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fix vulnerability #2149

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Merged
merged 4 commits into from
Mar 25, 2025
Merged

fix vulnerability #2149

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944ebb1
fix vulnerability
xin3he Mar 24, 2025
608af90
Update load_huggingface.py
xin3he Mar 24, 2025
aa8da34
change a better way to resolve it
xin3he Mar 24, 2025
707b767
Merge branch 'master' into xinhe/1
XuehaoSun Mar 25, 2025
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79 changes: 3 additions & 76 deletions neural_compressor/utils/load_huggingface.py
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Original file line number Diff line number Diff line change
Expand Up @@ -83,7 +83,7 @@ def from_pretrained(cls, model_name_or_path: str, **kwargs) -> torch.nn.Module:
**kwargs,
)

model_class = eval(f"transformers.{config.architectures[0]}")
model_class = transformers.AutoModelForSequenceClassification
if config.torch_dtype is not torch.int8:
model = model_class.from_pretrained(
model_name_or_path,
Expand All @@ -96,81 +96,8 @@ def from_pretrained(cls, model_name_or_path: str, **kwargs) -> torch.nn.Module:
)
return model
else:
logger.info("the quantization optimized model is loading.")
keys_to_ignore_on_load_unexpected = copy.deepcopy(
getattr(model_class, "_keys_to_ignore_on_load_unexpected", None)
)
keys_to_ignore_on_load_missing = copy.deepcopy(
getattr(model_class, "_keys_to_ignore_on_load_missing", None)
)

# Avoid unnecessary warnings resulting from quantized model initialization
quantized_keys_to_ignore_on_load = [
r"zero_point",
r"scale",
r"packed_params",
r"constant",
r"module",
r"best_configure",
]
if keys_to_ignore_on_load_unexpected is None:
model_class._keys_to_ignore_on_load_unexpected = quantized_keys_to_ignore_on_load
else:
model_class._keys_to_ignore_on_load_unexpected.extend(quantized_keys_to_ignore_on_load)
missing_keys_to_ignore_on_load = [r"weight", r"bias"]
if keys_to_ignore_on_load_missing is None:
model_class._keys_to_ignore_on_load_missing = missing_keys_to_ignore_on_load
else: # pragma: no cover
model_class._keys_to_ignore_on_load_missing.extend(missing_keys_to_ignore_on_load)

if not os.path.isdir(model_name_or_path) and not os.path.isfile(model_name_or_path): # pragma: no cover
from transformers.utils import cached_file

try:
# Load from URL or cache if already cached
resolved_weights_file = cached_file(
model_name_or_path,
filename=WEIGHTS_NAME,
cache_dir=cache_dir,
force_download=force_download,
resume_download=resume_download,
use_auth_token=use_auth_token,
)
except EnvironmentError as err: # pragma: no cover
logger.error(err)
msg = (
f"Can't load weights for '{model_name_or_path}'. Make sure that:\n\n"
f"- '{model_name_or_path}' is a correct model identifier "
f"listed on 'https://huggingface.co/models'\n (make sure "
f"'{model_name_or_path}' is not a path to a local directory with "
f"something else, in that case)\n\n- or '{model_name_or_path}' is "
f"the correct path to a directory containing a file "
f"named one of {WEIGHTS_NAME}\n\n"
)
if revision is not None:
msg += (
f"- or '{revision}' is a valid git identifier "
f"(branch name, a tag name, or a commit id) that "
f"exists for this model name as listed on its model "
f"page on 'https://huggingface.co/models'\n\n"
)
raise EnvironmentError(msg)
else:
resolved_weights_file = os.path.join(model_name_or_path, WEIGHTS_NAME)
state_dict = torch.load(resolved_weights_file, {})
model = model_class.from_pretrained(
model_name_or_path,
cache_dir=cache_dir,
force_download=force_download,
resume_download=resume_download,
use_auth_token=use_auth_token,
revision=revision,
state_dict=state_dict,
**kwargs,
)

model_class._keys_to_ignore_on_load_unexpected = keys_to_ignore_on_load_unexpected
model_class._keys_to_ignore_on_load_missing = keys_to_ignore_on_load_missing
config.torch_dtype = torch.float32
model = model_class.from_config(config)

if not os.path.isdir(model_name_or_path) and not os.path.isfile(model_name_or_path): # pragma: no cover
# pylint: disable=E0611
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