Merge pull request #1451 from JuliaOpt/bl/moiv0.6

Updates to MOI v0.6

REQUIRE

@@ -1,6 +1,6 @@
 julia 0.6
-MathOptInterface 0.5 0.6
-ForwardDiff 0.5 0.9
+MathOptInterface 0.6 0.7
+ForwardDiff 0.5 0.10
 Calculus
 DataStructures
 NaNMath 0.2.1

src/JuMP.jl

@@ -59,7 +59,20 @@ const MOIFIX = MOICON{MOI.SingleVariable,MOI.EqualTo{Float64}}
 const MOIINT = MOICON{MOI.SingleVariable,MOI.Integer}
 const MOIBIN = MOICON{MOI.SingleVariable,MOI.ZeroOne}
 
-@MOIU.model JuMPMOIModel (ZeroOne, Integer) (EqualTo, GreaterThan, LessThan, Interval) (Zeros, Nonnegatives, Nonpositives, SecondOrderCone, RotatedSecondOrderCone, GeometricMeanCone, PositiveSemidefiniteConeTriangle, PositiveSemidefiniteConeSquare, RootDetConeTriangle, RootDetConeSquare, LogDetConeTriangle, LogDetConeSquare) () (SingleVariable,) (ScalarAffineFunction,ScalarQuadraticFunction) (VectorOfVariables,) (VectorAffineFunction,)
+@MOIU.model(JuMPMOIModel,
+            (MOI.ZeroOne, MOI.Integer),
+            (MOI.EqualTo, MOI.GreaterThan, MOI.LessThan, MOI.Interval),
+            (MOI.Zeros, MOI.Nonnegatives, MOI.Nonpositives, MOI.SecondOrderCone,
+             MOI.RotatedSecondOrderCone, MOI.GeometricMeanCone,
+             MOI.PositiveSemidefiniteConeTriangle,
+             MOI.PositiveSemidefiniteConeSquare,
+             MOI.RootDetConeTriangle, MOI.RootDetConeSquare,
+             MOI.LogDetConeTriangle, MOI.LogDetConeSquare),
+            (),
+            (MOI.SingleVariable,),
+            (MOI.ScalarAffineFunction, MOI.ScalarQuadraticFunction),
+            (MOI.VectorOfVariables,),
+            (MOI.VectorAffineFunction,))
 
 """
     OptimizerFactory
@@ -123,7 +136,7 @@ end
 # Model has three modes:
 # 1) Automatic: moi_backend field holds a LazyBridgeOptimizer{CachingOptimizer} in Automatic mode.
 # 2) Manual: moi_backend field holds a LazyBridgeOptimizer{CachingOptimizer} in Manual mode.
-# 3) Direct: moi_backend field holds an AbstractOptimizer. No extra copy of the model is stored. The moi_backend must support addconstraint! etc.
+# 3) Direct: moi_backend field holds an AbstractOptimizer. No extra copy of the model is stored. The moi_backend must support add_constraint etc.
 # Methods to interact with the CachingOptimizer are defined in solverinterface.jl.
 @enum ModelMode Automatic Manual Direct
 
@@ -231,7 +244,7 @@ in mind the following implications of creating models using this *direct* mode:
 * The model created cannot be copied.
 """
 function direct_model(backend::MOI.ModelLike)
-    @assert MOI.isempty(backend)
+    @assert MOI.is_empty(backend)
     return Model(Dict{MOIVAR, MOILB}(),
                  Dict{MOIVAR, MOIUB}(),
                  Dict{MOIVAR, MOIFIX}(),
@@ -490,7 +503,7 @@ function delete(model::Model, constraint_ref::ConstraintRef{Model})
         error("The constraint reference you are trying to delete does not " *
               "belong to the model.")
     end
-    MOI.delete!(model.moi_backend, index(constraint_ref))
+    MOI.delete(model.moi_backend, index(constraint_ref))
 end
 
 """
@@ -500,7 +513,7 @@ Return `true` if `constraint_ref` refers to a valid constraint in `model`.
 """
 function is_valid(model::Model, constraint_ref::ConstraintRef{Model})
     return (model === constraint_ref.m &&
-            MOI.isvalid(model.moi_backend, constraint_ref.index))
+            MOI.is_valid(model.moi_backend, constraint_ref.index))
 end
 
