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RowVector, pinv, and quasi-division (#23067)
* Make pinv(::AbstractVector) return a RowVector Also broaden from StridedVector to AbstractVector while at it and don't employ full matrix SVD. * Add pinv(::RowVector) * Add /(::Number, ::AbstractVector) Also start testing consistency between division and multiplication with pseudo-inverse involving vectors. * Add \(::RowVector, ::RowVector), returning a scalar * Fix \ for AbstractVector LHS Let \(::AbstractVector, ::AbstractMatrix) return a RowVector and \(::AbstractVector, ::AbstractVector) return a scalar.
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Executing the daily benchmark build, I will reply here when finished:
@nanosoldier
runbenchmarks(ALL, isdaily = true)
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Your benchmark job has completed - possible performance regressions were detected. A full report can be found here. cc @ararslan
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I guess,
BaseBenchmarks.jl
usectranspose
(now deprecated), should be the reason for the sparse transpose regression.f1d3556
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Yes. I think that is the case. Maybe we can update
BaseBenchmarks
to use'
instead.f1d3556
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JuliaCI/BaseBenchmarks.jl#102 (
'
would be smart, but does not work for the in-placeadjoint
)