ArmNN
 24.08
ElementwiseBinaryLayer Class Reference

This layer represents a elementwiseBinary operation. More...

#include <ElementwiseBinaryLayer.hpp>

Inheritance diagram for ElementwiseBinaryLayer:
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Collaboration diagram for ElementwiseBinaryLayer:
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Public Member Functions

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the elementwiseBinary type. More...
 
ElementwiseBinaryLayerClone (Graph &graph) const override
 Creates a dynamically-allocated copy of this layer. More...
 
std::vector< TensorShapeInferOutputShapes (const std::vector< TensorShape > &inputShapes) const override
 Returns inputShapes by default. More...
 
void ValidateTensorShapesFromInputs () override
 Check if the input tensor shape(s) will lead to a valid configuration of ElementwiseBinaryLayer. More...
 
void ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this layer. More...
 
- Public Member Functions inherited from LayerWithParameters< ElementwiseBinaryDescriptor >
const ElementwiseBinaryDescriptorGetParameters () 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) override
 Set the backend of the IConnectableLayer. More...
 
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)
 
virtual const BaseDescriptorGetParameters () const override
 If the layer has a descriptor return it. More...
 

Protected Member Functions

 ElementwiseBinaryLayer (const ElementwiseBinaryDescriptor &param, const char *name)
 Constructor to create a ElementwiseBinaryLayer. More...
 
 ~ElementwiseBinaryLayer ()=default
 Default destructor. More...
 
- Protected Member Functions inherited from LayerWithParameters< ElementwiseBinaryDescriptor >
 LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const ElementwiseBinaryDescriptor &param, const char *name)
 
 ~LayerWithParameters ()=default
 
WorkloadInfo PrepInfoAndDesc (QueueDescriptor &descriptor) const
 Helper function to reduce duplication in *Layer::CreateWorkload. More...
 
void ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this layer. More...
 
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 *Layer::CreateWorkload. More...
 
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. More...
 

Additional Inherited Members

- Public Types inherited from LayerWithParameters< ElementwiseBinaryDescriptor >
using DescriptorType = ElementwiseBinaryDescriptor
 
- 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< ElementwiseBinaryDescriptor >
ElementwiseBinaryDescriptor 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 elementwiseBinary operation.

Definition at line 14 of file ElementwiseBinaryLayer.hpp.

Constructor & Destructor Documentation

◆ ElementwiseBinaryLayer()

ElementwiseBinaryLayer ( const ElementwiseBinaryDescriptor param,
const char *  name 
)
protected

Constructor to create a ElementwiseBinaryLayer.

Parameters
[in]paramElementwiseBinaryDescriptor to configure the ElementwiseBinaryLayer
[in]nameOptional name for the layer

Definition at line 13 of file ElementwiseBinaryLayer.cpp.

15 {
16 }

References armnn::ElementwiseBinary.

◆ ~ElementwiseBinaryLayer()

~ElementwiseBinaryLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

ElementwiseBinaryLayer * 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 26 of file ElementwiseBinaryLayer.cpp.

27 {
28  return CloneBase<ElementwiseBinaryLayer>(graph, m_Param, GetName());
29 }

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

◆ CreateWorkload()

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

Makes a workload for the elementwiseBinary 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 18 of file ElementwiseBinaryLayer.cpp.

19 {
20  ElementwiseBinaryQueueDescriptor descriptor;
21  SetAdditionalInfo(descriptor);
22 
23  return factory.CreateWorkload(LayerType::ElementwiseBinary, descriptor, PrepInfoAndDesc(descriptor));
24 }

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

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy strategy) const
overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 97 of file ElementwiseBinaryLayer.cpp.

98 {
99  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
100 }

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

◆ InferOutputShapes()

std::vector< TensorShape > InferOutputShapes ( const std::vector< TensorShape > &  inputShapes) const
overridevirtual

Returns inputShapes by default.

Parameters
[in]inputShapesThe input shapes layer has.
Returns
A vector to the inferred output shape.

Reimplemented from Layer.

Definition at line 31 of file ElementwiseBinaryLayer.cpp.

