Implement Matrix Division

[Tortar]

E.g. currently

julia> using Finch

julia> A = fsprand(Float64, 2, 2, 1.);

julia> b = [1.0, 0.1];

julia> b \ A
ERROR: MethodError: no method matching adjoint(::Tensor{SparseCOOLevel{2, Tuple{…}, Vector{…}, Tuple{…}, ElementLevel{…}}})

Closest candidates are:
  adjoint(::Missing)
   @ Base missing.jl:101
  adjoint(::LinearAlgebra.AdjointFactorization)
   @ LinearAlgebra ~/.julia/juliaup/julia-1.10.10+0.x64.linux.gnu/share/julia/stdlib/v1.10/LinearAlgebra/src/factorization.jl:61
  adjoint(::LinearAlgebra.BunchKaufman)
   @ LinearAlgebra ~/.julia/juliaup/julia-1.10.10+0.x64.linux.gnu/share/julia/stdlib/v1.10/LinearAlgebra/src/bunchkaufman.jl:283
  ...

Stacktrace:
 [1] \(x::Vector{Float64}, y::Tensor{SparseCOOLevel{2, Tuple{…}, Vector{…}, Tuple{…}, ElementLevel{…}}})
   @ Base ./operators.jl:625
 [2] top-level scope
   @ REPL[4]:1
Some type information was truncated. Use `show(err)` to see complete types.

julia> using SparseArrays

julia> A = sprand(Float64, 2, 2, 1.);

julia> b = [1.0, 0.1];

julia> b \ A # this works with SparseArrays
1×2 transpose(::Vector{Float64}) with eltype Float64:
 0.316286  0.146342