ArmNN
 24.02
BatchMatMulLayer Class Reference

#include <BatchMatMulLayer.hpp>

Inheritance diagram for BatchMatMulLayer:
[legend]
Collaboration diagram for BatchMatMulLayer:
[legend]

Public Member Functions

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the BatchMatMul type. More...
 
BatchMatMulLayerClone (Graph &graph) const override
 Creates a dynamically-allocated copy of this layer. More...
 
std::vector< TensorShapeInferOutputShapes (const std::vector< TensorShape > &inputShapes) const override
 Infers the output shape from the given input shapes. More...
 
void ValidateTensorShapesFromInputs () override
 Check if the input tensor shapes will lead to a valid configuration of BatchMatMulLayer. More...
 
- Public Member Functions inherited from LayerWithParameters< BatchMatMulDescriptor >
const BatchMatMulDescriptorGetParameters () 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

 BatchMatMulLayer (const BatchMatMulDescriptor &param, const char *name)
 Constructor to create a BatchMatMulLayer. More...
 
 ~BatchMatMulLayer ()=default
 Default destructor. More...
 
- Protected Member Functions inherited from LayerWithParameters< BatchMatMulDescriptor >
 LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const BatchMatMulDescriptor &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< BatchMatMulDescriptor >
using DescriptorType = BatchMatMulDescriptor
 
- 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< BatchMatMulDescriptor >
BatchMatMulDescriptor 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

Definition at line 13 of file BatchMatMulLayer.hpp.

Constructor & Destructor Documentation

◆ BatchMatMulLayer()

BatchMatMulLayer ( const BatchMatMulDescriptor param,
const char *  name 
)
protected

Constructor to create a BatchMatMulLayer.

Parameters
[in]paramBatchMatMulDescriptor to configure optional parameters for batch matrix multiplication
[in]nameOptional name for the layer

Definition at line 14 of file BatchMatMulLayer.cpp.

15  : LayerWithParameters(2, 1, LayerType::BatchMatMul, param, name)
16 {}

◆ ~BatchMatMulLayer()

~BatchMatMulLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

BatchMatMulLayer * 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 BatchMatMulLayer.cpp.

27 {
28  auto layer = CloneBase<BatchMatMulLayer>(graph, m_Param, GetName());
29 
30  return std::move(layer);
31 }

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

◆ CreateWorkload()

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

Makes a workload for the BatchMatMul 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 BatchMatMulLayer.cpp.

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

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

◆ InferOutputShapes()

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

Infers the output shape from the given input shapes.

Parameters
[in]inputShapesThe vector of input shapes for BatchMatMul.
Returns
A vector of inferred output shape.

Reimplemented from Layer.

Definition at line 33 of file BatchMatMulLayer.cpp.

34 {
35  ARMNN_ASSERT(inputShapes.size() == 2);
36 
37  TensorShape inputXShape = inputShapes[0];
38  TensorShape inputYShape = inputShapes[1];
39 
40  // Adjoint is assumed to be square, but we will apply the permute anyway
42  {
44  inputXShape);
45  inputXShape = armnnUtils::Permuted(inputXShape, permuteVec);
46  }
48  {
50  inputYShape);
51  inputYShape = armnnUtils::Permuted(inputYShape, permuteVec);
52  }
53 
54  TensorShape& longerInput = inputXShape.GetNumDimensions() >= inputYShape.GetNumDimensions()?
55  inputXShape : inputYShape;
56  TensorShape& shorterInput = inputXShape.GetNumDimensions() >= inputYShape.GetNumDimensions()?
57  inputYShape : inputXShape;
58 
59  unsigned int inputNumDimsOffset = longerInput.GetNumDimensions() - shorterInput.GetNumDimensions();
60 
61  unsigned int outputNumDimensions = longerInput.GetNumDimensions();
62 
63  std::vector<unsigned int> tensorDimensions(outputNumDimensions, 0);
64 
65  const auto& longerInputDataLayout = inputXShape.GetNumDimensions() >= inputYShape.GetNumDimensions()?
67  auto longerAxesToMul = BatchMatMulDescriptor::GetAxesToMul(longerInputDataLayout,
68  longerInput);
69 
70  for (unsigned int i = 0; i < outputNumDimensions; ++i)
71  {
72  if (i == longerAxesToMul.first)
73  {
74  tensorDimensions[i] = &shorterInput == &inputXShape ? inputXShape[i - inputNumDimsOffset] : inputXShape[i];
75  }
76  else if(i == longerAxesToMul.second)
77  {
78  tensorDimensions[i] = &shorterInput == &inputYShape ? inputYShape[i - inputNumDimsOffset] : inputYShape[i];
79  }
80  else // The other dimensions not to be multiplied (but may be broadcasted)
81  {
82  // Does NOT validate whether it's a valid broadcast - that's done in the validate func in WorkloadData.cpp
83  tensorDimensions[i] = static_cast<int>(i) - static_cast<int>(inputNumDimsOffset) < 0 ?
84  longerInput[i] :
85  std::max(longerInput[i], shorterInput[i - inputNumDimsOffset]);
86  }
87  }
88 
89  auto outputShape = TensorShape(outputNumDimensions, tensorDimensions.data());
90  return std::vector<TensorShape>({ outputShape });
91 }

