fix: cleanup after unloading + doc fixes (#258)

mlr-org · Jan 5, 2023 · 195a4bb · 195a4bb
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -49,4 +49,32 @@ Config/testthat/edition: 3
 Encoding: UTF-8
 NeedsCompilation: no
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.1
+RoxygenNote: 7.2.3
+Collate: 
+    'aaa.R'
+    'LearnerClassifCVGlmnet.R'
+    'LearnerClassifGlmnet.R'
+    'LearnerClassifKKNN.R'
+    'LearnerClassifLDA.R'
+    'LearnerClassifLogReg.R'
+    'LearnerClassifMultinom.R'
+    'LearnerClassifNaiveBayes.R'
+    'LearnerClassifNnet.R'
+    'LearnerClassifQDA.R'
+    'LearnerClassifRanger.R'
+    'LearnerClassifSVM.R'
+    'LearnerClassifXgboost.R'
+    'LearnerRegrCVGlmnet.R'
+    'LearnerRegrGlmnet.R'
+    'LearnerRegrKKNN.R'
+    'LearnerRegrKM.R'
+    'LearnerRegrLM.R'
+    'LearnerRegrNnet.R'
+    'LearnerRegrRanger.R'
+    'LearnerRegrSVM.R'
+    'LearnerRegrXgboost.R'
+    'bibentries.R'
+    'helpers.R'
+    'helpers_glmnet.R'
+    'helpers_ranger.R'
+    'zzz.R'
diff --git a/NEWS.md b/NEWS.md
@@ -1,3 +1,6 @@
+# mlr3learners 0.5.4-9000
+* fix: unloading `mlr3learners` removes learners from dictionary.
+
 # mlr3learners 0.5.4
 
 - Added `regr.nnet` learner.

diff --git a/R/LearnerClassifCVGlmnet.R b/R/LearnerClassifCVGlmnet.R
@@ -142,3 +142,6 @@ LearnerClassifCVGlmnet = R6Class("LearnerClassifCVGlmnet",
     }
   )
 )
+
+#' @include aaa.R
+learners[["classif.cv_glmnet"]] = LearnerClassifCVGlmnet
diff --git a/R/LearnerClassifGlmnet.R b/R/LearnerClassifGlmnet.R
@@ -152,3 +152,6 @@ LearnerClassifGlmnet = R6Class("LearnerClassifGlmnet",
     }
   )
 )
+
+#' @include aaa.R
+learners[["classif.glmnet"]] = LearnerClassifGlmnet
diff --git a/R/LearnerClassifKKNN.R b/R/LearnerClassifKKNN.R
@@ -90,3 +90,6 @@ LearnerClassifKKNN = R6Class("LearnerClassifKKNN",
     }
   )
 )
+
+#' @include aaa.R
+learners[["classif.kknn"]] = LearnerClassifKKNN
diff --git a/R/LearnerClassifLDA.R b/R/LearnerClassifLDA.R
@@ -74,3 +74,6 @@ LearnerClassifLDA = R6Class("LearnerClassifLDA",
     }
   )
 )
+
+#' @include aaa.R
+learners[["classif.lda"]] = LearnerClassifLDA
diff --git a/R/LearnerClassifLogReg.R b/R/LearnerClassifLogReg.R
@@ -100,3 +100,6 @@ LearnerClassifLogReg = R6Class("LearnerClassifLogReg",
     }
   )
 )
+
+#' @include aaa.R
+learners[["classif.log_reg"]] = LearnerClassifLogReg
diff --git a/R/LearnerClassifMultinom.R b/R/LearnerClassifMultinom.R
@@ -104,3 +104,6 @@ LearnerClassifMultinom = R6Class("LearnerClassifMultinom",
     }
   )
 )
+
+#' @include aaa.R
+learners[["classif.multinom"]] = LearnerClassifMultinom
diff --git a/R/LearnerClassifNaiveBayes.R b/R/LearnerClassifNaiveBayes.R
@@ -64,3 +64,6 @@ LearnerClassifNaiveBayes = R6Class("LearnerClassifNaiveBayes",
     }
   )
 )
+
+#' @include aaa.R
+learners[["classif.naive_bayes"]] = LearnerClassifNaiveBayes
diff --git a/R/LearnerClassifNnet.R b/R/LearnerClassifNnet.R
@@ -92,3 +92,6 @@ LearnerClassifNnet = R6Class("LearnerClassifNnet",
     }
   )
 )
+
+#' @include aaa.R
+learners[["classif.nnet"]] = LearnerClassifNnet
diff --git a/R/LearnerClassifQDA.R b/R/LearnerClassifQDA.R
@@ -72,3 +72,6 @@ LearnerClassifQDA = R6Class("LearnerClassifQDA",
     }
   )
 )
+
+#' @include aaa.R
+learners[["classif.qda"]] = LearnerClassifQDA
diff --git a/R/LearnerClassifRanger.R b/R/LearnerClassifRanger.R
@@ -160,3 +160,6 @@ default_values.LearnerClassifRanger = function(x, search_space, task, ...) { # n
   defaults = insert_named(default_values(x$param_set), special_defaults)
   defaults[search_space$ids()]
 }
+
+#' @include aaa.R
+learners[["classif.ranger"]] = LearnerClassifRanger
diff --git a/R/LearnerClassifSVM.R b/R/LearnerClassifSVM.R
@@ -95,3 +95,6 @@ default_values.LearnerClassifSVM = function(x, search_space, task, ...) { # noli
   defaults = insert_named(default_values(x$param_set), special_defaults)
   defaults[search_space$ids()]
 }
+
+#' @include aaa.R
+learners[["classif.svm"]] = LearnerClassifSVM
diff --git a/R/LearnerClassifXgboost.R b/R/LearnerClassifXgboost.R
@@ -10,6 +10,9 @@
 #' for binary classification problems and set to `"mlogloss"` for multiclass problems.
 #' This was necessary to silence a deprecation warning.
 #'
+#' Note that using the `watchlist` parameter directly will lead to problems when wrapping this [`Learner`] in a
+#' `mlr3pipelines` `GraphLearner` as the preprocessing steps will not be applied to the data in the watchlist.
+#'
 #' @template note_xgboost
 #' @section Initial parameter values:
 #' - `nrounds`:
@@ -232,6 +235,8 @@ LearnerClassifXgboost = R6Class("LearnerClassifXgboost",
         pv$watchlist = c(pv$watchlist, list(train = data))
       }
 
