opennlp.tools.chunker.ChunkSampleSequenceStream Maven / Gradle / Ivy
/*
* 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.chunker;
import java.io.IOException;
import opennlp.tools.ml.model.AbstractModel;
import opennlp.tools.ml.model.Event;
import opennlp.tools.ml.model.Sequence;
import opennlp.tools.ml.model.SequenceStream;
import opennlp.tools.util.ObjectStream;
/**
* A {@link SequenceStream} implementation encapsulating {@link ChunkSample samples}.
*/
public class ChunkSampleSequenceStream implements SequenceStream {
private final ObjectStream samples;
private final ChunkerContextGenerator contextGenerator;
/**
* Creates a {@link ChunkSampleSequenceStream} with given {@code samples} using
* a {@link ChunkerContextGenerator}.
*
* @param samples The data stream of {@link ChunkSample samples}.
* @param generator A {@link ChunkerContextGenerator} which shall be used.
*/
public ChunkSampleSequenceStream(ObjectStream samples, ChunkerContextGenerator generator) {
this.samples = samples;
this.contextGenerator = generator;
}
@Override
public Sequence read() throws IOException {
ChunkSample sample = samples.read();
if (sample != null) {
String[] sentence = sample.getSentence();
String[] tags = sample.getTags();
Event[] events = new Event[sentence.length];
for (int i = 0; i < sentence.length; i++) {
// it is safe to pass the tags as previous tags because
// the context generator does not look for non predicted tags
String[] context = contextGenerator.getContext(i, sentence, tags, null);
events[i] = new Event(tags[i], context);
}
return new Sequence<>(events,sample);
}
return null;
}
@Override
public Event[] updateContext(Sequence sequence, AbstractModel model) {
// TODO: Should be implemented for Perceptron sequence learning ...
return null;
}
@Override
public void reset() throws IOException, UnsupportedOperationException {
samples.reset();
}
@Override
public void close() throws IOException {
samples.close();
}
}