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View Code? Open in Web Editor NEWEMNLP 2018: Multi-Head Attention with Disagreement Regularization; NAACL 2019: Information Aggregation for Multi-Head Attention with Routing-by-Agreement
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cos_diff_square
cos_diff_square完全没有参与计算
损失函数符号问题
请问在实现代码时，实现的是负的余弦相似度吗
代码里cos_diff = tf.reduce_mean(cos_diff, axis=[-2,-1]) + 1.0最后加的1是什么意思。
cos_diff是表示加了负号的吗，还是没加负号的。论文里面是添加了负号的呀
请问能否添加复现的例子
你好！
我想基于您的工作继续做下去，不知道您是否能够添加一下能够复现的例子呢？
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