.. currentmodule:: dgl.distributed
DGL distributed module contains classes and functions to support distributed Graph Neural Network training and inference on a cluster of machines.
This includes a few submodules:
- distributed data structures including distributed graph, distributed tensor and distributed embeddings.
- distributed sampling.
- distributed workload split at runtime.
- graph partition.
.. autosummary:: :toctree: ../../generated/ initialize
.. autoclass:: DistGraph :members: ndata, edata, idtype, device, ntypes, etypes, number_of_nodes, number_of_edges, node_attr_schemes, edge_attr_schemes, rank, find_edges, get_partition_book, barrier, local_partition, num_nodes, num_edges, get_node_partition_policy, get_edge_partition_policy, get_etype_id, get_ntype_id, nodes, edges, out_degrees, in_degrees
.. autoclass:: DistTensor :members: part_policy, shape, dtype, name
.. autoclass:: DistEmbedding
.. autoclass:: dgl.distributed.optim.SparseAdagrad :members: step, save, load
.. autoclass:: dgl.distributed.optim.SparseAdam :members: step, save, load
.. autosummary:: :toctree: ../../generated/ node_split edge_split
.. autoclass:: DistDataLoader
.. autosummary:: :toctree: ../../generated/ sample_neighbors sample_etype_neighbors find_edges in_subgraph
.. autoclass:: GraphPartitionBook :members: shared_memory, num_partitions, metadata, nid2partid, eid2partid, partid2nids, partid2eids, nid2localnid, eid2localeid, partid, map_to_per_ntype, map_to_per_etype, map_to_homo_nid, map_to_homo_eid, canonical_etypes
.. autoclass:: PartitionPolicy :members: policy_str, part_id, partition_book, to_local, to_partid, get_part_size, get_size
.. autosummary:: :toctree: ../../generated/ load_partition load_partition_feats load_partition_book partition_graph dgl_partition_to_graphbolt