Last updated on 2026-08-05 00:50:11 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.11.0 | 37.99 | 651.62 | 689.61 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.11.0 | 23.88 | 459.17 | 483.05 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.11.0 | 65.00 | 1003.66 | 1068.66 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 0.11.0 | 26.00 | 461.17 | 487.17 | ERROR | |
| r-devel-windows-x86_64 | 0.11.0 | 38.00 | 446.00 | 484.00 | ERROR | |
| r-patched-linux-x86_64 | 0.11.0 | 55.20 | 634.10 | 689.30 | ERROR | |
| r-release-linux-x86_64 | 0.11.0 | 36.91 | 619.82 | 656.73 | ERROR | |
| r-release-macos-arm64 | 0.11.0 | 8.00 | 106.00 | 114.00 | OK | |
| r-release-macos-x86_64 | 0.11.0 | 24.00 | 528.00 | 552.00 | OK | |
| r-release-windows-x86_64 | 0.11.0 | 39.00 | 486.00 | 525.00 | ERROR | |
| r-oldrel-macos-arm64 | 0.11.0 | OK | ||||
| r-oldrel-macos-x86_64 | 0.11.0 | 28.00 | 883.00 | 911.00 | OK | |
| r-oldrel-windows-x86_64 | 0.11.0 | 55.00 | 632.00 | 687.00 | 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 4.753 0.091 10.401
mlr_pipeops 3.717 0.080 7.995
mlr_pipeops_boxcox 2.828 0.116 5.691
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [372s/195s]
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]
> test_pipeop_blsmote.R: "Borderline-SMOTE done"
Saving _problems/test_pipeop_classbalancing-13.R
Saving _problems/test_pipeop_classweights-17.R
Saving _problems/test_pipeop_classweights-36.R
Saving _problems/test_pipeop_imputelearner-7.R
Saving _problems/test_pipeop_imputelearner-138.R
> test_pipeop_isomap.R: 2026-08-04 07:01:37.390497: Isomap START
> test_pipeop_isomap.R: 2026-08-04 07:01:37.391351: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:37.408256: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:37.430161: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 07:01:37.489896: Isomap START
> test_pipeop_isomap.R: 2026-08-04 07:01:37.490461: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:37.501951: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:37.522625: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 07:01:37.55342: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 07:01:37.554143: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:37.574727: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:37.61855: embedding
> test_pipeop_isomap.R: 2026-08-04 07:01:37.61991: DONE
> test_pipeop_isomap.R: 2026-08-04 07:01:37.652239: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 07:01:37.652759: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:37.672587: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:37.73614: embedding
> test_pipeop_isomap.R: 2026-08-04 07:01:37.738741: DONE
> test_pipeop_isomap.R: 2026-08-04 07:01:37.834885: Isomap START
> test_pipeop_isomap.R: 2026-08-04 07:01:37.835399: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:37.856368: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:37.954406: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 07:01:37.992054: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 07:01:37.992784: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:38.025728: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-04 07:01:38.222244: embedding
> test_pipeop_isomap.R: 2026-08-04 07:01:38.225447: DONE
> test_pipeop_isomap.R: 2026-08-04 07:01:38.390636: Isomap START
> test_pipeop_isomap.R: 2026-08-04 07:01:38.391157: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:38.401749: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:38.420222: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 07:01:38.458466: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 07:01:38.459205: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:38.48702: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:38.528149: embedding
> test_pipeop_isomap.R: 2026-08-04 07:01:38.529434: DONE
> test_pipeop_isomap.R: 2026-08-04 07:01:38.682409: Isomap START
> test_pipeop_isomap.R: 2026-08-04 07:01:38.682916: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:38.695985: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:38.714795: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 07:01:38.765809: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 07:01:38.766527: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:38.785956: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:38.826209: embedding
> test_pipeop_isomap.R: 2026-08-04 07:01:38.827371: DONE
> test_pipeop_isomap.R: 2026-08-04 07:01:38.914464: Isomap START
> test_pipeop_isomap.R: 2026-08-04 07:01:38.914969: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:38.925578: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:38.943937: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 07:01:38.993665: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 07:01:38.994373: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:39.010803: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:39.052372: embedding
> test_pipeop_isomap.R: 2026-08-04 07:01:39.053553: DONE
> test_pipeop_isomap.R: 2026-08-04 07:01:39.156238: Isomap START
> test_pipeop_isomap.R: 2026-08-04 07:01:39.15677: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:39.168095: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:39.190397: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 07:01:39.246348: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 07:01:39.247078: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:39.265602: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:39.301767: embedding
> test_pipeop_isomap.R: 2026-08-04 07:01:39.302962: DONE
> test_pipeop_isomap.R: 2026-08-04 07:01:39.390954: Isomap START
> test_pipeop_isomap.R: 2026-08-04 07:01:39.391457: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:39.401857: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:39.419584: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 07:01:39.470327: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 07:01:39.471053: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:39.48812: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:39.529781: embedding
> test_pipeop_isomap.R: 2026-08-04 07:01:39.531013: DONE
> test_pipeop_isomap.R: 2026-08-04 07:01:39.629535: Isomap START
> test_pipeop_isomap.R: 2026-08-04 07:01:39.630085: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:39.642533: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:39.661147: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 07:01:39.749467: Isomap START
> test_pipeop_isomap.R: 2026-08-04 07:01:39.751742: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:39.773232: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:39.791084: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 07:01:39.815425: Isomap START
> test_pipeop_isomap.R: 2026-08-04 07:01:39.815907: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 07:01:39.828808: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 07:01:39.847319: 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:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_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_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_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-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’ [277s/180s]
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:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
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]
> test_pipeop_blsmote.R: "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: 2026-08-04 18:16:45.818479: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:16:45.819294: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:45.838857: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:45.856759: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:16:45.904552: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:16:45.907434: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:45.919306: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:45.935956: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:16:45.965731: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:16:45.966362: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:45.98406: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:46.017795: embedding
> test_pipeop_isomap.R: 2026-08-04 18:16:46.018825: DONE
> test_pipeop_isomap.R: 2026-08-04 18:16:46.041508: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:16:46.044462: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:46.063174: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:46.100186: embedding
> test_pipeop_isomap.R: 2026-08-04 18:16:46.101349: DONE
> test_pipeop_isomap.R: 2026-08-04 18:16:46.177213: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:16:46.179938: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:46.196528: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:46.272087: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:16:46.318354: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:16:46.322013: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:46.38165: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:46.550812: embedding
> test_pipeop_isomap.R: 2026-08-04 18:16:46.554706: DONE
