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

#include <Convolution2dLayer.hpp>

Inheritance diagram for Convolution2dLayer:

Public Member Functions
virtual std::unique_ptr< IWorkload >	CreateWorkload (const IWorkloadFactory &factory) const override

Convolution2dLayer *	Clone (Graph &graph) const override

void	ValidateTensorShapesFromInputs () override

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

void	Accept (ILayerVisitor &visitor) const override

void	SerializeLayerParameters (ParameterStringifyFunction &fn) const override

Public Member Functions inherited from LayerWithParameters< Convolution2dDescriptor >
const Convolution2dDescriptor &	GetParameters () const

void	SerializeLayerParameters (ParameterStringifyFunction &fn) const override

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)

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

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

virtual void	ReleaseConstantData ()

template<typename Op >
void	OperateOnConstantTensors (Op op)

const char *	GetName () const override

unsigned int	GetNumInputSlots () const override

unsigned int	GetNumOutputSlots () const override

const InputSlot &	GetInputSlot (unsigned int index) const override

InputSlot &	GetInputSlot (unsigned int index) override

const OutputSlot &	GetOutputSlot (unsigned int index=0) const override

OutputSlot &	GetOutputSlot (unsigned int index=0) override

void	SetGuid (LayerGuid guid)

LayerGuid	GetGuid () const final

void	AddRelatedLayerName (const std::string layerName)

const std::list< std::string > &	GetRelatedLayerNames ()

virtual void	Reparent (Graph &dest, std::list< Layer *>::const_iterator iterator)=0

Public Attributes
std::unique_ptr< ScopedCpuTensorHandle >	m_Weight
	A unique pointer to store Weight values. More...

std::unique_ptr< ScopedCpuTensorHandle >	m_Bias
	A unique pointer to store Bias values. More...

Protected Member Functions
	Convolution2dLayer (const Convolution2dDescriptor &param, const char *name)

	~Convolution2dLayer ()=default
	Default destructor. More...

ConstantTensors	GetConstantTensorsByRef () override

Protected Member Functions inherited from LayerWithParameters< Convolution2dDescriptor >
	LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const Convolution2dDescriptor &param, const char *name)

	~LayerWithParameters ()=default

WorkloadInfo	PrepInfoAndDesc (QueueDescriptor &descriptor) const
	Helper function to reduce duplication in *LayerCreateWorkload. 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

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

Protected Member Functions inherited from IConnectableLayer
	~IConnectableLayer ()
	Objects are not deletable via the handle. More...

Additional Inherited Members
Public Types inherited from LayerWithParameters< Convolution2dDescriptor >
using	DescriptorType = Convolution2dDescriptor

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

Protected Attributes inherited from LayerWithParameters< Convolution2dDescriptor >
Convolution2dDescriptor	m_Param
	The parameters for the layer (not including tensor-valued weights etc.). More...

Protected Attributes inherited from Layer
std::vector< OutputHandler >	m_OutputHandlers

Detailed Description

This layer represents a convolution 2d operation.

Definition at line 15 of file Convolution2dLayer.hpp.

Constructor & Destructor Documentation

◆ Convolution2dLayer()

Convolution2dLayer	(	const Convolution2dDescriptor &	param,
		const char *	name
	)

protected

Constructor to create a Convolution2dLayer.

Parameters

[in]	param	Convolution2dDescriptor to configure the convolution2d operation.
[in]	name	Optional name for the layer.

Definition at line 23 of file Convolution2dLayer.cpp.

References armnn::Convolution2d.

     : LayerWithParameters(1, 1, LayerType::Convolution2d, param, name)
 {
 
 }

◆ ~Convolution2dLayer()

~Convolution2dLayer ( )

protecteddefault

Default destructor.

Member Function Documentation

◆ Accept()

void Accept ( ILayerVisitor & visitor ) const

overridevirtual

Implements IConnectableLayer.

Definition at line 139 of file Convolution2dLayer.cpp.

References Layer::GetName(), LayerWithParameters< Convolution2dDescriptor >::GetParameters(), Convolution2dLayer::m_Bias, Convolution2dLayer::m_Weight, and ILayerVisitor::VisitConvolution2dLayer().

 {
     ConstTensor weightsTensor(m_Weight->GetTensorInfo(), m_Weight->Map(true)) ;
     Optional<ConstTensor> optionalBiasTensor = EmptyOptional();
 
     if (GetParameters().m_BiasEnabled)
     {
         ConstTensor biasTensor(m_Bias->GetTensorInfo(), m_Bias->Map(true));
         optionalBiasTensor = Optional<ConstTensor>(biasTensor);
     }
 
     visitor.VisitConvolution2dLayer(this, GetParameters(), weightsTensor, optionalBiasTensor, GetName());
 }

◆ Clone()

Convolution2dLayer * 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 66 of file Convolution2dLayer.cpp.

