Store a feature tensor for graph representation?

Questions
#1

Assume I have g = dgl.DGLGraph() with
DGLGraph(num_nodes=11795, num_edges=15000, ndata_schemes={'id': Scheme(shape=(), dtype=torch.int64)} edata_schemes={'id': Scheme(shape=(), dtype=torch.int64), 'type': Scheme(shape=(), dtype=torch.int64)}),
how can I set a graph feature of size (200, 500) for g instead of allocating memory for each node or edge in g.ndata or g.edata?
Note that the graph feature will vary as the nodes and edges update.

#2

If your reason for storing graph features is due the variable nature of node and edge updates, perhaps you could consider Heterograph.

#3

Hi,

Why you want to store it in the graph? It’s not supported and You can just put the tensor aside and use it wherever you want.