 """
@@ -510,15 +523,15 @@ Add a constraint `c` to `Model m` and sets its name.
 """
 function add_constraint(m::Model, c::AbstractConstraint, name::String="")
     f, s = moi_function_and_set(c)
-    if !MOI.supportsconstraint(m.moi_backend, typeof(f), typeof(s))
+    if !MOI.supports_constraint(m.moi_backend, typeof(f), typeof(s))
         if m.moi_backend isa MOI.Bridges.LazyBridgeOptimizer
             bridge_message = " and there are no bridges that can reformulate it into supported constraints."
         else
             bridge_message = ", try using `bridge_constraints=true` in the `JuMP.Model` constructor if you believe the constraint can be reformulated to constraints supported by the solver."
         end
         error("Constraints of type $(typeof(f))-in-$(typeof(s)) are not supported by the solver" * bridge_message)
     end
-    cindex = MOI.addconstraint!(m.moi_backend, f, s)
+    cindex = MOI.add_constraint(m.moi_backend, f, s)
     cref = ConstraintRef(m, cindex, shape(c))
     if !isempty(name)
         set_name(cref, name)
@@ -573,8 +586,9 @@ end
 
 index(cr::ConstraintRef) = cr.index
 
-function has_result_dual(m::Model, REF::Type{<:ConstraintRef{Model, T}}) where {T <: MOICON}
-    MOI.canget(m, MOI.ConstraintDual(), REF)
+function has_result_dual(model::Model,
+                         REF::Type{<:ConstraintRef{Model, T}}) where {T <: MOICON}
+    MOI.get(model, MOI.DualStatus()) != MOI.NoSolution
 end
 
 """
@@ -595,20 +609,7 @@ Get a constraint's name.
 """
 name(cr::ConstraintRef{Model,<:MOICON}) = MOI.get(cr.m, MOI.ConstraintName(), cr)
 
-set_name(cr::ConstraintRef{Model,<:MOICON}, s::String) = MOI.set!(cr.m, MOI.ConstraintName(), cr, s)
-
-"""
-    canget(m::JuMP.Model, attr::MathOptInterface.AbstractModelAttribute)::Bool
-
-Return `true` if one may query the attribute `attr` from the model's MOI backend.
-false if not.
-"""
-MOI.canget(m::Model, attr::MOI.AbstractModelAttribute) = MOI.canget(m.moi_backend, attr)
-MOI.canget(m::Model, attr::MOI.AbstractVariableAttribute, ::Type{VariableRef}) = MOI.canget(m.moi_backend, attr, MOIVAR)
-function MOI.canget(model::Model, attr::MOI.AbstractConstraintAttribute,
-                    ::Type{<:ConstraintRef{Model, T}}) where {T <: MOICON}
-    return MOI.canget(model.moi_backend, attr, T)
-end
+set_name(cr::ConstraintRef{Model,<:MOICON}, s::String) = MOI.set(cr.m, MOI.ConstraintName(), cr, s)
 
 """
     get(m::JuMP.Model, attr::MathOptInterface.AbstractModelAttribute)
@@ -625,14 +626,14 @@ function MOI.get(m::Model, attr::MOI.AbstractConstraintAttribute, cr::Constraint
     MOI.get(m.moi_backend, attr, index(cr))
 end
 
-MOI.set!(m::Model, attr::MOI.AbstractModelAttribute, value) = MOI.set!(m.moi_backend, attr, value)
-function MOI.set!(m::Model, attr::MOI.AbstractVariableAttribute, v::VariableRef, value)
+MOI.set(m::Model, attr::MOI.AbstractModelAttribute, value) = MOI.set(m.moi_backend, attr, value)
+function MOI.set(m::Model, attr::MOI.AbstractVariableAttribute, v::VariableRef, value)
     @assert m === v.m
-    MOI.set!(m.moi_backend, attr, index(v), value)
+    MOI.set(m.moi_backend, attr, index(v), value)
 end
-function MOI.set!(m::Model, attr::MOI.AbstractConstraintAttribute, cr::ConstraintRef, value)
+function MOI.set(m::Model, attr::MOI.AbstractConstraintAttribute, cr::ConstraintRef, value)
     @assert m === cr.m
-    MOI.set!(m.moi_backend, attr, index(cr), value)
+    MOI.set(m.moi_backend, attr, index(cr), value)
 end
 
