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OPENNLP-1653 Add thread-safe version of LemmatizerME
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mawiesne committed Nov 23, 2024
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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.lemmatizer;

import java.util.List;

import opennlp.tools.commons.ThreadSafe;

/**
* A thread-safe version of the {@link LemmatizerME}. Using it is completely transparent.
* You can use it in a single-threaded context as well, it only incurs a minimal overhead.
* <p>
* Note, however, that 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.
* </p>
* <p>
* Be careful when using this in a Jakarta EE application, for example.
* </p>
* The user is responsible for clearing the {@link ThreadLocal}.
*
* @see Lemmatizer
*/
@ThreadSafe
public class ThreadSafeLemmatizerME implements Lemmatizer, AutoCloseable {

private final LemmatizerModel model;

private final ThreadLocal<LemmatizerME> threadLocal = new ThreadLocal<>();

/**
* Initializes a {@link ThreadSafeLemmatizerME} with the specified {@code model}.
*
* @param model A valid {@link LemmatizerModel}.
*/
public ThreadSafeLemmatizerME(LemmatizerModel model) {
super();
this.model = model;
}

private LemmatizerME getLemmatizer() {
LemmatizerME tagger = threadLocal.get();
if (tagger == null) {
tagger = new LemmatizerME(model);
threadLocal.set(tagger);
}
return tagger;
}

@Override
public String[] lemmatize(String[] toks, String[] tags) {
return getLemmatizer().lemmatize(toks, tags);
}

@Override
public List<List<String>> lemmatize(List<String> toks, List<String> tags) {
return getLemmatizer().lemmatize(toks, tags);
}

@Override
public void close() {
threadLocal.remove();
}

}

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