Last updated on 2026-08-09 20:50:24 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.11.0 | 38.04 | 651.88 | 689.92 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.11.0 | 23.77 | 422.08 | 445.85 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.11.0 | 25.00 | 408.83 | 433.83 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 0.11.0 | 25.00 | 422.94 | 447.94 | ERROR | |
| r-devel-windows-x86_64 | 0.11.0 | 37.00 | 443.00 | 480.00 | ERROR | |
| r-patched-linux-x86_64 | 0.11.0 | 54.19 | 617.16 | 671.35 | ERROR | |
| r-release-linux-x86_64 | 0.11.0 | 35.00 | 627.02 | 662.02 | 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 | 40.00 | 490.00 | 530.00 | ERROR | |
| r-oldrel-macos-arm64 | 0.11.0 | 8.00 | 113.00 | 121.00 | OK | |
| r-oldrel-macos-x86_64 | 0.11.0 | 28.00 | 883.00 | 911.00 | OK | |
| r-oldrel-windows-x86_64 | 0.11.0 | 55.00 | 619.00 | 674.00 | 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 4.647 0.097 7.71
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [374s/196s]
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: 2026-08-07 06:58:37.206005: Isomap START
> test_pipeop_isomap.R: 2026-08-07 06:58:37.206802: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:37.219285: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:37.237223: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 06:58:37.292957: Isomap START
> test_pipeop_isomap.R: 2026-08-07 06:58:37.293466: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:37.306105: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:37.324475: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 06:58:37.353322: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 06:58:37.35404: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:37.371592: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:37.412736: embedding
> test_pipeop_isomap.R: 2026-08-07 06:58:37.413867: DONE
> test_pipeop_isomap.R: 2026-08-07 06:58:37.440544: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 06:58:37.441037: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:37.485027: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:37.526613: embedding
> test_pipeop_isomap.R: 2026-08-07 06:58:37.527848: DONE
> test_pipeop_isomap.R: 2026-08-07 06:58:37.623679: Isomap START
> test_pipeop_isomap.R: 2026-08-07 06:58:37.624207: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:37.641046: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:37.739123: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 06:58:37.778576: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 06:58:37.77928: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:37.809798: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:38.008321: embedding
> test_pipeop_isomap.R: 2026-08-07 06:58:38.010964: DONE
> test_pipeop_isomap.R: 2026-08-07 06:58:38.166037: Isomap START
> test_pipeop_isomap.R: 2026-08-07 06:58:38.166522: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:38.176932: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:38.195091: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 06:58:38.243497: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 06:58:38.245865: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:38.263041: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:38.305199: embedding
> test_pipeop_isomap.R: 2026-08-07 06:58:38.306439: DONE
> test_pipeop_isomap.R: 2026-08-07 06:58:38.455699: Isomap START
> test_pipeop_isomap.R: 2026-08-07 06:58:38.456188: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:38.466627: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:38.48693: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 06:58:38.538257: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 06:58:38.538974: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:38.55591: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:38.597356: embedding
> test_pipeop_isomap.R: 2026-08-07 06:58:38.598563: DONE
> test_pipeop_isomap.R: 2026-08-07 06:58:38.685193: Isomap START
> test_pipeop_isomap.R: 2026-08-07 06:58:38.685675: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:38.696505: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:38.715618: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 06:58:38.77025: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 06:58:38.77099: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:38.790547: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:38.832859: embedding
> test_pipeop_isomap.R: 2026-08-07 06:58:38.834266: DONE
> test_pipeop_isomap.R: 2026-08-07 06:58:38.942789: Isomap START
> test_pipeop_isomap.R: 2026-08-07 06:58:38.943279: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:38.953775: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:38.975296: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 06:58:39.02803: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 06:58:39.028733: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:39.046276: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:39.088859: embedding
> test_pipeop_isomap.R: 2026-08-07 06:58:39.090147: DONE
> test_pipeop_isomap.R: 2026-08-07 06:58:39.182996: Isomap START
> test_pipeop_isomap.R: 2026-08-07 06:58:39.183481: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:39.193711: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:39.211655: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 06:58:39.26389: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 06:58:39.264618: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:39.281581: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:39.325102: embedding
> test_pipeop_isomap.R: 2026-08-07 06:58:39.32637: DONE
> test_pipeop_isomap.R: 2026-08-07 06:58:39.426241: Isomap START
> test_pipeop_isomap.R: 2026-08-07 06:58:39.42676: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:39.437707: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:39.456608: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 06:58:39.555551: Isomap START
> test_pipeop_isomap.R: 2026-08-07 06:58:39.556055: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:39.566951: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:39.585819: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 06:58:39.624339: Isomap START
> test_pipeop_isomap.R: 2026-08-07 06:58:39.624824: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 06:58:39.637055: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 06:58:39.656487: 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:
> 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_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_boxcox.R:7:3',
'test_pipeop_classweights.R:10:3', 'test_pipeop_classweightsex.R:9:3',
'test_pipeop_colapply.R:9:3', 'test_pipeop_collapsefactors.R:6:3',
'test_pipeop_copy.R:5:3', 'test_pipeop_colroles.R:6:3',
'test_pipeop_decode.R:14:3', 'test_pipeop_encode.R:21:3',
'test_pipeop_datefeatures.R:10:3', 'test_pipeop_encodeimpact.R:11:3',
'test_pipeop_encodepl.R:5:3', 'test_pipeop_encodepl.R:72:3',
'test_pipeop_encodelmer.R:15:3', 'test_pipeop_encodelmer.R:37:3',
'test_pipeop_encodelmer.R:80:3', '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_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-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’ [242s/125s]
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: 2026-08-08 18:21:28.330685: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:21:28.331367: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:28.342623: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:28.356661: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:21:28.398876: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:21:28.399325: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:28.408087: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:28.421694: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:21:28.443108: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:21:28.443695: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:28.460299: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:28.492514: embedding
