Last updated on 2025-12-21 11:50:38 CET.
| Package | ERROR | NOTE | OK |
|---|---|---|---|
| bbotk | 4 | 9 | |
| farff | 13 | ||
| mlr3 | 4 | 1 | 8 |
| mlr3batchmark | 4 | 9 | |
| mlr3data | 13 | ||
| mlr3db | 4 | 3 | 6 |
| mlr3filters | 4 | 9 | |
| mlr3fselect | 4 | 9 | |
| mlr3hyperband | 4 | 9 | |
| mlr3learners | 4 | 9 | |
| mlr3mbo | 4 | 9 | |
| mlr3measures | 13 | ||
| mlr3misc | 13 | ||
| mlr3spatial | 13 | ||
| mlr3tuning | 5 | 8 | |
| mlr3tuningspaces | 4 | 9 | |
| mlr3verse | 3 | 10 | |
| mlr3viz | 4 | 3 | 6 |
| rush | 13 |
Current CRAN status: ERROR: 4, OK: 9
Version: 1.8.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [284s/375s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ test_check("bbotk")
+ }
Loading required package: bbotk
Loading required package: paradox
[ FAIL 4 | WARN 0 | SKIP 53 | PASS 1160 ]
══ Skipped tests (53) ══════════════════════════════════════════════════════════
• On CRAN (52): 'test_ArchiveAsync.R:2:3', 'test_ArchiveAsync.R:61:3',
'test_ArchiveAsyncFrozen.R:2:3', 'test_ArchiveBatch.R:1:1',
'test_CallbackAsync.R:4:3', 'test_CallbackAsync.R:31:3',
'test_CallbackAsync.R:59:3', 'test_CallbackAsync.R:88:3',
'test_CallbackAsync.R:118:3', 'test_CallbackAsync.R:154:3',
'test_CallbackAsync.R:183:3', 'test_CallbackAsync.R:210:3',
'test_CallbackAsync.R:239:3', 'test_CallbackAsync.R:269:3',
'test_CallbackAsync.R:297:3', 'test_Objective.R:1:1',
'test_OptimInstanceAsyncSingleCrit.R:2:3',
'test_OptimInstanceAsyncSingleCrit.R:26:3',
'test_OptimInstanceAsyncSingleCrit.R:45:3',
'test_OptimInstanceAsyncSingleCrit.R:65:3',
'test_OptimInstanceAsyncSingleCrit.R:82:3',
'test_OptimInstanceAsyncSingleCrit.R:109:3',
'test_OptimInstanceBatchMultiCrit.R:1:1',
'test_OptimInstanceBatchSingleCrit.R:1:1',
'test_OptimizerAsynDesignPoints.R:2:3', 'test_OptimizerAsynGridSearch.R:2:3',
'test_OptimizerAsync.R:2:3', 'test_OptimizerAsync.R:26:3',
'test_OptimizerAsync.R:50:3', 'test_OptimizerAsync.R:73:3',
'test_OptimizerAsync.R:95:3', 'test_OptimizerAsync.R:124:3',
'test_OptimizerAsync.R:155:3', 'test_OptimizerAsync.R:178:3',
'test_OptimizerAsyncRandomSearch.R:2:3', 'test_OptimizerBatchCmaes.R:1:1',
'test_OptimizerBatchDesignPoints.R:1:1',
'test_OptimizerBatchFocusSearch.R:1:1', 'test_OptimizerBatchGenSA.R:1:1',
'test_OptimizerBatchGridSearch.R:1:1', 'test_OptimizerBatchNLoptr.R:1:1',
'test_OptimizerBatchRandomSearch.R:1:1', 'test_TerminatorClockTime.R:1:1',
'test_TerminatorCombo.R:1:1', 'test_TerminatorEvals.R:1:1',
'test_TerminatorNone.R:1:1', 'test_TerminatorPerfReached.R:1:1',
'test_TerminatorRunTime.R:2:5', 'test_TerminatorStagnation.R:1:1',
'test_TerminatorStagnationBatch.R:1:1',
'test_TerminatorStagnationBatch.R:15:1', 'test_mlr_callbacks.R:58:3'
• TRUE is TRUE (1): 'test_mlr_callbacks.R:19:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_OptimizerBatchIrace.R:23:3'): OptimizerBatchIrace minimize works ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:23:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
── Error ('test_OptimizerBatchIrace.R:63:3'): OptimizerBatchIrace maximize works ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:63:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
── Error ('test_OptimizerBatchIrace.R:129:3'): OptimizerBatchIrace works with passed constants set ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:129:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
── Error ('test_OptimizerBatchIrace.R:154:3'): OptimizerBatchIrace works without passed constants set ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:154:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
[ FAIL 4 | WARN 0 | SKIP 53 | PASS 1160 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.8.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [191s/214s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ test_check("bbotk")
+ }
Loading required package: bbotk
Loading required package: paradox
[ FAIL 4 | WARN 0 | SKIP 53 | PASS 1160 ]
══ Skipped tests (53) ══════════════════════════════════════════════════════════
• On CRAN (52): 'test_ArchiveAsync.R:2:3', 'test_ArchiveAsync.R:61:3',
'test_ArchiveAsyncFrozen.R:2:3', 'test_ArchiveBatch.R:1:1',
'test_CallbackAsync.R:4:3', 'test_CallbackAsync.R:31:3',
'test_CallbackAsync.R:59:3', 'test_CallbackAsync.R:88:3',
'test_CallbackAsync.R:118:3', 'test_CallbackAsync.R:154:3',
'test_CallbackAsync.R:183:3', 'test_CallbackAsync.R:210:3',
'test_CallbackAsync.R:239:3', 'test_CallbackAsync.R:269:3',
'test_CallbackAsync.R:297:3', 'test_Objective.R:1:1',
'test_OptimInstanceAsyncSingleCrit.R:2:3',
'test_OptimInstanceAsyncSingleCrit.R:26:3',
'test_OptimInstanceAsyncSingleCrit.R:45:3',
'test_OptimInstanceAsyncSingleCrit.R:65:3',
'test_OptimInstanceAsyncSingleCrit.R:82:3',
'test_OptimInstanceAsyncSingleCrit.R:109:3',
'test_OptimInstanceBatchMultiCrit.R:1:1',
'test_OptimInstanceBatchSingleCrit.R:1:1',
'test_OptimizerAsynDesignPoints.R:2:3', 'test_OptimizerAsynGridSearch.R:2:3',
'test_OptimizerAsync.R:2:3', 'test_OptimizerAsync.R:26:3',
'test_OptimizerAsync.R:50:3', 'test_OptimizerAsync.R:73:3',
'test_OptimizerAsync.R:95:3', 'test_OptimizerAsync.R:124:3',
'test_OptimizerAsync.R:155:3', 'test_OptimizerAsync.R:178:3',
'test_OptimizerAsyncRandomSearch.R:2:3', 'test_OptimizerBatchCmaes.R:1:1',
'test_OptimizerBatchDesignPoints.R:1:1',
'test_OptimizerBatchFocusSearch.R:1:1', 'test_OptimizerBatchGenSA.R:1:1',
'test_OptimizerBatchGridSearch.R:1:1', 'test_OptimizerBatchNLoptr.R:1:1',
'test_OptimizerBatchRandomSearch.R:1:1', 'test_TerminatorClockTime.R:1:1',
'test_TerminatorCombo.R:1:1', 'test_TerminatorEvals.R:1:1',
'test_TerminatorNone.R:1:1', 'test_TerminatorPerfReached.R:1:1',
'test_TerminatorRunTime.R:2:5', 'test_TerminatorStagnation.R:1:1',
'test_TerminatorStagnationBatch.R:1:1',
'test_TerminatorStagnationBatch.R:15:1', 'test_mlr_callbacks.R:58:3'
• TRUE is TRUE (1): 'test_mlr_callbacks.R:19:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_OptimizerBatchIrace.R:23:3'): OptimizerBatchIrace minimize works ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:23:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
── Error ('test_OptimizerBatchIrace.R:63:3'): OptimizerBatchIrace maximize works ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:63:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
── Error ('test_OptimizerBatchIrace.R:129:3'): OptimizerBatchIrace works with passed constants set ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:129:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
── Error ('test_OptimizerBatchIrace.R:154:3'): OptimizerBatchIrace works without passed constants set ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:154:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
[ FAIL 4 | WARN 0 | SKIP 53 | PASS 1160 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.8.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [253s/260s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ test_check("bbotk")
+ }
Loading required package: bbotk
Loading required package: paradox
[ FAIL 4 | WARN 0 | SKIP 53 | PASS 1160 ]
══ Skipped tests (53) ══════════════════════════════════════════════════════════
• On CRAN (52): 'test_ArchiveAsync.R:2:3', 'test_ArchiveAsync.R:61:3',
'test_ArchiveAsyncFrozen.R:2:3', 'test_ArchiveBatch.R:1:1',
'test_CallbackAsync.R:4:3', 'test_CallbackAsync.R:31:3',
'test_CallbackAsync.R:59:3', 'test_CallbackAsync.R:88:3',
'test_CallbackAsync.R:118:3', 'test_CallbackAsync.R:154:3',
'test_CallbackAsync.R:183:3', 'test_CallbackAsync.R:210:3',
'test_CallbackAsync.R:239:3', 'test_CallbackAsync.R:269:3',
'test_CallbackAsync.R:297:3', 'test_Objective.R:1:1',
'test_OptimInstanceAsyncSingleCrit.R:2:3',
'test_OptimInstanceAsyncSingleCrit.R:26:3',
'test_OptimInstanceAsyncSingleCrit.R:45:3',
'test_OptimInstanceAsyncSingleCrit.R:65:3',
'test_OptimInstanceAsyncSingleCrit.R:82:3',
'test_OptimInstanceAsyncSingleCrit.R:109:3',
'test_OptimInstanceBatchMultiCrit.R:1:1',
'test_OptimInstanceBatchSingleCrit.R:1:1',
'test_OptimizerAsynDesignPoints.R:2:3', 'test_OptimizerAsynGridSearch.R:2:3',
'test_OptimizerAsync.R:2:3', 'test_OptimizerAsync.R:26:3',
'test_OptimizerAsync.R:50:3', 'test_OptimizerAsync.R:73:3',
'test_OptimizerAsync.R:95:3', 'test_OptimizerAsync.R:124:3',
'test_OptimizerAsync.R:155:3', 'test_OptimizerAsync.R:178:3',
'test_OptimizerAsyncRandomSearch.R:2:3', 'test_OptimizerBatchCmaes.R:1:1',
'test_OptimizerBatchDesignPoints.R:1:1',
'test_OptimizerBatchFocusSearch.R:1:1', 'test_OptimizerBatchGenSA.R:1:1',
'test_OptimizerBatchGridSearch.R:1:1', 'test_OptimizerBatchNLoptr.R:1:1',
'test_OptimizerBatchRandomSearch.R:1:1', 'test_TerminatorClockTime.R:1:1',
'test_TerminatorCombo.R:1:1', 'test_TerminatorEvals.R:1:1',
'test_TerminatorNone.R:1:1', 'test_TerminatorPerfReached.R:1:1',
'test_TerminatorRunTime.R:2:5', 'test_TerminatorStagnation.R:1:1',
'test_TerminatorStagnationBatch.R:1:1',
'test_TerminatorStagnationBatch.R:15:1', 'test_mlr_callbacks.R:58:3'
• TRUE is TRUE (1): 'test_mlr_callbacks.R:19:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_OptimizerBatchIrace.R:23:3'): OptimizerBatchIrace minimize works ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:23:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
── Error ('test_OptimizerBatchIrace.R:63:3'): OptimizerBatchIrace maximize works ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:63:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
── Error ('test_OptimizerBatchIrace.R:129:3'): OptimizerBatchIrace works with passed constants set ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:129:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
── Error ('test_OptimizerBatchIrace.R:154:3'): OptimizerBatchIrace works without passed constants set ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:154:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
[ FAIL 4 | WARN 0 | SKIP 53 | PASS 1160 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.8.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [269s/277s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ test_check("bbotk")
+ }
Loading required package: bbotk
Loading required package: paradox
[ FAIL 4 | WARN 0 | SKIP 53 | PASS 1160 ]
══ Skipped tests (53) ══════════════════════════════════════════════════════════
• On CRAN (52): 'test_ArchiveAsync.R:2:3', 'test_ArchiveAsync.R:61:3',
'test_ArchiveAsyncFrozen.R:2:3', 'test_ArchiveBatch.R:1:1',
'test_CallbackAsync.R:4:3', 'test_CallbackAsync.R:31:3',
'test_CallbackAsync.R:59:3', 'test_CallbackAsync.R:88:3',
'test_CallbackAsync.R:118:3', 'test_CallbackAsync.R:154:3',
'test_CallbackAsync.R:183:3', 'test_CallbackAsync.R:210:3',
'test_CallbackAsync.R:239:3', 'test_CallbackAsync.R:269:3',
'test_CallbackAsync.R:297:3', 'test_Objective.R:1:1',
'test_OptimInstanceAsyncSingleCrit.R:2:3',
'test_OptimInstanceAsyncSingleCrit.R:26:3',
'test_OptimInstanceAsyncSingleCrit.R:45:3',
'test_OptimInstanceAsyncSingleCrit.R:65:3',
'test_OptimInstanceAsyncSingleCrit.R:82:3',
'test_OptimInstanceAsyncSingleCrit.R:109:3',
'test_OptimInstanceBatchMultiCrit.R:1:1',
'test_OptimInstanceBatchSingleCrit.R:1:1',
'test_OptimizerAsynDesignPoints.R:2:3', 'test_OptimizerAsynGridSearch.R:2:3',
'test_OptimizerAsync.R:2:3', 'test_OptimizerAsync.R:26:3',
'test_OptimizerAsync.R:50:3', 'test_OptimizerAsync.R:73:3',
'test_OptimizerAsync.R:95:3', 'test_OptimizerAsync.R:124:3',
'test_OptimizerAsync.R:155:3', 'test_OptimizerAsync.R:178:3',
'test_OptimizerAsyncRandomSearch.R:2:3', 'test_OptimizerBatchCmaes.R:1:1',
'test_OptimizerBatchDesignPoints.R:1:1',
'test_OptimizerBatchFocusSearch.R:1:1', 'test_OptimizerBatchGenSA.R:1:1',
'test_OptimizerBatchGridSearch.R:1:1', 'test_OptimizerBatchNLoptr.R:1:1',
'test_OptimizerBatchRandomSearch.R:1:1', 'test_TerminatorClockTime.R:1:1',
'test_TerminatorCombo.R:1:1', 'test_TerminatorEvals.R:1:1',
'test_TerminatorNone.R:1:1', 'test_TerminatorPerfReached.R:1:1',
'test_TerminatorRunTime.R:2:5', 'test_TerminatorStagnation.R:1:1',
'test_TerminatorStagnationBatch.R:1:1',
'test_TerminatorStagnationBatch.R:15:1', 'test_mlr_callbacks.R:58:3'
• TRUE is TRUE (1): 'test_mlr_callbacks.R:19:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_OptimizerBatchIrace.R:23:3'): OptimizerBatchIrace minimize works ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:23:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
── Error ('test_OptimizerBatchIrace.R:63:3'): OptimizerBatchIrace maximize works ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:63:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
── Error ('test_OptimizerBatchIrace.R:129:3'): OptimizerBatchIrace works with passed constants set ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:129:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
── Error ('test_OptimizerBatchIrace.R:154:3'): OptimizerBatchIrace works without passed constants set ──
Error in ``[.data.table`(log, , `:=`("step", rleid("instance")), by = "iteration")`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(optimizer$optimize(instance)) at test_OptimizerBatchIrace.R:154:3
2. │ └─base::withVisible(...elt(i))
3. └─optimizer$optimize(instance)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
12. ├─log[, `:=`("step", rleid("instance")), by = "iteration"]
13. └─data.table:::`[.data.table`(...)
