Layer Class Reference

#include <Layer.hpp>

Inheritance diagram for Layer:

Collaboration 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)
void	ExecuteStrategy (IStrategy &strategy) const override
	Apply a visitor to this layer. More...
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 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
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
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
virtual ImmutableConstantTensors	GetConstantTensorsByRef () const override
void	SetAdditionalInfo (QueueDescriptor &descriptor) const
Protected Member Functions inherited from IConnectableLayer
	~IConnectableLayer ()
	Objects are not deletable via the handle. More...

Protected Attributes
AdditionalInfoObjectPtr	m_AdditionalInfoObject
std::vector< OutputHandler >	m_OutputHandlers
ShapeInferenceMethod	m_ShapeInferenceMethod

Friends
class	Graph

Additional Inherited Members
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 > >>

Detailed Description

Definition at line 230 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 247 of file Layer.cpp.

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

References armnn::NCHW.

Layer() [2/2]

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

Definition at line 220 of file Layer.cpp.

: m_OutputHandlers(numOutputSlots)
, m_ShapeInferenceMethod(ShapeInferenceMethod::ValidateOnly)
, m_LayerName(name ? name : "")
, m_Type(type)
, m_BackendId()
, m_BackendHint(EmptyOptional())
, m_Guid(arm::pipe::IProfilingService::GetNextGuid())
{
    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]);
    }
}

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

~Layer()

virtual ~Layer ( )

protectedvirtualdefault

Member Function Documentation

AddRelatedLayerName()

void AddRelatedLayerName ( const std::string  layerName )

inline

Definition at line 345 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.

By providing a BackendSelectionHint there is no guarantee the input backend supports that layer. If IsLayerSupported() returns false with the backend hint, we default to calling IsLayerSupported() on the BackendPreferences vector. Use SetBackendId() if we can guarantee a backend supports that layer (IsLayerSupported returns true for a specific backend).

Implements IConnectableLayer.

Definition at line 351 of file Layer.hpp.

    {
        m_BackendHint = backend;
    }

BeginInputSlots()

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

inline

Definition at line 262 of file Layer.hpp.

{ return m_InputSlots.begin(); }

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

BeginOutputSlots()

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

inline

Definition at line 266 of file Layer.hpp.

{ return m_OutputSlots.begin(); }

Referenced by armnn::CreateOutputsFrom(), Graph::Graph(), armnn::InsertDebugLayerAfter(), NeonBackend::OptimizeSubgraphView(), ClBackend::OptimizeSubgraphView(), ConvertFp32NetworkToFp16Impl::Run(), SquashEqualSiblingsImpl< Comparable >::Run(), and SplitterLayer::ValidateTensorShapesFromInputs().

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 QLstmLayer, QuantizedLstmLayer, OutputLayer, BatchNormalizationLayer, ConcatLayer, LstmLayer, UnidirectionalSequenceLstmLayer, SplitterLayer, TransposeConvolution2dLayer, DetectionPostProcessLayer, PreCompiledLayer, Convolution2dLayer, Convolution3dLayer, DepthwiseConvolution2dLayer, FullyConnectedLayer, FusedLayer, ConstantLayer, ReshapeLayer, ArgMinMaxLayer, ComparisonLayer, DepthToSpaceLayer, DivisionLayer, ElementwiseBinaryLayer, ElementwiseUnaryLayer, GatherLayer, LogicalBinaryLayer, LogSoftmaxLayer, MaximumLayer, MeanLayer, MinimumLayer, MultiplicationLayer, PadLayer, PermuteLayer, PreluLayer, ReduceLayer, ReverseV2Layer, SpaceToBatchNdLayer, SpaceToDepthLayer, StandInLayer, SubtractionLayer, TransposeLayer, AbsLayer, AdditionLayer, BatchMatMulLayer, BatchToSpaceNdLayer, CastLayer, ConvertFp16ToFp32Layer, DebugLayer, DequantizeLayer, FakeQuantizationLayer, FloorLayer, GatherNdLayer, InputLayer, InstanceNormalizationLayer, L2NormalizationLayer, MapLayer, MemCopyLayer, MemImportLayer, MergeLayer, NormalizationLayer, Pooling2dLayer, Pooling3dLayer, ResizeLayer, RsqrtLayer, ShapeLayer, SliceLayer, SoftmaxLayer, StackLayer, StridedSliceLayer, SwitchLayer, TileLayer, UnmapLayer, ActivationLayer, BroadcastToLayer, ConvertFp32ToFp16Layer, FillLayer, RankLayer, QuantizeLayer, and ChannelShuffleLayer.

Referenced by SubgraphView::GetWorkingCopy(), and Graph::Graph().

CloneBase()

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

protected

Definition at line 14 of file LayerCloneBase.hpp.

{
    LayerType* const layer = graph.AddLayer<LayerType>(std::forward<Params>(params)...);
 
    layer->BackendSelectionHint(GetBackendHint());
    layer->SetBackendId(GetBackendId());
    layer->SetGuid(GetGuid());
    layer->SetShapeInferenceMethod(m_ShapeInferenceMethod);
    layer->SetAllowExpandedDims(m_AllowExpandedDims);
 
    return layer;
}

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

CollectQueueDescriptorInputs()

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

inlineprotected

Definition at line 386 of file Layer.hpp.

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

References armnn::info, and QueueDescriptor::m_Inputs.

Referenced by Layer::PrepInfoAndDesc().

CollectQueueDescriptorOutputs()

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

inlineprotected

Definition at line 393 of file Layer.hpp.

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

References armnn::info, and QueueDescriptor::m_Outputs.

Referenced by Layer::PrepInfoAndDesc().

CreateTensorHandles()

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

virtual

Reimplemented in ConcatLayer, OutputLayer, and SplitterLayer.

Definition at line 292 of file Layer.cpp.

{
    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;
            handleFactory = registry.GetFactory(factoryId);
            ARMNN_ASSERT(handleFactory);
            handler.CreateTensorHandles(*handleFactory, IsMemoryManaged);
        }
    }
}

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

CreateWorkload()

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

pure virtual

Implemented in QLstmLayer, QuantizedLstmLayer, BatchNormalizationLayer, LstmLayer, UnidirectionalSequenceLstmLayer, PreCompiledLayer, TransposeConvolution2dLayer, DetectionPostProcessLayer, FusedLayer, Convolution2dLayer, Convolution3dLayer, DepthwiseConvolution2dLayer, FullyConnectedLayer, ChannelShuffleLayer, ConstantLayer, ReshapeLayer, ArgMinMaxLayer, ComparisonLayer, DepthToSpaceLayer, DivisionLayer, ElementwiseBinaryLayer, ElementwiseUnaryLayer, GatherLayer, LogicalBinaryLayer, LogSoftmaxLayer, MaximumLayer, MeanLayer, MinimumLayer, MultiplicationLayer, PadLayer, PermuteLayer, PreluLayer, ReduceLayer, ReverseV2Layer, SpaceToBatchNdLayer, SpaceToDepthLayer, StandInLayer, SubtractionLayer, TransposeLayer, AbsLayer, AdditionLayer, BatchMatMulLayer, BatchToSpaceNdLayer, CastLayer, ConcatLayer, ConvertFp16ToFp32Layer, DebugLayer, DequantizeLayer, FakeQuantizationLayer, FloorLayer, GatherNdLayer, InputLayer, InstanceNormalizationLayer, L2NormalizationLayer, MapLayer, MemCopyLayer, MemImportLayer, MergeLayer, NormalizationLayer, OutputLayer, Pooling2dLayer, Pooling3dLayer, ResizeLayer, RsqrtLayer, ShapeLayer, SliceLayer, SoftmaxLayer, SplitterLayer, StackLayer, StridedSliceLayer, SwitchLayer, TileLayer, UnmapLayer, ActivationLayer, BroadcastToLayer, ConvertFp32ToFp16Layer, FillLayer, QuantizeLayer, and RankLayer.

EndInputSlots()

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

inline

Definition at line 263 of file Layer.hpp.

{ return m_InputSlots.end(); }

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

EndOutputSlots()

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

inline

Definition at line 267 of file Layer.hpp.

{ return m_OutputSlots.end(); }

Referenced by armnn::CreateOutputsFrom(), armnn::InsertDebugLayerAfter(), NeonBackend::OptimizeSubgraphView(), ClBackend::OptimizeSubgraphView(), ConvertFp32NetworkToFp16Impl::Run(), SquashEqualSiblingsImpl< Comparable >::Run(), and SplitterLayer::ValidateTensorShapesFromInputs().

ExecuteStrategy()

void ExecuteStrategy ( IStrategy &  strategy ) const

overridevirtual

Apply a visitor to this layer.

Implements IConnectableLayer.

