ArmNN
 21.11
Convolution3dLayer Class Reference

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

#include <Convolution3dLayer.hpp>

Inheritance diagram for Convolution3dLayer:
LayerWithParameters< Convolution3dDescriptor > Layer IConnectableLayer

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...
 
ARMNN_NO_DEPRECATE_WARN_BEGIN void Accept (ILayerVisitor &visitor) const override
 
ARMNN_NO_DEPRECATE_WARN_END 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
 
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
 
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)
 
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)
 
template<typename T >
std::shared_ptr< T > GetAdditionalInformation () const
 
void SetAdditionalInfoForObject (const AdditionalInfoObjectPtr &additionalInfo)
 
- Public Member Functions inherited from IConnectableLayer
ARMNN_NO_DEPRECATE_WARN_BEGIN ARMNN_DEPRECATED_MSG_REMOVAL_DATE ("Accept is deprecated. The ILayerVisitor that works in conjunction with this " "Accept function is deprecated. Use IStrategy in combination with " "ExecuteStrategy instead, which is an ABI/API stable version of the " "visitor pattern.", "22.05") virtual void Accept(ILayerVisitor &visitor) const =0
 Apply a visitor to this layer. 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 *LayerCreateWorkload. More...
 
void ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this 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 *LayerCreateWorkload. More...
 
template<typename LayerType , typename ... Params>
LayerTypeCloneBase (Graph &graph, Params &&... params) const
 
virtual ConstantTensors GetConstantTensorsByRef ()
 
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
 
- Protected Types inherited from Layer
using ConstantTensors = std::vector< std::reference_wrapper< 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.

References armnn::Convolution3d.

20 {
21 }
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const Convolution3dDescriptor &param, const char *name)
uint32_t GetNumInputs() const
Get the number of views/inputs.

◆ ~Convolution3dLayer()

~Convolution3dLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Accept()

ARMNN_NO_DEPRECATE_WARN_BEGIN void Accept ( ILayerVisitor &  visitor) const
override

Definition at line 128 of file Convolution3dLayer.cpp.

References ARMNN_NO_DEPRECATE_WARN_END, and armnn::IgnoreUnused().

129 {
130  IgnoreUnused(visitor);
131  throw armnn::Exception("Convolution3dLayer: VisitConvolution3dLayer is not implemented");
132 }
void IgnoreUnused(Ts &&...)
Base class for all ArmNN exceptions so that users can filter to just those.
Definition: Exceptions.hpp:46

◆ 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.

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

57 {
58  auto layer = CloneBase<Convolution3dLayer>(graph, m_Param, GetName());
59  return std::move(layer);
60 }
Convolution3dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:311

◆ 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.

References IWorkloadFactory::CreateConvolution3d(), LayerWithParameters< Convolution3dDescriptor >::PrepInfoAndDesc(), and Layer::SetAdditionalInfo().

49 {
51  SetAdditionalInfo(descriptor);
52 
53  return factory.CreateConvolution3d(descriptor, PrepInfoAndDesc(descriptor));
54 }
virtual std::unique_ptr< IWorkload > CreateConvolution3d(const Convolution3dQueueDescriptor &descriptor, const WorkloadInfo &info) const
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:245
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.

◆ ExecuteStrategy()

ARMNN_NO_DEPRECATE_WARN_END void ExecuteStrategy ( IStrategy strategy) const
overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 135 of file Convolution3dLayer.cpp.

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

136 {
137  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
138 }
const Convolution3dDescriptor & GetParameters() const
virtual void ExecuteStrategy(const armnn::IConnectableLayer *layer, const armnn::BaseDescriptor &descriptor, const std::vector< armnn::ConstTensor > &constants, const char *name, const armnn::LayerBindingId id=0)=0
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:311

◆ 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.

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, DataLayoutIndexed::GetDepthIndex(), DataLayoutIndexed::GetHeightIndex(), 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 Convolution3dInferOutputShapeTest(), and Convolution3dLayer::ValidateTensorShapesFromInputs().

