text: from grm import GRM, preprocessing
  from pm4py.objects.log.util import sampling
  
  # import data
  data_raw = preprocessing.import_data("data", "BPI2020_PermitLog.csv", separator=";", quote='', case_id="Case ID",
                                       activity="Activity",
                                       time_stamp="Complete Timestamp", target="(case) Overspent")
  
  # Create new GRM model object
  hyper_params = {'num_epochs': 1}
  grm_model = GRM.GRM(data_raw, params=hyper_params)
  
  # Train GGNN model
  grm_model.train()
  
  # Evaluation of the GGNN model
  evaluation_metrics = grm_model.testing_log()
  print(evaluation_metrics)
  
  # Visualization as DFG (with sample of evaluation data)
  multi_instance_log = sampling.sample(data_raw, n=100)
  grm_model.visualize_dfg(save_file=False, log=multi_instance_log, file_name="multi")
  