Reimplemented in BindableLayer, QLstmLayer, QuantizedLstmLayer, PermuteLayer, TransposeLayer, LayerWithParameters< Parameters >, LayerWithParameters< SoftmaxDescriptor >, LayerWithParameters< FakeQuantizationDescriptor >, LayerWithParameters< ReduceDescriptor >, LayerWithParameters< LstmDescriptor >, LayerWithParameters< ChannelShuffleDescriptor >, LayerWithParameters< LogSoftmaxDescriptor >, LayerWithParameters< PreCompiledDescriptor >, LayerWithParameters< SpaceToBatchNdDescriptor >, LayerWithParameters< BatchToSpaceNdDescriptor >, LayerWithParameters< PermuteDescriptor >, LayerWithParameters< GatherDescriptor >, LayerWithParameters< ElementwiseUnaryDescriptor >, LayerWithParameters< DepthToSpaceDescriptor >, LayerWithParameters< OriginsDescriptor >, LayerWithParameters< SpaceToDepthDescriptor >, LayerWithParameters< ReshapeDescriptor >, LayerWithParameters< ViewsDescriptor >, LayerWithParameters< Pooling2dDescriptor >, LayerWithParameters< Convolution2dDescriptor >, LayerWithParameters< ActivationDescriptor >, LayerWithParameters< StandInDescriptor >, LayerWithParameters< MeanDescriptor >, LayerWithParameters< StackDescriptor >, LayerWithParameters< TransposeDescriptor >, LayerWithParameters< InstanceNormalizationDescriptor >, LayerWithParameters< ComparisonDescriptor >, LayerWithParameters< TransposeConvolution2dDescriptor >, LayerWithParameters< BroadcastToDescriptor >, LayerWithParameters< BatchNormalizationDescriptor >, LayerWithParameters< FusedDescriptor >, LayerWithParameters< BatchMatMulDescriptor >, LayerWithParameters< TileDescriptor >, LayerWithParameters< ArgMinMaxDescriptor >, LayerWithParameters< LogicalBinaryDescriptor >, LayerWithParameters< DetectionPostProcessDescriptor >, LayerWithParameters< PadDescriptor >, LayerWithParameters< L2NormalizationDescriptor >, LayerWithParameters< Convolution3dDescriptor >, LayerWithParameters< SliceDescriptor >, LayerWithParameters< QLstmDescriptor >, LayerWithParameters< FillDescriptor >, LayerWithParameters< DepthwiseConvolution2dDescriptor >, LayerWithParameters< NormalizationDescriptor >, LayerWithParameters< FullyConnectedDescriptor >, LayerWithParameters< ResizeDescriptor >, LayerWithParameters< Pooling3dDescriptor >, LayerWithParameters< ElementwiseBinaryDescriptor >, LayerWithParameters< StridedSliceDescriptor >, ReshapeLayer, UnidirectionalSequenceLstmLayer, ConcatLayer, LstmLayer, SplitterLayer, TransposeConvolution2dLayer, DetectionPostProcessLayer, OutputLayer, BatchNormalizationLayer, ConstantLayer, Convolution2dLayer, Convolution3dLayer, DepthwiseConvolution2dLayer, FullyConnectedLayer, ComparisonLayer, DepthToSpaceLayer, LogicalBinaryLayer, MeanLayer, PadLayer, PreluLayer, SpaceToBatchNdLayer, SpaceToDepthLayer, StandInLayer, ArgMinMaxLayer, BatchToSpaceNdLayer, ElementwiseUnaryLayer, GatherLayer, Pooling2dLayer, Pooling3dLayer, ReduceLayer, ResizeLayer, ReverseV2Layer, ShapeLayer, SliceLayer, StackLayer, StridedSliceLayer, BroadcastToLayer, ElementwiseBinaryLayer, MergeLayer, PreCompiledLayer, RankLayer, FakeQuantizationLayer, LogSoftmaxLayer, AbsLayer, ConvertFp16ToFp32Layer, DebugLayer, DequantizeLayer, FloorLayer, FusedLayer, InputLayer, InstanceNormalizationLayer, L2NormalizationLayer, MapLayer, MemCopyLayer, MemImportLayer, NormalizationLayer, RsqrtLayer, SoftmaxLayer, SwitchLayer, UnmapLayer, ConvertFp32ToFp16Layer, ElementwiseBaseLayer, FillLayer, ActivationLayer, DivisionLayer, MaximumLayer, MinimumLayer, MultiplicationLayer, SubtractionLayer, AdditionLayer, and QuantizeLayer.

Definition at line 549 of file Layer.cpp.

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

References IStrategy::ExecuteStrategy(), and Layer::GetName().

Referenced by armnn::IsNCHW().

GetAdditionalInformation()

std::shared_ptr<T> GetAdditionalInformation ( ) const

inline

Definition at line 368 of file Layer.hpp.

    {
        return std::static_pointer_cast<T>(m_AdditionalInfoObject);
    }

References Layer::m_AdditionalInfoObject.

Referenced by NeonBackend::OptimizeSubgraphView(), and ClBackend::OptimizeSubgraphView().

GetAllowExpandedDims()

bool GetAllowExpandedDims ( ) const

inline

Definition at line 256 of file Layer.hpp.

{ return m_AllowExpandedDims; };

Referenced by LayerWithParameters< StridedSliceDescriptor >::PrepInfoAndDesc().

GetBackendHint()

Optional<BackendId> GetBackendHint ( ) const

inline

Definition at line 355 of file Layer.hpp.

{ return m_BackendHint; }

Referenced by NetworkImpl::AddPrecompiledLayer(), and Layer::CloneBase().

GetBackendId()

const BackendId& GetBackendId ( ) const

inline

Definition at line 290 of file Layer.hpp.

{ return m_BackendId; }

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

GetConstantTensorsByRef() [1/2]

virtual ImmutableConstantTensors GetConstantTensorsByRef ( ) const

inlineoverrideprotectedvirtual

Implements IConnectableLayer.

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

Definition at line 427 of file Layer.hpp.

{ return ImmutableConstantTensors(); };

GetConstantTensorsByRef() [2/2]

Layer::ConstantTensors GetConstantTensorsByRef ( )

finaloverrideprotectedvirtual

Implements IConnectableLayer.

Definition at line 554 of file Layer.cpp.

{
    const Layer *constThis = const_cast<const Layer*>(this);
    ConstantTensors res;
 
    ImmutableConstantTensors immutableData = constThis->GetConstantTensorsByRef();
    for (auto i : immutableData)
    {
        res.push_back(const_cast<std::shared_ptr<ConstTensorHandle>&>(i.get()));
    }
    return res;
}

References Layer::GetConstantTensorsByRef().

Referenced by Layer::GetConstantTensorsByRef(), and Layer::OperateOnConstantTensors().

GetDataType()

DataType GetDataType

(

)

const

Definition at line 326 of file Layer.cpp.

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

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

Referenced by ConvertFp32NetworkToFp16Impl::Run(), ConvertConstPermuteLayersToConstLayers::Run(), FuseBatchNorm< ConvLayer, ArmnnType, T >::Run(), IsFloat32Layer::Test(), and IsFloat16Layer::Test().

GetGuid()

LayerGuid GetGuid ( ) const

inlinefinalvirtual

Returns the unique id of the layer.

Implements IConnectableLayer.

Definition at line 343 of file Layer.hpp.

{ return m_Guid; }

Referenced by Layer::CloneBase(), ConvertConstantToTosaOperator(), DebugLayer::CreateWorkload(), GenerateUniqueName(), OutputSlot::GetOwningLayerGuid(), RefBackend::OptimizeSubgraphView(), NeonBackend::OptimizeSubgraphView(), ClBackend::OptimizeSubgraphView(), GpuFsaBackend::OptimizeSubgraphView(), armnn::RemoveReshapeLayer(), and Graph::SerializeToDot().

GetInputSlot() [1/2]

const InputSlot& GetInputSlot ( unsigned int  index ) const

inlineoverridevirtual

Get a const input slot handle by slot index.

Implements IConnectableLayer.

Examples

AsyncExecutionSample.cpp, and SimpleSample.cpp.

Definition at line 337 of file Layer.hpp.

{ return m_InputSlots.at(index); }

Referenced by Graph::AddCompatibilityLayers(), armnn::ApplyBackendOptimizations(), armnn::ChainReduceLayers(), armnn::ConnectedToLayerType(), armnn::ConnectedToLayerWithNCHW(), ConvertActivationToTosaOperator(), ConvertAvgPool2DIgnoreValueToTosaOperator(), ConvertConcatToTosaOperator(), ConvertConv2dToTosaOperator(), ConvertElementwiseBinaryToTosaOperator(), ConvertElementwiseUnaryOperator(), ConvertPooling2DToTosaOperator(), ConvertQuantizeToTosaOperator(), ConvertReshapeToTosaOperator(), ConvertResizeToTosaOperator(), ConvertSliceToTosaOperator(), ConvertTransposeConv2dToTosaOperator(), ConvertTransposeToTosaOperator(), DebugLayer::CreateWorkload(), armnn::optimizations::pad_fold::FoldPadIntoLayer2dImpl(), LayerWithParameters< StridedSliceDescriptor >::GetConnectedConstantAsInputTensors(), Layer::GetDataType(), armnn::GetLayerInOutDatatype(), Graph::Graph(), InputSlot::Insert(), armnn::InsertConvertFp16ToFp32LayersBefore(), armnn::InsertConvertFp32ToFp16LayersAfter(), armnn::InsertDebugLayerAfter(), RefBackend::OptimizeSubgraphView(), NeonBackend::OptimizeSubgraphView(), ClBackend::OptimizeSubgraphView(), GpuFsaBackend::OptimizeSubgraphView(), armnn::RemoveReshapeLayer(), PermuteAsReshapeImpl::Run(), TransposeAsReshapeImpl::Run(), OptimizeConsecutiveReshapesImpl::Run(), PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteType >::Run(), OptimizeInverseConversionsImpl::Run(), MovePermuteUpImpl::Run(), MoveTransposeUpImpl::Run(), OptimizeInversePermutesImpl< PermuteType >::Run(), AddBroadcastReshapeLayerImpl::Run(), FuseBatchNorm< ConvLayer, ArmnnType, T >::Run(), Convolution2dLayer::SerializeLayerParameters(), Convolution3dLayer::SerializeLayerParameters(), DepthwiseConvolution2dLayer::SerializeLayerParameters(), ElementwiseBaseLayer::ValidateTensorShapesFromInputs(), QuantizeLayer::ValidateTensorShapesFromInputs(), ChannelShuffleLayer::ValidateTensorShapesFromInputs(), ActivationLayer::ValidateTensorShapesFromInputs(), ConvertFp32ToFp16Layer::ValidateTensorShapesFromInputs(), FillLayer::ValidateTensorShapesFromInputs(), StackLayer::ValidateTensorShapesFromInputs(), SliceLayer::ValidateTensorShapesFromInputs(), SoftmaxLayer::ValidateTensorShapesFromInputs(), FakeQuantizationLayer::ValidateTensorShapesFromInputs(), ConvertFp16ToFp32Layer::ValidateTensorShapesFromInputs(), FloorLayer::ValidateTensorShapesFromInputs(), SwitchLayer::ValidateTensorShapesFromInputs(), InstanceNormalizationLayer::ValidateTensorShapesFromInputs(), TransposeLayer::ValidateTensorShapesFromInputs(), DebugLayer::ValidateTensorShapesFromInputs(), DequantizeLayer::ValidateTensorShapesFromInputs(), MemCopyLayer::ValidateTensorShapesFromInputs(), L2NormalizationLayer::ValidateTensorShapesFromInputs(), MemImportLayer::ValidateTensorShapesFromInputs(), MergeLayer::ValidateTensorShapesFromInputs(), BatchToSpaceNdLayer::ValidateTensorShapesFromInputs(), NormalizationLayer::ValidateTensorShapesFromInputs(), CastLayer::ValidateTensorShapesFromInputs(), Pooling2dLayer::ValidateTensorShapesFromInputs(), Pooling3dLayer::ValidateTensorShapesFromInputs(), AbsLayer::ValidateTensorShapesFromInputs(), PermuteLayer::ValidateTensorShapesFromInputs(), ResizeLayer::ValidateTensorShapesFromInputs(), RsqrtLayer::ValidateTensorShapesFromInputs(), ShapeLayer::ValidateTensorShapesFromInputs(), PadLayer::ValidateTensorShapesFromInputs(), MeanLayer::ValidateTensorShapesFromInputs(), LogSoftmaxLayer::ValidateTensorShapesFromInputs(), ReshapeLayer::ValidateTensorShapesFromInputs(), FullyConnectedLayer::ValidateTensorShapesFromInputs(), DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs(), Convolution2dLayer::ValidateTensorShapesFromInputs(), Convolution3dLayer::ValidateTensorShapesFromInputs(), GatherNdLayer::ValidateTensorShapesFromInputs(), TileLayer::ValidateTensorShapesFromInputs(), BatchMatMulLayer::ValidateTensorShapesFromInputs(), ElementwiseBinaryLayer::ValidateTensorShapesFromInputs(), ReduceLayer::ValidateTensorShapesFromInputs(), ElementwiseUnaryLayer::ValidateTensorShapesFromInputs(), ReverseV2Layer::ValidateTensorShapesFromInputs(), DetectionPostProcessLayer::ValidateTensorShapesFromInputs(), GatherLayer::ValidateTensorShapesFromInputs(), StridedSliceLayer::ValidateTensorShapesFromInputs(), ArgMinMaxLayer::ValidateTensorShapesFromInputs(), SpaceToBatchNdLayer::ValidateTensorShapesFromInputs(), PreluLayer::ValidateTensorShapesFromInputs(), ComparisonLayer::ValidateTensorShapesFromInputs(), LogicalBinaryLayer::ValidateTensorShapesFromInputs(), TransposeConvolution2dLayer::ValidateTensorShapesFromInputs(), DepthToSpaceLayer::ValidateTensorShapesFromInputs(), SpaceToDepthLayer::ValidateTensorShapesFromInputs(), UnidirectionalSequenceLstmLayer::ValidateTensorShapesFromInputs(), LstmLayer::ValidateTensorShapesFromInputs(), ConcatLayer::ValidateTensorShapesFromInputs(), BatchNormalizationLayer::ValidateTensorShapesFromInputs(), OutputLayer::ValidateTensorShapesFromInputs(), QuantizedLstmLayer::ValidateTensorShapesFromInputs(), QLstmLayer::ValidateTensorShapesFromInputs(), and Layer::VerifyLayerConnections().

