code: def test_rwd():
      layer = RandomWindowDiscriminator(
          cond_channels=80,
          window_sizes=(512, 1024, 2048, 4096, 8192),
          cond_disc_downsample_factors=[
              (8, 4, 2, 2, 2),
              (8, 4, 2, 2),
              (8, 4, 2),
              (8, 4),
              (4, 2, 2),
          ],
          hop_length=256,
      )
      x = torch.rand([4, 1, 22050])
      c = torch.rand([4, 80, 22050 // 256])
  
      scores, _ = layer(x, c)
      assert len(scores) == 10
      assert np.all(scores[0].shape == (4, 1, 1))
  
imports: import torch
  import numpy
  from TTS.vocoder.models.random_window_discriminator import RandomWindowDiscriminator
label_desc: Use image node_id 1 for calling a global function with example usage: test_rwd() without return types