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bugfix: Fix signature mismatch in benchmark's get_tokenizer function (#11982)

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Signed-off-by: elijah <f1renze.142857@gmail.com>
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elijah 2025-01-13 23:22:07 +08:00 committed by GitHub
parent a7d59688fb
commit c6db21313c
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GPG Key ID: B5690EEEBB952194
1 changed files with 24 additions and 3 deletions
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27
benchmarks/backend_request_func.py
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@ -417,14 +417,35 @@ def get_model(pretrained_model_name_or_path: str) -> str:
def get_tokenizer(
pretrained_model_name_or_path: str, trust_remote_code: bool
pretrained_model_name_or_path: str,
tokenizer_mode: str = "auto",
trust_remote_code: bool = False,
**kwargs,
) -> Union[PreTrainedTokenizer, PreTrainedTokenizerFast]:
if pretrained_model_name_or_path is not None and not os.path.exists(
pretrained_model_name_or_path):
pretrained_model_name_or_path = get_model(
pretrained_model_name_or_path)
return AutoTokenizer.from_pretrained(pretrained_model_name_or_path,
trust_remote_code=trust_remote_code)
if tokenizer_mode == "slow":
if kwargs.get("use_fast", False):
raise ValueError(
"Cannot use the fast tokenizer in slow tokenizer mode.")
kwargs["use_fast"] = False
if tokenizer_mode == "mistral":
try:
from vllm.transformers_utils.tokenizer import MistralTokenizer
except ImportError as e:
raise ImportError("MistralTokenizer requires vllm package.\n"
"Please install it with `pip install vllm` "
"to use mistral tokenizer mode.") from e
return MistralTokenizer.from_pretrained(
str(pretrained_model_name_or_path))
else:
return AutoTokenizer.from_pretrained(
pretrained_model_name_or_path,
trust_remote_code=trust_remote_code,
**kwargs,
)
ASYNC_REQUEST_FUNCS = {