Reducing need for unique generated methods

Project.toml

@@ -1,20 +1,23 @@
 name = "ArrayInterface"
 uuid = "4fba245c-0d91-5ea0-9b3e-6abc04ee57a9"
-version = "2.14.17"
+version = "3.0.0"
 
 [deps]
+IfElse = "615f187c-cbe4-4ef1-ba3b-2fcf58d6d173"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 
 [compat]
+IfElse = "0.1"
 Requires = "0.5, 1.0"
 julia = "1.2"
 
 [extras]
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 BandedMatrices = "aae01518-5342-5314-be14-df237901396f"
 BlockBandedMatrices = "ffab5731-97b5-5995-9138-79e8c1846df0"
+IfElse = "615f187c-cbe4-4ef1-ba3b-2fcf58d6d173"
 LabelledArrays = "2ee39098-c373-598a-b85f-a56591580800"
 OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
@@ -23,4 +26,4 @@ SuiteSparse = "4607b0f0-06f3-5cda-b6b1-a6196a1729e9"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Test", "LabelledArrays", "StaticArrays", "BandedMatrices", "BlockBandedMatrices", "SuiteSparse", "Random", "OffsetArrays", "Aqua"]
+test = ["Test", "LabelledArrays", "StaticArrays", "BandedMatrices", "BlockBandedMatrices", "SuiteSparse", "Random", "OffsetArrays", "Aqua", "IfElse"]

README.md

@@ -183,7 +183,7 @@ julia> using StaticArrays, ArrayInterface
 julia> A = @SMatrix rand(3,4);
 
 julia> ArrayInterface.size(A)
-(StaticInt{3}(), StaticInt{4}())
+(static(3), static(4))
 ```
 
 ## ArrayInterface.strides(A)
@@ -196,7 +196,7 @@ julia> using ArrayInterface
 julia> A = rand(3,4);
 
 julia> ArrayInterface.strides(A)
-(StaticInt{1}(), 3)
+(static(1), 3)
 ```
 ## offsets(A)
 

src/ArrayInterface.jl

@@ -1,15 +1,19 @@
 module ArrayInterface
 
+using IfElse
 using Requires
 using LinearAlgebra
 using SparseArrays
 
-using Base: @propagate_inbounds, tail, OneTo, LogicalIndex, Slice
+using Base: @pure, @propagate_inbounds, tail, OneTo, LogicalIndex, Slice, ReinterpretArray
 
 Base.@pure __parameterless_type(T) = Base.typename(T).wrapper
 parameterless_type(x) = parameterless_type(typeof(x))
 parameterless_type(x::Type) = __parameterless_type(x)
 
+const VecAdjTrans{T,V<:AbstractVector{T}} = Union{Transpose{T,V},Adjoint{T,V}}
+const MatAdjTrans{T,M<:AbstractMatrix{T}} = Union{Transpose{T,M},Adjoint{T,M}}
+
 """
     parent_type(::Type{T})
 
@@ -25,11 +29,7 @@ parent_type(::Type{<:LinearAlgebra.AbstractTriangular{T,S}}) where {T,S} = S
 parent_type(::Type{<:PermutedDimsArray{T,N,I1,I2,A}}) where {T,N,I1,I2,A} = A
 parent_type(::Type{Slice{T}}) where {T} = T
 parent_type(::Type{T}) where {T} = T
-function parent_type(
-    ::Type{R},
-) where {S,T,A<:AbstractArray{S},N,R<:Base.ReinterpretArray{T,N,S,A}}
-    return A
-end
+parent_type(::Type{R}) where {S,T,A,N,R<:Base.ReinterpretArray{T,N,S,A}} = A
 
 """
     known_length(::Type{T})
@@ -794,12 +794,14 @@ function __init__()
         known_length(::Type{A}) where {A <: StaticArrays.StaticArray} = known_length(StaticArrays.Length(A))
 
         device(::Type{<:StaticArrays.MArray}) = CPUPointer()
-        contiguous_axis(::Type{<:StaticArrays.StaticArray}) = Contiguous{1}()
-        contiguous_batch_size(::Type{<:StaticArrays.StaticArray}) = ContiguousBatch{0}()
-        stride_rank(::Type{T}) where {N,T<:StaticArrays.StaticArray{<:Any,<:Any,N}} =
-            StrideRank{ntuple(identity, Val{N}())}()
-        dense_dims(::Type{<:StaticArrays.StaticArray{S,T,N}}) where {S,T,N} =
-            DenseDims{ntuple(_ -> true, Val(N))}()
+        contiguous_axis(::Type{<:StaticArrays.StaticArray}) = StaticInt{1}()
+        contiguous_batch_size(::Type{<:StaticArrays.StaticArray}) = StaticInt{0}()
+        function stride_rank(::Type{T}) where {N,T<:StaticArrays.StaticArray{<:Any,<:Any,N}}
+            return ArrayInterface.nstatic(Val(N))
+        end
+        function dense_dims(::Type{<:StaticArrays.StaticArray{S,T,N}}) where {S,T,N}
+            return ArrayInterface._all_dense(Val(N))
+        end
         defines_strides(::Type{<:StaticArrays.MArray}) = true
 
