Update function.jl

Changed the position of the MOO function checks in instantiate_function.

Author: ParasPuneetSingh

src/function.jl

@@ -43,13 +43,17 @@ function that is not defined, an error is thrown.
 For more information on the use of automatic differentiation, see the
 documentation of the `AbstractADType` types.
 """
-function instantiate_function(f, x, ::SciMLBase.NoAD,
+
+
+function instantiate_function(f::MultiObjectiveOptimizationFunction, x, ::SciMLBase.NoAD,
         p, num_cons = 0)
-    grad = f.grad === nothing ? nothing : (G, x, args...) -> f.grad(G, x, p, args...)
-    hess = f.hess === nothing ? nothing : (H, x, args...) -> f.hess(H, x, p, args...)
+    jac = f.jac === nothing ? nothing : (J, x, args...) -> f.jac(J, x, p, args...)
+    hess = f.hess === nothing ? nothing : [(H, x, args...) -> h(H, x, p, args...) for h in f.hess]
     hv = f.hv === nothing ? nothing : (H, x, v, args...) -> f.hv(H, x, v, p, args...)
     cons = f.cons === nothing ? nothing : (res, x) -> f.cons(res, x, p)
     cons_j = f.cons_j === nothing ? nothing : (res, x) -> f.cons_j(res, x, p)
+    cons_jvp = f.cons_jvp === nothing ? nothing : (res, x) -> f.cons_jvp(res, x, p)
+    cons_vjp = f.cons_vjp === nothing ? nothing : (res, x) -> f.cons_vjp(res, x, p)
     cons_h = f.cons_h === nothing ? nothing : (res, x) -> f.cons_h(res, x, p)
     hess_prototype = f.hess_prototype === nothing ? nothing :
                      convert.(eltype(x), f.hess_prototype)
@@ -61,9 +65,9 @@ function instantiate_function(f, x, ::SciMLBase.NoAD,
     expr = symbolify(f.expr)
     cons_expr = symbolify.(f.cons_expr)
 
-    return OptimizationFunction{true}(f.f, SciMLBase.NoAD(); grad = grad, hess = hess,
+    return MultiObjectiveOptimizationFunction{true}(f.f, SciMLBase.NoAD(); jac = jac, hess = hess,
         hv = hv,
-        cons = cons, cons_j = cons_j, cons_h = cons_h,
+        cons = cons, cons_j = cons_j, cons_jvp = cons_jvp, cons_vjp = cons_vjp, cons_h = cons_h,
         hess_prototype = hess_prototype,
         cons_jac_prototype = cons_jac_prototype,
         cons_hess_prototype = cons_hess_prototype,
@@ -72,13 +76,28 @@ function instantiate_function(f, x, ::SciMLBase.NoAD,
         observed = f.observed)
 end
 
-function instantiate_function(f, cache::ReInitCache, ::SciMLBase.NoAD,
+function instantiate_function(f::MultiObjectiveOptimizationFunction, x, adtype::ADTypes.AbstractADType,
+        p, num_cons = 0)
+    adtypestr = string(adtype)
+    _strtind = findfirst('.', adtypestr)
+    strtind = isnothing(_strtind) ? 5 : _strtind + 5
+    open_nrmlbrkt_ind = findfirst('(', adtypestr)
+    open_squigllybrkt_ind = findfirst('{', adtypestr)
+    open_brkt_ind = isnothing(open_squigllybrkt_ind) ? open_nrmlbrkt_ind :
+                    min(open_nrmlbrkt_ind, open_squigllybrkt_ind)
+    adpkg = adtypestr[strtind:(open_brkt_ind - 1)]
+    throw(ArgumentError("The passed automatic differentiation backend choice is not available. Please load the corresponding AD package $adpkg."))
+end
+
+function instantiate_function(f::MultiObjectiveOptimizationFunction, cache::ReInitCache, ::SciMLBase.NoAD,
         num_cons = 0)
-    grad = f.grad === nothing ? nothing : (G, x, args...) -> f.grad(G, x, cache.p, args...)
-    hess = f.hess === nothing ? nothing : (H, x, args...) -> f.hess(H, x, cache.p, args...)
+    jac = f.jac === nothing ? nothing : (J, x, args...) -> f.jac(J, x, cache.p, args...)
+    hess = f.hess === nothing ? nothing : [(H, x, args...) -> h(H, x, cache.p, args...) for h in f.hess]
     hv = f.hv === nothing ? nothing : (H, x, v, args...) -> f.hv(H, x, v, cache.p, args...)
     cons = f.cons === nothing ? nothing : (res, x) -> f.cons(res, x, cache.p)
     cons_j = f.cons_j === nothing ? nothing : (res, x) -> f.cons_j(res, x, cache.p)
+    cons_jvp = f.cons_jvp === nothing ? nothing : (res, x) -> f.cons_jvp(res, x, cache.p)
+    cons_vjp = f.cons_vjp === nothing ? nothing : (res, x) -> f.cons_vjp(res, x, cache.p)
     cons_h = f.cons_h === nothing ? nothing : (res, x) -> f.cons_h(res, x, cache.p)
     hess_prototype = f.hess_prototype === nothing ? nothing :
                      convert.(eltype(cache.u0), f.hess_prototype)
@@ -90,9 +109,9 @@ function instantiate_function(f, cache::ReInitCache, ::SciMLBase.NoAD,
     expr = symbolify(f.expr)
     cons_expr = symbolify.(f.cons_expr)
 
