Last updated on 2026-08-22 12:51:59 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.11.0 | 37.81 | 637.67 | 675.48 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.11.0 | 24.81 | 457.38 | 482.19 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.11.0 | 26.00 | 416.30 | 442.30 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 0.11.0 | 25.00 | 422.60 | 447.60 | ERROR | |
| r-devel-windows-x86_64 | 0.11.0 | 40.00 | 490.00 | 530.00 | ERROR | |
| r-patched-linux-x86_64 | 0.11.0 | 54.57 | 636.56 | 691.13 | ERROR | |
| r-release-linux-x86_64 | 0.11.0 | 36.17 | 620.02 | 656.19 | ERROR | |
| r-release-macos-arm64 | 0.11.0 | 8.00 | 106.00 | 114.00 | OK | |
| r-release-macos-x86_64 | 0.11.0 | 24.00 | 528.00 | 552.00 | OK | |
| r-release-windows-x86_64 | 0.11.0 | 39.00 | 477.00 | 516.00 | ERROR | |
| r-oldrel-macos-arm64 | 0.11.0 | OK | ||||
| r-oldrel-macos-x86_64 | 0.11.0 | 28.00 | 883.00 | 911.00 | OK | |
| r-oldrel-windows-x86_64 | 0.11.0 | 34.00 | 487.00 | 521.00 | ERROR |
Version: 0.11.0
Check: R code for possible problems
Result: NOTE
Found calls to structure() using deprecated special names:
mlr3pipelines/R/PipeOpFilter.R (.Names: 1)
'.Names' should be changed to 'names'.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64
Version: 0.11.0
Check: examples
Result: ERROR
Running examples in ‘mlr3pipelines-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: mlr_pipeops_imputeconstant
> ### Title: Impute Features by a Constant
> ### Aliases: mlr_pipeops_imputeconstant PipeOpImputeConstant
>
> ### ** Examples
>
> library("mlr3")
>
> task = tsk("pima")
Warning in data(list = id, package = package, envir = ee) :
data set ‘PimaIndiansDiabetes2’ not found
Error in UseMethod("as_data_backend") :
no applicable method for 'as_data_backend' applied to an object of class "NULL"
Calls: tsk ... dictionary_initialize_item -> do.call -> <Anonymous> -> as_data_backend
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
mlr_graphs_ovr 4.543 0.121 5.422
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [364s/184s]
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: [[1]]
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> test_multiplicities.R:
> 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
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-21 07:09:46.955502: Isomap START
> test_pipeop_isomap.R: 2026-08-21 07:09:46.956397: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:46.971807: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:46.990871: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 07:09:47.053711: Isomap START
> test_pipeop_isomap.R: 2026-08-21 07:09:47.054205: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:47.065126: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:47.085455: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 07:09:47.114382: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 07:09:47.115104: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:47.134593: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:47.177049: embedding
> test_pipeop_isomap.R: 2026-08-21 07:09:47.178445: DONE
> test_pipeop_isomap.R: 2026-08-21 07:09:47.209561: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 07:09:47.210102: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:47.230832: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:47.273317: embedding
> test_pipeop_isomap.R: 2026-08-21 07:09:47.27472: DONE
> test_pipeop_isomap.R: 2026-08-21 07:09:47.375236: Isomap START
> test_pipeop_isomap.R: 2026-08-21 07:09:47.375752: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:47.403885: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:47.501106: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 07:09:47.539176: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 07:09:47.539925: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:47.572617: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:47.772287: embedding
> test_pipeop_isomap.R: 2026-08-21 07:09:47.775546: DONE
> test_pipeop_isomap.R: 2026-08-21 07:09:47.940996: Isomap START
> test_pipeop_isomap.R: 2026-08-21 07:09:47.941513: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:47.96133: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:47.979366: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 07:09:48.016745: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 07:09:48.019054: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:48.036903: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:48.079268: embedding
> test_pipeop_isomap.R: 2026-08-21 07:09:48.080586: DONE
> test_pipeop_isomap.R: 2026-08-21 07:09:48.238725: Isomap START
> test_pipeop_isomap.R: 2026-08-21 07:09:48.239239: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:48.2503: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:48.268825: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 07:09:48.324742: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 07:09:48.327182: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:48.344693: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:48.386139: embedding
> test_pipeop_isomap.R: 2026-08-21 07:09:48.38738: DONE
> test_pipeop_isomap.R: 2026-08-21 07:09:48.488849: Isomap START
> test_pipeop_isomap.R: 2026-08-21 07:09:48.489356: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:48.500228: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:48.518722: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 07:09:48.575233: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 07:09:48.575988: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:48.595494: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:48.638315: embedding
> test_pipeop_isomap.R: 2026-08-21 07:09:48.639556: DONE
> test_pipeop_isomap.R: 2026-08-21 07:09:48.727795: Isomap START
> test_pipeop_isomap.R: 2026-08-21 07:09:48.728284: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:48.739013: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:48.757824: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 07:09:48.813907: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 07:09:48.814632: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:48.831884: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:48.874035: embedding
> test_pipeop_isomap.R: 2026-08-21 07:09:48.875236: DONE
> test_pipeop_isomap.R: 2026-08-21 07:09:48.973062: Isomap START
> test_pipeop_isomap.R: 2026-08-21 07:09:48.973583: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:48.985892: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:49.004905: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 07:09:49.06058: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 07:09:49.061352: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:49.078716: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:49.120497: embedding
> test_pipeop_isomap.R: 2026-08-21 07:09:49.121805: DONE
> test_pipeop_isomap.R: 2026-08-21 07:09:49.220343: Isomap START
> test_pipeop_isomap.R: 2026-08-21 07:09:49.22083: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:49.231399: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:49.249871: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 07:09:49.342606: Isomap START
> test_pipeop_isomap.R: 2026-08-21 07:09:49.343109: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:49.36436: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:49.384539: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 07:09:49.411256: Isomap START
> test_pipeop_isomap.R: 2026-08-21 07:09:49.411762: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 07:09:49.423691: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 07:09:49.442493: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> 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
> test_pipeop_task_preproc.R:
> test_pipeop_nmf.R: [PipeOpNMFstate]
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 21 | 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_dictionary.R:7:3',
'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_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_boxcox.R:7:3',
'test_pipeop_classbalancing.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_encodelmer.R:15:3',
'test_pipeop_encodelmer.R:37:3', 'test_pipeop_encodelmer.R:80:3',
'test_pipeop_encodepl.R:5:3', 'test_pipeop_encodepl.R:72:3',
'test_pipeop_ensemble.R:3:1', '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_kernelpca.R:9:3', 'test_pipeop_isomap.R:10:3',
'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_multiplicityimply.R:9:3',
'test_pipeop_nearmiss.R:7:3', '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_task_preproc.R:4:3',
'test_pipeop_task_preproc.R:14:3', 'test_pipeop_nmf.R:6:3',
'test_pipeop_textvectorizer.R:37:3', 'test_pipeop_textvectorizer.R:186:3',
'test_pipeop_tomek.R:7:3', '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 21 | SKIP 128 | PASS 8462 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.11.0
Check: examples
Result: ERROR
Running examples in ‘mlr3pipelines-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: mlr_pipeops_imputeconstant
> ### Title: Impute Features by a Constant
> ### Aliases: mlr_pipeops_imputeconstant PipeOpImputeConstant
>
> ### ** Examples
>
> library("mlr3")
>
> task = tsk("pima")
Warning in data(list = id, package = package, envir = ee) :
data set ‘PimaIndiansDiabetes2’ not found
Error in UseMethod("as_data_backend") :
no applicable method for 'as_data_backend' applied to an object of class "NULL"
Calls: tsk ... dictionary_initialize_item -> do.call -> <Anonymous> -> as_data_backend
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [273s/169s]
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:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R:
> 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:
> 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:
> 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: [1] 0
> test_multiplicities.R:
> test_multiplicities.R:
> test_pipeop_blsmote.R: [1]
> test_pipeop_blsmote.R: "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1]
> test_pipeop_blsmote.R: "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
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-21 18:30:37.140195: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:30:37.140968: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:37.156951: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:37.171578: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:30:37.216483: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:30:37.219236: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:37.231877: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:37.24805: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:30:37.274997: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:30:37.275692: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:37.295448: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:37.352168: embedding
> test_pipeop_isomap.R: 2026-08-21 18:30:37.35857: DONE
> test_pipeop_isomap.R: 2026-08-21 18:30:37.412492: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:30:37.413001: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:37.446671: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:37.522558: embedding
> test_pipeop_isomap.R: 2026-08-21 18:30:37.523602: DONE
> test_pipeop_isomap.R: 2026-08-21 18:30:37.642655: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:30:37.643132: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:37.674262: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:37.755673: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:30:37.810215: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:30:37.811423: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:37.890759: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:38.09488: embedding
> test_pipeop_isomap.R: 2026-08-21 18:30:38.099608: DONE
> test_pipeop_isomap.R: 2026-08-21 18:30:38.224407: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:30:38.226061: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:38.242862: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:38.268445: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:30:38.311474: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:30:38.314349: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:38.340264: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:38.413258: embedding
> test_pipeop_isomap.R: 2026-08-21 18:30:38.414265: DONE
> test_pipeop_isomap.R: 2026-08-21 18:30:38.566783: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:30:38.569149: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:38.579024: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:38.594682: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:30:38.633157: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:30:38.63547: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:38.651641: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:38.699068: embedding
> test_pipeop_isomap.R: 2026-08-21 18:30:38.70024: DONE
> test_pipeop_isomap.R: 2026-08-21 18:30:38.777039: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:30:38.77744: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:38.788276: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:38.807469: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:30:38.895908: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:30:38.896552: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:38.912827: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:38.954139: embedding
> test_pipeop_isomap.R: 2026-08-21 18:30:38.955204: DONE
> test_pipeop_isomap.R: 2026-08-21 18:30:39.025683: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:30:39.027825: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:39.03881: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:39.055173: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:30:39.114242: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:30:39.114875: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:39.1317: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:39.166408: embedding
> test_pipeop_isomap.R: 2026-08-21 18:30:39.167553: DONE
> test_pipeop_isomap.R: 2026-08-21 18:30:39.240497: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:30:39.241845: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:39.253952: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:39.270357: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:30:39.337614: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:30:39.341209: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:39.374479: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:39.44375: embedding
> test_pipeop_isomap.R: 2026-08-21 18:30:39.447675: DONE
> test_pipeop_isomap.R: 2026-08-21 18:30:39.564863: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:30:39.565309: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:39.577918: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:39.606876: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:30:39.708275: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:30:39.710773: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:39.72106: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:39.736822: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:30:39.759643: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:30:39.760092: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:30:39.769313: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:30:39.784044: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> 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:
> 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:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> 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:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> 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:
> test_pipeop_nmf.R: [PipeOpNMFstate]
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 21 | 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_boxcox.R:7:3', 'test_pipeop_classbalancing.R:7:3',
'test_pipeop_classweights.R:10:3', 'test_pipeop_classweightsex.R:9:3',
'test_pipeop_collapsefactors.R:6:3', 'test_pipeop_colapply.R:9:3',
'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_featureunion.R:9:3', 'test_pipeop_featureunion.R:134:3',
'test_pipeop_histbin.R:7:3', 'test_pipeop_ica.R:7:3',
'test_pipeop_imputelearner.R:43:3', 'test_pipeop_info.R:3:1',
'test_pipeop_impute.R:4:3', 'test_pipeop_kernelpca.R:9:3',
'test_pipeop_isomap.R:10:3', '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_task_preproc.R:4:3', 'test_pipeop_task_preproc.R:14:3',
'test_pipeop_nmf.R:6:3', '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 21 | SKIP 128 | PASS 8462 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.11.0
Check: examples
Result: ERROR
Running examples in ‘mlr3pipelines-Ex.R’ failed
The error most likely occurred in:
> ### Name: mlr_pipeops_imputeconstant
> ### Title: Impute Features by a Constant
> ### Aliases: mlr_pipeops_imputeconstant PipeOpImputeConstant
>
> ### ** Examples
>
> library("mlr3")
>
> task = tsk("pima")
Error: Element with key 'pima' not found in DictionaryTask!
