Merge pull request #191 from JuliaAI/update-learning-network-use-in-t…

…ests

Fix some tests that use deprecated MLJBase code

test/models/simple_composite_model.jl

@@ -12,7 +12,7 @@ intended for internal testing .
 
 """
 mutable struct SimpleDeterministicCompositeModel{L<:Deterministic,
- T<:Unsupervised} <: DeterministicComposite
+ T<:Unsupervised} <: DeterministicNetworkComposite
  model::L
  transformer::T
 
@@ -33,20 +33,23 @@ end
 
 MLJBase.is_wrapper(::Type{<:SimpleDeterministicCompositeModel}) = true
 
-function MLJBase.fit(composite::SimpleDeterministicCompositeModel,
- verbosity::Integer, Xtrain, ytrain)
+function MLJBase.prefit(
+ composite::SimpleDeterministicCompositeModel,
+ verbosity,
+ Xtrain,
+ ytrain,
+ )
+
  X = source(Xtrain) # instantiates a source node
  y = source(ytrain)
 
- t = machine(composite.transformer, X)
+ t = machine(:transformer, X)
  Xt = transform(t, X)
 
- l = machine(composite.model, Xt, y)
+ l = machine(:model, Xt, y)
  yhat = predict(l, Xt)
 
- mach = machine(Deterministic(), X, y; predict=yhat)
- return!(mach, composite, verbosity)
-
+ (predict=yhat,)
 end
 
 MLJBase.load_path(::Type{<:SimpleDeterministicCompositeModel}) =

test/strategies/grid.jl

@@ -150,9 +150,8 @@ end
  tuned = machine(tuned_model, X, y)
 
  fit!(tuned, verbosity=0)
- r = MLJBase.report(tuned)
- @test :model in collect(keys(r.best_report))
  rep = MLJBase.report(tuned)
+ @test :best_report in keys(rep)
  fp = fitted_params(tuned)
  @test :model in collect(keys(fp.best_fitted_params))
  b = fp.best_model
@@ -181,11 +180,11 @@ end
  @test e_training != report(tuned).best_history_entry.measurement[1]
 
  # test plotting part of report:
- @test r.plotting.parameter_names ==
+ @test rep.plotting.parameter_names ==
  ["transformer.features", "model.lambda"]
- @test r.plotting.parameter_scales == [:none, :log10]
- @test r.plotting.measurements == measurements
- @test size(r.plotting.parameter_values) == (40, 2)
+ @test rep.plotting.parameter_scales == [:none, :log10]
+ @test rep.plotting.measurements == measurements
+ @test size(rep.plotting.parameter_values) == (40, 2)
 
 end