code: def vectorize_dialogue_ohe(self, dia):
          
          # we squeeze it because it's coming out with an extra empty
          # dimension at the front of the shape: (1 x dia x utt x word)
          return np.array([[self.vectorize_utterance_ohe(utt) for utt in dia]]).squeeze()
docs: Take in a dialogue (a sequence of tokenized utterances) and transform it into a
          sequence of sequences of one-hot vectors