-    return OptimizationFunction{true}(f.f, SciMLBase.NoAD(); grad = grad, hess = hess,
+    return MultiObjectiveOptimizationFunction{true}(f.f, SciMLBase.NoAD(); jac = jac, hess = hess,
         hv = hv,
-        cons = cons, cons_j = cons_j, cons_h = cons_h,
+        cons = cons, cons_j = cons_j, cons_jvp = cons_jvp, cons_vjp = cons_vjp, cons_h = cons_h,
         hess_prototype = hess_prototype,
         cons_jac_prototype = cons_jac_prototype,
         cons_hess_prototype = cons_hess_prototype,
@@ -101,28 +120,14 @@ function instantiate_function(f, cache::ReInitCache, ::SciMLBase.NoAD,
         observed = f.observed)
 end
 
-function instantiate_function(f, x, adtype::ADTypes.AbstractADType,
-        p, num_cons = 0)
-    adtypestr = string(adtype)
-    _strtind = findfirst('.', adtypestr)
-    strtind = isnothing(_strtind) ? 5 : _strtind + 5
-    open_nrmlbrkt_ind = findfirst('(', adtypestr)
-    open_squigllybrkt_ind = findfirst('{', adtypestr)
-    open_brkt_ind = isnothing(open_squigllybrkt_ind) ? open_nrmlbrkt_ind :
-                    min(open_nrmlbrkt_ind, open_squigllybrkt_ind)
-    adpkg = adtypestr[strtind:(open_brkt_ind - 1)]
-    throw(ArgumentError("The passed automatic differentiation backend choice is not available. Please load the corresponding AD package $adpkg."))
-end
 
-function instantiate_function(f::MultiObjectiveOptimizationFunction, x, ::SciMLBase.NoAD,
+function instantiate_function(f, x, ::SciMLBase.NoAD,
         p, num_cons = 0)
-    jac = f.jac === nothing ? nothing : (J, x, args...) -> f.jac(J, x, p, args...)
-    hess = f.hess === nothing ? nothing : [(H, x, args...) -> h(H, x, p, args...) for h in f.hess]
+    grad = f.grad === nothing ? nothing : (G, x, args...) -> f.grad(G, x, p, args...)
+    hess = f.hess === nothing ? nothing : (H, x, args...) -> f.hess(H, x, p, args...)
     hv = f.hv === nothing ? nothing : (H, x, v, args...) -> f.hv(H, x, v, p, args...)
     cons = f.cons === nothing ? nothing : (res, x) -> f.cons(res, x, p)
     cons_j = f.cons_j === nothing ? nothing : (res, x) -> f.cons_j(res, x, p)
-    cons_jvp = f.cons_jvp === nothing ? nothing : (res, x) -> f.cons_jvp(res, x, p)
-    cons_vjp = f.cons_vjp === nothing ? nothing : (res, x) -> f.cons_vjp(res, x, p)
     cons_h = f.cons_h === nothing ? nothing : (res, x) -> f.cons_h(res, x, p)
     hess_prototype = f.hess_prototype === nothing ? nothing :
                      convert.(eltype(x), f.hess_prototype)
@@ -134,9 +139,9 @@ function instantiate_function(f::MultiObjectiveOptimizationFunction, x, ::SciMLB
     expr = symbolify(f.expr)
     cons_expr = symbolify.(f.cons_expr)
 
-    return MultiObjectiveOptimizationFunction{true}(f.f, SciMLBase.NoAD(); jac = jac, hess = hess,
+    return OptimizationFunction{true}(f.f, SciMLBase.NoAD(); grad = grad, hess = hess,
         hv = hv,
-        cons = cons, cons_j = cons_j, cons_jvp = cons_jvp, cons_vjp = cons_vjp, cons_h = cons_h,
+        cons = cons, cons_j = cons_j, cons_h = cons_h,
         hess_prototype = hess_prototype,
         cons_jac_prototype = cons_jac_prototype,
         cons_hess_prototype = cons_hess_prototype,
@@ -145,28 +150,13 @@ function instantiate_function(f::MultiObjectiveOptimizationFunction, x, ::SciMLB
         observed = f.observed)
 end
 
