GenerationConfig validate both constraints and force_words_ids

[FredericOdermatt]

What does this PR do?

There is currently two ways to pass constraints to constrained beam search, either constraints or force_words_ids. They get merged here which is after the GenerationConfig initialization. I was following the blog on constrained decoding (using force_words_ids and was checking for myself which other options constrained beam search can be combined with (Ex: can I sample and constrained beam search? [no])

This snippet raised a ValueError:

    generated_tokens = self.model.generate(
        **encoded_source,
        forced_bos_token_id=forced_bos_token_id,
        num_beams=5,
        num_return_sequences=1,
        constraints=constraints,
        do_sample=True
    )

while this snipped didn't:

    generated_tokens = self.model.generate(
        **encoded_source,
        forced_bos_token_id=forced_bos_token_id,
        num_beams=5,
        num_return_sequences=1,
        force_words_ids=force_words_ids,
        do_sample=True
    )

I've added the additional check to GenerationConfig.validate() to include force_words_ids and I've added two new tests:

        with self.assertRaises(ValueError):
            # dummy constraint
            GenerationConfig(do_sample=True, num_beams=2, constraints=["dummy"])
        with self.assertRaises(ValueError):
            GenerationConfig(do_sample=True, num_beams=2, force_words_ids=[[[1, 2, 3]]])

Without the change only the first test passes, with the change both tests pass as they now both raise ValueErrors (Expected behavior).

This is my first time opening a PR here, so let me know what I can improve. I've followed the docs on contribution for this PR, though after running all tests after installation there were 5 tests that failed before I changed anything.

Cheers! :)

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Who can review?

maybe @gante

[gante]

Thank you for noticing this issue and for fixing it 💛

[ArthurZucker]

Thanks!