References Layer::GetName(), Convolution2dLayer::m_Bias, LayerWithParameters< Convolution2dDescriptor >::m_Param, and Convolution2dLayer::m_Weight.

 {
     auto layer = CloneBase<Convolution2dLayer>(graph, m_Param, GetName());
 
     layer->m_Weight = m_Weight ? std::make_unique<ScopedCpuTensorHandle>(*m_Weight) : nullptr;
 
     if (layer->m_Param.m_BiasEnabled)
     {
         layer->m_Bias = m_Bias ? std::make_unique<ScopedCpuTensorHandle>(*m_Bias) : nullptr;
     }
 
     return std::move(layer);
 }

◆ CreateWorkload()

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

overridevirtual

Makes a workload for the Convolution2d 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 49 of file Convolution2dLayer.cpp.

References IWorkloadFactory::CreateConvolution2d(), Convolution2dLayer::m_Bias, Convolution2dQueueDescriptor::m_Bias, Convolution2dDescriptor::m_BiasEnabled, LayerWithParameters< Convolution2dDescriptor >::m_Param, Convolution2dLayer::m_Weight, Convolution2dQueueDescriptor::m_Weight, and LayerWithParameters< Convolution2dDescriptor >::PrepInfoAndDesc().

 {
     // on this level constant data should not be released..
     BOOST_ASSERT_MSG(m_Weight != nullptr, "Convolution2dLayer: Weights data should not be null.");
 
     Convolution2dQueueDescriptor descriptor;
 
     descriptor.m_Weight = m_Weight.get();
 
     if (m_Param.m_BiasEnabled)
     {
         BOOST_ASSERT_MSG(m_Bias != nullptr, "Convolution2dLayer: Bias data should not be null.");
         descriptor.m_Bias = m_Bias.get();
     }
     return factory.CreateConvolution2d(descriptor, PrepInfoAndDesc(descriptor));
 }

◆ GetConstantTensorsByRef()

Layer::ConstantTensors GetConstantTensorsByRef ( )

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 134 of file Convolution2dLayer.cpp.

References Convolution2dLayer::m_Bias, and Convolution2dLayer::m_Weight.

 {
     return {m_Weight, m_Bias};
 }

◆ 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 80 of file Convolution2dLayer.cpp.

References Convolution2dDescriptor::m_DataLayout, Convolution2dDescriptor::m_DilationX, Convolution2dDescriptor::m_DilationY, Convolution2dDescriptor::m_PadBottom, Convolution2dDescriptor::m_PadLeft, Convolution2dDescriptor::m_PadRight, Convolution2dDescriptor::m_PadTop, LayerWithParameters< Convolution2dDescriptor >::m_Param, Convolution2dDescriptor::m_StrideX, Convolution2dDescriptor::m_StrideY, and armnn::NHWC.

Referenced by Convolution2dInferOutputShapeTest(), and Convolution2dLayer::ValidateTensorShapesFromInputs().

 {
     BOOST_ASSERT(inputShapes.size() == 2);
     const TensorShape& inputShape = inputShapes[0];
     const TensorShape filterShape = inputShapes[1];
 
     // If we support multiple batch dimensions in the future, then this assert will need to change.
     BOOST_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Convolutions will always have 4D input.");
 
     DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
 
     unsigned int inWidth = inputShape[dataLayoutIndex.GetWidthIndex()];
     unsigned int inHeight = inputShape[dataLayoutIndex.GetHeightIndex()];
     unsigned int inBatchSize = inputShape[0];
 
     unsigned int filterWidth = filterShape[dataLayoutIndex.GetWidthIndex()];
     unsigned int dilatedFilterWidth = filterWidth + (m_Param.m_DilationX - 1) * (filterWidth - 1);
     unsigned int readWidth = (inWidth + m_Param.m_PadLeft + m_Param.m_PadRight) - dilatedFilterWidth;
     unsigned int outWidth = 1 + (readWidth / m_Param.m_StrideX);
 
     unsigned int filterHeight = filterShape[dataLayoutIndex.GetHeightIndex()];
     unsigned int dilatedFilterHeight = filterHeight + (m_Param.m_DilationY - 1) * (filterHeight - 1);
     unsigned int readHeight = (inHeight + m_Param.m_PadTop + m_Param.m_PadBottom) - dilatedFilterHeight;
     unsigned int outHeight = 1 + (readHeight / m_Param.m_StrideY);
 
     unsigned int outChannels = filterShape[0];
     unsigned int outBatchSize = inBatchSize;
 
     TensorShape tensorShape = m_Param.m_DataLayout == armnn::DataLayout::NHWC ?
         TensorShape( { outBatchSize, outHeight, outWidth, outChannels } ) :
         TensorShape( { outBatchSize, outChannels, outHeight, outWidth });
 
     return std::vector<TensorShape>({ tensorShape });
 }

◆ 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 Convolution2dLayer.cpp.

