add opt "flush_denormal" in training_args.
To solve the low performance issue caused by denormal numbers, user could enable this opt

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

# What does this PR do?
[Denormal number](https://en.wikipedia.org/wiki/Denormal_number) is used to store extremely small numbers which are close to 0. Computations with denormal numbers are remarkably slower than normalized number. To solve the low performance issue caused by denormal numbers, users can use the following opt "flush_denormal"

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## Who can review?
@sgugger, please help review it

@yao-matrix @sgugger please help review<|||||>The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_18574). All of your documentation changes will be reflected on that endpoint.<|||||>Thanks for your PR but I don't completely understand why this should leave in the Trainer? Users can just add `torch.set_flush_denormal(True)` to their script.<|||||>Hi, I think not all the data scientists are familiar with the option, if we add it to the training arg. at least they could see it from --help  and get the point. @sgugger

> Thanks for your PR but I don't completely understand why this should leave in the Trainer? Users can just add `torch.set_flush_denormal(True)` to their script.

<|||||>Maybe it could be documented somewhere in this case, but I doubt adding yet another training argument is going to make it any more visible. There are currently 90 of them.<|||||>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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