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Description
Here is a super stripped down MWE.
In the example below, I would expect M'*x to return a Vector{Float64} equivalent to [2.0]. But it looks like the fact that the matrix elements themselves should be adjoint is lost somewhere along the way to generic_matvecmul, which attempts straight multiplication of two vectors, rather than taking their inner product.
julia> M = [[[1.0]];;]
1×1 Matrix{Vector{Float64}}:
[1.0]
julia> x = [[[2.0]];]
1-element Vector{Vector{Float64}}:
[2.0]
julia> M'*x
ERROR: MethodError: no method matching *(::Vector{Float64}, ::Vector{Float64})
Closest candidates are:
*(::Any, ::Any, ::Any, ::Any...) at /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/base/operators.jl:655
*(::StridedMatrix{T}, ::StridedVector{S}) where {T<:Union{Float32, Float64, ComplexF32, ComplexF64}, S<:Real} at /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/LinearAlgebra/src/matmul.jl:44
*(::StridedVecOrMat, ::Adjoint{<:Any, <:LinearAlgebra.LQPackedQ}) at /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/LinearAlgebra/src/lq.jl:266
...
Stacktrace:
[1] generic_matvecmul!(C::Vector{Union{}}, tA::Char, A::Matrix{Vector{Float64}}, B::Vector{Vector{Float64}}, _add::LinearAlgebra.MulAddMul{true, true, Bool, Bool})
@ LinearAlgebra /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/LinearAlgebra/src/matmul.jl:745
[2] mul!
@ /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/LinearAlgebra/src/matmul.jl:129 [inlined]
[3] mul!
@ /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/LinearAlgebra/src/matmul.jl:275 [inlined]
[4] *(adjA::Adjoint{Adjoint{Float64, Vector{Float64}}, Matrix{Vector{Float64}}}, x::Vector{Vector{Float64}})
@ LinearAlgebra /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/LinearAlgebra/src/matmul.jl:113
[5] top-level scope
@ REPL[152]:1
In contrast, these three other similar operations, seem to work correctly:
julia> M'*M
1×1 Matrix{Float64}:
1.0
julia> x'*x
4.0
julia> N = [[[1.0]'];;]
1×1 Matrix{Adjoint{Float64, Vector{Float64}}}:
[1.0;;]
julia> N*x
1-element Vector{Float64}:
2.0
julia> versioninfo()
Julia Version 1.7.2
Commit bf53498635 (2022-02-06 15:21 UTC)
Platform Info:
OS: macOS (x86_64-apple-darwin19.5.0)
CPU: Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-12.0.1 (ORCJIT, skylake)
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