dgl.rand_graphο
- dgl.rand_graph(num_nodes, num_edges, idtype=torch.int64, device=device(type='cpu'))[source]ο
Generate a random graph of the given number of nodes/edges and return.
It uniformly chooses
num_edges
from all possible node pairs and form a graph. The random choice is without replacement, which means there will be no multi-edge in the resulting graph.To control the randomness, set the random seed via
dgl.seed()
.- Parameters:
num_nodes (int) β The number of nodes
num_edges (int) β The number of edges
idtype (int32, int64, optional) β The data type for storing the structure-related graph information such as node and edge IDs. It should be a framework-specific data type object (e.g., torch.int32). By default, DGL uses int64.
device (Device context, optional) β The device of the resulting graph. It should be a framework-specific device object (e.g., torch.device). By default, DGL stores the graph on CPU.
- Returns:
The generated random graph.
- Return type:
See also
Examples
>>> import dgl >>> dgl.rand_graph(100, 10) Graph(num_nodes=100, num_edges=10, ndata_schemes={} edata_schemes={})