dmlc--dgl
xiang song(charlie.song)
508197e807
* fix. * fix. * fix. * fix. * Fix test * Deprecate old DistEmbedding impl, use synchronized embedding impl * Basic imple of heterogeneous on homogenenous sampling * make pass * Pass C++ test * Add python test code * lint * lint * Add MultiLayerEtypeNeighborSampler * Add unitest for single machine dataloader * Add dist dataloader test for edge type sampler * Fix lint * fix * support for per etype sample * Fix some bug and enable distributed training with per edge sample * fix * Now distributed training works * turn off some mxnet * turn off mxnet for some dist test * fix * upd * upd according to the comments * Fix * Fix test and now distributed works. * upd * upd * Fix * Fix bug * remove dead code. * upd * Fix * upd * Fix Co-authored-by: Ubuntu <ubuntu@ip-172-31-71-112.ec2.internal> Co-authored-by: Ubuntu <ubuntu@ip-172-31-2-66.ec2.internal> Co-authored-by: Da Zheng <zhengda1936@gmail.com>
32 行
1.0 KiB
Python
32 行
1.0 KiB
Python
"""DGL distributed module contains classes and functions to support
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distributed graph neural network training and inference in a cluster of
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machines.
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This includes a few submodules:
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* distributed data structures including distributed graph, distributed tensor
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and distributed embeddings.
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* distributed sampling.
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* distributed workload split at runtime.
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* graph partition.
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"""
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import os
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import sys
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from .dist_graph import DistGraphServer, DistGraph, node_split, edge_split
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from .dist_tensor import DistTensor
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from .partition import partition_graph, load_partition, load_partition_book
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from .graph_partition_book import GraphPartitionBook, PartitionPolicy
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from .nn import *
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from . import optim
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from .rpc import *
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from .rpc_server import start_server
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from .rpc_client import connect_to_server
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from .dist_context import initialize, exit_client
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from .kvstore import KVServer, KVClient
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from .server_state import ServerState
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from .dist_dataloader import DistDataLoader
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from .graph_services import sample_neighbors, sample_etype_neighbors, in_subgraph
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