error when JuMP tries autodiff User-defined Function

[KestutisMa]

Hello, I am trying to optimize User-defined function and I got this error:

ERROR: LoadError: MethodError: no method matching Float64(::ForwardDiff.Dual{ForwardDiff.Tag{getfield(JuMP, Symbol("##84#86")){typeof(min_f)},Float64},Float64,11})
Closest candidates are:
  Float64(::Real, ::RoundingMode) where T<:AbstractFloat at rounding.jl:194
  Float64(::T<:Number) where T<:Number at boot.jl:741
  Float64(::Int8) at float.jl:60
  ...
Stacktrace:
 [1] convert(::Type{Float64}, ::ForwardDiff.Dual{ForwardDiff.Tag{getfield(JuMP, Symbol("##84#86")){typeof(min_f)},Float64},Float64,11}) at ./number.jl:7
 [2] setindex! at ./array.jl:769 [inlined]
 [3] MC36SM_Mindaugo_SS(::Float64, ::NTuple{32,ForwardDiff.Dual{ForwardDiff.Tag{getfield(JuMP, Symbol("##84#86")){typeof(min_f)},Float64},Float64,11}}, ::Array{Float64,1}, ::Float64, ::Float64) at /home/kest/Projects/gjJulia/testMC36SM.jl:90

Looks like that it is because of trying to do (in User-defined function for JuMP):

g = zeros(36, 4);
.....
g[.....,.....] = Go[1]

g type is 2D Array of Float64, but Go[1] (optimization variable) passed by JuMP autodiff type is:

Dual{ForwardDiff.Tag{getfield(JuMP, Symbol("##84#86")){typeof(min_f)},Float64}}(0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0)

Any ideas how to solve such type mismatch?

[mlubin]

This was answered at https://discourse.julialang.org/t/dual-forwarddiff-type-error-when-jump-tries-autodiff-user-defined-function/25639/2. In the future, please cross-link when double posting a question.

[KestutisMa]

Ok.