code: def delayed(function):
      """Decorator used to capture the arguments of a function.
  
      This alternative to `joblib.delayed` is meant to be used in conjunction
      with `sklearn.utils.parallel.Parallel`. The latter captures the scikit-
      learn configuration by calling `sklearn.get_config()` in the current
      thread, prior to dispatching the first task. The captured configuration is
      then propagated and enabled for the duration of the execution of the
      delayed function in the joblib workers.
  
      .. versionchanged:: 1.3
         `delayed` was moved from `sklearn.utils.fixes` to `sklearn.utils.parallel`
         in scikit-learn 1.3.
  
      Parameters
      ----------
      function : callable
          The function to be delayed.
  
      Returns
      -------
      output: tuple
          Tuple containing the delayed function, the positional arguments, and the
          keyword arguments.
      """
  
      @functools.wraps(function)
      def delayed_function(*args, **kwargs):
          return _FuncWrapper(function), args, kwargs
  
      return delayed_function
  
file_path: scikit-learn/sklearn/utils/parallel.py
imports: import functools
  import warnings
  from functools import update_wrapper
  import joblib
  from .._config import config_context, get_config
label_desc: Use image node_id 2 for calling a global function with example usage: delayed(function) and returns: delayed_function, _FuncWrapper,  args,  kwargs