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@BestJuly BestJuly commented Nov 3, 2025

What does this PR do ?

In previous implementation, reduce across DP is added for the correct aux_loss logging. However, current reduction will cause redundant communication

  • For seq_load_balancing_loss and load_balancing_loss, self.tp_cp_group is used (code, code)
  • For global_load_balancing_loss, self.tp_dp_cp_group is used (code).

Therefore, related reduction has already been conducted across corresponding parallel group. And we can remove the duplicated one for better perf.

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@BestJuly BestJuly requested review from a team as code owners November 3, 2025 08:02
@ko3n1g ko3n1g added this to the Core 0.16 milestone Nov 3, 2025
@BestJuly BestJuly requested a review from fanshiqing November 3, 2025 08:04
@BestJuly BestJuly self-assigned this Nov 3, 2025
@yanring yanring requested a review from Victarry November 3, 2025 08:11
torch.distributed.all_reduce(values, group=tracker[name].get('reduce_group'))
# Need to conduct reduction across data parallel ranks. When the reduce_group
# does not have 'dp' attribute, do it manually.
if not hasattr(tracker[name]["reduce_group"], 'dp'):
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IIUC, tracker[name]["reduce_group"] should be a ProcessGroup object. How can we get the dp attribute?

@Victarry Victarry disabled auto-merge November 19, 2025 13:06
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5 participants