ArmNN
 24.02
BatchNormalizationLayer Class Reference

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

#include <BatchNormalizationLayer.hpp>

Inheritance diagram for BatchNormalizationLayer:
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Collaboration diagram for BatchNormalizationLayer:
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Public Member Functions

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the BatchNormalization type. More...
 
BatchNormalizationLayerClone (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 ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this layer. More...
 
- Public Member Functions inherited from LayerWithParameters< BatchNormalizationDescriptor >
const BatchNormalizationDescriptorGetParameters () 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 OutputHandlerGetOutputHandler (unsigned int i=0) const
 
OutputHandlerGetOutputHandler (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 BackendIdGetBackendId () 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
 
std::vector< TensorShapeInferOutputShapes (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 InputSlotGetInputSlot (unsigned int index) const override
 Get a const input slot handle by slot index. More...
 
InputSlotGetInputSlot (unsigned int index) override
 Get the input slot handle by slot index. More...
 
const OutputSlotGetOutputSlot (unsigned int index=0) const override
 Get the const output slot handle by slot index. More...
 
OutputSlotGetOutputSlot (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< BackendIdGetBackendHint () 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 BaseDescriptorGetParameters () const override
 If the layer has a descriptor return it. More...
 

Public Attributes

std::shared_ptr< ConstTensorHandlem_Mean
 A unique pointer to store Mean values. More...
 
std::shared_ptr< ConstTensorHandlem_Variance
 A unique pointer to store Variance values. More...
 
std::shared_ptr< ConstTensorHandlem_Beta
 A unique pointer to store Beta values. More...
 
std::shared_ptr< ConstTensorHandlem_Gamma
 A unique pointer to store Gamma values. More...
 

Protected Member Functions

 BatchNormalizationLayer (const BatchNormalizationDescriptor &param, const char *name)
 Constructor to create a BatchNormalizationLayer. More...
 
 ~BatchNormalizationLayer ()=default
 Default destructor. More...
 
ImmutableConstantTensors GetConstantTensorsByRef () const 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 *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>
LayerTypeCloneBase (Graph &graph, Params &&... params) const
 
virtual ConstantTensors GetConstantTensorsByRef () override final
 
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< BatchNormalizationDescriptor >
using DescriptorType = BatchNormalizationDescriptor
 
- 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< 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< OutputHandlerm_OutputHandlers
 
ShapeInferenceMethod m_ShapeInferenceMethod
 

Detailed Description

This layer represents a batch normalization operation.

Definition at line 15 of file BatchNormalizationLayer.hpp.

Constructor & Destructor Documentation

◆ BatchNormalizationLayer()

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

Constructor to create a BatchNormalizationLayer.

Parameters
[in]paramBatchNormalizationDescriptor to configure the batch normalization operation.
[in]nameOptional name for the layer.

Definition at line 16 of file BatchNormalizationLayer.cpp.

18 {
19 }

References armnn::BatchNormalization.

◆ ~BatchNormalizationLayer()

~BatchNormalizationLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

BatchNormalizationLayer * Clone ( Graph graph) const
overridevirtual

Creates a dynamically-allocated copy of this layer.

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

Implements Layer.

Definition at line 40 of file BatchNormalizationLayer.cpp.

41 {
42  auto layer = CloneBase<BatchNormalizationLayer>(graph, m_Param, GetName());
43 
44  layer->m_Mean = m_Mean ? m_Mean : nullptr;
45  layer->m_Variance = m_Variance ? m_Variance : nullptr;
46  layer->m_Beta = m_Beta ? m_Beta : nullptr;
47  layer->m_Gamma = m_Gamma ? m_Gamma : nullptr;
48 
49  return std::move(layer);
50 }

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

◆ CreateWorkload()

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

Makes a workload for the BatchNormalization type.

Parameters
[in]graphThe graph where this layer can be found.
[in]factoryThe workload factory which will create the workload.
Returns
A pointer to the created workload, or nullptr if not created.

Implements Layer.

Definition at line 21 of file BatchNormalizationLayer.cpp.

