LstmLayer Class Reference

This layer represents a LSTM operation. More...

#include <LstmLayer.hpp>

Inheritance diagram for LstmLayer:

Public Member Functions
virtual std::unique_ptr< IWorkload >	CreateWorkload (const IWorkloadFactory &factory) const override
	Makes a workload for the LSTM type. More...
LstmLayer *	Clone (Graph &graph) const override
	Creates a dynamically-allocated copy of this layer. More...
void	ValidateTensorShapesFromInputs () override
	Check if the input tensor shape(s) will lead to a valid configuration of LstmLayer. More...
std::vector< TensorShape >	InferOutputShapes (const std::vector< TensorShape > &inputShapes) const override
	By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties. More...
ARMNN_NO_DEPRECATE_WARN_BEGIN void	Accept (ILayerVisitor &visitor) const override
ARMNN_NO_DEPRECATE_WARN_END void	ExecuteStrategy (IStrategy &strategy) const override
	Apply a visitor to this layer. More...
Public Member Functions inherited from LayerWithParameters< LstmDescriptor >
const LstmDescriptor &	GetParameters () const
void	SerializeLayerParameters (ParameterStringifyFunction &fn) const override
	Helper to serialize the layer parameters to string (currently used in DotSerializer and company). More...
Public Member Functions inherited from Layer
	Layer (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char *name)
	Layer (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, DataLayout layout, const char *name)
const std::string &	GetNameStr () const
const OutputHandler &	GetOutputHandler (unsigned int i=0) const
OutputHandler &	GetOutputHandler (unsigned int i=0)
ShapeInferenceMethod	GetShapeInferenceMethod () const
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)
virtual void	CreateTensorHandles (const TensorHandleFactoryRegistry &registry, const IWorkloadFactory &factory, const bool IsMemoryManaged=true)
void	VerifyLayerConnections (unsigned int expectedConnections, const CheckLocation &location) const
virtual void	ReleaseConstantData ()
template<typename Op >
void	OperateOnConstantTensors (Op op)
const char *	GetName () const override
	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)
template<typename T >
std::shared_ptr< T >	GetAdditionalInformation () const
void	SetAdditionalInfoForObject (const AdditionalInfoObjectPtr &additionalInfo)
Public Member Functions inherited from IConnectableLayer
ARMNN_NO_DEPRECATE_WARN_BEGIN	ARMNN_DEPRECATED_MSG_REMOVAL_DATE ("Accept is deprecated. The ILayerVisitor that works in conjunction with this " "Accept function is deprecated. Use IStrategy in combination with " "ExecuteStrategy instead, which is an ABI/API stable version of the " "visitor pattern.", "22.05") virtual void Accept(ILayerVisitor &visitor) const =0
	Apply a visitor to this layer. More...

Public Attributes
LstmBasicParameters	m_BasicParameters
LstmOptCifgParameters	m_CifgParameters
LstmOptProjectionParameters	m_ProjectionParameters
LstmOptPeepholeParameters	m_PeepholeParameters
LstmOptLayerNormParameters	m_LayerNormParameters

Protected Member Functions
	LstmLayer (const LstmDescriptor &param, const char *name)
	Constructor to create a LstmLayer. More...
	~LstmLayer ()=default
	Default destructor. More...
Layer::ConstantTensors	GetConstantTensorsByRef () override
	Retrieve the handles to the constant values stored by the layer. More...
Protected Member Functions inherited from LayerWithParameters< LstmDescriptor >
	LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const LstmDescriptor &param, const char *name)
	~LayerWithParameters ()=default
WorkloadInfo	PrepInfoAndDesc (QueueDescriptor &descriptor) const
	Helper function to reduce duplication in *LayerCreateWorkload. More...
void	ExecuteStrategy (IStrategy &strategy) const override
	Apply a visitor to this layer. More...
Protected Member Functions inherited from Layer
virtual	~Layer ()=default
template<typename QueueDescriptor >
void	CollectQueueDescriptorInputs (QueueDescriptor &descriptor, WorkloadInfo &info) const
template<typename QueueDescriptor >
void	CollectQueueDescriptorOutputs (QueueDescriptor &descriptor, WorkloadInfo &info) const
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 *LayerCreateWorkload. More...
template<typename LayerType , typename ... Params>
LayerType *	CloneBase (Graph &graph, Params &&... params) const
void	SetAdditionalInfo (QueueDescriptor &descriptor) const
Protected Member Functions inherited from IConnectableLayer
	~IConnectableLayer ()
	Objects are not deletable via the handle. More...

Additional Inherited Members
Public Types inherited from LayerWithParameters< LstmDescriptor >
using	DescriptorType = LstmDescriptor
Protected Types inherited from Layer
using	ConstantTensors = std::vector< std::reference_wrapper< std::shared_ptr< ConstTensorHandle > >>
Protected Attributes inherited from LayerWithParameters< LstmDescriptor >
LstmDescriptor	m_Param
	The parameters for the layer (not including tensor-valued weights etc.). More...
Protected Attributes inherited from Layer
AdditionalInfoObjectPtr	m_AdditionalInfoObject
std::vector< OutputHandler >	m_OutputHandlers
ShapeInferenceMethod	m_ShapeInferenceMethod

Detailed Description

This layer represents a LSTM operation.

Definition at line 16 of file LstmLayer.hpp.

Constructor & Destructor Documentation

LstmLayer()

LstmLayer ( const LstmDescriptor &  param, const char *  name  )

protected

Constructor to create a LstmLayer.

Parameters

[in]	param	LstmDescriptor to configure the lstm operation.
[in]	name	Optional name for the layer.

Definition at line 17 of file LstmLayer.cpp.

References armnn::Lstm.

        : LayerWithParameters(3, 4, LayerType::Lstm, param, name)
{
}

~LstmLayer()

~LstmLayer ( )

protecteddefault

Default destructor.

Member Function Documentation

Accept()

ARMNN_NO_DEPRECATE_WARN_BEGIN void Accept ( ILayerVisitor &  visitor ) const

override

Definition at line 304 of file LstmLayer.cpp.

