WGAN real and generated (fake) image dimension mismatch during fake image generation

Question

I\'m training a WGAN-GP (Wasserstein GAN with Gradient Penalty) as such, but incur mismatch in my real and fake dimensions: gradient = get_gradient(crit, real, fake.de