ArmNN
 21.02
LstmLayer Class Reference

This layer represents a LSTM operation. More...

#include <LstmLayer.hpp>

Inheritance diagram for LstmLayer:
LayerWithParameters< LstmDescriptor > Layer IConnectableLayer

Public Member Functions

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the LSTM type. More...
 
LstmLayerClone (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< TensorShapeInferOutputShapes (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...
 
void Accept (ILayerVisitor &visitor) const override
 Apply a visitor to this layer. More...
 
void ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this layer. More...
 
- Public Member Functions inherited from LayerWithParameters< LstmDescriptor >
const LstmDescriptorGetParameters () 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 OutputHandlerGetOutputHandler (unsigned int i=0) const
 
OutputHandlerGetOutputHandler (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 BackendIdGetBackendId () 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 InputSlotGetInputSlot (unsigned int index) const override
 Get a const input slot handle by slot index. More...
 
InputSlotGetInputSlot (unsigned int index) override
 Get the input slot handle by slot index. More...
 
const OutputSlotGetOutputSlot (unsigned int index=0) const override
 Get the const output slot handle by slot index. More...
 
OutputSlotGetOutputSlot (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< BackendIdGetBackendHint () const
 
void SetShapeInferenceMethod (ShapeInferenceMethod shapeInferenceMethod)
 
template<typename T >
std::shared_ptr< T > GetAdditionalInformation () const
 
void SetAdditionalInfoForObject (const AdditionalInfoObjectPtr &additionalInfo)
 

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>
LayerTypeCloneBase (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::unique_ptr< ScopedCpuTensorHandle > >>
 
- 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< OutputHandlerm_OutputHandlers
 
ShapeInferenceMethod m_ShapeInferenceMethod
 

Detailed Description

This layer represents a LSTM operation.

Definition at line 77 of file LstmLayer.hpp.

Constructor & Destructor Documentation

◆ LstmLayer()

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

Constructor to create a LstmLayer.

Parameters
[in]paramLstmDescriptor to configure the lstm operation.
[in]nameOptional name for the layer.

Definition at line 17 of file LstmLayer.cpp.

References armnn::Lstm.

18  : LayerWithParameters(3, 4, LayerType::Lstm, param, name)
19 {
20 }
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const LstmDescriptor &param, const char *name)

◆ ~LstmLayer()

~LstmLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Accept()

void Accept ( ILayerVisitor visitor) const
overridevirtual

Apply a visitor to this layer.

Implements IConnectableLayer.

Definition at line 303 of file LstmLayer.cpp.

References Layer::GetName(), LayerWithParameters< LstmDescriptor >::GetParameters(), LstmLayer::m_BasicParameters, LstmInputParams::m_CellBias, LstmBasicParameters::m_CellBias, LstmOptLayerNormParameters::m_CellLayerNormWeights, LstmInputParams::m_CellLayerNormWeights, LstmOptPeepholeParameters::m_CellToForgetWeights, LstmInputParams::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 ILayerVisitor::VisitLstmLayer().

