Running ‘testthat.R’ [48s/55s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > if (requireNamespace("testthat", quietly = TRUE)) {
  +   library("testthat")
  +   library("checkmate")
  +   library("mlr3hyperband")
  +   test_check("mlr3hyperband")
  + }
  Loading required package: mlr3tuning
  Loading required package: mlr3
  Loading required package: paradox
  Saving _problems/test_TunerBatchHyperband-4.R
  Saving _problems/test_TunerBatchHyperband-10.R
  Saving _problems/test_TunerBatchHyperband-16.R
  Saving _problems/test_TunerBatchHyperband-22.R
  Saving _problems/test_TunerBatchHyperband-37.R
  Saving _problems/test_TunerBatchHyperband-48.R
  Saving _problems/test_TunerBatchHyperband-55.R
  Saving _problems/test_TunerBatchHyperband-69.R
  Saving _problems/test_TunerBatchHyperband-90.R
  Saving _problems/test_TunerBatchHyperband-116.R
  Saving _problems/test_TunerBatchHyperband-136.R
  Saving _problems/test_TunerBatchHyperband-156.R
  Saving _problems/test_TunerBatchHyperband-162.R
  Saving _problems/test_TunerBatchHyperband-172.R
  Saving _problems/test_TunerBatchHyperband-182.R
  Saving _problems/test_TunerBatchHyperband-194.R
  Saving _problems/test_TunerBatchHyperband-208.R
  Saving _problems/test_TunerBatchHyperband-223.R
  Saving _problems/test_TunerBatchSuccessiveHalving-4.R
  Saving _problems/test_TunerBatchSuccessiveHalving-10.R
  Saving _problems/test_TunerBatchSuccessiveHalving-16.R
  Saving _problems/test_TunerBatchSuccessiveHalving-22.R
  Saving _problems/test_TunerBatchSuccessiveHalving-28.R
  Saving _problems/test_TunerBatchSuccessiveHalving-49.R
  Saving _problems/test_TunerBatchSuccessiveHalving-60.R
  Saving _problems/test_TunerBatchSuccessiveHalving-68.R
  Saving _problems/test_TunerBatchSuccessiveHalving-79.R
  Saving _problems/test_TunerBatchSuccessiveHalving-100.R
  Saving _problems/test_TunerBatchSuccessiveHalving-126.R
  Saving _problems/test_TunerBatchSuccessiveHalving-146.R
  Saving _problems/test_TunerBatchSuccessiveHalving-166.R
  Saving _problems/test_TunerBatchSuccessiveHalving-177.R
  Saving _problems/test_TunerBatchSuccessiveHalving-189.R
  Saving _problems/test_TunerBatchSuccessiveHalving-196.R
  Saving _problems/test_TunerBatchSuccessiveHalving-208.R
  Saving _problems/test_TunerBatchSuccessiveHalving-222.R
  Saving _problems/test_TunerBatchSuccessiveHalving-237.R
  Saving _problems/test_TunerBatchSuccessiveHalving-245.R
  Saving _problems/test_TunerBatchSuccessiveHalving-251.R
  Saving _problems/test_TunerBatchSuccessiveHalving-257.R
  [ FAIL 40 | WARN 40 | SKIP 1 | PASS 28 ]
  
  ══ Skipped tests (1) ═══════════════════════════════════════════════════════════
  • On CRAN (1): 'test_TunerAsyncSuccessiveHalving.R:2:1'
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test_TunerBatchHyperband.R:4:3'): TunerBatchHyperband works ─────────
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:4:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:28:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima")
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:10:3'): TunerBatchHyperband works with minimum budget > 1 ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:10:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:28:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:28:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:16:3'): TunerBatchHyperband rounds budget ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:16:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:28:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:28:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:22:3'): TunerBatchHyperband works with eta = 2.5 ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2.5, learner) at test_TunerBatchHyperband.R:22:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:28:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:28:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:37:3'): TunerBatchHyperband works with xgboost ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:37:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:28:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:28:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:48:3'): TunerBatchHyperband works with subsampling ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_hyperband(eta = 3, graph_learner) at test_TunerBatchHyperband.R:48:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:28:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:28:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:55:3'): TunerBatchHyperband works works with multi-crit ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:55:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:28:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:28:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:69:3'): TunerBatchHyperband works with custom sampler ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner, sampler = sampler) at test_TunerBatchHyperband.R:69:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:28:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:28:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:80:3'): TunerBatchHyperband errors if not enough parameters are sampled ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─testthat::expect_error(...) at test_TunerBatchHyperband.R:80:3
    2. │ └─testthat:::expect_condition_matching_(...)
    3. │   └─testthat:::quasi_capture(...)
    4. │     ├─testthat (local) .capture(...)
    5. │     │ └─base::withCallingHandlers(...)
