Layer Class Reference

#include <Layer.hpp>

Inheritance diagram for Layer:

Public Member Functions
	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 std::unique_ptr< IWorkload >	CreateWorkload (const IWorkloadFactory &factory) const =0
virtual void	CreateTensorHandles (const TensorHandleFactoryRegistry &registry, const IWorkloadFactory &factory, const bool IsMemoryManaged=true)
virtual Layer *	Clone (Graph &graph) const =0
	Creates a dynamically-allocated copy of this layer. More...
void	VerifyLayerConnections (unsigned int expectedConnections, const CheckLocation &location) const
virtual void	ValidateTensorShapesFromInputs ()=0
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	SerializeLayerParameters (ParameterStringifyFunction &fn) const
	Helper to serialize the layer parameters to string. 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
Public Member Functions inherited from IConnectableLayer
virtual void	Accept (ILayerVisitor &visitor) const =0
	Apply a visitor to this layer. More...

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

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

Protected Attributes
std::vector< OutputHandler >	m_OutputHandlers

Friends
class	Graph

Detailed Description

Definition at line 209 of file Layer.hpp.

Member Typedef Documentation

ConstantTensors

using ConstantTensors = std::vector<std::reference_wrapper<std::unique_ptr<ScopedCpuTensorHandle> >>

protected

Definition at line 363 of file Layer.hpp.

Constructor & Destructor Documentation

Layer() [1/2]

Layer	(	unsigned int	numInputSlots,
		unsigned int	numOutputSlots,
		LayerType	type,
		const char *	name
	)

Parameters

name	- Optional name for the layer (may be nullptr).

Definition at line 213 of file Layer.cpp.

References Layer::GetInputSlots(), Layer::m_OutputHandlers, and WorkloadDataCollector::Push().

: Layer(numInputSlots, numOutputSlots, type, DataLayout::NCHW, name)
{
}

Layer() [2/2]

Layer	(	unsigned int	numInputSlots,
		unsigned int	numOutputSlots,
		LayerType	type,
		DataLayout	layout,
		const char *	name
	)

Definition at line 187 of file Layer.cpp.

References armnn::IgnoreUnused(), and Layer::m_OutputHandlers.

: m_OutputHandlers(numOutputSlots)
, m_LayerName(name ? name : "")
, m_Type(type)
, m_BackendId()
, m_BackendHint(EmptyOptional())
, m_Guid(profiling::ProfilingService::Instance().NextGuid())
{
    IgnoreUnused(layout);
    m_InputSlots.reserve(numInputSlots);
    for (unsigned int i = 0; i < numInputSlots; ++i)
    {
        m_InputSlots.emplace_back(*this, i);
    }

    m_OutputSlots.reserve(numOutputSlots);
    for (unsigned int i = 0; i < numOutputSlots; ++i)
    {
        m_OutputSlots.emplace_back(*this, m_OutputHandlers[i]);
    }
}

~Layer()

virtual ~Layer ( )

protectedvirtualdefault

Member Function Documentation

AddRelatedLayerName()

void AddRelatedLayerName ( const std::string  layerName )

inline

Definition at line 318 of file Layer.hpp.

{ m_RelatedLayerNames.emplace_back(layerName); }

BackendSelectionHint()

void BackendSelectionHint ( Optional< BackendId >  backend )

inlinefinalvirtual

Provide a hint for the optimizer as to which backend to prefer for this layer.

Implements IConnectableLayer.

Definition at line 324 of file Layer.hpp.

Referenced by BOOST_AUTO_TEST_CASE().

    {
        m_BackendHint = backend;
    }

BeginInputSlots()

std::vector<InputSlot>::iterator BeginInputSlots ( )

inline

Definition at line 235 of file Layer.hpp.

Referenced by armnn::InsertConvertFp16ToFp32LayersBefore(), ConvertFp32NetworkToFp16Impl::Run(), MovePermuteUpImpl::Run(), and MoveTransposeUpImpl::Run().

{ return m_InputSlots.begin(); }

BeginOutputSlots()

std::vector<OutputSlot>::iterator BeginOutputSlots ( )

inline

Definition at line 239 of file Layer.hpp.

Referenced by Graph::Graph(), armnn::InsertDebugLayerAfter(), ConvertFp32NetworkToFp16Impl::Run(), and SquashEqualSiblingsImpl< Comparable >::Run().

{ return m_OutputSlots.begin(); }

Clone()

virtual Layer* Clone ( Graph &  graph ) const

pure virtual

Creates a dynamically-allocated copy of this layer.

Parameters

graph

- The Graph into which this Layer is being cloned.

Implemented in LstmLayer, QuantizedLstmLayer, OutputLayer, BatchNormalizationLayer, SplitterLayer, ConcatLayer, Convolution2dLayer, DepthwiseConvolution2dLayer, FullyConnectedLayer, TransposeConvolution2dLayer, DetectionPostProcessLayer, PreCompiledLayer, ConstantLayer, ArgMinMaxLayer, ComparisonLayer, ConvertFp16ToFp32Layer, DepthToSpaceLayer, DivisionLayer, ElementwiseUnaryLayer, GatherLayer, LogSoftmaxLayer, MaximumLayer, MeanLayer, MinimumLayer, MultiplicationLayer, PadLayer, PreluLayer, SpaceToBatchNdLayer, SpaceToDepthLayer, StandInLayer, SubtractionLayer, AbsLayer, AdditionLayer, BatchToSpaceNdLayer, ConvertFp32ToFp16Layer, DebugLayer, DequantizeLayer, FakeQuantizationLayer, FloorLayer, InputLayer, InstanceNormalizationLayer, L2NormalizationLayer, MemCopyLayer, MemImportLayer, MergeLayer, NormalizationLayer, PermuteLayer, Pooling2dLayer, ReshapeLayer, ResizeLayer, RsqrtLayer, SliceLayer, SoftmaxLayer, StackLayer, StridedSliceLayer, SwitchLayer, ActivationLayer, TransposeLayer, and QuantizeLayer.

Referenced by Graph::Graph().

CloneBase()

LayerType * CloneBase ( Graph &  graph, Params &&...  params  ) const

protected

Definition at line 14 of file LayerCloneBase.hpp.

References Graph::AddLayer(), Layer::GetBackendId(), and Layer::GetGuid().

{
    LayerType* const layer = graph.AddLayer<LayerType>(std::forward<Params>(params)...);

    layer->SetBackendId(GetBackendId());
    layer->SetGuid(GetGuid());

    return layer;
}

CollectQueueDescriptorInputs()

void CollectQueueDescriptorInputs ( QueueDescriptor &  descriptor, WorkloadInfo &  info  ) const

inlineprotected

Definition at line 336 of file Layer.hpp.

