All Downloads are FREE. Search and download functionalities are using the official Maven repository.

opennlp.tools.chunker.ThreadSafeChunkerME Maven / Gradle / Ivy

The newest version!
/*
 * 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 opennlp.tools.commons.ThreadSafe;
import opennlp.tools.util.Sequence;
import opennlp.tools.util.Span;

/**
 * A thread-safe version of the {@link ChunkerME}. Using it is completely transparent.
 * You can use it in a single-threaded context as well, it only incurs a minimal overhead.
 *
 * @implNote
 * This implementation uses a {@link ThreadLocal}. Although the implementation is
 * lightweight because the model is not duplicated, if you have many long-running threads,
 * you may run into memory problems.
 * 

* Be careful when using this in a Jakarta EE application, for example. *

* The user is responsible for clearing the {@link ThreadLocal}. * * @see Chunker * @see ChunkerME */ @ThreadSafe public class ThreadSafeChunkerME implements Chunker, AutoCloseable { private final ChunkerModel model; private final ThreadLocal threadLocal = new ThreadLocal<>(); /** * Initializes a {@link ThreadSafeChunkerME} with the specified {@code model}. * * @param model A valid {@link ChunkerModel}. */ public ThreadSafeChunkerME(ChunkerModel model) { super(); this.model = model; } private ChunkerME getChunker() { ChunkerME c = threadLocal.get(); if (c == null) { c = new ChunkerME(model); threadLocal.set(c); } return c; } @Override public String[] chunk(String[] toks, String[] tags) { return getChunker().chunk(toks, tags); } @Override public Span[] chunkAsSpans(String[] toks, String[] tags) { return getChunker().chunkAsSpans(toks, tags); } @Override public Sequence[] topKSequences(String[] sentence, String[] tags) { return getChunker().topKSequences(sentence, tags); } @Override public Sequence[] topKSequences(String[] sentence, String[] tags, double minSequenceScore) { return getChunker().topKSequences(sentence, tags, minSequenceScore); } @Override public void close() { threadLocal.remove(); } }




© 2015 - 2025 Weber Informatics LLC | Privacy Policy