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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_word_embs(self, word_dims):
 """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 """

        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)