Last updated on 2026-07-24 20:49:02 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.11.0 | 39.30 | 700.37 | 739.67 | NOTE | |
| r-devel-linux-x86_64-debian-gcc | 0.11.0 | 22.68 | 480.19 | 502.87 | NOTE | |
| r-devel-linux-x86_64-fedora-clang | 0.11.0 | 64.00 | 813.40 | 877.40 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 0.11.0 | 25.00 | 415.42 | 440.42 | ERROR | |
| r-devel-windows-x86_64 | 0.11.0 | 37.00 | 503.00 | 540.00 | NOTE | |
| r-patched-linux-x86_64 | 0.11.0 | 52.73 | 683.03 | 735.76 | OK | |
| r-release-linux-x86_64 | 0.11.0 | 36.09 | 691.80 | 727.89 | OK | |
| 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 | 37.00 | 547.00 | 584.00 | OK | |
| 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 | 52.00 | 713.00 | 765.00 | OK |
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:
> ### 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
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [449s/221s]
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:
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: 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:
> 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: 2026-07-24 10:13:09.746776: Isomap START
> test_pipeop_isomap.R: 2026-07-24 10:13:09.747876: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:09.767791: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:09.79611: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 10:13:09.882093: Isomap START
> test_pipeop_isomap.R: 2026-07-24 10:13:09.882814: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:09.898142: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:09.9259: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 10:13:09.970359: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 10:13:09.971532: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:09.998547: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:10.060891: embedding
> test_pipeop_isomap.R: 2026-07-24 10:13:10.062554: DONE
> test_pipeop_isomap.R: 2026-07-24 10:13:10.105469: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 10:13:10.10623: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:10.147315: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:10.209491: embedding
> test_pipeop_isomap.R: 2026-07-24 10:13:10.211377: DONE
> test_pipeop_isomap.R: 2026-07-24 10:13:10.34708: Isomap START
> test_pipeop_isomap.R: 2026-07-24 10:13:10.347817: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:10.373432: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:10.51502: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 10:13:10.571116: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 10:13:10.572266: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:10.620244: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:10.909604: embedding
> test_pipeop_isomap.R: 2026-07-24 10:13:10.926808: DONE
> test_pipeop_isomap.R: 2026-07-24 10:13:11.161672: Isomap START
> test_pipeop_isomap.R: 2026-07-24 10:13:11.162432: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:11.178478: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:11.206276: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 10:13:11.258423: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 10:13:11.259496: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:11.285456: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:11.347081: embedding
> test_pipeop_isomap.R: 2026-07-24 10:13:11.348843: DONE
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-07-24 10:13:11.665286: Isomap START
> test_pipeop_isomap.R: 2026-07-24 10:13:11.66625: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:11.685552: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:11.713799: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 10:13:11.792542: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 10:13:11.793655: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:11.821599: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:11.88375: embedding
> test_pipeop_isomap.R: 2026-07-24 10:13:11.885539: DONE
> test_pipeop_isomap.R: 2026-07-24 10:13:12.013571: Isomap START
> test_pipeop_isomap.R: 2026-07-24 10:13:12.014321: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:12.030327: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:12.058155: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 10:13:12.13609: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 10:13:12.137183: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:12.178527: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:12.24067: embedding
> test_pipeop_isomap.R: 2026-07-24 10:13:12.242481: DONE
> test_pipeop_isomap.R: 2026-07-24 10:13:12.370924: Isomap START
> test_pipeop_isomap.R: 2026-07-24 10:13:12.371667: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:12.387948: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:12.415842: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 10:13:12.495502: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 10:13:12.496655: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:12.525895: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:12.587809: embedding
> test_pipeop_isomap.R: 2026-07-24 10:13:12.589577: DONE
> test_pipeop_isomap.R: 2026-07-24 10:13:12.722236: Isomap START
> test_pipeop_isomap.R: 2026-07-24 10:13:12.722962: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:12.755195: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:12.783009: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 10:13:12.861187: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 10:13:12.862247: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:12.888827: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:12.950382: embedding
