Comments (8)
Hi @parimuns, sorry about the errors here from the older code here. This primal and dual residual look okay, I think the solution being returned here may be good and you can ignore the warning here and let the experiment keep running. How do the results look when you let it keep running?
\cc @priyald17
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@bamos.Thanks for replying. I didn't get any solution. I ran the main.py file for testing in command interface with only 1 run and paramset (2) and then I got the above error. I didn't get any solution.
If there is something in code or folder which I am missing , please let me know.
I
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Hmm, this message should just be a warning that the solver internally hit these NaNs and I think it will return the best solution it got so that the experiment can keep running
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(But I've not run this code in a while and it may be erroring out because of this or some other reason)
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Okay. Is there any new update in the code? Can you pls run this code and help me in this issue. This work is really beneficial to me and will be helpful in my research work
I am trying to contact @priyald17 , but she is not replying.
Thanks a lot.
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Hi @parimuns, should be able to get back to you in the next few days!
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@bamos feel free to resolve this issue here, as there's already an issue open on the e2e-learning repo.
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Ah yeah, let's continue the discussion in locuslab/e2e-model-learning#8 if that's related here. Also the trace there isn't because of this qpth warning
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Related Issues (20)
- Running Error HOT 1
- Query for Equation (7) and (8) in main paper HOT 1
- Infeasibility HOT 1
- Accuracy issues with batches HOT 3
- Accessing dual variables
- What is the mean of print? HOT 2
- Compute the gradient of z with regard to what?
- Canβt solve QP problem when dimension is too high. HOT 3
- How to suppress warning HOT 1
- CVXPY not defined as dependency HOT 2
- how should i installed dpth? HOT 1
- Error in running qpth of e2e-model-learning. AttributeError: module 'torch' has no attribute 'all'
- How to solve a just Linear problem? HOT 1
- Can we solve QP with only equality constraints?
- Missing comma in setup.py HOT 1
- Trivial problem returns NaN
- torch.eig is deprecated for a long time and is being removed HOT 7
- Hard to follow the equation (7), (8) in the OptNet paper HOT 2
- Missing comma in setup.py file uploaded to pipy. HOT 3
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