ArmNN
 24.02
UnidirectionalSequenceLstmLayer Class Reference

This layer represents a LSTM operation. More...

#include <UnidirectionalSequenceLstmLayer.hpp>

Inheritance diagram for UnidirectionalSequenceLstmLayer:
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Collaboration diagram for UnidirectionalSequenceLstmLayer:
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Public Member Functions

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the UnidirectionalSequence LSTM type. More...
 
UnidirectionalSequenceLstmLayerClone (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 UnidirectionalSequenceLstmLayer. 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 ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this layer. More...
 
- Public Member Functions inherited from LayerWithParameters< LstmDescriptor >
const LstmDescriptorGetParameters () const override
 If the layer has a descriptor return it. More...
 
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
 
bool GetAllowExpandedDims () const
 
const std::vector< InputSlot > & GetInputSlots () const
 
const std::vector< OutputSlot > & GetOutputSlots () const
 
std::vector< InputSlot >::iterator BeginInputSlots ()
 
std::vector< InputSlot >::iterator EndInputSlots ()
 
std::vector< OutputSlot >::iterator BeginOutputSlots ()
 
std::vector< OutputSlot >::iterator EndOutputSlots ()
 
bool IsOutputUnconnected ()
 
void ResetPriority () const
 
LayerPriority GetPriority () const
 
LayerType GetType () const override
 Returns the armnn::LayerType of this layer. More...
 
DataType GetDataType () const
 
const BackendIdGetBackendId () const
 
void SetBackendId (const BackendId &id) override
 Set the backend of the IConnectableLayer. More...
 
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)
 
void SetAllowExpandedDims (bool allowExpandedDims)
 
template<typename T >
std::shared_ptr< T > GetAdditionalInformation () const
 
void SetAdditionalInfoForObject (const AdditionalInfoObjectPtr &additionalInfo)
 
virtual const BaseDescriptorGetParameters () const override
 If the layer has a descriptor return it. More...
 

Public Attributes

LstmBasicParameters m_BasicParameters
 
LstmOptCifgParameters m_CifgParameters
 
LstmOptProjectionParameters m_ProjectionParameters
 
LstmOptPeepholeParameters m_PeepholeParameters
 
LstmOptLayerNormParameters m_LayerNormParameters
 

Protected Member Functions

 UnidirectionalSequenceLstmLayer (const LstmDescriptor &param, const char *name)
 Constructor to create a UnidirectionalSequenceLstmLayer. More...
 
 ~UnidirectionalSequenceLstmLayer ()=default
 Default destructor. More...
 
Layer::ImmutableConstantTensors GetConstantTensorsByRef () const 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 *Layer::CreateWorkload. More...
 
void ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this layer. More...
 
Layer::ImmutableConstantTensors GetConnectedConstantAsInputTensors () const
 
- 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 *Layer::CreateWorkload. More...
 
template<typename LayerType , typename ... Params>
LayerTypeCloneBase (Graph &graph, Params &&... params) const
 
virtual ConstantTensors GetConstantTensorsByRef () override final
 
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
 
- Public Types inherited from IConnectableLayer
using ConstantTensors = std::vector< std::reference_wrapper< std::shared_ptr< ConstTensorHandle > >>
 
using ImmutableConstantTensors = std::vector< std::reference_wrapper< const std::shared_ptr< ConstTensorHandle > >>
 
- 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 16 of file UnidirectionalSequenceLstmLayer.hpp.

Constructor & Destructor Documentation

◆ UnidirectionalSequenceLstmLayer()

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

Constructor to create a UnidirectionalSequenceLstmLayer.

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

Definition at line 17 of file UnidirectionalSequenceLstmLayer.cpp.

19 {
20 }

References armnn::UnidirectionalSequenceLstm.

◆ ~UnidirectionalSequenceLstmLayer()

~UnidirectionalSequenceLstmLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

UnidirectionalSequenceLstmLayer * 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 UnidirectionalSequenceLstmLayer.cpp.

