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This layer represents a mean operation. + More...

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#include <MeanLayer.hpp>

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+Inheritance diagram for MeanLayer:

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

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

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

void	Accept (ILayerVisitor &visitor) const override
	Apply a visitor to this layer. More...

Public Member Functions inherited from LayerWithParameters< MeanDescriptor >
const MeanDescriptor &	GetParameters () const

void	SerializeLayerParameters (ParameterStringifyFunction &fn) const override
	Helper to serialize the layer parameters to string (currently used in DotSerializer and company). More...

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)

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

DataType	GetDataType () const

const BackendId &	GetBackendId () const

void	SetBackendId (const BackendId &id)

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

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

std::vector< TensorShape >	InferOutputShapes (const std::vector< TensorShape > &inputShapes) const override
	Infer the shape of the output(s) based on the provided input shape(s) More...

virtual void	ReleaseConstantData ()

template<typename Op >
void	OperateOnConstantTensors (Op op)

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

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

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

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

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

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

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

void	SetGuid (LayerGuid guid)

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

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. More...

Optional< BackendId >	GetBackendHint () const

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+Protected Member Functions
	MeanLayer (const MeanDescriptor &param, const char *name)
	Constructor to create a MeanLayer. More...

	~MeanLayer ()=default
	Default destructor. More...

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. More...

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

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

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

virtual ConstantTensors	GetConstantTensorsByRef ()

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

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+Additional Inherited Members
Public Types inherited from LayerWithParameters< MeanDescriptor >
using	DescriptorType = MeanDescriptor

Protected Types inherited from Layer
using	ConstantTensors = std::vector< std::reference_wrapper< std::unique_ptr< ScopedCpuTensorHandle > >>

Protected Attributes inherited from LayerWithParameters< MeanDescriptor >
MeanDescriptor	m_Param
	The parameters for the layer (not including tensor-valued weights etc.). More...

Protected Attributes inherited from Layer
std::vector< OutputHandler >	m_OutputHandlers

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Detailed Description

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This layer represents a mean operation.

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Definition at line 14 of file MeanLayer.hpp.

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Constructor & Destructor Documentation

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◆ MeanLayer()

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

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+protected

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Constructor to create a MeanLayer.

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Parameters

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

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Definition at line 18 of file MeanLayer.cpp.

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

20 {}

armnn::LayerWithParameters< MeanDescriptor >::LayerWithParameters

LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const MeanDescriptor &param, const char *name)

Definition: LayerWithParameters.hpp:29

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armnn::LayerType::Mean

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◆ ~MeanLayer()

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~MeanLayer ( )

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+protecteddefault

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Default destructor.

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Member Function Documentation

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◆ Accept()

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void Accept ( ILayerVisitor & visitor ) const

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+overridevirtual

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Apply a visitor to this layer.

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Implements IConnectableLayer.

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Definition at line 102 of file MeanLayer.cpp.

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References Layer::GetName(), LayerWithParameters< MeanDescriptor >::GetParameters(), and ILayerVisitor::VisitMeanLayer().

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 {
     visitor.VisitMeanLayer(this, GetParameters(), GetName());
 }

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◆ Clone()

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MeanLayer * Clone ( Graph & graph ) const

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+overridevirtual

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Creates a dynamically-allocated copy of this layer.

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Parameters

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

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Implements Layer.

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Definition at line 31 of file MeanLayer.cpp.

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References Layer::GetName(), MeanDescriptor::m_Axis, LayerWithParameters< Parameters >::m_Param, and LayerWithParameters< MeanDescriptor >::m_Param.

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 {
     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);
 }

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◆ CreateWorkload()

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

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+overridevirtual

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Makes a workload for the Mean type.

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Parameters

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

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

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Implements Layer.

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Definition at line 22 of file MeanLayer.cpp.

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References IWorkloadFactory::CreateMean(), MeanDescriptor::m_Axis, MeanDescriptor::m_KeepDims, LayerWithParameters< MeanDescriptor >::m_Param, QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters, and LayerWithParameters< MeanDescriptor >::PrepInfoAndDesc().

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 {
     MeanQueueDescriptor descriptor;
     descriptor.m_Parameters.m_Axis = m_Param.m_Axis;
     descriptor.m_Parameters.m_KeepDims = m_Param.m_KeepDims;
 
     return factory.CreateMean(descriptor, PrepInfoAndDesc(descriptor));
 }

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◆ ValidateTensorShapesFromInputs()

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void ValidateTensorShapesFromInputs ( )

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+overridevirtual

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

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Implements Layer.

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Definition at line 41 of file MeanLayer.cpp.

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References CHECK_LOCATION, InputSlot::GetConnection(), Layer::GetInputSlot(), TensorInfo::GetNumDimensions(), Layer::GetOutputSlot(), TensorInfo::GetShape(), IOutputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), MeanDescriptor::m_Axis, MeanDescriptor::m_KeepDims, LayerWithParameters< MeanDescriptor >::m_Param, armnn::numeric_cast(), and Layer::VerifyLayerConnections().

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 {
     VerifyLayerConnections(1, CHECK_LOCATION());
 
     const TensorInfo& input = GetInputSlot(0).GetConnection()->GetTensorInfo();
 
     BOOST_ASSERT_MSG(input.GetNumDimensions() > 0 && input.GetNumDimensions() <= 4,
                      "MeanLayer: Mean 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() - boost::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] = boost::numeric_cast<unsigned int>(input.GetShape()[i]);
                 ++outputIndex;
             }
             else if (m_Param.m_KeepDims)
             {
                 dimSizes[outputIndex] = 1;
                 ++outputIndex;
             }
         }
     }
     const TensorShape& inferredShape = TensorShape(outputRank, dimSizes.data());
 
     ConditionalThrowIfNotEqual<LayerValidationException>(
         "MeanLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
         GetOutputSlot(0).GetTensorInfo().GetShape(),
         inferredShape);
 }

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

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

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+Public Member Functions

+Protected Member Functions

+Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ MeanLayer()

◆ ~MeanLayer()

Member Function Documentation

◆ Accept()

◆ Clone()

◆ CreateWorkload()

◆ ValidateTensorShapesFromInputs()