| /* |
| * 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.FileInputStream; |
| 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)); |
| } |
| } |
| |
| } |