81 {
82  auto layer = CloneBase<UnidirectionalSequenceLstmLayer>(graph, m_Param, GetName());
83 
84  layer->m_BasicParameters.m_InputToForgetWeights = m_BasicParameters.m_InputToForgetWeights ?
86  : nullptr;
87  layer->m_BasicParameters.m_InputToCellWeights = m_BasicParameters.m_InputToCellWeights ?
89  layer->m_BasicParameters.m_InputToOutputWeights = m_BasicParameters.m_InputToOutputWeights ?
91  layer->m_BasicParameters.m_RecurrentToForgetWeights = m_BasicParameters.m_RecurrentToForgetWeights ?
93  layer->m_BasicParameters.m_RecurrentToCellWeights = m_BasicParameters.m_RecurrentToCellWeights ?
95  layer->m_BasicParameters.m_RecurrentToOutputWeights = m_BasicParameters.m_RecurrentToOutputWeights ?
97  layer->m_BasicParameters.m_ForgetGateBias = m_BasicParameters.m_ForgetGateBias ?
99  layer->m_BasicParameters.m_CellBias = m_BasicParameters.m_CellBias ?
100  m_BasicParameters.m_CellBias : nullptr;
101  layer->m_BasicParameters.m_OutputGateBias = m_BasicParameters.m_OutputGateBias ?
103 
104  if (!m_Param.m_CifgEnabled)
105  {
106  layer->m_CifgParameters.m_InputToInputWeights = m_CifgParameters.m_InputToInputWeights ?
108  layer->m_CifgParameters.m_RecurrentToInputWeights = m_CifgParameters.m_RecurrentToInputWeights ?
110  layer->m_CifgParameters.m_InputGateBias = m_CifgParameters.m_InputGateBias ?
112  }
113 
115  {
116  layer->m_ProjectionParameters.m_ProjectionWeights = m_ProjectionParameters.m_ProjectionWeights ?
118  layer->m_ProjectionParameters.m_ProjectionBias = m_ProjectionParameters.m_ProjectionBias ?
120  }
121 
123  {
124  if (!m_Param.m_CifgEnabled)
125  {
126  layer->m_PeepholeParameters.m_CellToInputWeights = m_PeepholeParameters.m_CellToInputWeights ?
128  }
129  layer->m_PeepholeParameters.m_CellToForgetWeights = m_PeepholeParameters.m_CellToForgetWeights ?
131  layer->m_PeepholeParameters.m_CellToOutputWeights = m_PeepholeParameters.m_CellToOutputWeights ?
133  }
134 
136  {
137  layer->m_LayerNormParameters.m_InputLayerNormWeights = m_LayerNormParameters.m_InputLayerNormWeights ?
139  layer->m_LayerNormParameters.m_ForgetLayerNormWeights = m_LayerNormParameters.m_ForgetLayerNormWeights ?
141  layer->m_LayerNormParameters.m_CellLayerNormWeights = m_LayerNormParameters.m_CellLayerNormWeights ?
143  layer->m_LayerNormParameters.m_OutputLayerNormWeights = m_LayerNormParameters.m_OutputLayerNormWeights ?
145  }
146 
147  return std::move(layer);
148 }

