Thinklab-SJTU/LinSATNet

Marginal distributions are not matched

Yansa2000 opened this issue · 4 comments

Yansa2000 commented

Hello, when I used LinSATNet to optimize a traffic engineering problem, I encountered this issue:
line 146 in ./LinSATNet/linsat.py

if not torch.all(torch.abs(_sum_dim(A, dim=-1) - b.sum(dim=-1)) < 1e-4):
        raise RuntimeError('Marginal distributions are not matched! Please report this issue on GitHub.')

I wonder what it means and if there exists a method to cope with this issue. Thank you very much!

rogerwwww commented

Hi, thank you so much for your interest in the code. Can you please provide a minimal example for this issue? I think providing the A b C d E f matrices will be fine.

Yansa2000 commented

I did not use E and f. The A, b and C, d I used are as follows:
https://github.com/saYan502/TE-problem

The input x here denotes the traffic on each path. A and b provide capacity constraints while C and d offer a lower bound of x.

rogerwwww commented

I think one point worth noting is that all x is assumed to be in the range [0, 1]. So all your constraints with d == 0 is unnecessary, and the other C, d constraints seem to be unsatisfiable. I will spend some time adding error/warnings to the code. For your specific tasks, you can define a multiplier to scale the value

Yansa2000 commented

Thank you very much for your explanation. I understand now.

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