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logger.warning when using remote code (#1171)

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* logger warning when using remote code

Co-authored-by: suluyan <suluyan.sly@alibaba-inc.com>
This commit is contained in:
suluyana
2025-01-10 15:38:05 +08:00
committed by GitHub
parent 768f953b9d
commit cc6fbbab5f
12 changed files with 89 additions and 1 deletions
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6
modelscope/models/nlp/polylm/text_generation.py
View File

@@ -10,8 +10,11 @@ from modelscope.models.base import Tensor, TorchModel
from modelscope.models.builder import MODELS
from modelscope.utils.constant import Tasks
from modelscope.utils.hub import read_config
from modelscope.utils.logger import get_logger
from modelscope.utils.streaming_output import StreamingOutputMixin
logger = get_logger()
__all__ = ['PolyLMForTextGeneration']
@@ -27,6 +30,9 @@ class PolyLMForTextGeneration(TorchModel, StreamingOutputMixin):
super().__init__(model_dir, *args, **kwargs)
self.tokenizer = AutoTokenizer.from_pretrained(
model_dir, legacy=False, use_fast=False)
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {model_dir}. Please make sure '
'that you can trust the external codes.')
self.model = AutoModelForCausalLM.from_pretrained(
model_dir, device_map='auto', trust_remote_code=True)
self.model.eval()

5
modelscope/msdatasets/data_loader/data_loader.py
View File

@@ -133,6 +133,11 @@ class OssDownloader(BaseDownloader):
raise f'meta-file: {dataset_name}.py not found on the modelscope hub.'
if dataset_py_script and dataset_formation == DatasetFormations.hf_compatible:
if trust_remote_code:
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {dataset_name}. Please make '
'sure that you can trust the external codes.')
self.dataset = hf_load_dataset(
dataset_py_script,
name=subset_name,

9
modelscope/msdatasets/data_loader/data_loader_manager.py
View File

@@ -71,6 +71,11 @@ class LocalDataLoaderManager(DataLoaderManager):
# Select local data loader
# TODO: more loaders to be supported.
if data_loader_type == LocalDataLoaderType.HF_DATA_LOADER:
if trust_remote_code:
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {dataset_name}. Please make '
'sure that you can trust the external codes.')
# Build huggingface data loader and return dataset.
return hf_data_loader(
dataset_name,
@@ -110,6 +115,10 @@ class RemoteDataLoaderManager(DataLoaderManager):
# To use the huggingface data loader
if data_loader_type == RemoteDataLoaderType.HF_DATA_LOADER:
if trust_remote_code:
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {dataset_name}. Please make '
'sure that you can trust the external codes.')
dataset_ret = hf_data_loader(
dataset_name,
name=subset_name,

5
modelscope/msdatasets/ms_dataset.py
View File

@@ -237,6 +237,11 @@ class MsDataset:
if not namespace or not dataset_name:
raise 'The dataset_name should be in the form of `namespace/dataset_name` or `dataset_name`.'
if trust_remote_code:
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {dataset_name}. Please make sure that '
'you can trust the external codes.')
# Init context config
dataset_context_config = DatasetContextConfig(
dataset_name=dataset_name,

16
modelscope/msdatasets/utils/hf_datasets_util.py
View File

@@ -835,6 +835,8 @@ def get_module_with_script(self) -> DatasetModule:
if not os.path.exists(importable_file_path):
trust_remote_code = resolve_trust_remote_code(trust_remote_code=self.trust_remote_code, repo_id=self.name)
if trust_remote_code:
logger.warning(f'Use trust_remote_code=True. Will invoke codes from {repo_id}. Please make sure that '
'you can trust the external codes.')
_create_importable_file(
local_path=local_script_path,
local_imports=local_imports,
@@ -934,6 +936,11 @@ class DatasetsWrapperHF:
verification_mode or VerificationMode.BASIC_CHECKS
) if not save_infos else VerificationMode.ALL_CHECKS)
if trust_remote_code:
logger.warning(f'Use trust_remote_code=True. Will invoke codes from {path}. Please make sure '
'that you can trust the external codes.'
)
# Create a dataset builder
builder_instance = DatasetsWrapperHF.load_dataset_builder(
path=path,
@@ -1061,6 +1068,11 @@ class DatasetsWrapperHF:
) if download_config else DownloadConfig()
download_config.storage_options.update(storage_options)
if trust_remote_code:
logger.warning(f'Use trust_remote_code=True. Will invoke codes from {path}. Please make sure '
'that you can trust the external codes.'
)
dataset_module = DatasetsWrapperHF.dataset_module_factory(
path,
revision=revision,
@@ -1171,6 +1183,10 @@ class DatasetsWrapperHF:
# -> the module from the python file in the dataset repository
# - if path has one "/" and is dataset repository on the HF hub without a python file
# -> use a packaged module (csv, text etc.) based on content of the repository
if trust_remote_code:
logger.warning(f'Use trust_remote_code=True. Will invoke codes from {path}. Please make sure '
'that you can trust the external codes.'
)
# Try packaged
if path in _PACKAGED_DATASETS_MODULES:

6
modelscope/pipelines/accelerate/vllm.py
View File

@@ -1,8 +1,11 @@
from typing import List, Union
from modelscope import get_logger
from modelscope.pipelines.accelerate.base import InferFramework
from modelscope.utils.import_utils import is_vllm_available
logger = get_logger()
class Vllm(InferFramework):
@@ -27,6 +30,9 @@ class Vllm(InferFramework):
if not Vllm.check_gpu_compatibility(8) and (dtype
in ('bfloat16', 'auto')):
dtype = 'float16'
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {self.model_dir}. Please make '
'sure that you can trust the external codes.')
self.model = LLM(
self.model_dir,
dtype=dtype,

7
modelscope/pipelines/multi_modal/ovis_vl_pipeline.py
View File

@@ -2,7 +2,7 @@ from typing import Any, Dict, Union
import torch
from modelscope import AutoModelForCausalLM
from modelscope import AutoModelForCausalLM, get_logger
from modelscope.metainfo import Pipelines, Preprocessors
from modelscope.models.base import Model
from modelscope.outputs import OutputKeys
@@ -13,6 +13,8 @@ from modelscope.pipelines.multi_modal.visual_question_answering_pipeline import
from modelscope.preprocessors import Preprocessor, load_image
from modelscope.utils.constant import Fields, Frameworks, Tasks
logger = get_logger()
@PIPELINES.register_module(
Tasks.visual_question_answering, module_name='ovis-vl')
@@ -35,6 +37,9 @@ class VisionChatPipeline(VisualQuestionAnsweringPipeline):
torch_dtype = kwargs.get('torch_dtype', torch.float16)
multimodal_max_length = kwargs.get('multimodal_max_length', 8192)
self.device = 'cuda' if device == 'gpu' else device
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {model}. Please make '
'sure that you can trust the external codes.')
self.model = AutoModelForCausalLM.from_pretrained(
model,
torch_dtype=torch_dtype,

12
modelscope/pipelines/nlp/llm_pipeline.py
View File

@@ -97,6 +97,9 @@ class LLMPipeline(Pipeline, PipelineStreamingOutputMixin):
assert base_model is not None, 'Cannot get adapter_cfg.model_id_or_path from configuration.json file.'
revision = self.cfg.safe_get('adapter_cfg.model_revision',
'master')
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {base_model}. Please make sure that you can '
'trust the external codes.')
base_model = Model.from_pretrained(
base_model,
revision,
@@ -134,6 +137,9 @@ class LLMPipeline(Pipeline, PipelineStreamingOutputMixin):
model) else snapshot_download(model)
# TODO: Temporary use of AutoModelForCausalLM
# Need to be updated into a universal solution
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {model_dir}. Please make sure '
'that you can trust the external codes.')
model = AutoModelForCausalLM.from_pretrained(
model_dir,
device_map=self.device_map,
@@ -173,6 +179,9 @@ class LLMPipeline(Pipeline, PipelineStreamingOutputMixin):
self.llm_framework = llm_framework
if os.path.exists(kwargs['model']):
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {kwargs["model"]}. Please make sure '
'that you can trust the external codes.')
config = AutoConfig.from_pretrained(
kwargs['model'], trust_remote_code=True)
q_config = config.__dict__.get('quantization_config', None)
@@ -423,6 +432,9 @@ class LLMPipeline(Pipeline, PipelineStreamingOutputMixin):
model_dir = self.model.model_dir
if tokenizer_class is None:
tokenizer_class = AutoTokenizer
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {model_dir}. Please make sure '
'that you can trust the external codes.')
return tokenizer_class.from_pretrained(
model_dir, trust_remote_code=True)