References QueueDescriptor::m_Inputs, and WorkloadInfo::m_InputTensorInfos.

    {
        WorkloadDataCollector dataCollector(descriptor.m_Inputs, info.m_InputTensorInfos);
        CollectWorkloadInputs(dataCollector);
    }

CollectQueueDescriptorOutputs()

void CollectQueueDescriptorOutputs ( QueueDescriptor &  descriptor, WorkloadInfo &  info  ) const

inlineprotected

Definition at line 343 of file Layer.hpp.

References QueueDescriptor::m_Outputs, and WorkloadInfo::m_OutputTensorInfos.

    {
        WorkloadDataCollector dataCollector(descriptor.m_Outputs, info.m_OutputTensorInfos);
        CollectWorkloadOutputs(dataCollector);
    }

CreateTensorHandles()

void CreateTensorHandles ( const TensorHandleFactoryRegistry &  registry, const IWorkloadFactory &  factory, const bool  IsMemoryManaged = true  )

virtual

Reimplemented in SplitterLayer, ConcatLayer, and OutputLayer.

Definition at line 240 of file Layer.cpp.

References OutputHandler::CreateTensorHandles(), TensorHandleFactoryRegistry::GetFactory(), Layer::GetNumOutputSlots(), Layer::GetOutputHandler(), Layer::GetOutputSlot(), OutputSlot::GetTensorHandleFactoryId(), and ITensorHandleFactory::LegacyFactoryId.

{
    for (unsigned int idx=0; idx < GetNumOutputSlots(); idx++)
    {

        OutputSlot& slot = GetOutputSlot(idx);
        ITensorHandleFactory::FactoryId factoryId = slot.GetTensorHandleFactoryId();

        OutputHandler& handler = GetOutputHandler(idx);
        if (factoryId == ITensorHandleFactory::LegacyFactoryId)
        {
            handler.CreateTensorHandles(workloadFactory, IsMemoryManaged);
        }
        else
        {
            ITensorHandleFactory* handleFactory = registry.GetFactory(factoryId);
            BOOST_ASSERT(handleFactory);
            handler.CreateTensorHandles(*handleFactory, IsMemoryManaged);
        }
    }
}

CreateWorkload()

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

pure virtual

Implemented in LstmLayer, QuantizedLstmLayer, BatchNormalizationLayer, Convolution2dLayer, PreCompiledLayer, DepthwiseConvolution2dLayer, FullyConnectedLayer, TransposeConvolution2dLayer, DetectionPostProcessLayer, ConstantLayer, ArgMinMaxLayer, ComparisonLayer, ConvertFp16ToFp32Layer, DepthToSpaceLayer, DivisionLayer, ElementwiseUnaryLayer, GatherLayer, LogSoftmaxLayer, MaximumLayer, MeanLayer, MinimumLayer, MultiplicationLayer, PadLayer, PreluLayer, SpaceToBatchNdLayer, SpaceToDepthLayer, StandInLayer, SubtractionLayer, AbsLayer, AdditionLayer, BatchToSpaceNdLayer, ConcatLayer, ConvertFp32ToFp16Layer, DebugLayer, DequantizeLayer, FakeQuantizationLayer, FloorLayer, InputLayer, InstanceNormalizationLayer, L2NormalizationLayer, MemCopyLayer, MemImportLayer, MergeLayer, NormalizationLayer, OutputLayer, PermuteLayer, Pooling2dLayer, QuantizeLayer, ReshapeLayer, ResizeLayer, RsqrtLayer, SliceLayer, SoftmaxLayer, SplitterLayer, StackLayer, StridedSliceLayer, SwitchLayer, ActivationLayer, and TransposeLayer.

EndInputSlots()

std::vector<InputSlot>::iterator EndInputSlots ( )

inline

Definition at line 236 of file Layer.hpp.

Referenced by armnn::InsertConvertFp16ToFp32LayersBefore(), ConvertFp32NetworkToFp16Impl::Run(), MovePermuteUpImpl::Run(), and MoveTransposeUpImpl::Run().

{ return m_InputSlots.end(); }

EndOutputSlots()

std::vector<OutputSlot>::iterator EndOutputSlots ( )

inline

Definition at line 240 of file Layer.hpp.

Referenced by armnn::InsertDebugLayerAfter(), and ConvertFp32NetworkToFp16Impl::Run().

{ return m_OutputSlots.end(); }

GetBackendHint()

Optional<BackendId> GetBackendHint ( ) const

inline

Definition at line 328 of file Layer.hpp.

{ return m_BackendHint; }

GetBackendId()

const BackendId& GetBackendId ( ) const

inline

Definition at line 263 of file Layer.hpp.

Referenced by Graph::AddCompatibilityLayers(), armnn::ApplyBackendOptimizations(), armnn::AttemptBackendAssignment(), BOOST_AUTO_TEST_CASE(), armnn::CalculateEdgeStrategy(), armnn::CalculateSlotOption(), armnn::CalculateSlotOptionForInput(), Layer::CloneBase(), LoadedNetwork::GetOutputTensorInfo(), and armnn::SelectTensorHandleStrategy().

{ return m_BackendId; }

GetConstantTensorsByRef()

virtual ConstantTensors GetConstantTensorsByRef ( )

inlineprotectedvirtual

Reimplemented in LstmLayer, QuantizedLstmLayer, Convolution2dLayer, DepthwiseConvolution2dLayer, FullyConnectedLayer, TransposeConvolution2dLayer, BatchNormalizationLayer, ConstantLayer, and DetectionPostProcessLayer.

Definition at line 364 of file Layer.hpp.

{return ConstantTensors(); };

GetDataType()

DataType GetDataType

(

)

const

Definition at line 273 of file Layer.cpp.

References InputSlot::GetConnection(), TensorInfo::GetDataType(), Layer::GetInputSlot(), Layer::GetNumInputSlots(), Layer::GetOutputSlot(), IOutputSlot::GetTensorInfo(), and OutputSlot::GetTensorInfo().

Referenced by BOOST_AUTO_TEST_CASE(), ConvertFp32NetworkToFp16Impl::Run(), IsFloat32Layer::Test(), and IsFloat16Layer::Test().

{
    if (GetNumInputSlots() > 0) // Ignore the input layer.
    {
        return GetInputSlot(0).GetConnection()->GetTensorInfo().GetDataType();
    }
    return GetOutputSlot(0).GetTensorInfo().GetDataType();
}

GetGuid()

LayerGuid GetGuid ( ) const

inlinefinalvirtual

Returns the unique id of the layer.