63 {
64  ARMNN_ASSERT(inputShapes.size() == 2);
65  const TensorShape& inputShape = inputShapes[0];
66  const TensorShape& filterShape = inputShapes[1];
67 
68  ARMNN_ASSERT_MSG(inputShape.GetNumDimensions() == 5, "Convolutions will always have 5D input.");
69 
73 
74  DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
75 
76  unsigned int inWidth = inputShape[dataLayoutIndex.GetWidthIndex()];
77  unsigned int inHeight = inputShape[dataLayoutIndex.GetHeightIndex()];
78  unsigned int inDepth = inputShape[dataLayoutIndex.GetDepthIndex()];
79  unsigned int inBatchSize = inputShape[0];
80 
81  // Conv3d Filter Layout: [D,H,W,I,O]
82  unsigned int filterDepth = filterShape[0];
83  unsigned int dilatedFilterDepth = filterDepth + (m_Param.m_DilationZ - 1) * (filterDepth - 1);
84  unsigned int readDepth = (inDepth + m_Param.m_PadFront + m_Param.m_PadBack) - dilatedFilterDepth;
85  unsigned int outDepth = 1 + (readDepth / m_Param.m_StrideZ);
86 
87  unsigned int filterHeight = filterShape[1];
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 filterWidth = filterShape[2];
93  unsigned int dilatedFilterWidth = filterWidth + (m_Param.m_DilationX - 1) * (filterWidth - 1);
94  unsigned int readWidth = (inWidth + m_Param.m_PadLeft + m_Param.m_PadRight) - dilatedFilterWidth;
95  unsigned int outWidth = 1 + (readWidth / m_Param.m_StrideX);
96 
97  unsigned int outChannels = filterShape[4];
98  unsigned int outBatchSize = inBatchSize;
99 
101  TensorShape( { outBatchSize, outDepth, outHeight, outWidth, outChannels } ) :
102  TensorShape( { outBatchSize, outChannels, outDepth, outHeight, outWidth });
103 
104  return std::vector<TensorShape>({ tensorShape });
105 }
Convolution3dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
uint32_t m_PadBack
Padding back value in the depth dimension.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
uint32_t m_PadBottom
Padding bottom value in the height dimension.
uint32_t m_DilationX
Dilation along x axis.
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout...
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
uint32_t m_PadFront
Padding front value in the depth dimension.
uint32_t m_PadLeft
Padding left value in the width dimension.
uint32_t m_PadRight
Padding right value in the width dimension.
DataLayout m_DataLayout
The data layout to be used (NDHWC, NCDHW).
uint32_t m_PadTop
Padding top value in the height dimension.
uint32_t m_DilationZ
Dilation along z axis.
uint32_t m_StrideZ
Stride value when proceeding through input for the depth dimension.
uint32_t m_DilationY
Dilation along y axis.

◆ 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.

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

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 }
const TensorShape & GetShape() const
Definition: Tensor.hpp:191
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string (currently used in DotSerializer and company)...
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:199
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:316
virtual const TensorInfo & GetTensorInfo() const =0

◆ 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 107 of file Convolution3dLayer.cpp.

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

108 {
110 
111  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
112 
114 
115  ARMNN_ASSERT_MSG(GetInputSlot(1).GetConnection(),
116  "Convolution3dLayer: Weights should be connected to input slot 1.");
117 
118  auto inferredShapes = InferOutputShapes({
121 
122  ARMNN_ASSERT(inferredShapes.size() == 1);
123 
124  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "Convolution3dLayer");
125 }
Convolution3dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
const TensorShape & GetShape() const
Definition: Tensor.hpp:191
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.
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:433
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:199
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Definition: Layer.cpp:393
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:349
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:316
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
#define CHECK_LOCATION()
Definition: Exceptions.hpp:209
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:318
virtual const TensorInfo & GetTensorInfo() const =0
uint32_t GetNumInputs() const
Get the number of views/inputs.
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:63
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:408

The documentation for this class was generated from the following files: