ArmNN
 24.08
Convolution3dLayer Class Reference

This layer represents a convolution 3d operation. More...

#include <Convolution3dLayer.hpp>

Inheritance diagram for Convolution3dLayer:
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Collaboration diagram for Convolution3dLayer:
[legend]

Public Member Functions

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the Convolution3d type. More...
 
Convolution3dLayerClone (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 Convolution3dLayer. 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...
 
- Public Member Functions inherited from LayerWithParameters< Convolution3dDescriptor >
const Convolution3dDescriptorGetParameters () const override
 If the layer has a descriptor return it. More...
 
void SerializeLayerParameters (ParameterStringifyFunction &fn) const override
 Helper to serialize the layer parameters to string (currently used in DotSerializer and company). More...
 
- Public Member Functions inherited from Layer
 Layer (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char *name)
 
 Layer (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, DataLayout layout, const char *name)
 
const std::string & GetNameStr () const
 
const OutputHandlerGetOutputHandler (unsigned int i=0) const
 
OutputHandlerGetOutputHandler (unsigned int i=0)
 
ShapeInferenceMethod GetShapeInferenceMethod () const
 
bool GetAllowExpandedDims () const
 
const std::vector< InputSlot > & GetInputSlots () const
 
const std::vector< OutputSlot > & GetOutputSlots () const
 
std::vector< InputSlot >::iterator BeginInputSlots ()
 
std::vector< InputSlot >::iterator EndInputSlots ()
 
std::vector< OutputSlot >::iterator BeginOutputSlots ()
 
std::vector< OutputSlot >::iterator EndOutputSlots ()
 
bool IsOutputUnconnected ()
 
void ResetPriority () const
 
LayerPriority GetPriority () const
 
LayerType GetType () const override
 Returns the armnn::LayerType of this layer. More...
 
DataType GetDataType () const
 
const BackendIdGetBackendId () const
 
void SetBackendId (const BackendId &id) override
 Set the backend of the IConnectableLayer. More...
 
virtual void CreateTensorHandles (const TensorHandleFactoryRegistry &registry, const IWorkloadFactory &factory, const bool IsMemoryManaged=true)
 
void VerifyLayerConnections (unsigned int expectedConnections, const CheckLocation &location) const
 
virtual void ReleaseConstantData ()
 
template<typename Op >
void OperateOnConstantTensors (Op op)
 
const char * GetName () const override
 Returns the name of the layer. More...
 
unsigned int GetNumInputSlots () const override
 Returns the number of connectable input slots. More...
 
unsigned int GetNumOutputSlots () const override
 Returns the number of connectable output slots. More...
 
const InputSlotGetInputSlot (unsigned int index) const override
 Get a const input slot handle by slot index. More...
 
InputSlotGetInputSlot (unsigned int index) override
 Get the input slot handle by slot index. More...
 
const OutputSlotGetOutputSlot (unsigned int index=0) const override
 Get the const output slot handle by slot index. More...
 
OutputSlotGetOutputSlot (unsigned int index=0) override
 Get the output slot handle by slot index. More...
 
void SetGuid (LayerGuid guid)
 
LayerGuid GetGuid () const final
 Returns the unique id of the layer. More...
 
void AddRelatedLayerName (const std::string layerName)
 
const std::list< std::string > & GetRelatedLayerNames ()
 
virtual void Reparent (Graph &dest, std::list< Layer * >::const_iterator iterator)=0
 
void BackendSelectionHint (Optional< BackendId > backend) final
 Provide a hint for the optimizer as to which backend to prefer for this layer. More...
 
Optional< BackendIdGetBackendHint () const
 
void SetShapeInferenceMethod (ShapeInferenceMethod shapeInferenceMethod)
 
void SetAllowExpandedDims (bool allowExpandedDims)
 
template<typename T >
std::shared_ptr< T > GetAdditionalInformation () const
 
void SetAdditionalInfoForObject (const AdditionalInfoObjectPtr &additionalInfo)
 
virtual const BaseDescriptorGetParameters () const override
 If the layer has a descriptor return it. More...
 

