* fast_generate: clear error for vLLM-style inputs when fast_inference=False
When fast_inference=False, fast_generate falls back to HuggingFace
generate, and the wrapper already rejects vLLM-only usage (a
sampling_params or lora_request kwarg, or a string prompt). A vLLM prompt
dict ({'prompt':..., 'multi_modal_data':...}) or a SamplingParams passed
positionally slipped through and hit transformers.generate, raising a
cryptic 'SamplingParams object has no attribute update'. Detect both and
raise the same clear 'only supported with fast_inference=True' error.
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* fast_generate: also reject positional list of SamplingParams and list of vLLM prompt dicts
Address review feedback: the slow-mode guard missed SamplingParams passed inside a
positional list and a list of {"prompt": ...} dicts, both valid vLLM batched shapes
that leaked into transformers.generate. Fold the checks into small predicates and
extend the GPU-free test (now 7 reject + 3 pass).
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* test_fast_generate_slow_guard: expose assertions via a test_ function so pytest collects them
The assertions lived in run(), only called from __main__, so pytest reported no tests
collected and CI skipped the coverage. Rename to test_fast_generate_slow_guard; the
standalone script entrypoint still works.
* fast_generate: reject vLLM tokenized/embeds prompt dicts in the slow-mode guard
vLLM also accepts prompt dicts keyed by prompt_token_ids or prompt_embeds, not just
prompt/multi_modal_data. Those slipped past the slow-mode guard and fell through to
HuggingFace generate with a cryptic error. Recognize all vLLM prompt-dict keys and
add a TokensPrompt test case (now 8 reject + 3 pass).
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* fast_generate slow-mode guard: catch vLLM prompts= keyword form
vLLM's generate names its first argument `prompts`, so a slow-mode call
like fast_generate(prompts="hi") or prompts=[{"prompt": ...}] bypassed the
guard and leaked into HuggingFace generate as an unexpected kwarg. Check
kwargs["prompts"] with the same _is_vllm_prompt predicate and add two test
cases.
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* fast_generate slow-mode guard: reject vLLM tokenized prompt kwargs
vLLM's legacy call shape passes tokens as prompt_token_ids= (and prompt_embeds=),
which are not HuggingFace generate arguments. In slow mode these bypassed the
guard and leaked into HF generate as unexpected kwargs. Reject their presence
with the same tokenize-first message and add a test case.
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* fast_generate slow-mode guard: treat prompts= as vLLM-only
prompts is a vLLM keyword, not a HuggingFace generate argument, so any value
passed as prompts= (including a bare token-id list, which _is_vllm_prompt
deliberately ignores for positional HF token ids) is a vLLM-style call. Reject
prompts= / prompt_token_ids= / prompt_embeds= on presence, and keep the
conservative _is_vllm_prompt check only for the positional arg.
* fast_generate slow-mode guard: reject vLLM prompt kwargs on presence
prompts / prompt_token_ids / prompt_embeds are vLLM-only keyword names that
HuggingFace generate does not accept, so a defaulted call like prompts=None
should raise the actionable slow-mode error instead of leaking a None kwarg
into HF generate. Check membership in kwargs rather than a non-None value.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Wasim Yousef Said <wasimysdev@gmail.com>
Daniel Han