> test_pipeop_isomap.R: 2026-07-24 10:13:12.952266: DONE
> test_pipeop_isomap.R: 2026-07-24 10:13:13.099158: Isomap START
> test_pipeop_isomap.R: 2026-07-24 10:13:13.099928: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:13.11619: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:13.144198: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 10:13:13.307353: Isomap START
> test_pipeop_isomap.R: 2026-07-24 10:13:13.308082: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:13.325126: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:13.353817: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 10:13:13.395211: Isomap START
> test_pipeop_isomap.R: 2026-07-24 10:13:13.395963: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 10:13:13.411451: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 10:13:13.437507: 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_dictionary.R:7:3',
'test_learner_weightedaverage.R:5:3', 'test_learner_weightedaverage.R:57:3',
'test_learner_weightedaverage.R:105:3',
'test_learner_weightedaverage.R:152:3', 'test_meta.R:39:3',
'test_mlr_graphs_branching.R:26:3', 'test_mlr_graphs_bagging.R:6:3',
'test_mlr_graphs_robustify.R:5:3', 'test_pipeop_adas.R:8:3',
'test_pipeop_blsmote.R:8:3', 'test_pipeop_branch.R:4:3',
'test_pipeop_chunk.R:4:3', 'test_pipeop_classbalancing.R:7:3',
'test_pipeop_boxcox.R:7:3', 'test_pipeop_classweights.R:10:3',
'test_pipeop_classweightsex.R:9:3', 'test_pipeop_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_featureunion.R:9:3', 'test_pipeop_featureunion.R:134:3',
'test_pipeop_ica.R:7:3', 'test_pipeop_imputelearner.R:43:3',
'test_pipeop_info.R:3:1', 'test_pipeop_impute.R:4:3',
'test_pipeop_isomap.R:10:3', 'test_pipeop_kernelpca.R:9:3',
'test_pipeop_learner.R:17:3', 'test_pipeop_learnerpicvplus.R:2:1',
'test_pipeop_learnercv.R:3:3', 'test_pipeop_learnercv.R:43:3',
'test_pipeop_learnercv.R:73:3', 'test_pipeop_learnercv.R:92:3',
'test_pipeop_learnercv.R:141:3', 'test_pipeop_learnercv.R:157:3',
'test_pipeop_learnercv.R:203:3', 'test_pipeop_learnercv.R:249:3',
'test_pipeop_learnercv.R:278:3', 'test_pipeop_learnercv.R:332:3',
'test_pipeop_learnercv.R:359:3', 'test_pipeop_learnercv.R:389:3',
'test_pipeop_learnercv.R:399:3', 'test_pipeop_learnercv.R:432:3',
'test_pipeop_learnercv.R:472:3', 'test_pipeop_learnercv.R:481:3',
'test_pipeop_learnercv.R:498:3', 'test_pipeop_learnercv.R:506:3',
'test_pipeop_learnercv.R:530:3', 'test_pipeop_learnercv.R:554:3',
'test_pipeop_learnercv.R:634:3', 'test_pipeop_learnercv.R:654:3',
'test_pipeop_learnercv.R:669:3', 'test_pipeop_learnercv.R:754:3',
'test_pipeop_learnercv.R:799:3', 'test_pipeop_learnercv.R:827:3',
'test_pipeop_modelmatrix.R:7:3', 'test_pipeop_multiplicityexply.R:9:3',
'test_pipeop_mutate.R:9:3', 'test_pipeop_multiplicityimply.R:9:3',
'test_pipeop_nearmiss.R:7:3', 'test_pipeop_ovr.R:9:3',
'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3', 'test_pipeop_proxy.R:2:1',
'test_pipeop_quantilebin.R:5:3', 'test_pipeop_randomprojection.R:6:3',
'test_pipeop_randomresponse.R:5:3', 'test_pipeop_removeconstants.R:6:3',
'test_pipeop_renamecolumns.R:6:3', 'test_pipeop_replicate.R:9:3',
'test_pipeop_rowapply.R:6:3', 'test_pipeop_scale.R:6:3',
'test_pipeop_scale.R:10:3', 'test_pipeop_scalemaxabs.R:6:3',
'test_pipeop_scalerange.R:7:3', 'test_pipeop_select.R:9:3',
'test_pipeop_smote.R:10:3', 'test_pipeop_smotenc.R:8:3',
'test_pipeop_spatialsign.R:3:1', 'test_pipeop_splines.R:3:1',
'test_pipeop_subsample.R:6:3', 'test_pipeop_targetinvert.R:4:3',
'test_pipeop_targetmutate.R:5:3', 'test_pipeop_targettrafo.R:4:3',
'test_pipeop_targettrafoscalerange.R:5:3', 'test_pipeop_task_preproc.R:4:3',
'test_pipeop_task_preproc.R:14:3', 'test_pipeop_textvectorizer.R:37:3',
'test_pipeop_textvectorizer.R:186:3', 'test_pipeop_nmf.R:6:3',
'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’ [246s/123s]
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:
> 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: 2026-07-24 08:25:11.638569: Isomap START
> test_pipeop_isomap.R: 2026-07-24 08:25:11.639194: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:11.649539: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:11.66402: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 08:25:11.700778: Isomap START
> test_pipeop_isomap.R: 2026-07-24 08:25:11.7012: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:11.709145: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:11.723189: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 08:25:11.741667: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 08:25:11.742247: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:11.756085: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:11.789078: embedding
> test_pipeop_isomap.R: 2026-07-24 08:25:11.790076: DONE
> test_pipeop_isomap.R: 2026-07-24 08:25:11.80863: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 08:25:11.809042: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:11.832572: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:11.865685: embedding
> test_pipeop_isomap.R: 2026-07-24 08:25:11.866683: DONE
> test_pipeop_isomap.R: 2026-07-24 08:25:11.92518: Isomap START
