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/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you 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 opennlp.tools.dl;
import java.io.InputStream;
import java.util.Arrays;
import java.util.Collection;
import java.util.List;
import java.util.Random;
import org.apache.commons.io.IOUtils;
import org.junit.Before;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.junit.runners.Parameterized;
/**
* CV tests for {@link RNN}
*/
@RunWith(Parameterized.class)
public class RNNTest {
private float learningRate;
private int seqLength;
private int hiddenLayerSize;
private int epochs;
private Random r = new Random();
private String text;
private List<String> words;
public RNNTest(float learningRate, int seqLength, int hiddenLayerSize, int epochs) {
this.learningRate = learningRate;
this.seqLength = seqLength;
this.hiddenLayerSize = hiddenLayerSize;
this.epochs = epochs;
}
@Before
public void setUp() throws Exception {
InputStream stream = getClass().getResourceAsStream("/text/sentences.txt");
text = IOUtils.toString(stream);
words = Arrays.asList(text.split("\\s"));
stream.close();
}
@Parameterized.Parameters
public static Collection<Object[]> data() {
return Arrays.asList(new Object[][] {
{1e-1f, 15, 20, 5},
});
}
@Test
public void testVanillaCharRNNLearn() throws Exception {
RNN rnn = new RNN(learningRate, seqLength, hiddenLayerSize, epochs, text, 5, true);
evaluate(rnn, true);
rnn.serialize("target/crnn-weights-");
}
@Test
public void testVanillaWordRNNLearn() throws Exception {
RNN rnn = new RNN(learningRate, seqLength, hiddenLayerSize, epochs, text, 1, false);
evaluate(rnn, true);
rnn.serialize("target/wrnn-weights-");
}
private void evaluate(RNN rnn, boolean checkRatio) {
System.out.println(rnn);
rnn.learn();
double c = 0;
for (int i = 0; i < 2; i++) {
int seed = r.nextInt(rnn.getVocabSize());
String sample = rnn.sample(seed);
if (checkRatio && rnn.useChars) {
String[] sampleWords = sample.split(" ");
for (String sw : sampleWords) {
if (words.contains(sw)) {
c++;
}
}
if (c > 0) {
c /= sampleWords.length;
}
}
}
if (checkRatio && rnn.useChars) {
System.out.println("average correct word ratio: " + (c / 10d));
}
}
}