This layer represents a Logical Binary operation. More...

#include <LogicalBinaryLayer.hpp>

Inheritance diagram for LogicalBinaryLayer:

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

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

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. More...

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

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

Public Member Functions inherited from LayerWithParameters< LogicalBinaryDescriptor >
const LogicalBinaryDescriptor &	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)

ShapeInferenceMethod	GetShapeInferenceMethod () 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. More...

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

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

void	SetShapeInferenceMethod (ShapeInferenceMethod shapeInferenceMethod)

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

void	SetAdditionalInfoForObject (const AdditionalInfoObjectPtr &additionalInfo)

Protected Member Functions
	LogicalBinaryLayer (const LogicalBinaryDescriptor &param, const char *name)
	Constructor to create a LogicalBinaryLayer. More...

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

Protected Member Functions inherited from LayerWithParameters< LogicalBinaryDescriptor >
	LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const LogicalBinaryDescriptor &param, const char *name)

	~LayerWithParameters ()=default

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

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

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. More...

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

virtual ConstantTensors	GetConstantTensorsByRef ()

void	SetAdditionalInfo (QueueDescriptor &descriptor) const

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

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

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

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

Protected Attributes inherited from Layer
AdditionalInfoObjectPtr	m_AdditionalInfoObject

std::vector< OutputHandler >	m_OutputHandlers

ShapeInferenceMethod	m_ShapeInferenceMethod

Detailed Description

This layer represents a Logical Binary operation.

Definition at line 14 of file LogicalBinaryLayer.hpp.

Constructor & Destructor Documentation

◆ LogicalBinaryLayer()

LogicalBinaryLayer	(	const LogicalBinaryDescriptor &	param,
		const char *	name
	)

protected

Constructor to create a LogicalBinaryLayer.

Parameters

[in]	param	LogicalBinaryDescriptor to configure the LogicalBinaryLayer
[in]	name	Optional name for the layer

Definition at line 18 of file LogicalBinaryLayer.cpp.

References armnn::LogicalBinary.

     : LayerWithParameters(2, 1, LayerType::LogicalBinary, param, name)
 {
 }

◆ ~LogicalBinaryLayer()

~LogicalBinaryLayer ( )

protecteddefault

Default destructor.

Member Function Documentation

◆ Accept()

void Accept ( ILayerVisitor & visitor ) const

overridevirtual

Apply a visitor to this layer.

Implements IConnectableLayer.

Definition at line 75 of file LogicalBinaryLayer.cpp.

References Layer::GetName(), LayerWithParameters< LogicalBinaryDescriptor >::GetParameters(), and ILayerVisitor::VisitLogicalBinaryLayer().

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

◆ Clone()

LogicalBinaryLayer * 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 29 of file LogicalBinaryLayer.cpp.

References Layer::GetName(), and LayerWithParameters< LogicalBinaryDescriptor >::m_Param.

 {
     return CloneBase<LogicalBinaryLayer>(graph, m_Param, GetName());
 }

◆ CreateWorkload()

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

overridevirtual

Makes a workload for the LogicalBinary 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 LogicalBinaryLayer.cpp.

References IWorkloadFactory::CreateLogicalBinary(), and LayerWithParameters< LogicalBinaryDescriptor >::PrepInfoAndDesc().

 {
     LogicalBinaryQueueDescriptor descriptor;
     return factory.CreateLogicalBinary(descriptor, PrepInfoAndDesc(descriptor));
 }

◆ 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 34 of file LogicalBinaryLayer.cpp.

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, and TensorShape::GetNumDimensions().

Referenced by LogicalBinaryLayer::ValidateTensorShapesFromInputs().

 {
     ARMNN_ASSERT(inputShapes.size() == 2);
     const TensorShape& input0 = inputShapes[0];
     const TensorShape& input1 = inputShapes[1];
 
     ARMNN_ASSERT(input0.GetNumDimensions() == input1.GetNumDimensions());
     unsigned int numDims = input0.GetNumDimensions();
 
     std::vector<unsigned int> dims(numDims);
     for (unsigned int i = 0; i < numDims; i++)
     {
         unsigned int dim0 = input0[i];
         unsigned int dim1 = input1[i];
 
         ARMNN_ASSERT_MSG(dim0 == dim1 || dim0 == 1 || dim1 == 1,
                          "Dimensions should either match or one should be of size 1.");
 
         dims[i] = std::max(dim0, dim1);
     }
 
     return std::vector<TensorShape>({ TensorShape(numDims, dims.data()) });
 }

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )

overridevirtual

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

Parameters

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

Implements Layer.

Definition at line 58 of file LogicalBinaryLayer.cpp.

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

 {
     VerifyLayerConnections(2, CHECK_LOCATION());
 
     const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
 
     VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
 
     std::vector<TensorShape> inferredShapes = InferOutputShapes({
         GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
         GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape()
     });
     ARMNN_ASSERT(inferredShapes.size() == 1);
 
     ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "LogicalBinaryLayer");
 }

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

src/armnn/layers/LogicalBinaryLayer.hpp
src/armnn/layers/LogicalBinaryLayer.cpp

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ LogicalBinaryLayer()

◆ ~LogicalBinaryLayer()

Member Function Documentation

◆ Accept()

◆ Clone()

◆ CreateWorkload()

◆ InferOutputShapes()

◆ ValidateTensorShapesFromInputs()