Fix for https://github.com/instructlab/training/issues/254 #273
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Signed-off-by: ashna000 <[email protected]>
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@RobotSail Can you please review this ? |
Signed-off-by: ashna000 <[email protected]>
RobotSail
reviewed
Oct 16, 2024
| @@ -76,7 +76,7 @@ def get_effective_samples_per_minibatch(num_tokens_per_gpu): | |||
| padding=True, | |||
| ) | |||
| batches = sampler.generate_batches() | |||
| return len(dataset) / len(batches) | |||
| return len(dataset) / len(batches) if len(batches) > 0 else None | |||
There was a problem hiding this comment.
If we're hitting a scenario where Multipack generated no batches, then we need to either error out and have the calling function handle it (by falling back to DistributedDataSampler, or simply by preventing us from using multipack in the first place.
My recommendation here is to do this:
- Raise an appropriate exception here (either
RuntimeErrororDivisionByZeroError) - Have the calling function check for this additional exception and fall back to the naive sampler
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Thanks for this PR @ashna000, this will be a really important fix ! I've left a comment on how we should handle this problem. |
nathan-weinberg
requested changes
Oct 16, 2024
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@ashna000 these still need to be squashed |
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Added checks for resolving the issue reported in #254