+      # the last element in the watchlist is used as the early stopping set
+
       if (pv$early_stopping_set == "test" && !is.null(task$row_roles$test)) {
         test_data = task$data(rows = task$row_roles$test, cols = task$feature_names)
         test_label = nlvls - as.integer(task$truth(rows = task$row_roles$test))
@@ -307,3 +312,6 @@ LearnerClassifXgboost = R6Class("LearnerClassifXgboost",
     }
   )
 )
+
+#' @include aaa.R
+learners[["classif.xgboost"]] = LearnerClassifXgboost
diff --git a/R/LearnerRegrCVGlmnet.R b/R/LearnerRegrCVGlmnet.R
@@ -121,3 +121,6 @@ LearnerRegrCVGlmnet = R6Class("LearnerRegrCVGlmnet",
     }
   )
 )
+
+#' @include aaa.R
+learners[["regr.cv_glmnet"]] = LearnerRegrCVGlmnet
diff --git a/R/LearnerRegrGlmnet.R b/R/LearnerRegrGlmnet.R
@@ -123,3 +123,6 @@ LearnerRegrGlmnet = R6Class("LearnerRegrGlmnet",
     }
   )
 )
+
+#' @include aaa.R
+learners[["regr.glmnet"]] = LearnerRegrGlmnet
diff --git a/R/LearnerRegrKKNN.R b/R/LearnerRegrKKNN.R
@@ -85,3 +85,6 @@ LearnerRegrKKNN = R6Class("LearnerRegrKKNN",
     }
   )
 )
+
+#' @include aaa.R
+learners[["regr.kknn"]] = LearnerRegrKKNN
diff --git a/R/LearnerRegrKM.R b/R/LearnerRegrKM.R
@@ -126,3 +126,6 @@ LearnerRegrKM = R6Class("LearnerRegrKM",
     }
   )
 )
+
+#' @include aaa.R
+learners[["regr.km"]] = LearnerRegrKM
diff --git a/R/LearnerRegrLM.R b/R/LearnerRegrLM.R
@@ -80,3 +80,6 @@ LearnerRegrLM = R6Class("LearnerRegrLM",
     }
   )
 )
+
+#' @include aaa.R
+learners[["regr.lm"]] = LearnerRegrLM
diff --git a/R/LearnerRegrNnet.R b/R/LearnerRegrNnet.R
@@ -83,3 +83,6 @@ LearnerRegrNnet = R6Class("LearnerRegrNnet",
     }
   )
 )
+
+#' @include aaa.R
+learners[["regr.nnet"]] = LearnerRegrNnet
diff --git a/R/LearnerRegrRanger.R b/R/LearnerRegrRanger.R
@@ -150,3 +150,6 @@ default_values.LearnerRegrRanger = function(x, search_space, task, ...) { # noli
   defaults = insert_named(default_values(x$param_set), special_defaults)
   defaults[search_space$ids()]
 }
+
+#' @include aaa.R
+learners[["regr.ranger"]] = LearnerRegrRanger
diff --git a/R/LearnerRegrSVM.R b/R/LearnerRegrSVM.R
@@ -80,3 +80,6 @@ default_values.LearnerRegrSVM = function(x, search_space, task, ...) { # nolint
   defaults = insert_named(default_values(x$param_set), special_defaults)
   defaults[search_space$ids()]
 }
+
+#' @include aaa.R
+learners[["regr.svm"]] = LearnerRegrSVM
diff --git a/R/LearnerRegrXgboost.R b/R/LearnerRegrXgboost.R
@@ -9,6 +9,9 @@
 #' To compute on GPUs, you first need to compile \CRANpkg{xgboost} yourself and link
 #' against CUDA. See \url{https://xgboost.readthedocs.io/en/stable/build.html#building-with-gpu-support}.
 #'
+#' Note that using the `watchlist` parameter directly will lead to problems when wrapping this [`Learner`] in a
+#' `mlr3pipelines` `GraphLearner` as the preprocessing steps will not be applied to the data in the watchlist.
+#'
 #' @template note_xgboost
 #' @inheritSection mlr_learners_classif.xgboost Early stopping
 #' @inheritSection mlr_learners_classif.xgboost Initial parameter values
@@ -180,6 +183,8 @@ LearnerRegrXgboost = R6Class("LearnerRegrXgboost",
         pv$watchlist = c(pv$watchlist, list(train = data))
       }
 
+      # the last element in the watchlist is used as the early stopping set
+
       if (pv$early_stopping_set == "test" && !is.null(task$row_roles$test)) {
         test_data = task$data(rows = task$row_roles$test, cols = task$feature_names)
         test_target =  task$data(rows = task$row_roles$test, cols = task$target_names)
@@ -222,3 +227,6 @@ LearnerRegrXgboost = R6Class("LearnerRegrXgboost",
     }
   )
 )
+
+#' @include aaa.R
+learners[["regr.xgboost"]] = LearnerRegrXgboost
diff --git a/R/aaa.R b/R/aaa.R
@@ -0,0 +1 @@
+learners = list()
diff --git a/R/zzz.R b/R/zzz.R
@@ -13,37 +13,21 @@
 #' Feel invited to contribute a missing learner to the \CRANpkg{mlr3} ecosystem!
 "_PACKAGE"
 
+#' @include aaa.R
 register_mlr3 = function() {
   x = utils::getFromNamespace("mlr_learners", ns = "mlr3")
 
-  # classification learners
-  x$add("classif.cv_glmnet", LearnerClassifCVGlmnet)
-  x$add("classif.glmnet", LearnerClassifGlmnet)
-  x$add("classif.kknn", LearnerClassifKKNN)
-  x$add("classif.lda", LearnerClassifLDA)
-  x$add("classif.log_reg", LearnerClassifLogReg)
-  x$add("classif.multinom", LearnerClassifMultinom)
-  x$add("classif.naive_bayes", LearnerClassifNaiveBayes)
-  x$add("classif.nnet", LearnerClassifNnet)
-  x$add("classif.qda", LearnerClassifQDA)
-  x$add("classif.ranger", LearnerClassifRanger)
-  x$add("classif.svm", LearnerClassifSVM)
-  x$add("classif.xgboost", LearnerClassifXgboost)
-
-  # regression learners
-  x$add("regr.cv_glmnet", LearnerRegrCVGlmnet)
-  x$add("regr.glmnet", LearnerRegrGlmnet)
-  x$add("regr.kknn", LearnerRegrKKNN)
-  x$add("regr.km", LearnerRegrKM)
-  x$add("regr.lm", LearnerRegrLM)
-  x$add("regr.nnet", LearnerRegrNnet)
-  x$add("regr.ranger", LearnerRegrRanger)
-  x$add("regr.svm", LearnerRegrSVM)
-  x$add("regr.xgboost", LearnerRegrXgboost)
+  iwalk(learners, function(obj, nm) x$add(nm, obj))
 }
 
 .onLoad = function(libname, pkgname) { # nolint
   register_namespace_callback(pkgname, "mlr3", register_mlr3)
 } # nocov end
 
+.onUnload = function(libpaths) { # nolint
+  mlr_learners = mlr3::mlr_learners
+
+  walk(names(learners), function(id) mlr_learners$remove(id))
+}
+
 leanify_package()
diff --git a/man/mlr_learners_classif.xgboost.Rd b/man/mlr_learners_classif.xgboost.Rd
diff --git a/man/mlr_learners_regr.xgboost.Rd b/man/mlr_learners_regr.xgboost.Rd
diff --git a/tests/testthat/test_unload.R b/tests/testthat/test_unload.R
@@ -0,0 +1,8 @@
+test_that("unloading leaves no trace", {
+  library(mlr3learners)
+  n_learners = length(learners)
+  n_total = length(mlr_learners$keys())
+  unloadNamespace("mlr3learners")
+  n_mlr = length(mlr_learners$keys())
+  expect_true(n_learners == n_total - n_mlr)
+})