From 6f92c8e9f8bb38dcf5dccf8deeff5112ecd8e37c Mon Sep 17 00:00:00 2001 From: Nikhil Raj Date: Wed, 22 Nov 2023 11:41:15 +0000 Subject: Update Doxygen for 23.11 Signed-off-by: Nikhil Raj Change-Id: I47cd933f5002cb94a73aa97689d7b3d9c93cb849 --- ...mnn_1_1_unidirectional_sequence_lstm_layer.html | 1263 ++++++++++++++++++++ 1 file changed, 1263 insertions(+) create mode 100644 23.11/classarmnn_1_1_unidirectional_sequence_lstm_layer.html (limited to '23.11/classarmnn_1_1_unidirectional_sequence_lstm_layer.html') diff --git a/23.11/classarmnn_1_1_unidirectional_sequence_lstm_layer.html b/23.11/classarmnn_1_1_unidirectional_sequence_lstm_layer.html new file mode 100644 index 0000000000..0e2d32faf6 --- /dev/null +++ b/23.11/classarmnn_1_1_unidirectional_sequence_lstm_layer.html @@ -0,0 +1,1263 @@ + + + + + + + + +Arm NN: UnidirectionalSequenceLstmLayer Class Reference + + + + + + + + + + + + + + + + +
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+ + + + ArmNN + + + +
+
+  23.11 +
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+ + +
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+Public Member Functions | +Public Attributes | +Protected Member Functions | +List of all members
+
+
UnidirectionalSequenceLstmLayer Class Reference
+
+
+ +

This layer represents a LSTM operation. + More...

+ +

#include <UnidirectionalSequenceLstmLayer.hpp>

+
+Inheritance diagram for UnidirectionalSequenceLstmLayer:
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[legend]
+
+Collaboration diagram for UnidirectionalSequenceLstmLayer:
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[legend]
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

virtual std::unique_ptr< IWorkload > CreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the UnidirectionalSequence LSTM type. More...
 
UnidirectionalSequenceLstmLayer * Clone (Graph &graph) const override
 Creates a dynamically-allocated copy of this layer. More...
 
void ValidateTensorShapesFromInputs () override
 Check if the input tensor shape(s) will lead to a valid configuration of UnidirectionalSequenceLstmLayer. More...
 
std::vector< TensorShape > InferOutputShapes (const std::vector< TensorShape > &inputShapes) const override
 By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties. More...
 
void ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this layer. More...
 
- Public Member Functions inherited from LayerWithParameters< LstmDescriptor >
const LstmDescriptor & GetParameters () 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 OutputHandler & GetOutputHandler (unsigned int i=0) const
 
OutputHandler & GetOutputHandler (unsigned int i=0)
 
ShapeInferenceMethod GetShapeInferenceMethod () const
 
bool GetAllowExpandedDims () const
 
const std::vector< InputSlot > & GetInputSlots () const
 
const std::vector< OutputSlot > & GetOutputSlots () const
 
std::vector< InputSlot >::iterator BeginInputSlots ()
 
std::vector< InputSlot >::iterator EndInputSlots ()
 
std::vector< OutputSlot >::iterator BeginOutputSlots ()
 
std::vector< OutputSlot >::iterator EndOutputSlots ()
 
bool IsOutputUnconnected ()
 
void ResetPriority () const
 
LayerPriority GetPriority () const
 
LayerType GetType () const override
 Returns the armnn::LayerType of this layer. More...
 
DataType GetDataType () const
 
const BackendId & GetBackendId () const
 
void SetBackendId (const BackendId &id) override
 Set the backend of the IConnectableLayer. More...
 
virtual void CreateTensorHandles (const TensorHandleFactoryRegistry &registry, const IWorkloadFactory &factory, const bool IsMemoryManaged=true)
 
void VerifyLayerConnections (unsigned int expectedConnections, const CheckLocation &location) const
 
virtual void ReleaseConstantData ()
 
template<typename Op >
void OperateOnConstantTensors (Op op)
 
const char * GetName () const override
 Returns the name of the layer. More...
 
unsigned int GetNumInputSlots () const override
 Returns the number of connectable input slots. More...
 
unsigned int GetNumOutputSlots () const override
 Returns the number of connectable output slots. More...
 
const InputSlot & GetInputSlot (unsigned int index) const override
 Get a const input slot handle by slot index. More...
 
