ArmNN
 21.02
Pooling2dLayer Class Reference

This layer represents a pooling 2d operation. More...

#include <Pooling2dLayer.hpp>

Inheritance diagram for Pooling2dLayer:
LayerWithParameters< Pooling2dDescriptor > Layer IConnectableLayer

Public Member Functions

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the Pooling2d type. More...
 
Pooling2dLayerClone (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 Pooling2dLayer. 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 Accept (ILayerVisitor &visitor) const override
 Apply a visitor to this layer. More...
 
- Public Member Functions inherited from LayerWithParameters< Pooling2dDescriptor >
const Pooling2dDescriptorGetParameters () 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)
 

Protected Member Functions

 Pooling2dLayer (const Pooling2dDescriptor &param, const char *name)
 Constructor to create a Pooling2dLayer. More...
 
 ~Pooling2dLayer ()=default
 Default destructor. More...
 
- Protected Member Functions inherited from LayerWithParameters< Pooling2dDescriptor >
 LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const Pooling2dDescriptor &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< Pooling2dDescriptor >
using DescriptorType = Pooling2dDescriptor
 
- Protected Types inherited from Layer
using ConstantTensors = std::vector< std::reference_wrapper< std::unique_ptr< ScopedCpuTensorHandle > >>
 
- Protected Attributes inherited from LayerWithParameters< Pooling2dDescriptor >
Pooling2dDescriptor 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 pooling 2d operation.

Definition at line 13 of file Pooling2dLayer.hpp.

Constructor & Destructor Documentation

◆ Pooling2dLayer()

Pooling2dLayer ( const Pooling2dDescriptor param,
const char *  name 
)
protected

Constructor to create a Pooling2dLayer.

Parameters
[in]paramPooling2dDescriptor to configure the pooling2d operation.
[in]nameOptional name for the layer.

Definition at line 22 of file Pooling2dLayer.cpp.

References armnn::Pooling2d().

23  : LayerWithParameters(1, 1, LayerType::Pooling2d, param, name)
24 {
25 }
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const Pooling2dDescriptor &param, const char *name)

◆ ~Pooling2dLayer()

~Pooling2dLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Accept()

void Accept ( ILayerVisitor visitor) const
overridevirtual

Apply a visitor to this layer.

Implements IConnectableLayer.

Definition at line 120 of file Pooling2dLayer.cpp.

References Layer::GetName(), LayerWithParameters< Pooling2dDescriptor >::GetParameters(), and ILayerVisitor::VisitPooling2dLayer().

121 {
122  visitor.VisitPooling2dLayer(this, GetParameters(), GetName());
123 }
const Pooling2dDescriptor & GetParameters() const
virtual void VisitPooling2dLayer(const IConnectableLayer *layer, const Pooling2dDescriptor &pooling2dDescriptor, const char *name=nullptr)=0
Function that a pooling layer should call back to when its Accept(ILayerVisitor&) function is invoked...
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:311

◆ Clone()

Pooling2dLayer * 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 35 of file Pooling2dLayer.cpp.

References Layer::GetName(), and LayerWithParameters< Pooling2dDescriptor >::m_Param.

36 {
37  return CloneBase<Pooling2dLayer>(graph, m_Param, GetName());
38 }
Pooling2dDescriptor 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 Pooling2d 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 27 of file Pooling2dLayer.cpp.

References IWorkloadFactory::CreatePooling2d(), LayerWithParameters< Pooling2dDescriptor >::PrepInfoAndDesc(), and Layer::SetAdditionalInfo().

28 {
29  Pooling2dQueueDescriptor descriptor;
30  SetAdditionalInfo(descriptor);
31 
32  return factory.CreatePooling2d(descriptor, PrepInfoAndDesc(descriptor));
33 }
virtual std::unique_ptr< IWorkload > CreatePooling2d(const Pooling2dQueueDescriptor &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.

◆ 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 40 of file Pooling2dLayer.cpp.

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, armnn::Ceiling, armnn::Floor, DataLayoutIndexed::GetChannelsIndex(), DataLayoutIndexed::GetHeightIndex(), DataLayoutIndexed::GetWidthIndex(), Pooling2dDescriptor::m_DataLayout, Pooling2dDescriptor::m_OutputShapeRounding, Pooling2dDescriptor::m_PadBottom, Pooling2dDescriptor::m_PadLeft, Pooling2dDescriptor::m_PadRight, Pooling2dDescriptor::m_PadTop, LayerWithParameters< Pooling2dDescriptor >::m_Param, Pooling2dDescriptor::m_PoolHeight, Pooling2dDescriptor::m_PoolWidth, Pooling2dDescriptor::m_StrideX, Pooling2dDescriptor::m_StrideY, and armnn::NHWC.

