code: def generate_fake_eval_dataset(path):
      """
      Generate fake evaluation dataset
      """
      aa = AudioAdapter.default()
      n_songs = 2
      fs = 44100
      duration = 3
      n_channels = 2
      rng = np.random.RandomState(seed=0)
      for song in range(n_songs):
          song_path = join(path, "test", f"song{song}")
          makedirs(song_path, exist_ok=True)
          for instr in ["mixture", "vocals", "bass", "drums", "other"]:
              filename = join(song_path, f"{instr}.wav")
              data = rng.rand(duration * fs, n_channels) - 0.5
              aa.save(filename, data, fs)
  
imports: from os import makedirs
  from os.path import join
  from tempfile import TemporaryDirectory
  import numpy
  from spleeter.__main__ import evaluate
  from spleeter.audio.adapter import AudioAdapter
label_desc: Use image node_id 1 for calling a global function with example usage: generate_fake_eval_dataset(path) without return types