code: def _mock_dataset(root_dir, num_speaker):
      dirnames = ["mix"] + [f"s{i+1}" for i in range(num_speaker)]
      for dirname in dirnames:
          os.makedirs(os.path.join(root_dir, dirname), exist_ok=True)
  
      seed = 0
      sample_rate = 8000
      expected = []
      for filename in _FILENAMES:
          mix = None
          src = []
          for dirname in dirnames:
              waveform = get_whitenoise(
                  sample_rate=8000,
                  duration=1,
                  n_channels=1,
                  dtype="int16",
                  seed=seed,
              )
              seed += 1
  
              path = os.path.join(root_dir, dirname, filename)
              save_wav(path, waveform, sample_rate)
              waveform = normalize_wav(waveform)
  
              if dirname == "mix":
                  mix = waveform
              else:
                  src.append(waveform)
          expected.append((sample_rate, mix, src))
      return expected
  
file_path: audio/test/torchaudio_unittest/example/souce_sepration/wsj0mix_test.py
imports: import os
  from source_separation.utils.dataset import wsj0mix
  from torchaudio_unittest.common_utils import get_whitenoise, normalize_wav, save_wav, TempDirMixin, TorchaudioTestCase
label_desc: Use image node_id 1 for calling a global function with example usage: _mock_dataset(root_dir, num_speaker) and returns: expected