code: def test_evaluate():
      with TemporaryDirectory() as dataset:
          with TemporaryDirectory() as evaluation:
              generate_fake_eval_dataset(dataset)
              metrics = evaluate(
                  adapter="spleeter.audio.ffmpeg.FFMPEGProcessAudioAdapter",
                  output_path=evaluation,
                  params_filename="spleeter:4stems",
                  mus_dir=dataset,
                  mwf=False,
                  verbose=False,
              )
              for instrument, metric in metrics.items():
                  for m, value in metric.items():
                      assert np.allclose(
                          np.median(value),
                          res_4stems[instrument][m],
                          atol=1e-3,
                      )
  
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 2 for calling a global function with example usage: test_evaluate() without return types