Last updated on 2026-07-24 20:49:02 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.6.0 | 14.04 | 667.93 | 681.97 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.6.0 | 9.96 | 466.97 | 476.93 | OK | |
| r-devel-linux-x86_64-fedora-clang | 1.6.0 | 25.00 | 739.41 | 764.41 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 1.6.0 | 10.00 | 299.79 | 309.79 | ERROR | |
| r-devel-windows-x86_64 | 1.6.0 | 17.00 | 627.00 | 644.00 | OK | |
| r-patched-linux-x86_64 | 1.6.0 | 17.10 | 643.63 | 660.73 | OK | |
| r-release-linux-x86_64 | 1.6.0 | 14.42 | 644.42 | 658.84 | OK | |
| r-release-macos-arm64 | 1.6.0 | 3.00 | 147.00 | 150.00 | OK | |
| r-release-macos-x86_64 | 1.6.0 | 10.00 | 780.00 | 790.00 | OK | |
| r-release-windows-x86_64 | 1.6.0 | 17.00 | 641.00 | 658.00 | OK | |
| r-oldrel-macos-arm64 | 1.6.0 | 3.00 | 147.00 | 150.00 | OK | |
| r-oldrel-macos-x86_64 | 1.6.0 | 10.00 | 606.00 | 616.00 | OK | |
| r-oldrel-windows-x86_64 | 1.6.0 | 22.00 | 903.00 | 925.00 | OK |
Version: 1.6.0
Check: examples
Result: ERROR
Running examples in ‘mlr3tuning-Ex.R’ failed
The error most likely occurred in:
> ### Name: auto_tuner
> ### Title: Function for Automatic Tuning
> ### Aliases: auto_tuner
>
> ### ** Examples
>
> at = auto_tuner(
+ tuner = tnr("random_search"),
+ learner = lrn("classif.rpart", cp = to_tune(1e-04, 1e-1, logscale = TRUE)),
+ resampling = rsmp ("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 4)
>
> at$train(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: <Anonymous> ... dictionary_initialize_item -> do.call -> <Anonymous> -> as_data_backend
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 1.6.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [9m/11m]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3tuning")
+ test_check("mlr3tuning")
+ }
Loading required package: mlr3
Loading required package: paradox
Saving _problems/test_ArchiveBatchTuning-123.R
Saving _problems/test_ArchiveBatchTuning-274.R
Saving _problems/test_AutoTuner-234.R
Saving _problems/test_AutoTuner-308.R
Saving _problems/test_AutoTuner-389.R
Saving _problems/test_CallbackBatchTuning-17.R
Saving _problems/test_CallbackBatchTuning-37.R
Saving _problems/test_CallbackBatchTuning-59.R
Saving _problems/test_CallbackBatchTuning-80.R
Saving _problems/test_CallbackBatchTuning-103.R
Saving _problems/test_CallbackBatchTuning-127.R
Saving _problems/test_CallbackBatchTuning-150.R
Saving _problems/test_CallbackBatchTuning-171.R
Saving _problems/test_CallbackBatchTuning-191.R
Saving _problems/test_CallbackBatchTuning-214.R
Saving _problems/test_CallbackBatchTuning-235.R
Saving _problems/test_CallbackBatchTuning-255.R
Saving _problems/test_CallbackBatchTuning-284.R
Saving _problems/test_CallbackBatchTuning-312.R
Saving _problems/test_CallbackBatchTuning-339.R
Saving _problems/test_CallbackBatchTuning-367.R
Saving _problems/test_ObjectiveTuningAsync-9.R
Saving _problems/test_ObjectiveTuningAsync-29.R
Saving _problems/test_ObjectiveTuningAsync-51.R
Saving _problems/test_ObjectiveTuningAsync-73.R
Saving _problems/test_Tuner-262.R
Saving _problems/test_Tuner-291.R
Saving _problems/test_TunerBatchCmaes-19.R
Saving _problems/test_TunerBatchFromOptimizerBatch-8.R
Saving _problems/test_TunerInternal-14.R
Saving _problems/test_TuningInstanceBatchMultiCrit-2.R
Saving _problems/test_TuningInstanceBatchMultiCrit-129.R
Saving _problems/test_TuningInstanceBatchMultiCrit-183.R
Saving _problems/test_TuningInstanceBatchSingleCrit-83.R
