code: def meta_config(*args: any, is_meta=True):
      r"""
      Identifies configuration as meta parameter
  
      Arguments:
          *args: list of configurations
          is_meta (bool, optional): whether the provided configuration
              items are meta. Defaults to ``True``.
      """
  
      for arg in args:
          config_class = _get_config_class(arg)
          if config_class is None:
              raise ConfigsError(
                  "You need to pass config items to set hyperparams"
              )
          config_class.set_meta(arg, is_meta=is_meta)
  
file_path: labml/client/labml/configs.py
imports: from typing import List, Callable, overload, Union, Tuple
  from labml.internal.configs.base import Configs
  from labml.internal.configs.config_item import ConfigItem
  from labml.utils.errors import ConfigsError
label_desc: Use image node_id 13 for calling a global function with example usage: meta_config() without return types