         @generated function axes_types(::Type{<:StaticArrays.StaticArray{S}}) where {S}

src/dimensions.jl

@@ -1,4 +1,70 @@
 
+#julia> @btime ArrayInterface.is_increasing(ArrayInterface.nstatic(Val(10)))
+#  0.045 ns (0 allocations: 0 bytes)
+#ArrayInterface.True()
+function is_increasing(perm::Tuple{StaticInt{X},StaticInt{Y},Vararg}) where {X, Y}
+    if X <= Y
+        return is_increasing(tail(perm))
+    else
+        return False()
+    end
+end
+function is_increasing(perm::Tuple{StaticInt{X},StaticInt{Y}}) where {X, Y}
+    if X <= Y
+        return True()
+    else
+        return False()
+    end
+end
+is_increasing(::Tuple{StaticInt{X}}) where {X} = True()
+
+"""
+    from_parent_dims(::Type{T}) -> Bool
+
+Returns the mapping from parent dimensions to child dimensions.
+"""
+from_parent_dims(::Type{T}) where {T} = nstatic(Val(ndims(T)))
+from_parent_dims(::Type{T}) where {T<:Union{Transpose,Adjoint}} = (StaticInt(2), One())
+from_parent_dims(::Type{<:SubArray{T,N,A,I}}) where {T,N,A,I} = _from_sub_dims(A, I)
+@generated function _from_sub_dims(::Type{A}, ::Type{I}) where {A,N,I<:Tuple{Vararg{Any,N}}}
+    out = Expr(:tuple)
+    n = 1
+    for p in I.parameters
+        if argdims(A, p) > 0
+            push!(out.args, :(StaticInt($n)))
+            n += 1
+        else
+            push!(out.args, :(StaticInt(0)))
+        end
+    end
+    out
+end
+function from_parent_dims(::Type{<:PermutedDimsArray{T,N,<:Any,I}}) where {T,N,I}
+    return _val_to_static(Val(I))
+end
+
+"""
+    to_parent_dims(::Type{T}) -> Bool
+
+Returns the mapping from child dimensions to parent dimensions.
+"""
+to_parent_dims(x) = to_parent_dims(typeof(x))
+to_parent_dims(::Type{T}) where {T} = nstatic(Val(ndims(T)))
+to_parent_dims(::Type{T}) where {T<:Union{Transpose,Adjoint}} = (StaticInt(2), One())
+to_parent_dims(::Type{<:PermutedDimsArray{T,N,I}}) where {T,N,I} = _val_to_static(Val(I))
+to_parent_dims(::Type{<:SubArray{T,N,A,I}}) where {T,N,A,I} = _to_sub_dims(A, I)
+@generated function _to_sub_dims(::Type{A}, ::Type{I}) where {A,N,I<:Tuple{Vararg{Any,N}}}
+    out = Expr(:tuple)
+    n = 1
+    for p in I.parameters
+        if argdims(A, p) > 0
+            push!(out.args, :(StaticInt($n)))
+        end
+        n += 1
+    end
+    out
+end
+
 """
     has_dimnames(::Type{T}) -> Bool
 
