Static arrays + autodiff

I tried using static vectors for parameters, which works nicely. But not when combined with autodiff:

julia> using Optimization, OptimizationOptimJL, StaticArrays, ForwardDiff

# don't specify inplace/outofplace:

julia> of = OptimizationFunction((x, p) -> sum(x), Optimization.AutoForwardDiff())
julia> prob = OptimizationProblem(of, SVector(0., 0.), nothing)
julia> solve(prob, Optim.GradientDescent())
ERROR: setindex!(::SVector{2, Float64}, value, ::Int) is not defined.

# specify out of place:

julia> of = OptimizationFunction{false}((x, p) -> sum(x), Optimization.AutoForwardDiff())
julia> prob = OptimizationProblem(of, SVector(0., 0.), nothing)
julia> solve(prob, Optim.GradientDescent())
ERROR: Use OptimizationFunction to pass the derivatives or automatically generate them with one of the autodiff backends

Is this expected?

Reproduce both Julia examples from the issue using Optimization, OptimizationOptimJL, StaticArrays, and ForwardDiff. Trace how OptimizationFunction and Optim.GradientDescent handle SVector inputs and autodiff, then inspect existing tests for static or out-of-place objectives. Done means the supported behavior is verified and covered, or the limitation is clearly documented.