NOTE: this is an abstract class to encapsulate the element wise operations, it does not implement: std::unique_ptr<IWorkload> Layer::CreateWorkload(const IWorkloadFactory& factory) const = 0; Layer* Clone(Graph& graph) const = 0;. More...

#include <ElementwiseBaseLayer.hpp>

Inheritance diagram for ElementwiseBaseLayer:

Public Member Functions
void	ValidateTensorShapesFromInputs () override
	Check if the input tensor shape(s) will lead to a valid configuration of the element wise operation. 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	ExecuteStrategy (IStrategy &strategy) const override
	Apply a visitor to this layer. 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

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. More...

DataType	GetDataType () const

const BackendId &	GetBackendId () const

void	SetBackendId (const BackendId &id)

virtual std::unique_ptr< IWorkload >	CreateWorkload (const IWorkloadFactory &factory) const =0

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

virtual Layer *	Clone (Graph &graph) const =0
	Creates a dynamically-allocated copy of this layer. More...

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

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

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. More...

Protected Member Functions
	ElementwiseBaseLayer (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char *name)

	~ElementwiseBaseLayer ()=default
	Default destructor. 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 () override

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 IConnectableLayer
using	ConstantTensors = std::vector< std::reference_wrapper< std::shared_ptr< ConstTensorHandle > >>

Protected Attributes inherited from Layer
AdditionalInfoObjectPtr	m_AdditionalInfoObject

std::vector< OutputHandler >	m_OutputHandlers

ShapeInferenceMethod	m_ShapeInferenceMethod

Detailed Description

NOTE: this is an abstract class to encapsulate the element wise operations, it does not implement: std::unique_ptr<IWorkload> Layer::CreateWorkload(const IWorkloadFactory& factory) const = 0; Layer* Clone(Graph& graph) const = 0;.

Definition at line 16 of file ElementwiseBaseLayer.hpp.

Constructor & Destructor Documentation

◆ ElementwiseBaseLayer()

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

protected

Parameters

numInputSlots	The number of input slots for the layer.
numOutputSlots	The number of output slots for the layer.
type	The layer type.
name	Optional name for the layer.

Definition at line 16 of file ElementwiseBaseLayer.cpp.

20 : Layer(numInputSlots, numOutputSlots, type, name)

21 {}

armnn::Layer::Layer

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

Definition: Layer.cpp:247

◆ ~ElementwiseBaseLayer()

~ElementwiseBaseLayer ( )

protecteddefault

Default destructor.

Member Function Documentation

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy & strategy ) const

overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Reimplemented in MaximumLayer, MinimumLayer, MultiplicationLayer, and SubtractionLayer.

Definition at line 92 of file ElementwiseBaseLayer.cpp.

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

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

◆ 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 23 of file ElementwiseBaseLayer.cpp.

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, CHECK_LOCATION, armnn::GetLayerTypeAsCString(), Layer::GetName(), TensorShape::GetNumDimensions(), Layer::GetType(), armnn::InferAndValidate, Layer::m_ShapeInferenceMethod, and armnn::ValidateOnly.

Referenced by ElementwiseBaseLayer::ValidateTensorShapesFromInputs().

 {
     ARMNN_ASSERT(inputShapes.size() == 2);
     TensorShape input0 = inputShapes[0];
     TensorShape input1 = inputShapes[1];
 
     if (m_ShapeInferenceMethod == ShapeInferenceMethod::ValidateOnly)
     {
         if (input0.GetNumDimensions() != input1.GetNumDimensions())
         {
             std::stringstream errorMessage;
             errorMessage << GetLayerTypeAsCString(GetType()) << " layer \"" << GetName() << "\": ";
             errorMessage << "The tensor inputs to an element-wise operator are expected to have equal number of "
                             "dimensions. First = "
                          << input0.GetNumDimensions() << " second = " << input1.GetNumDimensions();
             throw InvalidArgumentException(errorMessage.str(), CHECK_LOCATION());
         }
     }
     else if (m_ShapeInferenceMethod == ShapeInferenceMethod::InferAndValidate &&
              inputShapes[0].GetNumDimensions() < inputShapes[1].GetNumDimensions())
     {
         input1 = inputShapes[0];
         input0 = inputShapes[1];
     }
 
     unsigned int numDims     = input0.GetNumDimensions();
     unsigned int shiftedDims = input0.GetNumDimensions() - input1.GetNumDimensions();
 
     // Get the max of the inputs.
     std::vector<unsigned int> dims(numDims);
     for (unsigned int i = shiftedDims; i < numDims; i++)
     {
         unsigned int dim0 = input0[i];
         unsigned int dim1 = input1[i - shiftedDims];
 
 #if !NDEBUG
         // Validate inputs are broadcast compatible.
         ARMNN_ASSERT_MSG(dim0 == dim1 || dim0 == 1 || dim1 == 1,
                          "Dimensions should either match or one should be of size 1.");
 #endif
 
         dims[i] = std::max(dim0, dim1);
     }
 
     // Fill in the rest of the shifted dimensions.
     for (unsigned int i = 0; i < shiftedDims; i++)
     {
         dims[i] = input0[i];
     }
 
     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 the element wise operation.

Parameters

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

Implements Layer.

Definition at line 76 of file ElementwiseBaseLayer.cpp.

References ARMNN_ASSERT, CHECK_LOCATION, InputSlot::GetConnection(), Layer::GetInputSlot(), armnn::GetLayerTypeAsCString(), Layer::GetOutputSlot(), TensorInfo::GetShape(), IOutputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), Layer::GetType(), ElementwiseBaseLayer::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);
 
     auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
                                               GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape() });
 
     ARMNN_ASSERT(inferredShapes.size() == 1);
 
     ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, GetLayerTypeAsCString(GetType()));
 }

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

src/armnn/layers/ElementwiseBaseLayer.hpp
src/armnn/layers/ElementwiseBaseLayer.cpp

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ ElementwiseBaseLayer()

◆ ~ElementwiseBaseLayer()

Member Function Documentation

◆ ExecuteStrategy()

◆ InferOutputShapes()

◆ ValidateTensorShapesFromInputs()