[ FAIL 4 | WARN 0 | SKIP 53 | PASS 1160 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Current CRAN status: OK: 13
Current CRAN status: ERROR: 4, NOTE: 1, OK: 8
Version: 1.3.0
Check: examples
Result: ERROR
Running examples in ‘mlr3-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: BenchmarkResult
> ### Title: Container for Benchmarking Results
> ### Aliases: BenchmarkResult
>
> ### ** Examples
>
> set.seed(123)
> learners = list(
+ lrn("classif.featureless", predict_type = "prob"),
+ lrn("classif.rpart", predict_type = "prob")
+ )
>
> design = benchmark_grid(
+ tasks = list(tsk("sonar"), tsk("penguins")),
+ learners = learners,
+ resamplings = rsmp("cv", folds = 3)
+ )
> print(design)
task learner resampling
<char> <char> <char>
1: sonar classif.featureless cv
2: sonar classif.rpart cv
3: penguins classif.featureless cv
4: penguins classif.rpart cv
>
> bmr = benchmark(design)
INFO [04:34:53.818] [mlr3] Running benchmark with 12 resampling iterations
INFO [04:34:54.018] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3)
INFO [04:34:54.088] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3)
INFO [04:34:54.167] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3)
INFO [04:34:54.198] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3)
INFO [04:34:54.261] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3)
INFO [04:34:54.309] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3)
INFO [04:34:54.360] [mlr3] Applying learner 'classif.featureless' on task 'penguins' (iter 1/3)
INFO [04:34:54.464] [mlr3] Applying learner 'classif.featureless' on task 'penguins' (iter 2/3)
INFO [04:34:54.491] [mlr3] Applying learner 'classif.featureless' on task 'penguins' (iter 3/3)
INFO [04:34:54.519] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 1/3)
INFO [04:34:54.555] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 2/3)
INFO [04:34:54.590] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 3/3)
INFO [04:34:54.633] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: benchmark ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [211s/227s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ test_check("mlr3")
+ }
Saving _problems/test_CallbackResample-20.R
Saving _problems/test_CallbackResample-39.R
Saving _problems/test_CallbackResample-58.R
Saving _problems/test_CallbackResample-77.R
Saving _problems/test_CallbackResample-94.R
Saving _problems/test_CallbackResample-127.R
Saving _problems/test_CallbackResample-162.R
Saving _problems/test_CallbackResample-184.R
Saving _problems/test_CallbackResample-225.R
Saving _problems/test_CallbackResample-244.R
Saving _problems/test_Learner-197.R
Saving _problems/test_Learner-479.R
Saving _problems/test_Learner-562.R
<Mlr3TestError:
x a
> Class: Mlr3TestError
>
<Mlr3ErrorLearnerNoModel:
x No model stored
> Class: Mlr3ErrorLearnerNoModel
>
Saving _problems/test_Learner-1021.R
Saving _problems/test_Measure-21.R
Saving _problems/test_Measure-66.R
Saving _problems/test_Measure-90.R
Saving _problems/test_Measure-106.R
Saving _problems/test_Measure-122.R
Saving _problems/test_Measure-199.R
Saving _problems/test_Measure-285.R
Saving _problems/test_Measure-306.R
Saving _problems/test_MeasureInternalValidScore-5.R
Saving _problems/test_MeasureRegrRSQ-112.R
Saving _problems/test_MeasureRegrRSQ-183.R
Saving _problems/test_PredictionClassif-119.R
Saving _problems/test_PredictionRegr-22.R
Saving _problems/test_PredictionRegr-44.R
Saving _problems/test_Task-874.R
Saving _problems/test_Task-1031.R
Saving _problems/test_autotest-60.R
Saving _problems/test_autotest-162.R
Saving _problems/test_benchmark-6.R
Saving _problems/test_encapsulate-49.R
Saving _problems/test_encapsulate-87.R
Saving _problems/test_errorhandling-63.R
Saving _problems/test_errorhandling-80.R
Saving _problems/test_fallback-48.R
Saving _problems/test_fallback-65.R
Saving _problems/test_hotstart-134.R
Saving _problems/test_hotstart-158.R
Saving _problems/test_hotstart-187.R
Saving _problems/test_hotstart-222.R
Saving _problems/test_hotstart-246.R
Saving _problems/test_install_pkgs-25.R
Saving _problems/test_lgr-20.R
Saving _problems/test_mlr_callbacks-9.R
Saving _problems/test_mlr_callbacks-30.R
Saving _problems/test_mlr_learners_classif_debug-28.R
Saving _problems/test_mlr_learners_classif_featureless-4.R
Saving _problems/test_mlr_learners_classif_featureless-43.R
Saving _problems/test_mlr_learners_classif_rpart-4.R
Saving _problems/test_mlr_learners_regr_featureless-4.R
Saving _problems/test_mlr_learners_regr_featureless-11.R
Saving _problems/test_mlr_learners_regr_rpart-4.R
Saving _problems/test_mlr_measures-31.R
Saving _problems/test_mlr_measures_selected_features-6.R
Saving _problems/test_mlr_measures_similarity-3.R
Saving _problems/test_mlr_reflections-60.R
Saving _problems/test_mlr_reflections-76.R
Saving _problems/test_mlr_reflections-105.R
Saving _problems/test_mlr_resampling_holdout-39.R
Saving _problems/test_parallel_future-12.R
Saving _problems/test_parallel_future-25.R
Saving _problems/test_parallel_future-42.R
Saving _problems/test_parallel_future-69.R
Saving _problems/test_parallel_future-82.R
Saving _problems/test_parallel_mirai-7.R
Saving _problems/test_parallel_mirai-18.R
Saving _problems/test_parallel_mirai-30.R
Saving _problems/test_parallel_mirai-99.R
Saving _problems/test_resample-4.R
Saving _problems/test_resultdata-9.R
Saving _problems/test_resultdata-58.R
Saving _problems/test_resultdata-93.R
Saving _problems/test_resultdata-131.R
Saving _problems/test_resultdata-190.R
[ FAIL 79 | WARN 0 | SKIP 12 | PASS 8474 ]
══ Skipped tests (12) ══════════════════════════════════════════════════════════
• Not on GitHub Actions (1): 'test_backward_compatibility.R:1:1'
• On CRAN (9): 'test_Learner.R:641:3', 'test_Learner.R:847:3',
'test_Learner.R:870:3', 'test_Learner.R:893:3', 'test_Learner.R:916:3',
'test_Measure.R:129:3', 'test_parallel_future.R:91:3',
'test_parallel_mirai.R:48:3', 'test_parallel_mirai.R:66:3'
• empty test (1): 'test_Task.R:911:1'
• {distr6} is not installed (1): 'test_PredictionRegr.R:54:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_CallbackResample.R:20:3'): on_resample_begin works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:20:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:39:3'): on_resample_before_train works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:39:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:58:3'): on_resample_before_predict works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:58:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:77:3'): on_resample_end works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:77:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:94:3'): writing to learner$state works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:94:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:127:3'): writing to data_extra works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:127:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:162:3'): data_extra is a list column ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:162:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:184:3'): data_extra is null ─────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:184:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:225:3'): learner cloning in workhorse is passed to context ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:225:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:244:3'): returning data_extra sometimes works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, callbacks = callback) at test_CallbackResample.R:244:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Learner.R:197:3'): predict train + test set ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, hout) at test_Learner.R:197:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Failure ('test_Learner.R:479:3'): internal_valid_task is created correctly ──
Expected `resample(task2, learner2, resampling)` not to throw any errors.
Actually got a <simpleError> with message:
attempt access index 9/9 in VECTOR_ELT
── Error ('test_Learner.R:562:3'): learner state contains internal valid task information ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Learner.R:562:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Learner.R:1021:3'): oob_error is available without storing models via $.extract_oob_error() ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout"), store_models = FALSE) at test_Learner.R:1021:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:21:5'): average with micro/macro ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_Measure.R:19:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, rs) at test_Measure.R:21:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:66:3'): check_prerequisites / task_properties ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Measure.R:66:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:90:3'): check_prerequisites / predict_type ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Measure.R:90:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:106:3'): check_prerequisites / predict_sets ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Measure.R:106:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:122:3'): time_train works with different predict type (#832) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(...) at test_Measure.R:122:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:199:3'): measure weights ─────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, resampling) at test_Measure.R:199:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:285:3'): primary iters are respected ─────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_Measure.R:285:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:306:3'): no predict_sets required (#1094) ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(...) at test_Measure.R:306:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_MeasureInternalValidScore.R:5:3'): internal valid score ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_MeasureInternalValidScore.R:5:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_MeasureRegrRSQ.R:112:3'): MeasureRegrRSQ works with weights during resampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_MeasureRegrRSQ.R:112:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_MeasureRegrRSQ.R:183:3'): MeasureRegrRSQ use_weights works ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task_plain, learner, resampling) at test_MeasureRegrRSQ.R:183:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_PredictionClassif.R:119:3'): c ─────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_PredictionClassif.R:119:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_PredictionRegr.R:22:3'): c ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_PredictionRegr.R:22:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_PredictionRegr.R:44:3'): c drops se (#250) ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_PredictionRegr.R:44:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Task.R:874:3'): $characteristics works ─────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design) at test_Task.R:874:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Task.R:1031:3'): weights_measure + stratum works during resampling (#1405) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(...) at test_Task.R:1031:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, lrn("classif.featureless"), rsmp("cv", folds = 3))
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_autotest.R:60:3'): autotest configure_learner works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, 10, exclude = exclude, configure_learner = cfg_lrn) at test_autotest.R:60:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_autotest.R:162:7'): autotest on encapsulation ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_autotest.R:160:5
2. │ └─base::force(expr)
3. └─global run_experiment(task, learner1) at test_autotest.R:162:7
4. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_benchmark.R:6:1'): (code run outside of `test_that()`) ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design) at test_benchmark.R:6:1
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_encapsulate.R:49:3'): evaluate / resample ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_encapsulate.R:49:3
2. │ └─base::withCallingHandlers(...)
3. ├─base::suppressWarnings(...)
4. │ └─base::withCallingHandlers(...)
5. └─mlr3::resample(task, disable_encapsulation(learner), resampling)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_encapsulate.R:87:3'): encapsulate methods produce the same results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_encapsulate.R:87:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_errorhandling.R:63:3'): encapsulation / resample ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_errorhandling.R:63:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_errorhandling.R:80:3'): encapsulation / benchmark ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(benchmark_grid(task, learner, rsmp("cv", folds = 3))) at test_errorhandling.R:80:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_fallback.R:48:3'): fail during resample ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, rsmp("cv", folds = 3)) at test_fallback.R:48:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_fallback.R:65:3'): incomplete predictions ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, rsmp("cv", folds = 3)) at test_fallback.R:65:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:134:3'): learners are hotstarted when resample is used ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner_1, resampling, store_models = TRUE) at test_hotstart.R:134:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:158:3'): learners are hotstarted when benchmark is called ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, store_models = TRUE) at test_hotstart.R:158:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:187:3'): learners are trained and hotstarted when benchmark is called ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, store_models = TRUE) at test_hotstart.R:187:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:222:3'): learners are cloned when hotstarting is applied ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, store_models = TRUE, allow_hotstart = TRUE) at test_hotstart.R:222:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:246:3'): hotstarting works when col role is set in task ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner_1, resampling, store_models = TRUE) at test_hotstart.R:246:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_install_pkgs.R:25:3'): extract_pkgs works ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("mtcars"), lrn("regr.featureless"), rsmp("holdout")) at test_install_pkgs.R:25:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_lgr.R:20:3'): log to text file ─────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressWarnings(resample(task, learner, resampling)) at test_lgr.R:20:3
2. │ └─base::withCallingHandlers(...)
3. └─mlr3::resample(task, learner, resampling)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_lgr.R:38:3'): logger works ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::capture_output(...) at test_lgr.R:38:3
2. │ └─testthat::capture_output_lines(code, print, width = width)
3. │ └─testthat:::eval_with_output(code, print = print, width = width)
4. │ ├─withr::with_output_sink(path, withVisible(code))
5. │ │ └─base::force(code)
6. │ └─base::withVisible(code)
7. └─mlr3::resample(...)
8. └─ResultData$new(data, data_extra, store_backends = store_backends)
9. └─mlr3 (local) initialize(...)
10. └─mlr3:::.__ResultData__initialize(...)
11. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
12. └─data.table:::`[.data.table`(...)
── Error ('test_lgr.R:70:5'): thresholds are restored on workers ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::capture_output(...) at test_lgr.R:69:3
2. │ └─testthat::capture_output_lines(code, print, width = width)
3. │ └─testthat:::eval_with_output(code, print = print, width = width)
4. │ ├─withr::with_output_sink(path, withVisible(code))
5. │ │ └─base::force(code)
6. │ └─base::withVisible(code)
7. ├─global with_future(...)
8. │ └─base::force(expr)
9. └─mlr3::resample(...) at test_lgr.R:70:5
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:9:3'): model extractor works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling = resampling, callbacks = callback) at test_mlr_callbacks.R:9:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:30:3'): holdout task works ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling = resampling, callbacks = callback) at test_mlr_callbacks.R:30:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_debug.R:28:3'): updating model works / resample ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, rsmp("holdout"), store_models = TRUE) at test_mlr_learners_classif_debug.R:28:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_featureless.R:4:3'): autotest ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "sanity") at test_mlr_learners_classif_featureless.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_featureless.R:43:3'): classif.featureless works on featureless task ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_mlr_learners_classif_featureless.R:43:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_rpart.R:4:3'): autotest ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_mlr_learners_classif_rpart.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_regr_featureless.R:4:3'): autotest ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "sanity") at test_mlr_learners_regr_featureless.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_regr_featureless.R:11:3'): regr.featureless works on featureless task ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_mlr_learners_regr_featureless.R:11:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_regr_rpart.R:4:3'): autotest ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_mlr_learners_regr_rpart.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_measures.R:31:3'): custom aggregation ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_mlr_measures.R:31:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_measures_selected_features.R:6:3'): selected_features ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("holdout"), store_models = TRUE) at test_mlr_measures_selected_features.R:6:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_measures_similarity.R:3:1'): (code run outside of `test_that()`) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_mlr_measures_similarity.R:3:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_reflections.R:60:3'): resampling works ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_mlr_reflections.R:60:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_reflections.R:76:3'): benchmark works ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid) at test_mlr_reflections.R:76:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_reflections.R:105:5'): external packages can set column roles ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_mlr_reflections.R:104:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, lrn("classif.rpart"), rsmp("cv", folds = 3)) at test_mlr_reflections.R:105:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_resampling_holdout.R:39:3'): prediction does not drop dimension (#551) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design) at test_mlr_resampling_holdout.R:39:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:12:7'): parallel resample ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_parallel_future.R:7:3
2. │ └─base::force(expr)
3. ├─progressr::with_progress(...) at test_parallel_future.R:11:5
4. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_parallel_future.R:12:7
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:25:3'): seeds work identical during sequential and parallel execution ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_parallel_future.R:25:3
2. │ └─base::force(expr)
3. ├─global with_future(future::sequential, resample(task, learner, resampling))
4. │ └─base::force(expr)
5. └─mlr3::resample(task, learner, resampling)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:42:7'): parallel benchmark ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_parallel_future.R:40:3
2. │ └─base::force(expr)
3. ├─progressr::with_progress(...) at test_parallel_future.R:41:5
4. └─mlr3::benchmark(benchmark_grid(task, learner, rsmp("cv", folds = 3))) at test_parallel_future.R:42:7
5. └─ResultData$new(grid, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:69:7'): real parallel resample ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_parallel_future.R:64:3
2. │ └─base::force(expr)
3. ├─progressr::with_progress(...) at test_parallel_future.R:68:5
4. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_parallel_future.R:69:7
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:82:3'): parallel seed ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(123, resample(task, learner, rsmp("cv", folds = 3))) at test_parallel_future.R:82:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, rsmp("cv", folds = 3))
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:7:5'): parallel resample ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:4:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_parallel_mirai.R:7:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:18:5'): parallel benchmark ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:17:3
2. │ └─base::force(expr)
3. └─mlr3::benchmark(benchmark_grid(task, learner, rsmp("cv", folds = 3))) at test_parallel_mirai.R:18:5
4. └─ResultData$new(grid, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:30:5'): mirai resample is reproducible ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:26:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, resampling, store_models = TRUE) at test_parallel_mirai.R:30:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:99:5'): mirai compute profile can be changed ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:94:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, resampling, store_models = TRUE) at test_parallel_mirai.R:99:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_resample.R:4:1'): (code run outside of `test_that()`) ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_resample.R:4:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:9:3'): results are ordered ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_resultdata.R:9:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:58:3'): mlr3tuning use case ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(...) at test_resultdata.R:58:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:93:3'): predict set selection ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_resultdata.R:93:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:131:3'): data_extra works ─────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::as_result_data(...) at test_resultdata.R:131:3
2. └─ResultData$new(...)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:190:3'): combine with data_extra works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::as_result_data(...) at test_resultdata.R:190:3
2. └─ResultData$new(...)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
[ FAIL 79 | WARN 0 | SKIP 12 | PASS 8474 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.3.0
Check: examples
Result: ERROR
Running examples in ‘mlr3-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: BenchmarkResult
> ### Title: Container for Benchmarking Results
> ### Aliases: BenchmarkResult
>
> ### ** Examples
>
> set.seed(123)
> learners = list(
+ lrn("classif.featureless", predict_type = "prob"),
+ lrn("classif.rpart", predict_type = "prob")
+ )
>
> design = benchmark_grid(
+ tasks = list(tsk("sonar"), tsk("penguins")),
+ learners = learners,
+ resamplings = rsmp("cv", folds = 3)
+ )
> print(design)
task learner resampling
<char> <char> <char>
1: sonar classif.featureless cv
2: sonar classif.rpart cv
3: penguins classif.featureless cv
4: penguins classif.rpart cv
>
> bmr = benchmark(design)
INFO [17:18:41.943] [mlr3] Running benchmark with 12 resampling iterations
INFO [17:18:42.067] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3)
INFO [17:18:42.123] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3)
INFO [17:18:42.159] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3)
INFO [17:18:42.192] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3)
INFO [17:18:42.239] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3)
INFO [17:18:42.278] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3)
INFO [17:18:42.320] [mlr3] Applying learner 'classif.featureless' on task 'penguins' (iter 1/3)
INFO [17:18:42.400] [mlr3] Applying learner 'classif.featureless' on task 'penguins' (iter 2/3)
INFO [17:18:42.484] [mlr3] Applying learner 'classif.featureless' on task 'penguins' (iter 3/3)
INFO [17:18:42.560] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 1/3)
INFO [17:18:42.586] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 2/3)
INFO [17:18:42.612] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 3/3)
INFO [17:18:42.645] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: benchmark ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [130s/179s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ test_check("mlr3")
+ }
Saving _problems/test_CallbackResample-20.R
Saving _problems/test_CallbackResample-39.R
Saving _problems/test_CallbackResample-58.R
Saving _problems/test_CallbackResample-77.R
Saving _problems/test_CallbackResample-94.R
Saving _problems/test_CallbackResample-127.R
Saving _problems/test_CallbackResample-162.R
Saving _problems/test_CallbackResample-184.R
Saving _problems/test_CallbackResample-225.R
Saving _problems/test_CallbackResample-244.R
Saving _problems/test_Learner-197.R
Saving _problems/test_Learner-479.R
Saving _problems/test_Learner-562.R
<Mlr3TestError:
x a
> Class: Mlr3TestError
>
<Mlr3ErrorLearnerNoModel:
x No model stored
> Class: Mlr3ErrorLearnerNoModel
>
Saving _problems/test_Learner-1021.R
Saving _problems/test_Measure-21.R
Saving _problems/test_Measure-66.R
Saving _problems/test_Measure-90.R
Saving _problems/test_Measure-106.R
Saving _problems/test_Measure-122.R
Saving _problems/test_Measure-199.R
Saving _problems/test_Measure-285.R
Saving _problems/test_Measure-306.R
Saving _problems/test_MeasureInternalValidScore-5.R
Saving _problems/test_MeasureRegrRSQ-112.R
Saving _problems/test_MeasureRegrRSQ-183.R
Saving _problems/test_PredictionClassif-119.R
Saving _problems/test_PredictionRegr-22.R
Saving _problems/test_PredictionRegr-44.R
Saving _problems/test_Task-874.R
Saving _problems/test_Task-1031.R
Saving _problems/test_autotest-60.R
Saving _problems/test_autotest-162.R
Saving _problems/test_benchmark-6.R
Saving _problems/test_encapsulate-49.R
Saving _problems/test_encapsulate-87.R
Saving _problems/test_errorhandling-63.R
Saving _problems/test_errorhandling-80.R
Saving _problems/test_fallback-48.R
Saving _problems/test_fallback-65.R
Saving _problems/test_hotstart-134.R
Saving _problems/test_hotstart-158.R
Saving _problems/test_hotstart-187.R
Saving _problems/test_hotstart-222.R
Saving _problems/test_hotstart-246.R
Saving _problems/test_install_pkgs-25.R
Saving _problems/test_lgr-20.R
Saving _problems/test_mlr_callbacks-9.R
Saving _problems/test_mlr_callbacks-30.R
Saving _problems/test_mlr_learners_classif_debug-28.R
Saving _problems/test_mlr_learners_classif_featureless-4.R
Saving _problems/test_mlr_learners_classif_featureless-43.R
Saving _problems/test_mlr_learners_classif_rpart-4.R
Saving _problems/test_mlr_learners_regr_featureless-4.R
Saving _problems/test_mlr_learners_regr_featureless-11.R
Saving _problems/test_mlr_learners_regr_rpart-4.R
Saving _problems/test_mlr_measures-31.R
Saving _problems/test_mlr_measures_selected_features-6.R
Saving _problems/test_mlr_measures_similarity-3.R
Saving _problems/test_mlr_reflections-60.R
Saving _problems/test_mlr_reflections-76.R
Saving _problems/test_mlr_reflections-105.R
Saving _problems/test_mlr_resampling_holdout-39.R
Saving _problems/test_parallel_future-12.R
Saving _problems/test_parallel_future-25.R
Saving _problems/test_parallel_future-42.R
Saving _problems/test_parallel_future-69.R
Saving _problems/test_parallel_future-82.R
Saving _problems/test_parallel_mirai-7.R
Saving _problems/test_parallel_mirai-18.R
Saving _problems/test_parallel_mirai-30.R
Saving _problems/test_parallel_mirai-99.R
Saving _problems/test_resample-4.R
Saving _problems/test_resultdata-9.R
Saving _problems/test_resultdata-58.R
Saving _problems/test_resultdata-93.R
Saving _problems/test_resultdata-131.R
Saving _problems/test_resultdata-190.R
[ FAIL 79 | WARN 0 | SKIP 12 | PASS 8474 ]
══ Skipped tests (12) ══════════════════════════════════════════════════════════
• Not on GitHub Actions (1): 'test_backward_compatibility.R:1:1'
• On CRAN (9): 'test_Learner.R:641:3', 'test_Learner.R:847:3',
'test_Learner.R:870:3', 'test_Learner.R:893:3', 'test_Learner.R:916:3',
'test_Measure.R:129:3', 'test_parallel_future.R:91:3',
'test_parallel_mirai.R:48:3', 'test_parallel_mirai.R:66:3'
• empty test (1): 'test_Task.R:911:1'
• {distr6} is not installed (1): 'test_PredictionRegr.R:54:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_CallbackResample.R:20:3'): on_resample_begin works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:20:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:39:3'): on_resample_before_train works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:39:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:58:3'): on_resample_before_predict works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:58:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:77:3'): on_resample_end works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:77:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:94:3'): writing to learner$state works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:94:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:127:3'): writing to data_extra works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:127:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:162:3'): data_extra is a list column ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:162:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:184:3'): data_extra is null ─────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:184:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:225:3'): learner cloning in workhorse is passed to context ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:225:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:244:3'): returning data_extra sometimes works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, callbacks = callback) at test_CallbackResample.R:244:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Learner.R:197:3'): predict train + test set ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, hout) at test_Learner.R:197:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Failure ('test_Learner.R:479:3'): internal_valid_task is created correctly ──
Expected `resample(task2, learner2, resampling)` not to throw any errors.
Actually got a <simpleError> with message:
attempt access index 9/9 in VECTOR_ELT
── Error ('test_Learner.R:562:3'): learner state contains internal valid task information ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Learner.R:562:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Learner.R:1021:3'): oob_error is available without storing models via $.extract_oob_error() ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout"), store_models = FALSE) at test_Learner.R:1021:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:21:5'): average with micro/macro ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_Measure.R:19:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, rs) at test_Measure.R:21:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:66:3'): check_prerequisites / task_properties ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Measure.R:66:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:90:3'): check_prerequisites / predict_type ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Measure.R:90:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:106:3'): check_prerequisites / predict_sets ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Measure.R:106:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:122:3'): time_train works with different predict type (#832) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(...) at test_Measure.R:122:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:199:3'): measure weights ─────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, resampling) at test_Measure.R:199:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:285:3'): primary iters are respected ─────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_Measure.R:285:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:306:3'): no predict_sets required (#1094) ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(...) at test_Measure.R:306:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_MeasureInternalValidScore.R:5:3'): internal valid score ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_MeasureInternalValidScore.R:5:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_MeasureRegrRSQ.R:112:3'): MeasureRegrRSQ works with weights during resampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_MeasureRegrRSQ.R:112:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_MeasureRegrRSQ.R:183:3'): MeasureRegrRSQ use_weights works ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task_plain, learner, resampling) at test_MeasureRegrRSQ.R:183:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_PredictionClassif.R:119:3'): c ─────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_PredictionClassif.R:119:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_PredictionRegr.R:22:3'): c ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_PredictionRegr.R:22:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_PredictionRegr.R:44:3'): c drops se (#250) ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_PredictionRegr.R:44:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Task.R:874:3'): $characteristics works ─────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design) at test_Task.R:874:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Task.R:1031:3'): weights_measure + stratum works during resampling (#1405) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(...) at test_Task.R:1031:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, lrn("classif.featureless"), rsmp("cv", folds = 3))
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_autotest.R:60:3'): autotest configure_learner works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, 10, exclude = exclude, configure_learner = cfg_lrn) at test_autotest.R:60:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_autotest.R:162:7'): autotest on encapsulation ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_autotest.R:160:5
2. │ └─base::force(expr)
3. └─global run_experiment(task, learner1) at test_autotest.R:162:7
4. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_benchmark.R:6:1'): (code run outside of `test_that()`) ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design) at test_benchmark.R:6:1
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_encapsulate.R:49:3'): evaluate / resample ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_encapsulate.R:49:3
2. │ └─base::withCallingHandlers(...)
3. ├─base::suppressWarnings(...)
4. │ └─base::withCallingHandlers(...)
5. └─mlr3::resample(task, disable_encapsulation(learner), resampling)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_encapsulate.R:87:3'): encapsulate methods produce the same results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_encapsulate.R:87:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_errorhandling.R:63:3'): encapsulation / resample ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_errorhandling.R:63:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_errorhandling.R:80:3'): encapsulation / benchmark ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(benchmark_grid(task, learner, rsmp("cv", folds = 3))) at test_errorhandling.R:80:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_fallback.R:48:3'): fail during resample ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, rsmp("cv", folds = 3)) at test_fallback.R:48:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_fallback.R:65:3'): incomplete predictions ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, rsmp("cv", folds = 3)) at test_fallback.R:65:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:134:3'): learners are hotstarted when resample is used ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner_1, resampling, store_models = TRUE) at test_hotstart.R:134:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:158:3'): learners are hotstarted when benchmark is called ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, store_models = TRUE) at test_hotstart.R:158:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:187:3'): learners are trained and hotstarted when benchmark is called ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, store_models = TRUE) at test_hotstart.R:187:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:222:3'): learners are cloned when hotstarting is applied ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, store_models = TRUE, allow_hotstart = TRUE) at test_hotstart.R:222:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:246:3'): hotstarting works when col role is set in task ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner_1, resampling, store_models = TRUE) at test_hotstart.R:246:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_install_pkgs.R:25:3'): extract_pkgs works ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("mtcars"), lrn("regr.featureless"), rsmp("holdout")) at test_install_pkgs.R:25:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_lgr.R:20:3'): log to text file ─────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressWarnings(resample(task, learner, resampling)) at test_lgr.R:20:3
2. │ └─base::withCallingHandlers(...)
3. └─mlr3::resample(task, learner, resampling)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_lgr.R:38:3'): logger works ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::capture_output(...) at test_lgr.R:38:3
2. │ └─testthat::capture_output_lines(code, print, width = width)
3. │ └─testthat:::eval_with_output(code, print = print, width = width)
4. │ ├─withr::with_output_sink(path, withVisible(code))
5. │ │ └─base::force(code)
6. │ └─base::withVisible(code)
7. └─mlr3::resample(...)
8. └─ResultData$new(data, data_extra, store_backends = store_backends)
9. └─mlr3 (local) initialize(...)
10. └─mlr3:::.__ResultData__initialize(...)
11. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
12. └─data.table:::`[.data.table`(...)
── Error ('test_lgr.R:70:5'): thresholds are restored on workers ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::capture_output(...) at test_lgr.R:69:3
2. │ └─testthat::capture_output_lines(code, print, width = width)
3. │ └─testthat:::eval_with_output(code, print = print, width = width)
4. │ ├─withr::with_output_sink(path, withVisible(code))
5. │ │ └─base::force(code)
6. │ └─base::withVisible(code)
7. ├─global with_future(...)
8. │ └─base::force(expr)
9. └─mlr3::resample(...) at test_lgr.R:70:5
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:9:3'): model extractor works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling = resampling, callbacks = callback) at test_mlr_callbacks.R:9:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:30:3'): holdout task works ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling = resampling, callbacks = callback) at test_mlr_callbacks.R:30:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_debug.R:28:3'): updating model works / resample ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, rsmp("holdout"), store_models = TRUE) at test_mlr_learners_classif_debug.R:28:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_featureless.R:4:3'): autotest ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "sanity") at test_mlr_learners_classif_featureless.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_featureless.R:43:3'): classif.featureless works on featureless task ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_mlr_learners_classif_featureless.R:43:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_rpart.R:4:3'): autotest ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_mlr_learners_classif_rpart.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_regr_featureless.R:4:3'): autotest ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "sanity") at test_mlr_learners_regr_featureless.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_regr_featureless.R:11:3'): regr.featureless works on featureless task ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_mlr_learners_regr_featureless.R:11:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_regr_rpart.R:4:3'): autotest ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_mlr_learners_regr_rpart.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_measures.R:31:3'): custom aggregation ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_mlr_measures.R:31:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_measures_selected_features.R:6:3'): selected_features ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("holdout"), store_models = TRUE) at test_mlr_measures_selected_features.R:6:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_measures_similarity.R:3:1'): (code run outside of `test_that()`) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_mlr_measures_similarity.R:3:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_reflections.R:60:3'): resampling works ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_mlr_reflections.R:60:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_reflections.R:76:3'): benchmark works ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid) at test_mlr_reflections.R:76:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_reflections.R:105:5'): external packages can set column roles ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_mlr_reflections.R:104:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, lrn("classif.rpart"), rsmp("cv", folds = 3)) at test_mlr_reflections.R:105:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_resampling_holdout.R:39:3'): prediction does not drop dimension (#551) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design) at test_mlr_resampling_holdout.R:39:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:12:7'): parallel resample ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_parallel_future.R:7:3
2. │ └─base::force(expr)
3. ├─progressr::with_progress(...) at test_parallel_future.R:11:5
4. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_parallel_future.R:12:7
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:25:3'): seeds work identical during sequential and parallel execution ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_parallel_future.R:25:3
2. │ └─base::force(expr)
3. ├─global with_future(future::sequential, resample(task, learner, resampling))
4. │ └─base::force(expr)
5. └─mlr3::resample(task, learner, resampling)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:42:7'): parallel benchmark ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_parallel_future.R:40:3
2. │ └─base::force(expr)
3. ├─progressr::with_progress(...) at test_parallel_future.R:41:5
4. └─mlr3::benchmark(benchmark_grid(task, learner, rsmp("cv", folds = 3))) at test_parallel_future.R:42:7
5. └─ResultData$new(grid, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:69:7'): real parallel resample ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_parallel_future.R:64:3
2. │ └─base::force(expr)
3. ├─progressr::with_progress(...) at test_parallel_future.R:68:5
4. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_parallel_future.R:69:7
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:82:3'): parallel seed ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(123, resample(task, learner, rsmp("cv", folds = 3))) at test_parallel_future.R:82:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, rsmp("cv", folds = 3))
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:7:5'): parallel resample ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:4:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_parallel_mirai.R:7:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:18:5'): parallel benchmark ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:17:3
2. │ └─base::force(expr)
3. └─mlr3::benchmark(benchmark_grid(task, learner, rsmp("cv", folds = 3))) at test_parallel_mirai.R:18:5
4. └─ResultData$new(grid, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:30:5'): mirai resample is reproducible ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:26:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, resampling, store_models = TRUE) at test_parallel_mirai.R:30:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:99:5'): mirai compute profile can be changed ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:94:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, resampling, store_models = TRUE) at test_parallel_mirai.R:99:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_resample.R:4:1'): (code run outside of `test_that()`) ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_resample.R:4:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:9:3'): results are ordered ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_resultdata.R:9:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:58:3'): mlr3tuning use case ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(...) at test_resultdata.R:58:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:93:3'): predict set selection ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_resultdata.R:93:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:131:3'): data_extra works ─────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::as_result_data(...) at test_resultdata.R:131:3
2. └─ResultData$new(...)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:190:3'): combine with data_extra works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::as_result_data(...) at test_resultdata.R:190:3
2. └─ResultData$new(...)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
[ FAIL 79 | WARN 0 | SKIP 12 | PASS 8474 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.3.0
Check: examples
Result: ERROR
Running examples in ‘mlr3-Ex.R’ failed
The error most likely occurred in:
> ### Name: BenchmarkResult
> ### Title: Container for Benchmarking Results
> ### Aliases: BenchmarkResult
>
> ### ** Examples
>
> set.seed(123)
> learners = list(
+ lrn("classif.featureless", predict_type = "prob"),
+ lrn("classif.rpart", predict_type = "prob")
+ )
>
> design = benchmark_grid(
+ tasks = list(tsk("sonar"), tsk("penguins")),
+ learners = learners,
+ resamplings = rsmp("cv", folds = 3)
+ )
> print(design)
task learner resampling
<char> <char> <char>
1: sonar classif.featureless cv
2: sonar classif.rpart cv
3: penguins classif.featureless cv
4: penguins classif.rpart cv
>
> bmr = benchmark(design)
INFO [17:49:34.539] [mlr3] Running benchmark with 12 resampling iterations
INFO [17:49:35.144] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3)
INFO [17:49:35.264] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3)
INFO [17:49:35.429] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3)
INFO [17:49:35.579] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3)
INFO [17:49:35.907] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3)
INFO [17:49:36.012] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3)
INFO [17:49:36.165] [mlr3] Applying learner 'classif.featureless' on task 'penguins' (iter 1/3)
INFO [17:49:36.241] [mlr3] Applying learner 'classif.featureless' on task 'penguins' (iter 2/3)
INFO [17:49:36.347] [mlr3] Applying learner 'classif.featureless' on task 'penguins' (iter 3/3)
INFO [17:49:36.401] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 1/3)
INFO [17:49:36.473] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 2/3)
INFO [17:49:36.539] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 3/3)
INFO [17:49:36.783] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: benchmark ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [286s/551s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ test_check("mlr3")
+ }
Saving _problems/test_CallbackResample-20.R
Saving _problems/test_CallbackResample-39.R
Saving _problems/test_CallbackResample-58.R
Saving _problems/test_CallbackResample-77.R
Saving _problems/test_CallbackResample-94.R
Saving _problems/test_CallbackResample-127.R
Saving _problems/test_CallbackResample-162.R
Saving _problems/test_CallbackResample-184.R
Saving _problems/test_CallbackResample-225.R
Saving _problems/test_CallbackResample-244.R
Saving _problems/test_Learner-197.R
Saving _problems/test_Learner-479.R
Saving _problems/test_Learner-562.R
<Mlr3TestError:
x a
> Class: Mlr3TestError
>
<Mlr3ErrorLearnerNoModel:
x No model stored
> Class: Mlr3ErrorLearnerNoModel
>
Saving _problems/test_Learner-1021.R
Saving _problems/test_Measure-21.R
Saving _problems/test_Measure-66.R
Saving _problems/test_Measure-90.R
Saving _problems/test_Measure-106.R
Saving _problems/test_Measure-122.R
Saving _problems/test_Measure-199.R
Saving _problems/test_Measure-285.R
Saving _problems/test_Measure-306.R
Saving _problems/test_MeasureInternalValidScore-5.R
Saving _problems/test_MeasureRegrRSQ-112.R
Saving _problems/test_MeasureRegrRSQ-183.R
Saving _problems/test_PredictionClassif-119.R
Saving _problems/test_PredictionRegr-22.R
Saving _problems/test_PredictionRegr-44.R
Saving _problems/test_Task-874.R
Saving _problems/test_Task-1031.R
Saving _problems/test_autotest-60.R
Saving _problems/test_autotest-162.R
Saving _problems/test_benchmark-6.R
Saving _problems/test_encapsulate-49.R
Saving _problems/test_encapsulate-87.R
Saving _problems/test_errorhandling-63.R
Saving _problems/test_errorhandling-80.R
Saving _problems/test_fallback-48.R
Saving _problems/test_fallback-65.R
Saving _problems/test_hotstart-134.R
Saving _problems/test_hotstart-158.R
Saving _problems/test_hotstart-187.R
Saving _problems/test_hotstart-222.R
Saving _problems/test_hotstart-246.R
Saving _problems/test_install_pkgs-25.R
Saving _problems/test_lgr-20.R
Saving _problems/test_mlr_callbacks-9.R
Saving _problems/test_mlr_callbacks-30.R
Saving _problems/test_mlr_learners_classif_debug-28.R
Saving _problems/test_mlr_learners_classif_featureless-4.R
Saving _problems/test_mlr_learners_classif_featureless-43.R
Saving _problems/test_mlr_learners_classif_rpart-4.R
Saving _problems/test_mlr_learners_regr_featureless-4.R
Saving _problems/test_mlr_learners_regr_featureless-11.R
Saving _problems/test_mlr_learners_regr_rpart-4.R
Saving _problems/test_mlr_measures-31.R
Saving _problems/test_mlr_measures_selected_features-6.R
Saving _problems/test_mlr_measures_similarity-3.R
Saving _problems/test_mlr_reflections-60.R
Saving _problems/test_mlr_reflections-76.R
Saving _problems/test_mlr_reflections-105.R
Saving _problems/test_mlr_resampling_holdout-39.R
Saving _problems/test_parallel_future-12.R
Saving _problems/test_parallel_future-25.R
Saving _problems/test_parallel_future-42.R
Saving _problems/test_parallel_future-69.R
Saving _problems/test_parallel_future-82.R
Saving _problems/test_parallel_mirai-7.R
Saving _problems/test_parallel_mirai-18.R
Saving _problems/test_parallel_mirai-30.R
Saving _problems/test_parallel_mirai-99.R
Saving _problems/test_resample-4.R
Saving _problems/test_resultdata-9.R
Saving _problems/test_resultdata-58.R
Saving _problems/test_resultdata-93.R
Saving _problems/test_resultdata-131.R
Saving _problems/test_resultdata-190.R
[ FAIL 79 | WARN 0 | SKIP 12 | PASS 8474 ]
══ Skipped tests (12) ══════════════════════════════════════════════════════════
• Not on GitHub Actions (1): 'test_backward_compatibility.R:1:1'
• On CRAN (9): 'test_Learner.R:641:3', 'test_Learner.R:847:3',
'test_Learner.R:870:3', 'test_Learner.R:893:3', 'test_Learner.R:916:3',
'test_Measure.R:129:3', 'test_parallel_future.R:91:3',
'test_parallel_mirai.R:48:3', 'test_parallel_mirai.R:66:3'
• empty test (1): 'test_Task.R:911:1'
• {distr6} is not installed (1): 'test_PredictionRegr.R:54:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_CallbackResample.R:20:3'): on_resample_begin works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:20:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:39:3'): on_resample_before_train works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:39:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:58:3'): on_resample_before_predict works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:58:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:77:3'): on_resample_end works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:77:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:94:3'): writing to learner$state works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:94:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:127:3'): writing to data_extra works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:127:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:162:3'): data_extra is a list column ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:162:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:184:3'): data_extra is null ─────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:184:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:225:3'): learner cloning in workhorse is passed to context ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:225:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:244:3'): returning data_extra sometimes works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, callbacks = callback) at test_CallbackResample.R:244:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Learner.R:197:3'): predict train + test set ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, hout) at test_Learner.R:197:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Failure ('test_Learner.R:479:3'): internal_valid_task is created correctly ──
Expected `resample(task2, learner2, resampling)` not to throw any errors.
Actually got a <simpleError> with message:
attempt access index 9/9 in VECTOR_ELT
── Error ('test_Learner.R:562:3'): learner state contains internal valid task information ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Learner.R:562:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Learner.R:1021:3'): oob_error is available without storing models via $.extract_oob_error() ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout"), store_models = FALSE) at test_Learner.R:1021:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:21:5'): average with micro/macro ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_Measure.R:19:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, rs) at test_Measure.R:21:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:66:3'): check_prerequisites / task_properties ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Measure.R:66:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:90:3'): check_prerequisites / predict_type ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Measure.R:90:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:106:3'): check_prerequisites / predict_sets ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Measure.R:106:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:122:3'): time_train works with different predict type (#832) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(...) at test_Measure.R:122:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:199:3'): measure weights ─────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, resampling) at test_Measure.R:199:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:285:3'): primary iters are respected ─────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_Measure.R:285:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:306:3'): no predict_sets required (#1094) ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(...) at test_Measure.R:306:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_MeasureInternalValidScore.R:5:3'): internal valid score ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_MeasureInternalValidScore.R:5:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_MeasureRegrRSQ.R:112:3'): MeasureRegrRSQ works with weights during resampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_MeasureRegrRSQ.R:112:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_MeasureRegrRSQ.R:183:3'): MeasureRegrRSQ use_weights works ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task_plain, learner, resampling) at test_MeasureRegrRSQ.R:183:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_PredictionClassif.R:119:3'): c ─────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_PredictionClassif.R:119:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_PredictionRegr.R:22:3'): c ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_PredictionRegr.R:22:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_PredictionRegr.R:44:3'): c drops se (#250) ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_PredictionRegr.R:44:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Task.R:874:3'): $characteristics works ─────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design) at test_Task.R:874:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Task.R:1031:3'): weights_measure + stratum works during resampling (#1405) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(...) at test_Task.R:1031:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, lrn("classif.featureless"), rsmp("cv", folds = 3))
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_autotest.R:60:3'): autotest configure_learner works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, 10, exclude = exclude, configure_learner = cfg_lrn) at test_autotest.R:60:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_autotest.R:162:7'): autotest on encapsulation ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_autotest.R:160:5
2. │ └─base::force(expr)
3. └─global run_experiment(task, learner1) at test_autotest.R:162:7
4. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_benchmark.R:6:1'): (code run outside of `test_that()`) ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design) at test_benchmark.R:6:1
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_encapsulate.R:49:3'): evaluate / resample ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_encapsulate.R:49:3
2. │ └─base::withCallingHandlers(...)
3. ├─base::suppressWarnings(...)
4. │ └─base::withCallingHandlers(...)
