SciML · ChrisRackauckas · Jun 21, 2021 · Jun 21, 2021 · Jun 21, 2021 · Jun 21, 2021
diff --git a/Project.toml b/Project.toml
@@ -5,22 +5,22 @@ version = "2.11.4"
 
 [deps]
 ArrayInterface = "4fba245c-0d91-5ea0-9b3e-6abc04ee57a9"
+ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
-ZygoteRules = "700de1a5-db45-46bc-99cf-38207098b444"
 
 [compat]
 ArrayInterface = "2.7, 3.0"
+ChainRulesCore = "0.10.7"
 DocStringExtensions = "0.8"
 RecipesBase = "0.7, 0.8, 1.0"
 Requires = "0.5, 1.0"
 StaticArrays = "0.12, 1.0"
-ZygoteRules = "0.2"
-julia = "1.3"
+julia = "1.6"
 
 [extras]
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"

diff --git a/src/RecursiveArrayTools.jl b/src/RecursiveArrayTools.jl
@@ -6,8 +6,10 @@ module RecursiveArrayTools
 
 using DocStringExtensions
   using Requires, RecipesBase, StaticArrays, Statistics,
-        ArrayInterface, ZygoteRules, LinearAlgebra
+        ArrayInterface, LinearAlgebra
 
+  import ChainRulesCore
+  import ChainRulesCore: NoTangent
   abstract type AbstractVectorOfArray{T, N, A} <: AbstractArray{T, N} end
   abstract type AbstractDiffEqArray{T, N, A} <: AbstractVectorOfArray{T, N, A} end
 

diff --git a/src/init.jl b/src/init.jl
@@ -17,16 +17,16 @@ function __init__()
       return CuArrays.CuArray(reshape(reduce(hcat,vecs),size(VA.u[1])...,length(VA.u)))
     end
     Base.convert(::Type{<:CuArrays.CuArray},VA::AbstractVectorOfArray) = CuArrays.CuArray(VA)
-    @adjoint CuArrays.CuArray(xs::AbstractVectorOfArray) = CuArrays.CuArray(xs), ȳ -> (ȳ,)
+    ChainRules.rrule(::Type{<:CuArrays.CuArray},xs::AbstractVectorOfArray) = CuArrays.CuArray(xs), ȳ -> (NoTangent(),ȳ)
   end
-  
+
   @require CUDA="052768ef-5323-5732-b1bb-66c8b64840ba" begin
     function CUDA.CuArray(VA::AbstractVectorOfArray)
       vecs = vec.(VA.u)
       return CUDA.CuArray(reshape(reduce(hcat,vecs),size(VA.u[1])...,length(VA.u)))
     end
     Base.convert(::Type{<:CUDA.CuArray},VA::AbstractVectorOfArray) = CUDA.CuArray(VA)
-    @adjoint CUDA.CuArray(xs::AbstractVectorOfArray) = CUDA.CuArray(xs), ȳ -> (ȳ,)
+    ChainRules.rrule(::Type{<:CUDA.CuArray},xs::AbstractVectorOfArray) = CUDA.CuArray(xs), ȳ -> (NoTangent(),ȳ)
   end
 
   @require Tracker="9f7883ad-71c0-57eb-9f7f-b5c9e6d3789c" begin

diff --git a/src/zygote.jl b/src/zygote.jl
@@ -1,41 +1,44 @@
-ZygoteRules.@adjoint function getindex(VA::AbstractVectorOfArray, i)
+function ChainRulesCore.rrule(::typeof(getindex),VA::AbstractVectorOfArray, i)
   function AbstractVectorOfArray_getindex_adjoint(Δ)
     Δ′ = [ (i == j ? Δ : zero(x)) for (x,j) in zip(VA.u, 1:length(VA))]
-    (Δ′,nothing)
+    (NoTangent(),Δ′,NoTangent())
   end
   VA[i],AbstractVectorOfArray_getindex_adjoint
 end
 
-ZygoteRules.@adjoint function getindex(VA::AbstractVectorOfArray, i, j...)
+function ChainRulesCore.rrule(::typeof(getindex),VA::AbstractVectorOfArray, i, j...)
   function AbstractVectorOfArray_getindex_adjoint(Δ)
     Δ′ = zero(VA)
     Δ′[i,j...] = Δ
-    (Δ′, i,map(_ -> nothing, j)...)
+    (NoTangent(), Δ′, i,map(_ -> NoTangent(), j)...)
   end
   VA[i,j...],AbstractVectorOfArray_getindex_adjoint
 end
 
-ZygoteRules.@adjoint function ArrayPartition(x::S, ::Type{Val{copy_x}} = Val{false}) where {S<:Tuple,copy_x}
+function ChainRulesCore.rrule(::Type{<:ArrayPartition}, x::S, ::Type{Val{copy_x}} = Val{false}) where {S<:Tuple,copy_x}
   function ArrayPartition_adjoint(_y)
       y = Array(_y)
       starts = vcat(0,cumsum(reduce(vcat,length.(x))))
-      ntuple(i -> reshape(y[starts[i]+1:starts[i+1]], size(x[i])), length(x)), nothing
+      NoTangent(), ntuple(i -> reshape(y[starts[i]+1:starts[i+1]], size(x[i])), length(x)), NoTangent()
   end
 
   ArrayPartition(x, Val{copy_x}), ArrayPartition_adjoint
 end
 
-ZygoteRules.@adjoint function VectorOfArray(u)
-  VectorOfArray(u),y -> ([y[ntuple(x->Colon(),ndims(y)-1)...,i] for i in 1:size(y)[end]],)
+function ChainRulesCore.rrule(::Type{<:VectorOfArray},u)
+  VectorOfArray(u),y -> (NoTangent(),[y[ntuple(x->Colon(),ndims(y)-1)...,i] for i in 1:size(y)[end]])
 end
 
-ZygoteRules.@adjoint function DiffEqArray(u,t)
-  DiffEqArray(u,t),y -> ([y[ntuple(x->Colon(),ndims(y)-1)...,i] for i in 1:size(y)[end]],nothing)
+function ChainRulesCore.rrule(::Type{<:DiffEqArray},u,t)
+  DiffEqArray(u,t),y -> (NoTangent(),[y[ntuple(x->Colon(),ndims(y)-1)...,i] for i in 1:size(y)[end]],NoTangent())
 end
 
-ZygoteRules.@adjoint function ZygoteRules.literal_getproperty(A::ArrayPartition, ::Val{:x})
-  function literal_ArrayPartition_x_adjoint(d)
-      (ArrayPartition((isnothing(d[i]) ? zero(A.x[i]) : d[i] for i in 1:length(d))...),)
-  end
-  A.x,literal_ArrayPartition_x_adjoint
+function ChainRulesCore.rrule(::typeof(getproperty),A::ArrayPartition, s::Symbol)
+    if s !== :x
+        error("$s is not a field of ArrayPartition")
+    end
+    function literal_ArrayPartition_x_adjoint(d)
+        (NoTangent(),ArrayPartition((isnothing(d[i]) ? zero(A.x[i]) : d[i] for i in 1:length(d))...))
+    end
+    A.x,literal_ArrayPartition_x_adjoint
 end