-function instantiate_function(f::MultiObjectiveOptimizationFunction, x, adtype::ADTypes.AbstractADType,
-        p, num_cons = 0)
-    adtypestr = string(adtype)
-    _strtind = findfirst('.', adtypestr)
-    strtind = isnothing(_strtind) ? 5 : _strtind + 5
-    open_nrmlbrkt_ind = findfirst('(', adtypestr)
-    open_squigllybrkt_ind = findfirst('{', adtypestr)
-    open_brkt_ind = isnothing(open_squigllybrkt_ind) ? open_nrmlbrkt_ind :
-                    min(open_nrmlbrkt_ind, open_squigllybrkt_ind)
-    adpkg = adtypestr[strtind:(open_brkt_ind - 1)]
-    throw(ArgumentError("The passed automatic differentiation backend choice is not available. Please load the corresponding AD package $adpkg."))
-end
-
-function instantiate_function(f::MultiObjectiveOptimizationFunction, cache::ReInitCache, ::SciMLBase.NoAD,
+function instantiate_function(f, cache::ReInitCache, ::SciMLBase.NoAD,
         num_cons = 0)
-    jac = f.jac === nothing ? nothing : (J, x, args...) -> f.jac(J, x, cache.p, args...)
-    hess = f.hess === nothing ? nothing : [(H, x, args...) -> h(H, x, cache.p, args...) for h in f.hess]
+    grad = f.grad === nothing ? nothing : (G, x, args...) -> f.grad(G, x, cache.p, args...)
+    hess = f.hess === nothing ? nothing : (H, x, args...) -> f.hess(H, x, cache.p, args...)
     hv = f.hv === nothing ? nothing : (H, x, v, args...) -> f.hv(H, x, v, cache.p, args...)
     cons = f.cons === nothing ? nothing : (res, x) -> f.cons(res, x, cache.p)
     cons_j = f.cons_j === nothing ? nothing : (res, x) -> f.cons_j(res, x, cache.p)
-    cons_jvp = f.cons_jvp === nothing ? nothing : (res, x) -> f.cons_jvp(res, x, cache.p)
-    cons_vjp = f.cons_vjp === nothing ? nothing : (res, x) -> f.cons_vjp(res, x, cache.p)
     cons_h = f.cons_h === nothing ? nothing : (res, x) -> f.cons_h(res, x, cache.p)
     hess_prototype = f.hess_prototype === nothing ? nothing :
                      convert.(eltype(cache.u0), f.hess_prototype)
@@ -178,13 +168,28 @@ function instantiate_function(f::MultiObjectiveOptimizationFunction, cache::ReIn
     expr = symbolify(f.expr)
     cons_expr = symbolify.(f.cons_expr)
 
-    return MultiObjectiveOptimizationFunction{true}(f.f, SciMLBase.NoAD(); jac = jac, hess = hess,
+    return OptimizationFunction{true}(f.f, SciMLBase.NoAD(); grad = grad, hess = hess,
         hv = hv,
-        cons = cons, cons_j = cons_j, cons_jvp = cons_jvp, cons_vjp = cons_vjp, cons_h = cons_h,
+        cons = cons, cons_j = cons_j, cons_h = cons_h,
         hess_prototype = hess_prototype,
         cons_jac_prototype = cons_jac_prototype,
         cons_hess_prototype = cons_hess_prototype,
         expr = expr, cons_expr = cons_expr,
         sys = f.sys,
         observed = f.observed)
 end
+
+function instantiate_function(f, x, adtype::ADTypes.AbstractADType,
+        p, num_cons = 0)
+    adtypestr = string(adtype)
+    _strtind = findfirst('.', adtypestr)
+    strtind = isnothing(_strtind) ? 5 : _strtind + 5
+    open_nrmlbrkt_ind = findfirst('(', adtypestr)
+    open_squigllybrkt_ind = findfirst('{', adtypestr)
+    open_brkt_ind = isnothing(open_squigllybrkt_ind) ? open_nrmlbrkt_ind :
+                    min(open_nrmlbrkt_ind, open_squigllybrkt_ind)
+    adpkg = adtypestr[strtind:(open_brkt_ind - 1)]
+    throw(ArgumentError("The passed automatic differentiation backend choice is not available. Please load the corresponding AD package $adpkg."))
+end
+
+