Last updated on 2024-06-30 00:59:46 CEST.
| Package | ERROR | NOTE | OK |
|---|---|---|---|
| bbotk | 2 | 11 | |
| farff | 1 | 12 | |
| mlr3 | 2 | 1 | 10 |
| mlr3batchmark | 13 | ||
| mlr3fselect | 3 | 10 | |
| mlr3hyperband | 3 | 10 | |
| mlr3learners | 2 | 11 | |
| mlr3spatial | 13 | ||
| mlr3tuning | 3 | 10 | |
| mlr3tuningspaces | 1 | 12 | |
| rush | 1 | 12 |
Current CRAN status: ERROR: 2, OK: 11
Version: 1.0.0
Check: package dependencies
Result: ERROR
Package required and available but unsuitable version: ‘paradox’
See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Current CRAN status: NOTE: 1, OK: 12
Version: 1.1.1
Check: Rd cross-references
Result: NOTE
Undeclared package ‘RWeka’ in Rd xrefs
Flavor: r-devel-linux-x86_64-fedora-clang
Current CRAN status: ERROR: 2, NOTE: 1, OK: 10
Version: 0.20.0
Check: Rd cross-references
Result: NOTE
Undeclared packages ‘mlr3tuning’, ‘mlr3batchmark’, ‘mlr3pipelines’ in Rd xrefs
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.20.0
Check: whether package can be installed
Result: WARN
Found the following significant warnings:
Note: possible error in 'p_int(1, default = 1, ': unused arguments (aggr = iter_aggr, in_tune_fn = iter_tune_fn, disable_in_tune = list(early_stopping = FALSE))
See ‘/Volumes/Builds/packages/big-sur-arm64/results/4.3/mlr3.Rcheck/00install.out’ for details.
Information on the location(s) of code generating the ‘Note’s can be
obtained by re-running with environment variable R_KEEP_PKG_SOURCE set
to ‘yes’.
Flavor: r-oldrel-macos-arm64
Version: 0.20.0
Check: R code for possible problems
Result: NOTE
.__LearnerClassifDebug__initialize: possible error in p_int(1, default
= 1, tags = c("train", "hotstart", "internal_tuning"), aggr =
iter_aggr, in_tune_fn = iter_tune_fn, disable_in_tune =
list(early_stopping = FALSE)): unused arguments (aggr = iter_aggr,
in_tune_fn = iter_tune_fn, disable_in_tune = list(early_stopping =
FALSE))
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Version: 0.20.0
Check: examples
Result: ERROR
Running examples in ‘mlr3-Ex.R’ failed
The error most likely occurred in:
> ### Name: HotstartStack
> ### Title: Stack for Hot Start Learners
> ### Aliases: HotstartStack
>
> ### ** Examples
>
> # train learner on pima task
> task = tsk("pima")
> learner = lrn("classif.debug", iter = 1)
Error in p_int(1, default = 1, tags = c("train", "hotstart", "internal_tuning"), :
unused arguments (aggr = iter_aggr, in_tune_fn = iter_tune_fn, disable_in_tune = list(early_stopping = FALSE))
Calls: lrn ... <Anonymous> -> initialize -> .__LearnerClassifDebug__initialize
Execution halted
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Version: 0.20.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [41s/46s]
Running the tests in ‘tests/testthat.R’ failed.
Last 13 lines of output:
Backtrace:
▆
1. └─mlr3::lrn("classif.debug") at test_set_threads.R:5:3
2. └─mlr3misc::dictionary_sugar_get(mlr_learners, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─LearnerClassifDebug$new()
8. └─mlr3 (local) initialize(...)
9. └─mlr3:::.__LearnerClassifDebug__initialize(...)
[ FAIL 123 | WARN 0 | SKIP 4 | PASS 11578 ]
Error: Test failures
Execution halted
Flavor: r-oldrel-macos-arm64
Version: 0.20.0
Check: whether package can be installed
Result: WARN
Found the following significant warnings:
Note: possible error in 'p_int(1, default = 1, ': unused arguments (aggr = iter_aggr, in_tune_fn = iter_tune_fn, disable_in_tune = list(early_stopping = FALSE))
See ‘/Volumes/Builds/packages/big-sur-x86_64/results/4.3/mlr3.Rcheck/00install.out’ for details.
Information on the location(s) of code generating the ‘Note’s can be
obtained by re-running with environment variable R_KEEP_PKG_SOURCE set
to ‘yes’.
Flavor: r-oldrel-macos-x86_64
Version: 0.20.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [72s/102s]
Running the tests in ‘tests/testthat.R’ failed.
Last 13 lines of output:
Backtrace:
▆
1. └─mlr3::lrn("classif.debug") at test_set_threads.R:5:3
2. └─mlr3misc::dictionary_sugar_get(mlr_learners, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3 (local) `<fn>`()
7. └─LearnerClassifDebug$new()
8. └─mlr3 (local) initialize(...)
9. └─mlr3:::.__LearnerClassifDebug__initialize(...)
[ FAIL 123 | WARN 0 | SKIP 4 | PASS 11578 ]
Error: Test failures
Execution halted
Flavor: r-oldrel-macos-x86_64
Current CRAN status: OK: 13
Current CRAN status: ERROR: 3, OK: 10
Version: 0.12.0
Check: R code for possible problems
Result: NOTE
.__FSelectorDesignPoints__initialize: no visible binding for global
variable ‘OptimizerDesignPoints’
.__FSelector__optimize: no visible binding for global variable
‘ContextOptimization’
.__FSelector__optimize: no visible global function definition for
‘optimize_default’
Undefined global functions or variables:
ContextOptimization OptimizerDesignPoints optimize_default
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.12.0
Check: Rd cross-references
Result: WARN
Missing link or links in Rd file 'CallbackFSelect.Rd':
‘[bbotk:CallbackOptimization]{bbotk::CallbackOptimization}’
Missing link or links in Rd file 'callback_fselect.Rd':
‘[bbotk:ContextOptimization]{bbotk::ContextOptimization}’
‘ContextOptimization’
See section 'Cross-references' in the 'Writing R Extensions' manual.
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.12.0
Check: examples
Result: ERROR
Running examples in ‘mlr3fselect-Ex.R’ failed
The error most likely occurred in:
> ### Name: CallbackFSelect
> ### Title: Create Feature Selection Callback
> ### Aliases: CallbackFSelect
>
> ### ** Examples
>
> # Write archive to disk
> callback_fselect("mlr3fselect.backup",
+ on_optimization_end = function(callback, context) {
+ saveRDS(context$instance$archive, "archive.rds")
+ }
+ )
Error: 'CallbackOptimization' is not an exported object from 'namespace:bbotk'
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.12.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [132s/82s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library(testthat)
+ library(checkmate)
+ library(mlr3fselect)
+ test_check("mlr3fselect")
+ }
Loading required package: mlr3
Starting 2 test processes
[ FAIL 94 | WARN 0 | SKIP 3 | PASS 125 ]
══ Skipped tests (3) ═══════════════════════════════════════════════════════════
• On CRAN (3): 'test_AutoFSelector.R:2:3', 'test_AutoFSelector.R:29:3',
'test_AutoFSelector.R:64:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ArchiveFSelect.R:2:3'): ArchiveFSelect access methods work ─────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveFSelect.R:2:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_ArchiveFSelect.R:54:3'): ArchiveFSelect as.data.table function works ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveFSelect.R:54:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_ArchiveFSelect.R:159:3'): global ties method works ─────────────
Error in `.__FSelectorDesignPoints__initialize(self = self, private = private,
super = super)`: object 'OptimizerDesignPoints' not found
Backtrace:
▆
1. ├─mlr3fselect::fselect(...) at test_ArchiveFSelect.R:159:3
2. │ └─mlr3fselect:::assert_fselector(fselector)
3. │ └─checkmate::assert_r6(fselector, "FSelector")
4. │ └─checkmate::checkR6(...)
5. └─mlr3fselect::fs("design_points", design = design)
6. └─mlr3misc::dictionary_sugar_get(mlr_fselectors, .key, ...)
7. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
8. │ └─checkmate::checkR6(...)
9. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
10. ├─base::do.call(constructor$new, cargs)
11. └─R6 (local) `<fn>`()
12. └─mlr3fselect (local) initialize(...)
13. └─mlr3fselect:::.__FSelectorDesignPoints__initialize(...)
14. └─super$initialize(optimizer = OptimizerDesignPoints$new(), man = "mlr3fselect::mlr_fselectors_design_points")
15. └─mlr3fselect:::.__FSelectorFromOptimizer__initialize(...)
16. └─bbotk::assert_optimizer(optimizer)
17. └─checkmate::assert_r6(optimizer, "Optimizer")
18. └─checkmate::checkR6(...)
── Error ('test_ArchiveFSelect.R:200:3'): local ties method works when maximize measure ──
Error in `.__FSelectorDesignPoints__initialize(self = self, private = private,
super = super)`: object 'OptimizerDesignPoints' not found
Backtrace:
▆
1. ├─mlr3fselect::fselect(...) at test_ArchiveFSelect.R:200:3
2. │ └─mlr3fselect:::assert_fselector(fselector)
3. │ └─checkmate::assert_r6(fselector, "FSelector")
4. │ └─checkmate::checkR6(...)
5. └─mlr3fselect::fs("design_points", design = design)
6. └─mlr3misc::dictionary_sugar_get(mlr_fselectors, .key, ...)
7. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
8. │ └─checkmate::checkR6(...)
9. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
10. ├─base::do.call(constructor$new, cargs)
11. └─R6 (local) `<fn>`()
12. └─mlr3fselect (local) initialize(...)
13. └─mlr3fselect:::.__FSelectorDesignPoints__initialize(...)
14. └─super$initialize(optimizer = OptimizerDesignPoints$new(), man = "mlr3fselect::mlr_fselectors_design_points")
15. └─mlr3fselect:::.__FSelectorFromOptimizer__initialize(...)
16. └─bbotk::assert_optimizer(optimizer)
17. └─checkmate::assert_r6(optimizer, "Optimizer")
18. └─checkmate::checkR6(...)
── Error ('test_ArchiveFSelect.R:228:3'): local ties method works when minimize measure ──
Error in `.__FSelectorDesignPoints__initialize(self = self, private = private,
super = super)`: object 'OptimizerDesignPoints' not found
Backtrace:
▆
1. ├─mlr3fselect::fselect(...) at test_ArchiveFSelect.R:228:3
2. │ └─mlr3fselect:::assert_fselector(fselector)
3. │ └─checkmate::assert_r6(fselector, "FSelector")
4. │ └─checkmate::checkR6(...)
5. └─mlr3fselect::fs("design_points", design = design)
6. └─mlr3misc::dictionary_sugar_get(mlr_fselectors, .key, ...)
7. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
8. │ └─checkmate::checkR6(...)
9. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
10. ├─base::do.call(constructor$new, cargs)
11. └─R6 (local) `<fn>`()
12. └─mlr3fselect (local) initialize(...)
13. └─mlr3fselect:::.__FSelectorDesignPoints__initialize(...)
14. └─super$initialize(optimizer = OptimizerDesignPoints$new(), man = "mlr3fselect::mlr_fselectors_design_points")
15. └─mlr3fselect:::.__FSelectorFromOptimizer__initialize(...)
16. └─bbotk::assert_optimizer(optimizer)
17. └─checkmate::assert_r6(optimizer, "Optimizer")
18. └─checkmate::checkR6(...)
── Error ('test_ArchiveFSelect.R:256:3'): local ties method works with batches ──
Error in `.__FSelectorDesignPoints__initialize(self = self, private = private,
super = super)`: object 'OptimizerDesignPoints' not found
Backtrace:
▆
1. ├─mlr3fselect::fselect(...) at test_ArchiveFSelect.R:256:3
2. │ └─mlr3fselect:::assert_fselector(fselector)
3. │ └─checkmate::assert_r6(fselector, "FSelector")
4. │ └─checkmate::checkR6(...)
5. └─mlr3fselect::fs("design_points", design = design, batch_size = 1)
6. └─mlr3misc::dictionary_sugar_get(mlr_fselectors, .key, ...)
7. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
8. │ └─checkmate::checkR6(...)
9. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
10. ├─base::do.call(constructor$new, cargs)
11. └─R6 (local) `<fn>`()
12. └─mlr3fselect (local) initialize(...)
13. └─mlr3fselect:::.__FSelectorDesignPoints__initialize(...)
14. └─super$initialize(optimizer = OptimizerDesignPoints$new(), man = "mlr3fselect::mlr_fselectors_design_points")
15. └─mlr3fselect:::.__FSelectorFromOptimizer__initialize(...)
16. └─bbotk::assert_optimizer(optimizer)
17. └─checkmate::assert_r6(optimizer, "Optimizer")
18. └─checkmate::checkR6(...)
── Failure ('test_AutoFSelector.R:136:3'): AutoFSelector works with GraphLearner ──
exists("validate", lrn) is not TRUE
`actual`: FALSE
`expected`: TRUE
Backtrace:
▆
1. └─global expect_learner(at) at test_AutoFSelector.R:136:3
2. └─testthat::expect_true(exists("validate", lrn))
── Failure ('test_AutoFSelector.R:136:3'): AutoFSelector works with GraphLearner ──
exists("internal_valid_scores", envir = lrn) is not TRUE
`actual`: FALSE
`expected`: TRUE
Backtrace:
▆
1. └─global expect_learner(at) at test_AutoFSelector.R:136:3
2. └─testthat::expect_true(exists("internal_valid_scores", envir = lrn))
── Failure ('test_AutoFSelector.R:136:3'): AutoFSelector works with GraphLearner ──
Check on 'mlr3misc::get_private(lrn)$.extract_internal_valid_scores' failed: Must be a function, not 'NULL'
Backtrace:
▆
1. └─global expect_learner(at) at test_AutoFSelector.R:136:3
2. └─checkmate::expect_function(mlr3misc::get_private(lrn)$.extract_internal_valid_scores)
3. └─checkmate::makeExpectation(x, res, info, label)
── Error ('test_AutoFSelector.R:136:3'): AutoFSelector works with GraphLearner ──
Error: at least one parameter must support internal tuning when the learner is tagged as such
Backtrace:
▆
1. └─global expect_learner(at) at test_AutoFSelector.R:136:3
2. └─mlr3misc::stopf("at least one parameter must support internal tuning when the learner is tagged as such")
── Error ('test_AutoFSelector.R:166:3'): AutoFSelector get_base_learner method works ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─afs$train(tsk("pima")) at test_AutoFSelector.R:166:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AtFSlctr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3fselect:::.__AutoFSelector__.train(...)
12. └─self$fselector$optimize(instance)
13. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_AutoFSelector.R:209:3'): AutoFSelector hash works #647 in mlr3 ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_AutoFSelector.R:209:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_FSelectInstanceMultiCrit.R:4:3'): empty FSelectInstanceMultiCrit works ──
Error in ``$.R6`(inst$archive, data)`: R6 class ArchiveFSelect/Archive/R6 does not have slot 'data'!
Backtrace:
▆
1. ├─checkmate::expect_data_table(inst$archive$data, nrows = 0L) at test_FSelectInstanceMultiCrit.R:4:3
2. │ └─checkmate::checkDataTable(...)
3. ├─inst$archive$data
4. └─global `$.R6`(inst$archive, data)
── Error ('test_FSelectInstanceMultiCrit.R:16:3'): eval_batch works ────────────
Error in ``$.R6`(archive, "n_evals")`: R6 class ArchiveFSelect/Archive/R6 does not have slot 'n_evals'!
Backtrace:
▆
1. ├─inst$eval_batch(xdt) at test_FSelectInstanceMultiCrit.R:16:3
2. │ └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. │ ├─self$is_terminated
4. │ └─global `$.R6`(self, "is_terminated")
5. │ └─base::get(name, envir = x)
6. └─bbotk (local) `<fn>`()
7. └─bbotk:::.__OptimInstanceBatch__is_terminated(...)
8. └─self$terminator$is_terminated(self$archive)
9. └─bbotk:::.__TerminatorEvals__is_terminated(...)
10. ├─archive$n_evals
11. └─global `$.R6`(archive, "n_evals")
── Error ('test_FSelectInstanceMultiCrit.R:29:3'): objective_function works ────
Error in ``$.R6`(archive, "n_evals")`: R6 class ArchiveFSelect/Archive/R6 does not have slot 'n_evals'!
Backtrace:
▆
1. ├─inst$objective_function(c(1, 1, 0, 0)) at test_FSelectInstanceMultiCrit.R:29:3
2. │ └─bbotk:::.__OptimInstanceBatch__objective_function(...)
3. │ └─private$.objective_function(x, self, self$objective_multiplicator)
4. │ └─inst$eval_batch(xdt)
5. │ └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
6. │ ├─self$is_terminated
7. │ └─global `$.R6`(self, "is_terminated")
8. │ └─base::get(name, envir = x)
9. └─bbotk (local) `<fn>`()
10. └─bbotk:::.__OptimInstanceBatch__is_terminated(...)
11. └─self$terminator$is_terminated(self$archive)
12. └─bbotk:::.__TerminatorEvals__is_terminated(...)
13. ├─archive$n_evals
14. └─global `$.R6`(archive, "n_evals")
── Error ('test_FSelectInstanceMultiCrit.R:37:3'): store_benchmark_result flag works ──
Error in ``$.R6`(archive, "n_evals")`: R6 class ArchiveFSelect/Archive/R6 does not have slot 'n_evals'!
Backtrace:
▆
1. ├─inst$eval_batch(xdt) at test_FSelectInstanceMultiCrit.R:37:3
2. │ └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. │ ├─self$is_terminated
4. │ └─global `$.R6`(self, "is_terminated")
5. │ └─base::get(name, envir = x)
6. └─bbotk (local) `<fn>`()
7. └─bbotk:::.__OptimInstanceBatch__is_terminated(...)
8. └─self$terminator$is_terminated(self$archive)
9. └─bbotk:::.__TerminatorEvals__is_terminated(...)
10. ├─archive$n_evals
11. └─global `$.R6`(archive, "n_evals")
── Error ('test_FSelectInstanceMultiCrit.R:54:3'): result$features works ───────
Error in ``$.R6`(self, "callbacks")`: R6 class FSelectInstanceMultiCrit/OptimInstanceMultiCrit/OptimInstanceBatchMultiCrit/OptimInstanceBatch/OptimInstance/R6 does not have slot 'callbacks'!
Backtrace:
▆
1. └─inst$assign_result(xdt, ydt) at test_FSelectInstanceMultiCrit.R:54:3
2. └─mlr3fselect:::.__FSelectInstanceMultiCrit__assign_result(...)
3. ├─mlr3misc::call_back("on_result", self$callbacks, private$.context)
4. ├─self$callbacks
5. └─global `$.R6`(self, "callbacks")
── Error ('test_FSelectorDesignPoints.R:8:3'): default parameters work ─────────
Error in `.__FSelectorDesignPoints__initialize(self = self, private = private,
super = super)`: object 'OptimizerDesignPoints' not found
Backtrace:
▆
1. └─global test_fselector("design_points", design = design) at test_FSelectorDesignPoints.R:8:3
2. └─mlr3fselect::fs(.key, ...)
3. └─mlr3misc::dictionary_sugar_get(mlr_fselectors, .key, ...)
4. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
5. │ └─checkmate::checkR6(...)
6. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
7. ├─base::do.call(constructor$new, cargs)
8. └─R6 (local) `<fn>`()
9. └─mlr3fselect (local) initialize(...)
10. └─mlr3fselect:::.__FSelectorDesignPoints__initialize(...)
11. └─super$initialize(optimizer = OptimizerDesignPoints$new(), man = "mlr3fselect::mlr_fselectors_design_points")
12. └─mlr3fselect:::.__FSelectorFromOptimizer__initialize(...)
13. └─bbotk::assert_optimizer(optimizer)
14. └─checkmate::assert_r6(optimizer, "Optimizer")
15. └─checkmate::checkR6(...)
── Error ('test_FSelectorDesignPoints.R:20:3'): multi-crit works ───────────────
Error in `.__FSelectorDesignPoints__initialize(self = self, private = private,
super = super)`: object 'OptimizerDesignPoints' not found
Backtrace:
▆
1. └─global test_fselector_2D("design_points", design = design) at test_FSelectorDesignPoints.R:20:3
2. └─mlr3fselect::fs(.key, ...)
3. └─mlr3misc::dictionary_sugar_get(mlr_fselectors, .key, ...)
4. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
5. │ └─checkmate::checkR6(...)
6. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
7. ├─base::do.call(constructor$new, cargs)
8. └─R6 (local) `<fn>`()
9. └─mlr3fselect (local) initialize(...)
10. └─mlr3fselect:::.__FSelectorDesignPoints__initialize(...)
11. └─super$initialize(optimizer = OptimizerDesignPoints$new(), man = "mlr3fselect::mlr_fselectors_design_points")
12. └─mlr3fselect:::.__FSelectorFromOptimizer__initialize(...)
13. └─bbotk::assert_optimizer(optimizer)
14. └─checkmate::assert_r6(optimizer, "Optimizer")
15. └─checkmate::checkR6(...)
── Error ('test_FSelectorExhaustiveSearch.R:2:3'): default parameters work ─────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("exhaustive_search") at test_FSelectorExhaustiveSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorExhaustiveSearch.R:14:3'): max_features parameter works ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("exhaustive_search", max_features = 2) at test_FSelectorExhaustiveSearch.R:14:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorExhaustiveSearch.R:23:3'): multi-crit works ───────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector_2D("exhaustive_search") at test_FSelectorExhaustiveSearch.R:23:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorExhaustiveSearch.R:27:3'): batch_size parameter works ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("exhaustive_search", batch_size = 2) at test_FSelectorExhaustiveSearch.R:27:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectInstanceSingleCrit.R:4:3'): empty FSelectInstanceSingleCrit works ──
Error in ``$.R6`(inst$archive, data)`: R6 class ArchiveFSelect/Archive/R6 does not have slot 'data'!
Backtrace:
▆
1. ├─checkmate::expect_data_table(inst$archive$data, nrows = 0L) at test_FSelectInstanceSingleCrit.R:4:3
2. │ └─checkmate::checkDataTable(...)
3. ├─inst$archive$data
4. └─global `$.R6`(inst$archive, data)
── Error ('test_FSelectInstanceSingleCrit.R:16:3'): eval_batch works ───────────
Error in ``$.R6`(archive, "n_evals")`: R6 class ArchiveFSelect/Archive/R6 does not have slot 'n_evals'!
Backtrace:
▆
1. ├─inst$eval_batch(xdt) at test_FSelectInstanceSingleCrit.R:16:3
2. │ └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. │ ├─self$is_terminated
4. │ └─global `$.R6`(self, "is_terminated")
5. │ └─base::get(name, envir = x)
6. └─bbotk (local) `<fn>`()
7. └─bbotk:::.__OptimInstanceBatch__is_terminated(...)
8. └─self$terminator$is_terminated(self$archive)
9. └─bbotk:::.__TerminatorEvals__is_terminated(...)
10. ├─archive$n_evals
11. └─global `$.R6`(archive, "n_evals")
── Error ('test_FSelectInstanceSingleCrit.R:40:3'): objective_function works ───
Error in ``$.R6`(archive, "n_evals")`: R6 class ArchiveFSelect/Archive/R6 does not have slot 'n_evals'!
Backtrace:
▆
1. ├─inst$objective_function(c(1, 1, 0, 0)) at test_FSelectInstanceSingleCrit.R:40:3
2. │ └─bbotk:::.__OptimInstanceBatch__objective_function(...)
3. │ └─private$.objective_function(x, self, self$objective_multiplicator)
4. │ └─inst$eval_batch(xdt)
5. │ └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
6. │ ├─self$is_terminated
7. │ └─global `$.R6`(self, "is_terminated")
8. │ └─base::get(name, envir = x)
9. └─bbotk (local) `<fn>`()
10. └─bbotk:::.__OptimInstanceBatch__is_terminated(...)
11. └─self$terminator$is_terminated(self$archive)
12. └─bbotk:::.__TerminatorEvals__is_terminated(...)
13. ├─archive$n_evals
14. └─global `$.R6`(archive, "n_evals")
── Error ('test_FSelectInstanceSingleCrit.R:48:3'): store_benchmark_result flag works ──
Error in ``$.R6`(archive, "n_evals")`: R6 class ArchiveFSelect/Archive/R6 does not have slot 'n_evals'!
Backtrace:
▆
1. ├─inst$eval_batch(xdt) at test_FSelectInstanceSingleCrit.R:48:3
2. │ └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. │ ├─self$is_terminated
4. │ └─global `$.R6`(self, "is_terminated")
5. │ └─base::get(name, envir = x)
6. └─bbotk (local) `<fn>`()
7. └─bbotk:::.__OptimInstanceBatch__is_terminated(...)
8. └─self$terminator$is_terminated(self$archive)
9. └─bbotk:::.__TerminatorEvals__is_terminated(...)
10. ├─archive$n_evals
11. └─global `$.R6`(archive, "n_evals")
── Error ('test_FSelectInstanceSingleCrit.R:66:3'): result$features works ──────
Error in ``$.R6`(self, "callbacks")`: R6 class FSelectInstanceSingleCrit/OptimInstanceSingleCrit/OptimInstanceBatchSingleCrit/OptimInstanceBatch/OptimInstance/R6 does not have slot 'callbacks'!
Backtrace:
▆
1. └─inst$assign_result(xdt, y) at test_FSelectInstanceSingleCrit.R:66:3
2. └─mlr3fselect:::.__FSelectInstanceSingleCrit__assign_result(...)
3. ├─mlr3misc::call_back("on_result", self$callbacks, private$.context)
4. ├─self$callbacks
5. └─global `$.R6`(self, "callbacks")
── Error ('test_FSelectInstanceSingleCrit.R:77:3'): always include variable works ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectInstanceSingleCrit.R:77:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectInstanceSingleCrit.R:103:3'): always include variables works ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectInstanceSingleCrit.R:103:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorGeneticSearch.R:4:3'): default parameters work ────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("genetic_search", term_evals = 10) at test_FSelectorGeneticSearch.R:4:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFECV.R:12:3'): extra columns are stored in the archive ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:12:3
2. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFECV.R:32:3'): resampling is converted ───────────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:32:3
2. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFECV.R:61:3'): default parameters work ───────────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:61:3
2. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFECV.R:75:3'): learner without importance method throw an error ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_FSelectorRFECV.R:75:3
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. └─mlr3fselect::fselect(...)
8. └─fselector$optimize(instance)
9. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFECV.R:118:3'): optimal features are selected ────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:118:3
2. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRandomSearch.R:2:3'): default parameters work ─────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("random_search", batch_size = 5, term_evals = 10) at test_FSelectorRandomSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRandomSearch.R:6:3'): max_features parameter work ─────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("random_search", max_features = 1, term_evals = 10) at test_FSelectorRandomSearch.R:6:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRandomSearch.R:12:3'): multi-crit works ───────────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector_2D("random_search", batch_size = 5, term_evals = 10) at test_FSelectorRandomSearch.R:12:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFE.R:2:3'): importance is stored in the archive ──────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("rfe", store_models = TRUE) at test_FSelectorRFE.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFE.R:11:3'): default parameters work ─────────────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("rfe", store_models = TRUE) at test_FSelectorRFE.R:11:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFE.R:18:3'): recursive parameter works ───────────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("rfe", recursive = FALSE, store_models = TRUE) at test_FSelectorRFE.R:18:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFE.R:27:3'): feature_fraction parameter works ────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("rfe", feature_fraction = 0.9, store_models = TRUE) at test_FSelectorRFE.R:27:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFE.R:49:3'): feature_number parameter works ──────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("rfe", feature_number = 1, store_models = TRUE) at test_FSelectorRFE.R:49:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFE.R:63:3'): subset_size parameter works ─────────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("rfe", subset_sizes = c(3L, 1L), store_models = TRUE) at test_FSelectorRFE.R:63:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFE.R:83:3'): subset is full feature set works ────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("rfe", feature_number = 4, store_models = TRUE) at test_FSelectorRFE.R:83:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFE.R:92:3'): learner without importance method throw an error ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_FSelectorRFE.R:92:3
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. └─mlr3fselect::fselect(...)