12
modelscope/pipelines/nlp/text_generation_pipeline.py
View File

@@ -269,6 +269,9 @@ class ChatGLM6bV2TextGenerationPipeline(Pipeline):
if use_bf16:
default_torch_dtype = torch.bfloat16
torch_dtype = kwargs.get('torch_dtype', default_torch_dtype)
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {model_dir}. Please make sure '
'that you can trust the external codes.')
model = Model.from_pretrained(
model_dir,
trust_remote_code=True,
@@ -285,6 +288,9 @@ class ChatGLM6bV2TextGenerationPipeline(Pipeline):
self.model = model
self.model.eval()
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {self.model.model_dir}. Please '
'make sure that you can trust the external codes.')
self.tokenizer = AutoTokenizer.from_pretrained(
self.model.model_dir, trust_remote_code=True)
@@ -328,6 +334,9 @@ class QWenChatPipeline(Pipeline):
bf16 = False
if isinstance(model, str):
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {model}. Please make sure '
'that you can trust the external codes.')
self.tokenizer = AutoTokenizer.from_pretrained(
model, revision=revision, trust_remote_code=True)
self.model = AutoModelForCausalLM.from_pretrained(
@@ -392,6 +401,9 @@ class QWenTextGenerationPipeline(Pipeline):
bf16 = False
if isinstance(model, str):
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {model}. Please make sure '
'that you can trust the external codes.')
self.model = AutoModelForCausalLM.from_pretrained(
model,
device_map=device_map,

3
modelscope/preprocessors/templates/loader.py
View File

@@ -820,6 +820,9 @@ class TemplateLoader:
model_id,
revision=kwargs.pop('revision', 'master'),
ignore_file_pattern=ignore_file_pattern)
logger.warning(f'Use trust_remote_code=True. Will invoke codes from {model_dir}.'
' Please make sure that you can trust the external codes.'
)
tokenizer = AutoTokenizer.from_pretrained(
model_dir, trust_remote_code=True)
config = AutoConfig.from_pretrained(model_dir, trust_remote_code=True)

6
modelscope/utils/automodel_utils.py
View File

@@ -3,12 +3,15 @@ import os
from types import MethodType
from typing import Any, Optional
from modelscope import get_logger
from modelscope.metainfo import Tasks
from modelscope.utils.ast_utils import INDEX_KEY
from modelscope.utils.import_utils import (LazyImportModule,
is_torch_available,
is_transformers_available)
logger = get_logger()
def can_load_by_ms(model_dir: str, task_name: Optional[str],
model_type: Optional[str]) -> bool:
@@ -91,6 +94,9 @@ def get_hf_automodel_class(model_dir: str,
if not os.path.exists(config_path):
return None
try:
logger.warning(
f'Use trust_remote_code=True. Will invoke codes from {model_dir}. Please make sure '
'that you can trust the external codes.')
config = AutoConfig.from_pretrained(model_dir, trust_remote_code=True)
if task_name is None:
automodel_class = get_default_automodel(config)

3
modelscope/utils/plugins.py
View File

@@ -451,6 +451,9 @@ def register_plugins_repo(plugins: List[str]) -> None:
def register_modelhub_repo(model_dir, allow_remote=False) -> None:
""" Try to install and import remote model from modelhub"""
if allow_remote:
logger.warning(
f'Use allow_remote=True. Will invoke codes from {model_dir}. Please make sure '
'that you can trust the external codes.')
try:
import_module_from_model_dir(model_dir)
except KeyError: