code: def get_word_embs(self, word_dims):
          
          if self._pret_embeddings is not None:
              return np.random.randn(self.words_in_train, word_dims).astype(np.float32)
          return np.zeros((self.words_in_train, word_dims), dtype=np.float32)
docs: Get randomly initialized embeddings when pre-trained embeddings are used, otherwise zero vectors
  
          Parameters
          ----------
          word_dims : int
              word vector size
          Returns
          -------
          numpy.ndarray
              T x C numpy NDArray