how to implement Feature level Cutmix?
See original GitHub issueThanks for your sharing.
But I have a question about how to implement ‘ResNet-50 + Feature Cutmix’, since if we just use the replace operation like we did in the image level cutmix, the gradients will not be back propagated.
Actually, I encountered such problem:
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation
Could you give me some suggestions or hints to solve this feature level cutmix problem?
Issue Analytics
- State:
- Created 4 years ago
- Comments:5
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@EmmaW8 In our implementation, we put this cutmix operation into
forward
function ofresnet.py
model. For example, Feature CutMix after layer 1 is,From our experience,
inplace=True
option may cause the runtime error, so try withinplace=False
.Thanks!
@zzs1994
We do it in the same way of image-level CutMix.