GetInputSlot() [2/2]

InputSlot& GetInputSlot ( unsigned int  index )

inlineoverridevirtual

Get the input slot handle by slot index.

Implements IConnectableLayer.

Definition at line 338 of file Layer.hpp.

{ return  m_InputSlots.at(index); }

GetInputSlots()

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

inline

Definition at line 258 of file Layer.hpp.

{ return m_InputSlots; }

Referenced by armnn::AttemptBackendAssignment(), armnn::CalculateSlotOption(), armnn::ForEachLayerInput(), Layer::GetPriority(), GetTosaMappingFromLayer(), LoadedNetwork::ImportOutputs(), ConvertFp32NetworkToFp16Impl::Run(), and DeleteBroadcastToImpl::Run().

GetName()

const char* GetName ( ) const

inlineoverridevirtual

Returns the name of the layer.

Implements IConnectableLayer.

Definition at line 332 of file Layer.hpp.

{ return m_LayerName.c_str(); }

Referenced by Graph::AddCompatibilityLayers(), ChannelShuffleLayer::Clone(), QuantizeLayer::Clone(), BroadcastToLayer::Clone(), ActivationLayer::Clone(), FillLayer::Clone(), ConvertFp32ToFp16Layer::Clone(), RankLayer::Clone(), AbsLayer::Clone(), AdditionLayer::Clone(), InputLayer::Clone(), SoftmaxLayer::Clone(), InstanceNormalizationLayer::Clone(), DebugLayer::Clone(), L2NormalizationLayer::Clone(), StackLayer::Clone(), StridedSliceLayer::Clone(), CastLayer::Clone(), SwitchLayer::Clone(), TileLayer::Clone(), MapLayer::Clone(), UnmapLayer::Clone(), DequantizeLayer::Clone(), MemCopyLayer::Clone(), MemImportLayer::Clone(), MergeLayer::Clone(), NormalizationLayer::Clone(), Pooling2dLayer::Clone(), Pooling3dLayer::Clone(), ConvertFp16ToFp32Layer::Clone(), FakeQuantizationLayer::Clone(), BatchMatMulLayer::Clone(), FloorLayer::Clone(), BatchToSpaceNdLayer::Clone(), ResizeLayer::Clone(), GatherNdLayer::Clone(), RsqrtLayer::Clone(), ShapeLayer::Clone(), SliceLayer::Clone(), SpaceToBatchNdLayer::Clone(), SpaceToDepthLayer::Clone(), StandInLayer::Clone(), LogicalBinaryLayer::Clone(), SubtractionLayer::Clone(), LogSoftmaxLayer::Clone(), DepthToSpaceLayer::Clone(), TransposeLayer::Clone(), MaximumLayer::Clone(), MeanLayer::Clone(), ArgMinMaxLayer::Clone(), ComparisonLayer::Clone(), MinimumLayer::Clone(), DivisionLayer::Clone(), MultiplicationLayer::Clone(), PadLayer::Clone(), ElementwiseBinaryLayer::Clone(), PermuteLayer::Clone(), ElementwiseUnaryLayer::Clone(), PreluLayer::Clone(), ReduceLayer::Clone(), ReverseV2Layer::Clone(), GatherLayer::Clone(), ConstantLayer::Clone(), ReshapeLayer::Clone(), Convolution3dLayer::Clone(), DepthwiseConvolution2dLayer::Clone(), FullyConnectedLayer::Clone(), FusedLayer::Clone(), Convolution2dLayer::Clone(), DetectionPostProcessLayer::Clone(), PreCompiledLayer::Clone(), TransposeConvolution2dLayer::Clone(), SplitterLayer::Clone(), LstmLayer::Clone(), UnidirectionalSequenceLstmLayer::Clone(), ConcatLayer::Clone(), BatchNormalizationLayer::Clone(), OutputLayer::Clone(), QuantizedLstmLayer::Clone(), QLstmLayer::Clone(), QuantizeLayer::ExecuteStrategy(), AdditionLayer::ExecuteStrategy(), SubtractionLayer::ExecuteStrategy(), MaximumLayer::ExecuteStrategy(), MinimumLayer::ExecuteStrategy(), MultiplicationLayer::ExecuteStrategy(), DivisionLayer::ExecuteStrategy(), ActivationLayer::ExecuteStrategy(), ElementwiseBaseLayer::ExecuteStrategy(), FillLayer::ExecuteStrategy(), ConvertFp32ToFp16Layer::ExecuteStrategy(), SoftmaxLayer::ExecuteStrategy(), InputLayer::ExecuteStrategy(), InstanceNormalizationLayer::ExecuteStrategy(), L2NormalizationLayer::ExecuteStrategy(), SwitchLayer::ExecuteStrategy(), DebugLayer::ExecuteStrategy(), MemCopyLayer::ExecuteStrategy(), DequantizeLayer::ExecuteStrategy(), NormalizationLayer::ExecuteStrategy(), FloorLayer::ExecuteStrategy(), ConvertFp16ToFp32Layer::ExecuteStrategy(), FusedLayer::ExecuteStrategy(), RsqrtLayer::ExecuteStrategy(), LogSoftmaxLayer::ExecuteStrategy(), BroadcastToLayer::ExecuteStrategy(), MergeLayer::ExecuteStrategy(), RankLayer::ExecuteStrategy(), ElementwiseBinaryLayer::ExecuteStrategy(), PreCompiledLayer::ExecuteStrategy(), SliceLayer::ExecuteStrategy(), ResizeLayer::ExecuteStrategy(), ShapeLayer::ExecuteStrategy(), StackLayer::ExecuteStrategy(), GatherLayer::ExecuteStrategy(), ReverseV2Layer::ExecuteStrategy(), BatchToSpaceNdLayer::ExecuteStrategy(), StridedSliceLayer::ExecuteStrategy(), ArgMinMaxLayer::ExecuteStrategy(), Pooling2dLayer::ExecuteStrategy(), Pooling3dLayer::ExecuteStrategy(), ElementwiseUnaryLayer::ExecuteStrategy(), ReduceLayer::ExecuteStrategy(), SpaceToBatchNdLayer::ExecuteStrategy(), DepthToSpaceLayer::ExecuteStrategy(), MeanLayer::ExecuteStrategy(), SpaceToDepthLayer::ExecuteStrategy(), LogicalBinaryLayer::ExecuteStrategy(), StandInLayer::ExecuteStrategy(), PadLayer::ExecuteStrategy(), PreluLayer::ExecuteStrategy(), ComparisonLayer::ExecuteStrategy(), FullyConnectedLayer::ExecuteStrategy(), Convolution3dLayer::ExecuteStrategy(), Convolution2dLayer::ExecuteStrategy(), DepthwiseConvolution2dLayer::ExecuteStrategy(), BatchNormalizationLayer::ExecuteStrategy(), ConstantLayer::ExecuteStrategy(), DetectionPostProcessLayer::ExecuteStrategy(), OutputLayer::ExecuteStrategy(), TransposeConvolution2dLayer::ExecuteStrategy(), SplitterLayer::ExecuteStrategy(), ConcatLayer::ExecuteStrategy(), LstmLayer::ExecuteStrategy(), UnidirectionalSequenceLstmLayer::ExecuteStrategy(), ReshapeLayer::ExecuteStrategy(), LayerWithParameters< StridedSliceDescriptor >::ExecuteStrategy(), TransposeLayer::ExecuteStrategy(), PermuteLayer::ExecuteStrategy(), QuantizedLstmLayer::ExecuteStrategy(), QLstmLayer::ExecuteStrategy(), Layer::ExecuteStrategy(), BindableLayer::ExecuteStrategy(), armnn::optimizations::pad_fold::FoldPadIntoLayer2dImpl(), armnn::InsertConvertFp16ToFp32LayersBefore(), armnn::InsertConvertFp32ToFp16LayersAfter(), armnn::IsLayerOptimizable(), NeonBackend::OptimizeSubgraphView(), ClBackend::OptimizeSubgraphView(), Layer::PrepInfoAndDesc(), TransposeAsReshapeImpl::Run(), PermuteAsReshapeImpl::Run(), OptimizeConsecutiveReshapesImpl::Run(), FuseBatchNorm< ConvLayer, ArmnnType, T >::Run(), and ErasedLayerNamesObservable::Update().

GetNameStr()

const std::string& GetNameStr ( ) const

inline

Definition at line 240 of file Layer.hpp.

