How to check if a user-defined function is already registered in Julia/JuMP

Question

I want to check if a user-defined function is already registered in JuMP/julia. Here's an example:

function foo( f, f1, f2 )

  if !function_is_registered(:f)  # This is what I'm looking for
    JuMP.register(:f,1,f1,f2)
  end
  ####
    # Optimization problem here using f
    # Leads to some return statement
  ####
end

f(x) = exp( A * x )
f1(x) = A * exp( A * x )
f2(x) = A * A * exp( A * x )
    # Function to register

A = 2
use1 = foo(f, f1, f2)
use2 = foo(f, f1, f2)
    # This second usage would fail without the check.  Can't re-register f.

As should be obvious from the comments, the check is needed for the second usage. As far as I can tell, JuMP registers functions at a global level - once registered they can't be re-defined locally (right? If they can, this solves my problem too!).

Answer 1

This will do what you want.

using JuMP
using Ipopt

function set_A_sol( A )
  f = (x) -> exp( A * x ) - x
  f1 = (x) -> A * exp( A * x ) - 1.0
  f2 = (x) -> A * A * exp( A * x )
  # Local redefinition of f
  try
    JuMP.register(:f, 1, f, f1, f2)
  catch e
    if e.msg == "Operator f has already been defined"
      ind = pop!( ReverseDiffSparse.univariate_operator_to_id, :f);
      deleteat!( ReverseDiffSparse.univariate_operators, ind);
      pop!( ReverseDiffSparse.user_univariate_operator_f, ind);
      pop!( ReverseDiffSparse.user_univariate_operator_fprime, ind);
      pop!( ReverseDiffSparse.user_univariate_operator_fprimeprime, ind);
      JuMP.register(:f, 1, f, f1, f2);
    end
  end
  mod = Model(solver=Ipopt.IpoptSolver(print_level=0))
  @variable(mod, - Inf <= x <= Inf )
  @NLobjective(mod, Min, f(x) )
  status=solve(mod)
  return getvalue(x)
end

julia> ans1 = set_A_sol(0.5)
1.3862943611200509

julia> ans2 = set_A_sol(1.0)
0.0

julia> ans3 = set_A_sol(2.0)
-0.34657359027997264

Explanation:

If you look at the register function, defined in nlp.jl, "Registering" involves adding the symbol to a dictionary, held in ReverseDiffSparse. Register a function and check those dictionaries manually to see what they look like.

So "de-registering" simply involves removing all traces of :f and its derivatives from all the places where it has been recorded.