Clip floating point constants to bf16 range to avoid inf conversion
Author: sangeethabal
Pull request: yes

When running HuggingFace BERT (any size) fine-tuning tutorial with transformers version >= 4.21.0 and using XLA_USE_BF16=1 or XLA_DOWNCAST_BF16=1, I see NaNs in the loss after the first step. 

# What does this PR do?

This PR addresses the issue where the model code passes a value that is out of range for XLA_USE_BF16=1 or XLA_DOWNCAST_BF16=1, so the conversion would cast it to -inf.

The NaNs likely come from the transformers library change: https://github.com/huggingface/transformers/pull/17306 . This PR replaced many lines which used to be -float(inf) (or other small constants) with torch.finfo().min. For torch.float32 the min value is -3.4028234663852886e+38 which is smaller than the bfloat16 minimum of -3.3895313892515355e+38. So the problem is that torch.finfo(torch.float32).min = -3.4028234663852886e+38 gets converted to -inf. When the original encoder_extended_attention_mask is 1, then encoder_extended_attention_mask becomes (1.0 - 1.0 ) * -inf which becomes NaN (via IEEE rule Inf * 0.0 = NaN).

This PR ensures torch.finfo(torch.bfloat16).min = -3.3895313892515355e+38 and not -inf. Then the results would not have Nans.

The following lines checks for XLA_USE_BF16 or XLA_DOWNCAST_BF16 environment variable and sets the dtype accordingly:
```
if is_torch_tpu_available():
   if os.environ.get("XLA_USE_BF16"):
       return torch.bfloat16
   if os.environ.get("XLA_DOWNCAST_BF16"):
       if t.dtype == torch.float:
            return torch.bfloat16
       if t.dtype == torch.double:
            return torch.float32
```
<!--
Congratulations! You've made it this far! You're not quite done yet though.

Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.

Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change.

Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost.
-->

<!-- Remove if not applicable -->



## 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](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? 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](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

@sgugger
<!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @

 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @LysandreJik

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @n1t0, @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

 -->


Comments:
_The documentation is not available anymore as the PR was closed or merged._

Oh, looks like something went wrong in your rebase (see the diff showing lots of files). You can either force-push a commit (with --force) to repare the history for git, or close this PR and open a fresh one.