Running 'testthat.R' [239s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > if (requireNamespace("testthat", quietly = TRUE)) {
  +   library("checkmate")
  +   library("testthat")
  +   library("mlr3")
  +   library("paradox")
  +   library("mlr3pipelines")
  +   test_check("mlr3pipelines")
  + }
  Starting 2 test processes.
  > test_Graph.R: Training debug.multi with input list(input_1 = 1, input_2 = 1)
  > test_PipeOp.R: Training test_autotrain
  > test_PipeOp.R: Predicting test_autotrain
  > test_PipeOp.R: Training test_autotrain
  > test_PipeOp.R: Training test_autotrain
  > test_PipeOp.R: Predicting test_autotrain
  > test_PipeOp.R: Predicting test_autotrain
  > test_PipeOp.R: Training test_autotrain
  > test_PipeOp.R: Training test_autotrain
  > test_PipeOp.R: Training test_autotrain
  > test_PipeOp.R: Predicting test_autotrain
  > test_PipeOp.R: Predicting test_autotrain
  > test_PipeOp.R: Predicting test_autotrain
  > test_PipeOp.R: Training test_autotrain
  > test_PipeOp.R: Predicting test_autotrain
  > test_PipeOp.R: Training test_autotrain
  > test_PipeOp.R: Training test_autotrain
  > test_PipeOp.R: Predicting test_autotrain
  > test_PipeOp.R: Predicting test_autotrain
  > test_PipeOp.R: Training test_autotrain
  > test_PipeOp.R: Training test_autotrain
  > test_PipeOp.R: Training test_autotrain
  > test_PipeOp.R: Predicting test_autotrain
  > test_PipeOp.R: Predicting test_autotrain
  > test_PipeOp.R: Predicting test_autotrain
  > test_PipeOp.R: Training test_autotrain
  > test_PipeOp.R: Predicting test_autotrain
  Saving _problems/test_mlr_graphs_robustify-106.R
  > test_multiplicities.R: 
  > test_multiplicities.R: [[1]]
  > test_multiplicities.R: 
  > test_multiplicities.R: [1] 0
  > test_multiplicities.R: 
  > test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
  > test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
  > test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
  > test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
  Saving _problems/test_pipeop_classbalancing-13.R
  Saving _problems/test_pipeop_classweights-17.R
  Saving _problems/test_pipeop_classweights-36.R
  Saving _problems/test_pipeop_imputelearner-7.R
  Saving _problems/test_pipeop_imputelearner-138.R
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.573129: Isomap START
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.573781: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.588475: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.605404: Classical Scaling
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.664381: Isomap START
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.66519: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.682558: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.703968: Classical Scaling
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.753909: L-Isomap embed START
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.754961: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.786304: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.821447: embedding
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.823009: DONE
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.856678: L-Isomap embed START
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.857233: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.877472: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.912195: embedding
  > test_pipeop_isomap.R: 2026-08-17 08:31:19.914288: DONE
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.069489: Isomap START
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.070136: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.096475: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.213006: Classical Scaling
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.268969: L-Isomap embed START
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.269846: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.318421: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.547157: embedding
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.552634: DONE
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.773247: Isomap START
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.773729: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.784598: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.799383: Classical Scaling
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.846002: L-Isomap embed START
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.846668: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.879016: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.916162: embedding
  > test_pipeop_isomap.R: 2026-08-17 08:31:20.917844: DONE
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.114717: Isomap START
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.115339: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.132556: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.15442: Classical Scaling
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.234816: L-Isomap embed START