    6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    7. ├─mlr3tuning::tune(...)
    8. │ └─TuningInstance$new(...)
    9. │   └─mlr3tuning (local) initialize(...)
   10. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
   11. │       └─mlr3::assert_measures(...)
   12. │         └─base::lapply(...)
   13. │           └─mlr3 (local) FUN(X[[i]], ...)
   14. └─mlr3::tsk("pima")
   15.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   16.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   17.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   18.         ├─base::do.call(constructor, cargs)
   19.         └─mlr3 (local) `<fn>`()
   20.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:106:3'): TunerBatchHyperband errors if budget parameter is sampled ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─testthat::expect_error(...) at test_TunerBatchHyperband.R:106:3
    2. │ └─testthat:::expect_condition_matching_(...)
    3. │   └─testthat:::quasi_capture(...)
    4. │     ├─testthat (local) .capture(...)
    5. │     │ └─base::withCallingHandlers(...)
    6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    7. ├─mlr3tuning::tune(...)
    8. │ └─TuningInstance$new(...)
    9. │   └─mlr3tuning (local) initialize(...)
   10. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
   11. │       └─mlr3::assert_measures(...)
   12. │         └─base::lapply(...)
   13. │           └─mlr3 (local) FUN(X[[i]], ...)
   14. └─mlr3::tsk("pima")
   15.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   16.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   17.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   18.         ├─base::do.call(constructor, cargs)
   19.         └─mlr3 (local) `<fn>`()
   20.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:126:3'): TunerBatchHyperband errors if budget parameter is not numeric ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─testthat::expect_error(...) at test_TunerBatchHyperband.R:126:3
    2. │ └─testthat:::expect_condition_matching_(...)
    3. │   └─testthat:::quasi_capture(...)
    4. │     ├─testthat (local) .capture(...)
    5. │     │ └─base::withCallingHandlers(...)
    6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    7. ├─mlr3tuning::tune(...)
    8. │ └─TuningInstance$new(...)
    9. │   └─mlr3tuning (local) initialize(...)
   10. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
   11. │       └─mlr3::assert_measures(...)
   12. │         └─base::lapply(...)
   13. │           └─mlr3 (local) FUN(X[[i]], ...)
   14. └─mlr3::tsk("pima")
   15.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   16.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   17.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   18.         ├─base::do.call(constructor, cargs)
   19.         └─mlr3 (local) `<fn>`()
   20.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:146:3'): TunerBatchHyperband errors if multiple budget parameters are set ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─testthat::expect_error(...) at test_TunerBatchHyperband.R:146:3
    2. │ └─testthat:::expect_condition_matching_(...)
    3. │   └─testthat:::quasi_capture(...)
    4. │     ├─testthat (local) .capture(...)
    5. │     │ └─base::withCallingHandlers(...)
    6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    7. ├─mlr3tuning::tune(...)
    8. │ └─TuningInstance$new(...)
    9. │   └─mlr3tuning (local) initialize(...)
   10. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
   11. │       └─mlr3::assert_measures(...)
   12. │         └─base::lapply(...)
   13. │           └─mlr3 (local) FUN(X[[i]], ...)
   14. └─mlr3::tsk("pima")
   15.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   16.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   17.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   18.         ├─base::do.call(constructor, cargs)
   19.         └─mlr3 (local) `<fn>`()
   20.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:162:3'): TunerBatchHyperband minimizes measure ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:162:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:28:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   │             └─"weights_measure" %chin% task$properties
   10.   └─mlr3::tsk("pima") at ./helper.R:28:3
   11.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   12.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   13.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   14.           ├─base::do.call(constructor, cargs)
   15.           └─mlr3 (local) `<fn>`()
   16.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:172:3'): TunerBatchHyperband maximizes measure ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:172:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:28:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   │             └─"weights_measure" %chin% task$properties
   10.   └─mlr3::tsk("pima") at ./helper.R:28:3
   11.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   12.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   13.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   14.           ├─base::do.call(constructor, cargs)
   15.           └─mlr3 (local) `<fn>`()
   16.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:182:3'): TunerBatchHyperband works with single budget value ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:182:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:28:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:28:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:188:3'): TunerBatchHyperband works with repetitions ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:188:3
    2. │ └─TuningInstance$new(...)
    3. │   └─mlr3tuning (local) initialize(...)
    4. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    5. │       └─mlr3::assert_measures(...)
    6. │         └─base::lapply(...)
    7. │           └─mlr3 (local) FUN(X[[i]], ...)
    8. └─mlr3::tsk("pima")
    9.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   10.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   11.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   12.         ├─base::do.call(constructor, cargs)
   13.         └─mlr3 (local) `<fn>`()
   14.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:202:3'): TunerBatchHyperband terminates itself ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:202:3
    2. │ └─TuningInstance$new(...)
    3. │   └─mlr3tuning (local) initialize(...)
    4. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    5. │       └─mlr3::assert_measures(...)
    6. │         └─base::lapply(...)
    7. │           └─mlr3 (local) FUN(X[[i]], ...)
    8. └─mlr3::tsk("pima")
    9.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   10.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   11.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   12.         ├─base::do.call(constructor, cargs)
   13.         └─mlr3 (local) `<fn>`()
   14.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchHyperband.R:216:3'): TunerBatchHyperband works with infinite repetitions ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:216:3
    2. │ └─TuningInstance$new(...)
    3. │   └─mlr3tuning (local) initialize(...)
    4. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    5. │       └─mlr3::assert_measures(...)
    6. │         └─base::lapply(...)
    7. │           └─mlr3 (local) FUN(X[[i]], ...)
    8. └─mlr3::tsk("pima")
    9.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   10.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   11.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   12.         ├─base::do.call(constructor, cargs)
   13.         └─mlr3 (local) `<fn>`()
   14.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:4:3'): TunerBatchSuccessiveHalving works ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:4:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima")
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:10:3'): TunerBatchSuccessiveHalving works with minimum budget > 1 ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:10:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:69:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:16:3'): TunerBatchSuccessiveHalving rounds budget ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:16:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:69:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:22:3'): TunerBatchSuccessiveHalving works with eta = 2.5 ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:22:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:69:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:28:3'): TunerBatchSuccessiveHalving adjusts minimum budget ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:28:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:69:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:49:3'): TunerBatchSuccessiveHalving works with xgboost ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:49:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:69:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:60:3'): TunerBatchSuccessiveHalving works with subsampling ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:60:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:69:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:68:3'): TunerBatchSuccessiveHalving works with multi-crit ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:68:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:69:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:79:3'): TunerBatchSuccessiveHalving works with custom sampler ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:79:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:69:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:90:3'): TunerBatchSuccessiveHalving errors if not enough parameters are sampled ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─testthat::expect_error(...) at test_TunerBatchSuccessiveHalving.R:90:3
    2. │ └─testthat:::expect_condition_matching_(...)
    3. │   └─testthat:::quasi_capture(...)
    4. │     ├─testthat (local) .capture(...)
    5. │     │ └─base::withCallingHandlers(...)
    6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    7. ├─mlr3tuning::tune(...)
    8. │ └─TuningInstance$new(...)
    9. │   └─mlr3tuning (local) initialize(...)
   10. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
   11. │       └─mlr3::assert_measures(...)
   12. │         └─base::lapply(...)
   13. │           └─mlr3 (local) FUN(X[[i]], ...)
   14. └─mlr3::tsk("pima")
   15.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   16.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   17.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   18.         ├─base::do.call(constructor, cargs)
   19.         └─mlr3 (local) `<fn>`()
   20.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:116:3'): TunerBatchSuccessiveHalving errors if budget parameter is sampled ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─testthat::expect_error(...) at test_TunerBatchSuccessiveHalving.R:116:3
    2. │ └─testthat:::expect_condition_matching_(...)
    3. │   └─testthat:::quasi_capture(...)
    4. │     ├─testthat (local) .capture(...)
    5. │     │ └─base::withCallingHandlers(...)
    6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    7. ├─mlr3tuning::tune(...)
    8. │ └─TuningInstance$new(...)
    9. │   └─mlr3tuning (local) initialize(...)
   10. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
   11. │       └─mlr3::assert_measures(...)
   12. │         └─base::lapply(...)
   13. │           └─mlr3 (local) FUN(X[[i]], ...)
   14. └─mlr3::tsk("pima")
   15.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   16.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   17.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   18.         ├─base::do.call(constructor, cargs)
   19.         └─mlr3 (local) `<fn>`()
   20.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:136:3'): TunerBatchSuccessiveHalving errors if budget parameter is not numeric ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─testthat::expect_error(...) at test_TunerBatchSuccessiveHalving.R:136:3
    2. │ └─testthat:::expect_condition_matching_(...)
    3. │   └─testthat:::quasi_capture(...)
    4. │     ├─testthat (local) .capture(...)
    5. │     │ └─base::withCallingHandlers(...)
    6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    7. ├─mlr3tuning::tune(...)
    8. │ └─TuningInstance$new(...)
    9. │   └─mlr3tuning (local) initialize(...)
   10. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
   11. │       └─mlr3::assert_measures(...)
   12. │         └─base::lapply(...)
   13. │           └─mlr3 (local) FUN(X[[i]], ...)
   14. └─mlr3::tsk("pima")
   15.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   16.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   17.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   18.         ├─base::do.call(constructor, cargs)
   19.         └─mlr3 (local) `<fn>`()
   20.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:156:3'): TunerBatchSuccessiveHalving errors if multiple budget parameters are set ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─testthat::expect_error(...) at test_TunerBatchSuccessiveHalving.R:156:3
    2. │ └─testthat:::expect_condition_matching_(...)
    3. │   └─testthat:::quasi_capture(...)
    4. │     ├─testthat (local) .capture(...)
    5. │     │ └─base::withCallingHandlers(...)
    6. │     └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    7. ├─mlr3tuning::tune(...)
    8. │ └─TuningInstance$new(...)
    9. │   └─mlr3tuning (local) initialize(...)
   10. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
   11. │       └─mlr3::assert_measures(...)
   12. │         └─base::lapply(...)
   13. │           └─mlr3 (local) FUN(X[[i]], ...)
   14. └─mlr3::tsk("pima")
   15.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   16.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   17.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   18.         ├─base::do.call(constructor, cargs)
   19.         └─mlr3 (local) `<fn>`()
   20.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:172:3'): TunerBatchSuccessiveHalving minimizes measure ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:172:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   │             └─"weights_measure" %chin% task$properties
   10.   └─mlr3::tsk("pima") at ./helper.R:69:3
   11.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   12.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   13.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   14.           ├─base::do.call(constructor, cargs)
   15.           └─mlr3 (local) `<fn>`()
   16.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:184:3'): TunerBatchSuccessiveHalving maximizes measure ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:184:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   │             └─"weights_measure" %chin% task$properties
   10.   └─mlr3::tsk("pima") at ./helper.R:69:3
   11.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   12.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   13.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   14.           ├─base::do.call(constructor, cargs)
   15.           └─mlr3 (local) `<fn>`()
   16.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:196:3'): TunerBatchSuccessiveHalving works with single budget value ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:196:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:69:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:202:3'): TunerBatchSuccessiveHalving works with repetitions ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:202:3
    2. │ └─TuningInstance$new(...)
    3. │   └─mlr3tuning (local) initialize(...)
    4. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    5. │       └─mlr3::assert_measures(...)
    6. │         └─base::lapply(...)
    7. │           └─mlr3 (local) FUN(X[[i]], ...)
    8. └─mlr3::tsk("pima")
    9.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   10.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   11.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   12.         ├─base::do.call(constructor, cargs)
   13.         └─mlr3 (local) `<fn>`()
   14.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:216:3'): TunerBatchSuccessiveHalving terminates itself ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:216:3
    2. │ └─TuningInstance$new(...)
    3. │   └─mlr3tuning (local) initialize(...)
    4. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    5. │       └─mlr3::assert_measures(...)
    6. │         └─base::lapply(...)
    7. │           └─mlr3 (local) FUN(X[[i]], ...)
    8. └─mlr3::tsk("pima")
    9.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   10.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   11.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   12.         ├─base::do.call(constructor, cargs)
   13.         └─mlr3 (local) `<fn>`()
   14.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:230:3'): TunerBatchSuccessiveHalving works with infinite repetitions ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. ├─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:230:3
    2. │ └─TuningInstance$new(...)
    3. │   └─mlr3tuning (local) initialize(...)
    4. │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    5. │       └─mlr3::assert_measures(...)
    6. │         └─base::lapply(...)
    7. │           └─mlr3 (local) FUN(X[[i]], ...)
    8. └─mlr3::tsk("pima")
    9.   └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   10.     └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   11.       └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   12.         ├─base::do.call(constructor, cargs)
   13.         └─mlr3 (local) `<fn>`()
   14.           └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:245:3'): TunerBatchSuccessiveHalving works with r_max > n ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:245:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:69:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:251:3'): TunerBatchSuccessiveHalving works with r_max < n ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:251:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:69:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  ── Error ('test_TunerBatchSuccessiveHalving.R:257:3'): TunerBatchSuccessiveHalving works with r_max < n and adjust minimum budget ──
  Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
  Backtrace:
       ▆
    1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:257:3
    2.   ├─mlr3tuning::tune(...) at ./helper.R:69:3
    3.   │ └─TuningInstance$new(...)
    4.   │   └─mlr3tuning (local) initialize(...)
    5.   │     └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
    6.   │       └─mlr3::assert_measures(...)
    7.   │         └─base::lapply(...)
    8.   │           └─mlr3 (local) FUN(X[[i]], ...)
    9.   └─mlr3::tsk("pima") at ./helper.R:69:3
   10.     └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
   11.       └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
   12.         └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
   13.           ├─base::do.call(constructor, cargs)
   14.           └─mlr3 (local) `<fn>`()
   15.             └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
  
  [ FAIL 40 | WARN 40 | SKIP 1 | PASS 28 ]
  Error:
  ! Test failures.
  Execution halted