chunkmask tests
julia> A = Tensor(Dense(Dense(Element(0.0))), 15, 3)
15×3 Tensor{DenseLevel{Int64, DenseLevel{Int64, ElementLevel{0.0, Float64, Int64, Vector{Float64}}}}}:
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
julia> m = Finch.chunkmask(15, 5)
15×3 Finch.ChunkMask{Int64}:
 1  0  0
 1  0  0
 1  0  0
 1  0  0
 1  0  0
 0  1  0
 0  1  0
 0  1  0
 0  1  0
 0  1  0
 0  0  1
 0  0  1
 0  0  1
 0  0  1
 0  0  1
julia> @finch begin
        for i = _
            for j = _
                A[j, i] = m[j, i]
            end
        end
    end
NamedTuple()
julia> AsArray(A)
15×3 Tensor{DenseLevel{Int64, DenseLevel{Int64, ElementLevel{0.0, Float64, Int64, Vector{Float64}}}}}:
 1.0  0.0  0.0
 1.0  0.0  0.0
 1.0  0.0  0.0
 1.0  0.0  0.0
 1.0  0.0  0.0
 0.0  1.0  0.0
 0.0  1.0  0.0
 0.0  1.0  0.0
 0.0  1.0  0.0
 0.0  1.0  0.0
 0.0  0.0  1.0
 0.0  0.0  1.0
 0.0  0.0  1.0
 0.0  0.0  1.0
 0.0  0.0  1.0
julia> A = Tensor(Dense(Dense(Element(0.0))), 14, 3)
14×3 Tensor{DenseLevel{Int64, DenseLevel{Int64, ElementLevel{0.0, Float64, Int64, Vector{Float64}}}}}:
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
 0.0  0.0  0.0
julia> m = Finch.chunkmask(14, 5)
14×3 Finch.ChunkMask{Int64}:
 1  0  0
 1  0  0
 1  0  0
 1  0  0
 1  0  0
 0  1  0
 0  1  0
 0  1  0
 0  1  0
 0  1  0
 0  0  1
 0  0  1
 0  0  1
 0  0  1
julia> @finch begin
        for i = _
            for j = _
                A[j, i] = m[j, i]
            end
        end
    end
NamedTuple()
julia> AsArray(A)
14×3 Tensor{DenseLevel{Int64, DenseLevel{Int64, ElementLevel{0.0, Float64, Int64, Vector{Float64}}}}}:
 1.0  0.0  0.0
 1.0  0.0  0.0
 1.0  0.0  0.0
 1.0  0.0  0.0
 1.0  0.0  0.0
 0.0  1.0  0.0
 0.0  1.0  0.0
 0.0  1.0  0.0
 0.0  1.0  0.0
 0.0  1.0  0.0
 0.0  0.0  1.0
 0.0  0.0  1.0
 0.0  0.0  1.0
 0.0  0.0  1.0

