def METHOD_NAME(self, src_feat, dst_feat, edge_feat):
    """Apply ernie model on the edge.
    Args:
        src_feat (Tensor Dict): src feature tensor dict.
        dst_feat (Tensor Dict): dst feature tensor dict.
        edge_feat (Tensor Dict): edge feature tensor dict.
    Returns:
        Tensor Dict: tensor dict which use 'msg' as the key.
    """
    # input_ids
    cls = paddle.full(shape=[src_feat["term_ids"].shape[0], 1], dtype="int64", fill_value=self.cls_token_id)
    src_ids = paddle.concat([cls, src_feat["term_ids"]], 1)
    dst_ids = dst_feat["term_ids"]
    # sent_ids
    sent_ids = paddle.concat([paddle.zeros_like(src_ids), paddle.ones_like(dst_ids)], 1)
    term_ids = paddle.concat([src_ids, dst_ids], 1)
    # build position_ids
    input_mask = paddle.cast(term_ids > 0, "int64")
    position_ids = paddle.cumsum(input_mask, axis=1) - 1
    outputs = self.ernie(term_ids, sent_ids, position_ids)
    feature = outputs[1]
    return {"msg": feature}