ArmNN
 24.08
QLstmLayer Class Reference

This layer represents a QLstm operation. More...

#include <QLstmLayer.hpp>

Inheritance diagram for QLstmLayer:
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Collaboration diagram for QLstmLayer:
[legend]

Public Member Functions

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the QLstm type. More...
 
QLstmLayerClone (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 QLstmLayer. 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< QLstmDescriptor >
const QLstmDescriptorGetParameters () 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

QLstmBasicParameters m_BasicParameters
 
QLstmOptCifgParameters m_CifgParameters
 
QLstmOptProjectionParameters m_ProjectionParameters
 
QLstmOptPeepholeParameters m_PeepholeParameters
 
QLstmOptLayerNormParameters m_LayerNormParameters
 

Protected Member Functions

 QLstmLayer (const QLstmDescriptor &param, const char *name)
 Constructor to create a QLstmLayer. More...
 
 ~QLstmLayer ()=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< QLstmDescriptor >
 LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const QLstmDescriptor &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< QLstmDescriptor >
using DescriptorType = QLstmDescriptor
 
- 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< QLstmDescriptor >
QLstmDescriptor 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 QLstm operation.

Definition at line 79 of file QLstmLayer.hpp.

Constructor & Destructor Documentation

◆ QLstmLayer()

QLstmLayer ( const QLstmDescriptor param,
const char *  name 
)
protected

Constructor to create a QLstmLayer.

Parameters
[in]nameOptional name for the layer.

Definition at line 17 of file QLstmLayer.cpp.

18  : LayerWithParameters(3, 3, LayerType::QLstm, param, name)
19 {
20 }

References armnn::QLstm.

◆ ~QLstmLayer()

~QLstmLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

QLstmLayer * 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 81 of file QLstmLayer.cpp.

82 {
83  auto layer = CloneBase<QLstmLayer>(graph, m_Param, GetName());
84 
85  layer->m_BasicParameters.m_InputToForgetWeights = m_BasicParameters.m_InputToForgetWeights ?
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  layer->m_PeepholeParameters.m_CellToInputWeights = m_PeepholeParameters.m_CellToInputWeights ?
127  }
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  if (!m_Param.m_CifgEnabled) {
138  layer->m_LayerNormParameters.m_InputLayerNormWeights = m_LayerNormParameters.m_InputLayerNormWeights ?
140  }
141 
142  layer->m_LayerNormParameters.m_ForgetLayerNormWeights = m_LayerNormParameters.m_ForgetLayerNormWeights ?
144  layer->m_LayerNormParameters.m_CellLayerNormWeights = m_LayerNormParameters.m_CellLayerNormWeights ?
146  layer->m_LayerNormParameters.m_OutputLayerNormWeights = m_LayerNormParameters.m_OutputLayerNormWeights ?
148  }
149 
150  return std::move(layer);
151 }

References Layer::GetName(), QLstmLayer::m_BasicParameters, QLstmBasicParameters::m_CellBias, QLstmOptLayerNormParameters::m_CellLayerNormWeights, QLstmOptPeepholeParameters::m_CellToForgetWeights, QLstmOptPeepholeParameters::m_CellToInputWeights, QLstmOptPeepholeParameters::m_CellToOutputWeights, QLstmDescriptor::m_CifgEnabled, QLstmLayer::m_CifgParameters, QLstmBasicParameters::m_ForgetGateBias, QLstmOptLayerNormParameters::m_ForgetLayerNormWeights, QLstmOptCifgParameters::m_InputGateBias, QLstmOptLayerNormParameters::m_InputLayerNormWeights, QLstmBasicParameters::m_InputToCellWeights, QLstmBasicParameters::m_InputToForgetWeights, QLstmOptCifgParameters::m_InputToInputWeights, QLstmBasicParameters::m_InputToOutputWeights, QLstmDescriptor::m_LayerNormEnabled, QLstmLayer::m_LayerNormParameters, QLstmBasicParameters::m_OutputGateBias, QLstmOptLayerNormParameters::m_OutputLayerNormWeights, LayerWithParameters< QLstmDescriptor >::m_Param, QLstmDescriptor::m_PeepholeEnabled, QLstmLayer::m_PeepholeParameters, QLstmOptProjectionParameters::m_ProjectionBias, QLstmDescriptor::m_ProjectionEnabled, QLstmLayer::m_ProjectionParameters, QLstmOptProjectionParameters::m_ProjectionWeights, QLstmBasicParameters::m_RecurrentToCellWeights, QLstmBasicParameters::m_RecurrentToForgetWeights, QLstmOptCifgParameters::m_RecurrentToInputWeights, and QLstmBasicParameters::m_RecurrentToOutputWeights.

