def train_models(self, event, corpus, feature_set, **kwargs):
print "- training salience models..."
sm = SalienceModels()
sm.train_models(event, corpus, feature_set, self.key, **kwargs)
if not self.check_model_pipeline(event, corpus, feature_set, **kwargs):
raise Exception("Model training failed!")
def check_model_pipeline(self, event, corpus, feature_set, **kwargs):
sm = SalienceModels()
coverage = sm.check_coverage(event, corpus, feature_set, self.key,
**kwargs)
return coverage == 1