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.235735: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.262636: calculating geodesic distances
  Saving _problems/test_pipeop_impute-452.R
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.308637: embedding
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.31029: DONE
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.437392: Isomap START
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.438031: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.455874: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.477773: Classical Scaling
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.56089: L-Isomap embed START
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.561759: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.588861: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.63904: embedding
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.64052: DONE
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.760359: Isomap START
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.760987: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.776806: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.79919: Classical Scaling
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.877596: L-Isomap embed START
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.878544: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.903027: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.953445: embedding
  > test_pipeop_isomap.R: 2026-08-17 08:31:21.955341: DONE
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.062674: Isomap START
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.063276: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.077968: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.099: Classical Scaling
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.193122: L-Isomap embed START
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.194014: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.218666: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.264832: embedding
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.266288: DONE
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.405967: Isomap START
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.40671: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.421972: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.442891: Classical Scaling
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.543305: Isomap START
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.543927: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.559852: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.582667: Classical Scaling
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.619177: Isomap START
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.619887: constructing knn graph
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.636751: calculating geodesic distances
  > test_pipeop_isomap.R: 2026-08-17 08:31:22.667798: Classical Scaling
  Saving _problems/test_pipeop_missind-4.R
  > test_pipeop_nmf.R: [PipeOpNMFstate]
  > test_pipeop_nmf.R: [PipeOpNMFstate]
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  > test_pipeop_task_preproc.R: Training debug_affectcols
  Saving _problems/test_pipeop_unbranch-21.R
  Saving _problems/test_pipeop_tunethreshold-36.R
  Saving _problems/test_pipeop_tunethreshold-73.R
  Saving _problems/test_selector-6.R
  [ FAIL 12 | WARN 12 | SKIP 128 | PASS 8462 ]
  
  ══ Skipped tests (128) ═════════════════════════════════════════════════════════
  • On CRAN (125): 'test_CnfFormula_simplify.R:6:3', 'test_CnfFormula.R:591:3',
    'test_Graph.R:283:3', 'test_PipeOp.R:32:1', 'test_GraphLearner.R:5:3',
    'test_GraphLearner.R:221:3', 'test_GraphLearner.R:343:3',
    'test_GraphLearner.R:408:3', 'test_GraphLearner.R:571:3',
    'test_doublearrow.R:2:1', 'test_gunion.R:2:1',
    'test_learner_weightedaverage.R:5:3', 'test_learner_weightedaverage.R:57:3',
    'test_learner_weightedaverage.R:105:3',
    'test_learner_weightedaverage.R:152:3', 'test_dictionary.R:7:3',
    'test_meta.R:39:3', 'test_mlr_graphs_branching.R:26:3',
    'test_mlr_graphs_bagging.R:6:3', 'test_mlr_graphs_robustify.R:5:3',
    'test_pipeop_adas.R:8:3', 'test_pipeop_blsmote.R:8:3',
    'test_pipeop_branch.R:4:3', 'test_pipeop_chunk.R:4:3',
    'test_pipeop_classbalancing.R:7:3', 'test_pipeop_boxcox.R:7:3',
    'test_pipeop_classweights.R:10:3', 'test_pipeop_classweightsex.R:9:3',
    'test_pipeop_colapply.R:9:3', 'test_pipeop_collapsefactors.R:6:3',
    'test_pipeop_copy.R:5:3', 'test_pipeop_colroles.R:6:3',
    'test_pipeop_decode.R:14:3', 'test_pipeop_encode.R:21:3',
    'test_pipeop_datefeatures.R:10:3', 'test_pipeop_encodeimpact.R:11:3',
    'test_pipeop_encodepl.R:5:3', 'test_pipeop_encodepl.R:72:3',
    'test_pipeop_ensemble.R:3:1', 'test_pipeop_encodelmer.R:15:3',
    'test_pipeop_encodelmer.R:37:3', 'test_pipeop_encodelmer.R:80:3',
    'test_pipeop_filter.R:7:3', 'test_pipeop_fixfactors.R:9:3',
