ArmNN
 24.02
Convolution2dLayer Class Reference

This layer represents a convolution 2d operation. More...

#include <Convolution2dLayer.hpp>

Inheritance diagram for Convolution2dLayer:
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Collaboration diagram for Convolution2dLayer:
[legend]

Public Member Functions

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the Convolution2d type. More...
 
Convolution2dLayerClone (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 Convolution2dLayer. 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...
 
void SerializeLayerParameters (ParameterStringifyFunction &fn) const override
 Helper to serialize the layer parameters to string. More...
 
void ReleaseConstantData () override
 This layer does not have any data stored, weights and bias are now stored in constant layers. More...
 
- Public Member Functions inherited from LayerWithParameters< Convolution2dDescriptor >
const Convolution2dDescriptorGetParameters () const override
 If the layer has a descriptor return it. More...
 
void SerializeLayerParameters (ParameterStringifyFunction &fn) const override
 Helper to serialize the layer parameters to string (currently used in DotSerializer and company). More...
 
- Public Member Functions inherited from Layer
 Layer (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char *name)
 
 Layer (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, DataLayout layout, const char *name)
 
const std::string & GetNameStr () const
 
const OutputHandlerGetOutputHandler (unsigned int i=0) const
 
OutputHandlerGetOutputHandler (unsigned int i=0)
 
ShapeInferenceMethod GetShapeInferenceMethod () const
 
bool GetAllowExpandedDims () const
 
const std::vector< InputSlot > & GetInputSlots () const
 
const std::vector< OutputSlot > & GetOutputSlots () const
 
std::vector< InputSlot >::iterator BeginInputSlots ()
 
std::vector< InputSlot >::iterator EndInputSlots ()
 
std::vector< OutputSlot >::iterator BeginOutputSlots ()
 
std::vector< OutputSlot >::iterator EndOutputSlots ()
 
bool IsOutputUnconnected ()
 
void ResetPriority () const
 
LayerPriority GetPriority () const
 
LayerType GetType () const override
 Returns the armnn::LayerType of this layer. More...
 
DataType GetDataType () const
 
const BackendIdGetBackendId () const
 
void SetBackendId (const BackendId &id) override
 Set the backend of the IConnectableLayer. More...
 
virtual void CreateTensorHandles (const TensorHandleFactoryRegistry &registry, const IWorkloadFactory &factory, const bool IsMemoryManaged=true)
 
void VerifyLayerConnections (unsigned int expectedConnections, const CheckLocation &location) const
 
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...
 

Protected Member Functions

 Convolution2dLayer (const Convolution2dDescriptor &param, const char *name)
 Constructor to create a Convolution2dLayer. More...
 
 ~Convolution2dLayer ()=default
 Default destructor. More...
 
ImmutableConstantTensors GetConstantTensorsByRef () const override
 Retrieve the handles to the constant values connected to the layer. More...
 
- Protected Member Functions inherited from LayerWithParameters< Convolution2dDescriptor >
 LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const Convolution2dDescriptor &param, const char *name)
 
 ~LayerWithParameters ()=default
 
WorkloadInfo PrepInfoAndDesc (QueueDescriptor &descriptor) const
 Helper function to reduce duplication in *Layer::CreateWorkload. More...
 
void ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this layer. More...
 
Layer::ImmutableConstantTensors GetConnectedConstantAsInputTensors () const
 
- Protected Member Functions inherited from Layer
virtual ~Layer ()=default
 
template<typename QueueDescriptor >
void CollectQueueDescriptorInputs (QueueDescriptor &descriptor, WorkloadInfo &info) const
 
template<typename QueueDescriptor >
void CollectQueueDescriptorOutputs (QueueDescriptor &descriptor, WorkloadInfo &info) const
 
void ValidateAndCopyShape (const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
 
void VerifyShapeInferenceType (const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
 
template<typename QueueDescriptor >
WorkloadInfo PrepInfoAndDesc (QueueDescriptor &descriptor) const
 Helper function to reduce duplication in *Layer::CreateWorkload. More...
 
template<typename LayerType , typename ... Params>
LayerTypeCloneBase (Graph &graph, Params &&... params) const
 
virtual ConstantTensors GetConstantTensorsByRef () override final
 
void SetAdditionalInfo (QueueDescriptor &descriptor) const
 
- Protected Member Functions inherited from IConnectableLayer
 ~IConnectableLayer ()
 Objects are not deletable via the handle. More...
 

