code: def training_data(nlu_data_path: Text) -> TrainingData:
      return rasa.shared.nlu.training_data.loading.load_data(
          nlu_data_path
      )
  
imports: import copy
  import logging
  from typing import Callable, List, Text, Tuple
  import pytest
  from _pytest.logging import LogCaptureFixture
  from rasa.nlu.featurizers.dense_featurizer.spacy_featurizer import SpacyFeaturizer
  from rasa.nlu.tokenizers.spacy_tokenizer import SpacyTokenizer
  from rasa.nlu.utils.spacy_utils import SpacyModel, SpacyNLP
  import rasa.shared.nlu.training_data.loading
  from rasa.engine.graph import ExecutionContext, GraphComponent
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.nlu.classifiers.sklearn_intent_classifier import SklearnIntentClassifier
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.constants import TEXT, INTENT
  from rasa.shared.nlu.training_data.message import Message
label_desc: Use image node_id 1 for calling a global function with example usage: training_data(nlu_data_path) and returns: rasa