code: def _generate_random_example_for_one_session_and_one_marker(
      rng: np.random.Generator,
  ) -> Tuple[List[EventMetaData], List[int]]:
      """Generates a random marker extraction result for a single session and marker.
  
      Args:
          rng: a random number generator
      Returns:
          the event list representing the marker extraction result as well as
          the plain list of numbers used as "preceding user turns" in that extraction
          result
      """
      applied = int(rng.choice(10))
      all_preceding_user_turn_numbers = [
          int(rng.choice(20)) for _ in range(applied)
      ]
      event_list = [
          EventMetaData(
              idx=int(rng.choice(100)),
              preceding_user_turns=preceding_user_turns,
          )
          for preceding_user_turns in all_preceding_user_turn_numbers
      ]
      return event_list, all_preceding_user_turn_numbers
  
file_path: rasa/tests/core/evaluation/test_marker_stats.py
imports: import csv
  from pathlib import Path
  from typing import Dict, List, Text, Tuple
  import itertools
  import pytest
  import numpy
  from rasa.core.evaluation.marker_stats import EventMetaData, MarkerStatistics, compute_statistics
label_desc: Use image node_id 3 for calling a global function with example usage: _generate_random_example_for_one_session_and_one_marker(rng) and returns: event_list,  all_preceding_user_turn_numbers