455ea48570f1af63b1270c8ccda49fbe3deb9bcc,python/dgl/graph.py,DGLGraph,from_networkx,#DGLGraph#Any#Any#Any#,1022

Before Change

            for attr in node_attrs:
                self._node_frame[attr] = _batcher(attr_dict[attr])
        if edge_attrs is not None:
            attr_dict = {attr : [] for attr in edge_attrs}
            src, dst, _ = self._graph.edges()
            for u, v in zip(src.tolist(), dst.tolist()):
                for attr in edge_attrs:

After Change

            for attr in node_attrs:
                self._node_frame[attr] = _batcher(attr_dict[attr])
        if edge_attrs is not None:
            has_edge_id = "id" in next(iter(nx_graph.edges(data=True)))[-1]
            attr_dict = defaultdict(lambda: [None] * self.number_of_edges())
            if has_edge_id:
                for u, v, attrs in nx_graph.edges(data=True):
                    for key in edge_attrs:
                        attr_dict[key][attrs["id"]] = attrs[key]
            else:
                // XXX: assuming networkx iteration order is deterministic
                for eid, (_, _, attr) in enumerate(nx_graph.edges(data=True)):
                    for key in edge_attrs:
                        attr_dict[key][eid] = attrs[key]
            for attr in edge_attrs:
                self._edge_frame[attr] = _batcher(attr_dict[attr])

    def from_scipy_sparse_matrix(self, a):

Instances