dgl.DGLGraph.batch_num_edgesΒΆ
-
DGLGraph.
batch_num_edges
(etype=None)[source]ΒΆ Return the number of edges for each graph in the batch with the specified edge type.
- Parameters
etype (str or tuple of str, optional) β The edge type for query, which can be an edge type (str) or a canonical edge type (3-tuple of str). When an edge type appears in multiple canonical edge types, one must use a canonical edge type. If the graph has multiple edge types, one must specify the argument. Otherwise, it can be omitted.
- Returns
The number of edges with the specified type for each graph in the batch. The i-th element of it is the number of edges with the specified type for the i-th graph. If the graph is not a batched one, it will return a list of length 1 that holds the number of edges in the graph.
- Return type
Tensor
Examples
The following example uses PyTorch backend.
>>> import dgl >>> import torch
Query for homogeneous graphs.
>>> g1 = dgl.graph((torch.tensor([0, 1, 2]), torch.tensor([1, 2, 3]))) >>> g1.batch_num_edges() tensor([3]) >>> g2 = dgl.graph((torch.tensor([0, 0, 0, 1]), torch.tensor([0, 1, 2, 0]))) >>> bg = dgl.batch([g1, g2]) >>> bg.batch_num_edges() tensor([3, 4])
Query for heterogeneous graphs.
>>> hg1 = dgl.heterograph({ ... ('user', 'plays', 'game') : (torch.tensor([0, 1]), torch.tensor([0, 0]))}) >>> hg2 = dgl.heterograph({ ... ('user', 'plays', 'game') : (torch.tensor([0, 0]), torch.tensor([1, 0]))}) >>> bg = dgl.batch([hg1, hg2]) >>> bg.batch_num_edges('plays') tensor([2, 2])