Implements IConnectableLayer.

Definition at line 316 of file Layer.hpp.

Referenced by Layer::CloneBase(), DebugLayer::CreateWorkload(), OutputSlot::GetOwningLayerGuid(), QuantizerVisitor::QuantizerVisitor(), and Graph::SerializeToDot().

{ return m_Guid; }

GetInputSlot() [1/2]

const InputSlot& GetInputSlot ( unsigned int  index ) const

inlineoverridevirtual

Get a const input slot handle by slot index.

Implements IConnectableLayer.

Definition at line 310 of file Layer.hpp.

Referenced by BOOST_AUTO_TEST_CASE(), BOOST_FIXTURE_TEST_CASE(), CreateConvolution2dGraph(), CreateDepthwiseConvolution2dGraph(), CreateGatherGraph(), CreatePooling2dGraph(), CreateResizeBilinearGraph(), ConcatLayer::CreateWorkload(), DebugLayer::CreateWorkload(), Layer::GetDataType(), Graph::Graph(), InputSlot::Insert(), armnn::InsertConvertFp16ToFp32LayersBefore(), armnn::InsertConvertFp32ToFp16LayersAfter(), armnn::InsertDebugLayerAfter(), IWorkloadFactory::IsLayerSupported(), PermuteAsReshapeImpl::Run(), TransposeAsReshapeImpl::Run(), FoldPadIntoConvolution2dImpl::Run(), OptimizeConsecutiveReshapesImpl::Run(), PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteType >::Run(), OptimizeInverseConversionsImpl::Run(), OptimizeInversePermutesImpl< PermuteType >::Run(), MovePermuteUpImpl::Run(), MoveTransposeUpImpl::Run(), DepthwiseConvolution2dLayer::SerializeLayerParameters(), Convolution2dLayer::SerializeLayerParameters(), ElementwiseBaseLayer::ValidateTensorShapesFromInputs(), QuantizeLayer::ValidateTensorShapesFromInputs(), ActivationLayer::ValidateTensorShapesFromInputs(), TransposeLayer::ValidateTensorShapesFromInputs(), SoftmaxLayer::ValidateTensorShapesFromInputs(), L2NormalizationLayer::ValidateTensorShapesFromInputs(), BatchToSpaceNdLayer::ValidateTensorShapesFromInputs(), MemCopyLayer::ValidateTensorShapesFromInputs(), MemImportLayer::ValidateTensorShapesFromInputs(), NormalizationLayer::ValidateTensorShapesFromInputs(), DebugLayer::ValidateTensorShapesFromInputs(), MergeLayer::ValidateTensorShapesFromInputs(), PermuteLayer::ValidateTensorShapesFromInputs(), Pooling2dLayer::ValidateTensorShapesFromInputs(), DequantizeLayer::ValidateTensorShapesFromInputs(), ResizeLayer::ValidateTensorShapesFromInputs(), AbsLayer::ValidateTensorShapesFromInputs(), RsqrtLayer::ValidateTensorShapesFromInputs(), SliceLayer::ValidateTensorShapesFromInputs(), FakeQuantizationLayer::ValidateTensorShapesFromInputs(), StackLayer::ValidateTensorShapesFromInputs(), SwitchLayer::ValidateTensorShapesFromInputs(), FloorLayer::ValidateTensorShapesFromInputs(), InstanceNormalizationLayer::ValidateTensorShapesFromInputs(), ConvertFp32ToFp16Layer::ValidateTensorShapesFromInputs(), GatherLayer::ValidateTensorShapesFromInputs(), LogSoftmaxLayer::ValidateTensorShapesFromInputs(), MeanLayer::ValidateTensorShapesFromInputs(), ConvertFp16ToFp32Layer::ValidateTensorShapesFromInputs(), ElementwiseUnaryLayer::ValidateTensorShapesFromInputs(), StridedSliceLayer::ValidateTensorShapesFromInputs(), ArgMinMaxLayer::ValidateTensorShapesFromInputs(), PreluLayer::ValidateTensorShapesFromInputs(), SpaceToDepthLayer::ValidateTensorShapesFromInputs(), TransposeConvolution2dLayer::ValidateTensorShapesFromInputs(), DepthToSpaceLayer::ValidateTensorShapesFromInputs(), DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs(), ComparisonLayer::ValidateTensorShapesFromInputs(), FullyConnectedLayer::ValidateTensorShapesFromInputs(), SpaceToBatchNdLayer::ValidateTensorShapesFromInputs(), Convolution2dLayer::ValidateTensorShapesFromInputs(), ConcatLayer::ValidateTensorShapesFromInputs(), BatchNormalizationLayer::ValidateTensorShapesFromInputs(), OutputLayer::ValidateTensorShapesFromInputs(), QuantizedLstmLayer::ValidateTensorShapesFromInputs(), LstmLayer::ValidateTensorShapesFromInputs(), and Layer::VerifyLayerConnections().

{ return m_InputSlots.at(index); }

GetInputSlot() [2/2]

InputSlot& GetInputSlot ( unsigned int  index )

inlineoverridevirtual

Get the input slot handle by slot index.

Implements IConnectableLayer.

Definition at line 311 of file Layer.hpp.

{ return  m_InputSlots.at(index); }

GetInputSlots()

const std::vector<InputSlot>& GetInputSlots ( ) const

inline

Definition at line 231 of file Layer.hpp.

Referenced by BOOST_AUTO_TEST_CASE(), SplitterLayer::CreateWorkload(), LoadedNetwork::EnqueueWorkload(), armnn::ForEachLayerInput(), Layer::GetPriority(), IWorkloadFactory::IsLayerSupported(), and Layer::Layer().

{ return m_InputSlots; }

GetName()

const char* GetName ( ) const

inlineoverridevirtual

Returns the name of the layer.

Implements IConnectableLayer.

Definition at line 305 of file Layer.hpp.

