code: def train_comparison_models(
      story_file: Text,
      domain: Text,
      output_path: Text = "",
      exclusion_percentages: Optional[List] = None,
      policy_configs: Optional[List] = None,
      runs: int = 1,
      additional_arguments: Optional[Dict] = None,
  ) -> None:
      """Trains multiple models for comparison of policies."""
      import rasa.model_training
  
      exclusion_percentages = exclusion_percentages or []
      policy_configs = policy_configs or []
  
      for r in range(runs):
          logging.info("Starting run {}/{}".format(r + 1, runs))
  
          for current_run, percentage in enumerate(
              exclusion_percentages, 1
          ):
              for policy_config in policy_configs:
                  config_name = os.path.splitext(
                      os.path.basename(policy_config)
                  )[0]
                  logging.info(
                      "Starting to train {} round {}/{}"
                      " with {}% exclusion"
                      "".format(
                          config_name,
                          current_run,
                          len(exclusion_percentages),
                          percentage,
                      )
                  )
  
                  rasa.model_training.train_core(
                      domain,
                      policy_config,
                      stories=story_file,
                      output=str(Path(output_path, f"run_{r +1}")),
                      fixed_model_name=config_name
                      + PERCENTAGE_KEY
                      + str(percentage),
                      additional_arguments={
                          **additional_arguments,
                          "exclusion_percentage": percentage,
                      },
                  )
  
file_path: rasa/rasa/core/train.py
imports: import argparse
  import logging
  import os
  from pathlib import Path
  from typing import Dict, Optional, Text, List
  import rasa.shared.utils.io
  import rasa.utils.io
  from rasa.constants import NUMBER_OF_TRAINING_STORIES_FILE, PERCENTAGE_KEY
  from rasa.shared.importers.importer import TrainingDataImporter
label_desc: Use image node_id 1 for calling a global function with example usage: train_comparison_models(story_file, domain, output_path, exclusion_percentages, policy_configs, runs, additional_arguments) without return types