32 {
33  if (inputShapes.size() != 2)
34  {
35  throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
36  "\" - should be \"2\".");
37  }
38 
39  TensorShape input0 = inputShapes[0];
40  TensorShape input1 = inputShapes[1];
41 
42  if (inputShapes[0].GetNumDimensions() < inputShapes[1].GetNumDimensions())
43  {
44  input1 = inputShapes[0];
45  input0 = inputShapes[1];
46  }
47 
48  unsigned int numDims = input0.GetNumDimensions();
49  unsigned int shiftedDims = input0.GetNumDimensions() - input1.GetNumDimensions();
50 
51  // Get the max of the inputs.
52  std::vector<unsigned int> dims(numDims);
53  for (unsigned int i = shiftedDims; i < numDims; i++)
54  {
55  unsigned int dim0 = input0[i];
56  unsigned int dim1 = input1[i - shiftedDims];
57 
58  // Validate inputs are broadcast compatible.
59  if (dim0 != dim1 && dim0 != 1 && dim1 != 1)
60  {
61  throw armnn::Exception("Dimensions should either match or one should be of size 1.");
62  }
63 
64  dims[i] = std::max(dim0, dim1);
65  }
66 
67  // Fill in the rest of the shifted dimensions.
68  for (unsigned int i = 0; i < shiftedDims; i++)
69  {
70  dims[i] = input0[i];
71  }
72 
73  return std::vector<TensorShape>({ TensorShape(numDims, dims.data()) });
74 }

References TensorShape::GetNumDimensions().

Referenced by ElementwiseBinaryLayer::ValidateTensorShapesFromInputs().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

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

Implements Layer.

Definition at line 76 of file ElementwiseBinaryLayer.cpp.

77 {
79 
80  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
81 
83 
84  auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetTensorInfo().GetShape(),
86 
87  if (inferredShapes.size() != 1)
88  {
89  throw armnn::LayerValidationException("inferredShapes has "
90  + std::to_string(inferredShapes.size()) +
91  " elements - should only have 1.");
92  }
93 
94  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, GetLayerTypeAsCString(GetType()));
95 }

References CHECK_LOCATION, Layer::GetInputSlot(), armnn::GetLayerTypeAsCString(), Layer::GetOutputSlot(), TensorInfo::GetShape(), InputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), Layer::GetType(), ElementwiseBinaryLayer::InferOutputShapes(), Layer::m_ShapeInferenceMethod, Layer::ValidateAndCopyShape(), Layer::VerifyLayerConnections(), and Layer::VerifyShapeInferenceType().


The documentation for this class was generated from the following files:
armnn::GetLayerTypeAsCString
const char * GetLayerTypeAsCString(LayerType type)
Definition: InternalTypes.cpp:13
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:100
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
armnn::Layer::ValidateAndCopyShape
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Definition: Layer.cpp:457
armnn::Layer::GetOutputSlot
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:339
armnn::ElementwiseBinaryLayer::InferOutputShapes
std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override
Returns inputShapes by default.
Definition: ElementwiseBinaryLayer.cpp:31
armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:337
armnn::LayerWithParameters< ElementwiseBinaryDescriptor >::GetParameters
const ElementwiseBinaryDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
armnn::LayerType::ElementwiseBinary
@ ElementwiseBinary
armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:332
armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:614
armnn::LayerWithParameters< ElementwiseBinaryDescriptor >::m_Param
ElementwiseBinaryDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::LayerWithParameters< ElementwiseBinaryDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
armnn::LayerValidationException
Definition: Exceptions.hpp:105
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:526
armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:303
armnn::Exception
Base class for all ArmNN exceptions so that users can filter to just those.
Definition: Exceptions.hpp:46
armnn::Layer::GetType
LayerType GetType() const override
Returns the armnn::LayerType of this layer.
Definition: Layer.hpp:286
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:410
armnn::LayerWithParameters< ElementwiseBinaryDescriptor >::LayerWithParameters
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const ElementwiseBinaryDescriptor &param, const char *name)
Definition: LayerWithParameters.hpp:30
armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:441