ArmNN
 24.02
Public Member Functions | Public Attributes | Protected Member Functions | List of all members
TransposeConvolution2dLayer Class Reference

This layer represents a 2D transpose convolution operation. More...

#include <TransposeConvolution2dLayer.hpp>

Inheritance diagram for TransposeConvolution2dLayer:
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Collaboration diagram for TransposeConvolution2dLayer:
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Public Member Functions

virtual std::unique_ptr< IWorkload > CreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the TransposeConvolution2d type. More...
 
TransposeConvolution2dLayer * Clone (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 TransposeConvolution2dLayer. More...
 
std::vector< TensorShape > InferOutputShapes (const std::vector< TensorShape > &inputShapes) const override
 Infers the output shapes from given input shapes and layer properties. More...
 
void ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this layer. More...
 
- Public Member Functions inherited from LayerWithParameters< TransposeConvolution2dDescriptor >
const TransposeConvolution2dDescriptor & GetParameters () 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 OutputHandler & GetOutputHandler (unsigned int i=0) const
 
OutputHandler & GetOutputHandler (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 BackendId & GetBackendId () 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 InputSlot & GetInputSlot (unsigned int index) const override
 Get a const input slot handle by slot index. More...
 
InputSlot & GetInputSlot (unsigned int index) override
 Get the input slot handle by slot index. More...
 
const OutputSlot & GetOutputSlot (unsigned int index=0) const override
 Get the const output slot handle by slot index. More...
 
OutputSlot & GetOutputSlot (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< BackendId > GetBackendHint () 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 BaseDescriptor & GetParameters () const override
 If the layer has a descriptor return it. More...
 

Public Attributes

std::shared_ptr< ConstTensorHandle > m_Weight
 A unique pointer to store weight values. More...
 
std::shared_ptr< ConstTensorHandle > m_Bias
 A unique pointer to store bias values. More...
 

Protected Member Functions

 TransposeConvolution2dLayer (const TransposeConvolution2dDescriptor &param, const char *name)
 Constructor to create a TransposeConvolution2dLayer. More...
 
 ~TransposeConvolution2dLayer ()=default
 Default destructor. More...
 
ImmutableConstantTensors GetConstantTensorsByRef () const override
 Retrieve the handles to the constant values stored by the layer. More...
 
- Protected Member Functions inherited from LayerWithParameters< TransposeConvolution2dDescriptor >
 LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const TransposeConvolution2dDescriptor &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>
LayerType * CloneBase (Graph &graph, Params &&... params) const
 
virtual ConstantTensors GetConstantTensorsByRef () override final
 
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< TransposeConvolution2dDescriptor >
using DescriptorType = TransposeConvolution2dDescriptor
 
- 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< TransposeConvolution2dDescriptor >
TransposeConvolution2dDescriptor m_Param
 The parameters for the layer (not including tensor-valued weights etc.). More...
 
- Protected Attributes inherited from Layer
AdditionalInfoObjectPtr m_AdditionalInfoObject
 
std::vector< OutputHandler > m_OutputHandlers
 
ShapeInferenceMethod m_ShapeInferenceMethod
 

Detailed Description

This layer represents a 2D transpose convolution operation.

Definition at line 15 of file TransposeConvolution2dLayer.hpp.

Constructor & Destructor Documentation

◆ TransposeConvolution2dLayer()

TransposeConvolution2dLayer ( const TransposeConvolution2dDescriptor &  param,
const char *  name 
)
protected

Constructor to create a TransposeConvolution2dLayer.

Parameters
[in]paramTransposeConvolution2dDescriptor to configure the 2D transpose convolution operation.
[in]nameOptional name for the layer.

Definition at line 19 of file TransposeConvolution2dLayer.cpp.

21  : LayerWithParameters(1, 1, LayerType::TransposeConvolution2d, param, name)
22 {
23 }

References armnn::TransposeConvolution2d.

◆ ~TransposeConvolution2dLayer()

~TransposeConvolution2dLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

TransposeConvolution2dLayer * 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 43 of file TransposeConvolution2dLayer.cpp.

44 {
45  auto layer = CloneBase<TransposeConvolution2dLayer>(graph, m_Param, GetName());
46 
47  layer->m_Weight = m_Weight ? m_Weight : nullptr;
48 
49  if (layer->m_Param.m_BiasEnabled)
50  {
51  layer->m_Bias = m_Bias ? m_Bias : nullptr;
52  }
53 
54  return std::move(layer);
55 }

References Layer::GetName(), TransposeConvolution2dLayer::m_Bias, LayerWithParameters< TransposeConvolution2dDescriptor >::m_Param, and TransposeConvolution2dLayer::m_Weight.

