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I also noticed a small mistake in the PR that added LinearAlgebra.svd support. For a matrix, svd returns U, S as a vector, V as the adjoint of a matrix (Vᴴ). So I guess we want to replicate this, and thus have something like U, S, Vᴴ = svd_compact(t) # or svd_full
return U, diagview(S), adjoint(Vᴴ)Maybe you can also include this in the current PR? |
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Added a small fix to address @Jutho's comment (hopefully) |
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I'm slightly worried that the diagview will fail for the full case, since we don't return a diagonal in that case. LinearAlgebra actually outputs things that don't multiply correctly there, and I'm not sure how we want to handle this? |
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I guess this is why we didn't overload the linearalgebra methods 😂 |
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Should I just add a test for full and see what happens? |
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Alternatively: is anyone actually using these overloads? Can we just remove them, for now? |
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I'm happy to remove them again, definitely is independent of this PR |
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Since they don't seem to be tested anyway I say kill em all!!! |
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I think there's still an entry in the changelog that can be deleted again, afterwards I would just merge this
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Nightly failures are the same Zygote stuff as usual. Is this good to go? |
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Noticed some test failures in #325 due to the diagonal algorithms not returning a SectorVector, so I fixed that, added some tests and then found some other inconsistencies: svd_vals was sorting the entire SectorVector, effectively mixing up the blocks.
Both of these are fixed here.