304 {
305  LstmInputParams inputParams;
306  ConstTensor inputToInputWeightsTensor;
308  {
309  ConstTensor inputToInputWeightsTensorCopy(m_CifgParameters.m_InputToInputWeights->GetTensorInfo(),
311  inputToInputWeightsTensor = inputToInputWeightsTensorCopy;
312  inputParams.m_InputToInputWeights = &inputToInputWeightsTensor;
313  }
314  ConstTensor inputToForgetWeightsTensor;
316  {
317  ConstTensor inputToForgetWeightsTensorCopy(m_BasicParameters.m_InputToForgetWeights->GetTensorInfo(),
319  inputToForgetWeightsTensor = inputToForgetWeightsTensorCopy;
320  inputParams.m_InputToForgetWeights = &inputToForgetWeightsTensor;
321  }
322  ConstTensor inputToCellWeightsTensor;
324  {
325  ConstTensor inputToCellWeightsTensorCopy(m_BasicParameters.m_InputToCellWeights->GetTensorInfo(),
327  inputToCellWeightsTensor = inputToCellWeightsTensorCopy;
328  inputParams.m_InputToCellWeights = &inputToCellWeightsTensor;
329  }
330  ConstTensor inputToOutputWeightsTensor;
332  {
333  ConstTensor inputToOutputWeightsTensorCopy(m_BasicParameters.m_InputToOutputWeights->GetTensorInfo(),
335  inputToOutputWeightsTensor = inputToOutputWeightsTensorCopy;
336  inputParams.m_InputToOutputWeights = &inputToOutputWeightsTensor;
337  }
338  ConstTensor recurrentToInputWeightsTensor;
340  {
341  ConstTensor recurrentToInputWeightsTensorCopy(
344  recurrentToInputWeightsTensor = recurrentToInputWeightsTensorCopy;
345  inputParams.m_RecurrentToInputWeights = &recurrentToInputWeightsTensor;
346  }
347  ConstTensor recurrentToForgetWeightsTensor;
349  {
350  ConstTensor recurrentToForgetWeightsTensorCopy(
353  recurrentToForgetWeightsTensor = recurrentToForgetWeightsTensorCopy;
354  inputParams.m_RecurrentToForgetWeights = &recurrentToForgetWeightsTensor;
355  }
356  ConstTensor recurrentToCellWeightsTensor;
358  {
359  ConstTensor recurrentToCellWeightsTensorCopy(
362  recurrentToCellWeightsTensor = recurrentToCellWeightsTensorCopy;
363  inputParams.m_RecurrentToCellWeights = &recurrentToCellWeightsTensor;
364  }
365  ConstTensor recurrentToOutputWeightsTensor;
367  {
368  ConstTensor recurrentToOutputWeightsTensorCopy(
371  recurrentToOutputWeightsTensor = recurrentToOutputWeightsTensorCopy;
372  inputParams.m_RecurrentToOutputWeights = &recurrentToOutputWeightsTensor;
373  }
374  ConstTensor cellToInputWeightsTensor;
376  {
377  ConstTensor cellToInputWeightsTensorCopy(m_PeepholeParameters.m_CellToInputWeights->GetTensorInfo(),
379  cellToInputWeightsTensor = cellToInputWeightsTensorCopy;
380  inputParams.m_CellToInputWeights = &cellToInputWeightsTensor;
381  }
382  ConstTensor cellToForgetWeightsTensor;
384  {
385  ConstTensor cellToForgetWeightsTensorCopy(m_PeepholeParameters.m_CellToForgetWeights->GetTensorInfo(),
387  cellToForgetWeightsTensor = cellToForgetWeightsTensorCopy;
388  inputParams.m_CellToForgetWeights = &cellToForgetWeightsTensor;
389  }
390  ConstTensor cellToOutputWeightsTensor;
392  {
393  ConstTensor cellToOutputWeightsTensorCopy(m_PeepholeParameters.m_CellToOutputWeights->GetTensorInfo(),
395  cellToOutputWeightsTensor = cellToOutputWeightsTensorCopy;
396  inputParams.m_CellToOutputWeights = &cellToOutputWeightsTensor;
397  }
398  ConstTensor inputGateBiasTensor;
399  if (m_CifgParameters.m_InputGateBias != nullptr)
400  {
401  ConstTensor inputGateBiasTensorCopy(m_CifgParameters.m_InputGateBias->GetTensorInfo(),
402  m_CifgParameters.m_InputGateBias->Map(true));
403  inputGateBiasTensor = inputGateBiasTensorCopy;
404  inputParams.m_InputGateBias = &inputGateBiasTensor;
405  }
406  ConstTensor forgetGateBiasTensor;
407  if (m_BasicParameters.m_ForgetGateBias != nullptr)
408  {
409  ConstTensor forgetGateBiasTensorCopy(m_BasicParameters.m_ForgetGateBias->GetTensorInfo(),
411  forgetGateBiasTensor = forgetGateBiasTensorCopy;
412  inputParams.m_ForgetGateBias = &forgetGateBiasTensor;
413  }
414  ConstTensor cellBiasTensor;
415  if (m_BasicParameters.m_CellBias != nullptr)
416  {
417  ConstTensor cellBiasTensorCopy(m_BasicParameters.m_CellBias->GetTensorInfo(),
418  m_BasicParameters.m_CellBias->Map(true));
419  cellBiasTensor = cellBiasTensorCopy;
420  inputParams.m_CellBias = &cellBiasTensor;
421  }
422  ConstTensor outputGateBias;
423  if (m_BasicParameters.m_OutputGateBias != nullptr)
424  {
425  ConstTensor outputGateBiasCopy(m_BasicParameters.m_OutputGateBias->GetTensorInfo(),
427  outputGateBias = outputGateBiasCopy;