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [244s/157s]
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:
> 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:
> 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:
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R:
> 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:
Saving _problems/test_mlr_graphs_robustify-106.R
> test_multiplicities.R:
> test_multiplicities.R: [[1]]
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> 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
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-21 18:44:32.280215: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:44:32.28102: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:32.31027: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:32.351499: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:44:32.456963: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:44:32.460272: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:32.480572: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:32.510363: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:44:32.563635: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:44:32.564272: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:32.609463: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:32.677616: embedding
> test_pipeop_isomap.R: 2026-08-21 18:44:32.682967: DONE
> test_pipeop_isomap.R: 2026-08-21 18:44:32.747489: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:44:32.747985: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:32.801705: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:32.873899: embedding
> test_pipeop_isomap.R: 2026-08-21 18:44:32.874948: DONE
> test_pipeop_isomap.R: 2026-08-21 18:44:33.022523: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:44:33.022897: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:33.051426: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:33.160376: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:44:33.186241: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:44:33.18682: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:33.220575: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:33.524668: embedding
> test_pipeop_isomap.R: 2026-08-21 18:44:33.529357: DONE
> test_pipeop_isomap.R: 2026-08-21 18:44:33.705241: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:44:33.706948: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:33.71608: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:33.730994: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:44:33.756629: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:44:33.757202: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:33.780219: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:33.81384: embedding
> test_pipeop_isomap.R: 2026-08-21 18:44:33.816012: DONE
> test_pipeop_isomap.R: 2026-08-21 18:44:33.982193: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:44:33.9826: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:34.000624: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:34.03072: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:44:34.111199: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:44:34.115021: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:34.160099: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:34.228177: embedding
> test_pipeop_isomap.R: 2026-08-21 18:44:34.229037: DONE
> test_pipeop_isomap.R: 2026-08-21 18:44:34.376777: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:44:34.377181: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:34.402762: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:34.43972: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:44:34.521502: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:44:34.522084: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:34.704669: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:34.760536: embedding
> test_pipeop_isomap.R: 2026-08-21 18:44:34.761504: DONE
> test_pipeop_isomap.R: 2026-08-21 18:44:34.817433: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:44:34.817816: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:34.825742: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:34.839233: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:44:34.87449: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:44:34.875058: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:34.88829: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:34.920478: embedding
> test_pipeop_isomap.R: 2026-08-21 18:44:34.921386: DONE
> test_pipeop_isomap.R: 2026-08-21 18:44:34.982734: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:44:34.983166: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:34.991789: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:35.008573: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:44:35.090379: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 18:44:35.090949: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:35.105812: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:35.140814: embedding
> test_pipeop_isomap.R: 2026-08-21 18:44:35.143239: DONE
> test_pipeop_isomap.R: 2026-08-21 18:44:35.288893: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:44:35.289286: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:35.30608: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:35.334344: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:44:35.469723: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:44:35.470113: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:35.486806: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:35.515256: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 18:44:35.559236: Isomap START
> test_pipeop_isomap.R: 2026-08-21 18:44:35.559644: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 18:44:35.59309: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 18:44:35.624324: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> 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:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> 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:
> 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_nmf.R: [PipeOpNMFstate]
> test_pipeop_nmf.R: [PipeOpNMFstate]
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 9 | 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_dictionary.R:7:3', '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_meta.R:39:3',
'test_mlr_graphs_bagging.R:6:3', 'test_mlr_graphs_branching.R:26:3',
'test_mlr_graphs_robustify.R:5:3', 'test_pipeop_adas.R:8:3',
'test_pipeop_blsmote.R:8:3', 'test_pipeop_boxcox.R:7:3',
'test_pipeop_chunk.R:4:3', 'test_pipeop_classbalancing.R:7:3',
'test_pipeop_branch.R:4:3', 'test_pipeop_classweights.R:10:3',
'test_pipeop_colapply.R:9:3', 'test_pipeop_classweightsex.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_encodelmer.R:15:3',
'test_pipeop_encodelmer.R:37:3', 'test_pipeop_encodelmer.R:80:3',
'test_pipeop_ensemble.R:3:1', 'test_pipeop_encodepl.R:5:3',
'test_pipeop_encodepl.R:72:3', 'test_pipeop_featureunion.R:9:3',
'test_pipeop_featureunion.R:134:3', 'test_pipeop_fixfactors.R:9:3',
'test_pipeop_filter.R:7:3', 'test_pipeop_histbin.R:7:3',
'test_pipeop_ica.R:7:3', 'test_pipeop_imputelearner.R:43:3',
'test_pipeop_info.R:3:1', 'test_pipeop_impute.R:4:3',
'test_pipeop_kernelpca.R:9:3', 'test_pipeop_learner.R:17:3',
'test_pipeop_isomap.R:10:3', '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_multiplicityimply.R:9:3', 'test_pipeop_mutate.R:9:3',
'test_pipeop_nearmiss.R:7:3', '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_task_preproc.R:4:3',
'test_pipeop_task_preproc.R:14:3', 'test_pipeop_textvectorizer.R:37:3',
'test_pipeop_textvectorizer.R:186:3', 'test_pipeop_tomek.R:7:3',
'test_pipeop_nmf.R:6:3', '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 ──
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
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_retrieve_item(self, key, .dicts_suggest)
5. └─mlr3misc::stopf(...)
── Error ('test_pipeop_classbalancing.R:13:3'): PipeOpClassBalancing ───────────
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classbalancing.R:13:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_pipeop_classweights.R:17:3'): PipeOpClassWeights ───────────────
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr_tasks$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_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_pipeop_classweights.R:36:5'): PipeOpClassWeights - weight roles assigned ──
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
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_retrieve_item(self, key, .dicts_suggest)
5. └─mlr3misc::stopf(...)
── Error ('test_pipeop_imputelearner.R:7:3'): PipeOpImputeLearner - simple tests ──
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:7:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_pipeop_imputelearner.R:138:3'): PipeOpImputeLearner - model active binding to state ──
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr_tasks$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_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_pipeop_impute.R:452:3'): impute, test rows and affect_columns ──
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
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_retrieve_item(self, key, .dicts_suggest)
5. └─mlr3misc::stopf(...)
── Error ('test_pipeop_missind.R:4:3'): PipeOpMissInd ──────────────────────────
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_missind.R:4:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_pipeop_unbranch.R:21:3'): PipeOpUnbranch - train and predict ───
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr_tasks$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_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_pipeop_tunethreshold.R:36:3'): threshold works for binary ──────
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
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_retrieve_item(self, key, .dicts_suggest)
5. └─mlr3misc::stopf(...)
── Error ('test_pipeop_tunethreshold.R:73:3'): tunethreshold graph works ───────
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. ├─graph$train(tsk("pima")) at test_pipeop_tunethreshold.R:73:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. └─mlr3::tsk("pima")
5. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
6. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
7. └─mlr3misc:::dictionary_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_selector.R:6:3'): Selectors work ───────────────────────────────
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr3::mlr_tasks$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_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
[ FAIL 12 | WARN 9 | SKIP 128 | PASS 8462 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [251s/137s]
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_Graph.R:
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
> 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:
Saving _problems/test_mlr_graphs_robustify-106.R
> test_multiplicities.R:
> test_multiplicities.R: [[1]]
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> 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
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-21 20:46:40.265359: Isomap START
> test_pipeop_isomap.R: 2026-08-21 20:46:40.266022: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:40.281835: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:40.297736: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 20:46:40.341354: Isomap START
> test_pipeop_isomap.R: 2026-08-21 20:46:40.341792: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:40.353399: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:40.368745: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 20:46:40.391181: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 20:46:40.391815: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:40.421386: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:40.454391: embedding
> test_pipeop_isomap.R: 2026-08-21 20:46:40.455328: DONE
> test_pipeop_isomap.R: 2026-08-21 20:46:40.477443: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 20:46:40.479165: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:40.493803: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:40.526752: embedding
> test_pipeop_isomap.R: 2026-08-21 20:46:40.529083: DONE
> test_pipeop_isomap.R: 2026-08-21 20:46:40.598608: Isomap START
> test_pipeop_isomap.R: 2026-08-21 20:46:40.598981: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:40.615302: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:40.694872: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 20:46:40.732246: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 20:46:40.732814: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:40.783624: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:40.976756: embedding
> test_pipeop_isomap.R: 2026-08-21 20:46:40.984509: DONE
> test_pipeop_isomap.R: 2026-08-21 20:46:41.139836: Isomap START
> test_pipeop_isomap.R: 2026-08-21 20:46:41.140222: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:41.152463: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:41.168146: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 20:46:41.191541: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 20:46:41.192104: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:41.207914: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:41.241277: embedding
> test_pipeop_isomap.R: 2026-08-21 20:46:41.242191: DONE
> test_pipeop_isomap.R: 2026-08-21 20:46:41.358684: Isomap START
> test_pipeop_isomap.R: 2026-08-21 20:46:41.359058: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:41.368949: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:41.38521: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 20:46:41.421902: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 20:46:41.422466: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:41.444377: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:41.483337: embedding
> test_pipeop_isomap.R: 2026-08-21 20:46:41.484219: DONE
> test_pipeop_isomap.R: 2026-08-21 20:46:41.547765: Isomap START
> test_pipeop_isomap.R: 2026-08-21 20:46:41.548146: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:41.556469: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:41.572216: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 20:46:41.611512: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 20:46:41.612096: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:41.626921: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:41.663284: embedding
> test_pipeop_isomap.R: 2026-08-21 20:46:41.672626: DONE
> test_pipeop_isomap.R: 2026-08-21 20:46:41.73431: Isomap START
> test_pipeop_isomap.R: 2026-08-21 20:46:41.734713: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:41.744737: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:41.76055: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 20:46:41.805486: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 20:46:41.80619: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:41.824835: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:41.857908: embedding
> test_pipeop_isomap.R: 2026-08-21 20:46:41.860225: DONE
> test_pipeop_isomap.R: 2026-08-21 20:46:41.930034: Isomap START
> test_pipeop_isomap.R: 2026-08-21 20:46:41.930463: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:42.022041: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:42.03789: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 20:46:42.074807: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-21 20:46:42.076716: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:42.095417: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:42.129842: embedding
> test_pipeop_isomap.R: 2026-08-21 20:46:42.132186: DONE
> test_pipeop_isomap.R: 2026-08-21 20:46:42.200581: Isomap START
> test_pipeop_isomap.R: 2026-08-21 20:46:42.200977: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:42.210929: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:42.226646: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 20:46:42.290849: Isomap START
> test_pipeop_isomap.R: 2026-08-21 20:46:42.29253: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:42.302762: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:42.318437: Classical Scaling
> test_pipeop_isomap.R: 2026-08-21 20:46:42.362924: Isomap START
> test_pipeop_isomap.R: 2026-08-21 20:46:42.36334: constructing knn graph
> test_pipeop_isomap.R: 2026-08-21 20:46:42.382113: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-21 20:46:42.398087: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> 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:
> 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:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> 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:
> test_pipeop_nmf.R: [PipeOpNMFstate]
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 9 | 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_boxcox.R:7:3',
'test_pipeop_chunk.R:4:3', 'test_pipeop_classbalancing.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_encodeimpact.R:11:3', 'test_pipeop_datefeatures.R:10:3',
'test_pipeop_encodelmer.R:15:3', 'test_pipeop_encodelmer.R:37:3',
'test_pipeop_encodelmer.R:80:3', 'test_pipeop_encodepl.R:5:3',
'test_pipeop_encodepl.R:72:3', 'test_pipeop_ensemble.R:3:1',
'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_kernelpca.R:9:3',
'test_pipeop_isomap.R:10:3', 'test_pipeop_learner.R:17:3',
'test_pipeop_learnerpicvplus.R:2:1', 'test_pipeop_modelmatrix.R:7:3',
'test_pipeop_multiplicityexply.R:9:3', 'test_pipeop_multiplicityimply.R:9:3',
'test_pipeop_mutate.R:9:3', 'test_pipeop_nearmiss.R:7:3',
'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_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_task_preproc.R:4:3', 'test_pipeop_task_preproc.R:14:3',
'test_pipeop_nmf.R:6:3', '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 ──
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
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_retrieve_item(self, key, .dicts_suggest)
5. └─mlr3misc::stopf(...)
── Error ('test_pipeop_classbalancing.R:13:3'): PipeOpClassBalancing ───────────
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classbalancing.R:13:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_pipeop_classweights.R:17:3'): PipeOpClassWeights ───────────────
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr_tasks$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_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_pipeop_classweights.R:36:5'): PipeOpClassWeights - weight roles assigned ──
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
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_retrieve_item(self, key, .dicts_suggest)
5. └─mlr3misc::stopf(...)
── Error ('test_pipeop_imputelearner.R:7:3'): PipeOpImputeLearner - simple tests ──
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:7:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_pipeop_imputelearner.R:138:3'): PipeOpImputeLearner - model active binding to state ──
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr_tasks$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_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_pipeop_impute.R:452:3'): impute, test rows and affect_columns ──
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
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_retrieve_item(self, key, .dicts_suggest)
5. └─mlr3misc::stopf(...)
── Error ('test_pipeop_missind.R:4:3'): PipeOpMissInd ──────────────────────────
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_missind.R:4:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_pipeop_unbranch.R:21:3'): PipeOpUnbranch - train and predict ───
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr_tasks$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_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_pipeop_tunethreshold.R:36:3'): threshold works for binary ──────
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
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_retrieve_item(self, key, .dicts_suggest)
5. └─mlr3misc::stopf(...)
── Error ('test_pipeop_tunethreshold.R:73:3'): tunethreshold graph works ───────
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. ├─graph$train(tsk("pima")) at test_pipeop_tunethreshold.R:73:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. └─mlr3::tsk("pima")
5. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
6. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
7. └─mlr3misc:::dictionary_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
── Error ('test_selector.R:6:3'): Selectors work ───────────────────────────────
<Mlr3Error/error/condition>
Error: Element with key 'pima' not found in DictionaryTask!
Backtrace:
▆
1. └─mlr3::mlr_tasks$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_retrieve_item(self, key, .dicts_suggest)
8. └─mlr3misc::stopf(...)
[ FAIL 12 | WARN 9 | SKIP 128 | PASS 8462 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.11.0
Check: examples
Result: ERROR
Running examples in 'mlr3pipelines-Ex.R' failed
The error most likely occurred in:
> ### Name: mlr_pipeops_imputeconstant
> ### Title: Impute Features by a Constant
> ### Aliases: mlr_pipeops_imputeconstant PipeOpImputeConstant
>
> ### ** Examples
>
> library("mlr3")
>
> task = tsk("pima")
Warning in data(list = id, package = package, envir = ee) :
data set 'PimaIndiansDiabetes2' not found
Error in UseMethod("as_data_backend") :
no applicable method for 'as_data_backend' applied to an object of class "NULL"
Calls: tsk ... dictionary_initialize_item -> do.call -> <Anonymous> -> as_data_backend
Execution halted
Flavors: r-devel-windows-x86_64, r-release-windows-x86_64, r-oldrel-windows-x86_64
Version: 0.11.0
Check: tests
Result: ERROR
Running 'testthat.R' [172s]
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:
> 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
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-18 21:26:39.075348: Isomap START
> test_pipeop_isomap.R: 2026-08-18 21:26:39.077008: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:39.09463: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:39.114387: Classical Scaling
> test_pipeop_isomap.R: 2026-08-18 21:26:39.16557: Isomap START
> test_pipeop_isomap.R: 2026-08-18 21:26:39.166502: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:39.174918: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:39.189989: Classical Scaling
> test_pipeop_isomap.R: 2026-08-18 21:26:39.224435: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-18 21:26:39.225824: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:39.24816: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:39.290276: embedding
> test_pipeop_isomap.R: 2026-08-18 21:26:39.292772: DONE
> test_pipeop_isomap.R: 2026-08-18 21:26:39.327655: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-18 21:26:39.328929: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:39.348829: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:39.390461: embedding
> test_pipeop_isomap.R: 2026-08-18 21:26:39.393343: DONE
> test_pipeop_isomap.R: 2026-08-18 21:26:39.493021: Isomap START
> test_pipeop_isomap.R: 2026-08-18 21:26:39.494317: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:39.513: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:39.611009: Classical Scaling
> test_pipeop_isomap.R: 2026-08-18 21:26:39.647305: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-18 21:26:39.64867: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:39.678972: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:39.88349: embedding
> test_pipeop_isomap.R: 2026-08-18 21:26:39.896422: DONE
> test_pipeop_isomap.R: 2026-08-18 21:26:40.082116: Isomap START
> test_pipeop_isomap.R: 2026-08-18 21:26:40.083589: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:40.098485: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:40.116571: Classical Scaling
> test_pipeop_isomap.R: 2026-08-18 21:26:40.154874: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-18 21:26:40.156098: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:40.175164: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:40.219275: embedding
> test_pipeop_isomap.R: 2026-08-18 21:26:40.221505: DONE
> test_pipeop_isomap.R: 2026-08-18 21:26:40.40421: Isomap START
> test_pipeop_isomap.R: 2026-08-18 21:26:40.405569: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:40.42111: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:40.443527: Classical Scaling
> test_pipeop_isomap.R: 2026-08-18 21:26:40.500158: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-18 21:26:40.501549: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:40.520836: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:40.564515: embedding
> test_pipeop_isomap.R: 2026-08-18 21:26:40.566558: DONE
> test_pipeop_isomap.R: 2026-08-18 21:26:40.640465: Isomap START
> test_pipeop_isomap.R: 2026-08-18 21:26:40.641708: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:40.653135: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:40.668026: Classical Scaling
> test_pipeop_isomap.R: 2026-08-18 21:26:40.726948: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-18 21:26:40.728364: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:40.755544: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:40.798697: embedding
> test_pipeop_isomap.R: 2026-08-18 21:26:40.80083: DONE
> test_pipeop_isomap.R: 2026-08-18 21:26:40.893796: Isomap START
> test_pipeop_isomap.R: 2026-08-18 21:26:40.895197: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:40.905574: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:40.923043: Classical Scaling
> test_pipeop_isomap.R: 2026-08-18 21:26:40.975728: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-18 21:26:40.976843: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:40.99172: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:41.039317: embedding
> test_pipeop_isomap.R: 2026-08-18 21:26:41.04215: DONE
> test_pipeop_isomap.R: 2026-08-18 21:26:41.155062: Isomap START
> test_pipeop_isomap.R: 2026-08-18 21:26:41.156286: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:41.169285: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:41.18784: Classical Scaling
> test_pipeop_isomap.R: 2026-08-18 21:26:41.238545: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-18 21:26:41.2396: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:41.257786: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:41.301424: embedding
> test_pipeop_isomap.R: 2026-08-18 21:26:41.303547: DONE
> test_pipeop_isomap.R: 2026-08-18 21:26:41.396781: Isomap START
> test_pipeop_isomap.R: 2026-08-18 21:26:41.397923: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:41.40971: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:41.427712: Classical Scaling
> test_pipeop_isomap.R: 2026-08-18 21:26:41.516076: Isomap START
> test_pipeop_isomap.R: 2026-08-18 21:26:41.517269: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:41.52748: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:41.5445: Classical Scaling
> test_pipeop_isomap.R: 2026-08-18 21:26:41.57259: Isomap START
> test_pipeop_isomap.R: 2026-08-18 21:26:41.573893: constructing knn graph
> test_pipeop_isomap.R: 2026-08-18 21:26:41.583237: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-18 21:26:41.599183: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> 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
> test_pipeop_nmf.R: [PipeOpNMFstate]
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 21 | 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_encodeimpact.R:11:3', 'test_pipeop_datefeatures.R:10:3',
'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_kernelpca.R:9:3',
'test_pipeop_isomap.R:10:3', '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_task_preproc.R:4:3', 'test_pipeop_task_preproc.R:14:3',
'test_pipeop_nmf.R:6:3', '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 21 | SKIP 128 | PASS 8462 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-windows-x86_64
Version: 0.11.0
Check: examples
Result: ERROR
Running examples in ‘mlr3pipelines-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: mlr_pipeops_imputeconstant
> ### Title: Impute Features by a Constant
> ### Aliases: mlr_pipeops_imputeconstant PipeOpImputeConstant
>
> ### ** Examples
>
> library("mlr3")
>
> task = tsk("pima")
Warning in data(list = id, package = package, envir = ee) :
data set ‘PimaIndiansDiabetes2’ not found
Error in UseMethod("as_data_backend") :
no applicable method for 'as_data_backend' applied to an object of class "NULL"
Calls: tsk ... dictionary_initialize_item -> do.call -> <Anonymous> -> as_data_backend
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
mlr_graphs_ovr 4.204 0.137 5.543
Flavor: r-patched-linux-x86_64
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [359s/186s]
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: [1] 0
> test_multiplicities.R:
> 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
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-12 18:24:16.918409: Isomap START
> test_pipeop_isomap.R: 2026-08-12 18:24:16.919316: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:16.934583: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:16.953714: Classical Scaling
> test_pipeop_isomap.R: 2026-08-12 18:24:17.026078: Isomap START
> test_pipeop_isomap.R: 2026-08-12 18:24:17.026637: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:17.038301: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:17.056968: Classical Scaling
> test_pipeop_isomap.R: 2026-08-12 18:24:17.089084: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-12 18:24:17.089908: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:17.110732: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:17.152917: embedding
> test_pipeop_isomap.R: 2026-08-12 18:24:17.154496: DONE
> test_pipeop_isomap.R: 2026-08-12 18:24:17.187533: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-12 18:24:17.188104: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:17.207717: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:17.249507: embedding
> test_pipeop_isomap.R: 2026-08-12 18:24:17.250908: DONE
> test_pipeop_isomap.R: 2026-08-12 18:24:17.361221: Isomap START
> test_pipeop_isomap.R: 2026-08-12 18:24:17.36181: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:17.395115: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:17.491959: Classical Scaling
> test_pipeop_isomap.R: 2026-08-12 18:24:17.536902: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-12 18:24:17.540073: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:17.571714: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:17.768295: embedding
> test_pipeop_isomap.R: 2026-08-12 18:24:17.771579: DONE
> test_pipeop_isomap.R: 2026-08-12 18:24:17.944504: Isomap START
> test_pipeop_isomap.R: 2026-08-12 18:24:17.945052: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:17.956189: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:17.975078: Classical Scaling
> test_pipeop_isomap.R: 2026-08-12 18:24:18.023891: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-12 18:24:18.024628: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:18.042325: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:18.086856: embedding
> test_pipeop_isomap.R: 2026-08-12 18:24:18.088165: DONE
> test_pipeop_isomap.R: 2026-08-12 18:24:18.247621: Isomap START
> test_pipeop_isomap.R: 2026-08-12 18:24:18.250128: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:18.261373: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:18.280103: Classical Scaling
> test_pipeop_isomap.R: 2026-08-12 18:24:18.335846: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-12 18:24:18.336654: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:18.356651: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:18.398822: embedding
> test_pipeop_isomap.R: 2026-08-12 18:24:18.400052: DONE
> test_pipeop_isomap.R: 2026-08-12 18:24:18.493217: Isomap START
> test_pipeop_isomap.R: 2026-08-12 18:24:18.493775: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:18.50737: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:18.52618: Classical Scaling
> test_pipeop_isomap.R: 2026-08-12 18:24:18.598762: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-12 18:24:18.599526: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:18.61727: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:18.658944: embedding
> test_pipeop_isomap.R: 2026-08-12 18:24:18.660219: DONE
> test_pipeop_isomap.R: 2026-08-12 18:24:18.754323: Isomap START
> test_pipeop_isomap.R: 2026-08-12 18:24:18.754869: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:18.766201: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:18.785159: Classical Scaling
> test_pipeop_isomap.R: 2026-08-12 18:24:18.844279: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-12 18:24:18.845037: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:18.862878: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:18.912369: embedding
> test_pipeop_isomap.R: 2026-08-12 18:24:18.914482: DONE
> test_pipeop_isomap.R: 2026-08-12 18:24:19.03027: Isomap START
> test_pipeop_isomap.R: 2026-08-12 18:24:19.030876: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:19.046997: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:19.065853: Classical Scaling
> test_pipeop_isomap.R: 2026-08-12 18:24:19.131783: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-12 18:24:19.132647: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:19.177646: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:19.219429: embedding
> test_pipeop_isomap.R: 2026-08-12 18:24:19.220777: DONE
> test_pipeop_isomap.R: 2026-08-12 18:24:19.325372: Isomap START
> test_pipeop_isomap.R: 2026-08-12 18:24:19.325915: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:19.336651: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:19.358253: Classical Scaling
> test_pipeop_isomap.R: 2026-08-12 18:24:19.455604: Isomap START
> test_pipeop_isomap.R: 2026-08-12 18:24:19.456149: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:19.467107: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:19.485575: Classical Scaling
> test_pipeop_isomap.R: 2026-08-12 18:24:19.515675: Isomap START
> test_pipeop_isomap.R: 2026-08-12 18:24:19.516207: constructing knn graph
> test_pipeop_isomap.R: 2026-08-12 18:24:19.526545: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-12 18:24:19.545336: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> 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
> test_pipeop_nmf.R: [PipeOpNMFstate]
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_dictionary.R:7:3', '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_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_boxcox.R:7:3',
'test_pipeop_classbalancing.R:7:3', 'test_pipeop_classweights.R:10:3',
'test_pipeop_classweightsex.R:9:3', 'test_pipeop_collapsefactors.R:6:3',
'test_pipeop_colapply.R:9:3', '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_encodeimpact.R:11:3',
'test_pipeop_datefeatures.R:10:3', '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_kernelpca.R:9:3', 'test_pipeop_isomap.R:10:3',
'test_pipeop_learner.R:17:3', 'test_pipeop_learnerpicvplus.R:2:1',
'test_pipeop_modelmatrix.R:7:3', 'test_pipeop_multiplicityexply.R:9:3',
'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_mutate.R:9:3', 'test_pipeop_multiplicityimply.R:9:3',
'test_pipeop_nearmiss.R:7:3', '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_task_preproc.R:4:3',
'test_pipeop_task_preproc.R:14:3', 'test_pipeop_nmf.R:6:3',
'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
Flavor: r-patched-linux-x86_64
Version: 0.11.0
Check: examples
Result: ERROR
Running examples in ‘mlr3pipelines-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: mlr_pipeops_imputeconstant
> ### Title: Impute Features by a Constant
> ### Aliases: mlr_pipeops_imputeconstant PipeOpImputeConstant
>
> ### ** Examples
>
> library("mlr3")
>
> task = tsk("pima")
Warning in data(list = id, package = package, envir = ee) :
data set ‘PimaIndiansDiabetes2’ not found
Error in UseMethod("as_data_backend") :
no applicable method for 'as_data_backend' applied to an object of class "NULL"
Calls: tsk ... dictionary_initialize_item -> do.call -> <Anonymous> -> as_data_backend
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
mlr_graphs_ovr 4.573 0.075 7.696
Flavor: r-release-linux-x86_64
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [344s/177s]
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: [[1]]
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> test_multiplicities.R:
> 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
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-15 18:24:01.1193: Isomap START
> test_pipeop_isomap.R: 2026-08-15 18:24:01.120128: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:01.133715: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:01.15333: Classical Scaling
> test_pipeop_isomap.R: 2026-08-15 18:24:01.217587: Isomap START
> test_pipeop_isomap.R: 2026-08-15 18:24:01.218092: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:01.229548: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:01.247805: Classical Scaling
> test_pipeop_isomap.R: 2026-08-15 18:24:01.274529: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-15 18:24:01.275227: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:01.295931: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:01.337922: embedding
> test_pipeop_isomap.R: 2026-08-15 18:24:01.339081: DONE
> test_pipeop_isomap.R: 2026-08-15 18:24:01.366811: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-15 18:24:01.367283: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:01.385433: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:01.427358: embedding
> test_pipeop_isomap.R: 2026-08-15 18:24:01.428689: DONE
> test_pipeop_isomap.R: 2026-08-15 18:24:01.523941: Isomap START
> test_pipeop_isomap.R: 2026-08-15 18:24:01.524426: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:01.554239: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:01.651886: Classical Scaling
> test_pipeop_isomap.R: 2026-08-15 18:24:01.689051: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-15 18:24:01.689714: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:01.719552: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:01.925381: embedding
