DeBERTa/DeBERTa-v2/SEW Support for torch 1.11
The internal `torch` method `_softmax_backward_data` changed API between 1.10 and 1.11, from requiring a tensor as its last output to requiring a size.

This PR updates the concerned models so that they are correctly supported.

Torch 1.11: https://github.com/pytorch/pytorch/blame/e47a5a64bbf4d388b70397e3237f9d5710ee4c9c/tools/autograd/derivatives.yaml#L1861
Before: https://github.com/pytorch/pytorch/blame/768cfaa8f86bf7c7b0af441d1536f060274c27a0/tools/autograd/derivatives.yaml#L1704
_The documentation is not available anymore as the PR was closed or merged._<|||||>Addressed your comment @sgugger, could you do a second review? 

As seen with Sylvain offline, I've moved out the `packaging.version.parse` operation of the methods, as otherwise they would be called inside the methods themselves, which are called multipled times in forward passes. @patrickvonplaten could you check if that's fine with you?<|||||>@sgugger  @LysandreJik  Thanks for your awesome work on building this immensely valuable ecosystem (and community!). 
I'm waiting to release a package that requires this post-4.17 commit and it would be great to avoid pointing to a specific commit for packaging purposes. Is a 4.17.1 patch release planned? I asked on Discord but this was indicated to be a better forum for the question. Thanks again for helping lead this great community!<|||||>I don't think we have a patch planned. We will have 4.18 released probably next week instead :-) <|||||>> I don't think we have a patch planned. We will have 4.18 released probably next week instead :-)

AWESOME! looking forward to it!<|||||>Note that this evaluates True for pre-releases such as '1.11.0a0+b6df043'. So the the error is still present.
`is_torch_less_than_1_11 = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")` may help.
Am I missing something?
