• using R version 4.6.1 Patched (2026-08-10 r90391)
• using platform: x86_64-pc-linux-gnu
• R was compiled by     gcc-15 (Debian 15.3.0-2) 15.3.0     GNU Fortran (Debian 15.3.0-2) 15.3.0
• running under: Debian GNU/Linux forky/sid
• using session charset: UTF-8 * current time: 2026-08-12 16:18:20 UTC
• checking for file ‘mlr3pipelines/DESCRIPTION’ ... OK
• this is package ‘mlr3pipelines’ version ‘0.11.0’
• package encoding: UTF-8
• checking package namespace information ... OK
• checking package dependencies ... OK
• checking if this is a source package ... OK
• checking if there is a namespace ... OK
• checking for executable files ... OK
• checking for hidden files and directories ... OK
• checking for portable file names ... OK
• checking for sufficient/correct file permissions ... OK
• checking whether package ‘mlr3pipelines’ can be installed ... OK See the install log for details.
• checking package directory ... OK
• checking for future file timestamps ... OK
• checking ‘build’ directory ... OK
• checking DESCRIPTION meta-information ... OK
• checking top-level files ... OK
• checking for left-over files ... OK
• checking index information ... OK
• checking package subdirectories ... OK
• checking code files for non-ASCII characters ... OK
• checking R files for syntax errors ... OK
• checking whether the package can be loaded ... [1s/1s] OK
• checking whether the package can be loaded with stated dependencies ... [1s/2s] OK
• checking whether the package can be unloaded cleanly ... [1s/1s] OK
• checking whether the namespace can be loaded with stated dependencies ... [1s/1s] OK
• checking whether the namespace can be unloaded cleanly ... [1s/2s] OK
• checking loading without being on the library search path ... [1s/1s] OK
• checking whether startup messages can be suppressed ... [1s/1s] OK
• checking use of S3 registration ... OK
• checking dependencies in R code ... OK
• checking S3 generic/method consistency ... OK
• checking replacement functions ... OK
• checking foreign function calls ... OK
• checking R code for possible problems ... [95s/144s] OK
• checking Rd files ... [5s/7s] OK
• checking Rd metadata ... OK
• checking Rd line widths ... OK
• checking Rd cross-references ... OK
• checking for missing documentation entries ... OK
• checking for code/documentation mismatches ... OK
• checking Rd \usage sections ... OK
• checking Rd contents ... OK
• checking for unstated dependencies in examples ... OK
• checking installed files from ‘inst/doc’ ... OK
• checking files in ‘vignettes’ ... OK
• checking examples ... [26s/31s] ERROR Running examples in ‘mlr3pipelines-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: mlr_pipeops_imputeconstant > ### Title: Impute Features by a Constant > ### Aliases: mlr_pipeops_imputeconstant PipeOpImputeConstant > > ### ** Examples > > library("mlr3") > > task = tsk("pima") Warning in data(list = id, package = package, envir = ee) :   data set ‘PimaIndiansDiabetes2’ not found Error in UseMethod("as_data_backend") :   no applicable method for 'as_data_backend' applied to an object of class "NULL" Calls: tsk ... dictionary_initialize_item -> do.call -> <Anonymous> -> as_data_backend Execution halted Examples with CPU (user + system) or elapsed time > 5s                 user system elapsed mlr_graphs_ovr 4.204 0.137 5.543
• checking for unstated dependencies in ‘tests’ ... OK
• checking tests ... [360s/186s] ERROR   Running ‘testthat.R’ [359s/186s] Running the tests in ‘tests/testthat.R’ failed. Complete output:   > if (requireNamespace("testthat", quietly = TRUE)) {   + library("checkmate")   + library("testthat")   + library("mlr3")   + library("paradox")   + library("mlr3pipelines")   + test_check("mlr3pipelines")   + }   Starting 2 test processes.   > test_Graph.R: Training debug.multi with input list(input_1 = 1, input_2 = 1)   > test_PipeOp.R: Training test_autotrain   > test_PipeOp.R: Predicting test_autotrain   > test_PipeOp.R: Training test_autotrain   > test_PipeOp.R: Training test_autotrain   > test_PipeOp.R: Predicting test_autotrain   > test_PipeOp.R: Predicting test_autotrain   > test_PipeOp.R: Training test_autotrain   > test_PipeOp.R: Training test_autotrain   > test_PipeOp.R: Training test_autotrain   > test_PipeOp.R: Predicting test_autotrain   > test_PipeOp.R: Predicting test_autotrain   > test_PipeOp.R: Predicting test_autotrain   > test_PipeOp.R: Training test_autotrain   > test_PipeOp.R: Predicting test_autotrain   > test_PipeOp.R: Training test_autotrain   > test_PipeOp.R: Training test_autotrain   > test_PipeOp.R: Predicting test_autotrain   > test_PipeOp.R: Predicting test_autotrain   > test_PipeOp.R: Training test_autotrain   > test_PipeOp.R: Training test_autotrain   > test_PipeOp.R: Training test_autotrain   > test_PipeOp.R: Predicting test_autotrain   > test_PipeOp.R: Predicting test_autotrain   > test_PipeOp.R: Predicting test_autotrain   > test_PipeOp.R: Training test_autotrain   > test_PipeOp.R: Predicting test_autotrain   Saving _problems/test_mlr_graphs_robustify-106.R   > test_multiplicities.R:   > test_multiplicities.R: [[1]]   > test_multiplicities.R: [1] 0   > test_multiplicities.R:   > test_multiplicities.R:   > test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"   > test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"   > test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"   > test_pipeop_blsmote.R: [1] "Borderline-SMOTE done"   Saving _problems/test_pipeop_classbalancing-13.R   Saving _problems/test_pipeop_classweights-17.R   Saving _problems/test_pipeop_classweights-36.R   Saving _problems/test_pipeop_imputelearner-7.R   Saving _problems/test_pipeop_imputelearner-138.R   Saving _problems/test_pipeop_impute-452.R   > test_pipeop_isomap.R: 2026-08-12 18:24:16.918409: Isomap START   > test_pipeop_isomap.R: 2026-08-12 18:24:16.919316: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:16.934583: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:16.953714: Classical Scaling   > test_pipeop_isomap.R: 2026-08-12 18:24:17.026078: Isomap START   > test_pipeop_isomap.R: 2026-08-12 18:24:17.026637: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:17.038301: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:17.056968: Classical Scaling   > test_pipeop_isomap.R: 2026-08-12 18:24:17.089084: L-Isomap embed START   > test_pipeop_isomap.R: 2026-08-12 18:24:17.089908: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:17.110732: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:17.152917: embedding   > test_pipeop_isomap.R: 2026-08-12 18:24:17.154496: DONE   > test_pipeop_isomap.R: 2026-08-12 18:24:17.187533: L-Isomap embed START   > test_pipeop_isomap.R: 2026-08-12 18:24:17.188104: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:17.207717: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:17.249507: embedding   > test_pipeop_isomap.R: 2026-08-12 18:24:17.250908: DONE   > test_pipeop_isomap.R: 2026-08-12 18:24:17.361221: Isomap START   > test_pipeop_isomap.R: 2026-08-12 18:24:17.36181: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:17.395115: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:17.491959: Classical Scaling   > test_pipeop_isomap.R: 2026-08-12 18:24:17.536902: L-Isomap embed START   > test_pipeop_isomap.R: 2026-08-12 18:24:17.540073: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:17.571714: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:17.768295: embedding   > test_pipeop_isomap.R: 2026-08-12 18:24:17.771579: DONE   > test_pipeop_isomap.R: 2026-08-12 18:24:17.944504: Isomap START   > test_pipeop_isomap.R: 2026-08-12 18:24:17.945052: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:17.956189: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:17.975078: Classical Scaling   > test_pipeop_isomap.R: 2026-08-12 18:24:18.023891: L-Isomap embed START   > test_pipeop_isomap.R: 2026-08-12 18:24:18.024628: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:18.042325: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:18.086856: embedding   > test_pipeop_isomap.R: 2026-08-12 18:24:18.088165: DONE   > test_pipeop_isomap.R: 2026-08-12 18:24:18.247621: Isomap START   > test_pipeop_isomap.R: 2026-08-12 18:24:18.250128: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:18.261373: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:18.280103: Classical Scaling   > test_pipeop_isomap.R: 2026-08-12 18:24:18.335846: L-Isomap embed START   > test_pipeop_isomap.R: 2026-08-12 18:24:18.336654: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:18.356651: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:18.398822: embedding   > test_pipeop_isomap.R: 2026-08-12 18:24:18.400052: DONE   > test_pipeop_isomap.R: 2026-08-12 18:24:18.493217: Isomap START   > test_pipeop_isomap.R: 2026-08-12 18:24:18.493775: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:18.50737: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:18.52618: Classical Scaling   > test_pipeop_isomap.R: 2026-08-12 18:24:18.598762: L-Isomap embed START   > test_pipeop_isomap.R: 2026-08-12 18:24:18.599526: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:18.61727: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:18.658944: embedding   > test_pipeop_isomap.R: 2026-08-12 18:24:18.660219: DONE   > test_pipeop_isomap.R: 2026-08-12 18:24:18.754323: Isomap START   > test_pipeop_isomap.R: 2026-08-12 18:24:18.754869: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:18.766201: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:18.785159: Classical Scaling   > test_pipeop_isomap.R: 2026-08-12 18:24:18.844279: L-Isomap embed START   > test_pipeop_isomap.R: 2026-08-12 18:24:18.845037: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:18.862878: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:18.912369: embedding   > test_pipeop_isomap.R: 2026-08-12 18:24:18.914482: DONE   > test_pipeop_isomap.R: 2026-08-12 18:24:19.03027: Isomap START   > test_pipeop_isomap.R: 2026-08-12 18:24:19.030876: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:19.046997: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:19.065853: Classical Scaling   > test_pipeop_isomap.R: 2026-08-12 18:24:19.131783: L-Isomap embed START   > test_pipeop_isomap.R: 2026-08-12 18:24:19.132647: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:19.177646: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:19.219429: embedding   > test_pipeop_isomap.R: 2026-08-12 18:24:19.220777: DONE   > test_pipeop_isomap.R: 2026-08-12 18:24:19.325372: Isomap START   > test_pipeop_isomap.R: 2026-08-12 18:24:19.325915: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:19.336651: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:19.358253: Classical Scaling   > test_pipeop_isomap.R: 2026-08-12 18:24:19.455604: Isomap START   > test_pipeop_isomap.R: 2026-08-12 18:24:19.456149: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:19.467107: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:19.485575: Classical Scaling   > test_pipeop_isomap.R: 2026-08-12 18:24:19.515675: Isomap START   > test_pipeop_isomap.R: 2026-08-12 18:24:19.516207: constructing knn graph   > test_pipeop_isomap.R: 2026-08-12 18:24:19.526545: calculating geodesic distances   > test_pipeop_isomap.R: 2026-08-12 18:24:19.545336: Classical Scaling   Saving _problems/test_pipeop_missind-4.R   > test_pipeop_nmf.R: [PipeOpNMFstate]   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_task_preproc.R: Training debug_affectcols   > test_pipeop_nmf.R: [PipeOpNMFstate]   Saving _problems/test_pipeop_unbranch-21.R   Saving _problems/test_pipeop_tunethreshold-36.R   Saving _problems/test_pipeop_tunethreshold-73.R   Saving _problems/test_selector-6.R   [ FAIL 12 | WARN 12 | SKIP 128 | PASS 8462 ]      ══ Skipped tests (128) ═════════════════════════════════════════════════════════   • On CRAN (125): 'test_CnfFormula_simplify.R:6:3', 'test_CnfFormula.R:591:3',     'test_Graph.R:283:3', 'test_PipeOp.R:32:1', 'test_GraphLearner.R:5:3',     'test_GraphLearner.R:221:3', 