Add FP32 cast in ConvNext LayerNorm to prevent rounding errors with FP16 input
Author: jimypbr
Pull request: yes

# What does this PR do?

The `ConvNextLayerNorm` isn't stable if the inputs are in FP16: https://github.com/huggingface/transformers/blob/main/src/transformers/models/convnext/modeling_convnext.py#L111
 
If the inputs are FP16 then the whole calculation will be done in FP16:
```
            u = x.mean(1, keepdim=True)
            s = (x - u).pow(2).mean(1, keepdim=True)
            x = (x - u) / torch.sqrt(s + self.eps)
```
The mean of squares will suffer rounding errors. This PR just as a cast to `float` before the calculation and a cast back to input type afterwards, following the precendent in other models that have their own layernorms, e.g. https://github.com/huggingface/transformers/blob/main/src/transformers/models/deberta/modeling_deberta.py#L263


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Comments:
_The documentation is not available anymore as the PR was closed or merged._

Pingng @ydshieh here as there seems to be a CI issue

@jimypbr 

Could you follow the instruction here to refresh the CircleCI permission?

https://support.circleci.com/hc/en-us/articles/360048210711-How-to-Refresh-User-Permissions-