added changes in deberta dropout
# What does this PR do?

This PR does the foillowing. 
1- Add a task dropout to deberta config, that is, cls_dropout. This is similar to what Bert and others have. This is justified since in Deberta paper adjusting task dropout is very important, therefore I think it shouldn't be just be set to the hidden_dropout_prob. While the latter should, in general, not be changed, cls_dropout should be tuned to obtain best results, as stated in: https://arxiv.org/abs/2006.03654
2. Armonize the use of Dropout. In general, Deberta uses Stable Dropout, which was also used in Classification. However, I don't understand why, on Token Classification normal Dropout was used. In some experiments I carried out, StableDropout worked better than normal dropout also for token classification, and it is the type of dropout that is used in all other Deberta layers, therefore I think it is better to have the same type of dropout in all task layers. 
I also changed a little bit how the dropout is created to remove redundant lines, but as you see there are only a few changes, they're not many lines of code, but for clarity and simplicity I decided to change that also; e.g (instead of first getting cls_dropout if existing and then if it is None take hidden_dropout_prob, I do it all in one line in getattr).

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- [ ] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
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@BigBird01 @LysandreJik @patrickvonplaten 
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_16647). All of your documentation changes will be reflected on that endpoint.<|||||>Hi,

Just as an FYI, changing `nn.Dropout` to `StableDropout` will stop the models supporting `saved_model` for TensorFlow when trying to save them on disk for TensorFlow serving. This is already an issue in `TFDebertaV2ForSequenceClassification` which both `nn.Dropout` and `StableDropout` were tested on 4 different datasets for multi-class classification and the results were pretty much the same between these two. (I already changed it to nn.Dropout so I can save them as saved_model, the performance in production is exactly the same as StableDropout at least for me)

reference: https://github.com/huggingface/transformers/issues/16484
<|||||>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.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.