Protected Member Functions

 Convolution3dLayer (const Convolution3dDescriptor &param, const char *name)
 Constructor to create a Convolution3dLayer. More...
 
 ~Convolution3dLayer ()=default
 Default destructor. More...
 
- Protected Member Functions inherited from LayerWithParameters< Convolution3dDescriptor >
 LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const Convolution3dDescriptor &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
 
virtual ImmutableConstantTensors GetConstantTensorsByRef () const override
 
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< Convolution3dDescriptor >
using DescriptorType = Convolution3dDescriptor
 
- 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< Convolution3dDescriptor >
Convolution3dDescriptor 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 3d operation.

Definition at line 16 of file Convolution3dLayer.hpp.

Constructor & Destructor Documentation

◆ Convolution3dLayer()

Convolution3dLayer ( const Convolution3dDescriptor param,
const char *  name 
)
protected

Constructor to create a Convolution3dLayer.

Parameters
[in]paramConvolution3dDescriptor to configure the convolution3d operation.
[in]nameOptional name for the layer.

Definition at line 18 of file Convolution3dLayer.cpp.

20 {
21 }

References armnn::Convolution3d.

◆ ~Convolution3dLayer()

~Convolution3dLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

Convolution3dLayer * 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 56 of file Convolution3dLayer.cpp.

57 {
58  auto layer = CloneBase<Convolution3dLayer>(graph, m_Param, GetName());
59  return std::move(layer);
60 }

References Layer::GetName(), and LayerWithParameters< Convolution3dDescriptor >::m_Param.

◆ CreateWorkload()

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

Makes a workload for the Convolution3d 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 48 of file Convolution3dLayer.cpp.

49 {
51  SetAdditionalInfo(descriptor);
52 
53  return factory.CreateWorkload(LayerType::Convolution3d, descriptor, PrepInfoAndDesc(descriptor));
54 }

References armnn::Convolution3d, IWorkloadFactory::CreateWorkload(), LayerWithParameters< Convolution3dDescriptor >::PrepInfoAndDesc(), and Layer::SetAdditionalInfo().

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy strategy) const
overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 153 of file Convolution3dLayer.cpp.

154 {
155  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
156 }

References IStrategy::ExecuteStrategy(), Layer::GetName(), and LayerWithParameters< Convolution3dDescriptor >::GetParameters().

◆ 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 62 of file Convolution3dLayer.cpp.

63 {
64  if (inputShapes.size() != 2)
65  {
66  throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
67  "\" - should be \"2\".");
68  }
69 
70  const TensorShape& inputShape = inputShapes[0];
71  const TensorShape& filterShape = inputShapes[1];
72 
73  if (inputShape.GetNumDimensions() != 5)
74  {
75  throw armnn::Exception("Convolutions will always have 5D input.");
76  }
77 
78  if (m_Param.m_StrideX == 0)
79  {
80  throw armnn::Exception("m_StrideX cannot be 0.");
81  }
82 
83  if (m_Param.m_StrideY == 0)
84  {
85  throw armnn::Exception("m_StrideY cannot be 0.");
86  }
87 
88  if (m_Param.m_StrideZ == 0)
89  {
90  throw armnn::Exception("m_StrideZ cannot be 0.");
91  }
92 
93  DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
94 
95  unsigned int inWidth = inputShape[dataLayoutIndex.GetWidthIndex()];
96  unsigned int inHeight = inputShape[dataLayoutIndex.GetHeightIndex()];
97  unsigned int inDepth = inputShape[dataLayoutIndex.GetDepthIndex()];
98  unsigned int inBatchSize = inputShape[0];
99 
100  // Conv3d Filter Layout: [D,H,W,I,O]
101  unsigned int filterDepth = filterShape[0];
102  unsigned int dilatedFilterDepth = filterDepth + (m_Param.m_DilationZ - 1) * (filterDepth - 1);
103  unsigned int readDepth = (inDepth + m_Param.m_PadFront + m_Param.m_PadBack) - dilatedFilterDepth;
104  unsigned int outDepth = 1 + (readDepth / m_Param.m_StrideZ);
105 
106  unsigned int filterHeight = filterShape[1];
107  unsigned int dilatedFilterHeight = filterHeight + (m_Param.m_DilationY - 1) * (filterHeight - 1);
108  unsigned int readHeight = (inHeight + m_Param.m_PadTop + m_Param.m_PadBottom) - dilatedFilterHeight;
109  unsigned int outHeight = 1 + (readHeight / m_Param.m_StrideY);
110 
111  unsigned int filterWidth = filterShape[2];
112  unsigned int dilatedFilterWidth = filterWidth + (m_Param.m_DilationX - 1) * (filterWidth - 1);
113  unsigned int readWidth = (inWidth + m_Param.m_PadLeft + m_Param.m_PadRight) - dilatedFilterWidth;
114  unsigned int outWidth = 1 + (readWidth / m_Param.m_StrideX);
115 
116  unsigned int outChannels = filterShape[4];
117  unsigned int outBatchSize = inBatchSize;
118 
120  TensorShape( { outBatchSize, outDepth, outHeight, outWidth, outChannels } ) :
121  TensorShape( { outBatchSize, outChannels, outDepth, outHeight, outWidth });
122 
123  return std::vector<TensorShape>({ tensorShape });
124 }

