code: def test_clustering_persistence(tmpdir, preprocess_data):
      data = pycaret.datasets.get_data("jewellery")
      exp = ClusteringExperiment()
      exp.setup(
          data,
          normalize=True,
          html=False,
          session_id=123,
          n_jobs=1,
      )
      exp_path = os.path.join(tmpdir, "exp.pkl")
      exp.save_experiment(exp_path)
  
      new_exp = ClusteringExperiment.load_experiment(
          exp_path,
          data=data if preprocess_data else exp.data,
          preprocess_data=preprocess_data,
      )
      assert "normalize" in new_exp.pipeline.named_steps
      check_experiment_equality(exp, new_exp)
  
file_path: pycaret/tests/test_persistence_experiment.py
imports: import os
  import joblib
  import pytest
  import pycaret.anomaly
  import pycaret.classification
  import pycaret.clustering
  import pycaret.datasets
  import pycaret.regression
  import pycaret.time_series
  from pycaret.anomaly import AnomalyExperiment
  from pycaret.classification import ClassificationExperiment
  from pycaret.clustering import ClusteringExperiment
  from pycaret.regression import RegressionExperiment
  from pycaret.time_series import TSForecastingExperiment
label_desc: Use image node_id 3 for calling a global function with example usage: test_clustering_persistence(tmpdir, preprocess_data) without return types