5. └─mlr3::resample(task, disable_encapsulation(learner), resampling)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_encapsulate.R:87:3'): encapsulate methods produce the same results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_encapsulate.R:87:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_errorhandling.R:63:3'): encapsulation / resample ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_errorhandling.R:63:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_errorhandling.R:80:3'): encapsulation / benchmark ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(benchmark_grid(task, learner, rsmp("cv", folds = 3))) at test_errorhandling.R:80:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_fallback.R:48:3'): fail during resample ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, rsmp("cv", folds = 3)) at test_fallback.R:48:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_fallback.R:65:3'): incomplete predictions ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, rsmp("cv", folds = 3)) at test_fallback.R:65:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:134:3'): learners are hotstarted when resample is used ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner_1, resampling, store_models = TRUE) at test_hotstart.R:134:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:158:3'): learners are hotstarted when benchmark is called ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, store_models = TRUE) at test_hotstart.R:158:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:187:3'): learners are trained and hotstarted when benchmark is called ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, store_models = TRUE) at test_hotstart.R:187:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:222:3'): learners are cloned when hotstarting is applied ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, store_models = TRUE, allow_hotstart = TRUE) at test_hotstart.R:222:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:246:3'): hotstarting works when col role is set in task ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner_1, resampling, store_models = TRUE) at test_hotstart.R:246:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_install_pkgs.R:25:3'): extract_pkgs works ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("mtcars"), lrn("regr.featureless"), rsmp("holdout")) at test_install_pkgs.R:25:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_lgr.R:20:3'): log to text file ─────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressWarnings(resample(task, learner, resampling)) at test_lgr.R:20:3
2. │ └─base::withCallingHandlers(...)
3. └─mlr3::resample(task, learner, resampling)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_lgr.R:38:3'): logger works ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::capture_output(...) at test_lgr.R:38:3
2. │ └─testthat::capture_output_lines(code, print, width = width)
3. │ └─testthat:::eval_with_output(code, print = print, width = width)
4. │ ├─withr::with_output_sink(path, withVisible(code))
5. │ │ └─base::force(code)
6. │ └─base::withVisible(code)
7. └─mlr3::resample(...)
8. └─ResultData$new(data, data_extra, store_backends = store_backends)
9. └─mlr3 (local) initialize(...)
10. └─mlr3:::.__ResultData__initialize(...)
11. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
12. └─data.table:::`[.data.table`(...)
── Error ('test_lgr.R:70:5'): thresholds are restored on workers ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::capture_output(...) at test_lgr.R:69:3
2. │ └─testthat::capture_output_lines(code, print, width = width)
3. │ └─testthat:::eval_with_output(code, print = print, width = width)
4. │ ├─withr::with_output_sink(path, withVisible(code))
5. │ │ └─base::force(code)
6. │ └─base::withVisible(code)
7. ├─global with_future(...)
8. │ └─base::force(expr)
9. └─mlr3::resample(...) at test_lgr.R:70:5
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:9:3'): model extractor works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling = resampling, callbacks = callback) at test_mlr_callbacks.R:9:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:30:3'): holdout task works ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling = resampling, callbacks = callback) at test_mlr_callbacks.R:30:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_debug.R:28:3'): updating model works / resample ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, rsmp("holdout"), store_models = TRUE) at test_mlr_learners_classif_debug.R:28:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_featureless.R:4:3'): autotest ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "sanity") at test_mlr_learners_classif_featureless.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_featureless.R:43:3'): classif.featureless works on featureless task ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_mlr_learners_classif_featureless.R:43:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_rpart.R:4:3'): autotest ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_mlr_learners_classif_rpart.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_regr_featureless.R:4:3'): autotest ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "sanity") at test_mlr_learners_regr_featureless.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_regr_featureless.R:11:3'): regr.featureless works on featureless task ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_mlr_learners_regr_featureless.R:11:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_regr_rpart.R:4:3'): autotest ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_mlr_learners_regr_rpart.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_measures.R:31:3'): custom aggregation ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_mlr_measures.R:31:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_measures_selected_features.R:6:3'): selected_features ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("holdout"), store_models = TRUE) at test_mlr_measures_selected_features.R:6:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_measures_similarity.R:3:1'): (code run outside of `test_that()`) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_mlr_measures_similarity.R:3:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_reflections.R:60:3'): resampling works ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_mlr_reflections.R:60:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_reflections.R:76:3'): benchmark works ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid) at test_mlr_reflections.R:76:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_reflections.R:105:5'): external packages can set column roles ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_mlr_reflections.R:104:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, lrn("classif.rpart"), rsmp("cv", folds = 3)) at test_mlr_reflections.R:105:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_resampling_holdout.R:39:3'): prediction does not drop dimension (#551) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design) at test_mlr_resampling_holdout.R:39:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:12:7'): parallel resample ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_parallel_future.R:7:3
2. │ └─base::force(expr)
3. ├─progressr::with_progress(...) at test_parallel_future.R:11:5
4. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_parallel_future.R:12:7
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:25:3'): seeds work identical during sequential and parallel execution ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_parallel_future.R:25:3
2. │ └─base::force(expr)
3. ├─global with_future(future::sequential, resample(task, learner, resampling))
4. │ └─base::force(expr)
5. └─mlr3::resample(task, learner, resampling)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:42:7'): parallel benchmark ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_parallel_future.R:40:3
2. │ └─base::force(expr)
3. ├─progressr::with_progress(...) at test_parallel_future.R:41:5
4. └─mlr3::benchmark(benchmark_grid(task, learner, rsmp("cv", folds = 3))) at test_parallel_future.R:42:7
5. └─ResultData$new(grid, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:69:7'): real parallel resample ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_parallel_future.R:64:3
2. │ └─base::force(expr)
3. ├─progressr::with_progress(...) at test_parallel_future.R:68:5
4. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_parallel_future.R:69:7
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:82:3'): parallel seed ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(123, resample(task, learner, rsmp("cv", folds = 3))) at test_parallel_future.R:82:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, rsmp("cv", folds = 3))
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:7:5'): parallel resample ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:4:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_parallel_mirai.R:7:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:18:5'): parallel benchmark ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:17:3
2. │ └─base::force(expr)
3. └─mlr3::benchmark(benchmark_grid(task, learner, rsmp("cv", folds = 3))) at test_parallel_mirai.R:18:5
4. └─ResultData$new(grid, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:30:5'): mirai resample is reproducible ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:26:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, resampling, store_models = TRUE) at test_parallel_mirai.R:30:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:99:5'): mirai compute profile can be changed ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:94:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, resampling, store_models = TRUE) at test_parallel_mirai.R:99:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_resample.R:4:1'): (code run outside of `test_that()`) ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_resample.R:4:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:9:3'): results are ordered ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_resultdata.R:9:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:58:3'): mlr3tuning use case ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(...) at test_resultdata.R:58:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:93:3'): predict set selection ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_resultdata.R:93:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:131:3'): data_extra works ─────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::as_result_data(...) at test_resultdata.R:131:3
2. └─ResultData$new(...)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:190:3'): combine with data_extra works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::as_result_data(...) at test_resultdata.R:190:3
2. └─ResultData$new(...)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
[ FAIL 79 | WARN 0 | SKIP 12 | PASS 8474 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.3.0
Check: examples
Result: ERROR
Running examples in ‘mlr3-Ex.R’ failed
The error most likely occurred in:
> ### Name: BenchmarkResult
> ### Title: Container for Benchmarking Results
> ### Aliases: BenchmarkResult
>
> ### ** Examples
>
> set.seed(123)
> learners = list(
+ lrn("classif.featureless", predict_type = "prob"),
+ lrn("classif.rpart", predict_type = "prob")
+ )
>
> design = benchmark_grid(
+ tasks = list(tsk("sonar"), tsk("penguins")),
+ learners = learners,
+ resamplings = rsmp("cv", folds = 3)
+ )
> print(design)
task learner resampling
<char> <char> <char>
1: sonar classif.featureless cv
2: sonar classif.rpart cv
3: penguins classif.featureless cv
4: penguins classif.rpart cv
>
> bmr = benchmark(design)
INFO [12:29:24.656] [mlr3] Running benchmark with 12 resampling iterations
INFO [12:29:24.960] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3)
INFO [12:29:25.060] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3)
INFO [12:29:25.122] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3)
INFO [12:29:25.171] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3)
INFO [12:29:25.269] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3)
INFO [12:29:25.416] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3)
INFO [12:29:25.494] [mlr3] Applying learner 'classif.featureless' on task 'penguins' (iter 1/3)
INFO [12:29:25.565] [mlr3] Applying learner 'classif.featureless' on task 'penguins' (iter 2/3)
INFO [12:29:25.605] [mlr3] Applying learner 'classif.featureless' on task 'penguins' (iter 3/3)
INFO [12:29:25.652] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 1/3)
INFO [12:29:25.711] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 2/3)
INFO [12:29:25.769] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 3/3)
INFO [12:29:25.864] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: benchmark ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [247s/375s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("checkmate")
+ library("testthat")
+ library("mlr3")
+ test_check("mlr3")
+ }
Saving _problems/test_CallbackResample-20.R
Saving _problems/test_CallbackResample-39.R
Saving _problems/test_CallbackResample-58.R
Saving _problems/test_CallbackResample-77.R
Saving _problems/test_CallbackResample-94.R
Saving _problems/test_CallbackResample-127.R
Saving _problems/test_CallbackResample-162.R
Saving _problems/test_CallbackResample-184.R
Saving _problems/test_CallbackResample-225.R
Saving _problems/test_CallbackResample-244.R
Saving _problems/test_Learner-197.R
Saving _problems/test_Learner-479.R
Saving _problems/test_Learner-562.R
<Mlr3TestError:
x a
> Class: Mlr3TestError
>
<Mlr3ErrorLearnerNoModel:
x No model stored
> Class: Mlr3ErrorLearnerNoModel
>
Saving _problems/test_Learner-1021.R
Saving _problems/test_Measure-21.R
Saving _problems/test_Measure-66.R
Saving _problems/test_Measure-90.R
Saving _problems/test_Measure-106.R
Saving _problems/test_Measure-122.R
Saving _problems/test_Measure-199.R
Saving _problems/test_Measure-285.R
Saving _problems/test_Measure-306.R
Saving _problems/test_MeasureInternalValidScore-5.R
Saving _problems/test_MeasureRegrRSQ-112.R
Saving _problems/test_MeasureRegrRSQ-183.R
Saving _problems/test_PredictionClassif-119.R
Saving _problems/test_PredictionRegr-22.R
Saving _problems/test_PredictionRegr-44.R
Saving _problems/test_Task-874.R
Saving _problems/test_Task-1031.R
Saving _problems/test_autotest-60.R
Saving _problems/test_autotest-162.R
Saving _problems/test_benchmark-6.R
Saving _problems/test_encapsulate-49.R
Saving _problems/test_encapsulate-87.R
Saving _problems/test_errorhandling-63.R
Saving _problems/test_errorhandling-80.R
Saving _problems/test_fallback-48.R
Saving _problems/test_fallback-65.R
Saving _problems/test_hotstart-134.R
Saving _problems/test_hotstart-158.R
Saving _problems/test_hotstart-187.R
Saving _problems/test_hotstart-222.R
Saving _problems/test_hotstart-246.R
Saving _problems/test_install_pkgs-25.R
Saving _problems/test_lgr-20.R
Saving _problems/test_mlr_callbacks-9.R
Saving _problems/test_mlr_callbacks-30.R
Saving _problems/test_mlr_learners_classif_debug-28.R
Saving _problems/test_mlr_learners_classif_featureless-4.R
Saving _problems/test_mlr_learners_classif_featureless-43.R
Saving _problems/test_mlr_learners_classif_rpart-4.R
Saving _problems/test_mlr_learners_regr_featureless-4.R
Saving _problems/test_mlr_learners_regr_featureless-11.R
Saving _problems/test_mlr_learners_regr_rpart-4.R
Saving _problems/test_mlr_measures-31.R
Saving _problems/test_mlr_measures_selected_features-6.R
Saving _problems/test_mlr_measures_similarity-3.R
Saving _problems/test_mlr_reflections-60.R
Saving _problems/test_mlr_reflections-76.R
Saving _problems/test_mlr_reflections-105.R
Saving _problems/test_mlr_resampling_holdout-39.R
Saving _problems/test_parallel_future-12.R
Saving _problems/test_parallel_future-25.R
Saving _problems/test_parallel_future-42.R
Saving _problems/test_parallel_future-69.R
Saving _problems/test_parallel_future-82.R
Saving _problems/test_parallel_mirai-7.R
Saving _problems/test_parallel_mirai-18.R
Saving _problems/test_parallel_mirai-30.R
Saving _problems/test_parallel_mirai-99.R
Saving _problems/test_resample-4.R
Saving _problems/test_resultdata-9.R
Saving _problems/test_resultdata-58.R
Saving _problems/test_resultdata-93.R
Saving _problems/test_resultdata-131.R
Saving _problems/test_resultdata-190.R
[ FAIL 79 | WARN 0 | SKIP 12 | PASS 8474 ]
══ Skipped tests (12) ══════════════════════════════════════════════════════════
• Not on GitHub Actions (1): 'test_backward_compatibility.R:1:1'
• On CRAN (9): 'test_Learner.R:641:3', 'test_Learner.R:847:3',
'test_Learner.R:870:3', 'test_Learner.R:893:3', 'test_Learner.R:916:3',
'test_Measure.R:129:3', 'test_parallel_future.R:91:3',
'test_parallel_mirai.R:48:3', 'test_parallel_mirai.R:66:3'
• empty test (1): 'test_Task.R:911:1'
• {distr6} is not installed (1): 'test_PredictionRegr.R:54:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_CallbackResample.R:20:3'): on_resample_begin works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:20:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:39:3'): on_resample_before_train works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:39:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:58:3'): on_resample_before_predict works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:58:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:77:3'): on_resample_end works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(resample(task, learner, resampling, callbacks = callback)) at test_CallbackResample.R:77:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, learner, resampling, callbacks = callback)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:94:3'): writing to learner$state works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:94:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:127:3'): writing to data_extra works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:127:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:162:3'): data_extra is a list column ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:162:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:184:3'): data_extra is null ─────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:184:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:225:3'): learner cloning in workhorse is passed to context ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling, callbacks = callback) at test_CallbackResample.R:225:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackResample.R:244:3'): returning data_extra sometimes works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, callbacks = callback) at test_CallbackResample.R:244:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Learner.R:197:3'): predict train + test set ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, hout) at test_Learner.R:197:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Failure ('test_Learner.R:479:3'): internal_valid_task is created correctly ──
Expected `resample(task2, learner2, resampling)` not to throw any errors.