References DataLayoutIndexed::GetDepthIndex(), DataLayoutIndexed::GetHeightIndex(), TensorShape::GetNumDimensions(), DataLayoutIndexed::GetWidthIndex(), Convolution3dDescriptor::m_DataLayout, Convolution3dDescriptor::m_DilationX, Convolution3dDescriptor::m_DilationY, Convolution3dDescriptor::m_DilationZ, Convolution3dDescriptor::m_PadBack, Convolution3dDescriptor::m_PadBottom, Convolution3dDescriptor::m_PadFront, Convolution3dDescriptor::m_PadLeft, Convolution3dDescriptor::m_PadRight, Convolution3dDescriptor::m_PadTop, LayerWithParameters< Convolution3dDescriptor >::m_Param, Convolution3dDescriptor::m_StrideX, Convolution3dDescriptor::m_StrideY, Convolution3dDescriptor::m_StrideZ, and armnn::NDHWC.

Referenced by Convolution3dLayer::ValidateTensorShapesFromInputs().

◆ 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 23 of file Convolution3dLayer.cpp.

24 {
25  const std::vector<TensorShape>& inputShapes =
26  {
29  };
30 
31  // Conv3d Filter Layout: [D,H,W,I,O]
32  const TensorShape filterShape = inputShapes[1];
33  unsigned int filterDepth = filterShape[0];
34  unsigned int filterHeight = filterShape[1];
35  unsigned int filterWidth = filterShape[2];
36  unsigned int inChannels = filterShape[3];
37  unsigned int outChannels = filterShape[4];
38 
39  fn("FilterDepth",std::to_string(filterDepth));
40  fn("FilterHeight",std::to_string(filterHeight));
41  fn("FilterWidth",std::to_string(filterWidth));
42  fn("InputChannels",std::to_string(inChannels));
43  fn("OutputChannels",std::to_string(outChannels));
44 
46 }

References Layer::GetInputSlot(), TensorInfo::GetShape(), InputSlot::GetTensorInfo(), and LayerWithParameters< Parameters >::SerializeLayerParameters().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

Check if the input tensor shape(s) will lead to a valid configuration of Convolution3dLayer.

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

Implements Layer.

Definition at line 126 of file Convolution3dLayer.cpp.