8. └─fselector$optimize(instance)
9. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFE.R:154:3'): works without storing models ───────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectorRFE.R:154:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFE.R:233:3'): optimal features are selected with rank ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFE.R:233:3
2. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorRFE.R:290:3'): optimal features are selected with mean ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFE.R:290:3
2. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorSequential.R:2:3'): default parameters works ──────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorSequential.R:11:3'): sbs strategy works ───────────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("sequential", strategy = "sbs") at test_FSelectorSequential.R:11:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorSequential.R:20:3'): sfs strategy works with max_features parameter ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("sequential", max_features = 2) at test_FSelectorSequential.R:20:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorSequential.R:26:3'): sbs strategy works with max_features parameter ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("sequential", max_features = 2, strategy = "sbs") at test_FSelectorSequential.R:26:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorSequential.R:32:3'): optimization_path method works ───
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:32:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorSequential.R:39:3'): optimization_path method works with included uhash ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:39:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorShadowVariableSearch.R:2:3'): default parameters work ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_fselector("shadow_variable_search", store_models = TRUE) at test_FSelectorShadowVariableSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorShadowVariableSearch.R:14:3'): task is permuted ───────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:14:3
2. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorShadowVariableSearch.R:26:3'): first selected feature is a shadow variable works ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. ├─testthat::expect_error(fselector$optimize(instance), regexp = "The first selected feature is a shadow variable.") at test_FSelectorShadowVariableSearch.R:26:3
2. │ └─testthat:::expect_condition_matching(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. └─fselector$optimize(instance)
8. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorShadowVariableSearch.R:35:3'): second selected feature is a shadow variable works ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:35:3
2. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_FSelectorShadowVariableSearch.R:54:3'): search is terminated by terminator works ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:54:3
2. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_extract_inner_fselect_archives.R:2:3'): extract_inner_fselect_archives function works with resample and cv ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_extract_inner_fselect_archives.R:2:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. ├─future::value(fs)
7. └─future:::value.list(fs)
8. ├─future::resolve(...)
9. └─future:::resolve.list(...)
10. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
11. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_archives.R:11:3'): extract_inner_fselect_archives function works with resample and repeated cv ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_extract_inner_fselect_archives.R:11:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. ├─future::value(fs)
7. └─future:::value.list(fs)
8. ├─future::resolve(...)
9. └─future:::resolve.list(...)
10. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
11. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_archives.R:24:3'): extract_inner_fselect_archives function works with benchmark and cv ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_archives.R:24:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_archives.R:37:3'): extract_inner_fselect_archives function works with benchmark and repeated cv ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_archives.R:37:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_archives.R:50:3'): extract_inner_fselect_archives function works with multiple tasks ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_archives.R:50:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_archives.R:61:3'): extract_inner_fselect_archives function works with no models ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, resampling_outer, store_models = FALSE) at test_extract_inner_fselect_archives.R:61:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_archives.R:70:3'): extract_inner_fselect_archives function works with no instance ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, resampling_outer, store_models = TRUE) at test_extract_inner_fselect_archives.R:70:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_archives.R:80:3'): extract_inner_fselect_archives function works with benchmark and no models ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = FALSE) at test_extract_inner_fselect_archives.R:80:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_archives.R:92:3'): extract_inner_fselect_archives function works with mixed store instance ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_archives.R:92:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_archives.R:104:3'): extract_inner_fselect_archives function works with autofselector and learner ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_archives.R:104:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_fselect.R:2:3'): fselect function works with single measure ────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:2:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_fselect.R:11:3'): fselect function works with multiple measures ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:11:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_fselect.R:20:3'): fselect function accepts string input for method ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:20:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelector__optimize(...)
── Error ('test_extract_inner_fselect_result.R:2:3'): extract_inner_fselect_results function works with resample and cv ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_extract_inner_fselect_result.R:2:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. ├─future::value(fs)
7. └─future:::value.list(fs)
8. ├─future::resolve(...)
9. └─future:::resolve.list(...)
10. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
11. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_result.R:11:3'): extract_inner_fselect_results function works with resample and repeated cv ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_extract_inner_fselect_result.R:11:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. ├─future::value(fs)
7. └─future:::value.list(fs)
8. ├─future::resolve(...)
9. └─future:::resolve.list(...)
10. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
11. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_result.R:24:3'): extract_inner_fselect_results function works with benchmark and cv ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:24:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_result.R:37:3'): extract_inner_fselect_results function works with benchmark and repeated cv ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:37:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_result.R:50:3'): extract_inner_fselect_results function works with multiple tasks ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:50:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_result.R:61:3'): extract_inner_fselect_results function works with no model ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, resampling_outer, store_models = FALSE) at test_extract_inner_fselect_result.R:61:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_result.R:70:3'): extract_inner_fselect_results function works no instance ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, resampling_outer, store_models = TRUE) at test_extract_inner_fselect_result.R:70:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_result.R:80:3'): extract_inner_fselect_results function works with benchmark and no models ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = FALSE) at test_extract_inner_fselect_result.R:80:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_result.R:92:3'): extract_inner_fselect_results function works with mixed store instance ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:92:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_result.R:104:3'): extract_inner_fselect_results function works with learner and autotuner ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:104:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_result.R:113:3'): extract_inner_fselect_results function works with resample and return of instance ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_extract_inner_fselect_result.R:113:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. ├─future::value(fs)
7. └─future:::value.list(fs)
8. ├─future::resolve(...)
9. └─future:::resolve.list(...)
10. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
11. └─future:::signalConditions(...)
── Error ('test_extract_inner_fselect_result.R:125:3'): extract_inner_fselect_results function works with benchmark and return of instance ──
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:125:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_fselect_nested.R:2:3'): fselect_nested function works ──────────
Error in `.__FSelector__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_fselect_nested.R:2:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. ├─future::value(fs)
7. └─future:::value.list(fs)
8. ├─future::resolve(...)
9. └─future:::resolve.list(...)
10. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
11. └─future:::signalConditions(...)
── Error ('test_mlr_callbacks.R:4:3'): backup callback works ───────────────────
Error: 'CallbackOptimization' is not an exported object from 'namespace:bbotk'
Backtrace:
▆
1. ├─mlr3fselect::fselect(...) at test_mlr_callbacks.R:4:3
2. │ └─FSelectInstanceSingleCrit$new(...)
3. │ └─mlr3fselect (local) initialize(...)
4. │ └─mlr3fselect:::.__FSelectInstanceSingleCrit__initialize(...)
5. │ └─ObjectiveFSelect$new(...)
6. │ └─mlr3fselect (local) initialize(...)
7. │ └─mlr3fselect:::.__ObjectiveFSelect__initialize(...)
8. │ ├─mlr3misc::assert_callbacks(as_callbacks(callbacks))
9. │ │ └─base::lapply(callbacks, assert_callback)
10. │ └─mlr3misc::as_callbacks(callbacks)
11. └─mlr3misc::clbk("mlr3fselect.backup", path = file)
12. └─mlr3misc::dictionary_sugar_get(mlr_callbacks, .key)
13. └─mlr3misc:::dictionary_get(dict, .key)
14. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
15. ├─base::do.call(constructor, cargs)
16. └─mlr3fselect (local) `<fn>`()
17. └─mlr3fselect::callback_fselect(...)
18. └─CallbackFSelect$new(id, label, man)
19. └─R6 (local) get_inherit()
20. └─base::eval(inherit, parent_env, NULL)
21. └─base::eval(inherit, parent_env, NULL)
── Error ('test_mlr_callbacks.R:23:3'): svm_rfe callbacks works ────────────────
Error: 'CallbackOptimization' is not an exported object from 'namespace:bbotk'
Backtrace:
▆
1. ├─mlr3fselect::fselect(...) at test_mlr_callbacks.R:23:3
2. │ └─FSelectInstanceSingleCrit$new(...)
3. │ └─mlr3fselect (local) initialize(...)
4. │ └─mlr3fselect:::.__FSelectInstanceSingleCrit__initialize(...)
5. │ └─ObjectiveFSelect$new(...)
6. │ └─mlr3fselect (local) initialize(...)
7. │ └─mlr3fselect:::.__ObjectiveFSelect__initialize(...)
8. │ ├─mlr3misc::assert_callbacks(as_callbacks(callbacks))
9. │ │ └─base::lapply(callbacks, assert_callback)
10. │ └─mlr3misc::as_callbacks(callbacks)
11. └─mlr3misc::clbk("mlr3fselect.svm_rfe")
12. └─mlr3misc::dictionary_sugar_get(mlr_callbacks, .key)
13. └─mlr3misc:::dictionary_get(dict, .key)
14. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
15. ├─base::do.call(constructor, cargs)
16. └─mlr3fselect (local) `<fn>`()
17. └─mlr3fselect::callback_fselect(...)
18. └─CallbackFSelect$new(id, label, man)
19. └─R6 (local) get_inherit()
20. └─base::eval(inherit, parent_env, NULL)
21. └─base::eval(inherit, parent_env, NULL)
── Error ('test_mlr_callbacks.R:46:3'): one_se_rule callback works ─────────────
Error: 'CallbackOptimization' is not an exported object from 'namespace:bbotk'
Backtrace:
▆
1. ├─mlr3fselect::fselect(...) at test_mlr_callbacks.R:46:3
2. │ └─FSelectInstanceSingleCrit$new(...)
3. │ └─mlr3fselect (local) initialize(...)
4. │ └─mlr3fselect:::.__FSelectInstanceSingleCrit__initialize(...)
5. │ └─ObjectiveFSelect$new(...)
6. │ └─mlr3fselect (local) initialize(...)
7. │ └─mlr3fselect:::.__ObjectiveFSelect__initialize(...)
8. │ ├─mlr3misc::assert_callbacks(as_callbacks(callbacks))
9. │ │ └─base::lapply(callbacks, assert_callback)
10. │ └─mlr3misc::as_callbacks(callbacks)
11. └─mlr3misc::clbk("mlr3fselect.one_se_rule")
12. └─mlr3misc::dictionary_sugar_get(mlr_callbacks, .key)
13. └─mlr3misc:::dictionary_get(dict, .key)
14. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
15. ├─base::do.call(constructor, cargs)
16. └─mlr3fselect (local) `<fn>`()
17. └─mlr3fselect::callback_fselect(...)
18. └─CallbackFSelect$new(id, label, man)
19. └─R6 (local) get_inherit()
20. └─base::eval(inherit, parent_env, NULL)
21. └─base::eval(inherit, parent_env, NULL)
── Error ('test_fsi.R:35:5'): fsi and FSelectInstanceSingleCrit are equal ──────
Error: 'CallbackOptimization' is not an exported object from 'namespace:bbotk'
Backtrace:
▆
1. └─mlr3misc::clbk("mlr3fselect.backup") at test_fsi.R:35:5
2. └─mlr3misc::dictionary_sugar_get(mlr_callbacks, .key)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3fselect (local) `<fn>`()
7. └─mlr3fselect::callback_fselect(...)
8. └─CallbackFSelect$new(id, label, man)
9. └─R6 (local) get_inherit()
10. └─base::eval(inherit, parent_env, NULL)
11. └─base::eval(inherit, parent_env, NULL)
── Error ('test_fsi.R:58:5'): fsi and FSelectInstanceMultiCrit are equal ───────
Error: 'CallbackOptimization' is not an exported object from 'namespace:bbotk'
Backtrace:
▆
1. └─mlr3misc::clbk("mlr3fselect.backup") at test_fsi.R:58:5
2. └─mlr3misc::dictionary_sugar_get(mlr_callbacks, .key)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor, cargs)
6. └─mlr3fselect (local) `<fn>`()
7. └─mlr3fselect::callback_fselect(...)
8. └─CallbackFSelect$new(id, label, man)
9. └─R6 (local) get_inherit()
10. └─base::eval(inherit, parent_env, NULL)
11. └─base::eval(inherit, parent_env, NULL)
── Error ('test_mlr_fselectors.R:2:3'): mlr_fselectors ─────────────────────────
Error in `.__FSelectorDesignPoints__initialize(self = self, private = private,
super = super)`: object 'OptimizerDesignPoints' not found
Backtrace:
▆
1. └─global expect_dictionary(mlr_fselectors, min_items = 1L) at test_mlr_fselectors.R:2:3
2. ├─checkmate::expect_data_table(...)
3. │ └─checkmate::checkDataTable(...)
4. ├─data.table::as.data.table(d)
5. └─mlr3fselect:::as.data.table.DictionaryFSelector(d)
6. ├─data.table::setkeyv(...)
7. │ └─data.table::is.data.table(x)
8. └─mlr3misc::map_dtr(...)
9. ├─data.table::rbindlist(...)
10. ├─base::unname(map(.x, .f, ...))
11. └─mlr3misc::map(.x, .f, ...)
12. └─base::lapply(.x, .f, ...)
13. └─mlr3fselect (local) FUN(X[[i]], ...)
14. ├─base::withCallingHandlers(x$get(key), packageNotFoundWarning = function(w) invokeRestart("muffleWarning"))
15. └─x$get(key)
16. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─mlr3misc:::dictionary_get(self = self, key = key)
21. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
22. ├─base::do.call(constructor$new, cargs)
23. └─R6 (local) `<fn>`()
24. └─mlr3fselect (local) initialize(...)
25. └─mlr3fselect:::.__FSelectorDesignPoints__initialize(...)
26. └─super$initialize(optimizer = OptimizerDesignPoints$new(), man = "mlr3fselect::mlr_fselectors_design_points")
27. └─mlr3fselect:::.__FSelectorFromOptimizer__initialize(...)
28. └─bbotk::assert_optimizer(optimizer)
29. └─checkmate::assert_r6(optimizer, "Optimizer")
30. └─checkmate::checkR6(...)
── Error ('test_mlr_fselectors.R:17:3'): as.data.table objects parameter ───────
Error in `.__FSelectorDesignPoints__initialize(self = self, private = private,
super = super)`: object 'OptimizerDesignPoints' not found
Backtrace:
▆
1. ├─data.table::as.data.table(mlr_fselectors, objects = TRUE) at test_mlr_fselectors.R:17:3
2. └─mlr3fselect:::as.data.table.DictionaryFSelector(...)
3. ├─data.table::setkeyv(...)
4. │ └─data.table::is.data.table(x)
5. └─mlr3misc::map_dtr(...)
6. ├─data.table::rbindlist(...)
7. ├─base::unname(map(.x, .f, ...))
8. └─mlr3misc::map(.x, .f, ...)
9. └─base::lapply(.x, .f, ...)
10. └─mlr3fselect (local) FUN(X[[i]], ...)
11. ├─base::withCallingHandlers(x$get(key), packageNotFoundWarning = function(w) invokeRestart("muffleWarning"))
12. └─x$get(key)
13. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─mlr3misc:::dictionary_get(self = self, key = key)
18. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
19. ├─base::do.call(constructor$new, cargs)
20. └─R6 (local) `<fn>`()
21. └─mlr3fselect (local) initialize(...)
22. └─mlr3fselect:::.__FSelectorDesignPoints__initialize(...)
23. └─super$initialize(optimizer = OptimizerDesignPoints$new(), man = "mlr3fselect::mlr_fselectors_design_points")
24. └─mlr3fselect:::.__FSelectorFromOptimizer__initialize(...)
25. └─bbotk::assert_optimizer(optimizer)
26. └─checkmate::assert_r6(optimizer, "Optimizer")
27. └─checkmate::checkR6(...)
[ FAIL 94 | WARN 0 | SKIP 3 | PASS 125 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.0.0
Check: package dependencies
Result: ERROR
Packages required and available but unsuitable versions: 'bbotk', 'paradox'
See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Current CRAN status: ERROR: 3, OK: 10
Version: 0.5.0
Check: examples
Result: ERROR
Running examples in ‘mlr3hyperband-Ex.R’ failed
The error most likely occurred in:
> ### Name: mlr_optimizers_hyperband
> ### Title: Optimizer Using the Hyperband Algorithm
> ### Aliases: mlr_optimizers_hyperband OptimizerHyperband
>
> ### ** Examples
>
> library(bbotk)
> library(data.table)
>
> # set search space
> search_space = domain = ps(
+ x1 = p_dbl(-5, 10),
+ x2 = p_dbl(0, 15),
+ fidelity = p_dbl(1e-2, 1, tags = "budget")
+ )
>
> # Branin function with fidelity, see `bbotk::branin()`
> fun = function(xs) branin_wu(xs[["x1"]], xs[["x2"]], xs[["fidelity"]])
>
> # create objective
> objective = ObjectiveRFun$new(
+ fun = fun,
+ domain = domain,
+ codomain = ps(y = p_dbl(tags = "minimize"))
+ )
>
> # initialize instance and optimizer
> instance = OptimInstanceSingleCrit$new(
+ objective = objective,
+ search_space = search_space,
+ terminator = trm("evals", n_evals = 50)
+ )
OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
>
> optimizer = opt("hyperband")
>
> # optimize branin function
> optimizer$optimize(instance)
Error: attempt to apply non-function
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.5.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [86s/60s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3hyperband")
+ test_check("mlr3hyperband")
+ }
Loading required package: mlr3tuning
Loading required package: mlr3
Loading required package: paradox
Starting 2 test processes
[ FAIL 40 | WARN 0 | SKIP 0 | PASS 28 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_TunerHyperband.R:7:3'): TunerHyperband works ───────────────────
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerHyperband.R:7:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:16:3'): TunerHyperband works with minimum budget > 1 ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerHyperband.R:16:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:25:3'): TunerHyperband rounds budget ──────────
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerHyperband.R:25:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:34:3'): TunerHyperband works with eta = 2.5 ───
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2.5, learner) at test_TunerHyperband.R:34:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:47:3'): TunerHyperband works with xgboost ─────
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerHyperband.R:47:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:58:3'): TunerHyperband works with subsampling ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 3, graph_learner) at test_TunerHyperband.R:58:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:68:3'): TunerHyperband works works with multi-crit ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerHyperband.R:68:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:79:3'): TunerHyperband works with custom sampler ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner, sampler = sampler) at test_TunerHyperband.R:79:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:91:3'): TunerHyperband errors if not enough parameters are sampled ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerHyperband.R:91:3
2. │ └─testthat:::expect_condition_matching(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. └─mlr3tuning::tune(...)
8. └─tuner$optimize(instance)
9. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
10. ├─private$.optimizer$optimize
11. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:113:3'): TunerHyperband errors if budget parameter is sampled ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerHyperband.R:113:3
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. └─tuner$optimize(instance)
9. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
10. ├─private$.optimizer$optimize
11. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:130:3'): TunerHyperband errors if budget parameter is not numeric ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerHyperband.R:130:3
2. │ └─testthat:::expect_condition_matching(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. └─mlr3tuning::tune(...)
8. └─tuner$optimize(instance)
9. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
10. ├─private$.optimizer$optimize
11. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:147:3'): TunerHyperband errors if multiple budget parameters are set ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerHyperband.R:147:3
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. └─tuner$optimize(instance)
9. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
10. ├─private$.optimizer$optimize
11. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:164:3'): TunerHyperband minimizes measure ─────
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerHyperband.R:164:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:175:3'): TunerHyperband maximizes measure ─────
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerHyperband.R:175:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:186:3'): TunerHyperband works with single budget value ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerHyperband.R:186:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:195:3'): TunerHyperband works with repetitions ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerHyperband.R:195:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
4. ├─private$.optimizer$optimize
5. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:211:3'): TunerHyperband terminates itself ─────
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerHyperband.R:211:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
4. ├─private$.optimizer$optimize
5. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerHyperband.R:227:3'): TunerHyperband works with infinite repetitions ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerHyperband/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerHyperband.R:227:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
4. ├─private$.optimizer$optimize
5. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:7:3'): TunerSuccessiveHalving works ───
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:7:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:16:3'): TunerSuccessiveHalving works with minimum budget > 1 ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:16:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:25:3'): TunerSuccessiveHalving rounds budget ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:25:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:34:3'): TunerSuccessiveHalving works with eta = 2.5 ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:34:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:43:3'): TunerSuccessiveHalving adjusts minimum budget ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:43:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:65:3'): TunerSuccessiveHalving works with xgboost ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:65:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:76:3'): TunerSuccessiveHalving works with subsampling ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:76:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:85:3'): TunerSuccessiveHalving works with multi-crit ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:85:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:96:3'): TunerSuccessiveHalving works with custom sampler ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:96:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:108:3'): TunerSuccessiveHalving errors if not enough parameters are sampled ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerSuccessiveHalving.R:108:3
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. └─tuner$optimize(instance)
9. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
10. ├─private$.optimizer$optimize
11. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:130:3'): TunerSuccessiveHalving errors if budget parameter is sampled ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerSuccessiveHalving.R:130:3
2. │ └─testthat:::expect_condition_matching(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. └─mlr3tuning::tune(...)
8. └─tuner$optimize(instance)
9. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
10. ├─private$.optimizer$optimize
11. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:147:3'): TunerSuccessiveHalving errors if budget parameter is not numeric ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerSuccessiveHalving.R:147:3
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. └─tuner$optimize(instance)
9. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
10. ├─private$.optimizer$optimize
11. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:164:3'): TunerSuccessiveHalving errors if multiple budget parameters are set ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TunerSuccessiveHalving.R:164:3
2. │ └─testthat:::expect_condition_matching(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. └─mlr3tuning::tune(...)
8. └─tuner$optimize(instance)
9. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
10. ├─private$.optimizer$optimize
11. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:181:3'): TunerSuccessiveHalving minimizes measure ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:181:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:191:3'): TunerSuccessiveHalving maximizes measure ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:191:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:201:3'): TunerSuccessiveHalving works with single budget value ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:201:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:210:3'): TunerSuccessiveHalving works with repetitions ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerSuccessiveHalving.R:210:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
4. ├─private$.optimizer$optimize
5. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:226:3'): TunerSuccessiveHalving terminates itself ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerSuccessiveHalving.R:226:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
4. ├─private$.optimizer$optimize
5. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:242:3'): TunerSuccessiveHalving works with infinite repetitions ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerSuccessiveHalving.R:242:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
4. ├─private$.optimizer$optimize
5. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:259:3'): TunerSuccessiveHalving works with r_max > n ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:259:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:268:3'): TunerSuccessiveHalving works with r_max < n ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:268:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
── Error ('test_TunerSuccessiveHalving.R:277:3'): TunerSuccessiveHalving works with r_max < n and adjust minimum budget ──
Error in ``$.R6`(private$.optimizer, "optimize")`: R6 class OptimizerSuccessiveHalving/Optimizer/R6 does not have slot 'optimize'!
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerSuccessiveHalving.R:277:3
2. └─mlr3tuning::tune(...) at tests/testthat/helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerFromOptimizer__optimize(...)
5. ├─private$.optimizer$optimize
6. └─global `$.R6`(private$.optimizer, "optimize")
[ FAIL 40 | WARN 0 | SKIP 0 | PASS 28 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.6.0
Check: package dependencies
Result: ERROR
Packages required and available but unsuitable versions:
'mlr3tuning', 'bbotk'
See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Current CRAN status: ERROR: 2, OK: 11
Version: 0.7.0
Check: package dependencies
Result: ERROR
Packages required and available but unsuitable versions: 'mlr3', 'paradox'
See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Current CRAN status: OK: 13
Current CRAN status: ERROR: 3, OK: 10
Version: 0.20.0
Check: R code for possible problems
Result: NOTE
.__TunerCmaes__initialize: no visible binding for global variable
‘OptimizerCmaes’
.__TunerDesignPoints__initialize: no visible binding for global
variable ‘OptimizerDesignPoints’
.__TunerGenSA__initialize: no visible binding for global variable
‘OptimizerGenSA’
.__TunerIrace__initialize: no visible binding for global variable
‘OptimizerIrace’
.__TunerNLoptr__initialize: no visible binding for global variable
‘OptimizerNLoptr’
.__TunerRandomSearch__initialize: no visible binding for global
variable ‘OptimizerRandomSearch’
.__Tuner__optimize: no visible binding for global variable
‘ContextOptimization’
.__Tuner__optimize: no visible global function definition for
‘optimize_default’
Undefined global functions or variables:
ContextOptimization OptimizerCmaes OptimizerDesignPoints
OptimizerGenSA OptimizerIrace OptimizerNLoptr OptimizerRandomSearch
optimize_default
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.20.0
Check: Rd cross-references
Result: WARN
Missing link or links in Rd file 'CallbackTuning.Rd':
‘[bbotk:CallbackOptimization]{bbotk::CallbackOptimization}’
Missing link or links in Rd file 'ContextEval.Rd':
‘[bbotk:ContextOptimization]{bbotk::ContextOptimization}’
Missing link or links in Rd file 'callback_tuning.Rd':
‘[bbotk:ContextOptimization]{bbotk::ContextOptimization}’
‘ContextOptimization’
See section 'Cross-references' in the 'Writing R Extensions' manual.
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.20.0
Check: examples
Result: ERROR
Running examples in ‘mlr3tuning-Ex.R’ failed
The error most likely occurred in:
> ### Name: AutoTuner
> ### Title: Class for Automatic Tuning
> ### Aliases: AutoTuner
>
> ### ** Examples
>
> # Automatic Tuning
>
> # split to train and external set
> task = tsk("penguins")
> split = partition(task, ratio = 0.8)
>
> # load learner and set search space
> learner = lrn("classif.rpart",
+ cp = to_tune(1e-04, 1e-1, logscale = TRUE)
+ )
>
> # create auto tuner
> at = auto_tuner(
+ tuner = tnr("random_search"),
+ learner = learner,
+ resampling = rsmp ("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 4)
Error in .__TunerRandomSearch__initialize(self = self, private = private, :
object 'OptimizerRandomSearch' not found
Calls: auto_tuner ... .__TunerFromOptimizer__initialize -> assert_optimizer -> assert_r6 -> checkR6
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.20.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [96s/65s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3tuning")
+ test_check("mlr3tuning")
+ }
Loading required package: mlr3
Loading required package: paradox
Starting 2 test processes
[ FAIL 95 | WARN 0 | SKIP 1 | PASS 149 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test_mlr_callbacks.R:2:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ArchiveTuning.R:6:3'): ArchiveTuning access methods work ───────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("random_search", batch_size = 2) at test_ArchiveTuning.R:6:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
4. │ └─checkmate::checkR6(...)
5. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
6. ├─base::do.call(constructor$new, cargs)
7. └─R6 (local) `<fn>`()
8. └─mlr3tuning (local) initialize(...)
9. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
10. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
11. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
12. └─bbotk::assert_optimizer(optimizer)
13. └─checkmate::assert_r6(optimizer, "Optimizer")
14. └─checkmate::checkR6(...)
── Error ('test_ArchiveTuning.R:117:3'): ArchiveTuning as.data.table function works ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("random_search", batch_size = 2) at test_ArchiveTuning.R:117:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
4. │ └─checkmate::checkR6(...)
5. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
6. ├─base::do.call(constructor$new, cargs)
7. └─R6 (local) `<fn>`()
8. └─mlr3tuning (local) initialize(...)
9. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
10. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
11. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
12. └─bbotk::assert_optimizer(optimizer)
13. └─checkmate::assert_r6(optimizer, "Optimizer")
14. └─checkmate::checkR6(...)
── Error ('test_ObjectiveTuning.R:105:3'): tuner can modify resampling ─────────
Error in ``$.R6`(self$archive, "add_evals")`: R6 class ArchiveTuning/Archive/R6 does not have slot 'add_evals'!
Backtrace:
▆
1. └─instance$eval_batch(data.table(cp = 0.001)) at test_ObjectiveTuning.R:105:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. ├─self$archive$add_evals
4. └─global `$.R6`(self$archive, "add_evals")
── Error ('test_AutoTuner.R:9:3'): AutoTuner / train+predict ───────────────────
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:9:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_AutoTuner.R:41:3'): AutoTuner / resample ───────────────────────
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, r_outer, store_models = TRUE) at test_AutoTuner.R:41:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_AutoTuner.R:66:3'): nested resamppling results are consistent ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─AutoTuner$new(...) at test_AutoTuner.R:66:3
2. │ └─mlr3tuning (local) initialize(...)
3. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
4. │ └─mlr3tuning:::assert_tuner(tuner)
5. │ └─checkmate::assert_r6(tuner, "Tuner")
6. │ └─checkmate::checkR6(...)
7. └─mlr3tuning::tnr("random_search")
8. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
9. └─mlr3misc:::dictionary_get(dict, .key)
10. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
11. ├─base::do.call(constructor$new, cargs)
12. └─R6 (local) `<fn>`()
13. └─mlr3tuning (local) initialize(...)
14. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
15. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
16. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
17. └─bbotk::assert_optimizer(optimizer)
18. └─checkmate::assert_r6(optimizer, "Optimizer")
19. └─checkmate::checkR6(...)
── Error ('test_AutoTuner.R:90:3'): AT training does not change learner in instance args ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─AutoTuner$new(...) at test_AutoTuner.R:90:3
2. │ └─mlr3tuning (local) initialize(...)
3. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
4. │ └─mlr3tuning:::assert_tuner(tuner)
5. │ └─checkmate::assert_r6(tuner, "Tuner")
6. │ └─checkmate::checkR6(...)
7. └─TunerRandomSearch$new()
8. └─mlr3tuning (local) initialize(...)
9. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
10. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
11. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
12. └─bbotk::assert_optimizer(optimizer)
13. └─checkmate::assert_r6(optimizer, "Optimizer")
14. └─checkmate::checkR6(...)
── Failure ('test_AutoTuner.R:116:3'): AutoTuner works with graphlearner ───────
exists("validate", lrn) is not TRUE
`actual`: FALSE
`expected`: TRUE
Backtrace:
▆
1. └─global expect_learner(at) at test_AutoTuner.R:116:3
2. └─testthat::expect_true(exists("validate", lrn))
── Failure ('test_AutoTuner.R:116:3'): AutoTuner works with graphlearner ───────
exists("internal_valid_scores", envir = lrn) is not TRUE
`actual`: FALSE
`expected`: TRUE
Backtrace:
▆
1. └─global expect_learner(at) at test_AutoTuner.R:116:3
2. └─testthat::expect_true(exists("internal_valid_scores", envir = lrn))
── Failure ('test_AutoTuner.R:116:3'): AutoTuner works with graphlearner ───────
Check on 'mlr3misc::get_private(lrn)$.extract_internal_valid_scores' failed: Must be a function, not 'NULL'
Backtrace:
▆
1. └─global expect_learner(at) at test_AutoTuner.R:116:3
2. └─checkmate::expect_function(mlr3misc::get_private(lrn)$.extract_internal_valid_scores)
3. └─checkmate::makeExpectation(x, res, info, label)
── Error ('test_AutoTuner.R:116:3'): AutoTuner works with graphlearner ─────────
Error: at least one parameter must support internal tuning when the learner is tagged as such
Backtrace:
▆
1. └─global expect_learner(at) at test_AutoTuner.R:116:3
2. └─mlr3misc::stopf("at least one parameter must support internal tuning when the learner is tagged as such")
── Error ('test_AutoTuner.R:155:3'): Nested resampling works with graphlearner ──
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::resample(task, at, resampling_outer, store_models = TRUE) at test_AutoTuner.R:155:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_AutoTuner.R:184:3'): store_tuning_instance, store_benchmark_result and store_models flags work ──
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:184:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_AutoTuner.R:243:3'): predict_type works ────────────────────────
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:243:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_AutoTuner.R:256:3'): search space from TuneToken works ─────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─AutoTuner$new(...) at test_AutoTuner.R:256:3
2. │ └─mlr3tuning (local) initialize(...)
3. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
4. │ └─mlr3tuning:::assert_tuner(tuner)
5. │ └─checkmate::assert_r6(tuner, "Tuner")
6. │ └─checkmate::checkR6(...)
7. └─mlr3tuning::tnr("random_search")
8. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
9. └─mlr3misc:::dictionary_get(dict, .key)
10. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
11. ├─base::do.call(constructor$new, cargs)
12. └─R6 (local) `<fn>`()
13. └─mlr3tuning (local) initialize(...)
14. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
15. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
16. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
17. └─bbotk::assert_optimizer(optimizer)
18. └─checkmate::assert_r6(optimizer, "Optimizer")
19. └─checkmate::checkR6(...)
── Error ('test_AutoTuner.R:280:3'): AutoTuner get_base_learner method works ───
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::auto_tuner(...) at test_AutoTuner.R:280:3
2. │ └─AutoTuner$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
5. │ └─mlr3tuning:::assert_tuner(tuner)
6. │ └─checkmate::assert_r6(tuner, "Tuner")
7. │ └─checkmate::checkR6(...)
8. └─mlr3tuning::tnr("random_search")
9. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor$new, cargs)
13. └─R6 (local) `<fn>`()
14. └─mlr3tuning (local) initialize(...)
15. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
16. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
17. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
18. └─bbotk::assert_optimizer(optimizer)
19. └─checkmate::assert_r6(optimizer, "Optimizer")
20. └─checkmate::checkR6(...)
── Error ('test_AutoTuner.R:349:3'): AutoTuner hash works #647 in mlr3 ─────────
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_AutoTuner.R:349:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_AutoTuner.R:357:3'): AutoTuner works with empty search space ───
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::auto_tuner(...) at test_AutoTuner.R:357:3
2. │ └─AutoTuner$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
5. │ └─mlr3tuning:::assert_tuner(tuner)
6. │ └─checkmate::assert_r6(tuner, "Tuner")
7. │ └─checkmate::checkR6(...)
8. └─mlr3tuning::tnr("random_search", batch_size = 5)
9. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
10. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
11. │ └─checkmate::checkR6(...)
12. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
13. ├─base::do.call(constructor$new, cargs)
14. └─R6 (local) `<fn>`()
15. └─mlr3tuning (local) initialize(...)
16. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
17. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
18. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
19. └─bbotk::assert_optimizer(optimizer)
20. └─checkmate::assert_r6(optimizer, "Optimizer")
21. └─checkmate::checkR6(...)
── Error ('test_AutoTuner.R:387:3'): AutoTuner importance method works ─────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::auto_tuner(...) at test_AutoTuner.R:387:3
2. │ └─AutoTuner$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
5. │ └─mlr3tuning:::assert_tuner(tuner)
6. │ └─checkmate::assert_r6(tuner, "Tuner")
7. │ └─checkmate::checkR6(...)
8. └─mlr3tuning::tnr("random_search", batch_size = 2)
9. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
10. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
11. │ └─checkmate::checkR6(...)
12. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
13. ├─base::do.call(constructor$new, cargs)
14. └─R6 (local) `<fn>`()
15. └─mlr3tuning (local) initialize(...)
16. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
17. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
18. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
19. └─bbotk::assert_optimizer(optimizer)
20. └─checkmate::assert_r6(optimizer, "Optimizer")
21. └─checkmate::checkR6(...)
── Error ('test_AutoTuner.R:401:3'): AutoTuner selected_features method works ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::auto_tuner(...) at test_AutoTuner.R:401:3
2. │ └─AutoTuner$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
5. │ └─mlr3tuning:::assert_tuner(tuner)
6. │ └─checkmate::assert_r6(tuner, "Tuner")
7. │ └─checkmate::checkR6(...)
8. └─mlr3tuning::tnr("random_search", batch_size = 2)
9. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
10. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
11. │ └─checkmate::checkR6(...)
12. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
13. ├─base::do.call(constructor$new, cargs)
14. └─R6 (local) `<fn>`()
15. └─mlr3tuning (local) initialize(...)
16. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
17. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
18. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
19. └─bbotk::assert_optimizer(optimizer)
20. └─checkmate::assert_r6(optimizer, "Optimizer")
21. └─checkmate::checkR6(...)
── Error ('test_AutoTuner.R:415:3'): AutoTuner oob_error method works ──────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::auto_tuner(...) at test_AutoTuner.R:415:3
2. │ └─AutoTuner$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
5. │ └─mlr3tuning:::assert_tuner(tuner)
6. │ └─checkmate::assert_r6(tuner, "Tuner")
7. │ └─checkmate::checkR6(...)
8. └─mlr3tuning::tnr("random_search", batch_size = 2)
9. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
10. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
11. │ └─checkmate::checkR6(...)
12. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
13. ├─base::do.call(constructor$new, cargs)
14. └─R6 (local) `<fn>`()
15. └─mlr3tuning (local) initialize(...)
16. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
17. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
18. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
19. └─bbotk::assert_optimizer(optimizer)
20. └─checkmate::assert_r6(optimizer, "Optimizer")
21. └─checkmate::checkR6(...)
── Error ('test_AutoTuner.R:427:3'): AutoTuner loglik method works ─────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::auto_tuner(...) at test_AutoTuner.R:427:3
2. │ └─AutoTuner$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
5. │ └─mlr3tuning:::assert_tuner(tuner)
6. │ └─checkmate::assert_r6(tuner, "Tuner")
7. │ └─checkmate::checkR6(...)
8. └─mlr3tuning::tnr("random_search", batch_size = 2)
9. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
10. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
11. │ └─checkmate::checkR6(...)
12. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
13. ├─base::do.call(constructor$new, cargs)
14. └─R6 (local) `<fn>`()
15. └─mlr3tuning (local) initialize(...)
16. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
17. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
18. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
19. └─bbotk::assert_optimizer(optimizer)
20. └─checkmate::assert_r6(optimizer, "Optimizer")
21. └─checkmate::checkR6(...)
── Error ('test_AutoTuner.R:449:3'): AutoTuner works with instantiated resampling ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::auto_tuner(...) at test_AutoTuner.R:449:3
2. │ └─AutoTuner$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
5. │ └─mlr3tuning:::assert_tuner(tuner)
6. │ └─checkmate::assert_r6(tuner, "Tuner")
7. │ └─checkmate::checkR6(...)
8. └─mlr3tuning::tnr("random_search")
9. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor$new, cargs)
13. └─R6 (local) `<fn>`()
14. └─mlr3tuning (local) initialize(...)
15. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
16. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
17. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
18. └─bbotk::assert_optimizer(optimizer)
19. └─checkmate::assert_r6(optimizer, "Optimizer")
20. └─checkmate::checkR6(...)
── Error ('test_AutoTuner.R:470:3'): AutoTuner errors when train set is not a subset of task ids ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::auto_tuner(...) at test_AutoTuner.R:470:3
2. │ └─AutoTuner$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
5. │ └─mlr3tuning:::assert_tuner(tuner)
6. │ └─checkmate::assert_r6(tuner, "Tuner")
7. │ └─checkmate::checkR6(...)
8. └─mlr3tuning::tnr("random_search")
9. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor$new, cargs)
13. └─R6 (local) `<fn>`()
14. └─mlr3tuning (local) initialize(...)
15. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
16. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
17. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
18. └─bbotk::assert_optimizer(optimizer)
19. └─checkmate::assert_r6(optimizer, "Optimizer")
20. └─checkmate::checkR6(...)
── Error ('test_AutoTuner.R:497:3'): AutoTuner errors when second train set is not a subset of task ids ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::auto_tuner(...) at test_AutoTuner.R:497:3
2. │ └─AutoTuner$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
5. │ └─mlr3tuning:::assert_tuner(tuner)
6. │ └─checkmate::assert_r6(tuner, "Tuner")
7. │ └─checkmate::checkR6(...)
8. └─mlr3tuning::tnr("random_search")
9. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor$new, cargs)
13. └─R6 (local) `<fn>`()
14. └─mlr3tuning (local) initialize(...)
15. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
16. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
17. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
18. └─bbotk::assert_optimizer(optimizer)
19. └─checkmate::assert_r6(optimizer, "Optimizer")
20. └─checkmate::checkR6(...)
── Error ('test_AutoTuner.R:524:3'): AutoTuner errors when test set is not a subset of task ids ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::auto_tuner(...) at test_AutoTuner.R:524:3
2. │ └─AutoTuner$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
5. │ └─mlr3tuning:::assert_tuner(tuner)
6. │ └─checkmate::assert_r6(tuner, "Tuner")
7. │ └─checkmate::checkR6(...)
8. └─mlr3tuning::tnr("random_search")
9. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor$new, cargs)
13. └─R6 (local) `<fn>`()
14. └─mlr3tuning (local) initialize(...)
15. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
16. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
17. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
18. └─bbotk::assert_optimizer(optimizer)
19. └─checkmate::assert_r6(optimizer, "Optimizer")
20. └─checkmate::checkR6(...)
── Error ('test_AutoTuner.R:551:3'): AutoTuner errors when second test set is not a subset of task ids ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::auto_tuner(...) at test_AutoTuner.R:551:3
2. │ └─AutoTuner$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
5. │ └─mlr3tuning:::assert_tuner(tuner)
6. │ └─checkmate::assert_r6(tuner, "Tuner")
7. │ └─checkmate::checkR6(...)
8. └─mlr3tuning::tnr("random_search")
9. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor$new, cargs)
13. └─R6 (local) `<fn>`()
14. └─mlr3tuning (local) initialize(...)
15. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
16. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
17. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
18. └─bbotk::assert_optimizer(optimizer)
19. └─checkmate::assert_r6(optimizer, "Optimizer")
20. └─checkmate::checkR6(...)
── Error ('test_TunerCmaes.R:3:1'): TunerCmaes ─────────────────────────────────
Error in `.__TunerCmaes__initialize(self = self, private = private, super = super)`: object 'OptimizerCmaes' not found
Backtrace:
▆
1. ├─global expect_tuner(tnr("cmaes")) at test_TunerCmaes.R:3:1
2. │ └─checkmate::expect_r6(...)
3. │ └─checkmate::checkR6(...)
4. └─mlr3tuning::tnr("cmaes")
5. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
6. └─mlr3misc:::dictionary_get(dict, .key)
7. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
8. ├─base::do.call(constructor$new, cargs)
9. └─R6 (local) `<fn>`()
10. └─mlr3tuning (local) initialize(...)
11. └─mlr3tuning:::.__TunerCmaes__initialize(...)
12. └─super$initialize(optimizer = OptimizerCmaes$new(), man = "mlr3tuning::mlr_tuners_cmaes")
13. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
14. └─bbotk::assert_optimizer(optimizer)
15. └─checkmate::assert_r6(optimizer, "Optimizer")
16. └─checkmate::checkR6(...)
── Error ('test_TunerDesignPoints.R:3:3'): TunerDesignPoints ───────────────────
Error in `.__TunerDesignPoints__initialize(self = self, private = private,
super = super)`: object 'OptimizerDesignPoints' not found
Backtrace:
▆
1. └─global test_tuner(...) at test_TunerDesignPoints.R:3:3
2. └─mlr3tuning::tnr(key, ...)
3. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
4. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
5. │ └─checkmate::checkR6(...)
6. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
7. ├─base::do.call(constructor$new, cargs)
8. └─R6 (local) `<fn>`()
9. └─mlr3tuning (local) initialize(...)
10. └─mlr3tuning:::.__TunerDesignPoints__initialize(...)
11. └─super$initialize(optimizer = OptimizerDesignPoints$new(), man = "mlr3tuning::mlr_tuners_design_points")
12. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
13. └─bbotk::assert_optimizer(optimizer)
14. └─checkmate::assert_r6(optimizer, "Optimizer")
15. └─checkmate::checkR6(...)
── Error ('test_Tuner.R:3:5'): API ─────────────────────────────────────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. └─TunerRandomSearch$new() at test_Tuner.R:3:5
2. └─mlr3tuning (local) initialize(...)
3. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
4. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
5. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
6. └─bbotk::assert_optimizer(optimizer)
7. └─checkmate::assert_r6(optimizer, "Optimizer")
8. └─checkmate::checkR6(...)
── Error ('test_Tuner.R:21:3'): proper error if tuner cannot handle deps ───────
Error in `.__TunerGenSA__initialize(self = self, private = private, super = super)`: object 'OptimizerGenSA' not found
Backtrace:
▆
1. └─TunerGenSA$new() at test_Tuner.R:21:3
2. └─mlr3tuning (local) initialize(...)
3. └─mlr3tuning:::.__TunerGenSA__initialize(...)
── Error ('test_Tuner.R:46:3'): we get a result when some subordinate params are not fulfilled ──
Error in ``$.R6`(archive, "n_evals")`: R6 class ArchiveTuning/Archive/R6 does not have slot 'n_evals'!
Backtrace:
▆
1. ├─inst$eval_batch(d) at test_Tuner.R:46:3
2. │ └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. │ ├─self$is_terminated
4. │ └─global `$.R6`(self, "is_terminated")
5. │ └─base::get(name, envir = x)
6. └─bbotk (local) `<fn>`()
7. └─bbotk:::.__OptimInstanceBatch__is_terminated(...)
8. └─self$terminator$is_terminated(self$archive)
9. └─bbotk:::.__TerminatorEvals__is_terminated(...)
10. ├─archive$n_evals
11. └─global `$.R6`(archive, "n_evals")
── Error ('test_Tuner.R:86:3'): optimize does not work in abstract class ───────
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. ├─testthat::expect_error(tuner$optimize(inst), "abstract") at test_Tuner.R:86:3
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. └─tuner$optimize(inst)
8. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_Tuner.R:109:3'): Tuner works with graphlearner ─────────────────
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─tuner$optimize(inst) at test_Tuner.R:109:3
2. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_Tuner.R:139:3'): Tuner works with instantiated resampling ──────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. └─TunerRandomSearch$new() at test_Tuner.R:139:3
2. └─mlr3tuning (local) initialize(...)
3. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
4. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
5. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
6. └─bbotk::assert_optimizer(optimizer)
7. └─checkmate::assert_r6(optimizer, "Optimizer")
8. └─checkmate::checkR6(...)
── Error ('test_TunerGenSA.R:4:3'): TunerGenSA ─────────────────────────────────
Error in `.__TunerGenSA__initialize(self = self, private = private, super = super)`: object 'OptimizerGenSA' not found
Backtrace:
▆
1. └─global test_tuner("gensa") at test_TunerGenSA.R:4:3
2. └─mlr3tuning::tnr(key, ...)
3. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
4. └─mlr3misc:::dictionary_get(dict, .key)
5. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
6. ├─base::do.call(constructor$new, cargs)
7. └─R6 (local) `<fn>`()
8. └─mlr3tuning (local) initialize(...)
9. └─mlr3tuning:::.__TunerGenSA__initialize(...)
── Error ('test_TunerGenSA.R:22:3'): TunerGenSA with int params and trafo ──────
Error in `.__TunerGenSA__initialize(self = self, private = private, super = super)`: object 'OptimizerGenSA' not found
Backtrace:
▆
1. └─TunerGenSA$new() at test_TunerGenSA.R:22:3
2. └─mlr3tuning (local) initialize(...)
3. └─mlr3tuning:::.__TunerGenSA__initialize(...)
── Error ('test_TunerGenSA.R:30:3'): TunerGenSA - Optimize wrapper with maximize measure ──
Error in `.__TunerGenSA__initialize(self = self, private = private, super = super)`: object 'OptimizerGenSA' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("gensa", smooth = TRUE) at test_TunerGenSA.R:30:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
4. │ └─checkmate::checkR6(...)
5. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
6. ├─base::do.call(constructor$new, cargs)
7. └─R6 (local) `<fn>`()
8. └─mlr3tuning (local) initialize(...)
9. └─mlr3tuning:::.__TunerGenSA__initialize(...)
── Error ('test_TunerIrace.R:4:3'): TunerIrace ─────────────────────────────────
Error in `.__TunerIrace__initialize(self = self, private = private, super = super)`: object 'OptimizerIrace' not found
Backtrace:
▆
1. └─global test_tuner("irace", term_evals = 42, real_evals = 39) at test_TunerIrace.R:4:3
2. └─mlr3tuning::tnr(key, ...)
3. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
4. └─mlr3misc:::dictionary_get(dict, .key)
5. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
6. ├─base::do.call(constructor$new, cargs)
7. └─R6 (local) `<fn>`()
8. └─mlr3tuning (local) initialize(...)
9. └─mlr3tuning:::.__TunerIrace__initialize(...)
── Error ('test_TunerIrace.R:31:3'): TunerIrace works with dependencies ────────
Error in `.__TunerIrace__initialize(self = self, private = private, super = super)`: object 'OptimizerIrace' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("irace") at test_TunerIrace.R:31:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor$new, cargs)
6. └─R6 (local) `<fn>`()
7. └─mlr3tuning (local) initialize(...)
8. └─mlr3tuning:::.__TunerIrace__initialize(...)
── Error ('test_TunerIrace.R:43:3'): TunerIrace works with logical parameters ──
Error in `.__TunerIrace__initialize(self = self, private = private, super = super)`: object 'OptimizerIrace' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("irace") at test_TunerIrace.R:43:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor$new, cargs)
6. └─R6 (local) `<fn>`()
7. └─mlr3tuning (local) initialize(...)
8. └─mlr3tuning:::.__TunerIrace__initialize(...)
── Error ('test_TunerIrace.R:52:3'): TunerIrace uses digits ────────────────────
Error in `.__TunerIrace__initialize(self = self, private = private, super = super)`: object 'OptimizerIrace' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("irace", nbIterations = 1L, minNbSurvival = 1) at test_TunerIrace.R:52:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
4. │ └─checkmate::checkR6(...)
5. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
6. ├─base::do.call(constructor$new, cargs)
7. └─R6 (local) `<fn>`()
8. └─mlr3tuning (local) initialize(...)
9. └─mlr3tuning:::.__TunerIrace__initialize(...)
── Error ('test_TunerIrace.R:61:3'): TunerIrace works with unnamed discrete values ──
Error in `.__TunerIrace__initialize(self = self, private = private, super = super)`: object 'OptimizerIrace' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("irace") at test_TunerIrace.R:61:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor$new, cargs)
6. └─R6 (local) `<fn>`()
7. └─mlr3tuning (local) initialize(...)
8. └─mlr3tuning:::.__TunerIrace__initialize(...)
── Error ('test_TunerNLoptr.R:3:3'): TunerNLoptr ───────────────────────────────
Error in `.__TunerNLoptr__initialize(self = self, private = private, super = super)`: object 'OptimizerNLoptr' not found
Backtrace:
▆
1. └─global test_tuner("nloptr", algorithm = "NLOPT_LN_BOBYQA", term_evals = 4) at test_TunerNLoptr.R:3:3
2. └─mlr3tuning::tnr(key, ...)
3. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
4. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
5. │ └─checkmate::checkR6(...)
6. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
7. ├─base::do.call(constructor$new, cargs)
8. └─R6 (local) `<fn>`()
9. └─mlr3tuning (local) initialize(...)
10. └─mlr3tuning:::.__TunerNLoptr__initialize(...)
11. └─super$initialize(optimizer = OptimizerNLoptr$new(), man = "mlr3tuning::mlr_tuners_nloptr")
12. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
13. └─bbotk::assert_optimizer(optimizer)
14. └─checkmate::assert_r6(optimizer, "Optimizer")
15. └─checkmate::checkR6(...)
── Error ('test_TunerGridSearch.R:2:3'): TunerGridSearch ───────────────────────
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─global test_tuner(...) at test_TunerGridSearch.R:2:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_TunerGridSearch.R:22:3'): TunerGridSearch with TerminatorNone ──
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TunerGridSearch.R:22:3
2. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_TunerGridSearch.R:31:3'): TunerGridSearch works with forward hotstart parameter ──
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerGridSearch.R:31:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_TunerGridSearch.R:51:3'): TunerGridSearch works with forward hotstart parameter ──
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerGridSearch.R:51:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_TunerGridSearch.R:71:3'): TunerGridSearch works with forward and backward hotstart parameter ──
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerGridSearch.R:71:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_TunerRandomSearch.R:2:3'): TunerRandomSearch ───────────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. └─global test_tuner("random_search") at test_TunerRandomSearch.R:2:3
2. └─mlr3tuning::tnr(key, ...)
3. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
4. └─mlr3misc:::dictionary_get(dict, .key)
5. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
6. ├─base::do.call(constructor$new, cargs)
7. └─R6 (local) `<fn>`()
8. └─mlr3tuning (local) initialize(...)
9. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
10. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
11. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
12. └─bbotk::assert_optimizer(optimizer)
13. └─checkmate::assert_r6(optimizer, "Optimizer")
14. └─checkmate::checkR6(...)
── Error ('test_TuningInstanceMultiCrit.R:15:3'): tuning with multiple objectives ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("random_search") at test_TuningInstanceMultiCrit.R:15:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor$new, cargs)
6. └─R6 (local) `<fn>`()
7. └─mlr3tuning (local) initialize(...)
8. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
9. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
10. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
11. └─bbotk::assert_optimizer(optimizer)
12. └─checkmate::assert_r6(optimizer, "Optimizer")
13. └─checkmate::checkR6(...)
── Error ('test_TuningInstanceMultiCrit.R:35:3'): store_benchmark_result and store_models flag works ──
Error in ``$.R6`(archive, "n_evals")`: R6 class ArchiveTuning/Archive/R6 does not have slot 'n_evals'!
Backtrace:
▆
1. ├─inst$eval_batch(...) at test_TuningInstanceMultiCrit.R:35:3
2. │ └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. │ ├─self$is_terminated
4. │ └─global `$.R6`(self, "is_terminated")
5. │ └─base::get(name, envir = x)
6. └─bbotk (local) `<fn>`()
7. └─bbotk:::.__OptimInstanceBatch__is_terminated(...)
8. └─self$terminator$is_terminated(self$archive)
9. └─bbotk:::.__TerminatorEvals__is_terminated(...)
10. ├─archive$n_evals
11. └─global `$.R6`(archive, "n_evals")
── Error ('test_TuningInstanceMultiCrit.R:59:3'): check_values flag with parameter set dependencies ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("random_search") at test_TuningInstanceMultiCrit.R:59:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor$new, cargs)
6. └─R6 (local) `<fn>`()
7. └─mlr3tuning (local) initialize(...)
8. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
9. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
10. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
11. └─bbotk::assert_optimizer(optimizer)
12. └─checkmate::assert_r6(optimizer, "Optimizer")
13. └─checkmate::checkR6(...)
── Error ('test_TuningInstanceMultiCrit.R:113:3'): TuneToken and result_learner_param_vals works ──
Error in `.__TunerDesignPoints__initialize(self = self, private = private,
super = super)`: object 'OptimizerDesignPoints' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("design_points", design = xdt) at test_TuningInstanceMultiCrit.R:113:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
4. │ └─checkmate::checkR6(...)
5. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
6. ├─base::do.call(constructor$new, cargs)
7. └─R6 (local) `<fn>`()
8. └─mlr3tuning (local) initialize(...)
9. └─mlr3tuning:::.__TunerDesignPoints__initialize(...)
10. └─super$initialize(optimizer = OptimizerDesignPoints$new(), man = "mlr3tuning::mlr_tuners_design_points")
11. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
12. └─bbotk::assert_optimizer(optimizer)
13. └─checkmate::assert_r6(optimizer, "Optimizer")
14. └─checkmate::checkR6(...)
── Error ('test_TuningInstanceMultiCrit.R:122:3'): TuningInstanceMultiCrit and empty search space works ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TuningInstanceMultiCrit.R:122:3
2. │ └─mlr3tuning:::assert_tuner(tuner)
3. │ └─checkmate::assert_r6(tuner, "Tuner")
4. │ └─checkmate::checkR6(...)
5. └─mlr3tuning::tnr("random_search", batch_size = 5)
6. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
7. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
8. │ └─checkmate::checkR6(...)
9. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
10. ├─base::do.call(constructor$new, cargs)
11. └─R6 (local) `<fn>`()
12. └─mlr3tuning (local) initialize(...)
13. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
14. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
15. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
16. └─bbotk::assert_optimizer(optimizer)
17. └─checkmate::assert_r6(optimizer, "Optimizer")
18. └─checkmate::checkR6(...)
── Error ('test_auto_tuner.R:5:3'): auto_tuner function works ──────────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::auto_tuner(...) at test_auto_tuner.R:5:3
2. │ └─AutoTuner$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
5. │ └─mlr3tuning:::assert_tuner(tuner)
6. │ └─checkmate::assert_r6(tuner, "Tuner")
7. │ └─checkmate::checkR6(...)
8. └─mlr3tuning::tnr("random_search", batch_size = 10)
9. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
10. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
11. │ └─checkmate::checkR6(...)
12. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
13. ├─base::do.call(constructor$new, cargs)
14. └─R6 (local) `<fn>`()
15. └─mlr3tuning (local) initialize(...)
16. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
17. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
18. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
19. └─bbotk::assert_optimizer(optimizer)
20. └─checkmate::assert_r6(optimizer, "Optimizer")
21. └─checkmate::checkR6(...)
── Error ('test_error_handling.R:8:3'): failing learner ────────────────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("random_search") at test_error_handling.R:8:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor$new, cargs)
6. └─R6 (local) `<fn>`()
7. └─mlr3tuning (local) initialize(...)
8. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
9. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
10. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
11. └─bbotk::assert_optimizer(optimizer)
12. └─checkmate::assert_r6(optimizer, "Optimizer")
13. └─checkmate::checkR6(...)
── Error ('test_error_handling.R:33:3'): predictions missing ───────────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("random_search") at test_error_handling.R:33:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor$new, cargs)
6. └─R6 (local) `<fn>`()
7. └─mlr3tuning (local) initialize(...)
8. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
9. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
10. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
11. └─bbotk::assert_optimizer(optimizer)
12. └─checkmate::assert_r6(optimizer, "Optimizer")
13. └─checkmate::checkR6(...)
── Error ('test_extract_inner_tuning_archives.R:11:3'): extract_inner_tuning_archives function works ──
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3::resample(task, at, resampling_outer, store_models = TRUE) at test_extract_inner_tuning_archives.R:11:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. ├─future::value(fs)
6. └─future:::value.list(fs)
7. ├─future::resolve(...)
8. └─future:::resolve.list(...)
9. └─future (local) signalConditionsASAP(obj, resignal = FALSE, pos = ii)
10. └─future:::signalConditions(...)
── Error ('test_extract_inner_tuning_results.R:6:3'): extract_inner_tuning_results function works ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("random_search") at test_extract_inner_tuning_results.R:6:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor$new, cargs)
6. └─R6 (local) `<fn>`()
7. └─mlr3tuning (local) initialize(...)
8. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
9. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
10. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
11. └─bbotk::assert_optimizer(optimizer)
12. └─checkmate::assert_r6(optimizer, "Optimizer")
13. └─checkmate::checkR6(...)
── Error ('test_extract_inner_tuning_results.R:122:3'): extract_inner_tuning_results returns tuning_instance ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::auto_tuner(...) at test_extract_inner_tuning_results.R:122:3
2. │ └─AutoTuner$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
5. │ └─mlr3tuning:::assert_tuner(tuner)
6. │ └─checkmate::assert_r6(tuner, "Tuner")
7. │ └─checkmate::checkR6(...)
8. └─mlr3tuning::tnr("random_search")
9. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
10. └─mlr3misc:::dictionary_get(dict, .key)
11. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
12. ├─base::do.call(constructor$new, cargs)
13. └─R6 (local) `<fn>`()
14. └─mlr3tuning (local) initialize(...)
15. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
16. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
17. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
18. └─bbotk::assert_optimizer(optimizer)
19. └─checkmate::assert_r6(optimizer, "Optimizer")
20. └─checkmate::checkR6(...)
── Error ('test_TuningInstanceSingleCrit.R:4:3'): TuningInstanceSingleCrit ─────
Error in ``$.R6`(inst$archive, data)`: R6 class ArchiveTuning/Archive/R6 does not have slot 'data'!
Backtrace:
▆
1. ├─checkmate::expect_data_table(inst$archive$data, nrows = 0) at test_TuningInstanceSingleCrit.R:4:3
2. │ └─checkmate::checkDataTable(...)
3. ├─inst$archive$data
4. └─global `$.R6`(inst$archive, data)
── Error ('test_TuningInstanceSingleCrit.R:46:3'): archive one row (#40) ───────
Error in ``$.R6`(archive, "n_evals")`: R6 class ArchiveTuning/Archive/R6 does not have slot 'n_evals'!
Backtrace:
▆
1. ├─inst$eval_batch(data.table(cp = 0.1)) at test_TuningInstanceSingleCrit.R:46:3
2. │ └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. │ ├─self$is_terminated
4. │ └─global `$.R6`(self, "is_terminated")
5. │ └─base::get(name, envir = x)
6. └─bbotk (local) `<fn>`()
7. └─bbotk:::.__OptimInstanceBatch__is_terminated(...)
8. └─self$terminator$is_terminated(self$archive)
9. └─bbotk:::.__TerminatorEvals__is_terminated(...)
10. ├─archive$n_evals
11. └─global `$.R6`(archive, "n_evals")
── Error ('test_TuningInstanceSingleCrit.R:55:3'): eval_batch and termination ──
Error in ``$.R6`(archive, "n_evals")`: R6 class ArchiveTuning/Archive/R6 does not have slot 'n_evals'!
Backtrace:
▆
1. ├─inst$eval_batch(design[1:2, ]) at test_TuningInstanceSingleCrit.R:55:3
2. │ └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. │ ├─self$is_terminated
4. │ └─global `$.R6`(self, "is_terminated")
5. │ └─base::get(name, envir = x)
6. └─bbotk (local) `<fn>`()
7. └─bbotk:::.__OptimInstanceBatch__is_terminated(...)
8. └─self$terminator$is_terminated(self$archive)
9. └─bbotk:::.__TerminatorEvals__is_terminated(...)
10. ├─archive$n_evals
11. └─global `$.R6`(archive, "n_evals")
── Error ('test_TuningInstanceSingleCrit.R:76:3'): the same experiment can be added twice ──
Error in ``$.R6`(archive, "n_evals")`: R6 class ArchiveTuning/Archive/R6 does not have slot 'n_evals'!
Backtrace:
▆
1. ├─inst$eval_batch(d) at test_TuningInstanceSingleCrit.R:76:3
2. │ └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. │ ├─self$is_terminated
4. │ └─global `$.R6`(self, "is_terminated")
5. │ └─base::get(name, envir = x)
6. └─bbotk (local) `<fn>`()
7. └─bbotk:::.__OptimInstanceBatch__is_terminated(...)
8. └─self$terminator$is_terminated(self$archive)
9. └─bbotk:::.__TerminatorEvals__is_terminated(...)
10. ├─archive$n_evals
11. └─global `$.R6`(archive, "n_evals")
── Error ('test_TuningInstanceSingleCrit.R:96:3'): tuning with custom resampling ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("random_search") at test_TuningInstanceSingleCrit.R:96:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor$new, cargs)
6. └─R6 (local) `<fn>`()
7. └─mlr3tuning (local) initialize(...)
8. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
9. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
10. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
11. └─bbotk::assert_optimizer(optimizer)
12. └─checkmate::assert_r6(optimizer, "Optimizer")
13. └─checkmate::checkR6(...)
── Error ('test_TuningInstanceSingleCrit.R:131:3'): non-scalar hyperpars (#201) ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("random_search") at test_TuningInstanceSingleCrit.R:131:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor$new, cargs)
6. └─R6 (local) `<fn>`()
7. └─mlr3tuning (local) initialize(...)
8. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
9. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
10. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
11. └─bbotk::assert_optimizer(optimizer)
12. └─checkmate::assert_r6(optimizer, "Optimizer")
13. └─checkmate::checkR6(...)
── Error ('test_TuningInstanceSingleCrit.R:139:3'): store_benchmark_result and store_models flag works ──
Error in ``$.R6`(archive, "n_evals")`: R6 class ArchiveTuning/Archive/R6 does not have slot 'n_evals'!
Backtrace:
▆
1. ├─inst$eval_batch(...) at test_TuningInstanceSingleCrit.R:139:3
2. │ └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. │ ├─self$is_terminated
4. │ └─global `$.R6`(self, "is_terminated")
5. │ └─base::get(name, envir = x)
6. └─bbotk (local) `<fn>`()
7. └─bbotk:::.__OptimInstanceBatch__is_terminated(...)
8. └─self$terminator$is_terminated(self$archive)
9. └─bbotk:::.__TerminatorEvals__is_terminated(...)
10. ├─archive$n_evals
11. └─global `$.R6`(archive, "n_evals")
── Error ('test_TuningInstanceSingleCrit.R:169:3'): check_values flag with parameter set dependencies ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("random_search") at test_TuningInstanceSingleCrit.R:169:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. └─mlr3misc:::dictionary_get(dict, .key)
4. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
5. ├─base::do.call(constructor$new, cargs)
6. └─R6 (local) `<fn>`()
7. └─mlr3tuning (local) initialize(...)
8. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
9. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
10. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
11. └─bbotk::assert_optimizer(optimizer)
12. └─checkmate::assert_r6(optimizer, "Optimizer")
13. └─checkmate::checkR6(...)
── Error ('test_TuningInstanceSingleCrit.R:222:3'): TuneToken and result_learner_param_vals works ──
Error in `.__TunerDesignPoints__initialize(self = self, private = private,
super = super)`: object 'OptimizerDesignPoints' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("design_points", design = xdt) at test_TuningInstanceSingleCrit.R:222:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
4. │ └─checkmate::checkR6(...)
5. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
6. ├─base::do.call(constructor$new, cargs)
7. └─R6 (local) `<fn>`()
8. └─mlr3tuning (local) initialize(...)
9. └─mlr3tuning:::.__TunerDesignPoints__initialize(...)
10. └─super$initialize(optimizer = OptimizerDesignPoints$new(), man = "mlr3tuning::mlr_tuners_design_points")
11. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
12. └─bbotk::assert_optimizer(optimizer)
13. └─checkmate::assert_r6(optimizer, "Optimizer")
14. └─checkmate::checkR6(...)
── Error ('test_TuningInstanceSingleCrit.R:233:3'): TuningInstanceSingleCrit and empty search space works ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_TuningInstanceSingleCrit.R:233:3
2. │ └─mlr3tuning:::assert_tuner(tuner)
3. │ └─checkmate::assert_r6(tuner, "Tuner")
4. │ └─checkmate::checkR6(...)
5. └─mlr3tuning::tnr("random_search", batch_size = 5)
6. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
7. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
8. │ └─checkmate::checkR6(...)
9. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
10. ├─base::do.call(constructor$new, cargs)
11. └─R6 (local) `<fn>`()
12. └─mlr3tuning (local) initialize(...)
13. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
14. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
15. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
16. └─bbotk::assert_optimizer(optimizer)
17. └─checkmate::assert_r6(optimizer, "Optimizer")
18. └─checkmate::checkR6(...)
── Error ('test_mlr_callbacks.R:52:3'): backup callback works ──────────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_mlr_callbacks.R:52:3
2. │ └─mlr3tuning:::assert_tuner(tuner)
3. │ └─checkmate::assert_r6(tuner, "Tuner")
4. │ └─checkmate::checkR6(...)
5. └─mlr3tuning::tnr("random_search", batch_size = 2)
6. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
7. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
8. │ └─checkmate::checkR6(...)
9. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
10. ├─base::do.call(constructor$new, cargs)
11. └─R6 (local) `<fn>`()
12. └─mlr3tuning (local) initialize(...)
13. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
14. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
15. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
16. └─bbotk::assert_optimizer(optimizer)
17. └─checkmate::assert_r6(optimizer, "Optimizer")
18. └─checkmate::checkR6(...)
── Error ('test_mlr_callbacks.R:69:3'): backup callback works with standalone tuner ──
Error: 'CallbackOptimization' is not an exported object from 'namespace:bbotk'
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_mlr_callbacks.R:69:3
2. │ └─TuningInstance$new(...)
3. │ └─mlr3tuning (local) initialize(...)
4. │ └─mlr3tuning:::.__TuningInstanceSingleCrit__initialize(...)
5. │ └─ObjectiveTuning$new(...)
6. │ └─mlr3tuning (local) initialize(...)
7. │ └─mlr3tuning:::.__ObjectiveTuning__initialize(...)
8. │ ├─mlr3misc::assert_callbacks(as_callbacks(callbacks))
9. │ │ └─base::lapply(callbacks, assert_callback)
10. │ └─mlr3misc::as_callbacks(callbacks)
11. └─mlr3misc::clbk("mlr3tuning.backup", path = file)
12. └─mlr3misc::dictionary_sugar_get(mlr_callbacks, .key)
13. └─mlr3misc:::dictionary_get(dict, .key)
14. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
15. ├─base::do.call(constructor, cargs)
16. └─mlr3tuning (local) `<fn>`()
17. └─mlr3tuning::callback_tuning(...)
18. └─CallbackTuning$new(id, label, man)
19. └─R6 (local) get_inherit()
20. └─base::eval(inherit, parent_env, NULL)
21. └─base::eval(inherit, parent_env, NULL)
── Error ('test_mlr_tuners.R:2:3'): mlr_tuners ─────────────────────────────────
Error in `.__TunerCmaes__initialize(self = self, private = private, super = super)`: object 'OptimizerCmaes' not found
Backtrace:
▆
1. └─global expect_dictionary(mlr_tuners, min_items = 1L) at test_mlr_tuners.R:2:3
2. ├─checkmate::expect_data_table(...)
3. │ └─checkmate::checkDataTable(...)
4. ├─data.table::as.data.table(d)
5. └─mlr3tuning:::as.data.table.DictionaryTuner(d)
6. ├─data.table::setkeyv(...)
7. │ └─data.table::is.data.table(x)
8. └─mlr3misc::map_dtr(...)
9. ├─data.table::rbindlist(...)
10. ├─base::unname(map(.x, .f, ...))
11. └─mlr3misc::map(.x, .f, ...)
12. └─base::lapply(.x, .f, ...)
13. └─mlr3tuning (local) FUN(X[[i]], ...)
14. ├─base::withCallingHandlers(x$get(key), packageNotFoundWarning = function(w) invokeRestart("muffleWarning"))
15. └─x$get(key)
16. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─mlr3misc:::dictionary_get(self = self, key = key)
21. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
22. ├─base::do.call(constructor$new, cargs)
23. └─R6 (local) `<fn>`()
24. └─mlr3tuning (local) initialize(...)
25. └─mlr3tuning:::.__TunerCmaes__initialize(...)
26. └─super$initialize(optimizer = OptimizerCmaes$new(), man = "mlr3tuning::mlr_tuners_cmaes")
27. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
28. └─bbotk::assert_optimizer(optimizer)
29. └─checkmate::assert_r6(optimizer, "Optimizer")
30. └─checkmate::checkR6(...)
── Error ('test_mlr_tuners.R:12:3'): mlr_tuners sugar ──────────────────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─checkmate::expect_class(tnr("random_search"), "Tuner") at test_mlr_tuners.R:12:3
2. │ └─checkmate::checkClass(x, classes, ordered, null.ok)
3. └─mlr3tuning::tnr("random_search")
4. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
5. └─mlr3misc:::dictionary_get(dict, .key)
6. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
7. ├─base::do.call(constructor$new, cargs)
8. └─R6 (local) `<fn>`()
9. └─mlr3tuning (local) initialize(...)
10. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
11. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
12. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
13. └─bbotk::assert_optimizer(optimizer)
14. └─checkmate::assert_r6(optimizer, "Optimizer")
15. └─checkmate::checkR6(...)
── Error ('test_mlr_tuners.R:17:3'): as.data.table objects parameter ───────────
Error in `.__TunerCmaes__initialize(self = self, private = private, super = super)`: object 'OptimizerCmaes' not found
Backtrace:
▆
1. ├─data.table::as.data.table(mlr_tuners, objects = TRUE) at test_mlr_tuners.R:17:3
2. └─mlr3tuning:::as.data.table.DictionaryTuner(mlr_tuners, objects = TRUE)
3. ├─data.table::setkeyv(...)
4. │ └─data.table::is.data.table(x)
5. └─mlr3misc::map_dtr(...)
6. ├─data.table::rbindlist(...)
7. ├─base::unname(map(.x, .f, ...))
8. └─mlr3misc::map(.x, .f, ...)
9. └─base::lapply(.x, .f, ...)
10. └─mlr3tuning (local) FUN(X[[i]], ...)
11. ├─base::withCallingHandlers(x$get(key), packageNotFoundWarning = function(w) invokeRestart("muffleWarning"))
12. └─x$get(key)
13. ├─mlr3misc::invoke(dictionary_get, self = self, key = key, .args = args)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─mlr3misc:::dictionary_get(self = self, key = key)
18. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
19. ├─base::do.call(constructor$new, cargs)
20. └─R6 (local) `<fn>`()
21. └─mlr3tuning (local) initialize(...)
22. └─mlr3tuning:::.__TunerCmaes__initialize(...)
23. └─super$initialize(optimizer = OptimizerCmaes$new(), man = "mlr3tuning::mlr_tuners_cmaes")
24. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
25. └─bbotk::assert_optimizer(optimizer)
26. └─checkmate::assert_r6(optimizer, "Optimizer")
27. └─checkmate::checkR6(...)
