Support parallel for operations, like data parallel training, model parallel training etc #3102
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What changes were proposed in this pull request?
Support ParallelFor pipeline features for each operation. Set
parallel_count > 2
to start parallel operations like distributed training, distributed data processing etc. Below are features/limitations:TF_CONFIG
for Tensorflow andMASTER_ADDR
,MASTER_PORT
for 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.py
to ensure argumentparallel_count
is working.TODO: