Running ‘testthat.R’ [134s/169s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > if (requireNamespace("testthat", quietly = TRUE)) {
  +   library(testthat)
  +   library(mlr3learners)
  +   test_check("mlr3learners")
  + }
  ── 1. Error: prob column reordering (#155) (@test_classif_cv_glmnet.R#19)  ─────
  'NA' indices are not (yet?) supported for sparse Matrices
  Backtrace:
    1. learner$train(task)
    2. mlr3:::.__Learner__train(...)
    3. mlr3:::learner_train(self, task, row_ids)
    4. mlr3misc::encapsulate(...)
    9. mlr3:::.f(learner = <environment>, task = <environment>)
   10. get_private(learner)$.train(task)
   11. mlr3learners:::.__LearnerClassifCVGlmnet__.train(...)
   16. glmnet::cv.glmnet(x = data, y = target, family = "binomial")
   17. glmnet:::cv.glmnet.raw(...)
   19. glmnet:::buildPredmat.lognetlist(...)
   20. glmnet:::buildPredmat.default(...)
   24. glmnet::predict.glmnet(...)
   26. nbeta[, lamlist$left, drop = FALSE]
   27. Matrix:::subCsp_cols(x, j, drop = drop)
   28. Matrix:::intI(j, n = x@Dim[2], dn[[2]], give.dn = FALSE)
  
  ── 2. Error: prob column reordering (#155) (@test_classif_glmnet.R#20)  ────────
  need at least two non-NA values to interpolate
  Backtrace:
    1. learner$predict(task)
    2. mlr3:::.__Learner__predict(...)
    3. mlr3:::learner_predict(self, task, row_ids)
    4. mlr3misc::encapsulate(...)
    9. mlr3:::.f(task = <environment>, learner = <environment>)
   10. get_private(learner)$.predict(task)
   11. mlr3learners:::.__LearnerClassifGlmnet__.predict(...)
   19. glmnet::predict.glmnet(...)
   20. glmnet:::lambda.interp(lambda, s)
   21. stats::approx(lambda, seq(lambda), sfrac)
  
  ══ testthat results  ═══════════════════════════════════════════════════════════
  [ OK: 347 | SKIPPED: 7 | WARNINGS: 0 | FAILED: 2 ]
  1. Error: prob column reordering (#155) (@test_classif_cv_glmnet.R#19) 
  2. Error: prob column reordering (#155) (@test_classif_glmnet.R#20) 
  
  Error: testthat unit tests failed
  Execution halted