Hi! I am trying to take the gradient of an ODESystem containing a loop using either Zygote or ForwardDiff. Both seem to fail when I do so. Here is a minimal working example (taken from a previous JuliaForum post)

```
using Zygote, SciMLSensitivity, ForwardDiff, DifferentialEquations
# succeeds
function fiip(du,u,p,t)
du[1] = dx = p[1]*u[1] - p[2]*u[1]*u[2]
du[2] = dy = -p[3]*u[2] + p[4]*u[1]*u[2]
end
p = [1.5,1.0,3.0,1.0]; u0 = [1.0;1.0]
prob = ODEProblem(fiip,u0,(0.0,10.0),p)
sol = solve(prob,Tsit5())
plot(sol)
function sum_of_solution(x)
_prob = remake(prob,p=x)
sum(solve(_prob,Tsit5(),saveat=0.1))
end
ForwardDiff.gradient(sum_of_solution,p)
# fails with both Zygote and ForwardDiff
function fiip(du,u,p,t,N)
sv = zeros(Int64(2))
for i in 1:N
sv[i] = u[i]
end
du[1] = dx = p[1]*sv[1] - p[2]*u[1]*u[2]
du[2] = dy = -p[3]*sv[2] + p[4]*u[1]*u[2]
end
p = [1.5,1.0,3.0,1.0]; u0 = [1.0;1.0]
fiip2(du,u0,p,t) = fiip(du,u0,p,t, 2)
prob = ODEProblem(fiip2,u0,(0.0,10.0),p)
sol = solve(prob,Tsit5())
plot(sol)
function sum_of_solution(x)
_prob = remake(prob,p=x)
sum(solve(_prob,Tsit5(),saveat=0.1))
end
ForwardDiff.gradient(sum_of_solution,p)
```

The loop really is necessary in my minimum working example, as using a state variable that is a sum of lots of the us… Any idea how to get this working?