coref_model.py 文件源码

def softmax_loss(self, antecedent_scores, antecedent_labels):
    gold_scores = antecedent_scores + tf.log(tf.to_float(antecedent_labels)) # [num_mentions, max_ant + 1]
    marginalized_gold_scores = tf.reduce_logsumexp(gold_scores, [1]) # [num_mentions]
    log_norm = tf.reduce_logsumexp(antecedent_scores, [1]) # [num_mentions]
    return log_norm - marginalized_gold_scores # [num_mentions]