[BlockSparseArrays] Update to BlockArrays v1.1, fix some issues with nested views

[mtfishman]

Fixes some issues with nested views, for example this now works:

julia> using BlockArrays: Block

julia> using NDTensors.BlockSparseArrays: BlockSparseArray

julia> a = BlockSparseArray{Float64}([2, 3], [2, 3])
typeof(axes) = Tuple{BlockArrays.BlockedOneTo{Int64, Vector{Int64}}, BlockArrays.BlockedOneTo{Int64, Vector{Int64}}}

Warning: To temporarily circumvent a bug in printing BlockSparseArrays with mixtures of dual and non-dual axes, the types of the dual axes printed below might not be accurate. The types printed above this message are the correct ones.

2×2-blocked 5×5 BlockSparseArray{Float64, 2, Matrix{Float64}, NDTensors.SparseArrayDOKs.SparseArrayDOK{Matrix{Float64}, 2, NDTensors.BlockSparseArrays.BlockZero{Tuple{BlockArrays.BlockedOneTo{Int64, Vector{Int64}}, BlockArrays.BlockedOneTo{Int64, Vector{Int64}}}}}, Tuple{BlockArrays.BlockedOneTo{Int64, Vector{Int64}}, BlockArrays.BlockedOneTo{Int64, Vector{Int64}}}}:
 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> b = @view a[[Block(2), Block(1)], [Block(2), Block(1)]]
5×5 view(::BlockSparseArray{Float64, 2, Matrix{Float64}, NDTensors.SparseArrayDOKs.SparseArrayDOK{Matrix{Float64}, 2, NDTensors.BlockSparseArrays.BlockZero{Tuple{BlockArrays.BlockedOneTo{Int64, Vector{Int64}}, BlockArrays.BlockedOneTo{Int64, Vector{Int64}}}}}, Tuple{BlockArrays.BlockedOneTo{Int64, Vector{Int64}}, BlockArrays.BlockedOneTo{Int64, Vector{Int64}}}}, [3, 4, 5, 1, 2], [3, 4, 5, 1, 2]) with eltype Float64 with indices BlockArrays.BlockedOneTo([3, 5])×BlockArrays.BlockedOneTo([3, 5]):
 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> b[Block(1, 1)] .= randn(3, 3)
3×3 view(view(::BlockSparseArray{Float64, 2, Matrix{Float64}, NDTensors.SparseArrayDOKs.SparseArrayDOK{Matrix{Float64}, 2, NDTensors.BlockSparseArrays.BlockZero{Tuple{BlockArrays.BlockedOneTo{Int64, Vector{Int64}}, BlockArrays.BlockedOneTo{Int64, Vector{Int64}}}}}, Tuple{BlockArrays.BlockedOneTo{Int64, Vector{Int64}}, BlockArrays.BlockedOneTo{Int64, Vector{Int64}}}}, [3, 4, 5, 1, 2], [3, 4, 5, 1, 2]), BlockSlice(Block(1),1:3), BlockSlice(Block(1),1:3)) with eltype Float64:
  0.994707   0.611011    0.110323
 -1.42947    0.0876526   0.808757
  0.887843  -0.267044   -0.909812

julia> a
typeof(axes) = Tuple{BlockArrays.BlockedOneTo{Int64, Vector{Int64}}, BlockArrays.BlockedOneTo{Int64, Vector{Int64}}}

Warning: To temporarily circumvent a bug in printing BlockSparseArrays with mixtures of dual and non-dual axes, the types of the dual axes printed below might not be accurate. The types printed above this message are the correct ones.

2×2-blocked 5×5 BlockSparseArray{Float64, 2, Matrix{Float64}, NDTensors.SparseArrayDOKs.SparseArrayDOK{Matrix{Float64}, 2, NDTensors.BlockSparseArrays.BlockZero{Tuple{BlockArrays.BlockedOneTo{Int64, Vector{Int64}}, BlockArrays.BlockedOneTo{Int64, Vector{Int64}}}}}, Tuple{BlockArrays.BlockedOneTo{Int64, Vector{Int64}}, BlockArrays.BlockedOneTo{Int64, Vector{Int64}}}}:
 0.0  0.0  │   0.0        0.0         0.0     
 0.0  0.0  │   0.0        0.0         0.0     
 ──────────┼──────────────────────────────────
 0.0  0.0  │   0.994707   0.611011    0.110323
 0.0  0.0  │  -1.42947    0.0876526   0.808757
 0.0  0.0  │   0.887843  -0.267044   -0.909812

julia> b
5×5 view(::BlockSparseArray{Float64, 2, Matrix{Float64}, NDTensors.SparseArrayDOKs.SparseArrayDOK{Matrix{Float64}, 2, NDTensors.BlockSparseArrays.BlockZero{Tuple{BlockArrays.BlockedOneTo{Int64, Vector{Int64}}, BlockArrays.BlockedOneTo{Int64, Vector{Int64}}}}}, Tuple{BlockArrays.BlockedOneTo{Int64, Vector{Int64}}, BlockArrays.BlockedOneTo{Int64, Vector{Int64}}}}, [3, 4, 5, 1, 2], [3, 4, 5, 1, 2]) with eltype Float64 with indices BlockArrays.BlockedOneTo([3, 5])×BlockArrays.BlockedOneTo([3, 5]):
  0.994707   0.611011    0.110323  │  0.0  0.0
 -1.42947    0.0876526   0.808757  │  0.0  0.0
  0.887843  -0.267044   -0.909812  │  0.0  0.0
 ──────────────────────────────────┼──────────
  0.0        0.0         0.0       │  0.0  0.0
  0.0        0.0         0.0       │  0.0  0.0