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'