428  inputParams.m_OutputGateBias = &outputGateBias;
429  }
430  ConstTensor projectionWeightsTensor;
432  {
433  ConstTensor projectionWeightsTensorCopy(m_ProjectionParameters.m_ProjectionWeights->GetTensorInfo(),
435  projectionWeightsTensor = projectionWeightsTensorCopy;
436  inputParams.m_ProjectionWeights = &projectionWeightsTensor;
437  }
438  ConstTensor projectionBiasTensor;
440  {
441  ConstTensor projectionBiasTensorCopy(m_ProjectionParameters.m_ProjectionBias->GetTensorInfo(),
443  projectionBiasTensor = projectionBiasTensorCopy;
444  inputParams.m_ProjectionBias = &projectionBiasTensor;
445  }
446  ConstTensor inputLayerNormTensor;
448  {
449  ConstTensor inputLayerNormTensorCopy(m_LayerNormParameters.m_InputLayerNormWeights->GetTensorInfo(),
451  inputLayerNormTensor = inputLayerNormTensorCopy;
452  inputParams.m_InputLayerNormWeights = &inputLayerNormTensor;
453  }
454  ConstTensor forgetLayerNormTensor;
456  {
457  ConstTensor forgetLayerNormTensorCopy(m_LayerNormParameters.m_ForgetLayerNormWeights->GetTensorInfo(),
459  forgetLayerNormTensor = forgetLayerNormTensorCopy;
460  inputParams.m_ForgetLayerNormWeights = &forgetLayerNormTensor;
461  }
462  ConstTensor cellLayerNormTensor;
464  {
465  ConstTensor cellLayerNormTensorCopy(m_LayerNormParameters.m_CellLayerNormWeights->GetTensorInfo(),
467  cellLayerNormTensor = cellLayerNormTensorCopy;
468  inputParams.m_CellLayerNormWeights = &cellLayerNormTensor;
469  }
470  ConstTensor outputLayerNormTensor;
472  {
473  ConstTensor outputLayerNormTensorCopy(m_LayerNormParameters.m_OutputLayerNormWeights->GetTensorInfo(),
475  outputLayerNormTensor = outputLayerNormTensorCopy;
476  inputParams.m_OutputLayerNormWeights = &outputLayerNormTensor;
477  }
478 
479 
480  visitor.VisitLstmLayer(this, GetParameters(), inputParams, GetName());
481 }
std::unique_ptr< ScopedCpuTensorHandle > m_ForgetGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:69
std::unique_ptr< ScopedCpuTensorHandle > m_InputToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:61
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:65
LstmBasicParameters m_BasicParameters
Definition: LstmLayer.hpp:81
std::unique_ptr< ScopedCpuTensorHandle > m_InputToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:29
std::unique_ptr< ScopedCpuTensorHandle > m_CellLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:21
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:63
std::unique_ptr< ScopedCpuTensorHandle > m_OutputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:73
std::unique_ptr< ScopedCpuTensorHandle > m_InputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:17
std::unique_ptr< ScopedCpuTensorHandle > m_CellBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:71
std::unique_ptr< ScopedCpuTensorHandle > m_CellToForgetWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:49
std::unique_ptr< ScopedCpuTensorHandle > m_OutputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:23
std::unique_ptr< ScopedCpuTensorHandle > m_CellToInputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:47
LstmOptLayerNormParameters m_LayerNormParameters
Definition: LstmLayer.hpp:85
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:31
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:67
LstmOptPeepholeParameters m_PeepholeParameters
Definition: LstmLayer.hpp:84
LstmOptProjectionParameters m_ProjectionParameters
Definition: LstmLayer.hpp:83
std::unique_ptr< ScopedCpuTensorHandle > m_ProjectionBias
A unique pointer to represent 1D weights tensor with dimensions [output_size].
Definition: LstmLayer.hpp:41
std::unique_ptr< ScopedCpuTensorHandle > m_InputToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:59
std::unique_ptr< ScopedCpuTensorHandle > m_CellToOutputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:51
std::unique_ptr< ScopedCpuTensorHandle > m_ProjectionWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:39
std::unique_ptr< ScopedCpuTensorHandle > m_ForgetLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:19
LstmOptCifgParameters m_CifgParameters
Definition: LstmLayer.hpp:82
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:311
std::unique_ptr< ScopedCpuTensorHandle > m_InputToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:57
std::unique_ptr< ScopedCpuTensorHandle > m_InputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:33

◆ Clone()

LstmLayer * Clone ( Graph graph) const
overridevirtual

Creates a dynamically-allocated copy of this layer.

Parameters
[in]graphThe 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.

81 {
82  auto layer = CloneBase<LstmLayer>(graph, m_Param, GetName());
83 
84  layer->m_BasicParameters.m_InputToForgetWeights = m_BasicParameters.m_InputToForgetWeights ?
85  std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_InputToForgetWeights)
86  : nullptr;
87  layer->m_BasicParameters.m_InputToCellWeights = m_BasicParameters.m_InputToCellWeights ?
88  std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_InputToCellWeights) : nullptr;
89  layer->m_BasicParameters.m_InputToOutputWeights = m_BasicParameters.m_InputToOutputWeights ?
90  std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_InputToOutputWeights) : nullptr;
91  layer->m_BasicParameters.m_RecurrentToForgetWeights = m_BasicParameters.m_RecurrentToForgetWeights ?
92  std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_RecurrentToForgetWeights) : nullptr;
93  layer->m_BasicParameters.m_RecurrentToCellWeights = m_BasicParameters.m_RecurrentToCellWeights ?
94  std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_RecurrentToCellWeights) : nullptr;
95  layer->m_BasicParameters.m_RecurrentToOutputWeights = m_BasicParameters.m_RecurrentToOutputWeights ?
96  std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_RecurrentToOutputWeights) : nullptr;
97  layer->m_BasicParameters.m_ForgetGateBias = m_BasicParameters.m_ForgetGateBias ?
98  std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_ForgetGateBias) : nullptr;
99  layer->m_BasicParameters.m_CellBias = m_BasicParameters.m_CellBias ?
100  std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_CellBias) : nullptr;
101  layer->m_BasicParameters.m_OutputGateBias = m_BasicParameters.m_OutputGateBias ?
102  std::make_unique<ScopedCpuTensorHandle>(*m_BasicParameters.m_OutputGateBias) : nullptr;
103 
104  if (!m_Param.m_CifgEnabled)
105  {
106  layer->m_CifgParameters.m_InputToInputWeights = m_CifgParameters.m_InputToInputWeights ?
107  std::make_unique<ScopedCpuTensorHandle>(*m_CifgParameters.m_InputToInputWeights) : nullptr;
108  layer->m_CifgParameters.m_RecurrentToInputWeights = m_CifgParameters.m_RecurrentToInputWeights ?
109  std::make_unique<ScopedCpuTensorHandle>(*m_CifgParameters.m_RecurrentToInputWeights) : nullptr;
110  layer->m_CifgParameters.m_InputGateBias = m_CifgParameters.m_InputGateBias ?
111  std::make_unique<ScopedCpuTensorHandle>(*m_CifgParameters.m_InputGateBias) : nullptr;
112  }
113 
114  if (m_Param.m_ProjectionEnabled)
115  {
116  layer->m_ProjectionParameters.m_ProjectionWeights = m_ProjectionParameters.m_ProjectionWeights ?
117  std::make_unique<ScopedCpuTensorHandle>(*m_ProjectionParameters.m_ProjectionWeights) : nullptr;
118  layer->m_ProjectionParameters.m_ProjectionBias = m_ProjectionParameters.m_ProjectionBias ?
119  std::make_unique<ScopedCpuTensorHandle>(*m_ProjectionParameters.m_ProjectionBias) : nullptr;
120  }
121 
122  if (m_Param.m_PeepholeEnabled)
123  {
124  if (!m_Param.m_CifgEnabled)
125  {
126  layer->m_PeepholeParameters.m_CellToInputWeights = m_PeepholeParameters.m_CellToInputWeights ?
127  std::make_unique<ScopedCpuTensorHandle>(*m_PeepholeParameters.m_CellToInputWeights) : nullptr;
128  }
129  layer->m_PeepholeParameters.m_CellToForgetWeights = m_PeepholeParameters.m_CellToForgetWeights ?
130  std::make_unique<ScopedCpuTensorHandle>(*m_PeepholeParameters.m_CellToForgetWeights) : nullptr;
131  layer->m_PeepholeParameters.m_CellToOutputWeights = m_PeepholeParameters.m_CellToOutputWeights ?
132  std::make_unique<ScopedCpuTensorHandle>(*m_PeepholeParameters.m_CellToOutputWeights) : nullptr;
133  }
134 
135  if (m_Param.m_LayerNormEnabled)
136  {
137  layer->m_LayerNormParameters.m_InputLayerNormWeights = m_LayerNormParameters.m_InputLayerNormWeights ?
138  std::make_unique<ScopedCpuTensorHandle>(*m_LayerNormParameters.m_InputLayerNormWeights) : nullptr;
139  layer->m_LayerNormParameters.m_ForgetLayerNormWeights = m_LayerNormParameters.m_ForgetLayerNormWeights ?
140  std::make_unique<ScopedCpuTensorHandle>(*m_LayerNormParameters.m_ForgetLayerNormWeights) : nullptr;
141  layer->m_LayerNormParameters.m_CellLayerNormWeights = m_LayerNormParameters.m_CellLayerNormWeights ?
142  std::make_unique<ScopedCpuTensorHandle>(*m_LayerNormParameters.m_CellLayerNormWeights) : nullptr;
143  layer->m_LayerNormParameters.m_OutputLayerNormWeights = m_LayerNormParameters.m_OutputLayerNormWeights ?
144  std::make_unique<ScopedCpuTensorHandle>(*m_LayerNormParameters.m_OutputLayerNormWeights) : nullptr;
145  }
146 
147  return std::move(layer);
148 }
std::unique_ptr< ScopedCpuTensorHandle > m_ForgetGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:69
std::unique_ptr< ScopedCpuTensorHandle > m_InputToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:61
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:65
LstmBasicParameters m_BasicParameters
Definition: LstmLayer.hpp:81
LstmDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
std::unique_ptr< ScopedCpuTensorHandle > m_InputToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:29
std::unique_ptr< ScopedCpuTensorHandle > m_CellLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:21
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:63
std::unique_ptr< ScopedCpuTensorHandle > m_OutputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:73
std::unique_ptr< ScopedCpuTensorHandle > m_InputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:17
std::unique_ptr< ScopedCpuTensorHandle > m_CellBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:71
std::unique_ptr< ScopedCpuTensorHandle > m_CellToForgetWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:49
std::unique_ptr< ScopedCpuTensorHandle > m_OutputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:23
std::unique_ptr< ScopedCpuTensorHandle > m_CellToInputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:47
LstmOptLayerNormParameters m_LayerNormParameters
Definition: LstmLayer.hpp:85
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:31
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:67
LstmOptPeepholeParameters m_PeepholeParameters
Definition: LstmLayer.hpp:84
LstmOptProjectionParameters m_ProjectionParameters
Definition: LstmLayer.hpp:83
std::unique_ptr< ScopedCpuTensorHandle > m_ProjectionBias
A unique pointer to represent 1D weights tensor with dimensions [output_size].
Definition: LstmLayer.hpp:41
std::unique_ptr< ScopedCpuTensorHandle > m_InputToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:59
std::unique_ptr< ScopedCpuTensorHandle > m_CellToOutputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:51
std::unique_ptr< ScopedCpuTensorHandle > m_ProjectionWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:39
std::unique_ptr< ScopedCpuTensorHandle > m_ForgetLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:19
LstmOptCifgParameters m_CifgParameters
Definition: LstmLayer.hpp:82
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:311
std::unique_ptr< ScopedCpuTensorHandle > m_InputToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:57
std::unique_ptr< ScopedCpuTensorHandle > m_InputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:33

◆ CreateWorkload()

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

Makes a workload for the LSTM type.

Parameters
[in]graphThe graph where this layer can be found.
[in]factoryThe 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().

