def __call__(self, g):
        r"""
        Parameters
        ----------
        g : DGLGraph
            The input graph, should be a homogeneous directed graph.

        Returns
        -------
        DGLGraph
            The Levi graph of input, will be a heterogeneous graph, where nodes of
            ntypes ``'node'`` and ``'edge'`` have corresponding IDs of nodes and edges
            in the original graph. Edge features of the input graph are copied to
            corresponding new nodes of ntype ``'edge'``.
        """
        device = g.device
        idtype = g.idtype

        edge_list = g.edges()
        n2e = edge_list[0], F.arange(0, g.num_edges(), idtype, device)
        e2n = F.arange(0, g.num_edges(), idtype, device), edge_list[1]
        graph_data = {
            ("node", "n2e", "edge"): n2e,
            ("edge", "e2n", "node"): e2n,
        }
        levi_g = convert.heterograph(graph_data, idtype=idtype, device=device)

        # Copy ndata and edata
        # Since the node types in dgl.heterograph are in alphabetical order
        # ('edge' < 'node'), edge_frames should be in front of node_frames.
        node_frames = utils.extract_node_subframes(g, nodes_or_device=device)
        edge_frames = utils.extract_edge_subframes(g, edges_or_device=device)
        utils.set_new_frames(levi_g, node_frames=edge_frames + node_frames)

        return levi_g

        Parameters
        ----------
        g : DGLGraph
            The input graph, should be a homogeneous directed graph.

        Returns
        -------
        DGLGraph
            The Levi graph of input, will be a heterogeneous graph, where nodes of
            ntypes ``'node'`` and ``'edge'`` have corresponding IDs of nodes and edges
            in the original graph. Edge features of the input graph are copied to
            corresponding new nodes of ntype ``'edge'``.
        
python/dgl/transforms/module.py