import tensorflow as tf

            end_loss = tf.nn.softmax_cross_entropy_with_logits(
                logits=self.logits2, labels=end_label)
            self.loss = tf.reduce_mean(start_loss + end_loss)
        else:
            start_loss = focal_loss(tf.nn.softmax(self.logits1, -1), start_label)
            end_loss = focal_loss(tf.nn.softmax(self.logits2, -1), end_label)
            self.loss = tf.reduce_mean(start_loss + end_loss)
        self.logger.info("loss type %s" % self.config.loss_type)

        self.all_params = tf.trainable_variables()