References Layer::GetName(), UnidirectionalSequenceLstmLayer::m_BasicParameters, LstmBasicParameters::m_CellBias, LstmOptLayerNormParameters::m_CellLayerNormWeights, LstmOptPeepholeParameters::m_CellToForgetWeights, LstmOptPeepholeParameters::m_CellToInputWeights, LstmOptPeepholeParameters::m_CellToOutputWeights, LstmDescriptor::m_CifgEnabled, UnidirectionalSequenceLstmLayer::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, UnidirectionalSequenceLstmLayer::m_LayerNormParameters, LstmBasicParameters::m_OutputGateBias, LstmOptLayerNormParameters::m_OutputLayerNormWeights, LayerWithParameters< LstmDescriptor >::m_Param, LstmDescriptor::m_PeepholeEnabled, UnidirectionalSequenceLstmLayer::m_PeepholeParameters, LstmOptProjectionParameters::m_ProjectionBias, LstmDescriptor::m_ProjectionEnabled, UnidirectionalSequenceLstmLayer::m_ProjectionParameters, LstmOptProjectionParameters::m_ProjectionWeights, LstmBasicParameters::m_RecurrentToCellWeights, LstmBasicParameters::m_RecurrentToForgetWeights, LstmOptCifgParameters::m_RecurrentToInputWeights, and LstmBasicParameters::m_RecurrentToOutputWeights.

◆ CreateWorkload()

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

Makes a workload for the UnidirectionalSequence 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 UnidirectionalSequenceLstmLayer.cpp.

23 {
24  UnidirectionalSequenceLstmQueueDescriptor 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.CreateWorkload(LayerType::UnidirectionalSequenceLstm, descriptor, PrepInfoAndDesc(descriptor));
78 }

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

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy strategy) const
overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 311 of file UnidirectionalSequenceLstmLayer.cpp.