◆ CreateWorkload()

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

Makes a workload for the TransposeConvolution2d 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 25 of file TransposeConvolution2dLayer.cpp.

26 {
27  ARMNN_ASSERT_MSG(m_Weight != nullptr, "TransposeConvolution2dLayer: Weights data should not be null.");
28 
29  TransposeConvolution2dQueueDescriptor descriptor;
30  descriptor.m_Weight = m_Weight.get();
31 
32  if (m_Param.m_BiasEnabled)
33  {
34  ARMNN_ASSERT_MSG(m_Bias != nullptr, "TransposeConvolution2dLayer: Bias data should not be null.");
35  descriptor.m_Bias = m_Bias.get();
36  }
37 
38  SetAdditionalInfo(descriptor);
39 
40  return factory.CreateWorkload(LayerType::TransposeConvolution2d, descriptor, PrepInfoAndDesc(descriptor));
41 }

References ARMNN_ASSERT_MSG, IWorkloadFactory::CreateWorkload(), TransposeConvolution2dLayer::m_Bias, TransposeConvolution2dQueueDescriptor::m_Bias, TransposeConvolution2dDescriptor::m_BiasEnabled, LayerWithParameters< TransposeConvolution2dDescriptor >::m_Param, TransposeConvolution2dLayer::m_Weight, TransposeConvolution2dQueueDescriptor::m_Weight, LayerWithParameters< TransposeConvolution2dDescriptor >::PrepInfoAndDesc(), Layer::SetAdditionalInfo(), and armnn::TransposeConvolution2d.

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy &  strategy) const
overridevirtual

Apply a visitor to this layer.

Reimplemented from Layer.

Definition at line 130 of file TransposeConvolution2dLayer.cpp.

131 {
132  ManagedConstTensorHandle managedWeight(m_Weight);
133  std::vector<armnn::ConstTensor> constTensors { { managedWeight.GetTensorInfo(), managedWeight.Map() } };
134 
135  ManagedConstTensorHandle managedBias(m_Bias);
136  if (GetParameters().m_BiasEnabled)
137  {
138  constTensors.emplace_back(ConstTensor(managedBias.GetTensorInfo(), managedBias.Map()));
139  }
140 
141  strategy.ExecuteStrategy(this, GetParameters(), constTensors, GetName());
142 }

References IStrategy::ExecuteStrategy(), Layer::GetName(), LayerWithParameters< TransposeConvolution2dDescriptor >::GetParameters(), ManagedConstTensorHandle::GetTensorInfo(), TransposeConvolution2dLayer::m_Bias, TransposeConvolution2dLayer::m_Weight, and ManagedConstTensorHandle::Map().

◆ GetConstantTensorsByRef()

Layer::ImmutableConstantTensors GetConstantTensorsByRef ( ) const
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 124 of file TransposeConvolution2dLayer.cpp.

125 {
126  // For API stability DO NOT ALTER order and add new members to the end of vector
127  return {m_Weight, m_Bias};
128 }

References TransposeConvolution2dLayer::m_Bias, and TransposeConvolution2dLayer::m_Weight.

◆ InferOutputShapes()

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

Infers the output shapes from given input shapes and layer properties.

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

Reimplemented from Layer.

Definition at line 57 of file TransposeConvolution2dLayer.cpp.

59 {
60  ARMNN_ASSERT(inputShapes.size() == 2);
61  const TensorShape& inputShape = inputShapes[0];
62  const TensorShape& kernelShape = inputShapes[1];
63 
64  ARMNN_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Transpose convolutions will always have 4D input");
65 
66  DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
67 
68  const unsigned int batches = inputShape[0];
69 
70  const unsigned int wInput = inputShape[dataLayoutIndex.GetWidthIndex()];
71  const unsigned int hInput = inputShape[dataLayoutIndex.GetHeightIndex()];
72 
73  const unsigned int wKernel = kernelShape[dataLayoutIndex.GetWidthIndex()];
74  const unsigned int hKernel = kernelShape[dataLayoutIndex.GetHeightIndex()];
75 
76  unsigned int wPadding = m_Param.m_PadLeft + m_Param.m_PadRight;
77  unsigned int hPadding = m_Param.m_PadTop + m_Param.m_PadBottom;
78 
79  unsigned int wOutput = (wInput - 1) * m_Param.m_StrideX + wKernel - wPadding;
80  unsigned int hOutput = (hInput - 1) * m_Param.m_StrideY + hKernel - hPadding;
81  unsigned int cOutput = kernelShape[0];
82 
83  TensorShape tensorShape = m_Param.m_DataLayout == armnn::DataLayout::NHWC ?
84  TensorShape( { batches, hOutput, wOutput, cOutput } ) :
85  TensorShape( { batches, cOutput, hOutput, wOutput });
86 
87  return std::vector<TensorShape>({ tensorShape });
88 }

