ArmNN
 24.02
QuantizedLstmLayer Class Reference

This layer represents a QuantizedLstm operation. More...

#include <QuantizedLstmLayer.hpp>

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

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the QuantizedLstm type. More...
 
QuantizedLstmLayerClone (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 QuantizedLstmLayer. 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 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 SerializeLayerParameters (ParameterStringifyFunction &fn) const
 Helper to serialize the layer parameters to string. More...
 
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

QuantizedLstmParameters m_QuantizedLstmParameters
 

Protected Member Functions

 QuantizedLstmLayer (const char *name)
 Constructor to create a QuantizedLstmLayer. More...
 
 ~QuantizedLstmLayer ()=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 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 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 Layer
AdditionalInfoObjectPtr m_AdditionalInfoObject
 
std::vector< OutputHandlerm_OutputHandlers
 
ShapeInferenceMethod m_ShapeInferenceMethod
 

Detailed Description

This layer represents a QuantizedLstm operation.

Definition at line 45 of file QuantizedLstmLayer.hpp.

Constructor & Destructor Documentation

◆ QuantizedLstmLayer()

QuantizedLstmLayer ( const char *  name)
protected

Constructor to create a QuantizedLstmLayer.

Parameters
[in]nameOptional name for the layer.

Definition at line 17 of file QuantizedLstmLayer.cpp.

18  : Layer(3, 2, LayerType::QuantizedLstm, name)
19 {
20 }

References armnn::QuantizedLstm.

◆ ~QuantizedLstmLayer()

~QuantizedLstmLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

QuantizedLstmLayer * 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 47 of file QuantizedLstmLayer.cpp.

48 {
49  auto layer = CloneBase<QuantizedLstmLayer>(graph, GetName());
50 
51  layer->m_QuantizedLstmParameters.m_InputToInputWeights = m_QuantizedLstmParameters.m_InputToInputWeights ?
53  layer->m_QuantizedLstmParameters.m_InputToForgetWeights = m_QuantizedLstmParameters.m_InputToForgetWeights ?
55  layer->m_QuantizedLstmParameters.m_InputToCellWeights = m_QuantizedLstmParameters.m_InputToCellWeights ?
57  layer->m_QuantizedLstmParameters.m_InputToOutputWeights = m_QuantizedLstmParameters.m_InputToOutputWeights ?
59 
60  layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights = m_QuantizedLstmParameters.m_RecurrentToInputWeights ?
62  layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights = m_QuantizedLstmParameters.m_RecurrentToForgetWeights
64  layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights = m_QuantizedLstmParameters.m_RecurrentToCellWeights ?
66  layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights = m_QuantizedLstmParameters.m_RecurrentToOutputWeights
68 
69  layer->m_QuantizedLstmParameters.m_InputGateBias = m_QuantizedLstmParameters.m_InputGateBias ?
71  layer->m_QuantizedLstmParameters.m_ForgetGateBias = m_QuantizedLstmParameters.m_ForgetGateBias ?
73  layer->m_QuantizedLstmParameters.m_CellBias = m_QuantizedLstmParameters.m_CellBias ?
75  layer->m_QuantizedLstmParameters.m_OutputGateBias = m_QuantizedLstmParameters.m_OutputGateBias ?
77 
78  return std::move(layer);
79 }

References Layer::GetName(), QuantizedLstmParameters::m_CellBias, QuantizedLstmParameters::m_ForgetGateBias, QuantizedLstmParameters::m_InputGateBias, QuantizedLstmParameters::m_InputToCellWeights, QuantizedLstmParameters::m_InputToForgetWeights, QuantizedLstmParameters::m_InputToInputWeights, QuantizedLstmParameters::m_InputToOutputWeights, QuantizedLstmParameters::m_OutputGateBias, QuantizedLstmLayer::m_QuantizedLstmParameters, QuantizedLstmParameters::m_RecurrentToCellWeights, QuantizedLstmParameters::m_RecurrentToForgetWeights, QuantizedLstmParameters::m_RecurrentToInputWeights, and QuantizedLstmParameters::m_RecurrentToOutputWeights.