> test_pipeop_isomap.R: 2026-08-04 18:16:46.72604: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:16:46.729374: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:46.744525: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:46.770658: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:16:46.799496: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:16:46.802657: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:46.819422: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:46.855868: embedding
> test_pipeop_isomap.R: 2026-08-04 18:16:46.859168: DONE
> test_pipeop_isomap.R: 2026-08-04 18:16:46.99306: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:16:46.996115: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:47.011268: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:47.034017: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:16:47.10606: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:16:47.107865: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:47.128702: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:47.163863: embedding
> test_pipeop_isomap.R: 2026-08-04 18:16:47.167058: DONE
> test_pipeop_isomap.R: 2026-08-04 18:16:47.264751: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:16:47.267946: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:47.28258: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:47.29878: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:16:47.358144: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:16:47.358839: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:47.37463: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:47.420001: embedding
> test_pipeop_isomap.R: 2026-08-04 18:16:47.421011: DONE
> test_pipeop_isomap.R: 2026-08-04 18:16:47.514832: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:16:47.515271: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:47.523299: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:47.541534: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:16:47.590122: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:16:47.590848: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:47.606244: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:47.640352: embedding
> test_pipeop_isomap.R: 2026-08-04 18:16:47.643647: DONE
> test_pipeop_isomap.R: 2026-08-04 18:16:47.739198: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:16:47.739701: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:47.757014: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:47.800352: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:16:47.874804: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 18:16:47.878377: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:47.910027: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:48.00344: embedding
> test_pipeop_isomap.R: 2026-08-04 18:16:48.004415: DONE
> test_pipeop_isomap.R: 2026-08-04 18:16:48.101698: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:16:48.102116: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:48.109553: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:48.125055: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:16:48.277728: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:16:48.281029: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:48.298084: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:48.318143: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 18:16:48.335792: Isomap START
> test_pipeop_isomap.R: 2026-08-04 18:16:48.336205: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 18:16:48.34364: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 18:16:48.357457: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> test_pipeop_nmf.R: [PipeOpNMFstate]
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_nmf.R: [PipeOpNMFstate]
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
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_blsmote.R:8:3', 'test_pipeop_adas.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_ica.R:7:3',
'test_pipeop_featureunion.R:9:3', 'test_pipeop_featureunion.R:134:3',
'test_pipeop_imputelearner.R:43:3', 'test_pipeop_info.R:3:1',
'test_pipeop_impute.R:4:3', 'test_pipeop_kernelpca.R:9:3',
'test_pipeop_isomap.R:10:3', 'test_pipeop_learner.R:17:3',
'test_pipeop_learnerpicvplus.R:2:1', 'test_pipeop_learnercv.R:3:3',
'test_pipeop_learnercv.R:43:3', 'test_pipeop_learnercv.R:73:3',
'test_pipeop_learnercv.R:92:3', 'test_pipeop_learnercv.R:141:3',
'test_pipeop_learnercv.R:157:3', 'test_pipeop_learnercv.R:203:3',
'test_pipeop_learnercv.R:249:3', 'test_pipeop_learnercv.R:278:3',
'test_pipeop_learnercv.R:332:3', 'test_pipeop_learnercv.R:359:3',
'test_pipeop_learnercv.R:389:3', 'test_pipeop_learnercv.R:399:3',
'test_pipeop_learnercv.R:432:3', 'test_pipeop_learnercv.R:472:3',
'test_pipeop_learnercv.R:481:3', 'test_pipeop_learnercv.R:498:3',
'test_pipeop_learnercv.R:506:3', 'test_pipeop_learnercv.R:530:3',
'test_pipeop_learnercv.R:554:3', 'test_pipeop_learnercv.R:634:3',
'test_pipeop_learnercv.R:654:3', 'test_pipeop_learnercv.R:669:3',
'test_pipeop_learnercv.R:754:3', 'test_pipeop_learnercv.R:799:3',
'test_pipeop_learnercv.R:827:3', 'test_pipeop_modelmatrix.R:7:3',
'test_pipeop_multiplicityexply.R:9:3', 'test_pipeop_mutate.R:9:3',
'test_pipeop_multiplicityimply.R:9:3', 'test_pipeop_nearmiss.R:7:3',
'test_pipeop_ovr.R:9:3', 'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3',
'test_pipeop_proxy.R:2:1', 'test_pipeop_quantilebin.R:5:3',
'test_pipeop_randomprojection.R:6:3', 'test_pipeop_randomresponse.R:5:3',
'test_pipeop_removeconstants.R:6:3', 'test_pipeop_renamecolumns.R:6:3',
'test_pipeop_replicate.R:9:3', 'test_pipeop_rowapply.R:6:3',
'test_pipeop_scale.R:6:3', 'test_pipeop_scale.R:10:3',
'test_pipeop_scalemaxabs.R:6:3', 'test_pipeop_scalerange.R:7:3',
'test_pipeop_select.R:9:3', 'test_pipeop_smote.R:10:3',
'test_pipeop_smotenc.R:8:3', 'test_pipeop_spatialsign.R:3:1',
'test_pipeop_splines.R:3:1', 'test_pipeop_subsample.R:6:3',
'test_pipeop_targetinvert.R:4:3', 'test_pipeop_targetmutate.R:5:3',
'test_pipeop_targettrafo.R:4:3', 'test_pipeop_targettrafoscalerange.R:5:3',
'test_pipeop_nmf.R:6:3', 'test_pipeop_task_preproc.R:4:3',
'test_pipeop_task_preproc.R:14:3', 'test_pipeop_tomek.R:7:3',
'test_pipeop_textvectorizer.R:37:3', 'test_pipeop_textvectorizer.R:186:3',
'test_pipeop_unbranch.R:10:3', 'test_pipeop_updatetarget.R:89:3',
'test_pipeop_vtreat.R:9:3', 'test_pipeop_yeojohnson.R:7:3',
'test_pipeop_tunethreshold.R:111:3', 'test_pipeop_tunethreshold.R:191:3',
'test_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’ [583s/389s]
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:
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: 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:
> 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:
Saving _problems/test_mlr_graphs_robustify-106.R
> test_multiplicities.R:
> test_multiplicities.R: [[1]]
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> test_multiplicities.R:
> test_pipeop_blsmote.R: [1]
> test_pipeop_blsmote.R: "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1]
> test_pipeop_blsmote.R: "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1]
> test_pipeop_blsmote.R: "Borderline-SMOTE done"
Saving _problems/test_pipeop_classbalancing-13.R
Saving _problems/test_pipeop_classweights-17.R
Saving _problems/test_pipeop_classweights-36.R
Saving _problems/test_pipeop_imputelearner-7.R
Saving _problems/test_pipeop_imputelearner-138.R
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-04 17:23:55.539155: Isomap START
> test_pipeop_isomap.R: 2026-08-04 17:23:55.540329: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:55.567255: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:55.598848: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 17:23:55.698013: Isomap START
> test_pipeop_isomap.R: 2026-08-04 17:23:55.701515: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:55.720402: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:55.75125: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 17:23:55.798946: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 17:23:55.802657: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:55.833097: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:55.898502: embedding
> test_pipeop_isomap.R: 2026-08-04 17:23:55.900333: DONE
> test_pipeop_isomap.R: 2026-08-04 17:23:55.958972: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 17:23:55.959864: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:55.996392: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:56.080509: embedding
> test_pipeop_isomap.R: 2026-08-04 17:23:56.085367: DONE
> test_pipeop_isomap.R: 2026-08-04 17:23:56.265466: Isomap START
> test_pipeop_isomap.R: 2026-08-04 17:23:56.266268: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:56.296844: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:56.439608: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 17:23:56.506393: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 17:23:56.510136: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:56.577884: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:57.013258: embedding
> test_pipeop_isomap.R: 2026-08-04 17:23:57.021318: DONE
