Throws an error when legacy JuMP model is used

[sshin23]

closes #198
cc: @klamike @odow

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diff --git a/ext/ExaModelsJuMP.jl b/ext/ExaModelsJuMP.jl
index 879aee6..b66df0d 100644
--- a/ext/ExaModelsJuMP.jl
+++ b/ext/ExaModelsJuMP.jl
@@ -7,7 +7,7 @@ function ExaModels.ExaModel(jm::JuMP.GenericModel{T}; options...) where {T}
     if JuMP.nonlinear_model(jm) != nothing
         error("The legacy nonlinear model interface is not supported. Please use the new MOI-based interface.")
     end
-    
+
     return ExaModels.ExaModel(JuMP.backend(jm); T = T, options...)
 end
 
diff --git a/test/JuMPTest/JuMPTest.jl b/test/JuMPTest/JuMPTest.jl
index 60f2c9a..782cd71 100644
--- a/test/JuMPTest/JuMPTest.jl
+++ b/test/JuMPTest/JuMPTest.jl
@@ -28,14 +28,14 @@ function nlp_legacy_runtests()
     jm = JuMP.Model()
 
     JuMP.@variable(jm, x[1:10])
-    JuMP.@NLobjective(jm, Min, sum(x[i] for i=1:10))
+    JuMP.@NLobjective(jm, Min, sum(x[i] for i in 1:10))
 
     @test_throws ErrorException ExaModel(jm)
 
     jm = JuMP.Model(() -> ExaModels.Optimizer(NLPModelsIpopt.ipopt))
-    @test_throws ErrorException optimize!(jm)
+    return @test_throws ErrorException optimize!(jm)
 end
-    
+
 function fixed_variable_e2etest()
     N=5
     jm = JuMP.Model()

[klamike]

Is it possible to do something similar to this for the ExaModel(::MOI.ModelLike) API?

[amontoison]

Can you be more specific @klamike ?

[klamike]

There are two APIs, ExaModels.Optimizer for solving with ExaModels and ExaModel(::JuMP.Model) to get the underlying examodel directly. I think this fix only covers the first case, not the second.