I am using NNs created using `Flux`

to parameterize a function which I want to approximate in an optimal control problem. I formulate the associated optimization problem and call `Optim`

, which works thanks to `FLuXOptTools`

. However, I am getting the following message:

```
Warning: `ForwardDiff.derivative(f, x)` within Zygote cannot track gradients with respect to `f`,
│ and `f` appears to be a closure, or a struct with fields (according to `issingletontype(typeof(f))`).
│ typeof(f) = var"#7#8"{Vector{Float64}}
└ @ Zygote C:\Users\Gabriel\.julia\packages\Zygote\TSj5C\src\lib\forward.jl:158
```

*Does anyone know why I am getting this?* I’ve tried perusing around `Zygote`

but couldn’t understand where this is coming from. I am afraid this has to do with second derivatives, so it ends up not affecting my algorithm since I am using first-order methods only (?).

As a matter of fact, the objective function decreases as well as the gradient norm, but it gets stuck halfway through. Most likely a numerical issue, and not related to the warning above, but figured I would share nonetheless… Thank you!