- using R version 4.6.1 (2026-06-24)
- using platform: x86_64-pc-linux-gnu
- R was compiled by
gcc-16 (Debian 16.1.0-3) 16.1.0
GNU Fortran (Debian 16.1.0-3) 16.1.0
- running under: Debian GNU/Linux forky/sid
- using session charset: UTF-8
* current time: 2026-08-01 16:05:15 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/1s] 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/1s] OK
- checking loading without being on the library search path ... [1s/2s] 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 ... [93s/104s] OK
- checking Rd files ... [4s/4s] 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 ... [27s/35s] 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
- checking for unstated dependencies in ‘tests’ ... OK
- checking tests ... [347s/179s] 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
- checking for unstated dependencies in vignettes ... OK
- checking package vignettes ... OK
- checking re-building of vignette outputs ... [5s/6s] OK
- checking PDF version of manual ... [32s/44s] OK
- checking HTML version of manual ... [49s/58s] OK
- checking for non-standard things in the check directory ... OK
- DONE
Status: 2 ERRORs