Can not using LION optimizer
### Feature request

Error:

```
RuntimeError: Expected to mark a variable ready only once. This error is caused by one of the following reasons: 1) Use of a module parameter outside the `forward` function. Please make sure model parameters are not shared across 
multiple concurrent forward-backward passes. or try to use _set_static_graph() as a workaround if this module graph does not change during training loop.2) Reused parameters in multiple reentrant backward passes. For example, if 
you use multiple `checkpoint` functions to wrap the same part of your model, it would result in the same set of parameters been used by different reentrant backward passes multiple times, and hence marking a variable ready 
multiple times. DDP does not support such use cases in default. You can try to use _set_static_graph() as a workaround if your module graph does not change over iterations.
Parameter at index 129 has been marked as ready twice. This means that multiple autograd engine  hooks have fired for this particular parameter during this iteration. You can set the environment variable TORCH_DISTRIBUTED_DEBUG to
either INFO or DETAIL to print parameter names for further debugging.
  0%|    
```

Does there any example code of using LION optimzier?

I using code from here https://github.com/lucidrains/lion-pytorch/blob/main/lion_pytorch/lion_pytorch.py but got error above.

### Motivation

LION need to be support since it converges more faster.

### Your contribution

no
We can't do anything to help without knowing the code that triggered the error.<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

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