    {
        return m_LayerName;
    }

Referenced by armnn::CheckScaleSetOnQuantizedType(), DebugLayer::CreateWorkload(), armnn::GetFusedName(), Layer::InferOutputShapes(), armnn::InsertDebugLayerAfter(), IsConnected(), LayerNameAndTypeCheck::operator()(), AddBroadcastReshapeLayerImpl::Run(), and Layer::VerifyLayerConnections().

GetNumInputSlots()

unsigned int GetNumInputSlots ( ) const

inlineoverridevirtual

Returns the number of connectable input slots.

Implements IConnectableLayer.

Definition at line 334 of file Layer.hpp.

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

Referenced by armnn::ApplyBackendOptimizations(), armnn::AssertNumberOfInputSlots(), CheckNumberOfInputSlot(), LayerWithParameters< StridedSliceDescriptor >::GetConnectedConstantAsInputTensors(), Layer::GetDataType(), armnn::GetLayerInOutDatatype(), Layer::InferOutputShapes(), armnn::InsertConvertFp16ToFp32LayersBefore(), GpuFsaBackend::OptimizeSubgraphView(), StackLayer::ValidateTensorShapesFromInputs(), ConcatLayer::ValidateTensorShapesFromInputs(), and Layer::VerifyLayerConnections().

GetNumOutputSlots()

unsigned int GetNumOutputSlots ( ) const

inlineoverridevirtual

Returns the number of connectable output slots.

Implements IConnectableLayer.

Definition at line 335 of file Layer.hpp.

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

Referenced by OutputSlot::CalculateIndexOnOwner(), CheckNumberOfOutputSlot(), armnn::CheckScaleSetOnQuantizedType(), Layer::CreateTensorHandles(), armnn::GetLayerInOutDatatype(), Layer::InferOutputShapes(), InputSlot::Insert(), armnn::InsertConvertFp32ToFp16LayersAfter(), armnn::InsertDebugLayerAfter(), Layer::IsOutputUnconnected(), GpuFsaBackend::OptimizeSubgraphView(), armnn::SelectTensorHandleStrategy(), SwitchLayer::ValidateTensorShapesFromInputs(), MapLayer::ValidateTensorShapesFromInputs(), UnmapLayer::ValidateTensorShapesFromInputs(), and DetectionPostProcessLayer::ValidateTensorShapesFromInputs().

GetOutputHandler() [1/2]

OutputHandler& GetOutputHandler ( unsigned int  i = 0 )

inline

Definition at line 250 of file Layer.hpp.

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

References Layer::GetOutputHandler().

GetOutputHandler() [2/2]

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

inline

Definition at line 245 of file Layer.hpp.

    {
        return m_OutputHandlers[i];
    }

References Layer::m_OutputHandlers.

Referenced by Layer::CreateTensorHandles(), Layer::GetOutputHandler(), InputSlot::Insert(), PermuteAsReshapeImpl::Run(), TransposeAsReshapeImpl::Run(), OptimizeConsecutiveReshapesImpl::Run(), MovePermuteUpImpl::Run(), MoveTransposeUpImpl::Run(), and InputLayer::ValidateTensorShapesFromInputs().

GetOutputSlot() [1/2]

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

inlineoverridevirtual

Get the const output slot handle by slot index.

Implements IConnectableLayer.

Examples

AsyncExecutionSample.cpp, and SimpleSample.cpp.

Definition at line 339 of file Layer.hpp.

{ return m_OutputSlots.at(index); }

Referenced by Graph::AddCompatibilityLayers(), armnn::ApplyBackendOptimizations(), armnn::AttemptBackendAssignment(), OutputSlot::CalculateIndexOnOwner(), armnn::ChainReduceLayers(), armnn::CheckScaleSetOnQuantizedType(), armnn::ConnectedToLayerType(), armnn::ConnectedToLayerWithNCHW(), SplitterLayer::CreateTensorHandles(), ConcatLayer::CreateTensorHandles(), Layer::CreateTensorHandles(), armnn::optimizations::pad_fold::FoldPadIntoLayer2dImpl(), GenerateUniqueOutputName(), Layer::GetDataType(), armnn::GetLayerInOutDatatype(), InputSlot::Insert(), armnn::InsertConvertFp16ToFp32LayersBefore(), armnn::InsertConvertFp32ToFp16LayersAfter(), armnn::InsertDebugLayerAfter(), IsConnected(), RefBackend::OptimizeSubgraphView(), ClBackend::OptimizeSubgraphView(), GpuFsaBackend::OptimizeSubgraphView(), armnn::RemoveReshapeLayer(), PermuteAsReshapeImpl::Run(), TransposeAsReshapeImpl::Run(), OptimizeConsecutiveReshapesImpl::Run(), DeleteBroadcastToImpl::Run(), OptimizeInverseConversionsImpl::Run(), PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteType >::Run(), MoveTransposeUpImpl::Run(), MovePermuteUpImpl::Run(), AddBroadcastReshapeLayerImpl::Run(), FuseBatchNorm< ConvLayer, ArmnnType, T >::Run(), armnn::SelectTensorHandleStrategy(), Layer::ValidateAndCopyShape(), ElementwiseBaseLayer::ValidateTensorShapesFromInputs(), QuantizeLayer::ValidateTensorShapesFromInputs(), ActivationLayer::ValidateTensorShapesFromInputs(), ChannelShuffleLayer::ValidateTensorShapesFromInputs(), FillLayer::ValidateTensorShapesFromInputs(), ConvertFp32ToFp16Layer::ValidateTensorShapesFromInputs(), RankLayer::ValidateTensorShapesFromInputs(), SliceLayer::ValidateTensorShapesFromInputs(), SoftmaxLayer::ValidateTensorShapesFromInputs(), FakeQuantizationLayer::ValidateTensorShapesFromInputs(), Pooling3dLayer::ValidateTensorShapesFromInputs(), FloorLayer::ValidateTensorShapesFromInputs(), SwitchLayer::ValidateTensorShapesFromInputs(), TransposeLayer::ValidateTensorShapesFromInputs(), InstanceNormalizationLayer::ValidateTensorShapesFromInputs(), L2NormalizationLayer::ValidateTensorShapesFromInputs(), Pooling2dLayer::ValidateTensorShapesFromInputs(), MemImportLayer::ValidateTensorShapesFromInputs(), ConvertFp16ToFp32Layer::ValidateTensorShapesFromInputs(), MemCopyLayer::ValidateTensorShapesFromInputs(), MergeLayer::ValidateTensorShapesFromInputs(), NormalizationLayer::ValidateTensorShapesFromInputs(), BatchToSpaceNdLayer::ValidateTensorShapesFromInputs(), DebugLayer::ValidateTensorShapesFromInputs(), PermuteLayer::ValidateTensorShapesFromInputs(), DequantizeLayer::ValidateTensorShapesFromInputs(), StackLayer::ValidateTensorShapesFromInputs(), CastLayer::ValidateTensorShapesFromInputs(), ResizeLayer::ValidateTensorShapesFromInputs(), AbsLayer::ValidateTensorShapesFromInputs(), RsqrtLayer::ValidateTensorShapesFromInputs(), ShapeLayer::ValidateTensorShapesFromInputs(), PadLayer::ValidateTensorShapesFromInputs(), MeanLayer::ValidateTensorShapesFromInputs(), LogSoftmaxLayer::ValidateTensorShapesFromInputs(), ReshapeLayer::ValidateTensorShapesFromInputs(), ConstantLayer::ValidateTensorShapesFromInputs(), BroadcastToLayer::ValidateTensorShapesFromInputs(), FullyConnectedLayer::ValidateTensorShapesFromInputs(), Convolution2dLayer::ValidateTensorShapesFromInputs(), Convolution3dLayer::ValidateTensorShapesFromInputs(), DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs(), GatherNdLayer::ValidateTensorShapesFromInputs(), ElementwiseBinaryLayer::ValidateTensorShapesFromInputs(), TileLayer::ValidateTensorShapesFromInputs(), BatchMatMulLayer::ValidateTensorShapesFromInputs(), ReverseV2Layer::ValidateTensorShapesFromInputs(), ReduceLayer::ValidateTensorShapesFromInputs(), GatherLayer::ValidateTensorShapesFromInputs(), ElementwiseUnaryLayer::ValidateTensorShapesFromInputs(), ArgMinMaxLayer::ValidateTensorShapesFromInputs(), StridedSliceLayer::ValidateTensorShapesFromInputs(), DetectionPostProcessLayer::ValidateTensorShapesFromInputs(), LogicalBinaryLayer::ValidateTensorShapesFromInputs(), DepthToSpaceLayer::ValidateTensorShapesFromInputs(), ComparisonLayer::ValidateTensorShapesFromInputs(), SpaceToDepthLayer::ValidateTensorShapesFromInputs(), PreluLayer::ValidateTensorShapesFromInputs(), TransposeConvolution2dLayer::ValidateTensorShapesFromInputs(), SpaceToBatchNdLayer::ValidateTensorShapesFromInputs(), SplitterLayer::ValidateTensorShapesFromInputs(), LstmLayer::ValidateTensorShapesFromInputs(), ConcatLayer::ValidateTensorShapesFromInputs(), UnidirectionalSequenceLstmLayer::ValidateTensorShapesFromInputs(), BatchNormalizationLayer::ValidateTensorShapesFromInputs(), QuantizedLstmLayer::ValidateTensorShapesFromInputs(), and QLstmLayer::ValidateTensorShapesFromInputs().

GetOutputSlot() [2/2]

OutputSlot& GetOutputSlot ( unsigned int  index = 0 )

inlineoverridevirtual

Get the output slot handle by slot index.

Implements IConnectableLayer.

Definition at line 340 of file Layer.hpp.

{ return m_OutputSlots.at(index); }

GetOutputSlots()

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

inline

Definition at line 259 of file Layer.hpp.

{ return m_OutputSlots; }

Referenced by Graph::AddCompatibilityLayers(), armnn::ForEachLayerOutput(), GetTosaMappingFromLayer(), LoadedNetwork::ImportInputs(), Layer::IsOutputUnconnected(), and Graph::Print().

GetParameters()

virtual const BaseDescriptor& GetParameters ( ) const

inlineoverridevirtual

If the layer has a descriptor return it.

The base descriptor can then be cast to the correct descriptor class. If the layer has no associated descriptor a struct of type NullDescriptor will be returned. Note: NullDescriptors can be detected because they return true when the BaseDescriptor IsNull function is invoked.

Implements IConnectableLayer.

Reimplemented in LayerWithParameters< Parameters >.

Definition at line 378 of file Layer.hpp.

