def get_word_embs(self, word_dims):
if self._pret_embeddings is not None:<EOL><INDENT>return np.random.randn(self.words_in_train, word_dims).astype(np.float32)<EOL><DEDENT>return np.zeros((self.words_in_train, word_dims), dtype=np.float32)<EOL>
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