Last updated on 2026-08-03 15:51:04 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.11.0 | 37.69 | 635.90 | 673.59 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.11.0 | 24.70 | 442.29 | 466.99 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.11.0 | 45.00 | 556.76 | 601.76 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 0.11.0 | 24.00 | 394.10 | 418.10 | 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 | 8.00 | 113.00 | 121.00 | OK | |
| r-oldrel-macos-x86_64 | 0.11.0 | 28.00 | 883.00 | 911.00 | OK | |
| r-oldrel-windows-x86_64 | 0.11.0 | 53.00 | 622.00 | 675.00 | 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 4.583 0.051 5.33
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [359s/184s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ library("paradox")
+ library("mlr3pipelines")
+ test_check("mlr3pipelines")
+ }
Starting 2 test processes.
> test_Graph.R: Training debug.multi with input list(input_1 = 1, input_2 = 1)
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
Saving _problems/test_mlr_graphs_robustify-106.R
> test_multiplicities.R:
> test_multiplicities.R: [[1]]
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> test_multiplicities.R:
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
Saving _problems/test_pipeop_classbalancing-13.R
Saving _problems/test_pipeop_classweights-17.R
Saving _problems/test_pipeop_classweights-36.R
Saving _problems/test_pipeop_imputelearner-7.R
Saving _problems/test_pipeop_imputelearner-138.R
> test_pipeop_isomap.R: 2026-07-31 06:43:36.617018: Isomap START
> test_pipeop_isomap.R: 2026-07-31 06:43:36.617827: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:36.633142: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:36.654827: Classical Scaling
> test_pipeop_isomap.R: 2026-07-31 06:43:36.780957: Isomap START
> test_pipeop_isomap.R: 2026-07-31 06:43:36.781474: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:36.793419: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:36.811696: Classical Scaling
> test_pipeop_isomap.R: 2026-07-31 06:43:36.840388: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-31 06:43:36.841125: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:36.86257: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:36.906624: embedding
> test_pipeop_isomap.R: 2026-07-31 06:43:36.907919: DONE
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-07-31 06:43:37.418873: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-31 06:43:37.420892: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:37.437234: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:37.478839: embedding
> test_pipeop_isomap.R: 2026-07-31 06:43:37.481796: DONE
> test_pipeop_isomap.R: 2026-07-31 06:43:37.571804: Isomap START
> test_pipeop_isomap.R: 2026-07-31 06:43:37.572306: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:37.590622: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:37.689277: Classical Scaling
> test_pipeop_isomap.R: 2026-07-31 06:43:37.728808: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-31 06:43:37.72952: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:37.761497: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:37.952903: embedding
> test_pipeop_isomap.R: 2026-07-31 06:43:37.958455: DONE
> test_pipeop_isomap.R: 2026-07-31 06:43:38.118407: Isomap START
> test_pipeop_isomap.R: 2026-07-31 06:43:38.118884: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:38.131252: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:38.149585: Classical Scaling
> test_pipeop_isomap.R: 2026-07-31 06:43:38.186674: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-31 06:43:38.187399: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:38.209668: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:38.251737: embedding
> test_pipeop_isomap.R: 2026-07-31 06:43:38.253153: DONE
> test_pipeop_isomap.R: 2026-07-31 06:43:38.424376: Isomap START
> test_pipeop_isomap.R: 2026-07-31 06:43:38.424865: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:38.435633: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:38.454302: Classical Scaling
> test_pipeop_isomap.R: 2026-07-31 06:43:38.50506: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-31 06:43:38.505765: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:38.523073: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:38.567753: embedding
> test_pipeop_isomap.R: 2026-07-31 06:43:38.568908: DONE
> test_pipeop_isomap.R: 2026-07-31 06:43:38.653347: Isomap START
> test_pipeop_isomap.R: 2026-07-31 06:43:38.653804: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:38.664252: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:38.682914: Classical Scaling
> test_pipeop_isomap.R: 2026-07-31 06:43:38.736429: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-31 06:43:38.737155: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:38.754354: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:38.796571: embedding
> test_pipeop_isomap.R: 2026-07-31 06:43:38.797725: DONE
> test_pipeop_isomap.R: 2026-07-31 06:43:38.881871: Isomap START
> test_pipeop_isomap.R: 2026-07-31 06:43:38.882347: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:38.894304: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:38.912211: Classical Scaling
> test_pipeop_isomap.R: 2026-07-31 06:43:38.963892: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-31 06:43:38.964578: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:38.983674: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:39.033938: embedding
> test_pipeop_isomap.R: 2026-07-31 06:43:39.035368: DONE
> test_pipeop_isomap.R: 2026-07-31 06:43:39.133988: Isomap START
> test_pipeop_isomap.R: 2026-07-31 06:43:39.134505: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:39.147537: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:39.169274: Classical Scaling
> test_pipeop_isomap.R: 2026-07-31 06:43:39.223018: L-Isomap embed START
