fix: measure checks

R/Measure.R

@@ -197,6 +197,9 @@ Measure = R6Class("Measure",
       assert_measure(self, task = task, learner = learner, prediction = prediction)
       assert_prediction(prediction, null.ok = "requires_no_prediction" %nin% self$properties)
 
+      # check should be added to assert_measure()
+      # except when the checks are superfluous for rr$score() and bmr$score()
+      # these checks should be added bellow
       if ("requires_task" %in% self$properties && is.null(task)) {
         stopf("Measure '%s' requires a task", self$id)
       }
@@ -205,21 +208,14 @@ Measure = R6Class("Measure",
         stopf("Measure '%s' requires a learner", self$id)
       }
 
-      if ("requires_model" %in% self$properties && (is.null(learner) || is.null(learner$model))) {
-        stopf("Measure '%s' requires the trained model", self$id)
-      }
-      if ("requires_model" %in% self$properties && is_marshaled_model(learner$model)) {
-        stopf("Measure '%s' requires the trained model, but model is in marshaled form", self$id)
+      if (!is_scalar_na(self$task_type) && self$task_type != prediction$task_type) {
+        stopf("Measure '%s' incompatible with task type '%s'", self$id, prediction$task_type)
       }
 
       if ("requires_train_set" %in% self$properties && is.null(train_set)) {
         stopf("Measure '%s' requires the train_set", self$id)
       }
 
-      if (!is_scalar_na(self$task_type) && self$task_type != prediction$task_type) {
-        stopf("Measure '%s' incompatible with task type '%s'", self$id, prediction$task_type)
-      }
-
       score_single_measure(self, task, learner, train_set, prediction)
     },
 
@@ -358,8 +354,6 @@ score_single_measure = function(measure, task, learner, train_set, prediction) {
     return(NaN)
   }
 
-
-
   if (!is_scalar_na(measure$predict_type) && measure$predict_type %nin% prediction$predict_types) {
     # TODO lgr$debug()
     return(NaN)
@@ -370,7 +364,6 @@ score_single_measure = function(measure, task, learner, train_set, prediction) {
     return(NaN)
   }
 
-
   get_private(measure)$.score(prediction = prediction, task = task, learner = learner, train_set = train_set)
 }
 

R/MeasureInternalValidScore.R

@@ -33,7 +33,7 @@ MeasureInternalValidScore = R6Class("MeasureInternalValidScore",
       super$initialize(
         id = select %??% "internal_valid_score",
         task_type = NA_character_,
-        properties = c("na_score", "requires_model", "requires_learner", "requires_no_prediction"),
+        properties = c("na_score", "requires_learner", "requires_no_prediction"),
         predict_sets = NULL,
         predict_type = NA_character_,
         range = c(-Inf, Inf),

R/assertions.R

@@ -206,6 +206,7 @@ assert_measure = function(measure, task = NULL, learner = NULL, prediction = NUL
   assert_class(measure, "Measure", .var.name = .var.name)
 
   if (!is.null(task)) {
+
     if (!is_scalar_na(measure$task_type) && !test_matching_task_type(task$task_type, measure, "measure")) {
       stopf("Measure '%s' is not compatible with type '%s' of task '%s'",
         measure$id, task$task_type, task$id)
@@ -221,6 +222,15 @@ assert_measure = function(measure, task = NULL, learner = NULL, prediction = NUL
   }
 
   if (!is.null(learner)) {
+
+    if ("requires_model" %in% measure$properties && is.null(learner$model)) {
+      stopf("Measure '%s' requires the trained model", measure$id)
+    }
+
+    if ("requires_model" %in% measure$properties && is_marshaled_model(learner$model)) {
+      stopf("Measure '%s' requires the trained model, but model is in marshaled form", measure$id)
+    }
+
     if (!is_scalar_na(measure$task_type) && measure$task_type != learner$task_type) {
       stopf("Measure '%s' is not compatible with type '%s' of learner '%s'",
         measure$id, learner$task_type, learner$id)

tests/testthat/_snaps/Task.md

@@ -0,0 +1,19 @@
+# $characteristics works
+
+    Code
+      task
+    Output
+      <TaskClassif:spam> (4601 x 58): HP Spam Detection
+      * Target: type
+      * Properties: twoclass
+      * Features (57):
+        - dbl (57): address, addresses, all, business, capitalAve,
+          capitalLong, capitalTotal, charDollar, charExclamation, charHash,
+          charRoundbracket, charSemicolon, charSquarebracket, conference,
+          credit, cs, data, direct, edu, email, font, free, george, hp, hpl,
+          internet, lab, labs, mail, make, meeting, money, num000, num1999,
+          num3d, num415, num650, num85, num857, order, original, our, over,
+          parts, people, pm, project, re, receive, remove, report, table,
+          technology, telnet, will, you, your
+      * Characteristics:  foo=1, bar=a
+

tests/testthat/test_resample.R

@@ -520,3 +520,8 @@ test_that("resampling instantiated on a different task throws an error", {
   expect_error(resample(tsk("pima"), lrn("classif.rpart"), resampling), "The resampling was probably instantiated on a different task")
 
 })
+
+test_that("$score() checks for models", {
+  rr = resample(tsk("mtcars"), lrn("regr.debug"), rsmp("holdout"))
+  expect_error(rr$score(msr("aic")), "requires the trained model")
+})