Merge pull request #58 from alan-turing-institute/collapse-machines2

MLJBase 0.14 update
JuliaAI · Jun 26, 2020 · 284c50c · 284c50c
2 parents 54224a6 + 187705b
commit 284c50c
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Showing 3 changed files with 8 additions and 8 deletions.
diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "MLJTuning"
 uuid = "03970b2e-30c4-11ea-3135-d1576263f10f"
 authors = ["Anthony D. Blaom <anthony.blaom@gmail.com>"]
-version = "0.3.7"
+version = "0.4.0"
 
 [deps]
 ComputationalResources = "ed09eef8-17a6-5b46-8889-db040fac31e3"
@@ -16,7 +16,7 @@ RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
 [compat]
 ComputationalResources = "^0.3"
 Distributions = "^0.22,^0.23"
-MLJBase = "^0.12.2,^0.13"
+MLJBase = "^0.12.2,^0.13,^0.14"
 MLJModelInterface = "^0.3"
 ProgressMeter = "^1.3"
 RecipesBase = "^0.8,^0,9,^1.0"

diff --git a/test/models/simple_composite_model.jl b/test/models/simple_composite_model.jl
@@ -36,17 +36,18 @@ MLJBase.is_wrapper(::Type{<:SimpleDeterministicCompositeModel}) = true
 function MLJBase.fit(composite::SimpleDeterministicCompositeModel,
                      verbosity::Integer, Xtrain, ytrain)
     X = source(Xtrain) # instantiates a source node
-    y = source(ytrain, kind=:target)
+    y = source(ytrain)
 
     t = machine(composite.transformer, X)
     Xt = transform(t, X)
 
     l = machine(composite.model, Xt, y)
     yhat = predict(l, Xt)
 
-    fit!(yhat, verbosity=verbosity)
+    mach = machine(Deterministic(), X, y; predict=yhat)
+    fit!(mach, verbosity=verbosity)
 
-    return fitresults(yhat)
+    return mach()
 end
 
 MLJBase.load_path(::Type{<:SimpleDeterministicCompositeModel}) =

diff --git a/test/strategies/grid.jl b/test/strategies/grid.jl
@@ -153,12 +153,11 @@ end
 
     fit!(tuned, verbosity=0)
     r = report(tuned)
-    @test r.best_report isa NamedTuple{(:machines, :report_given_machine)}
+    @test :model in collect(keys(r.best_report))
     fit!(tuned, verbosity=0)
     rep = report(tuned)
     fp = fitted_params(tuned)
-    @test fp.best_fitted_params isa
-        NamedTuple{(:machines, :fitted_params_given_machine)}
+    @test :model in collect(keys(fp.best_fitted_params))
     b = fp.best_model
     @test b isa SimpleDeterministicCompositeModel