def EndDialog(self, rc): self.trainedPhrases = [] if TrainInBatchMode and self.Batch: natlink.finishTraining(0) print 'results not processed' self._obj_.EndDialog(rc) return
def EndDialog(self, rc): self.trainedPhrases=[] if TrainInBatchMode and self.Batch: natlink.finishTraining(0) print 'results not processed' self._obj_.EndDialog(rc) return
def trainingPass(combinedResults,trainingType): count = len(combinedResults) print 'Performing %s on %d utterances... ' % (trainingType,count), natlink.startTraining(trainingType) for result in combinedResults: result[1].correction(result[0]) count = count - 1 sys.stdout.write('\b\b\b\b\b\b\b\b\b\b%5d left' % count) natlink.finishTraining() print ''
def trainingPass(combinedResults, trainingType): count = len(combinedResults) print 'Performing %s on %d utterances... ' % (trainingType, count), natlink.startTraining(trainingType) for result in combinedResults: result[1].correction(result[0]) count = count - 1 sys.stdout.write('\b\b\b\b\b\b\b\b\b\b%5d left' % count) natlink.finishTraining() print ''
def OnOK(self): self.onStop(0, 0) self.correctResults() if TrainInBatchMode and self.Batch: print 'batch processing results' try: natlink.finishTraining() print 'results processed' except: print 'results processing not possible' self.Batch = 0 else: print 'Done'
def OnOK(self): self.onStop(0,0) self.correctResults() if TrainInBatchMode and self.Batch: print 'batch processing results' try: natlink.finishTraining() print 'results processed' except: print 'results processing not possible' self.Batch=0 else: print 'Done'