Support parallel for operations, like data parallel training, model parallel training etc #3102
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akchinSTC
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Signed-off-by: typhoonzero <[email protected]>
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typhoonzero
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@akchinSTC Can you please checkout this feature |
What is the current status of this PR? I still see the |
This PR is ready for review now. Work under the TODO list will move on after this feature is merged. |
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What changes were proposed in this pull request?
Support ParallelFor pipeline features for each operation. Set
parallel_count > 2to start parallel operations like distributed training, distributed data processing etc. Below are features/limitations:TF_CONFIGfor Tensorflow andMASTER_ADDR,MASTER_PORTfor Pytorch. Yet in some cases, workers rank >=1 should wait for rank0 to start. This can be achieved by waiting rank0's TCP server port by user.How was this pull request tested?
Unit tests are included in
test_bootstrapper.pyto ensure argumentparallel_countis working.TODO: