bump some deps versions (#5)

* bump some deps versions

* some fixes

* fix max_time

* improve CI config

.github/workflows/ci.yml

@@ -1,7 +1,12 @@
 name: CI
 on:
-  - push
-  - pull_request
+  pull_request:
+    branches:
+      - master
+  push:
+    branches:
+      - master
+    tags: '*'
 jobs:
   test:
     name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ github.event_name }}

Project.toml

@@ -13,11 +13,11 @@ Percival = "01435c0c-c90d-11e9-3788-63660f8fbccc"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 
 [compat]
-ADNLPModels = "0.1, 0.2, 0.3"
-NLPModelsModifiers = "0.1, 0.2, 0.4"
+ADNLPModels = "0.3"
+NLPModelsModifiers = "0.5"
 NonconvexCore = "1"
 Parameters = "0.12"
-Percival = "0.3.1"
+Percival = "0.5"
 Reexport = "1"
 julia = "1"
 

src/NonconvexPercival.jl

@@ -63,7 +63,7 @@ end
 function _percival(nlp;
     T = eltype(nlp.meta.x0),
     μ::Real = convert(T, 10),
-    max_iter::Int = 1000, max_time::Real = convert(T, Inf),
+    max_iter::Int = 1000, max_time::Real = Inf,
     max_eval::Int = 100000, atol::Real = convert(T, 1e-6),
     rtol::Real = convert(T, 1e-6), ctol::Real = convert(T, 1e-6),
     first_order = true, memory = 5,
@@ -73,7 +73,7 @@ function _percival(nlp;
     modifier = m -> begin
         op = NLPModelsModifiers.LinearOperators.LBFGSOperator(T, m.meta.nvar; mem = memory)
         return NLPModelsModifiers.LBFGSModel(m.meta, m, op)
-    end
+    end  
     _kwargs = (
         max_iter = max_iter, max_time = max_time,
         max_eval = max_eval, atol = atol, rtol = rtol,
@@ -162,7 +162,41 @@ function get_percival_problem(obj, ineq_constr, eq_constr, x0, xlb, xub)
     end
     lcon = [fill(convert(T, -Inf), ineq_nconstr); zeros(T, eq_nconstr)]
     ucon = zeros(T, ineq_nconstr + eq_nconstr)
-    return ADNLPModels.ADNLPModel(obj, x0, xlb, xub, c, lcon, ucon, adbackend = ADNLPModels.ZygoteAD())
+    nlp = zygote_nlp_model(obj, x0, xlb, xub, c, lcon, ucon)
+    return nlp
+end
+
+function zygote_nlp_model(f, x0::S, lvar::S, uvar::S, c, lcon::S, ucon::S) where {S}
+    T = eltype(S)
+    y0 = fill!(similar(lcon), zero(T))
+    name::String = "Generic"
+    lin::AbstractVector{<:Integer} = Int[]
+    backend = ADNLPModels.ZygoteAD(0, 0)
+    AD = typeof(backend)
+    minimize::Bool = true
+    nvar = length(x0)
+    ncon = length(lcon)
+
+    nnzh = nvar * (nvar + 1) / 2
+    nnzj = nvar * ncon
+    meta = ADNLPModels.NLPModelMeta{T, S}(
+        nvar,
+        x0 = x0,
+        lvar = lvar,
+        uvar = uvar,
+        ncon = ncon,
+        y0 = y0,
+        lcon = lcon,
+        ucon = ucon,
+        nnzj = nnzj,
+        nnzh = nnzh,
+        lin = lin,
+        minimize = minimize,
+        islp = false,
+        name = name,
+    )
+    adbackend = AD(nvar, f, ncon; x0 = x0)
+    return ADNLPModels.ADNLPModel(meta, ADNLPModels.Counters(), adbackend, f, c)
 end
 
 end

test/runtests.jl

@@ -7,7 +7,7 @@ alg = AugLag()
 
 @testset "Simple constraints" begin
     m = Model(f)
-    addvar!(m, [0.0, 0.0], [10.0, 10.0])
+    addvar!(m, [1e-4, 1e-4], [10.0, 10.0])
     add_ineq_constraint!(m, x -> g(x, 2, 0))
     add_ineq_constraint!(m, x -> g(x, -1, 1))
     for first_order in (true, false)
@@ -20,7 +20,7 @@ end
 
 @testset "Equality constraints" begin
     m = Model(f)
-    addvar!(m, [0.0, 0.0], [10.0, 10.0])
+    addvar!(m, [1e-4, 1e-4], [10.0, 10.0])
     add_ineq_constraint!(m, x -> g(x, 2, 0))
     add_ineq_constraint!(m, x -> g(x, -1, 1))
     add_eq_constraint!(m, x -> sum(x) - 1/3 - 8/27)
@@ -35,7 +35,7 @@ end
 @testset "Equality constraints BigFloat" begin
     T = BigFloat
     m = Model(f)
-    addvar!(m, T.([0.0, 0.0]), T.([10.0, 10.0]))
+    addvar!(m, T.([1e-4, 1e-4]), T.([10.0, 10.0]))
     add_ineq_constraint!(m, x -> g(x, T(2), T(0)))
     add_ineq_constraint!(m, x -> g(x, T(-1), T(1)))
     add_eq_constraint!(m, x -> sum(x) - T(1/3) - T(8/27))
@@ -51,7 +51,7 @@ end
 
 @testset "Block constraints" begin
     m = Model(f)
-    addvar!(m, [0.0, 0.0], [10.0, 10.0])
+    addvar!(m, [1e-4, 1e-4], [10.0, 10.0])
     add_ineq_constraint!(m, FunctionWrapper(x -> [g(x, 2, 0), g(x, -1, 1)], 2))
 
     for first_order in (true, false)
@@ -65,7 +65,7 @@ end
 @testset "Infinite bounds" begin
     @testset "Infinite upper bound" begin
         m = Model(f)
-        addvar!(m, [0.0, 0.0], [Inf, Inf])
+        addvar!(m, [1e-4, 1e-4], [Inf, Inf])
         add_ineq_constraint!(m, x -> g(x, 2, 0))
         add_ineq_constraint!(m, x -> g(x, -1, 1))