import tensorflow as tf

                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)
