code: def set_default(cfg):
      """A special hook to register the default values for decorated Estimator.
  
      Parameters
      ----------
      cfg : autocfg.dataclass
          Default config as dataclass object
      """
  
      def _apply(cls):
          # docstring
          cls.__doc__ = str(cls.__doc__) if cls.__doc__ else ""
          cls.__doc__ += (
              "\n\nParameters\n"
              "----------\n"
              "config : str, dict\n"
              "  Config used to override default configurations. \n"
              "  If `str`, assume config file (.yml, .yaml) is used. \n"
              "logger : logger, default is `None`.\n"
              "  If not `None`, will use default logging object.\n"
          )
          cls.__doc__ += (
              "\nDefault configurations: \n--------------------\n"
          )
          sio = io.StringIO()
          cfg.save(sio)
          cls.__doc__ += "\n" + sio.getvalue()
          cls._default_cfg = cfg
          cls._default_cfg.freeze()
          return cls
  
      return _apply
  
imports: import os
  import math
  import pickle
  import io
  import logging
  from datetime import datetime
  import numpy
  import pandas
  from ...utils import random
  from ...utils.filesystem import temporary_filename
  from .utils import _suggest_load_context
label_desc: Use image node_id 1 for calling a global function with example usage: set_default(cfg) and returns: _apply, cls