def METHOD_NAME(batch_size):
  images = np.random.rand(*image_shape(batch_size)).astype(np.float32)
  num_classes = 1000
  labels = np.random.randint(
      low=0, high=num_classes, size=[batch_size]).astype(np.int32)
  one_hot = np.zeros((batch_size, num_classes)).astype(np.float32)
  one_hot[np.arange(batch_size), labels] = 1.
  return images, one_hot