> test_pipeop_isomap.R: 2026-07-31 06:43:39.223711: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:39.252853: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:39.292001: embedding
> test_pipeop_isomap.R: 2026-07-31 06:43:39.293215: DONE
> test_pipeop_isomap.R: 2026-07-31 06:43:39.38448: Isomap START
> test_pipeop_isomap.R: 2026-07-31 06:43:39.384911: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:39.394715: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:39.412061: Classical Scaling
> test_pipeop_isomap.R: 2026-07-31 06:43:39.511873: Isomap START
> test_pipeop_isomap.R: 2026-07-31 06:43:39.512345: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:39.522822: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:39.540931: Classical Scaling
> test_pipeop_isomap.R: 2026-07-31 06:43:39.568317: Isomap START
> test_pipeop_isomap.R: 2026-07-31 06:43:39.568812: constructing knn graph
> test_pipeop_isomap.R: 2026-07-31 06:43:39.580723: calculating geodesic distances
> test_pipeop_isomap.R: 2026-07-31 06:43:39.599222: 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:
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_nmf.R: [PipeOpNMFstate]
Saving _problems/test_pipeop_unbranch-21.R
Saving _problems/test_pipeop_tunethreshold-36.R
Saving _problems/test_pipeop_tunethreshold-73.R
Saving _problems/test_selector-6.R
[ FAIL 12 | WARN 21 | SKIP 128 | PASS 8462 ]
══ Skipped tests (128) ═════════════════════════════════════════════════════════
• On CRAN (125): 'test_CnfFormula_simplify.R:6:3', 'test_CnfFormula.R:591:3',
'test_Graph.R:283:3', 'test_PipeOp.R:32:1', 'test_GraphLearner.R:5:3',
'test_GraphLearner.R:221:3', 'test_GraphLearner.R:343:3',
'test_GraphLearner.R:408:3', 'test_GraphLearner.R:571:3',
'test_doublearrow.R:2:1', 'test_gunion.R:2:1',
'test_learner_weightedaverage.R:5:3', 'test_learner_weightedaverage.R:57:3',
'test_learner_weightedaverage.R:105:3',
'test_learner_weightedaverage.R:152:3', 'test_meta.R:39:3',
'test_dictionary.R:7:3', 'test_mlr_graphs_branching.R:26:3',
'test_mlr_graphs_bagging.R:6:3', 'test_mlr_graphs_robustify.R:5:3',
'test_pipeop_adas.R:8:3', 'test_pipeop_blsmote.R:8:3',
'test_pipeop_branch.R:4:3', 'test_pipeop_chunk.R:4:3',
'test_pipeop_classbalancing.R:7:3', 'test_pipeop_boxcox.R:7:3',
'test_pipeop_classweights.R:10:3', 'test_pipeop_classweightsex.R:9:3',
'test_pipeop_colapply.R:9:3', 'test_pipeop_collapsefactors.R:6:3',
'test_pipeop_copy.R:5:3', 'test_pipeop_colroles.R:6:3',
'test_pipeop_decode.R:14:3', 'test_pipeop_encode.R:21:3',
'test_pipeop_datefeatures.R:10:3', 'test_pipeop_encodeimpact.R:11:3',
'test_pipeop_encodepl.R:5:3', 'test_pipeop_encodepl.R:72:3',
'test_pipeop_ensemble.R:3:1', 'test_pipeop_encodelmer.R:15:3',
'test_pipeop_encodelmer.R:37:3', 'test_pipeop_encodelmer.R:80:3',
'test_pipeop_filter.R:7:3', 'test_pipeop_fixfactors.R:9:3',
'test_pipeop_featureunion.R:9:3', 'test_pipeop_featureunion.R:134:3',
'test_pipeop_histbin.R:7:3', 'test_pipeop_ica.R:7:3',
'test_pipeop_imputelearner.R:43:3', 'test_pipeop_info.R:3:1',
'test_pipeop_impute.R:4:3', 'test_pipeop_kernelpca.R:9:3',
'test_pipeop_isomap.R:10:3', 'test_pipeop_learner.R:17:3',
'test_pipeop_learnerpicvplus.R:2:1', 'test_pipeop_learnercv.R:3:3',
'test_pipeop_learnercv.R:43:3', 'test_pipeop_learnercv.R:73:3',
'test_pipeop_learnercv.R:92:3', 'test_pipeop_learnercv.R:141:3',
'test_pipeop_learnercv.R:157:3', 'test_pipeop_learnercv.R:203:3',
'test_pipeop_learnercv.R:249:3', 'test_pipeop_learnercv.R:278:3',
'test_pipeop_learnercv.R:332:3', 'test_pipeop_learnercv.R:359:3',
'test_pipeop_learnercv.R:389:3', 'test_pipeop_learnercv.R:399:3',
'test_pipeop_learnercv.R:432:3', 'test_pipeop_learnercv.R:472:3',
'test_pipeop_learnercv.R:481:3', 'test_pipeop_learnercv.R:498:3',
'test_pipeop_learnercv.R:506:3', 'test_pipeop_learnercv.R:530:3',
'test_pipeop_learnercv.R:554:3', 'test_pipeop_learnercv.R:634:3',
'test_pipeop_learnercv.R:654:3', 'test_pipeop_learnercv.R:669:3',
'test_pipeop_learnercv.R:754:3', 'test_pipeop_learnercv.R:799:3',
'test_pipeop_learnercv.R:827:3', 'test_pipeop_modelmatrix.R:7:3',
'test_pipeop_multiplicityexply.R:9:3', 'test_pipeop_mutate.R:9:3',
'test_pipeop_nearmiss.R:7:3', 'test_pipeop_multiplicityimply.R:9:3',
'test_pipeop_ovr.R:9:3', 'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3',
'test_pipeop_proxy.R:2:1', 'test_pipeop_quantilebin.R:5:3',
'test_pipeop_randomprojection.R:6:3', 'test_pipeop_randomresponse.R:5:3',
'test_pipeop_removeconstants.R:6:3', 'test_pipeop_renamecolumns.R:6:3',
'test_pipeop_replicate.R:9:3', 'test_pipeop_rowapply.R:6:3',
'test_pipeop_scale.R:6:3', 'test_pipeop_scale.R:10:3',
'test_pipeop_scalemaxabs.R:6:3', 'test_pipeop_scalerange.R:7:3',
'test_pipeop_select.R:9:3', 'test_pipeop_smote.R:10:3',
'test_pipeop_smotenc.R:8:3', 'test_pipeop_spatialsign.R:3:1',
'test_pipeop_splines.R:3:1', 'test_pipeop_subsample.R:6:3',
'test_pipeop_targetinvert.R:4:3', 'test_pipeop_targetmutate.R:5:3',
'test_pipeop_targettrafo.R:4:3', 'test_pipeop_targettrafoscalerange.R:5:3',
'test_pipeop_task_preproc.R:4:3', 'test_pipeop_task_preproc.R:14:3',
'test_pipeop_nmf.R:6:3', 'test_pipeop_textvectorizer.R:37:3',
'test_pipeop_textvectorizer.R:186:3', 'test_pipeop_tomek.R:7:3',
'test_pipeop_unbranch.R:10:3', 'test_pipeop_updatetarget.R:89:3',
'test_pipeop_vtreat.R:9:3', 'test_pipeop_yeojohnson.R:7:3',
'test_pipeop_tunethreshold.R:111:3', 'test_pipeop_tunethreshold.R:191:3',
'test_ppl.R:63:3', 'test_typecheck.R:188:3'
• Skipping (1): 'test_GraphLearner.R:1278:3'
• empty test (2): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_mlr_graphs_robustify.R:106:3'): Robustify Pipeline Impute Missings ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_mlr_graphs_robustify.R:106:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classbalancing.R:13:3'): PipeOpClassBalancing ───────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classbalancing.R:13:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:17:3'): PipeOpClassWeights ───────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classweights.R:17:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:36:5'): PipeOpClassWeights - weight roles assigned ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_classweights.R:36:5
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:7:3'): PipeOpImputeLearner - simple tests ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:7:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:138:3'): PipeOpImputeLearner - model active binding to state ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:138:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_impute.R:452:3'): impute, test rows and affect_columns ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_impute.R:452:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_missind.R:4:3'): PipeOpMissInd ──────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_missind.R:4:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_unbranch.R:21:3'): PipeOpUnbranch - train and predict ───
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_unbranch.R:21:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:36:3'): threshold works for binary ──────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_tunethreshold.R:36:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:73:3'): tunethreshold graph works ───────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─graph$train(tsk("pima")) at test_pipeop_tunethreshold.R:73:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. └─mlr3::tsk("pima")
5. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
6. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_selector.R:6:3'): Selectors work ───────────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::mlr_tasks$get("pima") at test_selector.R:6:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
[ FAIL 12 | WARN 21 | SKIP 128 | PASS 8462 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.11.0
Check: examples
Result: ERROR
Running examples in ‘mlr3pipelines-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: mlr_pipeops_imputeconstant
> ### Title: Impute Features by a Constant
> ### Aliases: mlr_pipeops_imputeconstant PipeOpImputeConstant
>
> ### ** Examples
>
> library("mlr3")
>
> task = tsk("pima")
Warning in data(list = id, package = package, envir = ee) :
data set ‘PimaIndiansDiabetes2’ not found
Error in UseMethod("as_data_backend") :
no applicable method for 'as_data_backend' applied to an object of class "NULL"
Calls: tsk ... dictionary_initialize_item -> do.call -> <Anonymous> -> as_data_backend
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [264s/131s]
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: 2026-08-02 18:15:24.560034: Isomap START
> test_pipeop_isomap.R: 2026-08-02 18:15:24.560961: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:24.574474: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:24.588872: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 18:15:24.629695: Isomap START
> test_pipeop_isomap.R: 2026-08-02 18:15:24.630252: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:24.639636: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:24.653985: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 18:15:24.716197: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 18:15:24.716945: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:24.733426: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:24.766192: embedding
> test_pipeop_isomap.R: 2026-08-02 18:15:24.767302: DONE
> test_pipeop_isomap.R: 2026-08-02 18:15:24.78725: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 18:15:24.787747: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:24.801273: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:24.834333: embedding
> test_pipeop_isomap.R: 2026-08-02 18:15:24.835358: DONE
> test_pipeop_isomap.R: 2026-08-02 18:15:24.900359: Isomap START
> test_pipeop_isomap.R: 2026-08-02 18:15:24.900844: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:24.914404: calculating geodesic distances
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-02 18:15:25.003635: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 18:15:25.035891: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 18:15:25.036594: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:25.067018: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:25.240479: embedding
> test_pipeop_isomap.R: 2026-08-02 18:15:25.26681: DONE
> test_pipeop_isomap.R: 2026-08-02 18:15:25.390488: Isomap START
> test_pipeop_isomap.R: 2026-08-02 18:15:25.390943: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:25.402097: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:25.416557: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 18:15:25.441741: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 18:15:25.442518: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:25.459523: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:25.492581: embedding
> test_pipeop_isomap.R: 2026-08-02 18:15:25.493869: DONE
> test_pipeop_isomap.R: 2026-08-02 18:15:25.618533: Isomap START
> test_pipeop_isomap.R: 2026-08-02 18:15:25.619006: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:25.628583: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:25.64208: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 18:15:25.68174: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 18:15:25.682464: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:25.696311: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:25.726785: embedding
> test_pipeop_isomap.R: 2026-08-02 18:15:25.727862: DONE
> test_pipeop_isomap.R: 2026-08-02 18:15:25.801589: Isomap START
> test_pipeop_isomap.R: 2026-08-02 18:15:25.802071: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:25.810949: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:25.824985: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 18:15:25.864789: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 18:15:25.865423: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:25.87941: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:25.912033: embedding
> test_pipeop_isomap.R: 2026-08-02 18:15:25.913048: DONE
> test_pipeop_isomap.R: 2026-08-02 18:15:25.971656: Isomap START
> test_pipeop_isomap.R: 2026-08-02 18:15:25.972106: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:25.980706: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:25.995182: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 18:15:26.033442: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 18:15:26.034101: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:26.047685: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:26.078968: embedding
> test_pipeop_isomap.R: 2026-08-02 18:15:26.080014: DONE
> test_pipeop_isomap.R: 2026-08-02 18:15:26.137523: Isomap START
> test_pipeop_isomap.R: 2026-08-02 18:15:26.137985: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:26.146315: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:26.160564: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 18:15:26.196783: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 18:15:26.19743: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:26.222767: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:26.254644: embedding
> test_pipeop_isomap.R: 2026-08-02 18:15:26.255774: DONE
> test_pipeop_isomap.R: 2026-08-02 18:15:26.316684: Isomap START
> test_pipeop_isomap.R: 2026-08-02 18:15:26.31716: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:26.325467: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:26.338758: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 18:15:26.39836: Isomap START
> test_pipeop_isomap.R: 2026-08-02 18:15:26.398827: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:26.407316: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:26.420927: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 18:15:26.438881: Isomap START
> test_pipeop_isomap.R: 2026-08-02 18:15:26.439312: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 18:15:26.447003: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 18:15:26.461281: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> test_pipeop_nmf.R: [PipeOpNMFstate]
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_nmf.R: [PipeOpNMFstate]
Saving _problems/test_pipeop_unbranch-21.R
Saving _problems/test_pipeop_tunethreshold-36.R
Saving _problems/test_pipeop_tunethreshold-73.R
Saving _problems/test_selector-6.R
[ FAIL 12 | WARN 21 | SKIP 128 | PASS 8462 ]
══ Skipped tests (128) ═════════════════════════════════════════════════════════
• On CRAN (125): 'test_CnfFormula_simplify.R:6:3', 'test_CnfFormula.R:591:3',
'test_Graph.R:283:3', 'test_PipeOp.R:32:1', 'test_GraphLearner.R:5:3',
'test_GraphLearner.R:221:3', 'test_GraphLearner.R:343:3',
'test_GraphLearner.R:408:3', 'test_GraphLearner.R:571:3',
'test_doublearrow.R:2:1', 'test_gunion.R:2:1',
'test_learner_weightedaverage.R:5:3', 'test_learner_weightedaverage.R:57:3',
'test_learner_weightedaverage.R:105:3',
'test_learner_weightedaverage.R:152:3', 'test_meta.R:39:3',
'test_dictionary.R:7:3', 'test_mlr_graphs_branching.R:26:3',
'test_mlr_graphs_bagging.R:6:3', 'test_mlr_graphs_robustify.R:5:3',
'test_pipeop_adas.R:8:3', 'test_pipeop_blsmote.R:8:3',
'test_pipeop_branch.R:4:3', 'test_pipeop_chunk.R:4:3',
'test_pipeop_boxcox.R:7:3', 'test_pipeop_classbalancing.R:7:3',
'test_pipeop_classweights.R:10:3', 'test_pipeop_classweightsex.R:9:3',
'test_pipeop_colapply.R:9:3', 'test_pipeop_collapsefactors.R:6:3',
'test_pipeop_copy.R:5:3', 'test_pipeop_colroles.R:6:3',
'test_pipeop_decode.R:14:3', 'test_pipeop_encode.R:21:3',
'test_pipeop_datefeatures.R:10:3', 'test_pipeop_encodeimpact.R:11:3',
'test_pipeop_encodelmer.R:15:3', 'test_pipeop_encodelmer.R:37:3',
'test_pipeop_encodelmer.R:80:3', 'test_pipeop_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_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_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 21 | SKIP 128 | PASS 8462 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.11.0
Check: for new files in some other directories
Result: NOTE
Found the following files/directories:
‘~/tmp/scratch/Rtmp0289ke’ ‘~/tmp/scratch/Rtmp0Md8Ui’
‘~/tmp/scratch/Rtmp0XLWTH’ ‘~/tmp/scratch/Rtmp0goRj4’
‘~/tmp/scratch/Rtmp1NASZs’ ‘~/tmp/scratch/Rtmp1PkjCZ’
‘~/tmp/scratch/Rtmp1VsDfQ’ ‘~/tmp/scratch/Rtmp1fcB9S’
‘~/tmp/scratch/Rtmp1qUwQQ’ ‘~/tmp/scratch/Rtmp2uPSom’
‘~/tmp/scratch/Rtmp3oRHIg’ ‘~/tmp/scratch/Rtmp4S67Nu’
‘~/tmp/scratch/Rtmp4bSQRr’ ‘~/tmp/scratch/Rtmp5HMzRO’
‘~/tmp/scratch/Rtmp5Sn99r’ ‘~/tmp/scratch/Rtmp5x29DN’
‘~/tmp/scratch/Rtmp61bvkf’ ‘~/tmp/scratch/Rtmp6weB3n’
‘~/tmp/scratch/Rtmp7H9qbw’ ‘~/tmp/scratch/Rtmp83wqLb’
‘~/tmp/scratch/Rtmp8V8YY4’ ‘~/tmp/scratch/Rtmp8ibMYe’
‘~/tmp/scratch/Rtmp9JU4R9’ ‘~/tmp/scratch/Rtmp9YQQtI’
‘~/tmp/scratch/Rtmp9ZCGBP’ ‘~/tmp/scratch/Rtmp9zOycq’
‘~/tmp/scratch/RtmpA4Hl1T’ ‘~/tmp/scratch/RtmpARArEV’
‘~/tmp/scratch/RtmpAg03n3’ ‘~/tmp/scratch/RtmpAnZEdQ’
‘~/tmp/scratch/RtmpAuIMwr’ ‘~/tmp/scratch/RtmpBNgkrb’
‘~/tmp/scratch/RtmpBzb4YM’ ‘~/tmp/scratch/RtmpCHwJ4r’
‘~/tmp/scratch/RtmpCLeFFp’ ‘~/tmp/scratch/RtmpCsHXmC’
‘~/tmp/scratch/RtmpDHIHt4’ ‘~/tmp/scratch/RtmpDfLFFB’
‘~/tmp/scratch/RtmpDyqrwo’ ‘~/tmp/scratch/RtmpETYZN7’
‘~/tmp/scratch/RtmpEUu1LM’ ‘~/tmp/scratch/RtmpEZPQRZ’
‘~/tmp/scratch/RtmpEaPB3q’ ‘~/tmp/scratch/RtmpEbJrXI’
‘~/tmp/scratch/RtmpEjD88J’ ‘~/tmp/scratch/RtmpF2r78V’
‘~/tmp/scratch/RtmpFjnfVK’ ‘~/tmp/scratch/RtmpG1yqDi’
‘~/tmp/scratch/RtmpGGDhel’ ‘~/tmp/scratch/RtmpGOt5I9’
‘~/tmp/scratch/RtmpGlx7IB’ ‘~/tmp/scratch/RtmpGtV4q1’
‘~/tmp/scratch/RtmpHWmaEW’ ‘~/tmp/scratch/RtmpHlS1jW’
‘~/tmp/scratch/RtmpHvdvEh’ ‘~/tmp/scratch/RtmpHy73Up’
‘~/tmp/scratch/RtmpHzo3od’ ‘~/tmp/scratch/RtmpIPJtTp’
‘~/tmp/scratch/RtmpISVJEO’ ‘~/tmp/scratch/RtmpIY2NJz’
‘~/tmp/scratch/RtmpIttjnV’ ‘~/tmp/scratch/RtmpJAW4BX’
‘~/tmp/scratch/RtmpJIqxuP’ ‘~/tmp/scratch/RtmpL1JuJq’
‘~/tmp/scratch/RtmpLSOqvR’ ‘~/tmp/scratch/RtmpLmoI8z’
‘~/tmp/scratch/RtmpM0jSUJ’ ‘~/tmp/scratch/RtmpMLn40N’
‘~/tmp/scratch/RtmpMkiT4d’ ‘~/tmp/scratch/RtmpMxu27R’