References ARMNN_NO_DEPRECATE_WARN_END, Layer::GetName(), LayerWithParameters< LstmDescriptor >::GetParameters(), ManagedConstTensorHandle::GetTensorInfo(), LstmLayer::m_BasicParameters, LstmInputParams::m_CellBias, LstmBasicParameters::m_CellBias, LstmOptLayerNormParameters::m_CellLayerNormWeights, LstmInputParams::m_CellLayerNormWeights, LstmInputParams::m_CellToForgetWeights, LstmOptPeepholeParameters::m_CellToForgetWeights, LstmOptPeepholeParameters::m_CellToInputWeights, LstmInputParams::m_CellToInputWeights, LstmInputParams::m_CellToOutputWeights, LstmOptPeepholeParameters::m_CellToOutputWeights, LstmLayer::m_CifgParameters, LstmInputParams::m_ForgetGateBias, LstmBasicParameters::m_ForgetGateBias, LstmOptLayerNormParameters::m_ForgetLayerNormWeights, LstmInputParams::m_ForgetLayerNormWeights, LstmOptCifgParameters::m_InputGateBias, LstmInputParams::m_InputGateBias, LstmOptLayerNormParameters::m_InputLayerNormWeights, LstmInputParams::m_InputLayerNormWeights, LstmInputParams::m_InputToCellWeights, LstmBasicParameters::m_InputToCellWeights, LstmInputParams::m_InputToForgetWeights, LstmBasicParameters::m_InputToForgetWeights, LstmOptCifgParameters::m_InputToInputWeights, LstmInputParams::m_InputToInputWeights, LstmInputParams::m_InputToOutputWeights, LstmBasicParameters::m_InputToOutputWeights, LstmLayer::m_LayerNormParameters, LstmInputParams::m_OutputGateBias, LstmBasicParameters::m_OutputGateBias, LstmOptLayerNormParameters::m_OutputLayerNormWeights, LstmInputParams::m_OutputLayerNormWeights, LstmLayer::m_PeepholeParameters, LstmOptProjectionParameters::m_ProjectionBias, LstmInputParams::m_ProjectionBias, LstmLayer::m_ProjectionParameters, LstmOptProjectionParameters::m_ProjectionWeights, LstmInputParams::m_ProjectionWeights, LstmInputParams::m_RecurrentToCellWeights, LstmBasicParameters::m_RecurrentToCellWeights, LstmInputParams::m_RecurrentToForgetWeights, LstmBasicParameters::m_RecurrentToForgetWeights, LstmOptCifgParameters::m_RecurrentToInputWeights, LstmInputParams::m_RecurrentToInputWeights, LstmInputParams::m_RecurrentToOutputWeights, LstmBasicParameters::m_RecurrentToOutputWeights, and ManagedConstTensorHandle::Map().

{
    LstmInputParams inputParams;
    ManagedConstTensorHandle managedInputToForgetWeights(m_BasicParameters.m_InputToForgetWeights);
    ManagedConstTensorHandle managedInputToCellWeights(m_BasicParameters.m_InputToCellWeights);
    ManagedConstTensorHandle managedInputToOutputWeights(m_BasicParameters.m_InputToOutputWeights);
    ManagedConstTensorHandle managedRecurrentToForgetWeights(m_BasicParameters.m_RecurrentToForgetWeights);
    ManagedConstTensorHandle managedRecurrentToCellWeights(m_BasicParameters.m_RecurrentToCellWeights);
    ManagedConstTensorHandle managedRecurrentToOutputWeights(m_BasicParameters.m_RecurrentToOutputWeights);
    ManagedConstTensorHandle managedForgetGateBias(m_BasicParameters.m_ForgetGateBias);
    ManagedConstTensorHandle managedCellBias(m_BasicParameters.m_CellBias);
    ManagedConstTensorHandle managedOutputGateBias(m_BasicParameters.m_OutputGateBias);

    // Cifg parameters
    ManagedConstTensorHandle managedInputToInputWeights(m_CifgParameters.m_InputToInputWeights);
    ManagedConstTensorHandle managedRecurrentToInputWeights(m_CifgParameters.m_RecurrentToInputWeights);
    ManagedConstTensorHandle managedInputGateBias(m_CifgParameters.m_InputGateBias);

    // Projection parameters
    ManagedConstTensorHandle managedProjectionWeights(m_ProjectionParameters.m_ProjectionWeights);
    ManagedConstTensorHandle managedProjectionBias(m_ProjectionParameters.m_ProjectionBias);

    // Peephole parameters
    ManagedConstTensorHandle managedCellToInputWeights(m_PeepholeParameters.m_CellToInputWeights);
    ManagedConstTensorHandle managedCellToForgetWeights(m_PeepholeParameters.m_CellToForgetWeights);
    ManagedConstTensorHandle managedCellToOutputWeights(m_PeepholeParameters.m_CellToOutputWeights);

    // Layer normalisation parameters
    ManagedConstTensorHandle managedInputLayerNormWeights(m_LayerNormParameters.m_InputLayerNormWeights);
    ManagedConstTensorHandle managedForgetLayerNormWeights(m_LayerNormParameters.m_ForgetLayerNormWeights);
    ManagedConstTensorHandle managedCellLayerNormWeights(m_LayerNormParameters.m_CellLayerNormWeights);
    ManagedConstTensorHandle managedOutputLayerNormWeights(m_LayerNormParameters.m_OutputLayerNormWeights);

    ConstTensor inputToInputWeightsTensor;
    if (m_CifgParameters.m_InputToInputWeights != nullptr)
    {
        ConstTensor inputToInputWeightsTensorCopy(managedInputToInputWeights.GetTensorInfo(),
                                                  managedInputToInputWeights.Map());
        inputToInputWeightsTensor = inputToInputWeightsTensorCopy;
        inputParams.m_InputToInputWeights = &inputToInputWeightsTensor;
    }
    ConstTensor inputToForgetWeightsTensor;
    if (m_BasicParameters.m_InputToForgetWeights != nullptr)
    {
        ConstTensor inputToForgetWeightsTensorCopy(managedInputToForgetWeights.GetTensorInfo(),
                                                   managedInputToForgetWeights.Map());
        inputToForgetWeightsTensor = inputToForgetWeightsTensorCopy;
        inputParams.m_InputToForgetWeights = &inputToForgetWeightsTensor;
    }
    ConstTensor inputToCellWeightsTensor;
    if (m_BasicParameters.m_InputToCellWeights != nullptr)
    {
        ConstTensor inputToCellWeightsTensorCopy(managedInputToCellWeights.GetTensorInfo(),
                                                 managedInputToCellWeights.Map());
        inputToCellWeightsTensor = inputToCellWeightsTensorCopy;
        inputParams.m_InputToCellWeights = &inputToCellWeightsTensor;
    }
    ConstTensor inputToOutputWeightsTensor;
    if (m_BasicParameters.m_InputToOutputWeights != nullptr)
    {
        ConstTensor inputToOutputWeightsTensorCopy(managedInputToOutputWeights.GetTensorInfo(),
                                                   managedInputToOutputWeights.Map());
        inputToOutputWeightsTensor = inputToOutputWeightsTensorCopy;
        inputParams.m_InputToOutputWeights = &inputToOutputWeightsTensor;
    }
    ConstTensor recurrentToInputWeightsTensor;
    if (m_CifgParameters.m_RecurrentToInputWeights != nullptr)
    {
        ConstTensor recurrentToInputWeightsTensorCopy(
                managedRecurrentToInputWeights.GetTensorInfo(),
                managedRecurrentToInputWeights.Map());
        recurrentToInputWeightsTensor = recurrentToInputWeightsTensorCopy;
        inputParams.m_RecurrentToInputWeights = &recurrentToInputWeightsTensor;
    }
    ConstTensor recurrentToForgetWeightsTensor;
    if (m_BasicParameters.m_RecurrentToForgetWeights != nullptr)
    {
        ConstTensor recurrentToForgetWeightsTensorCopy(
                managedRecurrentToForgetWeights.GetTensorInfo(),
                managedRecurrentToForgetWeights.Map());
        recurrentToForgetWeightsTensor = recurrentToForgetWeightsTensorCopy;
        inputParams.m_RecurrentToForgetWeights = &recurrentToForgetWeightsTensor;
    }
    ConstTensor recurrentToCellWeightsTensor;
    if (m_BasicParameters.m_RecurrentToCellWeights != nullptr)
    {
        ConstTensor recurrentToCellWeightsTensorCopy(
                managedRecurrentToCellWeights.GetTensorInfo(),
                managedRecurrentToCellWeights.Map());
        recurrentToCellWeightsTensor = recurrentToCellWeightsTensorCopy;
        inputParams.m_RecurrentToCellWeights = &recurrentToCellWeightsTensor;
    }
    ConstTensor recurrentToOutputWeightsTensor;
    if (m_BasicParameters.m_RecurrentToOutputWeights != nullptr)
    {
        ConstTensor recurrentToOutputWeightsTensorCopy(
                managedRecurrentToOutputWeights.GetTensorInfo(),
                managedRecurrentToOutputWeights.Map());
        recurrentToOutputWeightsTensor = recurrentToOutputWeightsTensorCopy;
        inputParams.m_RecurrentToOutputWeights = &recurrentToOutputWeightsTensor;
    }
    ConstTensor cellToInputWeightsTensor;
    if (m_PeepholeParameters.m_CellToInputWeights != nullptr)
    {
        ConstTensor cellToInputWeightsTensorCopy(managedCellToInputWeights.GetTensorInfo(),
                                                 managedCellToInputWeights.Map());
        cellToInputWeightsTensor = cellToInputWeightsTensorCopy;
        inputParams.m_CellToInputWeights = &cellToInputWeightsTensor;
    }
    ConstTensor cellToForgetWeightsTensor;
    if (m_PeepholeParameters.m_CellToForgetWeights != nullptr)
    {
        ConstTensor cellToForgetWeightsTensorCopy(managedCellToForgetWeights.GetTensorInfo(),
                                                  managedCellToForgetWeights.Map());
        cellToForgetWeightsTensor = cellToForgetWeightsTensorCopy;
        inputParams.m_CellToForgetWeights = &cellToForgetWeightsTensor;
    }
    ConstTensor cellToOutputWeightsTensor;
    if (m_PeepholeParameters.m_CellToOutputWeights != nullptr)
    {
        ConstTensor cellToOutputWeightsTensorCopy(managedCellToOutputWeights.GetTensorInfo(),
                                                  managedCellToOutputWeights.Map());
        cellToOutputWeightsTensor = cellToOutputWeightsTensorCopy;
        inputParams.m_CellToOutputWeights = &cellToOutputWeightsTensor;
    }
    ConstTensor inputGateBiasTensor;
    if (m_CifgParameters.m_InputGateBias != nullptr)
    {
        ConstTensor inputGateBiasTensorCopy(managedInputGateBias.GetTensorInfo(),
                                        managedInputGateBias.Map());
        inputGateBiasTensor = inputGateBiasTensorCopy;
        inputParams.m_InputGateBias = &inputGateBiasTensor;
    }
    ConstTensor forgetGateBiasTensor;
    if (m_BasicParameters.m_ForgetGateBias != nullptr)
    {
        ConstTensor forgetGateBiasTensorCopy(managedForgetGateBias.GetTensorInfo(),
                                             managedForgetGateBias.Map());
        forgetGateBiasTensor = forgetGateBiasTensorCopy;
        inputParams.m_ForgetGateBias = &forgetGateBiasTensor;
    }
    ConstTensor cellBiasTensor;
    if (m_BasicParameters.m_CellBias != nullptr)
    {
        ConstTensor cellBiasTensorCopy(managedCellBias.GetTensorInfo(),
                                       managedCellBias.Map());
        cellBiasTensor = cellBiasTensorCopy;
        inputParams.m_CellBias = &cellBiasTensor;
    }
    ConstTensor outputGateBias;
    if (m_BasicParameters.m_OutputGateBias != nullptr)
    {
        ConstTensor outputGateBiasCopy(managedOutputGateBias.GetTensorInfo(),
                                       managedOutputGateBias.Map());
        outputGateBias = outputGateBiasCopy;
        inputParams.m_OutputGateBias = &outputGateBias;
    }
    ConstTensor projectionWeightsTensor;
    if (m_ProjectionParameters.m_ProjectionWeights != nullptr)
    {
        ConstTensor projectionWeightsTensorCopy(managedProjectionWeights.GetTensorInfo(),
                                                managedProjectionWeights.Map());
        projectionWeightsTensor = projectionWeightsTensorCopy;
        inputParams.m_ProjectionWeights = &projectionWeightsTensor;
    }
    ConstTensor projectionBiasTensor;
    if (m_ProjectionParameters.m_ProjectionBias != nullptr)
    {
        ConstTensor projectionBiasTensorCopy(managedProjectionBias.GetTensorInfo(),
                                             managedProjectionBias.Map());
        projectionBiasTensor = projectionBiasTensorCopy;
        inputParams.m_ProjectionBias = &projectionBiasTensor;
    }
    ConstTensor inputLayerNormTensor;
    if (m_LayerNormParameters.m_InputLayerNormWeights != nullptr)
    {
        ConstTensor inputLayerNormTensorCopy(managedInputLayerNormWeights.GetTensorInfo(),
                                             managedInputLayerNormWeights.Map());
        inputLayerNormTensor = inputLayerNormTensorCopy;
        inputParams.m_InputLayerNormWeights = &inputLayerNormTensor;
    }
    ConstTensor forgetLayerNormTensor;
    if (m_LayerNormParameters.m_ForgetLayerNormWeights != nullptr)
    {
        ConstTensor forgetLayerNormTensorCopy(managedForgetLayerNormWeights.GetTensorInfo(),
                                             managedForgetLayerNormWeights.Map());
        forgetLayerNormTensor = forgetLayerNormTensorCopy;
        inputParams.m_ForgetLayerNormWeights = &forgetLayerNormTensor;
    }
    ConstTensor cellLayerNormTensor;
    if (m_LayerNormParameters.m_CellLayerNormWeights != nullptr)
    {
        ConstTensor cellLayerNormTensorCopy(managedCellLayerNormWeights.GetTensorInfo(),
                                              managedCellLayerNormWeights.Map());
        cellLayerNormTensor = cellLayerNormTensorCopy;
        inputParams.m_CellLayerNormWeights = &cellLayerNormTensor;
    }
    ConstTensor outputLayerNormTensor;
    if (m_LayerNormParameters.m_OutputLayerNormWeights != nullptr)
    {
        ConstTensor outputLayerNormTensorCopy(managedOutputLayerNormWeights.GetTensorInfo(),
                                            managedOutputLayerNormWeights.Map());
        outputLayerNormTensor = outputLayerNormTensorCopy;
        inputParams.m_OutputLayerNormWeights = &outputLayerNormTensor;
    }


    visitor.VisitLstmLayer(this, GetParameters(), inputParams, GetName());
}

Clone()

LstmLayer * Clone ( Graph &  graph ) const

overridevirtual

Creates a dynamically-allocated copy of this layer.

Parameters

[in]

graph

The graph into which this layer is being cloned.

Implements Layer.

Definition at line 80 of file LstmLayer.cpp.

