Merge pull request #382 from AayushSabharwal/as/fix-adjoints

fix: fix `Base.view` adjoints

Author: ChrisRackauckas

ext/RecursiveArrayToolsZygoteExt.jl

@@ -88,7 +88,7 @@ end
 
 @adjoint function Base.copy(u::VectorOfArray)
     copy(u),
-    y -> (copy(y),)
+    tuple ∘ copy
 end
 
 @adjoint function DiffEqArray(u, t)
@@ -115,26 +115,33 @@ end
     adj = let VA = VA
         function Array_adjoint(y)
             VA = recursivecopy(VA)
-            copyto!(VA, y)
+            VA .= y
             return (VA,)
         end
     end
     Array(VA), adj
 end
 
 @adjoint function Base.view(A::AbstractVectorOfArray, I::Colon...)
-    function adjoint(y)
-        (recursivecopy(parent(y)), map(_ -> nothing, I)...)
+    view_adjoint = let A = A, I = I
+        function (y)
+            A = recursivecopy(A)
+            A .= y
+            (A, map(_ -> nothing, I)...)
+        end
     end
-    return view(A, I...), adjoint
+    return view(A, I...), view_adjoint
 end
 
 @adjoint function Base.view(A::AbstractVectorOfArray, I...)
-    function view_adjoint(y)
-        A = recursivecopy(parent(y))
-        recursivefill!(A, zero(eltype(A)))
-        A[I...] .= y
-        return (A, map(_ -> nothing, I)...)
+    view_adjoint = let A = A, I = I
+        function (y)
+            A = recursivecopy(A)
+            recursivefill!(A, zero(eltype(A)))
+            v = view(A, I...)
+            v .= y
+            return (A, map(_ -> nothing, I)...)
+        end
     end
     view(A, I...), view_adjoint
 end

test/adjoints.jl

@@ -66,6 +66,16 @@ function loss9(x)
     return VectorOfArray([collect((3i):(3i + 3)) .* x for i in 1:5])
 end
 
+function loss10(x)
+    voa = VectorOfArray([i * x for i in 1:5])
+    return sum(view(voa, 2:4, 3:5))
+end
+
+function loss11(x)
+    voa = VectorOfArray([i * x for i in 1:5])
+    return sum(view(voa, :, :))
+end
+
 x = float.(6:10)
 loss(x)
 @test Zygote.gradient(loss, x)[1] == ForwardDiff.gradient(loss, x)
@@ -78,3 +88,5 @@ loss(x)
 @test Zygote.gradient(loss8, x)[1] == ForwardDiff.gradient(loss8, x)
 @test ForwardDiff.derivative(loss9, 0.0) ==
       VectorOfArray([collect((3i):(3i + 3)) for i in 1:5])
+@test Zygote.gradient(loss10, x)[1] == ForwardDiff.gradient(loss10, x)
+@test Zygote.gradient(loss11, x)[1] == ForwardDiff.gradient(loss11, x)