def METHOD_NAME(self, g, h):
    """
    Description
    -----------
    Forward computation
    Parameters
    ----------
    g : DGLGraph
        The graph.
    feat : mxnet.NDArray or pair of mxnet.NDArray
        :math:`(N, D)` where :math:`N` is the number of nodes and
        :math:`D` is the number of feature dimensions.
        If a pair of mxnet.NDArray is given, the graph must be a uni-bipartite graph
        with only one edge type, and the two tensors must have the same
        dimensionality on all except the first axis.
    Returns
    -------
    mxnet.NDArray
        New node features.
    Raises
    ------
    DGLError
        If there are 0-in-degree nodes in the input graph, it will raise DGLError
        since no message will be passed to those nodes. This will cause invalid output.
        The error can be ignored by setting ``allow_zero_in_degree`` parameter to ``True``.
    """
    with g.local_scope():
        if not self._allow_zero_in_degree:
            if g.in_degrees().min() == 0:
                raise DGLError(
                    "There are 0-in-degree nodes in the graph, "
                    "output for those nodes will be invalid. "
                    "This is harmful for some applications, "
                    "causing silent performance regression. "
                    "Adding self-loop on the input graph by "
                    "calling `g = dgl.add_self_loop(g)` will resolve "
                    "the issue. Setting ``allow_zero_in_degree`` "
                    "to be `True` when constructing this module will "
                    "suppress the check and let the code run."
                )
        h_src, h_dst = expand_as_pair(h, g)
        g.srcdata["x"] = h_src
        g.dstdata["x"] = h_dst
        g.apply_edges(fn.v_sub_u("x", "x", "theta"))
        g.edata["theta"] = self.theta(g.edata["theta"])
        g.dstdata["phi"] = self.phi(g.dstdata["x"])
        if not self.batch_norm:
            g.update_all(fn.e_add_v("theta", "phi", "e"), fn.max("e", "x"))
        else:
            g.apply_edges(fn.e_add_v("theta", "phi", "e"))
            g.edata["e"] = self.bn(g.edata["e"])
            g.update_all(fn.copy_e("e", "m"), fn.max("m", "x"))
        return g.dstdata["x"]