/* * 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 org.cogroo.tools.chunker2; 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; public class ChunkSampleSequenceStream implements SequenceStream { private final ObjectStream<ChunkSample> samples; private final ChunkerContextGenerator contextGenerator; public ChunkSampleSequenceStream(ObjectStream<ChunkSample> samples, ChunkerContextGenerator contextGenerator) { this.samples = samples; this.contextGenerator = contextGenerator; } @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(); } }