> test_pipeop_isomap.R: 2026-08-08 18:21:28.493438: DONE
> test_pipeop_isomap.R: 2026-08-08 18:21:28.512375: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:21:28.51282: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:28.53543: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:28.568034: embedding
> test_pipeop_isomap.R: 2026-08-08 18:21:28.569111: DONE
> test_pipeop_isomap.R: 2026-08-08 18:21:28.63626: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:21:28.636712: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:28.651729: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:28.728328: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:21:28.757124: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:21:28.757757: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:28.792316: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:28.962269: embedding
> test_pipeop_isomap.R: 2026-08-08 18:21:28.964636: DONE
> test_pipeop_isomap.R: 2026-08-08 18:21:29.154449: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:21:29.154899: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:29.165382: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:29.179194: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:21:29.205343: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:21:29.205978: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:29.220573: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:29.25261: embedding
> test_pipeop_isomap.R: 2026-08-08 18:21:29.253603: DONE
> test_pipeop_isomap.R: 2026-08-08 18:21:29.358137: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:21:29.358557: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:29.367226: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:29.380974: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:21:29.41957: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:21:29.420171: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:29.44731: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:29.482213: embedding
> test_pipeop_isomap.R: 2026-08-08 18:21:29.483396: DONE
> test_pipeop_isomap.R: 2026-08-08 18:21:29.550031: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:21:29.550455: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:29.559654: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:29.57318: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:21:29.612788: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:21:29.613398: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:29.627964: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:29.660175: embedding
> test_pipeop_isomap.R: 2026-08-08 18:21:29.66266: DONE
> test_pipeop_isomap.R: 2026-08-08 18:21:29.727478: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:21:29.727908: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:29.736952: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:29.750523: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:21:29.807783: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:21:29.808424: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:29.822167: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:29.854197: embedding
> test_pipeop_isomap.R: 2026-08-08 18:21:29.855167: DONE
> test_pipeop_isomap.R: 2026-08-08 18:21:29.913549: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:21:29.913975: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:29.922774: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:29.936542: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:21:29.974703: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:21:29.975312: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:29.990303: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:30.022065: embedding
> test_pipeop_isomap.R: 2026-08-08 18:21:30.023025: DONE
> test_pipeop_isomap.R: 2026-08-08 18:21:30.106253: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:21:30.106745: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:30.115513: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:30.129179: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:21:30.196259: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:21:30.196674: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:30.205173: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:30.219953: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:21:30.238335: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:21:30.238742: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:21:30.246164: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:21:30.259402: 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:
> 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_classweights.R:10:3',
'test_pipeop_boxcox.R:7:3', '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_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 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")
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-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, 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’ [240s/120s]
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]
> test_pipeop_blsmote.R: "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: 2026-08-09 09:55:16.570564: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:55:16.571424: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:16.58459: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:16.598882: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:55:16.636506: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:55:16.63691: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:16.644532: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:16.65812: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:55:16.678377: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:55:16.678968: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:16.692722: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:16.724627: embedding
> test_pipeop_isomap.R: 2026-08-09 09:55:16.725606: DONE
> test_pipeop_isomap.R: 2026-08-09 09:55:16.745158: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:55:16.74559: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:16.758116: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:16.789881: embedding
> test_pipeop_isomap.R: 2026-08-09 09:55:16.790804: DONE
> test_pipeop_isomap.R: 2026-08-09 09:55:16.85256: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:55:16.852959: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:16.868924: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:16.969174: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:55:16.996137: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:55:16.9967: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:17.019916: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:17.173326: embedding
> test_pipeop_isomap.R: 2026-08-09 09:55:17.176476: DONE
> test_pipeop_isomap.R: 2026-08-09 09:55:17.276089: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:55:17.276489: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:17.284122: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:17.297624: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:55:17.320067: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:55:17.320609: constructing knn graph
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-09 09:55:17.341716: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:17.373783: embedding
> test_pipeop_isomap.R: 2026-08-09 09:55:17.37478: DONE
> test_pipeop_isomap.R: 2026-08-09 09:55:17.470484: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:55:17.47084: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:17.478673: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:17.492161: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:55:17.5271: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:55:17.527646: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:17.540507: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:17.57226: embedding
> test_pipeop_isomap.R: 2026-08-09 09:55:17.573186: DONE
> test_pipeop_isomap.R: 2026-08-09 09:55:17.627215: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:55:17.627576: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:17.635381: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:17.649987: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:55:17.685031: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:55:17.685573: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:17.698728: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:17.730509: embedding
> test_pipeop_isomap.R: 2026-08-09 09:55:17.739423: DONE
> test_pipeop_isomap.R: 2026-08-09 09:55:17.795329: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:55:17.7957: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:17.803356: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:17.816728: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:55:17.851058: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:55:17.851584: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:17.864285: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:17.905745: embedding
> test_pipeop_isomap.R: 2026-08-09 09:55:17.908339: DONE
> test_pipeop_isomap.R: 2026-08-09 09:55:17.975939: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:55:17.976337: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:17.986641: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:18.000393: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:55:18.03986: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:55:18.040455: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:18.056027: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:18.088042: embedding
> test_pipeop_isomap.R: 2026-08-09 09:55:18.089216: DONE
> test_pipeop_isomap.R: 2026-08-09 09:55:18.173176: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:55:18.173568: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:18.182631: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:18.196132: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:55:18.259976: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:55:18.260342: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:18.268664: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:18.282237: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:55:18.300828: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:55:18.301212: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:55:18.308905: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:55:18.322383: 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_classweights.R:10:3',
'test_pipeop_boxcox.R:7:3', '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_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-fedora-clang
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [250s/119s]
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:
> test_multiplicities.R: [[1]]
> 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: 2026-08-09 09:40:25.773447: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:40:25.774121: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:25.786173: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:25.801509: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:40:25.837263: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:40:25.837668: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:25.845506: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:25.859584: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:40:25.878703: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:40:25.879283: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:25.893259: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:25.925881: embedding
> test_pipeop_isomap.R: 2026-08-09 09:40:25.926893: DONE
> test_pipeop_isomap.R: 2026-08-09 09:40:25.946051: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:40:25.946469: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:25.959825: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:25.992791: embedding
> test_pipeop_isomap.R: 2026-08-09 09:40:25.993825: DONE
> test_pipeop_isomap.R: 2026-08-09 09:40:26.064149: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:40:26.064619: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:26.079746: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:26.157016: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:40:26.184199: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:40:26.184782: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:26.212498: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:26.371313: embedding
> test_pipeop_isomap.R: 2026-08-09 09:40:26.383154: DONE
> test_pipeop_isomap.R: 2026-08-09 09:40:26.491148: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:40:26.491547: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:26.499796: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-09 09:40:26.513861: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:40:26.536997: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:40:26.537559: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:26.551482: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:26.584208: embedding
> test_pipeop_isomap.R: 2026-08-09 09:40:26.585198: DONE
> test_pipeop_isomap.R: 2026-08-09 09:40:26.685666: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:40:26.686046: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:26.704236: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:26.718846: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:40:26.75813: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:40:26.758714: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:26.772566: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:26.805989: embedding
> test_pipeop_isomap.R: 2026-08-09 09:40:26.806993: DONE
> test_pipeop_isomap.R: 2026-08-09 09:40:26.866137: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:40:26.866538: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:26.874877: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:26.889315: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:40:26.925031: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:40:26.925608: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:26.948858: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:26.982294: embedding
> test_pipeop_isomap.R: 2026-08-09 09:40:26.983417: DONE
> test_pipeop_isomap.R: 2026-08-09 09:40:27.046173: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:40:27.04656: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:27.054841: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:27.069448: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:40:27.105061: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:40:27.105622: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:27.119696: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:27.152599: embedding
> test_pipeop_isomap.R: 2026-08-09 09:40:27.20929: DONE
> test_pipeop_isomap.R: 2026-08-09 09:40:27.275684: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:40:27.276078: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:27.284559: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:27.299074: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:40:27.335229: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-09 09:40:27.335799: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:27.349924: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:27.382927: embedding
> test_pipeop_isomap.R: 2026-08-09 09:40:27.383932: DONE
