Fix a bunch of depwarns

SciML · Sep 10, 2024 · cc39cac · cc39cac
1 parent b2ebe7e
commit cc39cac
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Showing 5 changed files with 13 additions and 13 deletions.
diff --git a/test/newton_neural_ode_tests.jl b/test/newton_neural_ode_tests.jl
@@ -34,10 +34,10 @@
  optprob = Optimization.OptimizationProblem(optf, psd)
 
  res = Optimization.solve(optprob, NewtonTrustRegion(); maxiters = 100, callback = cb)
- @test loss_function(res.minimizer) < l1
+ @test loss_function(res.u) < l1
  res = Optimization.solve(optprob, OptimizationOptimJL.Optim.KrylovTrustRegion();
  maxiters = 100, callback = cb)
- @test loss_function(res.minimizer) < l1
+ @test loss_function(res.u) < l1
 
  @info "ROCK2"
  nODE = NeuralODE(NN, tspan, ROCK2(); reltol = 1.0f-4, saveat = [tspan[end]])
@@ -55,8 +55,8 @@
  optprob = Optimization.OptimizationProblem(optfunc, psd)
 
  res = Optimization.solve(optprob, NewtonTrustRegion(); maxiters = 100, callback = cb)
- @test loss_function(res.minimizer) < l1
+ @test loss_function(res.u) < l1
  res = Optimization.solve(optprob, OptimizationOptimJL.Optim.KrylovTrustRegion();
  maxiters = 100, callback = cb)
- @test loss_function(res.minimizer) < l1
+ @test loss_function(res.u) < l1
 end
diff --git a/test/second_order_ode_tests.jl b/test/second_order_ode_tests.jl
@@ -39,7 +39,7 @@
  (x, p) -> loss_n_ode(x), Optimization.AutoZygote())
  optprob = Optimization.OptimizationProblem(optfunc, p)
  res = Optimization.solve(optprob, Adam(0.01f0); callback = callback, maxiters = 100)
- l2 = loss_n_ode(res.minimizer)
+ l2 = loss_n_ode(res.u)
  @test l2 < l1
 
  function predict(p)
@@ -59,7 +59,7 @@
  (x, p) -> loss_n_ode(x), Optimization.AutoZygote())
  optprob = Optimization.OptimizationProblem(optfunc, p)
  res = Optimization.solve(optprob, Adam(0.01f0); callback = callback, maxiters = 100)
- l2 = loss_n_ode(res.minimizer)
+ l2 = loss_n_ode(res.u)
  @test l2 < l1
 
  function predict(p)
@@ -79,6 +79,6 @@
  (x, p) -> loss_n_ode(x), Optimization.AutoZygote())
  optprob = Optimization.OptimizationProblem(optfunc, p)
  res = Optimization.solve(optprob, Adam(0.01f0); callback = callback, maxiters = 100)
- l2 = loss_n_ode(res.minimizer)
+ l2 = loss_n_ode(res.u)
  @test l2 < l1
 end
diff --git a/test/spline_layer_tests.jl b/test/spline_layer_tests.jl
@@ -26,9 +26,9 @@
  optprob = Optimization.OptimizationProblem(optfunc, ps)
  res = Optimization.solve(optprob, Adam(0.1); callback = callback, maxiters = 100)
 
- optprob = Optimization.OptimizationProblem(optfunc, res.minimizer)
+ optprob = Optimization.OptimizationProblem(optfunc, res.u)
  res = Optimization.solve(optprob, Adam(0.1); callback = callback, maxiters = 100)
- opt = res.minimizer
+ opt = res.u
 
  data_validate_vals = rand(100)
  data_validate_fn = f.(data_validate_vals)

diff --git a/test/stiff_nested_ad_tests.jl b/test/stiff_nested_ad_tests.jl
@@ -39,7 +39,7 @@
  optprob = Optimization.OptimizationProblem(optfunc, ps)
  res = Optimization.solve(
  optprob, Adam(0.1); callback = callback(solver), maxiters = 100)
- loss2 = loss_n_ode(lux_model, res.minimizer)
+ loss2 = loss_n_ode(lux_model, res.u)
  @test loss2 < loss1
  end
 end
diff --git a/test/tensor_product_tests.jl b/test/tensor_product_tests.jl
@@ -26,12 +26,12 @@
  optprob = Optimization.OptimizationProblem(optfunc, ps)
  res = Optimization.solve(
  optprob, OptimizationOptimisers.Adam(0.1); callback = cb, maxiters = 100)
- optprob = Optimization.OptimizationProblem(optfunc, res.minimizer)
+ optprob = Optimization.OptimizationProblem(optfunc, res.u)
  res = Optimization.solve(
  optprob, OptimizationOptimisers.Adam(0.01); callback = cb, maxiters = 100)
- optprob = Optimization.OptimizationProblem(optfunc, res.minimizer)
+ optprob = Optimization.OptimizationProblem(optfunc, res.u)
  res = Optimization.solve(optprob, BFGS(); callback = cb, maxiters = 200)
- opt = res.minimizer
+ opt = res.u
 
  data_validate_vals = [rand(N) for k in 1:100]
  data_validate_fn = f.(data_validate_vals)