Fix slurm multinode example #3229
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Compute metric with evaluate from main process only, avoiding bug in multinode evaluate.
Enforce --multi_gpu on multiple nodes. Moreover, make sure that each rank gets correctly addressed based on the $SLURM_PROCID. $SLURM_NNODES has now been deprecated and replaced by $SLURM_JOB_NUM_NODES. Fixed typo in $CMD as well.
muellerzr
reviewed
Dec 2, 2024
Comment on lines
-249
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| eval_metric = metric.compute() | ||
| # Use accelerator.print to print only on the main process. | ||
| accelerator.print(f"epoch {epoch}:", eval_metric) | ||
| if accelerator.is_main_process: | ||
| # Computing metrics in a distributed manner requires calling evaluate.load() with the | ||
| # n_process and process_id arguments. However, the metric.add_batch() step will fail | ||
| # due to a bug with datasets and evaluate (see https://github.com/huggingface/evaluate/issues/542) | ||
| # and related | ||
| eval_metric = metric.compute() | ||
| # Use accelerator.print to print only on the main process. | ||
| accelerator.print(f"epoch {epoch}:", eval_metric) |
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This breaking is a first for me, let me try to repr this
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What does this PR do?
The SLURM multinode submit script doesn't work for multiple reasons (see also #1239 which is still open). This PR aims at solving some of those issues, namely:
$CMDcommand$SLURM_NNODESwas recently deprecated in favour of$SLURM_JOB_NUM_NODES--multi-gpuand the rank of each process has to be set with--machine-rankcomplete_nlp_exampledoesn't handle distributed evaluation correctly. In particular, either the evaluate GLUE mrpc metric has to be loaded with the--num_processand--process_idflags (which will subsequently fail due to several breakages due to recentdatasetsevaluate#542 & related) or metric computation has to happen only on the main process. This PR goes for the second.Fixes #3206
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Who can review?
@muellerzr or @SunMarc