◆ CreateWorkload()

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

Makes a workload for the QuantizedLstm 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 QuantizedLstmLayer.cpp.

23 {
24  QuantizedLstmQueueDescriptor descriptor;
25 
26  // QuantizedLstmLayer parameters - there are no optional params
27  descriptor.m_InputToInputWeights = m_QuantizedLstmParameters.m_InputToInputWeights.get();
28  descriptor.m_InputToForgetWeights = m_QuantizedLstmParameters.m_InputToForgetWeights.get();
29  descriptor.m_InputToCellWeights = m_QuantizedLstmParameters.m_InputToCellWeights.get();
30  descriptor.m_InputToOutputWeights = m_QuantizedLstmParameters.m_InputToOutputWeights.get();
31 
32  descriptor.m_RecurrentToInputWeights = m_QuantizedLstmParameters.m_RecurrentToInputWeights.get();
33  descriptor.m_RecurrentToForgetWeights = m_QuantizedLstmParameters.m_RecurrentToForgetWeights.get();
34  descriptor.m_RecurrentToCellWeights = m_QuantizedLstmParameters.m_RecurrentToCellWeights.get();
35  descriptor.m_RecurrentToOutputWeights = m_QuantizedLstmParameters.m_RecurrentToOutputWeights.get();
36 
37  descriptor.m_InputGateBias = m_QuantizedLstmParameters.m_InputGateBias.get();
38  descriptor.m_ForgetGateBias = m_QuantizedLstmParameters.m_ForgetGateBias.get();
39  descriptor.m_CellBias = m_QuantizedLstmParameters.m_CellBias.get();
40  descriptor.m_OutputGateBias = m_QuantizedLstmParameters.m_OutputGateBias.get();
41 
42  SetAdditionalInfo(descriptor);
43 
44  return factory.CreateWorkload(LayerType::QuantizedLstm, descriptor, PrepInfoAndDesc(descriptor));
45 }

References IWorkloadFactory::CreateWorkload(), QuantizedLstmParameters::m_CellBias, QuantizedLstmQueueDescriptor::m_CellBias, QuantizedLstmParameters::m_ForgetGateBias, QuantizedLstmQueueDescriptor::m_ForgetGateBias, QuantizedLstmParameters::m_InputGateBias, QuantizedLstmQueueDescriptor::m_InputGateBias, QuantizedLstmParameters::m_InputToCellWeights, QuantizedLstmQueueDescriptor::m_InputToCellWeights, QuantizedLstmParameters::m_InputToForgetWeights, QuantizedLstmQueueDescriptor::m_InputToForgetWeights, QuantizedLstmParameters::m_InputToInputWeights, QuantizedLstmQueueDescriptor::m_InputToInputWeights, QuantizedLstmParameters::m_InputToOutputWeights, QuantizedLstmQueueDescriptor::m_InputToOutputWeights, QuantizedLstmParameters::m_OutputGateBias, QuantizedLstmQueueDescriptor::m_OutputGateBias, QuantizedLstmLayer::m_QuantizedLstmParameters, QuantizedLstmParameters::m_RecurrentToCellWeights, QuantizedLstmQueueDescriptor::m_RecurrentToCellWeights, QuantizedLstmParameters::m_RecurrentToForgetWeights, QuantizedLstmQueueDescriptor::m_RecurrentToForgetWeights, QuantizedLstmParameters::m_RecurrentToInputWeights, QuantizedLstmQueueDescriptor::m_RecurrentToInputWeights, QuantizedLstmParameters::m_RecurrentToOutputWeights, QuantizedLstmQueueDescriptor::m_RecurrentToOutputWeights, Layer::PrepInfoAndDesc(), armnn::QuantizedLstm, and Layer::SetAdditionalInfo().

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy strategy) const
overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 173 of file QuantizedLstmLayer.cpp.

174 {
175  std::vector<ConstTensor> constTensors;
176 
177  ManagedConstTensorHandle managedInputToInputWeights(m_QuantizedLstmParameters.m_InputToInputWeights);
178  ManagedConstTensorHandle managedInputToForgetWeights(m_QuantizedLstmParameters.m_InputToForgetWeights);
179  ManagedConstTensorHandle managedInputToCellWeights(m_QuantizedLstmParameters.m_InputToCellWeights);
180  ManagedConstTensorHandle managedInputToOutputWeights(m_QuantizedLstmParameters.m_InputToOutputWeights);
181 
182  ManagedConstTensorHandle managedRecurrentToInputWeights(m_QuantizedLstmParameters.m_RecurrentToInputWeights);
183  ManagedConstTensorHandle managedRecurrentToForgetWeights(m_QuantizedLstmParameters.m_RecurrentToForgetWeights);
184  ManagedConstTensorHandle managedRecurrentToCellWeights(m_QuantizedLstmParameters.m_RecurrentToCellWeights);
185  ManagedConstTensorHandle managedRecurrentToOutputWeights(m_QuantizedLstmParameters.m_RecurrentToOutputWeights);
186 
187  ManagedConstTensorHandle managedInputGateBias(m_QuantizedLstmParameters.m_InputGateBias);
188  ManagedConstTensorHandle managedForgetGateBias(m_QuantizedLstmParameters.m_ForgetGateBias);
189  ManagedConstTensorHandle managedCellBias(m_QuantizedLstmParameters.m_CellBias);
190  ManagedConstTensorHandle managedOutputGateBias(m_QuantizedLstmParameters.m_OutputGateBias);
191 
192  // InputToX weight tensors
194  {
195  constTensors.emplace_back(ConstTensor(managedInputToInputWeights.GetTensorInfo(),
196  managedInputToInputWeights.Map()));
197  }
198 
200  {
201  constTensors.emplace_back(ConstTensor(managedInputToForgetWeights.GetTensorInfo(),
202  managedInputToForgetWeights.Map()));
203  }
204 
206  {
207  constTensors.emplace_back(ConstTensor(managedInputToCellWeights.GetTensorInfo(),
208  managedInputToCellWeights.Map()));
209  }
210 
212  {
213  constTensors.emplace_back(ConstTensor(managedInputToOutputWeights.GetTensorInfo(),
214  managedInputToOutputWeights.Map()));
215  }
216 
217  // RecurrentToX weight tensors
219  {
220  constTensors.emplace_back(ConstTensor(
221  managedRecurrentToInputWeights.GetTensorInfo(),
222  managedRecurrentToInputWeights.Map()));
223  }
224 
226  {
227  constTensors.emplace_back(ConstTensor(
228  managedRecurrentToForgetWeights.GetTensorInfo(),
229  managedRecurrentToForgetWeights.Map()));
230  }
231 
233  {
234  constTensors.emplace_back(ConstTensor(
235  managedRecurrentToCellWeights.GetTensorInfo(),
236  managedRecurrentToCellWeights.Map()));
237  }
238 
240  {
241  constTensors.emplace_back(ConstTensor(
242  managedRecurrentToOutputWeights.GetTensorInfo(),
243  managedRecurrentToOutputWeights.Map()));
244  }
245 
246  // Bias tensors
248  {
249  constTensors.emplace_back(ConstTensor(managedInputGateBias.GetTensorInfo(),
250  managedInputGateBias.Map()));
251  }
252 
254  {
255  constTensors.emplace_back(ConstTensor(managedForgetGateBias.GetTensorInfo(),
256  managedForgetGateBias.Map()));
257  }
258 
259  if (m_QuantizedLstmParameters.m_CellBias != nullptr)
260  {
261  constTensors.emplace_back(ConstTensor(managedCellBias.GetTensorInfo(),
262  managedCellBias.Map()));
263  }
264 
266  {
267  constTensors.emplace_back(ConstTensor(managedOutputGateBias.GetTensorInfo(),
268  managedOutputGateBias.Map()));
269  }
270 
271 
272  strategy.ExecuteStrategy(this, BaseDescriptor(), constTensors, GetName());
273 }