 ###############################################################################

src/affexpr.jl

@@ -287,8 +287,8 @@ function set_objective(m::Model, sense::Symbol, a::AffExpr)
         @assert sense == :Max
         moisense = MOI.MaxSense
     end
-    MOI.set!(m.moi_backend, MOI.ObjectiveSense(), moisense)
-    MOI.set!(m.moi_backend, MOI.ObjectiveFunction{MOI.ScalarAffineFunction{Float64}}(), MOI.ScalarAffineFunction(a))
+    MOI.set(m.moi_backend, MOI.ObjectiveSense(), moisense)
+    MOI.set(m.moi_backend, MOI.ObjectiveFunction{MOI.ScalarAffineFunction{Float64}}(), MOI.ScalarAffineFunction(a))
     nothing
 end
 

src/copy.jl

@@ -107,8 +107,8 @@ function copy_model(model::Model)
     # Copy the MOI backend, note that variable and constraint indices may have
     # changed, the `index_map` gives the map between the indices of
     # `model.moi_backend` and the indices of `new_model.moi_backend`.
-    index_map = MOI.copy!(new_model.moi_backend, model.moi_backend,
-                          copynames = true)
+    index_map = MOI.copy_to(new_model.moi_backend, model.moi_backend,
+                            copy_names = true)
     # TODO copynames is needed because of https://github.com/JuliaOpt/MathOptInterface.jl/issues/494
     #      we can remove it when this is fixed and released
 

src/macros.jl

@@ -1301,7 +1301,7 @@ macro variable(args...)
         addkwargs!(buildcall, extra_kwargs)
         variablecall = :( add_variable($model, $buildcall, $(namecall(basename, idxvars))) )
         code = :( $(refcall) = $variablecall )
-        # Determine the return type of addvariable. This is needed to create the container holding them.
+        # Determine the return type of add_variable. This is needed to create the container holding them.
         vartype = :( variabletype($model, $(extra...)) )
 
         if symmetric

src/nlp.jl

@@ -17,7 +17,7 @@ function set_objective(m::Model, sense::Symbol, ex::NonlinearExprData)
         @assert sense == :Max
         moisense = MOI.MaxSense
     end
-    MOI.set!(m.moi_backend, MOI.ObjectiveSense(), moisense)
+    MOI.set(m.moi_backend, MOI.ObjectiveSense(), moisense)
     m.nlp_data.nlobj = ex
     # TODO: what do we do about existing objectives in the MOI backend?
     return
@@ -120,9 +120,6 @@ end
 function result_dual(c::ConstraintRef{Model,NonlinearConstraintIndex})
     initNLP(c.m)
     nldata::NLPData = c.m.nlp_data
-    if !MOI.canget(c.m, MOI.NLPBlockDual())
-        error("Duals not available.")
-    end
     # The array is cleared on every solve.
     if length(nldata.nlconstr_duals) != length(nldata.nlconstr)
         nldata.nlconstr_duals = MOI.get(c.m, MOI.NLPBlockDual())
@@ -269,7 +266,7 @@ function SubexpressionStorage(nd::Vector{NodeData}, const_values, num_variables,
 
 end
 
-function MOI.initialize!(d::NLPEvaluator, requested_features::Vector{Symbol})
+function MOI.initialize(d::NLPEvaluator, requested_features::Vector{Symbol})
     nldata::NLPData = d.m.nlp_data
 
     # Check if we have any user-defined operators, in which case we need to

src/optimizerinterface.jl

@@ -40,7 +40,7 @@ function optimize!(model::Model,
     # The nlp_data is not kept in sync, so re-set it here.
     # TODO: Consider how to handle incremental solves.
     if model.nlp_data !== nothing
-        MOI.set!(model, MOI.NLPBlock(), create_nlp_block_data(model))
+        MOI.set(model, MOI.NLPBlock(), create_nlp_block_data(model))
         empty!(model.nlp_data.nlconstr_duals)
     end
 

src/parseexpr.jl

@@ -241,7 +241,7 @@ function destructive_add!(ex::GenericQuadExpr{C,V}, c::GenericAffExpr{C,V}, x::G
     destructive_add!(ex, 1.0, c*x)
 end
 
