From 8efb48a6847c5cd166c561127ae6611150963ce3 Mon Sep 17 00:00:00 2001 From: Nikhil Raj Date: Fri, 19 May 2023 11:14:28 +0100 Subject: Update Doxygen docu for 23.05 Signed-off-by: Nikhil Raj Change-Id: I0a992286f14fa68fcc6e5eba31ac39fed003cbbe --- 23.05/classarmnn_1_1_quantized_lstm_layer.xhtml | 922 ++++++++++++++++++++++++ 1 file changed, 922 insertions(+) create mode 100644 23.05/classarmnn_1_1_quantized_lstm_layer.xhtml (limited to '23.05/classarmnn_1_1_quantized_lstm_layer.xhtml') diff --git a/23.05/classarmnn_1_1_quantized_lstm_layer.xhtml b/23.05/classarmnn_1_1_quantized_lstm_layer.xhtml new file mode 100644 index 0000000000..ce2a327fe9 --- /dev/null +++ b/23.05/classarmnn_1_1_quantized_lstm_layer.xhtml @@ -0,0 +1,922 @@ + + + + + + + + + + + + + +ArmNN: QuantizedLstmLayer Class Reference + + + + + + + + + + + + + + + + +
+
+ + + + ArmNN + + + +
+
+  23.05 +
+
+
+ + + + + + + +
+
+ +
+
+
+ +
+ +
+
+ + +
+ +
+ +
+
+Public Member Functions | +Public Attributes | +Protected Member Functions | +List of all members
+
+
QuantizedLstmLayer Class Reference
+
+
+ +

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

+ +

#include <QuantizedLstmLayer.hpp>

+
+Inheritance diagram for QuantizedLstmLayer:
+
+
+ + +Layer +IConnectableLayer + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

virtual std::unique_ptr< IWorkload > CreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the QuantizedLstm type. More...
 
QuantizedLstmLayer * 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 QuantizedLstmLayer. 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 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 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 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

