code: def test_train_nlu_finetune_with_model(
      run_in_simple_project_with_model: Callable[..., RunResult]
  ):
      temp_dir = os.getcwd()
  
      files = rasa.shared.utils.io.list_files(
          os.path.join(temp_dir, "models")
      )
      assert len(files) == 1
  
      model_name = os.path.relpath(files[0])
      output = run_in_simple_project_with_model(
          "train", "--finetune", model_name
      )
      assert any(
          "Your Rasa model is trained and saved at" in line
          for line in output.outlines
      )
  
imports: import os
  import sys
  from pathlib import Path
  from _pytest.capture import CaptureFixture
  import pytest
  from typing import Callable, List
  from _pytest.pytester import RunResult
  from _pytest.tmpdir import TempPathFactory
  import rasa.shared.utils.io
  from rasa.constants import NUMBER_OF_TRAINING_STORIES_FILE
  from rasa.core.policies.policy import Policy
  from rasa.engine.storage.local_model_storage import LocalModelStorage
  from rasa.engine.storage.resource import Resource
  from rasa.shared.core.domain import Domain
  from rasa.model_training import CODE_NEEDS_TO_BE_RETRAINED, CODE_FORCED_TRAINING
  from rasa.shared.constants import LATEST_TRAINING_DATA_FORMAT_VERSION
  from rasa.shared.nlu.training_data.training_data import DEFAULT_TRAINING_DATA_OUTPUT_PATH
  import rasa.utils.io
  from tests.cli.conftest import RASA_EXE
label_desc: Use image node_id 20 for calling a global function with example usage: test_train_nlu_finetune_with_model(run_in_simple_project_with_model) without return types