This layer represents a 2D transpose convolution operation. More...

#include <TransposeConvolution2dLayer.hpp>

Inheritance diagram for TransposeConvolution2dLayer:

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

TransposeConvolution2dLayer *	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

Public Member Functions inherited from LayerWithParameters< TransposeConvolution2dDescriptor >
const TransposeConvolution2dDescriptor &	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
	TransposeConvolution2dLayer (const TransposeConvolution2dDescriptor &param, const char *name)

	~TransposeConvolution2dLayer ()=default
	Default destructor. More...

ConstantTensors	GetConstantTensorsByRef () override

Protected Member Functions inherited from LayerWithParameters< TransposeConvolution2dDescriptor >
	LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const TransposeConvolution2dDescriptor &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< TransposeConvolution2dDescriptor >
using	DescriptorType = TransposeConvolution2dDescriptor

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

Protected Attributes inherited from LayerWithParameters< TransposeConvolution2dDescriptor >
TransposeConvolution2dDescriptor	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 2D transpose convolution operation.

Definition at line 15 of file TransposeConvolution2dLayer.hpp.

Constructor & Destructor Documentation

◆ TransposeConvolution2dLayer()

TransposeConvolution2dLayer	(	const TransposeConvolution2dDescriptor &	param,
		const char *	name
	)

protected

Constructor to create a TransposeConvolution2dLayer.

Parameters

[in]	param	TransposeConvolution2dDescriptor to configure the 2D transpose convolution operation.
[in]	name	Optional name for the layer.

Definition at line 21 of file TransposeConvolution2dLayer.cpp.

References armnn::TransposeConvolution2d.

     : LayerWithParameters(1, 1, LayerType::TransposeConvolution2d, param, name)
 {
 }

◆ ~TransposeConvolution2dLayer()

~TransposeConvolution2dLayer ( )

protecteddefault

Default destructor.

Member Function Documentation

◆ Accept()

void Accept ( ILayerVisitor & visitor ) const

overridevirtual

Implements IConnectableLayer.

Definition at line 120 of file TransposeConvolution2dLayer.cpp.

References Layer::GetName(), LayerWithParameters< TransposeConvolution2dDescriptor >::GetParameters(), TransposeConvolution2dLayer::m_Bias, TransposeConvolution2dLayer::m_Weight, and ILayerVisitor::VisitTransposeConvolution2dLayer().

 {
     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.VisitTransposeConvolution2dLayer(this, GetParameters(), weightsTensor, optionalBiasTensor, GetName());
 }

◆ Clone()

TransposeConvolution2dLayer * 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 43 of file TransposeConvolution2dLayer.cpp.

References Layer::GetName(), TransposeConvolution2dLayer::m_Bias, LayerWithParameters< TransposeConvolution2dDescriptor >::m_Param, and TransposeConvolution2dLayer::m_Weight.

 {
     auto layer = CloneBase<TransposeConvolution2dLayer>(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 TransposeConvolution2d 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 27 of file TransposeConvolution2dLayer.cpp.

References IWorkloadFactory::CreateTransposeConvolution2d(), TransposeConvolution2dLayer::m_Bias, TransposeConvolution2dQueueDescriptor::m_Bias, TransposeConvolution2dDescriptor::m_BiasEnabled, LayerWithParameters< TransposeConvolution2dDescriptor >::m_Param, TransposeConvolution2dLayer::m_Weight, TransposeConvolution2dQueueDescriptor::m_Weight, and LayerWithParameters< TransposeConvolution2dDescriptor >::PrepInfoAndDesc().

 {
     BOOST_ASSERT_MSG(m_Weight != nullptr, "TransposeConvolution2dLayer: Weights data should not be null.");
 
     TransposeConvolution2dQueueDescriptor descriptor;
     descriptor.m_Weight = m_Weight.get();
 
     if (m_Param.m_BiasEnabled)
     {
         BOOST_ASSERT_MSG(m_Bias != nullptr, "TransposeConvolution2dLayer: Bias data should not be null.");
         descriptor.m_Bias = m_Bias.get();
     }
 
     return factory.CreateTransposeConvolution2d(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 115 of file TransposeConvolution2dLayer.cpp.

