org.deeplearning4j.models.embeddings.learning.impl.elements

Class CBOW<T extends SequenceElement>

java.lang.Object

org.deeplearning4j.models.embeddings.learning.impl.elements.CBOW<T>

All Implemented Interfaces:

ElementsLearningAlgorithm<T>

public class CBOW<T extends SequenceElement>
extends Object
implements ElementsLearningAlgorithm<T>

CBOW implementation for DeepLearning4j

Author:

[email protected]

Field Summary

Fields

Modifier and Type	Field and Description
protected double[]	expTable
protected static double	MAX_EXP
protected double	negative
protected double	sampling
protected org.nd4j.linalg.api.ndarray.INDArray	syn0
protected org.nd4j.linalg.api.ndarray.INDArray	syn1
protected org.nd4j.linalg.api.ndarray.INDArray	syn1Neg
protected org.nd4j.linalg.api.ndarray.INDArray	table
protected boolean	useAdaGrad
protected int[]	variableWindows
protected int	window

Constructor Summary

Constructors

Constructor and Description
CBOW()

Method Summary

Modifier and Type	Method and Description
Sequence<T>	applySubsampling(Sequence<T> sequence, AtomicLong nextRandom)
void	cbow(int i, List<T> sentence, int b, AtomicLong nextRandom, double alpha, int currentWindow)
void	configure(VocabCache<T> vocabCache, WeightLookupTable<T> lookupTable, VectorsConfiguration configuration)
String	getCodeName()
boolean	isEarlyTerminationHit()
org.nd4j.linalg.api.ndarray.INDArray	iterateSample(T currentWord, org.nd4j.linalg.api.ndarray.INDArray neu1, AtomicLong nextRandom, double alpha)
double	learnSequence(Sequence<T> sequence, AtomicLong nextRandom, double learningRate) This method does training over the sequence of elements passed into it
void	pretrain(SequenceIterator<T> iterator) CBOW doesn't involve any pretraining

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

MAX_EXP

protected static double MAX_EXP

window

protected int window

useAdaGrad

protected boolean useAdaGrad

negative

protected double negative

sampling

protected double sampling

variableWindows

protected int[] variableWindows

expTable

protected double[] expTable

syn0

protected org.nd4j.linalg.api.ndarray.INDArray syn0

syn1

protected org.nd4j.linalg.api.ndarray.INDArray syn1

syn1Neg

protected org.nd4j.linalg.api.ndarray.INDArray syn1Neg

table

protected org.nd4j.linalg.api.ndarray.INDArray table

Constructor Detail

CBOW

public CBOW()

Method Detail

getCodeName

public String getCodeName()

Specified by:

getCodeName in interface ElementsLearningAlgorithm<T extends SequenceElement>

configure

public void configure(@NonNull
                      VocabCache<T> vocabCache,
                      @NonNull
                      WeightLookupTable<T> lookupTable,
                      @NonNull
                      VectorsConfiguration configuration)

Specified by:

configure in interface ElementsLearningAlgorithm<T extends SequenceElement>

pretrain

public void pretrain(SequenceIterator<T> iterator)

CBOW doesn't involve any pretraining

Specified by:

pretrain in interface ElementsLearningAlgorithm<T extends SequenceElement>

Parameters:

iterator -

learnSequence

public double learnSequence(Sequence<T> sequence,
                            AtomicLong nextRandom,
                            double learningRate)

Description copied from interface: ElementsLearningAlgorithm

This method does training over the sequence of elements passed into it

Specified by:

learnSequence in interface ElementsLearningAlgorithm<T extends SequenceElement>

Returns:

average score for this sequence

isEarlyTerminationHit

public boolean isEarlyTerminationHit()

Specified by:

isEarlyTerminationHit in interface ElementsLearningAlgorithm<T extends SequenceElement>

iterateSample

public org.nd4j.linalg.api.ndarray.INDArray iterateSample(T currentWord,
                                                          org.nd4j.linalg.api.ndarray.INDArray neu1,
                                                          AtomicLong nextRandom,
                                                          double alpha)

cbow

public void cbow(int i,
                 List<T> sentence,
                 int b,
                 AtomicLong nextRandom,
                 double alpha,
                 int currentWindow)

applySubsampling

public Sequence<T> applySubsampling(@NonNull
                                    Sequence<T> sequence,
                                    @NonNull
                                    AtomicLong nextRandom)