ArmNN
 25.11
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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.
Convolution3dLayerClone (Graph &graph) const override
 Creates a dynamically-allocated copy of this layer.
void ValidateTensorShapesFromInputs () override
 Check if the input tensor shape(s) will lead to a valid configuration of Convolution3dLayer.
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.
void ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this layer.
void SerializeLayerParameters (ParameterStringifyFunction &fn) const override
 Helper to serialize the layer parameters to string.
Public Member Functions inherited from LayerWithParameters< Convolution3dDescriptor >
const Convolution3dDescriptorGetParameters () const override
 If the layer has a descriptor return it.
void SerializeLayerParameters (ParameterStringifyFunction &fn) const override
 Helper to serialize the layer parameters to string (currently used in DotSerializer and company).
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.
DataType GetDataType () const
const BackendIdGetBackendId () const
void SetBackendId (const BackendId &id) override
 Set the backend of the IConnectableLayer.
virtual void CreateTensorHandles (const TensorHandleFactoryRegistry &registry, const IWorkloadFactory &factory, const bool IsMemoryManaged=true)
void VerifyLayerConnections (unsigned int expectedConnections, const CheckLocation &location) const
std::vector< TensorShapeInferOutputShapes (const std::vector< TensorShape > &inputShapes) const override
 Infer the shape of the output(s) based on the provided input shape(s)
virtual void ReleaseConstantData ()
template<typename Op>
void OperateOnConstantTensors (Op op)
const char * GetName () const override
 Returns the name of the layer.
unsigned int GetNumInputSlots () const override
 Returns the number of connectable input slots.
unsigned int GetNumOutputSlots () const override
 Returns the number of connectable output slots.
const InputSlotGetInputSlot (unsigned int index) const override
 Get a const input slot handle by slot index.
InputSlotGetInputSlot (unsigned int index) override
 Get the input slot handle by slot index.
const OutputSlotGetOutputSlot (unsigned int index=0) const override
 Get the const output slot handle by slot index.
OutputSlotGetOutputSlot (unsigned int index=0) override
 Get the output slot handle by slot index.
void SetGuid (LayerGuid guid)
LayerGuid GetGuid () const final
 Returns the unique id of the layer.
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.
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)

Protected Member Functions

 Convolution3dLayer (const Convolution3dDescriptor &param, const char *name)
 Constructor to create a Convolution3dLayer.
 ~Convolution3dLayer ()=default
 Default destructor.
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.
void ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this layer.
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 *LayerCreateWorkload.
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.

Additional Inherited Members

Public Types inherited from LayerWithParameters< Convolution3dDescriptor >
using DescriptorType
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.).
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}
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.

References armnn::Convolution3d, armnn::GetNumInputs(), and LayerWithParameters< Convolution3dDescriptor >::LayerWithParameters().

Referenced by Clone().

◆ ~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}
LayerType * CloneBase(Graph &graph, Params &&... params) const
const char * GetName() const override
Returns the name of the layer.
Definition Layer.hpp:332

References Layer::CloneBase(), Convolution3dLayer(), 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{
50 Convolution3dQueueDescriptor descriptor;
51 SetAdditionalInfo(descriptor);
52
53 return factory.CreateWorkload(LayerType::Convolution3d, descriptor, PrepInfoAndDesc(descriptor));
54}
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.
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition Layer.cpp:303
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const

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

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy & strategy) const
overridevirtual

Apply a visitor to this layer.

Implements IConnectableLayer.

Definition at line 153 of file Convolution3dLayer.cpp.

154{
155 strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
156}
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
const Convolution3dDescriptor & GetParameters() const override

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.

Implements IConnectableLayer.

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
119 TensorShape tensorShape = m_Param.m_DataLayout == armnn::DataLayout::NDHWC ?
120 TensorShape( { outBatchSize, outDepth, outHeight, outWidth, outChannels } ) :
121 TensorShape( { outBatchSize, outChannels, outDepth, outHeight, outWidth });
122
123 return std::vector<TensorShape>({ tensorShape });
124}
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition Tensor.cpp:174
uint32_t m_PadRight
Padding right value in the width dimension.
uint32_t m_PadBack
Padding back value in the depth dimension.
uint32_t m_DilationZ
Dilation along z axis.
uint32_t m_DilationY
Dilation along y axis.
uint32_t m_StrideZ
Stride value when proceeding through input for the depth dimension.
uint32_t m_PadTop
Padding top value in the height dimension.
DataLayout m_DataLayout
The data layout to be used (NDHWC, NCDHW).
uint32_t m_PadFront
Padding front value in the depth dimension.
uint32_t m_DilationX
Dilation along x axis.
uint32_t m_PadBottom
Padding bottom value in the height dimension.
uint32_t m_PadLeft
Padding left value in the width dimension.
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.

References DataLayoutIndexed::GetDepthIndex(), DataLayoutIndexed::GetHeightIndex(), TensorShape::GetNumDimensions(), DataLayoutIndexed::GetWidthIndex(), LayerWithParameters< Convolution3dDescriptor >::m_Param, and armnn::NDHWC.

Referenced by 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}
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition Layer.cpp:614
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition Layer.hpp:337
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string (currently used in DotSerializer and company).
const TensorShape & GetShape() const
Definition Tensor.hpp:193

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}
#define CHECK_LOCATION()
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,...
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition Layer.cpp:410
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition Layer.cpp:526
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition Layer.hpp:339
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Definition Layer.cpp:457
ShapeInferenceMethod m_ShapeInferenceMethod
Definition Layer.hpp:441
const TensorInfo & GetTensorInfo() const override
Definition Layer.cpp:100

References CHECK_LOCATION, Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), InputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), 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: