Add a method hess_coord! for the Hessian of the objective (#135)

* Add a method hess_coord! for the Hessian of the objective

* Add unit tests for allocations

* Update tests

* Remove allocation tests

Author: amontoison

src/nlp.jl

@@ -672,6 +672,17 @@ function _jtprod_nln!(cons, x, v, Jtv)
     sjacobian!(nothing, (Jtv, v), cons, x, one(eltype(Jtv)))
 end
 
+function hess_coord!(
+    m::ExaModel,
+    x::AbstractVector,
+    hess::AbstractVector;
+    obj_weight = one(eltype(x)),
+)
+    fill!(hess, zero(eltype(hess)))
+    _obj_hess_coord!(m.objs, x, hess, obj_weight)
+    return hess
+end
+
 function hess_coord!(
     m::ExaModel,
     x::AbstractVector,
@@ -680,14 +691,14 @@ function hess_coord!(
     obj_weight = one(eltype(x)),
 )
     fill!(hess, zero(eltype(hess)))
-    _obj_hess_coord!(m.objs, x, y, hess, obj_weight)
+    _obj_hess_coord!(m.objs, x, hess, obj_weight)
     _con_hess_coord!(m.cons, x, y, hess, obj_weight)
     return hess
 end
 
-_obj_hess_coord!(objs::ObjectiveNull, x, y, hess, obj_weight) = nothing
-function _obj_hess_coord!(objs, x, y, hess, obj_weight)
-    _obj_hess_coord!(objs.inner, x, y, hess, obj_weight)
+_obj_hess_coord!(objs::ObjectiveNull, x, hess, obj_weight) = nothing
+function _obj_hess_coord!(objs, x, hess, obj_weight)
+    _obj_hess_coord!(objs.inner, x, hess, obj_weight)
     shessian!(hess, nothing, objs, x, obj_weight, zero(eltype(hess)))
 end
 
@@ -697,6 +708,18 @@ function _con_hess_coord!(cons, x, y, hess, obj_weight)
     shessian!(hess, nothing, cons, x, y, zero(eltype(hess)))
 end
 
+function hprod!(
+    m::ExaModel,
+    x::AbstractVector,
+    v::AbstractVector,
+    Hv::AbstractVector;
+    obj_weight = one(eltype(x)),
+)
+    fill!(Hv, zero(eltype(Hv)))
+    _obj_hprod!(m.objs, x, v, Hv, obj_weight)
+    return Hv
+end
+
 function hprod!(
     m::ExaModel,
     x::AbstractVector,
@@ -706,14 +729,14 @@ function hprod!(
     obj_weight = one(eltype(x)),
 )
     fill!(Hv, zero(eltype(Hv)))
-    _obj_hprod!(m.objs, x, y, v, Hv, obj_weight)
+    _obj_hprod!(m.objs, x, v, Hv, obj_weight)
     _con_hprod!(m.cons, x, y, v, Hv, obj_weight)
     return Hv
 end
 
-_obj_hprod!(objs::ObjectiveNull, x, y, v, Hv, obj_weight) = nothing
-function _obj_hprod!(objs, x, y, v, Hv, obj_weight)
-    _obj_hprod!(objs.inner, x, y, v, Hv, obj_weight)
+_obj_hprod!(objs::ObjectiveNull, x, v, Hv, obj_weight) = nothing
+function _obj_hprod!(objs, x, v, Hv, obj_weight)
+    _obj_hprod!(objs.inner, x, v, Hv, obj_weight)
     shessian!((Hv, v), nothing, objs, x, obj_weight, zero(eltype(Hv)))
 end
 

test/NLPTest/NLPTest.jl

@@ -2,7 +2,8 @@ module NLPTest
 
 using ExaModels
 using Downloads, Test
-using NLPModels, JuMP, NLPModelsJuMP, PowerModels, NLPModelsIpopt, MadNLP, Percival
+using NLPModels, NLPModelsJuMP, NLPModelsIpopt, NLPModelsTest
+using JuMP, PowerModels, MadNLP, Percival
 
 import ..BACKENDS
 
@@ -141,7 +142,6 @@ function runtests()
                         set_optimizer_attribute(m, "print_level", MadNLP.ERROR)
                         optimize!(m)
 
-
                         m, vars1, cons1 = exa_model(backend, args)
                         m1 = WrapperNLPModel(m)
 

test/Project.toml

@@ -1,18 +1,19 @@
 [deps]
+AMDGPU = "21141c5a-9bdb-4563-92ae-f87d6854732e"
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 Downloads = "f43a241f-c20a-4ad4-852c-f6b1247861c6"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
+Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"
+JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 KernelAbstractions = "63c18a36-062a-441e-b654-da1e3ab1ce7c"
 MadNLP = "2621e9c9-9eb4-46b1-8089-e8c72242dfb6"
 NLPModels = "a4795742-8479-5a88-8948-cc11e1c8c1a6"
 NLPModelsIpopt = "f4238b75-b362-5c4c-b852-0801c9a21d71"
 NLPModelsJuMP = "792afdf1-32c1-5681-94e0-d7bf7a5df49e"
+NLPModelsTest = "7998695d-6960-4d3a-85c4-e1bceb8cd856"
 Percival = "01435c0c-c90d-11e9-3788-63660f8fbccc"
 PowerModels = "c36e90e8-916a-50a6-bd94-075b64ef4655"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
-AMDGPU = "21141c5a-9bdb-4563-92ae-f87d6854732e"
-Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"
-JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
-oneAPI = "8f75cd03-7ff8-4ecb-9b8f-daf728133b1b"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+oneAPI = "8f75cd03-7ff8-4ecb-9b8f-daf728133b1b"