code: def test_melgan_generator():
      model = MelganGenerator()
      print(model)
      dummy_input = torch.rand((4, 80, 64))
      output = model(dummy_input)
      assert np.all(output.shape == (4, 1, 64 * 256))
      output = model.inference(dummy_input)
      assert np.all(output.shape == (4, 1, (64 + 4) * 256))
  
imports: import numpy
  import torch
  from TTS.vocoder.models.melgan_generator import MelganGenerator
label_desc: Use image node_id 1 for calling a global function with example usage: test_melgan_generator() without return types