References Layer::GetName(), LstmLayer::m_BasicParameters, LstmBasicParameters::m_CellBias, LstmOptLayerNormParameters::m_CellLayerNormWeights, LstmOptPeepholeParameters::m_CellToForgetWeights, LstmOptPeepholeParameters::m_CellToInputWeights, LstmOptPeepholeParameters::m_CellToOutputWeights, LstmLayer::m_CifgParameters, LstmBasicParameters::m_ForgetGateBias, LstmOptLayerNormParameters::m_ForgetLayerNormWeights, LstmOptCifgParameters::m_InputGateBias, LstmOptLayerNormParameters::m_InputLayerNormWeights, LstmBasicParameters::m_InputToCellWeights, LstmBasicParameters::m_InputToForgetWeights, LstmOptCifgParameters::m_InputToInputWeights, LstmBasicParameters::m_InputToOutputWeights, LstmLayer::m_LayerNormParameters, LstmBasicParameters::m_OutputGateBias, LstmOptLayerNormParameters::m_OutputLayerNormWeights, LayerWithParameters< LstmDescriptor >::m_Param, LstmLayer::m_PeepholeParameters, LstmOptProjectionParameters::m_ProjectionBias, LstmLayer::m_ProjectionParameters, LstmOptProjectionParameters::m_ProjectionWeights, LstmBasicParameters::m_RecurrentToCellWeights, LstmBasicParameters::m_RecurrentToForgetWeights, LstmOptCifgParameters::m_RecurrentToInputWeights, and LstmBasicParameters::m_RecurrentToOutputWeights.

{
    auto layer = CloneBase<LstmLayer>(graph, m_Param, GetName());

    layer->m_BasicParameters.m_InputToForgetWeights = m_BasicParameters.m_InputToForgetWeights ?
            m_BasicParameters.m_InputToForgetWeights
                : nullptr;
    layer->m_BasicParameters.m_InputToCellWeights = m_BasicParameters.m_InputToCellWeights ?
            m_BasicParameters.m_InputToCellWeights : nullptr;
    layer->m_BasicParameters.m_InputToOutputWeights = m_BasicParameters.m_InputToOutputWeights ?
            m_BasicParameters.m_InputToOutputWeights : nullptr;
    layer->m_BasicParameters.m_RecurrentToForgetWeights = m_BasicParameters.m_RecurrentToForgetWeights ?
            m_BasicParameters.m_RecurrentToForgetWeights : nullptr;
    layer->m_BasicParameters.m_RecurrentToCellWeights = m_BasicParameters.m_RecurrentToCellWeights ?
            m_BasicParameters.m_RecurrentToCellWeights : nullptr;
    layer->m_BasicParameters.m_RecurrentToOutputWeights = m_BasicParameters.m_RecurrentToOutputWeights ?
            m_BasicParameters.m_RecurrentToOutputWeights : nullptr;
    layer->m_BasicParameters.m_ForgetGateBias = m_BasicParameters.m_ForgetGateBias ?
            m_BasicParameters.m_ForgetGateBias : nullptr;
    layer->m_BasicParameters.m_CellBias = m_BasicParameters.m_CellBias ?
            m_BasicParameters.m_CellBias : nullptr;
    layer->m_BasicParameters.m_OutputGateBias = m_BasicParameters.m_OutputGateBias ?
            m_BasicParameters.m_OutputGateBias : nullptr;

    if (!m_Param.m_CifgEnabled)
    {
        layer->m_CifgParameters.m_InputToInputWeights = m_CifgParameters.m_InputToInputWeights ?
                m_CifgParameters.m_InputToInputWeights : nullptr;
        layer->m_CifgParameters.m_RecurrentToInputWeights = m_CifgParameters.m_RecurrentToInputWeights ?
                m_CifgParameters.m_RecurrentToInputWeights : nullptr;
        layer->m_CifgParameters.m_InputGateBias = m_CifgParameters.m_InputGateBias ?
                m_CifgParameters.m_InputGateBias : nullptr;
    }

    if (m_Param.m_ProjectionEnabled)
    {
        layer->m_ProjectionParameters.m_ProjectionWeights = m_ProjectionParameters.m_ProjectionWeights ?
               m_ProjectionParameters.m_ProjectionWeights : nullptr;
        layer->m_ProjectionParameters.m_ProjectionBias = m_ProjectionParameters.m_ProjectionBias ?
               m_ProjectionParameters.m_ProjectionBias : nullptr;
    }

    if (m_Param.m_PeepholeEnabled)
    {
        if (!m_Param.m_CifgEnabled)
        {
            layer->m_PeepholeParameters.m_CellToInputWeights = m_PeepholeParameters.m_CellToInputWeights ?
                m_PeepholeParameters.m_CellToInputWeights : nullptr;
        }
        layer->m_PeepholeParameters.m_CellToForgetWeights = m_PeepholeParameters.m_CellToForgetWeights ?
               m_PeepholeParameters.m_CellToForgetWeights : nullptr;
        layer->m_PeepholeParameters.m_CellToOutputWeights = m_PeepholeParameters.m_CellToOutputWeights ?
               m_PeepholeParameters.m_CellToOutputWeights : nullptr;
    }

    if (m_Param.m_LayerNormEnabled)
    {
        layer->m_LayerNormParameters.m_InputLayerNormWeights = m_LayerNormParameters.m_InputLayerNormWeights ?
               m_LayerNormParameters.m_InputLayerNormWeights : nullptr;
        layer->m_LayerNormParameters.m_ForgetLayerNormWeights = m_LayerNormParameters.m_ForgetLayerNormWeights ?
               m_LayerNormParameters.m_ForgetLayerNormWeights : nullptr;
        layer->m_LayerNormParameters.m_CellLayerNormWeights = m_LayerNormParameters.m_CellLayerNormWeights ?
               m_LayerNormParameters.m_CellLayerNormWeights : nullptr;
        layer->m_LayerNormParameters.m_OutputLayerNormWeights = m_LayerNormParameters.m_OutputLayerNormWeights ?
               m_LayerNormParameters.m_OutputLayerNormWeights : nullptr;
    }

    return std::move(layer);
}

CreateWorkload()

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

overridevirtual

Makes a workload for the LSTM type.

Parameters

[in]	graph	The graph where this layer can be found.
[in]	factory	The workload factory which will create the workload.

Returns

A pointer to the created workload, or nullptr if not created.

Implements Layer.

Definition at line 22 of file LstmLayer.cpp.

References IWorkloadFactory::CreateLstm(), LstmLayer::m_BasicParameters, LstmBasicParameters::m_CellBias, LstmQueueDescriptor::m_CellBias, LstmOptLayerNormParameters::m_CellLayerNormWeights, LstmQueueDescriptor::m_CellLayerNormWeights, LstmOptPeepholeParameters::m_CellToForgetWeights, LstmQueueDescriptor::m_CellToForgetWeights, LstmOptPeepholeParameters::m_CellToInputWeights, LstmQueueDescriptor::m_CellToInputWeights, LstmOptPeepholeParameters::m_CellToOutputWeights, LstmQueueDescriptor::m_CellToOutputWeights, LstmDescriptor::m_CifgEnabled, LstmLayer::m_CifgParameters, LstmBasicParameters::m_ForgetGateBias, LstmQueueDescriptor::m_ForgetGateBias, LstmOptLayerNormParameters::m_ForgetLayerNormWeights, LstmQueueDescriptor::m_ForgetLayerNormWeights, LstmOptCifgParameters::m_InputGateBias, LstmQueueDescriptor::m_InputGateBias, LstmOptLayerNormParameters::m_InputLayerNormWeights, LstmQueueDescriptor::m_InputLayerNormWeights, LstmBasicParameters::m_InputToCellWeights, LstmQueueDescriptor::m_InputToCellWeights, LstmBasicParameters::m_InputToForgetWeights, LstmQueueDescriptor::m_InputToForgetWeights, LstmOptCifgParameters::m_InputToInputWeights, LstmQueueDescriptor::m_InputToInputWeights, LstmBasicParameters::m_InputToOutputWeights, LstmQueueDescriptor::m_InputToOutputWeights, LstmDescriptor::m_LayerNormEnabled, LstmLayer::m_LayerNormParameters, LstmBasicParameters::m_OutputGateBias, LstmQueueDescriptor::m_OutputGateBias, LstmOptLayerNormParameters::m_OutputLayerNormWeights, LstmQueueDescriptor::m_OutputLayerNormWeights, LayerWithParameters< LstmDescriptor >::m_Param, LstmDescriptor::m_PeepholeEnabled, LstmLayer::m_PeepholeParameters, LstmOptProjectionParameters::m_ProjectionBias, LstmQueueDescriptor::m_ProjectionBias, LstmDescriptor::m_ProjectionEnabled, LstmLayer::m_ProjectionParameters, LstmOptProjectionParameters::m_ProjectionWeights, LstmQueueDescriptor::m_ProjectionWeights, LstmBasicParameters::m_RecurrentToCellWeights, LstmQueueDescriptor::m_RecurrentToCellWeights, LstmBasicParameters::m_RecurrentToForgetWeights, LstmQueueDescriptor::m_RecurrentToForgetWeights, LstmOptCifgParameters::m_RecurrentToInputWeights, LstmQueueDescriptor::m_RecurrentToInputWeights, LstmBasicParameters::m_RecurrentToOutputWeights, LstmQueueDescriptor::m_RecurrentToOutputWeights, LayerWithParameters< LstmDescriptor >::PrepInfoAndDesc(), and Layer::SetAdditionalInfo().

