def METHOD_NAME(self, input):
    #[analogy_a, analogy_b, analogy_c] = inputs
    all_label = paddle.static.data(
        name="all_label",
        shape=[self.sparse_feature_number],
        dtype='int64')
    word2vec = Word2VecInferLayer(self.sparse_feature_number,
                                  self.sparse_feature_dim, "emb")
    val, pred_idx = word2vec.forward(input[0], input[1], input[2],
                                     all_label)
    fetch_dict = {'pred_idx': pred_idx}
    return fetch_dict