Implement Polyester Colored AD for oop functions

ext/SparseDiffToolsPolyesterExt.jl

@@ -1,3 +1,69 @@
 module SparseDiffToolsPolyesterExt
-
+
+using Adapt, ArrayInterface, ForwardDiff, FiniteDiff, Polyester, SparseDiffTools,
+      SparseArrays
+import SparseDiffTools: polyesterforwarddiff_color_jacobian, ForwardColorJacCache,
+                        __parameterless_type
+
+function cld_fast(a::A, b::B) where {A, B}
+    T = promote_type(A, B)
+    return cld_fast(a % T, b % T)
+end
+function cld_fast(n::T, d::T) where {T}
+    x = Base.udiv_int(n, d)
+    x += n != d * x
+    return x
+end
+
+function polyesterforwarddiff_color_jacobian(J::AbstractMatrix{<:Number}, f::F,
+        x::AbstractArray{<:Number}, jac_cache::ForwardColorJacCache) where {F}
+    t = jac_cache.t
+    dx = jac_cache.dx
+    p = jac_cache.p
+    colorvec = jac_cache.colorvec
+    sparsity = jac_cache.sparsity
+    chunksize = jac_cache.chunksize
+    maxcolor = maximum(colorvec)
+
+    vecx = vec(x)
+
+    nrows, ncols = size(J)
+
+    if !(sparsity isa Nothing)
+        rows_index, cols_index = ArrayInterface.findstructralnz(sparsity)
+        rows_index = [rows_index[i] for i in 1:length(rows_index)]
+        cols_index = [cols_index[i] for i in 1:length(cols_index)]
+    else
+        rows_index = 1:nrows
+        cols_index = 1:ncols
+    end
+
+    if J isa AbstractSparseMatrix
+        fill!(nonzeros(J), zero(eltype(J)))
+    else
+        fill!(J, zero(eltype(J)))
+    end
+
+    batch((length(p), min(length(p), Threads.nthreads()))) do _, start, stop
+        for i in start:stop
+            partial_i = p[i]
+            color_i = i
+            t_ = reshape(eltype(t).(vecx, ForwardDiff.Partials.(partial_i)), size(t))
+            fx = f(t_)
+            for j in 1:chunksize
+                dx = vec(ForwardDiff.partials.(fx, j))
+                pick_inds = [idx
+                             for idx in 1:length(rows_index)
+                             if colorvec[cols_index[idx]] == color_i]
+                rows_index_c = rows_index[pick_inds]
+                cols_index_c = cols_index[pick_inds]
+                @inbounds @simd for i in 1:length(rows_index_c)
+                    J[rows_index_c[i], cols_index_c[i]] = dx[rows_index_c[i]]
+                end
+            end
+        end
+    end
+    return J
+end
+
 end

ext/SparseDiffToolsPolyesterForwardDiffExt.jl

@@ -5,7 +5,9 @@ import ForwardDiff
 import SparseDiffTools: AbstractMaybeSparseJacobianCache, AbstractMaybeSparsityDetection,
                         ForwardColorJacCache, NoMatrixColoring, sparse_jacobian_cache,
                         sparse_jacobian!,
-                        sparse_jacobian_static_array, __standard_tag, __chunksize
+                        sparse_jacobian_static_array, __standard_tag, __chunksize,
+                        polyesterforwarddiff_color_jacobian,
+                        polyesterforwarddiff_color_jacobian!
 
 struct PolyesterForwardDiffJacobianCache{CO, CA, J, FX, X} <:
        AbstractMaybeSparseJacobianCache
@@ -25,8 +27,6 @@ function sparse_jacobian_cache(
         cache = __chunksize(ad, x)
         jac_prototype = nothing
     else
-        @warn """Currently PolyesterForwardDiff does not support sparsity detection
-                 natively. Falling back to using ForwardDiff.jl""" maxlog=1
         tag = __standard_tag(nothing, x)
         # Colored ForwardDiff passes `tag` directly into Dual so we need the `typeof`
         cache = ForwardColorJacCache(f, x, __chunksize(ad); coloring_result.colorvec,
@@ -45,7 +45,8 @@ function sparse_jacobian_cache(
         jac_prototype = nothing
     else
         @warn """Currently PolyesterForwardDiff does not support sparsity detection
-                 natively. Falling back to using ForwardDiff.jl""" maxlog=1
+                 natively for inplace functions. Falling back to using
+                ForwardDiff.jl""" maxlog=1
         tag = __standard_tag(nothing, x)
         # Colored ForwardDiff passes `tag` directly into Dual so we need the `typeof`
         cache = ForwardColorJacCache(f!, x, __chunksize(ad); coloring_result.colorvec,
@@ -58,7 +59,7 @@ end
 function sparse_jacobian!(J::AbstractMatrix, _, cache::PolyesterForwardDiffJacobianCache,
         f::F, x) where {F}
     if cache.cache isa ForwardColorJacCache
-        forwarddiff_color_jacobian(J, f, x, cache.cache) # Use Sparse ForwardDiff
+        polyesterforwarddiff_color_jacobian(J, f, x, cache.cache)
     else
         PolyesterForwardDiff.threaded_jacobian!(f, J, x, cache.cache) # Don't try to exploit sparsity
     end
@@ -68,7 +69,7 @@ end
 function sparse_jacobian!(J::AbstractMatrix, _, cache::PolyesterForwardDiffJacobianCache,
         f!::F, fx, x) where {F}
     if cache.cache isa ForwardColorJacCache
-        forwarddiff_color_jacobian!(J, f!, x, cache.cache) # Use Sparse ForwardDiff
+        forwarddiff_color_jacobian!(J, f!, x, cache.cache)
     else
         PolyesterForwardDiff.threaded_jacobian!(f!, fx, J, x, cache.cache) # Don't try to exploit sparsity
     end

src/differentiation/compute_jacobian_ad.jl

@@ -173,6 +173,9 @@ function forwarddiff_color_jacobian(f::F, x::AbstractArray{<:Number},
     end
 end
 
+# Defined in extension. Polyester version of `forwarddiff_color_jacobian`
+function polyesterforwarddiff_color_jacobian end
+
 # When J is mutable, this version of forwarddiff_color_jacobian will mutate J to avoid allocations
 function forwarddiff_color_jacobian(J::AbstractMatrix{<:Number}, f::F,
         x::AbstractArray{<:Number},
@@ -249,9 +252,8 @@ function forwarddiff_color_jacobian(J::AbstractMatrix{<:Number}, f::F,
 end
 
 # When J is immutable, this version of forwarddiff_color_jacobian will avoid mutating J
-function forwarddiff_color_jacobian_immutable(f, x::AbstractArray{<:Number},
-        jac_cache::ForwardColorJacCache,
-        jac_prototype = nothing)
+function forwarddiff_color_jacobian_immutable(f::F, x::AbstractArray{<:Number},
+        jac_cache::ForwardColorJacCache, jac_prototype = nothing) where {F}
     t = jac_cache.t
     dx = jac_cache.dx
     p = jac_cache.p
@@ -315,16 +317,16 @@ function forwarddiff_color_jacobian_immutable(f, x::AbstractArray{<:Number},
     return J
 end
 
-function forwarddiff_color_jacobian!(J::AbstractMatrix{<:Number}, f,
+function forwarddiff_color_jacobian!(J::AbstractMatrix{<:Number}, f::F,
         x::AbstractArray{<:Number}; dx = similar(x, size(J, 1)), colorvec = 1:length(x),
-        sparsity = ArrayInterface.has_sparsestruct(J) ? J : nothing)
+        sparsity = ArrayInterface.has_sparsestruct(J) ? J : nothing) where {F}
     forwarddiff_color_jacobian!(J, f, x, ForwardColorJacCache(f, x; dx, colorvec, sparsity))
 end
 
 function forwarddiff_color_jacobian!(J::AbstractMatrix{<:Number},
-        f,
+        f::F,
         x::AbstractArray{<:Number},
-        jac_cache::ForwardColorJacCache)
+        jac_cache::ForwardColorJacCache) where {F}
     t = jac_cache.t
     fx = jac_cache.fx
     dx = jac_cache.dx