def sample_with_labels()

in api/BigGAN/deployment/app.py [0:0]

• 18 lines of code
• 3 McCabe index (conditional complexity)

def sample_with_labels(sess, noise, label, truncation=1., batch_size=8,
           vocab_size=vocab_size):
  noise = np.asarray(noise)
  label = np.asarray(label)
  num = noise.shape[0]
  if label.shape[0] != num:
    raise ValueError('Got # noise samples ({}) != # label samples ({})'
                     .format(noise.shape[0], label.shape[0]))
  ims = []
  for batch_start in range(0, num, batch_size):
    s = slice(batch_start, min(num, batch_start + batch_size))
    feed_dict = {input_z: noise[s], input_y: label[s], input_trunc: truncation}
    ims.append(sess.run(output, feed_dict=feed_dict))
  ims = np.concatenate(ims, axis=0)
  assert ims.shape[0] == num
  ims = np.clip(((ims + 1) / 2.0) * 256, 0, 255)
  ims = np.uint8(ims)
  return ims