class_docstr: Provides NLU training data during training.
docstr: Persists NLU training data to model storage.
docstr_tok: ["Persists","NLU","training","data","to","model","storage","."]
code: def _persist(self, training_data: TrainingData) -> None:
      """Persists NLU training data to model storage."""
      with self._model_storage.write_to(
          self._resource
      ) as resource_directory:
          training_data.persist(
              dir_name=str(resource_directory),
              filename=DEFAULT_TRAINING_DATA_OUTPUT_PATH,
          )
  
file_path: rasa/rasa/graph_components/providers/nlu_training_data_provider.py
imports: from __future__ import annotations
  from typing import Dict, Text, Any
  from rasa.engine.graph import GraphComponent, ExecutionContext
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.shared.importers.importer import TrainingDataImporter
  from rasa.shared.nlu.training_data.training_data import TrainingData, DEFAULT_TRAINING_DATA_OUTPUT_PATH
label_desc: Use image node_id 4 for calling the NLUTrainingDataProvider obj's underlying member method code with example usage: obj._persist(training_data) without return types