[doc] use ddp to calculate loss of dev set #23
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whiteshirt0429
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wenet/utils/executor.py
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| num_seen_utts = torch.Tensor([num_seen_utts]).to(loss.get_device()) | ||
| # the default operator in all_reduce function is sum. | ||
| average_params(num_seen_utts) |
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directly calling torch.distributed.all_reduce here is better.
There is no need to wrap it into a new function. And the function name avarage_params is ambiguous.
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And do this calling affect no DDP training?
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