code: def _get_mocked_samples(dataset_dir, sample_rate):
      sample_count = 5
  
      all_samples = {"train": {}, "test": {}}
  
      folders = ["train", "test"]
      sources = ["bass", "drums", "other", "mixture", "vocals"]
  
      curr_idx = 0
      for folder in folders:
          for _ in range(sample_count):
              sample_list = []
              for source in sources:
                  sample = _save_sample(
                      dataset_dir,
                      folder,
                      str(curr_idx),
                      source,
                      sample_rate,
                      seed_dict.get(source),
                  )
                  sample_list.append(sample)
              all_samples[folder][str(curr_idx)] = sample_list
              curr_idx += 1
          if folder == "train":
              for name in _VALIDATION_SET:
                  sample_list = []
                  for source in sources:
                      sample = _save_sample(
                          dataset_dir,
                          folder,
                          name,
                          source,
                          sample_rate,
                          seed_dict.get(source),
                      )
                      sample_list.append(sample)
                  all_samples[folder][name] = sample_list
  
      return all_samples
  
file_path: audio/test/torchaudio_unittest/datasets/musdb_hq_test.py
imports: import os
  import torch
  from parameterized import parameterized
  from torchaudio.datasets import musdb_hq
  from torchaudio.datasets.musdb_hq import _VALIDATION_SET
  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_mocked_samples(dataset_dir, sample_rate) and returns: all_samples