dcgan-4.py

for i in range(5):
  plt.figure(figsize=(7,7))   
for k in range(20):
          noise=np.random.uniform(-1,1,size=[100,noise_shape])
          im=generator.predict(noise) 
          plt.subplot(5, 4, k+1)
          plt.imshow(im[k].reshape(64,64,3))
          plt.xticks([])
          plt.yticks([])
 
plt.tight_layout()
plt.show()