code: def radtts_model():
      this_test_dir = os.path.dirname(os.path.abspath(__file__))
  
      cfg = OmegaConf.load(
          os.path.join(
              this_test_dir,
              "../../../examples/tts/conf/rad-tts_feature_pred.yaml",
          )
      )
      cfg.model.init_from_ptl_ckpt = None
      cfg.model.train_ds.dataset.manifest_filepath = "dummy.json"
      cfg.model.train_ds.dataset.sup_data_path = "dummy.json"
      cfg.model.validation_ds.dataset.manifest_filepath = "dummy.json"
      cfg.model.validation_ds.dataset.sup_data_path = "dummy.json"
      cfg.pitch_mean = 212.35
      cfg.pitch_std = 68.52
  
      app_state = AppState()
      app_state.is_model_being_restored = True
      model = RadTTSModel(cfg=cfg.model)
      app_state.is_model_being_restored = False
      model.eval()
      model.set_export_config(
          {"enable_ragged_batches": "True", "enable_volume": "True"}
      )
      return model
  
file_path: NeMo/tests/collections/tts/test_tts_exportables.py
imports: import os
  import tempfile
  import pytest
  import torch
  from omegaconf import OmegaConf
  from nemo.collections.tts.models import FastPitchModel, HifiGanModel, RadTTSModel
  from nemo.utils.app_state import AppState
label_desc: Use image node_id 3 for calling a global function with example usage: radtts_model() and returns: model