Comments (3)
仔细看下原论文,会发现用于计算损失的label就是[q_1,q_2,...,q_{s-1},o_s,o_{s+1},....,o_s],其中q_1,q_2,...,q_{s-1}就是旧模型对于当前训练图片的输出,o_{s+1},....,o_s就是新类别的label,对于新类别图片,o_{s+1},....,o_s会有一个为1,对于旧类别图片,o_s,o_{s+1},....,o_s全为0
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您好,阅读了您的代码,写得很好,有个疑问,这里的损失您好像只计算了蒸馏的损失,对于论文中的第一项损失似乎没有计算?
新类损失在计算交叉熵的时候关于旧类的列标签都是0,所以直接置换旧类的列计算蒸馏损失。
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Related Issues (11)
- 请问保存旧样本的列表太大了总是报错有什么办法解决吗,或者说您用的GPU的内存是多少G的呢? HOT 7
- 一个小问题 HOT 7
- 问题请教
- 保存模型有误
- How to use my own dataset train my model? HOT 1
- 请教一下,为啥performence这么高? HOT 2
- Hey i see in the requirements, you have Pytorch1.3.0 linux. I run this on Windows and get the following:
- the size of test set
- 想问一下,为什么我复现您的实验结果时,正确率总是会偏低一些
- test module
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