Comments (5)
There should be a performance issue ; it should be really fast for 10 epochs.
The accuracy issue here comes from the number of epochs, you need those at least 1000 epochs for the neural networks to have learned something.
Can you give me your hardware setup ?
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You should try with more epochs. I will be closing this issue for inactivity, don't hesitate to reopen-it.
from causaldiscoverytoolbox.
Actually, we found a small bug that prevented the algorithm to run on the gpu.
I can send you the corrections if you want.
from causaldiscoverytoolbox.
Sure, I would be glad to fix this !
from causaldiscoverytoolbox.
When you want to run on one gpu and not multiple gpus, since you use a multi gpu wrapper, it switched to cpu by default. Therefore, we replaced the wrapper to the default single gpu wrapper.
Hope it helps!
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Related Issues (20)
- SID and SHD do not get the same results as the author of SID HOT 3
- SID error HOT 1
- Is it possible to insert prior knowledge before the causal graph creation? HOT 3
- [BUG] CGNN (Causal Graph Generation) + Usage of multiprocessing with pytorch HOT 1
- R Package (k)pcalg/RCIT is not available. RCIT has to be installed from https://github.com/Diviyan-Kalainathan/RCIT HOT 6
- [BUG] cdt.data.load_dataset('sachs') + one of the returned objects, 'target', is inconsistent with the paper(Sachs,etc 2005) HOT 1
- [fileNotFoundError: [Errno 2]] cdt.causality.graph.LiNGAM + No such file or directory: 'C:\\anaconda\\lib\\site-packages\\cdt\\utils\\R_templates\\test_import.R' HOT 1
- GIES targets and target.index parameter needs to be exposed HOT 2
- [BUG] orient_graph removes some of the edges
- [Question] What does the causal score in the pairwise model really indicate?
- ImportError: R Package (k)pcalg/RCIT is not available. HOT 3
- [BUG] CGNN run() Wrong way to calculate the score HOT 1
- FloatingPointError: The system is too ill-conditioned for this solver. The system is too ill-conditioned for this solver HOT 1
- Help! HOT 1
- Can PC algorithm be used for causal discovery under mixed types of data๏ผ
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