(output_real, output_fake)
return loss
r"""
    Computes the wasserstein loss for the discriminator.

    Args:
        output_real (Tensor): Discriminator output logits for real images.
        output_fake (Tensor): Discriminator output logits for fake images.

    Returns:
        Tensor: A scalar tensor loss output.
r"""
    Computes the wasserstein loss for the discriminator.
r Computes the wasserstein loss for the discriminator .
def wasserstein_loss_dis(output_real, output_fake):
    r"""
    Computes the wasserstein loss for the discriminator.

    Args:
        output_real (Tensor): Discriminator output logits for real images.
        output_fake (Tensor): Discriminator output logits for fake images.

    Returns:
        Tensor: A scalar tensor loss output.
    """
    loss = -1.0 * output_real.mean() + output_fake.mean()

    return loss
def wasserstein_loss_dis ( output_real , output_fake ) : loss = - 1.0 * output_real . mean ( ) + output_fake . mean ( ) return loss