* using log directory 'd:/Rcompile/CRANpkg/local/4.7/mlr3pipelines.Rcheck'
* using R Under development (unstable) (2026-07-28 r90311 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
    gcc.exe (GCC) 14.3.0
    GNU Fortran (GCC) 14.3.0
* running under: Windows Server 2022 x64 (build 20348)
* using session charset: UTF-8
* current time: 2026-07-29 10:45:28 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 hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'mlr3pipelines' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... 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] OK
* checking whether the package can be loaded with stated dependencies ... [1s] OK
* checking whether the package can be unloaded cleanly ... [1s] OK
* checking whether the namespace can be loaded with stated dependencies ... [1s] OK
* checking whether the namespace can be unloaded cleanly ... [1s] OK
* checking loading without being on the library search path ... [1s] OK
* checking whether startup messages can be suppressed ... [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 ... [60s] NOTE
Found calls to structure() using deprecated special names:
  mlr3pipelines/R/PipeOpFilter.R (.Names: 1)
'.Names' should be changed to 'names'.
* checking Rd files ... [6s] OK
* checking Rd metadata ... 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 ... [32s] 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
* checking for unstated dependencies in 'tests' ... OK
* checking tests ... [161s] 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
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... [5s] OK
* checking PDF version of manual ... [70s] OK
* checking HTML version of manual ... [36s] OK
* DONE
Status: 2 ERRORs, 1 NOTE