def train(self, epochs=2000, super_epochs=5, tqdm=None):
        '''
        Parameters
        ----------
        epochs : int
          Number of epochs to train for.  Default is 2000.
        super_epochs : int
            Number of times to repeat training process. Default is training_iterations.

        Returns
        -------
        A trained word2vec model.
        '''

        self._scan_and_build_vocab()
        myiter = range(super_epochs)
        if tqdm:
            myiter = tqdm(myiter, total=super_epochs)
        for _ in myiter:
            self.model.train(CorpusAdapterForGensim.get_sentences(self.corpus),
                             total_examples=self.model.corpus_count,
                             epochs=epochs)
        return self.model

        Parameters
        ----------
        epochs : int
          Number of epochs to train for.  Default is 2000.
        super_epochs : int
            Number of times to repeat training process. Default is training_iterations.

        Returns
        -------
        A trained word2vec model.
        
scattertext/representations/Word2VecFromParsedCorpus.py