weka.dl4j.layers

Class BatchNormalization

java.lang.Object

org.deeplearning4j.nn.conf.layers.Layer

org.deeplearning4j.nn.conf.layers.FeedForwardLayer

org.deeplearning4j.nn.conf.layers.BatchNormalization

weka.dl4j.layers.BatchNormalization

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, OptionHandler

public class BatchNormalization
extends org.deeplearning4j.nn.conf.layers.BatchNormalization
implements OptionHandler, java.io.Serializable

A version of DeepLearning4j's BatchNormalization layer that implements WEKA option handling.

Version:

$Revision: 11711 $

Author:

Christopher Beckham, Eibe Frank

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class org.deeplearning4j.nn.conf.layers.BatchNormalization

org.deeplearning4j.nn.conf.layers.BatchNormalization.Builder

Constructor Summary

Constructors

Constructor and Description
BatchNormalization() Constructor for setting some defaults.

Method Summary

Modifier and Type	Method and Description
org.nd4j.linalg.activations.IActivation	getActivationFn()
org.nd4j.linalg.activations.IActivation	getActivationFunction()
double	getAdamMeanDecay()
double	getAdamVarDecay()
double	getBeta()
double	getBiasInit()
double	getBiasL1()
double	getBiasL2()
double	getBiasLearningRate()
double	getDecay()
org.deeplearning4j.nn.conf.distribution.Distribution	getDist()
double	getDropOut()
double	getEps()
double	getEpsilon()
double	getGamma()
org.deeplearning4j.nn.conf.GradientNormalization	getGradientNormalization()
double	getGradientNormalizationThreshold()
double	getL1()
double	getL1Bias()
double	getL2()
double	getL2Bias()
java.lang.String	getLayerName()
double	getLearningRate()
java.util.Map<java.lang.Integer,java.lang.Double>	getLearningRateSchedule()
boolean	getLockGammaAndBeta()
double	getMomentum()
java.util.Map<java.lang.Integer,java.lang.Double>	getMomentumSchedule()
int	getNIn()
boolean	getNoMinibatch()
int	getNOut()
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
double	getRho()
double	getRmsDecay()
org.deeplearning4j.nn.conf.Updater	getUpdater()
org.deeplearning4j.nn.weights.WeightInit	getWeightInit()
java.lang.String	globalInfo() Global info.
boolean	isLockGammaBeta()
boolean	isMinibatch()
java.util.Enumeration<Option>	listOptions() Returns an enumeration describing the available options.
void	setActivationFn(org.nd4j.linalg.activations.IActivation fn)
void	setActivationFunction(org.nd4j.linalg.activations.IActivation activationFn)
void	setAdamMeanDecay(double adamMeanDecay)
void	setAdamVarDecay(double adamVarDecay)
void	setBeta(double beta)
void	setBiasInit(double biasInit)
void	setBiasL1(double biasL1)
void	setBiasL2(double biasL2)
void	setBiasLearningRate(double biasLearningRate)
void	setDecay(double decay)
void	setDist(org.deeplearning4j.nn.conf.distribution.Distribution dist)
void	setDropOut(double dropOut)
void	setEps(double eps)
void	setEpsilon(double epsilon)
void	setGamma(double gamma)
void	setGradientNormalization(org.deeplearning4j.nn.conf.GradientNormalization gradientNormalization)
void	setGradientNormalizationThreshold(double gradientNormalizationThreshold)
void	setL1(double l1)
void	setL1Bias(int l1bias)
void	setL2(double l2)
void	setL2Bias(int l2bias)
void	setLayerName(java.lang.String layerName)
void	setLearningRate(double learningRate)
void	setLearningRateSchedule(java.util.Map<java.lang.Integer,java.lang.Double> learningRateSchedule)
void	setLockGammaAndBeta(boolean lgb)
void	setLockGammaBeta(boolean lgb)
void	setMinibatch(boolean b)
void	setMomentum(double momentum)
void	setMomentumSchedule(java.util.Map<java.lang.Integer,java.lang.Double> momentumSchedule)
void	setNIn(int nIn)
void	setNoMinibatch(boolean b)
void	setNOut(int nOut)
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setRho(double rho)
void	setRmsDecay(double rmsDecay)
void	setUpdater(org.deeplearning4j.nn.conf.Updater updater)
void	setWeightInit(org.deeplearning4j.nn.weights.WeightInit weightInit)

Methods inherited from class org.deeplearning4j.nn.conf.layers.BatchNormalization

clone, equals, getL1ByParam, getL2ByParam, getLearningRateByParam, getOutputType, getPreProcessorForInputType, getUpdaterByParam, hashCode, initializer, instantiate, setNIn, toString

Methods inherited from class org.deeplearning4j.nn.conf.layers.Layer

resetLayerDefaultConfig, setL1Bias, setL2Bias

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

BatchNormalization

public BatchNormalization()

Constructor for setting some defaults.