312 {
313  std::vector<ConstTensor> constTensors;
314 
315  LstmDescriptor descriptor = GetParameters();
316 
317  ManagedConstTensorHandle managedInputToForgetWeights(m_BasicParameters.m_InputToForgetWeights);
318  ManagedConstTensorHandle managedInputToCellWeights(m_BasicParameters.m_InputToCellWeights);
319  ManagedConstTensorHandle managedInputToOutputWeights(m_BasicParameters.m_InputToOutputWeights);
320  ManagedConstTensorHandle managedRecurrentToForgetWeights(m_BasicParameters.m_RecurrentToForgetWeights);
321  ManagedConstTensorHandle managedRecurrentToCellWeights(m_BasicParameters.m_RecurrentToCellWeights);
322  ManagedConstTensorHandle managedRecurrentToOutputWeights(m_BasicParameters.m_RecurrentToOutputWeights);
323  ManagedConstTensorHandle managedForgetGateBias(m_BasicParameters.m_ForgetGateBias);
324  ManagedConstTensorHandle managedCellBias(m_BasicParameters.m_CellBias);
325  ManagedConstTensorHandle managedOutputGateBias(m_BasicParameters.m_OutputGateBias);
326 
327  // Cifg parameters
328  ManagedConstTensorHandle managedInputToInputWeights(m_CifgParameters.m_InputToInputWeights);
329  ManagedConstTensorHandle managedRecurrentToInputWeights(m_CifgParameters.m_RecurrentToInputWeights);
330  ManagedConstTensorHandle managedInputGateBias(m_CifgParameters.m_InputGateBias);
331 
332  // Projection parameters
333  ManagedConstTensorHandle managedProjectionWeights(m_ProjectionParameters.m_ProjectionWeights);
334  ManagedConstTensorHandle managedProjectionBias(m_ProjectionParameters.m_ProjectionBias);
335 
336  // Peephole parameters
337  ManagedConstTensorHandle managedCellToInputWeights(m_PeepholeParameters.m_CellToInputWeights);
338  ManagedConstTensorHandle managedCellToForgetWeights(m_PeepholeParameters.m_CellToForgetWeights);
339  ManagedConstTensorHandle managedCellToOutputWeights(m_PeepholeParameters.m_CellToOutputWeights);
340 
341  // Layer normalisation parameters
342  ManagedConstTensorHandle managedInputLayerNormWeights(m_LayerNormParameters.m_InputLayerNormWeights);
343  ManagedConstTensorHandle managedForgetLayerNormWeights(m_LayerNormParameters.m_ForgetLayerNormWeights);
344  ManagedConstTensorHandle managedCellLayerNormWeights(m_LayerNormParameters.m_CellLayerNormWeights);
345  ManagedConstTensorHandle managedOutputLayerNormWeights(m_LayerNormParameters.m_OutputLayerNormWeights);
346 
347  // First add mandatory/basic parameters
349  {
350  constTensors.emplace_back(ConstTensor(managedInputToForgetWeights.GetTensorInfo(),
351  managedInputToForgetWeights.Map()));
352  }
354  {
355  constTensors.emplace_back(ConstTensor(managedInputToCellWeights.GetTensorInfo(),
356  managedInputToCellWeights.Map()));
357  }
359  {
360  constTensors.emplace_back(ConstTensor(managedInputToOutputWeights.GetTensorInfo(),
361  managedInputToOutputWeights.Map()));
362  }
364  {
365  constTensors.emplace_back(ConstTensor(
366  managedRecurrentToForgetWeights.GetTensorInfo(),
367  managedRecurrentToForgetWeights.Map()));
368  }
370  {
371  constTensors.emplace_back(ConstTensor(
372  managedRecurrentToCellWeights.GetTensorInfo(),
373  managedRecurrentToCellWeights.Map()));
374  }
376  {
377  constTensors.emplace_back(ConstTensor(
378  managedRecurrentToOutputWeights.GetTensorInfo(),
379  managedRecurrentToOutputWeights.Map()));
380  }
381  if (m_BasicParameters.m_ForgetGateBias != nullptr)
382  {
383  constTensors.emplace_back(ConstTensor(managedForgetGateBias.GetTensorInfo(),
384  managedForgetGateBias.Map()));
385  }
386  if (m_BasicParameters.m_CellBias != nullptr)
387  {
388  constTensors.emplace_back(ConstTensor(managedCellBias.GetTensorInfo(),
389  managedCellBias.Map()));
390  }
391  if (m_BasicParameters.m_OutputGateBias != nullptr)
392  {
393  constTensors.emplace_back(ConstTensor(managedOutputGateBias.GetTensorInfo(),
394  managedOutputGateBias.Map()));
395  }
396 
397  // Add cifg parameters
398  if (!descriptor.m_CifgEnabled)
399  {
401  {
402  constTensors.emplace_back(ConstTensor(managedInputToInputWeights.GetTensorInfo(),
403  managedInputToInputWeights.Map()));
404  }
406  {
407  constTensors.emplace_back(ConstTensor(
408  managedRecurrentToInputWeights.GetTensorInfo(),
409  managedRecurrentToInputWeights.Map()));
410  }
411  if (m_CifgParameters.m_InputGateBias != nullptr)
412  {
413  constTensors.emplace_back(ConstTensor(managedInputGateBias.GetTensorInfo(),
414  managedInputGateBias.Map()));
415  }
416  }
417 
418  // Add peephole parameters
419  if (descriptor.m_PeepholeEnabled)
420  {
421  if (!descriptor.m_CifgEnabled)
422  {
424  {
425  constTensors.emplace_back(ConstTensor(managedCellToInputWeights.GetTensorInfo(),
426  managedCellToInputWeights.Map()));
427  }
428  }
430  {
431  constTensors.emplace_back(ConstTensor(managedCellToForgetWeights.GetTensorInfo(),
432  managedCellToForgetWeights.Map()));
433  }
435  {
436  constTensors.emplace_back(ConstTensor(managedCellToOutputWeights.GetTensorInfo(),
437  managedCellToOutputWeights.Map()));
438  }
439  }
440 
441  // Add projection parameters
442  if (descriptor.m_ProjectionEnabled)
443  {
445  {
446  constTensors.emplace_back(ConstTensor(managedProjectionWeights.GetTensorInfo(),
447  managedProjectionWeights.Map()));
448  }
450  {
451  constTensors.emplace_back(ConstTensor(managedProjectionBias.GetTensorInfo(),
452  managedProjectionBias.Map()));
453  }
454  }
455 
456  // Add norm parameters
457  if (descriptor.m_LayerNormEnabled)
458  {
459  if (!descriptor.m_CifgEnabled)
460  {
462  {
463  constTensors.emplace_back(ConstTensor(managedInputLayerNormWeights.GetTensorInfo(),
464  managedInputLayerNormWeights.Map()));
465  }
466  }
468  {
469  constTensors.emplace_back(ConstTensor(managedForgetLayerNormWeights.GetTensorInfo(),
470  managedForgetLayerNormWeights.Map()));
471  }
473  {
474  constTensors.emplace_back(ConstTensor(managedCellLayerNormWeights.GetTensorInfo(),
475  managedCellLayerNormWeights.Map()));
476  }
478  {
479  constTensors.emplace_back(ConstTensor(managedOutputLayerNormWeights.GetTensorInfo(),
480  managedOutputLayerNormWeights.Map()));
481  }
482  }
483 
484  strategy.ExecuteStrategy(this, GetParameters(), constTensors, GetName());
485 }