◆ CreateWorkload()

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

Makes a workload for the QLstm 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 QLstmLayer.cpp.

23 {
24  QLstmQueueDescriptor 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 
60  descriptor.m_CellToForgetWeights = m_PeepholeParameters.m_CellToForgetWeights.get();
61  descriptor.m_CellToOutputWeights = m_PeepholeParameters.m_CellToOutputWeights.get();
62  }
63 
64  // Layer normalisation parameters
66  {
68  {
69  descriptor.m_InputLayerNormWeights = m_LayerNormParameters.m_InputLayerNormWeights.get();
70  }
71  descriptor.m_ForgetLayerNormWeights = m_LayerNormParameters.m_ForgetLayerNormWeights.get();
72  descriptor.m_CellLayerNormWeights = m_LayerNormParameters.m_CellLayerNormWeights.get();
73  descriptor.m_OutputLayerNormWeights = m_LayerNormParameters.m_OutputLayerNormWeights.get();
74  }
75 
76  SetAdditionalInfo(descriptor);
77 
78  return factory.CreateWorkload(LayerType::QLstm, descriptor, PrepInfoAndDesc(descriptor));
79 }

References IWorkloadFactory::CreateWorkload(), QLstmLayer::m_BasicParameters, QLstmBasicParameters::m_CellBias, QLstmQueueDescriptor::m_CellBias, QLstmOptLayerNormParameters::m_CellLayerNormWeights, QLstmQueueDescriptor::m_CellLayerNormWeights, QLstmOptPeepholeParameters::m_CellToForgetWeights, QLstmQueueDescriptor::m_CellToForgetWeights, QLstmOptPeepholeParameters::m_CellToInputWeights, QLstmQueueDescriptor::m_CellToInputWeights, QLstmOptPeepholeParameters::m_CellToOutputWeights, QLstmQueueDescriptor::m_CellToOutputWeights, QLstmDescriptor::m_CifgEnabled, QLstmLayer::m_CifgParameters, QLstmBasicParameters::m_ForgetGateBias, QLstmQueueDescriptor::m_ForgetGateBias, QLstmOptLayerNormParameters::m_ForgetLayerNormWeights, QLstmQueueDescriptor::m_ForgetLayerNormWeights, QLstmOptCifgParameters::m_InputGateBias, QLstmQueueDescriptor::m_InputGateBias, QLstmOptLayerNormParameters::m_InputLayerNormWeights, QLstmQueueDescriptor::m_InputLayerNormWeights, QLstmBasicParameters::m_InputToCellWeights, QLstmQueueDescriptor::m_InputToCellWeights, QLstmBasicParameters::m_InputToForgetWeights, QLstmQueueDescriptor::m_InputToForgetWeights, QLstmOptCifgParameters::m_InputToInputWeights, QLstmQueueDescriptor::m_InputToInputWeights, QLstmBasicParameters::m_InputToOutputWeights, QLstmQueueDescriptor::m_InputToOutputWeights, QLstmDescriptor::m_LayerNormEnabled, QLstmLayer::m_LayerNormParameters, QLstmBasicParameters::m_OutputGateBias, QLstmQueueDescriptor::m_OutputGateBias, QLstmOptLayerNormParameters::m_OutputLayerNormWeights, QLstmQueueDescriptor::m_OutputLayerNormWeights, LayerWithParameters< QLstmDescriptor >::m_Param, QLstmDescriptor::m_PeepholeEnabled, QLstmLayer::m_PeepholeParameters, QLstmOptProjectionParameters::m_ProjectionBias, QLstmQueueDescriptor::m_ProjectionBias, QLstmDescriptor::m_ProjectionEnabled, QLstmLayer::m_ProjectionParameters, QLstmOptProjectionParameters::m_ProjectionWeights, QLstmQueueDescriptor::m_ProjectionWeights, QLstmBasicParameters::m_RecurrentToCellWeights, QLstmQueueDescriptor::m_RecurrentToCellWeights, QLstmBasicParameters::m_RecurrentToForgetWeights, QLstmQueueDescriptor::m_RecurrentToForgetWeights, QLstmOptCifgParameters::m_RecurrentToInputWeights, QLstmQueueDescriptor::m_RecurrentToInputWeights, QLstmBasicParameters::m_RecurrentToOutputWeights, QLstmQueueDescriptor::m_RecurrentToOutputWeights, LayerWithParameters< QLstmDescriptor >::PrepInfoAndDesc(), armnn::QLstm, and Layer::SetAdditionalInfo().

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy strategy) const
overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 403 of file QLstmLayer.cpp.

404 {
405  std::vector<ConstTensor> constTensors;
406  ManagedConstTensorHandle managedInputToForgetWeights(m_BasicParameters.m_InputToForgetWeights);
407  ManagedConstTensorHandle managedInputToCellWeights(m_BasicParameters.m_InputToCellWeights);
408  ManagedConstTensorHandle managedInputToOutputWeights(m_BasicParameters.m_InputToOutputWeights);
409  ManagedConstTensorHandle managedRecurrentToForgetWeights(m_BasicParameters.m_RecurrentToForgetWeights);
410  ManagedConstTensorHandle managedRecurrentToCellWeights(m_BasicParameters.m_RecurrentToCellWeights);
411  ManagedConstTensorHandle managedRecurrentToOutputWeights(m_BasicParameters.m_RecurrentToOutputWeights);
412  ManagedConstTensorHandle managedForgetGateBias(m_BasicParameters.m_ForgetGateBias);
413  ManagedConstTensorHandle managedCellBias(m_BasicParameters.m_CellBias);
414  ManagedConstTensorHandle managedOutputGateBias(m_BasicParameters.m_OutputGateBias);
415 
416  // Cifg parameters
417  ManagedConstTensorHandle managedInputToInputWeights(m_CifgParameters.m_InputToInputWeights);
418  ManagedConstTensorHandle managedRecurrentToInputWeights(m_CifgParameters.m_RecurrentToInputWeights);
419  ManagedConstTensorHandle managedInputGateBias(m_CifgParameters.m_InputGateBias);
420 
421  // Projection parameters
422  ManagedConstTensorHandle managedProjectionWeights(m_ProjectionParameters.m_ProjectionWeights);
423  ManagedConstTensorHandle managedProjectionBias(m_ProjectionParameters.m_ProjectionBias);
424 
425  // Peephole parameters
426  ManagedConstTensorHandle managedCellToInputWeights(m_PeepholeParameters.m_CellToInputWeights);
427  ManagedConstTensorHandle managedCellToForgetWeights(m_PeepholeParameters.m_CellToForgetWeights);
428  ManagedConstTensorHandle managedCellToOutputWeights(m_PeepholeParameters.m_CellToOutputWeights);
429 
430  // Layer normalisation parameters
431  ManagedConstTensorHandle managedInputLayerNormWeights(m_LayerNormParameters.m_InputLayerNormWeights);
432  ManagedConstTensorHandle managedForgetLayerNormWeights(m_LayerNormParameters.m_ForgetLayerNormWeights);
433  ManagedConstTensorHandle managedCellLayerNormWeights(m_LayerNormParameters.m_CellLayerNormWeights);
434  ManagedConstTensorHandle managedOutputLayerNormWeights(m_LayerNormParameters.m_OutputLayerNormWeights);
435 
436  // First add mandatory/basic parameters
438  {
439  constTensors.emplace_back(ConstTensor(managedInputToForgetWeights.GetTensorInfo(),
440  managedInputToForgetWeights.Map()));
441  }
443  {
444  constTensors.emplace_back(ConstTensor(managedInputToCellWeights.GetTensorInfo(),
445  managedInputToCellWeights.Map()));
446  }
448  {
449  constTensors.emplace_back(ConstTensor(managedInputToOutputWeights.GetTensorInfo(),
450  managedInputToOutputWeights.Map()));
451  }
453  {
454  constTensors.emplace_back(ConstTensor(
455  managedRecurrentToForgetWeights.GetTensorInfo(),
456  managedRecurrentToForgetWeights.Map()));
457  }
459  {
460  constTensors.emplace_back(ConstTensor(
461  managedRecurrentToCellWeights.GetTensorInfo(),
462  managedRecurrentToCellWeights.Map()));
463  }
465  {
466  constTensors.emplace_back(ConstTensor(
467  managedRecurrentToOutputWeights.GetTensorInfo(),
468  managedRecurrentToOutputWeights.Map()));
469  }
470  if (m_BasicParameters.m_ForgetGateBias != nullptr)
471  {
472  constTensors.emplace_back(ConstTensor(managedForgetGateBias.GetTensorInfo(),
473  managedForgetGateBias.Map()));
474  }
475  if (m_BasicParameters.m_CellBias != nullptr)
476  {
477  constTensors.emplace_back(ConstTensor(managedCellBias.GetTensorInfo(),
478  managedCellBias.Map()));
479  }
480  if (m_BasicParameters.m_OutputGateBias != nullptr)
481  {
482  constTensors.emplace_back(ConstTensor(managedOutputGateBias.GetTensorInfo(),
483  managedOutputGateBias.Map()));
484  }
485 
486  // Add cifig parameters
488  {
489  constTensors.emplace_back(ConstTensor(managedInputToInputWeights.GetTensorInfo(),
490  managedInputToInputWeights.Map()));
491  }
493  {
494  constTensors.emplace_back(ConstTensor(
495  managedRecurrentToInputWeights.GetTensorInfo(),
496  managedRecurrentToInputWeights.Map()));
497  }
498  if (m_CifgParameters.m_InputGateBias != nullptr)
499  {
500  constTensors.emplace_back(ConstTensor(managedInputGateBias.GetTensorInfo(),
501  managedInputGateBias.Map()));
502  }
503 
504  // Add peephole parameters
506  {
507  constTensors.emplace_back(ConstTensor(managedCellToInputWeights.GetTensorInfo(),
508  managedCellToInputWeights.Map()));
509  }
511  {
512  constTensors.emplace_back(ConstTensor(managedCellToForgetWeights.GetTensorInfo(),
513  managedCellToForgetWeights.Map()));
514  }
516  {
517  constTensors.emplace_back(ConstTensor(managedCellToOutputWeights.GetTensorInfo(),
518  managedCellToOutputWeights.Map()));
519  }
520 
521  // Add projection parameters
523  {
524  constTensors.emplace_back(ConstTensor(managedProjectionWeights.GetTensorInfo(),
525  managedProjectionWeights.Map()));
526  }
528  {
529  constTensors.emplace_back(ConstTensor(managedProjectionBias.GetTensorInfo(),
530  managedProjectionBias.Map()));
531  }
532 
533  // Add norm parameters
535  {
536  constTensors.emplace_back(ConstTensor(managedInputLayerNormWeights.GetTensorInfo(),
537  managedInputLayerNormWeights.Map()));
538  }
540  {
541  constTensors.emplace_back(ConstTensor(managedForgetLayerNormWeights.GetTensorInfo(),
542  managedForgetLayerNormWeights.Map()));
543  }
545  {
546  constTensors.emplace_back(ConstTensor(managedCellLayerNormWeights.GetTensorInfo(),
547  managedCellLayerNormWeights.Map()));
548  }
550  {
551  constTensors.emplace_back(ConstTensor(managedOutputLayerNormWeights.GetTensorInfo(),
552  managedOutputLayerNormWeights.Map()));
553  }
554  strategy.ExecuteStrategy(this, GetParameters(), constTensors, GetName());
555 }

