Information
- Paper topic: Images
- Software type: Code
- Able to run a replicability test: True
- Replicability score: 5
- Software language: Python
- License: unspecified
- Build mechanism: Not applicable (python, Matlab..)
- Dependencies: CUDA / CuDNN / sklearn / numpy / torchvision / matplotlib
- Documentation score {0,1,2}: 1
- Reviewer: David Coeurjolly <david.coeurjolly@liris.cnrs.fr>
- Time spent for the test (build->first run, timeout at 100min): 20min
Source code information
Comments
sklearn dependency was not explicitly mentioned in the README. To make the code working on recent pytorch, I needed to update in line of code :
@@ -92,7 +92,7 @@ class vgg19(nn.Module):
deconvolved_feature_forward = self.forward(level=src_level, start_level=dst_level, set_as_var = False)
loss_perceptual = criterionPerceptual(deconvolved_feature_forward, src_layer)
loss_perceptual.backward()
- error = loss_perceptual.data[0]
+ error = loss_perceptual.item()
self.update_last_losses(error)
if (i % 3 == 0) and (print_errors == True):
print("error: ", error)