import tensorflow as tf

    status = True
    if status:
      box_limits_x = [100, -100]
      # box_limits_y = [100, -100]
      box_limits_z = [100, -100]
      for i in range(labeled_translations.shape[0]):
        rot = tf.reshape(tf.gather(labeled_rotations[i], [0, 2, 6, 8]), [2, 2])

        min_x = tf.cast(0.0 - labeled_sizes[i][0] / 2.0, dtype=tf.float32)
        max_x = tf.cast(0.0 + labeled_sizes[i][0] / 2.0, dtype=tf.float32)
        # min_y = tf.cast(0.0 - labeled_sizes[i][1] / 2.0, dtype=tf.float32)
        # max_y = tf.cast(0.0 + labeled_sizes[i][1] / 2.0, dtype=tf.float32)
        min_z = tf.cast(0.0 - labeled_sizes[i][2] / 2.0, dtype=tf.float32)
        max_z = tf.cast(0.0 + labeled_sizes[i][2] / 2.0, dtype=tf.float32)

        translation = tf.reshape([labeled_translations[i][0],
                                  labeled_translations[i][2]], [2, 1])

