Fix failing XCLIPModelIntegrationTest

[Sai-Suraj-27]

What does this PR do?

Fixes failing XCLIPModelIntegrationTests.

self.get_attributes() will not return all the processor instance attributes, for example in case of x_clip because video_processor is added like this.

processor = XCLIPProcessor.from_pretrained(
    "microsoft/xclip-base-patch32", size=180, crop_size={"height": 180, "width": 180}
)
processor.get_attributes()
# ['image_processor', 'tokenizer']

Iterating directly over the attribute_to_kwargs in __call__ will check for all types at run-time.

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Who can review?

@Rocketknight1 @vasqu @zucchini-nlp

[Rocketknight1]

Hmm, this feels like a very core change for one model. cc @zucchini-nlp maybe?

[Sai-Suraj-27]

Hmm, this feels like a very core change for one model. cc @zucchini-nlp maybe?

Okayy, even now when looping through self.get_attributes() we are again making sure that it exists in attribute_to_kwargs, so directly looping through attribute_to_kwargs will not cause any new issues, hopefully. Else, I think having a custom __call__ for xclip would work too.

Also, found tvp processor to be similar.

[Sai-Suraj-27]

Tiny nudge @zucchini-nlp. If this still makes sense.

[zucchini-nlp]

i think we need to fix it in XCLIP processor since it is quite special, i.e. override the __call__ method like in some other processors (e.g. llava but ofc llava is more involved)

[zucchini-nlp]

the base __call__ is intended to delete repetitive code for common cases, and XCLIP is not very common. I don't want us to bloat the call here trying to catch every edge case

[Sai-Suraj-27]

Thanks for the review @zucchini-nlp. I will close this in favour of more recent: #45394. Sorry, couldn't follow up on this PR earlier, got caught up at work.