Hi,all
I’m trying to re-implement some network to classify SVHN data according to this paper.
‘Dropout: A Simple Way to Prevent Neural Networks from Overfitting’ (http://jmlr.org/papers/volume15/srivastava14a.old/srivastava14a.pdf 6)
In this paper, I have 2 questions.


This paper said they use 3 conv layer and 2 fc layer. but the number of  dropout p is 6. (0.9, 0.75, 0.75, 0.5, 0.5, 0.5).
Can anyone explain about this ?


What is the max-norm constarint and how can use this in pytorch?



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