code: def get_mock_dataset(dataset_dir: str):
      """Create mocked dataset for a sub directory.
  
      Args:
          dataset_dir (str): the path of the sub directory.
          The structure is: audio_type/speaker_id/chapter_id/filename.flac
      """
      mocked_data = []
      sample_rate = 16000  # 16kHz
      seed = 0
      for audio_type in ["clean", "other"]:
          for speaker_id in range(5):
              for chapter_id in range(3):
                  file_path = os.path.join(
                      dataset_dir,
                      audio_type,
                      str(speaker_id),
                      str(chapter_id),
                  )
                  os.makedirs(file_path, exist_ok=True)
                  trans_content = []
                  for utterance_id in range(3):
                      sample = _save_sample(
                          file_path,
                          speaker_id,
                          chapter_id,
                          utterance_id,
                          sample_rate,
                          seed,
                      )
                      trans_content.append(
                          f"{sample[3]}-{sample[4]}-{sample[5]:04d} {sample[2]}"
                      )
                      mocked_data.append(sample)
                      seed += 1
                  trans_filename = (
                      f"{speaker_id}-{chapter_id}.trans.txt"
                  )
                  trans_path = os.path.join(file_path, trans_filename)
                  with open(trans_path, "w") as f:
                      f.write("\n".join(trans_content))
      return mocked_data
  
file_path: audio/test/torchaudio_unittest/datasets/librilightlimited_test.py
imports: import os
  from torchaudio.datasets import librilight_limited
  from torchaudio_unittest.common_utils import get_whitenoise, save_wav, TempDirMixin, TorchaudioTestCase
label_desc: Use image node_id 2 for calling a global function with example usage: get_mock_dataset(dataset_dir) and returns: mocked_data