ArmNN
 22.08
DepthwiseConvolution2dLayer Class Reference

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

#include <DepthwiseConvolution2dLayer.hpp>

Inheritance diagram for DepthwiseConvolution2dLayer:
LayerWithParameters< DepthwiseConvolution2dDescriptor > Layer IConnectableLayer

Public Member Functions

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the DepthwiseConvolution2d type. More...
 
DepthwiseConvolution2dLayerClone (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 DepthwiseConvolution2dLayer. 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< DepthwiseConvolution2dDescriptor >
const DepthwiseConvolution2dDescriptorGetParameters () 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)
 
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)
 

Public Attributes

std::shared_ptr< ConstTensorHandlem_Weight
 A unique pointer to store Weight values. More...
 
std::shared_ptr< ConstTensorHandlem_Bias
 A unique pointer to store Bias values. More...
 

Protected Member Functions

 DepthwiseConvolution2dLayer (const DepthwiseConvolution2dDescriptor &param, const char *name)
 Constructor to create a DepthwiseConvolution2dLayer. More...
 
 ~DepthwiseConvolution2dLayer ()=default
 Default destructor. More...
 
ConstantTensors GetConstantTensorsByRef () override
 Retrieve the handles to the constant values stored by the layer. More...
 
- Protected Member Functions inherited from LayerWithParameters< DepthwiseConvolution2dDescriptor >
 LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const DepthwiseConvolution2dDescriptor &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...
 
Layer::ConstantTensors GetConnectedConstantAsInputTensors ()
 
- 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
 
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< DepthwiseConvolution2dDescriptor >
using DescriptorType = DepthwiseConvolution2dDescriptor
 
- Public Types inherited from IConnectableLayer
using ConstantTensors = std::vector< std::reference_wrapper< std::shared_ptr< ConstTensorHandle > >>
 
- Protected Attributes inherited from LayerWithParameters< DepthwiseConvolution2dDescriptor >
DepthwiseConvolution2dDescriptor 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 depthwise convolution 2d operation.

Definition at line 15 of file DepthwiseConvolution2dLayer.hpp.

Constructor & Destructor Documentation

◆ DepthwiseConvolution2dLayer()

DepthwiseConvolution2dLayer ( const DepthwiseConvolution2dDescriptor param,
const char *  name 
)
protected

Constructor to create a DepthwiseConvolution2dLayer.

Parameters
[in]paramDepthwiseConvolution2dDescriptor to configure the depthwise convolution2d.
[in]nameOptional name for the layer.

Definition at line 23 of file DepthwiseConvolution2dLayer.cpp.

References armnn::DepthwiseConvolution2d.

26 {
27 }
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const DepthwiseConvolution2dDescriptor &param, const char *name)
uint32_t GetNumInputs() const
Get the number of views/inputs.

◆ ~DepthwiseConvolution2dLayer()

~DepthwiseConvolution2dLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

DepthwiseConvolution2dLayer * 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 68 of file DepthwiseConvolution2dLayer.cpp.

References Layer::GetName(), DepthwiseConvolution2dLayer::m_Bias, LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param, and DepthwiseConvolution2dLayer::m_Weight.

69 {
70  auto layer = CloneBase<DepthwiseConvolution2dLayer>(graph, m_Param, GetName());
71  layer->m_Weight = m_Weight ? m_Weight : nullptr;
72 
73  if (layer->m_Param.m_BiasEnabled)
74  {
75  layer->m_Bias = m_Bias ? m_Bias : nullptr;
76  }
77 
78  return std::move(layer);
79 }
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
std::shared_ptr< ConstTensorHandle > m_Bias
A unique pointer to store Bias values.
std::shared_ptr< ConstTensorHandle > m_Weight
A unique pointer to store Weight values.
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:319

◆ CreateWorkload()

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

Makes a workload for the DepthwiseConvolution2d 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 50 of file DepthwiseConvolution2dLayer.cpp.

References IWorkloadFactory::CreateWorkload(), armnn::DepthwiseConvolution2d, DepthwiseConvolution2dLayer::m_Bias, DepthwiseConvolution2dQueueDescriptor::m_Bias, DepthwiseConvolution2dDescriptor::m_BiasEnabled, LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param, DepthwiseConvolution2dLayer::m_Weight, DepthwiseConvolution2dQueueDescriptor::m_Weight, LayerWithParameters< DepthwiseConvolution2dDescriptor >::PrepInfoAndDesc(), and Layer::SetAdditionalInfo().

51 {
53 
54  if (m_Weight)
55  {
56  descriptor.m_Weight = m_Weight.get();
57  }
59  {
60  descriptor.m_Bias = m_Bias.get();
61  }
62 
63  SetAdditionalInfo(descriptor);
64 
65  return factory.CreateWorkload(LayerType::DepthwiseConvolution2d, descriptor, PrepInfoAndDesc(descriptor));
66 }
bool m_BiasEnabled
Enable/disable bias.
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
std::shared_ptr< ConstTensorHandle > m_Bias
A unique pointer to store Bias values.
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:274
std::shared_ptr< ConstTensorHandle > m_Weight
A unique pointer to store Weight values.
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const
Depthwise Convolution 2D layer workload data.

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy strategy) const
overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 156 of file DepthwiseConvolution2dLayer.cpp.

References IStrategy::ExecuteStrategy(), Layer::GetName(), and LayerWithParameters< DepthwiseConvolution2dDescriptor >::GetParameters().

157 {
158  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
159 }
const DepthwiseConvolution2dDescriptor & GetParameters() const override
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 char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:319

◆ GetConstantTensorsByRef()

Layer::ConstantTensors GetConstantTensorsByRef ( )
overrideprotectedvirtual

Retrieve the handles to the constant values stored by the layer.

Returns
A vector of the constant tensors stored by this layer. Deprecated. GetConstantTensorsByRef is deprecated. m_Weights and m_Bias should be connected to layer as Constant Layers instead."

Reimplemented from Layer.

Definition at line 143 of file DepthwiseConvolution2dLayer.cpp.

References LayerWithParameters< DepthwiseConvolution2dDescriptor >::GetConnectedConstantAsInputTensors(), DepthwiseConvolution2dLayer::m_Bias, and DepthwiseConvolution2dLayer::m_Weight.

144 {
146 
147  if (!tensors.empty())
148  {
149  return tensors;
150  }
151 
152  // For API stability DO NOT ALTER order and add new members to the end of vector
153  return {m_Weight, m_Bias};
154 }
std::vector< std::reference_wrapper< std::shared_ptr< ConstTensorHandle > >> ConstantTensors
Definition: INetwork.hpp:114
std::shared_ptr< ConstTensorHandle > m_Bias
A unique pointer to store Bias values.
std::shared_ptr< ConstTensorHandle > m_Weight
A unique pointer to store Weight values.

◆ 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 82 of file DepthwiseConvolution2dLayer.cpp.

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, DataLayoutIndexed::GetHeightIndex(), DataLayoutIndexed::GetWidthIndex(), DepthwiseConvolution2dDescriptor::m_DataLayout, DepthwiseConvolution2dDescriptor::m_DilationX, DepthwiseConvolution2dDescriptor::m_DilationY, DepthwiseConvolution2dDescriptor::m_PadBottom, DepthwiseConvolution2dDescriptor::m_PadLeft, DepthwiseConvolution2dDescriptor::m_PadRight, DepthwiseConvolution2dDescriptor::m_PadTop, LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param, DepthwiseConvolution2dDescriptor::m_StrideX, DepthwiseConvolution2dDescriptor::m_StrideY, and armnn::NHWC.

Referenced by DepthwiseConvolution2dInferOutputShapeTest(), and DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs().

