Chris Elrod

> I've been meaning to re-write how it handles finalisers `|> (_ / n)` Ah, yeah, it doesn't like anonymous functions: ```julia julia> LoopVectorization.@avx unroll = 0 for x =...

Should be fixed by https://github.com/JuliaSIMD/LoopVectorization.jl/commit/a97368d10a8361f3bc8e6179247af6defdc8c24a

Should've been 14 days ago. So you should be able to close this now.

Could check array sizes vs number of cores * L2 cache size per core.

Extending LV to do smart Octavian-style blocking also wouldn't be all that hard, so I think effort would be better spent on the right solution than more hacks to better...

The warning will only print once by default. You can make it appear more often via `@turbo warn_check_args=5`, which will let it print 5 times (accepts any value that can...

> What are the types of the arrays here? I should probably have LV's warnings print those.

> with an AxisKeys.jl `KeyedArray` wrapper around them. Okay, that's why. ```julia julia> using LoopVectorization, AxisKeys julia> A = KeyedArray(rand(2,10), ([:a, :b], 10:10:100)) 2-dimensional KeyedArray(...) with keys: ↓ 2-element Vector{Symbol}...

If it's just a simple wrapper, then all that is needed is ```julia ArrayInterface.parent_type(::Type{ using AxisKeys, ArrayInterface, LoopVectorization julia> A = KeyedArray(rand(2,10), ([:a, :b], 10:10:100)) 2-dimensional KeyedArray(...) with keys: ↓...

On my "i9 whatever", Tullio is 5x faster: ```julia julia> using OMEinsum, Tullio julia> contract_WA_ein(W, a::AbstractVector{ contract_WA(W, a::AbstractVector{ W = rand(Float32, 18, 1024, 1024); julia> x = rand(Float32, 1024, 64);...