Last updated on 2026-07-24 20:49:02 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.1.0 | 5.96 | 312.97 | 318.93 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.1.0 | 4.59 | 206.62 | 211.21 | OK | |
| r-devel-linux-x86_64-fedora-clang | 1.1.0 | 10.00 | 129.96 | 139.96 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 1.1.0 | 60.51 | ERROR | |||
| r-devel-windows-x86_64 | 1.1.0 | 7.00 | 282.00 | 289.00 | OK | |
| r-patched-linux-x86_64 | 1.1.0 | 7.09 | 276.89 | 283.98 | OK | |
| r-release-linux-x86_64 | 1.1.0 | 6.21 | 277.30 | 283.51 | OK | |
| r-release-macos-arm64 | 1.1.0 | 2.00 | 65.00 | 67.00 | OK | |
| r-release-macos-x86_64 | 1.1.0 | 4.00 | 316.00 | 320.00 | OK | |
| r-release-windows-x86_64 | 1.1.0 | 9.00 | 287.00 | 296.00 | OK | |
| r-oldrel-macos-arm64 | 1.1.0 | 1.00 | 64.00 | 65.00 | OK | |
| r-oldrel-macos-x86_64 | 1.1.0 | 4.00 | 266.00 | 270.00 | OK | |
| r-oldrel-windows-x86_64 | 1.1.0 | 10.00 | 417.00 | 427.00 | OK |
Version: 1.1.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [48s/55s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3hyperband")
+ test_check("mlr3hyperband")
+ }
Loading required package: mlr3tuning
Loading required package: mlr3
Loading required package: paradox
Saving _problems/test_TunerBatchHyperband-4.R
Saving _problems/test_TunerBatchHyperband-10.R
Saving _problems/test_TunerBatchHyperband-16.R
Saving _problems/test_TunerBatchHyperband-22.R
Saving _problems/test_TunerBatchHyperband-37.R
Saving _problems/test_TunerBatchHyperband-48.R
Saving _problems/test_TunerBatchHyperband-55.R
Saving _problems/test_TunerBatchHyperband-69.R
Saving _problems/test_TunerBatchHyperband-90.R
Saving _problems/test_TunerBatchHyperband-116.R
Saving _problems/test_TunerBatchHyperband-136.R
Saving _problems/test_TunerBatchHyperband-156.R
Saving _problems/test_TunerBatchHyperband-162.R
Saving _problems/test_TunerBatchHyperband-172.R
Saving _problems/test_TunerBatchHyperband-182.R
Saving _problems/test_TunerBatchHyperband-194.R
Saving _problems/test_TunerBatchHyperband-208.R
Saving _problems/test_TunerBatchHyperband-223.R
Saving _problems/test_TunerBatchSuccessiveHalving-4.R
Saving _problems/test_TunerBatchSuccessiveHalving-10.R
Saving _problems/test_TunerBatchSuccessiveHalving-16.R
Saving _problems/test_TunerBatchSuccessiveHalving-22.R
Saving _problems/test_TunerBatchSuccessiveHalving-28.R
Saving _problems/test_TunerBatchSuccessiveHalving-49.R
Saving _problems/test_TunerBatchSuccessiveHalving-60.R
Saving _problems/test_TunerBatchSuccessiveHalving-68.R
Saving _problems/test_TunerBatchSuccessiveHalving-79.R
Saving _problems/test_TunerBatchSuccessiveHalving-100.R
Saving _problems/test_TunerBatchSuccessiveHalving-126.R
Saving _problems/test_TunerBatchSuccessiveHalving-146.R
Saving _problems/test_TunerBatchSuccessiveHalving-166.R
Saving _problems/test_TunerBatchSuccessiveHalving-177.R
Saving _problems/test_TunerBatchSuccessiveHalving-189.R
Saving _problems/test_TunerBatchSuccessiveHalving-196.R
Saving _problems/test_TunerBatchSuccessiveHalving-208.R
Saving _problems/test_TunerBatchSuccessiveHalving-222.R
Saving _problems/test_TunerBatchSuccessiveHalving-237.R
Saving _problems/test_TunerBatchSuccessiveHalving-245.R
Saving _problems/test_TunerBatchSuccessiveHalving-251.R
Saving _problems/test_TunerBatchSuccessiveHalving-257.R
[ FAIL 40 | WARN 40 | SKIP 1 | PASS 28 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test_TunerAsyncSuccessiveHalving.R:2:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_TunerBatchHyperband.R:4:3'): TunerBatchHyperband works ─────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:4:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima")
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:10:3'): TunerBatchHyperband works with minimum budget > 1 ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:10:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:16:3'): TunerBatchHyperband rounds budget ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:16:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:22:3'): TunerBatchHyperband works with eta = 2.5 ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2.5, learner) at test_TunerBatchHyperband.R:22:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:37:3'): TunerBatchHyperband works with xgboost ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:37:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:48:3'): TunerBatchHyperband works with subsampling ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 3, graph_learner) at test_TunerBatchHyperband.R:48:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:55:3'): TunerBatchHyperband works works with multi-crit ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:55:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:69:3'): TunerBatchHyperband works with custom sampler ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner, sampler = sampler) at test_TunerBatchHyperband.R:69:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:80:3'): TunerBatchHyperband errors if not enough parameters are sampled ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchHyperband.R:80:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:106:3'): TunerBatchHyperband errors if budget parameter is sampled ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchHyperband.R:106:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:126:3'): TunerBatchHyperband errors if budget parameter is not numeric ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchHyperband.R:126:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:146:3'): TunerBatchHyperband errors if multiple budget parameters are set ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchHyperband.R:146:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:162:3'): TunerBatchHyperband minimizes measure ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:162:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. │ └─"weights_measure" %chin% task$properties
10. └─mlr3::tsk("pima") at ./helper.R:28:3
11. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
12. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
13. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
14. ├─base::do.call(constructor, cargs)
15. └─mlr3 (local) `<fn>`()
16. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:172:3'): TunerBatchHyperband maximizes measure ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:172:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. │ └─"weights_measure" %chin% task$properties
10. └─mlr3::tsk("pima") at ./helper.R:28:3
11. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
12. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
13. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
14. ├─base::do.call(constructor, cargs)
15. └─mlr3 (local) `<fn>`()
16. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:182:3'): TunerBatchHyperband works with single budget value ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:182:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:188:3'): TunerBatchHyperband works with repetitions ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:188:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:202:3'): TunerBatchHyperband terminates itself ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:202:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:216:3'): TunerBatchHyperband works with infinite repetitions ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:216:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:4:3'): TunerBatchSuccessiveHalving works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:4:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima")
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:10:3'): TunerBatchSuccessiveHalving works with minimum budget > 1 ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:10:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:16:3'): TunerBatchSuccessiveHalving rounds budget ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:16:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:22:3'): TunerBatchSuccessiveHalving works with eta = 2.5 ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:22:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:28:3'): TunerBatchSuccessiveHalving adjusts minimum budget ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:28:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:49:3'): TunerBatchSuccessiveHalving works with xgboost ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:49:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:60:3'): TunerBatchSuccessiveHalving works with subsampling ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:60:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:68:3'): TunerBatchSuccessiveHalving works with multi-crit ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:68:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:79:3'): TunerBatchSuccessiveHalving works with custom sampler ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:79:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:90:3'): TunerBatchSuccessiveHalving errors if not enough parameters are sampled ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchSuccessiveHalving.R:90:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:116:3'): TunerBatchSuccessiveHalving errors if budget parameter is sampled ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchSuccessiveHalving.R:116:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:136:3'): TunerBatchSuccessiveHalving errors if budget parameter is not numeric ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchSuccessiveHalving.R:136:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:156:3'): TunerBatchSuccessiveHalving errors if multiple budget parameters are set ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchSuccessiveHalving.R:156:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:172:3'): TunerBatchSuccessiveHalving minimizes measure ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:172:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. │ └─"weights_measure" %chin% task$properties
10. └─mlr3::tsk("pima") at ./helper.R:69:3
11. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
12. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
13. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
14. ├─base::do.call(constructor, cargs)
15. └─mlr3 (local) `<fn>`()
16. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:184:3'): TunerBatchSuccessiveHalving maximizes measure ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:184:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. │ └─"weights_measure" %chin% task$properties
10. └─mlr3::tsk("pima") at ./helper.R:69:3
11. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
12. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
13. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
14. ├─base::do.call(constructor, cargs)
15. └─mlr3 (local) `<fn>`()
16. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:196:3'): TunerBatchSuccessiveHalving works with single budget value ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:196:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:202:3'): TunerBatchSuccessiveHalving works with repetitions ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:202:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:216:3'): TunerBatchSuccessiveHalving terminates itself ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:216:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:230:3'): TunerBatchSuccessiveHalving works with infinite repetitions ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:230:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:245:3'): TunerBatchSuccessiveHalving works with r_max > n ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:245:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:251:3'): TunerBatchSuccessiveHalving works with r_max < n ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:251:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:257:3'): TunerBatchSuccessiveHalving works with r_max < n and adjust minimum budget ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:257:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
[ FAIL 40 | WARN 40 | SKIP 1 | PASS 28 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.1.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [20s/21s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3hyperband")
+ test_check("mlr3hyperband")
+ }
Loading required package: mlr3tuning
Loading required package: mlr3
Loading required package: paradox
Saving _problems/test_TunerBatchHyperband-4.R
Saving _problems/test_TunerBatchHyperband-10.R