{
    LstmQueueDescriptor descriptor;

    // Basic parameters
    descriptor.m_InputToForgetWeights = m_BasicParameters.m_InputToForgetWeights.get();
    descriptor.m_InputToCellWeights = m_BasicParameters.m_InputToCellWeights.get();
    descriptor.m_InputToOutputWeights = m_BasicParameters.m_InputToOutputWeights.get();
    descriptor.m_RecurrentToForgetWeights = m_BasicParameters.m_RecurrentToForgetWeights.get();
    descriptor.m_RecurrentToCellWeights = m_BasicParameters.m_RecurrentToCellWeights.get();
    descriptor.m_RecurrentToOutputWeights = m_BasicParameters.m_RecurrentToOutputWeights.get();
    descriptor.m_ForgetGateBias = m_BasicParameters.m_ForgetGateBias.get();
    descriptor.m_CellBias = m_BasicParameters.m_CellBias.get();
    descriptor.m_OutputGateBias = m_BasicParameters.m_OutputGateBias.get();

    // Cifg parameters
    if (!m_Param.m_CifgEnabled)
    {
        descriptor.m_InputToInputWeights = m_CifgParameters.m_InputToInputWeights.get();
        descriptor.m_RecurrentToInputWeights = m_CifgParameters.m_RecurrentToInputWeights.get();
        descriptor.m_InputGateBias = m_CifgParameters.m_InputGateBias.get();
    }

    // Projection parameters
    if (m_Param.m_ProjectionEnabled)
    {
        descriptor.m_ProjectionWeights = m_ProjectionParameters.m_ProjectionWeights.get();
        descriptor.m_ProjectionBias    = m_ProjectionParameters.m_ProjectionBias.get();
    }

    // Peephole parameters
    if (m_Param.m_PeepholeEnabled)
    {
        if (!m_Param.m_CifgEnabled)
        {
            descriptor.m_CellToInputWeights = m_PeepholeParameters.m_CellToInputWeights.get();
        }
        descriptor.m_CellToForgetWeights = m_PeepholeParameters.m_CellToForgetWeights.get();
        descriptor.m_CellToOutputWeights = m_PeepholeParameters.m_CellToOutputWeights.get();
    }

    // Layer normalisation parameters
    if(m_Param.m_LayerNormEnabled)
    {
        if (!m_Param.m_CifgEnabled)
        {
            descriptor.m_InputLayerNormWeights = m_LayerNormParameters.m_InputLayerNormWeights.get();
        }
        descriptor.m_ForgetLayerNormWeights = m_LayerNormParameters.m_ForgetLayerNormWeights.get();
        descriptor.m_CellLayerNormWeights = m_LayerNormParameters.m_CellLayerNormWeights.get();
        descriptor.m_OutputLayerNormWeights = m_LayerNormParameters.m_OutputLayerNormWeights.get();
    }

    SetAdditionalInfo(descriptor);

    return factory.CreateLstm(descriptor, PrepInfoAndDesc(descriptor));
}

ExecuteStrategy()

ARMNN_NO_DEPRECATE_WARN_END void ExecuteStrategy ( IStrategy &  strategy ) const

overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 515 of file LstmLayer.cpp.

References IStrategy::ExecuteStrategy(), Layer::GetName(), LayerWithParameters< LstmDescriptor >::GetParameters(), ManagedConstTensorHandle::GetTensorInfo(), LstmLayer::m_BasicParameters, LstmBasicParameters::m_CellBias, LstmOptLayerNormParameters::m_CellLayerNormWeights, LstmOptPeepholeParameters::m_CellToForgetWeights, LstmOptPeepholeParameters::m_CellToInputWeights, LstmOptPeepholeParameters::m_CellToOutputWeights, LstmDescriptor::m_CifgEnabled, LstmLayer::m_CifgParameters, LstmBasicParameters::m_ForgetGateBias, LstmOptLayerNormParameters::m_ForgetLayerNormWeights, LstmOptCifgParameters::m_InputGateBias, LstmOptLayerNormParameters::m_InputLayerNormWeights, LstmBasicParameters::m_InputToCellWeights, LstmBasicParameters::m_InputToForgetWeights, LstmOptCifgParameters::m_InputToInputWeights, LstmBasicParameters::m_InputToOutputWeights, LstmDescriptor::m_LayerNormEnabled, LstmLayer::m_LayerNormParameters, LstmBasicParameters::m_OutputGateBias, LstmOptLayerNormParameters::m_OutputLayerNormWeights, LstmDescriptor::m_PeepholeEnabled, LstmLayer::m_PeepholeParameters, LstmOptProjectionParameters::m_ProjectionBias, LstmDescriptor::m_ProjectionEnabled, LstmLayer::m_ProjectionParameters, LstmOptProjectionParameters::m_ProjectionWeights, LstmBasicParameters::m_RecurrentToCellWeights, LstmBasicParameters::m_RecurrentToForgetWeights, LstmOptCifgParameters::m_RecurrentToInputWeights, LstmBasicParameters::m_RecurrentToOutputWeights, and ManagedConstTensorHandle::Map().

