org.deeplearning4j.nn.conf

Class MultiLayerConfiguration

java.lang.Object

org.deeplearning4j.nn.conf.MultiLayerConfiguration

All Implemented Interfaces:

Serializable

public class MultiLayerConfiguration
extends Object
implements Serializable

Configuration for a multi layer network

Author:

Adam Gibson

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	MultiLayerConfiguration.Builder

Field Summary

Fields

Modifier and Type	Field and Description
protected boolean	backward
protected List<NeuralNetConfiguration>	confs
protected double	dampingFactor
protected int[]	hiddenLayerSizes
protected Map<Integer,InputPreProcessor>	inputPreProcessors
protected boolean	pretrain
protected Map<Integer,OutputPreProcessor>	processors
protected boolean	useDropConnect
protected boolean	useGaussNewtonVectorProductBackProp
protected boolean	useRBMPropUpAsActivations

Constructor Summary

Constructors

Constructor and Description
MultiLayerConfiguration()
MultiLayerConfiguration(MultiLayerConfiguration multiLayerConfiguration)

Method Summary

Modifier and Type	Method and Description
MultiLayerConfiguration	clone()
boolean	equals(Object o)
static MultiLayerConfiguration	fromJson(String json) Create a neural net configuration from json
NeuralNetConfiguration	getConf(int i)
List<NeuralNetConfiguration>	getConfs()
double	getDampingFactor()
int[]	getHiddenLayerSizes()
InputPreProcessor	getInputPreProcess(int layer)
Map<Integer,InputPreProcessor>	getInputPreProcessors()
OutputPreProcessor	getPreProcessor(int layer)
Map<Integer,OutputPreProcessor>	getProcessors()
int	hashCode()
boolean	isBackward()
boolean	isPretrain()
boolean	isUseDropConnect()
boolean	isUseGaussNewtonVectorProductBackProp()
boolean	isUseRBMPropUpAsActivations()
void	setBackward(boolean backward)
void	setConfs(List<NeuralNetConfiguration> confs)
void	setDampingFactor(double dampingFactor)
void	setHiddenLayerSizes(int[] hiddenLayerSizes)
void	setInputPreProcessors(Map<Integer,InputPreProcessor> inputPreProcessors)
void	setPretrain(boolean pretrain)
void	setProcessors(Map<Integer,OutputPreProcessor> processors)
void	setUseDropConnect(boolean useDropConnect)
void	setUseGaussNewtonVectorProductBackProp(boolean useGaussNewtonVectorProductBackProp)
void	setUseRBMPropUpAsActivations(boolean useRBMPropUpAsActivations)
String	toJson()
String	toString()

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Field Detail

hiddenLayerSizes

protected int[] hiddenLayerSizes

confs

protected List<NeuralNetConfiguration> confs

useDropConnect

protected boolean useDropConnect

useGaussNewtonVectorProductBackProp

protected boolean useGaussNewtonVectorProductBackProp

pretrain

protected boolean pretrain

useRBMPropUpAsActivations

protected boolean useRBMPropUpAsActivations

dampingFactor

protected double dampingFactor

processors

protected Map<Integer,OutputPreProcessor> processors

inputPreProcessors

protected Map<Integer,InputPreProcessor> inputPreProcessors

backward

protected boolean backward

Constructor Detail

MultiLayerConfiguration

public MultiLayerConfiguration()

MultiLayerConfiguration

public MultiLayerConfiguration(MultiLayerConfiguration multiLayerConfiguration)

Method Detail

getConf

public NeuralNetConfiguration getConf(int i)

getPreProcessor

public OutputPreProcessor getPreProcessor(int layer)

getInputPreProcess

public InputPreProcessor getInputPreProcess(int layer)

getDampingFactor

public double getDampingFactor()

setDampingFactor

public void setDampingFactor(double dampingFactor)

isUseRBMPropUpAsActivations

public boolean isUseRBMPropUpAsActivations()

setUseRBMPropUpAsActivations

public void setUseRBMPropUpAsActivations(boolean useRBMPropUpAsActivations)

isUseDropConnect

public boolean isUseDropConnect()

setUseDropConnect

public void setUseDropConnect(boolean useDropConnect)

isUseGaussNewtonVectorProductBackProp

public boolean isUseGaussNewtonVectorProductBackProp()

setUseGaussNewtonVectorProductBackProp

public void setUseGaussNewtonVectorProductBackProp(boolean useGaussNewtonVectorProductBackProp)

isPretrain

public boolean isPretrain()

setPretrain

public void setPretrain(boolean pretrain)

getHiddenLayerSizes

public int[] getHiddenLayerSizes()

setHiddenLayerSizes

public void setHiddenLayerSizes(int[] hiddenLayerSizes)

getConfs

public List<NeuralNetConfiguration> getConfs()

setConfs

public void setConfs(List<NeuralNetConfiguration> confs)

getProcessors

public Map<Integer,OutputPreProcessor> getProcessors()

setProcessors

public void setProcessors(Map<Integer,OutputPreProcessor> processors)

isBackward

public boolean isBackward()

setBackward

public void setBackward(boolean backward)

getInputPreProcessors

public Map<Integer,InputPreProcessor> getInputPreProcessors()

setInputPreProcessors

public void setInputPreProcessors(Map<Integer,InputPreProcessor> inputPreProcessors)

toJson

public String toJson()

Returns:

JSON representation of NN configuration

fromJson

public static MultiLayerConfiguration fromJson(String json)

Create a neural net configuration from json

Parameters:

json - the neural net configuration from json

Returns:

MultiLayerConfiguration

toString

public String toString()

Overrides:

toString in class Object

equals

public boolean equals(Object o)

Overrides:

equals in class Object

hashCode

public int hashCode()

Overrides:

hashCode in class Object

clone

public MultiLayerConfiguration clone()

Overrides:

clone in class Object