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Java example source code file (DBOW.java)

This example Java source code file (DBOW.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

arraylist, atomiclong, dbow, list, logger, nonnull, override, sequence, sequenceelement, skipgram, string, util, vectorsconfiguration, vocabcache, weightlookuptable

The DBOW.java Java example source code

package org.deeplearning4j.models.embeddings.learning.impl.sequence;

import lombok.NonNull;
import org.deeplearning4j.models.embeddings.WeightLookupTable;
import org.deeplearning4j.models.embeddings.loader.VectorsConfiguration;
import org.deeplearning4j.models.embeddings.learning.SequenceLearningAlgorithm;
import org.deeplearning4j.models.embeddings.learning.impl.elements.SkipGram;
import org.deeplearning4j.models.sequencevectors.interfaces.SequenceIterator;
import org.deeplearning4j.models.sequencevectors.sequence.Sequence;
import org.deeplearning4j.models.sequencevectors.sequence.SequenceElement;
import org.deeplearning4j.models.word2vec.wordstore.VocabCache;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.atomic.AtomicLong;

 * @author raver119@gmail.com
public class DBOW<T extends SequenceElement> implements SequenceLearningAlgorithm{
    protected VocabCache<T> vocabCache;
    protected WeightLookupTable<T> lookupTable;
    protected VectorsConfiguration configuration;

    protected int window;
    protected boolean useAdaGrad;
    protected double negative;

    protected SkipGram<T> skipGram = new SkipGram<>();

    private static final Logger log = LoggerFactory.getLogger(DBOW.class);

    public DBOW() {


    public String getCodeName() {
        return "DBOW";

    public void configure(@NonNull VocabCache<T> vocabCache, @NonNull WeightLookupTable lookupTable, @NonNull VectorsConfiguration configuration) {
        this.vocabCache = vocabCache;
        this.lookupTable = lookupTable;

        this.window = configuration.getWindow();
        this.useAdaGrad = configuration.isUseAdaGrad();
        this.negative = configuration.getNegative();

        skipGram.configure(vocabCache, lookupTable, configuration);

     * DBOW doesn't involves any pretraining
     * @param iterator
    public void pretrain(SequenceIterator<T> iterator) {


    public void learnSequence(@NonNull Sequence<T> sequence, @NonNull AtomicLong nextRandom, double learningRate) {
  //      for(int i = 0; i < sequence.getElements().size(); i++) {
            dbow(0, sequence,  (int) nextRandom.get() % window, nextRandom, learningRate);
     //   }

     * DBOW has no reasons for early termination
     * @return
    public boolean isEarlyTerminationHit() {
        return false;

    protected void dbow(int i, Sequence<T> sequence, int b, AtomicLong nextRandom, double alpha) {

        //final T word = sequence.getElements().get(i);
        List<T> sentence = skipGram.applySubsampling(sequence,nextRandom).getElements();

        List<T> labels = new ArrayList<>();

        if (sequence.getSequenceLabel() == null) throw new IllegalStateException("Label is NULL");

        if(sentence.isEmpty() || labels.isEmpty())

        for (T lastWord: labels) {
            for (T word:  sentence) {
                if (word == null) continue;

                skipGram.iterateSample(word, lastWord,nextRandom,alpha);

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