import tensorflow as tf

    total_examples = tf.reduce_sum(tf.cast(final_mask, tf.float32))

    # add mask for glabels and cls_pred here
    glabels = tf.boolean_mask(tf.clip_by_value(glabels, 0, FLAGS.num_classes), tf.stop_gradient(final_mask))
    cls_pred = tf.boolean_mask(cls_pred, tf.stop_gradient(final_mask))
    location_pred = tf.boolean_mask(location_pred, tf.stop_gradient(positive_mask))
