error

[songbohui]

你好，请问您在代码调试过程中有没有遇到过同样的错误。
RuntimeError: Expected to have finished reduction in the prior iteration before starting a new one. This error indicates that your module has parameters that were not used in producing loss. You can enable unused parameter detection by passing the keyword argument find_unused_parameters=True to torch.nn.parallel.DistributedDataParallel, and by
making sure all forward function outputs participate in calculating loss.
If you already have done the above, then the distributed data parallel module wasn't able to locate the output tensors in the return value of your module's forward function. Please include the loss function and the structure of the return value of forward of your module when reporting this issue (e.g. list, dict, iterable).
Parameter indices which did not receive grad for rank 0: 1
In addition, you can set the environment variable TORCH_DISTRIBUTED_DEBUG to either INFO or DETAIL to print out information about which particular parameters did not receive gradient on this rank as part of this error

[buxiangzhiren]

你是不是加了什么层，然后没有把这个层设置为不可训练的了，或者这个层没有用到。

[songbohui]

你是不是加了什么层，然后没有把这个层设置为不可训练的了，或者这个层没有用到。

我没有更改代码的任何地方，只是将环境更改为torch1.9.0+cu11.1，我尝试在初始化过程中设置参数find_unused_parameters=True，不知道对模型的性能影响有多大，请问您当时所用到的torch和cuda版本是多少?

[buxiangzhiren]

这里应该是有啥参数被设置为可训练的了，但是没用上，你可以先设置成true看一下吧

[buxiangzhiren]

这里应该是有啥参数被设置为可训练的了，但是没用上，你可以先设置成true看一下吧

性能应该不会变

[songbohui]

这里应该是有啥参数被设置为可训练的了，但是没用上，你可以先设置成true看一下吧

性能应该不会变

确实没变化，感谢您的回答！