42 auto layer = CloneBase<BatchNormalizationLayer>(graph,
m_Param,
GetName());
49 return std::move(layer);
87 visitor.VisitBatchNormalizationLayer(
99 std::vector<armnn::ConstTensor> constTensors { { managedMean.
GetTensorInfo(), managedMean.
Map() },
This layer represents a batch normalization operation.
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the BatchNormalization type.
BatchNormalizationDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
BatchNormalizationLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
const TensorShape & GetShape() const
std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override
Infer the shape of the output(s) based on the provided input shape(s)
#define ARMNN_NO_DEPRECATE_WARN_BEGIN
virtual void ExecuteStrategy(const armnn::IConnectableLayer *layer, const armnn::BaseDescriptor &descriptor, const std::vector< armnn::ConstTensor > &constants, const char *name, const armnn::LayerBindingId id=0)=0
const ConstTensorHandle * m_Variance
std::shared_ptr< ConstTensorHandle > m_Mean
A unique pointer to store Mean values.
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
const TensorInfo & GetTensorInfo() const
Copyright (c) 2021 ARM Limited and Contributors.
const BatchNormalizationDescriptor & GetParameters() const override
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
std::shared_ptr< ConstTensorHandle > m_Beta
A unique pointer to store Beta values.
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
std::vector< std::reference_wrapper< std::shared_ptr< ConstTensorHandle > >> ConstantTensors
#define ARMNN_NO_DEPRECATE_WARN_END
#define ARMNN_ASSERT_MSG(COND, MSG)
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
#define ARMNN_ASSERT(COND)
std::shared_ptr< ConstTensorHandle > m_Gamma
A unique pointer to store Gamma values.
ARMNN_NO_DEPRECATE_WARN_BEGIN void Accept(ILayerVisitor &visitor) const override
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of BatchNormalizationLayer.
std::shared_ptr< ConstTensorHandle > m_Variance
A unique pointer to store Variance values.
void SetAdditionalInfo(QueueDescriptor &descriptor) const
ConstantTensors GetConstantTensorsByRef() override
Retrieve the handles to the constant values stored by the layer.
const ConstTensorHandle * m_Gamma
ARMNN_NO_DEPRECATE_WARN_END void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
virtual const TensorInfo & GetTensorInfo() const =0
const char * GetName() const override
Returns the name of the layer.
const void * Map(bool blocking=true)
RAII Managed resource Unmaps MemoryArea once out of scope.
const ConstTensorHandle * m_Mean
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const
const TensorInfo & GetTensorInfo() const override
const ConstTensorHandle * m_Beta
BatchNormalizationLayer(const BatchNormalizationDescriptor ¶m, const char *name)
Constructor to create a BatchNormalizationLayer.
ShapeInferenceMethod m_ShapeInferenceMethod
A BatchNormalizationDescriptor for the BatchNormalizationLayer.
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below...