ner_model.py 文件源码

def add_loss_op(self):
        """Defines the loss"""
        if self.config.use_crf:
            log_likelihood, trans_params = tf.contrib.crf.crf_log_likelihood(
                    self.logits, self.labels, self.sequence_lengths)
            self.trans_params = trans_params # need to evaluate it for decoding
            self.loss = tf.reduce_mean(-log_likelihood)
        else:
            losses = tf.nn.sparse_softmax_cross_entropy_with_logits(
                    logits=self.logits, labels=self.labels)
            mask = tf.sequence_mask(self.sequence_lengths)
            losses = tf.boolean_mask(losses, mask)
            self.loss = tf.reduce_mean(losses)

        # for tensorboard
        tf.summary.scalar("loss", self.loss)