Referenced by AdditionLayer::Accept(), QuantizeLayer::Accept(), MultiplicationLayer::Accept(), DivisionLayer::Accept(), MaximumLayer::Accept(), SubtractionLayer::Accept(), MinimumLayer::Accept(), ActivationLayer::Accept(), AbsLayer::Accept(), NormalizationLayer::Accept(), FloorLayer::Accept(), InputLayer::Accept(), InstanceNormalizationLayer::Accept(), RsqrtLayer::Accept(), SoftmaxLayer::Accept(), L2NormalizationLayer::Accept(), SwitchLayer::Accept(), DequantizeLayer::Accept(), PadLayer::Accept(), GatherLayer::Accept(), LogSoftmaxLayer::Accept(), MeanLayer::Accept(), MergeLayer::Accept(), ArgMinMaxLayer::Accept(), DetectionPostProcessLayer::Accept(), Pooling2dLayer::Accept(), ElementwiseUnaryLayer::Accept(), ResizeLayer::Accept(), SliceLayer::Accept(), BatchToSpaceNdLayer::Accept(), StackLayer::Accept(), StridedSliceLayer::Accept(), PreluLayer::Accept(), SpaceToBatchNdLayer::Accept(), SpaceToDepthLayer::Accept(), DepthToSpaceLayer::Accept(), ComparisonLayer::Accept(), StandInLayer::Accept(), ConstantLayer::Accept(), BatchNormalizationLayer::Accept(), OutputLayer::Accept(), TransposeConvolution2dLayer::Accept(), FullyConnectedLayer::Accept(), DepthwiseConvolution2dLayer::Accept(), Convolution2dLayer::Accept(), ConcatLayer::Accept(), ReshapeLayer::Accept(), SplitterLayer::Accept(), TransposeLayer::Accept(), PermuteLayer::Accept(), QuantizedLstmLayer::Accept(), LstmLayer::Accept(), Graph::AddCompatibilityLayers(), BOOST_AUTO_TEST_CASE(), armnnTfParser::CalcPadding(), QuantizeLayer::Clone(), TransposeLayer::Clone(), ActivationLayer::Clone(), NormalizationLayer::Clone(), PermuteLayer::Clone(), Pooling2dLayer::Clone(), FakeQuantizationLayer::Clone(), StackLayer::Clone(), FloorLayer::Clone(), MemImportLayer::Clone(), AbsLayer::Clone(), ConvertFp32ToFp16Layer::Clone(), ReshapeLayer::Clone(), ResizeLayer::Clone(), SoftmaxLayer::Clone(), MergeLayer::Clone(), L2NormalizationLayer::Clone(), SliceLayer::Clone(), InputLayer::Clone(), InstanceNormalizationLayer::Clone(), BatchToSpaceNdLayer::Clone(), DebugLayer::Clone(), StridedSliceLayer::Clone(), RsqrtLayer::Clone(), AdditionLayer::Clone(), SwitchLayer::Clone(), DequantizeLayer::Clone(), MemCopyLayer::Clone(), ConvertFp16ToFp32Layer::Clone(), StandInLayer::Clone(), PreluLayer::Clone(), MultiplicationLayer::Clone(), GatherLayer::Clone(), ArgMinMaxLayer::Clone(), PadLayer::Clone(), SpaceToDepthLayer::Clone(), DivisionLayer::Clone(), MinimumLayer::Clone(), ElementwiseUnaryLayer::Clone(), SpaceToBatchNdLayer::Clone(), SubtractionLayer::Clone(), MaximumLayer::Clone(), LogSoftmaxLayer::Clone(), MeanLayer::Clone(), ComparisonLayer::Clone(), DepthToSpaceLayer::Clone(), ConstantLayer::Clone(), PreCompiledLayer::Clone(), DetectionPostProcessLayer::Clone(), TransposeConvolution2dLayer::Clone(), FullyConnectedLayer::Clone(), DepthwiseConvolution2dLayer::Clone(), Convolution2dLayer::Clone(), ConcatLayer::Clone(), SplitterLayer::Clone(), BatchNormalizationLayer::Clone(), OutputLayer::Clone(), QuantizedLstmLayer::Clone(), LstmLayer::Clone(), armnn::InsertConvertFp16ToFp32LayersBefore(), armnn::InsertConvertFp32ToFp16LayersAfter(), TransposeAsReshapeImpl::Run(), PermuteAsReshapeImpl::Run(), FoldPadIntoConvolution2dImpl::Run(), OptimizeConsecutiveReshapesImpl::Run(), PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteType >::Run(), and ErasedLayerNamesObservable::Update().

{ return m_LayerName.c_str(); }

GetNameStr()

const std::string& GetNameStr ( ) const

inline

Definition at line 216 of file Layer.hpp.

Referenced by BOOST_AUTO_TEST_CASE(), armnn::CheckScaleSetOnQuantizedType(), DebugLayer::CreateWorkload(), LoadedNetwork::GetOutputTensorInfo(), Layer::InferOutputShapes(), armnn::InsertDebugLayerAfter(), IsConnected(), and Layer::VerifyLayerConnections().

    {
        return m_LayerName;
    }

GetNumInputSlots()

unsigned int GetNumInputSlots ( ) const

inlineoverridevirtual

Returns the number of connectable input slots.

Implements IConnectableLayer.

Definition at line 307 of file Layer.hpp.

Referenced by CheckNumberOfInputSlot(), ConcatLayer::CreateWorkload(), LoadedNetwork::EnqueueWorkload(), Layer::GetDataType(), Layer::InferOutputShapes(), InputSlot::Insert(), armnn::InsertConvertFp16ToFp32LayersBefore(), StackLayer::ValidateTensorShapesFromInputs(), ConcatLayer::ValidateTensorShapesFromInputs(), and Layer::VerifyLayerConnections().

{ return static_cast<unsigned int>(m_InputSlots.size()); }

GetNumOutputSlots()

unsigned int GetNumOutputSlots ( ) const

inlineoverridevirtual

Returns the number of connectable output slots.

Implements IConnectableLayer.

Definition at line 308 of file Layer.hpp.

Referenced by BOOST_AUTO_TEST_CASE(), armnnTfParser::CalcPadding(), OutputSlot::CalculateIndexOnOwner(), CheckNumberOfOutputSlot(), armnn::CheckScaleSetOnQuantizedType(), Layer::CreateTensorHandles(), LoadedNetwork::EnqueueWorkload(), Layer::InferOutputShapes(), InputSlot::Insert(), armnn::InsertConvertFp32ToFp16LayersAfter(), armnn::InsertDebugLayerAfter(), armnn::SelectTensorHandleStrategy(), SwitchLayer::ValidateTensorShapesFromInputs(), and DetectionPostProcessLayer::ValidateTensorShapesFromInputs().

{ return static_cast<unsigned int>(m_OutputSlots.size()); }

GetOutputHandler() [1/2]

const OutputHandler& GetOutputHandler ( unsigned int  i = 0 ) const

inline

Definition at line 221 of file Layer.hpp.

