ArmNN
 20.02
PreluLayer Class Reference

#include <PreluLayer.hpp>

Inheritance diagram for PreluLayer:
Layer IConnectableLayer

Public Member Functions

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the PReLU type. More...
 
PreluLayerClone (Graph &graph) const override
 Creates a dynamically-allocated copy of this layer. 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 ValidateTensorShapesFromInputs () override
 Check if the input tensor shape(s) will lead to a valid configuration of PreluLayer. More...
 
void Accept (ILayerVisitor &visitor) const override
 Apply a visitor to this layer. 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)
 
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 SerializeLayerParameters (ParameterStringifyFunction &fn) const
 Helper to serialize the layer parameters to string. More...
 
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
 

Protected Member Functions

 PreluLayer (const char *name)
 Constructor to create a PreluLayer. More...
 
 ~PreluLayer ()=default
 Default destructor. 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
 
virtual ConstantTensors GetConstantTensorsByRef ()
 
- Protected Member Functions inherited from IConnectableLayer
 ~IConnectableLayer ()
 Objects are not deletable via the handle. More...
 

Additional Inherited Members

- Protected Types inherited from Layer
using ConstantTensors = std::vector< std::reference_wrapper< std::unique_ptr< ScopedCpuTensorHandle > >>
 
- Protected Attributes inherited from Layer
std::vector< OutputHandlerm_OutputHandlers
 

Detailed Description

Definition at line 14 of file PreluLayer.hpp.

Constructor & Destructor Documentation

◆ PreluLayer()

PreluLayer ( const char *  name)
protected

Constructor to create a PreluLayer.

Parameters
[in]nameOptional name for the layer.

Definition at line 17 of file PreluLayer.cpp.

References armnn::Prelu.

18  : Layer(2, 1, LayerType::Prelu, name)
19 {}
Layer(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char *name)
Definition: Layer.cpp:213

◆ ~PreluLayer()

~PreluLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Accept()

void Accept ( ILayerVisitor visitor) const
overridevirtual

Apply a visitor to this layer.

Implements IConnectableLayer.

Definition at line 115 of file PreluLayer.cpp.

References Layer::GetName(), and ILayerVisitor::VisitPreluLayer().

116 {
117  visitor.VisitPreluLayer(this, GetName());
118 }
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:305

◆ Clone()

PreluLayer * 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 28 of file PreluLayer.cpp.

References Layer::GetName().

29 {
30  auto layer = CloneBase<PreluLayer>(graph, GetName());
31 
32  return std::move(layer);
33 }
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:305

◆ CreateWorkload()

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

Makes a workload for the PReLU 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 21 of file PreluLayer.cpp.

References IWorkloadFactory::CreatePrelu(), and Layer::PrepInfoAndDesc().

22 {
23  PreluQueueDescriptor descriptor;
24 
25  return factory.CreatePrelu(descriptor, PrepInfoAndDesc(descriptor));
26 }
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.
Definition: Layer.hpp:351

◆ 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 35 of file PreluLayer.cpp.

References TensorShape::GetNumDimensions(), and armnn::numeric_cast().

Referenced by PreluInferOutputShapeImpl(), and PreluLayer::ValidateTensorShapesFromInputs().

36 {
37  BOOST_ASSERT(inputShapes.size() == 2);
38 
39  const TensorShape& inputShape = inputShapes[0];
40  const TensorShape& alphaShape = inputShapes[1];
41 
42  const unsigned int inputShapeDimensions = inputShape.GetNumDimensions();
43  const unsigned int alphaShapeDimensions = alphaShape.GetNumDimensions();
44 
45  BOOST_ASSERT(inputShapeDimensions > 0);
46  BOOST_ASSERT(alphaShapeDimensions > 0);
47 
48  // The size of the output is the maximum size along each dimension of the input operands,
49  // it starts with the trailing dimensions, and works its way forward
50 
51  unsigned int outputDimensions = std::max(inputShapeDimensions, alphaShapeDimensions);
52 
53  TensorShape outputShape(outputDimensions);
54 
55  int inputShapeIndex = boost::numeric_cast<int>(inputShapeDimensions) - 1;
56  int alphaShapeIndex = boost::numeric_cast<int>(alphaShapeDimensions) - 1;
57  unsigned int outputShapeIndex = outputDimensions - 1;
58 
59  // Loop backwards through the common part of the shapes
60  while (inputShapeIndex >= 0 && alphaShapeIndex >= 0)
61  {
62  unsigned int inputDimension = inputShape[boost::numeric_cast<unsigned int>(inputShapeIndex)];
63  unsigned int alphaDimension = alphaShape[boost::numeric_cast<unsigned int>(alphaShapeIndex)];
64 
65  // Check that the inputs are broadcast compatible
66  BOOST_ASSERT_MSG(inputDimension == alphaDimension || inputDimension == 1 || alphaDimension == 1,
67  "PreluLayer: Dimensions should either match or one should be of size 1");
68 
69  outputShape[outputShapeIndex] = std::max(inputDimension, alphaDimension);
70 
71  inputShapeIndex--;
72  alphaShapeIndex--;
73  outputShapeIndex--;
74  }
75 
76  // Loop backwards through the remaing part of the input shape (if any)
77  while (inputShapeIndex >= 0)
78  {
79  outputShape[outputShapeIndex] = inputShape[boost::numeric_cast<unsigned int>(inputShapeIndex)];
80 
81  inputShapeIndex--;
82  outputShapeIndex--;
83  }
84 
85  // Loop backwards through the remaing part of the alpha shape (if any)
86  while (alphaShapeIndex >= 0)
87  {
88  outputShape[outputShapeIndex] = alphaShape[boost::numeric_cast<unsigned int>(alphaShapeIndex)];
89 
90  alphaShapeIndex--;
91  outputShapeIndex--;
92  }
93 
94  return { outputShape };
95 }
std::enable_if_t< std::is_unsigned< Source >::value &&std::is_unsigned< Dest >::value, Dest > numeric_cast(Source source)
Definition: NumericCast.hpp:33

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

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

Implements Layer.

Definition at line 97 of file PreluLayer.cpp.

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

98 {
100 
101  std::vector<TensorShape> inferredShapes = InferOutputShapes(
102  {
105  });
106 
107  BOOST_ASSERT(inferredShapes.size() == 1);
108 
109  ConditionalThrowIfNotEqual<LayerValidationException>(
110  "PreluLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
112  inferredShapes[0]);
113 }
const TensorShape & GetShape() const
Definition: Tensor.hpp:88
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:199
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:338
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:310
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.
Definition: PreluLayer.cpp:35
#define CHECK_LOCATION()
Definition: Exceptions.hpp:192
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:312
virtual const TensorInfo & GetTensorInfo() const =0
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:63

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