code: def load_experiment(
      path_or_file: Union[str, os.PathLike, BinaryIO],
      data: Optional[DATAFRAME_LIKE] = None,
      data_func: Optional[Callable[[], DATAFRAME_LIKE]] = None,
      preprocess_data: bool = True,
      **cloudpickle_kwargs,
  ) -> AnomalyExperiment:
      """
      Load an experiment saved with ``save_experiment`` from path
      or file.
  
      The data (and test data) is NOT saved with the experiment
      and will need to be specified again.
  
  
      path_or_file: str or BinaryIO (file pointer)
          The path/file pointer to load the experiment from.
          The pickle file must be created through ``save_experiment``.
  
  
      data: dataframe-like
          Data set with shape (n_samples, n_features), where n_samples is the
          number of samples and n_features is the number of features. If data
          is not a pandas dataframe, it's converted to one using default column
          names.
  
  
      data_func: Callable[[], DATAFRAME_LIKE] = None
          The function that generate ``data`` (the dataframe-like input). This
          is useful when the dataset is large, and you need parallel operations
          such as ``compare_models``. It can avoid broadcasting large dataset
          from driver to workers. Notice one and only one of ``data`` and
          ``data_func`` must be set.
  
  
      preprocess_data: bool, default = True
          If True, the data will be preprocessed again (through running ``setup``
          internally). If False, the data will not be preprocessed. This means
          you can save the value of the ``data`` attribute of an experiment
          separately, and then load it separately and pass it here with
          ``preprocess_data`` set to False. This is an advanced feature.
          We recommend leaving it set to True and passing the same data
          as passed to the initial ``setup`` call.
  
  
      **cloudpickle_kwargs:
          Kwargs to pass to the ``cloudpickle.load`` call.
  
  
      Returns:
          loaded experiment
  
      """
      exp = _EXPERIMENT_CLASS.load_experiment(
          path_or_file=path_or_file,
          data=data,
          data_func=data_func,
          preprocess_data=preprocess_data,
          **cloudpickle_kwargs,
      )
      set_current_experiment(exp)
      return exp
  
imports: import logging
  import os
  from typing import Any, BinaryIO, Callable, Dict, List, Optional, Union
  import pandas
  from joblib.memory import Memory
  from pycaret.anomaly.oop import AnomalyExperiment
  from pycaret.loggers.base_logger import BaseLogger
  from pycaret.utils.constants import DATAFRAME_LIKE, SEQUENCE_LIKE
  from pycaret.utils.generic import check_if_global_is_not_none
label_desc: Use image node_id 16 for calling a global function with example usage: load_experiment(path_or_file, data, data_func, preprocess_data) and returns: exp