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This layer represents a batch normalization operation. + More...

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#include <BatchNormalizationLayer.hpp>

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+Inheritance diagram for BatchNormalizationLayer:

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

BatchNormalizationLayer *	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 BatchNormalizationLayer. More...

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

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

Public Member Functions inherited from LayerWithParameters< BatchNormalizationDescriptor >
const BatchNormalizationDescriptor &	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

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

void	SetShapeInferenceMethod (ShapeInferenceMethod shapeInferenceMethod)

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

void	SetAdditionalInfoForObject (const AdditionalInfoObjectPtr &additionalInfo)

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+Public Attributes
std::unique_ptr< ScopedCpuTensorHandle >	m_Mean
	A unique pointer to store Mean values. More...

std::unique_ptr< ScopedCpuTensorHandle >	m_Variance
	A unique pointer to store Variance values. More...

std::unique_ptr< ScopedCpuTensorHandle >	m_Beta
	A unique pointer to store Beta values. More...

std::unique_ptr< ScopedCpuTensorHandle >	m_Gamma
	A unique pointer to store Gamma values. More...

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

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

ConstantTensors	GetConstantTensorsByRef () override
	Retrieve the handles to the constant values stored by the layer. More...

Protected Member Functions inherited from LayerWithParameters< BatchNormalizationDescriptor >
	LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const BatchNormalizationDescriptor &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

void	SetAdditionalInfo (QueueDescriptor &descriptor) const

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< BatchNormalizationDescriptor >
using	DescriptorType = BatchNormalizationDescriptor

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

Protected Attributes inherited from LayerWithParameters< BatchNormalizationDescriptor >
BatchNormalizationDescriptor	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

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Detailed Description

+

This layer represents a batch normalization operation.

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Definition at line 15 of file BatchNormalizationLayer.hpp.

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Constructor & Destructor Documentation

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◆ BatchNormalizationLayer()

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BatchNormalizationLayer	(	const BatchNormalizationDescriptor &	param,
		const char *	name
	)

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+protected

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Constructor to create a BatchNormalizationLayer.

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Parameters

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[in]	param	BatchNormalizationDescriptor to configure the batch normalization operation.
[in]	name	Optional name for the layer.

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Definition at line 16 of file BatchNormalizationLayer.cpp.

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References armnn::BatchNormalization.

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     : LayerWithParameters(1, 1, LayerType::BatchNormalization, param, name)
 {
 }

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◆ ~BatchNormalizationLayer()

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~BatchNormalizationLayer ( )

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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 73 of file BatchNormalizationLayer.cpp.

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References Layer::GetName(), LayerWithParameters< BatchNormalizationDescriptor >::GetParameters(), BatchNormalizationLayer::m_Beta, BatchNormalizationLayer::m_Gamma, BatchNormalizationLayer::m_Mean, BatchNormalizationLayer::m_Variance, and ILayerVisitor::VisitBatchNormalizationLayer().

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 {
     ConstTensor meanTensor(m_Mean->GetTensorInfo(), m_Mean->Map(true));
     ConstTensor varianceTensor(m_Variance->GetTensorInfo(), m_Variance->Map(true));
     ConstTensor betaTensor(m_Beta->GetTensorInfo(), m_Beta->Map(true));
     ConstTensor gammaTensor(m_Gamma->GetTensorInfo(), m_Gamma->Map(true));
     visitor.VisitBatchNormalizationLayer(
             this, GetParameters(), meanTensor, varianceTensor, betaTensor, gammaTensor, GetName());
 }

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◆ Clone()

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BatchNormalizationLayer * 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 40 of file BatchNormalizationLayer.cpp.

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References Layer::GetName(), BatchNormalizationLayer::m_Beta, BatchNormalizationLayer::m_Gamma, BatchNormalizationLayer::m_Mean, LayerWithParameters< BatchNormalizationDescriptor >::m_Param, and BatchNormalizationLayer::m_Variance.

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 {
     auto layer = CloneBase<BatchNormalizationLayer>(graph, m_Param, GetName());
 
     layer->m_Mean = m_Mean ? std::make_unique<ScopedCpuTensorHandle>(*m_Mean) : nullptr;
     layer->m_Variance = m_Variance ? std::make_unique<ScopedCpuTensorHandle>(*m_Variance) : nullptr;
     layer->m_Beta = m_Beta ? std::make_unique<ScopedCpuTensorHandle>(*m_Beta) : nullptr;
     layer->m_Gamma = m_Gamma ? std::make_unique<ScopedCpuTensorHandle>(*m_Gamma) : nullptr;
 
     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 BatchNormalization 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 21 of file BatchNormalizationLayer.cpp.

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References ARMNN_ASSERT_MSG, IWorkloadFactory::CreateBatchNormalization(), BatchNormalizationLayer::m_Beta, BatchNormalizationQueueDescriptor::m_Beta, BatchNormalizationLayer::m_Gamma, BatchNormalizationQueueDescriptor::m_Gamma, BatchNormalizationLayer::m_Mean, BatchNormalizationQueueDescriptor::m_Mean, BatchNormalizationLayer::m_Variance, BatchNormalizationQueueDescriptor::m_Variance, LayerWithParameters< BatchNormalizationDescriptor >::PrepInfoAndDesc(), and Layer::SetAdditionalInfo().