Saving _problems/test_TuningInstanceBatchSingleCrit-237.R
Saving _problems/test_TuningInstanceBatchSingleCrit-264.R
Saving _problems/test_TuningInstanceBatchSingleCrit-285.R
Saving _problems/test_TuningInstanceBatchSingleCrit-306.R
Saving _problems/test_TuningInstanceBatchSingleCrit-327.R
Saving _problems/test_TuningInstanceBatchSingleCrit-347.R
Saving _problems/test_TuningInstanceBatchSingleCrit-366.R
Saving _problems/test_TuningInstanceBatchSingleCrit-387.R
Saving _problems/test_TuningInstanceBatchSingleCrit-405.R
Saving _problems/test_TuningInstanceBatchSingleCrit-428.R
Saving _problems/test_TuningInstanceBatchSingleCrit-456.R
Saving _problems/test_mlr_callbacks-14.R
Saving _problems/test_mlr_callbacks-31.R
Saving _problems/test_mlr_callbacks-462.R
Saving _problems/test_ti-7.R
Saving _problems/test_ti-17.R
Saving _problems/test_tune-4.R
Saving _problems/test_tune-14.R
Saving _problems/test_tune-24.R
Saving _problems/test_tune_nested-6.R
[ FAIL 54 | WARN 54 | SKIP 24 | PASS 3684 ]
══ Skipped tests (24) ══════════════════════════════════════════════════════════
• On CRAN (24): 'test_ArchiveAsyncTuning.R:2:1',
'test_ArchiveAsyncTuningFrozen.R:2:1', 'test_AutoTuner.R:640:3',
'test_CallbackAsyncTuning.R:2:1', 'test_Tuner.R:53:1',
'test_TunerAsyncDesignPoints.R:2:1', 'test_TunerAsyncGridSearch.R:2:1',
'test_TunerAsyncRandomSearch.R:2:1',
'test_TuningInstanceAsyncMultiCrit.R:2:1',
'test_TuningInstanceAsyncSingleCrit.R:2:1', 'test_auto_tuner.R:25:3',
'test_auto_tuner.R:49:3', 'test_mlr_callbacks.R:40:3',
'test_mlr_callbacks.R:94:3', 'test_mlr_callbacks.R:120:3',
'test_mlr_callbacks.R:146:3', 'test_mlr_callbacks.R:169:3',
'test_mlr_callbacks.R:201:3', 'test_mlr_callbacks.R:229:3',
'test_mlr_callbacks.R:264:3', 'test_mlr_callbacks.R:425:3',
'test_mlr_callbacks.R:469:3', 'test_mlr_callbacks.R:497:3',
'test_ti_async.R:2:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ArchiveBatchTuning.R:117:3'): ArchiveTuning as.data.table function works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_ArchiveBatchTuning.R:117:3
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_ArchiveBatchTuning.R:267:3'): ArchiveBatchTuning as.data.table function works for internally tuned values ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_ArchiveBatchTuning.R:267:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_AutoTuner.R:234:3'): predict_type works ────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_AutoTuner.R:234:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_AutoTuner.R:308:3'): AutoTuner get_base_learner method works ───
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─at$train(tsk("pima")) at test_AutoTuner.R:308:3
2. │ └─mlr3:::.__Learner__train(...)
3. │ ├─mlr3::assert_task(as_task(task))
4. │ │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
5. │ │ └─checkmate::checkClass(x, classes, ordered, null.ok)
6. │ └─mlr3::as_task(task)
7. └─mlr3::tsk("pima")
8. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
9. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
10. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
11. ├─base::do.call(constructor, cargs)
12. └─mlr3 (local) `<fn>`()
13. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_AutoTuner.R:389:3'): AutoTuner works with empty search space ───
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─at$train(tsk("pima")) at test_AutoTuner.R:389:3
2. │ └─mlr3:::.__Learner__train(...)