-# Catch nonlinear expressions and parameters being used in addconstraint, etc.
+# Catch nonlinear expressions and parameters being used in add_constraint, etc.
 
 const _NLExpr = Union{NonlinearExpression,NonlinearParameter}
 _nlexprerr() = error("""Cannot use nonlinear expression or parameter in @constraint or @objective.

src/quadexpr.jl

@@ -210,8 +210,8 @@ function set_objective(m::Model, sense::Symbol, a::QuadExpr)
         @assert sense == :Max
         moisense = MOI.MaxSense
     end
-    MOI.set!(m.moi_backend, MOI.ObjectiveSense(), moisense)
-    MOI.set!(m.moi_backend, MOI.ObjectiveFunction{MOI.ScalarQuadraticFunction{Float64}}(), MOI.ScalarQuadraticFunction(a))
+    MOI.set(m.moi_backend, MOI.ObjectiveSense(), moisense)
+    MOI.set(m.moi_backend, MOI.ObjectiveFunction{MOI.ScalarQuadraticFunction{Float64}}(), MOI.ScalarQuadraticFunction(a))
     nothing
 end
 

src/variables.jl

@@ -121,7 +121,7 @@ function delete(model::Model, variable_ref::VariableRef)
         error("The variable reference you are trying to delete does not " *
               "belong to the model.")
     end
-    MOI.delete!(model.moi_backend, variable_ref.index)
+    MOI.delete(model.moi_backend, variable_ref.index)
 end
 
 """
@@ -131,7 +131,7 @@ Return `true` if `variable` refers to a valid variable in `model`.
 """
 function is_valid(model::Model, variable_ref::VariableRef)
     return (model === variable_ref.m &&
-            MOI.isvalid(model.moi_backend, variable_ref.index))
+            MOI.is_valid(model.moi_backend, variable_ref.index))
 end
 
 # The default hash is slow. It's important for the performance of AffExpr to
@@ -182,7 +182,7 @@ Base.haskey(vm::VariableToValueMap, v::VariableRef) = (vm.m === v.m) && haskey(v
 index(v::VariableRef) = v.index
 
 function VariableRef(m::Model)
-    index = MOI.addvariable!(m.moi_backend)
+    index = MOI.add_variable(m.moi_backend)
     return VariableRef(m, index)
 end
 
@@ -200,7 +200,7 @@ name(v::VariableRef) = MOI.get(v.m, MOI.VariableName(), v)
 
 Set a variable's name.
 """
-set_name(v::VariableRef, s::String) = MOI.set!(v.m, MOI.VariableName(), v, s)
+set_name(v::VariableRef, s::String) = MOI.set(v.m, MOI.VariableName(), v, s)
 
 MOI.SingleVariable(v::VariableRef) = MOI.SingleVariable(index(v))
 
@@ -217,8 +217,8 @@ function set_objective(m::Model, sense::Symbol, x::VariableRef)
         @assert sense == :Max
         moisense = MOI.MaxSense
     end
-    MOI.set!(m.moi_backend, MOI.ObjectiveSense(), moisense)
-    MOI.set!(m.moi_backend, MOI.ObjectiveFunction{MOI.SingleVariable}(),
+    MOI.set(m.moi_backend, MOI.ObjectiveSense(), moisense)
+    MOI.set(m.moi_backend, MOI.ObjectiveFunction{MOI.SingleVariable}(),
              MOI.SingleVariable(x))
 end
 