References IStrategy::ExecuteStrategy(), Layer::GetName(), LayerWithParameters< QLstmDescriptor >::GetParameters(), ManagedConstTensorHandle::GetTensorInfo(), QLstmLayer::m_BasicParameters, QLstmBasicParameters::m_CellBias, QLstmOptLayerNormParameters::m_CellLayerNormWeights, QLstmOptPeepholeParameters::m_CellToForgetWeights, QLstmOptPeepholeParameters::m_CellToInputWeights, QLstmOptPeepholeParameters::m_CellToOutputWeights, QLstmLayer::m_CifgParameters, QLstmBasicParameters::m_ForgetGateBias, QLstmOptLayerNormParameters::m_ForgetLayerNormWeights, QLstmOptCifgParameters::m_InputGateBias, QLstmOptLayerNormParameters::m_InputLayerNormWeights, QLstmBasicParameters::m_InputToCellWeights, QLstmBasicParameters::m_InputToForgetWeights, QLstmOptCifgParameters::m_InputToInputWeights, QLstmBasicParameters::m_InputToOutputWeights, QLstmLayer::m_LayerNormParameters, QLstmBasicParameters::m_OutputGateBias, QLstmOptLayerNormParameters::m_OutputLayerNormWeights, QLstmLayer::m_PeepholeParameters, QLstmOptProjectionParameters::m_ProjectionBias, QLstmLayer::m_ProjectionParameters, QLstmOptProjectionParameters::m_ProjectionWeights, QLstmBasicParameters::m_RecurrentToCellWeights, QLstmBasicParameters::m_RecurrentToForgetWeights, QLstmOptCifgParameters::m_RecurrentToInputWeights, QLstmBasicParameters::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 368 of file QLstmLayer.cpp.

