Comments (3)
顺便还有一个细节问题,我还想请教一下,代码里有一句 hash_codes = hash_codes.detach()
为什么要加上这一句呢?detach()是用于切断梯度传播的,这里加上这一句是要切断此处的梯度传播吗?
我试过把这句注释掉,代码也能正常训练,求解。
from non-local-sparse-attention.
Hi, 这里使用softmax的motivation是来源于hash操作的随机性。这段代码的意思是衡量每个round所分到bucket元素之间的亲和力,如果分到的bucket元素更related,那么那个round的权重更大。supplementary里有visualization,可以参考理解。1x1conv 是learnable的,我认为应该也是可行的。detach应该可以去掉,hashcode并没有gradient回传,感谢指出。
from non-local-sparse-attention.
Hi, 这里使用softmax的motivation是来源于hash操作的随机性。这段代码的意思是衡量每个round所分到bucket元素之间的亲和力,如果分到的bucket元素更related,那么那个round的权重更大。supplementary里有visualization,可以参考理解。1x1conv 是learnable的,我认为应该也是可行的。detach应该可以去掉,hashcode并没有gradient回传,感谢指出。
好的,感谢回复
from non-local-sparse-attention.
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