本文整理汇总了Java中cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood.shutdown方法的典型用法代码示例。如果您正苦于以下问题：Java CRFTrainerByThreadedLabelLikelihood.shutdown方法的具体用法？Java CRFTrainerByThreadedLabelLikelihood.shutdown怎么用？Java CRFTrainerByThreadedLabelLikelihood.shutdown使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood的用法示例。
在下文中一共展示了CRFTrainerByThreadedLabelLikelihood.shutdown方法的6个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: train
import cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood; //导入方法依赖的package包/类
public CRF train() {
t = 0;
do {
crf = new CRF(crf.getInputPipe(), crf.getOutputPipe());
crf.addStatesForBiLabelsConnectedAsIn(Ds);
trainer = new CRFTrainerByThreadedLabelLikelihood(crf, getThreads());
trainer.train(Ds);
trainer.shutdown();
runEvaluators();
t++;
System.err.println("Finished iteration " + t);
if (Rt.isEmpty())
break;
label();
select();
} while (!stop);
return crf;
}
示例2: trainOnce
import cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood; //导入方法依赖的package包/类
private TransducerTrainer trainOnce(Pipe pipe, InstanceList trainData) {
Stopwatch watch = Stopwatch.createStarted();
CRF crf = new CRF(pipe, null);
crf.addOrderNStates(trainData, new int[]{1}, null, null, null, null, false);
crf.addStartState();
crf.setWeightsDimensionAsIn(trainData, false);
if (initFrom != null) {
crf.initializeApplicableParametersFrom(initFrom);
}
log.info("Starting alignTag training...");
CRFTrainerByThreadedLabelLikelihood trainer = new CRFTrainerByThreadedLabelLikelihood(crf, 8);
trainer.setGaussianPriorVariance(2);
trainer.setAddNoFactors(true);
trainer.setUseSomeUnsupportedTrick(false);
trainer.train(trainData);
trainer.shutdown();
watch.stop();
log.info("Syll align Tag CRF Training took " + watch.toString());
crf.getInputAlphabet().stopGrowth();
crf.getOutputAlphabet().stopGrowth();
return trainer;
}
示例3: trainOnce
import cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood; //导入方法依赖的package包/类
private TransducerTrainer trainOnce(Pipe pipe, InstanceList examples) {
Stopwatch watch = Stopwatch.createStarted();
CRF crf = new CRF(pipe, null);
crf.addOrderNStates(examples, new int[]{1}, null, null, null, null, false);
crf.addStartState();
// crf.setWeightsDimensionAsIn(examples, false);
log.info("Starting syllchain training...");
CRFTrainerByThreadedLabelLikelihood trainer = new CRFTrainerByThreadedLabelLikelihood(crf, 8);
trainer.setGaussianPriorVariance(2);
// trainer.setUseSomeUnsupportedTrick(false);
// trainer.setAddNoFactors(true);
trainer.train(examples);
trainer.shutdown();
watch.stop();
log.info("SyllChain CRF Training took " + watch.toString());
crf.getInputAlphabet().stopGrowth();
crf.getOutputAlphabet().stopGrowth();
return trainer;
}
示例4: trainOnce
import cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood; //导入方法依赖的package包/类
private TransducerTrainer trainOnce(Pipe pipe, InstanceList trainData) {
Stopwatch watch = Stopwatch.createStarted();
CRF crf = new CRF(pipe, null);
crf.addOrderNStates(trainData, new int[]{1}, null, null, null, null, false);
crf.addStartState();
log.info("Starting alignTag training...");
CRFTrainerByThreadedLabelLikelihood trainer = new CRFTrainerByThreadedLabelLikelihood(crf, 8);
trainer.setGaussianPriorVariance(2);
// trainer.setUseSomeUnsupportedTrick(false);
trainer.train(trainData);
trainer.shutdown();
watch.stop();
log.info("Align Tag CRF Training took " + watch.toString());
crf.getInputAlphabet().stopGrowth();
crf.getOutputAlphabet().stopGrowth();
return trainer;
}
示例5: trainOnce
import cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood; //导入方法依赖的package包/类
private TransducerTrainer trainOnce(Pipe pipe, InstanceList examples) {
Stopwatch watch = Stopwatch.createStarted();
CRF crf = new CRF(pipe, null);
crf.addOrderNStates(examples, new int[]{1}, null, null, null, null, false);
crf.addStartState();
crf.setWeightsDimensionAsIn(examples, true);
if (initFrom != null) {
crf.initializeApplicableParametersFrom(initFrom);
}
log.info("Starting syllchain training...");
CRFTrainerByThreadedLabelLikelihood trainer = new CRFTrainerByThreadedLabelLikelihood(crf, 8);
trainer.setGaussianPriorVariance(2);
trainer.setAddNoFactors(true);
// trainer.setUseSomeUnsupportedTrick(true);
trainer.train(examples);
trainer.shutdown();
watch.stop();
log.info("SyllChain CRF Training took " + watch.toString());
crf.getInputAlphabet().stopGrowth();
crf.getOutputAlphabet().stopGrowth();
return trainer;
}
示例6: trainOnce
import cc.mallet.fst.CRFTrainerByThreadedLabelLikelihood; //导入方法依赖的package包/类
private TransducerTrainer trainOnce(Pipe pipe, InstanceList trainData) {
Stopwatch watch = Stopwatch.createStarted();
CRF crf = new CRF(pipe, null);
// O,O O,N -O,C-
// N,O N,N N,C
// C,O ?C,N? C,C
Pattern forbidden = null;
if (USE_ONC_CODING) {
forbidden = Pattern.compile("(O,C|<START>,C|O,<END>)", Pattern.CASE_INSENSITIVE);
}
crf.addOrderNStates(trainData, new int[]{1}, null, null, forbidden, null, false);
crf.addStartState();
crf.setWeightsDimensionAsIn(trainData);
if (this.pullFrom != null) {
crf.initializeApplicableParametersFrom(pullFrom);
}
log.info("Starting syll phone training...");
CRFTrainerByThreadedLabelLikelihood trainer = new CRFTrainerByThreadedLabelLikelihood(crf, 8);
trainer.setGaussianPriorVariance(2);
trainer.setAddNoFactors(false);
trainer.setUseSomeUnsupportedTrick(true);
trainer.train(trainData);
trainer.shutdown();
watch.stop();
pipe.getAlphabet().stopGrowth();
pipe.getTargetAlphabet().stopGrowth();
log.info("Align Tag CRF Training took " + watch.toString());
return trainer;
}