/*
* 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.cmdline.tokenizer;
import java.io.File;
import java.io.FileInputStream;
import java.io.IOException;
import opennlp.tools.cmdline.AbstractTrainerTool;
import opennlp.tools.cmdline.CmdLineUtil;
import opennlp.tools.cmdline.TerminateToolException;
import opennlp.tools.cmdline.params.TrainingToolParams;
import opennlp.tools.cmdline.tokenizer.TokenizerTrainerTool.TrainerToolParams;
import opennlp.tools.dictionary.Dictionary;
import opennlp.tools.ml.TrainerFactory;
import opennlp.tools.ml.TrainerFactory.TrainerType;
import opennlp.tools.tokenize.TokenSample;
import opennlp.tools.tokenize.TokenizerFactory;
import opennlp.tools.tokenize.TokenizerModel;
import opennlp.tools.util.model.ModelUtil;
public final class TokenizerTrainerTool
extends AbstractTrainerTool<TokenSample, TrainerToolParams> {
interface TrainerToolParams extends TrainingParams, TrainingToolParams {
}
public TokenizerTrainerTool() {
super(TokenSample.class, TrainerToolParams.class);
}
public String getShortDescription() {
return "trainer for the learnable tokenizer";
}
static Dictionary loadDict(File f) throws IOException {
Dictionary dict = null;
if (f != null) {
CmdLineUtil.checkInputFile("abb dict", f);
dict = new Dictionary(new FileInputStream(f));
}
return dict;
}
public void run(String format, String[] args) {
super.run(format, args);
mlParams = CmdLineUtil.loadTrainingParameters(params.getParams(), false);
if (mlParams != null) {
if (!TrainerFactory.isValid(mlParams.getSettings())) {
throw new TerminateToolException(1, "Training parameters file '" + params.getParams() +
"' is invalid!");
}
if (!TrainerType.EVENT_MODEL_TRAINER.equals(TrainerFactory.getTrainerType(mlParams.getSettings()))) {
throw new TerminateToolException(1, "Sequence training is not supported!");
}
}
if(mlParams == null) {
mlParams = ModelUtil.createDefaultTrainingParameters();
}
File modelOutFile = params.getModel();
CmdLineUtil.checkOutputFile("tokenizer model", modelOutFile);
TokenizerModel model;
try {
Dictionary dict = loadDict(params.getAbbDict());
TokenizerFactory tokFactory = TokenizerFactory.create(
params.getFactory(), params.getLang(), dict,
params.getAlphaNumOpt(), null);
model = opennlp.tools.tokenize.TokenizerME.train(sampleStream,
tokFactory, mlParams);
} 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("tokenizer", modelOutFile, model);
}
}