dgl.DGLGraph.find_edges¶
-
DGLGraph.
find_edges
(eid, etype=None)¶ Return the source and destination node ID(s) given the edge ID(s).
- Parameters
eid (edge ID(s)) –
The edge IDs. The allowed formats are:
int
: A single ID.Int Tensor: Each element is an ID. The tensor must have the same device type and ID data type as the graph’s.
iterable[int]: Each element is an ID.
etype (str or (str, str, str), optional) –
The type names of the edges. The allowed type name formats are:
(str, str, str)
for source node type, edge type and destination node type.or one
str
edge type name if the name can uniquely identify a triplet format in the graph.
Can be omitted if the graph has only one type of edges.
- Returns
Tensor – The source node IDs of the edges. The i-th element is the source node ID of the i-th edge.
Tensor – The destination node IDs of the edges. The i-th element is the destination node ID of the i-th edge.
Examples
The following example uses PyTorch backend.
>>> import dgl >>> import torch
Create a homogeneous graph.
>>> g = dgl.graph((torch.tensor([0, 0, 1, 1]), torch.tensor([1, 0, 2, 3])))
Find edges of IDs 0 and 2.
>>> g.find_edges(torch.tensor([0, 2])) (tensor([0, 1]), tensor([1, 2]))
For a graph of multiple edge types, it is required to specify the edge type in query.
>>> hg = dgl.heterograph({ ... ('user', 'follows', 'user'): (torch.tensor([0, 1]), torch.tensor([1, 2])), ... ('user', 'plays', 'game'): (torch.tensor([3, 4]), torch.tensor([5, 6])) ... }) >>> hg.find_edges(torch.tensor([1, 0]), 'plays') (tensor([4, 3]), tensor([6, 5]))