Fix error for PT backend when pytorch.distributed is not available #3652
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| @@ -924,7 +944,11 @@ | |||
| # Handle the case if rank 0 aborted and re-assigned | |||
| self.latest_model = Path(self.save_ckpt + f"-{_step_id + 1}.pt") | |||
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| module = self.wrapper.module if dist.is_initialized() else self.wrapper | |||
| module = ( | |||
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Additional details and impacted files@@ Coverage Diff @@
## devel #3652 +/- ##
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+ Coverage 81.72% 81.80% +0.07%
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Files 503 503
Lines 46007 46456 +449
Branches 2891 2952 +61
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+ Hits 37601 38004 +403
- Misses 7528 7559 +31
- Partials 878 893 +15 ☔ View full report in Codecov by Sentry. |
CaRoLZhangxy
approved these changes
Apr 8, 2024
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By default,
pytorch.distributedis not enabled on macOS by default (seepytorch.distributed.is_available()).In this case,
pytorch.distributed.is_initialized()will fail. To fix this issue,pytorch.distributed.is_available()needs to be tested first.This pull request allows passing the unittests while
distributedis disabled.USE_DISTRIBUTED=1to manually enable distributed training / dataloading on macOS. Set it to0to disable it on other platforms. Maybe this behavior needs to be documented somewhere?