{ return m_NullDescriptor; }

Referenced by QuantizeLayer::ExecuteStrategy(), AdditionLayer::ExecuteStrategy(), MaximumLayer::ExecuteStrategy(), SubtractionLayer::ExecuteStrategy(), DivisionLayer::ExecuteStrategy(), MinimumLayer::ExecuteStrategy(), MultiplicationLayer::ExecuteStrategy(), ConvertFp32ToFp16Layer::ExecuteStrategy(), AbsLayer::ExecuteStrategy(), FloorLayer::ExecuteStrategy(), RsqrtLayer::ExecuteStrategy(), SwitchLayer::ExecuteStrategy(), DebugLayer::ExecuteStrategy(), MemCopyLayer::ExecuteStrategy(), InputLayer::ExecuteStrategy(), DequantizeLayer::ExecuteStrategy(), ConvertFp16ToFp32Layer::ExecuteStrategy(), MergeLayer::ExecuteStrategy(), PreluLayer::ExecuteStrategy(), OutputLayer::ExecuteStrategy(), GetTosaMappingFromLayer(), and GpuFsaBackend::OptimizeSubgraphView().

GetPriority()

LayerPriority GetPriority

(

)

const

Definition at line 341 of file Layer.cpp.

{
    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;
}

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

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

GetRelatedLayerNames()

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

inline

Definition at line 347 of file Layer.hpp.

{ return m_RelatedLayerNames; }

Referenced by ErasedLayerNamesObservable::Update().

GetShapeInferenceMethod()

ShapeInferenceMethod GetShapeInferenceMethod ( ) const

inline

Definition at line 255 of file Layer.hpp.

{ return m_ShapeInferenceMethod; };

References Layer::m_ShapeInferenceMethod.

GetType()

LayerType GetType ( ) const

inlineoverridevirtual

Returns the armnn::LayerType of this layer.

Implements IConnectableLayer.

Definition at line 286 of file Layer.hpp.

{ return m_Type; }

Referenced by armnn::ApplyBackendOptimizations(), armnn::AssertNumberOfInputSlots(), armnn::AttemptBackendAssignment(), armnn::BuildAddMulAddTensorInfoLists(), armnn::CalculateEdgeStrategy(), armnn::CalculateSlotOption(), armnn::CalculateSlotOptionForInput(), armnn::CheckScaleSetOnQuantizedType(), armnn::ConnectedToLayerType(), GenerateUniqueName(), GenerateUniqueOutputName(), Layer::GetPriority(), GetTosaMappingFromLayer(), LoadedNetwork::ImportInputs(), LoadedNetwork::ImportOutputs(), Layer::InferOutputShapes(), ReshapeLayer::IsEqual(), TransposeLayer::IsEqual(), PermuteLayer::IsEqual(), TransposeLayer::IsInverse(), PermuteLayer::IsInverse(), IsLayerOfType(), armnn::IsLayerSupported(), armnn::IsSequenceLayerType(), LayerNameAndTypeCheck::operator()(), TosaRefBackend::OptimizeSubgraphView(), RefBackend::OptimizeSubgraphView(), NeonBackend::OptimizeSubgraphView(), ClBackend::OptimizeSubgraphView(), GpuFsaBackend::OptimizeSubgraphView(), armnn::RemoveReshapeLayer(), armnn::ReturnWithError(), ConvertFp32NetworkToFp16Impl::Run(), OptimizeConsecutiveReshapesImpl::Run(), AddDebugImpl::Run(), DeleteBroadcastToImpl::Run(), ConvertConstPermuteLayersToConstLayers::Run(), OptimizeInverseConversionsImpl::Run(), PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteType >::Run(), ConvertConstDequantisationLayersToConstLayersImpl::Run(), PermuteDepthwiseConv2dWeightsImpl::Run(), AddBroadcastReshapeLayerImpl::Run(), FuseBatchNorm< ConvLayer, ArmnnType, T >::Run(), AddDebugToFileImpl::Run(), OptimizeForTypeImpl< BaseType, OptimizeForConnectionImpl< BaseType, ChildType, Wrapped > >::Run(), armnn::SelectTensorHandleStrategy(), ElementwiseBaseLayer::ValidateTensorShapesFromInputs(), ElementwiseBinaryLayer::ValidateTensorShapesFromInputs(), ElementwiseUnaryLayer::ValidateTensorShapesFromInputs(), and Layer::VerifyLayerConnections().

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 QLstmLayer, QuantizedLstmLayer, ConcatLayer, LstmLayer, UnidirectionalSequenceLstmLayer, SplitterLayer, DetectionPostProcessLayer, TransposeConvolution2dLayer, Convolution2dLayer, Convolution3dLayer, DepthwiseConvolution2dLayer, FullyConnectedLayer, ConstantLayer, ReshapeLayer, MeanLayer, PadLayer, StandInLayer, BatchToSpaceNdLayer, PermuteLayer, Pooling2dLayer, Pooling3dLayer, ResizeLayer, ShapeLayer, SliceLayer, StackLayer, MergeLayer, RankLayer, TransposeLayer, ComparisonLayer, DepthToSpaceLayer, LogicalBinaryLayer, PreluLayer, ReduceLayer, ReverseV2Layer, SpaceToBatchNdLayer, SpaceToDepthLayer, ArgMinMaxLayer, ElementwiseBinaryLayer, ElementwiseUnaryLayer, GatherLayer, StridedSliceLayer, BatchMatMulLayer, GatherNdLayer, TileLayer, BroadcastToLayer, and ElementwiseBaseLayer.

Definition at line 410 of file Layer.cpp.

{
    ARMNN_ASSERT(GetNumInputSlots() != 0);
    ARMNN_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(
                fmt::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 {0} layer {1} (#inputs={2} #outputs={3}) {4}",
                            GetLayerTypeAsCString(this->GetType()),
                            GetNameStr(),
                            GetNumInputSlots(),
                            GetNumOutputSlots(),
                            CHECK_LOCATION().AsString()));
    }
    return inputShapes;
}

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

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

IsOutputUnconnected()

bool IsOutputUnconnected ( )

inline

Definition at line 270 of file Layer.hpp.

    {
        unsigned int numConnections = 0;
 
        for (auto&& output : GetOutputSlots())
        {
            numConnections += output.GetNumConnections();
        }
 
        return (GetNumOutputSlots() > 0) && (numConnections == 0);
    }

References Layer::GetNumOutputSlots(), and Layer::GetOutputSlots().

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

OperateOnConstantTensors()

void OperateOnConstantTensors ( Op  op )

inline

Definition at line 319 of file Layer.hpp.

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

References Layer::GetConstantTensorsByRef().

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

PrepInfoAndDesc()

WorkloadInfo PrepInfoAndDesc ( QueueDescriptor &  descriptor ) const

inlineprotected

Helper function to reduce duplication in *Layer::CreateWorkload.

Definition at line 409 of file Layer.hpp.

    {
        WorkloadInfo info;
        CollectQueueDescriptorInputs(descriptor, info);
        CollectQueueDescriptorOutputs(descriptor, info);
        info.m_Name = GetName();
        return info;
    }

References Layer::CollectQueueDescriptorInputs(), Layer::CollectQueueDescriptorOutputs(), Layer::GetName(), and armnn::info.

Referenced by ConvertFp32ToFp16Layer::CreateWorkload(), QuantizeLayer::CreateWorkload(), RankLayer::CreateWorkload(), SwitchLayer::CreateWorkload(), ShapeLayer::CreateWorkload(), DequantizeLayer::CreateWorkload(), MemImportLayer::CreateWorkload(), GatherNdLayer::CreateWorkload(), ConvertFp16ToFp32Layer::CreateWorkload(), FloorLayer::CreateWorkload(), AdditionLayer::CreateWorkload(), AbsLayer::CreateWorkload(), CastLayer::CreateWorkload(), RsqrtLayer::CreateWorkload(), MemCopyLayer::CreateWorkload(), UnmapLayer::CreateWorkload(), MapLayer::CreateWorkload(), DebugLayer::CreateWorkload(), MaximumLayer::CreateWorkload(), PreluLayer::CreateWorkload(), DivisionLayer::CreateWorkload(), SubtractionLayer::CreateWorkload(), MinimumLayer::CreateWorkload(), ReverseV2Layer::CreateWorkload(), MultiplicationLayer::CreateWorkload(), ConstantLayer::CreateWorkload(), QuantizedLstmLayer::CreateWorkload(), and LayerWithParameters< StridedSliceDescriptor >::PrepInfoAndDesc().

ReleaseConstantData()

void ReleaseConstantData ( )

virtual

Reimplemented in Convolution2dLayer, DepthwiseConvolution2dLayer, FullyConnectedLayer, and ConstantLayer.

Definition at line 317 of file Layer.cpp.

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

References Layer::OperateOnConstantTensors().

Reparent()

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

pure virtual

Referenced by Graph::operator=().

ResetPriority()

void ResetPriority

(

)

const

Definition at line 335 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 ConstantLayer, Convolution2dLayer, Convolution3dLayer, DepthwiseConvolution2dLayer, LayerWithParameters< Parameters >, LayerWithParameters< SoftmaxDescriptor >, LayerWithParameters< FakeQuantizationDescriptor >, LayerWithParameters< ReduceDescriptor >, LayerWithParameters< LstmDescriptor >, LayerWithParameters< ChannelShuffleDescriptor >, LayerWithParameters< LogSoftmaxDescriptor >, LayerWithParameters< PreCompiledDescriptor >, LayerWithParameters< SpaceToBatchNdDescriptor >, LayerWithParameters< BatchToSpaceNdDescriptor >, LayerWithParameters< PermuteDescriptor >, LayerWithParameters< GatherDescriptor >, LayerWithParameters< ElementwiseUnaryDescriptor >, LayerWithParameters< DepthToSpaceDescriptor >, LayerWithParameters< OriginsDescriptor >, LayerWithParameters< SpaceToDepthDescriptor >, LayerWithParameters< ReshapeDescriptor >, LayerWithParameters< ViewsDescriptor >, LayerWithParameters< Pooling2dDescriptor >, LayerWithParameters< Convolution2dDescriptor >, LayerWithParameters< ActivationDescriptor >, LayerWithParameters< StandInDescriptor >, LayerWithParameters< MeanDescriptor >, LayerWithParameters< StackDescriptor >, LayerWithParameters< TransposeDescriptor >, LayerWithParameters< InstanceNormalizationDescriptor >, LayerWithParameters< ComparisonDescriptor >, LayerWithParameters< TransposeConvolution2dDescriptor >, LayerWithParameters< BroadcastToDescriptor >, LayerWithParameters< BatchNormalizationDescriptor >, LayerWithParameters< FusedDescriptor >, LayerWithParameters< BatchMatMulDescriptor >, LayerWithParameters< TileDescriptor >, LayerWithParameters< ArgMinMaxDescriptor >, LayerWithParameters< LogicalBinaryDescriptor >, LayerWithParameters< DetectionPostProcessDescriptor >, LayerWithParameters< PadDescriptor >, LayerWithParameters< L2NormalizationDescriptor >, LayerWithParameters< Convolution3dDescriptor >, LayerWithParameters< SliceDescriptor >, LayerWithParameters< QLstmDescriptor >, LayerWithParameters< FillDescriptor >, LayerWithParameters< DepthwiseConvolution2dDescriptor >, LayerWithParameters< NormalizationDescriptor >, LayerWithParameters< FullyConnectedDescriptor >, LayerWithParameters< ResizeDescriptor >, LayerWithParameters< Pooling3dDescriptor >, LayerWithParameters< ElementwiseBinaryDescriptor >, and LayerWithParameters< StridedSliceDescriptor >.

