class dgl.dataloading.DistEdgeDataLoader(g, eids, graph_sampler, device=None, **kwargs)[source]

Sampled graph data loader over edges for distributed graph storage.

It wraps an iterable over a set of edges, generating the list of message flow graphs (MFGs) as computation dependency of the said minibatch for edge classification, edge regression, and link prediction, on a distributed graph.

All the arguments have the same meaning as the single-machine counterpart dgl.dataloading.EdgeDataLoader except the first argument g which must be a dgl.distributed.DistGraph.

__init__(g, eids, graph_sampler, device=None, **kwargs)[source]

Initialize self. See help(type(self)) for accurate signature.


__init__(g, eids, graph_sampler[, device])

Initialize self.