deprecate `sharded_ddp` training argument
Author: ji-huazhong
Pull request: yes

# What does this PR do?

This PR deprecates the `sharded_ddp` training arguments, since ShardedDDP has been [upstreamded to PyTorch](https://pytorch.org/blog/introducing-pytorch-fully-sharded-data-parallel-api/), so users can use the `fsdp` traning parameter instead.

---

~~According to fairscale([see](https://github.com/facebookresearch/fairscale)), PyTorch FSDP is the recommended method for scaling to large NN models. I think Sharded-DDP is dead and it's time to say goodbye to this library.~~

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Comments:
> That makes sense thanks! Note that while removing it entirely from the doc is fine, we can't abruptly remove it from the library like this. We will need to properly deprecate it first and in two-tree minor versions we can fully remove it.

@sgugger Thanks for pointing this out. I have rolled back the code changes and added a warning that `sharded_ddp` will be deprecated. Could you take a second look at this PR?


The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_24825). All of your documentation changes will be reflected on that endpoint.