[fix] batch inference for llava_onevision
Author: cyr0930
Pull request: yes

# What does this PR do?
This PR recovers batch inference feature for llava_onevision and fixes some contents in documentation.
Before this commit, putting single-image examples and multi-image examples in the same batch did not work appropriately, as iterable is not consumed correctly.
And also make test case cover this issue.


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- [x] Did you write any new necessary tests?


## Who can review?
@zucchini-nlp 

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Comments:
run-slow: llava_onevision

This comment contains run-slow, running the specified jobs: 

models: ['models/llava_onevision']
quantizations: [] ...

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_40021). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

**[For maintainers]** Suggested jobs to run (before merge)

run-slow: llava_onevision

Thanks for the review.

One additional fix to handle text-only or video-only case!
As we allow nested list, passing empty list for text-only instance looks more natural, imo.


run-slow: llava_onevision

> One additional fix to handle text-only or video-only case!

Isn't that already handled, text-only definitely is supported for all models currently. Unless you mean mixed text-only+multimodal batch inputs

This comment contains run-slow, running the specified jobs: 

models: ['models/llava_onevision']
quantizations: [] ...

> > One additional fix to handle text-only or video-only case!
> 
> Isn't that already handled, text-only definitely is supported for all models currently. Unless you mean mixed text-only+multimodal batch inputs

Yes you are right. I mean mixed cases :)

Ah oke. We haven't been paying attention is mixed cases of multimodal and text-only inputs are supported for any of the models tbh, so I guess we need a general pass over models to see if it is supported