{
    std::vector<ConstTensor> constTensors;

    LstmDescriptor descriptor = GetParameters();

    ManagedConstTensorHandle managedInputToForgetWeights(m_BasicParameters.m_InputToForgetWeights);
    ManagedConstTensorHandle managedInputToCellWeights(m_BasicParameters.m_InputToCellWeights);
    ManagedConstTensorHandle managedInputToOutputWeights(m_BasicParameters.m_InputToOutputWeights);
    ManagedConstTensorHandle managedRecurrentToForgetWeights(m_BasicParameters.m_RecurrentToForgetWeights);
    ManagedConstTensorHandle managedRecurrentToCellWeights(m_BasicParameters.m_RecurrentToCellWeights);
    ManagedConstTensorHandle managedRecurrentToOutputWeights(m_BasicParameters.m_RecurrentToOutputWeights);
    ManagedConstTensorHandle managedForgetGateBias(m_BasicParameters.m_ForgetGateBias);
    ManagedConstTensorHandle managedCellBias(m_BasicParameters.m_CellBias);
    ManagedConstTensorHandle managedOutputGateBias(m_BasicParameters.m_OutputGateBias);

    // Cifg parameters
    ManagedConstTensorHandle managedInputToInputWeights(m_CifgParameters.m_InputToInputWeights);
    ManagedConstTensorHandle managedRecurrentToInputWeights(m_CifgParameters.m_RecurrentToInputWeights);
    ManagedConstTensorHandle managedInputGateBias(m_CifgParameters.m_InputGateBias);

    // Projection parameters
    ManagedConstTensorHandle managedProjectionWeights(m_ProjectionParameters.m_ProjectionWeights);
    ManagedConstTensorHandle managedProjectionBias(m_ProjectionParameters.m_ProjectionBias);

    // Peephole parameters
    ManagedConstTensorHandle managedCellToInputWeights(m_PeepholeParameters.m_CellToInputWeights);
    ManagedConstTensorHandle managedCellToForgetWeights(m_PeepholeParameters.m_CellToForgetWeights);
    ManagedConstTensorHandle managedCellToOutputWeights(m_PeepholeParameters.m_CellToOutputWeights);

    // Layer normalisation parameters
    ManagedConstTensorHandle managedInputLayerNormWeights(m_LayerNormParameters.m_InputLayerNormWeights);
    ManagedConstTensorHandle managedForgetLayerNormWeights(m_LayerNormParameters.m_ForgetLayerNormWeights);
    ManagedConstTensorHandle managedCellLayerNormWeights(m_LayerNormParameters.m_CellLayerNormWeights);
    ManagedConstTensorHandle managedOutputLayerNormWeights(m_LayerNormParameters.m_OutputLayerNormWeights);

    // First add mandatory/basic parameters
    if (m_BasicParameters.m_InputToForgetWeights != nullptr)
    {
        constTensors.emplace_back(ConstTensor(managedInputToForgetWeights.GetTensorInfo(),
                                              managedInputToForgetWeights.Map()));
    }
    if (m_BasicParameters.m_InputToCellWeights != nullptr)
    {
        constTensors.emplace_back(ConstTensor(managedInputToCellWeights.GetTensorInfo(),
                                              managedInputToCellWeights.Map()));
    }
    if (m_BasicParameters.m_InputToOutputWeights != nullptr)
    {
        constTensors.emplace_back(ConstTensor(managedInputToOutputWeights.GetTensorInfo(),
                                              managedInputToOutputWeights.Map()));
    }
    if (m_BasicParameters.m_RecurrentToForgetWeights != nullptr)
    {
        constTensors.emplace_back(ConstTensor(
                managedRecurrentToForgetWeights.GetTensorInfo(),
                managedRecurrentToForgetWeights.Map()));
    }
    if (m_BasicParameters.m_RecurrentToCellWeights != nullptr)
    {
        constTensors.emplace_back(ConstTensor(
                managedRecurrentToCellWeights.GetTensorInfo(),
                managedRecurrentToCellWeights.Map()));
    }
    if (m_BasicParameters.m_RecurrentToOutputWeights != nullptr)
    {
        constTensors.emplace_back(ConstTensor(
                managedRecurrentToOutputWeights.GetTensorInfo(),
                managedRecurrentToOutputWeights.Map()));
    }
    if (m_BasicParameters.m_ForgetGateBias != nullptr)
    {
        constTensors.emplace_back(ConstTensor(managedForgetGateBias.GetTensorInfo(),
                                              managedForgetGateBias.Map()));
    }
    if (m_BasicParameters.m_CellBias != nullptr)
    {
        constTensors.emplace_back(ConstTensor(managedCellBias.GetTensorInfo(),
                                              managedCellBias.Map()));
    }
    if (m_BasicParameters.m_OutputGateBias != nullptr)
    {
        constTensors.emplace_back(ConstTensor(managedOutputGateBias.GetTensorInfo(),
                                              managedOutputGateBias.Map()));
    }

    // Add cifg parameters
    if (!descriptor.m_CifgEnabled)
    {
        if (m_CifgParameters.m_InputToInputWeights != nullptr)
        {
            constTensors.emplace_back(ConstTensor(managedInputToInputWeights.GetTensorInfo(),
                                                  managedInputToInputWeights.Map()));
        }
        if (m_CifgParameters.m_RecurrentToInputWeights != nullptr)
        {
            constTensors.emplace_back(ConstTensor(
                    managedRecurrentToInputWeights.GetTensorInfo(),
                    managedRecurrentToInputWeights.Map()));
        }
        if (m_CifgParameters.m_InputGateBias != nullptr)
        {
            constTensors.emplace_back(ConstTensor(managedInputGateBias.GetTensorInfo(),
                                                  managedInputGateBias.Map()));
        }
    }

    // Add peephole parameters
    if (descriptor.m_PeepholeEnabled)
    {
        if (!descriptor.m_CifgEnabled)
        {
            if (m_PeepholeParameters.m_CellToInputWeights != nullptr)
            {
                constTensors.emplace_back(ConstTensor(managedCellToInputWeights.GetTensorInfo(),
                                                      managedCellToInputWeights.Map()));
            }
        }
        if (m_PeepholeParameters.m_CellToForgetWeights != nullptr)
        {
            constTensors.emplace_back(ConstTensor(managedCellToForgetWeights.GetTensorInfo(),
                                                  managedCellToForgetWeights.Map()));
        }
        if (m_PeepholeParameters.m_CellToOutputWeights != nullptr)
        {
            constTensors.emplace_back(ConstTensor(managedCellToOutputWeights.GetTensorInfo(),
                                                  managedCellToOutputWeights.Map()));
        }
    }

    // Add projection parameters
    if (descriptor.m_ProjectionEnabled)
    {
        if (m_ProjectionParameters.m_ProjectionWeights != nullptr)
        {
            constTensors.emplace_back(ConstTensor(managedProjectionWeights.GetTensorInfo(),
                                                  managedProjectionWeights.Map()));
        }
        if (m_ProjectionParameters.m_ProjectionBias != nullptr)
        {
            constTensors.emplace_back(ConstTensor(managedProjectionBias.GetTensorInfo(),
                                                  managedProjectionBias.Map()));
        }
    }

    // Add norm parameters
    if (descriptor.m_LayerNormEnabled)
    {
        if (!descriptor.m_CifgEnabled)
        {
            if (m_LayerNormParameters.m_InputLayerNormWeights != nullptr)
            {
                constTensors.emplace_back(ConstTensor(managedInputLayerNormWeights.GetTensorInfo(),
                                                      managedInputLayerNormWeights.Map()));
            }
        }
        if (m_LayerNormParameters.m_ForgetLayerNormWeights != nullptr)
        {
            constTensors.emplace_back(ConstTensor(managedForgetLayerNormWeights.GetTensorInfo(),
                                                  managedForgetLayerNormWeights.Map()));
        }
        if (m_LayerNormParameters.m_CellLayerNormWeights != nullptr)
        {
            constTensors.emplace_back(ConstTensor(managedCellLayerNormWeights.GetTensorInfo(),
                                                  managedCellLayerNormWeights.Map()));
        }
        if (m_LayerNormParameters.m_OutputLayerNormWeights != nullptr)
        {
            constTensors.emplace_back(ConstTensor(managedOutputLayerNormWeights.GetTensorInfo(),
                                                  managedOutputLayerNormWeights.Map()));
        }
    }

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

GetConstantTensorsByRef()

Layer::ConstantTensors GetConstantTensorsByRef ( )

overrideprotectedvirtual

Retrieve the handles to the constant values stored by the layer.

Returns

A vector of the constant tensors stored by this layer.

Reimplemented from Layer.

Definition at line 270 of file LstmLayer.cpp.

References ARMNN_NO_DEPRECATE_WARN_BEGIN, LstmLayer::m_BasicParameters, LstmBasicParameters::m_CellBias, LstmOptLayerNormParameters::m_CellLayerNormWeights, LstmOptPeepholeParameters::m_CellToForgetWeights, LstmOptPeepholeParameters::m_CellToInputWeights, LstmOptPeepholeParameters::m_CellToOutputWeights, LstmLayer::m_CifgParameters, LstmBasicParameters::m_ForgetGateBias, LstmOptLayerNormParameters::m_ForgetLayerNormWeights, LstmOptCifgParameters::m_InputGateBias, LstmOptLayerNormParameters::m_InputLayerNormWeights, LstmBasicParameters::m_InputToCellWeights, LstmBasicParameters::m_InputToForgetWeights, LstmOptCifgParameters::m_InputToInputWeights, LstmBasicParameters::m_InputToOutputWeights, LstmLayer::m_LayerNormParameters, LstmBasicParameters::m_OutputGateBias, LstmOptLayerNormParameters::m_OutputLayerNormWeights, LstmLayer::m_PeepholeParameters, LstmOptProjectionParameters::m_ProjectionBias, LstmLayer::m_ProjectionParameters, LstmOptProjectionParameters::m_ProjectionWeights, LstmBasicParameters::m_RecurrentToCellWeights, LstmBasicParameters::m_RecurrentToForgetWeights, LstmOptCifgParameters::m_RecurrentToInputWeights, and LstmBasicParameters::m_RecurrentToOutputWeights.

{
    return {m_BasicParameters.m_InputToForgetWeights,
            m_BasicParameters.m_InputToCellWeights,
            m_BasicParameters.m_InputToOutputWeights,
            m_BasicParameters.m_RecurrentToForgetWeights,
            m_BasicParameters.m_RecurrentToCellWeights,
            m_BasicParameters.m_RecurrentToOutputWeights,
            m_BasicParameters.m_ForgetGateBias,
            m_BasicParameters.m_CellBias,
            m_BasicParameters.m_OutputGateBias,

            // Cifg parameters
            m_CifgParameters.m_InputToInputWeights,
            m_CifgParameters.m_RecurrentToInputWeights,
            m_CifgParameters.m_InputGateBias,

            // Projection parameters
            m_ProjectionParameters.m_ProjectionWeights,
            m_ProjectionParameters.m_ProjectionBias,

            // Peephole parameters
            m_PeepholeParameters.m_CellToInputWeights,
            m_PeepholeParameters.m_CellToForgetWeights,
            m_PeepholeParameters.m_CellToOutputWeights,

            // Layer normalisation parameters
            m_LayerNormParameters.m_InputLayerNormWeights,
            m_LayerNormParameters.m_ForgetLayerNormWeights,
            m_LayerNormParameters.m_CellLayerNormWeights,
            m_LayerNormParameters.m_OutputLayerNormWeights};
}

InferOutputShapes()

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

overridevirtual

By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties.

Parameters

[in]

inputShapes

The input shapes layer has.

Returns

A vector to the inferred output shape.

Reimplemented from Layer.

Definition at line 150 of file LstmLayer.cpp.

References ARMNN_ASSERT, LstmDescriptor::m_CifgEnabled, and LayerWithParameters< LstmDescriptor >::m_Param.

Referenced by LstmLayer::ValidateTensorShapesFromInputs().

{
    ARMNN_ASSERT(inputShapes.size() == 3);

    // Get input values for validation
    unsigned int batchSize = inputShapes[0][0];
    unsigned int outputSize = inputShapes[1][1];
    unsigned int numUnits = inputShapes[2][1];

    std::vector<TensorShape> outShapes;
    outShapes.push_back(TensorShape({batchSize, numUnits * (m_Param.m_CifgEnabled ? 3 : 4)}));
    outShapes.push_back(TensorShape({batchSize, outputSize}));
    outShapes.push_back(TensorShape({batchSize, numUnits}));
    outShapes.push_back(TensorShape({batchSize, outputSize}));

    return outShapes;
}

ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )

overridevirtual

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

Parameters

[in]

shapeInferenceMethod

Indicates if output shape shall be overwritten or just validated.

Implements Layer.

Definition at line 168 of file LstmLayer.cpp.

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, CHECK_LOCATION, InputSlot::GetConnection(), Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), armnn::GetTensorInfo(), IOutputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), LstmLayer::InferOutputShapes(), LstmLayer::m_BasicParameters, LstmBasicParameters::m_CellBias, LstmOptPeepholeParameters::m_CellToForgetWeights, LstmOptPeepholeParameters::m_CellToInputWeights, LstmOptPeepholeParameters::m_CellToOutputWeights, LstmDescriptor::m_CifgEnabled, LstmLayer::m_CifgParameters, LstmBasicParameters::m_ForgetGateBias, LstmOptCifgParameters::m_InputGateBias, LstmBasicParameters::m_InputToCellWeights, LstmBasicParameters::m_InputToForgetWeights, LstmOptCifgParameters::m_InputToInputWeights, LstmBasicParameters::m_InputToOutputWeights, LstmBasicParameters::m_OutputGateBias, LayerWithParameters< LstmDescriptor >::m_Param, LstmDescriptor::m_PeepholeEnabled, LstmLayer::m_PeepholeParameters, LstmDescriptor::m_ProjectionEnabled, LstmLayer::m_ProjectionParameters, LstmOptProjectionParameters::m_ProjectionWeights, LstmBasicParameters::m_RecurrentToCellWeights, LstmBasicParameters::m_RecurrentToForgetWeights, LstmOptCifgParameters::m_RecurrentToInputWeights, LstmBasicParameters::m_RecurrentToOutputWeights, Layer::m_ShapeInferenceMethod, Layer::ValidateAndCopyShape(), Layer::VerifyLayerConnections(), and Layer::VerifyShapeInferenceType().

