This layer represents a depthwise convolution 2d operation. More...

#include <DepthwiseConvolution2dLayer.hpp>

Inheritance diagram for DepthwiseConvolution2dLayer:

Collaboration diagram for DepthwiseConvolution2dLayer:

Public Member Functions
virtual std::unique_ptr< IWorkload >	CreateWorkload (const IWorkloadFactory &factory) const override
	Makes a workload for the DepthwiseConvolution2d type. More...

DepthwiseConvolution2dLayer *	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 DepthwiseConvolution2dLayer. 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...

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

void	ReleaseConstantData () override
	This layer does not have any data stored, weights and bias are now stored in constant layers. More...

Public Member Functions inherited from LayerWithParameters< DepthwiseConvolution2dDescriptor >
const DepthwiseConvolution2dDescriptor &	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

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
	DepthwiseConvolution2dLayer (const DepthwiseConvolution2dDescriptor &param, const char *name)
	Constructor to create a DepthwiseConvolution2dLayer. More...

	~DepthwiseConvolution2dLayer ()=default
	Default destructor. More...

ImmutableConstantTensors	GetConstantTensorsByRef () const override
	Retrieve the handles to the constant values connected to the layer. More...

Protected Member Functions inherited from LayerWithParameters< DepthwiseConvolution2dDescriptor >
	LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const DepthwiseConvolution2dDescriptor &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

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< DepthwiseConvolution2dDescriptor >
using	DescriptorType = DepthwiseConvolution2dDescriptor

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< DepthwiseConvolution2dDescriptor >
DepthwiseConvolution2dDescriptor	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 depthwise convolution 2d operation.

Definition at line 15 of file DepthwiseConvolution2dLayer.hpp.

Constructor & Destructor Documentation

◆ DepthwiseConvolution2dLayer()

DepthwiseConvolution2dLayer	(	const DepthwiseConvolution2dDescriptor &	param,
		const char *	name
	)

protected

Constructor to create a DepthwiseConvolution2dLayer.

Parameters

[in]	param	DepthwiseConvolution2dDescriptor to configure the depthwise convolution2d.
[in]	name	Optional name for the layer.

Definition at line 23 of file DepthwiseConvolution2dLayer.cpp.

     : LayerWithParameters(param.GetNumInputs(), 1, LayerType::DepthwiseConvolution2d, param, name)
 {
 }

References armnn::DepthwiseConvolution2d.

◆ ~DepthwiseConvolution2dLayer()

~DepthwiseConvolution2dLayer ( )

protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

DepthwiseConvolution2dLayer * 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 58 of file DepthwiseConvolution2dLayer.cpp.

 {
     auto layer      = CloneBase<DepthwiseConvolution2dLayer>(graph, m_Param, GetName());
     return std::move(layer);
 }

References Layer::GetName(), and LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param.

◆ CreateWorkload()

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

overridevirtual

Makes a workload for the DepthwiseConvolution2d 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 50 of file DepthwiseConvolution2dLayer.cpp.

 {
     DepthwiseConvolution2dQueueDescriptor descriptor;
     SetAdditionalInfo(descriptor);
  
     return factory.CreateWorkload(LayerType::DepthwiseConvolution2d, descriptor, PrepInfoAndDesc(descriptor));
 }

References IWorkloadFactory::CreateWorkload(), armnn::DepthwiseConvolution2d, LayerWithParameters< DepthwiseConvolution2dDescriptor >::PrepInfoAndDesc(), and Layer::SetAdditionalInfo().

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy & strategy ) const

overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 155 of file DepthwiseConvolution2dLayer.cpp.

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

References IStrategy::ExecuteStrategy(), Layer::GetName(), and LayerWithParameters< DepthwiseConvolution2dDescriptor >::GetParameters().

◆ GetConstantTensorsByRef()

Layer::ImmutableConstantTensors GetConstantTensorsByRef ( ) const

overrideprotectedvirtual

Retrieve the handles to the constant values connected to the layer.

Returns: A vector of the constant tensors connected to the layer.

Reimplemented from Layer.

Definition at line 149 of file DepthwiseConvolution2dLayer.cpp.

 {
     Layer::ImmutableConstantTensors tensors = GetConnectedConstantAsInputTensors();
     return tensors;
 }

References LayerWithParameters< DepthwiseConvolution2dDescriptor >::GetConnectedConstantAsInputTensors().

◆ 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 65 of file DepthwiseConvolution2dLayer.cpp.