References IStrategy::ExecuteStrategy(), Layer::GetName(), ManagedConstTensorHandle::GetTensorInfo(), QuantizedLstmParameters::m_CellBias, QuantizedLstmParameters::m_ForgetGateBias, QuantizedLstmParameters::m_InputGateBias, QuantizedLstmParameters::m_InputToCellWeights, QuantizedLstmParameters::m_InputToForgetWeights, QuantizedLstmParameters::m_InputToInputWeights, QuantizedLstmParameters::m_InputToOutputWeights, QuantizedLstmParameters::m_OutputGateBias, QuantizedLstmLayer::m_QuantizedLstmParameters, QuantizedLstmParameters::m_RecurrentToCellWeights, QuantizedLstmParameters::m_RecurrentToForgetWeights, QuantizedLstmParameters::m_RecurrentToInputWeights, QuantizedLstmParameters::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 151 of file QuantizedLstmLayer.cpp.

References QuantizedLstmParameters::m_CellBias, QuantizedLstmParameters::m_ForgetGateBias, QuantizedLstmParameters::m_InputGateBias, QuantizedLstmParameters::m_InputToCellWeights, QuantizedLstmParameters::m_InputToForgetWeights, QuantizedLstmParameters::m_InputToInputWeights, QuantizedLstmParameters::m_InputToOutputWeights, QuantizedLstmParameters::m_OutputGateBias, QuantizedLstmLayer::m_QuantizedLstmParameters, QuantizedLstmParameters::m_RecurrentToCellWeights, QuantizedLstmParameters::m_RecurrentToForgetWeights, QuantizedLstmParameters::m_RecurrentToInputWeights, and QuantizedLstmParameters::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 81 of file QuantizedLstmLayer.cpp.

82 {
83  ARMNN_ASSERT(inputShapes.size() == 3);
84 
85  // Get input values for validation
86  unsigned int numBatches = inputShapes[0][0];
87  unsigned int outputSize = inputShapes[1][1];
88 
89  std::vector<TensorShape> outShapes;
90  outShapes.push_back(TensorShape({numBatches, outputSize})); // cellStateOut
91  outShapes.push_back(TensorShape({numBatches, outputSize})); // output
92 
93  return outShapes;
94 }

References ARMNN_ASSERT.

Referenced by QuantizedLstmLayer::ValidateTensorShapesFromInputs().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

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

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

Implements Layer.

Definition at line 96 of file QuantizedLstmLayer.cpp.

97 {
99 
100  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
101 
103 
104  auto inferredShapes = InferOutputShapes(
105  {
106  GetInputSlot(0).GetTensorInfo().GetShape(), // input
107  GetInputSlot(1).GetTensorInfo().GetShape(), // previousCellStateIn
108  GetInputSlot(2).GetTensorInfo().GetShape() // previousOutputIn
109  });
110 
111  ARMNN_ASSERT(inferredShapes.size() == 2);
112 
113  // Check weights and bias for nullptr
115  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToInputWeights should not be null.");
117  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToForgetWeights should not be null.");
119  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToCellWeights should not be null.");
121  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToOutputWeights should not be null.");
122 
124  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToInputWeights should not be null.");
126  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToForgetWeights should not be null.");
128  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToCellWeights should not be null.");
130  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToOutputWeights should not be null.");
131 
133  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputGateBias should not be null.");
135  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_ForgetGateBias should not be null.");
137  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_CellBias should not be null.");
139  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_OutputGateBias should not be null.");
140 
141  // Check output TensorShape(s) match inferred shape
142  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "QuantizedLstmLayer");
143 
145  inferredShapes[1],
147  "QuantizedLstmLayer",
148  1);
149 }

