import tensorflow as tf


    geq = tf.cast((tgt1 - tgt2) > 0, tf.bool)
    tgt_larg = tf.where(geq, tgt1, tgt2)
    tgt_small = tf.where(geq, tgt2, tgt1)
    pred_larg = tf.where(geq, pred1, pred2)
    pred_small = tf.where(geq, pred2, pred1)

    loss = tf.maximum(0.0, ((tgt_larg - tgt_small) - (pred_larg - pred_small)))
    loss = tf.reduce_mean(loss)
    return loss


def apply_optimizers(objectives, trainer, config):
    # Make sure all losses are computed and apply loss scales.
    processed = []
    values = [ob.value for ob in objectives]
