Hi,
I am curious about if this is still the case that leveraging scipy sparse solver is a better option.
Which means that if I want to compute sparse matrix in my own Function, I first convert the tensor to scipy sparse matrix, and convert back to torch tensor ?
The main reason I am asking, is that I am searching for method to do something like the dense matrix case with btrifact() and btrisolve().
I am writing a layer that will solve several linear system, with different patterns across them.
Wondering if there is nice suggestion or anything I can do to help build up some relevant functions?
thx!