def hybrid_forward(self, F, words1, words2, weight):  
embeddings_words1 = F.Embedding(words1, weight,<EOL>input_dim=self._vocab_size,<EOL>output_dim=self._embed_size)<EOL>embeddings_words2 = F.Embedding(words2, weight,<EOL>input_dim=self._vocab_size,<EOL>output_dim=self._embed_size)<EOL>similarity = self.similarity(embeddings_words1, embeddings_words2)<EOL>return similarity<EOL>
Predict the similarity of words1 and words2.

        Parameters
        ----------
        words1 : Symbol or NDArray
            The indices of the words the we wish to compare to the words in words2.
        words2 : Symbol or NDArray
            The indices of the words the we wish to compare to the words in words1.

        Returns
        -------
        similarity : Symbol or NDArray
            The similarity computed by WordEmbeddingSimilarity.similarity_function.