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[Enc-Dec] Fix OOT tokenizer issue (#30144)

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Signed-off-by: NickLucche <nlucches@redhat.com>
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Nicolò Lucchesi 2025-12-05 20:23:33 +01:00 committed by GitHub
parent adb315060c
commit bff78310d9
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1 changed files with 4 additions and 3 deletions
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7
vllm/inputs/preprocess.py
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@ -198,7 +198,7 @@ class InputPreprocessor:
) -> dict[str, Any]:
kwargs = dict[str, Any]()
if self.model_config.hf_config.model_type == "whisper":
if self.model_config.is_encoder_decoder:
# For Whisper, special tokens should be provided by the user based
# on the task and language of their request. Also needed to avoid
# appending an EOS token to the prompt which disrupts generation.
@ -573,7 +573,6 @@ class InputPreprocessor:
"""
encoder_inputs: SingletonInputs
decoder_inputs: SingletonInputs | None
if is_explicit_encoder_decoder_prompt(prompt):
# `cast` is needed for mypy, but not pyright
prompt_ = cast(ExplicitEncoderDecoderPrompt, prompt)
@ -585,7 +584,9 @@ class InputPreprocessor:
if (decoder_input := prompt_["decoder_prompt"]) is None:
decoder_inputs = None
else:
decoder_inputs = self._prompt_to_llm_inputs(decoder_input)
decoder_inputs = self._prompt_to_llm_inputs(
decoder_input, tokenization_kwargs=tokenization_kwargs
)
# For multimodal model, override decoder prompt from processor
# with explicit decoder prompt.
if self.model_config.is_multimodal_model: