code: def hyperparams(*args: any, is_hyperparam=True):
      r"""
      Identifies configuration as (or not) hyper-parameters
  
      Arguments:
          *args: list of configurations
          is_hyperparam (bool, optional): whether the provided configuration
              items are hyper-parameters. 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_hyperparams(arg, is_hyperparam=is_hyperparam)
  
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 12 for calling a global function with example usage: hyperparams() without return types