code: def run_nlu_training(args: argparse.Namespace) -> Optional[Text]:
      """Trains an NLU model.
  
      Args:
          args: Namespace arguments.
  
      Returns:
          Path to a trained model or `None` if training was not successful.
      """
      from rasa.model_training import train_nlu
  
      config = rasa.cli.utils.get_validated_config(
          args.config, CONFIG_MANDATORY_KEYS_NLU
      )
      nlu_data = rasa.cli.utils.get_validated_path(
          args.nlu, "nlu", DEFAULT_DATA_PATH, none_is_valid=True
      )
  
      if args.domain:
          args.domain = rasa.cli.utils.get_validated_path(
              args.domain,
              "domain",
              DEFAULT_DOMAIN_PATH,
              none_is_valid=True,
          )
  
      return train_nlu(
          config=config,
          nlu_data=nlu_data,
          output=args.out,
          fixed_model_name=args.fixed_model_name,
          persist_nlu_training_data=args.persist_nlu_data,
          additional_arguments={
              **extract_nlu_additional_arguments(args),
              **_extract_additional_arguments(args),
          },
          domain=args.domain,
          model_to_finetune=_model_for_finetuning(args),
          finetuning_epoch_fraction=args.epoch_fraction,
      )
  
imports: import argparse
  import logging
  import sys
  from typing import Dict, List, Optional, Text
  from rasa.cli import SubParsersAction
  import rasa.cli.arguments.train
  import rasa.cli.utils
  from rasa.shared.importers.importer import TrainingDataImporter
  import rasa.utils.common
  from rasa.core.train import do_compare_training
  from rasa.plugin import plugin_manager
  from rasa.shared.constants import CONFIG_MANDATORY_KEYS_CORE, CONFIG_MANDATORY_KEYS_NLU, CONFIG_MANDATORY_KEYS, DEFAULT_DOMAIN_PATH, DEFAULT_DATA_PATH
label_desc: Use image node_id 5 for calling a global function with example usage: run_nlu_training(args) and returns: train_nlu