@@ -137,6 +203,95 @@ end
     end
     return Expr(:tuple, exs...)
 end
+@generated function _perm_tuple(::Type{T}, ::Val{P}) where {T,P}
+    out = Expr(:curly, :Tuple)
+    for p in P
+        push!(out.args, T.parameters[p])
+    end
+    Expr(:block, Expr(:meta, :inline), out)
+end
+
+"""
+    axes_types(::Type{T}[, d]) -> Type
+
+Returns the type of the axes for `T`
+"""
+axes_types(x) = axes_types(typeof(x))
+axes_types(x, d) = axes_types(typeof(x), d)
+@inline axes_types(::Type{T}, d) where {T} = axes_types(T).parameters[to_dims(T, d)]
+function axes_types(::Type{T}) where {T}
+    if parent_type(T) <: T
+        return Tuple{Vararg{OptionallyStaticUnitRange{One,Int},ndims(T)}}
+    else
+        return axes_types(parent_type(T))
+    end
+end
+function axes_types(::Type{T}) where {T<:Adjoint}
+    return _perm_tuple(axes_types(parent_type(T)), Val((2, 1)))
+end
+function axes_types(::Type{T}) where {T<:Transpose}
+    return _perm_tuple(axes_types(parent_type(T)), Val((2, 1)))
+end
+function axes_types(::Type{T}) where {I1,T<:PermutedDimsArray{<:Any,<:Any,I1}}
+    return _perm_tuple(axes_types(parent_type(T)), Val(I1))
+end
+function axes_types(::Type{T}) where {T<:AbstractRange}
+    if known_length(T) === nothing
+        return Tuple{OptionallyStaticUnitRange{One,Int}}
+    else
+        return Tuple{OptionallyStaticUnitRange{One,StaticInt{known_length(T)}}}
+    end
+end
+
+@inline function axes_types(::Type{T}) where {P,I,T<:SubArray{<:Any,<:Any,P,I}}
+    return _sub_axes_types(Val(ArrayStyle(T)), I, axes_types(P))
+end
+@generated function _sub_axes_types(
+    ::Val{S},
+    ::Type{I},
+    ::Type{PI},
+) where {S,I<:Tuple,PI<:Tuple}
+    out = Expr(:curly, :Tuple)
+    d = 1
+    for i in I.parameters
+        ad = argdims(S, i)
+        if ad > 0
+            push!(out.args, :(sub_axis_type($(PI.parameters[d]), $i)))
+            d += ad
+        else
+            d += 1
+        end
+    end
+    Expr(:block, Expr(:meta, :inline), out)
+end
+
+@inline function axes_types(::Type{T}) where {T<:Base.ReinterpretArray}
+    return _reinterpret_axes_types(
+        axes_types(parent_type(T)),
+        eltype(T),
+        eltype(parent_type(T)),
+    )
+end
+@generated function _reinterpret_axes_types(
+    ::Type{I},
+    ::Type{T},
+    ::Type{S},
+) where {I<:Tuple,T,S}
+    out = Expr(:curly, :Tuple)
+    for i = 1:length(I.parameters)
+        if i === 1
+            push!(out.args, reinterpret_axis_type(I.parameters[1], T, S))
+        else
+            push!(out.args, I.parameters[i])
+        end
+    end
+    Expr(:block, Expr(:meta, :inline), out)
+end
+
+function axes_types(::Type{T}) where {N,T<:Base.ReshapedArray{<:Any,N}}
+    return Tuple{Vararg{OptionallyStaticUnitRange{One,Int},N}}
+end
+
 
 """
   size(A)
@@ -162,6 +317,32 @@ end
     return (One(), static_length(x))
 end
 
+function size(B::S) where {N,NP,T,A<:AbstractArray{T,NP},I,S<:SubArray{T,N,A,I}}
+    return _size(size(parent(B)), B.indices, map(static_length, B.indices))
+end
+function strides(B::S) where {N,NP,T,A<:AbstractArray{T,NP},I,S<:SubArray{T,N,A,I}}
+    return _strides(strides(parent(B)), B.indices)
+end
+@generated function _size(A::Tuple{Vararg{Any,N}}, inds::I, l::L) where {N,I<:Tuple,L}
+    t = Expr(:tuple)
+    for n = 1:N
+        if (I.parameters[n] <: Base.Slice)
+            push!(t.args, :(@inbounds(_try_static(A[$n], l[$n]))))
+        elseif I.parameters[n] <: Number
+            nothing
+        else
+            push!(t.args, Expr(:ref, :l, n))
+        end
+    end
+    Expr(:block, Expr(:meta, :inline), t)
+end
+@inline size(v::AbstractVector) = (static_length(v),)
+@inline size(B::MatAdjTrans) = permute(size(parent(B)), Val{(2, 1)}())
+@inline function size(B::PermutedDimsArray{T,N,I1,I2,A}) where {T,N,I1,I2,A}
+    return permute(size(parent(B)), Val{I1}())
+end
+@inline size(A::AbstractArray, ::StaticInt{N}) where {N} = size(A)[N]
+@inline size(A::AbstractArray, ::Val{N}) where {N} = size(A)[N]
 """
     axes(A, d)
 

