import tensorflow as tf

      # model definition - distilled model
      if FLAGS.enbl_dst:
        logits_dst = self.helper_dst.calc_logits(sess, images)

      # model definition - weight-sparsified model
      with tf.variable_scope(self.model_scope):
        # loss & extra evaluation metrics
        logits = self.forward_train(images)
        self.maskable_var_names = [var.name for var in self.maskable_vars]
        loss, metrics = self.calc_loss(labels, logits, self.trainable_vars)