References InputSlot::GetConnection(), DataLayoutIndexed::GetHeightIndex(), Layer::GetInputSlot(), TensorInfo::GetShape(), IOutputSlot::GetTensorInfo(), DataLayoutIndexed::GetWidthIndex(), Convolution2dDescriptor::m_DataLayout, LayerWithParameters< Convolution2dDescriptor >::m_Param, Convolution2dLayer::m_Weight, and LayerWithParameters< Parameters >::SerializeLayerParameters().

 {
     //using DescriptorType = Parameters;
     const std::vector<TensorShape>& inputShapes =
     {
         GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
         m_Weight->GetTensorInfo().GetShape()
     };
     const TensorShape filterShape = inputShapes[1];
     DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
     unsigned int filterWidth = filterShape[dataLayoutIndex.GetWidthIndex()];
     unsigned int filterHeight = filterShape[dataLayoutIndex.GetHeightIndex()];
     unsigned int outChannels = filterShape[0];
 
     fn("OutputChannels",std::to_string(outChannels));
     fn("FilterWidth",std::to_string(filterWidth));
     fn("FilterHeight",std::to_string(filterHeight));
     LayerWithParameters<Convolution2dDescriptor>::SerializeLayerParameters(fn);
 }

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )

overridevirtual

Check if the input tensor shape(s) will lead to a valid configuration of Convolution2dLayer.

Implements Layer.

Definition at line 115 of file Convolution2dLayer.cpp.

References CHECK_LOCATION, InputSlot::GetConnection(), Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), IOutputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), Convolution2dLayer::InferOutputShapes(), Convolution2dLayer::m_Weight, and Layer::VerifyLayerConnections().

 {
     VerifyLayerConnections(1, CHECK_LOCATION());
 
     // check if we m_Weight data is not nullptr
     BOOST_ASSERT_MSG(m_Weight != nullptr, "Convolution2dLayer: Weights data should not be null.");
 
     auto inferredShapes = InferOutputShapes({
         GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
         m_Weight->GetTensorInfo().GetShape() });
 
     BOOST_ASSERT(inferredShapes.size() == 1);
 
     ConditionalThrowIfNotEqual<LayerValidationException>(
         "Convolution2dLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
         GetOutputSlot(0).GetTensorInfo().GetShape(),
         inferredShapes[0]);
 }

Member Data Documentation

◆ m_Bias

std::unique_ptr<ScopedCpuTensorHandle> m_Bias

A unique pointer to store Bias values.

Definition at line 22 of file Convolution2dLayer.hpp.

Referenced by Convolution2dLayer::Accept(), BOOST_AUTO_TEST_CASE(), Convolution2dLayer::Clone(), Convolution2dLayer::CreateWorkload(), and Convolution2dLayer::GetConstantTensorsByRef().

◆ m_Weight

std::unique_ptr<ScopedCpuTensorHandle> m_Weight

A unique pointer to store Weight values.

Definition at line 20 of file Convolution2dLayer.hpp.

Referenced by Convolution2dLayer::Accept(), Network::AddConcatLayer(), BOOST_AUTO_TEST_CASE(), Convolution2dLayer::Clone(), CreateConvolution2dGraph(), Convolution2dLayer::CreateWorkload(), Convolution2dLayer::GetConstantTensorsByRef(), Convolution2dLayer::SerializeLayerParameters(), and Convolution2dLayer::ValidateTensorShapesFromInputs().

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

src/armnn/layers/Convolution2dLayer.hpp
src/armnn/layers/Convolution2dLayer.cpp

Public Member Functions

Public Attributes

Protected Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ Convolution2dLayer()

◆ ~Convolution2dLayer()

Member Function Documentation

◆ Accept()

◆ Clone()

◆ CreateWorkload()

◆ GetConstantTensorsByRef()

◆ InferOutputShapes()

◆ SerializeLayerParameters()

◆ ValidateTensorShapesFromInputs()

Member Data Documentation

◆ m_Bias

◆ m_Weight