Uncomment some code

JuliaSmoothOptimizers · Dec 20, 2024 · 235bfe6 · 235bfe6
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Showing 2 changed files with 9 additions and 7 deletions.
diff --git a/test/Project.toml b/test/Project.toml
@@ -1,4 +1,6 @@
 [deps]
+ADNLPModels = "54578032-b7ea-4c30-94aa-7cbd1cce6c9a"
+Enzyme = "7da242da-08ed-463a-9acd-ee780be4f1d9"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 ManualNLPModels = "30dfa513-9b2f-4fb3-9796-781eabac1617"

diff --git a/test/nlp/basic.jl b/test/nlp/basic.jl
@@ -17,13 +17,13 @@ function test_autodiff_model(name; kwargs...)
   nlp = ADNLPModel(f, x0, c, [0.0], [0.0]; kwargs...)
   @test obj(nlp, x0) == f(x0)
 
-  # x = range(-1, stop = 1, length = 100)
-  # y = 2x .+ 3 + randn(100) * 0.1
-  # regr = LinearRegression(x, y)
-  # nlp = ADNLPModel(regr, ones(2); kwargs...)
-  # β = [ones(100) x] \ y
-  # @test abs(obj(nlp, β) - norm(y .- β[1] - β[2] * x)^2 / 2) < 1e-12
-  # @test norm(grad(nlp, β)) < 1e-12
+  x = range(-1, stop = 1, length = 100)
+  y = 2x .+ 3 + randn(100) * 0.1
+  regr = LinearRegression(x, y)
+  nlp = ADNLPModel(regr, ones(2); kwargs...)
+  β = [ones(100) x] \ y
+  @test abs(obj(nlp, β) - norm(y .- β[1] - β[2] * x)^2 / 2) < 1e-12
+  @test norm(grad(nlp, β)) < 1e-12
 
   test_getter_setter(nlp)