dgl.to_bidirectedΒΆ
-
dgl.
to_bidirected
(g, copy_ndata=False, readonly=None)[source]ΒΆ Convert the graph to a bi-directional simple graph and return.
For an input graph \(G\), return a new graph \(G'\) such that an edge \((u, v)\in G'\) exists if and only if there exists an edge \((v, u)\in G\). The resulting graph \(G'\) is a simple graph, meaning there is no parallel edge.
The operation only works for edges whose two endpoints belong to the same node type. DGL will raise error if the input graph is heterogeneous and contains edges with different types of endpoints.
- Parameters
- Returns
The bidirected graph
- Return type
Notes
If
copy_ndata
is True, the resulting graph will share the node feature tensors with the input graph. Hence, users should try to avoid in-place operations which will be visible to both graphs.This function discards the batch information. Please use
dgl.DGLGraph.set_batch_num_nodes()
anddgl.DGLGraph.set_batch_num_edges()
on the transformed graph to maintain the information.Examples
The following examples use PyTorch backend.
>>> import dgl >>> import torch as th >>> g = dgl.graph((th.tensor([0, 1, 2]), th.tensor([1, 2, 0]))) >>> bg1 = dgl.to_bidirected(g) >>> bg1.edges() (tensor([0, 1, 2, 1, 2, 0]), tensor([1, 2, 0, 0, 1, 2]))
The graph already have i->j and j->i
>>> g = dgl.graph((th.tensor([0, 1, 2, 0]), th.tensor([1, 2, 0, 2]))) >>> bg1 = dgl.to_bidirected(g) >>> bg1.edges() (tensor([0, 1, 2, 1, 2, 0]), tensor([1, 2, 0, 0, 1, 2]))
Heterogeneous graphs with Multiple Edge Types
>>> g = dgl.heterograph({ ... ('user', 'wins', 'user'): (th.tensor([0, 2, 0, 2]), th.tensor([1, 1, 2, 0])), ... ('user', 'follows', 'user'): (th.tensor([1, 2, 1]), th.tensor([2, 1, 1])) ... }) >>> bg1 = dgl.to_bidirected(g) >>> bg1.edges(etype='wins') (tensor([0, 0, 1, 1, 2, 2]), tensor([1, 2, 0, 2, 0, 1])) >>> bg1.edges(etype='follows') (tensor([1, 1, 2]), tensor([1, 2, 1]))