tflib.init_tf()

# Load pre-trained network.
url = 'https://drive.google.com/uc?id=1MEGjdvVpUsu1jB4zrXZN7Y4kBBOzizDQ' # karras2019stylegan-ffhq-1024x1024.pkl
with dnnlib.util.open_url(url, cache_dir=config.cache_dir) as f:
    _G, _D, Gs = pickle.load(f)
all = []
for i in range(20):
  print(i)
  rnd = np.random.RandomState()
  latents = rnd.randn(1, Gs.input_shape[1])
  fmt = dict(func=tflib.convert_images_to_uint8, nchw_to_nhwc=True)
  images = Gs.run(latents, None, truncation_psi=0.1, randomize_noise=True, output_transform=fmt)
  all.append(images[0])