Add canonical

Author: blegat

src/Utilities/functions.jl

@@ -1056,6 +1056,29 @@ function canonical(f::MOI.AbstractFunction)
     return g
 end
 
+# Workaround: both `is_canonical` and `canonicalize!` would be slow otherwise
+canonical(f::MOI.ScalarNonlinearFunction) = f
+
+function canonical(f::MOI.ScalarNonlinearFunction)
+    cache = Dict{MOI.AbstractScalarFunction,MOI.AbstractScalarFunction}()
+    # Don't use recursion here. This gets called for all scalar nonlinear
+    # constraints.
+    stack = Any[arg for arg in f.args]
+    while !isempty(stack)
+        arg = pop!(stack)
+        if arg isa MOI.ScalarNonlinearFunction
+            for a in arg.args
+                push!(stack, a)
+            end
+        else
+            if !is_canonical(arg)
+                return false
+            end
+        end
+    end
+    return true
+end
+
 canonicalize!(f::Union{MOI.VectorOfVariables,MOI.VariableIndex}) = f
 
 """

src/Utilities/vector_of_constraints.jl

@@ -73,7 +73,7 @@ function MOI.add_constraint(
 ) where {F<:MOI.AbstractFunction,S<:MOI.AbstractSet}
     # We canonicalize the constraint so that solvers can avoid having to
     # canonicalize it most of the time (they can check if they need to with
-    # `is_canonical`.
+    # `is_canonical`).
     # Note that the canonicalization is not guaranteed if for instance
     # `modify` is called and adds a new term.
     # See https://github.com/jump-dev/MathOptInterface.jl/pull/1118

src/functions.jl

@@ -360,7 +360,7 @@ function Base.copy(f::ScalarNonlinearFunction)
             # We need some sort of hint so that the next time we see this on the
             # stack we evaluate it using the args in `result_stack`. One option
             # would be a custom type. Or we can just wrap in (,) and then check
-            # for a Tuple, which isn't (curretly) a valid argument.
+            # for a Tuple, which isn't (currently) a valid argument.
             push!(stack, (arg,))
             for child in arg.args
                 push!(stack, child)