83 {
84  ARMNN_ASSERT(inputShapes.size() == 2);
85  const TensorShape& inputShape = inputShapes[0];
86  const TensorShape& filterShape = inputShapes[1];
87 
88  ARMNN_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Convolutions will always have 4D input.");
89 
92 
93  DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
94 
95  unsigned int inputBatchSize = inputShape[0];
96  unsigned int inputHeight = inputShape[dataLayoutIndex.GetHeightIndex()];
97  unsigned int inputWidth = inputShape[dataLayoutIndex.GetWidthIndex()];
98 
99  // Expected filter shape: [ 1, H, W, O ] - This shape does NOT depend on the data layout
100  // Namely: [ 1, filter height, filter width, output channels ]
101 
102  unsigned int filterHeight = filterShape[1];
103  unsigned int dilatedFilterHeight = filterHeight + (m_Param.m_DilationY - 1) * (filterHeight - 1);
104  unsigned int readHeight = (inputHeight + m_Param.m_PadTop + m_Param.m_PadBottom) - dilatedFilterHeight;
105  unsigned int outputHeight = 1 + (readHeight / m_Param.m_StrideY);
106 
107  unsigned int filterWidth = filterShape[2];
108  unsigned int dilatedFilterWidth = filterWidth + (m_Param.m_DilationX - 1) * (filterWidth - 1);
109  unsigned int readWidth = (inputWidth + m_Param.m_PadLeft + m_Param.m_PadRight) - dilatedFilterWidth;
110  unsigned int outputWidth = 1 + (readWidth / m_Param.m_StrideX);
111 
112  unsigned int outputChannels = filterShape[3];
113  unsigned int outputBatchSize = inputBatchSize;
114 
116  TensorShape{ outputBatchSize, outputHeight, outputWidth, outputChannels } :
117  TensorShape{ outputBatchSize, outputChannels, outputHeight, outputWidth };
118 
119  return std::vector<TensorShape>{ tensorShape };
120 }
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
uint32_t m_PadBottom
Padding bottom value in the height dimension.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
uint32_t m_PadLeft
Padding left value in the width dimension.
uint32_t m_DilationY
Dilation factor value for height dimension.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
uint32_t m_DilationX
Dilation factor value for width dimension.
uint32_t m_PadTop
Padding top value in 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_StrideY
Stride value when proceeding through input for the height dimension.
uint32_t m_PadRight
Padding right value in the width dimension.

◆ 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 DepthwiseConvolution2dLayer.cpp.

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

30 {
31  const std::vector<TensorShape>& inputShapes =
32  {
35  };
36  const TensorShape filterShape = inputShapes[1];
37  unsigned int inputChannels = filterShape[1];
38  unsigned int filterWidth = filterShape[3];
39  unsigned int filterHeight = filterShape[2];
40  unsigned int depthMultiplier = filterShape[0];
41 
42  fn("FilterWidth",std::to_string(filterWidth));
43  fn("FilterHeight",std::to_string(filterHeight));
44  fn("DepthMultiplier",std::to_string(depthMultiplier));
45  fn("InputChannels",std::to_string(inputChannels));
46 
48 }
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:206
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:324
virtual const TensorInfo & GetTensorInfo() const =0

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

Check if the input tensor shape(s) will lead to a valid configuration of DepthwiseConvolution2dLayer.

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

Implements Layer.

Definition at line 122 of file DepthwiseConvolution2dLayer.cpp.

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, CHECK_LOCATION, InputSlot::GetConnection(), Layer::GetInputSlot(), DepthwiseConvolution2dDescriptor::GetNumInputs(), Layer::GetOutputSlot(), TensorInfo::GetShape(), IOutputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), DepthwiseConvolution2dLayer::InferOutputShapes(), LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param, Layer::m_ShapeInferenceMethod, Layer::ValidateAndCopyShape(), Layer::VerifyLayerConnections(), and Layer::VerifyShapeInferenceType().

123 {
125 
126  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
127 
129 
130  ARMNN_ASSERT_MSG(GetInputSlot(1).GetConnection(),
131  "DepthwiseConvolution2dLayer: Weights data should not be null.");
132 
133  auto inferredShapes = InferOutputShapes({
136  });
137 
138  ARMNN_ASSERT(inferredShapes.size() == 1);
139 
140  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "DepthwiseConvolution2dLayer");
141 }
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.
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
const TensorShape & GetShape() const
Definition: Tensor.hpp:191
uint32_t GetNumInputs() const
Get the number of views/inputs.
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:491
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:206
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Definition: Layer.cpp:422
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:378
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:324
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:326
virtual const TensorInfo & GetTensorInfo() const =0
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:423

Member Data Documentation

◆ m_Bias

std::shared_ptr<ConstTensorHandle> m_Bias

A unique pointer to store Bias values.

Deprecated. Bias are stored in ConstantLayers now.

Definition at line 23 of file DepthwiseConvolution2dLayer.hpp.

Referenced by DepthwiseConvolution2dLayer::Clone(), DepthwiseConvolution2dLayer::CreateWorkload(), DepthwiseConvolution2dLayer::GetConstantTensorsByRef(), and TEST_SUITE().

◆ m_Weight

std::shared_ptr<ConstTensorHandle> m_Weight

A unique pointer to store Weight values.

Deprecated. Bias are stored in ConstantLayers now.

Definition at line 20 of file DepthwiseConvolution2dLayer.hpp.

Referenced by DepthwiseConvolution2dLayer::Clone(), DepthwiseConvolution2dLayer::CreateWorkload(), DepthwiseConvolution2dLayer::GetConstantTensorsByRef(), and TEST_SUITE().


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