Referenced by BOOST_AUTO_TEST_CASE(), Layer::CreateTensorHandles(), ConcatLayer::CreateWorkload(), LoadedNetwork::EnqueueWorkload(), InputSlot::Insert(), PermuteAsReshapeImpl::Run(), TransposeAsReshapeImpl::Run(), OptimizeConsecutiveReshapesImpl::Run(), FoldPadIntoConvolution2dImpl::Run(), PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteType >::Run(), MoveTransposeUpImpl::Run(), and MovePermuteUpImpl::Run().

    {
        return m_OutputHandlers[i];
    }

GetOutputHandler() [2/2]

OutputHandler& GetOutputHandler ( unsigned int  i = 0 )

inline

Definition at line 226 of file Layer.hpp.

    {
        return const_cast<OutputHandler&>(const_cast<const Layer*>(this)->GetOutputHandler(i));
    }

GetOutputSlot() [1/2]

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

inlineoverridevirtual

Get the const output slot handle by slot index.

Implements IConnectableLayer.

Definition at line 312 of file Layer.hpp.

Referenced by Graph::AddCompatibilityLayers(), BOOST_AUTO_TEST_CASE(), BOOST_FIXTURE_TEST_CASE(), armnnTfParser::CalcPadding(), OutputSlot::CalculateIndexOnOwner(), armnn::CheckScaleSetOnQuantizedType(), CreateConvolution2dGraph(), CreateDepthwiseConvolution2dGraph(), CreateGatherGraph(), CreatePooling2dGraph(), CreateResizeBilinearGraph(), ConcatLayer::CreateTensorHandles(), SplitterLayer::CreateTensorHandles(), Layer::CreateTensorHandles(), SplitterLayer::CreateWorkload(), ConcatLayer::CreateWorkload(), Layer::GetDataType(), InputSlot::Insert(), armnn::InsertConvertFp16ToFp32LayersBefore(), armnn::InsertConvertFp32ToFp16LayersAfter(), armnn::InsertDebugLayerAfter(), IsConnected(), IWorkloadFactory::IsLayerSupported(), PermuteAsReshapeImpl::Run(), TransposeAsReshapeImpl::Run(), OptimizeConsecutiveReshapesImpl::Run(), FoldPadIntoConvolution2dImpl::Run(), OptimizeInverseConversionsImpl::Run(), PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteType >::Run(), MovePermuteUpImpl::Run(), OptimizeInversePermutesImpl< PermuteType >::Run(), MoveTransposeUpImpl::Run(), armnn::SelectTensorHandleStrategy(), ElementwiseBaseLayer::ValidateTensorShapesFromInputs(), QuantizeLayer::ValidateTensorShapesFromInputs(), ActivationLayer::ValidateTensorShapesFromInputs(), TransposeLayer::ValidateTensorShapesFromInputs(), ConvertFp32ToFp16Layer::ValidateTensorShapesFromInputs(), InputLayer::ValidateTensorShapesFromInputs(), MemImportLayer::ValidateTensorShapesFromInputs(), DebugLayer::ValidateTensorShapesFromInputs(), MergeLayer::ValidateTensorShapesFromInputs(), NormalizationLayer::ValidateTensorShapesFromInputs(), PermuteLayer::ValidateTensorShapesFromInputs(), Pooling2dLayer::ValidateTensorShapesFromInputs(), BatchToSpaceNdLayer::ValidateTensorShapesFromInputs(), DequantizeLayer::ValidateTensorShapesFromInputs(), ReshapeLayer::ValidateTensorShapesFromInputs(), ResizeLayer::ValidateTensorShapesFromInputs(), RsqrtLayer::ValidateTensorShapesFromInputs(), SliceLayer::ValidateTensorShapesFromInputs(), SoftmaxLayer::ValidateTensorShapesFromInputs(), L2NormalizationLayer::ValidateTensorShapesFromInputs(), AbsLayer::ValidateTensorShapesFromInputs(), FakeQuantizationLayer::ValidateTensorShapesFromInputs(), MemCopyLayer::ValidateTensorShapesFromInputs(), FloorLayer::ValidateTensorShapesFromInputs(), StackLayer::ValidateTensorShapesFromInputs(), SwitchLayer::ValidateTensorShapesFromInputs(), InstanceNormalizationLayer::ValidateTensorShapesFromInputs(), GatherLayer::ValidateTensorShapesFromInputs(), LogSoftmaxLayer::ValidateTensorShapesFromInputs(), MeanLayer::ValidateTensorShapesFromInputs(), ConvertFp16ToFp32Layer::ValidateTensorShapesFromInputs(), ConstantLayer::ValidateTensorShapesFromInputs(), ArgMinMaxLayer::ValidateTensorShapesFromInputs(), DetectionPostProcessLayer::ValidateTensorShapesFromInputs(), ElementwiseUnaryLayer::ValidateTensorShapesFromInputs(), StridedSliceLayer::ValidateTensorShapesFromInputs(), TransposeConvolution2dLayer::ValidateTensorShapesFromInputs(), DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs(), SpaceToDepthLayer::ValidateTensorShapesFromInputs(), FullyConnectedLayer::ValidateTensorShapesFromInputs(), ComparisonLayer::ValidateTensorShapesFromInputs(), DepthToSpaceLayer::ValidateTensorShapesFromInputs(), SpaceToBatchNdLayer::ValidateTensorShapesFromInputs(), PreluLayer::ValidateTensorShapesFromInputs(), Convolution2dLayer::ValidateTensorShapesFromInputs(), SplitterLayer::ValidateTensorShapesFromInputs(), BatchNormalizationLayer::ValidateTensorShapesFromInputs(), QuantizedLstmLayer::ValidateTensorShapesFromInputs(), and LstmLayer::ValidateTensorShapesFromInputs().

{ return m_OutputSlots.at(index); }

GetOutputSlot() [2/2]

OutputSlot& GetOutputSlot ( unsigned int  index = 0 )

inlineoverridevirtual

Get the output slot handle by slot index.

Implements IConnectableLayer.

Definition at line 313 of file Layer.hpp.

{ return m_OutputSlots.at(index); }

GetOutputSlots()

const std::vector<OutputSlot>& GetOutputSlots ( ) const

inline

Definition at line 232 of file Layer.hpp.

Referenced by Graph::AddCompatibilityLayers(), armnn::ForEachLayerOutput(), and IWorkloadFactory::IsLayerSupported().

{ return m_OutputSlots; }

GetPriority()

LayerPriority GetPriority

(

)

const

Definition at line 288 of file Layer.cpp.

References Layer::GetInputSlots(), OutputSlot::GetOwningLayer(), Layer::GetPriority(), Layer::GetType(), armnn::Input, and armnn::Output.

Referenced by Layer::GetPriority(), and SquashEqualSiblingsImpl< Comparable >::Run().

{
    constexpr LayerPriority inputPrio = std::numeric_limits<LayerPriority>::lowest();
    constexpr LayerPriority outputPrio = std::numeric_limits<LayerPriority>::max();

    if (GetType() == LayerType::Input)
    {
        m_Priority = inputPrio;
    }
    else if (GetType() == LayerType::Output)
    {
        m_Priority = outputPrio;
    }
    else if (m_Priority == 0)
    {
        if (m_Visiting)
        {
            throw GraphValidationException("Graph has circular dependencies: cannot walk");
        }

        auto maxPrio = [](const LayerPriority prio, const InputSlot& slot) -> LayerPriority
            {
                const OutputSlot *outputSlot = slot.GetConnectedOutputSlot();
                if (outputSlot)
                {
                    const Layer& input = outputSlot->GetOwningLayer();
                    return std::max(prio, input.GetPriority());
                }
                else
                {
                    // unconnected input slot
                    return prio;
                }
            };

        m_Visiting = true;
        LayerPriority parentPrio = std::accumulate(GetInputSlots().cbegin(), GetInputSlots().cend(), 0U, maxPrio);
        m_Visiting = false;

        if (parentPrio >= outputPrio)
        {
            throw GraphValidationException("Graph has too many edges");
        }

        m_Priority = parentPrio + 1U;
    }

    return m_Priority;
}

GetRelatedLayerNames()

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

inline

Definition at line 320 of file Layer.hpp.

Referenced by ErasedLayerNamesObservable::Update().

{ return m_RelatedLayerNames; }

GetType()

LayerType GetType ( ) const

inline

Definition at line 259 of file Layer.hpp.

Referenced by armnn::ApplyBackendOptimizations(), armnn::AttemptBackendAssignment(), BOOST_AUTO_TEST_CASE(), BOOST_FIXTURE_TEST_CASE(), armnn::CalculateEdgeStrategy(), armnn::CalculateSlotOption(), armnn::CalculateSlotOptionForInput(), armnn::CheckScaleSetOnQuantizedType(), ConcatLayer::CreateWorkload(), LoadedNetwork::EnqueueWorkload(), Layer::GetPriority(), Layer::InferOutputShapes(), ReshapeLayer::IsEqual(), TransposeLayer::IsEqual(), PermuteLayer::IsEqual(), TransposeLayer::IsInverse(), PermuteLayer::IsInverse(), IsLayerOfType(), IWorkloadFactory::IsLayerSupported(), MockBackend::OptimizeSubgraphView(), armnn::ReturnWithError(), ConvertFp32NetworkToFp16Impl::Run(), AddDebugImpl::Run(), FoldPadIntoConvolution2dImpl::Run(), OptimizeConsecutiveReshapesImpl::Run(), PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteType >::Run(), OptimizeInverseConversionsImpl::Run(), MoveTransposeUpImpl::Run(), MovePermuteUpImpl::Run(), OptimizeForTypeImpl< BaseType, OptimizeForConnectionImpl< BaseType, ChildType, Wrapped > >::Run(), armnn::SelectTensorHandleStrategy(), ElementwiseBaseLayer::ValidateTensorShapesFromInputs(), and Layer::VerifyLayerConnections().

{ return m_Type; }

InferOutputShapes()

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

overridevirtual

Infer the shape of the output(s) based on the provided input shape(s)

Implements IConnectableLayer.

Reimplemented in LstmLayer, QuantizedLstmLayer, SplitterLayer, ConcatLayer, Convolution2dLayer, DepthwiseConvolution2dLayer, FullyConnectedLayer, TransposeConvolution2dLayer, ConstantLayer, StandInLayer, BatchToSpaceNdLayer, PermuteLayer, Pooling2dLayer, ReshapeLayer, ResizeLayer, SliceLayer, StackLayer, MergeLayer, TransposeLayer, ComparisonLayer, DepthToSpaceLayer, PreluLayer, SpaceToBatchNdLayer, SpaceToDepthLayer, ArgMinMaxLayer, ElementwiseUnaryLayer, StridedSliceLayer, and ElementwiseBaseLayer.

Definition at line 371 of file Layer.cpp.

References CHECK_LOCATION, armnn::GetLayerTypeAsCString(), Layer::GetNameStr(), Layer::GetNumInputSlots(), Layer::GetNumOutputSlots(), and Layer::GetType().

Referenced by QuantizeLayer::ValidateTensorShapesFromInputs(), ActivationLayer::ValidateTensorShapesFromInputs(), SoftmaxLayer::ValidateTensorShapesFromInputs(), RsqrtLayer::ValidateTensorShapesFromInputs(), SwitchLayer::ValidateTensorShapesFromInputs(), NormalizationLayer::ValidateTensorShapesFromInputs(), MemImportLayer::ValidateTensorShapesFromInputs(), AbsLayer::ValidateTensorShapesFromInputs(), FakeQuantizationLayer::ValidateTensorShapesFromInputs(), L2NormalizationLayer::ValidateTensorShapesFromInputs(), InstanceNormalizationLayer::ValidateTensorShapesFromInputs(), FloorLayer::ValidateTensorShapesFromInputs(), ConvertFp32ToFp16Layer::ValidateTensorShapesFromInputs(), DequantizeLayer::ValidateTensorShapesFromInputs(), MemCopyLayer::ValidateTensorShapesFromInputs(), DebugLayer::ValidateTensorShapesFromInputs(), ConvertFp16ToFp32Layer::ValidateTensorShapesFromInputs(), LogSoftmaxLayer::ValidateTensorShapesFromInputs(), and BatchNormalizationLayer::ValidateTensorShapesFromInputs().

{
    BOOST_ASSERT(GetNumInputSlots() != 0);
    BOOST_ASSERT(GetNumOutputSlots() != 0);

    // By default we return what we got, meaning the output shape(s) are the same as the input(s).
    // This only works if the number of inputs and outputs are the same. Since we are in the Layer
    // base class, this means the implementation needs to be overridden in the specific layers for
    // the other cases. So the missing implementation justifies the UnimplementedException.

    if (GetNumInputSlots() != GetNumOutputSlots())
    {
        throw UnimplementedException(
            boost::str(
                boost::format(
                    "Default implementation for InferOutputShapes can only be used for "
                    "layers with the same number of input and output slots. This doesn't "
                    "hold for %1% layer %2% (#inputs=%3% #outputs=%4%) %5%")
                    % GetLayerTypeAsCString(this->GetType())
                    % GetNameStr()
                    % GetNumInputSlots()
                    % GetNumOutputSlots()
                    % CHECK_LOCATION().AsString()));
    }
    return inputShapes;
}

IsOutputUnconnected()

bool IsOutputUnconnected ( )

inline

Definition at line 243 of file Layer.hpp.

Referenced by OptimizeForConnectionImpl< BaseType, ChildType, Wrapped >::Run().

    {
        unsigned int numConnections = 0;

        for (auto&& output : GetOutputSlots())
        {
            numConnections += output.GetNumConnections();
        }

        return (GetNumOutputSlots() > 0) && (numConnections == 0);
    }

OperateOnConstantTensors()

void OperateOnConstantTensors ( Op  op )

inline

Definition at line 292 of file Layer.hpp.

Referenced by Layer::ReleaseConstantData(), and ConvertConstants< Converter, Predicate >::Run().

    {
        for (auto constant : GetConstantTensorsByRef())
        {
            if (constant.get())
            {
                op(constant);
            }
        }
    };

PrepInfoAndDesc()

WorkloadInfo PrepInfoAndDesc ( QueueDescriptor &  descriptor ) const

inlineprotected

Helper function to reduce duplication in *LayerCreateWorkload.

Definition at line 351 of file Layer.hpp.

References armnn::info.

Referenced by AbsLayer::CreateWorkload(), AdditionLayer::CreateWorkload(), FloorLayer::CreateWorkload(), QuantizeLayer::CreateWorkload(), ConvertFp32ToFp16Layer::CreateWorkload(), RsqrtLayer::CreateWorkload(), SwitchLayer::CreateWorkload(), DebugLayer::CreateWorkload(), MemCopyLayer::CreateWorkload(), DequantizeLayer::CreateWorkload(), MemImportLayer::CreateWorkload(), PreluLayer::CreateWorkload(), SubtractionLayer::CreateWorkload(), DivisionLayer::CreateWorkload(), ConvertFp16ToFp32Layer::CreateWorkload(), GatherLayer::CreateWorkload(), MinimumLayer::CreateWorkload(), MultiplicationLayer::CreateWorkload(), MaximumLayer::CreateWorkload(), ConstantLayer::CreateWorkload(), QuantizedLstmLayer::CreateWorkload(), and LayerWithParameters< ResizeDescriptor >::PrepInfoAndDesc().

    {
        WorkloadInfo info;
        CollectQueueDescriptorInputs(descriptor, info);
        CollectQueueDescriptorOutputs(descriptor, info);
        return info;
    }

ReleaseConstantData()

void ReleaseConstantData ( )

virtual

Reimplemented in ConstantLayer.

Definition at line 264 of file Layer.cpp.

References Layer::OperateOnConstantTensors().

Referenced by BOOST_AUTO_TEST_CASE().

{
    // Now free up the static data.
    OperateOnConstantTensors([](std::unique_ptr<ScopedCpuTensorHandle>& handle)
                                 {
                                     handle.reset(nullptr);
                                 });
}

Reparent()

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

pure virtual

Referenced by Graph::operator=(), and Graph::SubstituteSubgraph().

ResetPriority()

void ResetPriority

(

)

const

Definition at line 282 of file Layer.cpp.

{
    m_Priority = 0;
    m_Visiting = false;
}

SerializeLayerParameters()

void SerializeLayerParameters ( ParameterStringifyFunction &  fn ) const

virtual

Helper to serialize the layer parameters to string.

(currently used in DotSerializer and company).

Reimplemented in Convolution2dLayer, DepthwiseConvolution2dLayer, LayerWithParameters< Parameters >, LayerWithParameters< FakeQuantizationDescriptor >, LayerWithParameters< SoftmaxDescriptor >, LayerWithParameters< LstmDescriptor >, LayerWithParameters< LogSoftmaxDescriptor >, LayerWithParameters< PreCompiledDescriptor >, LayerWithParameters< BatchToSpaceNdDescriptor >, LayerWithParameters< PermuteDescriptor >, LayerWithParameters< SpaceToBatchNdDescriptor >, LayerWithParameters< DepthToSpaceDescriptor >, LayerWithParameters< ReshapeDescriptor >, LayerWithParameters< ElementwiseUnaryDescriptor >, LayerWithParameters< SpaceToDepthDescriptor >, LayerWithParameters< OriginsDescriptor >, LayerWithParameters< ViewsDescriptor >, LayerWithParameters< Pooling2dDescriptor >, LayerWithParameters< Convolution2dDescriptor >, LayerWithParameters< ActivationDescriptor >, LayerWithParameters< StandInDescriptor >, LayerWithParameters< TransposeDescriptor >, LayerWithParameters< StackDescriptor >, LayerWithParameters< MeanDescriptor >, LayerWithParameters< ComparisonDescriptor >, LayerWithParameters< InstanceNormalizationDescriptor >, LayerWithParameters< TransposeConvolution2dDescriptor >, LayerWithParameters< BatchNormalizationDescriptor >, LayerWithParameters< ArgMinMaxDescriptor >, LayerWithParameters< DetectionPostProcessDescriptor >, LayerWithParameters< PadDescriptor >, LayerWithParameters< L2NormalizationDescriptor >, LayerWithParameters< SliceDescriptor >, LayerWithParameters< DepthwiseConvolution2dDescriptor >, LayerWithParameters< NormalizationDescriptor >, LayerWithParameters< FullyConnectedDescriptor >, LayerWithParameters< StridedSliceDescriptor >, and LayerWithParameters< ResizeDescriptor >.

Definition at line 398 of file Layer.cpp.

References armnn::GetLayerTypeAsCString().

Referenced by LayerWithParameters< ResizeDescriptor >::SerializeLayerParameters().

{
    std::string layerType = GetLayerTypeAsCString(m_Type);
    std::string backendId = std::string(m_BackendId);
    if(!(m_LayerName.compare("") == 0) && !m_LayerName.empty())
    {
        fn("LayerName",m_LayerName);
    }
    if(!(layerType.compare("") == 0) && !layerType.empty())
    {
        fn("LayerType",layerType);
    }
    if(!(backendId.compare("") == 0) && !backendId.empty())
    {
        fn("BackendID",backendId);
    }
}

SetBackendId()

void SetBackendId ( const BackendId &  id )

inline

Definition at line 264 of file Layer.hpp.

References CreateWorkload().

Referenced by armnn::AttemptBackendAssignment(), BOOST_AUTO_TEST_CASE(), BOOST_FIXTURE_TEST_CASE(), armnn::InsertDebugLayerAfter(), and MockBackend::OptimizeSubgraphView().