23 {
24  LstmQueueDescriptor descriptor;
25 
26  // Basic parameters
27  descriptor.m_InputToForgetWeights = m_BasicParameters.m_InputToForgetWeights.get();
28  descriptor.m_InputToCellWeights = m_BasicParameters.m_InputToCellWeights.get();
29  descriptor.m_InputToOutputWeights = m_BasicParameters.m_InputToOutputWeights.get();
30  descriptor.m_RecurrentToForgetWeights = m_BasicParameters.m_RecurrentToForgetWeights.get();
31  descriptor.m_RecurrentToCellWeights = m_BasicParameters.m_RecurrentToCellWeights.get();
32  descriptor.m_RecurrentToOutputWeights = m_BasicParameters.m_RecurrentToOutputWeights.get();
33  descriptor.m_ForgetGateBias = m_BasicParameters.m_ForgetGateBias.get();
34  descriptor.m_CellBias = m_BasicParameters.m_CellBias.get();
35  descriptor.m_OutputGateBias = m_BasicParameters.m_OutputGateBias.get();
36 
37  // Cifg parameters
39  {
40  descriptor.m_InputToInputWeights = m_CifgParameters.m_InputToInputWeights.get();
41  descriptor.m_RecurrentToInputWeights = m_CifgParameters.m_RecurrentToInputWeights.get();
42  descriptor.m_InputGateBias = m_CifgParameters.m_InputGateBias.get();
43  }
44 
45  // Projection parameters
47  {
48  descriptor.m_ProjectionWeights = m_ProjectionParameters.m_ProjectionWeights.get();
49  descriptor.m_ProjectionBias = m_ProjectionParameters.m_ProjectionBias.get();
50  }
51 
52  // Peephole parameters
54  {
56  {
57  descriptor.m_CellToInputWeights = m_PeepholeParameters.m_CellToInputWeights.get();
58  }
59  descriptor.m_CellToForgetWeights = m_PeepholeParameters.m_CellToForgetWeights.get();
60  descriptor.m_CellToOutputWeights = m_PeepholeParameters.m_CellToOutputWeights.get();
61  }
62 
63  // Layer normalisation parameters
65  {
67  {
68  descriptor.m_InputLayerNormWeights = m_LayerNormParameters.m_InputLayerNormWeights.get();
69  }
70  descriptor.m_ForgetLayerNormWeights = m_LayerNormParameters.m_ForgetLayerNormWeights.get();
71  descriptor.m_CellLayerNormWeights = m_LayerNormParameters.m_CellLayerNormWeights.get();
72  descriptor.m_OutputLayerNormWeights = m_LayerNormParameters.m_OutputLayerNormWeights.get();
73  }
74 
75  SetAdditionalInfo(descriptor);
76 
77  return factory.CreateLstm(descriptor, PrepInfoAndDesc(descriptor));
78 }
std::unique_ptr< ScopedCpuTensorHandle > m_ForgetGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:69
std::unique_ptr< ScopedCpuTensorHandle > m_InputToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:61
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:65
bool m_ProjectionEnabled
Enable/disable the projection layer.
LstmBasicParameters m_BasicParameters
Definition: LstmLayer.hpp:81
LstmDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
std::unique_ptr< ScopedCpuTensorHandle > m_InputToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:29
std::unique_ptr< ScopedCpuTensorHandle > m_CellLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:21
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:63
std::unique_ptr< ScopedCpuTensorHandle > m_OutputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:73
std::unique_ptr< ScopedCpuTensorHandle > m_InputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:17
std::unique_ptr< ScopedCpuTensorHandle > m_CellBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:71
std::unique_ptr< ScopedCpuTensorHandle > m_CellToForgetWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:49
std::unique_ptr< ScopedCpuTensorHandle > m_OutputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:23
std::unique_ptr< ScopedCpuTensorHandle > m_CellToInputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:47
bool m_PeepholeEnabled
Enable/disable peephole.
LstmOptLayerNormParameters m_LayerNormParameters
Definition: LstmLayer.hpp:85
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:31
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:67
LstmOptPeepholeParameters m_PeepholeParameters
Definition: LstmLayer.hpp:84
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:245
LstmOptProjectionParameters m_ProjectionParameters
Definition: LstmLayer.hpp:83
std::unique_ptr< ScopedCpuTensorHandle > m_ProjectionBias
A unique pointer to represent 1D weights tensor with dimensions [output_size].
Definition: LstmLayer.hpp:41
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
std::unique_ptr< ScopedCpuTensorHandle > m_InputToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:59
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.
std::unique_ptr< ScopedCpuTensorHandle > m_CellToOutputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:51
bool m_LayerNormEnabled
Enable/disable layer normalization.
std::unique_ptr< ScopedCpuTensorHandle > m_ProjectionWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:39
std::unique_ptr< ScopedCpuTensorHandle > m_ForgetLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:19
LstmOptCifgParameters m_CifgParameters
Definition: LstmLayer.hpp:82
std::unique_ptr< ScopedCpuTensorHandle > m_InputToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:57
std::unique_ptr< ScopedCpuTensorHandle > m_InputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:33

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy strategy) const
overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 483 of file LstmLayer.cpp.

References IStrategy::ExecuteStrategy(), Layer::GetName(), LayerWithParameters< LstmDescriptor >::GetParameters(), 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, and LstmBasicParameters::m_RecurrentToOutputWeights.