3. │ ├─mlr3::assert_task(as_task(task))
4. │ │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
5. │ │ └─checkmate::checkClass(x, classes, ordered, null.ok)
6. │ └─mlr3::as_task(task)
7. └─mlr3::tsk("pima")
8. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
9. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
10. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
11. ├─base::do.call(constructor, cargs)
12. └─mlr3 (local) `<fn>`()
13. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:10:3'): on_optimization_begin works ──────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:10:3
2. │ └─TuningInstance$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_CallbackBatchTuning.R:30:3'): on_optimization_end works ────────
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_CallbackBatchTuning.R:30:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:52:3'): on_optimizer_after_eval works ────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:52:3
2. │ └─TuningInstance$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_CallbackBatchTuning.R:73:3'): on_optimizer_after_eval works ────
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_CallbackBatchTuning.R:73:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:96:3'): on_eval_after_design works ───────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:96:3
2. │ └─TuningInstance$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_CallbackBatchTuning.R:120:3'): on_eval_after_benchmark and on_eval_before_archive works ──
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_CallbackBatchTuning.R:120:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:143:3'): on_tuning_result_begin in TuningInstanceSingleCrit works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:143:3
2. │ └─TuningInstance$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_CallbackBatchTuning.R:164:3'): on_result_end in TuningInstanceSingleCrit works ──
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_CallbackBatchTuning.R:164:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:184:3'): on_result in TuningInstanceSingleCrit works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:184:3
2. │ └─TuningInstance$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_CallbackBatchTuning.R:207:3'): on_tuning_result_begin in TuningInstanceBatchMultiCrit works ──
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_CallbackBatchTuning.R:207:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:228:3'): on_result_end in TuningInstanceBatchMultiCrit works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:228:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__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_CallbackBatchTuning.R:248:3'): on_result in TuningInstanceBatchMultiCrit works ──
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_CallbackBatchTuning.R:248:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:277:3'): on_resample_begin works ─────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:277:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__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_CallbackBatchTuning.R:305:3'): on_resample_before_train works ──
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_CallbackBatchTuning.R:305:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:332:3'): on_resample_before_predict works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:332:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__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_CallbackBatchTuning.R:360:3'): on_resample_end works ───────────
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_CallbackBatchTuning.R:360:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_ObjectiveTuningAsync.R:2:3'): objective async works ────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─ObjectiveTuningAsync$new(...) at test_ObjectiveTuningAsync.R:2:3
2. │ └─mlr3tuning (local) initialize(...)
3. │ └─mlr3tuning:::.__ObjectiveTuning__initialize(...)
4. │ ├─mlr3::assert_task(as_task(task, clone = TRUE))
5. │ │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
6. │ │ └─checkmate::checkClass(x, classes, ordered, null.ok)
7. │ └─mlr3::as_task(task, clone = TRUE)
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_ObjectiveTuningAsync.R:22:3'): store benchmark result works ────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─ObjectiveTuningAsync$new(...) at test_ObjectiveTuningAsync.R:22:3
2. │ └─mlr3tuning (local) initialize(...)
3. │ └─mlr3tuning:::.__ObjectiveTuning__initialize(...)
4. │ ├─mlr3::assert_task(as_task(task, clone = TRUE))
5. │ │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
6. │ │ └─checkmate::checkClass(x, classes, ordered, null.ok)
7. │ └─mlr3::as_task(task, clone = TRUE)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_ObjectiveTuningAsync.R:44:3'): store models works ──────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─ObjectiveTuningAsync$new(...) at test_ObjectiveTuningAsync.R:44:3
2. │ └─mlr3tuning (local) initialize(...)
3. │ └─mlr3tuning:::.__ObjectiveTuning__initialize(...)
4. │ ├─mlr3::assert_task(as_task(task, clone = TRUE))
5. │ │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
6. │ │ └─checkmate::checkClass(x, classes, ordered, null.ok)
7. │ └─mlr3::as_task(task, clone = TRUE)
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_ObjectiveTuningAsync.R:66:3'): rush objective with multiple measures works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─ObjectiveTuningAsync$new(...) at test_ObjectiveTuningAsync.R:66:3
2. │ └─mlr3tuning (local) initialize(...)
3. │ └─mlr3tuning:::.__ObjectiveTuning__initialize(...)
4. │ ├─mlr3::assert_task(as_task(task, clone = TRUE))
5. │ │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
6. │ │ └─checkmate::checkClass(x, classes, ordered, null.ok)
7. │ └─mlr3::as_task(task, clone = TRUE)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_Tuner.R:256:3'): proper error when primary search space is empty ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_Tuner.R:256:3
2. │ └─TuningInstance$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_Tuner.R:285:3'): internal tuning: branching ────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_Tuner.R:285:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchCmaes.R:12:3'): TunerBatchCmaes ──────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchCmaes.R:12:3
2. │ └─TuningInstance$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_TunerBatchFromOptimizerBatch.R:2:3'): TunerBatchFromOptimizerBatch parameter set works after cloning ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_TunerBatchFromOptimizerBatch.R:2:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerInternal.R:4:3'): tuner internal works ────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_TunerInternal.R:4:3
2. │ └─TuningInstance$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_TuningInstanceBatchMultiCrit.R:2:3'): tuning with multiple objectives ──
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_TuningInstanceBatchMultiCrit.R:2:3
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_TuningInstanceBatchMultiCrit.R:122:3'): TuningInstanceBatchMultiCrit and empty search space works ──
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_TuningInstanceBatchMultiCrit.R:122:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TuningInstanceBatchMultiCrit.R:176:3'): Batch multi-crit internal tuning works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_TuningInstanceBatchMultiCrit.R:176:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__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_TuningInstanceBatchSingleCrit.R:83:3'): tuning with custom resampling ──
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_TuningInstanceBatchSingleCrit.R:83:3
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_TuningInstanceBatchSingleCrit.R:230:3'): TuningInstanceBatchSingleCrit and empty search space works ──
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_TuningInstanceBatchSingleCrit.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_TuningInstanceBatchSingleCrit.R:264:3'): assign_result works with one hyperparameter ──
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_TuningInstanceBatchSingleCrit.R:264:3
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_TuningInstanceBatchSingleCrit.R:285:3'): assign_result works with two hyperparameters ──
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_TuningInstanceBatchSingleCrit.R:285:3
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_TuningInstanceBatchSingleCrit.R:306:3'): assign_result works with two hyperparameters and one constant ──
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_TuningInstanceBatchSingleCrit.R:306:3
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_TuningInstanceBatchSingleCrit.R:327:3'): assign_result works with no hyperparameters and one constant ──
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_TuningInstanceBatchSingleCrit.R:327:3
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_TuningInstanceBatchSingleCrit.R:347:3'): assign_result works with no hyperparameters and two constant ──
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_TuningInstanceBatchSingleCrit.R:347:3
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_TuningInstanceBatchSingleCrit.R:366:3'): assign_result works with one hyperparameters and one constant ──
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_TuningInstanceBatchSingleCrit.R:366:3
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_TuningInstanceBatchSingleCrit.R:387:3'): assign_result works with no hyperparameter and constant ──
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_TuningInstanceBatchSingleCrit.R:387:3
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_TuningInstanceBatchSingleCrit.R:405:3'): objective contains no benchmark results ──
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_TuningInstanceBatchSingleCrit.R:405:3
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_TuningInstanceBatchSingleCrit.R:422:3'): dependencies in defaults work ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─checkmate::expect_class(...) at test_TuningInstanceBatchSingleCrit.R:422:3
2. │ └─checkmate::checkClass(x, classes, ordered, null.ok)
3. ├─mlr3tuning::tune(...)
4. │ └─TuningInstance$new(...)
5. │ └─mlr3tuning (local) initialize(...)
6. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
7. │ └─mlr3::assert_measures(...)
8. │ └─base::lapply(...)
9. │ └─mlr3 (local) FUN(X[[i]], ...)
10. └─mlr3::tsk("pima")
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_TuningInstanceBatchSingleCrit.R:449:3'): Batch single-crit internal tuning works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_TuningInstanceBatchSingleCrit.R:449:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_mlr_callbacks.R:6:3'): backup callback works ───────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_mlr_callbacks.R:6:3
2. │ └─TuningInstance$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_mlr_callbacks.R:23:3'): backup callback works with standalone tuner ──
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_mlr_callbacks.R:23:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_mlr_callbacks.R:454:3'): one se rule callback works ────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_mlr_callbacks.R:454:3
2. │ └─TuningInstance$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_ti.R:2:3'): ti function creates a TuningInstanceBatchSingleCrit ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_ti.R:2:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_ti.R:12:3'): ti function creates a TuningInstanceBatchMultiCrit ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_ti.R:12:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__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_tune.R:3:3'): tune function works with one measure ─────────────
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_tune.R:3:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_tune.R:13:3'): tune function works with multiple measures ──────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_tune.R:13:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__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_tune.R:23:3'): tune function works without measure ─────────────
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_tune.R:23:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ ├─mlr3::assert_measures(...)
6. │ │ └─checkmate::assert_list(measures, types = "Measure")
7. │ │ └─checkmate::checkList(...)
8. │ │ └─... %and% checkListTypes(x, types)
9. │ │ └─base::isTRUE(lhs)
10. │ ├─mlr3::as_measures(measure, task_type = task$task_type)
11. │ └─mlr3:::as_measures.NULL(measure, task_type = task$task_type)
12. │ └─mlr3::default_measures(task_type)
13. └─mlr3::tsk("pima")
14. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
15. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
16. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
17. ├─base::do.call(constructor, cargs)
18. └─mlr3 (local) `<fn>`()
19. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_tune_nested.R:5:3'): tune_nested function works ────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune_nested(...) at test_tune_nested.R:5:3
2. │ └─mlr3::assert_task(task)
3. │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
4. │ └─checkmate::checkClass(x, classes, ordered, null.ok)
5. └─mlr3::tsk("pima")
6. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
7. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
8. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
9. ├─base::do.call(constructor, cargs)
10. └─mlr3 (local) `<fn>`()
11. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
[ FAIL 54 | WARN 54 | SKIP 24 | PASS 3684 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.6.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [224s/230s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3tuning")
+ test_check("mlr3tuning")
+ }
Loading required package: mlr3
Loading required package: paradox
Saving _problems/test_ArchiveBatchTuning-123.R
Saving _problems/test_ArchiveBatchTuning-274.R
Saving _problems/test_AutoTuner-234.R
Saving _problems/test_AutoTuner-308.R
Saving _problems/test_AutoTuner-389.R
Saving _problems/test_CallbackBatchTuning-17.R
Saving _problems/test_CallbackBatchTuning-37.R
Saving _problems/test_CallbackBatchTuning-59.R
Saving _problems/test_CallbackBatchTuning-80.R
Saving _problems/test_CallbackBatchTuning-103.R
Saving _problems/test_CallbackBatchTuning-127.R
Saving _problems/test_CallbackBatchTuning-150.R
Saving _problems/test_CallbackBatchTuning-171.R
Saving _problems/test_CallbackBatchTuning-191.R
Saving _problems/test_CallbackBatchTuning-214.R
Saving _problems/test_CallbackBatchTuning-235.R
Saving _problems/test_CallbackBatchTuning-255.R
Saving _problems/test_CallbackBatchTuning-284.R
Saving _problems/test_CallbackBatchTuning-312.R
Saving _problems/test_CallbackBatchTuning-339.R
Saving _problems/test_CallbackBatchTuning-367.R
Saving _problems/test_ObjectiveTuningAsync-9.R
Saving _problems/test_ObjectiveTuningAsync-29.R
Saving _problems/test_ObjectiveTuningAsync-51.R
Saving _problems/test_ObjectiveTuningAsync-73.R
Saving _problems/test_Tuner-262.R
Saving _problems/test_Tuner-291.R
Saving _problems/test_TunerBatchCmaes-19.R
Saving _problems/test_TunerBatchFromOptimizerBatch-8.R
Saving _problems/test_TunerInternal-14.R
Saving _problems/test_TuningInstanceBatchMultiCrit-2.R
Saving _problems/test_TuningInstanceBatchMultiCrit-129.R
Saving _problems/test_TuningInstanceBatchMultiCrit-183.R
Saving _problems/test_TuningInstanceBatchSingleCrit-83.R
Saving _problems/test_TuningInstanceBatchSingleCrit-237.R
Saving _problems/test_TuningInstanceBatchSingleCrit-264.R
Saving _problems/test_TuningInstanceBatchSingleCrit-285.R
Saving _problems/test_TuningInstanceBatchSingleCrit-306.R
Saving _problems/test_TuningInstanceBatchSingleCrit-327.R
Saving _problems/test_TuningInstanceBatchSingleCrit-347.R
Saving _problems/test_TuningInstanceBatchSingleCrit-366.R
Saving _problems/test_TuningInstanceBatchSingleCrit-387.R
Saving _problems/test_TuningInstanceBatchSingleCrit-405.R
Saving _problems/test_TuningInstanceBatchSingleCrit-428.R
Saving _problems/test_TuningInstanceBatchSingleCrit-456.R
Saving _problems/test_mlr_callbacks-14.R
Saving _problems/test_mlr_callbacks-31.R
Saving _problems/test_mlr_callbacks-462.R
Saving _problems/test_ti-7.R
Saving _problems/test_ti-17.R
Saving _problems/test_tune-4.R
Saving _problems/test_tune-14.R
Saving _problems/test_tune-24.R
Saving _problems/test_tune_nested-6.R
[ FAIL 54 | WARN 54 | SKIP 24 | PASS 3684 ]
══ Skipped tests (24) ══════════════════════════════════════════════════════════
• On CRAN (24): 'test_ArchiveAsyncTuning.R:2:1',
'test_ArchiveAsyncTuningFrozen.R:2:1', 'test_AutoTuner.R:640:3',
'test_CallbackAsyncTuning.R:2:1', 'test_Tuner.R:53:1',
'test_TunerAsyncDesignPoints.R:2:1', 'test_TunerAsyncGridSearch.R:2:1',
'test_TunerAsyncRandomSearch.R:2:1',
'test_TuningInstanceAsyncMultiCrit.R:2:1',
'test_TuningInstanceAsyncSingleCrit.R:2:1', 'test_auto_tuner.R:25:3',
'test_auto_tuner.R:49:3', 'test_mlr_callbacks.R:40:3',
'test_mlr_callbacks.R:94:3', 'test_mlr_callbacks.R:120:3',
'test_mlr_callbacks.R:146:3', 'test_mlr_callbacks.R:169:3',
'test_mlr_callbacks.R:201:3', 'test_mlr_callbacks.R:229:3',
'test_mlr_callbacks.R:264:3', 'test_mlr_callbacks.R:425:3',
'test_mlr_callbacks.R:469:3', 'test_mlr_callbacks.R:497:3',
'test_ti_async.R:2:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ArchiveBatchTuning.R:117:3'): ArchiveTuning as.data.table function works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_ArchiveBatchTuning.R:117:3
