[Trainer] Add optional communication backends for torch.distributed when using GPU

[heya5]

What does this PR do?

Add optional backends for torch.distributed when using GPU. I want to use other communication backends according the pytorch_distribution_tutorial, but I found Trainer only uses nccl when self.no_cuda is False . Fixes # (issue)

Before submitting

• [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
• [x] Did you read the contributor guideline, Pull Request section?
• [ ] Was this discussed/approved via a Github issue or the forum? Please add a link to it if that's the case.
• [ ] Did you make sure to update the documentation with your changes? Here are the documentation guidelines, and here are tips on formatting docstrings.
• [ ] Did you write any new necessary tests?

Who can review?

• trainer: @sgugger

[HuggingFaceDocBuilderDev]

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