22 {
23  // on this level constant data should not be released..
24  ARMNN_ASSERT_MSG(m_Mean != nullptr, "BatchNormalizationLayer: Mean data should not be null.");
25  ARMNN_ASSERT_MSG(m_Variance != nullptr, "BatchNormalizationLayer: Variance data should not be null.");
26  ARMNN_ASSERT_MSG(m_Beta != nullptr, "BatchNormalizationLayer: Beta data should not be null.");
27  ARMNN_ASSERT_MSG(m_Gamma != nullptr, "BatchNormalizationLayer: Gamma data should not be null.");
28 
29  BatchNormalizationQueueDescriptor descriptor;
30  SetAdditionalInfo(descriptor);
31 
32  descriptor.m_Mean = m_Mean.get();
33  descriptor.m_Variance = m_Variance.get();
34  descriptor.m_Beta = m_Beta.get();
35  descriptor.m_Gamma = m_Gamma.get();
36 
37  return factory.CreateWorkload(LayerType::BatchNormalization, descriptor, PrepInfoAndDesc(descriptor));
38 }

References ARMNN_ASSERT_MSG, armnn::BatchNormalization, IWorkloadFactory::CreateWorkload(), 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().

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy strategy) const
overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 74 of file BatchNormalizationLayer.cpp.

75 {
76  ManagedConstTensorHandle managedMean(m_Mean);
77  ManagedConstTensorHandle managedVariance(m_Variance);
78  ManagedConstTensorHandle managedBeta(m_Beta);
79  ManagedConstTensorHandle managedGamma(m_Gamma);
80 
81  std::vector<armnn::ConstTensor> constTensors { { managedMean.GetTensorInfo(), managedMean.Map() },
82  { managedVariance.GetTensorInfo(), managedVariance.Map() },
83  { managedBeta.GetTensorInfo(), managedBeta.Map() },
84  { managedGamma.GetTensorInfo(), managedGamma.Map() } };
85 
86  strategy.ExecuteStrategy(this, GetParameters(), constTensors, GetName());
87 }

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

◆ GetConstantTensorsByRef()

Layer::ImmutableConstantTensors GetConstantTensorsByRef ( ) const
overrideprotectedvirtual

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

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

Reimplemented from Layer.

Definition at line 68 of file BatchNormalizationLayer.cpp.

69 {
70  // For API stability DO NOT ALTER order and add new members to the end of vector
71  return {m_Mean, m_Variance, m_Beta, m_Gamma};
72 }

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

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

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

Parameters
[in]shapeInferenceMethodIndicates if output shape shall be overwritten or just validated.

Implements Layer.

Definition at line 52 of file BatchNormalizationLayer.cpp.

53 {
55 
56  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
57 
59 
60  auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetTensorInfo().GetShape() });
61 
62  ARMNN_ASSERT(inferredShapes.size() == 1);
63 
64  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "BatchNormalizationLayer");
65 
66 }

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

Member Data Documentation

◆ m_Beta

◆ m_Gamma

◆ m_Mean

◆ m_Variance


The documentation for this class was generated from the following files:
ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
armnn::LayerType::BatchNormalization
@ BatchNormalization
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92
armnn::BatchNormalizationLayer::m_Mean
std::shared_ptr< ConstTensorHandle > m_Mean
A unique pointer to store Mean values.
Definition: BatchNormalizationLayer.hpp:19
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
armnn::Layer::ValidateAndCopyShape
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Definition: Layer.cpp:435
armnn::Layer::GetOutputSlot
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:339
ARMNN_ASSERT_MSG
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:337
armnn::LayerWithParameters< BatchNormalizationDescriptor >::GetParameters
const BatchNormalizationDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:332
armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:592
armnn::BatchNormalizationLayer::m_Gamma
std::shared_ptr< ConstTensorHandle > m_Gamma
A unique pointer to store Gamma values.
Definition: BatchNormalizationLayer.hpp:25
armnn::LayerWithParameters< BatchNormalizationDescriptor >::m_Param
BatchNormalizationDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::BatchNormalizationLayer::m_Variance
std::shared_ptr< ConstTensorHandle > m_Variance
A unique pointer to store Variance values.
Definition: BatchNormalizationLayer.hpp:21
armnn::LayerWithParameters< BatchNormalizationDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:504
armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:287
armnn::BatchNormalizationLayer::m_Beta
std::shared_ptr< ConstTensorHandle > m_Beta
A unique pointer to store Beta values.
Definition: BatchNormalizationLayer.hpp:23
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn::Layer::InferOutputShapes
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)
Definition: Layer.cpp:410
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:391
armnn::LayerWithParameters< BatchNormalizationDescriptor >::LayerWithParameters
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const BatchNormalizationDescriptor &param, const char *name)
Definition: LayerWithParameters.hpp:30
armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:441