Method Detail

globalInfo

public java.lang.String globalInfo()

Global info.

Returns:

string describing this class.

getLayerName

@OptionMetadata(displayName="layer name",
                description="The name of the layer (default = Batch normalization Layer).",
                commandLineParamName="name",
                commandLineParamSynopsis="-name <string>",
                displayOrder=0)
public java.lang.String getLayerName()

Overrides:

getLayerName in class org.deeplearning4j.nn.conf.layers.Layer

setLayerName

public void setLayerName(java.lang.String layerName)

Overrides:

setLayerName in class org.deeplearning4j.nn.conf.layers.Layer

getDecay

@OptionMetadata(displayName="decay parameter",
                description="The decay parameter (default = 0.9).",
                commandLineParamName="decay",
                commandLineParamSynopsis="-decay <double>",
                displayOrder=1)
public double getDecay()

Overrides:

getDecay in class org.deeplearning4j.nn.conf.layers.BatchNormalization

setDecay

public void setDecay(double decay)

Overrides:

setDecay in class org.deeplearning4j.nn.conf.layers.BatchNormalization

getEps

@OptionMetadata(displayName="eps parameter",
                description="The eps parameter (default = 1e-5).",
                commandLineParamName="eps",
                commandLineParamSynopsis="-eps <double>",
                displayOrder=2)
public double getEps()

Overrides:

getEps in class org.deeplearning4j.nn.conf.layers.BatchNormalization

setEps

public void setEps(double eps)

Overrides:

setEps in class org.deeplearning4j.nn.conf.layers.BatchNormalization

getGamma

@OptionMetadata(displayName="gamma parameter",
                description="The gamma parameter (default = 1).",
                commandLineParamName="gamma",
                commandLineParamSynopsis="-gamma <double>",
                displayOrder=3)
public double getGamma()

Overrides:

getGamma in class org.deeplearning4j.nn.conf.layers.BatchNormalization

setGamma

public void setGamma(double gamma)

Overrides:

setGamma in class org.deeplearning4j.nn.conf.layers.BatchNormalization

getBeta

@OptionMetadata(displayName="beta parameter",
                description="The beta parameter (default = 0).",
                commandLineParamName="beta",
                commandLineParamSynopsis="-beta <double>",
                displayOrder=4)
public double getBeta()

Overrides:

getBeta in class org.deeplearning4j.nn.conf.layers.BatchNormalization

setBeta

public void setBeta(double beta)

Overrides:

setBeta in class org.deeplearning4j.nn.conf.layers.BatchNormalization

getLockGammaAndBeta

@OptionMetadata(displayName="lock gamma and beta",
                description="Whether to lock gamma and beta.",
                commandLineParamName="beta",
                commandLineParamSynopsis="-lockGammaBeta",
                displayOrder=5)
public boolean getLockGammaAndBeta()

setLockGammaAndBeta

public void setLockGammaAndBeta(boolean lgb)

isLockGammaBeta

@ProgrammaticProperty
public boolean isLockGammaBeta()

Overrides:

isLockGammaBeta in class org.deeplearning4j.nn.conf.layers.BatchNormalization

setLockGammaBeta

public void setLockGammaBeta(boolean lgb)

Overrides:

setLockGammaBeta in class org.deeplearning4j.nn.conf.layers.BatchNormalization

getNoMinibatch

@OptionMetadata(displayName="noMinibatch",
                description="Whether minibatches are not not used.",
                commandLineParamName="noMinibatch",
                commandLineParamSynopsis="-noMinibatch",
                displayOrder=6)
public boolean getNoMinibatch()

setNoMinibatch

public void setNoMinibatch(boolean b)

isMinibatch

@ProgrammaticProperty
public boolean isMinibatch()

Overrides:

isMinibatch in class org.deeplearning4j.nn.conf.layers.BatchNormalization

setMinibatch

public void setMinibatch(boolean b)

