def get_labels(self, include_freq=False, on_unicode_error='<STR_LIT:strict>'):
a = self.f.getArgs()<EOL>if a.model == model_name.supervised:<EOL><INDENT>pair = self.f.getLabels(on_unicode_error)<EOL>if include_freq:<EOL><INDENT>return (pair[<NUM_LIT:0>], np.array(pair[<NUM_LIT:1>]))<EOL><DEDENT>else:<EOL><INDENT>return pair[<NUM_LIT:0>]<EOL><DEDENT><DEDENT>else:<EOL><INDENT>return self.get_words(include_freq)<EOL><DEDENT>
Get the entire list of labels of the dictionary optionally
including the frequency of the individual labels. Unsupervised
models use words as labels, which is why get_labels
will call and return get_words for this type of
model.