Comments (2)
Hi, thanks for visiting this repository.
Self.feature_num corresponds to the number of dimensions of deep features obtained from the network, which is usually determined by the width of the model, and differs among different network structures. Basic ResNets for CIFAR share the same width while differ in depth. That's why self.feature_num remains the same.
Sincerely, Yulin Wang.
from isda-for-deep-networks.
ok now it is clear.
Thanks
from isda-for-deep-networks.
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from isda-for-deep-networks.