src/indexing.jl

@@ -28,14 +28,10 @@ argdims(::ArrayStyle, ::Type{T}) where {T<:AbstractArray} = ndims(T)
 argdims(::ArrayStyle, ::Type{T}) where {N,T<:CartesianIndex{N}} = N
 argdims(::ArrayStyle, ::Type{T}) where {N,T<:AbstractArray{CartesianIndex{N}}} = N
 argdims(::ArrayStyle, ::Type{T}) where {N,T<:AbstractArray{<:Any,N}} = N
-argdims(::ArrayStyle, ::Type{T}) where {N,T<:LogicalIndex{<:Any,<:AbstractArray{Bool,N}}} =
-    N
-@generated function argdims(s::ArrayStyle, ::Type{T}) where {N,T<:Tuple{Vararg{Any,N}}}
-    e = Expr(:tuple)
-    for p in T.parameters
-        push!(e.args, :(ArrayInterface.argdims(s, $p)))
-    end
-    Expr(:block, Expr(:meta, :inline), e)
+argdims(::ArrayStyle, ::Type{T}) where {N,T<:LogicalIndex{<:Any,<:AbstractArray{Bool,N}}} = N
+_argdims(s::ArrayStyle, ::Type{I}, i::StaticInt) where {I} = argdims(s, _get_tuple(I, i))
+function argdims(s::ArrayStyle, ::Type{T}) where {N,T<:Tuple{Vararg{Any,N}}}
+    return eachop(_argdims, s, T, nstatic(Val(N)))
 end
 
 """
@@ -186,11 +182,15 @@ can_flatten(::Type{A}, ::Type{T}) where {A,I<:CartesianIndex,T<:AbstractArray{I}
 can_flatten(::Type{A}, ::Type{T}) where {A,T<:CartesianIndices} = true
 can_flatten(::Type{A}, ::Type{T}) where {A,N,T<:AbstractArray{Bool,N}} = N > 1
 can_flatten(::Type{A}, ::Type{T}) where {A,N,T<:CartesianIndex{N}} = true
-@generated function can_flatten(::Type{A}, ::Type{T}) where {A,T<:Tuple}
-    for i in T.parameters
-        can_flatten(A, i) && return true
+function can_flatten(::Type{A}, ::Type{T}) where {A,N,T<:Tuple{Vararg{Any,N}}}
+    return any(eachop(_can_flat, A, T, nstatic(Val(N))))
+end
+function _can_flat(::Type{A}, ::Type{T}, i::StaticInt) where {A,T}
+    if can_flatten(A, _get_tuple(T, i)) === true
+        return True()
+    else
+        return False()
     end
-    return false
 end
 
 """
@@ -437,6 +437,8 @@ Changing indexing based on a given argument from `args` should be done through
         return unsafe_getindex(A, to_indices(A, ()); kwargs...)
     end
 end
+@propagate_inbounds getindex(x::Tuple, i::Int) = getfield(x, i)
+@propagate_inbounds getindex(x::Tuple, ::StaticInt{i}) where {i} = getfield(x, i)
 
 """
     unsafe_getindex(A, inds)
@@ -495,22 +497,26 @@ function unsafe_get_collection(A, inds; kwargs...)
     return dest
 end
 
-can_preserve_indices(::Type{T}) where {T<:AbstractRange} = known_step(T) === 1
+can_preserve_indices(::Type{T}) where {T<:AbstractRange} = true
 can_preserve_indices(::Type{T}) where {T<:Int} = true
 can_preserve_indices(::Type{T}) where {T} = false
 
-_ints2range(x::Integer) = x:x
-_ints2range(x::AbstractRange) = x
-
 # if linear indexing on multidim or can't reconstruct AbstractUnitRange
 # then construct Array of CartesianIndex/LinearIndices
-@generated function can_preserve_indices(::Type{T}) where {T<:Tuple}
-    for index_type in T.parameters
-        can_preserve_indices(index_type) || return false
+function can_preserve_indices(::Type{T}) where {N,T<:Tuple{Vararg{Any,N}}}
+    return all(eachop(_can_preserve_indices, T, nstatic(Val(N))))
+end
+function _can_preserve_indices(::Type{T}, i::StaticInt) where {T}
+    if can_preserve_indices(_get_tuple(T, i))
+        return True()
+    else
+        return False()
     end
-    return true
 end
 
+_ints2range(x::Integer) = x:x
+_ints2range(x::AbstractRange) = x
+
 @inline function unsafe_get_collection(A::CartesianIndices{N}, inds) where {N}
     if (length(inds) === 1 && N > 1) || !can_preserve_indices(typeof(inds))
         return Base._getindex(IndexStyle(A), A, inds...)