#下面的程序运行时报错：
C:\Users\Administrator\AppData\Local\Programs\Python\Python312\python.exe D:\2025-08-16文生图\千问.py
Traceback (most recent call last):
File "D:\2025-08-16文生图\千问.py", line 1, in <module>
from modelscope import DiffusionPipeline, FlowMatchEulerDiscreteScheduler
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python312\Lib\site-packages\modelscope\utils\import_utils.py", line 440, in __getattr__
value = self._extra_import_func(name)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python312\Lib\site-packages\modelscope\__init__.py", line 134, in try_import_from_hf
raise ImportError(
ImportError: Cannot import available module of FlowMatchEulerDiscreteScheduler in modelscope, or related packages(['transformers', 'peft', 'diffusers'])
进程已结束，退出代码为 1
=======================================================================================
# Copyright (c) Alibaba, Inc. and its affiliates.
import importlib
from typing import TYPE_CHECKING
from modelscope.utils.import_utils import (LazyImportModule,
is_transformers_available)
if TYPE_CHECKING:
from .exporters import Exporter, TfModelExporter, TorchModelExporter
from .hub.api import HubApi
from .hub.check_model import check_local_model_is_latest, check_model_is_id
from .hub.push_to_hub import push_to_hub, push_to_hub_async
from .hub.snapshot_download import snapshot_download, dataset_snapshot_download
from .hub.file_download import model_file_download, dataset_file_download
from .metrics import (
AccuracyMetric, AudioNoiseMetric, BleuMetric, ImageColorEnhanceMetric,
ImageColorizationMetric, ImageDenoiseMetric, ImageInpaintingMetric,
ImageInstanceSegmentationCOCOMetric, ImagePortraitEnhancementMetric,
ImageQualityAssessmentDegradationMetric,
ImageQualityAssessmentMosMetric, LossMetric, Metric,
MovieSceneSegmentationMetric, OCRRecognitionMetric, PplMetric,
ReferringVideoObjectSegmentationMetric, SequenceClassificationMetric,
TextGenerationMetric, TextRankingMetric, TokenClassificationMetric,
VideoFrameInterpolationMetric, VideoStabilizationMetric,
VideoSummarizationMetric, VideoSuperResolutionMetric,
task_default_metrics)
from .models import Model, TorchModel
from .msdatasets import MsDataset
from .pipelines import Pipeline, pipeline
from .preprocessors import Preprocessor
from .trainers import (EpochBasedTrainer, Hook, Priority, TrainingArgs,
build_dataset_from_file)
from .utils.constant import Tasks
from .utils.hf_util import patch_hub, patch_context, unpatch_hub
if is_transformers_available():
from .utils.hf_util import (
AutoModel, AutoProcessor, AutoFeatureExtractor, GenerationConfig,
AutoConfig, GPTQConfig, AwqConfig, BitsAndBytesConfig,
AutoModelForCausalLM, AutoModelForSeq2SeqLM,
AutoModelForVision2Seq, AutoModelForSequenceClassification,
AutoModelForTokenClassification, AutoModelForImageClassification,
AutoModelForImageTextToText,
AutoModelForZeroShotImageClassification,
AutoModelForKeypointDetection,
AutoModelForDocumentQuestionAnswering,
AutoModelForSemanticSegmentation,
AutoModelForUniversalSegmentation,
AutoModelForInstanceSegmentation, AutoModelForObjectDetection,
AutoModelForZeroShotObjectDetection,
AutoModelForAudioClassification, AutoModelForSpeechSeq2Seq,
AutoModelForMaskedImageModeling,
AutoModelForVisualQuestionAnswering,
AutoModelForTableQuestionAnswering, AutoModelForImageToImage,
AutoModelForImageSegmentation, AutoModelForQuestionAnswering,
AutoModelForMaskedLM, AutoTokenizer, AutoModelForMaskGeneration,
AutoModelForPreTraining, AutoModelForTextEncoding,
AutoImageProcessor, BatchFeature, Qwen2VLForConditionalGeneration,
T5EncoderModel, Qwen2_5_VLForConditionalGeneration, LlamaModel,
LlamaPreTrainedModel, LlamaForCausalLM, hf_pipeline)
else:
print(
'transformer is not installed, please install it if you want to use related modules'
)
from .utils.hub import create_model_if_not_exist, read_config
from .utils.logger import get_logger
from .version import __release_datetime__, __version__
else:
_import_structure = {
'version': ['__release_datetime__', '__version__'],
'trainers': [
'EpochBasedTrainer', 'TrainingArgs', 'Hook', 'Priority',
'build_dataset_from_file'
],
'exporters': [
'Exporter',
'TfModelExporter',
'TorchModelExporter',
],
'hub.api': ['HubApi'],
'hub.snapshot_download':
['snapshot_download', 'dataset_snapshot_download'],
'hub.file_download': ['model_file_download', 'dataset_file_download'],
'hub.push_to_hub': ['push_to_hub', 'push_to_hub_async'],
'hub.check_model':
['check_model_is_id', 'check_local_model_is_latest'],
'metrics': [
'AudioNoiseMetric', 'Metric', 'task_default_metrics',
'ImageColorEnhanceMetric', 'ImageDenoiseMetric',
'ImageInstanceSegmentationCOCOMetric',
'ImagePortraitEnhancementMetric', 'SequenceClassificationMetric',
'TextGenerationMetric', 'TokenClassificationMetric',
'VideoSummarizationMetric', 'MovieSceneSegmentationMetric',
'AccuracyMetric', 'BleuMetric', 'ImageInpaintingMetric',
'ReferringVideoObjectSegmentationMetric',
'VideoFrameInterpolationMetric', 'VideoStabilizationMetric',
'VideoSuperResolutionMetric', 'PplMetric',
'ImageQualityAssessmentDegradationMetric',
'ImageQualityAssessmentMosMetric', 'TextRankingMetric',
'LossMetric', 'ImageColorizationMetric', 'OCRRecognitionMetric'
],
'models': ['Model', 'TorchModel'],
'preprocessors': ['Preprocessor'],
'pipelines': ['Pipeline', 'pipeline'],
'utils.hub': ['read_config', 'create_model_if_not_exist'],
'utils.logger': ['get_logger'],
'utils.constant': ['Tasks'],
'msdatasets': ['MsDataset']
}
from modelscope.utils import hf_util
from modelscope.utils.hf_util.patcher import _patch_pretrained_class
extra_objects = {}
attributes = dir(hf_util)
imports = [attr for attr in attributes if not attr.startswith('__')]
for _import in imports:
extra_objects[_import] = getattr(hf_util, _import)
def try_import_from_hf(name):
hf_pkgs = ['transformers', 'peft', 'diffusers']
module = None
for pkg in hf_pkgs:
try:
module = getattr(importlib.import_module(pkg), name)
break
except Exception: # noqa
pass
if module is not None:
module = _patch_pretrained_class([module], wrap=True)
else:
raise ImportError(
f'Cannot import available module of {name} in modelscope,'
f' or related packages({hf_pkgs})')
return module[0]
import sys
sys.modules[__name__] = LazyImportModule(
__name__,
globals()['__file__'],
_import_structure,
module_spec=__spec__,
extra_objects=extra_objects,
extra_import_func=try_import_from_hf,
)
通过删除 AnimateDiff-LCM 并安装最新版本的 AnimateDiff-Evolved 解决
本文介绍了如何通过从过时的AnimateDiff-LCM版本升级到最新的AnimateDiff-Evolved版本，来解决可能遇到的技术问题，提供了解决方案的步骤。
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