484 {
485  std::vector<ConstTensor> constTensors;
486 
487  LstmDescriptor descriptor = GetParameters();
488 
489  // First add mandatory/basic parameters
491  {
492  constTensors.emplace_back(ConstTensor(m_BasicParameters.m_InputToForgetWeights->GetTensorInfo(),
494  }
496  {
497  constTensors.emplace_back(ConstTensor(m_BasicParameters.m_InputToCellWeights->GetTensorInfo(),
499  }
501  {
502  constTensors.emplace_back(ConstTensor(m_BasicParameters.m_InputToOutputWeights->GetTensorInfo(),
504  }
506  {
507  constTensors.emplace_back(ConstTensor(
510  }
512  {
513  constTensors.emplace_back(ConstTensor(
516  }
518  {
519  constTensors.emplace_back(ConstTensor(
522  }
523  if (m_BasicParameters.m_ForgetGateBias != nullptr)
524  {
525  constTensors.emplace_back(ConstTensor(m_BasicParameters.m_ForgetGateBias->GetTensorInfo(),
526  m_BasicParameters.m_ForgetGateBias->Map(true)));
527  }
528  if (m_BasicParameters.m_CellBias != nullptr)
529  {
530  constTensors.emplace_back(ConstTensor(m_BasicParameters.m_CellBias->GetTensorInfo(),
531  m_BasicParameters.m_CellBias->Map(true)));
532  }
533  if (m_BasicParameters.m_OutputGateBias != nullptr)
534  {
535  constTensors.emplace_back(ConstTensor(m_BasicParameters.m_OutputGateBias->GetTensorInfo(),
536  m_BasicParameters.m_OutputGateBias->Map(true)));
537  }
538 
539  // Add cifg parameters
540  if (!descriptor.m_CifgEnabled)
541  {
543  {
544  constTensors.emplace_back(ConstTensor(m_CifgParameters.m_InputToInputWeights->GetTensorInfo(),
546  }
548  {
549  constTensors.emplace_back(ConstTensor(
552  }
553  if (m_CifgParameters.m_InputGateBias != nullptr)
554  {
555  constTensors.emplace_back(ConstTensor(m_CifgParameters.m_InputGateBias->GetTensorInfo(),
556  m_CifgParameters.m_InputGateBias->Map(true)));
557  }
558  }
559 
560  // Add peephole parameters
561  if (descriptor.m_PeepholeEnabled)
562  {
563  if (!descriptor.m_CifgEnabled)
564  {
566  {
567  constTensors.emplace_back(ConstTensor(m_PeepholeParameters.m_CellToInputWeights->GetTensorInfo(),
569  }
570  }
572  {
573  constTensors.emplace_back(ConstTensor(m_PeepholeParameters.m_CellToForgetWeights->GetTensorInfo(),
575  }
577  {
578  constTensors.emplace_back(ConstTensor(m_PeepholeParameters.m_CellToOutputWeights->GetTensorInfo(),
580  }
581  }
582 
583  // Add projection parameters
584  if (descriptor.m_ProjectionEnabled)
585  {
587  {
588  constTensors.emplace_back(ConstTensor(m_ProjectionParameters.m_ProjectionWeights->GetTensorInfo(),
590  }
592  {
593  constTensors.emplace_back(ConstTensor(m_ProjectionParameters.m_ProjectionBias->GetTensorInfo(),
595  }
596  }
597 
598  // Add norm parameters
599  if (descriptor.m_LayerNormEnabled)
600  {
601  if (!descriptor.m_CifgEnabled)
602  {
604  {
605  constTensors.emplace_back(ConstTensor(m_LayerNormParameters.m_InputLayerNormWeights->GetTensorInfo(),
607  }
608  }
610  {
611  constTensors.emplace_back(ConstTensor(m_LayerNormParameters.m_ForgetLayerNormWeights->GetTensorInfo(),
613  }
615  {
616  constTensors.emplace_back(ConstTensor(m_LayerNormParameters.m_CellLayerNormWeights->GetTensorInfo(),
618  }
620  {
621  constTensors.emplace_back(ConstTensor(m_LayerNormParameters.m_OutputLayerNormWeights->GetTensorInfo(),
623  }
624  }
625 
626  strategy.ExecuteStrategy(this, GetParameters(), constTensors, GetName());
627 }
std::unique_ptr< ScopedCpuTensorHandle > m_ForgetGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:69
std::unique_ptr< ScopedCpuTensorHandle > m_InputToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:61
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:65
LstmBasicParameters m_BasicParameters
Definition: LstmLayer.hpp:81
std::unique_ptr< ScopedCpuTensorHandle > m_InputToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:29
std::unique_ptr< ScopedCpuTensorHandle > m_CellLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:21
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:63
std::unique_ptr< ScopedCpuTensorHandle > m_OutputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:73
std::unique_ptr< ScopedCpuTensorHandle > m_InputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:17
std::unique_ptr< ScopedCpuTensorHandle > m_CellBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:71
std::unique_ptr< ScopedCpuTensorHandle > m_CellToForgetWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:49
std::unique_ptr< ScopedCpuTensorHandle > m_OutputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:23
std::unique_ptr< ScopedCpuTensorHandle > m_CellToInputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:47
LstmOptLayerNormParameters m_LayerNormParameters
Definition: LstmLayer.hpp:85
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:31
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:67
LstmOptPeepholeParameters m_PeepholeParameters
Definition: LstmLayer.hpp:84
LstmOptProjectionParameters m_ProjectionParameters
Definition: LstmLayer.hpp:83
std::unique_ptr< ScopedCpuTensorHandle > m_ProjectionBias
A unique pointer to represent 1D weights tensor with dimensions [output_size].
Definition: LstmLayer.hpp:41
std::unique_ptr< ScopedCpuTensorHandle > m_InputToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:59
std::unique_ptr< ScopedCpuTensorHandle > m_CellToOutputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:51
std::unique_ptr< ScopedCpuTensorHandle > m_ProjectionWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:39
std::unique_ptr< ScopedCpuTensorHandle > m_ForgetLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:19
LstmOptCifgParameters m_CifgParameters
Definition: LstmLayer.hpp:82
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:311
std::unique_ptr< ScopedCpuTensorHandle > m_InputToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:57
std::unique_ptr< ScopedCpuTensorHandle > m_InputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:33

◆ 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 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.

271 {
281 
282  // Cifg parameters
286 
287  // Projection parameters
290 
291  // Peephole parameters
295 
296  // Layer normalisation parameters
301 }
std::unique_ptr< ScopedCpuTensorHandle > m_ForgetGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:69
std::unique_ptr< ScopedCpuTensorHandle > m_InputToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:61
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:65
LstmBasicParameters m_BasicParameters
Definition: LstmLayer.hpp:81
std::unique_ptr< ScopedCpuTensorHandle > m_InputToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:29
std::unique_ptr< ScopedCpuTensorHandle > m_CellLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:21
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:63
std::unique_ptr< ScopedCpuTensorHandle > m_OutputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:73
std::unique_ptr< ScopedCpuTensorHandle > m_InputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:17
std::unique_ptr< ScopedCpuTensorHandle > m_CellBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:71
std::unique_ptr< ScopedCpuTensorHandle > m_CellToForgetWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:49
std::unique_ptr< ScopedCpuTensorHandle > m_OutputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:23
std::unique_ptr< ScopedCpuTensorHandle > m_CellToInputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:47
LstmOptLayerNormParameters m_LayerNormParameters
Definition: LstmLayer.hpp:85
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:31
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:67
LstmOptPeepholeParameters m_PeepholeParameters
Definition: LstmLayer.hpp:84
LstmOptProjectionParameters m_ProjectionParameters
Definition: LstmLayer.hpp:83
std::unique_ptr< ScopedCpuTensorHandle > m_ProjectionBias
A unique pointer to represent 1D weights tensor with dimensions [output_size].
Definition: LstmLayer.hpp:41
std::unique_ptr< ScopedCpuTensorHandle > m_InputToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:59
std::unique_ptr< ScopedCpuTensorHandle > m_CellToOutputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:51
std::unique_ptr< ScopedCpuTensorHandle > m_ProjectionWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:39
std::unique_ptr< ScopedCpuTensorHandle > m_ForgetLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:19
LstmOptCifgParameters m_CifgParameters
Definition: LstmLayer.hpp:82
std::unique_ptr< ScopedCpuTensorHandle > m_InputToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:57
std::unique_ptr< ScopedCpuTensorHandle > m_InputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:33

◆ 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]inputShapesThe 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().

151 {
152  ARMNN_ASSERT(inputShapes.size() == 3);
153 
154  // Get input values for validation
155  unsigned int batchSize = inputShapes[0][0];
156  unsigned int outputSize = inputShapes[1][1];
157  unsigned int numUnits = inputShapes[2][1];
158 
159  std::vector<TensorShape> outShapes;
160  outShapes.push_back(TensorShape({batchSize, numUnits * (m_Param.m_CifgEnabled ? 3 : 4)}));
161  outShapes.push_back(TensorShape({batchSize, outputSize}));
162  outShapes.push_back(TensorShape({batchSize, numUnits}));
163  outShapes.push_back(TensorShape({batchSize, outputSize}));
164 
165  return outShapes;
166 }
LstmDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

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

Parameters
[in]shapeInferenceMethodIndicates 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().

169 {
171 
172  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
173 
175 
176  auto inferredShapes = InferOutputShapes( {
180  });
181 
182  ARMNN_ASSERT(inferredShapes.size() == 4);
183 
184  // Check if the weights are nullptr
186  "LstmLayer: m_BasicParameters.m_InputToForgetWeights should not be null.");
188  "LstmLayer: m_BasicParameters.m_InputToCellWeights should not be null.");
190  "LstmLayer: m_BasicParameters.m_InputToOutputWeights should not be null.");
192  "LstmLayer: m_BasicParameters.m_RecurrentToForgetWeights should not be null.");
194  "LstmLayer: m_BasicParameters.m_RecurrentToCellWeights should not be null.");
196  "LstmLayer: m_BasicParameters.m_RecurrentToOutputWeights should not be null.");
198  "LstmLayer: m_BasicParameters.m_ForgetGateBias should not be null.");
200  "LstmLayer: m_BasicParameters.m_CellBias should not be null.");
202  "LstmLayer: m_BasicParameters.m_OutputGateBias should not be null.");
203 
204  if (!m_Param.m_CifgEnabled)
205  {
207  "LstmLayer: m_CifgParameters.m_InputToInputWeights should not be null.");
209  "LstmLayer: m_CifgParameters.m_RecurrentToInputWeights should not be null.");
211  "LstmLayer: m_CifgParameters.m_InputGateBias should not be null.");
212 
213  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "LstmLayer");
214  }
215  else
216  {
218  "LstmLayer: m_CifgParameters.m_InputToInputWeights should not have a value when CIFG is enabled.");
220  "LstmLayer: m_CifgParameters.m_RecurrentToInputWeights should not have a value when CIFG is enabled.");
222  "LstmLayer: m_CifgParameters.m_InputGateBias should not have a value when CIFG is enabled.");
223 
224  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "LstmLayer");
225  }
226 
228  {
230  "LstmLayer: m_ProjectionParameters.m_ProjectionWeights should not be null.");
231  }
232 
234  {
235  if (!m_Param.m_CifgEnabled)
236  {
238  "LstmLayer: m_PeepholeParameters.m_CellToInputWeights should not be null "
239  "when Peephole is enabled and CIFG is disabled.");
240  }
242  "LstmLayer: m_PeepholeParameters.m_CellToForgetWeights should not be null.");
244  "LstmLayer: m_PeepholeParameters.m_CellToOutputWeights should not be null.");
245  }
246 
248  GetOutputSlot(1).GetTensorInfo().GetShape(), inferredShapes[1], m_ShapeInferenceMethod, "LstmLayer", 1);
250  GetOutputSlot(2).GetTensorInfo().GetShape(), inferredShapes[2], m_ShapeInferenceMethod, "LstmLayer", 2);
252  GetOutputSlot(3).GetTensorInfo().GetShape(), inferredShapes[3], m_ShapeInferenceMethod, "LstmLayer", 3);
253 
255  {
257  {
259  "LstmLayer: m_LayerNormParameters.m_inputLayerNormWeights should not be null.");
260  }
262  "LstmLayer: m_LayerNormParameters.m_forgetLayerNormWeights should not be null.");
264  "LstmLayer: m_LayerNormParameters.m_cellLayerNormWeights should not be null.");
266  "LstmLayer: m_LayerNormParameters.m_outputLayerNormWeights should not be null.");
267  }
268 }
std::unique_ptr< ScopedCpuTensorHandle > m_ForgetGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:69
std::unique_ptr< ScopedCpuTensorHandle > m_InputToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:61
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:65
bool m_ProjectionEnabled
Enable/disable the projection layer.
LstmBasicParameters m_BasicParameters
Definition: LstmLayer.hpp:81
LstmDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
const TensorShape & GetShape() const
Definition: Tensor.hpp:187
std::unique_ptr< ScopedCpuTensorHandle > m_InputToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:29
std::unique_ptr< ScopedCpuTensorHandle > m_CellLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:21
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:63
std::unique_ptr< ScopedCpuTensorHandle > m_OutputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:73
std::unique_ptr< ScopedCpuTensorHandle > m_InputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:17
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:432
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:199
std::unique_ptr< ScopedCpuTensorHandle > m_CellBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:71
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Definition: Layer.cpp:392
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:348
std::unique_ptr< ScopedCpuTensorHandle > m_CellToForgetWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:49
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:316
std::unique_ptr< ScopedCpuTensorHandle > m_OutputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:23
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
std::unique_ptr< ScopedCpuTensorHandle > m_CellToInputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:47
bool m_PeepholeEnabled
Enable/disable peephole.
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
LstmOptLayerNormParameters m_LayerNormParameters
Definition: LstmLayer.hpp:85
#define CHECK_LOCATION()
Definition: Exceptions.hpp:197
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:31
std::unique_ptr< ScopedCpuTensorHandle > m_RecurrentToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:67
LstmOptPeepholeParameters m_PeepholeParameters
Definition: LstmLayer.hpp:84
LstmOptProjectionParameters m_ProjectionParameters
Definition: LstmLayer.hpp:83
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
std::unique_ptr< ScopedCpuTensorHandle > m_InputToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:59
std::unique_ptr< ScopedCpuTensorHandle > m_CellToOutputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:51
bool m_LayerNormEnabled
Enable/disable layer normalization.
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:318
std::unique_ptr< ScopedCpuTensorHandle > m_ProjectionWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmLayer.hpp:39
virtual const TensorInfo & GetTensorInfo() const =0
std::unique_ptr< ScopedCpuTensorHandle > m_ForgetLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:19
LstmOptCifgParameters m_CifgParameters
Definition: LstmLayer.hpp:82
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.
Definition: LstmLayer.cpp:150
const TensorInfo & GetTensorInfo(const ITensorHandle *tensorHandle)
float32 helpers
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:63
std::unique_ptr< ScopedCpuTensorHandle > m_InputToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmLayer.hpp:57
std::unique_ptr< ScopedCpuTensorHandle > m_InputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmLayer.hpp:33
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:408

Member Data Documentation

◆ m_BasicParameters

◆ m_CifgParameters

◆ m_LayerNormParameters

◆ m_PeepholeParameters

◆ m_ProjectionParameters


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