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, CHECK_LOCATION, Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), armnn::GetTensorInfo(), InputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), QuantizedLstmLayer::InferOutputShapes(), QuantizedLstmParameters::m_CellBias, QuantizedLstmParameters::m_ForgetGateBias, QuantizedLstmParameters::m_InputGateBias, QuantizedLstmParameters::m_InputToCellWeights, QuantizedLstmParameters::m_InputToForgetWeights, QuantizedLstmParameters::m_InputToInputWeights, QuantizedLstmParameters::m_InputToOutputWeights, QuantizedLstmParameters::m_OutputGateBias, QuantizedLstmLayer::m_QuantizedLstmParameters, QuantizedLstmParameters::m_RecurrentToCellWeights, QuantizedLstmParameters::m_RecurrentToForgetWeights, QuantizedLstmParameters::m_RecurrentToInputWeights, QuantizedLstmParameters::m_RecurrentToOutputWeights, Layer::m_ShapeInferenceMethod, Layer::ValidateAndCopyShape(), Layer::VerifyLayerConnections(), and Layer::VerifyShapeInferenceType().

Member Data Documentation

◆ m_QuantizedLstmParameters


The documentation for this class was generated from the following files:
ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
armnn::QuantizedLstmParameters::m_InputToInputWeights
std::shared_ptr< ConstTensorHandle > m_InputToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8).
Definition: QuantizedLstmLayer.hpp:17
armnn::QuantizedLstmParameters::m_CellBias
std::shared_ptr< ConstTensorHandle > m_CellBias
A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32).
Definition: QuantizedLstmLayer.hpp:39
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92
armnn::QuantizedLstmParameters::m_OutputGateBias
std::shared_ptr< ConstTensorHandle > m_OutputGateBias
A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32).
Definition: QuantizedLstmLayer.hpp:41
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
armnn::Layer::ValidateAndCopyShape
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Definition: Layer.cpp:435
armnn::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::LayerType::QuantizedLstm
@ QuantizedLstm
ARMNN_ASSERT_MSG
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:337
armnn::Layer::Layer
Layer(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char *name)
Definition: Layer.cpp:247
armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:332
armnn::QuantizedLstmParameters::m_RecurrentToOutputWeights
std::shared_ptr< ConstTensorHandle > m_RecurrentToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8).
Definition: QuantizedLstmLayer.hpp:32
armnn::QuantizedLstmParameters::m_InputToForgetWeights
std::shared_ptr< ConstTensorHandle > m_InputToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8).
Definition: QuantizedLstmLayer.hpp:19
armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:592
armnn::QuantizedLstmParameters::m_InputToCellWeights
std::shared_ptr< ConstTensorHandle > m_InputToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8).
Definition: QuantizedLstmLayer.hpp:21
armnn::QuantizedLstmParameters::m_ForgetGateBias
std::shared_ptr< ConstTensorHandle > m_ForgetGateBias
A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32).
Definition: QuantizedLstmLayer.hpp:37
armnn::Layer::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: Layer.hpp:409
armnn::QuantizedLstmParameters::m_InputToOutputWeights
std::shared_ptr< ConstTensorHandle > m_InputToOutputWeights
A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8).
Definition: QuantizedLstmLayer.hpp:23
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:504
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:287
armnn::QuantizedLstmLayer::m_QuantizedLstmParameters
QuantizedLstmParameters m_QuantizedLstmParameters
Definition: QuantizedLstmLayer.hpp:49
armnn::QuantizedLstmLayer::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: QuantizedLstmLayer.cpp:81
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn::QuantizedLstmParameters::m_RecurrentToCellWeights
std::shared_ptr< ConstTensorHandle > m_RecurrentToCellWeights
A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8).
Definition: QuantizedLstmLayer.hpp:30
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:391
armnn::QuantizedLstmParameters::m_InputGateBias
std::shared_ptr< ConstTensorHandle > m_InputGateBias
A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32).
Definition: QuantizedLstmLayer.hpp:35
armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:441
armnn::QuantizedLstmParameters::m_RecurrentToInputWeights
std::shared_ptr< ConstTensorHandle > m_RecurrentToInputWeights
A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8).
Definition: QuantizedLstmLayer.hpp:26
armnn::QuantizedLstmParameters::m_RecurrentToForgetWeights
std::shared_ptr< ConstTensorHandle > m_RecurrentToForgetWeights
A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8).
Definition: QuantizedLstmLayer.hpp:28