{
    VerifyLayerConnections(3, CHECK_LOCATION());

    const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();

    VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);

    auto inferredShapes = InferOutputShapes( {
        GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
        GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape(),
        GetInputSlot(2).GetConnection()->GetTensorInfo().GetShape()
    });

    ARMNN_ASSERT(inferredShapes.size() == 4);

    // Check if the weights are nullptr
    ARMNN_ASSERT_MSG(m_BasicParameters.m_InputToForgetWeights != nullptr,
                     "LstmLayer: m_BasicParameters.m_InputToForgetWeights should not be null.");
    ARMNN_ASSERT_MSG(m_BasicParameters.m_InputToCellWeights != nullptr,
                     "LstmLayer: m_BasicParameters.m_InputToCellWeights should not be null.");
    ARMNN_ASSERT_MSG(m_BasicParameters.m_InputToOutputWeights != nullptr,
                     "LstmLayer: m_BasicParameters.m_InputToOutputWeights should not be null.");
    ARMNN_ASSERT_MSG(m_BasicParameters.m_RecurrentToForgetWeights != nullptr,
                     "LstmLayer: m_BasicParameters.m_RecurrentToForgetWeights should not be null.");
    ARMNN_ASSERT_MSG(m_BasicParameters.m_RecurrentToCellWeights != nullptr,
                     "LstmLayer: m_BasicParameters.m_RecurrentToCellWeights should not be null.");
    ARMNN_ASSERT_MSG(m_BasicParameters.m_RecurrentToOutputWeights != nullptr,
                     "LstmLayer: m_BasicParameters.m_RecurrentToOutputWeights should not be null.");
    ARMNN_ASSERT_MSG(m_BasicParameters.m_ForgetGateBias != nullptr,
                     "LstmLayer: m_BasicParameters.m_ForgetGateBias should not be null.");
    ARMNN_ASSERT_MSG(m_BasicParameters.m_CellBias != nullptr,
                     "LstmLayer: m_BasicParameters.m_CellBias should not be null.");
    ARMNN_ASSERT_MSG(m_BasicParameters.m_OutputGateBias != nullptr,
                     "LstmLayer: m_BasicParameters.m_OutputGateBias should not be null.");

    if (!m_Param.m_CifgEnabled)
    {
        ARMNN_ASSERT_MSG(m_CifgParameters.m_InputToInputWeights != nullptr,
                         "LstmLayer: m_CifgParameters.m_InputToInputWeights should not be null.");
        ARMNN_ASSERT_MSG(m_CifgParameters.m_RecurrentToInputWeights != nullptr,
                         "LstmLayer: m_CifgParameters.m_RecurrentToInputWeights should not be null.");
        ARMNN_ASSERT_MSG(m_CifgParameters.m_InputGateBias != nullptr,
                         "LstmLayer: m_CifgParameters.m_InputGateBias should not be null.");

        ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "LstmLayer");
    }
    else
    {
        ARMNN_ASSERT_MSG(m_CifgParameters.m_InputToInputWeights == nullptr,
            "LstmLayer: m_CifgParameters.m_InputToInputWeights should not have a value when CIFG is enabled.");
        ARMNN_ASSERT_MSG(m_CifgParameters.m_RecurrentToInputWeights == nullptr,
            "LstmLayer: m_CifgParameters.m_RecurrentToInputWeights should not have a value when CIFG is enabled.");
        ARMNN_ASSERT_MSG(m_CifgParameters.m_InputGateBias == nullptr,
            "LstmLayer: m_CifgParameters.m_InputGateBias should not have a value when CIFG is enabled.");

        ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "LstmLayer");
    }

    if (m_Param.m_ProjectionEnabled)
    {
        ARMNN_ASSERT_MSG(m_ProjectionParameters.m_ProjectionWeights != nullptr,
                         "LstmLayer: m_ProjectionParameters.m_ProjectionWeights should not be null.");
    }

    if (m_Param.m_PeepholeEnabled)
    {
        if (!m_Param.m_CifgEnabled)
        {
            ARMNN_ASSERT_MSG(m_PeepholeParameters.m_CellToInputWeights != nullptr,
                             "LstmLayer: m_PeepholeParameters.m_CellToInputWeights should not be null "
                             "when Peephole is enabled and CIFG is disabled.");
        }
        ARMNN_ASSERT_MSG(m_PeepholeParameters.m_CellToForgetWeights != nullptr,
                         "LstmLayer: m_PeepholeParameters.m_CellToForgetWeights should not be null.");
        ARMNN_ASSERT_MSG(m_PeepholeParameters.m_CellToOutputWeights != nullptr,
                         "LstmLayer: m_PeepholeParameters.m_CellToOutputWeights should not be null.");
    }

    ValidateAndCopyShape(
            GetOutputSlot(1).GetTensorInfo().GetShape(), inferredShapes[1], m_ShapeInferenceMethod, "LstmLayer", 1);
    ValidateAndCopyShape(
            GetOutputSlot(2).GetTensorInfo().GetShape(), inferredShapes[2], m_ShapeInferenceMethod, "LstmLayer", 2);
    ValidateAndCopyShape(
            GetOutputSlot(3).GetTensorInfo().GetShape(), inferredShapes[3], m_ShapeInferenceMethod, "LstmLayer", 3);

    if (m_Param.m_LayerNormEnabled)
    {
        if(!m_Param.m_CifgEnabled)
        {
            ARMNN_ASSERT_MSG(m_LayerNormParameters.m_InputLayerNormWeights != nullptr,
                             "LstmLayer: m_LayerNormParameters.m_inputLayerNormWeights should not be null.");
        }
        ARMNN_ASSERT_MSG(m_LayerNormParameters.m_ForgetLayerNormWeights != nullptr,
                         "LstmLayer: m_LayerNormParameters.m_forgetLayerNormWeights should not be null.");
        ARMNN_ASSERT_MSG(m_LayerNormParameters.m_CellLayerNormWeights != nullptr,
                         "LstmLayer: m_LayerNormParameters.m_cellLayerNormWeights should not be null.");
        ARMNN_ASSERT_MSG(m_LayerNormParameters.m_OutputLayerNormWeights != nullptr,
                         "LstmLayer: m_LayerNormParameters.m_outputLayerNormWeights should not be null.");
    }
}

Member Data Documentation

m_BasicParameters

LstmBasicParameters m_BasicParameters

Definition at line 20 of file LstmLayer.hpp.

Referenced by LstmLayer::Accept(), NetworkImpl::AddLstmLayer(), LstmLayer::Clone(), LstmLayer::CreateWorkload(), LstmLayer::ExecuteStrategy(), LstmLayer::GetConstantTensorsByRef(), and LstmLayer::ValidateTensorShapesFromInputs().

m_CifgParameters

LstmOptCifgParameters m_CifgParameters

Definition at line 21 of file LstmLayer.hpp.

Referenced by LstmLayer::Accept(), LstmLayer::Clone(), LstmLayer::CreateWorkload(), LstmLayer::ExecuteStrategy(), LstmLayer::GetConstantTensorsByRef(), and LstmLayer::ValidateTensorShapesFromInputs().

m_LayerNormParameters

LstmOptLayerNormParameters m_LayerNormParameters

Definition at line 24 of file LstmLayer.hpp.

Referenced by LstmLayer::Accept(), LstmLayer::Clone(), LstmLayer::CreateWorkload(), LstmLayer::ExecuteStrategy(), and LstmLayer::GetConstantTensorsByRef().

m_PeepholeParameters

LstmOptPeepholeParameters m_PeepholeParameters

Definition at line 23 of file LstmLayer.hpp.

Referenced by LstmLayer::Accept(), LstmLayer::Clone(), LstmLayer::CreateWorkload(), LstmLayer::ExecuteStrategy(), LstmLayer::GetConstantTensorsByRef(), and LstmLayer::ValidateTensorShapesFromInputs().

m_ProjectionParameters

LstmOptProjectionParameters m_ProjectionParameters

Definition at line 22 of file LstmLayer.hpp.

Referenced by LstmLayer::Accept(), LstmLayer::Clone(), LstmLayer::CreateWorkload(), LstmLayer::ExecuteStrategy(), LstmLayer::GetConstantTensorsByRef(), and LstmLayer::ValidateTensorShapesFromInputs().

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

• src/armnn/layers/LstmLayer.hpp
• src/armnn/layers/LstmLayer.cpp