def wgan_d_loss(scores_real, scores_fake):
  """
  Input:
  - scores_real: Tensor of shape (N,) giving scores for real samples
  - scores_fake: Tensor of shape (N,) giving scores for fake samples

  Output:
  - loss: Tensor of shape (,) giving WGAN discriminator loss
  """
  return scores_fake.mean() - scores_real.mean()