‘~/tmp/scratch/RtmpNciH1D’ ‘~/tmp/scratch/RtmpNd2LVA’
‘~/tmp/scratch/RtmpOeKC1V’ ‘~/tmp/scratch/RtmpPCVNv9’
‘~/tmp/scratch/RtmpPi5Hs9’ ‘~/tmp/scratch/RtmpPr2kak’
‘~/tmp/scratch/RtmpPsG8mp’ ‘~/tmp/scratch/RtmpQI3V1J’
‘~/tmp/scratch/RtmpQLAMR5’ ‘~/tmp/scratch/RtmpQVGWXQ’
‘~/tmp/scratch/RtmpQYH152’ ‘~/tmp/scratch/RtmpRBad6Q’
‘~/tmp/scratch/RtmpSEuY0d’ ‘~/tmp/scratch/RtmpSNkV4m’
‘~/tmp/scratch/RtmpT2CAm0’ ‘~/tmp/scratch/RtmpTlvf6x’
‘~/tmp/scratch/RtmpUAA9Mo’ ‘~/tmp/scratch/RtmpUFh4RL’
‘~/tmp/scratch/RtmpUxJGBu’ ‘~/tmp/scratch/RtmpV88st0’
‘~/tmp/scratch/RtmpVexwRg’ ‘~/tmp/scratch/RtmpVhBkyo’
‘~/tmp/scratch/RtmpVu6dJk’ ‘~/tmp/scratch/RtmpVzO2oQ’
‘~/tmp/scratch/RtmpWLqLEa’ ‘~/tmp/scratch/RtmpWnIwvS’
‘~/tmp/scratch/RtmpWwC3r6’ ‘~/tmp/scratch/RtmpX3KOPb’
‘~/tmp/scratch/RtmpXbxpIG’ ‘~/tmp/scratch/RtmpXdAnog’
‘~/tmp/scratch/RtmpYHfkmF’ ‘~/tmp/scratch/RtmpZ4Uhqk’
‘~/tmp/scratch/RtmpZ5BUdq’ ‘~/tmp/scratch/RtmpZOj8Gc’
‘~/tmp/scratch/RtmpZZpWrW’ ‘~/tmp/scratch/RtmpbEiHHO’
‘~/tmp/scratch/Rtmpbkzoyp’ ‘~/tmp/scratch/Rtmpc3QvNQ’
‘~/tmp/scratch/RtmpcDvU3B’ ‘~/tmp/scratch/RtmpcLeiuE’
‘~/tmp/scratch/RtmpcmYHa9’ ‘~/tmp/scratch/RtmpcqDIWH’
‘~/tmp/scratch/Rtmpd9MIwz’ ‘~/tmp/scratch/RtmpdH9shI’
‘~/tmp/scratch/RtmpdxYiBs’ ‘~/tmp/scratch/RtmpenguUJ’
‘~/tmp/scratch/RtmpeySa3X’ ‘~/tmp/scratch/Rtmpf8cUjn’
‘~/tmp/scratch/Rtmpg0Aaha’ ‘~/tmp/scratch/RtmpgA0BSu’
‘~/tmp/scratch/RtmpgRvb0d’ ‘~/tmp/scratch/RtmpgdFn6P’
‘~/tmp/scratch/RtmpgfX58Z’ ‘~/tmp/scratch/RtmpggbZNw’
‘~/tmp/scratch/RtmpgkLeCC’ ‘~/tmp/scratch/Rtmph0TL2B’
‘~/tmp/scratch/Rtmpi4tL9c’ ‘~/tmp/scratch/RtmpixcKPn’
‘~/tmp/scratch/RtmpjcT0eW’ ‘~/tmp/scratch/RtmpjyNkye’
‘~/tmp/scratch/Rtmpk642xN’ ‘~/tmp/scratch/RtmpkkpI4Y’
‘~/tmp/scratch/RtmpksVIMQ’ ‘~/tmp/scratch/Rtmpl2i91X’
‘~/tmp/scratch/RtmplQAxJj’ ‘~/tmp/scratch/Rtmplgld5w’
‘~/tmp/scratch/Rtmplw3QCX’ ‘~/tmp/scratch/RtmpmSwooB’
‘~/tmp/scratch/RtmpnFWC3d’ ‘~/tmp/scratch/RtmpnFppiG’
‘~/tmp/scratch/RtmpnHb57N’ ‘~/tmp/scratch/RtmpnYDDzA’
‘~/tmp/scratch/RtmpnZScIJ’ ‘~/tmp/scratch/Rtmpnfsv2w’
‘~/tmp/scratch/RtmpngzrU5’ ‘~/tmp/scratch/Rtmpni5EaS’
‘~/tmp/scratch/RtmpnqWtAu’ ‘~/tmp/scratch/Rtmpo6sRyl’
‘~/tmp/scratch/RtmpoUTECh’ ‘~/tmp/scratch/RtmpoXLQ3e’
‘~/tmp/scratch/Rtmpod27BE’ ‘~/tmp/scratch/Rtmpon1q3k’
‘~/tmp/scratch/RtmppKph2G’ ‘~/tmp/scratch/RtmppMJCev’
‘~/tmp/scratch/RtmppQGPXC’ ‘~/tmp/scratch/RtmppTvi5i’
‘~/tmp/scratch/Rtmpprrdhv’ ‘~/tmp/scratch/RtmppwgzgE’
‘~/tmp/scratch/Rtmpq0r91I’ ‘~/tmp/scratch/RtmpqDq46H’
‘~/tmp/scratch/RtmpqHuaZJ’ ‘~/tmp/scratch/RtmpqLjVik’
‘~/tmp/scratch/Rtmpqm6Ugd’ ‘~/tmp/scratch/RtmprEmLid’
‘~/tmp/scratch/Rtmprj14uo’ ‘~/tmp/scratch/RtmpsaJuVO’
‘~/tmp/scratch/RtmpsjMDR3’ ‘~/tmp/scratch/RtmpsuKrLa’
‘~/tmp/scratch/Rtmpt7sP4P’ ‘~/tmp/scratch/RtmptFZcaN’
‘~/tmp/scratch/RtmptGlfhY’ ‘~/tmp/scratch/RtmpthaTgg’
‘~/tmp/scratch/RtmptnQZ8Z’ ‘~/tmp/scratch/RtmpuD9Oep’
‘~/tmp/scratch/RtmpuYCM9e’ ‘~/tmp/scratch/RtmpvSrN5i’
‘~/tmp/scratch/RtmpvTzttu’ ‘~/tmp/scratch/RtmpvXyw2G’
‘~/tmp/scratch/RtmpvfmHr4’ ‘~/tmp/scratch/Rtmpwnu6lY’
‘~/tmp/scratch/RtmpxJWl9C’ ‘~/tmp/scratch/RtmpxNZP88’
‘~/tmp/scratch/RtmpxjDKwr’ ‘~/tmp/scratch/RtmpyHgCqi’
‘~/tmp/scratch/RtmpzVZVfY’ ‘~/tmp/scratch/RtmpzY4BTV’
‘~/tmp/scratch/RtmpzpTzPu’ ‘~/tmp/scratch/Rtmpzv7qz1’
‘~/tmp/scratch/Rtmpzxuouy’ ‘~/tmp/scratch/RtmpzzVGdn’
‘~/tmp/scratch/quarto-sessioneae617b641d51714’
‘~/tmp/scratch/xvfb-run.0MQ84t’ ‘~/tmp/scratch/xvfb-run.1IweUP’
‘~/tmp/scratch/xvfb-run.1KTY06’ ‘~/tmp/scratch/xvfb-run.1P7IuL’
‘~/tmp/scratch/xvfb-run.1rCwKX’ ‘~/tmp/scratch/xvfb-run.2FhbbG’
‘~/tmp/scratch/xvfb-run.3BMJTC’ ‘~/tmp/scratch/xvfb-run.3drPv8’
‘~/tmp/scratch/xvfb-run.4HZYjz’ ‘~/tmp/scratch/xvfb-run.4i1rJi’
‘~/tmp/scratch/xvfb-run.5JDntH’ ‘~/tmp/scratch/xvfb-run.6Rc7xQ’
‘~/tmp/scratch/xvfb-run.8B2fRv’ ‘~/tmp/scratch/xvfb-run.97kDg2’
‘~/tmp/scratch/xvfb-run.9R67eD’ ‘~/tmp/scratch/xvfb-run.C88ijI’
‘~/tmp/scratch/xvfb-run.D5VQRp’ ‘~/tmp/scratch/xvfb-run.EDAalK’
‘~/tmp/scratch/xvfb-run.EJWSm0’ ‘~/tmp/scratch/xvfb-run.KwqhT2’
‘~/tmp/scratch/xvfb-run.LWDFzE’ ‘~/tmp/scratch/xvfb-run.MCZSGu’
‘~/tmp/scratch/xvfb-run.MgopEr’ ‘~/tmp/scratch/xvfb-run.Mk7aUF’
‘~/tmp/scratch/xvfb-run.NGHuaS’ ‘~/tmp/scratch/xvfb-run.NHKdc8’
‘~/tmp/scratch/xvfb-run.OHF3z8’ ‘~/tmp/scratch/xvfb-run.R0vYng’
‘~/tmp/scratch/xvfb-run.RllwRL’ ‘~/tmp/scratch/xvfb-run.SIgTux’
‘~/tmp/scratch/xvfb-run.TFRQJg’ ‘~/tmp/scratch/xvfb-run.TGzffK’
‘~/tmp/scratch/xvfb-run.VKCsAA’ ‘~/tmp/scratch/xvfb-run.VyjrNA’
‘~/tmp/scratch/xvfb-run.WTV75T’ ‘~/tmp/scratch/xvfb-run.WVR0jM’
‘~/tmp/scratch/xvfb-run.Ww4u6f’ ‘~/tmp/scratch/xvfb-run.dJXvVi’
‘~/tmp/scratch/xvfb-run.dNfKxW’ ‘~/tmp/scratch/xvfb-run.dhc9v5’
‘~/tmp/scratch/xvfb-run.eVS6v6’ ‘~/tmp/scratch/xvfb-run.eXzpAl’
‘~/tmp/scratch/xvfb-run.ed6gfN’ ‘~/tmp/scratch/xvfb-run.ejrbbI’
‘~/tmp/scratch/xvfb-run.fjWkcx’ ‘~/tmp/scratch/xvfb-run.gks4aB’
‘~/tmp/scratch/xvfb-run.h4J8MI’ ‘~/tmp/scratch/xvfb-run.jJ0Ike’
‘~/tmp/scratch/xvfb-run.jf3ocp’ ‘~/tmp/scratch/xvfb-run.l5yZY7’
‘~/tmp/scratch/xvfb-run.lWcQQ0’ ‘~/tmp/scratch/xvfb-run.m6MlZ9’
‘~/tmp/scratch/xvfb-run.mxVcal’ ‘~/tmp/scratch/xvfb-run.oEPhxA’
‘~/tmp/scratch/xvfb-run.p94Oy6’ ‘~/tmp/scratch/xvfb-run.pilECr’
‘~/tmp/scratch/xvfb-run.psfAIj’ ‘~/tmp/scratch/xvfb-run.qHdEhL’
‘~/tmp/scratch/xvfb-run.qeKhwN’ ‘~/tmp/scratch/xvfb-run.qnUOkw’
‘~/tmp/scratch/xvfb-run.qoY7R4’ ‘~/tmp/scratch/xvfb-run.r1J0qr’
‘~/tmp/scratch/xvfb-run.uU87HV’ ‘~/tmp/scratch/xvfb-run.uUx5H5’
‘~/tmp/scratch/xvfb-run.umSHi8’ ‘~/tmp/scratch/xvfb-run.vQlLap’
‘~/tmp/scratch/xvfb-run.vWWm5L’ ‘~/tmp/scratch/xvfb-run.vuYOmw’
‘~/tmp/scratch/xvfb-run.wCs21c’ ‘~/tmp/scratch/xvfb-run.wQEWl8’
‘~/tmp/scratch/xvfb-run.wltCZ6’ ‘~/tmp/scratch/xvfb-run.wzFKbf’
‘~/tmp/scratch/xvfb-run.xrPZvW’ ‘~/tmp/scratch/xvfb-run.zTx0Gi’
‘/dev/shm/sm_segment.gimli1.1001.45b50000.0’
‘~/.cache/pocl/uncached/tempfile_0zQPeX’
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’ [312s/152s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ library("paradox")
+ library("mlr3pipelines")
+ test_check("mlr3pipelines")
+ }
Starting 2 test processes.
> test_Graph.R: Training debug.multi with input list(input_1 = 1, input_2 = 1)
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
Saving _problems/test_mlr_graphs_robustify-106.R
> test_multiplicities.R:
> test_multiplicities.R: [[1]]
> test_multiplicities.R: [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: 2026-08-02 07:13:57.195433: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:13:57.19621: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:57.209267: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:57.227426: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:13:57.294144: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:13:57.294683: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:57.307184: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:57.324643: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:13:57.355891: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:13:57.356704: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:57.378521: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:57.419301: embedding
> test_pipeop_isomap.R: 2026-08-02 07:13:57.420832: DONE
> test_pipeop_isomap.R: 2026-08-02 07:13:57.452342: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:13:57.452951: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:57.473688: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:57.514658: embedding
> test_pipeop_isomap.R: 2026-08-02 07:13:57.516152: DONE
> test_pipeop_isomap.R: 2026-08-02 07:13:57.614123: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:13:57.614657: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:57.644676: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:57.744738: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:13:57.777888: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:13:57.778601: constructing knn graph
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-02 07:13:57.807764: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:58.007207: embedding
> test_pipeop_isomap.R: 2026-08-02 07:13:58.011271: DONE
> test_pipeop_isomap.R: 2026-08-02 07:13:58.146867: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:13:58.14734: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:58.157447: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:58.175404: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:13:58.206554: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:13:58.207285: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:58.629354: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:58.672292: embedding
> test_pipeop_isomap.R: 2026-08-02 07:13:58.67351: DONE
> test_pipeop_isomap.R: 2026-08-02 07:13:58.802154: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:13:58.802637: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:58.812572: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:58.830756: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:13:58.875257: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:13:58.875952: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:58.892575: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:58.935195: embedding
> test_pipeop_isomap.R: 2026-08-02 07:13:58.936376: DONE
> test_pipeop_isomap.R: 2026-08-02 07:13:59.009979: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:13:59.010437: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:59.020408: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:59.03853: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:13:59.083606: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:13:59.084298: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:59.100646: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:59.14309: embedding
> test_pipeop_isomap.R: 2026-08-02 07:13:59.144319: DONE
> test_pipeop_isomap.R: 2026-08-02 07:13:59.223066: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:13:59.223585: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:59.234285: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:59.252611: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:13:59.302087: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:13:59.3028: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:59.320843: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:59.362739: embedding
> test_pipeop_isomap.R: 2026-08-02 07:13:59.364351: DONE
> test_pipeop_isomap.R: 2026-08-02 07:13:59.459907: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:13:59.460482: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:59.473955: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:59.491927: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:13:59.550699: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:13:59.551517: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:59.583249: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:59.626446: embedding
> test_pipeop_isomap.R: 2026-08-02 07:13:59.627714: DONE
> test_pipeop_isomap.R: 2026-08-02 07:13:59.716309: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:13:59.716883: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:59.727412: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:59.745489: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:13:59.821687: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:13:59.822158: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:59.83212: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:59.850172: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:13:59.873197: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:13:59.873652: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:13:59.88309: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:13:59.901573: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> test_pipeop_nmf.R: [PipeOpNMFstate]
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_nmf.R: [PipeOpNMFstate]
Saving _problems/test_pipeop_unbranch-21.R
Saving _problems/test_pipeop_tunethreshold-36.R
Saving _problems/test_pipeop_tunethreshold-73.R
Saving _problems/test_selector-6.R
[ FAIL 12 | WARN 21 | SKIP 128 | PASS 8462 ]
══ Skipped tests (128) ═════════════════════════════════════════════════════════
• On CRAN (125): 'test_CnfFormula_simplify.R:6:3', 'test_CnfFormula.R:591:3',
'test_Graph.R:283:3', 'test_PipeOp.R:32:1', 'test_GraphLearner.R:5:3',
'test_GraphLearner.R:221:3', 'test_GraphLearner.R:343:3',
'test_GraphLearner.R:408:3', 'test_GraphLearner.R:571:3',
'test_doublearrow.R:2:1', 'test_gunion.R:2:1',
'test_learner_weightedaverage.R:5:3', 'test_learner_weightedaverage.R:57:3',
'test_learner_weightedaverage.R:105:3',
'test_learner_weightedaverage.R:152:3', 'test_dictionary.R:7:3',
'test_meta.R:39:3', 'test_mlr_graphs_branching.R:26:3',
'test_mlr_graphs_bagging.R:6:3', 'test_mlr_graphs_robustify.R:5:3',
'test_pipeop_adas.R:8:3', 'test_pipeop_blsmote.R:8:3',
'test_pipeop_branch.R:4:3', 'test_pipeop_chunk.R:4:3',
'test_pipeop_classbalancing.R:7:3', 'test_pipeop_classweights.R:10:3',
'test_pipeop_boxcox.R:7:3', 'test_pipeop_classweightsex.R:9:3',
'test_pipeop_colapply.R:9:3', 'test_pipeop_collapsefactors.R:6:3',
'test_pipeop_copy.R:5:3', 'test_pipeop_colroles.R:6:3',
'test_pipeop_decode.R:14:3', 'test_pipeop_encode.R:21:3',
'test_pipeop_datefeatures.R:10:3', 'test_pipeop_encodeimpact.R:11:3',
'test_pipeop_encodepl.R:5:3', 'test_pipeop_encodepl.R:72:3',
'test_pipeop_ensemble.R:3:1', 'test_pipeop_encodelmer.R:15:3',
'test_pipeop_encodelmer.R:37:3', 'test_pipeop_encodelmer.R:80:3',
'test_pipeop_filter.R:7:3', 'test_pipeop_fixfactors.R:9:3',
'test_pipeop_histbin.R:7:3', 'test_pipeop_ica.R:7:3',
'test_pipeop_featureunion.R:9:3', 'test_pipeop_featureunion.R:134:3',
'test_pipeop_imputelearner.R:43:3', 'test_pipeop_info.R:3:1',
'test_pipeop_impute.R:4:3', 'test_pipeop_kernelpca.R:9:3',
'test_pipeop_isomap.R:10:3', 'test_pipeop_learner.R:17:3',
'test_pipeop_learnerpicvplus.R:2:1', 'test_pipeop_learnercv.R:3:3',
'test_pipeop_learnercv.R:43:3', 'test_pipeop_learnercv.R:73:3',
'test_pipeop_learnercv.R:92:3', 'test_pipeop_learnercv.R:141:3',
'test_pipeop_learnercv.R:157:3', 'test_pipeop_learnercv.R:203:3',
'test_pipeop_learnercv.R:249:3', 'test_pipeop_learnercv.R:278:3',
'test_pipeop_learnercv.R:332:3', 'test_pipeop_learnercv.R:359:3',
'test_pipeop_learnercv.R:389:3', 'test_pipeop_learnercv.R:399:3',
'test_pipeop_learnercv.R:432:3', 'test_pipeop_learnercv.R:472:3',
'test_pipeop_learnercv.R:481:3', 'test_pipeop_learnercv.R:498:3',
'test_pipeop_learnercv.R:506:3', 'test_pipeop_learnercv.R:530:3',
'test_pipeop_learnercv.R:554:3', 'test_pipeop_learnercv.R:634:3',
'test_pipeop_learnercv.R:654:3', 'test_pipeop_learnercv.R:669:3',
'test_pipeop_learnercv.R:754:3', 'test_pipeop_learnercv.R:799:3',
'test_pipeop_learnercv.R:827:3', 'test_pipeop_modelmatrix.R:7:3',
'test_pipeop_multiplicityexply.R:9:3', 'test_pipeop_mutate.R:9:3',
'test_pipeop_nearmiss.R:7:3', 'test_pipeop_multiplicityimply.R:9:3',
'test_pipeop_ovr.R:9:3', 'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3',
'test_pipeop_proxy.R:2:1', 'test_pipeop_quantilebin.R:5:3',
'test_pipeop_randomprojection.R:6:3', 'test_pipeop_randomresponse.R:5:3',
'test_pipeop_removeconstants.R:6:3', 'test_pipeop_renamecolumns.R:6:3',
'test_pipeop_replicate.R:9:3', 'test_pipeop_rowapply.R:6:3',
'test_pipeop_scale.R:6:3', 'test_pipeop_scale.R:10:3',
'test_pipeop_scalemaxabs.R:6:3', 'test_pipeop_scalerange.R:7:3',
'test_pipeop_select.R:9:3', 'test_pipeop_smote.R:10:3',
'test_pipeop_smotenc.R:8:3', 'test_pipeop_spatialsign.R:3:1',
'test_pipeop_splines.R:3:1', 'test_pipeop_subsample.R:6:3',
'test_pipeop_targetinvert.R:4:3', 'test_pipeop_targetmutate.R:5:3',
'test_pipeop_targettrafo.R:4:3', 'test_pipeop_targettrafoscalerange.R:5:3',
'test_pipeop_task_preproc.R:4:3', 'test_pipeop_task_preproc.R:14:3',
'test_pipeop_nmf.R:6:3', 'test_pipeop_tomek.R:7:3',
'test_pipeop_textvectorizer.R:37:3', 'test_pipeop_textvectorizer.R:186:3',
'test_pipeop_unbranch.R:10:3', 'test_pipeop_updatetarget.R:89:3',
'test_pipeop_vtreat.R:9:3', 'test_pipeop_yeojohnson.R:7:3',
'test_pipeop_tunethreshold.R:111:3', 'test_pipeop_tunethreshold.R:191:3',
'test_ppl.R:63:3', 'test_typecheck.R:188:3'
• Skipping (1): 'test_GraphLearner.R:1278:3'
• empty test (2): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_mlr_graphs_robustify.R:106:3'): Robustify Pipeline Impute Missings ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_mlr_graphs_robustify.R:106:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classbalancing.R:13:3'): PipeOpClassBalancing ───────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classbalancing.R:13:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:17:3'): PipeOpClassWeights ───────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classweights.R:17:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:36:5'): PipeOpClassWeights - weight roles assigned ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_classweights.R:36:5
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:7:3'): PipeOpImputeLearner - simple tests ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:7:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:138:3'): PipeOpImputeLearner - model active binding to state ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:138:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_impute.R:452:3'): impute, test rows and affect_columns ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_impute.R:452:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_missind.R:4:3'): PipeOpMissInd ──────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_missind.R:4:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_unbranch.R:21:3'): PipeOpUnbranch - train and predict ───
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_unbranch.R:21:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:36:3'): threshold works for binary ──────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_tunethreshold.R:36:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:73:3'): tunethreshold graph works ───────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─graph$train(tsk("pima")) at test_pipeop_tunethreshold.R:73:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. └─mlr3::tsk("pima")
5. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
6. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_selector.R:6:3'): Selectors work ───────────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::mlr_tasks$get("pima") at test_selector.R:6:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
[ FAIL 12 | WARN 21 | SKIP 128 | PASS 8462 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.11.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [231s/109s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ library("paradox")
+ library("mlr3pipelines")
+ test_check("mlr3pipelines")
+ }
Starting 2 test processes.
> test_Graph.R: Training debug.multi with input list(input_1 = 1, input_2 = 1)
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
Saving _problems/test_mlr_graphs_robustify-106.R
> test_multiplicities.R:
> test_multiplicities.R: [[1]]
> test_multiplicities.R: [1] 0
> test_multiplicities.R:
> test_multiplicities.R:
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
> test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"
Saving _problems/test_pipeop_classbalancing-13.R
Saving _problems/test_pipeop_classweights-17.R
Saving _problems/test_pipeop_classweights-36.R
Saving _problems/test_pipeop_imputelearner-7.R
Saving _problems/test_pipeop_imputelearner-138.R
Saving _problems/test_pipeop_impute-452.R
> test_pipeop_isomap.R: 2026-08-02 07:28:22.349232: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:28:22.349838: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:22.359655: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:22.373819: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:28:22.411258: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:28:22.411644: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:22.419198: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:22.433719: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:28:22.452176: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:28:22.452718: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:22.468823: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:22.501792: embedding
> test_pipeop_isomap.R: 2026-08-02 07:28:22.502933: DONE
> test_pipeop_isomap.R: 2026-08-02 07:28:22.521622: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:28:22.522024: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:22.543517: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:22.57654: embedding
> test_pipeop_isomap.R: 2026-08-02 07:28:22.577517: DONE
> test_pipeop_isomap.R: 2026-08-02 07:28:22.635397: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:28:22.635786: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:22.648828: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:22.727829: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:28:22.750571: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:28:22.751076: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:22.781643: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:22.939116: embedding
> test_pipeop_isomap.R: 2026-08-02 07:28:22.941486: DONE
> test_pipeop_isomap.R: 2026-08-02 07:28:23.034164: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:28:23.034532: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:23.042255: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:23.056608: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:28:23.077847: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:28:23.07835: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:23.097053: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:23.131597: embedding
> test_pipeop_isomap.R: 2026-08-02 07:28:23.132529: DONE
> test_pipeop_isomap.R: 2026-08-02 07:28:23.219823: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:28:23.220166: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:23.227978: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:23.242831: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:28:23.273521: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:28:23.274051: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:23.308346: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:23.341696: embedding
> test_pipeop_isomap.R: 2026-08-02 07:28:23.342882: DONE
> test_pipeop_isomap.R: 2026-08-02 07:28:23.414338: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:28:23.414733: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:23.423692: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:23.437686: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:28:23.474683: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:28:23.475304: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:23.588524: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:23.621135: embedding
> test_pipeop_isomap.R: 2026-08-02 07:28:23.622136: DONE
> test_pipeop_isomap.R: 2026-08-02 07:28:23.674176: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:28:23.674534: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:23.682418: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:23.697233: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:28:23.729871: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:28:23.730453: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:23.743895: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:23.776895: embedding
> test_pipeop_isomap.R: 2026-08-02 07:28:23.777914: DONE
> test_pipeop_isomap.R: 2026-08-02 07:28:23.830508: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:28:23.830851: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:23.839295: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:23.853268: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:28:23.892026: L-Isomap embed START
