in opennlp-tools/src/main/java/opennlp/tools/cmdline/parser/ParserTrainerTool.java [124:192]
public void run(String format, String[] args) {
super.run(format, args);
mlParams = CmdLineUtil.loadTrainingParameters(params.getParams(), true);
if (mlParams != null) {
if (!TrainerFactory.isValid(mlParams.getParameters("build"))) {
throw new TerminateToolException(1, "Build training parameters are invalid!");
}
if (!TrainerFactory.isValid(mlParams.getParameters("check"))) {
throw new TerminateToolException(1, "Check training parameters are invalid!");
}
if (!TrainerFactory.isValid(mlParams.getParameters("attach"))) {
throw new TerminateToolException(1, "Attach training parameters are invalid!");
}
if (!TrainerFactory.isValid(mlParams.getParameters("tagger"))) {
throw new TerminateToolException(1, "Tagger training parameters are invalid!");
}
if (!TrainerFactory.isValid(mlParams.getParameters("chunker"))) {
throw new TerminateToolException(1, "Chunker training parameters are invalid!");
}
}
if (mlParams == null) {
mlParams = ModelUtil.createDefaultTrainingParameters();
}
File modelOutFile = params.getModel();
CmdLineUtil.checkOutputFile("parser model", modelOutFile);
ParserModel model;
try {
HeadRules rules = createHeadRules(params);
ParserType type = parseParserType(params.getParserType());
if (params.getFun()) {
Parse.useFunctionTags(true);
}
if (ParserType.CHUNKING.equals(type)) {
model = opennlp.tools.parser.chunking.Parser.train(
params.getLang(), sampleStream, rules,
mlParams);
}
else if (ParserType.TREEINSERT.equals(type)) {
model = opennlp.tools.parser.treeinsert.Parser.train(params.getLang(), sampleStream, rules,
mlParams);
}
else {
throw new IllegalStateException();
}
}
catch (IOException e) {
throw createTerminationIOException(e);
}
finally {
try {
sampleStream.close();
} catch (IOException e) {
// sorry that this can fail
}
}
CmdLineUtil.writeModel("parser", modelOutFile, model);
}