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_ArchiveBatchTuning.R:267:3'): ArchiveBatchTuning as.data.table function works for internally tuned values ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_ArchiveBatchTuning.R:267:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_AutoTuner.R:234:3'): predict_type works ────────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3::tsk("pima") at test_AutoTuner.R:234:3
2. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_AutoTuner.R:308:3'): AutoTuner get_base_learner method works ───
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─at$train(tsk("pima")) at test_AutoTuner.R:308:3
2. │ └─mlr3:::.__Learner__train(...)
3. │ ├─mlr3::assert_task(as_task(task))
4. │ │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
5. │ │ └─checkmate::checkClass(x, classes, ordered, null.ok)
6. │ └─mlr3::as_task(task)
7. └─mlr3::tsk("pima")
8. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
9. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
10. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
11. ├─base::do.call(constructor, cargs)
12. └─mlr3 (local) `<fn>`()
13. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_AutoTuner.R:389:3'): AutoTuner works with empty search space ───
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─at$train(tsk("pima")) at test_AutoTuner.R:389:3
2. │ └─mlr3:::.__Learner__train(...)
3. │ ├─mlr3::assert_task(as_task(task))
4. │ │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
5. │ │ └─checkmate::checkClass(x, classes, ordered, null.ok)
6. │ └─mlr3::as_task(task)
7. └─mlr3::tsk("pima")
8. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
9. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
10. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
11. ├─base::do.call(constructor, cargs)
12. └─mlr3 (local) `<fn>`()
13. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:10:3'): on_optimization_begin works ──────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:10:3
2. │ └─TuningInstance$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_CallbackBatchTuning.R:30:3'): on_optimization_end works ────────
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_CallbackBatchTuning.R:30:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:52:3'): on_optimizer_after_eval works ────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:52:3
2. │ └─TuningInstance$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_CallbackBatchTuning.R:73:3'): on_optimizer_after_eval works ────
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_CallbackBatchTuning.R:73:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:96:3'): on_eval_after_design works ───────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:96:3
2. │ └─TuningInstance$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_CallbackBatchTuning.R:120:3'): on_eval_after_benchmark and on_eval_before_archive works ──
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_CallbackBatchTuning.R:120:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:143:3'): on_tuning_result_begin in TuningInstanceSingleCrit works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:143:3
2. │ └─TuningInstance$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_CallbackBatchTuning.R:164:3'): on_result_end in TuningInstanceSingleCrit works ──
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_CallbackBatchTuning.R:164:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:184:3'): on_result in TuningInstanceSingleCrit works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:184:3
2. │ └─TuningInstance$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_CallbackBatchTuning.R:207:3'): on_tuning_result_begin in TuningInstanceBatchMultiCrit works ──
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_CallbackBatchTuning.R:207:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:228:3'): on_result_end in TuningInstanceBatchMultiCrit works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:228:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__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_CallbackBatchTuning.R:248:3'): on_result in TuningInstanceBatchMultiCrit works ──
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_CallbackBatchTuning.R:248:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:277:3'): on_resample_begin works ─────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:277:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__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_CallbackBatchTuning.R:305:3'): on_resample_before_train works ──
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_CallbackBatchTuning.R:305:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_CallbackBatchTuning.R:332:3'): on_resample_before_predict works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:332:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__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_CallbackBatchTuning.R:360:3'): on_resample_end works ───────────
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_CallbackBatchTuning.R:360:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_ObjectiveTuningAsync.R:2:3'): objective async works ────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─ObjectiveTuningAsync$new(...) at test_ObjectiveTuningAsync.R:2:3
2. │ └─mlr3tuning (local) initialize(...)
