code: def _is_parameter_search_estimator(estimator):
      """
      :return: `True` if the specified scikit-learn estimator is a parameter search estimator,
               such as `GridSearchCV`. `False` otherwise.
      """
      from sklearn.model_selection import (
          GridSearchCV,
          RandomizedSearchCV,
      )
  
      parameter_search_estimators = [
          GridSearchCV,
          RandomizedSearchCV,
      ]
  
      return any(
          isinstance(estimator, param_search_estimator)
          for param_search_estimator in parameter_search_estimators
      )
  
imports: import collections
  import inspect
  import logging
  import pkgutil
  import platform
  import warnings
  from copy import deepcopy
  from importlib import import_module
  from numbers import Number
  from operator import itemgetter
  import numpy
  from packaging.version import Version
  from mlflow import MlflowClient
  from mlflow.utils.arguments_utils import _get_arg_names
  from mlflow.utils.file_utils import TempDir
  from mlflow.utils.mlflow_tags import MLFLOW_PARENT_RUN_ID
  from mlflow.utils.time import get_current_time_millis
label_desc: Use image node_id 17 for calling a global function with example usage: _is_parameter_search_estimator(estimator) and returns: any