Implement missing LinearAlgebra wrappers and add support for uplo parameter

[danielwe]

Finally got around to #46 (long since closed but never fixed)

Bonus: I noticed that the existing support for Symmetric was buggy as it didn't support the uplo parameter, i.e., adapt_structure would do the wrong thing with an instance of Symmetric with non-default uplo. So fixed that too for Symmetric and Hermitian.

[danielwe]

Reading the docstring for WrappedArray, shouldn't the {D,Bid,Trid,SymTrid}iagonal wrappers use the Src type parameter rather than Dst? They wrap 1-3 vectors and turn them into a matrix, so the wrapper has different dimensionality from the parent(s).

In this PR I just followed the pattern already in use for {D,Trid}iagonal, so I used Dst for {Bi,SymTri}diagonal.

[maleadt]

Thanks for the PR!

Reading the docstring for WrappedArray, shouldn't the {D,Bid,Trid,SymTrid}iagonal wrappers use the Src type parameter rather than Dst? They wrap 1-3 vectors and turn them into a matrix, so the wrapper has different dimensionality from the parent(s).

It seems that way, yes. Can you come up with a test to make sure this doesn't regress?

[danielwe]

I think that should do it. Testing that all wrapped arrays are subtypes of the appropriate dimension-specific AnyCustomArray{T,N} union.

[maleadt]

Thanks. Did you validate these changes with any of the packages that rely on Adapt.jl (like CUDA.jl)?

[codecov[bot]]

Codecov Report

Attention: 12 lines in your changes are missing coverage. Please review.

Comparison is base (5063b0f) 83.33% compared to head (d29a1e8) 77.77%. Report is 6 commits behind head on master.

Additional details and impacted files

@@            Coverage Diff             @@
##           master      #51      +/-   ##
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- Coverage   83.33%   77.77%   -5.56%     
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  Files           6        6              
  Lines          72       81       +9     
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+ Hits           60       63       +3     
- Misses         12       18       +6     

Files	Coverage Δ
src/wrappers.jl	64.44% <53.84%> (-7.78%)	:arrow_down:

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[danielwe]

Thanks for the reminder. The entire CUDA.jl test suite passes on my end.

Looks like UpperHessenberg only exists from 1.3 onwards. Is it important to maintain support for 1.2?

[maleadt]

No. We can bump the requirement to the latest LTS, 1.6, and then also include the other recent versions that are missing from the CI roster (1.6, 1.7, 1.8-beta1).

[mtfishman]

Can this be merged? I just hit a scalar indexing issue caused by missing adapt rules for Hermitian.

[mtfishman]

Thanks!

[maleadt]

Sorry, reverting this due to CUDA.jl breakage: https://github.com/JuliaGPU/Adapt.jl/pull/70#issue-1964143921