code: def test_squim_subjective_pretrained_weights(
      task, expected, mixture_source, clean_sources
  ):
      """Test that the metric scores estimated by SquimSubjective Bundle is identical to the expected result."""
      bundle = SQUIM_SUBJECTIVE
  
      # Get SquimObjective model
      model = bundle.get_model()
      # Load input mixture audio
      waveform, sample_rate = torchaudio.load(mixture_source)
      for i, source in enumerate(clean_sources):
          # Load clean reference
          clean_waveform, sample_rate = torchaudio.load(source)
          score = model(waveform, clean_waveform)
          assert abs(score.item() - expected[i]) < 1e-5
  
imports: import pytest
  import torchaudio
  from torchaudio.pipelines import SQUIM_OBJECTIVE, SQUIM_SUBJECTIVE
label_desc: Use image node_id 2 for calling a global function with example usage: test_squim_subjective_pretrained_weights(task, expected, mixture_source, clean_sources) without return types