127 {
129 
130  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
131 
133 
134  if (!GetInputSlot(1).GetConnection())
135  {
136  throw armnn::LayerValidationException("Convolution3dLayer: Weights should be connected to input slot 1.");
137  }
138 
139  auto inferredShapes = InferOutputShapes({
142 
143  if (inferredShapes.size() != 1)
144  {
145  throw armnn::LayerValidationException("inferredShapes has "
146  + std::to_string(inferredShapes.size()) +
147  " elements - should only have 1.");
148  }
149 
150  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "Convolution3dLayer");
151 }

References CHECK_LOCATION, Layer::GetInputSlot(), Convolution3dDescriptor::GetNumInputs(), Layer::GetOutputSlot(), TensorInfo::GetShape(), InputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), Convolution3dLayer::InferOutputShapes(), LayerWithParameters< Convolution3dDescriptor >::m_Param, Layer::m_ShapeInferenceMethod, Layer::ValidateAndCopyShape(), Layer::VerifyLayerConnections(), and Layer::VerifyShapeInferenceType().


The documentation for this class was generated from the following files:
armnn::Convolution3dLayer::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: Convolution3dLayer.cpp:62
armnn::Convolution3dDescriptor::GetNumInputs
uint32_t GetNumInputs() const
Get the number of views/inputs.
Definition: Descriptors.cpp:465
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:100
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::Convolution3dDescriptor::m_PadFront
uint32_t m_PadFront
Padding front value in the depth dimension.
Definition: Descriptors.hpp:637
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:457
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::Convolution3dDescriptor::m_PadTop
uint32_t m_PadTop
Padding top value in the height dimension.
Definition: Descriptors.hpp:633
armnn::Convolution3dDescriptor::m_DilationX
uint32_t m_DilationX
Dilation along x axis.
Definition: Descriptors.hpp:647
armnn::Convolution3dDescriptor::m_PadBottom
uint32_t m_PadBottom
Padding bottom value in the height dimension.
Definition: Descriptors.hpp:635
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< Convolution3dDescriptor >::GetParameters
const Convolution3dDescriptor & 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::Convolution3dQueueDescriptor
Definition: WorkloadData.hpp:216
armnn::DataLayout::NDHWC
@ NDHWC
armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:614
armnn::TensorShape
Definition: Tensor.hpp:20
armnn::Convolution3dDescriptor::m_PadRight
uint32_t m_PadRight
Padding right value in the width dimension.
Definition: Descriptors.hpp:631
armnn::LayerWithParameters< Convolution3dDescriptor >::m_Param
Convolution3dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::TensorShape::GetNumDimensions
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition: Tensor.cpp:174
armnn::LayerWithParameters< Convolution3dDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
armnn::Convolution3dDescriptor::m_DilationZ
uint32_t m_DilationZ
Dilation along z axis.
Definition: Descriptors.hpp:651
armnn::LayerValidationException
Definition: Exceptions.hpp:105
armnn::Convolution3dDescriptor::m_PadLeft
uint32_t m_PadLeft
Padding left value in the width dimension.
Definition: Descriptors.hpp:629
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:526
armnn::Convolution3dDescriptor::m_StrideY
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
Definition: Descriptors.hpp:643
armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:303
armnn::Convolution3dDescriptor::m_StrideX
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
Definition: Descriptors.hpp:641
armnn::Exception
Base class for all ArmNN exceptions so that users can filter to just those.
Definition: Exceptions.hpp:46
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn::Convolution3dDescriptor::m_PadBack
uint32_t m_PadBack
Padding back value in the depth dimension.
Definition: Descriptors.hpp:639
armnn::Convolution3dDescriptor::m_DilationY
uint32_t m_DilationY
Dilation along y axis.
Definition: Descriptors.hpp:649
armnn::Convolution3dDescriptor::m_StrideZ
uint32_t m_StrideZ
Stride value when proceeding through input for the depth dimension.
Definition: Descriptors.hpp:645
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:410
armnn::Convolution3dDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NDHWC, NCDHW).
Definition: Descriptors.hpp:655
armnn::LayerWithParameters< Convolution3dDescriptor >::LayerWithParameters
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const Convolution3dDescriptor &param, const char *name)
Definition: LayerWithParameters.hpp:30
armnn::LayerType::Convolution3d
@ Convolution3d
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