> test_pipeop_isomap.R: 2026-08-04 17:23:57.535955: Isomap START
> test_pipeop_isomap.R: 2026-08-04 17:23:57.536718: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:57.553194: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:57.580383: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 17:23:57.648244: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 17:23:57.649412: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:57.683323: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:57.750272: embedding
> test_pipeop_isomap.R: 2026-08-04 17:23:57.755912: DONE
> test_pipeop_isomap.R: 2026-08-04 17:23:58.110116: Isomap START
> test_pipeop_isomap.R: 2026-08-04 17:23:58.110863: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:58.143355: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:58.171299: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 17:23:58.303108: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 17:23:58.304282: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:58.338853: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:58.405616: embedding
> test_pipeop_isomap.R: 2026-08-04 17:23:58.410868: DONE
> test_pipeop_isomap.R: 2026-08-04 17:23:58.581796: Isomap START
> test_pipeop_isomap.R: 2026-08-04 17:23:58.582566: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:58.611704: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:58.643303: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 17:23:58.736058: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 17:23:58.737227: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:58.801455: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:58.901992: embedding
> test_pipeop_isomap.R: 2026-08-04 17:23:58.906876: DONE
> test_pipeop_isomap.R: 2026-08-04 17:23:59.140061: Isomap START
> test_pipeop_isomap.R: 2026-08-04 17:23:59.140836: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:59.1768: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:59.235683: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 17:23:59.421854: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 17:23:59.426075: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:59.511894: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:23:59.649133: embedding
> test_pipeop_isomap.R: 2026-08-04 17:23:59.657077: DONE
> test_pipeop_isomap.R: 2026-08-04 17:23:59.945993: Isomap START
> test_pipeop_isomap.R: 2026-08-04 17:23:59.946786: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:23:59.983166: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:24:00.044302: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 17:24:00.215022: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 17:24:00.21929: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:24:00.276889: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:24:00.443822: embedding
> test_pipeop_isomap.R: 2026-08-04 17:24:00.448715: DONE
> test_pipeop_isomap.R: 2026-08-04 17:24:00.805029: Isomap START
> test_pipeop_isomap.R: 2026-08-04 17:24:00.808872: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:24:00.841313: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:24:00.90102: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 17:24:01.21504: Isomap START
> test_pipeop_isomap.R: 2026-08-04 17:24:01.215845: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:24:01.251557: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:24:01.307649: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 17:24:01.40207: Isomap START
> test_pipeop_isomap.R: 2026-08-04 17:24:01.402849: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 17:24:01.471667: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 17:24:01.532168: 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:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: 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_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_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_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_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_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’ [279s/288s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ library("paradox")
+ library("mlr3pipelines")
+ test_check("mlr3pipelines")
+ }
Starting 2 test processes.
> test_Graph.R: Training debug.multi with input list(input_1 = 1, input_2 = 1)
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R:
> 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:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R:
> 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]
> test_pipeop_blsmote.R: "Borderline-SMOTE done"
Saving _problems/test_pipeop_classbalancing-13.R
Saving _problems/test_pipeop_classweights-17.R
Saving _problems/test_pipeop_classweights-36.R
Saving _problems/test_pipeop_imputelearner-7.R
Saving _problems/test_pipeop_imputelearner-138.R
> test_pipeop_isomap.R: 2026-08-04 21:14:23.365921: Isomap START
> test_pipeop_isomap.R: 2026-08-04 21:14:23.366683: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:23.393025: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:23.421769: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 21:14:23.545789: Isomap START
> test_pipeop_isomap.R: 2026-08-04 21:14:23.546239: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:23.574404: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:23.622924: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 21:14:23.692699: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 21:14:23.693386: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:23.779155: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:23.887011: embedding
> test_pipeop_isomap.R: 2026-08-04 21:14:23.895713: DONE
> test_pipeop_isomap.R: 2026-08-04 21:14:23.968213: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 21:14:23.972548: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:24.053654: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:24.162803: embedding
> test_pipeop_isomap.R: 2026-08-04 21:14:24.163945: DONE
> test_pipeop_isomap.R: 2026-08-04 21:14:24.42067: Isomap START
> test_pipeop_isomap.R: 2026-08-04 21:14:24.426472: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:24.788657: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:25.041707: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 21:14:25.150932: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 21:14:25.153669: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:25.276698: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-04 21:14:25.830857: embedding
> test_pipeop_isomap.R: 2026-08-04 21:14:25.8393: DONE
> test_pipeop_isomap.R: 2026-08-04 21:14:26.107321: Isomap START
> test_pipeop_isomap.R: 2026-08-04 21:14:26.107768: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:26.142019: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:26.194796: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 21:14:26.266802: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 21:14:26.267625: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:26.319456: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:26.386201: embedding
> test_pipeop_isomap.R: 2026-08-04 21:14:26.39144: DONE
> test_pipeop_isomap.R: 2026-08-04 21:14:26.613511: Isomap START
> test_pipeop_isomap.R: 2026-08-04 21:14:26.620617: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:26.644206: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:26.682027: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 21:14:26.806885: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 21:14:26.807581: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:28.21364: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:28.277303: embedding
> test_pipeop_isomap.R: 2026-08-04 21:14:28.28137: DONE
> test_pipeop_isomap.R: 2026-08-04 21:14:28.39985: Isomap START
> test_pipeop_isomap.R: 2026-08-04 21:14:28.40312: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:28.418967: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:28.443376: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 21:14:28.516206: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 21:14:28.516789: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:28.5487: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:28.615139: embedding
> test_pipeop_isomap.R: 2026-08-04 21:14:28.618234: DONE
> test_pipeop_isomap.R: 2026-08-04 21:14:28.686211: Isomap START
> test_pipeop_isomap.R: 2026-08-04 21:14:28.686626: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:28.695418: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:28.709799: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 21:14:28.751713: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 21:14:28.752303: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:28.770319: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:28.804839: embedding
> test_pipeop_isomap.R: 2026-08-04 21:14:28.806032: DONE
> test_pipeop_isomap.R: 2026-08-04 21:14:28.87611: Isomap START
> test_pipeop_isomap.R: 2026-08-04 21:14:28.876505: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:28.894161: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:28.917449: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 21:14:29.000637: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-04 21:14:29.001299: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:29.034912: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:29.107056: embedding
