShapes()

◆ ValidateTensorShapesFromInputs()