{ m_BackendId = id; }

SetGuid()

void SetGuid ( LayerGuid  guid )

inline

Definition at line 315 of file Layer.hpp.

{ m_Guid = guid; }

ValidateTensorShapesFromInputs()

virtual void ValidateTensorShapesFromInputs ( )

pure virtual

Implemented in LstmLayer, QuantizedLstmLayer, OutputLayer, BatchNormalizationLayer, SplitterLayer, ConcatLayer, Convolution2dLayer, ComparisonLayer, DepthToSpaceLayer, DepthwiseConvolution2dLayer, FullyConnectedLayer, PreluLayer, SpaceToBatchNdLayer, SpaceToDepthLayer, TransposeConvolution2dLayer, ArgMinMaxLayer, DetectionPostProcessLayer, ElementwiseUnaryLayer, StridedSliceLayer, PreCompiledLayer, ConstantLayer, ConvertFp16ToFp32Layer, GatherLayer, LogSoftmaxLayer, MeanLayer, PadLayer, StandInLayer, AbsLayer, BatchToSpaceNdLayer, ConvertFp32ToFp16Layer, DebugLayer, DequantizeLayer, FakeQuantizationLayer, FloorLayer, InputLayer, InstanceNormalizationLayer, L2NormalizationLayer, MemCopyLayer, MemImportLayer, MergeLayer, NormalizationLayer, PermuteLayer, Pooling2dLayer, ReshapeLayer, ResizeLayer, RsqrtLayer, SliceLayer, SoftmaxLayer, StackLayer, SwitchLayer, TransposeLayer, ActivationLayer, QuantizeLayer, and ElementwiseBaseLayer.

VerifyLayerConnections()

void VerifyLayerConnections	(	unsigned int	expectedConnections,
		const CheckLocation &	location
	)		const

Definition at line 338 of file Layer.cpp.

References CheckLocation::AsString(), Layer::GetInputSlot(), armnn::GetLayerTypeAsCString(), Layer::GetNameStr(), Layer::GetNumInputSlots(), and Layer::GetType().

Referenced by ElementwiseBaseLayer::ValidateTensorShapesFromInputs(), QuantizeLayer::ValidateTensorShapesFromInputs(), ActivationLayer::ValidateTensorShapesFromInputs(), TransposeLayer::ValidateTensorShapesFromInputs(), SwitchLayer::ValidateTensorShapesFromInputs(), L2NormalizationLayer::ValidateTensorShapesFromInputs(), AbsLayer::ValidateTensorShapesFromInputs(), Pooling2dLayer::ValidateTensorShapesFromInputs(), ConvertFp32ToFp16Layer::ValidateTensorShapesFromInputs(), SliceLayer::ValidateTensorShapesFromInputs(), RsqrtLayer::ValidateTensorShapesFromInputs(), FakeQuantizationLayer::ValidateTensorShapesFromInputs(), ReshapeLayer::ValidateTensorShapesFromInputs(), ResizeLayer::ValidateTensorShapesFromInputs(), FloorLayer::ValidateTensorShapesFromInputs(), SoftmaxLayer::ValidateTensorShapesFromInputs(), StackLayer::ValidateTensorShapesFromInputs(), PermuteLayer::ValidateTensorShapesFromInputs(), BatchToSpaceNdLayer::ValidateTensorShapesFromInputs(), InstanceNormalizationLayer::ValidateTensorShapesFromInputs(), DebugLayer::ValidateTensorShapesFromInputs(), DequantizeLayer::ValidateTensorShapesFromInputs(), MemCopyLayer::ValidateTensorShapesFromInputs(), MemImportLayer::ValidateTensorShapesFromInputs(), MergeLayer::ValidateTensorShapesFromInputs(), NormalizationLayer::ValidateTensorShapesFromInputs(), ConvertFp16ToFp32Layer::ValidateTensorShapesFromInputs(), GatherLayer::ValidateTensorShapesFromInputs(), MeanLayer::ValidateTensorShapesFromInputs(), LogSoftmaxLayer::ValidateTensorShapesFromInputs(), StridedSliceLayer::ValidateTensorShapesFromInputs(), ElementwiseUnaryLayer::ValidateTensorShapesFromInputs(), ArgMinMaxLayer::ValidateTensorShapesFromInputs(), DetectionPostProcessLayer::ValidateTensorShapesFromInputs(), DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs(), TransposeConvolution2dLayer::ValidateTensorShapesFromInputs(), SpaceToDepthLayer::ValidateTensorShapesFromInputs(), FullyConnectedLayer::ValidateTensorShapesFromInputs(), PreluLayer::ValidateTensorShapesFromInputs(), SpaceToBatchNdLayer::ValidateTensorShapesFromInputs(), ComparisonLayer::ValidateTensorShapesFromInputs(), DepthToSpaceLayer::ValidateTensorShapesFromInputs(), Convolution2dLayer::ValidateTensorShapesFromInputs(), ConcatLayer::ValidateTensorShapesFromInputs(), BatchNormalizationLayer::ValidateTensorShapesFromInputs(), QuantizedLstmLayer::ValidateTensorShapesFromInputs(), and LstmLayer::ValidateTensorShapesFromInputs().

{
    BOOST_ASSERT(GetNumInputSlots() == expectedConnections);

    for (unsigned int i=0; i<expectedConnections; ++i)
    {
        if (GetInputSlot(i).GetConnection() == nullptr)
        {
            throw LayerValidationException(
                boost::str(
                    boost::format(
                        "Input connection #%1% must be connected "
                        "for %2% layer %3% %4%")
                        % i
                        % GetLayerTypeAsCString(this->GetType())
                        % GetNameStr()
                        % location.AsString()));
        }
        if(! GetInputSlot(i).GetConnection()->IsTensorInfoSet())
        {
            throw LayerValidationException(
                boost::str(
                    boost::format(
                        "TensorInfo of Input connection #%1% must be set on connected OutputSlot for "
                        "%2% layer %3% %4%")
                        % i
                        % GetLayerTypeAsCString(this->GetType())
                        % GetNameStr()
                        % location.AsString()));
        }
    }
}

Friends And Related Function Documentation

Graph

friend class Graph

friend

Definition at line 332 of file Layer.hpp.

Member Data Documentation

m_OutputHandlers

std::vector<OutputHandler> m_OutputHandlers

protected

Definition at line 371 of file Layer.hpp.

Referenced by ConcatLayer::CreateWorkload(), SplitterLayer::CreateWorkload(), and Layer::Layer().

---

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

• src/armnn/Layer.hpp
• src/armnn/Layer.cpp
• src/armnn/layers/LayerCloneBase.hpp