References IStrategy::ExecuteStrategy(), Layer::GetName(), LayerWithParameters< LstmDescriptor >::GetParameters(), ManagedConstTensorHandle::GetTensorInfo(), UnidirectionalSequenceLstmLayer::m_BasicParameters, LstmBasicParameters::m_CellBias, LstmOptLayerNormParameters::m_CellLayerNormWeights, LstmOptPeepholeParameters::m_CellToForgetWeights, LstmOptPeepholeParameters::m_CellToInputWeights, LstmOptPeepholeParameters::m_CellToOutputWeights, LstmDescriptor::m_CifgEnabled, UnidirectionalSequenceLstmLayer::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, UnidirectionalSequenceLstmLayer::m_LayerNormParameters, LstmBasicParameters::m_OutputGateBias, LstmOptLayerNormParameters::m_OutputLayerNormWeights, LstmDescriptor::m_PeepholeEnabled, UnidirectionalSequenceLstmLayer::m_PeepholeParameters, LstmOptProjectionParameters::m_ProjectionBias, LstmDescriptor::m_ProjectionEnabled, UnidirectionalSequenceLstmLayer::m_ProjectionParameters, LstmOptProjectionParameters::m_ProjectionWeights, LstmBasicParameters::m_RecurrentToCellWeights, LstmBasicParameters::m_RecurrentToForgetWeights, LstmOptCifgParameters::m_RecurrentToInputWeights, LstmBasicParameters::m_RecurrentToOutputWeights, and ManagedConstTensorHandle::Map().

◆ GetConstantTensorsByRef()

Layer::ImmutableConstantTensors GetConstantTensorsByRef ( ) const
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 277 of file UnidirectionalSequenceLstmLayer.cpp.

References UnidirectionalSequenceLstmLayer::m_BasicParameters, LstmBasicParameters::m_CellBias, LstmOptLayerNormParameters::m_CellLayerNormWeights, LstmOptPeepholeParameters::m_CellToForgetWeights, LstmOptPeepholeParameters::m_CellToInputWeights, LstmOptPeepholeParameters::m_CellToOutputWeights, UnidirectionalSequenceLstmLayer::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, UnidirectionalSequenceLstmLayer::m_LayerNormParameters, LstmBasicParameters::m_OutputGateBias, LstmOptLayerNormParameters::m_OutputLayerNormWeights, UnidirectionalSequenceLstmLayer::m_PeepholeParameters, LstmOptProjectionParameters::m_ProjectionBias, UnidirectionalSequenceLstmLayer::m_ProjectionParameters, LstmOptProjectionParameters::m_ProjectionWeights, LstmBasicParameters::m_RecurrentToCellWeights, LstmBasicParameters::m_RecurrentToForgetWeights, LstmOptCifgParameters::m_RecurrentToInputWeights, and LstmBasicParameters::m_RecurrentToOutputWeights.

◆ 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 UnidirectionalSequenceLstmLayer.cpp.

