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CUDA error while calculating loss
I was trying to run train_RAPFT_step1 in cityscapes dataset. While trying to run the code, I am getting error saying CUDA error: device-side assert triggered. I tried using CUDA_LAUNCH_BLOCKING=1 and it is showing the following error.
Hi! A great work. When will the code be released?
Confusion matrices of the Figure A6.
code for performing model fine-tuning
I'm sorry to disturb you, but if possible, could you provide the code for performing model fine-tuning? I'm sorry, but it seems I can't find the relevant code in the file list. Thank you very much for your help.
About weight_IDD/BDD/city
Hi, @prachigarg23
Thanks for your nice work!
However, how did you calculate weight_IDD, weight_BDD, weight_city in your code like below?
Where can I earn these weights?
(I want to change ERFNet to other segmentation models)
weight_IDD = torch.tensor([3.235635601598852, 6.76221624390441, 9.458242359884549, 9.446818215454014, 9.947040673126763, 9.789672819856547, 9.476665808564432, 10.465565126694731, 9.59189547383129,
7.637805282159825, 8.990899026692638, 9.26222234098628, 10.265657138809514, 9.386517631614392, 8.357391489170013, 9.910382864314824, 10.389977663948363, 8.997422571963602,
10.418070541191673, 10.483262606962834, 9.511436923349441, 7.597725385711079, 6.1734896019878205, 9.787631041755187, 3.9178330193378708, 4.417448652936843, 10.313160683418731])
weight_BDD = torch.tensor([3.6525147483016243, 8.799815287822142, 4.781908267406055, 10.034828238618045, 9.5567865464289, 9.645099012085169, 10.315292989325766, 10.163473632969513, 4.791692009441432,
9.556915153488912, 4.142994047786311, 10.246903827488143, 10.47145010979545, 6.006704177894196, 9.60620532303246, 9.964959813857726, 10.478333987902301, 10.468010534454706,
10.440929141422366, 3.960822533003462])
weight_city = torch.tensor([2.8159904084894922, 6.9874672455551075, 3.7901719017455604, 9.94305485286704, 9.77037625072462, 9.511470001589007, 10.310780572569994, 10.025305236316246, 4.6341256102158805,
9.561389195953845, 7.869695292372276, 9.518873463871952, 10.374050047877898, 6.662394711556909, 10.26054487392723, 10.28786101490449, 10.289883605859952, 10.405463349170795,
10.138502340710136, 5.131658171724055])
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