import tensorflow as tf

              1) for i in range(num_boxes)], axis=0)
          rotations_y = tf.reshape(rotations_y, [-1, 1])
          predicted_boxes = tf.concat([detections['translations_3d'],
                                       detections['sizes_3d'],
                                       rotations_y], axis=1)

        labeled_classes = tf.cast(sample['groundtruth_valid_classes'], tf.int64)
        predicted_classes = tf.cast(detections['detection_classes'], tf.int64)
        confidences = detections['detection_scores']
        metric.update(scene_id, labeled_boxes, labeled_classes, predicted_boxes,
                      predicted_classes, confidences)
      elif isinstance(metric, IoUMetric):
        classes = sample['classes']
        mesh_names = sample['mesh_names']