Referenced by Pooling2dLayer::ValidateTensorShapesFromInputs().

41 {
42  ARMNN_ASSERT(inputShapes.size() == 1);
43  const TensorShape& inputShape = inputShapes[0];
44  const DataLayoutIndexed dimensionIndices = m_Param.m_DataLayout;
45 
46  // If we support multiple batch dimensions in the future, then this assert will need to change.
47  ARMNN_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Pooling2dLayer will always have 4D input.");
48 
49  unsigned int inWidth = inputShape[dimensionIndices.GetWidthIndex()];
50  unsigned int inHeight = inputShape[dimensionIndices.GetHeightIndex()];
51  unsigned int inChannels = inputShape[dimensionIndices.GetChannelsIndex()];
52  unsigned int inBatchSize = inputShape[0];
53 
54  bool isGlobalPooling = (m_Param.m_StrideX==0 && m_Param.m_StrideY==0);
55  unsigned int outWidth = 1;
56  unsigned int outHeight = 1;
57  if (!isGlobalPooling)
58  {
60  "Stride can only be zero when performing global pooling");
61 
62  auto CalcSize = [](auto inSize, auto lowPad, auto highPad, auto poolSize, auto stride, auto outputShapeRounding)
63  {
64  unsigned int readSize = inSize + lowPad + highPad - poolSize;
65  float div = static_cast<float>(readSize) / static_cast<float>(stride);
66 
67  unsigned int size = 0;
68  switch (outputShapeRounding)
69  {
71  size = static_cast<unsigned int>(ceil(div)) + 1;
72  break;
74  size = static_cast<unsigned int>(floor(div)) + 1;
75  break;
76  default:
77  ARMNN_ASSERT_MSG(false, "Unsupported Output Shape Rounding");
78  }
79 
80  // MakeS sure that border operations will start from inside the input and not the padded area.
81  // This is what both Caffe and CL do...
82  if ((size - 1)*stride >= inSize + lowPad)
83  {
84  --size;
85  }
86 
87  return size;
88  };
89 
90  outWidth = CalcSize(inWidth, m_Param.m_PadLeft, m_Param.m_PadRight, m_Param.m_PoolWidth, m_Param.m_StrideX,
92  outHeight = CalcSize(inHeight, m_Param.m_PadTop, m_Param.m_PadBottom, m_Param.m_PoolHeight, m_Param.m_StrideY,
94  }
95  unsigned int outChannels = inChannels;
96  unsigned int outBatchSize = inBatchSize;
97 
99  TensorShape( { outBatchSize, outHeight, outWidth, outChannels } ) :
100  TensorShape( { outBatchSize, outChannels, outHeight, outWidth });
101 
102  return std::vector<TensorShape>({ tensorShape });
103 }
uint32_t m_PadBottom
Padding bottom value in the height dimension.
Pooling2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
unsigned int GetWidthIndex() const
uint32_t m_PadLeft
Padding left value in the width dimension.
uint32_t m_PoolWidth
Pooling width value.
uint32_t m_PadTop
Padding top value in the height dimension.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
unsigned int GetHeightIndex() const
uint32_t m_PoolHeight
Pooling height value.
uint32_t m_PadRight
Padding right value in the width 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
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
OutputShapeRounding m_OutputShapeRounding
The rounding method for the output shape. (Floor, Ceiling).
unsigned int GetChannelsIndex() const
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

Check if the input tensor shape(s) will lead to a valid configuration of Pooling2dLayer.

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

Implements Layer.

Definition at line 105 of file Pooling2dLayer.cpp.

References ARMNN_ASSERT, CHECK_LOCATION, InputSlot::GetConnection(), Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), IOutputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), Pooling2dLayer::InferOutputShapes(), Layer::m_ShapeInferenceMethod, Layer::ValidateAndCopyShape(), Layer::VerifyLayerConnections(), and Layer::VerifyShapeInferenceType().

106 {
108 
109  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
110 
112 
113  auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape() });
114 
115  ARMNN_ASSERT(inferredShapes.size() == 1);
116 
117  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "Pooling2dLayer");
118 }
const TensorShape & GetShape() const
Definition: Tensor.hpp:187
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:432
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:392
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:348
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:316
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
#define CHECK_LOCATION()
Definition: Exceptions.hpp:197
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.
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
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: