No clamp for input after Gaussian data augumentation?
Opened this issue · 1 comments
xinghua-qu commented
# augment inputs with noise
inputs = inputs + torch.randn_like(inputs, device='cuda') * noise_sd
Line 109 in train.py
.
If there is no torch.clamp()
after line 109, it is possible that the input image will exceed its allowed pixel value range (i.e., [0,1]
)
vietvo89 commented
I have the same question. Why the implementation of this approach does not clip the image within the range [0,1]
. Without clarification, I think it is a pitfall. When using torch.clamp()
, the results of the paper are incorrect.