added error for predicting with untrained PipeOp + test

Author: advieser

R/PipeOp.R

@@ -188,7 +188,7 @@
 #'   should not modify the `PipeOp` in any way.\cr
 #'
 #' @section Inheriting:
-#' To create your own `PipeOp`, you need to overload the `private$.train()` and `private$.test()` functions.
+#' To create your own `PipeOp`, you need to overload the `private$.train()` and `private$.predict()` functions.
 #' It is most likely also necessary to overload the `$initialize()` function to do additional initialization.
 #' The `$initialize()` method should have at least the arguments `id` and `param_vals`, which should be passed on to `super$initialize()` unchanged.
 #' `id` should have a useful default value, and `param_vals` should have the default value `list()`, meaning no initialization of hyperparameters.
@@ -325,6 +325,10 @@ PipeOp = R6Class("PipeOp",
     predict = function(input) {
       assert_list(input, .var.name = sprintf("input to PipeOp %s's $predict()", self$id))
 
+      if (!self$is_trained) {
+        stopf("Cannot predict, PipeOp '%s' has not been trained yet", self$id)
+      }
+
       # need to load packages in train *and* predict, because they might run in different R instances
       require_namespaces(self$packages)
 

man/PipeOp.Rd

@@ -13,6 +13,7 @@ test_that("PipeOp - General functions", {
   expect_equal(po_1$packages, "mlr3pipelines")
   expect_null(po_1$state)
   assert_subset(po_1$tags, mlr_reflections$pipeops$valid_tags)
+  expect_error(po_1$predict(list(tsk("iris"))), "has not been trained yet")
 
   expect_output(expect_equal(po_1$train(list(1)), list(output = 1)), "Training debug.basic")
   expect_equal(po_1$state, list(input = 1))