means = -1
count = 0
fig, axes = plt.subplots(1, 10, gridspec_kw = {'wspace':0.1, 'hspace':0.1}, figsize=(16,16))
while means < 1 :
  random_latent_vectors = np.random.normal(size = (16, latent_dim), loc=means,
                                         scale=0.0)
  random_latent_vectors = random_latent_vectors.mean(axis=0)
  generated_images = generator.predict(np.array([random_latent_vectors]))
  axes[count].set_xticklabels([])
  axes[count].set_yticklabels([])
  axes[count].imshow(generated_images[0])
  axes[count].axis('off')
  means += 0.2
  count+= 1
plt.show()