References QLstmLayer::m_BasicParameters, QLstmBasicParameters::m_CellBias, QLstmOptLayerNormParameters::m_CellLayerNormWeights, QLstmOptPeepholeParameters::m_CellToForgetWeights, QLstmOptPeepholeParameters::m_CellToInputWeights, QLstmOptPeepholeParameters::m_CellToOutputWeights, QLstmLayer::m_CifgParameters, QLstmBasicParameters::m_ForgetGateBias, QLstmOptLayerNormParameters::m_ForgetLayerNormWeights, QLstmOptCifgParameters::m_InputGateBias, QLstmOptLayerNormParameters::m_InputLayerNormWeights, QLstmBasicParameters::m_InputToCellWeights, QLstmBasicParameters::m_InputToForgetWeights, QLstmOptCifgParameters::m_InputToInputWeights, QLstmBasicParameters::m_InputToOutputWeights, QLstmLayer::m_LayerNormParameters, QLstmBasicParameters::m_OutputGateBias, QLstmOptLayerNormParameters::m_OutputLayerNormWeights, QLstmLayer::m_PeepholeParameters, QLstmOptProjectionParameters::m_ProjectionBias, QLstmLayer::m_ProjectionParameters, QLstmOptProjectionParameters::m_ProjectionWeights, QLstmBasicParameters::m_RecurrentToCellWeights, QLstmBasicParameters::m_RecurrentToForgetWeights, QLstmOptCifgParameters::m_RecurrentToInputWeights, and QLstmBasicParameters::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 153 of file QLstmLayer.cpp.

154 {
155  if (inputShapes.size() != 3)
156  {
157  throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
158  "\" - should be \"3\".");
159  }
160 
161  // Get input values for validation
162  unsigned int batchSize = inputShapes[0][0];
163  unsigned int outputSize = inputShapes[1][1];
164  unsigned int numUnits = inputShapes[2][1];
165 
166  std::vector<TensorShape> outShapes;
167  outShapes.push_back(TensorShape({ batchSize, outputSize })); // outputStateOut
168  outShapes.push_back(TensorShape({ batchSize, numUnits })); // cellStateOut
169  outShapes.push_back(TensorShape({ batchSize, outputSize })); // output
170 
171  return outShapes;
172 }

Referenced by QLstmLayer::ValidateTensorShapesFromInputs().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

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

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

Implements Layer.

Definition at line 174 of file QLstmLayer.cpp.