Definition at line 518 of file Layer.cpp.

{
    std::string guid = std::to_string(m_Guid);
    std::string layerType = GetLayerTypeAsCString(m_Type);
    std::string backendId = std::string(m_BackendId);
    if (!(guid.compare("") == 0) && !guid.empty())
    {
        fn("Guid", guid);
    }
    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);
    }
    std::shared_ptr<ActivationDescriptor>
            activationDescPtr = GetAdditionalInformation<ActivationDescriptor>();
 
    if (activationDescPtr)
    {
        StringifyLayerParameters<ActivationDescriptor>::Serialize(fn, *activationDescPtr.get());
    }
}

References armnn::GetLayerTypeAsCString(), and StringifyLayerParameters< LayerParameter >::Serialize().

Referenced by LayerWithParameters< StridedSliceDescriptor >::SerializeLayerParameters(), and ConstantLayer::SerializeLayerParameters().

SetAdditionalInfo()

void SetAdditionalInfo ( QueueDescriptor &  descriptor ) const

protected

Definition at line 287 of file Layer.cpp.

{
    descriptor.m_AdditionalInfoObject = m_AdditionalInfoObject.get();
}

References QueueDescriptor::m_AdditionalInfoObject, and Layer::m_AdditionalInfoObject.

Referenced by ActivationLayer::CreateWorkload(), BroadcastToLayer::CreateWorkload(), ConvertFp32ToFp16Layer::CreateWorkload(), FillLayer::CreateWorkload(), QuantizeLayer::CreateWorkload(), RankLayer::CreateWorkload(), UnmapLayer::CreateWorkload(), AbsLayer::CreateWorkload(), InstanceNormalizationLayer::CreateWorkload(), L2NormalizationLayer::CreateWorkload(), SplitterLayer::CreateWorkload(), StackLayer::CreateWorkload(), StridedSliceLayer::CreateWorkload(), SoftmaxLayer::CreateWorkload(), SwitchLayer::CreateWorkload(), ShapeLayer::CreateWorkload(), TileLayer::CreateWorkload(), CastLayer::CreateWorkload(), DebugLayer::CreateWorkload(), MapLayer::CreateWorkload(), MemCopyLayer::CreateWorkload(), BatchMatMulLayer::CreateWorkload(), DequantizeLayer::CreateWorkload(), MemImportLayer::CreateWorkload(), NormalizationLayer::CreateWorkload(), Pooling2dLayer::CreateWorkload(), Pooling3dLayer::CreateWorkload(), FakeQuantizationLayer::CreateWorkload(), ConcatLayer::CreateWorkload(), FloorLayer::CreateWorkload(), AdditionLayer::CreateWorkload(), ConvertFp16ToFp32Layer::CreateWorkload(), ResizeLayer::CreateWorkload(), RsqrtLayer::CreateWorkload(), BatchToSpaceNdLayer::CreateWorkload(), SliceLayer::CreateWorkload(), GatherNdLayer::CreateWorkload(), SpaceToBatchNdLayer::CreateWorkload(), SubtractionLayer::CreateWorkload(), ArgMinMaxLayer::CreateWorkload(), SpaceToDepthLayer::CreateWorkload(), TransposeLayer::CreateWorkload(), GatherLayer::CreateWorkload(), MaximumLayer::CreateWorkload(), ReverseV2Layer::CreateWorkload(), ReduceLayer::CreateWorkload(), MinimumLayer::CreateWorkload(), LogSoftmaxLayer::CreateWorkload(), MultiplicationLayer::CreateWorkload(), PadLayer::CreateWorkload(), PermuteLayer::CreateWorkload(), DivisionLayer::CreateWorkload(), MeanLayer::CreateWorkload(), PreluLayer::CreateWorkload(), ElementwiseBinaryLayer::CreateWorkload(), ComparisonLayer::CreateWorkload(), DepthToSpaceLayer::CreateWorkload(), ReshapeLayer::CreateWorkload(), ConstantLayer::CreateWorkload(), ChannelShuffleLayer::CreateWorkload(), FullyConnectedLayer::CreateWorkload(), Convolution2dLayer::CreateWorkload(), Convolution3dLayer::CreateWorkload(), DepthwiseConvolution2dLayer::CreateWorkload(), FusedLayer::CreateWorkload(), DetectionPostProcessLayer::CreateWorkload(), TransposeConvolution2dLayer::CreateWorkload(), PreCompiledLayer::CreateWorkload(), LstmLayer::CreateWorkload(), UnidirectionalSequenceLstmLayer::CreateWorkload(), BatchNormalizationLayer::CreateWorkload(), QuantizedLstmLayer::CreateWorkload(), and QLstmLayer::CreateWorkload().

SetAdditionalInfoForObject()

void SetAdditionalInfoForObject ( const AdditionalInfoObjectPtr &  additionalInfo )

inline

Definition at line 373 of file Layer.hpp.

    {
        m_AdditionalInfoObject = additionalInfo;
    }

References Layer::m_AdditionalInfoObject.

Referenced by NeonBackend::OptimizeSubgraphView().

SetAllowExpandedDims()

void SetAllowExpandedDims ( bool  allowExpandedDims )

inline

Definition at line 362 of file Layer.hpp.

    {
        m_AllowExpandedDims = allowExpandedDims;
    }

SetBackendId()

void SetBackendId ( const BackendId &  id )

inlineoverridevirtual

Set the backend of the IConnectableLayer.

By using SetBackendId() we guarantee that the input backend supports that layer (IsLayerSupported returns true for a specific backend). If there is no guarantee the input backend supports that layer use BackendSelectionHint().

Implements IConnectableLayer.

Definition at line 291 of file Layer.hpp.

{ m_BackendId = id; }

Referenced by Graph::AddCompatibilityLayers(), NetworkImpl::AddPrecompiledLayer(), armnn::AttemptBackendAssignment(), and armnn::InsertDebugLayerAfter().

SetGuid()

void SetGuid ( LayerGuid  guid )

inline

Definition at line 342 of file Layer.hpp.

{ m_Guid = guid; }

SetShapeInferenceMethod()

void SetShapeInferenceMethod ( ShapeInferenceMethod  shapeInferenceMethod )

inline

Definition at line 357 of file Layer.hpp.

    {
        m_ShapeInferenceMethod = shapeInferenceMethod;
    }

References Layer::m_ShapeInferenceMethod.

ValidateAndCopyShape()

void ValidateAndCopyShape ( const TensorShape &  outputShape, const TensorShape &  inferredShape, const ShapeInferenceMethod  shapeInferenceMethod, const std::string &  layerName, const unsigned int  outputSlotIndex = 0  )

protected

Definition at line 435 of file Layer.cpp.

{
    if (shapeInferenceMethod == ShapeInferenceMethod::ValidateOnly)
    {
        if (m_AllowExpandedDims)
        {
            std::vector<unsigned int> outputDims = armnnUtils::SqueezeDims(outputShape);
            std::vector<unsigned int> inferredDims = armnnUtils::SqueezeDims(inferredShape);
 
            if (outputDims.size() != inferredDims.size())
            {
                std::stringstream ss;
                ss << layerName << ": TensorShape set on OutputSlot[" << outputSlotIndex <<
                   "] does not match the inferred shape. ";
                ss << outputShape << " != " << inferredShape;
                throw LayerValidationException(ss.str());
            }
            for (unsigned int i = 0; i < outputDims.size(); ++i)
            {
                if (outputDims[i] != inferredDims[i])
                {
                    std::stringstream ss;
                    ss << layerName << ": TensorShape set on OutputSlot[" << outputSlotIndex <<
                       "] does not match the inferred shape at dimension index [";
                    ss << i << "] " << outputShape << " != " << inferredShape;
                    throw LayerValidationException(ss.str());
                }
            }
            return;
        }
        else
        {
            ConditionalThrowIfNotEqual<LayerValidationException>(
                    layerName + ": TensorShape set on OutputSlot[0] does not match the inferred shape.",
                    outputShape,
                    inferredShape);
            return;
        }
    }
 
    if (outputShape.GetDimensionality() == Dimensionality::Specified)
    {
        for (unsigned int i = 0; i < outputShape.GetNumDimensions(); ++i)
        {
            if (outputShape.GetDimensionSpecificity(i) && outputShape[i] != inferredShape[i])
            {
                std::stringstream ss;
                ss << layerName << ": TensorShape set on OutputSlot[" << outputSlotIndex <<
                "] does not match the inferred shape at dimension index [";
                ss << i << "] " << outputShape << " != " << inferredShape;
                throw LayerValidationException(ss.str());
            }
        }
    }
 
    TensorInfo info = GetOutputSlot(outputSlotIndex).GetTensorInfo();
 
    armnn::TensorInfo inferredTensorInfo(inferredShape,
                                         info.GetDataType(),
                                         info.GetQuantizationScale(),
                                         info.GetQuantizationOffset());
 
    GetOutputSlot(outputSlotIndex).SetTensorInfo(inferredTensorInfo);
}

References TensorShape::GetDimensionality(), TensorShape::GetDimensionSpecificity(), TensorShape::GetNumDimensions(), Layer::GetOutputSlot(), OutputSlot::GetTensorInfo(), armnn::info, OutputSlot::SetTensorInfo(), armnn::Specified, armnnUtils::SqueezeDims(), and armnn::ValidateOnly.