References ARMNN_ASSERT, BatchMatMulDescriptor::GetAxesToMul(), TensorShape::GetNumDimensions(), BatchMatMulDescriptor::GetPermuteVec(), BatchMatMulDescriptor::m_AdjointX, BatchMatMulDescriptor::m_AdjointY, BatchMatMulDescriptor::m_DataLayoutX, BatchMatMulDescriptor::m_DataLayoutY, LayerWithParameters< BatchMatMulDescriptor >::m_Param, BatchMatMulDescriptor::m_TransposeX, BatchMatMulDescriptor::m_TransposeY, and armnnUtils::Permuted().

Referenced by BatchMatMulLayer::ValidateTensorShapesFromInputs().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

Check if the input tensor shapes will lead to a valid configuration of BatchMatMulLayer.

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

Implements Layer.

Definition at line 93 of file BatchMatMulLayer.cpp.

94 {
96 
97  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
98 
100 
101  auto inferredShapes = InferOutputShapes({
104 
105  ARMNN_ASSERT(inferredShapes.size() == 1);
106 
107  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "BatchMatMulLayer");
108 }

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


The documentation for this class was generated from the following files:
ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
armnn::BatchMatMulDescriptor::m_TransposeX
bool m_TransposeX
Transpose the slices of each input tensor Transpose and Adjoint can not both be set to true for the s...
Definition: Descriptors.hpp:1612
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92
armnn::BatchMatMulDescriptor::m_AdjointX
bool m_AdjointX
Adjoint the slices of each input tensor Transpose and Adjoint can not both be set to true for the sam...
Definition: Descriptors.hpp:1617
armnn::BatchMatMulDescriptor::GetAxesToMul
static std::pair< unsigned int, unsigned int > GetAxesToMul(DataLayout dataLayout, const TensorShape &tensorShape)
Static helper to get the two axes (for each input) for multiplication.
Definition: Descriptors.cpp:484
armnn::BatchMatMulDescriptor::m_DataLayoutX
DataLayout m_DataLayoutX
Data layout of each input tensor, such as NHWC/NDHWC (leave as default for arbitrary layout)
Definition: Descriptors.hpp:1621
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:435
armnn::BatchMatMulDescriptor::GetPermuteVec
static PermutationVector GetPermuteVec(DataLayout dataLayout, const TensorShape &tensorShape)
Static helper to get the axes which will be transposed.
Definition: Descriptors.cpp:522
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::BatchMatMulDescriptor::m_AdjointY
bool m_AdjointY
Definition: Descriptors.hpp:1618
armnnUtils::Permuted
armnn::TensorShape Permuted(const armnn::TensorShape &srcShape, const armnn::PermutationVector &mappings)
Definition: Permute.cpp:125
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::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:592
armnn::LayerWithParameters< BatchMatMulDescriptor >::m_Param
BatchMatMulDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::LayerWithParameters< BatchMatMulDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
armnn::BatchMatMulDescriptor::m_TransposeY
bool m_TransposeY
Definition: Descriptors.hpp:1613
armnn::BatchMatMulDescriptor::m_DataLayoutY
DataLayout m_DataLayoutY
Definition: Descriptors.hpp:1622
armnn::BatchMatMulLayer::InferOutputShapes
std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override
Infers the output shape from the given input shapes.
Definition: BatchMatMulLayer.cpp:33
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:504
armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:287
armnn::LayerType::BatchMatMul
@ BatchMatMul
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:391
armnn::LayerWithParameters< BatchMatMulDescriptor >::LayerWithParameters
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const BatchMatMulDescriptor &param, const char *name)
Definition: LayerWithParameters.hpp:30
armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:441