import tensorflow as tf

          loss += self.helper_dst.calc_loss(logits, logits_dst)
        tf.summary.scalar('loss', loss)
        for key, value in metrics.items():
          tf.summary.scalar(key, value)

        # learning rate schedule
        self.global_step = tf.train.get_or_create_global_step()
        lrn_rate, self.nb_iters_train = self.setup_lrn_rate(self.global_step)

        # overall pruning ratios of trainable & maskable variables
        pr_trainable = calc_prune_ratio(self.trainable_vars)
        pr_maskable = calc_prune_ratio(self.maskable_vars)