Referenced by ElementwiseBaseLayer::ValidateTensorShapesFromInputs(), QuantizeLayer::ValidateTensorShapesFromInputs(), ActivationLayer::ValidateTensorShapesFromInputs(), ChannelShuffleLayer::ValidateTensorShapesFromInputs(), RankLayer::ValidateTensorShapesFromInputs(), ConvertFp32ToFp16Layer::ValidateTensorShapesFromInputs(), AbsLayer::ValidateTensorShapesFromInputs(), DebugLayer::ValidateTensorShapesFromInputs(), TransposeLayer::ValidateTensorShapesFromInputs(), MemCopyLayer::ValidateTensorShapesFromInputs(), CastLayer::ValidateTensorShapesFromInputs(), SoftmaxLayer::ValidateTensorShapesFromInputs(), MemImportLayer::ValidateTensorShapesFromInputs(), ShapeLayer::ValidateTensorShapesFromInputs(), MergeLayer::ValidateTensorShapesFromInputs(), DequantizeLayer::ValidateTensorShapesFromInputs(), NormalizationLayer::ValidateTensorShapesFromInputs(), PermuteLayer::ValidateTensorShapesFromInputs(), Pooling2dLayer::ValidateTensorShapesFromInputs(), Pooling3dLayer::ValidateTensorShapesFromInputs(), BatchToSpaceNdLayer::ValidateTensorShapesFromInputs(), FakeQuantizationLayer::ValidateTensorShapesFromInputs(), FloorLayer::ValidateTensorShapesFromInputs(), ResizeLayer::ValidateTensorShapesFromInputs(), ConvertFp16ToFp32Layer::ValidateTensorShapesFromInputs(), RsqrtLayer::ValidateTensorShapesFromInputs(), SliceLayer::ValidateTensorShapesFromInputs(), InstanceNormalizationLayer::ValidateTensorShapesFromInputs(), StackLayer::ValidateTensorShapesFromInputs(), L2NormalizationLayer::ValidateTensorShapesFromInputs(), SwitchLayer::ValidateTensorShapesFromInputs(), LogSoftmaxLayer::ValidateTensorShapesFromInputs(), MeanLayer::ValidateTensorShapesFromInputs(), PadLayer::ValidateTensorShapesFromInputs(), ReshapeLayer::ValidateTensorShapesFromInputs(), Convolution2dLayer::ValidateTensorShapesFromInputs(), DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs(), FullyConnectedLayer::ValidateTensorShapesFromInputs(), Convolution3dLayer::ValidateTensorShapesFromInputs(), BroadcastToLayer::ValidateTensorShapesFromInputs(), GatherNdLayer::ValidateTensorShapesFromInputs(), BatchMatMulLayer::ValidateTensorShapesFromInputs(), ElementwiseBinaryLayer::ValidateTensorShapesFromInputs(), TileLayer::ValidateTensorShapesFromInputs(), GatherLayer::ValidateTensorShapesFromInputs(), ArgMinMaxLayer::ValidateTensorShapesFromInputs(), ReverseV2Layer::ValidateTensorShapesFromInputs(), StridedSliceLayer::ValidateTensorShapesFromInputs(), ReduceLayer::ValidateTensorShapesFromInputs(), DetectionPostProcessLayer::ValidateTensorShapesFromInputs(), ElementwiseUnaryLayer::ValidateTensorShapesFromInputs(), DepthToSpaceLayer::ValidateTensorShapesFromInputs(), TransposeConvolution2dLayer::ValidateTensorShapesFromInputs(), LogicalBinaryLayer::ValidateTensorShapesFromInputs(), SpaceToBatchNdLayer::ValidateTensorShapesFromInputs(), SpaceToDepthLayer::ValidateTensorShapesFromInputs(), ComparisonLayer::ValidateTensorShapesFromInputs(), PreluLayer::ValidateTensorShapesFromInputs(), SplitterLayer::ValidateTensorShapesFromInputs(), LstmLayer::ValidateTensorShapesFromInputs(), ConcatLayer::ValidateTensorShapesFromInputs(), UnidirectionalSequenceLstmLayer::ValidateTensorShapesFromInputs(), BatchNormalizationLayer::ValidateTensorShapesFromInputs(), QuantizedLstmLayer::ValidateTensorShapesFromInputs(), and QLstmLayer::ValidateTensorShapesFromInputs().

ValidateTensorShapesFromInputs()

virtual void ValidateTensorShapesFromInputs ( )

pure virtual

Implemented in QLstmLayer, QuantizedLstmLayer, OutputLayer, BatchNormalizationLayer, ConcatLayer, LstmLayer, UnidirectionalSequenceLstmLayer, SplitterLayer, ComparisonLayer, DepthToSpaceLayer, LogicalBinaryLayer, PreluLayer, SpaceToBatchNdLayer, SpaceToDepthLayer, TransposeConvolution2dLayer, ArgMinMaxLayer, DetectionPostProcessLayer, ElementwiseUnaryLayer, GatherLayer, ReduceLayer, ReverseV2Layer, StridedSliceLayer, BatchMatMulLayer, ElementwiseBinaryLayer, TileLayer, GatherNdLayer, BroadcastToLayer, Convolution2dLayer, Convolution3dLayer, DepthwiseConvolution2dLayer, FullyConnectedLayer, PreCompiledLayer, ConstantLayer, ReshapeLayer, LogSoftmaxLayer, MeanLayer, PadLayer, StandInLayer, AbsLayer, BatchToSpaceNdLayer, CastLayer, ConvertFp16ToFp32Layer, DebugLayer, DequantizeLayer, FakeQuantizationLayer, FloorLayer, FusedLayer, InputLayer, InstanceNormalizationLayer, L2NormalizationLayer, MapLayer, MemCopyLayer, MemImportLayer, MergeLayer, NormalizationLayer, PermuteLayer, Pooling2dLayer, Pooling3dLayer, ResizeLayer, RsqrtLayer, ShapeLayer, SliceLayer, SoftmaxLayer, StackLayer, SwitchLayer, TransposeLayer, UnmapLayer, ConvertFp32ToFp16Layer, FillLayer, RankLayer, ActivationLayer, ChannelShuffleLayer, QuantizeLayer, and ElementwiseBaseLayer.

Referenced by OutputSlot::IsTensorInfoSet().

VerifyLayerConnections()

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

Definition at line 391 of file Layer.cpp.

{
    ARMNN_ASSERT(GetNumInputSlots() == expectedConnections);
 
    for (unsigned int i=0; i<expectedConnections; ++i)
    {
        if (GetInputSlot(i).GetConnection() == nullptr)
        {
            throw LayerValidationException(
                    fmt::format("Input connection #{0} must be connected "
                                "for {1} layer {2} {3}",
                                i,
                                GetLayerTypeAsCString(this->GetType()),
                                GetNameStr(),
                                location.AsString()));
        }
    }
}

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

Referenced by ElementwiseBaseLayer::ValidateTensorShapesFromInputs(), QuantizeLayer::ValidateTensorShapesFromInputs(), ActivationLayer::ValidateTensorShapesFromInputs(), ChannelShuffleLayer::ValidateTensorShapesFromInputs(), ConvertFp32ToFp16Layer::ValidateTensorShapesFromInputs(), FillLayer::ValidateTensorShapesFromInputs(), RankLayer::ValidateTensorShapesFromInputs(), AbsLayer::ValidateTensorShapesFromInputs(), DebugLayer::ValidateTensorShapesFromInputs(), TransposeLayer::ValidateTensorShapesFromInputs(), UnmapLayer::ValidateTensorShapesFromInputs(), MapLayer::ValidateTensorShapesFromInputs(), SliceLayer::ValidateTensorShapesFromInputs(), CastLayer::ValidateTensorShapesFromInputs(), RsqrtLayer::ValidateTensorShapesFromInputs(), MemCopyLayer::ValidateTensorShapesFromInputs(), MemImportLayer::ValidateTensorShapesFromInputs(), DequantizeLayer::ValidateTensorShapesFromInputs(), MergeLayer::ValidateTensorShapesFromInputs(), NormalizationLayer::ValidateTensorShapesFromInputs(), PermuteLayer::ValidateTensorShapesFromInputs(), Pooling2dLayer::ValidateTensorShapesFromInputs(), Pooling3dLayer::ValidateTensorShapesFromInputs(), BatchToSpaceNdLayer::ValidateTensorShapesFromInputs(), FakeQuantizationLayer::ValidateTensorShapesFromInputs(), ResizeLayer::ValidateTensorShapesFromInputs(), ConvertFp16ToFp32Layer::ValidateTensorShapesFromInputs(), FloorLayer::ValidateTensorShapesFromInputs(), ShapeLayer::ValidateTensorShapesFromInputs(), InstanceNormalizationLayer::ValidateTensorShapesFromInputs(), SoftmaxLayer::ValidateTensorShapesFromInputs(), StackLayer::ValidateTensorShapesFromInputs(), L2NormalizationLayer::ValidateTensorShapesFromInputs(), SwitchLayer::ValidateTensorShapesFromInputs(), LogSoftmaxLayer::ValidateTensorShapesFromInputs(), MeanLayer::ValidateTensorShapesFromInputs(), PadLayer::ValidateTensorShapesFromInputs(), ReshapeLayer::ValidateTensorShapesFromInputs(), Convolution2dLayer::ValidateTensorShapesFromInputs(), Convolution3dLayer::ValidateTensorShapesFromInputs(), DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs(), BroadcastToLayer::ValidateTensorShapesFromInputs(), GatherNdLayer::ValidateTensorShapesFromInputs(), BatchMatMulLayer::ValidateTensorShapesFromInputs(), TileLayer::ValidateTensorShapesFromInputs(), ElementwiseBinaryLayer::ValidateTensorShapesFromInputs(), StridedSliceLayer::ValidateTensorShapesFromInputs(), ReduceLayer::ValidateTensorShapesFromInputs(), GatherLayer::ValidateTensorShapesFromInputs(), DetectionPostProcessLayer::ValidateTensorShapesFromInputs(), ElementwiseUnaryLayer::ValidateTensorShapesFromInputs(), ArgMinMaxLayer::ValidateTensorShapesFromInputs(), ReverseV2Layer::ValidateTensorShapesFromInputs(), PreluLayer::ValidateTensorShapesFromInputs(), LogicalBinaryLayer::ValidateTensorShapesFromInputs(), TransposeConvolution2dLayer::ValidateTensorShapesFromInputs(), SpaceToDepthLayer::ValidateTensorShapesFromInputs(), DepthToSpaceLayer::ValidateTensorShapesFromInputs(), ComparisonLayer::ValidateTensorShapesFromInputs(), SpaceToBatchNdLayer::ValidateTensorShapesFromInputs(), LstmLayer::ValidateTensorShapesFromInputs(), UnidirectionalSequenceLstmLayer::ValidateTensorShapesFromInputs(), ConcatLayer::ValidateTensorShapesFromInputs(), BatchNormalizationLayer::ValidateTensorShapesFromInputs(), QuantizedLstmLayer::ValidateTensorShapesFromInputs(), and QLstmLayer::ValidateTensorShapesFromInputs().

