tests: remove loading of mlr3pipelines (#471)

* ...

* ...

inst/testthat/helper_misc.R

@@ -131,13 +131,13 @@ LearnerRegrDepParams = R6Class("LearnerRegrDepParams", inherit = LearnerRegr,
 )
 
 MAKE_GL = function() {
-  g = Graph$new()
-  op_ds = PipeOpSubsample$new()
-  op_lrn = PipeOpLearner$new(lrn("classif.rpart"))
+  g = mlr3pipelines::Graph$new()
+  op_ds = mlr3pipelines::PipeOpSubsample$new()
+  op_lrn = mlr3pipelines::PipeOpLearner$new(lrn("classif.rpart"))
   g$add_pipeop(op_ds)
   g$add_pipeop(op_lrn)
   g$add_edge("subsample", "classif.rpart")
-  GraphLearner$new(g)
+  mlr3pipelines::GraphLearner$new(g)
 }
 
 flush_redis = function() {

tests/testthat/helper.R

@@ -1,7 +1,6 @@
 library(mlr3)
 library(checkmate)
 library(mlr3misc)
-library(mlr3pipelines)
 library(paradox)
 library(R6)
 

tests/testthat/test_AutoTuner.R

@@ -97,7 +97,6 @@ test_that("AT training does not change learner in instance args", {
 test_that("AutoTuner works with graphlearner", {
   skip_if_not_installed("mlr3pipelines")
   skip_if(packageVersion("mlr3pipelines") < "0.5.3")
-  requireNamespace("mlr3pipelines")
 
   gl = MAKE_GL()
   task = tsk("iris")
@@ -134,7 +133,6 @@ test_that("AutoTuner works with graphlearner", {
 
 test_that("Nested resampling works with graphlearner", {
   skip_if_not_installed("mlr3pipelines", "0.5.3")
-  requireNamespace("mlr3pipelines")
 
   gl = MAKE_GL()
   task = tsk("iris")
@@ -275,7 +273,7 @@ test_that("search space from TuneToken works", {
 
 test_that("AutoTuner get_base_learner method works", {
   skip_if_not_installed("mlr3pipelines", "0.5.3")
-  requireNamespace("mlr3pipelines")
+  `%>>%` = mlr3pipelines::`%>>%`
 
   # simple learner
   learner = lrn("classif.rpart", cp = to_tune(1e-04, 1e-1, logscale = TRUE))
@@ -293,7 +291,7 @@ test_that("AutoTuner get_base_learner method works", {
   expect_equal(at$base_learner(recursive = 0)$id, "classif.rpart")
 
   # graph learner
-  learner = as_learner(pipeline_robustify() %>>% lrn("classif.rpart"))
+  learner = as_learner(mlr3pipelines::pipeline_robustify() %>>% lrn("classif.rpart"))
   learner$param_set$values$classif.rpart.cp = to_tune(1e-04, 1e-1, logscale = TRUE)
   learner$id = "graphlearner.classif.rpart"
 

tests/testthat/test_Tuner.R

@@ -70,7 +70,6 @@ test_that("print method workds", {
 
 test_that("Tuner works with graphlearner", {
   skip_if_not_installed("mlr3pipelines")
-  requireNamespace("mlr3pipelines")
 
   gl = MAKE_GL()
   task = tsk("iris")
@@ -410,6 +409,7 @@ test_that("tag internal tune token manually in primary search space", {
 
 test_that("Can only pass internal tune tokens one way", {
   skip_if_not_installed("mlr3pipelines")
+
   l1 = lrn("classif.debug", early_stopping = TRUE)
   l1$id = "l1"
   l2 = l1$clone()
@@ -418,7 +418,7 @@ test_that("Can only pass internal tune tokens one way", {
   l1$param_set$set_values(
     iter = to_tune(upper = 100, internal = TRUE)
   )
-  l = ppl("branch", list(l1 = l1, l2 = l2))
+  l = mlr3pipelines::ppl("branch", list(l1 = l1, l2 = l2))
   l = as_learner(l)
   set_validate(l, 0.2, ids = c("l1", "l2"))
 

tests/testthat/test_TuningInstanceBatchSingleCrit.R

@@ -109,10 +109,7 @@ test_that("tuning with custom resampling", {
 
 test_that("non-scalar hyperpars (#201)", {
   skip_if_not_installed("mlr3pipelines")
-
-  requireNamespace("mlr3pipelines")
-  `%>>%` = getFromNamespace("%>>%", asNamespace("mlr3pipelines"))
-
+  `%>>%` = mlr3pipelines::`%>>%`
 
   learner = mlr3pipelines::po("select") %>>% lrn("classif.rpart")