> test_pipeop_isomap.R: 2026-08-15 18:24:01.928035: DONE
> test_pipeop_isomap.R: 2026-08-15 18:24:02.107747: Isomap START
> test_pipeop_isomap.R: 2026-08-15 18:24:02.108229: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:02.118954: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:02.137842: Classical Scaling
> test_pipeop_isomap.R: 2026-08-15 18:24:02.171722: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-15 18:24:02.172403: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:02.199655: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:02.241558: embedding
> test_pipeop_isomap.R: 2026-08-15 18:24:02.242749: DONE
> test_pipeop_isomap.R: 2026-08-15 18:24:02.389086: Isomap START
> test_pipeop_isomap.R: 2026-08-15 18:24:02.389546: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:02.400125: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:02.420187: Classical Scaling
> test_pipeop_isomap.R: 2026-08-15 18:24:02.473511: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-15 18:24:02.474204: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:02.491091: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:02.531918: embedding
> test_pipeop_isomap.R: 2026-08-15 18:24:02.533028: DONE
> test_pipeop_isomap.R: 2026-08-15 18:24:02.619854: Isomap START
> test_pipeop_isomap.R: 2026-08-15 18:24:02.620337: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:02.631885: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:02.650423: Classical Scaling
> test_pipeop_isomap.R: 2026-08-15 18:24:02.712505: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-15 18:24:02.713225: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:02.731082: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:02.775838: embedding
> test_pipeop_isomap.R: 2026-08-15 18:24:02.777092: DONE
> test_pipeop_isomap.R: 2026-08-15 18:24:02.859774: Isomap START
> test_pipeop_isomap.R: 2026-08-15 18:24:02.860222: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:02.870919: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:02.889456: Classical Scaling
> test_pipeop_isomap.R: 2026-08-15 18:24:02.940766: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-15 18:24:02.941491: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:02.95903: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:03.000717: embedding
> test_pipeop_isomap.R: 2026-08-15 18:24:03.001903: DONE
> test_pipeop_isomap.R: 2026-08-15 18:24:03.082371: Isomap START
> test_pipeop_isomap.R: 2026-08-15 18:24:03.082895: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:03.105599: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:03.123861: Classical Scaling
> test_pipeop_isomap.R: 2026-08-15 18:24:03.172397: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-15 18:24:03.173117: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:03.190434: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:03.233396: embedding
> test_pipeop_isomap.R: 2026-08-15 18:24:03.234612: DONE
> test_pipeop_isomap.R: 2026-08-15 18:24:03.321945: Isomap START
> test_pipeop_isomap.R: 2026-08-15 18:24:03.323797: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:03.33435: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:03.353482: Classical Scaling
> test_pipeop_isomap.R: 2026-08-15 18:24:03.438916: Isomap START
> test_pipeop_isomap.R: 2026-08-15 18:24:03.43946: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:03.449981: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:03.470825: Classical Scaling
> test_pipeop_isomap.R: 2026-08-15 18:24:03.496873: Isomap START
> test_pipeop_isomap.R: 2026-08-15 18:24:03.497393: constructing knn graph
> test_pipeop_isomap.R: 2026-08-15 18:24:03.507601: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-15 18:24:03.529063: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> 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
> test_pipeop_nmf.R: [PipeOpNMFstate]
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_boxcox.R:7:3', 'test_pipeop_classbalancing.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_kernelpca.R:9:3',
'test_pipeop_isomap.R:10:3', '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_multiplicityimply.R:9:3', 'test_pipeop_nearmiss.R:7:3',
'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_task_preproc.R:4:3', 'test_pipeop_task_preproc.R:14:3',
'test_pipeop_nmf.R:6:3', '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
Flavor: r-release-linux-x86_64
Version: 0.11.0
Check: tests
Result: ERROR
Running 'testthat.R' [158s]
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:
> 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: 2026-08-20 05:13:36.810629: Isomap START
> test_pipeop_isomap.R: 2026-08-20 05:13:36.811877: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:36.824381: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:36.840933: Classical Scaling
> test_pipeop_isomap.R: 2026-08-20 05:13:36.886582: Isomap START
> test_pipeop_isomap.R: 2026-08-20 05:13:36.887673: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:36.897107: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:36.912595: Classical Scaling
> test_pipeop_isomap.R: 2026-08-20 05:13:36.94182: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-20 05:13:36.942936: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:36.960195: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:36.997321: embedding
> test_pipeop_isomap.R: 2026-08-20 05:13:36.999189: DONE
> test_pipeop_isomap.R: 2026-08-20 05:13:37.02561: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-20 05:13:37.026641: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:37.135933: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:37.173829: embedding
> test_pipeop_isomap.R: 2026-08-20 05:13:37.175705: DONE
> test_pipeop_isomap.R: 2026-08-20 05:13:37.252443: Isomap START
> test_pipeop_isomap.R: 2026-08-20 05:13:37.253604: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:37.271695: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:37.350833: Classical Scaling
> test_pipeop_isomap.R: 2026-08-20 05:13:37.383526: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-20 05:13:37.384692: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:37.42175: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:37.580868: embedding
> test_pipeop_isomap.R: 2026-08-20 05:13:37.584062: DONE
> test_pipeop_isomap.R: 2026-08-20 05:13:37.713754: Isomap START
> test_pipeop_isomap.R: 2026-08-20 05:13:37.714767: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:37.723582: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:37.738582: Classical Scaling
> test_pipeop_isomap.R: 2026-08-20 05:13:37.767096: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-20 05:13:37.768207: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:37.792903: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:37.83208: embedding
> test_pipeop_isomap.R: 2026-08-20 05:13:37.833927: DONE
> test_pipeop_isomap.R: 2026-08-20 05:13:37.985139: Isomap START
> test_pipeop_isomap.R: 2026-08-20 05:13:37.986243: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:37.995944: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:38.011022: Classical Scaling
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-20 05:13:38.058833: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-20 05:13:38.060139: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:38.088569: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:38.119499: embedding
> test_pipeop_isomap.R: 2026-08-20 05:13:38.121108: DONE
> test_pipeop_isomap.R: 2026-08-20 05:13:38.205386: Isomap START
> test_pipeop_isomap.R: 2026-08-20 05:13:38.20647: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:38.216933: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:38.231057: Classical Scaling
> test_pipeop_isomap.R: 2026-08-20 05:13:38.266584: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-20 05:13:38.267548: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:38.278611: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:38.303813: embedding
> test_pipeop_isomap.R: 2026-08-20 05:13:38.304932: DONE
> test_pipeop_isomap.R: 2026-08-20 05:13:38.371092: Isomap START
> test_pipeop_isomap.R: 2026-08-20 05:13:38.372206: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:38.39604: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:38.414277: Classical Scaling
> test_pipeop_isomap.R: 2026-08-20 05:13:38.472781: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-20 05:13:38.473901: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:38.495221: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:38.544164: embedding
