ERROR: type Symbol has no field head

[odow]

https://github.com/lanl-ansi/Alpine.jl/issues/223 rises from the grave.

I don't remember if we support user-defined functions, but we should at least throw a nicer error message:

(alpine) pkg> st
      Status `/private/tmp/alpine/Project.toml`
  [07493b3f] Alpine v0.5.2 `~/.julia/dev/Alpine`
  [87dc4568] HiGHS v1.4.3
  [b6b21f68] Ipopt v1.1.0
  [4076af6c] JuMP v1.7.0
  [2ddba703] Juniper v0.9.1

julia> using JuMP, Alpine, HiGHS, Ipopt, Juniper

julia> nlp_solver = optimizer_with_attributes(Ipopt.Optimizer, MOI.Silent() => true, "sb" => "yes", "max_iter" => Int(1e4));

julia> mip_solver = JuMP.optimizer_with_attributes(HiGHS.Optimizer, "presolve" => "on", "log_to_console" => false);

julia> m = Model(
           optimizer_with_attributes(
               Alpine.Optimizer, 
               "minlp_solver" => optimizer_with_attributes(
                   Juniper.Optimizer,
                   MOI.Silent() => true, 
                   "mip_solver" => mip_solver, 
                   "nl_solver" => nlp_solver,
               ), 
               "nlp_solver" => nlp_solver, 
               "mip_solver" => mip_solver, 
           )
       )
A JuMP Model
Feasibility problem with:
Variables: 0
Model mode: AUTOMATIC
CachingOptimizer state: EMPTY_OPTIMIZER
Solver name: Alpine

julia> @variable(m, x[1:3], Bin)
3-element Vector{VariableRef}:
 x[1]
 x[2]
 x[3]

julia> f_objective(x::T...) where {T<:Real} = x[1] + x[2] + x[3]
f_objective (generic function with 1 method)

julia> register(m, :f_objective, 3, f_objective; autodiff = true)

julia> @NLobjective(m, Min, f_objective(x...))

julia> optimize!(m)
ERROR: type Symbol has no field head
Stacktrace:
  [1] getproperty(x::Symbol, f::Symbol)
    @ Base ./Base.jl:33
  [2] traverse_expr_linear_to_affine(expr::Symbol, lhscoeffs::Vector{Any}, lhsvars::Vector{Any}, rhs::Float64, bufferVal::Nothing, bufferVar::Nothing, sign::Float64, coef::Float64, level::Int64)
    @ Alpine ~/.julia/dev/Alpine/src/nlexpr.jl:356
  [3] traverse_expr_linear_to_affine(expr::Expr, lhscoeffs::Vector{Any}, lhsvars::Vector{Any}, rhs::Float64, bufferVal::Nothing, bufferVar::Nothing, sign::Float64, coef::Float64, level::Int64)
    @ Alpine ~/.julia/dev/Alpine/src/nlexpr.jl:374
  [4] traverse_expr_linear_to_affine
    @ ~/.julia/dev/Alpine/src/nlexpr.jl:332 [inlined]
  [5] expr_linear_to_affine(expr::Expr)
    @ Alpine ~/.julia/dev/Alpine/src/nlexpr.jl:299
  [6] expr_conversion(m::Alpine.Optimizer)
    @ Alpine ~/.julia/dev/Alpine/src/nlexpr.jl:89
  [7] process_expr
    @ ~/.julia/dev/Alpine/src/nlexpr.jl:10 [inlined]
  [8] load!(m::Alpine.Optimizer)
    @ Alpine ~/.julia/dev/Alpine/src/main_algorithm.jl:110
  [9] optimize!(m::Alpine.Optimizer)
    @ Alpine ~/.julia/dev/Alpine/src/main_algorithm.jl:151
 [10] optimize!
    @ ~/.julia/packages/MathOptInterface/NCblk/src/Bridges/bridge_optimizer.jl:376 [inlined]
 [11] optimize!
    @ ~/.julia/packages/MathOptInterface/NCblk/src/MathOptInterface.jl:83 [inlined]
 [12] optimize!(m::MathOptInterface.Utilities.CachingOptimizer{MathOptInterface.Bridges.LazyBridgeOptimizer{Alpine.Optimizer}, MathOptInterface.Utilities.UniversalFallback{MathOptInterface.Utilities.Model{Float64}}})
    @ MathOptInterface.Utilities ~/.julia/packages/MathOptInterface/NCblk/src/Utilities/cachingoptimizer.jl:316
 [13] optimize!(model::Model; ignore_optimize_hook::Bool, _differentiation_backend::MathOptInterface.Nonlinear.SparseReverseMode, kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
    @ JuMP ~/.julia/packages/JuMP/yYfHy/src/optimizer_interface.jl:480
 [14] optimize!(model::Model)
    @ JuMP ~/.julia/packages/JuMP/yYfHy/src/optimizer_interface.jl:458
 [15] top-level scope
    @ REPL[19]:1