weka.dl4j.layers

Class SubsamplingLayer

java.lang.Object

org.deeplearning4j.nn.conf.layers.Layer

org.deeplearning4j.nn.conf.layers.SubsamplingLayer

weka.dl4j.layers.SubsamplingLayer

All Implemented Interfaces:

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

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

A version of DeepLearning4j's SubsamplingLayer 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.SubsamplingLayer

org.deeplearning4j.nn.conf.layers.SubsamplingLayer.Builder, org.deeplearning4j.nn.conf.layers.SubsamplingLayer.PoolingType

Constructor Summary

Constructors

Constructor and Description
SubsamplingLayer() 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	getBiasInit()
double	getBiasL1()
double	getBiasL2()
double	getBiasLearningRate()
org.deeplearning4j.nn.conf.ConvolutionMode	getConvolutionMode()
org.deeplearning4j.nn.conf.distribution.Distribution	getDist()
double	getDropOut()
double	getEps()
double	getEpsilon()
org.deeplearning4j.nn.conf.GradientNormalization	getGradientNormalization()
double	getGradientNormalizationThreshold()
int[]	getKernelSize()
int	getKernelSizeX()
int	getKernelSizeY()
double	getL1()
double	getL1Bias()
double	getL2()
double	getL2Bias()
java.lang.String	getLayerName()
double	getLearningRate()
java.util.Map<java.lang.Integer,java.lang.Double>	getLearningRateSchedule()
double	getMomentum()
java.util.Map<java.lang.Integer,java.lang.Double>	getMomentumSchedule()
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
int[]	getPadding()
int	getPaddingX()
int	getPaddingY()
int	getPnorm()
org.deeplearning4j.nn.conf.layers.PoolingType	getPoolingType()
double	getRho()
double	getRmsDecay()
int[]	getStride()
int	getStrideX()
int	getStrideY()
org.deeplearning4j.nn.conf.Updater	getUpdater()
org.deeplearning4j.nn.weights.WeightInit	getWeightInit()
java.lang.String	globalInfo() Global info.
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	setBiasInit(double biasInit)
void	setBiasL1(double biasL1)
void	setBiasL2(double biasL2)
void	setBiasLearningRate(double biasLearningRate)
void	setConvolutionMode(org.deeplearning4j.nn.conf.ConvolutionMode convolutionMode)
void	setDist(org.deeplearning4j.nn.conf.distribution.Distribution dist)
void	setDropOut(double dropOut)
void	setEps(double e)
void	setEpsilon(double epsilon)
void	setGradientNormalization(org.deeplearning4j.nn.conf.GradientNormalization gradientNormalization)
void	setGradientNormalizationThreshold(double gradientNormalizationThreshold)
void	setKernelSize(int[] kernelSize)
void	setKernelSizeX(int kernelSize)
void	setKernelSizeY(int kernelSize)
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	setMomentum(double momentum)
void	setMomentumSchedule(java.util.Map<java.lang.Integer,java.lang.Double> momentumSchedule)
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	setPadding(int[] padding)
void	setPaddingX(int padding)
void	setPaddingY(int padding)
void	setPnorm(int p)
void	setPoolingType(org.deeplearning4j.nn.conf.layers.PoolingType poolingType)
void	setRho(double rho)
void	setRmsDecay(double rmsDecay)
void	setStride(int[] stride)
void	setStrideX(int stride)
void	setStrideY(int stride)
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.SubsamplingLayer

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

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

getUpdaterByParam, resetLayerDefaultConfig, setL1Bias, setL2Bias

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

SubsamplingLayer

public SubsamplingLayer()

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 = Convolutional 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

getConvolutionMode

@OptionMetadata(displayName="convolution mode",
                description="The convolution mode (default = Truncate).",
                commandLineParamName="mode",
                commandLineParamSynopsis="-mode <string>",
                displayOrder=1)
public org.deeplearning4j.nn.conf.ConvolutionMode getConvolutionMode()

Overrides:

getConvolutionMode in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

setConvolutionMode

public void setConvolutionMode(org.deeplearning4j.nn.conf.ConvolutionMode convolutionMode)

Overrides:

setConvolutionMode in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

getEps

@OptionMetadata(displayName="eps",
                description="The value of the eps parameter (default = 1e-8).",
                commandLineParamName="eps",
                commandLineParamSynopsis="-eps <double>",
                displayOrder=2)
public double getEps()

Overrides:

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

setEps

public void setEps(double e)

Overrides:

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

getPnorm

@OptionMetadata(displayName="pnorm",
                description="The value of the pnorm parameter (default = 1).",
                commandLineParamName="pnorm",
                commandLineParamSynopsis="-pnorm <int>",
                displayOrder=3)
public int getPnorm()

Overrides:

getPnorm in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

setPnorm

public void setPnorm(int p)

Overrides:

setPnorm in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

getKernelSizeX

@OptionMetadata(displayName="number of columns in kernel",
                description="The number of columns in the kernel (default = 5).",
                commandLineParamName="kernelSizeX",
                commandLineParamSynopsis="-kernelSizeX <int>",
                displayOrder=4)
public int getKernelSizeX()

setKernelSizeX

public void setKernelSizeX(int kernelSize)

getKernelSizeY

@OptionMetadata(displayName="number of rows in kernel",
                description="The number of rows in the kernel (default = 5).",
                commandLineParamName="kernelSizeY",
                commandLineParamSynopsis="-kernelSizeY <int>",
                displayOrder=5)
public int getKernelSizeY()

setKernelSizeY

public void setKernelSizeY(int kernelSize)

getKernelSize

@ProgrammaticProperty
public int[] getKernelSize()

Overrides:

getKernelSize in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

setKernelSize

public void setKernelSize(int[] kernelSize)

Overrides:

setKernelSize in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

getStrideX

@OptionMetadata(displayName="number of columns in stride",
                description="The number of columns in the stride (default = 1).",
                commandLineParamName="strideX",
                commandLineParamSynopsis="-strideX <int>",
                displayOrder=6)
public int getStrideX()

setStrideX

public void setStrideX(int stride)

getStrideY

@OptionMetadata(displayName="number of rows in stride",
                description="The number of rows in the stride (default = 1).",
                commandLineParamName="strideY",
                commandLineParamSynopsis="-strideY <int>",
                displayOrder=7)
public int getStrideY()

setStrideY

public void setStrideY(int stride)

getStride

@ProgrammaticProperty
public int[] getStride()

Overrides:

getStride in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

setStride

public void setStride(int[] stride)

Overrides:

setStride in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

getPaddingX

@OptionMetadata(displayName="number of columns in padding",
                description="The number of columns in the padding (default = 0).",
                commandLineParamName="paddingX",
                commandLineParamSynopsis="-paddingX <int>",
                displayOrder=8)
public int getPaddingX()

setPaddingX

public void setPaddingX(int padding)

getPaddingY

@OptionMetadata(displayName="number of rows in padding",
                description="The number of rows in the padding (default = 0).",
                commandLineParamName="paddingY",
                commandLineParamSynopsis="-paddingY <int>",
                displayOrder=9)
public int getPaddingY()

setPaddingY

public void setPaddingY(int padding)

getPadding

@ProgrammaticProperty
public int[] getPadding()

Overrides:

getPadding in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

setPadding

public void setPadding(int[] padding)

Overrides:

setPadding in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

getPoolingType

@OptionMetadata(displayName="pooling type",
                description="The type of pooling to use (default = MAX; options: MAX, AVG, SUM, NONE).",
                commandLineParamName="poolingType",
                commandLineParamSynopsis="-poolingType <string>",
                displayOrder=10)
public org.deeplearning4j.nn.conf.layers.PoolingType getPoolingType()

Overrides:

getPoolingType in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

setPoolingType

public void setPoolingType(org.deeplearning4j.nn.conf.layers.PoolingType poolingType)

Overrides:

setPoolingType in class org.deeplearning4j.nn.conf.layers.SubsamplingLayer

getActivationFunction

@OptionMetadata(displayName="activation function",
                description="The activation function to use (default = Identity).",
                commandLineParamName="activation",
                commandLineParamSynopsis="-activation <specification>",
                displayOrder=11)
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=12)
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=13)
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=14)
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=15)
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=16)
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=17)
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=18)
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=19)
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=20)
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=21)
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=22)
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=23)
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=24)
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=25)
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=26)
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=27)
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=28)
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=29)
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=30)
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=31)
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=32)
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

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