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Java example source code file (Word2VecTest.java)

This example Java source code file (Word2VecTest.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

collection, commonpreprocessor, defaulttokenizerfactory, exception, file, indarray, inmemorylookuptable, javasparkcontext, string, test, util, vocabword, word2vec, word2vectest, wordvectors

The Word2VecTest.java Java example source code

/*
 *
 *  * Copyright 2015 Skymind,Inc.
 *  *
 *  *    Licensed under the Apache License, Version 2.0 (the "License");
 *  *    you may not use this file except in compliance with the License.
 *  *    You may obtain a copy of the License at
 *  *
 *  *        http://www.apache.org/licenses/LICENSE-2.0
 *  *
 *  *    Unless required by applicable law or agreed to in writing, software
 *  *    distributed under the License is distributed on an "AS IS" BASIS,
 *  *    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  *    See the License for the specific language governing permissions and
 *  *    limitations under the License.
 *
 */

package org.deeplearning4j.spark.models.embeddings.word2vec;

import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.canova.api.util.ClassPathResource;
import org.deeplearning4j.models.embeddings.inmemory.InMemoryLookupTable;
import org.deeplearning4j.models.embeddings.loader.WordVectorSerializer;
import org.deeplearning4j.models.embeddings.reader.impl.BasicModelUtils;
import org.deeplearning4j.models.embeddings.reader.impl.FlatModelUtils;
import org.deeplearning4j.models.embeddings.wordvectors.WordVectors;
import org.deeplearning4j.models.word2vec.VocabWord;
import org.deeplearning4j.models.word2vec.wordstore.VocabCache;
import org.deeplearning4j.text.tokenization.tokenizer.preprocessor.CommonPreprocessor;
import org.deeplearning4j.text.tokenization.tokenizerfactory.DefaultTokenizerFactory;
import org.deeplearning4j.text.tokenization.tokenizerfactory.TokenizerFactory;
import org.junit.Ignore;
import org.junit.Test;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;


import java.io.File;
import java.util.Arrays;
import java.util.Collection;

import static org.junit.Assert.*;

/**
 * @author jeffreytang
 */
public class Word2VecTest {

    @Test
    public void testConcepts() throws Exception {
        // These are all default values for word2vec
       SparkConf sparkConf = new SparkConf().setMaster("local[8]").setAppName("sparktest");

        // Set SparkContext
        JavaSparkContext sc = new JavaSparkContext(sparkConf);

        // Path of data part-00000
        String dataPath = new ClassPathResource("/big/raw_sentences.txt").getFile().getAbsolutePath();
//        dataPath = "/ext/Temp/part-00000";
//        String dataPath = new ClassPathResource("spark_word2vec_test.txt").getFile().getAbsolutePath();

        // Read in data
        JavaRDD<String> corpus = sc.textFile(dataPath);

        TokenizerFactory t = new DefaultTokenizerFactory();
        t.setTokenPreProcessor(new CommonPreprocessor());

        Word2Vec word2Vec = new Word2Vec.Builder()
                .setNGrams(1)
           //     .setTokenizer("org.deeplearning4j.text.tokenization.tokenizerfactory.DefaultTokenizerFactory")
           //     .setTokenPreprocessor("org.deeplearning4j.text.tokenization.tokenizer.preprocessor.CommonPreprocessor")
           //     .setRemoveStop(false)
                .tokenizerFactory(t)
                .seed(42L)
                .negative(10)
                .useAdaGrad(false)
                .layerSize(150)
                .windowSize(5)
                .learningRate(0.025)
                .minLearningRate(0.0001)
                .iterations(1)
                .batchSize(100)
                .minWordFrequency(5)
                .stopWords(Arrays.asList("three"))
                .useUnknown(true)
                .build();

        word2Vec.train(corpus);

        //word2Vec.setModelUtils(new FlatModelUtils());

        System.out.println("UNK: " + word2Vec.getWordVectorMatrix("UNK"));

        InMemoryLookupTable<VocabWord> table = (InMemoryLookupTable) word2Vec.lookupTable();

        double sim = word2Vec.similarity("day", "night");
        System.out.println("day/night similarity: " + sim);
/*
        System.out.println("Hornjo: " + word2Vec.getWordVectorMatrix("hornjoserbsce"));
        System.out.println("carro: " + word2Vec.getWordVectorMatrix("carro"));

        Collection<String> portu = word2Vec.wordsNearest("carro", 10);
        printWords("carro", portu, word2Vec);

        portu = word2Vec.wordsNearest("davi", 10);
        printWords("davi", portu, word2Vec);

        System.out.println("---------------------------------------");
        */

        Collection<String> words = word2Vec.wordsNearest("day", 10);
        printWords("day", words, word2Vec);

        assertTrue(words.contains("night"));
        assertTrue(words.contains("week"));
        assertTrue(words.contains("year"));

        sim = word2Vec.similarity("two", "four");
        System.out.println("two/four similarity: " + sim);

        words = word2Vec.wordsNearest("two", 10);
        printWords("two", words, word2Vec);

        // three should be absent due to stopWords
        assertFalse(words.contains("three"));

        assertTrue(words.contains("five"));
        assertTrue(words.contains("four"));

        sc.stop();


        // test serialization
        File tempFile = File.createTempFile("temp","tmp");
        tempFile.deleteOnExit();

        int idx1 = word2Vec.vocab().wordFor("day").getIndex();

        INDArray array1 = word2Vec.getWordVectorMatrix("day").dup();

        VocabWord word1 = word2Vec.vocab().elementAtIndex(0);

        WordVectorSerializer.writeWordVectors(word2Vec.getLookupTable(), tempFile);

        WordVectors vectors = WordVectorSerializer.loadTxtVectors(tempFile);

        VocabWord word2 = ((VocabCache<VocabWord>)vectors.vocab()).elementAtIndex(0);
        VocabWord wordIT = ((VocabCache<VocabWord>)vectors.vocab()).wordFor("it");
        int idx2 = vectors.vocab().wordFor("day").getIndex();

        INDArray array2 = vectors.getWordVectorMatrix("day").dup();

        System.out.println("word 'i': " + word2);
        System.out.println("word 'it': " + wordIT);

        assertEquals(idx1, idx2);
        assertEquals(word1, word2);
        assertEquals(array1, array2);
    }

    @Test
    @Ignore
    public void testPortugeseW2V() throws Exception {
        WordVectors word2Vec = WordVectorSerializer.loadTxtVectors(new File("/ext/Temp/para.txt"));
        word2Vec.setModelUtils(new FlatModelUtils());

        Collection<String> portu = word2Vec.wordsNearest("carro", 10);
        printWords("carro", portu, word2Vec);

        portu = word2Vec.wordsNearest("davi", 10);
        printWords("davi", portu, word2Vec);
    }

    private static void printWords(String target, Collection<String> list, WordVectors vec) {
        System.out.println("Words close to ["+target+"]:");
        for (String word: list) {
            double sim = vec.similarity(target, word);
            System.out.print("'"+ word+"': ["+ sim+"], ");
        }
        System.out.print("\n");
    }
}

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