Fix the tests with Zygote

JuliaSmoothOptimizers · Nov 26, 2024 · ae65c66 · ae65c66
1 parent 9c10a5c
commit ae65c66
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Showing 3 changed files with 27 additions and 26 deletions.
diff --git a/test/runtests.jl b/test/runtests.jl
@@ -51,32 +51,7 @@ ReverseDiffAD(nvar, f) = ADNLPModels.ADModelBackend(
   hessian_backend = ADNLPModels.ReverseDiffADHessian,
 )
 
-function test_getter_setter(nlp)
-  @test get_adbackend(nlp) == nlp.adbackend
-  if typeof(nlp) <: ADNLPModel
-    set_adbackend!(nlp, ReverseDiffAD(nlp.meta.nvar, nlp.f))
-  elseif typeof(nlp) <: ADNLSModel
-    function F(x; nequ = nlp.nls_meta.nequ)
-      Fx = similar(x, nequ)
-      nlp.F!(Fx, x)
-      return Fx
-    end
-    set_adbackend!(nlp, ReverseDiffAD(nlp.meta.nvar, x -> sum(F(x) .^ 2)))
-  end
-  @test typeof(get_adbackend(nlp).gradient_backend) <: ADNLPModels.ReverseDiffADGradient
-  @test typeof(get_adbackend(nlp).hprod_backend) <: ADNLPModels.ReverseDiffADHvprod
-  @test typeof(get_adbackend(nlp).hessian_backend) <: ADNLPModels.ReverseDiffADHessian
-  set_adbackend!(
-    nlp,
-    gradient_backend = ADNLPModels.ForwardDiffADGradient,
-    jtprod_backend = ADNLPModels.GenericForwardDiffADJtprod(),
-  )
-  @test typeof(get_adbackend(nlp).gradient_backend) <: ADNLPModels.ForwardDiffADGradient
-  @test typeof(get_adbackend(nlp).hprod_backend) <: ADNLPModels.ReverseDiffADHvprod
-  @test typeof(get_adbackend(nlp).jtprod_backend) <: ADNLPModels.GenericForwardDiffADJtprod
-  @test typeof(get_adbackend(nlp).hessian_backend) <: ADNLPModels.ReverseDiffADHessian
-end
-
+include("utils.jl")
 include("nlp/basic.jl")
 include("nls/basic.jl")
 include("nlp/nlpmodelstest.jl")

diff --git a/test/utils.jl b/test/utils.jl
@@ -0,0 +1,25 @@
+function test_getter_setter(nlp)
+  @test get_adbackend(nlp) == nlp.adbackend
+  if typeof(nlp) <: ADNLPModel
+    set_adbackend!(nlp, ReverseDiffAD(nlp.meta.nvar, nlp.f))
+  elseif typeof(nlp) <: ADNLSModel
+    function F(x; nequ = nlp.nls_meta.nequ)
+      Fx = similar(x, nequ)
+      nlp.F!(Fx, x)
+      return Fx
+    end
+    set_adbackend!(nlp, ReverseDiffAD(nlp.meta.nvar, x -> sum(F(x) .^ 2)))
+  end
+  @test typeof(get_adbackend(nlp).gradient_backend) <: ADNLPModels.ReverseDiffADGradient
+  @test typeof(get_adbackend(nlp).hprod_backend) <: ADNLPModels.ReverseDiffADHvprod
+  @test typeof(get_adbackend(nlp).hessian_backend) <: ADNLPModels.ReverseDiffADHessian
+  set_adbackend!(
+    nlp,
+    gradient_backend = ADNLPModels.ForwardDiffADGradient,
+    jtprod_backend = ADNLPModels.GenericForwardDiffADJtprod(),
+  )
+  @test typeof(get_adbackend(nlp).gradient_backend) <: ADNLPModels.ForwardDiffADGradient
+  @test typeof(get_adbackend(nlp).hprod_backend) <: ADNLPModels.ReverseDiffADHvprod
+  @test typeof(get_adbackend(nlp).jtprod_backend) <: ADNLPModels.GenericForwardDiffADJtprod
+  @test typeof(get_adbackend(nlp).hessian_backend) <: ADNLPModels.ReverseDiffADHessian
+end
diff --git a/test/zygote.jl b/test/zygote.jl
@@ -68,6 +68,7 @@ ADNLPModels.predefined_backend = Dict(
 # Automatically loads the code for Zygote with Requires
 import Zygote
 
+include("utils.jl")
 include("nlp/basic.jl")
 include("nls/basic.jl")
 include("nlp/nlpmodelstest.jl")