opennlp.tools.cmdline.chunker.ChunkerTrainerTool Maven / Gradle / Ivy
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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,
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* See the License for the specific language governing permissions and
* limitations under the License.
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package opennlp.tools.cmdline.chunker;
import java.io.File;
import java.io.IOException;
import opennlp.tools.chunker.ChunkSample;
import opennlp.tools.chunker.ChunkerFactory;
import opennlp.tools.chunker.ChunkerME;
import opennlp.tools.chunker.ChunkerModel;
import opennlp.tools.cmdline.AbstractTrainerTool;
import opennlp.tools.cmdline.CmdLineUtil;
import opennlp.tools.cmdline.TerminateToolException;
import opennlp.tools.cmdline.chunker.ChunkerTrainerTool.TrainerToolParams;
import opennlp.tools.cmdline.params.TrainingToolParams;
import opennlp.tools.util.model.ModelUtil;
public class ChunkerTrainerTool
extends AbstractTrainerTool {
interface TrainerToolParams extends TrainingParams, TrainingToolParams {
}
public ChunkerTrainerTool() {
super(ChunkSample.class, TrainerToolParams.class);
}
public String getName() {
return "ChunkerTrainerME";
}
public String getShortDescription() {
return "trainer for the learnable chunker";
}
public void run(String format, String[] args) {
super.run(format, args);
mlParams = CmdLineUtil.loadTrainingParameters(params.getParams(), false);
if(mlParams == null) {
mlParams = ModelUtil.createDefaultTrainingParameters();
}
File modelOutFile = params.getModel();
CmdLineUtil.checkOutputFile("sentence detector model", modelOutFile);
ChunkerModel model;
try {
ChunkerFactory chunkerFactory = ChunkerFactory
.create(params.getFactory());
model = ChunkerME.train(params.getLang(), sampleStream, mlParams,
chunkerFactory);
} catch (IOException e) {
throw new TerminateToolException(-1, "IO error while reading training data or indexing data: " +
e.getMessage(), e);
}
finally {
try {
sampleStream.close();
} catch (IOException e) {
// sorry that this can fail
}
}
CmdLineUtil.writeModel("chunker", modelOutFile, model);
}
}