Additional Inherited Members

- Public Types inherited from LayerWithParameters< Convolution2dDescriptor >
using DescriptorType = Convolution2dDescriptor
 
- 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< Convolution2dDescriptor >
Convolution2dDescriptor m_Param
 The parameters for the layer (not including tensor-valued weights etc.). More...
 
- Protected Attributes inherited from Layer
AdditionalInfoObjectPtr m_AdditionalInfoObject
 
std::vector< OutputHandlerm_OutputHandlers
 
ShapeInferenceMethod m_ShapeInferenceMethod
 

Detailed Description

This layer represents a convolution 2d operation.

Definition at line 15 of file Convolution2dLayer.hpp.

Constructor & Destructor Documentation

◆ Convolution2dLayer()

Convolution2dLayer ( const Convolution2dDescriptor param,
const char *  name 
)
protected

Constructor to create a Convolution2dLayer.

Parameters
[in]paramConvolution2dDescriptor to configure the convolution2d operation.
[in]nameOptional name for the layer.

Definition at line 23 of file Convolution2dLayer.cpp.

25 {
26 
27 }

References armnn::Convolution2d.

◆ ~Convolution2dLayer()

~Convolution2dLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

Convolution2dLayer * 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 58 of file Convolution2dLayer.cpp.

59 {
60  auto layer = CloneBase<Convolution2dLayer>(graph, m_Param, GetName());
61  return std::move(layer);
62 }

References Layer::GetName(), and LayerWithParameters< Convolution2dDescriptor >::m_Param.

◆ CreateWorkload()

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

Makes a workload for the Convolution2d 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 49 of file Convolution2dLayer.cpp.

50 {
51  ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "Convolution2dLayer_CreateWorkload");
53  SetAdditionalInfo(descriptor);
54 
55  return factory.CreateWorkload(LayerType::Convolution2d, descriptor, PrepInfoAndDesc(descriptor));
56 }

References ARMNN_SCOPED_PROFILING_EVENT, armnn::Convolution2d, IWorkloadFactory::CreateWorkload(), LayerWithParameters< Convolution2dDescriptor >::PrepInfoAndDesc(), Layer::SetAdditionalInfo(), and armnn::Undefined.

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy strategy) const
overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 128 of file Convolution2dLayer.cpp.

129 {
130  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
131 }

References IStrategy::ExecuteStrategy(), Layer::GetName(), and LayerWithParameters< Convolution2dDescriptor >::GetParameters().

◆ GetConstantTensorsByRef()

Layer::ImmutableConstantTensors GetConstantTensorsByRef ( ) const
overrideprotectedvirtual

Retrieve the handles to the constant values connected to the layer.

Returns
A vector of the constant tensors connected to the layer.

Reimplemented from Layer.

Definition at line 122 of file Convolution2dLayer.cpp.

123 {
125  return tensors;
126 }

References LayerWithParameters< Convolution2dDescriptor >::GetConnectedConstantAsInputTensors().

◆ 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 64 of file Convolution2dLayer.cpp.

65 {
66  ARMNN_ASSERT(inputShapes.size() == 2);
67  const TensorShape& inputShape = inputShapes[0];
68  const TensorShape filterShape = inputShapes[1];
69 
70  // If we support multiple batch dimensions in the future, then this assert will need to change.
71  ARMNN_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Convolutions will always have 4D input.");
72 
75 
76  DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
77 
78  unsigned int inWidth = inputShape[dataLayoutIndex.GetWidthIndex()];
79  unsigned int inHeight = inputShape[dataLayoutIndex.GetHeightIndex()];
80  unsigned int inBatchSize = inputShape[0];
81 
82  unsigned int filterWidth = filterShape[dataLayoutIndex.GetWidthIndex()];
83  unsigned int dilatedFilterWidth = filterWidth + (m_Param.m_DilationX - 1) * (filterWidth - 1);
84  unsigned int readWidth = (inWidth + m_Param.m_PadLeft + m_Param.m_PadRight) - dilatedFilterWidth;
85  unsigned int outWidth = 1 + (readWidth / m_Param.m_StrideX);
86 
87  unsigned int filterHeight = filterShape[dataLayoutIndex.GetHeightIndex()];
88  unsigned int dilatedFilterHeight = filterHeight + (m_Param.m_DilationY - 1) * (filterHeight - 1);
89  unsigned int readHeight = (inHeight + m_Param.m_PadTop + m_Param.m_PadBottom) - dilatedFilterHeight;
90  unsigned int outHeight = 1 + (readHeight / m_Param.m_StrideY);
91 
92  unsigned int outChannels = filterShape[0];
93  unsigned int outBatchSize = inBatchSize;
94 
96  TensorShape( { outBatchSize, outHeight, outWidth, outChannels } ) :
97  TensorShape( { outBatchSize, outChannels, outHeight, outWidth });
98 
99  return std::vector<TensorShape>({ tensorShape });
100 }

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, DataLayoutIndexed::GetHeightIndex(), TensorShape::GetNumDimensions(), DataLayoutIndexed::GetWidthIndex(), Convolution2dDescriptor::m_DataLayout, Convolution2dDescriptor::m_DilationX, Convolution2dDescriptor::m_DilationY, Convolution2dDescriptor::m_PadBottom, Convolution2dDescriptor::m_PadLeft, Convolution2dDescriptor::m_PadRight, Convolution2dDescriptor::m_PadTop, LayerWithParameters< Convolution2dDescriptor >::m_Param, Convolution2dDescriptor::m_StrideX, Convolution2dDescriptor::m_StrideY, and armnn::NHWC.

Referenced by Convolution2dLayer::ValidateTensorShapesFromInputs().

◆ ReleaseConstantData()

void ReleaseConstantData ( )
inlineoverridevirtual

This layer does not have any data stored, weights and bias are now stored in constant layers.

We do not want to release the data in the constant layer, that is why we override with an empty function.

Reimplemented from Layer.

Definition at line 46 of file Convolution2dLayer.hpp.

46 {}

◆ SerializeLayerParameters()

void SerializeLayerParameters ( ParameterStringifyFunction fn) const
overridevirtual

Helper to serialize the layer parameters to string.

(currently used in DotSerializer and company).

Reimplemented from Layer.

Definition at line 29 of file Convolution2dLayer.cpp.

30 {
31  //using DescriptorType = Parameters;
32  const std::vector<TensorShape>& inputShapes =
33  {
36  };
37  const TensorShape filterShape = inputShapes[1];
38  DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
39  unsigned int filterWidth = filterShape[dataLayoutIndex.GetWidthIndex()];
40  unsigned int filterHeight = filterShape[dataLayoutIndex.GetHeightIndex()];
41  unsigned int outChannels = filterShape[0];
42 
43  fn("OutputChannels",std::to_string(outChannels));
44  fn("FilterWidth",std::to_string(filterWidth));
45  fn("FilterHeight",std::to_string(filterHeight));
47 }

References DataLayoutIndexed::GetHeightIndex(), Layer::GetInputSlot(), TensorInfo::GetShape(), InputSlot::GetTensorInfo(), DataLayoutIndexed::GetWidthIndex(), Convolution2dDescriptor::m_DataLayout, LayerWithParameters< Convolution2dDescriptor >::m_Param, and LayerWithParameters< Parameters >::SerializeLayerParameters().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

Check if the input tensor shape(s) will lead to a valid configuration of Convolution2dLayer.

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

Implements Layer.

Definition at line 102 of file Convolution2dLayer.cpp.

103 {
105 
106  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
107 
109 
110  ARMNN_ASSERT_MSG(GetInputSlot(1).GetConnection(),
111  "Convolution2dLayer: Weights should be connected to input slot 1.");
112 
113  std::vector<TensorShape> inferredShapes = InferOutputShapes({
116 
117  ARMNN_ASSERT(inferredShapes.size() == 1);
118 
119  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "Convolution2dLayer");
120 }

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, CHECK_LOCATION, Layer::GetInputSlot(), Convolution2dDescriptor::GetNumInputs(), Layer::GetOutputSlot(), TensorInfo::GetShape(), InputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), Convolution2dLayer::InferOutputShapes(), LayerWithParameters< Convolution2dDescriptor >::m_Param, Layer::m_ShapeInferenceMethod, Layer::ValidateAndCopyShape(), Layer::VerifyLayerConnections(), and Layer::VerifyShapeInferenceType().