VerifyShapeInferenceType()

void VerifyShapeInferenceType ( const TensorShape &  outputShape, ShapeInferenceMethod  shapeInferenceMethod  )

protected

Definition at line 504 of file Layer.cpp.

{
    if (shapeInferenceMethod == ShapeInferenceMethod::ValidateOnly)
    {
        ConditionalThrow<LayerValidationException>(
                outputShape.GetDimensionality() != Dimensionality::NotSpecified,
                "Dimensionality can not be NotSpecified while using ShapeInferenceMethod::ValidateOnly");
 
        ConditionalThrow<LayerValidationException>(
                outputShape.AreAllDimensionsSpecified(),
                "Unspecified dimension while using ShapeInferenceMethod::ValidateOnly");
    }
}

References TensorShape::AreAllDimensionsSpecified(), TensorShape::GetDimensionality(), armnn::NotSpecified, and armnn::ValidateOnly.

Referenced by ElementwiseBaseLayer::ValidateTensorShapesFromInputs(), QuantizeLayer::ValidateTensorShapesFromInputs(), ActivationLayer::ValidateTensorShapesFromInputs(), ChannelShuffleLayer::ValidateTensorShapesFromInputs(), ConvertFp32ToFp16Layer::ValidateTensorShapesFromInputs(), FillLayer::ValidateTensorShapesFromInputs(), RankLayer::ValidateTensorShapesFromInputs(), AbsLayer::ValidateTensorShapesFromInputs(), DebugLayer::ValidateTensorShapesFromInputs(), TransposeLayer::ValidateTensorShapesFromInputs(), CastLayer::ValidateTensorShapesFromInputs(), MemCopyLayer::ValidateTensorShapesFromInputs(), SliceLayer::ValidateTensorShapesFromInputs(), MemImportLayer::ValidateTensorShapesFromInputs(), RsqrtLayer::ValidateTensorShapesFromInputs(), DequantizeLayer::ValidateTensorShapesFromInputs(), MergeLayer::ValidateTensorShapesFromInputs(), NormalizationLayer::ValidateTensorShapesFromInputs(), PermuteLayer::ValidateTensorShapesFromInputs(), Pooling2dLayer::ValidateTensorShapesFromInputs(), Pooling3dLayer::ValidateTensorShapesFromInputs(), BatchToSpaceNdLayer::ValidateTensorShapesFromInputs(), FakeQuantizationLayer::ValidateTensorShapesFromInputs(), ResizeLayer::ValidateTensorShapesFromInputs(), ConvertFp16ToFp32Layer::ValidateTensorShapesFromInputs(), FloorLayer::ValidateTensorShapesFromInputs(), ShapeLayer::ValidateTensorShapesFromInputs(), InstanceNormalizationLayer::ValidateTensorShapesFromInputs(), SoftmaxLayer::ValidateTensorShapesFromInputs(), L2NormalizationLayer::ValidateTensorShapesFromInputs(), StackLayer::ValidateTensorShapesFromInputs(), SwitchLayer::ValidateTensorShapesFromInputs(), LogSoftmaxLayer::ValidateTensorShapesFromInputs(), MeanLayer::ValidateTensorShapesFromInputs(), PadLayer::ValidateTensorShapesFromInputs(), ReshapeLayer::ValidateTensorShapesFromInputs(), Convolution3dLayer::ValidateTensorShapesFromInputs(), BroadcastToLayer::ValidateTensorShapesFromInputs(), DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs(), FullyConnectedLayer::ValidateTensorShapesFromInputs(), Convolution2dLayer::ValidateTensorShapesFromInputs(), GatherNdLayer::ValidateTensorShapesFromInputs(), BatchMatMulLayer::ValidateTensorShapesFromInputs(), ElementwiseBinaryLayer::ValidateTensorShapesFromInputs(), TileLayer::ValidateTensorShapesFromInputs(), ReverseV2Layer::ValidateTensorShapesFromInputs(), ArgMinMaxLayer::ValidateTensorShapesFromInputs(), ReduceLayer::ValidateTensorShapesFromInputs(), StridedSliceLayer::ValidateTensorShapesFromInputs(), ElementwiseUnaryLayer::ValidateTensorShapesFromInputs(), DetectionPostProcessLayer::ValidateTensorShapesFromInputs(), GatherLayer::ValidateTensorShapesFromInputs(), TransposeConvolution2dLayer::ValidateTensorShapesFromInputs(), DepthToSpaceLayer::ValidateTensorShapesFromInputs(), LogicalBinaryLayer::ValidateTensorShapesFromInputs(), SpaceToBatchNdLayer::ValidateTensorShapesFromInputs(), PreluLayer::ValidateTensorShapesFromInputs(), SpaceToDepthLayer::ValidateTensorShapesFromInputs(), ComparisonLayer::ValidateTensorShapesFromInputs(), SplitterLayer::ValidateTensorShapesFromInputs(), LstmLayer::ValidateTensorShapesFromInputs(), UnidirectionalSequenceLstmLayer::ValidateTensorShapesFromInputs(), ConcatLayer::ValidateTensorShapesFromInputs(), BatchNormalizationLayer::ValidateTensorShapesFromInputs(), QuantizedLstmLayer::ValidateTensorShapesFromInputs(), and QLstmLayer::ValidateTensorShapesFromInputs().

Friends And Related Function Documentation

Graph

friend class Graph

friend

Definition at line 382 of file Layer.hpp.

Member Data Documentation

m_AdditionalInfoObject

AdditionalInfoObjectPtr m_AdditionalInfoObject

protected

Definition at line 427 of file Layer.hpp.

Referenced by FusedLayer::Clone(), Layer::GetAdditionalInformation(), Layer::SetAdditionalInfo(), and Layer::SetAdditionalInfoForObject().

m_OutputHandlers

std::vector<OutputHandler> m_OutputHandlers

protected

Definition at line 440 of file Layer.hpp.

Referenced by Layer::GetOutputHandler(), and Layer::Layer().

m_ShapeInferenceMethod

ShapeInferenceMethod m_ShapeInferenceMethod

protected

Definition at line 441 of file Layer.hpp.

Referenced by Layer::CloneBase(), Layer::GetShapeInferenceMethod(), Layer::SetShapeInferenceMethod(), ElementwiseBaseLayer::ValidateTensorShapesFromInputs(), QuantizeLayer::ValidateTensorShapesFromInputs(), ActivationLayer::ValidateTensorShapesFromInputs(), ChannelShuffleLayer::ValidateTensorShapesFromInputs(), ConvertFp32ToFp16Layer::ValidateTensorShapesFromInputs(), FillLayer::ValidateTensorShapesFromInputs(), RankLayer::ValidateTensorShapesFromInputs(), InstanceNormalizationLayer::ValidateTensorShapesFromInputs(), SoftmaxLayer::ValidateTensorShapesFromInputs(), SwitchLayer::ValidateTensorShapesFromInputs(), ShapeLayer::ValidateTensorShapesFromInputs(), L2NormalizationLayer::ValidateTensorShapesFromInputs(), BatchToSpaceNdLayer::ValidateTensorShapesFromInputs(), TransposeLayer::ValidateTensorShapesFromInputs(), DebugLayer::ValidateTensorShapesFromInputs(), MemCopyLayer::ValidateTensorShapesFromInputs(), DequantizeLayer::ValidateTensorShapesFromInputs(), MemImportLayer::ValidateTensorShapesFromInputs(), MergeLayer::ValidateTensorShapesFromInputs(), NormalizationLayer::ValidateTensorShapesFromInputs(), PermuteLayer::ValidateTensorShapesFromInputs(), Pooling2dLayer::ValidateTensorShapesFromInputs(), CastLayer::ValidateTensorShapesFromInputs(), Pooling3dLayer::ValidateTensorShapesFromInputs(), FakeQuantizationLayer::ValidateTensorShapesFromInputs(), ResizeLayer::ValidateTensorShapesFromInputs(), AbsLayer::ValidateTensorShapesFromInputs(), FloorLayer::ValidateTensorShapesFromInputs(), RsqrtLayer::ValidateTensorShapesFromInputs(), SliceLayer::ValidateTensorShapesFromInputs(), ConvertFp16ToFp32Layer::ValidateTensorShapesFromInputs(), StackLayer::ValidateTensorShapesFromInputs(), LogSoftmaxLayer::ValidateTensorShapesFromInputs(), MeanLayer::ValidateTensorShapesFromInputs(), PadLayer::ValidateTensorShapesFromInputs(), ReshapeLayer::ValidateTensorShapesFromInputs(), Convolution2dLayer::ValidateTensorShapesFromInputs(), FullyConnectedLayer::ValidateTensorShapesFromInputs(), BroadcastToLayer::ValidateTensorShapesFromInputs(), DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs(), Convolution3dLayer::ValidateTensorShapesFromInputs(), GatherNdLayer::ValidateTensorShapesFromInputs(), TileLayer::ValidateTensorShapesFromInputs(), ElementwiseBinaryLayer::ValidateTensorShapesFromInputs(), BatchMatMulLayer::ValidateTensorShapesFromInputs(), StridedSliceLayer::ValidateTensorShapesFromInputs(), ReverseV2Layer::ValidateTensorShapesFromInputs(), ArgMinMaxLayer::ValidateTensorShapesFromInputs(), ElementwiseUnaryLayer::ValidateTensorShapesFromInputs(), DetectionPostProcessLayer::ValidateTensorShapesFromInputs(), ReduceLayer::ValidateTensorShapesFromInputs(), GatherLayer::ValidateTensorShapesFromInputs(), TransposeConvolution2dLayer::ValidateTensorShapesFromInputs(), LogicalBinaryLayer::ValidateTensorShapesFromInputs(), SpaceToDepthLayer::ValidateTensorShapesFromInputs(), SpaceToBatchNdLayer::ValidateTensorShapesFromInputs(), PreluLayer::ValidateTensorShapesFromInputs(), ComparisonLayer::ValidateTensorShapesFromInputs(), DepthToSpaceLayer::ValidateTensorShapesFromInputs(), SplitterLayer::ValidateTensorShapesFromInputs(), ConcatLayer::ValidateTensorShapesFromInputs(), LstmLayer::ValidateTensorShapesFromInputs(), UnidirectionalSequenceLstmLayer::ValidateTensorShapesFromInputs(), BatchNormalizationLayer::ValidateTensorShapesFromInputs(), QuantizedLstmLayer::ValidateTensorShapesFromInputs(), and QLstmLayer::ValidateTensorShapesFromInputs().

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

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