code: def test_handles_pipeline_with_non_existing_component(
      tmp_path: Path,
      pretrained_embeddings_spacy_config: Dict,
      nlu_as_json_path: Text,
  ):
      pretrained_embeddings_spacy_config["pipeline"].append(
          {"name": "my_made_up_component"}
      )
  
      config_file = tmp_path / "config.yml"
      rasa.shared.utils.io.dump_obj_as_json_to_file(
          config_file, pretrained_embeddings_spacy_config
      )
  
      with pytest.raises(
          Exception,
          match="Can't load class for name 'my_made_up_component'",
      ):
          rasa.model_training.train_nlu(
              str(config_file), nlu_as_json_path, output=str(tmp_path)
          )
  
imports: from pathlib import Path
  import pytest
  from _pytest.tmpdir import TempPathFactory
  from rasa.core.agent import Agent
  from rasa.core.policies.policy import Policy
  from rasa.engine.storage.local_model_storage import LocalModelStorage
  from rasa.shared.nlu.training_data.formats import RasaYAMLReader
  from rasa.utils.tensorflow.constants import EPOCHS, RUN_EAGERLY
  from typing import Any, Dict, List, Tuple, Text, Union, Optional
  import rasa.model_training
  import rasa.shared.utils.io
  import rasa.engine.recipes.default_components
label_desc: Use image node_id 8 for calling a global function with example usage: test_handles_pipeline_with_non_existing_component(tmp_path, pretrained_embeddings_spacy_config, nlu_as_json_path) without return types