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 {
     // on this level constant data should not be released..
     ARMNN_ASSERT_MSG(m_Mean != nullptr, "BatchNormalizationLayer: Mean data should not be null.");
     ARMNN_ASSERT_MSG(m_Variance != nullptr, "BatchNormalizationLayer: Variance data should not be null.");
     ARMNN_ASSERT_MSG(m_Beta != nullptr, "BatchNormalizationLayer: Beta data should not be null.");
     ARMNN_ASSERT_MSG(m_Gamma != nullptr, "BatchNormalizationLayer: Gamma data should not be null.");
 
     BatchNormalizationQueueDescriptor descriptor;
     SetAdditionalInfo(descriptor);
 
     descriptor.m_Mean = m_Mean.get();
     descriptor.m_Variance = m_Variance.get();
     descriptor.m_Beta = m_Beta.get();
     descriptor.m_Gamma = m_Gamma.get();
 
     return factory.CreateBatchNormalization(descriptor, PrepInfoAndDesc(descriptor));
 }

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◆ ExecuteStrategy()

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void ExecuteStrategy ( IStrategy & strategy ) const

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+overridevirtual

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Apply a visitor to this layer.

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Reimplemented from Layer.

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Definition at line 83 of file BatchNormalizationLayer.cpp.

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References IStrategy::ExecuteStrategy(), Layer::GetName(), LayerWithParameters< BatchNormalizationDescriptor >::GetParameters(), BatchNormalizationLayer::m_Beta, BatchNormalizationLayer::m_Gamma, BatchNormalizationLayer::m_Mean, and BatchNormalizationLayer::m_Variance.

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 {
     std::vector<armnn::ConstTensor> constTensors { {m_Mean->GetTensorInfo(), m_Mean->Map(true)},
                                                    {m_Variance->GetTensorInfo(), m_Variance->Map(true)},
                                                    {m_Beta->GetTensorInfo(), m_Beta->Map(true)},
                                                    {m_Gamma->GetTensorInfo(), m_Gamma->Map(true)} };
 
     strategy.ExecuteStrategy(this, GetParameters(), constTensors, GetName());
 }

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◆ GetConstantTensorsByRef()

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Layer::ConstantTensors GetConstantTensorsByRef ( )

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+overrideprotectedvirtual

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Retrieve the handles to the constant values stored by the layer.

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Returns: A vector of the constant tensors stored by this layer.

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Reimplemented from Layer.

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Definition at line 68 of file BatchNormalizationLayer.cpp.

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References BatchNormalizationLayer::m_Beta, BatchNormalizationLayer::m_Gamma, BatchNormalizationLayer::m_Mean, and BatchNormalizationLayer::m_Variance.

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 {
     return {m_Mean, m_Variance, m_Beta, m_Gamma};
 }

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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 BatchNormalizationLayer.

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Parameters

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

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Implements Layer.

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Definition at line 52 of file BatchNormalizationLayer.cpp.

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

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

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Member Data Documentation

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◆ m_Beta

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std::unique_ptr<ScopedCpuTensorHandle> m_Beta

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A unique pointer to store Beta values.

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Definition at line 23 of file BatchNormalizationLayer.hpp.

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Referenced by BatchNormalizationLayer::Accept(), BOOST_AUTO_TEST_CASE(), BatchNormalizationLayer::Clone(), BatchNormalizationLayer::CreateWorkload(), BatchNormalizationLayer::ExecuteStrategy(), BatchNormalizationLayer::GetConstantTensorsByRef(), NeonBackend::OptimizeSubgraphView(), and ClBackend::OptimizeSubgraphView().

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◆ m_Gamma

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std::unique_ptr<ScopedCpuTensorHandle> m_Gamma

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A unique pointer to store Gamma values.

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Definition at line 25 of file BatchNormalizationLayer.hpp.

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Referenced by BatchNormalizationLayer::Accept(), BOOST_AUTO_TEST_CASE(), BatchNormalizationLayer::Clone(), BatchNormalizationLayer::CreateWorkload(), BatchNormalizationLayer::ExecuteStrategy(), BatchNormalizationLayer::GetConstantTensorsByRef(), NeonBackend::OptimizeSubgraphView(), and ClBackend::OptimizeSubgraphView().

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◆ m_Mean

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std::unique_ptr<ScopedCpuTensorHandle> m_Mean

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A unique pointer to store Mean values.

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Definition at line 19 of file BatchNormalizationLayer.hpp.

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Referenced by BatchNormalizationLayer::Accept(), NetworkImpl::AddBatchNormalizationLayer(), BOOST_AUTO_TEST_CASE(), BatchNormalizationLayer::Clone(), BatchNormalizationLayer::CreateWorkload(), BatchNormalizationLayer::ExecuteStrategy(), BatchNormalizationLayer::GetConstantTensorsByRef(), NeonBackend::OptimizeSubgraphView(), and ClBackend::OptimizeSubgraphView().

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◆ m_Variance

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std::unique_ptr<ScopedCpuTensorHandle> m_Variance

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A unique pointer to store Variance values.

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Definition at line 21 of file BatchNormalizationLayer.hpp.

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Referenced by BatchNormalizationLayer::Accept(), BOOST_AUTO_TEST_CASE(), BatchNormalizationLayer::Clone(), BatchNormalizationLayer::CreateWorkload(), BatchNormalizationLayer::ExecuteStrategy(), BatchNormalizationLayer::GetConstantTensorsByRef(), NeonBackend::OptimizeSubgraphView(), and ClBackend::OptimizeSubgraphView().

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

src/armnn/layers/BatchNormalizationLayer.hpp
src/armnn/layers/BatchNormalizationLayer.cpp

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+Public Member Functions

+Public Attributes

+Protected Member Functions

+Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ BatchNormalizationLayer()

◆ ~BatchNormalizationLayer()

Member Function Documentation

◆ Accept()

◆ Clone()

◆ CreateWorkload()

◆ ExecuteStrategy()

◆ GetConstantTensorsByRef()

◆ ValidateTensorShapesFromInputs()

Member Data Documentation

◆ m_Beta

◆ m_Gamma

◆ m_Mean

◆ m_Variance