Closed mikirui closed 5 years ago
It seems it can be solved by the modification below:
In network/components.py
AdaIn()
function:
std_feat = (torch.std(feature, dim=2) + self.eps).view(B, C, 1)
can be written as:
std_feat = torch.var(feature, dim=2) + self.eps
std_feat = std_feat.sqrt().view(B, C, 1)
Hi @MrCaracara ,
I try your latest code, but found the training would easily get Nan during about first 40 - 50 iteration in the first epoch, would you have any suggestions for solving this?