175 {
177 
178  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
179 
181 
182  auto inferredShapes = InferOutputShapes(
183  {
184  GetInputSlot(0).GetTensorInfo().GetShape(), // input
185  GetInputSlot(1).GetTensorInfo().GetShape(), // previousOutputIn
186  GetInputSlot(2).GetTensorInfo().GetShape() // previousCellStateIn
187  });
188 
189  if (inferredShapes.size() != 3)
190  {
191  throw armnn::LayerValidationException("inferredShapes has "
192  + std::to_string(inferredShapes.size()) +
193  " element(s) - should only have 3.");
194  }
195 
196  // Check if the weights are nullptr for basic params
198  {
199  throw armnn::LayerValidationException("QLstmLayer: "
200  "m_BasicParameters.m_InputToForgetWeights should not be null.");
201  }
202 
204  {
205  throw armnn::LayerValidationException("QLstmLayer: "
206  "m_BasicParameters.m_InputToCellWeights should not be null.");
207  }
208 
210  {
211  throw armnn::LayerValidationException("QLstmLayer: "
212  "m_BasicParameters.m_InputToOutputWeights should not be null.");
213  }
214 
216  {
217  throw armnn::LayerValidationException("QLstmLayer: "
218  "m_BasicParameters.m_RecurrentToForgetWeights should not be null.");
219  }
220 
222  {
223  throw armnn::LayerValidationException("QLstmLayer: "
224  "m_BasicParameters.m_RecurrentToCellWeights should not be null.");
225  }
226 
228  {
229  throw armnn::LayerValidationException("QLstmLayer: "
230  "m_BasicParameters.m_RecurrentToOutputWeights should not be null.");
231  }
232 
234  {
235  throw armnn::LayerValidationException("QLstmLayer: "
236  "m_BasicParameters.m_ForgetGateBias should not be null.");
237  }
238 
240  {
241  throw armnn::LayerValidationException("QLstmLayer: "
242  "m_BasicParameters.m_CellBias should not be null.");
243  }
244 
246  {
247  throw armnn::LayerValidationException("QLstmLayer: "
248  "m_BasicParameters.m_OutputGateBias should not be null.");
249  }
250 
251  if (!m_Param.m_CifgEnabled)
252  {
254  {
255  throw armnn::LayerValidationException("QLstmLayer: "
256  "m_CifgParameters.m_InputToInputWeights should not be null.");
257  }
258 
260  {
261  throw armnn::LayerValidationException("QLstmLayer: "
262  "m_CifgParameters.m_RecurrentToInputWeights should not be null.");
263  }
264 
266  {
267  throw armnn::LayerValidationException("QLstmLayer: "
268  "m_CifgParameters.m_InputGateBias should not be null.");
269  }
270 
271  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "QLstmLayer");
272  }
273  else
274  {
276  {
277  throw armnn::LayerValidationException("QLstmLayer: "
278  "m_CifgParameters.m_InputToInputWeights "
279  "should not have a value when CIFG is enabled.");
280  }
281 
283  {
284  throw armnn::LayerValidationException("QLstmLayer: "
285  "m_CifgParameters.m_RecurrentToInputWeights "
286  "should not have a value when CIFG is enabled.");
287  }
288 
290  {
291  throw armnn::LayerValidationException("QLstmLayer: "
292  "m_CifgParameters.m_InputGateBias "
293  "should not have a value when CIFG is enabled.");
294  }
295 
296  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "QLstmLayer");
297  }
298 
300  {
302  {
303  throw armnn::LayerValidationException("QLstmLayer: "
304  "m_ProjectionParameters.m_ProjectionWeights should not be null.");
305  }
306  }
307 
309  {
310  if (!m_Param.m_CifgEnabled) {
312  {
313  throw armnn::LayerValidationException("QLstmLayer: "
314  "m_PeepholeParameters.m_CellToInputWeights should not be null "
315  "when Peephole is enabled and CIFG is disabled.");
316  }
317  }
318 
320  {
321  throw armnn::LayerValidationException("QLstmLayer: "
322  "m_PeepholeParameters.m_CellToForgetWeights should not be null.");
323  }
324 
326  {
327  throw armnn::LayerValidationException("QLstmLayer: "
328  "m_PeepholeParameters.m_CellToOutputWeights should not be null.");
329  }
330  }
331 
333  GetOutputSlot(1).GetTensorInfo().GetShape(), inferredShapes[1], m_ShapeInferenceMethod, "QLstmLayer", 1);
335  GetOutputSlot(2).GetTensorInfo().GetShape(), inferredShapes[2], m_ShapeInferenceMethod, "QLstmLayer", 2);
336 
338  {
339  if (!m_Param.m_CifgEnabled)
340  {
342  {
343  throw armnn::LayerValidationException("QLstmLayer: m_LayerNormParameters.m_InputLayerNormWeights "
344  "should not be null.");
345  }
346  }
347 
349  {
350  throw armnn::LayerValidationException("QLstmLayer: "
351  "m_LayerNormParameters.m_ForgetLayerNormWeights should not be null.");
352  }
353 
355  {
356  throw armnn::LayerValidationException("QLstmLayer: "
357  "m_LayerNormParameters.m_CellLayerNormWeights should not be null.");
358  }
359 
361  {
362  throw armnn::LayerValidationException("QLstmLayer: "
363  "m_LayerNormParameters.m_UutputLayerNormWeights should not be null.");
364  }
365  }
366 }

References CHECK_LOCATION, Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), armnn::GetTensorInfo(), InputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), QLstmLayer::InferOutputShapes(), QLstmLayer::m_BasicParameters, QLstmBasicParameters::m_CellBias, QLstmOptPeepholeParameters::m_CellToForgetWeights, QLstmOptPeepholeParameters::m_CellToInputWeights, QLstmOptPeepholeParameters::m_CellToOutputWeights, QLstmDescriptor::m_CifgEnabled, QLstmLayer::m_CifgParameters, QLstmBasicParameters::m_ForgetGateBias, QLstmOptCifgParameters::m_InputGateBias, QLstmBasicParameters::m_InputToCellWeights, QLstmBasicParameters::m_InputToForgetWeights, QLstmOptCifgParameters::m_InputToInputWeights, QLstmBasicParameters::m_InputToOutputWeights, QLstmBasicParameters::m_OutputGateBias, LayerWithParameters< QLstmDescriptor >::m_Param, QLstmDescriptor::m_PeepholeEnabled, QLstmLayer::m_PeepholeParameters, QLstmDescriptor::m_ProjectionEnabled, QLstmLayer::m_ProjectionParameters, QLstmOptProjectionParameters::m_ProjectionWeights, QLstmBasicParameters::m_RecurrentToCellWeights, QLstmBasicParameters::m_RecurrentToForgetWeights, QLstmOptCifgParameters::m_RecurrentToInputWeights, QLstmBasicParameters::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::QLstmLayer::m_CifgParameters
QLstmOptCifgParameters m_CifgParameters
Definition: QLstmLayer.hpp:84
armnn::QLstmOptPeepholeParameters::m_CellToForgetWeights
std::shared_ptr< ConstTensorHandle > m_CellToForgetWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units] (QSymmS16).
Definition: QLstmLayer.hpp:51
armnn::QLstmBasicParameters::m_ForgetGateBias
std::shared_ptr< ConstTensorHandle > m_ForgetGateBias
A unique pointer to represent 1D bias tensor with dimensions [num_units] (int32).
Definition: QLstmLayer.hpp:31
armnn::QLstmDescriptor::m_ProjectionEnabled
bool m_ProjectionEnabled
Enable/disable the projection layer.
Definition: Descriptors.hpp:1422
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:100
armnn::QLstmOptLayerNormParameters::m_ForgetLayerNormWeights
std::shared_ptr< ConstTensorHandle > m_ForgetLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units] (QSymmS16).
Definition: QLstmLayer.hpp:71
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
armnn::QLstmOptPeepholeParameters::m_CellToOutputWeights
std::shared_ptr< ConstTensorHandle > m_CellToOutputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units] (QSymmS16).
Definition: QLstmLayer.hpp:53
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:457
armnn::QLstmOptLayerNormParameters::m_OutputLayerNormWeights
std::shared_ptr< ConstTensorHandle > m_OutputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units] (QSymmS16).
Definition: QLstmLayer.hpp:75
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::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< QLstmDescriptor >::GetParameters
const QLstmDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
armnn::QLstmOptProjectionParameters::m_ProjectionWeights
std::shared_ptr< ConstTensorHandle > m_ProjectionWeights
A unique pointer to represent 2D weights tensor with dimensions [output_size, num_units] (QSymmS8).
Definition: QLstmLayer.hpp:41
armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:332
armnn::QLstmOptLayerNormParameters::m_CellLayerNormWeights
std::shared_ptr< ConstTensorHandle > m_CellLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units] (QSymmS16).
Definition: QLstmLayer.hpp:73
armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:614
armnn::LayerWithParameters< QLstmDescriptor >::m_Param
QLstmDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::QLstmOptPeepholeParameters::m_CellToInputWeights
std::shared_ptr< ConstTensorHandle > m_CellToInputWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units] (QSymmS16).
Definition: QLstmLayer.hpp:49
armnn::LayerWithParameters< QLstmDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
armnn::LayerValidationException
Definition: Exceptions.hpp:105
armnn::QLstmOptCifgParameters::m_RecurrentToInputWeights
std::shared_ptr< ConstTensorHandle > m_RecurrentToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units] (QSymmS8).
Definition: QLstmLayer.hpp:61
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:526
armnn::GetTensorInfo
