code: def add_test_nlu_argument_group(
      parser: Union[argparse.ArgumentParser, argparse._ActionsContainer]
  ) -> None:
      add_nlu_data_param(
          parser, help_text="File or folder containing your NLU data."
      )
  
      add_out_param(
          parser,
          default=DEFAULT_RESULTS_PATH,
          help_text="Output path for any files created during the evaluation.",
      )
      parser.add_argument(
          "-c",
          "--config",
          nargs="+",
          default=None,
          help="Model configuration file. If a single file is passed and cross "
          "validation mode is chosen, cross-validation is performed, if "
          "multiple configs or a folder of configs are passed, models "
          "will be trained and compared directly.",
      )
  
      parser.add_argument(
          "-d",
          "--domain",
          type=str,
          default=DEFAULT_DOMAIN_PATH,
          help="Domain specification. This can be a single YAML file, or a directory "
          "that contains several files with domain specifications in it. The content "
          "of these files will be read and merged together.",
      )
  
      cross_validation_arguments = parser.add_argument_group(
          "Cross Validation"
      )
      cross_validation_arguments.add_argument(
          "--cross-validation",
          action="store_true",
          default=False,
          help="Switch on cross validation mode. Any provided model will be ignored.",
      )
      cross_validation_arguments.add_argument(
          "-f",
          "--folds",
          required=False,
          default=5,
          help="Number of cross validation folds (cross validation only).",
      )
      comparison_arguments = parser.add_argument_group(
          "Comparison Mode"
      )
      comparison_arguments.add_argument(
          "-r",
          "--runs",
          required=False,
          default=3,
          type=int,
          help="Number of comparison runs to make.",
      )
      comparison_arguments.add_argument(
          "-p",
          "--percentages",
          required=False,
          nargs="+",
          type=int,
          default=[0, 25, 50, 75],
          help="Percentages of training data to exclude during comparison.",
      )
  
      add_no_plot_param(parser)
      add_errors_success_params(parser)
  
file_path: rasa/rasa/cli/arguments/test.py
imports: import argparse
  from typing import Union
  from rasa.shared.constants import DEFAULT_MODELS_PATH, DEFAULT_RESULTS_PATH
  from rasa.cli.arguments.default_arguments import add_stories_param, add_model_param, add_nlu_data_param, add_endpoint_param, add_out_param
  from rasa.model import get_latest_model
  from rasa.shared.constants import DEFAULT_DOMAIN_PATH
label_desc: Use image node_id 5 for calling a global function with example usage: add_test_nlu_argument_group(parser) without return types