Include `timeout` attribute (related to DDP) to TrainingArguments
### Feature request

Would it be possible to include a `timeout` attribute to the `TrainingArguments` dataclass, such as it will be used as an argument of the `torch.distributed.init_process_group` calls?

Reference: https://pytorch.org/docs/stable/distributed.html#torch.distributed.init_process_group

### Motivation

Essentially, if a process uses DDP and performs a set of operations prior to using the GPUs, such as tokenization/mapping, for more than `timeout` seconds (defaults to 30 minutes), the process will stop and get killed due to a `Socket Timeout`. (issue #17106).

By adding a `timeout` argument to the `TrainingArguments` class, we will be able to let users decide in overriding the default timeout defined by PyTorch and hopefully introduce a way to prevent `Socket Timeouts` when mapping large datasets.

### Your contribution

I could definitely submit a PR, seems to be pretty straightforward to add a new attribute to the `TrainingArguments` class.
Hi @gugarosa 

I have started the work on it. Will create PR for the same by tomorrow.<|||||>That's amazing @dvlshah! Thank you so much for doing it!<|||||>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.

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