    'test_pipeop_histbin.R:7:3', 'test_pipeop_ica.R:7:3',
    'test_pipeop_featureunion.R:9:3', 'test_pipeop_featureunion.R:134:3',
    'test_pipeop_imputelearner.R:43:3', 'test_pipeop_info.R:3:1',
    'test_pipeop_impute.R:4:3', 'test_pipeop_isomap.R:10:3',
    'test_pipeop_kernelpca.R:9:3', 'test_pipeop_learner.R:17:3',
    'test_pipeop_learnerpicvplus.R:2:1', 'test_pipeop_learnercv.R:3:3',
    'test_pipeop_learnercv.R:43:3', 'test_pipeop_learnercv.R:73:3',
    'test_pipeop_learnercv.R:92:3', 'test_pipeop_learnercv.R:141:3',
    'test_pipeop_learnercv.R:157:3', 'test_pipeop_learnercv.R:203:3',
    'test_pipeop_learnercv.R:249:3', 'test_pipeop_learnercv.R:278:3',
    'test_pipeop_learnercv.R:332:3', 'test_pipeop_learnercv.R:359:3',
    'test_pipeop_learnercv.R:389:3', 'test_pipeop_learnercv.R:399:3',
    'test_pipeop_learnercv.R:432:3', 'test_pipeop_learnercv.R:472:3',
    'test_pipeop_learnercv.R:481:3', 'test_pipeop_learnercv.R:498:3',
    'test_pipeop_learnercv.R:506:3', 'test_pipeop_learnercv.R:530:3',
    'test_pipeop_learnercv.R:554:3', 'test_pipeop_learnercv.R:634:3',
    'test_pipeop_learnercv.R:654:3', 'test_pipeop_learnercv.R:669:3',
    'test_pipeop_learnercv.R:754:3', 'test_pipeop_learnercv.R:799:3',
    'test_pipeop_learnercv.R:827:3', 'test_pipeop_modelmatrix.R:7:3',
    'test_pipeop_multiplicityexply.R:9:3', 'test_pipeop_mutate.R:9:3',
    'test_pipeop_nearmiss.R:7:3', 'test_pipeop_multiplicityimply.R:9:3',
    'test_pipeop_ovr.R:9:3', 'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3',
    'test_pipeop_proxy.R:2:1', 'test_pipeop_quantilebin.R:5:3',
    'test_pipeop_randomprojection.R:6:3', 'test_pipeop_randomresponse.R:5:3',
    'test_pipeop_removeconstants.R:6:3', 'test_pipeop_renamecolumns.R:6:3',
    'test_pipeop_replicate.R:9:3', 'test_pipeop_rowapply.R:6:3',
    'test_pipeop_scale.R:6:3', 'test_pipeop_scale.R:10:3',
    'test_pipeop_scalemaxabs.R:6:3', 'test_pipeop_scalerange.R:7:3',
    'test_pipeop_select.R:9:3', 'test_pipeop_smote.R:10:3',
    'test_pipeop_smotenc.R:8:3', 'test_pipeop_spatialsign.R:3:1',
    'test_pipeop_splines.R:3:1', 'test_pipeop_subsample.R:6:3',
    'test_pipeop_targetinvert.R:4:3', 'test_pipeop_targetmutate.R:5:3',
    'test_pipeop_targettrafo.R:4:3', 'test_pipeop_targettrafoscalerange.R:5:3',
    'test_pipeop_nmf.R:6:3', 'test_pipeop_task_preproc.R:4:3',
    'test_pipeop_task_preproc.R:14:3', 'test_pipeop_tomek.R:7:3',
    'test_pipeop_textvectorizer.R:37:3', 'test_pipeop_textvectorizer.R:186:3',
    'test_pipeop_unbranch.R:10:3', 'test_pipeop_updatetarget.R:89:3',
    'test_pipeop_vtreat.R:9:3', 'test_pipeop_yeojohnson.R:7:3',
    'test_pipeop_tunethreshold.R:111:3', 'test_pipeop_tunethreshold.R:191:3',
    'test_ppl.R:63:3', 'test_typecheck.R:188:3'
  • Skipping (1): 'test_GraphLearner.R:1278:3'
  • empty test (2): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1'
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test_mlr_graphs_robustify.R:106:3'): Robustify Pipeline Impute Missings ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
      ▆
   1. └─mlr3::tsk("pima") at test_mlr_graphs_robustify.R:106:3
   2.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   3.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   4.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   5.         ├─base::do.call(constructor, cargs)
   6.         └─mlr3 (local) `<fn>`()
   7.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_pipeop_classbalancing.R:13:3'): PipeOpClassBalancing ───────────
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr_tasks$get("pima") at test_pipeop_classbalancing.R:13:3
    2.   ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
    3.   │ └─base::eval.parent(expr, n = 1L)
    4.   │   └─base::eval(expr, p)
    5.   │     └─base::eval(expr, p)
    6.   └─mlr3misc:::dictionary_get(self = self, key = key)
    7.     └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
    8.       ├─base::do.call(constructor, cargs)
    9.       └─mlr3 (local) `<fn>`()
   10.         └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_pipeop_classweights.R:17:3'): PipeOpClassWeights ───────────────
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr_tasks$get("pima") at test_pipeop_classweights.R:17:3
    2.   ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
    3.   │ └─base::eval.parent(expr, n = 1L)
    4.   │   └─base::eval(expr, p)
    5.   │     └─base::eval(expr, p)
    6.   └─mlr3misc:::dictionary_get(self = self, key = key)
    7.     └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
    8.       ├─base::do.call(constructor, cargs)
    9.       └─mlr3 (local) `<fn>`()
   10.         └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_pipeop_classweights.R:36:5'): PipeOpClassWeights - weight roles assigned ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
      ▆
   1. └─mlr3::tsk("pima") at test_pipeop_classweights.R:36:5
   2.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   3.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   4.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   5.         ├─base::do.call(constructor, cargs)
   6.         └─mlr3 (local) `<fn>`()
   7.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_pipeop_imputelearner.R:7:3'): PipeOpImputeLearner - simple tests ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:7:3
    2.   ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
    3.   │ └─base::eval.parent(expr, n = 1L)
    4.   │   └─base::eval(expr, p)
    5.   │     └─base::eval(expr, p)
    6.   └─mlr3misc:::dictionary_get(self = self, key = key)
    7.     └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
    8.       ├─base::do.call(constructor, cargs)
    9.       └─mlr3 (local) `<fn>`()
   10.         └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_pipeop_imputelearner.R:138:3'): PipeOpImputeLearner - model active binding to state ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:138:3
    2.   ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
    3.   │ └─base::eval.parent(expr, n = 1L)
    4.   │   └─base::eval(expr, p)
    5.   │     └─base::eval(expr, p)
    6.   └─mlr3misc:::dictionary_get(self = self, key = key)
    7.     └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
    8.       ├─base::do.call(constructor, cargs)
    9.       └─mlr3 (local) `<fn>`()
   10.         └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_pipeop_impute.R:452:3'): impute, test rows and affect_columns ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
      ▆
   1. └─mlr3::tsk("pima") at test_pipeop_impute.R:452:3
   2.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   3.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   4.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   5.         ├─base::do.call(constructor, cargs)
   6.         └─mlr3 (local) `<fn>`()
   7.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_pipeop_missind.R:4:3'): PipeOpMissInd ──────────────────────────
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr_tasks$get("pima") at test_pipeop_missind.R:4:3
    2.   ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
    3.   │ └─base::eval.parent(expr, n = 1L)
    4.   │   └─base::eval(expr, p)
    5.   │     └─base::eval(expr, p)
    6.   └─mlr3misc:::dictionary_get(self = self, key = key)
    7.     └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
    8.       ├─base::do.call(constructor, cargs)
    9.       └─mlr3 (local) `<fn>`()
   10.         └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_pipeop_unbranch.R:21:3'): PipeOpUnbranch - train and predict ───
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr_tasks$get("pima") at test_pipeop_unbranch.R:21:3
    2.   ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
    3.   │ └─base::eval.parent(expr, n = 1L)
    4.   │   └─base::eval(expr, p)
    5.   │     └─base::eval(expr, p)
    6.   └─mlr3misc:::dictionary_get(self = self, key = key)
    7.     └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
    8.       ├─base::do.call(constructor, cargs)
    9.       └─mlr3 (local) `<fn>`()
   10.         └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_pipeop_tunethreshold.R:36:3'): threshold works for binary ──────
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
      ▆
   1. └─mlr3::tsk("pima") at test_pipeop_tunethreshold.R:36:3
   2.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   3.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   4.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   5.         ├─base::do.call(constructor, cargs)
   6.         └─mlr3 (local) `<fn>`()
   7.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_pipeop_tunethreshold.R:73:3'): tunethreshold graph works ───────
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─graph$train(tsk("pima")) at test_pipeop_tunethreshold.R:73:3
    2. │ └─mlr3pipelines:::.__Graph__train(...)
    3. │   └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
    4. └─mlr3::tsk("pima")
    5.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
    6.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
    7.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
    8.         ├─base::do.call(constructor, cargs)
    9.         └─mlr3 (local) `<fn>`()
   10.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_selector.R:6:3'): Selectors work ───────────────────────────────
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3::mlr_tasks$get("pima") at test_selector.R:6:3
    2.   ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
    3.   │ └─base::eval.parent(expr, n = 1L)
    4.   │   └─base::eval(expr, p)
    5.   │     └─base::eval(expr, p)
    6.   └─mlr3misc:::dictionary_get(self = self, key = key)
    7.     └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
    8.       ├─base::do.call(constructor, cargs)
    9.       └─mlr3 (local) `<fn>`()
   10.         └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  
  [ FAIL 12 | WARN 12 | SKIP 128 | PASS 8462 ]
  Error:
  ! Test failures.
  Execution halted