Improve the error message for VectorNonlinearFunction

src/MOI_wrapper.jl

@@ -81,10 +81,10 @@ end
 
 MOI.supports_constraint(::Optimizer, ::Type{VI}, ::Type{<:ALS}) = true
 MOI.supports_constraint(::Optimizer, ::Type{SAF}, ::Type{<:ALS}) = true
-MOI.supports_constraint(::Optimizer, ::Type{MOI.ScalarNonlinearFunction}, ::Type{<:ALS}) = true
 MOI.supports_constraint(::Optimizer, ::Type{VAF}, ::Type{<:VLS}) = true
 MOI.supports_constraint(::Optimizer, ::Type{SQF}, ::Type{<:ALS}) = true
 MOI.supports_constraint(::Optimizer, ::Type{VQF}, ::Type{<:VLS}) = true
+MOI.supports_constraint(::Optimizer, ::Type{SNF}, ::Type{<:ALS}) = true
 
 function MOI.copy_to(dest::Optimizer, src::MOI.ModelLike)
   if !haskey(dest.options, "solver")

src/utils.jl

@@ -19,6 +19,11 @@ const SQF = MOI.ScalarQuadraticFunction{Float64}  # ScalarQuadraticFunction{T}(a
 const VQF = MOI.VectorQuadraticFunction{Float64}  # VectorQuadraticFunction{T}(affine_terms, quadratic_terms, constants)
 const QF = Union{SQF, VQF}
 
+# ScalarNonlinearFunction and VectorNonlinearFunction
+const SNF = MOI.ScalarNonlinearFunction
+const VNF = MOI.VectorNonlinearFunction
+const NF = Union{SNF, VNF}
+
 # AffLinSets and VecLinSets
 const ALS = Union{
   MOI.EqualTo{Float64},
@@ -375,11 +380,8 @@ function parser_MOI(moimodel, index_map, nvar)
 
   contypes = MOI.get(moimodel, MOI.ListOfConstraintTypesPresent())
   for (F, S) in contypes
-    F <: AF ||
-      F <: QF ||
-      F == MOI.ScalarNonlinearFunction ||
-      F == VI ||
-      error("Function $F is not supported.")
+    (F == VNF) && error("The function $F is not supported. Please use `.<=`, `.==`, and `.>=` in your constraints to ensure compatibility with ScalarNonlinearFunction.")
+    F <: AF || F <: QF || F == SNF || F == VI || error("Function $F is not supported.")
     S <: LS || error("Set $S is not supported.")
 
     conindices = MOI.get(moimodel, MOI.ListOfConstraintIndices{F, S}())
@@ -431,7 +433,7 @@ _nlp_model(::MOI.Nonlinear.Model, ::MOI.ModelLike, ::Type, ::Type) = false
 function _nlp_model(
   dest::MOI.Nonlinear.Model,
   src::MOI.ModelLike,
-  F::Type{<:Union{MOI.ScalarNonlinearFunction, MOI.VectorNonlinearFunction}},
+  F::Type{SNF},
   S::Type,
 )
   has_nonlinear = false
@@ -460,7 +462,7 @@ function _nlp_model(model::MOI.ModelLike)::Union{Nothing, MOI.Nonlinear.Model}
     has_nonlinear |= _nlp_model(nlp_model, model, F, S)
   end
   F = MOI.get(model, MOI.ObjectiveFunctionType())
-  if F <: MOI.ScalarNonlinearFunction
+  if F <: SNF
     MOI.Nonlinear.set_objective(nlp_model, MOI.get(model, MOI.ObjectiveFunction{F}()))
     has_nonlinear = true
   end

test/nlp_problems/nf.jl

@@ -0,0 +1,10 @@
+function nf()
+  f(x::Vector{VariableRef}) = sqrt.(x)
+  g(x::Vector{VariableRef}) = x.^3
+  h(x::Vector{VariableRef}) = sum(x.^4)
+  nlp = Model()
+  @variable(nlp, x[1:2])
+  @constraint(nlp, f(x) .- g(x) .>= 0)
+  @objective(nlp, Max, h(x))
+  return nlp
+end

test/runtests.jl

@@ -5,7 +5,7 @@ using Test, Printf
 nlp_problems = setdiff(NLPModelsTest.nlp_problems, ["MGH01Feas"])
 nls_problems = NLPModelsTest.nls_problems
 
-extra_nlp_problems = ["nohesspb", "hs61", "hs100", "hs219", "quadcon", "operatorspb"]
+extra_nlp_problems = ["nohesspb", "hs61", "hs100", "hs219", "quadcon", "operatorspb", "nf"]
 extra_nls_problems = ["nlsnohesspb", "HS30", "HS43", "MGH07", "nlsqc"]
 
 for problem in lowercase.(nlp_problems ∪ extra_nlp_problems)