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Randomised_CP function throws a Singular Matrix error #531
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Is there a bound on the value of rank for a given tensor?
(Btw, I checked the arXiv paper again today and could not find the tensor rank section any more. Not sure why but I am trying to find the version I read a few days ago.) Regarding the singular matrix error, specifically
In numpy/linalg/linalg.py
It seems that the singular matrix error occurs when
Inspecting the calculation steps:
There can be multiple causes for |
chaoyihu is right about what the issues is here. I'll elaborate a bit further. The issue is not with the choice of rank, but rather the choice of number of samples ( To see why this is a problem, suppose In practice, since the sampling is done uniformly at random, even if As a side note, |
Steps or Code to Reproduce
Error
The snippet runs successfully when rank==1, however fails for all other values. Is there a bound on the value of rank for a given tensor?
Versions
numpy version : 1.25.2
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