> test_pipeop_isomap.R: 2026-07-24 08:25:11.925583: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:11.939739: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:12.016927: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 08:25:12.041396: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 08:25:12.041955: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:12.076334: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-07-24 08:25:12.234114: embedding
> test_pipeop_isomap.R: 2026-07-24 08:25:12.238389: DONE
> test_pipeop_isomap.R: 2026-07-24 08:25:12.405347: Isomap START
> test_pipeop_isomap.R: 2026-07-24 08:25:12.405783: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:12.415683: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:12.430081: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 08:25:12.45664: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 08:25:12.457243: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:12.471095: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:12.50485: embedding
> test_pipeop_isomap.R: 2026-07-24 08:25:12.506982: DONE
> test_pipeop_isomap.R: 2026-07-24 08:25:12.612755: Isomap START
> test_pipeop_isomap.R: 2026-07-24 08:25:12.613158: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:12.621382: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:12.635531: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 08:25:12.668665: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 08:25:12.669214: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:12.682623: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:12.715452: embedding
> test_pipeop_isomap.R: 2026-07-24 08:25:12.716446: DONE
> test_pipeop_isomap.R: 2026-07-24 08:25:12.789977: Isomap START
> test_pipeop_isomap.R: 2026-07-24 08:25:12.790349: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:12.79856: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:12.812886: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 08:25:12.846231: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 08:25:12.846773: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:12.860314: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:12.893521: embedding
> test_pipeop_isomap.R: 2026-07-24 08:25:12.894528: DONE
> test_pipeop_isomap.R: 2026-07-24 08:25:12.947663: Isomap START
> test_pipeop_isomap.R: 2026-07-24 08:25:12.948044: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:12.956237: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:12.970458: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 08:25:13.004824: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 08:25:13.005382: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:13.019233: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:13.052273: embedding
> test_pipeop_isomap.R: 2026-07-24 08:25:13.053282: DONE
> test_pipeop_isomap.R: 2026-07-24 08:25:13.121514: Isomap START
> test_pipeop_isomap.R: 2026-07-24 08:25:13.121907: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:13.129965: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:13.144106: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 08:25:13.178139: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-24 08:25:13.178699: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:13.192611: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:13.225597: embedding
> test_pipeop_isomap.R: 2026-07-24 08:25:13.226659: DONE
> test_pipeop_isomap.R: 2026-07-24 08:25:13.288459: Isomap START
> test_pipeop_isomap.R: 2026-07-24 08:25:13.288858: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:13.297006: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:13.311211: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 08:25:13.36916: Isomap START
> test_pipeop_isomap.R: 2026-07-24 08:25:13.369543: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:13.377591: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:13.391676: Classical Scaling
> test_pipeop_isomap.R: 2026-07-24 08:25:13.420653: Isomap START
> test_pipeop_isomap.R: 2026-07-24 08:25:13.421079: constructing knn graph
> test_pipeop_isomap.R: 2026-07-24 08:25:13.430083: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-24 08:25:13.444309: 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_chunk.R:4:3',
'test_pipeop_branch.R:4:3', 'test_pipeop_classbalancing.R:7:3',
'test_pipeop_classweights.R:10:3', 'test_pipeop_classweightsex.R:9:3',
'test_pipeop_colapply.R:9:3', 'test_pipeop_collapsefactors.R:6:3',
'test_pipeop_copy.R:5:3', 'test_pipeop_colroles.R:6:3',
'test_pipeop_decode.R:14:3', 'test_pipeop_encode.R:21:3',
'test_pipeop_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_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_multiplicityimply.R:9:3',
'test_pipeop_mutate.R:9:3', 'test_pipeop_nearmiss.R:7:3',
'test_pipeop_ovr.R:9:3', 'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3',
'test_pipeop_proxy.R:2:1', 'test_pipeop_quantilebin.R:5:3',
'test_pipeop_randomprojection.R:6:3', 'test_pipeop_randomresponse.R:5:3',
'test_pipeop_removeconstants.R:6:3', 'test_pipeop_renamecolumns.R:6:3',
'test_pipeop_replicate.R:9:3', 'test_pipeop_rowapply.R:6:3',
'test_pipeop_scale.R:6:3', 'test_pipeop_scale.R:10:3',
'test_pipeop_scalemaxabs.R:6:3', 'test_pipeop_scalerange.R:7:3',
'test_pipeop_select.R:9:3', 'test_pipeop_smote.R:10:3',
'test_pipeop_smotenc.R:8:3', 'test_pipeop_spatialsign.R:3:1',
'test_pipeop_splines.R:3:1', 'test_pipeop_subsample.R:6:3',
'test_pipeop_targetinvert.R:4:3', 'test_pipeop_targetmutate.R:5:3',
'test_pipeop_targettrafo.R:4:3', 'test_pipeop_targettrafoscalerange.R:5:3',
'test_pipeop_task_preproc.R:4:3', 'test_pipeop_task_preproc.R:14:3',
'test_pipeop_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