[Flakes342]

What does this PR do?

Fixes #41060

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@gante

Problem

Qwen3 generate() was non-deterministic even with do_sample=False due to merged model defaults
(top_k, top_p, temperature) overriding the requested greedy decoding (do_sample = False and num_beams = 1 as per the documentation).

Reproduction

Even though Greedy Decoding is supposed to be deterministic because it doesn’t sample from the probability distribution but instead always takes the argmax, given the same model, same input, and same context, it will always produce the exact same output sequence. But in our case we can see different outputs for same input with greedy decoding flags enabled.

Solution

Enforce temperature=1.0, top_k=0, top_p=1.0 whenever do_sample=False and num_beams = 1 in _prepare_generation_config in generation/utils.py

Tests

Added a simple regression test to ensure future releases maintain deterministic behavior by passing the same input twice to Qwen3-0.6B model.

Additional Notes

Please feel free to let me know if there are any mistakes or oversight and I'd be happy to fix it and resubmit this PR. Thank you!

[github-actions]

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

run-slow: qwen3

[gante]

Thank you for opening the PR @Flakes342 🤗

However, this is not the correct fix for this (very complex) problem. For more details and a temporary fix, have a look at this comment :)

[ArthurZucker]

Thanks for the PR, and sorry it didn't make it in! This branch is based on v4, and v5 is very different, so rather than rebasing we'd love to invite you to open a new PR against main using our latest tools and good practices:

• Transformers tenets
• mlinter and the modeling rules it enforces (make typing)
• Modular transformers
• Contributing guide

Closing this one in the meantime, thanks again!