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License: MIT License
Implementation of the paper 'Deep Learning of Graph Matching', CVPR 2018.
License: MIT License
Hello,
I tried running the command python main.py --dataset sintel --data_path ~/Desktop/jug-pc-x/05_Repositories/dlgm/
and run into the following error. Any suggestions on what could be the issue? (I have cudatoolkit 9.0 and pytorch 1.1.0 setup in the environment). Thank you for your time!
log path logs/sintel/sintel_seed-7.log
Using 1 GPUs!
Traceback (most recent call last):
File "main.py", line 294, in <module>
model = model.to(args.device)
File "/home/manan/.local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 386, in to
return self._apply(convert)
File "/home/manan/.local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 193, in _apply
module._apply(fn)
File "/home/manan/.local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 199, in _apply
param.data = fn(param.data)
File "/home/manan/.local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 384, in convert
return t.to(device, dtype if t.is_floating_point() else None, non_blocking)
RuntimeError: CUDA error: unknown error
Hello, In the main.py/class VGG_graph_matching/biStochastic_forward() function:
S = v.view(n,m)
for i in range(N):
S = torch.mm(S, torch.mm(torch.ones(1,n),S).inverse())
S = torch.mm(torch.mv(S, torch.ones(m,1)).inverse(), S)
return S
The A.inverse() function need the matrix A to be a square matrix, so this cannot work?
Hi, thanks for your reproducing. And I want to know have you test the code on the datasets in the paper? I mean I will be very appreciated if you could provide more information about this paper.
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