'test_GraphLearner.R:343:3',     'test_GraphLearner.R:408:3', 'test_GraphLearner.R:571:3',     'test_doublearrow.R:2:1', 'test_dictionary.R:7:3', 'test_gunion.R:2:1',     'test_learner_weightedaverage.R:5:3', 'test_learner_weightedaverage.R:57:3',     'test_learner_weightedaverage.R:105:3',     'test_learner_weightedaverage.R:152:3', 'test_meta.R:39:3',     'test_mlr_graphs_branching.R:26:3', 'test_mlr_graphs_bagging.R:6:3',     'test_mlr_graphs_robustify.R:5:3', 'test_pipeop_adas.R:8:3',     'test_pipeop_blsmote.R:8:3', 'test_pipeop_branch.R:4:3',     'test_pipeop_chunk.R:4:3', 'test_pipeop_boxcox.R:7:3',     'test_pipeop_classbalancing.R:7:3', 'test_pipeop_classweights.R:10:3',     'test_pipeop_classweightsex.R:9:3', 'test_pipeop_collapsefactors.R:6:3',     'test_pipeop_colapply.R:9:3', 'test_pipeop_copy.R:5:3',     'test_pipeop_colroles.R:6:3', 'test_pipeop_decode.R:14:3',     'test_pipeop_encode.R:21:3', 'test_pipeop_encodeimpact.R:11:3',     'test_pipeop_datefeatures.R:10:3', 'test_pipeop_encodepl.R:5:3',     'test_pipeop_encodepl.R:72:3', 'test_pipeop_ensemble.R:3:1',     'test_pipeop_encodelmer.R:15:3', 'test_pipeop_encodelmer.R:37:3',     'test_pipeop_encodelmer.R:80:3', 'test_pipeop_filter.R:7:3',     'test_pipeop_fixfactors.R:9:3', 'test_pipeop_histbin.R:7:3',     'test_pipeop_ica.R:7:3', 'test_pipeop_featureunion.R:9:3',     'test_pipeop_featureunion.R:134:3', 'test_pipeop_imputelearner.R:43:3',     'test_pipeop_info.R:3:1', 'test_pipeop_impute.R:4:3',     'test_pipeop_kernelpca.R:9:3', 'test_pipeop_isomap.R:10:3',     'test_pipeop_learner.R:17:3', 'test_pipeop_learnerpicvplus.R:2:1',     'test_pipeop_modelmatrix.R:7:3', 'test_pipeop_multiplicityexply.R:9:3',     'test_pipeop_learnercv.R:3:3', 'test_pipeop_learnercv.R:43:3',     'test_pipeop_learnercv.R:73:3', 'test_pipeop_learnercv.R:92:3',     'test_pipeop_learnercv.R:141:3', 'test_pipeop_learnercv.R:157:3',     'test_pipeop_learnercv.R:203:3', 'test_pipeop_learnercv.R:249:3',     'test_pipeop_learnercv.R:278:3', 'test_pipeop_learnercv.R:332:3',     'test_pipeop_learnercv.R:359:3', 'test_pipeop_learnercv.R:389:3',     'test_pipeop_learnercv.R:399:3', 'test_pipeop_learnercv.R:432:3',     'test_pipeop_learnercv.R:472:3', 'test_pipeop_learnercv.R:481:3',     'test_pipeop_learnercv.R:498:3', 'test_pipeop_learnercv.R:506:3',     'test_pipeop_learnercv.R:530:3', 'test_pipeop_learnercv.R:554:3',     'test_pipeop_learnercv.R:634:3', 'test_pipeop_learnercv.R:654:3',     'test_pipeop_learnercv.R:669:3', 'test_pipeop_learnercv.R:754:3',     'test_pipeop_learnercv.R:799:3', 'test_pipeop_learnercv.R:827:3',     'test_pipeop_mutate.R:9:3', 'test_pipeop_multiplicityimply.R:9:3',     'test_pipeop_nearmiss.R:7:3', 'test_pipeop_ovr.R:9:3',     'test_pipeop_ovr.R:48:3', 'test_pipeop_pca.R:8:3', 'test_pipeop_proxy.R:2:1',     'test_pipeop_quantilebin.R:5:3', 'test_pipeop_randomprojection.R:6:3',     'test_pipeop_randomresponse.R:5:3', 'test_pipeop_removeconstants.R:6:3',     'test_pipeop_renamecolumns.R:6:3', 'test_pipeop_replicate.R:9:3',     'test_pipeop_rowapply.R:6:3', 'test_pipeop_scale.R:6:3',     'test_pipeop_scale.R:10:3', 'test_pipeop_scalemaxabs.R:6:3',     'test_pipeop_scalerange.R:7:3', 'test_pipeop_select.R:9:3',     'test_pipeop_smote.R:10:3', 'test_pipeop_smotenc.R:8:3',     'test_pipeop_spatialsign.R:3:1', 'test_pipeop_splines.R:3:1',     'test_pipeop_subsample.R:6:3', 'test_pipeop_targetinvert.R:4:3',     'test_pipeop_targetmutate.R:5:3', 'test_pipeop_targettrafo.R:4:3',     'test_pipeop_targettrafoscalerange.R:5:3', 'test_pipeop_task_preproc.R:4:3',     'test_pipeop_task_preproc.R:14:3', 'test_pipeop_nmf.R:6:3',     'test_pipeop_tomek.R:7:3', 'test_pipeop_textvectorizer.R:37:3',     'test_pipeop_textvectorizer.R:186:3', 'test_pipeop_unbranch.R:10:3',     'test_pipeop_updatetarget.R:89:3', 'test_pipeop_vtreat.R:9:3',     'test_pipeop_yeojohnson.R:7:3', 'test_pipeop_tunethreshold.R:111:3',     'test_pipeop_tunethreshold.R:191:3', 'test_ppl.R:63:3',     'test_typecheck.R:188:3'   • Skipping (1): 'test_GraphLearner.R:1278:3'   • empty test (2): 'test_pipeop_isomap.R:111:1', 'test_pipeop_missind.R:101:1'      ══ Failed tests ════════════════════════════════════════════════════════════════   ── Error ('test_mlr_graphs_robustify.R:106:3'): Robustify Pipeline Impute Missings ──   Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"   Backtrace:       ▆    1. └─mlr3::tsk("pima") at test_mlr_graphs_robustify.R:106:3    2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)    3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)    4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)    5. ├─base::do.call(constructor, cargs)    6. └─mlr3 (local) `<fn>`()    7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))   ── Error ('test_pipeop_classbalancing.R:13:3'): PipeOpClassBalancing ───────────   Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"   Backtrace:        ▆     1. └─mlr_tasks$get("pima") at test_pipeop_classbalancing.R:13:3     2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)     3. │ └─base::eval.parent(expr, n = 1L)     4. │ └─base::eval(expr, p)     5. │ └─base::eval(expr, p)     6. └─mlr3misc:::dictionary_get(self = self, key = key)     7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)     8. ├─base::do.call(constructor, cargs)     9. └─mlr3 (local) `<fn>`()    10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))   ── Error ('test_pipeop_classweights.R:17:3'): PipeOpClassWeights ───────────────   Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"   Backtrace:        ▆     1. └─mlr_tasks$get("pima") at test_pipeop_classweights.R:17:3     2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)     3. │ └─base::eval.parent(expr, n = 1L)     4. │ └─base::eval(expr, p)     5. │ └─base::eval(expr, p)     6. └─mlr3misc:::dictionary_get(self = self, key = key)     7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)     8. ├─base::do.call(constructor, cargs)     9. └─mlr3 (local) `<fn>`()    10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))   ── Error ('test_pipeop_classweights.R:36:5'): PipeOpClassWeights - weight roles assigned ──   Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"   Backtrace:       ▆    1. └─mlr3::tsk("pima") at test_pipeop_classweights.R:36:5    2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)    3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)    4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)    5. ├─base::do.call(constructor, cargs)    6. └─mlr3 (local) `<fn>`()    7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))   ── Error ('test_pipeop_imputelearner.R:7:3'): PipeOpImputeLearner - simple tests ──   Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"   Backtrace:        ▆     1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:7:3     2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)     3. │ └─base::eval.parent(expr, n = 1L)     4. │ └─base::eval(expr, p)     5. │ └─base::eval(expr, p)     6. └─mlr3misc:::dictionary_get(self = self, key = key)     7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)     8. ├─base::do.call(constructor, cargs)     9. └─mlr3 (local) `<fn>`()    10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))   ── Error ('test_pipeop_imputelearner.R:138:3'): PipeOpImputeLearner - model active binding to state ──   Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"   Backtrace:        ▆     1. └─mlr_tasks$get("pima") at test_pipeop_imputelearner.R:138:3     2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)     3. │ └─base::eval.parent(expr, n = 1L)     4. │ └─base::eval(expr, p)     5. │ └─base::eval(expr, p)     6. └─mlr3misc:::dictionary_get(self = self, key = key)     7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)     8. ├─base::do.call(constructor, cargs)     9. └─mlr3 (local) `<fn>`()    10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))   ── Error ('test_pipeop_impute.R:452:3'): impute, test rows and affect_columns ──   Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"   Backtrace:       ▆    1. └─mlr3::tsk("pima") at test_pipeop_impute.R:452:3    2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)    3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)    4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)    5. ├─base::do.call(constructor, cargs)    6. └─mlr3 (local) `<fn>`()    7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))   ── Error ('test_pipeop_missind.R:4:3'): PipeOpMissInd ──────────────────────────   Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"   Backtrace:        ▆     1. └─mlr_tasks$get("pima") at test_pipeop_missind.R:4:3     2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)     3. │ └─base::eval.parent(expr, n = 1L)     4. │ └─base::eval(expr, p)     5. │ └─base::eval(expr, p)     6. └─mlr3misc:::dictionary_get(self = self, key = key)     7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)     8. ├─base::do.call(constructor, cargs)     9. └─mlr3 (local) `<fn>`()    10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))   ── Error ('test_pipeop_unbranch.R:21:3'): PipeOpUnbranch - train and predict ───   Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"   Backtrace:        ▆     1. └─mlr_tasks$get("pima") at test_pipeop_unbranch.R:21:3     2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)     3. │ └─base::eval.parent(expr, n = 1L)     4. │ └─base::eval(expr, p)     5. │ └─base::eval(expr, p)     6. └─mlr3misc:::dictionary_get(self = self, key = key)     7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)     8. ├─base::do.call(constructor, cargs)     9. └─mlr3 (local) `<fn>`()    10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))   ── Error ('test_pipeop_tunethreshold.R:36:3'): threshold works for binary ──────   Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"   Backtrace:       ▆    1. └─mlr3::tsk("pima") at test_pipeop_tunethreshold.R:36:3    2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)    3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)    4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)    5. ├─base::do.call(constructor, cargs)    6. └─mlr3 (local) `<fn>`()    7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))   ── Error ('test_pipeop_tunethreshold.R:73:3'): tunethreshold graph works ───────   Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"   Backtrace:        ▆     1. ├─graph$train(tsk("pima")) at test_pipeop_tunethreshold.R:73:3     2. │ └─mlr3pipelines:::.__Graph__train(...)     3. │ └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)     4. └─mlr3::tsk("pima")     5. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)     6. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)     7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)     8. ├─base::do.call(constructor, cargs)     9. └─mlr3 (local) `<fn>`()    10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))   ── Error ('test_selector.R:6:3'): Selectors work ───────────────────────────────   Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"   Backtrace:        ▆     1. └─mlr3::mlr_tasks$get("pima") at test_selector.R:6:3     2. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)     3. │ └─base::eval.parent(expr, n = 1L)     4. │ └─base::eval(expr, p)     5. │ └─base::eval(expr, p)     6. └─mlr3misc:::dictionary_get(self = self, key = key)     7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)     8. ├─base::do.call(constructor, cargs)     9. └─mlr3 (local) `<fn>`()    10. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))      [ FAIL 12 | WARN 12 | SKIP 128 | PASS 8462 ]   Error:   ! Test failures.   Execution halted
• checking for unstated dependencies in vignettes ... OK
• checking package vignettes ... OK
• checking re-building of vignette outputs ... [5s/5s] OK
• checking PDF version of manual ... [32s/45s] OK
• checking HTML version of manual ... [50s/68s] OK
• checking for non-standard things in the check directory ... OK
• DONE

Status: 2 ERRORs