Comments (1)
I think it's torch issue in windows.
I think solution is to add torch.cuda.current_device()
before any other cuda calls, so you can add to this scripts after import torch
import torch
torch.cuda.current_device()
from dbpn-pytorch.
Related Issues (20)
- What's class D_DownBlock(torch.nn.Module) mean?What's num_stages mean?
- The question about train. HOT 3
- I inserted some layers into dbpn.py,and it can be trained successfully.But failed to test. HOT 1
- I inserted some layers into dbpn.py,and it can be trained successfully.But failed to test.
- How to use correctly
- Question in main.py HOT 1
- normalization for DBPNITER
- cannot download zip file in any way
- I trained and eval got black images HOT 3
- what is the size of input ?
- Can't get the same results as in the article with pretrained model. HOT 2
- About training on GAN HOT 1
- Is it appropriate that the last convolutional layer of DBPN has no activation function?
- Training on other datasets HOT 1
- Did you initialize all models with zero 'a'?
- what's real critertion in main.py?
- Questions about the setting of network when denoising.
- Doubt about the patch_size parameter
- Discriminator pretrained model missing
- no valid convolution algorithms available in CuDNN
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from dbpn-pytorch.