code: def get_model_loaders_to_tasks(
      tasks_to_model_loaders: Dict[str, Union[str, Tuple[str]]]
  ) -> Dict[str, str]:
      """
      Reverses tasks_to_model_loaders while flattening the case where the same task maps to several
      auto classes (e.g. automatic-speech-recognition).
      """
      model_loaders_to_tasks = {}
      for task, model_loaders in tasks_to_model_loaders.items():
          if isinstance(model_loaders, str):
              model_loaders_to_tasks[model_loaders] = task
          else:
              model_loaders_to_tasks.update(
                  {
                      model_loader_name: task
                      for model_loader_name in model_loaders
                  }
              )
  
      return model_loaders_to_tasks
  
imports: import importlib
  import inspect
  import itertools
  import json
  import os
  from functools import partial
  from pathlib import Path
  from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Set, Tuple, Type, Union
  import huggingface_hub
  from packaging import version
  from requests.exceptions import ConnectionError
  from transformers import AutoConfig, PretrainedConfig, is_tf_available, is_torch_available
  from transformers.utils import SAFE_WEIGHTS_NAME, TF2_WEIGHTS_NAME, WEIGHTS_NAME, logging
  from ..utils import CONFIG_NAME
  from ..utils.import_utils import is_onnx_available
label_desc: Use image node_id 4 for calling a global function with example usage: get_model_loaders_to_tasks(tasks_to_model_loaders) and returns: model_loaders_to_tasks