Raise warning when trying to cache examples but not all inputs have examples

[freddyaboulton]

Description

Fixes #2239

I originally intended to raise an exception if the length of input_with_examples did not match the length of the non_none_examples but that would prevent a user from deliberately providing partial examples and then just adding defaults to their prediction function.

I'm raising a warning instead. It's not a change in behavior so it's low risk of breaking someone's current workflow. If users get an exception when they try to cache an incomplete example, the warning message will hopefully point them in the right direction.

Checklist:

• I have performed a self-review of my own code
• My code follows the style guidelines of this project
• I have commented my code in hard-to-understand areas
• I have made corresponding changes to the documentation
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes

[github-actions]

All the demos for this PR have been deployed at https://huggingface.co/spaces/gradio-pr-deploys/pr-2279-all-demos

[abidlabs]

Suggested change

	"sure all of your inputs have example values for all of your examples."
	"sure all of your inputs have example values for all of your examples or you provide default values for those particular parameters in your function."

[abidlabs]

Will probably need to be re-formatted.

[abidlabs]

Extraneous?

[abidlabs]

What about an example like this:

def many_missing(a, b, c):
    return a * b

gr.Interface(
    many_missing,
    inputs=["text", "number", "number"],
    outputs=["text"],
    examples=[["foo", None, None], ["bar", None, None]],
    cache_examples=True,
)`

Because the 2nd and 3rd parameters are missing from all examples, it won't raise the warning. But I believe it should right?

Otherwise, LGTM

[abidlabs]

very nit

Suggested change

	a * b
	return a * b