> test_pipeop_isomap.R: 2026-08-09 09:40:27.442955: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:40:27.44331: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:27.45126: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:27.465904: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:40:27.522739: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:40:27.523134: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:27.532071: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:27.546083: Classical Scaling
> test_pipeop_isomap.R: 2026-08-09 09:40:27.576634: Isomap START
> test_pipeop_isomap.R: 2026-08-09 09:40:27.577056: constructing knn graph
> test_pipeop_isomap.R: 2026-08-09 09:40:27.585836: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-09 09:40:27.600684: 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_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_boxcox.R:7:3', '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_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_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_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-fedora-gcc
Version: 0.11.0
Check: tests
Result: ERROR
Running 'testthat.R' [161s]
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:
> 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:
> 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: 2026-08-04 18:28:37.829258: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:28:37.831185: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:37.850849: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:37.874539: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:28:38.042103: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:28:38.043596: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:38.054645: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:38.074072: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:28:38.106069: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:28:38.10755: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:38.126609: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:38.167739: embedding
> test_pipeop_isomap.R: 2026-08-04 18:28:38.169316: DONE
> test_pipeop_isomap.R: 2026-08-04 18:28:38.195551: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:28:38.196509: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:38.224091: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:38.268564: embedding
> test_pipeop_isomap.R: 2026-08-04 18:28:38.270582: DONE
> test_pipeop_isomap.R: 2026-08-04 18:28:38.367164: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:28:38.368407: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:38.387826: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:38.471345: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:28:38.518746: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:28:38.520086: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:38.551291: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-04 18:28:39.22724: embedding
> test_pipeop_isomap.R: 2026-08-04 18:28:39.231598: DONE
> test_pipeop_isomap.R: 2026-08-04 18:28:39.384191: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:28:39.385101: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:39.393002: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:39.406509: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:28:39.442399: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:28:39.444009: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:39.462306: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:39.503995: embedding
> test_pipeop_isomap.R: 2026-08-04 18:28:39.505769: DONE
> test_pipeop_isomap.R: 2026-08-04 18:28:39.682581: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:28:39.684: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:39.69947: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:39.722241: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:28:39.785046: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:28:39.786581: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:39.811638: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:39.861073: embedding
> test_pipeop_isomap.R: 2026-08-04 18:28:39.862893: DONE
> test_pipeop_isomap.R: 2026-08-04 18:28:39.963397: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:28:39.964715: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:39.997607: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:40.014609: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:28:40.072896: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:28:40.074418: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:40.094362: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:40.13032: embedding
> test_pipeop_isomap.R: 2026-08-04 18:28:40.131832: DONE
> test_pipeop_isomap.R: 2026-08-04 18:28:40.209183: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:28:40.210116: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:40.220521: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:40.23909: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:28:40.296345: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:28:40.297753: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:40.317286: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:40.358061: embedding
> test_pipeop_isomap.R: 2026-08-04 18:28:40.360313: DONE
> test_pipeop_isomap.R: 2026-08-04 18:28:40.447556: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:28:40.448749: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:40.462783: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:40.48203: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:28:40.54018: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:28:40.541582: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:40.573299: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:40.612706: embedding
> test_pipeop_isomap.R: 2026-08-04 18:28:40.614641: DONE
> test_pipeop_isomap.R: 2026-08-04 18:28:40.720404: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:28:40.721685: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:40.733861: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:40.75698: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:28:40.864213: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:28:40.865571: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:40.880006: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:40.902174: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:28:40.932208: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:28:40.933586: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:28:40.948182: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:28:40.970582: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> test_pipeop_nmf.R: [PipeOpNMFstate]
> test_pipeop_nmf.R: [PipeOpNMFstate]
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
Saving _problems/test_pipeop_unbranch-21.R
Saving _problems/test_pipeop_tunethreshold-36.R
Saving _problems/test_pipeop_tunethreshold-73.R
Saving _problems/test_selector-6.R
[ FAIL 12 | WARN 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_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_datefeatures.R:10:3',
'test_pipeop_encode.R:21:3', '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_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_nmf.R:6:3',
'test_pipeop_targettrafo.R:4:3', 'test_pipeop_targetmutate.R:5:3',
'test_pipeop_targettrafoscalerange.R:5:3', 'test_pipeop_task_preproc.R:4:3',
'test_pipeop_task_preproc.R:14:3', 'test_pipeop_tomek.R:7:3',
'test_pipeop_textvectorizer.R:37:3', 'test_pipeop_textvectorizer.R:186:3',
'test_pipeop_unbranch.R:10:3', 'test_pipeop_updatetarget.R:89:3',
'test_pipeop_vtreat.R:9:3', 'test_pipeop_yeojohnson.R:7:3',
'test_pipeop_tunethreshold.R:111:3', 'test_pipeop_tunethreshold.R:191:3',
'test_ppl.R:63:3', 'test_typecheck.R:188:3'
• Skipping (1): 'test_GraphLearner.R:1278:3'
• empty test (2): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_mlr_graphs_robustify.R:106:3'): Robustify Pipeline Impute Missings ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_mlr_graphs_robustify.R:106:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classbalancing.R:13:3'): PipeOpClassBalancing ───────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classbalancing.R:13:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:17:3'): PipeOpClassWeights ───────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classweights.R:17:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:36:5'): PipeOpClassWeights - weight roles assigned ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_classweights.R:36:5
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:7:3'): PipeOpImputeLearner - simple tests ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:7:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:138:3'): PipeOpImputeLearner - model active binding to state ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:138:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_impute.R:452:3'): impute, test rows and affect_columns ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_impute.R:452:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_missind.R:4:3'): PipeOpMissInd ──────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_missind.R:4:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_unbranch.R:21:3'): PipeOpUnbranch - train and predict ───
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_unbranch.R:21:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:36:3'): threshold works for binary ──────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_tunethreshold.R:36:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:73:3'): tunethreshold graph works ───────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─graph$train(tsk("pima")) at test_pipeop_tunethreshold.R:73:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. └─mlr3::tsk("pima")
5. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
6. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_selector.R:6:3'): Selectors work ───────────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::mlr_tasks$get("pima") at test_selector.R:6:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
[ FAIL 12 | WARN 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 4.382 0.110 5.254
mlr_pipeops 3.431 0.068 5.019
Flavor: r-patched-linux-x86_64
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [346s/176s]
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
> test_pipeop_isomap.R: 2026-08-05 18:18:57.861743: Isomap START
> test_pipeop_isomap.R: 2026-08-05 18:18:57.862499: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:57.87585: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:57.894586: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 18:18:57.953246: Isomap START
> test_pipeop_isomap.R: 2026-08-05 18:18:57.953741: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:57.981537: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:58.000085: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 18:18:58.027669: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 18:18:58.02837: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:58.048602: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:58.090126: embedding
> test_pipeop_isomap.R: 2026-08-05 18:18:58.091318: DONE
> test_pipeop_isomap.R: 2026-08-05 18:18:58.1196: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 18:18:58.120171: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:58.137057: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:58.179677: embedding
> test_pipeop_isomap.R: 2026-08-05 18:18:58.18089: DONE
> test_pipeop_isomap.R: 2026-08-05 18:18:58.271232: Isomap START
> test_pipeop_isomap.R: 2026-08-05 18:18:58.271722: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:58.361235: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:58.461574: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 18:18:58.499517: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 18:18:58.50025: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:58.532578: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-05 18:18:58.736329: embedding
> test_pipeop_isomap.R: 2026-08-05 18:18:58.748259: DONE
> test_pipeop_isomap.R: 2026-08-05 18:18:58.923763: Isomap START
> test_pipeop_isomap.R: 2026-08-05 18:18:58.924407: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:58.939404: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:58.961984: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 18:18:59.002456: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 18:18:59.003211: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:59.023561: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:59.063345: embedding
> test_pipeop_isomap.R: 2026-08-05 18:18:59.06471: DONE
> test_pipeop_isomap.R: 2026-08-05 18:18:59.246534: Isomap START
> test_pipeop_isomap.R: 2026-08-05 18:18:59.247037: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:59.259717: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:59.277953: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 18:18:59.333739: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 18:18:59.33448: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:59.351677: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:59.393746: embedding
> test_pipeop_isomap.R: 2026-08-05 18:18:59.394912: DONE
> test_pipeop_isomap.R: 2026-08-05 18:18:59.479637: Isomap START
> test_pipeop_isomap.R: 2026-08-05 18:18:59.480133: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:59.504148: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:59.522874: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 18:18:59.573182: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 18:18:59.573908: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:59.593009: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:59.634995: embedding
> test_pipeop_isomap.R: 2026-08-05 18:18:59.636209: DONE
> test_pipeop_isomap.R: 2026-08-05 18:18:59.720287: Isomap START
> test_pipeop_isomap.R: 2026-08-05 18:18:59.72079: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:59.731328: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:59.760046: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 18:18:59.812767: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 18:18:59.813431: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:59.830032: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:59.876294: embedding
> test_pipeop_isomap.R: 2026-08-05 18:18:59.877551: DONE
> test_pipeop_isomap.R: 2026-08-05 18:18:59.962277: Isomap START
> test_pipeop_isomap.R: 2026-08-05 18:18:59.962777: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:18:59.975434: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:18:59.993855: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 18:19:00.061752: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 18:19:00.06251: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:19:00.081522: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:19:00.123604: embedding
> test_pipeop_isomap.R: 2026-08-05 18:19:00.124903: DONE
> test_pipeop_isomap.R: 2026-08-05 18:19:00.221359: Isomap START
> test_pipeop_isomap.R: 2026-08-05 18:19:00.221861: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:19:00.233001: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:19:00.251661: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 18:19:00.345017: Isomap START
> test_pipeop_isomap.R: 2026-08-05 18:19:00.3455: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:19:00.356132: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:19:00.374352: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 18:19:00.402005: Isomap START
> test_pipeop_isomap.R: 2026-08-05 18:19:00.402539: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 18:19:00.425136: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 18:19:00.443877: 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_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_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_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 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 4.677 0.151 8.443
mlr_pipeops 3.578 0.035 6.323
mlr_pipeops_boxcox 2.782 0.105 5.749
Flavor: r-release-linux-x86_64
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [352s/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:
> 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: 2026-08-08 18:23:33.679: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:23:33.679752: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:33.692188: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:33.710668: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:23:33.7743: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:23:33.776241: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:33.785751: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:33.803612: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:23:33.831568: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:23:33.832299: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:33.853497: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:33.900823: embedding
> test_pipeop_isomap.R: 2026-08-08 18:23:33.901951: DONE
> test_pipeop_isomap.R: 2026-08-08 18:23:33.930034: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:23:33.93052: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:33.950763: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:33.994426: embedding
> test_pipeop_isomap.R: 2026-08-08 18:23:33.995834: DONE
> test_pipeop_isomap.R: 2026-08-08 18:23:34.093207: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:23:34.093707: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:34.124245: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:34.225601: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:23:34.264139: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:23:34.264859: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:34.298781: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:34.495774: embedding
> test_pipeop_isomap.R: 2026-08-08 18:23:34.498645: DONE
> test_pipeop_isomap.R: 2026-08-08 18:23:34.652294: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:23:34.652787: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:34.663633: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:34.682494: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:23:34.718468: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:23:34.727666: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:34.745953: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:34.78889: embedding
> test_pipeop_isomap.R: 2026-08-08 18:23:34.790129: DONE
> test_pipeop_isomap.R: 2026-08-08 18:23:34.938626: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:23:34.939115: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:34.952905: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:34.971982: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:23:35.028751: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:23:35.029506: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:35.048395: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:35.092825: embedding
> test_pipeop_isomap.R: 2026-08-08 18:23:35.094095: DONE
> test_pipeop_isomap.R: 2026-08-08 18:23:35.18697: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:23:35.187446: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:35.199338: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:35.217705: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:23:35.790777: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:23:35.791488: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:35.809438: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:35.852309: embedding
> test_pipeop_isomap.R: 2026-08-08 18:23:35.853578: DONE
> test_pipeop_isomap.R: 2026-08-08 18:23:35.938436: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:23:35.938972: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:35.951651: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:35.970338: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:23:36.022243: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:23:36.022969: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:36.040765: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:36.083248: embedding
> test_pipeop_isomap.R: 2026-08-08 18:23:36.086114: DONE
> test_pipeop_isomap.R: 2026-08-08 18:23:36.170916: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:23:36.171391: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:36.181844: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:36.202967: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:23:36.256508: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-08 18:23:36.257225: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:36.278961: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:36.320365: embedding
> test_pipeop_isomap.R: 2026-08-08 18:23:36.32314: DONE
> test_pipeop_isomap.R: 2026-08-08 18:23:36.421569: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:23:36.422059: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:36.435098: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:36.454166: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:23:36.557507: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:23:36.558045: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:36.570941: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:36.591635: Classical Scaling
> test_pipeop_isomap.R: 2026-08-08 18:23:36.622702: Isomap START
> test_pipeop_isomap.R: 2026-08-08 18:23:36.623243: constructing knn graph
> test_pipeop_isomap.R: 2026-08-08 18:23:36.636033: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-08 18:23:36.65654: 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_modelmatrix.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_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_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 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' [165s]
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:
> test_multiplicities.R: [[1]]
> 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: 2026-08-07 16:11:14.351975: Isomap START
> test_pipeop_isomap.R: 2026-08-07 16:11:14.35376: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:14.371758: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:14.394355: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 16:11:14.463422: Isomap START
> test_pipeop_isomap.R: 2026-08-07 16:11:14.465062: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:14.478191: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:14.49845: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 16:11:14.531898: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 16:11:14.53303: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:14.554196: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:14.596158: embedding
> test_pipeop_isomap.R: 2026-08-07 16:11:14.598329: DONE
> test_pipeop_isomap.R: 2026-08-07 16:11:14.638696: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 16:11:14.640221: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:14.655065: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:14.68666: embedding
> test_pipeop_isomap.R: 2026-08-07 16:11:14.688389: DONE
> test_pipeop_isomap.R: 2026-08-07 16:11:14.756282: Isomap START
> test_pipeop_isomap.R: 2026-08-07 16:11:14.757147: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:14.787743: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:14.883399: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 16:11:14.91363: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 16:11:14.914753: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:14.943166: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:15.136428: embedding
> test_pipeop_isomap.R: 2026-08-07 16:11:15.140577: DONE
> test_pipeop_isomap.R: 2026-08-07 16:11:15.299195: Isomap START
> test_pipeop_isomap.R: 2026-08-07 16:11:15.308135: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:15.320822: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:15.336622: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 16:11:15.374553: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 16:11:15.375801: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:15.391153: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:15.426074: embedding
> test_pipeop_isomap.R: 2026-08-07 16:11:15.427841: DONE
> test_pipeop_isomap.R: 2026-08-07 16:11:15.555687: Isomap START
> test_pipeop_isomap.R: 2026-08-07 16:11:15.556519: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:15.571518: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:15.584084: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 16:11:15.634876: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 16:11:15.635798: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:15.651044: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-07 16:11:15.690837: embedding
> test_pipeop_isomap.R: 2026-08-07 16:11:15.69244: DONE
> test_pipeop_isomap.R: 2026-08-07 16:11:15.761949: Isomap START
> test_pipeop_isomap.R: 2026-08-07 16:11:15.762979: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:15.772851: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:15.790948: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 16:11:15.863667: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 16:11:15.865062: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:15.883115: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:15.923643: embedding
> test_pipeop_isomap.R: 2026-08-07 16:11:15.925243: DONE
> test_pipeop_isomap.R: 2026-08-07 16:11:16.013745: Isomap START
> test_pipeop_isomap.R: 2026-08-07 16:11:16.015002: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:16.027111: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:16.04653: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 16:11:16.110562: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 16:11:16.111654: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:16.124489: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:16.158305: embedding
> test_pipeop_isomap.R: 2026-08-07 16:11:16.16041: DONE
> test_pipeop_isomap.R: 2026-08-07 16:11:16.262219: Isomap START
> test_pipeop_isomap.R: 2026-08-07 16:11:16.263571: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:16.275913: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:16.292716: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 16:11:16.356818: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-07 16:11:16.358234: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:16.390912: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:16.436216: embedding
> test_pipeop_isomap.R: 2026-08-07 16:11:16.438139: DONE
> test_pipeop_isomap.R: 2026-08-07 16:11:16.535603: Isomap START
> test_pipeop_isomap.R: 2026-08-07 16:11:16.536924: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:16.548709: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:16.567747: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 16:11:16.657182: Isomap START
> test_pipeop_isomap.R: 2026-08-07 16:11:16.658429: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:16.679519: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:16.69777: Classical Scaling
> test_pipeop_isomap.R: 2026-08-07 16:11:16.728263: Isomap START
> test_pipeop_isomap.R: 2026-08-07 16:11:16.72946: constructing knn graph
> test_pipeop_isomap.R: 2026-08-07 16:11:16.739863: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-07 16:11:16.756515: 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_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
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_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_ica.R:7:3', 'test_pipeop_histbin.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_nearmiss.R:7:3', 'test_pipeop_multiplicityimply.R:9:3',
'test_pipeop_ovr.R:9:3', 'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3',
'test_pipeop_proxy.R:2:1', 'test_pipeop_quantilebin.R:5:3',
'test_pipeop_randomprojection.R:6:3', 'test_pipeop_randomresponse.R:5:3',
'test_pipeop_removeconstants.R:6:3', 'test_pipeop_renamecolumns.R:6:3',
'test_pipeop_replicate.R:9:3', 'test_pipeop_rowapply.R:6:3',
'test_pipeop_scale.R:6:3', 'test_pipeop_scale.R:10:3',
'test_pipeop_scalemaxabs.R:6:3', 'test_pipeop_scalerange.R:7:3',
'test_pipeop_select.R:9:3', 'test_pipeop_smote.R:10:3',
'test_pipeop_smotenc.R:8:3', 'test_pipeop_spatialsign.R:3:1',
'test_pipeop_splines.R:3:1', 'test_pipeop_subsample.R:6:3',
'test_pipeop_targetinvert.R:4:3', 'test_pipeop_targetmutate.R:5:3',
'test_pipeop_targettrafo.R:4:3', 'test_pipeop_targettrafoscalerange.R:5:3',
'test_pipeop_nmf.R:6:3', 'test_pipeop_task_preproc.R:4:3',
'test_pipeop_task_preproc.R:14:3', 'test_pipeop_tomek.R:7:3',
'test_pipeop_textvectorizer.R:37:3', 'test_pipeop_textvectorizer.R:186:3',
'test_pipeop_unbranch.R:10:3', 'test_pipeop_updatetarget.R:89:3',
'test_pipeop_vtreat.R:9:3', 'test_pipeop_yeojohnson.R:7:3',
'test_pipeop_tunethreshold.R:111:3', 'test_pipeop_tunethreshold.R:191:3',
'test_ppl.R:63:3', 'test_typecheck.R:188:3'
• Skipping (1): 'test_GraphLearner.R:1278:3'
• empty test (2): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_mlr_graphs_robustify.R:106:3'): Robustify Pipeline Impute Missings ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_mlr_graphs_robustify.R:106:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classbalancing.R:13:3'): PipeOpClassBalancing ───────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classbalancing.R:13:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:17:3'): PipeOpClassWeights ───────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classweights.R:17:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:36:5'): PipeOpClassWeights - weight roles assigned ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_classweights.R:36:5
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:7:3'): PipeOpImputeLearner - simple tests ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:7:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:138:3'): PipeOpImputeLearner - model active binding to state ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:138:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_impute.R:452:3'): impute, test rows and affect_columns ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_impute.R:452:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_missind.R:4:3'): PipeOpMissInd ──────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_missind.R:4:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_unbranch.R:21:3'): PipeOpUnbranch - train and predict ───
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_unbranch.R:21:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:36:3'): threshold works for binary ──────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_tunethreshold.R:36:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:73:3'): tunethreshold graph works ───────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─graph$train(tsk("pima")) at test_pipeop_tunethreshold.R:73:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. └─mlr3::tsk("pima")
5. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
6. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_selector.R:6:3'): Selectors work ───────────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::mlr_tasks$get("pima") at test_selector.R:6:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
[ FAIL 12 | WARN 12 | SKIP 128 | PASS 8462 ]
Error:
! Test failures.
Execution halted
Flavor: r-release-windows-x86_64
Version: 0.11.0
Check: tests
Result: ERROR
Running 'testthat.R' [242s]
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:
> 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:
> 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:
> test_multiplicities.R: [[1]]
> 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: 2026-08-05 19:15:38.385148: Isomap START
> test_pipeop_isomap.R: 2026-08-05 19:15:38.385969: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:38.403713: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:38.424978: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 19:15:38.508547: Isomap START
> test_pipeop_isomap.R: 2026-08-05 19:15:38.509375: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:38.528964: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:38.54564: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 19:15:38.588115: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 19:15:38.589017: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:38.617521: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:38.663235: embedding
> test_pipeop_isomap.R: 2026-08-05 19:15:38.665024: DONE
> test_pipeop_isomap.R: 2026-08-05 19:15:38.697531: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 19:15:38.698197: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:38.729454: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:38.79891: embedding
> test_pipeop_isomap.R: 2026-08-05 19:15:38.80167: DONE
> test_pipeop_isomap.R: 2026-08-05 19:15:38.933457: Isomap START
> test_pipeop_isomap.R: 2026-08-05 19:15:38.934192: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:38.960725: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-05 19:15:39.074509: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 19:15:39.136212: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 19:15:39.13723: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:39.190846: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:39.41596: embedding
> test_pipeop_isomap.R: 2026-08-05 19:15:39.430388: DONE
> test_pipeop_isomap.R: 2026-08-05 19:15:39.636637: Isomap START
> test_pipeop_isomap.R: 2026-08-05 19:15:39.637105: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:39.650053: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:39.672157: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 19:15:39.726629: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 19:15:39.727534: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:39.753361: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:39.802674: embedding
> test_pipeop_isomap.R: 2026-08-05 19:15:39.804208: DONE
> test_pipeop_isomap.R: 2026-08-05 19:15:40.01902: Isomap START
> test_pipeop_isomap.R: 2026-08-05 19:15:40.019684: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:40.052974: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:40.07506: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 19:15:40.155038: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 19:15:40.155985: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:40.179893: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:40.227915: embedding
> test_pipeop_isomap.R: 2026-08-05 19:15:40.229407: DONE
> test_pipeop_isomap.R: 2026-08-05 19:15:40.351131: Isomap START
> test_pipeop_isomap.R: 2026-08-05 19:15:40.351789: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:40.36627: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:40.38774: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 19:15:40.455145: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 19:15:40.455797: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:40.494092: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:40.538308: embedding
> test_pipeop_isomap.R: 2026-08-05 19:15:40.540143: DONE
> test_pipeop_isomap.R: 2026-08-05 19:15:40.659313: Isomap START
> test_pipeop_isomap.R: 2026-08-05 19:15:40.659875: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:40.669734: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:40.691316: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 19:15:40.771059: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 19:15:40.771926: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:40.795864: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:40.844367: embedding
> test_pipeop_isomap.R: 2026-08-05 19:15:40.846353: DONE
> test_pipeop_isomap.R: 2026-08-05 19:15:40.984189: Isomap START
> test_pipeop_isomap.R: 2026-08-05 19:15:40.984902: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:41.020843: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:41.042911: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 19:15:41.121515: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-05 19:15:41.122484: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:41.145747: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:41.195046: embedding
> test_pipeop_isomap.R: 2026-08-05 19:15:41.196965: DONE
> test_pipeop_isomap.R: 2026-08-05 19:15:41.3405: Isomap START
> test_pipeop_isomap.R: 2026-08-05 19:15:41.341165: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:41.354977: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:41.373096: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 19:15:41.488736: Isomap START
> test_pipeop_isomap.R: 2026-08-05 19:15:41.489354: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:41.518598: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:41.540243: Classical Scaling
> test_pipeop_isomap.R: 2026-08-05 19:15:41.578308: Isomap START
> test_pipeop_isomap.R: 2026-08-05 19:15:41.578947: constructing knn graph
> test_pipeop_isomap.R: 2026-08-05 19:15:41.592939: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-05 19:15:41.614578: 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_boxcox.R:7:3', '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_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_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-oldrel-windows-x86_64