Add hess_op for RegularizedNLPModels (#81)

* add hess_op for RegularizedNLPModels

* add hess_op test

* fix formatting for targets

* fix test

Author: MaxenceGollier

Project.toml

@@ -18,29 +18,35 @@ SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 [compat]
 ADNLPModels = "^0.3, 0.4, 0.7"
 Distributions = "0.25"
+LinearOperators = "2.11.0"
 ManualNLPModels = "0.2"
 MLDatasets = "^0.7.4"
 NLPModels = "0.16, 0.17, 0.18, 0.19, 0.20, 0.21"
+NLPModelsModifiers = "0.7.3"
 Noise = "0.2"
 Requires = "1"
 julia = "^1.6.0"
 
 [extras]
 ADNLPModels = "54578032-b7ea-4c30-94aa-7cbd1cce6c9a"
 DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
+LinearOperators = "5c8ed15e-5a4c-59e4-a42b-c7e8811fb125"
 MLDatasets = "eb30cadb-4394-5ae3-aed4-317e484a6458"
+NLPModelsModifiers = "e01155f1-5c6f-4375-a9d8-616dd036575f"
 ProximalOperators = "a725b495-10eb-56fe-b38b-717eba820537"
 QuadraticModels = "f468eda6-eac5-11e8-05a5-ff9e497bcd19"
 ShiftedProximalOperators = "d4fd37fa-580c-4e43-9b30-361c21aae263"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
 test = [
-  "ADNLPModels",
-  "DifferentialEquations",
-  "MLDatasets",
-  "ProximalOperators",
-  "QuadraticModels",
-  "ShiftedProximalOperators",
-  "Test",
+  "ADNLPModels", 
+  "DifferentialEquations", 
+  "LinearOperators", 
+  "MLDatasets", 
+  "NLPModelsModifiers", 
+  "ProximalOperators", 
+  "QuadraticModels", 
+  "ShiftedProximalOperators", 
+  "Test"
 ]

src/types.jl

@@ -61,6 +61,10 @@ function NLPModels.obj(rnlp::AbstractRegularizedNLPModel, x::AbstractVector)
   obj(rnlp.model, x) + rnlp.h(x)
 end
 
+function NLPModels.hess_op(rnlp::AbstractRegularizedNLPModel, x::AbstractVector)
+  return hess_op(rnlp.model, x)
+end
+
 # Forward meta getters so they grab info from the smooth model
 for field ∈ fieldnames(NLPModels.NLPModelMeta)
   meth = Symbol("get_", field)

test/rmodel_tests.jl

@@ -15,6 +15,8 @@ using ProximalOperators
   @test get_nequ(rlsmodel) == get_nequ(nls_model)
   obj(nls_model, nls_model.meta.x0)
   @test neval_obj(rlsmodel) == neval_obj(nls_model)
+  rmodel_lbfgs = RegularizedNLPModel(LBFGSModel(model), h)
+  @test typeof(hess_op(rmodel_lbfgs, model.meta.x0)) <: LBFGSOperator
 end
 
 @testset "Problem combos" begin

test/runtests.jl

@@ -1,5 +1,5 @@
 using LinearAlgebra, Test
-using ADNLPModels, DifferentialEquations, ManualNLPModels, MLDatasets, NLPModels, QuadraticModels
+using ADNLPModels, DifferentialEquations, LinearOperators, ManualNLPModels, MLDatasets, NLPModels, NLPModelsModifiers, QuadraticModels
 using RegularizedProblems
 
 function test_well_defined(model, nls_model, sol)