Add missing downgrade constructor to NonDifferentiable from higher di… (

#133) * Add missing downgrade constructor to NonDifferentiable from higher diffs. * Update nondifferentiable.jl * Update nondifferentiable.jl * Update NLSolversBase.jl * Fixitup.
JuliaNLSolvers · Oct 2, 2020 · 0c30a5e · 0c30a5e
1 parent fa47b94
commit 0c30a5e
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diff --git a/src/NLSolversBase.jl b/src/NLSolversBase.jl
@@ -69,4 +69,7 @@ include("objective_types/incomplete.jl")
 include("objective_types/constraints.jl")
 include("interface.jl")
 
+NonDifferentiable(f::OnceDifferentiable, x::AbstractArray) = NonDifferentiable(f.f, x, copy(f.F))
+NonDifferentiable(f::TwiceDifferentiable, x::AbstractArray) = NonDifferentiable(f.f, x, copy(f.F))
+NonDifferentiable(f::TwiceDifferentiableHV, x::AbstractArray) = NonDifferentiable(f.f, x, copy(f.F))
 end # module
diff --git a/test/incomplete.jl b/test/incomplete.jl
@@ -95,6 +95,9 @@
     v = randn(10)
     od_fg_and_hv = TwiceDifferentiableHV(only_fg_and_hv!(just_fg!, just_hv!), x)
     od_fghv      = TwiceDifferentiableHV(only_fghv!(just_fghv!), x)
+    ndtdhv = NonDifferentiable(od_fghv, v)
+    @test value(ndtdhv, v) === value(od_fghv, v)
+
     for OD in (od_fg_and_hv, od_fghv)
         gradient!(OD, x)
         @test gradient(OD) == g(x)

diff --git a/test/objective_types.jl b/test/objective_types.jl
@@ -36,6 +36,8 @@
         od = OnceDifferentiable(exponential, exponential_gradient!, x_seed, 0.0, g_seed)
         xrand = rand(2)
         value_gradient!(od, xrand)
+        ndod = NonDifferentiable(od, xrand)
+        @test value(ndod, xrand) === value(od, xrand)
         fcache = value(od)
         gcache = copy(gradient(od))
         value_gradient!(od, zeros(2))
@@ -58,6 +60,9 @@
         td = TwiceDifferentiable(exponential, exponential_gradient!, exponential_hessian!, x_seed, 0.0, g_seed)
         xrand = rand(2)
         value_gradient!(td, xrand)
+        ndtd = NonDifferentiable(td, xrand)
+        @test value(ndtd, xrand) === value(td, xrand)
+
         fcache = value(td)
         gcache = copy(gradient(td))
         value_gradient!(td, zeros(2))