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🤖 [master] Bump the LinearAlgebra stdlib from 07725da to 5d3d02a #58242

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Stdlib: LinearAlgebra
URL: https://github.com/JuliaLang/LinearAlgebra.jl.git
Stdlib branch: master
Julia branch: master
Old commit: 07725da
New commit: 5d3d02a
Julia version: 1.13.0-DEV
LinearAlgebra version: 1.12.0(Does not match)
Bump invoked by: @jishnub
Powered by: BumpStdlibs.jl

Diff: JuliaLang/LinearAlgebra.jl@07725da...5d3d02a

$ git log --oneline 07725da..5d3d02a
5d3d02a Branch on Bool alpha in bidiag matmul (#1257)
e4e8c19 Only `@noinline` error path in `matmul_size_check` (#1310)
bfab205 Band indexing for adj/trans (#1299)
e7a8a15 Use method deletion instead of custom sysimage (#1312)
88dba5d `setindex!` with `BandIndex` (#1259)
8e6dcfb correctly forward `io` argument in `show` method (#1306)
799ca1a Add `diagm` example (#1298)
a145117 Check types locally in triangular tests (#1308)
2e428a5 Reduce allocations in triangular tests (#1309)
d550716 correctly forward `io` argument in `show` method
fd115f4 Fewer `MulAddMul` branches in `Diagonal`-triangular mul (#1272)
e30c9c3 Precise `axes` in `generic_mattrimul!` (#1300)
0a84e1d Inline `generic_matmatmul!` branch in strided triangular matmul (#1262)
a3c2681 Fix docstring for reflectorApply! (#1301)
b5cc56a Test two combinations in triangular test sets (#1294)
d451800 fix herk with complex α (#1297)
537ee46 Zero padding
14ac1f7 Add `diagm` example
27de9e9 Unaliasing and short-circuiting in `copytrito!` (#1287)
a32a281 add generic syrk/herk (#1249)
cab0dc6 Compile-time check for zero alpha in matmul (#1293)
78e6156 Treat real transposes like adjoint in internal dispatch (#1296)
d21ad8c Matrix constructor for triangular (#1282)
dcf579c Multiplication instead of division in triangular eigen test (#1295)

@jishnub
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jishnub commented Apr 27, 2025

@KristofferC The test failures here are because LinearAlgebra isn't being precompiled. I guess the issue was avoided on the LinearAlgebra repo by specifying the --compiled-modules=existing flag. I wonder if there is a way around the failure here, as we may skip the pruning?

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I wonder if there is a way around the failure here, as we may skip the pruning?

We should detect when it is run here and not do it.

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3 participants