refactor: predict_type and predict_types (#1233)

* refactor: predict_type and predict_types

* ...

* ...

NEWS.md

@@ -1,5 +1,8 @@
 # mlr3 (development version)
 
+* BREAKING CHANGE: `Learner$predict_types` is read-only now.
+* docs: Clear up behavior of `Learner$predict_type` after training.
+
 # mlr3 0.22.1
 
 * fix: Extend `assert_measure()` with checks for trained models in `assert_scorable()`.

R/Learner.R

@@ -157,11 +157,6 @@ Learner = R6Class("Learner",
     #' @template field_task_type
     task_type = NULL,
 
-    #' @field predict_types (`character()`)\cr
-    #' Stores the possible predict types the learner is capable of.
-    #' A complete list of candidate predict types, grouped by task type, is stored in [`mlr_reflections$learner_predict_types`][mlr_reflections].
-    predict_types = NULL,
-
     #' @field feature_types (`character()`)\cr
     #' Stores the feature types the learner can handle, e.g. `"logical"`, `"numeric"`, or `"factor"`.
     #' A complete list of candidate feature types, grouped by task type, is stored in [`mlr_reflections$task_feature_types`][mlr_reflections].
@@ -214,7 +209,7 @@ Learner = R6Class("Learner",
       self$task_type = assert_choice(task_type, mlr_reflections$task_types$type)
       private$.param_set = assert_param_set(param_set)
       self$feature_types = assert_ordered_set(feature_types, mlr_reflections$task_feature_types, .var.name = "feature_types")
-      self$predict_types = assert_ordered_set(predict_types, names(mlr_reflections$learner_predict_types[[task_type]]),
+      private$.predict_types = assert_ordered_set(predict_types, names(mlr_reflections$learner_predict_types[[task_type]]),
         empty.ok = FALSE, .var.name = "predict_types")
       private$.predict_type = predict_types[1L]
       self$properties = sort(assert_subset(properties, mlr_reflections$learner_properties[[task_type]]))
@@ -627,6 +622,8 @@ Learner = R6Class("Learner",
     #' @field predict_type (`character(1)`)\cr
     #' Stores the currently active predict type, e.g. `"response"`.
     #' Must be an element of `$predict_types`.
+    #' A few learners already use the predict type during training.
+    #' So there is no guarantee that changing the predict type after training will have any effect or does not lead to errors.
     predict_type = function(rhs) {
       if (missing(rhs)) {
         return(private$.predict_type)
@@ -648,8 +645,6 @@ Learner = R6Class("Learner",
       private$.param_set
     },
 
-
-
     #' @field fallback ([Learner])\cr
     #' Returns the fallback learner set with `$encapsulate()`.
     fallback = function(rhs) {
@@ -672,13 +667,23 @@ Learner = R6Class("Learner",
       }
       assert_r6(rhs, "HotstartStack", null.ok = TRUE)
       private$.hotstart_stack = rhs
+    },
+
+    #' @field predict_types (`character()`)\cr
+    #' Stores the possible predict types the learner is capable of.
+    #' A complete list of candidate predict types, grouped by task type, is stored in [`mlr_reflections$learner_predict_types`][mlr_reflections].
+    #' This field is read-only.
+    predict_types = function(rhs) {
+      assert_ro_binding(rhs)
+      return(private$.predict_types)
     }
   ),
 
   private = list(
     .encapsulation = c(train = "none", predict = "none"),
     .fallback = NULL,
     .predict_type = NULL,
+    .predict_types = NULL,
     .param_set = NULL,
     .hotstart_stack = NULL,