add FlashAttentionKwargs and seq_idx to flat collator
Author: garrett361
Pull request: yes

# What does this PR do?

Adds additional, optional return values in `DataCollatorWithFlattening` as needed for padding-free training with particular models.

Relates to #35861 and #35941.

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Comments:
Hi 👋, thank you for opening this pull request! The pull request is converted to draft by default. When it is ready for review, please click the `Ready for review` button (at the bottom of the PR page).

I'd like to take a look as well when you think you're ready, so gladly ping then :)

cc @ArthurZucker 

@vasqu could you please take a look when you have time? Thank you.

> I think it would be nice to have equivalent collator tests on torch at least

I found it a little surprising that it's all `numpy`, as far as I saw.

Would you be willing to add the other paths or at least pt? Seems like an oversight on the initial PR 👀 

> Would you be willing to add the other paths or at least pt? Seems like an oversight on the initial PR

Yep, and I just discovered that the `"pt"` path is broken because `int` entries like those in `cu_seq_lens_{q,k}` turn into `torch.int64`'s whereas FA2 needs them to be `torch.int32`s 😭 

So, this is all going to take some reworking. I'll ping again later.

Alright, made a few changes:
* No batch dimension is expected on any of the `FlashAttentionKwargs`, and all these variables and `seq_idx` must be `int32` rather than the default `int64`. I removed the reliance on the default data collators to achieve this.
* I added a `ModelTesterMixin::test_flash_attention_2_padding_matches_padding_free_with_position_ids_from_flat_collator` which both has an awfully long name and is probably an unnecessarily expensive addition to the test suite.
* Added `tf` and `pt` tests for the flat collator.

Do you have any advice on the test @vasqu ? I wanted a non-trivial test that the collator outputs are in the right format (which is easy to get wrong), but the above seems like overkill.

**EDIT**: I only verified that the `LlamaModelTest::test_flash_attention_2_padding_matches_padding_free_with_position_ids_from_flat_collator` version of the test passes, I should probably say.

Looks like you'll need to run `make style` for the ci to be happy. I think the PR is overall ready tho.

@ArthurZucker please let me know if I can answer any further questions

@vasqu any advice here?

@garrett361 sorry don't have anything to add. Arthur is quite busy so notifications can easily get lost at times, I'm gonna cc again.

cc core maintainer review @ArthurZucker @Cyrilvallez 

> Thanks for your PR, sorry that it got lost

No worries, I know you're super busy. Will make these changes and ping.

The failing test is due to infra issues:
```
Couldn't find 'hf-internal-testing/librispeech_asr_dummy'
```

Believe I made all the requested changes. CC @ArthurZucker @Cyrilvallez 

Ah, yeah, if that's causing compile problems then let me fix it.

Alright @vasqu `max_len_{q,k}` are returned as simple py ints now.  Tests updated correspondingly.

CC @ArthurZucker @Cyrilvallez 

Hi @Cyrilvallez and @ArthurZucker , a reminder about this one, please.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_36456). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

Thanks @Cyrilvallez !