Multiple installations of CuPy package has been detected.
You should select only one package from from ['cupy-cuda102', 'cupy-cuda101', 'cupy-cuda100', 'cupy-cuda92', 'cupy-cuda91', 'cupy-cuda90', 'cupy-cuda80', 'cupy'].
Follow these steps to resolve this issue:
pip list to list CuPy packages installed
pip uninstall <package name> to uninstall all CuPy packages
pip install <package name> to install the proper one
'''.format(name=name, pkgs=pkgs))
loading filelist... done
setup model... done
check forward path... done
starting processes of dataset sampler... done
epoch: 0
inner epoch: 0
best loss on training dataset: 0.002381
best score on validation dataset: PSNR 22.072546 dB
elapsed time: 881.055754 sec
inner epoch: 1
best loss on training dataset: 0.001941
best score on validation dataset: PSNR 22.579106 dB
elapsed time: 103.186740 sec
inner epoch: 2
best loss on training dataset: 0.001810
best score on validation dataset: PSNR 22.679653 dB
elapsed time: 97.545877 sec
inner epoch: 3
best loss on training dataset: 0.001732
best score on validation dataset: PSNR 23.013222 dB
elapsed time: 91.364418 sec
epoch: 1
inner epoch: 0
best score on validation dataset: PSNR 23.169959 dB
elapsed time: 106.030671 sec
inner epoch: 1
best loss on training dataset: 0.001652
best score on validation dataset: PSNR 23.181128 dB
elapsed time: 102.384226 sec
inner epoch: 2
best loss on training dataset: 0.001593
best score on validation dataset: PSNR 23.337347 dB
elapsed time: 99.998622 sec
inner epoch: 3
best loss on training dataset: 0.001545
elapsed time: 91.267800 sec
epoch: 2
inner epoch: 0
best score on validation dataset: PSNR 23.427455 dB
elapsed time: 106.444332 sec
inner epoch: 1
elapsed time: 103.891084 sec
inner epoch: 2
best loss on training dataset: 0.001530
elapsed time: 98.481055 sec
inner epoch: 3
best loss on training dataset: 0.001489
best score on validation dataset: PSNR 23.479888 dB
elapsed time: 91.023230 sec
epoch: 3
inner epoch: 0
best score on validation dataset: PSNR 23.528935 dB
elapsed time: 106.155661 sec
inner epoch: 1
elapsed time: 103.248413 sec
inner epoch: 2
best loss on training dataset: 0.001455
elapsed time: 98.362952 sec
inner epoch: 3
best loss on training dataset: 0.001421
learning rate decay: 0.000225
elapsed time: 90.741462 sec
epoch: 4
inner epoch: 0
best score on validation dataset: PSNR 23.533943 dB
elapsed time: 105.805502 sec
inner epoch: 1
best score on validation dataset: PSNR 23.573726 dB
elapsed time: 103.978917 sec
inner epoch: 2
best score on validation dataset: PSNR 23.623575 dB
elapsed time: 99.085195 sec
inner epoch: 3
best loss on training dataset: 0.001405
best score on validation dataset: PSNR 23.658209 dB
elapsed time: 91.353107 sec
epoch: 5
inner epoch: 0
best score on validation dataset: PSNR 23.710338 dB
elapsed time: 106.360211 sec
inner epoch: 1
best score on validation dataset: PSNR 23.714681 dB
elapsed time: 104.392316 sec
inner epoch: 2
elapsed time: 99.168070 sec
inner epoch: 3
best loss on training dataset: 0.001383
elapsed time: 91.488422 sec
epoch: 6
inner epoch: 0
best score on validation dataset: PSNR 23.732231 dB
elapsed time: 107.400784 sec
inner epoch: 1
best score on validation dataset: PSNR 23.761270 dB
elapsed time: 105.255023 sec
inner epoch: 2
elapsed time: 99.553206 sec
inner epoch: 3
elapsed time: 91.538299 sec
epoch: 7
inner epoch: 0
best score on validation dataset: PSNR 23.764517 dB
elapsed time: 106.978499 sec
inner epoch: 1
elapsed time: 104.257074 sec
inner epoch: 2
elapsed time: 99.090099 sec
inner epoch: 3
best loss on training dataset: 0.001361
learning rate decay: 0.000203
elapsed time: 91.054147 sec
epoch: 8
inner epoch: 0
best score on validation dataset: PSNR 23.816657 dB
elapsed time: 105.482888 sec
inner epoch: 1
best score on validation dataset: PSNR 23.883949 dB
elapsed time: 104.894173 sec
inner epoch: 2
elapsed time: 99.114435 sec
inner epoch: 3
elapsed time: 90.749769 sec
epoch: 9
inner epoch: 0
learning rate decay: 0.000182
elapsed time: 92.891063 sec
inner epoch: 1
elapsed time: 90.760490 sec
inner epoch: 2
elapsed time: 90.826175 sec
inner epoch: 3
best loss on training dataset: 0.001345
learning rate decay: 0.000164
elapsed time: 90.922554 sec`
I read that the PSNR for the pretrained model is 30+, is 23dB too low? Maybe my training set is bad? My training set consists of mostly black and white images, specifically Japanese comic book pages, if that matters.
'''.format(name=name, pkgs=pkgs))
epoch: 0
inner epoch: 0
inner epoch: 1
inner epoch: 2
inner epoch: 3
epoch: 1
inner epoch: 0
inner epoch: 1
inner epoch: 2
inner epoch: 3
epoch: 2
inner epoch: 0
inner epoch: 1
inner epoch: 2
inner epoch: 3
epoch: 3
inner epoch: 0
inner epoch: 1
inner epoch: 2
inner epoch: 3
epoch: 4
inner epoch: 0
inner epoch: 1
inner epoch: 2
inner epoch: 3
epoch: 5
inner epoch: 0
inner epoch: 1
inner epoch: 2
inner epoch: 3
epoch: 6
inner epoch: 0
inner epoch: 1
inner epoch: 2
inner epoch: 3
epoch: 7
inner epoch: 0
inner epoch: 1
inner epoch: 2
inner epoch: 3
epoch: 8
inner epoch: 0
inner epoch: 1
inner epoch: 2
inner epoch: 3
epoch: 9
inner epoch: 0
inner epoch: 1
inner epoch: 2
inner epoch: 3
I read that the PSNR for the pretrained model is 30+, is 23dB too low? Maybe my training set is bad? My training set consists of mostly black and white images, specifically Japanese comic book pages, if that matters.