code: def test_demo_data(files: List[Text]):
      from rasa.shared.importers.utils import training_data_from_paths
  
      trainingdata = training_data_from_paths(files, language="en")
      assert trainingdata.intents == {
          "affirm",
          "greet",
          "restaurant_search",
          "goodbye",
          "chitchat",
      }
      assert trainingdata.entities == {"location", "cuisine"}
      assert set(trainingdata.responses.keys()) == {
          "utter_chitchat/ask_name",
          "utter_chitchat/ask_weather",
      }
      assert len(trainingdata.training_examples) == 46
      assert len(trainingdata.intent_examples) == 46
      assert len(trainingdata.response_examples) == 4
      assert len(trainingdata.entity_examples) == 11
      assert len(trainingdata.responses) == 2
  
      assert trainingdata.entity_synonyms == {
          "Chines": "chinese",
          "Chinese": "chinese",
          "chines": "chinese",
          "vegg": "vegetarian",
          "veggie": "vegetarian",
      }
  
      assert trainingdata.regex_features == [
          {"name": "greet", "pattern": r"hey[^\s]*"},
          {"name": "zipcode", "pattern": r"[0-9]{5}"},
      ]
  
imports: from pathlib import Path
  from typing import Text, List, Dict, Any
  from unittest.mock import Mock
  from _pytest.monkeypatch import MonkeyPatch
  import pytest
  import numpy
  import rasa.shared.utils.io
  from rasa.shared.core.constants import USER_INTENT_OUT_OF_SCOPE
  from rasa.shared.nlu.constants import TEXT, INTENT_RESPONSE_KEY, ENTITY_ATTRIBUTE_START, ENTITY_ATTRIBUTE_END, ENTITY_ATTRIBUTE_VALUE, ENTITY_ATTRIBUTE_TYPE, ENTITIES, INTENT, ACTION_NAME, FEATURE_TYPE_SENTENCE
  from rasa.nlu.convert import convert_training_data
  from rasa.nlu.extractors.mitie_entity_extractor import MitieEntityExtractor
  from rasa.nlu.tokenizers.whitespace_tokenizer import WhitespaceTokenizer
  from rasa.shared.nlu.training_data.features import Features
  from rasa.shared.nlu.training_data.message import Message
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.loading import guess_format, UNK, load_data
  from rasa.shared.nlu.training_data.util import get_file_format_extension, template_key_to_intent_response_key, intent_response_key_to_template_key
  import rasa.shared.data
  from rasa.shared.core.domain import Domain
  from rasa.shared.core.events import UserUttered, ActionExecuted
  from rasa.shared.core.training_data.structures import StoryGraph, StoryStep
  from rasa.shared.importers.importer import TrainingDataImporter, E2EImporter
label_desc: Use image node_id 9 for calling a global function with example usage: test_demo_data(files) without return types