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Java example source code file (TreeModelUtils.java)

This example Java source code file (TreeModelUtils.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, basicmodelutils, collection, datapoint, hashset, indarray, override, sequenceelement, string, treemodelutils, util, vptree, weightlookuptable

The TreeModelUtils.java Java example source code

package org.deeplearning4j.models.embeddings.reader.impl;

import lombok.NonNull;
import org.deeplearning4j.clustering.sptree.DataPoint;
import org.deeplearning4j.clustering.vptree.VPTree;
import org.deeplearning4j.models.embeddings.WeightLookupTable;
import org.deeplearning4j.models.sequencevectors.sequence.SequenceElement;
import org.deeplearning4j.util.SetUtils;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;

import java.util.*;

/**
 * This is VPTree-based implementation for wordsNearest method, suited for multiple consequent calls.
 * Please note: VPTree will take some memory, dependant on your model size.
 *
 * @author raver119@gmail.com
 */
public class TreeModelUtils<T extends SequenceElement> extends BasicModelUtils {
    protected VPTree vpTree;

    @Override
    public void init(@NonNull WeightLookupTable<T> lookupTable) {
        super.init(lookupTable);
        vpTree = null;
    }

    protected synchronized void checkTree() {
        // build new tree if it wasn't created before
        if (vpTree == null) {
            List<DataPoint> points = new ArrayList<>();
            for (String word: vocabCache.words()) {
                points.add(new DataPoint(vocabCache.indexOf(word), lookupTable.vector(word)));
            }
            vpTree = new VPTree(points);
        }
    }


    /**
     * This method returns nearest words for target word, based on tree structure.
     * This method is recommended to use if you're going to call for nearest words multiple times.
     * VPTree will be built upon firt call to this method
     *
     * @param label label of element we're looking nearest words to
     * @param n number of nearest elements to return
     * @return
     */
    @Override
    public Collection<String> wordsNearest(String label, int n) {
        if (!vocabCache.hasToken(label)) return new ArrayList<>();

        Collection<String> collection = wordsNearest(Arrays.asList(label),new ArrayList(),n + 1);
        if (collection.contains(label)) collection.remove(label);

        return collection;
    }

    @Override
    public Collection<String> wordsNearest(Collection positive, Collection negative, int top) {

        // Check every word is in the model
        for (String p : SetUtils.union(new HashSet<>(positive), new HashSet<>(negative))) {
            if (!vocabCache.containsWord(p)) {
                return new ArrayList<>();
            }
        }

        INDArray words = Nd4j.create(positive.size() + negative.size(), lookupTable.layerSize());
        int row = 0;
        for (String s : positive) {
            words.putRow(row++, lookupTable.vector(s));
        }

        for (String s : negative) {
            words.putRow(row++, lookupTable.vector(s).mul(-1));
        }

        INDArray mean = words.isMatrix() ? words.mean(0) : words;

        return wordsNearest(mean, top);
    }

    @Override
    public Collection<String> wordsNearest(INDArray words, int top) {
        checkTree();

        List<DataPoint> add = new ArrayList<>();
        List<Double> distances = new ArrayList<>();

        // we need n+1 to address original datapoint removal
        vpTree.search(new DataPoint(0, words), top, add, distances );

        Collection<String> ret = new ArrayList<>();
        for (DataPoint e: add) {
            String word  = vocabCache.wordAtIndex(e.getIndex());
            ret.add(word);
        }

        return super.wordsNearest(words, top);
    }
}

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