code: def finder_selector(module_name):
      """Selects the appropriate :class:`ResultFinder` to use for `module_name`
  
      Parameters
      ----------
      module_name: String
          Module from whence the algorithm being used came
  
      Returns
      -------
      Uninitialized :class:`ResultFinder`, or one of its descendants
  
      Examples
      --------
      >>> assert finder_selector("Keras") == KerasResultFinder
      >>> assert finder_selector("xgboost") == ResultFinder
      >>> assert finder_selector("lightgbm") == ResultFinder
      """
      if module_name.lower() == "keras":
          return KerasResultFinder
      else:
          return ResultFinder
  
imports: from hyperparameter_hunter.feature_engineering import EngineerStep, FeatureEngineer
  from hyperparameter_hunter.i_o.exceptions import IncompatibleCandidateError
  from hyperparameter_hunter.compat.keras_helper import keras_callback_to_dict, keras_initializer_to_dict
  from hyperparameter_hunter.settings import G
  from hyperparameter_hunter.space.dimensions import Categorical, RejectedOptional
  from hyperparameter_hunter.space.space_core import Space
  from hyperparameter_hunter.utils.boltons_utils import remap, get_path
  from hyperparameter_hunter.utils.general_utils import multi_visit
  from hyperparameter_hunter.utils.optimization_utils import does_fit_in_space, get_ids_by, get_scored_params
  from copy import deepcopy
  from numbers import Number
  from pathlib import Path
  from typing import Dict, List, Tuple, Union
  import wrapt
label_desc: Use image node_id 1 for calling a global function with example usage: finder_selector(module_name) and returns: KerasResultFinder, ResultFinder