Add new dim to `num_items_in_batch` if necessary
Author: regisss
Pull request: yes

# What does this PR do?

<!--
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 -->

https://github.com/huggingface/transformers/pull/36861 introduced an issue with multi-gpu runs. See [this comment](https://github.com/huggingface/transformers/pull/36861#issuecomment-2747698449) for a script that enables to reproduce it.

`num_items_in_batch` can be a scalar and, in that case, Torch DataParallel will raise an error as a scalar cannot be split in chunks. The fix consists in adding a dimension to the this tensor. Note that this is only needed for DataParallel as DistributedDataParallel was not affected by this issue.

Should fix https://github.com/huggingface/trl/issues/2338 and https://github.com/huggingface/transformers/issues/36492 too.


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request),
      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.

<!-- 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:

- text models: @ArthurZucker
- vision models: @amyeroberts, @qubvel
- speech models: @eustlb
- graph models: @clefourrier

Library:

- flax: @gante and @Rocketknight1
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Rocketknight1
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @SunMarc
- chat templates: @Rocketknight1

Integrations:

- deepspeed: HF Trainer/Accelerate: @muellerzr
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc @MekkCyber

Documentation: @stevhliu

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @Rocketknight1
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1

 -->


Comments:
Hi 👋, thank you for opening this pull request! The pull request is converted to draft by default. The CI will be paused while the PR is in draft mode. When it is ready for review, please click the `Ready for review` button (at the bottom of the PR page). This will assign reviewers.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_36967). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

cc @IlyasMoutawwakil who reviewed the previous PR!

@regisss did you test if this causes any issues when dividing the loss by `num_items_in_batch` ?
https://github.com/huggingface/transformers/blob/b56d8f07e4503b5abdae87926596876739145d80/src/transformers/loss/loss_utils.py#L29

Any updates on this PR?

@BenjaminBossan I pushed a change to apply the fix only in the case where Data Parallel is used (i.e. `n_gpu > 1`). DDP and no-parallelism cases are thus not impacted and didn't need any fix here anyway. Can you please test the branch again and let me know if it still works?

This fixes [#37151](https://github.com/huggingface/transformers/issues/37151).

> I pushed a change to apply the fix only in the case where Data Parallel is used (i.e. `n_gpu > 1`). DDP and no-parallelism cases are thus not impacted and didn't need any fix here anyway. Can you please test the branch again and let me know if it still works?

Thanks, the PR still solves the original issue for me :+1: