- using R Under development (unstable) (2026-07-23 r90295)
- using platform: x86_64-pc-linux-gnu
- R was compiled by
gcc-16 (Debian 16.1.0-2) 16.1.0
GNU Fortran (Debian 16.1.0-2) 16.1.0
- running under: Debian GNU/Linux forky/sid
- using session charset: UTF-8
* current time: 2026-07-24 16:05:26 UTC
- checking for file ‘mlr3hyperband/DESCRIPTION’ ... OK
- this is package ‘mlr3hyperband’ version ‘1.1.0’
- package encoding: UTF-8
- checking CRAN incoming feasibility ... [2s/2s] OK
- checking package namespace information ... OK
- checking package dependencies ... OK
- checking if this is a source package ... OK
- checking if there is a namespace ... OK
- checking for executable files ... OK
- checking for hidden files and directories ... OK
- checking for portable file names ... OK
- checking for sufficient/correct file permissions ... OK
- checking serialization versions ... OK
- checking whether package ‘mlr3hyperband’ can be installed ... OK
See the install log for details.
- checking package directory ... OK
- checking for future file timestamps ... OK
- checking DESCRIPTION meta-information ... OK
- checking top-level files ... OK
- checking for left-over files ... OK
- checking index information ... OK
- checking package subdirectories ... OK
- checking code files for non-ASCII characters ... OK
- checking R files for syntax errors ... OK
- checking whether the package can be loaded ... [1s/2s] OK
- checking whether the package can be loaded with stated dependencies ... [1s/1s] OK
- checking whether the package can be unloaded cleanly ... [1s/1s] OK
- checking whether the namespace can be loaded with stated dependencies ... [1s/1s] OK
- checking whether the namespace can be unloaded cleanly ... [1s/1s] OK
- checking loading without being on the library search path ... [1s/1s] OK
- checking whether startup messages can be suppressed ... [1s/1s] OK
- checking use of S3 registration ... OK
- checking dependencies in R code ... OK
- checking S3 generic/method consistency ... OK
- checking replacement functions ... OK
- checking foreign function calls ... OK
- checking R code for possible problems ... [8s/12s] OK
- checking Rd files ... [0s/1s] OK
- checking Rd metadata ... OK
- checking Rd line widths ... OK
- checking Rd cross-references ... OK
- checking for missing documentation entries ... OK
- checking for code/documentation mismatches ... OK
- checking Rd \usage sections ... OK
- checking Rd contents ... OK
- checking for unstated dependencies in examples ... OK
- checking examples ... [4s/4s] OK
- checking for unstated dependencies in ‘tests’ ... OK
- checking tests ... [21s/26s] ERROR
Running ‘testthat.R’ [21s/25s]
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
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Saving _problems/test_TunerBatchSuccessiveHalving-4.R
Saving _problems/test_TunerBatchSuccessiveHalving-10.R
Saving _problems/test_TunerBatchSuccessiveHalving-16.R
Saving _problems/test_TunerBatchSuccessiveHalving-22.R
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[ 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
- checking PDF version of manual ... [4s/5s] OK
- checking HTML version of manual ... [1s/2s] OK
- checking for non-standard things in the check directory ... OK
- DONE
Status: 1 ERROR