code: def run_models(offset=0, step=1):
      """Check if all the models are downloadable and tts models run correctly."""
      print(" > Run synthesizer with all the models.")
      output_path = os.path.join(get_tests_output_path(), "output.wav")
      manager = ModelManager(
          output_prefix=get_tests_output_path(), progress_bar=False
      )
      model_names = [
          name
          for name in manager.list_models()
          if name not in MODELS_WITH_SEP_TESTS
      ]
      print("Model names:", model_names)
      for model_name in model_names[offset::step]:
          print(f"\n > Run - {model_name}")
          model_path, _, _ = manager.download_model(model_name)
          if "tts_models" in model_name:
              local_download_dir = os.path.dirname(model_path)
              # download and run the model
              speaker_files = glob.glob(
                  local_download_dir + "/speaker*"
              )
              language_files = glob.glob(
                  local_download_dir + "/language*"
              )
              language_id = ""
              if len(speaker_files) > 0:
                  # multi-speaker model
                  if "speaker_ids" in speaker_files[0]:
                      speaker_manager = SpeakerManager(
                          speaker_id_file_path=speaker_files[0]
                      )
                  elif "speakers" in speaker_files[0]:
                      speaker_manager = SpeakerManager(
                          d_vectors_file_path=speaker_files[0]
                      )
  
                  # multi-lingual model - Assuming multi-lingual models are also multi-speaker
                  if (
                      len(language_files) > 0
                      and "language_ids" in language_files[0]
                  ):
                      language_manager = LanguageManager(
                          language_ids_file_path=language_files[0]
                      )
                      language_id = language_manager.language_names[0]
  
                  speaker_id = list(speaker_manager.name_to_id.keys())[
                      0
                  ]
                  run_cli(
                      f"tts --model_name  {model_name} "
                      f'--text "This is an example." --out_path "{output_path}" --speaker_idx "{speaker_id}" --language_idx "{language_id}" --progress_bar False'
                  )
              else:
                  # single-speaker model
                  run_cli(
                      f"tts --model_name  {model_name} "
                      f'--text "This is an example." --out_path "{output_path}" --progress_bar False'
                  )
              # remove downloaded models
              shutil.rmtree(local_download_dir)
              shutil.rmtree(get_user_data_dir("tts"))
          elif "voice_conversion_models" in model_name:
              speaker_wav = os.path.join(
                  get_tests_data_path(),
                  "ljspeech",
                  "wavs",
                  "LJ001-0001.wav",
              )
              reference_wav = os.path.join(
                  get_tests_data_path(),
                  "ljspeech",
                  "wavs",
                  "LJ001-0032.wav",
              )
              run_cli(
                  f"tts --model_name  {model_name} "
                  f'--out_path "{output_path}" --source_wav "{speaker_wav}" --target_wav "{reference_wav}" --progress_bar False'
              )
          else:
              # only download the model
              manager.download_model(model_name)
          print(f" | > OK: {model_name}")
  
file_path: TTS/tests/zoo_tests/test_models.py
imports: import glob
  import os
  import shutil
  import torch
  from tests import get_tests_data_path, get_tests_output_path, run_cli
  from TTS.tts.utils.languages import LanguageManager
  from TTS.tts.utils.speakers import SpeakerManager
  from TTS.utils.generic_utils import get_user_data_dir
  from TTS.utils.manage import ModelManager
label_desc: Use image node_id 1 for calling a global function with example usage: run_models(offset, step) without return types