|
| 1 | +""" |
| 2 | + struct Sizes |
| 3 | + ndims::Vector{Int} |
| 4 | + size_offset::Vector{Int} |
| 5 | + size::Vector{Int} |
| 6 | + storage_offset::Vector{Int} |
| 7 | + end |
| 8 | +
|
| 9 | +The node at index `k` is an array of `ndims[k]` dimensions and size `sizes[size_offset[k] .+ (1:ndims[k])]`. |
| 10 | +Note that `size_offset` is a nonincreasing vector so that `sizes` can be filled in a forward pass, |
| 11 | +which goes through the nodes in decreasing index order. |
| 12 | +""" |
| 13 | +struct Sizes |
| 14 | + ndims::Vector{Int} |
| 15 | + size_offset::Vector{Int} |
| 16 | + size::Vector{Int} |
| 17 | + storage_offset::Vector{Int} |
| 18 | +end |
| 19 | + |
| 20 | +function _size(sizes::Sizes, k::Int, dim::Int) |
| 21 | + return sizes.size[sizes.size_offset[k]+dim] |
| 22 | +end |
| 23 | + |
| 24 | +function _size(sizes::Sizes, k::Int) |
| 25 | + return view(sizes.size, sizes.size_offset[k] .+ Base.OneTo(sizes.ndims[k])) |
| 26 | +end |
| 27 | + |
| 28 | +function _length(sizes::Sizes, k::Int) |
| 29 | + if sizes.ndims[k] == 0 |
| 30 | + return 1 |
| 31 | + else |
| 32 | + return prod(_size(sizes, k)) |
| 33 | + end |
| 34 | +end |
| 35 | + |
| 36 | +_eachindex(sizes::Sizes, k) = Base.OneTo(_length(sizes, k)) |
| 37 | + |
| 38 | +_length(sizes::Sizes) = sizes.storage_offset[end] |
| 39 | + |
| 40 | +function _storage_range(sizes::Sizes, k::Int) |
| 41 | + return sizes.storage_offset[k] .+ _eachindex(sizes, k) |
| 42 | +end |
| 43 | + |
| 44 | +function _getindex(x, sizes::Sizes, k::Int, j) |
| 45 | + return x[sizes.storage_offset[k]+j] |
| 46 | +end |
| 47 | + |
| 48 | +function _setindex!(x, value, sizes::Sizes, k::Int, j) |
| 49 | + return x[sizes.storage_offset[k]+j] = value |
| 50 | +end |
| 51 | + |
| 52 | +# /!\ Can only be called in decreasing `k` order |
| 53 | +function _add_size!(sizes::Sizes, k::Int, size::Tuple) |
| 54 | + sizes.ndims[k] = length(size) |
| 55 | + sizes.size_offset[k] = length(sizes.size) |
| 56 | + append!(sizes.size, size) |
| 57 | + return |
| 58 | +end |
| 59 | + |
| 60 | +function _copy_size!(sizes::Sizes, k::Int, child::Int) |
| 61 | + sizes.ndims[k] = sizes.ndims[child] |
| 62 | + sizes.size_offset[k] = length(sizes.size) |
| 63 | + for i in (sizes.size_offset[child] .+ Base.OneTo(sizes.ndims[child])) |
| 64 | + push!(sizes.size, sizes.size[i]) |
| 65 | + end |
| 66 | + return |
| 67 | +end |
| 68 | + |
| 69 | +function _assert_scalar_children(sizes, children_arr, children_indices, op) |
| 70 | + for c_idx in children_indices |
| 71 | + @inbounds ix = children_arr[c_idx] |
| 72 | + # We don't support nested vectors of vectors, |
| 73 | + # we only support real numbers and array of real numbers |
| 74 | + @assert sizes.ndims[ix] == 0 "Array argument when expected scalar argument for operator `$op`" |
| 75 | + end |
| 76 | +end |
| 77 | + |
| 78 | +function _infer_sizes( |
| 79 | + nodes::Vector{Nonlinear.Node}, |
| 80 | + adj::SparseArrays.SparseMatrixCSC{Bool,Int}, |
| 81 | +) |
| 82 | + sizes = Sizes( |
| 83 | + zeros(Int, length(nodes)), |
| 84 | + zeros(Int, length(nodes)), |
| 85 | + Int[], |
| 86 | + zeros(Int, length(nodes) + 1), |
| 87 | + ) |
| 88 | + children_arr = SparseArrays.rowvals(adj) |
| 89 | + for k in length(nodes):-1:1 |
| 90 | + node = nodes[k] |
| 91 | + children_indices = SparseArrays.nzrange(adj, k) |
| 92 | + N = length(children_indices) |
| 93 | + if node.type == Nonlinear.NODE_CALL_MULTIVARIATE |
| 94 | + if !( |
| 95 | + node.index in |
| 96 | + eachindex(MOI.Nonlinear.DEFAULT_MULTIVARIATE_OPERATORS) |
| 97 | + ) |
| 98 | + # TODO user-defined operators |
| 99 | + continue |
| 100 | + end |
| 101 | + op = MOI.Nonlinear.DEFAULT_MULTIVARIATE_OPERATORS[node.index] |
| 102 | + if op == :vect |
| 103 | + _assert_scalar_children( |
| 104 | + sizes, |
| 105 | + children_arr, |
| 106 | + children_indices, |
| 107 | + op, |
| 108 | + ) |
| 109 | + _add_size!(sizes, k, (N,)) |
| 110 | + elseif op == :dot |
| 111 | + # TODO assert all arguments have same size |
| 112 | + elseif op == :+ || op == :- |
| 113 | + # TODO assert all arguments have same size |
| 114 | + _copy_size!(sizes, k, children_arr[first(children_indices)]) |
| 115 | + elseif op == :* |
| 116 | + # TODO assert compatible sizes and all ndims should be 0 or 2 |
| 117 | + first_matrix = findfirst(children_indices) do i |
| 118 | + return !iszero(sizes.ndims[children_arr[i]]) |
| 119 | + end |
| 120 | + if !isnothing(first_matrix) |
| 121 | + last_matrix = findfirst(children_indices) do i |
| 122 | + return !iszero(sizes.ndims[children_arr[i]]) |
| 123 | + end |
| 124 | + _add_size!( |
| 125 | + sizes, |
| 126 | + k, |
| 127 | + ( |
| 128 | + _size(sizes, first_matrix, 1), |
| 129 | + _size(sizes, last_matrix, sizes.ndims[last_matrix]), |
| 130 | + ), |
| 131 | + ) |
| 132 | + end |
| 133 | + elseif op == :^ || op == :/ |
| 134 | + @assert N == 2 |
| 135 | + _assert_scalar_children( |
| 136 | + sizes, |
| 137 | + children_arr, |
| 138 | + children_indices[2:end], |
| 139 | + op, |
| 140 | + ) |
| 141 | + _copy_size!(sizes, k, children_arr[first(children_indices)]) |
| 142 | + else |
| 143 | + _assert_scalar_children( |
| 144 | + sizes, |
| 145 | + children_arr, |
| 146 | + children_indices, |
| 147 | + op, |
| 148 | + ) |
| 149 | + end |
| 150 | + elseif node.type == Nonlinear.NODE_CALL_UNIVARIATE |
| 151 | + if !( |
| 152 | + node.index in |
| 153 | + eachindex(MOI.Nonlinear.DEFAULT_UNIVARIATE_OPERATORS) |
| 154 | + ) |
| 155 | + # TODO user-defined operators |
| 156 | + continue |
| 157 | + end |
| 158 | + @assert N == 1 |
| 159 | + op = MOI.Nonlinear.DEFAULT_UNIVARIATE_OPERATORS[node.index] |
| 160 | + if op == :+ || op == :- |
| 161 | + _copy_size!(sizes, k, children_arr[first(children_indices)]) |
| 162 | + else |
| 163 | + _assert_scalar_children( |
| 164 | + sizes, |
| 165 | + children_arr, |
| 166 | + children_indices, |
| 167 | + op, |
| 168 | + ) |
| 169 | + end |
| 170 | + end |
| 171 | + end |
| 172 | + for k in eachindex(nodes) |
| 173 | + sizes.storage_offset[k+1] = sizes.storage_offset[k] + _length(sizes, k) |
| 174 | + end |
| 175 | + return sizes |
| 176 | +end |
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