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, DataLayoutIndexed::GetHeightIndex(), TensorShape::GetNumDimensions(), DataLayoutIndexed::GetWidthIndex(), TransposeConvolution2dDescriptor::m_DataLayout, TransposeConvolution2dDescriptor::m_PadBottom, TransposeConvolution2dDescriptor::m_PadLeft, TransposeConvolution2dDescriptor::m_PadRight, TransposeConvolution2dDescriptor::m_PadTop, LayerWithParameters< TransposeConvolution2dDescriptor >::m_Param, TransposeConvolution2dDescriptor::m_StrideX, TransposeConvolution2dDescriptor::m_StrideY, and armnn::NHWC.

Referenced by TransposeConvolution2dLayer::ValidateTensorShapesFromInputs().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

Check if the input tensor shape(s) will lead to a valid configuration of TransposeConvolution2dLayer.

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

Implements Layer.

Definition at line 90 of file TransposeConvolution2dLayer.cpp.

91 {
92  VerifyLayerConnections(1, CHECK_LOCATION());
93 
94  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
95 
96  VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
97 
98  ARMNN_ASSERT_MSG(m_Weight != nullptr, "TransposeConvolution2dLayer: Weight data cannot be null.");
99 
100  std::vector<TensorShape> expectedOutputShape;
101  std::vector<TensorShape> outputShapeGivenAsInput;
102 
103  expectedOutputShape = InferOutputShapes({GetInputSlot(0).GetTensorInfo().GetShape(),
104  m_Weight->GetTensorInfo().GetShape() });
105 
106  ARMNN_ASSERT(expectedOutputShape.size() == 1);
107 
108  // If output_shape was specified then use it rather than calculate an inferred output shape.
109  if (m_Param.m_OutputShapeEnabled)
110  {
111  TensorShape shapeAsTensorShape(static_cast<unsigned int>(m_Param.m_OutputShape.size()),
112  m_Param.m_OutputShape.data());
113  outputShapeGivenAsInput.push_back(shapeAsTensorShape);
114 
115  ARMNN_ASSERT(outputShapeGivenAsInput.size() == 1);
116  ARMNN_ASSERT_MSG(expectedOutputShape == outputShapeGivenAsInput,
117  "TransposeConvolution2dLayer: output calculated by InferOutputShapes and "
118  "the output given as an input parameter to the layer are not matching");
119  }
120 
121  ValidateAndCopyShape(outputShape, expectedOutputShape[0], m_ShapeInferenceMethod, "TransposeConvolution2dLayer");
122 }

References ARMNN_ASSERT, ARMNN_ASSERT_MSG, CHECK_LOCATION, Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), InputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), TransposeConvolution2dLayer::InferOutputShapes(), TransposeConvolution2dDescriptor::m_OutputShape, TransposeConvolution2dDescriptor::m_OutputShapeEnabled, LayerWithParameters< TransposeConvolution2dDescriptor >::m_Param, Layer::m_ShapeInferenceMethod, TransposeConvolution2dLayer::m_Weight, Layer::ValidateAndCopyShape(), Layer::VerifyLayerConnections(), and Layer::VerifyShapeInferenceType().

Member Data Documentation

◆ m_Bias

std::shared_ptr<ConstTensorHandle> m_Bias

A unique pointer to store bias values.

Definition at line 21 of file TransposeConvolution2dLayer.hpp.

Referenced by TransposeConvolution2dLayer::Clone(), TransposeConvolution2dLayer::CreateWorkload(), TransposeConvolution2dLayer::ExecuteStrategy(), and TransposeConvolution2dLayer::GetConstantTensorsByRef().

◆ m_Weight

std::shared_ptr<ConstTensorHandle> m_Weight

A unique pointer to store weight values.

Definition at line 19 of file TransposeConvolution2dLayer.hpp.

