MOI wrapper does not validate problem is DCP

[odow]

This line:

Convex.jl/src/MOI_wrapper.jl

Line 243 in 55931d7

MOI.optimize!(model::Optimizer) = MOI.optimize!(model.context.model)

skips checks like:

Convex.jl/src/solution.jl

Lines 101 to 103 in 55931d7

	if problem_vexity(p) in (ConcaveVexity(), NotDcp())
	throw(DCPViolationError())
	end

[odow]

julia> using JuMP, Convex, SCS

julia> model = Model(() -> Convex.Optimizer(SCS.Optimizer))
A JuMP Model
├ solver: Convex with SCS
├ objective_sense: FEASIBILITY_SENSE
├ num_variables: 0
├ num_constraints: 0
└ Names registered in the model: none

julia> @variable(model, x)
x

julia> @constraint(model, @force_nonlinear(x^2) >= 1)
(x ^ 2.0) - 1.0 ≥ 0

julia> optimize!(model)
------------------------------------------------------------------
	       SCS v3.2.7 - Splitting Conic Solver
	(c) Brendan O'Donoghue, Stanford University, 2012
------------------------------------------------------------------
problem:  variables n: 2, constraints m: 4
cones: 	  l: linear vars: 1
	  q: soc vars: 3, qsize: 1
settings: eps_abs: 1.0e-04, eps_rel: 1.0e-04, eps_infeas: 1.0e-07
	  alpha: 1.50, scale: 1.00e-01, adaptive_scale: 1
	  max_iters: 100000, normalize: 1, rho_x: 1.00e-06
	  acceleration_lookback: 10, acceleration_interval: 10
	  compiled with openmp parallelization enabled
lin-sys:  sparse-direct-amd-qdldl
	  nnz(A): 4, nnz(P): 0
------------------------------------------------------------------
 iter | pri res | dua res |   gap   |   obj   |  scale  | time (s)
------------------------------------------------------------------
     0| 3.54e-01  1.11e-01  1.11e-01  5.54e-02  1.00e-01  1.65e-04 
    25| 1.16e-08  8.48e-18  1.27e-17  6.36e-18  1.00e-01  2.44e-04 
------------------------------------------------------------------
status:  solved
timings: total: 2.49e-04s = setup: 7.09e-05s + solve: 1.78e-04s
	 lin-sys: 4.95e-06s, cones: 2.99e-06s, accel: 1.55e-06s
------------------------------------------------------------------
objective = 0.000000
------------------------------------------------------------------

julia> solution_summary(model; verbose = true)
* Solver : Convex with SCS

* Status
  Result count       : 1
  Termination status : OPTIMAL
  Message from the solver:
  "solved"

* Candidate solution (result #1)
  Primal status      : FEASIBLE_POINT
  Dual status        : FEASIBLE_POINT
  Objective value    : 0.00000e+00
  Dual objective value : 1.27215e-17
  Primal solution :
    x : 0.00000e+00
  Dual solution :

* Work counters
  Solve time (sec)   : 2.49338e-04


julia> primal_feasibility_report(model)
Dict{Any, Float64} with 1 entry:
  (x ^ 2.0) - 1.0 ≥ 0 => 1.0