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>
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 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< OutputHandler > m_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 ?
+
52  m_QuantizedLstmParameters.m_InputToInputWeights : nullptr;
+
53  layer->m_QuantizedLstmParameters.m_InputToForgetWeights = m_QuantizedLstmParameters.m_InputToForgetWeights ?
+
54  m_QuantizedLstmParameters.m_InputToForgetWeights : nullptr;
+
55  layer->m_QuantizedLstmParameters.m_InputToCellWeights = m_QuantizedLstmParameters.m_InputToCellWeights ?
+
56  m_QuantizedLstmParameters.m_InputToCellWeights : nullptr;
+
57  layer->m_QuantizedLstmParameters.m_InputToOutputWeights = m_QuantizedLstmParameters.m_InputToOutputWeights ?
+
58  m_QuantizedLstmParameters.m_InputToOutputWeights : nullptr;
+
59 
+
60  layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights = m_QuantizedLstmParameters.m_RecurrentToInputWeights ?
+
61  m_QuantizedLstmParameters.m_RecurrentToInputWeights : nullptr;
+
62  layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights = m_QuantizedLstmParameters.m_RecurrentToForgetWeights
+
63  ? m_QuantizedLstmParameters.m_RecurrentToForgetWeights : nullptr;
+
64  layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights = m_QuantizedLstmParameters.m_RecurrentToCellWeights ?
+
65  m_QuantizedLstmParameters.m_RecurrentToCellWeights : nullptr;
+
66  layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights = m_QuantizedLstmParameters.m_RecurrentToOutputWeights
+
67  ? m_QuantizedLstmParameters.m_RecurrentToOutputWeights : nullptr;
+
68 
+
69  layer->m_QuantizedLstmParameters.m_InputGateBias = m_QuantizedLstmParameters.m_InputGateBias ?
+
70  m_QuantizedLstmParameters.m_InputGateBias : nullptr;
+
71  layer->m_QuantizedLstmParameters.m_ForgetGateBias = m_QuantizedLstmParameters.m_ForgetGateBias ?
+
72  m_QuantizedLstmParameters.m_ForgetGateBias : nullptr;
+
73  layer->m_QuantizedLstmParameters.m_CellBias = m_QuantizedLstmParameters.m_CellBias ?
+
74  m_QuantizedLstmParameters.m_CellBias : nullptr;
+
75  layer->m_QuantizedLstmParameters.m_OutputGateBias = m_QuantizedLstmParameters.m_OutputGateBias ?
+
76  m_QuantizedLstmParameters.m_OutputGateBias : nullptr;
+
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
+
193  if (m_QuantizedLstmParameters.m_InputToInputWeights != nullptr)
+
194  {
+
195  constTensors.emplace_back(ConstTensor(managedInputToInputWeights.GetTensorInfo(),
+
196  managedInputToInputWeights.Map()));
+
197  }
+
198 
+
199  if (m_QuantizedLstmParameters.m_InputToForgetWeights != nullptr)
+
200  {
+
201  constTensors.emplace_back(ConstTensor(managedInputToForgetWeights.GetTensorInfo(),
+
202  managedInputToForgetWeights.Map()));
+
203  }
+
204 
+
205  if (m_QuantizedLstmParameters.m_InputToCellWeights != nullptr)
+
206  {
+
207  constTensors.emplace_back(ConstTensor(managedInputToCellWeights.GetTensorInfo(),
+
208  managedInputToCellWeights.Map()));
+
209  }
+
210 
+
211  if (m_QuantizedLstmParameters.m_InputToOutputWeights != nullptr)
+
212  {
+
213  constTensors.emplace_back(ConstTensor(managedInputToOutputWeights.GetTensorInfo(),
+
214  managedInputToOutputWeights.Map()));
+
215  }
+
216 
+
217  // RecurrentToX weight tensors
+
218  if (m_QuantizedLstmParameters.m_RecurrentToInputWeights != nullptr)
+
219  {
+
220  constTensors.emplace_back(ConstTensor(
+
221  managedRecurrentToInputWeights.GetTensorInfo(),
+
222  managedRecurrentToInputWeights.Map()));
+
223  }
+
224 
+
225  if (m_QuantizedLstmParameters.m_RecurrentToForgetWeights != nullptr)
+
226  {
+
227  constTensors.emplace_back(ConstTensor(
+
228  managedRecurrentToForgetWeights.GetTensorInfo(),
+
229  managedRecurrentToForgetWeights.Map()));
+
230  }
+
231 
+
232  if (m_QuantizedLstmParameters.m_RecurrentToCellWeights != nullptr)
+
233  {
+
234  constTensors.emplace_back(ConstTensor(
+
235  managedRecurrentToCellWeights.GetTensorInfo(),
+
236  managedRecurrentToCellWeights.Map()));
+
237  }
+
238 
+
239  if (m_QuantizedLstmParameters.m_RecurrentToOutputWeights != nullptr)
+
240  {
+
241  constTensors.emplace_back(ConstTensor(
+
242  managedRecurrentToOutputWeights.GetTensorInfo(),
+
243  managedRecurrentToOutputWeights.Map()));
+
244  }
+
245 
+
246  // Bias tensors
+
247  if (m_QuantizedLstmParameters.m_InputGateBias != nullptr)
+
248  {
+
249  constTensors.emplace_back(ConstTensor(managedInputGateBias.GetTensorInfo(),
+
250  managedInputGateBias.Map()));
+
251  }
+
252 
+
253  if (m_QuantizedLstmParameters.m_ForgetGateBias != nullptr)
+
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 
+
265  if (m_QuantizedLstmParameters.m_OutputGateBias != nullptr)
+
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.

+
152 {
+
153  // For API stability DO NOT ALTER order and add new members to the end of vector
+
154  return
+
155  {
+
156  m_QuantizedLstmParameters.m_InputToInputWeights,
+
157  m_QuantizedLstmParameters.m_InputToForgetWeights,
+
158  m_QuantizedLstmParameters.m_InputToCellWeights,
+
159  m_QuantizedLstmParameters.m_InputToOutputWeights,
+
160 
+
161  m_QuantizedLstmParameters.m_RecurrentToInputWeights,
+
162  m_QuantizedLstmParameters.m_RecurrentToForgetWeights,
+
163  m_QuantizedLstmParameters.m_RecurrentToCellWeights,
+
164  m_QuantizedLstmParameters.m_RecurrentToOutputWeights,
+
165 
+
166  m_QuantizedLstmParameters.m_InputGateBias,
+
167  m_QuantizedLstmParameters.m_ForgetGateBias,
+
168  m_QuantizedLstmParameters.m_CellBias,
+
169  m_QuantizedLstmParameters.m_OutputGateBias
+
170  };
+
171 }
+
+

