import tensorflow as tf

             predicted_sdfs, predicted_classes, predicted_poses):
    """Update."""
    if labeled_sdfs or labeled_classes:
      print(labeled_sdfs)
    mean_x = tf.reduce_mean(labeled_poses[1][:, 0])
    mean_z = tf.reduce_mean(labeled_poses[1][:, 2])
    samples_world = grid.generate(
        (mean_x - 0.5, 0.0, mean_z - 0.5), (mean_x + 0.5, 1.0, mean_z + 0.5),
        [self.resolution, self.resolution, self.resolution])
    samples_world = tf.reshape(samples_world, [-1, 3])