References TransposeConvolution2dLayer::m_Bias, and TransposeConvolution2dLayer::m_Weight.

 {
     return {m_Weight, m_Bias};
 }

◆ InferOutputShapes()

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

overridevirtual

Infers the output shapes from given input shapes and layer properties.

Parameters

[in] inputShapes The input shapes the layer has.

Returns: A vector of the inferred output shape.

Reimplemented from Layer.

Definition at line 57 of file TransposeConvolution2dLayer.cpp.

References TransposeConvolution2dDescriptor::m_DataLayout, TransposeConvolution2dDescriptor::m_PadBottom, TransposeConvolution2dDescriptor::m_PadLeft, TransposeConvolution2dDescriptor::m_PadRight, TransposeConvolution2dDescriptor::m_PadTop, LayerWithParameters< TransposeConvolution2dDescriptor >::m_Param, TransposeConvolution2dDescriptor::m_StrideX, TransposeConvolution2dDescriptor::m_StrideY, and armnn::NHWC.

Referenced by TransposeConvolution2dInferOutputShapeTest(), and TransposeConvolution2dLayer::ValidateTensorShapesFromInputs().

 {
     BOOST_ASSERT(inputShapes.size() == 2);
     const TensorShape& inputShape  = inputShapes[0];
     const TensorShape& kernelShape = inputShapes[1];
 
     BOOST_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Transpose convolutions will always have 4D input");
 
     DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
 
     const unsigned int batches = inputShape[0];
 
     const unsigned int wInput = inputShape[dataLayoutIndex.GetWidthIndex()];
     const unsigned int hInput = inputShape[dataLayoutIndex.GetHeightIndex()];
 
     const unsigned int wKernel = kernelShape[dataLayoutIndex.GetWidthIndex()];
     const unsigned int hKernel = kernelShape[dataLayoutIndex.GetHeightIndex()];
 
     unsigned int wPadding = m_Param.m_PadLeft + m_Param.m_PadRight;
     unsigned int hPadding = m_Param.m_PadTop + m_Param.m_PadBottom;
 
     unsigned int wOutput = (wInput - 1) * m_Param.m_StrideX + wKernel - wPadding;
     unsigned int hOutput = (hInput - 1) * m_Param.m_StrideY + hKernel - hPadding;
 
     unsigned int kernelElements = kernelShape[0] * kernelShape[dataLayoutIndex.GetChannelsIndex()];
     unsigned int inputElements  = batches * inputShape[dataLayoutIndex.GetChannelsIndex()];
 
     BOOST_ASSERT_MSG(inputElements != 0, "Invalid number of input elements");
     BOOST_ASSERT_MSG(kernelElements % inputElements == 0, "Invalid number of elements");
 
     unsigned int channels =  kernelElements / inputElements;
 
     TensorShape tensorShape = m_Param.m_DataLayout == armnn::DataLayout::NHWC ?
          TensorShape( { batches, hOutput, wOutput, channels } ) :
          TensorShape( { batches, channels, hOutput, wOutput });
 
     return std::vector<TensorShape>({ tensorShape });
 }

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )

overridevirtual

Check if the input tensor shape(s) will lead to a valid configuration of TransposeConvolution2dLayer.

Implements Layer.

Definition at line 97 of file TransposeConvolution2dLayer.cpp.

References CHECK_LOCATION, InputSlot::GetConnection(), Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), IOutputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), TransposeConvolution2dLayer::InferOutputShapes(), TransposeConvolution2dLayer::m_Weight, and Layer::VerifyLayerConnections().

 {
     VerifyLayerConnections(1, CHECK_LOCATION());
 
     BOOST_ASSERT_MSG(m_Weight != nullptr, "TransposeConvolution2dLayer: Weight data cannot be null.");
 
     auto inferredShapes = InferOutputShapes({
          GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
          m_Weight->GetTensorInfo().GetShape() });
 
     BOOST_ASSERT(inferredShapes.size() == 1);
 
     ConditionalThrowIfNotEqual<LayerValidationException>(
         "TransposeConvolution2dLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
         GetOutputSlot(0).GetTensorInfo().GetShape(),
         inferredShapes[0]);
 }