@@ -297,10 +297,10 @@ function set_lower_bound(v::VariableRef,lower::Number)
     # do we have a lower bound already?
     if has_lower_bound(v)
         cindex = lower_bound_index(v)
-        MOI.set!(v.m.moi_backend, MOI.ConstraintSet(), cindex, newset)
+        MOI.set(v.m.moi_backend, MOI.ConstraintSet(), cindex, newset)
     else
         @assert !is_fixed(v)
-        cindex = MOI.addconstraint!(v.m.moi_backend, MOI.SingleVariable(index(v)), newset)
+        cindex = MOI.add_constraint(v.m.moi_backend, MOI.SingleVariable(index(v)), newset)
         set_lower_bound_index(v, cindex)
     end
     nothing
@@ -354,10 +354,10 @@ function set_upper_bound(v::VariableRef,upper::Number)
     # do we have an upper bound already?
     if has_upper_bound(v)
         cindex = upper_bound_index(v)
-        MOI.set!(v.m.moi_backend, MOI.ConstraintSet(), cindex, newset)
+        MOI.set(v.m.moi_backend, MOI.ConstraintSet(), cindex, newset)
     else
         @assert !is_fixed(v)
-        cindex = MOI.addconstraint!(v.m.moi_backend, MOI.SingleVariable(index(v)), newset)
+        cindex = MOI.add_constraint(v.m.moi_backend, MOI.SingleVariable(index(v)), newset)
         set_upper_bound_index(v, cindex)
     end
     nothing
@@ -411,10 +411,10 @@ function fix(v::VariableRef,upper::Number)
     # are we already fixed?
     if is_fixed(v)
         cindex = fix_index(v)
-        MOI.set!(v.m.moi_backend, MOI.ConstraintSet(), cindex, newset)
+        MOI.set(v.m.moi_backend, MOI.ConstraintSet(), cindex, newset)
     else
         @assert !has_upper_bound(v) && !has_lower_bound(v) # Do we want to remove these instead of throwing an error?
-        cindex = MOI.addconstraint!(v.m.moi_backend, MOI.SingleVariable(index(v)), newset)
+        cindex = MOI.add_constraint(v.m.moi_backend, MOI.SingleVariable(index(v)), newset)
         set_fix_index(v, cindex)
     end
     nothing
@@ -470,7 +470,7 @@ function set_integer(variable_ref::VariableRef)
         error("Cannot set the variable_ref $(variable_ref) to integer as it " *
               "is already binary.")
     end
-    constraint_ref = MOI.addconstraint!(variable_ref.m.moi_backend,
+    constraint_ref = MOI.add_constraint(variable_ref.m.moi_backend,
                                 MOI.SingleVariable(index(variable_ref)),
                                 MOI.Integer())
     set_integer_index(variable_ref, constraint_ref)
@@ -510,7 +510,7 @@ function set_binary(variable_ref::VariableRef)
         error("Cannot set the variable_ref $(variable_ref) to binary as it " *
               "is already integer.")
     end
-    constraint_ref = MOI.addconstraint!(variable_ref.m.moi_backend,
+    constraint_ref = MOI.add_constraint(variable_ref.m.moi_backend,
                                 MOI.SingleVariable(index(variable_ref)),
                                 MOI.ZeroOne())
     set_binary_index(variable_ref, constraint_ref)
@@ -530,7 +530,7 @@ end
 
 
 start_value(v::VariableRef) = MOI.get(v.m, MOI.VariablePrimalStart(), v)
-set_start_value(v::VariableRef, val::Number) = MOI.set!(v.m, MOI.VariablePrimalStart(), v, val)
+set_start_value(v::VariableRef, val::Number) = MOI.set(v.m, MOI.VariablePrimalStart(), v, val)
 
 """
     result_value(v::VariableRef)
@@ -540,7 +540,9 @@ Use `has_result_values` to check if a result exists before asking for values.
 Replaces `getvalue` for most use cases.
 """
 result_value(v::VariableRef) = MOI.get(v.m, MOI.VariablePrimal(), v)
-has_result_values(m::Model) = MOI.canget(m, MOI.VariablePrimal(), VariableRef)
+function has_result_values(model::Model)
+    return MOI.get(model, MOI.PrimalStatus()) != MOI.NoSolution
+end
 
 @Base.deprecate setvalue(v::VariableRef, val::Number) set_start_value(v, val)
 

test/JuMPExtension.jl

@@ -152,8 +152,14 @@ function JuMP.set_objective(m::MyModel, sense::Symbol, f::JuMP.AbstractJuMPScala
 end
 JuMP.objective_sense(m::MyModel) = m.objectivesense
 function JuMP.objective_function(m::MyModel, FT::Type)
-    # ErrorException should be thrown, this is needed in `objective.jl`
-    m.objective_function isa FT || error("The objective function is not of type $FT")
+    # InexactError should be thrown, this is needed in `objective.jl`
+    if !(m.objective_function isa FT)
+        if VERSION < v"0.7-"
+            throw(InexactError())
+        else
+            throw(InexactError(:objective_function, FT, typeof(m.objective_function)))
+        end
+    end
     m.objective_function
 end