3. │ └─mlr3tuning:::.__ObjectiveTuning__initialize(...)
4. │ ├─mlr3::assert_task(as_task(task, clone = TRUE))
5. │ │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
6. │ │ └─checkmate::checkClass(x, classes, ordered, null.ok)
7. │ └─mlr3::as_task(task, clone = TRUE)
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_ObjectiveTuningAsync.R:22:3'): store benchmark result works ────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─ObjectiveTuningAsync$new(...) at test_ObjectiveTuningAsync.R:22:3
2. │ └─mlr3tuning (local) initialize(...)
3. │ └─mlr3tuning:::.__ObjectiveTuning__initialize(...)
4. │ ├─mlr3::assert_task(as_task(task, clone = TRUE))
5. │ │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
6. │ │ └─checkmate::checkClass(x, classes, ordered, null.ok)
7. │ └─mlr3::as_task(task, clone = TRUE)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_ObjectiveTuningAsync.R:44:3'): store models works ──────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─ObjectiveTuningAsync$new(...) at test_ObjectiveTuningAsync.R:44:3
2. │ └─mlr3tuning (local) initialize(...)
3. │ └─mlr3tuning:::.__ObjectiveTuning__initialize(...)
4. │ ├─mlr3::assert_task(as_task(task, clone = TRUE))
5. │ │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
6. │ │ └─checkmate::checkClass(x, classes, ordered, null.ok)
7. │ └─mlr3::as_task(task, clone = TRUE)
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_ObjectiveTuningAsync.R:66:3'): rush objective with multiple measures works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─ObjectiveTuningAsync$new(...) at test_ObjectiveTuningAsync.R:66:3
2. │ └─mlr3tuning (local) initialize(...)
3. │ └─mlr3tuning:::.__ObjectiveTuning__initialize(...)
4. │ ├─mlr3::assert_task(as_task(task, clone = TRUE))
5. │ │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
6. │ │ └─checkmate::checkClass(x, classes, ordered, null.ok)
7. │ └─mlr3::as_task(task, clone = TRUE)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_Tuner.R:256:3'): proper error when primary search space is empty ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_Tuner.R:256:3
2. │ └─TuningInstance$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_Tuner.R:285:3'): internal tuning: branching ────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_Tuner.R:285:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchCmaes.R:12:3'): TunerBatchCmaes ──────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchCmaes.R:12:3
2. │ └─TuningInstance$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_TunerBatchFromOptimizerBatch.R:2:3'): TunerBatchFromOptimizerBatch parameter set works after cloning ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_TunerBatchFromOptimizerBatch.R:2:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerInternal.R:4:3'): tuner internal works ────────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_TunerInternal.R:4:3
2. │ └─TuningInstance$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_TuningInstanceBatchMultiCrit.R:2:3'): tuning with multiple objectives ──
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_TuningInstanceBatchMultiCrit.R:2:3
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_TuningInstanceBatchMultiCrit.R:122:3'): TuningInstanceBatchMultiCrit and empty search space works ──
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_TuningInstanceBatchMultiCrit.R:122:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TuningInstanceBatchMultiCrit.R:176:3'): Batch multi-crit internal tuning works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_TuningInstanceBatchMultiCrit.R:176:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__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_TuningInstanceBatchSingleCrit.R:83:3'): tuning with custom resampling ──
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_TuningInstanceBatchSingleCrit.R:83:3
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_TuningInstanceBatchSingleCrit.R:230:3'): TuningInstanceBatchSingleCrit and empty search space works ──
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_TuningInstanceBatchSingleCrit.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_TuningInstanceBatchSingleCrit.R:264:3'): assign_result works with one hyperparameter ──
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_TuningInstanceBatchSingleCrit.R:264:3
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_TuningInstanceBatchSingleCrit.R:285:3'): assign_result works with two hyperparameters ──
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_TuningInstanceBatchSingleCrit.R:285:3
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_TuningInstanceBatchSingleCrit.R:306:3'): assign_result works with two hyperparameters and one constant ──
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_TuningInstanceBatchSingleCrit.R:306:3
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_TuningInstanceBatchSingleCrit.R:327:3'): assign_result works with no hyperparameters and one constant ──