Actually got a <simpleError> with message:
attempt access index 9/9 in VECTOR_ELT
── Error ('test_Learner.R:562:3'): learner state contains internal valid task information ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Learner.R:562:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Learner.R:1021:3'): oob_error is available without storing models via $.extract_oob_error() ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout"), store_models = FALSE) at test_Learner.R:1021:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:21:5'): average with micro/macro ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_Measure.R:19:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, rs) at test_Measure.R:21:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:66:3'): check_prerequisites / task_properties ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Measure.R:66:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:90:3'): check_prerequisites / predict_type ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Measure.R:90:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:106:3'): check_prerequisites / predict_sets ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_Measure.R:106:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:122:3'): time_train works with different predict type (#832) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(...) at test_Measure.R:122:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:199:3'): measure weights ─────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, resampling) at test_Measure.R:199:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:285:3'): primary iters are respected ─────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_Measure.R:285:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Measure.R:306:3'): no predict_sets required (#1094) ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(...) at test_Measure.R:306:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_MeasureInternalValidScore.R:5:3'): internal valid score ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_MeasureInternalValidScore.R:5:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_MeasureRegrRSQ.R:112:3'): MeasureRegrRSQ works with weights during resampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_MeasureRegrRSQ.R:112:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_MeasureRegrRSQ.R:183:3'): MeasureRegrRSQ use_weights works ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task_plain, learner, resampling) at test_MeasureRegrRSQ.R:183:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_PredictionClassif.R:119:3'): c ─────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_PredictionClassif.R:119:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_PredictionRegr.R:22:3'): c ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_PredictionRegr.R:22:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_PredictionRegr.R:44:3'): c drops se (#250) ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_PredictionRegr.R:44:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Task.R:874:3'): $characteristics works ─────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design) at test_Task.R:874:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_Task.R:1031:3'): weights_measure + stratum works during resampling (#1405) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global expect_resample_result(...) at test_Task.R:1031:3
2. │ └─checkmate::expect_r6(rr, "ResampleResult")
3. │ └─checkmate::checkR6(...)
4. └─mlr3::resample(task, lrn("classif.featureless"), rsmp("cv", folds = 3))
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_autotest.R:60:3'): autotest configure_learner works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, 10, exclude = exclude, configure_learner = cfg_lrn) at test_autotest.R:60:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_autotest.R:162:7'): autotest on encapsulation ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_autotest.R:160:5
2. │ └─base::force(expr)
3. └─global run_experiment(task, learner1) at test_autotest.R:162:7
4. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_benchmark.R:6:1'): (code run outside of `test_that()`) ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design) at test_benchmark.R:6:1
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_encapsulate.R:49:3'): evaluate / resample ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_encapsulate.R:49:3
2. │ └─base::withCallingHandlers(...)
3. ├─base::suppressWarnings(...)
4. │ └─base::withCallingHandlers(...)
5. └─mlr3::resample(task, disable_encapsulation(learner), resampling)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_encapsulate.R:87:3'): encapsulate methods produce the same results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_encapsulate.R:87:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_errorhandling.R:63:3'): encapsulation / resample ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_errorhandling.R:63:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_errorhandling.R:80:3'): encapsulation / benchmark ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(benchmark_grid(task, learner, rsmp("cv", folds = 3))) at test_errorhandling.R:80:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_fallback.R:48:3'): fail during resample ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, rsmp("cv", folds = 3)) at test_fallback.R:48:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_fallback.R:65:3'): incomplete predictions ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, rsmp("cv", folds = 3)) at test_fallback.R:65:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:134:3'): learners are hotstarted when resample is used ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner_1, resampling, store_models = TRUE) at test_hotstart.R:134:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:158:3'): learners are hotstarted when benchmark is called ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, store_models = TRUE) at test_hotstart.R:158:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:187:3'): learners are trained and hotstarted when benchmark is called ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, store_models = TRUE) at test_hotstart.R:187:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:222:3'): learners are cloned when hotstarting is applied ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design, store_models = TRUE, allow_hotstart = TRUE) at test_hotstart.R:222:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_hotstart.R:246:3'): hotstarting works when col role is set in task ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner_1, resampling, store_models = TRUE) at test_hotstart.R:246:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_install_pkgs.R:25:3'): extract_pkgs works ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("mtcars"), lrn("regr.featureless"), rsmp("holdout")) at test_install_pkgs.R:25:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_lgr.R:20:3'): log to text file ─────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressWarnings(resample(task, learner, resampling)) at test_lgr.R:20:3
2. │ └─base::withCallingHandlers(...)
3. └─mlr3::resample(task, learner, resampling)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_lgr.R:38:3'): logger works ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::capture_output(...) at test_lgr.R:38:3
2. │ └─testthat::capture_output_lines(code, print, width = width)
3. │ └─testthat:::eval_with_output(code, print = print, width = width)
4. │ ├─withr::with_output_sink(path, withVisible(code))
5. │ │ └─base::force(code)
6. │ └─base::withVisible(code)
7. └─mlr3::resample(...)
8. └─ResultData$new(data, data_extra, store_backends = store_backends)
9. └─mlr3 (local) initialize(...)
10. └─mlr3:::.__ResultData__initialize(...)
11. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
12. └─data.table:::`[.data.table`(...)
── Error ('test_lgr.R:70:5'): thresholds are restored on workers ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::capture_output(...) at test_lgr.R:69:3
2. │ └─testthat::capture_output_lines(code, print, width = width)
3. │ └─testthat:::eval_with_output(code, print = print, width = width)
4. │ ├─withr::with_output_sink(path, withVisible(code))
5. │ │ └─base::force(code)
6. │ └─base::withVisible(code)
7. ├─global with_future(...)
8. │ └─base::force(expr)
9. └─mlr3::resample(...) at test_lgr.R:70:5
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:9:3'): model extractor works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling = resampling, callbacks = callback) at test_mlr_callbacks.R:9:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:30:3'): holdout task works ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling = resampling, callbacks = callback) at test_mlr_callbacks.R:30:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_debug.R:28:3'): updating model works / resample ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), learner, rsmp("holdout"), store_models = TRUE) at test_mlr_learners_classif_debug.R:28:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_featureless.R:4:3'): autotest ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "sanity") at test_mlr_learners_classif_featureless.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_featureless.R:43:3'): classif.featureless works on featureless task ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_mlr_learners_classif_featureless.R:43:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_classif_rpart.R:4:3'): autotest ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_mlr_learners_classif_rpart.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_regr_featureless.R:4:3'): autotest ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "sanity") at test_mlr_learners_regr_featureless.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_regr_featureless.R:11:3'): regr.featureless works on featureless task ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout")) at test_mlr_learners_regr_featureless.R:11:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_learners_regr_rpart.R:4:3'): autotest ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_mlr_learners_regr_rpart.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_measures.R:31:3'): custom aggregation ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("cv", folds = 3)) at test_mlr_measures.R:31:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_measures_selected_features.R:6:3'): selected_features ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, lrn, rsmp("holdout"), store_models = TRUE) at test_mlr_measures_selected_features.R:6:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_measures_similarity.R:3:1'): (code run outside of `test_that()`) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_mlr_measures_similarity.R:3:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_reflections.R:60:3'): resampling works ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_mlr_reflections.R:60:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_reflections.R:76:3'): benchmark works ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid) at test_mlr_reflections.R:76:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_reflections.R:105:5'): external packages can set column roles ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_mlr_reflections.R:104:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, lrn("classif.rpart"), rsmp("cv", folds = 3)) at test_mlr_reflections.R:105:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_resampling_holdout.R:39:3'): prediction does not drop dimension (#551) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(design) at test_mlr_resampling_holdout.R:39:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:12:7'): parallel resample ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_parallel_future.R:7:3
2. │ └─base::force(expr)
3. ├─progressr::with_progress(...) at test_parallel_future.R:11:5
4. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_parallel_future.R:12:7
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:25:3'): seeds work identical during sequential and parallel execution ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_parallel_future.R:25:3
2. │ └─base::force(expr)
3. ├─global with_future(future::sequential, resample(task, learner, resampling))
4. │ └─base::force(expr)
5. └─mlr3::resample(task, learner, resampling)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:42:7'): parallel benchmark ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_parallel_future.R:40:3
2. │ └─base::force(expr)
3. ├─progressr::with_progress(...) at test_parallel_future.R:41:5
4. └─mlr3::benchmark(benchmark_grid(task, learner, rsmp("cv", folds = 3))) at test_parallel_future.R:42:7
5. └─ResultData$new(grid, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:69:7'): real parallel resample ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_parallel_future.R:64:3
2. │ └─base::force(expr)
3. ├─progressr::with_progress(...) at test_parallel_future.R:68:5
4. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_parallel_future.R:69:7
5. └─ResultData$new(data, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_future.R:82:3'): parallel seed ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(123, resample(task, learner, rsmp("cv", folds = 3))) at test_parallel_future.R:82:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, rsmp("cv", folds = 3))
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:7:5'): parallel resample ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:4:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, rsmp("cv", folds = 3)) at test_parallel_mirai.R:7:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:18:5'): parallel benchmark ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:17:3
2. │ └─base::force(expr)
3. └─mlr3::benchmark(benchmark_grid(task, learner, rsmp("cv", folds = 3))) at test_parallel_mirai.R:18:5
4. └─ResultData$new(grid, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:30:5'): mirai resample is reproducible ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:26:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, resampling, store_models = TRUE) at test_parallel_mirai.R:30:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_parallel_mirai.R:99:5'): mirai compute profile can be changed ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_mirai(...) at test_parallel_mirai.R:94:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, resampling, store_models = TRUE) at test_parallel_mirai.R:99:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_resample.R:4:1'): (code run outside of `test_that()`) ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_resample.R:4:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:9:3'): results are ordered ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_resultdata.R:9:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:58:3'): mlr3tuning use case ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(...) at test_resultdata.R:58:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:93:3'): predict set selection ─────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_resultdata.R:93:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:131:3'): data_extra works ─────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::as_result_data(...) at test_resultdata.R:131:3
2. └─ResultData$new(...)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_resultdata.R:190:3'): combine with data_extra works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::as_result_data(...) at test_resultdata.R:190:3
2. └─ResultData$new(...)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
[ FAIL 79 | WARN 0 | SKIP 12 | PASS 8474 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.3.0
Check: installed package size
Result: NOTE
installed size is 5.0Mb
sub-directories of 1Mb or more:
R 2.0Mb
help 2.2Mb
Flavor: r-oldrel-macos-x86_64
Current CRAN status: ERROR: 4, OK: 9
Version: 0.2.2
Check: examples
Result: ERROR
Running examples in ‘mlr3batchmark-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: batchmark
> ### Title: Benchmark Experiments on Batch Systems
> ### Aliases: batchmark
>
> ### ** Examples
>
> tasks = list(mlr3::tsk("iris"), mlr3::tsk("sonar"))
> learners = list(mlr3::lrn("classif.featureless"), mlr3::lrn("classif.rpart"))
> resamplings = list(mlr3::rsmp("cv", folds = 3), mlr3::rsmp("holdout"))
>
> design = mlr3::benchmark_grid(
+ tasks = tasks,
+ learners = learners,
+ resamplings = resamplings
+ )
>
> reg = batchtools::makeExperimentRegistry(NA)
No readable configuration file found
Created registry in '/home/hornik/tmp/scratch/RtmpYTX6uK/registry3a6fc761f3ac7' using cluster functions 'Interactive'
> batchmark(design, reg = reg)
Adding algorithm 'run_learner'
Error in `[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", :
attempt access index 8/8 in VECTOR_ELT
Calls: batchmark -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.2.2
Check: tests
Result: ERROR
Running ‘testthat.R’ [4s/5s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3batchmark")
+ test_check("mlr3batchmark")
+ }
Loading required package: batchtools
Saving _problems/test_batchmark-13.R
Saving _problems/test_batchmark-42.R
Saving _problems/test_batchmark-67.R
Saving _problems/test_batchmark-92.R
Saving _problems/test_batchmark-114.R
Saving _problems/test_reduceResultsBatchmark-13.R
Saving _problems/test_reduceResultsBatchmark-50.R
[ FAIL 7 | WARN 0 | SKIP 0 | PASS 0 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_batchmark.R:13:3'): basic workflow ─────────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:13:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:42:3'): parallel multicore ─────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:42:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:67:3'): failing jobs ───────────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:67:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:92:3'): marshaling ─────────────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(...) at test_batchmark.R:92:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:114:3'): adding parameter values works ─────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:114:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_reduceResultsBatchmark.R:13:3'): reduceResultsBatchmark ────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg, store_models = TRUE) at test_reduceResultsBatchmark.R:13:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_reduceResultsBatchmark.R:50:3'): warning is given when mlr3 versions mismatch ──
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(...) at test_reduceResultsBatchmark.R:50:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 0 | SKIP 0 | PASS 0 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.2.2
Check: examples
Result: ERROR
Running examples in ‘mlr3batchmark-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: batchmark
> ### Title: Benchmark Experiments on Batch Systems
> ### Aliases: batchmark
>
> ### ** Examples
>
> tasks = list(mlr3::tsk("iris"), mlr3::tsk("sonar"))
> learners = list(mlr3::lrn("classif.featureless"), mlr3::lrn("classif.rpart"))
> resamplings = list(mlr3::rsmp("cv", folds = 3), mlr3::rsmp("holdout"))
>
> design = mlr3::benchmark_grid(
+ tasks = tasks,
+ learners = learners,
+ resamplings = resamplings
+ )
>
> reg = batchtools::makeExperimentRegistry(NA)
No readable configuration file found
Created registry in '/tmp/RtmpPBrj84/registry18c6ed7cb1c778' using cluster functions 'Interactive'
> batchmark(design, reg = reg)
Adding algorithm 'run_learner'
Error in `[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", :
attempt access index 8/8 in VECTOR_ELT
Calls: batchmark -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.2.2
