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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
 
DepthwiseConvolution2dLayerClone (Graph &graph) const override
 
void ValidateTensorShapesFromInputs () override
 
std::vector< TensorShapeInferOutputShapes (const std::vector< TensorShape > &inputShapes) const override
 
void Accept (ILayerVisitor &visitor) const override
 
void SerializeLayerParameters (ParameterStringifyFunction &fn) const override
 
- Public Member Functions inherited from LayerWithParameters< DepthwiseConvolution2dDescriptor >
const DepthwiseConvolution2dDescriptorGetParameters () const
 
void SerializeLayerParameters (ParameterStringifyFunction &fn) const override
 
- 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)
 
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
 
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
 
unsigned int GetNumInputSlots () const override
 
unsigned int GetNumOutputSlots () const override
 
const InputSlotGetInputSlot (unsigned int index) const override
 
InputSlotGetInputSlot (unsigned int index) override
 
const OutputSlotGetOutputSlot (unsigned int index=0) const override
 
OutputSlotGetOutputSlot (unsigned int index=0) override
 
void SetGuid (LayerGuid guid)
 
LayerGuid GetGuid () const final
 
void AddRelatedLayerName (const std::string layerName)
 
const std::list< std::string > & GetRelatedLayerNames ()
 
virtual void Reparent (Graph &dest, std::list< Layer *>::const_iterator iterator)=0
 

Public Attributes

std::unique_ptr< ScopedCpuTensorHandlem_Weight
 A unique pointer to store Weight values. More...
 
std::unique_ptr< ScopedCpuTensorHandlem_Bias
 A unique pointer to store Bias values. More...
 

Protected Member Functions

 DepthwiseConvolution2dLayer (const DepthwiseConvolution2dDescriptor &param, const char *name)
 
 ~DepthwiseConvolution2dLayer ()=default
 Default destructor. More...
 
ConstantTensors GetConstantTensorsByRef () override
 
- 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...
 
- 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
 
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
 
- 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
 
- Protected Types inherited from Layer
using ConstantTensors = std::vector< std::reference_wrapper< std::unique_ptr< ScopedCpuTensorHandle > >>
 
- 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
std::vector< OutputHandlerm_OutputHandlers
 

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)

◆ ~DepthwiseConvolution2dLayer()

~DepthwiseConvolution2dLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Accept()

void Accept ( ILayerVisitor visitor) const
overridevirtual

Implements IConnectableLayer.

Definition at line 147 of file DepthwiseConvolution2dLayer.cpp.

References Layer::GetName(), LayerWithParameters< DepthwiseConvolution2dDescriptor >::GetParameters(), DepthwiseConvolution2dLayer::m_Bias, DepthwiseConvolution2dLayer::m_Weight, and ILayerVisitor::VisitDepthwiseConvolution2dLayer().

148 {
149  ConstTensor weightsTensor(m_Weight->GetTensorInfo(), m_Weight->Map(true));
150  Optional<ConstTensor> optionalBiasTensor = EmptyOptional();
151 
152  if (GetParameters().m_BiasEnabled)
153  {
154  ConstTensor biasTensor(m_Bias->GetTensorInfo(), m_Bias->Map(true));
155  optionalBiasTensor = Optional<ConstTensor>(biasTensor);
156  }
157 
158  visitor.VisitDepthwiseConvolution2dLayer(this, GetParameters(), weightsTensor, optionalBiasTensor, GetName());
159 }
const char * GetName() const override
Definition: Layer.hpp:305
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:199
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
virtual void VisitDepthwiseConvolution2dLayer(const IConnectableLayer *layer, const DepthwiseConvolution2dDescriptor &convolution2dDescriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr)=0
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
const DepthwiseConvolution2dDescriptor & GetParameters() const

◆ 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 ? std::make_unique<ScopedCpuTensorHandle>(*m_Weight) : nullptr;
72 
73  if (layer->m_Param.m_BiasEnabled)
74  {
75  layer->m_Bias = m_Bias ? std::make_unique<ScopedCpuTensorHandle>(*m_Bias) : nullptr;
76  }
77 
78  return std::move(layer);
79 }
const char * GetName() const override
Definition: Layer.hpp:305
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).

◆ 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 51 of file DepthwiseConvolution2dLayer.cpp.

References IWorkloadFactory::CreateDepthwiseConvolution2d(), DepthwiseConvolution2dLayer::m_Bias, DepthwiseConvolution2dQueueDescriptor::m_Bias, DepthwiseConvolution2dDescriptor::m_BiasEnabled, LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param, DepthwiseConvolution2dLayer::m_Weight, DepthwiseConvolution2dQueueDescriptor::m_Weight, and LayerWithParameters< DepthwiseConvolution2dDescriptor >::PrepInfoAndDesc().

52 {
53  // on this level constant data should not be released..
54  BOOST_ASSERT_MSG(m_Weight != nullptr, "DepthwiseConvolution2dLayer: Weights data should not be null.");
55 
57 
58  descriptor.m_Weight = m_Weight.get();
59 
61  {
62  BOOST_ASSERT_MSG(m_Bias != nullptr, "DepthwiseConvolution2dLayer: Bias data should not be null.");
63  descriptor.m_Bias = m_Bias.get();
64  }
65  return factory.CreateDepthwiseConvolution2d(descriptor, PrepInfoAndDesc(descriptor));
66 }
virtual std::unique_ptr< IWorkload > CreateDepthwiseConvolution2d(const DepthwiseConvolution2dQueueDescriptor &descriptor, const WorkloadInfo &info) const
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.
bool m_BiasEnabled
Enable/disable bias.

◆ 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.

Reimplemented from Layer.

Definition at line 142 of file DepthwiseConvolution2dLayer.cpp.

References DepthwiseConvolution2dLayer::m_Bias, and DepthwiseConvolution2dLayer::m_Weight.

143 {
144  return {m_Weight, m_Bias};
145 }
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
std::unique_ptr< ScopedCpuTensorHandle > 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 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  BOOST_ASSERT(inputShapes.size() == 2);
85  const TensorShape& inputShape = inputShapes[0];
86  const TensorShape& filterShape = inputShapes[1];
87 
88  BOOST_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Convolutions will always have 4D input.");
89 
90  DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
91 
92  unsigned int inputBatchSize = inputShape[0];
93  unsigned int inputHeight = inputShape[dataLayoutIndex.GetHeightIndex()];
94  unsigned int inputWidth = inputShape[dataLayoutIndex.GetWidthIndex()];
95  unsigned int inputChannels = inputShape[dataLayoutIndex.GetChannelsIndex()];
96 
97  // Expected filter shape: [ M, I, H, W ] - This shape does NOT depend on the data layout
98  // Namely: [ depth multiplier, input channels, filter height, filter width ]
99  // Output channels = input channels * depthMultiplier
100  unsigned int depthMultiplier = filterShape[0];
101 
102  unsigned int filterHeight = filterShape[2];
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[3];
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 = inputChannels * depthMultiplier;
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 }
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 factor value for width dimension.
uint32_t m_PadLeft
Padding left value in the width dimension.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
uint32_t m_PadTop
Padding top value in the height dimension.
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
uint32_t m_DilationY
Dilation factor value for 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(), DepthwiseConvolution2dDescriptor::m_DataLayout, LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param, DepthwiseConvolution2dLayer::m_Weight, and LayerWithParameters< Parameters >::SerializeLayerParameters().

30 {
31  const std::vector<TensorShape>& inputShapes =
32  {
34  m_Weight->GetTensorInfo().GetShape()
35  };
36  const TensorShape filterShape = inputShapes[1];
37  DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
38  unsigned int inputChannels = filterShape[1];
39  unsigned int filterWidth = filterShape[3];
40  unsigned int filterHeight = filterShape[2];
41  unsigned int depthMultiplier = filterShape[0];
42 
43  fn("FilterWidth",std::to_string(filterWidth));
44  fn("FilterHeight",std::to_string(filterHeight));
45  fn("DepthMultiplier",std::to_string(depthMultiplier));
46  fn("InputChannels",std::to_string(inputChannels));
47 
49 }
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
virtual const TensorInfo & GetTensorInfo() const =0
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:199
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
const TensorShape & GetShape() const
Definition: Tensor.hpp:88
const InputSlot & GetInputSlot(unsigned int index) const override
Definition: Layer.hpp:310

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

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

Implements Layer.

Definition at line 122 of file DepthwiseConvolution2dLayer.cpp.

References CHECK_LOCATION, InputSlot::GetConnection(), Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), IOutputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), DepthwiseConvolution2dLayer::InferOutputShapes(), DepthwiseConvolution2dLayer::m_Weight, and Layer::VerifyLayerConnections().

123 {
125 
126  // on this level constant data should not be released..
127  BOOST_ASSERT_MSG(m_Weight != nullptr, "DepthwiseConvolution2dLayer: Weights data should not be null.");
128 
129  auto inferredShapes = InferOutputShapes({
131  m_Weight->GetTensorInfo().GetShape()
132  });
133 
134  BOOST_ASSERT(inferredShapes.size() == 1);
135 
136  ConditionalThrowIfNotEqual<LayerValidationException>(
137  "DepthwiseConvolution2dLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
139  inferredShapes[0]);
140 }
virtual const TensorInfo & GetTensorInfo() const =0
#define CHECK_LOCATION()
Definition: Exceptions.hpp:169
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:199
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:337
std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override
const TensorShape & GetShape() const
Definition: Tensor.hpp:88
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:63
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Definition: Layer.hpp:312
const InputSlot & GetInputSlot(unsigned int index) const override
Definition: Layer.hpp:310

Member Data Documentation

◆ m_Bias

◆ m_Weight


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