I want to use my own function as the objective function and optimize it using JuMP.jl.

In this function, I use JuMP variables internally as **Vector{Float64}** to make the calculation more efficient.

However, the type of JuMP variable is **VariableRef**, and if it cannot be converted to **Float64**, an error occurs.

**How can I retrieve the values?**

For example, I assume the following sample program.

```
using JuMP
import Enzyme
import Ipopt
import Test
function f(x)
vec = Vector{Float64}(undef, length(x))
for i in eachindex(vec)
vec[i] = x[i]
end
return (1 - vec[1])^2 + 100 * (vec[2] - vec[1]^2)^2
end
"""
enzyme_derivatives(f::Function) -> Function
Return a tuple of functions that evaluate the gradient and Hessian of `f` using
Enzyme.jl.
"""
function enzyme_derivatives(f::Function)
function ∇f(g::AbstractVector{T}, x::Vararg{T,N}) where {T, N}
g .= Enzyme.autodiff(Enzyme.Reverse, f, Enzyme.Active.(x))[1]
return
end
return ∇f
end
function enzyme_rosenbrock()
model = Model(Ipopt.Optimizer)
set_silent(model)
@variable(model, x[1:2])
@operator(model, op_rosenbrock, 2, f, enzyme_derivatives(f))
@objective(model, Min, op_rosenbrock(x))
optimize!(model)
Test.@test is_solved_and_feasible(model)
return value.(x)
end
s = enzyme_rosenbrock()
display(s)
```

This is a slightly modified version of the JuMP.jl tutorial.

However, when executed, the following error occurs:

```
ERROR: MethodError: Cannot `convert` an object of type VariableRef to an object of type Float64
Closest candidates are:
convert(::Type{T}, ::T) where T
@ Base Base.jl:84
convert(::Type{T}, ::CartesianIndex{1}) where T<:Number
@ Base multidimensional.jl:135
convert(::Type{T}, ::AbstractChar) where T<:Number
@ Base char.jl:185
...
Stacktrace:
[1] setindex!(A::Vector{Float64}, x::VariableRef, i1::Int64)
@ Base ./array.jl:1021
[2] f
@ ~/my_program/GitHub/JuliaOptOS/tests/JuMP/enzyme_sample_approx_hessian2.jl:10 [inlined]
[3] NonlinearOperator
@ ~/.julia/packages/JuMP/7rBNn/src/nlp_expr.jl:893 [inlined]
[4] macro expansion
@ ~/.julia/packages/MutableArithmetics/SXYDN/src/rewrite.jl:340 [inlined]
[5] macro expansion
@ ~/.julia/packages/JuMP/7rBNn/src/macros.jl:257 [inlined]
[6] macro expansion
@ ~/.julia/packages/JuMP/7rBNn/src/macros/@objective.jl:66 [inlined]
[7] enzyme_rosenbrock()
@ Main ~/my_program/GitHub/JuliaOptOS/tests/JuMP/enzyme_sample_approx_hessian2.jl:36
[8] top-level scope
@ ~/my_program/GitHub/JuliaOptOS/tests/JuMP/enzyme_sample_approx_hessian2.jl:42
```