#include <BatchMatMulLayer.hpp>

Inheritance diagram for BatchMatMulLayer:

Collaboration diagram for BatchMatMulLayer:

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

BatchMatMulLayer *	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
	Infers the output shape from the given input shapes. More...

void	ValidateTensorShapesFromInputs () override
	Check if the input tensor shapes will lead to a valid configuration of BatchMatMulLayer. More...

Public Member Functions inherited from LayerWithParameters< BatchMatMulDescriptor >
const BatchMatMulDescriptor &	GetParameters () const override
	If the layer has a descriptor return it. More...

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

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) override
	Set the backend of the IConnectableLayer. More...

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)

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
	BatchMatMulLayer (const BatchMatMulDescriptor &param, const char *name)
	Constructor to create a BatchMatMulLayer. More...

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

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

	~LayerWithParameters ()=default

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

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

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 *Layer::CreateWorkload. More...

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. More...

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

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< BatchMatMulDescriptor >
BatchMatMulDescriptor	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

Definition at line 13 of file BatchMatMulLayer.hpp.

Constructor & Destructor Documentation

◆ BatchMatMulLayer()

BatchMatMulLayer	(	const BatchMatMulDescriptor &	param,
		const char *	name
	)

protected

Constructor to create a BatchMatMulLayer.

Parameters

[in]	param	BatchMatMulDescriptor to configure optional parameters for batch matrix multiplication
[in]	name	Optional name for the layer

Definition at line 14 of file BatchMatMulLayer.cpp.

15 : LayerWithParameters(2, 1, LayerType::BatchMatMul, param, name)

16 {}

◆ ~BatchMatMulLayer()

~BatchMatMulLayer ( )

protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

BatchMatMulLayer * 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 26 of file BatchMatMulLayer.cpp.

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

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

◆ CreateWorkload()

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

overridevirtual

Makes a workload for the BatchMatMul 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 18 of file BatchMatMulLayer.cpp.

 {
     BatchMatMulQueueDescriptor descriptor;
     SetAdditionalInfo(descriptor);
  
     return factory.CreateWorkload(LayerType::BatchMatMul, descriptor, PrepInfoAndDesc(descriptor));
 }

References armnn::BatchMatMul, IWorkloadFactory::CreateWorkload(), LayerWithParameters< BatchMatMulDescriptor >::PrepInfoAndDesc(), and Layer::SetAdditionalInfo().

◆ InferOutputShapes()

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

overridevirtual

Infers the output shape from the given input shapes.

Parameters

[in] inputShapes The vector of input shapes for BatchMatMul.

Returns: A vector of inferred output shape.

Reimplemented from Layer.

Definition at line 33 of file BatchMatMulLayer.cpp.

 {
     if (inputShapes.size() != 2)
     {
         throw armnn::LayerValidationException("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
                                               "\" - should be \"2\".");
     }
  
     TensorShape inputXShape = inputShapes[0];
     TensorShape inputYShape = inputShapes[1];
  
     // Adjoint is assumed to be square, but we will apply the permute anyway
     if(m_Param.m_TransposeX || m_Param.m_AdjointX)
     {
         auto permuteVec = BatchMatMulDescriptor::GetPermuteVec(m_Param.m_DataLayoutX,
                                                                inputXShape);
         inputXShape = armnnUtils::Permuted(inputXShape, permuteVec);
     }
     if(m_Param.m_TransposeY || m_Param.m_AdjointY)
     {
         auto permuteVec = BatchMatMulDescriptor::GetPermuteVec(m_Param.m_DataLayoutY,
                                                                inputYShape);
         inputYShape = armnnUtils::Permuted(inputYShape, permuteVec);
     }
  
     TensorShape& longerInput = inputXShape.GetNumDimensions() >= inputYShape.GetNumDimensions()?
                                inputXShape : inputYShape;
     TensorShape& shorterInput = inputXShape.GetNumDimensions() >= inputYShape.GetNumDimensions()?
                                 inputYShape : inputXShape;
  
     unsigned int inputNumDimsOffset = longerInput.GetNumDimensions() - shorterInput.GetNumDimensions();
  
     unsigned int outputNumDimensions = longerInput.GetNumDimensions();
  
     std::vector<unsigned int> tensorDimensions(outputNumDimensions, 0);
  
     const auto& longerInputDataLayout = inputXShape.GetNumDimensions() >= inputYShape.GetNumDimensions()?
                                         m_Param.m_DataLayoutX : m_Param.m_DataLayoutY;
     auto longerAxesToMul = BatchMatMulDescriptor::GetAxesToMul(longerInputDataLayout,
                                                                longerInput);
  
     for (unsigned int i = 0; i < outputNumDimensions; ++i)
     {
         if (i == longerAxesToMul.first)
         {
             tensorDimensions[i] = &shorterInput == &inputXShape ? inputXShape[i - inputNumDimsOffset] : inputXShape[i];
         }
         else if(i == longerAxesToMul.second)
         {
             tensorDimensions[i] = &shorterInput == &inputYShape ? inputYShape[i - inputNumDimsOffset] : inputYShape[i];
         }
         else // The other dimensions not to be multiplied (but may be broadcasted)
         {
             // Does NOT validate whether it's a valid broadcast - that's done in the validate func in WorkloadData.cpp
             tensorDimensions[i] = static_cast<int>(i) - static_cast<int>(inputNumDimsOffset) < 0 ?
                 longerInput[i] :
                 std::max(longerInput[i], shorterInput[i - inputNumDimsOffset]);
         }
     }
  
     auto outputShape = TensorShape(outputNumDimensions, tensorDimensions.data());
     return std::vector<TensorShape>({ outputShape });
 }

References BatchMatMulDescriptor::GetAxesToMul(), TensorShape::GetNumDimensions(), BatchMatMulDescriptor::GetPermuteVec(), BatchMatMulDescriptor::m_AdjointX, BatchMatMulDescriptor::m_AdjointY, BatchMatMulDescriptor::m_DataLayoutX, BatchMatMulDescriptor::m_DataLayoutY, LayerWithParameters< BatchMatMulDescriptor >::m_Param, BatchMatMulDescriptor::m_TransposeX, BatchMatMulDescriptor::m_TransposeY, and armnnUtils::Permuted().

Referenced by BatchMatMulLayer::ValidateTensorShapesFromInputs().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )

overridevirtual

Check if the input tensor shapes will lead to a valid configuration of BatchMatMulLayer.

Parameters

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

Implements Layer.

Definition at line 97 of file BatchMatMulLayer.cpp.

 {
     VerifyLayerConnections(2, CHECK_LOCATION());
  
     const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
  
     VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
  
     auto 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, "BatchMatMulLayer");
 }

References CHECK_LOCATION, Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), InputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), BatchMatMulLayer::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/BatchMatMulLayer.hpp
src/armnn/layers/BatchMatMulLayer.cpp

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ BatchMatMulLayer()

◆ ~BatchMatMulLayer()

Member Function Documentation

◆ Clone()

◆ CreateWorkload()

◆ InferOutputShapes()

◆ ValidateTensorShapesFromInputs()