code: def test_melgan_multi_scale_discriminator():
      model = MelganMultiscaleDiscriminator()
      print(model)
      dummy_input = torch.rand((4, 1, 256 * 16))
      scores, feats = model(dummy_input)
      assert len(scores) == 3
      assert len(scores) == len(feats)
      assert np.all(scores[0].shape == (4, 1, 64))
      assert np.all(feats[0][0].shape == (4, 16, 4096))
      assert np.all(feats[0][1].shape == (4, 64, 1024))
      assert np.all(feats[0][2].shape == (4, 256, 256))
  
imports: import numpy
  import torch
  from TTS.vocoder.models.melgan_discriminator import MelganDiscriminator
  from TTS.vocoder.models.melgan_multiscale_discriminator import MelganMultiscaleDiscriminator
label_desc: Use image node_id 2 for calling a global function with example usage: test_melgan_multi_scale_discriminator() without return types