 {
     if (inputShapes.size() != 2)
     {
         throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
                                "\" - should be \"2\".");
     }
  
     const TensorShape& inputShape  = inputShapes[0];
     const TensorShape& filterShape = inputShapes[1];
  
     if (inputShape.GetNumDimensions() != 4)
     {
         throw armnn::Exception("Convolutions will always have 4D input.");
     }
  
     if (m_Param.m_StrideX == 0)
     {
         throw armnn::Exception("m_StrideX cannot be 0.");
     }
  
     if (m_Param.m_StrideY == 0)
     {
         throw armnn::Exception("m_StrideY cannot be 0.");
     }
  
  
     DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
  
     unsigned int inputBatchSize = inputShape[0];
     unsigned int inputHeight    = inputShape[dataLayoutIndex.GetHeightIndex()];
     unsigned int inputWidth     = inputShape[dataLayoutIndex.GetWidthIndex()];
  
     // Expected filter shape: [ 1, H, W, O ] - This shape does NOT depend on the data layout
     // Namely: [ 1, filter height, filter width, output channels ]
  
     unsigned int filterHeight = filterShape[1];
     unsigned int dilatedFilterHeight = filterHeight + (m_Param.m_DilationY - 1) * (filterHeight - 1);
     unsigned int readHeight   = (inputHeight + m_Param.m_PadTop + m_Param.m_PadBottom) - dilatedFilterHeight;
     unsigned int outputHeight = 1 + (readHeight / m_Param.m_StrideY);
  
     unsigned int filterWidth = filterShape[2];
     unsigned int dilatedFilterWidth = filterWidth + (m_Param.m_DilationX - 1) * (filterWidth - 1);
     unsigned int readWidth   = (inputWidth + m_Param.m_PadLeft + m_Param.m_PadRight) - dilatedFilterWidth;
     unsigned int outputWidth = 1 + (readWidth / m_Param.m_StrideX);
  
     unsigned int outputChannels  = filterShape[3];
     unsigned int outputBatchSize = inputBatchSize;
  
     TensorShape tensorShape = m_Param.m_DataLayout == armnn::DataLayout::NHWC ?
                               TensorShape{ outputBatchSize, outputHeight, outputWidth, outputChannels } :
                               TensorShape{ outputBatchSize, outputChannels, outputHeight, outputWidth };
  
     return std::vector<TensorShape>{ tensorShape };
 }

Referenced by DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs().

◆ ReleaseConstantData()

void ReleaseConstantData ( )

inlineoverridevirtual

This layer does not have any data stored, weights and bias are now stored in constant layers.

We do not want to release the data in the constant layer, that is why we override with an empty function.

Reimplemented from Layer.

Definition at line 46 of file DepthwiseConvolution2dLayer.hpp.

46 {}

◆ SerializeLayerParameters()

void SerializeLayerParameters ( ParameterStringifyFunction & fn ) const

overridevirtual

Helper to serialize the layer parameters to string.

(currently used in DotSerializer and company).

Reimplemented from Layer.

Definition at line 29 of file DepthwiseConvolution2dLayer.cpp.

 {
     const std::vector<TensorShape>& inputShapes =
     {
         GetInputSlot(0).GetTensorInfo().GetShape(),
         GetInputSlot(1).GetTensorInfo().GetShape()
     };
     const TensorShape filterShape = inputShapes[1];
     unsigned int inputChannels = filterShape[1];
     unsigned int filterWidth = filterShape[3];
     unsigned int filterHeight = filterShape[2];
     unsigned int depthMultiplier = filterShape[0];
  
     fn("FilterWidth",std::to_string(filterWidth));
     fn("FilterHeight",std::to_string(filterHeight));
     fn("DepthMultiplier",std::to_string(depthMultiplier));
     fn("InputChannels",std::to_string(inputChannels));
  
     LayerWithParameters<DepthwiseConvolution2dDescriptor>::SerializeLayerParameters(fn);
 }

References Layer::GetInputSlot(), TensorInfo::GetShape(), InputSlot::GetTensorInfo(), and LayerWithParameters< Parameters >::SerializeLayerParameters().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )

overridevirtual

Check if the input tensor shape(s) will lead to a valid configuration of DepthwiseConvolution2dLayer.

Parameters

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

Implements Layer.

Definition at line 121 of file DepthwiseConvolution2dLayer.cpp.

 {
     VerifyLayerConnections(m_Param.GetNumInputs(), CHECK_LOCATION());
  
     const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
  
     VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
  
     if (!GetInputSlot(1).GetConnection())
     {
         throw armnn::LayerValidationException("DepthwiseConvolution2dLayer: Weights data should not be null.");
     }
  
     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, "DepthwiseConvolution2dLayer");
 }

References CHECK_LOCATION, Layer::GetInputSlot(), DepthwiseConvolution2dDescriptor::GetNumInputs(), Layer::GetOutputSlot(), TensorInfo::GetShape(), InputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), DepthwiseConvolution2dLayer::InferOutputShapes(), LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param, Layer::m_ShapeInferenceMethod, Layer::ValidateAndCopyShape(), Layer::VerifyLayerConnections(), and Layer::VerifyShapeInferenceType().

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

src/armnn/layers/DepthwiseConvolution2dLayer.hpp
src/armnn/layers/DepthwiseConvolution2dLayer.cpp

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ DepthwiseConvolution2dLayer()

◆ ~DepthwiseConvolution2dLayer()

Member Function Documentation

◆ Clone()

◆ CreateWorkload()

◆ ExecuteStrategy()

◆ GetConstantTensorsByRef()

◆ InferOutputShapes()

◆ ReleaseConstantData()

◆ SerializeLayerParameters()

◆ ValidateTensorShapesFromInputs()