Add literal_getproperty disptach for VectorOfArray

ext/RecursiveArrayToolsZygoteExt.jl

@@ -99,6 +99,30 @@ end
     end
 end
 
+Zygote.@adjoint function Zygote.literal_getproperty(A::RecursiveArrayTools.AbstractVectorOfArray, ::Val{:u})
+    function literal_AbstractVofA_u_adjoint(d)
+        dA = vofa_u_adjoint(d, A)
+        (dA, nothing)
+    end
+    A.u, literal_AbstractVofA_u_adjoint
+end
+
+function vofa_u_adjoint(d, A::RecursiveArrayTools.AbstractVectorOfArray)
+    m = map(enumerate(d)) do (idx, d_i)
+        isnothing(d_i) && return zero(A.u[idx])
+        d_i
+    end
+    VectorOfArray(m)
+end
+
+function vofa_u_adjoint(d, A::RecursiveArrayTools.AbstractDiffEqArray)
+    m = map(enumerate(d)) do (idx, d_i)
+        isnothing(d_i) && return zero(A.u[idx])
+        d_i
+    end
+    DiffEqArray(m, A.t)
+end
+
 @adjoint function 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))...),)

test/adjoints.jl

@@ -92,3 +92,9 @@ loss(x)
       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)
+
+voa = RecursiveArrayTools.VectorOfArray(fill(rand(3), 3))
+voa_gs, = Zygote.gradient(voa) do x
+    sum(sum.(x.u))
+end
+@test voa_gs isa RecursiveArrayTools.VectorOfArray