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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## master #472 +/- ##
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Coverage 74.31% 74.31%
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| training_objects, # type: ignore | ||
| recalculate_all_logprobs=(not is_on_policy_iter), | ||
| reduction="sum" if args.distributed or args.loss == "SubTB" else "mean", # type: ignore | ||
| reduction="sum" if args.loss == "SubTB" else "mean", # type: ignore |
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Sorry - what was the bug here? This can produce unintended behaviour as you scale up with DDP, but maybe it actually produces incorrect scaling for distributed async training. We should discuss on the call tomorrow.
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Cleanup, instead of manually dividing by per_node_batch_size which is prone to bug, just use mean