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_TuningInstanceBatchSingleCrit.R:327:3
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_TuningInstanceBatchSingleCrit.R:347:3'): assign_result works with no hyperparameters and two constant ──
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_TuningInstanceBatchSingleCrit.R:347:3
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_TuningInstanceBatchSingleCrit.R:366:3'): assign_result works with one hyperparameters and one constant ──
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_TuningInstanceBatchSingleCrit.R:366:3
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_TuningInstanceBatchSingleCrit.R:387:3'): assign_result works with no hyperparameter and constant ──
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_TuningInstanceBatchSingleCrit.R:387:3
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_TuningInstanceBatchSingleCrit.R:405:3'): objective contains no benchmark results ──
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_TuningInstanceBatchSingleCrit.R:405:3
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_TuningInstanceBatchSingleCrit.R:422:3'): dependencies in defaults work ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─checkmate::expect_class(...) at test_TuningInstanceBatchSingleCrit.R:422:3
2. │ └─checkmate::checkClass(x, classes, ordered, null.ok)
3. ├─mlr3tuning::tune(...)
4. │ └─TuningInstance$new(...)
5. │ └─mlr3tuning (local) initialize(...)
6. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
7. │ └─mlr3::assert_measures(...)
8. │ └─base::lapply(...)
9. │ └─mlr3 (local) FUN(X[[i]], ...)
10. └─mlr3::tsk("pima")
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_TuningInstanceBatchSingleCrit.R:449:3'): Batch single-crit internal tuning works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_TuningInstanceBatchSingleCrit.R:449:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_mlr_callbacks.R:6:3'): backup callback works ───────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_mlr_callbacks.R:6:3
2. │ └─TuningInstance$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_mlr_callbacks.R:23:3'): backup callback works with standalone tuner ──
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_mlr_callbacks.R:23:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_mlr_callbacks.R:454:3'): one se rule callback works ────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_mlr_callbacks.R:454:3
2. │ └─TuningInstance$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_ti.R:2:3'): ti function creates a TuningInstanceBatchSingleCrit ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_ti.R:2:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_ti.R:12:3'): ti function creates a TuningInstanceBatchMultiCrit ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::ti(...) at test_ti.R:12:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__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_tune.R:3:3'): tune function works with one measure ─────────────
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_tune.R:3:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_tune.R:13:3'): tune function works with multiple measures ──────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_tune.R:13:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__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_tune.R:23:3'): tune function works without measure ─────────────
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_tune.R:23:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ ├─mlr3::assert_measures(...)
6. │ │ └─checkmate::assert_list(measures, types = "Measure")
7. │ │ └─checkmate::checkList(...)
8. │ │ └─... %and% checkListTypes(x, types)
9. │ │ └─base::isTRUE(lhs)
10. │ ├─mlr3::as_measures(measure, task_type = task$task_type)
11. │ └─mlr3:::as_measures.NULL(measure, task_type = task$task_type)
12. │ └─mlr3::default_measures(task_type)
13. └─mlr3::tsk("pima")
14. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
15. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
16. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
17. ├─base::do.call(constructor, cargs)
18. └─mlr3 (local) `<fn>`()
19. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_tune_nested.R:5:3'): tune_nested function works ────────────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune_nested(...) at test_tune_nested.R:5:3
2. │ └─mlr3::assert_task(task)
3. │ └─checkmate::assert_class(task, "Task", .var.name = .var.name)
4. │ └─checkmate::checkClass(x, classes, ordered, null.ok)
5. └─mlr3::tsk("pima")
6. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
7. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
8. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
9. ├─base::do.call(constructor, cargs)
10. └─mlr3 (local) `<fn>`()
11. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
[ FAIL 54 | WARN 54 | SKIP 24 | PASS 3684 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc