Move SparseArrays support to an extension

Project.toml

@@ -1,12 +1,18 @@
 name = "ChainRulesCore"
 uuid = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
-version = "1.17.0"
+version = "1.18.0"
 
 [deps]
 Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 
+[weakdeps]
+SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
+
+[extensions]
+ChainRulesCoreSparseArraysExt = "SparseArrays"
+
 [compat]
 BenchmarkTools = "0.5"
 Compat = "2, 3, 4"
@@ -19,8 +25,9 @@ julia = "1.6"
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
 FiniteDifferences = "26cc04aa-876d-5657-8c51-4c34ba976000"
 OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
+SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Test", "BenchmarkTools", "FiniteDifferences", "OffsetArrays", "StaticArrays"]
+test = ["Test", "BenchmarkTools", "FiniteDifferences", "OffsetArrays", "SparseArrays", "StaticArrays"]

ext/ChainRulesCoreSparseArraysExt.jl

@@ -0,0 +1,103 @@
+module ChainRulesCoreSparseArraysExt
+
+using ChainRulesCore
+using ChainRulesCore: project_type, _projection_mismatch
+using SparseArrays: SparseVector, SparseMatrixCSC, nzrange, rowvals
+
+ChainRulesCore.is_inplaceable_destination(::SparseVector) = true
+ChainRulesCore.is_inplaceable_destination(::SparseMatrixCSC) = true
+
+# Word from on high is that we should regard all un-stored values of sparse arrays as
+# structural zeros. Thus ProjectTo needs to store nzind, and get only those.
+# This implementation very naiive, can probably be made more efficient.
+
+function ChainRulesCore.ProjectTo(x::SparseVector{T}) where {T<:Number}
+    return ProjectTo{SparseVector}(;
+        element=ProjectTo(zero(T)), nzind=x.nzind, axes=axes(x)
+    )
+end
+function (project::ProjectTo{SparseVector})(dx::AbstractArray)
+    dy = if axes(dx) == project.axes
+        dx
+    else
+        if size(dx, 1) != length(project.axes[1])
+            throw(_projection_mismatch(project.axes, size(dx)))
+        end
+        reshape(dx, project.axes)
+    end
+    nzval = map(i -> project.element(dy[i]), project.nzind)
+    return SparseVector(length(dx), project.nzind, nzval)
+end
+function (project::ProjectTo{SparseVector})(dx::SparseVector)
+    if size(dx) != map(length, project.axes)
+        throw(_projection_mismatch(project.axes, size(dx)))
+    end
+    # When sparsity pattern is unchanged, all the time is in checking this,
+    # perhaps some simple hash/checksum might be good enough?
+    samepattern = project.nzind == dx.nzind
+    # samepattern = length(project.nzind) == length(dx.nzind)
+    if eltype(dx) <: project_type(project.element) && samepattern
+        return dx
+    elseif samepattern
+        nzval = map(project.element, dx.nzval)
+        SparseVector(length(dx), dx.nzind, nzval)
+    else
+        nzind = project.nzind
+        # Or should we intersect? Can this exploit sorting?
+        # nzind = intersect(project.nzind, dx.nzind)
+        nzval = map(i -> project.element(dx[i]), nzind)
+        return SparseVector(length(dx), nzind, nzval)
+    end
+end
+
+function ChainRulesCore.ProjectTo(x::SparseMatrixCSC{T}) where {T<:Number}
+    return ProjectTo{SparseMatrixCSC}(;
+        element=ProjectTo(zero(T)),
+        axes=axes(x),
+        rowval=rowvals(x),
+        nzranges=nzrange.(Ref(x), axes(x, 2)),
+        colptr=x.colptr,
+    )
+end
+# You need not really store nzranges, you can get them from colptr -- TODO
+# nzrange(S::AbstractSparseMatrixCSC, col::Integer) = getcolptr(S)[col]:(getcolptr(S)[col+1]-1)
+function (project::ProjectTo{SparseMatrixCSC})(dx::AbstractArray)
+    dy = if axes(dx) == project.axes
+        dx
+    else
+        if size(dx) != (length(project.axes[1]), length(project.axes[2]))
+            throw(_projection_mismatch(project.axes, size(dx)))
+        end
+        reshape(dx, project.axes)
+    end
+    nzval = Vector{project_type(project.element)}(undef, length(project.rowval))
+    k = 0
+    for col in project.axes[2]
+        for i in project.nzranges[col]
+            row = project.rowval[i]
+            val = dy[row, col]
+            nzval[k += 1] = project.element(val)
+        end
+    end
+    m, n = map(length, project.axes)
+    return SparseMatrixCSC(m, n, project.colptr, project.rowval, nzval)
+end
+
+function (project::ProjectTo{SparseMatrixCSC})(dx::SparseMatrixCSC)
+    if size(dx) != map(length, project.axes)
+        throw(_projection_mismatch(project.axes, size(dx)))
+    end
+    samepattern = dx.colptr == project.colptr && dx.rowval == project.rowval
+    # samepattern = length(dx.colptr) == length(project.colptr) && dx.colptr[end] == project.colptr[end]
+    if eltype(dx) <: project_type(project.element) && samepattern
+        return dx
+    elseif samepattern
+        nzval = map(project.element, dx.nzval)
+        m, n = size(dx)
+        return SparseMatrixCSC(m, n, dx.colptr, dx.rowval, nzval)
+    else
+        invoke(project, Tuple{AbstractArray}, dx)
+    end
+end
+
+end # module

src/ChainRulesCore.jl

@@ -2,7 +2,6 @@ module ChainRulesCore
 using Base.Broadcast: broadcasted, Broadcasted, broadcastable, materialize, materialize!
 using Base.Meta
 using LinearAlgebra
-using SparseArrays: SparseVector, SparseMatrixCSC
 using Compat: hasfield, hasproperty
 
 export frule, rrule  # core function
@@ -36,4 +35,9 @@ include("ignore_derivatives.jl")
 
 include("deprecated.jl")
 