> test_pipeop_isomap.R: 2026-08-04 21:14:29.108286: DONE
> test_pipeop_isomap.R: 2026-08-04 21:14:29.265351: Isomap START
> test_pipeop_isomap.R: 2026-08-04 21:14:29.265791: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:29.287429: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:29.314937: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 21:14:29.484153: Isomap START
> test_pipeop_isomap.R: 2026-08-04 21:14:29.487442: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:29.505401: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:29.536064: Classical Scaling
> test_pipeop_isomap.R: 2026-08-04 21:14:29.58048: Isomap START
> test_pipeop_isomap.R: 2026-08-04 21:14:29.580909: constructing knn graph
> test_pipeop_isomap.R: 2026-08-04 21:14:29.596363: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-04 21:14:29.635148: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> test_pipeop_nmf.R: [PipeOpNMFstate]
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_nmf.R: [PipeOpNMFstate]
Saving _problems/test_pipeop_unbranch-21.R
Saving _problems/test_pipeop_tunethreshold-36.R
Saving _problems/test_pipeop_tunethreshold-73.R
Saving _problems/test_selector-6.R
[ FAIL 12 | WARN 21 | SKIP 128 | PASS 8462 ]
══ Skipped tests (128) ═════════════════════════════════════════════════════════
• On CRAN (125): 'test_CnfFormula_simplify.R:6:3', 'test_CnfFormula.R:591:3',
'test_Graph.R:283:3', 'test_PipeOp.R:32:1', 'test_GraphLearner.R:5:3',
'test_GraphLearner.R:221:3', 'test_GraphLearner.R:343:3',
'test_GraphLearner.R:408:3', 'test_GraphLearner.R:571:3',
'test_doublearrow.R:2:1', 'test_gunion.R:2:1',
'test_learner_weightedaverage.R:5:3', 'test_learner_weightedaverage.R:57:3',
'test_learner_weightedaverage.R:105:3',
'test_learner_weightedaverage.R:152:3', 'test_dictionary.R:7:3',
'test_meta.R:39:3', 'test_mlr_graphs_branching.R:26:3',
'test_mlr_graphs_bagging.R:6:3', 'test_mlr_graphs_robustify.R:5:3',
'test_pipeop_adas.R:8:3', 'test_pipeop_blsmote.R:8:3',
'test_pipeop_branch.R:4:3', 'test_pipeop_chunk.R:4:3',
'test_pipeop_classbalancing.R:7:3', 'test_pipeop_boxcox.R:7:3',
'test_pipeop_classweights.R:10:3', 'test_pipeop_classweightsex.R:9:3',
'test_pipeop_colapply.R:9:3', 'test_pipeop_collapsefactors.R:6:3',
'test_pipeop_copy.R:5:3', 'test_pipeop_colroles.R:6:3',
'test_pipeop_decode.R:14:3', 'test_pipeop_encode.R:21:3',
'test_pipeop_encodeimpact.R:11:3', 'test_pipeop_datefeatures.R:10:3',
'test_pipeop_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_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_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_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-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: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
Saving _problems/test_mlr_graphs_robustify-106.R
> test_multiplicities.R:
> test_multiplicities.R: [[1]]
> test_multiplicities.R:
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
Saving _problems/test_pipeop_classbalancing-13.R
Saving _problems/test_pipeop_classweights-17.R
Saving _problems/test_pipeop_classweights-36.R
Saving _problems/test_pipeop_imputelearner-7.R
Saving _problems/test_pipeop_imputelearner-138.R
> test_pipeop_isomap.R: 2026-07-29 12:49:30.494463: Isomap START
> test_pipeop_isomap.R: 2026-07-29 12:49:30.495764: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:30.513126: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:30.530864: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 12:49:30.576388: Isomap START
> test_pipeop_isomap.R: 2026-07-29 12:49:30.577406: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:30.589958: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:30.60872: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 12:49:30.634242: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 12:49:30.63524: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:30.64899: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:30.684261: embedding
> test_pipeop_isomap.R: 2026-07-29 12:49:30.68614: DONE
> test_pipeop_isomap.R: 2026-07-29 12:49:30.708127: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 12:49:30.708869: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:30.727013: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:30.775723: embedding
> test_pipeop_isomap.R: 2026-07-29 12:49:30.777368: DONE
> test_pipeop_isomap.R: 2026-07-29 12:49:30.86755: Isomap START
> test_pipeop_isomap.R: 2026-07-29 12:49:30.868273: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:30.888716: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:31.006984: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 12:49:31.04661: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 12:49:31.04801: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:31.083463: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:31.293892: embedding
> test_pipeop_isomap.R: 2026-07-29 12:49:31.298168: DONE
> test_pipeop_isomap.R: 2026-07-29 12:49:31.435849: Isomap START
> test_pipeop_isomap.R: 2026-07-29 12:49:31.436664: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:31.459069: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:31.476202: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 12:49:31.521104: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 12:49:31.522164: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:31.537222: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-07-29 12:49:31.570905: embedding
> test_pipeop_isomap.R: 2026-07-29 12:49:31.572675: DONE
> test_pipeop_isomap.R: 2026-07-29 12:49:31.745587: Isomap START
> test_pipeop_isomap.R: 2026-07-29 12:49:31.746756: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:31.759358: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:31.777277: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 12:49:31.831129: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 12:49:31.832395: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:31.848732: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:31.886743: embedding
> test_pipeop_isomap.R: 2026-07-29 12:49:31.888765: DONE
> test_pipeop_isomap.R: 2026-07-29 12:49:31.975897: Isomap START
> test_pipeop_isomap.R: 2026-07-29 12:49:31.976944: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:31.986757: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:32.002833: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 12:49:32.05532: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 12:49:32.056652: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:32.073728: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:32.119459: embedding
> test_pipeop_isomap.R: 2026-07-29 12:49:32.121306: DONE
> test_pipeop_isomap.R: 2026-07-29 12:49:32.205071: Isomap START
> test_pipeop_isomap.R: 2026-07-29 12:49:32.206237: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:32.217814: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:32.237657: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 12:49:32.295321: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 12:49:32.296844: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:32.328514: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:32.376663: embedding
> test_pipeop_isomap.R: 2026-07-29 12:49:32.378717: DONE
> test_pipeop_isomap.R: 2026-07-29 12:49:32.458314: Isomap START
> test_pipeop_isomap.R: 2026-07-29 12:49:32.459238: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:32.470874: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:32.491018: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 12:49:32.548181: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 12:49:32.549503: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:32.566565: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:32.609347: embedding
> test_pipeop_isomap.R: 2026-07-29 12:49:32.611138: DONE
> test_pipeop_isomap.R: 2026-07-29 12:49:32.695158: Isomap START
> test_pipeop_isomap.R: 2026-07-29 12:49:32.696309: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:32.705353: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:32.722969: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 12:49:32.815613: Isomap START
> test_pipeop_isomap.R: 2026-07-29 12:49:32.816398: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:32.825924: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:32.841646: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 12:49:32.871074: Isomap START
> test_pipeop_isomap.R: 2026-07-29 12:49:32.87201: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 12:49:32.880506: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 12:49:32.893143: 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_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_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_nmf.R:6:3',
'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_typecheck.R:188:3', 'test_ppl.R:63:3'
• Skipping (1): 'test_GraphLearner.R:1278:3'
• empty test (2): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_mlr_graphs_robustify.R:106:3'): Robustify Pipeline Impute Missings ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_mlr_graphs_robustify.R:106:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classbalancing.R:13:3'): PipeOpClassBalancing ───────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classbalancing.R:13:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:17:3'): PipeOpClassWeights ───────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classweights.R:17:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:36:5'): PipeOpClassWeights - weight roles assigned ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_classweights.R:36:5
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:7:3'): PipeOpImputeLearner - simple tests ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:7:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:138:3'): PipeOpImputeLearner - model active binding to state ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:138:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_impute.R:452:3'): impute, test rows and affect_columns ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_impute.R:452:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_missind.R:4:3'): PipeOpMissInd ──────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_missind.R:4:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_unbranch.R:21:3'): PipeOpUnbranch - train and predict ───
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_unbranch.R:21:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:36:3'): threshold works for binary ──────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_tunethreshold.R:36:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:73:3'): tunethreshold graph works ───────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─graph$train(tsk("pima")) at test_pipeop_tunethreshold.R:73:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. └─mlr3::tsk("pima")
5. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
6. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_selector.R:6:3'): Selectors work ───────────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::mlr_tasks$get("pima") at test_selector.R:6:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
[ FAIL 12 | WARN 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 4.308 0.098 5.407
Flavor: r-patched-linux-x86_64
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [362s/187s]
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: 2026-07-29 18:08:10.956738: Isomap START
> test_pipeop_isomap.R: 2026-07-29 18:08:10.95758: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:10.971577: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:10.993032: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 18:08:11.050625: Isomap START
> test_pipeop_isomap.R: 2026-07-29 18:08:11.051149: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:11.062078: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:11.080642: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 18:08:11.111879: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 18:08:11.112661: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:11.131981: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:11.176595: embedding
> test_pipeop_isomap.R: 2026-07-29 18:08:11.177912: DONE
> test_pipeop_isomap.R: 2026-07-29 18:08:11.207629: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 18:08:11.208193: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:11.226001: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:11.267231: embedding
> test_pipeop_isomap.R: 2026-07-29 18:08:11.294299: DONE
> test_pipeop_isomap.R: 2026-07-29 18:08:11.387609: Isomap START
> test_pipeop_isomap.R: 2026-07-29 18:08:11.388122: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:11.405658: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:11.505041: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 18:08:11.543434: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 18:08:11.544158: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:11.575591: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-07-29 18:08:11.777835: embedding
> test_pipeop_isomap.R: 2026-07-29 18:08:11.782432: DONE
> test_pipeop_isomap.R: 2026-07-29 18:08:11.942607: Isomap START
> test_pipeop_isomap.R: 2026-07-29 18:08:11.943129: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:11.955766: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:11.974662: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 18:08:12.012843: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 18:08:12.013559: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:12.034392: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:12.077118: embedding
> test_pipeop_isomap.R: 2026-07-29 18:08:12.078603: DONE
> test_pipeop_isomap.R: 2026-07-29 18:08:12.242087: Isomap START
> test_pipeop_isomap.R: 2026-07-29 18:08:12.24262: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:12.267823: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:12.286201: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 18:08:12.339852: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 18:08:12.340611: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:12.358102: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:12.400994: embedding
> test_pipeop_isomap.R: 2026-07-29 18:08:12.40219: DONE
> test_pipeop_isomap.R: 2026-07-29 18:08:12.492835: Isomap START
> test_pipeop_isomap.R: 2026-07-29 18:08:12.493343: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:12.503973: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:12.523005: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 18:08:12.577616: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 18:08:12.578329: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:12.595901: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:12.637881: embedding
> test_pipeop_isomap.R: 2026-07-29 18:08:12.640771: DONE
> test_pipeop_isomap.R: 2026-07-29 18:08:12.727103: Isomap START
> test_pipeop_isomap.R: 2026-07-29 18:08:12.727619: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:12.740214: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:12.759322: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 18:08:12.813903: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 18:08:12.814652: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:12.834106: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:12.876134: embedding
> test_pipeop_isomap.R: 2026-07-29 18:08:12.877378: DONE
> test_pipeop_isomap.R: 2026-07-29 18:08:12.96683: Isomap START
> test_pipeop_isomap.R: 2026-07-29 18:08:12.967335: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:12.978209: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:12.9969: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 18:08:13.054411: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-29 18:08:13.055199: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:13.086286: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:13.13028: embedding
> test_pipeop_isomap.R: 2026-07-29 18:08:13.131579: DONE
> test_pipeop_isomap.R: 2026-07-29 18:08:13.229705: Isomap START
> test_pipeop_isomap.R: 2026-07-29 18:08:13.231935: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:13.242735: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:13.262384: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 18:08:13.352256: Isomap START
> test_pipeop_isomap.R: 2026-07-29 18:08:13.352801: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:13.36598: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:13.385861: Classical Scaling
> test_pipeop_isomap.R: 2026-07-29 18:08:13.413581: Isomap START
> test_pipeop_isomap.R: 2026-07-29 18:08:13.414091: constructing knn graph
> test_pipeop_isomap.R: 2026-07-29 18:08:13.424096: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-29 18:08:13.442828: 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_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_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_encodepl.R:5:3',
'test_pipeop_encodepl.R:72:3', 'test_pipeop_ensemble.R:3:1',
'test_pipeop_encodelmer.R:15:3', 'test_pipeop_encodelmer.R:37:3',
'test_pipeop_encodelmer.R:80:3', 'test_pipeop_filter.R:7:3',
'test_pipeop_fixfactors.R:9:3', 'test_pipeop_histbin.R:7:3',
'test_pipeop_ica.R:7:3', 'test_pipeop_featureunion.R:9:3',
'test_pipeop_featureunion.R:134:3', 'test_pipeop_imputelearner.R:43:3',
'test_pipeop_info.R:3:1', 'test_pipeop_impute.R:4:3',
'test_pipeop_isomap.R:10:3', 'test_pipeop_kernelpca.R:9:3',
'test_pipeop_learner.R:17:3', 'test_pipeop_learnerpicvplus.R:2:1',
'test_pipeop_learnercv.R:3:3', 'test_pipeop_learnercv.R:43:3',
'test_pipeop_learnercv.R:73:3', 'test_pipeop_learnercv.R:92:3',
'test_pipeop_learnercv.R:141:3', 'test_pipeop_learnercv.R:157:3',
'test_pipeop_learnercv.R:203:3', 'test_pipeop_learnercv.R:249:3',
'test_pipeop_learnercv.R:278:3', 'test_pipeop_learnercv.R:332:3',
'test_pipeop_learnercv.R:359:3', 'test_pipeop_learnercv.R:389:3',
'test_pipeop_learnercv.R:399:3', 'test_pipeop_learnercv.R:432:3',
'test_pipeop_learnercv.R:472:3', 'test_pipeop_learnercv.R:481:3',
'test_pipeop_learnercv.R:498:3', 'test_pipeop_learnercv.R:506:3',
'test_pipeop_learnercv.R:530:3', 'test_pipeop_learnercv.R:554:3',
'test_pipeop_learnercv.R:634:3', 'test_pipeop_learnercv.R:654:3',
'test_pipeop_learnercv.R:669:3', 'test_pipeop_learnercv.R:754:3',
'test_pipeop_learnercv.R:799:3', 'test_pipeop_learnercv.R:827:3',
'test_pipeop_modelmatrix.R:7:3', 'test_pipeop_multiplicityexply.R:9:3',
'test_pipeop_mutate.R:9:3', 'test_pipeop_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_ppl.R:63:3',
'test_pipeop_tunethreshold.R:111:3', 'test_pipeop_tunethreshold.R:191:3',
'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 4.564 0.073 6.273
Flavor: r-release-linux-x86_64
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [347s/179s]
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: 2026-08-01 18:10:11.736573: Isomap START
> test_pipeop_isomap.R: 2026-08-01 18:10:11.737387: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:11.750726: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:11.769926: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 18:10:11.960575: Isomap START
> test_pipeop_isomap.R: 2026-08-01 18:10:11.96112: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:11.974217: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:11.993511: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 18:10:12.024404: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 18:10:12.025131: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:12.045502: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:12.087984: embedding
> test_pipeop_isomap.R: 2026-08-01 18:10:12.089203: DONE
> test_pipeop_isomap.R: 2026-08-01 18:10:12.118236: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 18:10:12.11878: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:12.135116: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:12.180037: embedding
> test_pipeop_isomap.R: 2026-08-01 18:10:12.181285: DONE
> test_pipeop_isomap.R: 2026-08-01 18:10:12.27949: Isomap START
> test_pipeop_isomap.R: 2026-08-01 18:10:12.280029: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:12.308573: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:12.408108: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 18:10:12.448265: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 18:10:12.449001: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:12.482333: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:12.692166: embedding
> test_pipeop_isomap.R: 2026-08-01 18:10:12.695525: DONE
> test_pipeop_isomap.R: 2026-08-01 18:10:12.85928: Isomap START
> test_pipeop_isomap.R: 2026-08-01 18:10:12.85982: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:12.872692: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:12.891901: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 18:10:12.927203: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 18:10:12.927862: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:13.360971: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-01 18:10:13.405167: embedding
> test_pipeop_isomap.R: 2026-08-01 18:10:13.406421: DONE
> test_pipeop_isomap.R: 2026-08-01 18:10:13.550889: Isomap START
> test_pipeop_isomap.R: 2026-08-01 18:10:13.551419: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:13.562278: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:13.583608: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 18:10:13.635533: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 18:10:13.636281: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:13.653225: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:13.698097: embedding
> test_pipeop_isomap.R: 2026-08-01 18:10:13.699324: DONE
> test_pipeop_isomap.R: 2026-08-01 18:10:13.783659: Isomap START
> test_pipeop_isomap.R: 2026-08-01 18:10:13.785614: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:13.796656: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:13.815749: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 18:10:13.871758: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 18:10:13.872504: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:13.891856: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:13.934256: embedding
> test_pipeop_isomap.R: 2026-08-01 18:10:13.93558: DONE
> test_pipeop_isomap.R: 2026-08-01 18:10:14.036419: Isomap START
> test_pipeop_isomap.R: 2026-08-01 18:10:14.036974: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:14.050256: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:14.069695: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 18:10:14.131095: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 18:10:14.131848: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:14.153563: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:14.195264: embedding
> test_pipeop_isomap.R: 2026-08-01 18:10:14.19674: DONE
> test_pipeop_isomap.R: 2026-08-01 18:10:14.305032: Isomap START
> test_pipeop_isomap.R: 2026-08-01 18:10:14.305628: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:14.319539: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:14.338655: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 18:10:14.397403: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 18:10:14.398201: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:14.435524: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:14.480315: embedding
> test_pipeop_isomap.R: 2026-08-01 18:10:14.481746: DONE
> test_pipeop_isomap.R: 2026-08-01 18:10:14.586228: Isomap START
> test_pipeop_isomap.R: 2026-08-01 18:10:14.586744: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:14.598441: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:14.61816: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 18:10:14.716875: Isomap START
> test_pipeop_isomap.R: 2026-08-01 18:10:14.717428: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:14.731281: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:14.749671: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 18:10:14.778496: Isomap START
> test_pipeop_isomap.R: 2026-08-01 18:10:14.778992: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 18:10:14.789703: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 18:10:14.811597: 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_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_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_targetmutate.R:5:3',
'test_pipeop_targettrafo.R:4:3', 'test_pipeop_targettrafoscalerange.R:5:3',
'test_pipeop_task_preproc.R:4:3', 'test_pipeop_task_preproc.R:14:3',
'test_pipeop_nmf.R:6:3', 'test_pipeop_tomek.R:7:3',
'test_pipeop_textvectorizer.R:37:3', 'test_pipeop_textvectorizer.R:186:3',
'test_pipeop_unbranch.R:10:3', 'test_pipeop_updatetarget.R:89:3',
'test_pipeop_vtreat.R:9:3', 'test_pipeop_yeojohnson.R:7:3',
'test_pipeop_tunethreshold.R:111:3', 'test_pipeop_tunethreshold.R:191:3',
'test_ppl.R:63:3', 'test_typecheck.R:188:3'
• Skipping (1): 'test_GraphLearner.R:1278:3'
• empty test (2): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_mlr_graphs_robustify.R:106:3'): Robustify Pipeline Impute Missings ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_mlr_graphs_robustify.R:106:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classbalancing.R:13:3'): PipeOpClassBalancing ───────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classbalancing.R:13:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:17:3'): PipeOpClassWeights ───────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classweights.R:17:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:36:5'): PipeOpClassWeights - weight roles assigned ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_classweights.R:36:5
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:7:3'): PipeOpImputeLearner - simple tests ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:7:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:138:3'): PipeOpImputeLearner - model active binding to state ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:138:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_impute.R:452:3'): impute, test rows and affect_columns ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_impute.R:452:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_missind.R:4:3'): PipeOpMissInd ──────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_missind.R:4:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_unbranch.R:21:3'): PipeOpUnbranch - train and predict ───
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_unbranch.R:21:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:36:3'): threshold works for binary ──────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_tunethreshold.R:36:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:73:3'): tunethreshold graph works ───────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─graph$train(tsk("pima")) at test_pipeop_tunethreshold.R:73:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. └─mlr3::tsk("pima")
5. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
6. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_selector.R:6:3'): Selectors work ───────────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::mlr_tasks$get("pima") at test_selector.R:6:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
[ FAIL 12 | WARN 12 | SKIP 128 | PASS 8462 ]
Error:
! Test failures.
Execution halted
Flavor: r-release-linux-x86_64
Version: 0.11.0
Check: tests
Result: ERROR
Running 'testthat.R' [162s]
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:
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
Saving _problems/test_mlr_graphs_robustify-106.R
> test_multiplicities.R:
> test_multiplicities.R: [[1]]
> test_multiplicities.R:
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
Saving _problems/test_pipeop_classbalancing-13.R
Saving _problems/test_pipeop_classweights-17.R
Saving _problems/test_pipeop_classweights-36.R
Saving _problems/test_pipeop_imputelearner-7.R
Saving _problems/test_pipeop_imputelearner-138.R
> test_pipeop_isomap.R: 2026-08-01 12:50:51.5895: Isomap START
> test_pipeop_isomap.R: 2026-08-01 12:50:51.591062: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:51.606834: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:51.624204: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 12:50:51.688872: Isomap START
> test_pipeop_isomap.R: 2026-08-01 12:50:51.690181: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:51.701566: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:51.718552: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 12:50:51.749011: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 12:50:51.750251: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:51.769293: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:51.806359: embedding
> test_pipeop_isomap.R: 2026-08-01 12:50:51.808221: DONE
> test_pipeop_isomap.R: 2026-08-01 12:50:51.831815: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 12:50:51.832847: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:51.85935: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:51.895435: embedding
> test_pipeop_isomap.R: 2026-08-01 12:50:51.897033: DONE
> test_pipeop_isomap.R: 2026-08-01 12:50:51.981323: Isomap START
> test_pipeop_isomap.R: 2026-08-01 12:50:51.982341: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:52.001087: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-01 12:50:52.081607: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 12:50:52.113306: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 12:50:52.1145: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:52.14924: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:52.316616: embedding
> test_pipeop_isomap.R: 2026-08-01 12:50:52.319415: DONE
> test_pipeop_isomap.R: 2026-08-01 12:50:52.487204: Isomap START
> test_pipeop_isomap.R: 2026-08-01 12:50:52.488329: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:52.500244: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:52.516853: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 12:50:52.550359: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 12:50:52.551612: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:52.570648: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:52.6071: embedding
> test_pipeop_isomap.R: 2026-08-01 12:50:52.615823: DONE
> test_pipeop_isomap.R: 2026-08-01 12:50:52.768373: Isomap START
> test_pipeop_isomap.R: 2026-08-01 12:50:52.769465: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:52.782188: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:52.798075: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 12:50:52.857235: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 12:50:52.858597: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:52.876532: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:52.914563: embedding
> test_pipeop_isomap.R: 2026-08-01 12:50:52.916519: DONE
> test_pipeop_isomap.R: 2026-08-01 12:50:53.387136: Isomap START
> test_pipeop_isomap.R: 2026-08-01 12:50:53.388638: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:53.404008: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:53.422175: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 12:50:53.484139: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 12:50:53.485505: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:53.503109: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:53.547401: embedding
> test_pipeop_isomap.R: 2026-08-01 12:50:53.549609: DONE
> test_pipeop_isomap.R: 2026-08-01 12:50:53.638524: Isomap START
> test_pipeop_isomap.R: 2026-08-01 12:50:53.639826: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:53.65355: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:53.675214: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 12:50:53.739089: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 12:50:53.740504: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:53.762214: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:53.796054: embedding
> test_pipeop_isomap.R: 2026-08-01 12:50:53.798254: DONE
> test_pipeop_isomap.R: 2026-08-01 12:50:53.877245: Isomap START
> test_pipeop_isomap.R: 2026-08-01 12:50:53.878157: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:53.890303: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:53.907188: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 12:50:53.974239: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 12:50:53.975681: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:54.001832: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:54.045533: embedding
> test_pipeop_isomap.R: 2026-08-01 12:50:54.04826: DONE
> test_pipeop_isomap.R: 2026-08-01 12:50:54.172652: Isomap START
> test_pipeop_isomap.R: 2026-08-01 12:50:54.173944: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:54.186791: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:54.205951: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 12:50:54.292579: Isomap START
> test_pipeop_isomap.R: 2026-08-01 12:50:54.293768: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:54.306122: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:54.323972: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 12:50:54.34965: Isomap START
> test_pipeop_isomap.R: 2026-08-01 12:50:54.350835: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 12:50:54.361856: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 12:50:54.379694: 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_nmf.R: [PipeOpNMFstate]
> 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_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_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_ica.R:7:3',
'test_pipeop_featureunion.R:9:3', 'test_pipeop_featureunion.R:134:3',
'test_pipeop_imputelearner.R:43:3', 'test_pipeop_info.R:3:1',
'test_pipeop_impute.R:4:3', 'test_pipeop_kernelpca.R:9:3',
'test_pipeop_isomap.R:10:3', 'test_pipeop_learner.R:17:3',
'test_pipeop_learnerpicvplus.R:2:1', 'test_pipeop_learnercv.R:3:3',
'test_pipeop_learnercv.R:43:3', 'test_pipeop_learnercv.R:73:3',
'test_pipeop_learnercv.R:92:3', 'test_pipeop_learnercv.R:141:3',
'test_pipeop_learnercv.R:157:3', 'test_pipeop_learnercv.R:203:3',
'test_pipeop_learnercv.R:249:3', 'test_pipeop_learnercv.R:278:3',
'test_pipeop_learnercv.R:332:3', 'test_pipeop_learnercv.R:359:3',
'test_pipeop_learnercv.R:389:3', 'test_pipeop_learnercv.R:399:3',
'test_pipeop_learnercv.R:432:3', 'test_pipeop_learnercv.R:472:3',
'test_pipeop_learnercv.R:481:3', 'test_pipeop_learnercv.R:498:3',
'test_pipeop_learnercv.R:506:3', 'test_pipeop_learnercv.R:530:3',
'test_pipeop_learnercv.R:554:3', 'test_pipeop_learnercv.R:634:3',
'test_pipeop_learnercv.R:654:3', 'test_pipeop_learnercv.R:669:3',
'test_pipeop_learnercv.R:754:3', 'test_pipeop_learnercv.R:799:3',
'test_pipeop_learnercv.R:827:3', 'test_pipeop_modelmatrix.R:7:3',
'test_pipeop_multiplicityexply.R:9:3', 'test_pipeop_mutate.R:9:3',
'test_pipeop_nearmiss.R:7:3', 'test_pipeop_multiplicityimply.R:9:3',
'test_pipeop_ovr.R:9:3', 'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3',
'test_pipeop_proxy.R:2:1', 'test_pipeop_quantilebin.R:5:3',
'test_pipeop_randomprojection.R:6:3', 'test_pipeop_randomresponse.R:5:3',
'test_pipeop_removeconstants.R:6:3', 'test_pipeop_renamecolumns.R:6:3',
'test_pipeop_replicate.R:9:3', 'test_pipeop_rowapply.R:6:3',
'test_pipeop_scale.R:6:3', 'test_pipeop_scale.R:10:3',
'test_pipeop_scalemaxabs.R:6:3', 'test_pipeop_scalerange.R:7:3',
'test_pipeop_select.R:9:3', 'test_pipeop_smote.R:10:3',
'test_pipeop_smotenc.R:8:3', 'test_pipeop_spatialsign.R:3:1',
'test_pipeop_splines.R:3:1', 'test_pipeop_subsample.R:6:3',
'test_pipeop_targetinvert.R:4:3', 'test_pipeop_targetmutate.R:5:3',
'test_pipeop_targettrafo.R:4:3', 'test_pipeop_targettrafoscalerange.R:5:3',
'test_pipeop_nmf.R:6:3', 'test_pipeop_task_preproc.R:4:3',
'test_pipeop_task_preproc.R:14:3', 'test_pipeop_tomek.R:7:3',
'test_pipeop_textvectorizer.R:37:3', 'test_pipeop_textvectorizer.R:186:3',
'test_pipeop_unbranch.R:10:3', 'test_pipeop_updatetarget.R:89:3',
'test_pipeop_vtreat.R:9:3', 'test_pipeop_yeojohnson.R:7:3',
'test_pipeop_tunethreshold.R:111:3', 'test_pipeop_tunethreshold.R:191:3',
'test_typecheck.R:188:3', 'test_ppl.R:63:3'
• Skipping (1): 'test_GraphLearner.R:1278:3'
• empty test (2): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_mlr_graphs_robustify.R:106:3'): Robustify Pipeline Impute Missings ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_mlr_graphs_robustify.R:106:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classbalancing.R:13:3'): PipeOpClassBalancing ───────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classbalancing.R:13:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:17:3'): PipeOpClassWeights ───────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classweights.R:17:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:36:5'): PipeOpClassWeights - weight roles assigned ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_classweights.R:36:5
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:7:3'): PipeOpImputeLearner - simple tests ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:7:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:138:3'): PipeOpImputeLearner - model active binding to state ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:138:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_impute.R:452:3'): impute, test rows and affect_columns ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_impute.R:452:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_missind.R:4:3'): PipeOpMissInd ──────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_missind.R:4:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_unbranch.R:21:3'): PipeOpUnbranch - train and predict ───
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_unbranch.R:21:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:36:3'): threshold works for binary ──────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_tunethreshold.R:36:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:73:3'): tunethreshold graph works ───────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─graph$train(tsk("pima")) at test_pipeop_tunethreshold.R:73:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. └─mlr3::tsk("pima")
5. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
6. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_selector.R:6:3'): Selectors work ───────────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::mlr_tasks$get("pima") at test_selector.R:6:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
[ FAIL 12 | WARN 12 | SKIP 128 | PASS 8462 ]
Error:
! Test failures.
Execution halted
Flavor: r-release-windows-x86_64
Version: 0.11.0
Check: tests
Result: ERROR
Running 'testthat.R' [246s]
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: 2026-08-01 03:40:56.270276: Isomap START
> test_pipeop_isomap.R: 2026-08-01 03:40:56.271196: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:56.294067: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:56.314503: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 03:40:56.392983: Isomap START
> test_pipeop_isomap.R: 2026-08-01 03:40:56.393617: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:56.410044: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:56.430508: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 03:40:56.490947: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 03:40:56.491873: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:56.518226: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:56.561664: embedding
> test_pipeop_isomap.R: 2026-08-01 03:40:56.563725: DONE
> test_pipeop_isomap.R: 2026-08-01 03:40:56.612959: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 03:40:56.613701: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:56.639978: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:56.689296: embedding
> test_pipeop_isomap.R: 2026-08-01 03:40:56.691466: DONE
> test_pipeop_isomap.R: 2026-08-01 03:40:56.838446: Isomap START
> test_pipeop_isomap.R: 2026-08-01 03:40:56.839159: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:56.866848: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:56.980388: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 03:40:57.041297: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 03:40:57.042269: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:57.102288: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:57.336164: embedding
> test_pipeop_isomap.R: 2026-08-01 03:40:57.342136: DONE
> test_pipeop_isomap.R: 2026-08-01 03:40:57.609624: Isomap START
> test_pipeop_isomap.R: 2026-08-01 03:40:57.610291: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:57.627978: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:57.651066: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 03:40:57.703811: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 03:40:57.704687: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:57.734262: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:57.783174: embedding
> test_pipeop_isomap.R: 2026-08-01 03:40:57.784993: DONE
> test_pipeop_isomap.R: 2026-08-01 03:40:57.995235: Isomap START
> test_pipeop_isomap.R: 2026-08-01 03:40:57.995889: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:58.011162: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:58.032802: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 03:40:58.109452: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 03:40:58.110322: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:58.134414: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:58.173359: embedding
> test_pipeop_isomap.R: 2026-08-01 03:40:58.175102: DONE
> test_pipeop_isomap.R: 2026-08-01 03:40:58.317028: Isomap START
> test_pipeop_isomap.R: 2026-08-01 03:40:58.31771: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:58.333021: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:58.355853: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 03:40:58.437586: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 03:40:58.438566: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:58.464284: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:58.511559: embedding
> test_pipeop_isomap.R: 2026-08-01 03:40:58.513224: DONE
> test_pipeop_isomap.R: 2026-08-01 03:40:59.186235: Isomap START
> test_pipeop_isomap.R: 2026-08-01 03:40:59.18693: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:59.202815: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:59.224809: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 03:40:59.294492: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 03:40:59.295447: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:59.316135: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-01 03:40:59.363366: embedding
> test_pipeop_isomap.R: 2026-08-01 03:40:59.3649: DONE
> test_pipeop_isomap.R: 2026-08-01 03:40:59.471321: Isomap START
> test_pipeop_isomap.R: 2026-08-01 03:40:59.471796: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:59.483204: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:59.499542: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 03:40:59.577213: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-01 03:40:59.578144: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:59.604367: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:59.649172: embedding
> test_pipeop_isomap.R: 2026-08-01 03:40:59.65098: DONE
> test_pipeop_isomap.R: 2026-08-01 03:40:59.805164: Isomap START
> test_pipeop_isomap.R: 2026-08-01 03:40:59.805862: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:59.824994: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:59.846898: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 03:40:59.954926: Isomap START
> test_pipeop_isomap.R: 2026-08-01 03:40:59.955583: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:40:59.973044: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:40:59.995232: Classical Scaling
> test_pipeop_isomap.R: 2026-08-01 03:41:00.035942: Isomap START
> test_pipeop_isomap.R: 2026-08-01 03:41:00.036582: constructing knn graph
> test_pipeop_isomap.R: 2026-08-01 03:41:00.069748: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-01 03:41:00.091057: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> test_pipeop_nmf.R: [PipeOpNMFstate]
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_nmf.R: [PipeOpNMFstate]
Saving _problems/test_pipeop_unbranch-21.R
Saving _problems/test_pipeop_tunethreshold-36.R
Saving _problems/test_pipeop_tunethreshold-73.R
Saving _problems/test_selector-6.R
[ FAIL 12 | WARN 12 | SKIP 128 | PASS 8462 ]
══ Skipped tests (128) ═════════════════════════════════════════════════════════
• On CRAN (125): 'test_CnfFormula_simplify.R:6:3', 'test_CnfFormula.R:591:3',
'test_Graph.R:283:3', 'test_PipeOp.R:32:1', 'test_GraphLearner.R:5:3',
'test_GraphLearner.R:221:3', 'test_GraphLearner.R:343:3',
'test_GraphLearner.R:408:3', 'test_GraphLearner.R:571:3',
'test_doublearrow.R:2:1', 'test_gunion.R:2:1',
'test_learner_weightedaverage.R:5:3', 'test_learner_weightedaverage.R:57:3',
'test_learner_weightedaverage.R:105:3',
'test_learner_weightedaverage.R:152:3', 'test_meta.R:39:3',
'test_dictionary.R:7:3', 'test_mlr_graphs_branching.R:26:3',
'test_mlr_graphs_bagging.R:6:3', 'test_mlr_graphs_robustify.R:5:3',
'test_pipeop_adas.R:8:3', 'test_pipeop_blsmote.R:8:3',
'test_pipeop_branch.R:4:3', 'test_pipeop_chunk.R:4:3',
'test_pipeop_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_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_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