BatchNormOperator

public class BatchNormOperator: ComputableOperator

Batch normalization operator.

Normalize on input tensors by each tensor’s mean and variance.

All input tensors should have same dimentsion.

output tensors should have same channel order as input

Currently, only support 2D tensor with channel information.

Attributes

computationDelegate
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
Declaration
Swift

public var computationDelegate: OperatorCalculationDelegate?
Show on GitHub
metalKernelFuncLabel
Declaration
Swift

public var metalKernelFuncLabel: String
Show on GitHub
operatorLabel
Declaration
Swift

public var operatorLabel: String
Show on GitHub
inputTensors
Declaration
Swift

public var inputTensors: [Tensor]?
Show on GitHub
outputTensors
Declaration
Swift

public var outputTensors: [Tensor]?
Show on GitHub
disableInputOutputCheck
Declaration
Swift

public var disableInputOutputCheck: Bool
Show on GitHub
trainable
Declaration
Swift

public var trainable: Bool
Show on GitHub
mapType
Declaration
Swift

public var mapType: OperatorMappingType
Show on GitHub
inPlaceble
Declaration
Swift

public var inPlaceble: Bool = true
Show on GitHub
channelOrder
Channel order of input
Declaration
Swift

public var channelOrder: TensorChannelOrder
Show on GitHub
movingMean
Moving mean. Should be same dimension with feature axis.
Declaration
Swift

public var movingMean: Tensor?
Show on GitHub
movingVar
Moving varience Should be same dimension with feature axis.
Declaration
Swift

public var movingVar: Tensor?
Show on GitHub
epsilon
A small float number to avoid dividing by 0. default is 0.001
Declaration
Swift

public var epsilon: Float
Show on GitHub
useScale
If use scale tensor
Declaration
Swift

public var useScale: Bool
Show on GitHub
scale
Scale tensor to output. Should be same dimension with feature axis.
Declaration
Swift

public var scale: Tensor?
Show on GitHub
useOffset
If use offset tensor
Declaration
Swift

public var useOffset: Bool
Show on GitHub
offset
offset tensor to output. Should be same dimension with feature axis.
Declaration
Swift

public var offset: Tensor?
Show on GitHub
inputShape
Input shape. Should not be nil if used in Graph API.
Declaration
Swift

public var inputShape: TensorShape?
Show on GitHub
inTraining
If in training or not.
Declaration
Swift

public var inTraining: Bool
Show on GitHub

init


                    
                    
                    init(channelOrder:movingMean:movingVar:useScale:scale:useOffset:offset:epsilon:metalKernelFuncLabel:operatorLabel:inputTensors:outputTensors:disableInputOutputCheck:trainable:mapType:inputShape:inTraining:)

Undocumented

Declaration

Swift

public init(channelOrder: TensorChannelOrder = TensorChannelOrder.Last,
            movingMean: Tensor? = nil,
            movingVar: Tensor? = nil,
            useScale: Bool = true,
            scale: Tensor? = nil,
            useOffset: Bool = true,
            offset: Tensor? = nil,
            epsilon: Float = 0.001,
            metalKernelFuncLabel: String = "",
            operatorLabel: String = "BatchNormalizationOperator",
            inputTensors: [Tensor]? = nil,
            outputTensors: [Tensor]? = nil,
            disableInputOutputCheck: Bool = false,
            trainable: Bool = false,
            mapType: OperatorMappingType = OperatorMappingType.OneToOne,
            inputShape: TensorShape? = nil,
            inTraining: Bool = false)

Show on GitHub

Conforms to ComputableOperator, forward


                    
                    
                    outputShape(shapeArray:)

Outputshape are same as input shapes.

Note

All input shapes should have same dimension

Declaration

Swift

public func outputShape(shapeArray shapes: [TensorShape]) -> [TensorShape]?

Parameters


                                shapes

Return Value

Show on GitHub


                    
                    
                    inputOutputTensorsCheck()

Declaration

Swift

public func inputOutputTensorsCheck() -> (check: Bool, msg: String)

Show on GitHub


                    
                    
                    compute(_:)

Declaration

Swift

public func compute(_ computationMode: OperatorComputationMode)

Show on GitHub


                    
                    
                    computeAsync(_:)

Declaration

Swift

public func computeAsync(_ computationMode: OperatorComputationMode)

Show on GitHub

cpu()
Undocumented
Declaration
Swift

internal func cpu()
Show on GitHub
gpu()
Undocumented
Declaration
Swift

internal func gpu()
Show on GitHub
cpu_train()
CPU in training
Declaration
Swift

internal func cpu_train()
Show on GitHub
gpu_train()
GPU in training
Declaration
Swift

internal func gpu_train()
Show on GitHub
cpu_inference()
CPU in inference
Declaration
Swift

internal func cpu_inference()
Show on GitHub
gpu_inference()
GPU in inference
Declaration
Swift

internal func gpu_inference()
Show on GitHub

Conforms to ComputableOperator, backward

gradCompute(_:)
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
Declaration
Swift

public func gradCompute(_ computationMode: OperatorComputationMode) -> [String : DataSymbolSupportedDataType]
Show on GitHub


                    
                    
                    gradComputAsync(_:)

Declaration

Swift

public func gradComputAsync(_ computationMode: OperatorComputationMode)

Show on GitHub

Graph API support

bindParamSymbols(_:)
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
Declaration
Swift

public func bindParamSymbols(_ symbols: [GraphSymbol])
Show on GitHub


                    
                    
                    paramSymbols()

Declaration

Swift

public func paramSymbols() -> [GraphSymbol]

Show on GitHub