InputSlot & GetInputSlot (unsigned int index) override
 Get the input slot handle by slot index. More...
 
const OutputSlot & GetOutputSlot (unsigned int index=0) const override
 Get the const output slot handle by slot index. More...
 
OutputSlot & GetOutputSlot (unsigned int index=0) override
 Get the output slot handle by slot index. More...
 
void SetGuid (LayerGuid guid)
 
LayerGuid GetGuid () const final
 Returns the unique id of the layer. More...
 
void AddRelatedLayerName (const std::string layerName)
 
const std::list< std::string > & GetRelatedLayerNames ()
 
virtual void Reparent (Graph &dest, std::list< Layer * >::const_iterator iterator)=0
 
void BackendSelectionHint (Optional< BackendId > backend) final
 Provide a hint for the optimizer as to which backend to prefer for this layer. More...
 
Optional< BackendId > GetBackendHint () const
 
void SetShapeInferenceMethod (ShapeInferenceMethod shapeInferenceMethod)
 
void SetAllowExpandedDims (bool allowExpandedDims)
 
template<typename T >
std::shared_ptr< T > GetAdditionalInformation () const
 
void SetAdditionalInfoForObject (const AdditionalInfoObjectPtr &additionalInfo)
 
virtual const BaseDescriptor & GetParameters () const override
 If the layer has a descriptor return it. More...
 
+ + + + + + + + + + + +

+Public Attributes

LstmBasicParameters m_BasicParameters
 
LstmOptCifgParameters m_CifgParameters
 
LstmOptProjectionParameters m_ProjectionParameters
 
LstmOptPeepholeParameters m_PeepholeParameters
 
LstmOptLayerNormParameters m_LayerNormParameters
 
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+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>
LayerType * CloneBase (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< OutputHandler > m_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.

+
18  : LayerWithParameters(3, 3, LayerType::UnidirectionalSequenceLstm, param, name)
+
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 ?
+
85  m_BasicParameters.m_InputToForgetWeights
+
86  : nullptr;
+
87  layer->m_BasicParameters.m_InputToCellWeights = m_BasicParameters.m_InputToCellWeights ?
+
88  m_BasicParameters.m_InputToCellWeights : nullptr;
+
89  layer->m_BasicParameters.m_InputToOutputWeights = m_BasicParameters.m_InputToOutputWeights ?
+
90  m_BasicParameters.m_InputToOutputWeights : nullptr;
+
91  layer->m_BasicParameters.m_RecurrentToForgetWeights = m_BasicParameters.m_RecurrentToForgetWeights ?
+
92  m_BasicParameters.m_RecurrentToForgetWeights : nullptr;
+
93  layer->m_BasicParameters.m_RecurrentToCellWeights = m_BasicParameters.m_RecurrentToCellWeights ?
+
94  m_BasicParameters.m_RecurrentToCellWeights : nullptr;
+
95  layer->m_BasicParameters.m_RecurrentToOutputWeights = m_BasicParameters.m_RecurrentToOutputWeights ?
+
96  m_BasicParameters.m_RecurrentToOutputWeights : nullptr;
+
97  layer->m_BasicParameters.m_ForgetGateBias = m_BasicParameters.m_ForgetGateBias ?
+
98  m_BasicParameters.m_ForgetGateBias : nullptr;
+
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 ?
+
102  m_BasicParameters.m_OutputGateBias : nullptr;
+
103 
+
104  if (!m_Param.m_CifgEnabled)
+
105  {
+
106  layer->m_CifgParameters.m_InputToInputWeights = m_CifgParameters.m_InputToInputWeights ?
+
107  m_CifgParameters.m_InputToInputWeights : nullptr;
+
108  layer->m_CifgParameters.m_RecurrentToInputWeights = m_CifgParameters.m_RecurrentToInputWeights ?
+
109  m_CifgParameters.m_RecurrentToInputWeights : nullptr;
+
110  layer->m_CifgParameters.m_InputGateBias = m_CifgParameters.m_InputGateBias ?
+
111  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  m_ProjectionParameters.m_ProjectionWeights : nullptr;
+
118  layer->m_ProjectionParameters.m_ProjectionBias = m_ProjectionParameters.m_ProjectionBias ?
+
119  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  m_PeepholeParameters.m_CellToInputWeights : nullptr;
+
128  }
+
129  layer->m_PeepholeParameters.m_CellToForgetWeights = m_PeepholeParameters.m_CellToForgetWeights ?
+
130  m_PeepholeParameters.m_CellToForgetWeights : nullptr;
+
131  layer->m_PeepholeParameters.m_CellToOutputWeights = m_PeepholeParameters.m_CellToOutputWeights ?
+
132  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  m_LayerNormParameters.m_InputLayerNormWeights : nullptr;
+
139  layer->m_LayerNormParameters.m_ForgetLayerNormWeights = m_LayerNormParameters.m_ForgetLayerNormWeights ?
+
140  m_LayerNormParameters.m_ForgetLayerNormWeights : nullptr;
+
141  layer->m_LayerNormParameters.m_CellLayerNormWeights = m_LayerNormParameters.m_CellLayerNormWeights ?
+
142  m_LayerNormParameters.m_CellLayerNormWeights : nullptr;
+
143  layer->m_LayerNormParameters.m_OutputLayerNormWeights = m_LayerNormParameters.m_OutputLayerNormWeights ?
+
144  m_LayerNormParameters.m_OutputLayerNormWeights : nullptr;
+
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
+
38  if (!m_Param.m_CifgEnabled)
+
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
+
46  if (m_Param.m_ProjectionEnabled)
+
47  {
+
48  descriptor.m_ProjectionWeights = m_ProjectionParameters.m_ProjectionWeights.get();
+
49  descriptor.m_ProjectionBias = m_ProjectionParameters.m_ProjectionBias.get();
+
50  }
+
51 
+
52  // Peephole parameters
+
53  if (m_Param.m_PeepholeEnabled)
+
54  {
+
55  if (!m_Param.m_CifgEnabled)
+
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
+
64  if(m_Param.m_LayerNormEnabled)
+
65  {
+
66  if (!m_Param.m_CifgEnabled)
+
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
+
348  if (m_BasicParameters.m_InputToForgetWeights != nullptr)
+
349  {
+
350  constTensors.emplace_back(ConstTensor(managedInputToForgetWeights.GetTensorInfo(),
+
351  managedInputToForgetWeights.Map()));
+
352  }
+
353  if (m_BasicParameters.m_InputToCellWeights != nullptr)
+
354  {
+
355  constTensors.emplace_back(ConstTensor(managedInputToCellWeights.GetTensorInfo(),
+
356  managedInputToCellWeights.Map()));
+
357  }
+
358  if (m_BasicParameters.m_InputToOutputWeights != nullptr)
+
359  {
+
360  constTensors.emplace_back(ConstTensor(managedInputToOutputWeights.GetTensorInfo(),
+
361  managedInputToOutputWeights.Map()));
+
362  }
+
363  if (m_BasicParameters.m_RecurrentToForgetWeights != nullptr)
+
364  {
+
365  constTensors.emplace_back(ConstTensor(
+
366  managedRecurrentToForgetWeights.GetTensorInfo(),
+
367  managedRecurrentToForgetWeights.Map()));
+
368  }
+
369  if (m_BasicParameters.m_RecurrentToCellWeights != nullptr)
+
370  {
+
371  constTensors.emplace_back(ConstTensor(
+
372  managedRecurrentToCellWeights.GetTensorInfo(),
+
373  managedRecurrentToCellWeights.Map()));
+
374  }
+
375  if (m_BasicParameters.m_RecurrentToOutputWeights != nullptr)
+
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  {
+
400  if (m_CifgParameters.m_InputToInputWeights != nullptr)
+
401  {
+
402  constTensors.emplace_back(ConstTensor(managedInputToInputWeights.GetTensorInfo(),
+
403  managedInputToInputWeights.Map()));
+
404  }
+
405  if (m_CifgParameters.m_RecurrentToInputWeights != nullptr)
+
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  {
+
423  if (m_PeepholeParameters.m_CellToInputWeights != nullptr)
+
424  {
+
425  constTensors.emplace_back(ConstTensor(managedCellToInputWeights.GetTensorInfo(),
+
426  managedCellToInputWeights.Map()));
+
427  }
+
428  }
+
429  if (m_PeepholeParameters.m_CellToForgetWeights != nullptr)
+
430  {
+
431  constTensors.emplace_back(ConstTensor(managedCellToForgetWeights.GetTensorInfo(),
+
432  managedCellToForgetWeights.Map()));
+
433  }
+
434  if (m_PeepholeParameters.m_CellToOutputWeights != nullptr)
+
435  {
+
436  constTensors.emplace_back(ConstTensor(managedCellToOutputWeights.GetTensorInfo(),
+
437  managedCellToOutputWeights.Map()));
+
438  }
+
439  }
+
440 
+
441  // Add projection parameters
+
442  if (descriptor.m_ProjectionEnabled)
+
443  {
+
444  if (m_ProjectionParameters.m_ProjectionWeights != nullptr)
+
445  {
+
446  constTensors.emplace_back(ConstTensor(managedProjectionWeights.GetTensorInfo(),
+
447  managedProjectionWeights.Map()));
+
448  }
+
449  if (m_ProjectionParameters.m_ProjectionBias != nullptr)
+
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  {
+
461  if (m_LayerNormParameters.m_InputLayerNormWeights != nullptr)
+
462  {
+
463  constTensors.emplace_back(ConstTensor(managedInputLayerNormWeights.GetTensorInfo(),
+
464  managedInputLayerNormWeights.Map()));
+
465  }
+
466  }
+
467  if (m_LayerNormParameters.m_ForgetLayerNormWeights != nullptr)
+
468  {
+
469  constTensors.emplace_back(ConstTensor(managedForgetLayerNormWeights.GetTensorInfo(),
+
470  managedForgetLayerNormWeights.Map()));
+
471  }
+
472  if (m_LayerNormParameters.m_CellLayerNormWeights != nullptr)
+
473  {
+
474  constTensors.emplace_back(ConstTensor(managedCellLayerNormWeights.GetTensorInfo(),
+
475  managedCellLayerNormWeights.Map()));
+
476  }
+
477  if (m_LayerNormParameters.m_OutputLayerNormWeights != nullptr)
+
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.

+
278 {
+
279  // For API stability DO NOT ALTER order and add new members to the end of vector
+
280  return {m_BasicParameters.m_InputToForgetWeights,
+
281  m_BasicParameters.m_InputToCellWeights,
+
282  m_BasicParameters.m_InputToOutputWeights,
+
283  m_BasicParameters.m_RecurrentToForgetWeights,
+
284  m_BasicParameters.m_RecurrentToCellWeights,
+
285  m_BasicParameters.m_RecurrentToOutputWeights,
+
286  m_BasicParameters.m_ForgetGateBias,
+
287  m_BasicParameters.m_CellBias,
+
288  m_BasicParameters.m_OutputGateBias,
+
289 
+
290  // Cifg parameters
+
291  m_CifgParameters.m_InputToInputWeights,
+
292  m_CifgParameters.m_RecurrentToInputWeights,
+
293  m_CifgParameters.m_InputGateBias,
+
294 
+
295  // Projection parameters
+
296  m_ProjectionParameters.m_ProjectionWeights,
+
297  m_ProjectionParameters.m_ProjectionBias,
+
298 
+
299  // Peephole parameters
+
300  m_PeepholeParameters.m_CellToInputWeights,
+
301  m_PeepholeParameters.m_CellToForgetWeights,
+
302  m_PeepholeParameters.m_CellToOutputWeights,
+
303 
+
304  // Layer normalisation parameters
+
305  m_LayerNormParameters.m_InputLayerNormWeights,
+
306  m_LayerNormParameters.m_ForgetLayerNormWeights,
+
307  m_LayerNormParameters.m_CellLayerNormWeights,
+
308  m_LayerNormParameters.m_OutputLayerNormWeights};
+
309 }
+
+

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 {
+
172  VerifyLayerConnections(3, CHECK_LOCATION());
+
173 
+
174  const TensorShape& outputShape = GetOutputSlot(2).GetTensorInfo().GetShape();
+
175 
+
176  VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
+
177 
+
178  auto inferredShapes = InferOutputShapes( {
+
179  GetInputSlot(0).GetTensorInfo().GetShape(),
+
180  GetInputSlot(1).GetTensorInfo().GetShape(),
+
181  GetInputSlot(2).GetTensorInfo().GetShape()
+
182  });
+
183 
+
184  ARMNN_ASSERT(inferredShapes.size() == 1);
+
185 
+
186  // Check if the weights are nullptr
+
187  ARMNN_ASSERT_MSG(m_BasicParameters.m_InputToForgetWeights != nullptr,
+
188  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_InputToForgetWeights should not be null.");
+
189  ARMNN_ASSERT_MSG(m_BasicParameters.m_InputToCellWeights != nullptr,
+
190  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_InputToCellWeights should not be null.");
+
191  ARMNN_ASSERT_MSG(m_BasicParameters.m_InputToOutputWeights != nullptr,
+
192  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_InputToOutputWeights should not be null.");
+
193  ARMNN_ASSERT_MSG(m_BasicParameters.m_RecurrentToForgetWeights != nullptr,
+
194  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_RecurrentToForgetWeights "
+
195  "should not be null.");
+
196  ARMNN_ASSERT_MSG(m_BasicParameters.m_RecurrentToCellWeights != nullptr,
+
197  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_RecurrentToCellWeights should not be null.");
+
198  ARMNN_ASSERT_MSG(m_BasicParameters.m_RecurrentToOutputWeights != nullptr,
+
199  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_RecurrentToOutputWeights "
+
200  "should not be null.");
+
201  ARMNN_ASSERT_MSG(m_BasicParameters.m_ForgetGateBias != nullptr,
+
202  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_ForgetGateBias should not be null.");
+
203  ARMNN_ASSERT_MSG(m_BasicParameters.m_CellBias != nullptr,
+
204  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_CellBias should not be null.");
+
205  ARMNN_ASSERT_MSG(m_BasicParameters.m_OutputGateBias != nullptr,
+
206  "UnidirectionalSequenceLstmLayer: m_BasicParameters.m_OutputGateBias should not be null.");
+
207 
+
208  if (!m_Param.m_CifgEnabled)
+
209  {
+
210  ARMNN_ASSERT_MSG(m_CifgParameters.m_InputToInputWeights != nullptr,
+
211  "UnidirectionalSequenceLstmLayer: m_CifgParameters.m_InputToInputWeights should not be null.");
+
212  ARMNN_ASSERT_MSG(m_CifgParameters.m_RecurrentToInputWeights != nullptr,
+
213  "UnidirectionalSequenceLstmLayer: m_CifgParameters.m_RecurrentToInputWeights "
+
214  "should not be null.");
+
215  ARMNN_ASSERT_MSG(m_CifgParameters.m_InputGateBias != nullptr,
+
216  "UnidirectionalSequenceLstmLayer: m_CifgParameters.m_InputGateBias should not be null.");
+
217  }
+
218  else
+
219  {
+
220  ARMNN_ASSERT_MSG(m_CifgParameters.m_InputToInputWeights == nullptr,
+
221  "UnidirectionalSequenceLstmLayer: m_CifgParameters.m_InputToInputWeights should not have a value "
+
222  "when CIFG is enabled.");
+
223  ARMNN_ASSERT_MSG(m_CifgParameters.m_RecurrentToInputWeights == nullptr,
+
224  "UnidirectionalSequenceLstmLayer: m_CifgParameters.m_RecurrentToInputWeights should not have a value "
+
225  "when CIFG is enabled.");
+
226  ARMNN_ASSERT_MSG(m_CifgParameters.m_InputGateBias == nullptr,
+
227  "UnidirectionalSequenceLstmLayer: m_CifgParameters.m_InputGateBias should not have a value "
+
228  "when CIFG is enabled.");
+
229  }
+
230 
+
231  if (m_Param.m_ProjectionEnabled)
+
232  {
+
233  ARMNN_ASSERT_MSG(m_ProjectionParameters.m_ProjectionWeights != nullptr,
+
234  "UnidirectionalSequenceLstmLayer: m_ProjectionParameters.m_ProjectionWeights "
+
235  "should not be null.");
+
236  }
+
237 
+
238  if (m_Param.m_PeepholeEnabled)
+
239  {
+
240  if (!m_Param.m_CifgEnabled)
+
241  {
+
242  ARMNN_ASSERT_MSG(m_PeepholeParameters.m_CellToInputWeights != nullptr,
+
243  "UnidirectionalSequenceLstmLayer: m_PeepholeParameters.m_CellToInputWeights "
+
244  "should not be null "
+
245  "when Peephole is enabled and CIFG is disabled.");
+
246  }
+
247  ARMNN_ASSERT_MSG(m_PeepholeParameters.m_CellToForgetWeights != nullptr,
+
248  "UnidirectionalSequenceLstmLayer: m_PeepholeParameters.m_CellToForgetWeights "
+
249  "should not be null.");
+
250  ARMNN_ASSERT_MSG(m_PeepholeParameters.m_CellToOutputWeights != nullptr,
+
251  "UnidirectionalSequenceLstmLayer: m_PeepholeParameters.m_CellToOutputWeights "
+
252  "should not be null.");
+
253  }
+
254 
+
255  if (m_Param.m_LayerNormEnabled)
+
256  {
+
257  if(!m_Param.m_CifgEnabled)
+
258  {
+
259  ARMNN_ASSERT_MSG(m_LayerNormParameters.m_InputLayerNormWeights != nullptr,
+
260  "UnidirectionalSequenceLstmLayer: m_LayerNormParameters.m_inputLayerNormWeights "
+
261  "should not be null.");
+
262  }
+
263  ARMNN_ASSERT_MSG(m_LayerNormParameters.m_ForgetLayerNormWeights != nullptr,
+
264  "UnidirectionalSequenceLstmLayer: m_LayerNormParameters.m_forgetLayerNormWeights "
+
265  "should not be null.");
+
266  ARMNN_ASSERT_MSG(m_LayerNormParameters.m_CellLayerNormWeights != nullptr,
+
267  "UnidirectionalSequenceLstmLayer: m_LayerNormParameters.m_cellLayerNormWeights "
+
268  "should not be null.");
+
269  ARMNN_ASSERT_MSG(m_LayerNormParameters.m_OutputLayerNormWeights != nullptr,
+
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

+ +
+
+ + + + +
LstmBasicParameters m_BasicParameters
+
+ +

Definition at line 20 of file UnidirectionalSequenceLstmLayer.hpp.

+ +

Referenced by NetworkImpl::AddUnidirectionalSequenceLstmLayer(), UnidirectionalSequenceLstmLayer::Clone(), UnidirectionalSequenceLstmLayer::CreateWorkload(), UnidirectionalSequenceLstmLayer::ExecuteStrategy(), UnidirectionalSequenceLstmLayer::GetConstantTensorsByRef(), and UnidirectionalSequenceLstmLayer::ValidateTensorShapesFromInputs().

+ +
+
+ +

◆ m_CifgParameters

+ +
+
+ + + + +
LstmOptCifgParameters m_CifgParameters
+
+ +

Definition at line 21 of file UnidirectionalSequenceLstmLayer.hpp.

+ +

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

+ +
+
+ +

◆ m_LayerNormParameters

+ +
+
+ + + + +
LstmOptLayerNormParameters m_LayerNormParameters
+
+ +

Definition at line 24 of file UnidirectionalSequenceLstmLayer.hpp.

+ +

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

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◆ m_PeepholeParameters

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LstmOptPeepholeParameters m_PeepholeParameters
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Definition at line 23 of file UnidirectionalSequenceLstmLayer.hpp.

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

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◆ m_ProjectionParameters

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LstmOptProjectionParameters m_ProjectionParameters
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Definition at line 22 of file UnidirectionalSequenceLstmLayer.hpp.

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

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The documentation for this class was generated from the following files: +
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ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
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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
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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
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armnn::LstmDescriptor::m_TimeMajor
bool m_TimeMajor
Enable/disable time major.
Definition: Descriptors.hpp:1154
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armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92
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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
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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
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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
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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
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CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
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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
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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
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ARMNN_ASSERT_MSG
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
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armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:337
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armnn::LayerWithParameters< LstmDescriptor >::GetParameters
const LstmDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
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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
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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
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armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:332
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armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:592
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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
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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
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armnn::LstmDescriptor::m_PeepholeEnabled
bool m_PeepholeEnabled
Enable/disable peephole.
Definition: Descriptors.hpp:1148
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armnn::LayerWithParameters< LstmDescriptor >::m_Param
LstmDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
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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
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armnn::LayerWithParameters< LstmDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
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armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:504
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armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:287
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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
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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
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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
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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
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armnn::LstmDescriptor::m_CifgEnabled
bool m_CifgEnabled
Enable/disable cifg (coupled input & forget gate).
Definition: Descriptors.hpp:1146
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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
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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
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armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:191
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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
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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
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armnn::LstmDescriptor::m_LayerNormEnabled
bool m_LayerNormEnabled
Enable/disable layer normalization.
Definition: Descriptors.hpp:1152
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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
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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
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armnn::LstmDescriptor::m_ProjectionEnabled
bool m_ProjectionEnabled
Enable/disable the projection layer.
Definition: Descriptors.hpp:1150
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armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:391
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armnn::LayerWithParameters< LstmDescriptor >::LayerWithParameters
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const LstmDescriptor &param, const char *name)
Definition: LayerWithParameters.hpp:30
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armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:441
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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
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