[Bugfix] fix when skip tokenizer init

[lengrongfu]

Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)". [Bug]: vLLM 0.10.0 breaks skip_tokenizer_init=True #21846
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

Purpose

Fix when set skip_tokenizer_init after can't running vllm.

Test success.

import vllm
from transformers import AutoTokenizer

model_name = "Qwen/Qwen2.5-1.5B-Instruct"
llm = vllm.LLM(model_name, skip_tokenizer_init=True)
tokenizer = AutoTokenizer.from_pretrained(model_name)
input_ids = tokenizer.encode("test")
print(llm.generate([{"prompt_token_ids": input_ids}]))

Resolves #21846.

Test Plan

Test Result

(Optional) Documentation Update

[gemini-code-assist]

Code Review

The pull request aims to fix a crash when skip_tokenizer_init=True. The changes correctly guard against a None tokenizer in two places, preventing crashes during input validation and processing. However, the fix is incomplete and will still lead to a crash during output processing because detokenization is attempted without a tokenizer. I've identified this critical issue and suggested a more comprehensive fix to make the skip_tokenizer_init feature robust.

[gemini-code-assist]

This change correctly handles the case where allowed_token_ids are provided with skip_tokenizer_init=True. However, the PR is incomplete and will still lead to a crash in other common scenarios.

When skip_tokenizer_init=True, OutputProcessor is initialized with tokenizer=None. This will cause a crash in process_outputs when it tries to create a Detokenizer, which will raise a ValueError: Tokenizer not initialized. This happens even if the user sets detokenize=False in SamplingParams, because the default SamplingParams has detokenize=True. The test case in the PR description will trigger this crash.

Additionally, if bad_words are provided, they are silently ignored as update_from_tokenizer is skipped, but no warning or error is raised to the user.

To properly fix this, we should validate these unsupported parameter combinations when skip_tokenizer_init=True and raise an error, similar to how structured output is handled. A good place for these checks would be in _validate_params or at the beginning of this method (_validate_sampling_params).

For example:

if self.tokenizer is None:
    if params.detokenize:
        raise ValueError(
            "Detokenization is not supported when `skip_tokenizer_init=True`. "
            "Please set `detokenize=False` in `SamplingParams`."
        )
    if params.bad_words:
        raise ValueError(
            "`bad_words` is not supported when `skip_tokenizer_init=True`."
        )

Without this, the bug is not fully fixed and the feature remains partially broken.

[njhill]

This will cause a crash in process_outputs when it tries to create a Detokenizer, which will raise a ValueError: Tokenizer not initialized.

I don't think this is correct, may be getting confused with v0.

[github-actions]

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[njhill]

Thanks @lengrongfu! Do you think you could also add a unit test?

I thought we had test coverage for this already but perhaps it was only for the V0 case...

[lengrongfu]

Thanks @lengrongfu! Do you think you could also add a unit test?

I thought we had test coverage for this already but perhaps it was only for the V0 case...

I add a unit test, can test this case.

[DarkLight1337]

Can you merge from main to fix the CI failures?