Saving _problems/test_TunerBatchHyperband-16.R
Saving _problems/test_TunerBatchHyperband-22.R
Saving _problems/test_TunerBatchHyperband-37.R
Saving _problems/test_TunerBatchHyperband-48.R
Saving _problems/test_TunerBatchHyperband-55.R
Saving _problems/test_TunerBatchHyperband-69.R
Saving _problems/test_TunerBatchHyperband-90.R
Saving _problems/test_TunerBatchHyperband-116.R
Saving _problems/test_TunerBatchHyperband-136.R
Saving _problems/test_TunerBatchHyperband-156.R
Saving _problems/test_TunerBatchHyperband-162.R
Saving _problems/test_TunerBatchHyperband-172.R
Saving _problems/test_TunerBatchHyperband-182.R
Saving _problems/test_TunerBatchHyperband-194.R
Saving _problems/test_TunerBatchHyperband-208.R
Saving _problems/test_TunerBatchHyperband-223.R
Saving _problems/test_TunerBatchSuccessiveHalving-4.R
Saving _problems/test_TunerBatchSuccessiveHalving-10.R
Saving _problems/test_TunerBatchSuccessiveHalving-16.R
Saving _problems/test_TunerBatchSuccessiveHalving-22.R
Saving _problems/test_TunerBatchSuccessiveHalving-28.R
Saving _problems/test_TunerBatchSuccessiveHalving-49.R
Saving _problems/test_TunerBatchSuccessiveHalving-60.R
Saving _problems/test_TunerBatchSuccessiveHalving-68.R
Saving _problems/test_TunerBatchSuccessiveHalving-79.R
Saving _problems/test_TunerBatchSuccessiveHalving-100.R
Saving _problems/test_TunerBatchSuccessiveHalving-126.R
Saving _problems/test_TunerBatchSuccessiveHalving-146.R
Saving _problems/test_TunerBatchSuccessiveHalving-166.R
Saving _problems/test_TunerBatchSuccessiveHalving-177.R
Saving _problems/test_TunerBatchSuccessiveHalving-189.R
Saving _problems/test_TunerBatchSuccessiveHalving-196.R
Saving _problems/test_TunerBatchSuccessiveHalving-208.R
Saving _problems/test_TunerBatchSuccessiveHalving-222.R
Saving _problems/test_TunerBatchSuccessiveHalving-237.R
Saving _problems/test_TunerBatchSuccessiveHalving-245.R
Saving _problems/test_TunerBatchSuccessiveHalving-251.R
Saving _problems/test_TunerBatchSuccessiveHalving-257.R
[ FAIL 40 | WARN 40 | SKIP 1 | PASS 28 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test_TunerAsyncSuccessiveHalving.R:2:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_TunerBatchHyperband.R:4:3'): TunerBatchHyperband works ─────────
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:4:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima")
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:10:3'): TunerBatchHyperband works with minimum budget > 1 ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:10:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:16:3'): TunerBatchHyperband rounds budget ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:16:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:22:3'): TunerBatchHyperband works with eta = 2.5 ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2.5, learner) at test_TunerBatchHyperband.R:22:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:37:3'): TunerBatchHyperband works with xgboost ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:37:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:48:3'): TunerBatchHyperband works with subsampling ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 3, graph_learner) at test_TunerBatchHyperband.R:48:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:55:3'): TunerBatchHyperband works works with multi-crit ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:55:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:69:3'): TunerBatchHyperband works with custom sampler ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner, sampler = sampler) at test_TunerBatchHyperband.R:69:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:80:3'): TunerBatchHyperband errors if not enough parameters are sampled ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchHyperband.R:80:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:106:3'): TunerBatchHyperband errors if budget parameter is sampled ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchHyperband.R:106:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:126:3'): TunerBatchHyperband errors if budget parameter is not numeric ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchHyperband.R:126:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:146:3'): TunerBatchHyperband errors if multiple budget parameters are set ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchHyperband.R:146:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:162:3'): TunerBatchHyperband minimizes measure ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:162:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. │ └─"weights_measure" %chin% task$properties
10. └─mlr3::tsk("pima") at ./helper.R:28:3
11. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
12. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
13. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
14. ├─base::do.call(constructor, cargs)
15. └─mlr3 (local) `<fn>`()
16. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:172:3'): TunerBatchHyperband maximizes measure ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:172:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. │ └─"weights_measure" %chin% task$properties
10. └─mlr3::tsk("pima") at ./helper.R:28:3
11. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
12. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
13. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
14. ├─base::do.call(constructor, cargs)
15. └─mlr3 (local) `<fn>`()
16. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:182:3'): TunerBatchHyperband works with single budget value ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:182:3
2. ├─mlr3tuning::tune(...) at ./helper.R:28:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:28:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:188:3'): TunerBatchHyperband works with repetitions ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:188:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:202:3'): TunerBatchHyperband terminates itself ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:202:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchHyperband.R:216:3'): TunerBatchHyperband works with infinite repetitions ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:216:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:4:3'): TunerBatchSuccessiveHalving works ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:4:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima")
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:10:3'): TunerBatchSuccessiveHalving works with minimum budget > 1 ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:10:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:16:3'): TunerBatchSuccessiveHalving rounds budget ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:16:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:22:3'): TunerBatchSuccessiveHalving works with eta = 2.5 ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:22:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:28:3'): TunerBatchSuccessiveHalving adjusts minimum budget ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:28:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:49:3'): TunerBatchSuccessiveHalving works with xgboost ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:49:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:60:3'): TunerBatchSuccessiveHalving works with subsampling ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:60:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:68:3'): TunerBatchSuccessiveHalving works with multi-crit ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:68:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchMultiCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:79:3'): TunerBatchSuccessiveHalving works with custom sampler ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:79:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:90:3'): TunerBatchSuccessiveHalving errors if not enough parameters are sampled ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchSuccessiveHalving.R:90:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:116:3'): TunerBatchSuccessiveHalving errors if budget parameter is sampled ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchSuccessiveHalving.R:116:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:136:3'): TunerBatchSuccessiveHalving errors if budget parameter is not numeric ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchSuccessiveHalving.R:136:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:156:3'): TunerBatchSuccessiveHalving errors if multiple budget parameters are set ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerBatchSuccessiveHalving.R:156:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─TuningInstance$new(...)
9. │ └─mlr3tuning (local) initialize(...)
10. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
11. │ └─mlr3::assert_measures(...)
12. │ └─base::lapply(...)
13. │ └─mlr3 (local) FUN(X[[i]], ...)
14. └─mlr3::tsk("pima")
15. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
16. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
17. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
18. ├─base::do.call(constructor, cargs)
19. └─mlr3 (local) `<fn>`()
20. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:172:3'): TunerBatchSuccessiveHalving minimizes measure ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:172:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. │ └─"weights_measure" %chin% task$properties
10. └─mlr3::tsk("pima") at ./helper.R:69:3
11. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
12. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
13. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
14. ├─base::do.call(constructor, cargs)
15. └─mlr3 (local) `<fn>`()
16. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:184:3'): TunerBatchSuccessiveHalving maximizes measure ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:184:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. │ └─"weights_measure" %chin% task$properties
10. └─mlr3::tsk("pima") at ./helper.R:69:3
11. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
12. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
13. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
14. ├─base::do.call(constructor, cargs)
15. └─mlr3 (local) `<fn>`()
16. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:196:3'): TunerBatchSuccessiveHalving works with single budget value ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:196:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:202:3'): TunerBatchSuccessiveHalving works with repetitions ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:202:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:216:3'): TunerBatchSuccessiveHalving terminates itself ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:216:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:230:3'): TunerBatchSuccessiveHalving works with infinite repetitions ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:230:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
5. │ └─mlr3::assert_measures(...)
6. │ └─base::lapply(...)
7. │ └─mlr3 (local) FUN(X[[i]], ...)
8. └─mlr3::tsk("pima")
9. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor, cargs)
13. └─mlr3 (local) `<fn>`()
14. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:245:3'): TunerBatchSuccessiveHalving works with r_max > n ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:245:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:251:3'): TunerBatchSuccessiveHalving works with r_max < n ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:251:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
── Error ('test_TunerBatchSuccessiveHalving.R:257:3'): TunerBatchSuccessiveHalving works with r_max < n and adjust minimum budget ──
Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL"
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:257:3
2. ├─mlr3tuning::tune(...) at ./helper.R:69:3
3. │ └─TuningInstance$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__TuningInstanceBatchSingleCrit__initialize(...)
6. │ └─mlr3::assert_measures(...)
7. │ └─base::lapply(...)
8. │ └─mlr3 (local) FUN(X[[i]], ...)
9. └─mlr3::tsk("pima") at ./helper.R:69:3
10. └─mlr3misc::dictionary_sugar_get(dict = mlr_tasks, .key, ...)
11. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest)
12. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
13. ├─base::do.call(constructor, cargs)
14. └─mlr3 (local) `<fn>`()
15. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench"))
[ FAIL 40 | WARN 40 | SKIP 1 | PASS 28 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc