Fixes for multi-node execution with torchrun + LocalExecutor in Slurm environment #251
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- do prepare stage only from single process or rank - for --node-rank, also look for SLURM_NODEID Signed-off-by: Pramod Kumbhar <prkumbhar@nvidia.com>
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…NeMo#251) - do prepare stage only from single process or rank - for --node-rank, also look for SLURM_NODEID Signed-off-by: Pramod Kumbhar <prkumbhar@nvidia.com> Signed-off-by: Zoey Zhang <zozhang@nvidia.com>
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Summary
--node-rankargument totorchrun, look forSLURM_NODEIDas wellIssues Addressed
Multi-node execution with torchrun+LocalExecutor was mentioned in #130 but I don't think this feature has been tested thoroughly. This PR fixes two issues that I saw while testing multi-node execution with torchrun + localexecutor:
1. args to torchrun are not expanded properly
In this case,
$${node_rank_var}is not expanded properly.2. prepare stage is not "protected" for execution from multiple ranks / processes
We typically run multi-node execution job as:
srun -N ${SLURM_NNODES} --ntasks-per-node=1 -n ${SLURM_NNODES} python train.pyAs multiple processes are executing from the beginning, we see errors like:
Testing
An example with torchrun+localexecutor:
Job script:
Additional Notes
Note that further improvements might be needed (as a separate PR) such as logging from only from single rank because currently we see some logging messages from all ranks:
But with this PR, I wanted to at least get a working example.