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 {
+
98  VerifyLayerConnections(3, CHECK_LOCATION());
+
99 
+
100  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
+
101 
+
102  VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
+
103 
+
104  auto inferredShapes = InferOutputShapes(
+
105  {
+
106  GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(), // input
+
107  GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape(), // previousCellStateIn
+
108  GetInputSlot(2).GetConnection()->GetTensorInfo().GetShape() // previousOutputIn
+
109  });
+
110 
+
111  ARMNN_ASSERT(inferredShapes.size() == 2);
+
112 
+
113  // Check weights and bias for nullptr
+
114  ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_InputToInputWeights != nullptr,
+
115  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToInputWeights should not be null.");
+
116  ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_InputToForgetWeights != nullptr,
+
117  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToForgetWeights should not be null.");
+
118  ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_InputToCellWeights != nullptr,
+
119  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToCellWeights should not be null.");
+
120  ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_InputToOutputWeights != nullptr,
+
121  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToOutputWeights should not be null.");
+
122 
+
123  ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_RecurrentToInputWeights != nullptr,
+
124  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToInputWeights should not be null.");
+
125  ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_RecurrentToForgetWeights != nullptr,
+
126  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToForgetWeights should not be null.");
+
127  ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_RecurrentToCellWeights != nullptr,
+
128  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToCellWeights should not be null.");
+
129  ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_RecurrentToOutputWeights != nullptr,
+
130  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToOutputWeights should not be null.");
+
131 
+
132  ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_InputGateBias != nullptr,
+
133  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputGateBias should not be null.");
+
134  ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_ForgetGateBias != nullptr,
+
135  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_ForgetGateBias should not be null.");
+
136  ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_CellBias != nullptr,
+
137  "QuantizedLstmLayer: m_QuantizedLstmParameters.m_CellBias should not be null.");
+
138  ARMNN_ASSERT_MSG(m_QuantizedLstmParameters.m_OutputGateBias != nullptr,
+
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 
+
144  ValidateAndCopyShape(GetOutputSlot(1).GetTensorInfo().GetShape(),
+
145  inferredShapes[1],
+
146  m_ShapeInferenceMethod,
+
147  "QuantizedLstmLayer",
+
148  1);
+
149 }
+
+

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, CHECK_LOCATION, InputSlot::GetConnection(), Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), armnn::GetTensorInfo(), IOutputSlot::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

+ +
+
+ + + + +
QuantizedLstmParameters m_QuantizedLstmParameters
+
+ +

Definition at line 49 of file QuantizedLstmLayer.hpp.

+ +

Referenced by NetworkImpl::AddQuantizedLstmLayer(), QuantizedLstmLayer::Clone(), QuantizedLstmLayer::CreateWorkload(), QuantizedLstmLayer::ExecuteStrategy(), QuantizedLstmLayer::GetConstantTensorsByRef(), and QuantizedLstmLayer::ValidateTensorShapesFromInputs().

+ +
+
+
The documentation for this class was generated from the following files: +
+
+
armnn::GetTensorInfo
const TensorInfo & GetTensorInfo(const ITensorHandle *tensorHandle)
float32 helpers
Definition: RefWorkloadUtils.hpp:27
+
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
+
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
+
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::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:378
+
armnn::InputSlot::GetConnection
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:206
+
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::QuantizedLstmLayer::m_QuantizedLstmParameters
QuantizedLstmParameters m_QuantizedLstmParameters
Definition: QuantizedLstmLayer.hpp:49
+
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:491
+ +
armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:274
+
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:427
+
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:422
+
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92
+
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::IOutputSlot::GetTensorInfo
virtual const TensorInfo & GetTensorInfo() const =0
+
armnn::Layer::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: Layer.hpp:396
+
armnn::Layer::GetOutputSlot
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:326
+
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_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::Layer::Layer
Layer(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char *name)
Definition: Layer.cpp:247
+
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::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:191
+
ARMNN_ASSERT_MSG
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
+
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
+
armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:324
+
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::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
+
ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
+
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::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::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:319
+ + + + -- cgit v1.2.1