> test_pipeop_isomap.R: 2026-08-20 05:13:38.546602: DONE
> test_pipeop_isomap.R: 2026-08-20 05:13:38.630174: Isomap START
> test_pipeop_isomap.R: 2026-08-20 05:13:38.631294: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:38.643247: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:38.660577: Classical Scaling
> test_pipeop_isomap.R: 2026-08-20 05:13:38.72074: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-20 05:13:38.721921: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:38.750691: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:38.7933: embedding
> test_pipeop_isomap.R: 2026-08-20 05:13:38.795581: DONE
> test_pipeop_isomap.R: 2026-08-20 05:13:38.907495: Isomap START
> test_pipeop_isomap.R: 2026-08-20 05:13:38.90873: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:38.919808: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:38.938416: Classical Scaling
> test_pipeop_isomap.R: 2026-08-20 05:13:39.036211: Isomap START
> test_pipeop_isomap.R: 2026-08-20 05:13:39.037522: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:39.05015: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:39.069156: Classical Scaling
> test_pipeop_isomap.R: 2026-08-20 05:13:39.09026: Isomap START
> test_pipeop_isomap.R: 2026-08-20 05:13:39.091266: constructing knn graph
> test_pipeop_isomap.R: 2026-08-20 05:13:39.109421: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-20 05:13:39.125476: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> 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
> test_pipeop_nmf.R: [PipeOpNMFstate]
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_meta.R:39:3',
'test_dictionary.R:7:3', '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_classweights.R:10:3',
'test_pipeop_boxcox.R:7:3', '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_featureunion.R:9:3',
'test_pipeop_featureunion.R:134:3', 'test_pipeop_ica.R:7:3',
'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_multiplicityimply.R:9:3', 'test_pipeop_nearmiss.R:7:3',
'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_task_preproc.R:4:3', 'test_pipeop_task_preproc.R:14:3',
'test_pipeop_nmf.R:6:3', '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_typecheck.R:188:3', 'test_ppl.R:63:3'
• 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
Flavor: r-release-windows-x86_64
Version: 0.11.0
Check: tests
Result: ERROR
Running 'testthat.R' [152s]
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: 2026-08-19 13:05:05.137801: Isomap START
> test_pipeop_isomap.R: 2026-08-19 13:05:05.138426: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:05.151119: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:05.165579: Classical Scaling
> test_pipeop_isomap.R: 2026-08-19 13:05:05.241458: Isomap START
> test_pipeop_isomap.R: 2026-08-19 13:05:05.242043: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:05.257331: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:05.27887: Classical Scaling
> test_pipeop_isomap.R: 2026-08-19 13:05:05.318869: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-19 13:05:05.319549: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:05.340324: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:05.379871: embedding
> test_pipeop_isomap.R: 2026-08-19 13:05:05.381318: DONE
> test_pipeop_isomap.R: 2026-08-19 13:05:05.41251: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-19 13:05:05.412987: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:05.433497: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:05.473356: embedding
> test_pipeop_isomap.R: 2026-08-19 13:05:05.474808: DONE
> test_pipeop_isomap.R: 2026-08-19 13:05:05.569246: Isomap START
> test_pipeop_isomap.R: 2026-08-19 13:05:05.569716: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:05.592092: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:05.686589: Classical Scaling
> test_pipeop_isomap.R: 2026-08-19 13:05:05.740867: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-19 13:05:05.741553: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:05.776828: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-19 13:05:05.937179: embedding
> test_pipeop_isomap.R: 2026-08-19 13:05:05.940799: DONE
> test_pipeop_isomap.R: 2026-08-19 13:05:06.07732: Isomap START
> test_pipeop_isomap.R: 2026-08-19 13:05:06.077726: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:06.087207: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:06.101372: Classical Scaling
> test_pipeop_isomap.R: 2026-08-19 13:05:06.133609: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-19 13:05:06.134223: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:06.151239: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:06.184162: embedding
> test_pipeop_isomap.R: 2026-08-19 13:05:06.185456: DONE
> test_pipeop_isomap.R: 2026-08-19 13:05:06.339264: Isomap START
> test_pipeop_isomap.R: 2026-08-19 13:05:06.33969: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:06.350547: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:06.364747: Classical Scaling
> test_pipeop_isomap.R: 2026-08-19 13:05:06.411129: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-19 13:05:06.411744: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:06.429146: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:06.462658: embedding
> test_pipeop_isomap.R: 2026-08-19 13:05:06.463741: DONE
> test_pipeop_isomap.R: 2026-08-19 13:05:06.540311: Isomap START
> test_pipeop_isomap.R: 2026-08-19 13:05:06.540722: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:06.551789: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:06.565835: Classical Scaling
> test_pipeop_isomap.R: 2026-08-19 13:05:06.612119: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-19 13:05:06.612701: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:06.62844: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:06.673932: embedding
> test_pipeop_isomap.R: 2026-08-19 13:05:06.675407: DONE
> test_pipeop_isomap.R: 2026-08-19 13:05:06.760818: Isomap START
> test_pipeop_isomap.R: 2026-08-19 13:05:06.761222: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:06.772494: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:06.786898: Classical Scaling
> test_pipeop_isomap.R: 2026-08-19 13:05:06.834352: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-19 13:05:06.834946: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:06.863312: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:06.896667: embedding
> test_pipeop_isomap.R: 2026-08-19 13:05:06.89778: DONE
> test_pipeop_isomap.R: 2026-08-19 13:05:06.971235: Isomap START
> test_pipeop_isomap.R: 2026-08-19 13:05:06.971648: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:06.98111: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:06.995358: Classical Scaling
> test_pipeop_isomap.R: 2026-08-19 13:05:07.04655: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-19 13:05:07.047169: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:07.06489: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:07.098277: embedding
> test_pipeop_isomap.R: 2026-08-19 13:05:07.099343: DONE
> test_pipeop_isomap.R: 2026-08-19 13:05:07.183564: Isomap START
> test_pipeop_isomap.R: 2026-08-19 13:05:07.183983: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:07.194407: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:07.208584: Classical Scaling
> test_pipeop_isomap.R: 2026-08-19 13:05:07.282692: Isomap START
> test_pipeop_isomap.R: 2026-08-19 13:05:07.283121: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:07.292156: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:07.306298: Classical Scaling
> test_pipeop_isomap.R: 2026-08-19 13:05:07.328769: Isomap START
> test_pipeop_isomap.R: 2026-08-19 13:05:07.329182: constructing knn graph
> test_pipeop_isomap.R: 2026-08-19 13:05:07.337767: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-19 13:05:07.35169: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> 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_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
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_dictionary.R:7:3',
'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_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_encodeimpact.R:11:3',
'test_pipeop_datefeatures.R:10:3', '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_kernelpca.R:9:3', 'test_pipeop_isomap.R:10:3',
'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_multiplicityimply.R:9:3',
'test_pipeop_nearmiss.R:7:3', '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_typecheck.R:188:3',
'test_ppl.R:63:3'
• 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
Flavor: r-oldrel-windows-x86_64