code: def get_engine(estimator: str) -> Optional[str]:
      """Gets the model engine currently set in the experiment for the specified
      model.
      Parameters
      ----------
      estimator : str
          Identifier for the model for which the engine should be retrieved,
          e.g. "auto_arima"
      Returns
      -------
      Optional[str]
          The engine for the model. If the model only supports the default sktime
          engine, then it return `None`.
      """
  
      return _CURRENT_EXPERIMENT.get_engine(estimator=estimator)
  
imports: import logging
  import os
  from typing import Any, BinaryIO, Callable, Dict, List, Optional, Union
  import pandas
  from joblib.memory import Memory
  from pycaret.internal.parallel.parallel_backend import ParallelBackend
  from pycaret.loggers.base_logger import BaseLogger
  from pycaret.regression.oop import RegressionExperiment
  from pycaret.utils.constants import DATAFRAME_LIKE, SEQUENCE_LIKE, TARGET_LIKE
  from pycaret.utils.generic import check_if_global_is_not_none
label_desc: Use image node_id 4 for calling a global function with example usage: get_engine(estimator) and returns: _CURRENT_EXPERIMENT