[model] support minimax_m3#121
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| if not to_mcore: | ||
| is_moe = torch.tensor([is_moe], dtype=torch.bool, device='cuda') | ||
| if self.pp_size > 1: | ||
| dist.all_reduce(is_moe, group=self.pp_group) |
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Using dist.all_reduce directly on a boolean tensor with the default SUM reduction operator will crash when pp_size > 1 because NCCL does not support SUM on boolean tensors. Additionally, evaluating a CUDA tensor directly in an if statement forces an implicit device-to-host synchronization, which can hurt performance. We should use the existing helper method self._reduce_tensor_pp_group(is_moe, to_mcore) which correctly uses ReduceOp.MAX and returns a standard Python boolean.
is_moe = self._reduce_tensor_pp_group(is_moe, to_mcore)
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