Examples with SentenceTransformer org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer used on opensource projects

Example 1 with SentenceTransformer

use of org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer in project deeplearning4j by deeplearning4j.

the class Word2Vec method setSentenceIterator.

/**
     * This method defines SentenceIterator instance, that will be used as training corpus source
     *
     * @param iterator SentenceIterator instance
     */
public void setSentenceIterator(@NonNull SentenceIterator iterator) {
    if (tokenizerFactory != null) {
        SentenceTransformer transformer = new SentenceTransformer.Builder().iterator(iterator).tokenizerFactory(tokenizerFactory).allowMultithreading(configuration == null || configuration.isAllowParallelTokenization()).build();
        this.iterator = new AbstractSequenceIterator.Builder<>(transformer).build();
    } else
        log.error("Please call setTokenizerFactory() prior to setSentenceIter() call.");
}

Example 2 with SentenceTransformer

use of org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer in project deeplearning4j by deeplearning4j.

the class ParallelTransformerIteratorTest method testSpeedComparison1.

@Test
public void testSpeedComparison1() throws Exception {
    SentenceIterator iterator = new MutipleEpochsSentenceIterator(new BasicLineIterator(new ClassPathResource("/big/raw_sentences.txt").getFile()), 25);
    SentenceTransformer transformer = new SentenceTransformer.Builder().iterator(iterator).allowMultithreading(false).tokenizerFactory(factory).build();
    Iterator<Sequence<VocabWord>> iter = transformer.iterator();
    int cnt = 0;
    long time1 = System.currentTimeMillis();
    while (iter.hasNext()) {
        Sequence<VocabWord> sequence = iter.next();
        assertNotEquals("Failed on [" + cnt + "] iteration", null, sequence);
        assertNotEquals("Failed on [" + cnt + "] iteration", 0, sequence.size());
        cnt++;
    }
    long time2 = System.currentTimeMillis();
    log.info("Single-threaded time: {} ms", time2 - time1);
    iterator.reset();
    transformer = new SentenceTransformer.Builder().iterator(iterator).allowMultithreading(true).tokenizerFactory(factory).build();
    iter = transformer.iterator();
    time1 = System.currentTimeMillis();
    while (iter.hasNext()) {
        Sequence<VocabWord> sequence = iter.next();
        assertNotEquals("Failed on [" + cnt + "] iteration", null, sequence);
        assertNotEquals("Failed on [" + cnt + "] iteration", 0, sequence.size());
        cnt++;
    }
    time2 = System.currentTimeMillis();
    log.info("Multi-threaded time: {} ms", time2 - time1);
    SentenceIterator baseIterator = iterator;
    baseIterator.reset();
    LabelAwareIterator lai = new BasicLabelAwareIterator.Builder(new MutipleEpochsSentenceIterator(new BasicLineIterator(new ClassPathResource("/big/raw_sentences.txt").getFile()), 25)).build();
    transformer = new SentenceTransformer.Builder().iterator(lai).allowMultithreading(false).tokenizerFactory(factory).build();
    iter = transformer.iterator();
    time1 = System.currentTimeMillis();
    while (iter.hasNext()) {
        Sequence<VocabWord> sequence = iter.next();
        assertNotEquals("Failed on [" + cnt + "] iteration", null, sequence);
        assertNotEquals("Failed on [" + cnt + "] iteration", 0, sequence.size());
        cnt++;
    }
    time2 = System.currentTimeMillis();
    log.info("Prefetched Single-threaded time: {} ms", time2 - time1);
    lai.reset();
    transformer = new SentenceTransformer.Builder().iterator(lai).allowMultithreading(true).tokenizerFactory(factory).build();
    iter = transformer.iterator();
    time1 = System.currentTimeMillis();
    while (iter.hasNext()) {
        Sequence<VocabWord> sequence = iter.next();
        assertNotEquals("Failed on [" + cnt + "] iteration", null, sequence);
        assertNotEquals("Failed on [" + cnt + "] iteration", 0, sequence.size());
        cnt++;
    }
    time2 = System.currentTimeMillis();
    log.info("Prefetched Multi-threaded time: {} ms", time2 - time1);
}

Example 3 with SentenceTransformer

use of org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer in project deeplearning4j by deeplearning4j.

the class VocabConstructorTest method testBuildJointVocabulary2.

@Test
public void testBuildJointVocabulary2() throws Exception {
    File inputFile = new ClassPathResource("big/raw_sentences.txt").getFile();
    SentenceIterator iter = new BasicLineIterator(inputFile);
    VocabCache<VocabWord> cache = new AbstractCache.Builder<VocabWord>().build();
    SentenceTransformer transformer = new SentenceTransformer.Builder().iterator(iter).tokenizerFactory(t).build();
    AbstractSequenceIterator<VocabWord> sequenceIterator = new AbstractSequenceIterator.Builder<>(transformer).build();
    VocabConstructor<VocabWord> constructor = new VocabConstructor.Builder<VocabWord>().addSource(sequenceIterator, 5).useAdaGrad(false).setTargetVocabCache(cache).build();
    constructor.buildJointVocabulary(false, true);
    //        assertFalse(cache.hasToken("including"));
    assertEquals(242, cache.numWords());
    assertEquals("i", cache.wordAtIndex(1));
    assertEquals("it", cache.wordAtIndex(0));
    assertEquals(634303, cache.totalWordOccurrences());
}

Example 4 with SentenceTransformer

use of org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer in project deeplearning4j by deeplearning4j.

the class VocabConstructorTest method testBuildJointVocabulary1.

@Test
public void testBuildJointVocabulary1() throws Exception {
    File inputFile = new ClassPathResource("big/raw_sentences.txt").getFile();
    SentenceIterator iter = new BasicLineIterator(inputFile);
    VocabCache<VocabWord> cache = new AbstractCache.Builder<VocabWord>().build();
    SentenceTransformer transformer = new SentenceTransformer.Builder().iterator(iter).tokenizerFactory(t).build();
    /*
            And we pack that transformer into AbstractSequenceIterator
         */
    AbstractSequenceIterator<VocabWord> sequenceIterator = new AbstractSequenceIterator.Builder<>(transformer).build();
    VocabConstructor<VocabWord> constructor = new VocabConstructor.Builder<VocabWord>().addSource(sequenceIterator, 0).useAdaGrad(false).setTargetVocabCache(cache).build();
    constructor.buildJointVocabulary(true, false);
    assertEquals(244, cache.numWords());
    assertEquals(0, cache.totalWordOccurrences());
}

Example 5 with SentenceTransformer

use of org.deeplearning4j.models.sequencevectors.transformers.impl.SentenceTransformer in project deeplearning4j by deeplearning4j.

the class SequenceVectorsTest method testInternalVocabConstruction.

@Test
public void testInternalVocabConstruction() throws Exception {
    ClassPathResource resource = new ClassPathResource("big/raw_sentences.txt");
    File file = resource.getFile();
    BasicLineIterator underlyingIterator = new BasicLineIterator(file);
    TokenizerFactory t = new DefaultTokenizerFactory();
    t.setTokenPreProcessor(new CommonPreprocessor());
    SentenceTransformer transformer = new SentenceTransformer.Builder().iterator(underlyingIterator).tokenizerFactory(t).build();
    AbstractSequenceIterator<VocabWord> sequenceIterator = new AbstractSequenceIterator.Builder<>(transformer).build();
    SequenceVectors<VocabWord> vectors = new SequenceVectors.Builder<VocabWord>(new VectorsConfiguration()).minWordFrequency(5).iterate(sequenceIterator).batchSize(250).iterations(1).epochs(1).resetModel(false).trainElementsRepresentation(true).build();
    logger.info("Fitting model...");
    vectors.fit();
    logger.info("Model ready...");
    double sim = vectors.similarity("day", "night");
    logger.info("Day/night similarity: " + sim);
    assertTrue(sim > 0.6d);
    Collection<String> labels = vectors.wordsNearest("day", 10);
    logger.info("Nearest labels to 'day': " + labels);
}