152 {
153  ARMNN_ASSERT(inputShapes.size() == 3);
154 
155  // Get input values for validation
156  unsigned int outputSize = inputShapes[1][1];
157 
158  std::vector<TensorShape> outShapes;
159  if (m_Param.m_TimeMajor)
160  {
161  outShapes.push_back(TensorShape({inputShapes[0][0], inputShapes[0][1], outputSize}));
162  }
163  else
164  {
165  outShapes.push_back(TensorShape({inputShapes[0][0], inputShapes[0][1], outputSize}));
166  }
167  return outShapes;
168 }

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

Referenced by UnidirectionalSequenceLstmLayer::ValidateTensorShapesFromInputs().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

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

Parameters
[in]shapeInferenceMethodIndicates if output shape shall be overwritten or just validated.

Implements Layer.

Definition at line 170 of file UnidirectionalSequenceLstmLayer.cpp.

171 {
173 
174  const TensorShape& outputShape = GetOutputSlot(2).GetTensorInfo().GetShape();
175 
177 
178  auto inferredShapes = InferOutputShapes( {
182  });
183 
184  ARMNN_ASSERT(inferredShapes.size() == 1);
185 
186  // Check if the weights are nullptr
188  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_InputToForgetWeights should not be null.");
190  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_InputToCellWeights should not be null.");
192  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_InputToOutputWeights should not be null.");
194  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_RecurrentToForgetWeights "
195  "should not be null.");
197  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_RecurrentToCellWeights should not be null.");
199  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_RecurrentToOutputWeights "
200  "should not be null.");
202  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_ForgetGateBias should not be null.");
204  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_CellBias should not be null.");
206  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_OutputGateBias should not be null.");
207 
208  if (!m_Param.m_CifgEnabled)
209  {
211  "UnidirectionalSequenceLstmLayer: m_CifgParameters.m_InputToInputWeights should not be null.");
213  "UnidirectionalSequenceLstmLayer: m_CifgParameters.m_RecurrentToInputWeights "
214  "should not be null.");
216  "UnidirectionalSequenceLstmLayer: m_CifgParameters.m_InputGateBias should not be null.");
217  }
218  else
219  {
221  "UnidirectionalSequenceLstmLayer: m_CifgParameters.m_InputToInputWeights should not have a value "
222  "when CIFG is enabled.");
224  "UnidirectionalSequenceLstmLayer: m_CifgParameters.m_RecurrentToInputWeights should not have a value "
225  "when CIFG is enabled.");
227  "UnidirectionalSequenceLstmLayer: m_CifgParameters.m_InputGateBias should not have a value "
228  "when CIFG is enabled.");
229  }
230 
232  {
234  "UnidirectionalSequenceLstmLayer: m_ProjectionParameters.m_ProjectionWeights "
235  "should not be null.");
236  }
237 
239  {
240  if (!m_Param.m_CifgEnabled)
241  {
243  "UnidirectionalSequenceLstmLayer: m_PeepholeParameters.m_CellToInputWeights "
244  "should not be null "
245  "when Peephole is enabled and CIFG is disabled.");
246  }
248  "UnidirectionalSequenceLstmLayer: m_PeepholeParameters.m_CellToForgetWeights "
249  "should not be null.");
251  "UnidirectionalSequenceLstmLayer: m_PeepholeParameters.m_CellToOutputWeights "
252  "should not be null.");
253  }
254 
256  {
258  {
260  "UnidirectionalSequenceLstmLayer: m_LayerNormParameters.m_inputLayerNormWeights "
261  "should not be null.");
262  }
264  "UnidirectionalSequenceLstmLayer: m_LayerNormParameters.m_forgetLayerNormWeights "
265  "should not be null.");
267  "UnidirectionalSequenceLstmLayer: m_LayerNormParameters.m_cellLayerNormWeights "
268  "should not be null.");
270  "UnidirectionalSequenceLstmLayer: m_LayerNormParameters.m_outputLayerNormWeights "
271  "should not be null.");
272  }
273 
274  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "UnidirectionalSequenceLstmLayer");
275 }

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, CHECK_LOCATION, Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), InputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), UnidirectionalSequenceLstmLayer::InferOutputShapes(), UnidirectionalSequenceLstmLayer::m_BasicParameters, LstmBasicParameters::m_CellBias, LstmOptLayerNormParameters::m_CellLayerNormWeights, LstmOptPeepholeParameters::m_CellToForgetWeights, LstmOptPeepholeParameters::m_CellToInputWeights, LstmOptPeepholeParameters::m_CellToOutputWeights, LstmDescriptor::m_CifgEnabled, UnidirectionalSequenceLstmLayer::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, UnidirectionalSequenceLstmLayer::m_LayerNormParameters, LstmBasicParameters::m_OutputGateBias, LstmOptLayerNormParameters::m_OutputLayerNormWeights, LayerWithParameters< LstmDescriptor >::m_Param, LstmDescriptor::m_PeepholeEnabled, UnidirectionalSequenceLstmLayer::m_PeepholeParameters, LstmDescriptor::m_ProjectionEnabled, UnidirectionalSequenceLstmLayer::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().

Member Data Documentation

◆ m_BasicParameters

◆ m_CifgParameters

◆ m_LayerNormParameters

◆ m_PeepholeParameters

◆ m_ProjectionParameters


The documentation for this class was generated from the following files:
ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
armnn::LstmOptProjectionParameters::m_ProjectionWeights
std::shared_ptr< ConstTensorHandle > m_ProjectionWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmParameters.hpp:39
armnn::LstmOptLayerNormParameters::m_OutputLayerNormWeights
std::shared_ptr< ConstTensorHandle > m_OutputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmParameters.hpp:23
armnn::LstmDescriptor::m_TimeMajor
bool m_TimeMajor
Enable/disable time major.
Definition: Descriptors.hpp:1154
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92
armnn::LstmBasicParameters::m_InputToCellWeights
std::shared_ptr< ConstTensorHandle > m_InputToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmParameters.hpp:59
armnn::LstmOptLayerNormParameters::m_InputLayerNormWeights
std::shared_ptr< ConstTensorHandle > m_InputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmParameters.hpp:17
armnn::LstmOptCifgParameters::m_InputGateBias
std::shared_ptr< ConstTensorHandle > m_InputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmParameters.hpp:33
armnn::LstmOptPeepholeParameters::m_CellToInputWeights
std::shared_ptr< ConstTensorHandle > m_CellToInputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmParameters.hpp:47
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
armnn::Layer::ValidateAndCopyShape
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Definition: Layer.cpp:435
armnn::UnidirectionalSequenceLstmLayer::m_BasicParameters
LstmBasicParameters m_BasicParameters
Definition: UnidirectionalSequenceLstmLayer.hpp:20
armnn::Layer::GetOutputSlot
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:339
ARMNN_ASSERT_MSG
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:337
armnn::LayerWithParameters< LstmDescriptor >::GetParameters
const LstmDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
armnn::LstmOptProjectionParameters::m_ProjectionBias
std::shared_ptr< ConstTensorHandle > m_ProjectionBias
A unique pointer to represent 1D weights tensor with dimensions [output_size].
Definition: LstmParameters.hpp:41
armnn::LstmBasicParameters::m_InputToOutputWeights
std::shared_ptr< ConstTensorHandle > m_InputToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmParameters.hpp:61
armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:332
armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:592
armnn::LstmBasicParameters::m_ForgetGateBias
std::shared_ptr< ConstTensorHandle > m_ForgetGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmParameters.hpp:69
armnn::LstmOptLayerNormParameters::m_CellLayerNormWeights
std::shared_ptr< ConstTensorHandle > m_CellLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmParameters.hpp:21