── Error ('test_hotstart.R:5:3'): hotstart works forwards ──────────────────────
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_hotstart.R:5:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_hotstart.R:26:3'): hotstart works backwards ────────────────────
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_hotstart.R:26:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_hotstart.R:47:3'): hotstart works forwards and backwards ───────
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_hotstart.R:47:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_hotstart.R:67:3'): hotstart flag is not set to TRUE if learners does not support hotstarting ──
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_hotstart.R:67:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_hotstart.R:84:3'): models are discarded after storing them in the stack ──
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_hotstart.R:84:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_hotstart.R:107:3'): objects are cloned ─────────────────────────
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_hotstart.R:107:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_trafos.R:8:3'): simple exp trafo works ─────────────────────────
Error in `.__TunerDesignPoints__initialize(self = self, private = private,
super = super)`: object 'OptimizerDesignPoints' not found
Backtrace:
▆
1. └─mlr3tuning::tnr("design_points", design = d) at test_trafos.R:8:3
2. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
3. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
4. │ └─checkmate::checkR6(...)
5. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
6. ├─base::do.call(constructor$new, cargs)
7. └─R6 (local) `<fn>`()
8. └─mlr3tuning (local) initialize(...)
9. └─mlr3tuning:::.__TunerDesignPoints__initialize(...)
10. └─super$initialize(optimizer = OptimizerDesignPoints$new(), man = "mlr3tuning::mlr_tuners_design_points")
11. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
12. └─bbotk::assert_optimizer(optimizer)
13. └─checkmate::assert_r6(optimizer, "Optimizer")
14. └─checkmate::checkR6(...)
── Error ('test_trafos.R:34:3'): trafo where param names change ────────────────
Error in `.__Tuner__optimize(self = self, private = private, super = super,
inst = inst)`: object 'ContextOptimization' not found
Backtrace:
▆
1. └─tuner$optimize(inst) at test_trafos.R:34:3
2. └─mlr3tuning:::.__Tuner__optimize(...)
── Error ('test_tune_nested.R:5:3'): tune_nested function works ────────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::tune_nested(...) at test_tune_nested.R:5:3
2. │ └─mlr3tuning::auto_tuner(...)
3. │ └─AutoTuner$new(...)
4. │ └─mlr3tuning (local) initialize(...)
5. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
6. │ └─mlr3tuning:::assert_tuner(tuner)
7. │ └─checkmate::assert_r6(tuner, "Tuner")
8. │ └─checkmate::checkR6(...)
9. └─mlr3tuning::tnr("random_search", batch_size = 1)
10. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
11. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
12. │ └─checkmate::checkR6(...)
13. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
14. ├─base::do.call(constructor$new, cargs)
15. └─R6 (local) `<fn>`()
16. └─mlr3tuning (local) initialize(...)
17. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
18. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
19. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
20. └─bbotk::assert_optimizer(optimizer)
21. └─checkmate::assert_r6(optimizer, "Optimizer")
22. └─checkmate::checkR6(...)
── Error ('test_tune.R:3:3'): tune function works with one measure ─────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_tune.R:3:3
2. │ └─mlr3tuning:::assert_tuner(tuner)
3. │ └─checkmate::assert_r6(tuner, "Tuner")
4. │ └─checkmate::checkR6(...)
5. └─mlr3tuning::tnr("random_search", batch_size = 1)
6. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
7. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
8. │ └─checkmate::checkR6(...)
9. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
10. ├─base::do.call(constructor$new, cargs)
11. └─R6 (local) `<fn>`()
12. └─mlr3tuning (local) initialize(...)
13. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
14. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
15. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
16. └─bbotk::assert_optimizer(optimizer)
17. └─checkmate::assert_r6(optimizer, "Optimizer")
18. └─checkmate::checkR6(...)
── Error ('test_tune.R:13:3'): tune function works with multiple measures ──────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_tune.R:13:3
2. │ └─mlr3tuning:::assert_tuner(tuner)
3. │ └─checkmate::assert_r6(tuner, "Tuner")
4. │ └─checkmate::checkR6(...)
5. └─mlr3tuning::tnr("random_search", batch_size = 1)
6. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
7. ├─checkmate::assert_r6(dictionary_initialize_item(.key, obj, dots[ii]))
8. │ └─checkmate::checkR6(...)
9. └─mlr3misc:::dictionary_initialize_item(.key, obj, dots[ii])
10. ├─base::do.call(constructor$new, cargs)
11. └─R6 (local) `<fn>`()
12. └─mlr3tuning (local) initialize(...)
13. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
14. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
15. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
16. └─bbotk::assert_optimizer(optimizer)
17. └─checkmate::assert_r6(optimizer, "Optimizer")
18. └─checkmate::checkR6(...)
── Error ('test_tune.R:23:3'): tune function works without measure ─────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_tune.R:23:3
2. │ └─mlr3tuning:::assert_tuner(tuner)
3. │ └─checkmate::assert_r6(tuner, "Tuner")
4. │ └─checkmate::checkR6(...)
5. └─mlr3tuning::tnr("random_search")
6. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
7. └─mlr3misc:::dictionary_get(dict, .key)
8. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
9. ├─base::do.call(constructor$new, cargs)
10. └─R6 (local) `<fn>`()
11. └─mlr3tuning (local) initialize(...)
12. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
13. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
14. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
15. └─bbotk::assert_optimizer(optimizer)
16. └─checkmate::assert_r6(optimizer, "Optimizer")
17. └─checkmate::checkR6(...)
── Error ('test_tune.R:55:3'): evaluate_default works ──────────────────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_tune.R:55:3
2. │ └─mlr3tuning:::assert_tuner(tuner)
3. │ └─checkmate::assert_r6(tuner, "Tuner")
4. │ └─checkmate::checkR6(...)
5. └─mlr3tuning::tnr("random_search")
6. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
7. └─mlr3misc:::dictionary_get(dict, .key)
8. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
9. ├─base::do.call(constructor$new, cargs)
10. └─R6 (local) `<fn>`()
11. └─mlr3tuning (local) initialize(...)
12. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
13. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
14. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
15. └─bbotk::assert_optimizer(optimizer)
16. └─checkmate::assert_r6(optimizer, "Optimizer")
17. └─checkmate::checkR6(...)
── Error ('test_tune.R:72:3'): evaluate_default works with logscale ────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_tune.R:72:3
2. │ └─mlr3tuning:::assert_tuner(tuner)
3. │ └─checkmate::assert_r6(tuner, "Tuner")
4. │ └─checkmate::checkR6(...)
5. └─mlr3tuning::tnr("random_search")
6. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
7. └─mlr3misc:::dictionary_get(dict, .key)
8. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
9. ├─base::do.call(constructor$new, cargs)
10. └─R6 (local) `<fn>`()
11. └─mlr3tuning (local) initialize(...)
12. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
13. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
14. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
15. └─bbotk::assert_optimizer(optimizer)
16. └─checkmate::assert_r6(optimizer, "Optimizer")
17. └─checkmate::checkR6(...)
── Error ('test_tune.R:89:3'): evaluate_default errors with trafo ──────────────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_tune.R:89:3
2. │ └─testthat:::expect_condition_matching(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─mlr3tuning:::assert_tuner(tuner)
9. │ └─checkmate::assert_r6(tuner, "Tuner")
10. │ └─checkmate::checkR6(...)
11. └─mlr3tuning::tnr("random_search")
12. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
13. └─mlr3misc:::dictionary_get(dict, .key)
14. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
15. ├─base::do.call(constructor$new, cargs)
16. └─R6 (local) `<fn>`()
17. └─mlr3tuning (local) initialize(...)
18. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
19. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
20. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
21. └─bbotk::assert_optimizer(optimizer)
22. └─checkmate::assert_r6(optimizer, "Optimizer")
23. └─checkmate::checkR6(...)
── Error ('test_tune.R:105:3'): evaluate_default works without transformation and with logscale ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─mlr3tuning::tune(...) at test_tune.R:105:3
2. │ └─mlr3tuning:::assert_tuner(tuner)
3. │ └─checkmate::assert_r6(tuner, "Tuner")
4. │ └─checkmate::checkR6(...)
5. └─mlr3tuning::tnr("random_search")
6. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
7. └─mlr3misc:::dictionary_get(dict, .key)
8. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
9. ├─base::do.call(constructor$new, cargs)
10. └─R6 (local) `<fn>`()
11. └─mlr3tuning (local) initialize(...)
12. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
13. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
14. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
15. └─bbotk::assert_optimizer(optimizer)
16. └─checkmate::assert_r6(optimizer, "Optimizer")
17. └─checkmate::checkR6(...)
── Error ('test_tune.R:127:3'): evaluate_default errors without transformation and with logscale and trafo ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_tune.R:127:3
2. │ └─testthat:::expect_condition_matching(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─mlr3tuning:::assert_tuner(tuner)
9. │ └─checkmate::assert_r6(tuner, "Tuner")
10. │ └─checkmate::checkR6(...)
11. └─mlr3tuning::tnr("random_search")
12. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
13. └─mlr3misc:::dictionary_get(dict, .key)
14. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
15. ├─base::do.call(constructor$new, cargs)
16. └─R6 (local) `<fn>`()
17. └─mlr3tuning (local) initialize(...)
18. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
19. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
20. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
21. └─bbotk::assert_optimizer(optimizer)
22. └─checkmate::assert_r6(optimizer, "Optimizer")
23. └─checkmate::checkR6(...)
── Error ('test_tune.R:150:3'): evaluate_default errors with extra trafo ───────
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_tune.R:150:3
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. │ └─mlr3tuning:::assert_tuner(tuner)
9. │ └─checkmate::assert_r6(tuner, "Tuner")
10. │ └─checkmate::checkR6(...)
11. └─mlr3tuning::tnr("random_search")
12. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
13. └─mlr3misc:::dictionary_get(dict, .key)
14. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
15. ├─base::do.call(constructor$new, cargs)
16. └─R6 (local) `<fn>`()
17. └─mlr3tuning (local) initialize(...)
18. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
19. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
20. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
21. └─bbotk::assert_optimizer(optimizer)
22. └─checkmate::assert_r6(optimizer, "Optimizer")
23. └─checkmate::checkR6(...)
── Error ('test_tune.R:168:3'): evaluate_default errors with old parameter set api ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_tune.R:168:3
2. │ └─testthat:::expect_condition_matching(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. ├─mlr3tuning::tune(...)
8. │ └─mlr3tuning:::assert_tuner(tuner)
9. │ └─checkmate::assert_r6(tuner, "Tuner")
10. │ └─checkmate::checkR6(...)
11. └─mlr3tuning::tnr("random_search")
12. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
13. └─mlr3misc:::dictionary_get(dict, .key)
14. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
15. ├─base::do.call(constructor$new, cargs)
16. └─R6 (local) `<fn>`()
17. └─mlr3tuning (local) initialize(...)
18. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
19. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
20. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
21. └─bbotk::assert_optimizer(optimizer)
22. └─checkmate::assert_r6(optimizer, "Optimizer")
23. └─checkmate::checkR6(...)
[ FAIL 95 | WARN 0 | SKIP 1 | PASS 149 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.0.0
Check: package dependencies
Result: ERROR
Packages required and available but unsuitable versions:
'mlr3', 'paradox', 'bbotk'
See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64
Current CRAN status: ERROR: 1, OK: 12
Version: 0.5.1
Check: examples
Result: ERROR
Running examples in ‘mlr3tuningspaces-Ex.R’ failed
The error most likely occurred in:
> ### Name: TuningSpace
> ### Title: Tuning Spaces
> ### Aliases: TuningSpace
>
> ### ** Examples
>
> library(mlr3tuning)
>
> # get default tuning space of rpart learner
> tuning_space = lts("classif.rpart.default")
>
> # get learner and set tuning space
> learner = lrn("classif.rpart")
> learner$param_set$values = tuning_space$values
>
> # tune learner
> instance = tune(
+ tnr("random_search"),
+ task = tsk("pima"),
+ learner = learner,
+ resampling = rsmp ("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 10)
Error in .__TunerRandomSearch__initialize(self = self, private = private, :
object 'OptimizerRandomSearch' not found
Calls: tune ... .__TunerFromOptimizer__initialize -> assert_optimizer -> assert_r6 -> checkR6
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.5.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [64s/83s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3tuningspaces")
+ test_check("mlr3tuningspaces")
+ }
Loading required package: mlr3tuning
Loading required package: mlr3
Loading required package: paradox
OptimInstanceSingleCrit is deprecated. Use OptimInstanceBatchSingleCrit instead.
OptimInstanceMultiCrit is deprecated. Use OptimInstanceBatchMultiCrit instead.
[ FAIL 1 | WARN 0 | SKIP 0 | PASS 1338 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_as_search_space.R:30:3'): search space from TuningSpace works ──
Error in `.__TunerRandomSearch__initialize(self = self, private = private,
super = super)`: object 'OptimizerRandomSearch' not found
Backtrace:
▆
1. ├─AutoTuner$new(...) at test_as_search_space.R:30:3
2. │ └─mlr3tuning (local) initialize(...)
3. │ └─mlr3tuning:::.__AutoTuner__initialize(...)
4. │ └─mlr3tuning:::assert_tuner(tuner)
5. │ └─checkmate::assert_r6(tuner, "Tuner")
6. │ └─checkmate::checkR6(...)
7. └─mlr3tuning::tnr("random_search")
8. └─mlr3misc::dictionary_sugar_get(mlr_tuners, .key, ...)
9. └─mlr3misc:::dictionary_get(dict, .key)
10. └─mlr3misc:::dictionary_initialize_item(key, obj, dots)
11. ├─base::do.call(constructor$new, cargs)
12. └─R6 (local) `<fn>`()
13. └─mlr3tuning (local) initialize(...)
14. └─mlr3tuning:::.__TunerRandomSearch__initialize(...)
15. └─super$initialize(optimizer = OptimizerRandomSearch$new(), man = "mlr3tuning::mlr_tuners_random_search")
16. └─mlr3tuning:::.__TunerFromOptimizer__initialize(...)
17. └─bbotk::assert_optimizer(optimizer)
18. └─checkmate::assert_r6(optimizer, "Optimizer")
19. └─checkmate::checkR6(...)
[ FAIL 1 | WARN 0 | SKIP 0 | PASS 1338 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Current CRAN status: NOTE: 1, OK: 12
Version: 0.1.0
Check: Rd cross-references
Result: NOTE
Undeclared package ‘R6’ in Rd xrefs
Flavor: r-devel-linux-x86_64-fedora-clang