code: def test_vits_model_pt(self):
      speech_generator = pipeline(
          task="text-to-audio",
          model="facebook/mms-tts-eng",
          framework="pt",
      )
  
      outputs = speech_generator("This is a test")
      self.assertEqual(outputs["sampling_rate"], 16000)
  
      audio = outputs["audio"]
      self.assertEqual(ANY(np.ndarray), audio)
  
      # test two examples side-by-side
      outputs = speech_generator(
          ["This is a test", "This is a second test"]
      )
      audio = [output["audio"] for output in outputs]
      self.assertEqual([ANY(np.ndarray), ANY(np.ndarray)], audio)
  
      # test batching
      outputs = speech_generator(
          ["This is a test", "This is a second test"], batch_size=2
      )
      self.assertEqual(ANY(np.ndarray), outputs[0]["audio"])
  
file_path: transformers/tests/pipelines/test_pipelines_text_to_audio.py
imports: import unittest
  import numpy
  from transformers import MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING, AutoProcessor, TextToAudioPipeline, pipeline
  from transformers.testing_utils import is_pipeline_test, require_torch, require_torch_accelerator, require_torch_or_tf, slow, torch_device
  from transformers.trainer_utils import set_seed
  from .test_pipelines_common import ANY
label_desc: Use image node_id 4 for calling the TextToAudioPipelineTests obj's underlying member method code with example usage: obj.test_vits_model_pt() without return types