code: def _fetch_class_library_tuple(module):
      # import it here to avoid circular import
      diffusers_module = importlib.import_module(__name__.split(".")[0])
      pipelines = getattr(diffusers_module, "pipelines")
  
      # register the config from the original module, not the dynamo compiled one
      not_compiled_module = _unwrap_model(module)
      library = not_compiled_module.__module__.split(".")[0]
  
      # check if the module is a pipeline module
      module_path_items = not_compiled_module.__module__.split(".")
      pipeline_dir = (
          module_path_items[-2] if len(module_path_items) > 2 else None
      )
  
      path = not_compiled_module.__module__.split(".")
      is_pipeline_module = pipeline_dir in path and hasattr(
          pipelines, pipeline_dir
      )
  
      # if library is not in LOADABLE_CLASSES, then it is a custom module.
      # Or if it's a pipeline module, then the module is inside the pipeline
      # folder so we set the library to module name.
      if is_pipeline_module:
          library = pipeline_dir
      elif library not in LOADABLE_CLASSES:
          library = not_compiled_module.__module__
  
      # retrieve class_name
      class_name = not_compiled_module.__class__.__name__
  
      return (library, class_name)
  
imports: import fnmatch
  import importlib
  import inspect
  import os
  import re
  import sys
  import warnings
  from dataclasses import dataclass
  from pathlib import Path
  from typing import Any, Callable, Dict, List, Optional, Union
  import numpy
  import PIL.Image
  import requests
  import torch
  from huggingface_hub import ModelCard, create_repo, hf_hub_download, model_info, snapshot_download
  from huggingface_hub.utils import OfflineModeIsEnabled, validate_hf_hub_args
  from packaging import version
  from requests.exceptions import HTTPError
  from tqdm.auto import tqdm
  from ..None import __version__
  from ..configuration_utils import ConfigMixin
  from ..models.modeling_utils import _LOW_CPU_MEM_USAGE_DEFAULT
  from ..schedulers.scheduling_utils import SCHEDULER_CONFIG_NAME
  from ..utils import CONFIG_NAME, DEPRECATED_REVISION_ARGS, SAFETENSORS_WEIGHTS_NAME, WEIGHTS_NAME, BaseOutput, deprecate, get_class_from_dynamic_module, is_accelerate_available, is_accelerate_version, is_peft_available, is_torch_version, is_transformers_available, logging, numpy_to_pil
  from ..utils.torch_utils import is_compiled_module
  from ..utils import FLAX_WEIGHTS_NAME, ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, PushToHubMixin
label_desc: Use image node_id 9 for calling a global function with example usage: _fetch_class_library_tuple(module) and returns: library,  class_name