> test_pipeop_isomap.R: 2026-08-02 07:28:23.892564: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:23.905977: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:23.940399: embedding
> test_pipeop_isomap.R: 2026-08-02 07:28:23.941369: DONE
> test_pipeop_isomap.R: 2026-08-02 07:28:23.997143: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:28:23.99749: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:24.005078: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:24.018879: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:28:24.07289: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:28:24.073242: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:24.080857: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:24.095967: Classical Scaling
> test_pipeop_isomap.R: 2026-08-02 07:28:24.112191: Isomap START
> test_pipeop_isomap.R: 2026-08-02 07:28:24.112536: constructing knn graph
> test_pipeop_isomap.R: 2026-08-02 07:28:24.126873: calculating geodesic distances
> test_pipeop_isomap.R: 2026-08-02 07:28:24.142205: Classical Scaling
Saving _problems/test_pipeop_missind-4.R
> test_pipeop_nmf.R: [PipeOpNMFstate]
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_task_preproc.R: Training debug_affectcols
> test_pipeop_nmf.R: [PipeOpNMFstate]
Saving _problems/test_pipeop_unbranch-21.R
Saving _problems/test_pipeop_tunethreshold-36.R
Saving _problems/test_pipeop_tunethreshold-73.R
Saving _problems/test_selector-6.R
[ FAIL 12 | WARN 21 | SKIP 128 | PASS 8462 ]
══ Skipped tests (128) ═════════════════════════════════════════════════════════
• On CRAN (125): 'test_CnfFormula_simplify.R:6:3', 'test_CnfFormula.R:591:3',
'test_Graph.R:283:3', 'test_PipeOp.R:32:1', 'test_GraphLearner.R:5:3',
'test_GraphLearner.R:221:3', 'test_GraphLearner.R:343:3',
'test_GraphLearner.R:408:3', 'test_GraphLearner.R:571:3',
'test_doublearrow.R:2:1', 'test_gunion.R:2:1',
'test_learner_weightedaverage.R:5:3', 'test_learner_weightedaverage.R:57:3',
'test_learner_weightedaverage.R:105:3',
'test_learner_weightedaverage.R:152:3', 'test_dictionary.R:7:3',
'test_meta.R:39:3', 'test_mlr_graphs_branching.R:26:3',
'test_mlr_graphs_bagging.R:6:3', 'test_mlr_graphs_robustify.R:5:3',
'test_pipeop_adas.R:8:3', 'test_pipeop_blsmote.R:8:3',
'test_pipeop_branch.R:4:3', 'test_pipeop_chunk.R:4:3',
'test_pipeop_boxcox.R:7:3', 'test_pipeop_classbalancing.R:7:3',
'test_pipeop_classweights.R:10:3', 'test_pipeop_classweightsex.R:9:3',
'test_pipeop_colapply.R:9:3', 'test_pipeop_collapsefactors.R:6:3',
'test_pipeop_copy.R:5:3', 'test_pipeop_colroles.R:6:3',
'test_pipeop_decode.R:14:3', 'test_pipeop_encode.R:21:3',
'test_pipeop_datefeatures.R:10:3', 'test_pipeop_encodeimpact.R:11:3',
'test_pipeop_encodepl.R:5:3', 'test_pipeop_encodepl.R:72:3',
'test_pipeop_ensemble.R:3:1', 'test_pipeop_encodelmer.R:15:3',
'test_pipeop_encodelmer.R:37:3', 'test_pipeop_encodelmer.R:80:3',
'test_pipeop_filter.R:7:3', 'test_pipeop_fixfactors.R:9:3',
'test_pipeop_histbin.R:7:3', 'test_pipeop_ica.R:7:3',
'test_pipeop_featureunion.R:9:3', 'test_pipeop_featureunion.R:134:3',
'test_pipeop_imputelearner.R:43:3', 'test_pipeop_info.R:3:1',
'test_pipeop_impute.R:4:3', 'test_pipeop_kernelpca.R:9:3',
'test_pipeop_isomap.R:10:3', 'test_pipeop_learner.R:17:3',
'test_pipeop_learnerpicvplus.R:2:1', 'test_pipeop_modelmatrix.R:7:3',
'test_pipeop_multiplicityexply.R:9:3', 'test_pipeop_multiplicityimply.R:9:3',
'test_pipeop_mutate.R:9:3', 'test_pipeop_nearmiss.R:7:3',
'test_pipeop_learnercv.R:3:3', 'test_pipeop_learnercv.R:43:3',
'test_pipeop_learnercv.R:73:3', 'test_pipeop_learnercv.R:92:3',
'test_pipeop_learnercv.R:141:3', 'test_pipeop_learnercv.R:157:3',
'test_pipeop_learnercv.R:203:3', 'test_pipeop_learnercv.R:249:3',
'test_pipeop_learnercv.R:278:3', 'test_pipeop_learnercv.R:332:3',
'test_pipeop_learnercv.R:359:3', 'test_pipeop_learnercv.R:389:3',
'test_pipeop_learnercv.R:399:3', 'test_pipeop_learnercv.R:432:3',
'test_pipeop_learnercv.R:472:3', 'test_pipeop_learnercv.R:481:3',
'test_pipeop_learnercv.R:498:3', 'test_pipeop_learnercv.R:506:3',
'test_pipeop_learnercv.R:530:3', 'test_pipeop_learnercv.R:554:3',
'test_pipeop_learnercv.R:634:3', 'test_pipeop_learnercv.R:654:3',
'test_pipeop_learnercv.R:669:3', 'test_pipeop_learnercv.R:754:3',
'test_pipeop_learnercv.R:799:3', 'test_pipeop_learnercv.R:827:3',
'test_pipeop_ovr.R:9:3', 'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3',
'test_pipeop_proxy.R:2:1', 'test_pipeop_quantilebin.R:5:3',
'test_pipeop_randomprojection.R:6:3', 'test_pipeop_randomresponse.R:5:3',
'test_pipeop_removeconstants.R:6:3', 'test_pipeop_renamecolumns.R:6:3',
'test_pipeop_replicate.R:9:3', 'test_pipeop_rowapply.R:6:3',
'test_pipeop_scale.R:6:3', 'test_pipeop_scale.R:10:3',
'test_pipeop_scalemaxabs.R:6:3', 'test_pipeop_scalerange.R:7:3',
'test_pipeop_select.R:9:3', 'test_pipeop_smote.R:10:3',
'test_pipeop_smotenc.R:8:3', 'test_pipeop_spatialsign.R:3:1',
'test_pipeop_splines.R:3:1', 'test_pipeop_subsample.R:6:3',
'test_pipeop_targetinvert.R:4:3', 'test_pipeop_targetmutate.R:5:3',
'test_pipeop_targettrafo.R:4:3', 'test_pipeop_targettrafoscalerange.R:5:3',
'test_pipeop_task_preproc.R:4:3', 'test_pipeop_task_preproc.R:14:3',
'test_pipeop_nmf.R:6:3', 'test_pipeop_textvectorizer.R:37:3',
'test_pipeop_textvectorizer.R:186:3', 'test_pipeop_tomek.R:7:3',
'test_pipeop_unbranch.R:10:3', 'test_pipeop_updatetarget.R:89:3',
'test_pipeop_vtreat.R:9:3', 'test_pipeop_yeojohnson.R:7:3',
'test_pipeop_tunethreshold.R:111:3', 'test_pipeop_tunethreshold.R:191:3',
'test_ppl.R:63:3', 'test_typecheck.R:188:3'
• Skipping (1): 'test_GraphLearner.R:1278:3'
• empty test (2): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_mlr_graphs_robustify.R:106:3'): Robustify Pipeline Impute Missings ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_mlr_graphs_robustify.R:106:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classbalancing.R:13:3'): PipeOpClassBalancing ───────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classbalancing.R:13:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:17:3'): PipeOpClassWeights ───────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_classweights.R:17:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_classweights.R:36:5'): PipeOpClassWeights - weight roles assigned ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_classweights.R:36:5
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:7:3'): PipeOpImputeLearner - simple tests ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:7:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_imputelearner.R:138:3'): PipeOpImputeLearner - model active binding to state ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:138:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_impute.R:452:3'): impute, test rows and affect_columns ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_impute.R:452:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_missind.R:4:3'): PipeOpMissInd ──────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_missind.R:4:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_unbranch.R:21:3'): PipeOpUnbranch - train and predict ───
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr_tasks$get("pima") at test_pipeop_unbranch.R:21:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:36:3'): threshold works for binary ──────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_pipeop_tunethreshold.R:36:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_pipeop_tunethreshold.R:73:3'): tunethreshold graph works ───────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─graph$train(tsk("pima")) at test_pipeop_tunethreshold.R:73:3
2. │ └─mlr3pipelines:::.__Graph__train(...)
3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
4. └─mlr3::tsk("pima")
5. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
6. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_selector.R:6:3'): Selectors work ───────────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::mlr_tasks$get("pima") at test_selector.R:6:3
2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
3. │ └─base::eval.parent(expr, n = 1L)
4. │ └─base::eval(expr, p)
5. │ └─base::eval(expr, p)
6. └─mlr3misc:::dictionary_get(self = self, key = key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor, cargs)
9. └─mlr3 (local) `<fn>`()
10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
[ FAIL 12 | WARN 21 | SKIP 128 | PASS 8462 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.11.0
Check: tests
Result: ERROR
Running 'testthat.R' [161s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ library("paradox")
+ library("mlr3pipelines")
+ test_check("mlr3pipelines")
+ }
Starting 2 test processes.
> test_Graph.R: Training debug.multi with input list(input_1 = 1, input_2 = 1)
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Training test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: Predicting test_autotrain
> test_PipeOp.R: 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