armnn::LstmDescriptor::m_PeepholeEnabled
bool m_PeepholeEnabled
Enable/disable peephole.
Definition: Descriptors.hpp:1148
armnn::LayerWithParameters< LstmDescriptor >::m_Param
LstmDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::LstmOptCifgParameters::m_RecurrentToInputWeights
std::shared_ptr< ConstTensorHandle > m_RecurrentToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmParameters.hpp:31
armnn::LayerWithParameters< LstmDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:504
armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:287
armnn::UnidirectionalSequenceLstmLayer::m_PeepholeParameters
LstmOptPeepholeParameters m_PeepholeParameters
Definition: UnidirectionalSequenceLstmLayer.hpp:23
armnn::LstmBasicParameters::m_OutputGateBias
std::shared_ptr< ConstTensorHandle > m_OutputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmParameters.hpp:73
armnn::LstmBasicParameters::m_CellBias
std::shared_ptr< ConstTensorHandle > m_CellBias
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmParameters.hpp:71
armnn::LstmOptCifgParameters::m_InputToInputWeights
std::shared_ptr< ConstTensorHandle > m_InputToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmParameters.hpp:29
armnn::LstmBasicParameters::m_InputToForgetWeights
std::shared_ptr< ConstTensorHandle > m_InputToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units].
Definition: LstmParameters.hpp:57
armnn::LstmDescriptor::m_CifgEnabled
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
Definition: Descriptors.hpp:1146
armnn::LstmBasicParameters::m_RecurrentToCellWeights
std::shared_ptr< ConstTensorHandle > m_RecurrentToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmParameters.hpp:65
armnn::LstmBasicParameters::m_RecurrentToForgetWeights
std::shared_ptr< ConstTensorHandle > m_RecurrentToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmParameters.hpp:63
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn::UnidirectionalSequenceLstmLayer::InferOutputShapes
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,...
Definition: UnidirectionalSequenceLstmLayer.cpp:150
armnn::LstmBasicParameters::m_RecurrentToOutputWeights
std::shared_ptr< ConstTensorHandle > m_RecurrentToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units].
Definition: LstmParameters.hpp:67
armnn::LstmDescriptor::m_LayerNormEnabled
bool m_LayerNormEnabled
Enable/disable layer normalization.
Definition: Descriptors.hpp:1152
armnn::LayerType::UnidirectionalSequenceLstm
@ UnidirectionalSequenceLstm
armnn::LstmOptPeepholeParameters::m_CellToOutputWeights
std::shared_ptr< ConstTensorHandle > m_CellToOutputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmParameters.hpp:51
armnn::UnidirectionalSequenceLstmLayer::m_LayerNormParameters
LstmOptLayerNormParameters m_LayerNormParameters
Definition: UnidirectionalSequenceLstmLayer.hpp:24
armnn::LstmOptLayerNormParameters::m_ForgetLayerNormWeights
std::shared_ptr< ConstTensorHandle > m_ForgetLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmParameters.hpp:19
armnn::UnidirectionalSequenceLstmLayer::m_CifgParameters
LstmOptCifgParameters m_CifgParameters
Definition: UnidirectionalSequenceLstmLayer.hpp:21
armnn::LstmDescriptor::m_ProjectionEnabled
bool m_ProjectionEnabled
Enable/disable the projection layer.
Definition: Descriptors.hpp:1150
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:391
armnn::LayerWithParameters< LstmDescriptor >::LayerWithParameters
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const LstmDescriptor &param, const char *name)
Definition: LayerWithParameters.hpp:30
armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:441
armnn::LstmOptPeepholeParameters::m_CellToForgetWeights
std::shared_ptr< ConstTensorHandle > m_CellToForgetWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units].
Definition: LstmParameters.hpp:49
armnn::UnidirectionalSequenceLstmLayer::m_ProjectionParameters
LstmOptProjectionParameters m_ProjectionParameters
Definition: UnidirectionalSequenceLstmLayer.hpp:22