+# SparseArrays support on Julia < 1.9
+if !isdefined(Base, :get_extension)
+    include("../ext/ChainRulesCoreSparseArraysExt.jl")
+end
+
 end # module

src/accumulation.jl

@@ -56,9 +56,6 @@ is_inplaceable_destination(::Any) = false
 is_inplaceable_destination(::Array) = true
 is_inplaceable_destination(:: Array{<:Integer}) = false
 
-is_inplaceable_destination(::SparseVector) = true
-is_inplaceable_destination(::SparseMatrixCSC) = true
-
 function is_inplaceable_destination(x::SubArray)
     alpha = is_inplaceable_destination(parent(x))
     beta = x.indices isa Tuple{Vararg{Union{Integer, Base.Slice, UnitRange}}}

src/projection.jl

@@ -515,101 +515,3 @@ function (project::ProjectTo{Tridiagonal})(dx::AbstractArray)
     return Tridiagonal(dy)
 end
 # Note that backing(::Tridiagonal) doesn't work, https://github.com/JuliaDiff/ChainRulesCore.jl/issues/392
-
-#####
-##### `SparseArrays`
-#####
-
-using SparseArrays
-# Word from on high is that we should regard all un-stored values of sparse arrays as
-# structural zeros. Thus ProjectTo needs to store nzind, and get only those.
-# This implementation very naiive, can probably be made more efficient.
-
-function ProjectTo(x::SparseVector{T}) where {T<:Number}
-    return ProjectTo{SparseVector}(;
-        element=ProjectTo(zero(T)), nzind=x.nzind, axes=axes(x)
-    )
-end
-function (project::ProjectTo{SparseVector})(dx::AbstractArray)
-    dy = if axes(dx) == project.axes
-        dx
-    else
-        if size(dx, 1) != length(project.axes[1])
-            throw(_projection_mismatch(project.axes, size(dx)))
-        end
-        reshape(dx, project.axes)
-    end
-    nzval = map(i -> project.element(dy[i]), project.nzind)
-    return SparseVector(length(dx), project.nzind, nzval)
-end
-function (project::ProjectTo{SparseVector})(dx::SparseVector)
-    if size(dx) != map(length, project.axes)
-        throw(_projection_mismatch(project.axes, size(dx)))
-    end
-    # When sparsity pattern is unchanged, all the time is in checking this,
-    # perhaps some simple hash/checksum might be good enough?
-    samepattern = project.nzind == dx.nzind
-    # samepattern = length(project.nzind) == length(dx.nzind)
-    if eltype(dx) <: project_type(project.element) && samepattern
-        return dx
-    elseif samepattern
-        nzval = map(project.element, dx.nzval)
-        SparseVector(length(dx), dx.nzind, nzval)
-    else
-        nzind = project.nzind
-        # Or should we intersect? Can this exploit sorting?
-        # nzind = intersect(project.nzind, dx.nzind)
-        nzval = map(i -> project.element(dx[i]), nzind)
-        return SparseVector(length(dx), nzind, nzval)
-    end
-end
-
-function ProjectTo(x::SparseMatrixCSC{T}) where {T<:Number}
-    return ProjectTo{SparseMatrixCSC}(;
-        element=ProjectTo(zero(T)),
-        axes=axes(x),
-        rowval=rowvals(x),
-        nzranges=nzrange.(Ref(x), axes(x, 2)),
-        colptr=x.colptr,
-    )
-end
-# You need not really store nzranges, you can get them from colptr -- TODO
-# nzrange(S::AbstractSparseMatrixCSC, col::Integer) = getcolptr(S)[col]:(getcolptr(S)[col+1]-1)
-function (project::ProjectTo{SparseMatrixCSC})(dx::AbstractArray)
-    dy = if axes(dx) == project.axes
-        dx
-    else
-        if size(dx) != (length(project.axes[1]), length(project.axes[2]))
-            throw(_projection_mismatch(project.axes, size(dx)))
-        end
-        reshape(dx, project.axes)
-    end
-    nzval = Vector{project_type(project.element)}(undef, length(project.rowval))
-    k = 0
-    for col in project.axes[2]
-        for i in project.nzranges[col]
-            row = project.rowval[i]
-            val = dy[row, col]
-            nzval[k += 1] = project.element(val)
-        end
-    end
-    m, n = map(length, project.axes)
-    return SparseMatrixCSC(m, n, project.colptr, project.rowval, nzval)
-end
-
-function (project::ProjectTo{SparseMatrixCSC})(dx::SparseMatrixCSC)
-    if size(dx) != map(length, project.axes)
-        throw(_projection_mismatch(project.axes, size(dx)))
-    end
-    samepattern = dx.colptr == project.colptr && dx.rowval == project.rowval
-    # samepattern = length(dx.colptr) == length(project.colptr) && dx.colptr[end] == project.colptr[end]
-    if eltype(dx) <: project_type(project.element) && samepattern
-        return dx
-    elseif samepattern
-        nzval = map(project.element, dx.nzval)
-        m, n = size(dx)
-        return SparseMatrixCSC(m, n, dx.colptr, dx.rowval, nzval)
-    else
-        invoke(project, Tuple{AbstractArray}, dx)
-    end
-end