train_op.zero_grad()
loss.backward()
train_op.step()
print np.mean(loss_)
show_adn_save...("real",make_grid(v.view(32,1,28,28).data))
show_adn_save("generate",make_grid(v1.view(32,1,28,28).data...))
def show_adn_save(file_name,img):
npimg = np.transpose(img.numpy(),(1,2,0))
f = ".