[Bugfix]: Fix messy code when using logprobs

[chaunceyjiang]

FIX #19177

[github-actions]

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[gemini-code-assist]

Hello @chaunceyjiang, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

Summary of Changes

As gemini-code-assist, I've reviewed this pull request. The primary goal of this PR, as indicated by the title and linked issue (#19177), is to fix an issue where the output, particularly when using log probabilities, appears "messy" or incorrectly formatted. The core change addresses this by modifying the detokenization logic within the vllm/transformers_utils/detokenizer_utils.py file. Specifically, it switches from using tokenizer.convert_ids_to_tokens to tokenizer.decode to convert token IDs back into strings. This change is likely aimed at improving how special tokens, whitespace, and subword units are handled during the conversion process, leading to cleaner and more accurate text output, which is essential for correct logprob interpretation.

Highlights

• Bugfix: Addresses issue #19177 concerning messy output when log probabilities are enabled.
• Detokenization Logic Update: Changes the method used for converting token IDs back to strings in the convert_ids_list_to_tokens function.

Changelog

• vllm/transformers_utils/detokenizer_utils.py
  • Modified the convert_ids_list_to_tokens function (line 92) to use tokenizer.decode(token_ids) instead of tokenizer.convert_ids_to_tokens(token_ids) for detokenization, aiming to fix output formatting issues related to logprobs.

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---

IDs flow from model,
Convert to text, a story told.
Decode makes it clean,
A bug fixed, a better scene.

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[gemini-code-assist]

Code Review

The pull request addresses an issue related to messy code when using log probabilities. The change replaces tokenizer.convert_ids_to_tokens with tokenizer.decode in the convert_ids_list_to_tokens function. This seems like a reasonable fix. I have a minor suggestion.

Merge Readiness

The change appears to be a straightforward bug fix. The suggestion is minor and can be addressed before or after merging. I am unable to directly approve the pull request, and other reviewers should review and approve this code before merging.

[chaunceyjiang]

/cc @njhill PTAL

[ywang96]

I left a comment - I think it also makes sense to add a unit test for this if possible, but we can probably leave it for a later PR

[chaunceyjiang]

test

from transformers import AutoTokenizer
from vllm.transformers_utils.detokenizer_utils import convert_ids_list_to_tokens
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-1.5B-Instruct")
token_ids = tokenizer.encode("Hello, world!", add_special_tokens=True)
print(token_ids)
print(tokenizer.convert_ids_to_tokens([9707]))
print(tokenizer.convert_ids_to_tokens([11]))
print(tokenizer.convert_ids_to_tokens([1879]))
print(tokenizer.convert_ids_to_tokens([0]))
print(tokenizer.convert_ids_to_tokens(token_ids))
print("-----")
print(tokenizer.decode([9707]))
print(tokenizer.decode([11]))
print(tokenizer.decode([1879]))
print(tokenizer.decode([0]))
print("-----")
texts = convert_ids_list_to_tokens(tokenizer,[9707, 11, 1879, 0])
print(texts)

[9707, 11, 1879, 0]
['Hello']
[',']
['Ġworld']
['!']
['Hello', ',', 'Ġworld', '!']
-----
Hello
,
 world
!
-----
['Hello', ',', ' world', '!']

We can observe that using tokenizer.convert_ids_to_tokens() leads to messy code.

[chaunceyjiang]

@DarkLight1337 @ywang96 @ProExpertProg PTAL.

[chaunceyjiang]

Directly using tokenizer.convert_ids_to_tokens() does not produce human-readable text; it still needs to be passed through tokenizer.convert_tokens_to_string(). However, using tokenizer.decode() directly yields human-readable output.

Reference: https://github.com/huggingface/transformers/blob/main/src/transformers/tokenization_utils.py#L1090-L1115

[mgoin]

The CI failures look related to detokenize changes, PTAL

[chaunceyjiang]

The CI failures look related to detokenize changes,

Yes. I'm currently investigating this issue.

[ericg108]

@chaunceyjiang Hi, any update for this? thanks.

[chaunceyjiang]

Hi, @ericg108 I was on vacation last week. I will complete this PR this week.

[ericg108]

btw, is there any way to postprocess to get the expected token, like from the bytes array or messy code?

[ericg108]

Hi, @ericg108 I was on vacation last week. I will complete this PR this week.

thank you for your kindly effort @chaunceyjiang

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @chaunceyjiang.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[chaunceyjiang]

@DarkLight1337 @ywang96 The docker-build-image-cpu test failure is unrelated to my code. All other tests have passed.
PTAL.

[DarkLight1337]

I believe this PR broke mistral models: https://buildkite.com/organizations/vllm/analytics/suites/ci-1/tests/41bf2871-4779-8f39-b029-6db37181eed7?period=14days&tags=scm.branch%3Amain

[DarkLight1337]

Mistral models don't support skip_special_tokens=False

[chaunceyjiang]

Oh, it's my mistake—I didn't notice that detail.

#20910