Overrides:

setMinibatch in class org.deeplearning4j.nn.conf.layers.BatchNormalization

getActivationFunction

@OptionMetadata(displayName="activation function",
                description="The activation function to use (default = Identity).",
                commandLineParamName="activation",
                commandLineParamSynopsis="-activation <specification>",
                displayOrder=7)
public org.nd4j.linalg.activations.IActivation getActivationFunction()

setActivationFunction

public void setActivationFunction(org.nd4j.linalg.activations.IActivation activationFn)

getActivationFn

@ProgrammaticProperty
public org.nd4j.linalg.activations.IActivation getActivationFn()

Overrides:

getActivationFn in class org.deeplearning4j.nn.conf.layers.Layer

setActivationFn

public void setActivationFn(org.nd4j.linalg.activations.IActivation fn)

Overrides:

setActivationFn in class org.deeplearning4j.nn.conf.layers.Layer

getWeightInit

@OptionMetadata(displayName="weight initialization method",
                description="The method for weight initialization (default = XAVIER).",
                commandLineParamName="weightInit",
                commandLineParamSynopsis="-weightInit <specification>",
                displayOrder=8)
public org.deeplearning4j.nn.weights.WeightInit getWeightInit()

Overrides:

getWeightInit in class org.deeplearning4j.nn.conf.layers.Layer

setWeightInit

public void setWeightInit(org.deeplearning4j.nn.weights.WeightInit weightInit)

Overrides:

setWeightInit in class org.deeplearning4j.nn.conf.layers.Layer

getBiasInit

@OptionMetadata(displayName="bias initialization",
                description="The bias initialization (default = 1.0).",
                commandLineParamName="biasInit",
                commandLineParamSynopsis="-biasInit <double>",
                displayOrder=9)
public double getBiasInit()

Overrides:

getBiasInit in class org.deeplearning4j.nn.conf.layers.Layer

setBiasInit

public void setBiasInit(double biasInit)

Overrides:

setBiasInit in class org.deeplearning4j.nn.conf.layers.Layer

getDist

@OptionMetadata(displayName="distribution",
                description="The distribution (default = NormalDistribution(1e-3, 1)).",
                commandLineParamName="dist",
                commandLineParamSynopsis="-dist <specification>",
                displayOrder=10)
public org.deeplearning4j.nn.conf.distribution.Distribution getDist()

Overrides:

getDist in class org.deeplearning4j.nn.conf.layers.Layer

setDist

public void setDist(org.deeplearning4j.nn.conf.distribution.Distribution dist)

Overrides:

setDist in class org.deeplearning4j.nn.conf.layers.Layer

getLearningRate

@OptionMetadata(displayName="learning rate",
                description="The learning rate (default = 0.01).",
                commandLineParamName="lr",
                commandLineParamSynopsis="-lr <double>",
                displayOrder=11)
public double getLearningRate()

Overrides:

getLearningRate in class org.deeplearning4j.nn.conf.layers.Layer

setLearningRate

public void setLearningRate(double learningRate)

Overrides:

setLearningRate in class org.deeplearning4j.nn.conf.layers.Layer

getBiasLearningRate

@OptionMetadata(displayName="bias learning rate",
                description="The bias learning rate (default = 0.01).",
                commandLineParamName="blr",
                commandLineParamSynopsis="-blr <double>",
                displayOrder=12)
public double getBiasLearningRate()

Overrides:

getBiasLearningRate in class org.deeplearning4j.nn.conf.layers.Layer

setBiasLearningRate

public void setBiasLearningRate(double biasLearningRate)

Overrides:

setBiasLearningRate in class org.deeplearning4j.nn.conf.layers.Layer

getLearningRateSchedule

@OptionMetadata(displayName="learning rate schedule",
                description="The learning rate schedule.",
                commandLineParamName="lrSchedule",
                commandLineParamSynopsis="-lrSchedule <specification>",
                displayOrder=13)
public java.util.Map<java.lang.Integer,java.lang.Double> getLearningRateSchedule()

Overrides:

getLearningRateSchedule in class org.deeplearning4j.nn.conf.layers.Layer

setLearningRateSchedule

public void setLearningRateSchedule(java.util.Map<java.lang.Integer,java.lang.Double> learningRateSchedule)

Overrides:

setLearningRateSchedule in class org.deeplearning4j.nn.conf.layers.Layer

getMomentum

@OptionMetadata(displayName="momentum",
                description="The momentum (default = 0.9).",
                commandLineParamName="momentum",
                commandLineParamSynopsis="-momentum <double>",
                displayOrder=14)
public double getMomentum()

Overrides:

getMomentum in class org.deeplearning4j.nn.conf.layers.Layer

setMomentum

public void setMomentum(double momentum)

Overrides:

setMomentum in class org.deeplearning4j.nn.conf.layers.Layer

getMomentumSchedule

@OptionMetadata(displayName="momentum schedule",
                description="The momentum schedule.",
                commandLineParamName="momentumSchedule",
                commandLineParamSynopsis="-momentumSchedule <specification>",
                displayOrder=15)
public java.util.Map<java.lang.Integer,java.lang.Double> getMomentumSchedule()

Overrides:

getMomentumSchedule in class org.deeplearning4j.nn.conf.layers.Layer

setMomentumSchedule

public void setMomentumSchedule(java.util.Map<java.lang.Integer,java.lang.Double> momentumSchedule)

Overrides:

setMomentumSchedule in class org.deeplearning4j.nn.conf.layers.Layer

getL1

@OptionMetadata(displayName="L1",
                description="The L1 parameter (default = 0).",
                commandLineParamName="L1",
                commandLineParamSynopsis="-L1 <double>",
                displayOrder=16)
public double getL1()

Overrides:

getL1 in class org.deeplearning4j.nn.conf.layers.Layer

setL1

public void setL1(double l1)

Overrides:

setL1 in class org.deeplearning4j.nn.conf.layers.Layer

getL2

@OptionMetadata(displayName="L2",
                description="The L2 parameter (default = 0).",
                commandLineParamName="L2",
                commandLineParamSynopsis="-L2 <double>",
                displayOrder=17)
public double getL2()

Overrides:

getL2 in class org.deeplearning4j.nn.conf.layers.Layer

setL2

public void setL2(double l2)

Overrides:

setL2 in class org.deeplearning4j.nn.conf.layers.Layer

getBiasL1

@OptionMetadata(displayName="L1 bias",
                description="The L1 bias parameter (default = 0).",
                commandLineParamName="l1Bias",
                commandLineParamSynopsis="-l1Bias <double>",
                displayOrder=18)
public double getBiasL1()

setBiasL1

public void setBiasL1(double biasL1)

getBiasL2

@OptionMetadata(displayName="L2 bias",
                description="The L2 bias parameter (default = 0).",
                commandLineParamName="l2Bias",
                commandLineParamSynopsis="-l2Bias <double>",
                displayOrder=19)
public double getBiasL2()

setBiasL2

public void setBiasL2(double biasL2)

getDropOut

@OptionMetadata(displayName="dropout parameter",
                description="The dropout parameter (default = 0).",
                commandLineParamName="dropout",
                commandLineParamSynopsis="-dropout <double>",
                displayOrder=20)
public double getDropOut()

Overrides:

getDropOut in class org.deeplearning4j.nn.conf.layers.Layer

setDropOut

public void setDropOut(double dropOut)

Overrides:

setDropOut in class org.deeplearning4j.nn.conf.layers.Layer

getUpdater

@OptionMetadata(displayName="updater for stochastic gradient descent",
                description="The updater for stochastic gradient descent (default NESTEROVS).",
                commandLineParamName="updater",
                commandLineParamSynopsis="-updater <speficiation>",
                displayOrder=21)
public org.deeplearning4j.nn.conf.Updater getUpdater()

Overrides:

getUpdater in class org.deeplearning4j.nn.conf.layers.Layer

setUpdater

public void setUpdater(org.deeplearning4j.nn.conf.Updater updater)

Overrides:

setUpdater in class org.deeplearning4j.nn.conf.layers.Layer

getRho

@OptionMetadata(displayName="ADADELTA\'s rho parameter",
                description="ADADELTA\'s rho parameter (default = 0).",
                commandLineParamName="rho",
                commandLineParamSynopsis="-rho <double>",
                displayOrder=22)
public double getRho()

Overrides:

getRho in class org.deeplearning4j.nn.conf.layers.Layer

setRho

public void setRho(double rho)

Overrides:

setRho in class org.deeplearning4j.nn.conf.layers.Layer

getEpsilon

@OptionMetadata(displayName="ADADELTA\'s epsilon parameter",
                description="ADADELTA\'s epsilon parameter (default = 1e-6).",
                commandLineParamName="epsilon",
                commandLineParamSynopsis="-epsilon <double>",
                displayOrder=23)
public double getEpsilon()

Overrides:

getEpsilon in class org.deeplearning4j.nn.conf.layers.Layer

setEpsilon

public void setEpsilon(double epsilon)

Overrides:

setEpsilon in class org.deeplearning4j.nn.conf.layers.Layer

getRmsDecay

@OptionMetadata(displayName="RMSPROP\'s RMS decay parameter",
                description="RMSPROP\'s RMS decay parameter (default = 0.95).",
                commandLineParamName="rmsDecay",
                commandLineParamSynopsis="-rmsDecay <double>",
                displayOrder=24)
public double getRmsDecay()

Overrides:

getRmsDecay in class org.deeplearning4j.nn.conf.layers.Layer

setRmsDecay

public void setRmsDecay(double rmsDecay)

Overrides:

setRmsDecay in class org.deeplearning4j.nn.conf.layers.Layer

getAdamMeanDecay

@OptionMetadata(displayName="ADAM\'s mean decay parameter",
                description="ADAM\'s mean decay parameter (default 0.9).",
                commandLineParamName="adamMeanDecay",
                commandLineParamSynopsis="-adamMeanDecay <double>",
                displayOrder=25)
public double getAdamMeanDecay()

Overrides:

getAdamMeanDecay in class org.deeplearning4j.nn.conf.layers.Layer

setAdamMeanDecay

public void setAdamMeanDecay(double adamMeanDecay)

Overrides:

setAdamMeanDecay in class org.deeplearning4j.nn.conf.layers.Layer

getAdamVarDecay

@OptionMetadata(displayName="ADAMS\'s var decay parameter",
                description="ADAM\'s var decay parameter (default 0.999).",
                commandLineParamName="adamVarDecay",
                commandLineParamSynopsis="-adamVarDecay <double>",
                displayOrder=26)
public double getAdamVarDecay()

Overrides:

getAdamVarDecay in class org.deeplearning4j.nn.conf.layers.Layer

setAdamVarDecay

public void setAdamVarDecay(double adamVarDecay)

Overrides:

setAdamVarDecay in class org.deeplearning4j.nn.conf.layers.Layer

getGradientNormalization

@OptionMetadata(displayName="gradient normalization method",
                description="The gradient normalization method (default = None).",
                commandLineParamName="gradientNormalization",
                commandLineParamSynopsis="-gradientNormalization <specification>",
                displayOrder=27)
public org.deeplearning4j.nn.conf.GradientNormalization getGradientNormalization()

Overrides:

getGradientNormalization in class org.deeplearning4j.nn.conf.layers.Layer

setGradientNormalization

public void setGradientNormalization(org.deeplearning4j.nn.conf.GradientNormalization gradientNormalization)

Overrides:

setGradientNormalization in class org.deeplearning4j.nn.conf.layers.Layer

getGradientNormalizationThreshold

@OptionMetadata(displayName="gradient normalization threshold",
                description="The gradient normalization threshold (default = 1).",
                commandLineParamName="gradNormThreshold",
                commandLineParamSynopsis="-gradNormThreshold <double>",
                displayOrder=28)
public double getGradientNormalizationThreshold()

Overrides:

getGradientNormalizationThreshold in class org.deeplearning4j.nn.conf.layers.Layer

setGradientNormalizationThreshold

public void setGradientNormalizationThreshold(double gradientNormalizationThreshold)

Overrides:

setGradientNormalizationThreshold in class org.deeplearning4j.nn.conf.layers.Layer

getNIn

@ProgrammaticProperty
public int getNIn()

Overrides:

getNIn in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer

setNIn

public void setNIn(int nIn)

Overrides:

setNIn in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer

getNOut

@ProgrammaticProperty
public int getNOut()

Overrides:

getNOut in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer

setNOut

public void setNOut(int nOut)

Overrides:

setNOut in class org.deeplearning4j.nn.conf.layers.FeedForwardLayer

getL1Bias

@ProgrammaticProperty
public double getL1Bias()

Overrides:

getL1Bias in class org.deeplearning4j.nn.conf.layers.Layer

setL1Bias

public void setL1Bias(int l1bias)

getL2Bias

@ProgrammaticProperty
public double getL2Bias()

Overrides:

getL2Bias in class org.deeplearning4j.nn.conf.layers.Layer

setL2Bias

public void setL2Bias(int l2bias)

listOptions

public java.util.Enumeration<Option> listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface OptionHandler

Returns:

an enumeration of all the available options.

getOptions

public java.lang.String[] getOptions()

Gets the current settings of the Classifier.

Specified by:

getOptions in interface OptionHandler

Returns:

an array of strings suitable for passing to setOptions

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.Exception

Parses a given list of options.

Specified by:

setOptions in interface OptionHandler

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported