Merge pull request #524 from alan-turing-institute/dev

For a 0.17.7 release
JuliaAI · Mar 15, 2021 · a327547 · a327547
2 parents e3b2f8c + 757b5ee
commit a327547
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Showing 5 changed files with 23 additions and 6 deletions.
diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "MLJBase"
 uuid = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 authors = ["Anthony D. Blaom <[email protected]>"]
-version = "0.17.6"
+version = "0.17.7"
 
 [deps]
 CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
@@ -39,15 +39,15 @@ InvertedIndices = "^1"
 JLSO = "^2.1,^2.2"
 JSON = "^0.21"
 LossFunctions = "0.5, 0.6"
-MLJModelInterface = "^0.4"
+MLJModelInterface = "^0.4.1"
 MLJScientificTypes = "^0.4.1"
 Missings = "^0.4"
 OrderedCollections = "^1.1"
 Parameters = "^0.12"
 PrettyTables = "^0.8,^0.9,^0.10,^0.11"
 ProgressMeter = "^1.3"
 StatsBase = "^0.32,^0.33"
-StatisticalTraits = "^0.1"
+StatisticalTraits = "^0.1.1"
 Tables = "^0.2,^1.0"
 julia = "1"
 

diff --git a/src/MLJBase.jl b/src/MLJBase.jl
@@ -25,7 +25,7 @@ import MLJModelInterface: fit, update, update_data, transform,
     predict_mode, predict_mean, predict_median, predict_joint,
     evaluate, clean!, is_same_except,
     save, restore, is_same_except, istransparent,
-    params
+    params, training_losses
 
 # Macros
 using Parameters
@@ -105,7 +105,7 @@ export @mlj_model, metadata_pkg, metadata_model
 export fit, update, update_data, transform, inverse_transform,
     fitted_params, predict,
     predict_mode, predict_mean, predict_median, predict_joint,
-    evaluate, clean!
+    evaluate, clean!, training_losses
 
 # data operations
 export matrix, int, classes, decoder, table,

diff --git a/src/machines.jl b/src/machines.jl
@@ -652,6 +652,19 @@ reports keyed on those machines.
 """
 report(mach::Machine) = mach.report
 
+"""
+    training_losses(mach::Machine)
+
+Return a list of training losses, for models that make these
+available. Otherwise, returns `nothing`.
+
+"""
+
+training_losses(mach::Machine) =
+    training_losses(mach.model, mach.report)
+
+
+
 
 ## SERIALIZATION
 

diff --git a/src/resampling.jl b/src/resampling.jl
@@ -1173,12 +1173,14 @@ StatisticalTraits.package_name(::Type{<:Resampler}) = "MLJBase"
 
 StatisticalTraits.load_path(::Type{<:Resampler}) = "MLJBase.Resampler"
 
-evaluate(resampler::Resampler, fitresult) = fitresult.evaluation
+fitted_params(::Resampler, fitresult) = fitresult
 
+evaluate(resampler::Resampler, fitresult) = fitresult.evaluation
 function evaluate(machine::Machine{<:Resampler})
     if isdefined(machine, :fitresult)
         return evaluate(machine.model, machine.fitresult)
     else
         throw(error("$machine has not been trained."))
     end
 end
+
diff --git a/test/machines.jl b/test/machines.jl
@@ -26,6 +26,8 @@ t = machine(tree, X, y)
 t.model.max_depth = 1
 @test_logs (:info, r"Updating") fit!(t)
 
+@test training_losses(t) === nothing
+
 predict(t, selectrows(X,test));
 @test rms(predict(t, selectrows(X, test)), y[test]) < std(y)