[hiyouga]

What does this PR do?

This PR follows #35558 #40263

Consider a batch of image lists, where the first example has 1 image and the second example has 0 image. e.g.,

images = [
  [Image],
  []
]

Using the latest code, it will receive a value error Invalid input type. Must be a single image, a list of images, or a list of batches of images..

In this PR, we use any instead of all to judge if it is a valid nested list of images. Note that this behavior is the same as the one in transformers 4.48.0.

https://github.com/huggingface/transformers/blob/v4.48.0/src/transformers/models/mllama/image_processing_mllama.py#L535-L541

transformers/src/transformers/models/mllama/image_processing_mllama.py

Lines 535 to 541 in 6bc0fbc

	# If it's a list of batches, it's already in the right format
	elif (
	isinstance(images, (list, tuple))
	and all(isinstance(images_i, (list, tuple)) for images_i in images)
	and any(is_valid_list_of_images(images_i) for images_i in images)
	):
	output_images = images

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,
  Pull Request section?
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  to it if that's the case.
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  documentation guidelines, and
  here are tips on formatting docstrings.
• Did you write any new necessary tests?

Who can review?

@zucchini-nlp

[github-actions]

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[zucchini-nlp]

Question before reviewing: why we pass an empty list for no-image prompt? What if we just do images = [ [Image]] instead of images = [ [Image], [] ] ?

[hiyouga]

@zucchini-nlp Assuming the batch size is 2, we expect that the length of image lists should be the same is the batch size

[zucchini-nlp]

I see, makes sense. Also cc @yonigozlan since you added these functions, do you see any edge cases if we check any?

Otherwise LGTM

[yonigozlan]

Hi @hiyouga ! Thanks for flagging this issue. I agree we should support inputs such as [[image1], []] Right now it seems to be causing some issues with SmolVLM processor, but this is more of a problem with SmolVLM than with this PR.

The issue I see is that we wouldn't catch an error now if we have [[image1], image2] for example, when we should. But we cannot catch every possible wrong input formats, so this might not be too bad. WDYT @zucchini-nlp ?

[zucchini-nlp]

@yonigozlan agreed, I think we can expect users to use consistent format within one input.

@hiyouga there's a failing test which is caused by this PR i think, can you take a look?

[hiyouga]

Hi @zucchini-nlp , I have made necessary changes to Gemma3ImageProcessor, Idefics2ImageProcessor, Idefics3ImageProcessor and SmolVLMImageProcessor, to make them support inputs like [[image], []] and [[], [image]]

[zucchini-nlp]

didn't get why this doesn't throw error anymore, IMO passing flat images is ambiguous, and we throw errors instead of trying to infer which text corresponds to which image

[zucchini-nlp]

@hiyouga great, thanks for handling the tests!

I see why we need to flatten images with the new changes, but i don't like calling it every time when one image is needed. I'd suggest to save one image in a variable at the beginning and add a small comment we we do that, so future us don't delete it :)

[qubvel]

Waiting for the CI to be green to merge 😄

[hiyouga]

@qubvel It seems that the integration of llama4 breaks all the processor unit tests https://github.com/huggingface/transformers/commits/main/

[ArthurZucker]

Can you documment what this enables? Like in the pipeline md?

[hiyouga]

@ArthurZucker This PR mainly enables the ImageTextToTextPipeline to have both image-text and text-only inputs in a whole batch. However, I'm not sure where I should add the document. Could you provide some instructions?

[ArthurZucker]

sorry you are right its kind of obvious that it should support batch > 1 image, what I mean is to have a small doc example somewhere for people to play with it! Let's fix the conflicts and get this merged 🔥

[zucchini-nlp]

@hiyouga I am taking over this PR, due to a demand from TRL team to support the feature. Would be great to merge it soon

[zucchini-nlp]

@ArthurZucker let's merge this to fix VLM training in TRL

If anyone wants to have another look, I added a test case, fixed a few new models and changed all occurrences of make_list_of_images with make_flat_list_of_images. The first one should be deleted with a small deprecation as it is not used anywhere, the two have same functionality

I will merge end of week if no-one has comments

[HuggingFaceDocBuilderDev]

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

[github-actions]

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

run-slow: beit, bit, chinese_clip, conditional_detr, convnext, deformable_detr, deit, depth_pro, detr, donut, dpt, efficientnet, emu3, eomt, flava, fuyu