The documentation for this class was generated from the following files:
ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
armnn::Convolution2dDescriptor::m_PadTop
uint32_t m_PadTop
Padding top value in the height dimension.
Definition: Descriptors.hpp:570
armnn::Compute::Undefined
@ Undefined
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92
armnn::LayerWithParameters::SerializeLayerParameters
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string (currently used in DotSerializer and company).
Definition: LayerWithParameters.hpp:23
armnn::DataLayout::NHWC
@ NHWC
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
armnnUtils::DataLayoutIndexed
Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout.
Definition: DataLayoutIndexed.hpp:17
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::Convolution2dDescriptor::m_StrideY
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
Definition: Descriptors.hpp:576
ARMNN_ASSERT_MSG
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
armnn::Convolution2dDescriptor::m_PadLeft
uint32_t m_PadLeft
Padding left value in the width dimension.
Definition: Descriptors.hpp:566
armnn::Convolution2dDescriptor::m_DilationY
uint32_t m_DilationY
Dilation along y axis.
Definition: Descriptors.hpp:580
armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:337
armnn::LayerWithParameters< Convolution2dDescriptor >::GetParameters
const Convolution2dDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:332
armnn::IConnectableLayer::ImmutableConstantTensors
std::vector< std::reference_wrapper< const std::shared_ptr< ConstTensorHandle > >> ImmutableConstantTensors
Definition: INetwork.hpp:141
armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:592
armnn::LayerWithParameters< Convolution2dDescriptor >::GetConnectedConstantAsInputTensors
Layer::ImmutableConstantTensors GetConnectedConstantAsInputTensors() const
Definition: LayerWithParameters.hpp:59
armnn::TensorShape
Definition: Tensor.hpp:20
armnn::LayerWithParameters< Convolution2dDescriptor >::m_Param
Convolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::Convolution2dDescriptor::GetNumInputs
uint32_t GetNumInputs() const
Definition: Descriptors.cpp:469
armnn::TensorShape::GetNumDimensions
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition: Tensor.cpp:174
armnn::Convolution2dQueueDescriptor
Definition: WorkloadData.hpp:210
ARMNN_SCOPED_PROFILING_EVENT
#define ARMNN_SCOPED_PROFILING_EVENT(backendId, name)
Definition: Profiling.hpp:220
armnn::LayerWithParameters< Convolution2dDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:504
armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:287
armnn::Convolution2dDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Definition: Descriptors.hpp:584
armnn::Convolution2dDescriptor::m_PadBottom
uint32_t m_PadBottom
Padding bottom value in the height dimension.
Definition: Descriptors.hpp:572
armnn::Convolution2dDescriptor::m_StrideX
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
Definition: Descriptors.hpp:574
armnn::Convolution2dDescriptor::m_PadRight
uint32_t m_PadRight
Padding right value in the width dimension.
Definition: Descriptors.hpp:568
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn::Convolution2dDescriptor::m_DilationX
uint32_t m_DilationX
Dilation along x axis.
Definition: Descriptors.hpp:578
armnn::Convolution2dLayer::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: Convolution2dLayer.cpp:64
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:391
armnn::LayerType::Convolution2d
@ Convolution2d
armnn::LayerWithParameters< Convolution2dDescriptor >::LayerWithParameters
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const Convolution2dDescriptor &param, const char *name)
Definition: LayerWithParameters.hpp:30
armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:441
armnn::IWorkloadFactory::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const =0
Backends should implement their own CreateWorkload function with a switch statement.
armnn::IStrategy::ExecuteStrategy
virtual void ExecuteStrategy(const IConnectableLayer *layer, const armnn::BaseDescriptor &descriptor, const std::vector< armnn::ConstTensor > &constants, const char *name, const armnn::LayerBindingId id=0)=0