Merge pull request #221 from JuliaAI/dev

For a 1.12 release

Author: ablaom

Project.toml

@@ -1,9 +1,10 @@
 name = "MLJModelInterface"
 uuid = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
 authors = ["Thibaut Lienart and Anthony Blaom"]
-version = "1.11.1"
+version = "1.12.0"
 
 [deps]
+InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
 REPL = "3fa0cd96-eef1-5676-8a61-b3b8758bbffb"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 ScientificTypesBase = "30f210dd-8aff-4c5f-94ba-8e64358c1161"
@@ -21,7 +22,7 @@ REPL = "<0.0.1, 1"
 Random = "<0.0.1, 1"
 ScientificTypes = "3"
 ScientificTypesBase = "3"
-StatisticalTraits = "3.4"
+StatisticalTraits = "3.5"
 Tables = "1"
 Test = "<0.0.1, 1"
 julia = "1.6"

src/MLJModelInterface.jl

@@ -22,6 +22,7 @@ const MODEL_TRAITS = [
     :docstring,
     :name,
     :human_name,
+    :tags,
     :is_supervised,
     :prediction_type,
     :abstract_type,
@@ -63,7 +64,8 @@ const ABSTRACT_MODEL_SUBTYPES = [
 using ScientificTypesBase
 using StatisticalTraits
 using Random
-using REPL # apparently needed to get Base.Docs.doc to work
+using InteractiveUtils
+using REPL # needed to get Base.Docs.doc to work
 
 import StatisticalTraits: info
 

src/equality.jl

@@ -158,6 +158,7 @@ Base.in(x::MLJType, itr::Set) = special_in(x, itr)
 Base.in(x::MLJType, itr::AbstractVector{<:MLJType}) = special_in(x, itr)
 Base.in(x::MLJType, itr::AbstractRange{<:MLJType}) = special_in(x, itr)
 Base.in(x::MLJType, itr::Tuple) = special_in(x, itr)
+Base.in(x::MLJType, itr::Tuple{(Any for _ in 1:32)..., Vararg{Any}}) = special_in(x, itr)
 
 # A version of `in` that actually uses `==`:
 

src/model_traits.jl

@@ -50,11 +50,10 @@ function StatTraits.target_scitype(::Type{<:DeterministicDetector})
     return AbstractVector{<:Union{Missing, OrderedFactor{2}}}
 end
 
-# implementation is deferred as it requires methodswith which depends upon
-# InteractiveUtils which we don't want to bring here as a dependency
-# (even if it's stdlib).
-implemented_methods(M::Type) = implemented_methods(get_interface_mode(), M)
+implemented_methods(M::Type) = getfield.(methodswith(M), :name) |> unique
 implemented_methods(model) = implemented_methods(typeof(model))
+
+# can be removed in MLJModelInterface 2.0:
 implemented_methods(::LightInterface, M) = errlight("implemented_methods")
 
 for M in ABSTRACT_MODEL_SUBTYPES

test/metadata_utils.jl

@@ -142,7 +142,7 @@ infos =  Dict(trait => eval(:(MLJModelInterface.$trait))(FooRegressor) for
     @test infos[:hyperparameters] == (:a, :b)
     @test infos[:hyperparameter_types] == ("Int64", "Any")
     @test infos[:hyperparameter_ranges] == (nothing, nothing)
-    @test !infos[:supports_training_losses] 
+    @test !infos[:supports_training_losses]
     @test !infos[:reports_feature_importances]
 end
 

test/model_traits.jl

@@ -33,6 +33,7 @@ bar(::P1) = nothing
 M.package_name(::Type{<:S1}) = "Sibelius"
 M.package_url(::Type{<:S1}) = "www.find_the_eighth.org"
 M.human_name(::Type{<:S1}) = "silly model"
+M.tags(::Type{<:S1}) = ["regression", "gradient descent"]
 
 M.package_name(::Type{<:U1}) = "Bach"
 M.package_url(::Type{<:U1}) = "www.did_he_write_565.com"
@@ -103,6 +104,7 @@ M.input_scitype(::Type{<:SupervisedTransformer}) = Finite
 
     @test name(ms) == "S1"
     @test human_name(ms) == "silly model"
+    @test tags(ms) == ["regression", "gradient descent"]
 
 
     @test is_supervised(ms)
@@ -117,18 +119,14 @@ M.input_scitype(::Type{<:SupervisedTransformer}) = Finite
     @test hyperparameters(md) == (:a,)
     @test hyperparameter_types(md) == ("Int64",)
 
-    # implemented methods is deferred
-    setlight()
-    @test_throws M.InterfaceError implemented_methods(mp)
-
-    setfull()
+    @test implemented_methods(ms) == [:clean!,]
 
     @test Set(implemented_methods(mp)) == Set([:clean!,:bar,:foo])
 
-    @test fit_data_scitype(mu) == Tuple{Unknown};;;
+    @test fit_data_scitype(mu) == Tuple{Unknown}
     @test fit_data_scitype(mu) == Tuple{Unknown}
     @test fit_data_scitype(supervised_transformer) == Tuple{Finite,Continuous}
- 
+
 end
 
 @testset "`_density` - helper for predict_scitype fallback" begin