const TensorInfo & GetTensorInfo(const ITensorHandle *tensorHandle)
float32 helpers
Definition: RefWorkloadUtils.hpp:33
armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:303
armnn::Exception
Base class for all ArmNN exceptions so that users can filter to just those.
Definition: Exceptions.hpp:46
armnn::QLstmOptCifgParameters::m_InputGateBias
std::shared_ptr< ConstTensorHandle > m_InputGateBias
A unique pointer to represent 1D weights tensor with dimensions [num_units] (int32).
Definition: QLstmLayer.hpp:63
armnn::QLstmOptLayerNormParameters::m_InputLayerNormWeights
std::shared_ptr< ConstTensorHandle > m_InputLayerNormWeights
A unique pointer to represent 1D weights tensor with dimensions [num_units] (QSymmS16).
Definition: QLstmLayer.hpp:69
armnn::QLstmLayer::m_LayerNormParameters
QLstmOptLayerNormParameters m_LayerNormParameters
Definition: QLstmLayer.hpp:87
armnn::QLstmBasicParameters::m_RecurrentToOutputWeights
std::shared_ptr< ConstTensorHandle > m_RecurrentToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [num_units, outputSize] (QSymmS8).
Definition: QLstmLayer.hpp:28
armnn::QLstmLayer::m_PeepholeParameters
QLstmOptPeepholeParameters m_PeepholeParameters
Definition: QLstmLayer.hpp:86
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn::QLstmBasicParameters::m_CellBias
std::shared_ptr< ConstTensorHandle > m_CellBias
A unique pointer to represent 1D bias tensor with dimensions [num_units] (int32).
Definition: QLstmLayer.hpp:33
armnn::QLstmBasicParameters::m_OutputGateBias
std::shared_ptr< ConstTensorHandle > m_OutputGateBias
A unique pointer to represent 1D bias tensor with dimensions [num_units] (int32).
Definition: QLstmLayer.hpp:35
armnn::QLstmBasicParameters::m_RecurrentToCellWeights
std::shared_ptr< ConstTensorHandle > m_RecurrentToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [num_units, outputSize] (QSymmS8).
Definition: QLstmLayer.hpp:26
armnn::QLstmDescriptor::m_CifgEnabled
bool m_CifgEnabled
Enable/disable CIFG (coupled input & forget gate).
Definition: Descriptors.hpp:1418
armnn::QLstmOptCifgParameters::m_InputToInputWeights
std::shared_ptr< ConstTensorHandle > m_InputToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units] (QSymmS8).
Definition: QLstmLayer.hpp:59
armnn::QLstmLayer::m_ProjectionParameters
QLstmOptProjectionParameters m_ProjectionParameters
Definition: QLstmLayer.hpp:85
armnn::QLstmLayer::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: QLstmLayer.cpp:153
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:410
armnn::QLstmBasicParameters::m_RecurrentToForgetWeights
std::shared_ptr< ConstTensorHandle > m_RecurrentToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [num_units, outputSize] (QSymmS8).
Definition: QLstmLayer.hpp:24
armnn::QLstmDescriptor::m_LayerNormEnabled
bool m_LayerNormEnabled
Enable/disable layer normalization.
Definition: Descriptors.hpp:1424
armnn::QLstmOptProjectionParameters::m_ProjectionBias
std::shared_ptr< ConstTensorHandle > m_ProjectionBias
A unique pointer to represent 1D weights tensor with dimensions [output_size] (int32).
Definition: QLstmLayer.hpp:43
armnn::LayerWithParameters< QLstmDescriptor >::LayerWithParameters
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const QLstmDescriptor &param, const char *name)
Definition: LayerWithParameters.hpp:30
armnn::QLstmLayer::m_BasicParameters
QLstmBasicParameters m_BasicParameters
Definition: QLstmLayer.hpp:83
armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:441
armnn::QLstmBasicParameters::m_InputToOutputWeights
std::shared_ptr< ConstTensorHandle > m_InputToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [num_units, inputSize] (QSymmS8).
Definition: QLstmLayer.hpp:21
armnn::QLstmDescriptor::m_PeepholeEnabled
bool m_PeepholeEnabled
Enable/disable peephole.
Definition: Descriptors.hpp:1420
armnn::LayerType::QLstm
@ QLstm
armnn::QLstmBasicParameters::m_InputToForgetWeights
std::shared_ptr< ConstTensorHandle > m_InputToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [num_units, inputSize] (QSymmS8).
Definition: QLstmLayer.hpp:17
armnn::QLstmBasicParameters::m_InputToCellWeights
std::shared_ptr< ConstTensorHandle > m_InputToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [num_units, inputSize] (QSymmS8).
Definition: QLstmLayer.hpp:19