Referenced by NetworkImpl::AddTransposeConvolution2dLayer(), TransposeConvolution2dLayer::Clone(), TransposeConvolution2dLayer::CreateWorkload(), TransposeConvolution2dLayer::ExecuteStrategy(), TransposeConvolution2dLayer::GetConstantTensorsByRef(), and TransposeConvolution2dLayer::ValidateTensorShapesFromInputs().

The documentation for this class was generated from the following files:
ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
armnn::TransposeConvolution2dDescriptor::m_PadLeft
uint32_t m_PadLeft
Padding left value in the width dimension.
Definition: Descriptors.hpp:1469
armnn::TransposeConvolution2dDescriptor::m_StrideX
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
Definition: Descriptors.hpp:1477
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92
armnn::DataLayout::NHWC
@ NHWC
armnn::TransposeConvolution2dQueueDescriptor::m_Weight
const ConstTensorHandle * m_Weight
Definition: WorkloadData.hpp:551
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
armnnUtils::DataLayoutIndexed
Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout.
Definition: DataLayoutIndexed.hpp:17
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::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_ASSERT_MSG
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
armnn::ManagedConstTensorHandle
Definition: TensorHandle.hpp:187
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< TransposeConvolution2dDescriptor >::GetParameters
const TransposeConvolution2dDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
armnn::TransposeConvolution2dDescriptor::m_PadBottom
uint32_t m_PadBottom
Padding bottom value in the height dimension.
Definition: Descriptors.hpp:1475
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::TransposeConvolution2dLayer::m_Bias
std::shared_ptr< ConstTensorHandle > m_Bias
A unique pointer to store bias values.
Definition: TransposeConvolution2dLayer.hpp:21
armnn::TensorShape
Definition: Tensor.hpp:20
armnn::LayerWithParameters< TransposeConvolution2dDescriptor >::m_Param
TransposeConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::TensorShape::GetNumDimensions
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition: Tensor.cpp:174
armnn::LayerWithParameters< TransposeConvolution2dDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
armnn::LayerType::TransposeConvolution2d
@ TransposeConvolution2d
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::TransposeConvolution2dLayer::InferOutputShapes
std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override
Infers the output shapes from given input shapes and layer properties.
Definition: TransposeConvolution2dLayer.cpp:57
armnn::TransposeConvolution2dDescriptor::m_StrideY
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
Definition: Descriptors.hpp:1479
armnn::TransposeConvolution2dQueueDescriptor::m_Bias
const ConstTensorHandle * m_Bias
Definition: WorkloadData.hpp:552
armnn::TransposeConvolution2dQueueDescriptor
Definition: WorkloadData.hpp:544
armnn::TransposeConvolution2dDescriptor::m_OutputShape
std::vector< unsigned int > m_OutputShape
Definition: Descriptors.hpp:1486
armnn::TransposeConvolution2dLayer::m_Weight
std::shared_ptr< ConstTensorHandle > m_Weight
A unique pointer to store weight values.
Definition: TransposeConvolution2dLayer.hpp:19
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn::TransposeConvolution2dDescriptor::m_PadTop
uint32_t m_PadTop
Padding top value in the height dimension.
Definition: Descriptors.hpp:1473
armnn::TransposeConvolution2dDescriptor::m_PadRight
uint32_t m_PadRight
Padding right value in the width dimension.
Definition: Descriptors.hpp:1471
armnn::ConstTensor
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:329
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:391
armnn::TransposeConvolution2dDescriptor::m_OutputShapeEnabled
bool m_OutputShapeEnabled
Output shape if it has been specified.
Definition: Descriptors.hpp:1485
armnn::TransposeConvolution2dDescriptor::m_BiasEnabled
bool m_BiasEnabled
Enable/disable bias.
Definition: Descriptors.hpp:1481
armnn::TransposeConvolution2dDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Definition: Descriptors.hpp:1483
armnn::LayerWithParameters< TransposeConvolution2dDescriptor >::LayerWithParameters
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const TransposeConvolution2dDescriptor &param, const char *name)
Definition: LayerWithParameters.hpp:30
armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:441
armnn::IWorkloadFactory::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const =0
Backends should implement their own CreateWorkload function with a switch statement.
armnn::IStrategy::ExecuteStrategy
virtual void ExecuteStrategy(const IConnectableLayer *layer, const armnn::BaseDescriptor &descriptor, const std::vector< armnn::ConstTensor > &constants, const char *name, const armnn::LayerBindingId id=0)=0