Check: tests
Result: ERROR
Running ‘testthat.R’ [2s/3s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3batchmark")
+ test_check("mlr3batchmark")
+ }
Loading required package: batchtools
Saving _problems/test_batchmark-13.R
Saving _problems/test_batchmark-42.R
Saving _problems/test_batchmark-67.R
Saving _problems/test_batchmark-92.R
Saving _problems/test_batchmark-114.R
Saving _problems/test_reduceResultsBatchmark-13.R
Saving _problems/test_reduceResultsBatchmark-50.R
[ FAIL 7 | WARN 0 | SKIP 0 | PASS 0 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_batchmark.R:13:3'): basic workflow ─────────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:13:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:42:3'): parallel multicore ─────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:42:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:67:3'): failing jobs ───────────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:67:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:92:3'): marshaling ─────────────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(...) at test_batchmark.R:92:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:114:3'): adding parameter values works ─────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:114:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_reduceResultsBatchmark.R:13:3'): reduceResultsBatchmark ────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg, store_models = TRUE) at test_reduceResultsBatchmark.R:13:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_reduceResultsBatchmark.R:50:3'): warning is given when mlr3 versions mismatch ──
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(...) at test_reduceResultsBatchmark.R:50:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 0 | SKIP 0 | PASS 0 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.2.2
Check: examples
Result: ERROR
Running examples in ‘mlr3batchmark-Ex.R’ failed
The error most likely occurred in:
> ### Name: batchmark
> ### Title: Benchmark Experiments on Batch Systems
> ### Aliases: batchmark
>
> ### ** Examples
>
> tasks = list(mlr3::tsk("iris"), mlr3::tsk("sonar"))
> learners = list(mlr3::lrn("classif.featureless"), mlr3::lrn("classif.rpart"))
> resamplings = list(mlr3::rsmp("cv", folds = 3), mlr3::rsmp("holdout"))
>
> design = mlr3::benchmark_grid(
+ tasks = tasks,
+ learners = learners,
+ resamplings = resamplings
+ )
>
> reg = batchtools::makeExperimentRegistry(NA)
No readable configuration file found
Created registry in '/tmp/RtmpU4NVGm/working_dir/RtmpWiZZe7/registry17a57e77454669' using cluster functions 'Interactive'
> batchmark(design, reg = reg)
Adding algorithm 'run_learner'
Error in `[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", :
attempt access index 8/8 in VECTOR_ELT
Calls: batchmark -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.2.2
Check: tests
Result: ERROR
Running ‘testthat.R’ [6s/11s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3batchmark")
+ test_check("mlr3batchmark")
+ }
Loading required package: batchtools
Saving _problems/test_batchmark-13.R
Saving _problems/test_batchmark-42.R
Saving _problems/test_batchmark-67.R
Saving _problems/test_batchmark-92.R
Saving _problems/test_batchmark-114.R
Saving _problems/test_reduceResultsBatchmark-13.R
Saving _problems/test_reduceResultsBatchmark-50.R
[ FAIL 7 | WARN 0 | SKIP 0 | PASS 0 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_batchmark.R:13:3'): basic workflow ─────────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:13:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:42:3'): parallel multicore ─────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:42:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:67:3'): failing jobs ───────────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:67:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:92:3'): marshaling ─────────────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(...) at test_batchmark.R:92:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:114:3'): adding parameter values works ─────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:114:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_reduceResultsBatchmark.R:13:3'): reduceResultsBatchmark ────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg, store_models = TRUE) at test_reduceResultsBatchmark.R:13:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_reduceResultsBatchmark.R:50:3'): warning is given when mlr3 versions mismatch ──
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(...) at test_reduceResultsBatchmark.R:50:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 0 | SKIP 0 | PASS 0 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.2.2
Check: examples
Result: ERROR
Running examples in ‘mlr3batchmark-Ex.R’ failed
The error most likely occurred in:
> ### Name: batchmark
> ### Title: Benchmark Experiments on Batch Systems
> ### Aliases: batchmark
>
> ### ** Examples
>
> tasks = list(mlr3::tsk("iris"), mlr3::tsk("sonar"))
> learners = list(mlr3::lrn("classif.featureless"), mlr3::lrn("classif.rpart"))
> resamplings = list(mlr3::rsmp("cv", folds = 3), mlr3::rsmp("holdout"))
>
> design = mlr3::benchmark_grid(
+ tasks = tasks,
+ learners = learners,
+ resamplings = resamplings
+ )
>
> reg = batchtools::makeExperimentRegistry(NA)
No readable configuration file found
Created registry in '/tmp/RtmphNKjBj/working_dir/RtmpOePGkF/registry1c7e028a68fc3' using cluster functions 'Interactive'
> batchmark(design, reg = reg)
Adding algorithm 'run_learner'
Error in `[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", :
attempt access index 8/8 in VECTOR_ELT
Calls: batchmark -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.2.2
Check: tests
Result: ERROR
Running ‘testthat.R’
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3batchmark")
+ test_check("mlr3batchmark")
+ }
Loading required package: batchtools
Saving _problems/test_batchmark-13.R
Saving _problems/test_batchmark-42.R
Saving _problems/test_batchmark-67.R
Saving _problems/test_batchmark-92.R
Saving _problems/test_batchmark-114.R
Saving _problems/test_reduceResultsBatchmark-13.R
Saving _problems/test_reduceResultsBatchmark-50.R
[ FAIL 7 | WARN 0 | SKIP 0 | PASS 0 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_batchmark.R:13:3'): basic workflow ─────────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:13:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:42:3'): parallel multicore ─────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:42:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:67:3'): failing jobs ───────────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:67:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:92:3'): marshaling ─────────────────────────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(...) at test_batchmark.R:92:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_batchmark.R:114:3'): adding parameter values works ─────────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg) at test_batchmark.R:114:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_reduceResultsBatchmark.R:13:3'): reduceResultsBatchmark ────────
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(design, reg = reg, store_models = TRUE) at test_reduceResultsBatchmark.R:13:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
── Error ('test_reduceResultsBatchmark.R:50:3'): warning is given when mlr3 versions mismatch ──
Error in ``[.data.table`(design, , `:=`("group", .GRP), by = c("task_hash", "resampling_hash"))`: attempt access index 8/8 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3batchmark::batchmark(...) at test_reduceResultsBatchmark.R:50:3
2. ├─design[, `:=`("group", .GRP), by = c("task_hash", "resampling_hash")]
3. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 0 | SKIP 0 | PASS 0 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Current CRAN status: OK: 13
Current CRAN status: ERROR: 4, NOTE: 3, OK: 6
Version: 0.7.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [78s/112s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3db")
+ test_check("mlr3db")
+ }
Loading required package: mlr3
Loading required namespace: RSQLite
Loading required namespace: RSQLite
Saving _problems/test_train_predict_dplyr-20.R
Saving _problems/test_train_predict_duckdb-18.R
[ FAIL 2 | WARN 0 | SKIP 3 | PASS 998 ]
══ Skipped tests (3) ═══════════════════════════════════════════════════════════
• {polars} is not installed (3): 'test_as_polars_backend.R:1:1',
'test_polars.R:1:1', 'test_train_predict_polars.R:1:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_train_predict_dplyr.R:20:5'): resample works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_train_predict_dplyr.R:19:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, mlr3::rsmp("cv", folds = 3)) at test_train_predict_dplyr.R:20:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_train_predict_duckdb.R:18:5'): resample works ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_train_predict_duckdb.R:17:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, mlr3::rsmp("cv", folds = 3)) at test_train_predict_duckdb.R:18:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
[ FAIL 2 | WARN 0 | SKIP 3 | PASS 998 ]
Error:
! Test failures.
Warning message:
call dbDisconnect() when finished working with a connection
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.7.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [56s/97s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3db")
+ test_check("mlr3db")
+ }
Loading required package: mlr3
Loading required namespace: RSQLite
Loading required namespace: RSQLite
Saving _problems/test_train_predict_dplyr-20.R
Saving _problems/test_train_predict_duckdb-18.R
[ FAIL 2 | WARN 0 | SKIP 3 | PASS 998 ]
══ Skipped tests (3) ═══════════════════════════════════════════════════════════
• {polars} is not installed (3): 'test_as_polars_backend.R:1:1',
'test_polars.R:1:1', 'test_train_predict_polars.R:1:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_train_predict_dplyr.R:20:5'): resample works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_train_predict_dplyr.R:19:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, mlr3::rsmp("cv", folds = 3)) at test_train_predict_dplyr.R:20:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_train_predict_duckdb.R:18:5'): resample works ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_train_predict_duckdb.R:17:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, mlr3::rsmp("cv", folds = 3)) at test_train_predict_duckdb.R:18:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
[ FAIL 2 | WARN 0 | SKIP 3 | PASS 998 ]
Error:
! Test failures.
Warning message:
call dbDisconnect() when finished working with a connection
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.7.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [123s/260s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3db")
+ test_check("mlr3db")
+ }
Loading required package: mlr3
Loading required namespace: RSQLite
Loading required namespace: RSQLite
Saving _problems/test_train_predict_dplyr-20.R
Saving _problems/test_train_predict_duckdb-18.R
[ FAIL 2 | WARN 0 | SKIP 3 | PASS 998 ]
══ Skipped tests (3) ═══════════════════════════════════════════════════════════
• {polars} is not installed (3): 'test_as_polars_backend.R:1:1',
'test_polars.R:1:1', 'test_train_predict_polars.R:1:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_train_predict_dplyr.R:20:5'): resample works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_train_predict_dplyr.R:19:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, mlr3::rsmp("cv", folds = 3)) at test_train_predict_dplyr.R:20:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_train_predict_duckdb.R:18:5'): resample works ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_train_predict_duckdb.R:17:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, mlr3::rsmp("cv", folds = 3)) at test_train_predict_duckdb.R:18:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
[ FAIL 2 | WARN 0 | SKIP 3 | PASS 998 ]
Error:
! Test failures.
Warning message:
call dbDisconnect() when finished working with a connection
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.7.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [113s/158s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3db")
+ test_check("mlr3db")
+ }
Loading required package: mlr3
Loading required namespace: RSQLite
Loading required namespace: RSQLite
Saving _problems/test_train_predict_dplyr-20.R
Saving _problems/test_train_predict_duckdb-18.R
[ FAIL 2 | WARN 1 | SKIP 3 | PASS 998 ]
══ Skipped tests (3) ═══════════════════════════════════════════════════════════
• {polars} is not installed (3): 'test_as_polars_backend.R:1:1',
'test_polars.R:1:1', 'test_train_predict_polars.R:1:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_train_predict_dplyr.R:20:5'): resample works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_train_predict_dplyr.R:19:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, mlr3::rsmp("cv", folds = 3)) at test_train_predict_dplyr.R:20:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_train_predict_duckdb.R:18:5'): resample works ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_future(...) at test_train_predict_duckdb.R:17:3
2. │ └─base::force(expr)
3. └─mlr3::resample(task, learner, mlr3::rsmp("cv", folds = 3)) at test_train_predict_duckdb.R:18:5
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
[ FAIL 2 | WARN 1 | SKIP 3 | PASS 998 ]
Error:
! Test failures.
Warning message:
call dbDisconnect() when finished working with a connection
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.7.0
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘polars’
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 0.7.0
Check: Rd cross-references
Result: NOTE
Package unavailable to check Rd xrefs: ‘polars’
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Current CRAN status: ERROR: 4, OK: 9
Version: 0.9.0
Check: examples
Result: ERROR
Running examples in ‘mlr3filters-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: mlr_filters_performance
> ### Title: Predictive Performance Filter
> ### Aliases: mlr_filters_performance FilterPerformance
>
> ### ** Examples
>
> if (requireNamespace("rpart")) {
+ task = mlr3::tsk("iris")
+ learner = mlr3::lrn("classif.rpart")
+ filter = flt("performance", learner = learner)
+ filter$calculate(task)
+ as.data.table(filter)
+ }
INFO [04:33:52.610] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/1)
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: <Anonymous> ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.9.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [52s/70s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3filters")
+ test_check("mlr3filters")
+ }
Saving _problems/test_FilterPerformance-8.R
Saving _problems/test_FilterPermutation-7.R
Saving _problems/test_filter_classif-9.R
Saving _problems/test_filter_classif-34.R
[ FAIL 4 | WARN 0 | SKIP 3 | PASS 470 ]
══ Skipped tests (3) ═══════════════════════════════════════════════════════════
• {mlr3proba} is not installed (2): 'test_FilterUnivariateCox.R:1:1',
'test_filter_surv.R:1:1'
• {mlr3spatiotempcv} is not installed (1): 'test_mlr3spatiotempcv.R:1:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_FilterPerformance.R:8:3'): FilterPerformance ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_FilterPerformance.R:8:3
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPerformance__.calculate(...)
5. └─mlr3misc::map_dbl(...)
6. └─mlr3misc:::map_mold(.x, .f, NA_real_, ...)
7. └─base::vapply(.x, .f, FUN.VALUE = .value, USE.NAMES = FALSE, ...)
8. └─mlr3filters (local) FUN(X[[i]], ...)
9. └─mlr3::resample(task, self$learner, resampling, clone = character())
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_FilterPermutation.R:7:3'): FilterPermutation ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_FilterPermutation.R:7:3
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPermutation__.calculate(...)
5. └─mlr3::resample(task, self$learner, self$resampling)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_filter_classif.R:9:7'): all classif filters return correct filter values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_filter_classif.R:9:7
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPerformance__.calculate(...)
5. └─mlr3misc::map_dbl(...)
6. └─mlr3misc:::map_mold(.x, .f, NA_real_, ...)
7. └─base::vapply(.x, .f, FUN.VALUE = .value, USE.NAMES = FALSE, ...)
8. └─mlr3filters (local) FUN(X[[i]], ...)
9. └─mlr3::resample(task, self$learner, resampling, clone = character())
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_filter_classif.R:34:7'): filters throw errors on missing values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_filter_classif.R:34:7
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPerformance__.calculate(...)
5. └─mlr3misc::map_dbl(...)
6. └─mlr3misc:::map_mold(.x, .f, NA_real_, ...)
7. └─base::vapply(.x, .f, FUN.VALUE = .value, USE.NAMES = FALSE, ...)
8. └─mlr3filters (local) FUN(X[[i]], ...)
9. └─mlr3::resample(task, self$learner, resampling, clone = character())
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
[ FAIL 4 | WARN 0 | SKIP 3 | PASS 470 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.9.0
Check: examples
Result: ERROR
Running examples in ‘mlr3filters-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: mlr_filters_performance
> ### Title: Predictive Performance Filter
> ### Aliases: mlr_filters_performance FilterPerformance
>
> ### ** Examples
>
> if (requireNamespace("rpart")) {
+ task = mlr3::tsk("iris")
+ learner = mlr3::lrn("classif.rpart")
+ filter = flt("performance", learner = learner)
+ filter$calculate(task)
+ as.data.table(filter)
+ }
INFO [17:17:53.843] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/1)
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: <Anonymous> ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.9.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [37s/59s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3filters")
+ test_check("mlr3filters")
+ }
Saving _problems/test_FilterPerformance-8.R
Saving _problems/test_FilterPermutation-7.R
Saving _problems/test_filter_classif-9.R
Saving _problems/test_filter_classif-34.R
[ FAIL 4 | WARN 0 | SKIP 3 | PASS 470 ]
══ Skipped tests (3) ═══════════════════════════════════════════════════════════
• {mlr3proba} is not installed (2): 'test_FilterUnivariateCox.R:1:1',
'test_filter_surv.R:1:1'
• {mlr3spatiotempcv} is not installed (1): 'test_mlr3spatiotempcv.R:1:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_FilterPerformance.R:8:3'): FilterPerformance ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_FilterPerformance.R:8:3
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPerformance__.calculate(...)
5. └─mlr3misc::map_dbl(...)
6. └─mlr3misc:::map_mold(.x, .f, NA_real_, ...)
7. └─base::vapply(.x, .f, FUN.VALUE = .value, USE.NAMES = FALSE, ...)
8. └─mlr3filters (local) FUN(X[[i]], ...)
9. └─mlr3::resample(task, self$learner, resampling, clone = character())
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_FilterPermutation.R:7:3'): FilterPermutation ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_FilterPermutation.R:7:3
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPermutation__.calculate(...)
5. └─mlr3::resample(task, self$learner, self$resampling)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_filter_classif.R:9:7'): all classif filters return correct filter values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_filter_classif.R:9:7
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPerformance__.calculate(...)
5. └─mlr3misc::map_dbl(...)
6. └─mlr3misc:::map_mold(.x, .f, NA_real_, ...)
7. └─base::vapply(.x, .f, FUN.VALUE = .value, USE.NAMES = FALSE, ...)
8. └─mlr3filters (local) FUN(X[[i]], ...)
9. └─mlr3::resample(task, self$learner, resampling, clone = character())
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_filter_classif.R:34:7'): filters throw errors on missing values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_filter_classif.R:34:7
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPerformance__.calculate(...)
5. └─mlr3misc::map_dbl(...)
6. └─mlr3misc:::map_mold(.x, .f, NA_real_, ...)
7. └─base::vapply(.x, .f, FUN.VALUE = .value, USE.NAMES = FALSE, ...)
8. └─mlr3filters (local) FUN(X[[i]], ...)
9. └─mlr3::resample(task, self$learner, resampling, clone = character())
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
[ FAIL 4 | WARN 0 | SKIP 3 | PASS 470 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.9.0
Check: examples
Result: ERROR
Running examples in ‘mlr3filters-Ex.R’ failed
The error most likely occurred in:
> ### Name: mlr_filters_performance
> ### Title: Predictive Performance Filter
> ### Aliases: mlr_filters_performance FilterPerformance
>
> ### ** Examples
>
> if (requireNamespace("rpart")) {
+ task = mlr3::tsk("iris")
+ learner = mlr3::lrn("classif.rpart")
+ filter = flt("performance", learner = learner)
+ filter$calculate(task)
+ as.data.table(filter)
+ }
INFO [17:45:39.544] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/1)
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: <Anonymous> ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.9.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [90s/178s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3filters")
+ test_check("mlr3filters")
+ }
Saving _problems/test_FilterPerformance-8.R
Saving _problems/test_FilterPermutation-7.R
Saving _problems/test_filter_classif-9.R
Saving _problems/test_filter_classif-34.R
[ FAIL 4 | WARN 0 | SKIP 3 | PASS 470 ]
══ Skipped tests (3) ═══════════════════════════════════════════════════════════
• {mlr3proba} is not installed (2): 'test_FilterUnivariateCox.R:1:1',
'test_filter_surv.R:1:1'
• {mlr3spatiotempcv} is not installed (1): 'test_mlr3spatiotempcv.R:1:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_FilterPerformance.R:8:3'): FilterPerformance ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_FilterPerformance.R:8:3
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPerformance__.calculate(...)
5. └─mlr3misc::map_dbl(...)
6. └─mlr3misc:::map_mold(.x, .f, NA_real_, ...)
7. └─base::vapply(.x, .f, FUN.VALUE = .value, USE.NAMES = FALSE, ...)
8. └─mlr3filters (local) FUN(X[[i]], ...)
9. └─mlr3::resample(task, self$learner, resampling, clone = character())
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_FilterPermutation.R:7:3'): FilterPermutation ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_FilterPermutation.R:7:3
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPermutation__.calculate(...)
5. └─mlr3::resample(task, self$learner, self$resampling)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_filter_classif.R:9:7'): all classif filters return correct filter values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_filter_classif.R:9:7
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPerformance__.calculate(...)
5. └─mlr3misc::map_dbl(...)
6. └─mlr3misc:::map_mold(.x, .f, NA_real_, ...)
7. └─base::vapply(.x, .f, FUN.VALUE = .value, USE.NAMES = FALSE, ...)
8. └─mlr3filters (local) FUN(X[[i]], ...)
9. └─mlr3::resample(task, self$learner, resampling, clone = character())
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_filter_classif.R:34:7'): filters throw errors on missing values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_filter_classif.R:34:7
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPerformance__.calculate(...)
5. └─mlr3misc::map_dbl(...)
6. └─mlr3misc:::map_mold(.x, .f, NA_real_, ...)
7. └─base::vapply(.x, .f, FUN.VALUE = .value, USE.NAMES = FALSE, ...)
8. └─mlr3filters (local) FUN(X[[i]], ...)
9. └─mlr3::resample(task, self$learner, resampling, clone = character())
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
[ FAIL 4 | WARN 0 | SKIP 3 | PASS 470 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.9.0
Check: examples
Result: ERROR
Running examples in ‘mlr3filters-Ex.R’ failed
The error most likely occurred in:
> ### Name: mlr_filters_performance
> ### Title: Predictive Performance Filter
> ### Aliases: mlr_filters_performance FilterPerformance
>
> ### ** Examples
>
> if (requireNamespace("rpart")) {
+ task = mlr3::tsk("iris")
+ learner = mlr3::lrn("classif.rpart")
+ filter = flt("performance", learner = learner)
+ filter$calculate(task)
+ as.data.table(filter)
+ }
INFO [12:28:56.656] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/1)
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: <Anonymous> ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.9.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [80s/128s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3filters")
+ test_check("mlr3filters")
+ }
Saving _problems/test_FilterPerformance-8.R
Saving _problems/test_FilterPermutation-7.R
Saving _problems/test_filter_classif-9.R
Saving _problems/test_filter_classif-34.R
[ FAIL 4 | WARN 0 | SKIP 3 | PASS 470 ]
══ Skipped tests (3) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test_mlr3spatiotempcv.R:2:1'
• {mlr3proba} is not installed (2): 'test_FilterUnivariateCox.R:1:1',
'test_filter_surv.R:1:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_FilterPerformance.R:8:3'): FilterPerformance ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_FilterPerformance.R:8:3
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPerformance__.calculate(...)
5. └─mlr3misc::map_dbl(...)
6. └─mlr3misc:::map_mold(.x, .f, NA_real_, ...)
7. └─base::vapply(.x, .f, FUN.VALUE = .value, USE.NAMES = FALSE, ...)
8. └─mlr3filters (local) FUN(X[[i]], ...)
9. └─mlr3::resample(task, self$learner, resampling, clone = character())
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_FilterPermutation.R:7:3'): FilterPermutation ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_FilterPermutation.R:7:3
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPermutation__.calculate(...)
5. └─mlr3::resample(task, self$learner, self$resampling)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_filter_classif.R:9:7'): all classif filters return correct filter values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_filter_classif.R:9:7
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPerformance__.calculate(...)
5. └─mlr3misc::map_dbl(...)
6. └─mlr3misc:::map_mold(.x, .f, NA_real_, ...)
7. └─base::vapply(.x, .f, FUN.VALUE = .value, USE.NAMES = FALSE, ...)
8. └─mlr3filters (local) FUN(X[[i]], ...)
9. └─mlr3::resample(task, self$learner, resampling, clone = character())
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_filter_classif.R:34:7'): filters throw errors on missing values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─f$calculate(task) at test_filter_classif.R:34:7
2. └─mlr3filters:::.__Filter__calculate(...)
3. └─private$.calculate(task, nfeat)
4. └─mlr3filters:::.__FilterPerformance__.calculate(...)
5. └─mlr3misc::map_dbl(...)
6. └─mlr3misc:::map_mold(.x, .f, NA_real_, ...)
7. └─base::vapply(.x, .f, FUN.VALUE = .value, USE.NAMES = FALSE, ...)
8. └─mlr3filters (local) FUN(X[[i]], ...)
9. └─mlr3::resample(task, self$learner, resampling, clone = character())
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
[ FAIL 4 | WARN 0 | SKIP 3 | PASS 470 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Current CRAN status: ERROR: 4, OK: 9
Version: 1.5.0
Check: examples
Result: ERROR
Running examples in ‘mlr3fselect-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: auto_fselector
> ### Title: Function for Automatic Feature Selection
> ### Aliases: auto_fselector
>
> ### ** Examples
>
> afs = auto_fselector(
+ fselector = fs("random_search"),
+ learner = lrn("classif.rpart"),
+ resampling = rsmp("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 4)
>
> afs$train(tsk("pima"))
INFO [04:34:21.791] [bbotk] Starting to optimize 8 parameter(s) with '<FSelectorBatchRandomSearch>' and '<TerminatorEvals> [n_evals=4, k=0]'
INFO [04:34:21.871] [bbotk] Evaluating 10 configuration(s)
INFO [04:34:22.003] [mlr3] Running benchmark with 10 resampling iterations
INFO [04:34:22.205] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [04:34:22.266] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [04:34:22.306] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [04:34:22.339] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [04:34:22.372] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [04:34:22.404] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [04:34:22.443] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [04:34:22.479] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [04:34:22.520] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [04:34:22.639] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [04:34:22.752] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: <Anonymous> ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.5.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [170s/259s]
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
Attaching package: 'data.table'
The following object is masked from 'package:base':
%notin%
Saving _problems/test_ArchiveBatchFSelect-8.R
Saving _problems/test_ArchiveBatchFSelect-58.R
Saving _problems/test_ArchiveBatchFSelect-164.R
Saving _problems/test_ArchiveBatchFSelect-204.R
Saving _problems/test_ArchiveBatchFSelect-232.R
Saving _problems/test_ArchiveBatchFSelect-260.R
Saving _problems/test_AutoFSelector-137.R
Saving _problems/test_AutoFSelector-166.R
Saving _problems/test_AutoFSelector-211.R
Saving _problems/test_FSelectInstanceMultiCrit-16.R
Saving _problems/test_FSelectInstanceMultiCrit-29.R
Saving _problems/test_FSelectInstanceMultiCrit-37.R
Saving _problems/test_FSelectInstanceSingleCrit-16.R
Saving _problems/test_FSelectInstanceSingleCrit-40.R
Saving _problems/test_FSelectInstanceSingleCrit-48.R
Saving _problems/test_FSelectInstanceSingleCrit-85.R
Saving _problems/test_FSelectInstanceSingleCrit-111.R
Saving _problems/test_FSelectInstanceSingleCrit-131.R
Saving _problems/test_FSelectorBatchDesignPoints-8.R
Saving _problems/test_FSelectorBatchDesignPoints-20.R
Saving _problems/test_FSelectorExhaustiveSearch-2.R
Saving _problems/test_FSelectorExhaustiveSearch-14.R
Saving _problems/test_FSelectorExhaustiveSearch-23.R
Saving _problems/test_FSelectorExhaustiveSearch-27.R
Saving _problems/test_FSelectorGeneticSearch-4.R
Saving _problems/test_FSelectorRFE-2.R
Saving _problems/test_FSelectorRFE-11.R
Saving _problems/test_FSelectorRFE-18.R
Saving _problems/test_FSelectorRFE-27.R
Saving _problems/test_FSelectorRFE-49.R
Saving _problems/test_FSelectorRFE-63.R
Saving _problems/test_FSelectorRFE-83.R
Saving _problems/test_FSelectorRFE-131.R
Saving _problems/test_FSelectorRFE-142.R
Saving _problems/test_FSelectorRFE-161.R
Saving _problems/test_FSelectorRFE-233.R
Saving _problems/test_FSelectorRFE-290.R
Saving _problems/test_FSelectorRFECV-12.R
Saving _problems/test_FSelectorRFECV-32.R
Saving _problems/test_FSelectorRFECV-61.R
Saving _problems/test_FSelectorRFECV-118.R
Saving _problems/test_FSelectorRandomSearch-2.R
Saving _problems/test_FSelectorRandomSearch-6.R
Saving _problems/test_FSelectorRandomSearch-12.R
Saving _problems/test_FSelectorSequential-2.R
Saving _problems/test_FSelectorSequential-11.R
Saving _problems/test_FSelectorSequential-20.R
Saving _problems/test_FSelectorSequential-26.R
Saving _problems/test_FSelectorSequential-32.R
Saving _problems/test_FSelectorSequential-39.R
Saving _problems/test_FSelectorShadowVariableSearch-2.R
Saving _problems/test_FSelectorShadowVariableSearch-14.R
Saving _problems/test_FSelectorShadowVariableSearch-26.R
Saving _problems/test_FSelectorShadowVariableSearch-35.R
Saving _problems/test_FSelectorShadowVariableSearch-54.R
Saving _problems/test_ObjectiveFSelect-15.R
Saving _problems/test_ObjectiveFSelect-35.R
Saving _problems/test_ObjectiveFSelect-54.R
Saving _problems/test_ObjectiveFSelect-74.R
Saving _problems/test_ObjectiveFSelect-126.R
Saving _problems/test_ObjectiveFSelectAsync-15.R
Saving _problems/test_ObjectiveFSelectAsync-37.R
Saving _problems/test_ObjectiveFSelectAsync-61.R
Saving _problems/test_ObjectiveFSelectAsync-85.R
Saving _problems/test_embedded_ensemble_fselect-9.R
Saving _problems/test_embedded_ensemble_fselect-74.R
Saving _problems/test_ensemble_fselect-13.R
Saving _problems/test_ensemble_fselect-108.R
Saving _problems/test_ensemble_fselect-359.R
Saving _problems/test_extract_inner_fselect_archives-3.R
Saving _problems/test_extract_inner_fselect_archives-12.R
Saving _problems/test_extract_inner_fselect_archives-24.R
Saving _problems/test_extract_inner_fselect_archives-37.R
Saving _problems/test_extract_inner_fselect_archives-50.R
Saving _problems/test_extract_inner_fselect_archives-61.R
Saving _problems/test_extract_inner_fselect_archives-70.R
Saving _problems/test_extract_inner_fselect_archives-80.R
Saving _problems/test_extract_inner_fselect_archives-92.R
Saving _problems/test_extract_inner_fselect_archives-104.R
Saving _problems/test_extract_inner_fselect_result-3.R
Saving _problems/test_extract_inner_fselect_result-12.R
Saving _problems/test_extract_inner_fselect_result-24.R
Saving _problems/test_extract_inner_fselect_result-37.R
Saving _problems/test_extract_inner_fselect_result-50.R
Saving _problems/test_extract_inner_fselect_result-61.R
Saving _problems/test_extract_inner_fselect_result-70.R
Saving _problems/test_extract_inner_fselect_result-80.R
Saving _problems/test_extract_inner_fselect_result-92.R
Saving _problems/test_extract_inner_fselect_result-104.R
Saving _problems/test_extract_inner_fselect_result-113.R
Saving _problems/test_extract_inner_fselect_result-125.R
Saving _problems/test_fselect-3.R
Saving _problems/test_fselect-12.R
Saving _problems/test_fselect-21.R
Saving _problems/test_fselect_nested-4.R
Saving _problems/test_mlr_callbacks-12.R
Saving _problems/test_mlr_callbacks-32.R
Saving _problems/test_mlr_callbacks-53.R
Saving _problems/test_mlr_callbacks-73.R
Saving _problems/test_mlr_callbacks-96.R
[ FAIL 100 | WARN 27 | SKIP 52 | PASS 235 ]
══ Skipped tests (52) ══════════════════════════════════════════════════════════
• On CRAN (52): 'test_ArchiveAsyncFSelect.R:2:3',
'test_ArchiveAsyncFSelect.R:51:3', 'test_ArchiveAsyncFSelect.R:107:3',
'test_ArchiveAsyncFSelect.R:133:3', 'test_ArchiveAsyncFSelect.R:155:3',
'test_ArchiveAsyncFSelect.R:181:3', 'test_ArchiveAsyncFSelectFrozen.R:2:3',
'test_AutoFSelector.R:2:3', 'test_AutoFSelector.R:29:3',
'test_AutoFSelector.R:64:3', 'test_AutoFSelector.R:219:3',
'test_CallbackAsyncFSelect.R:4:3', 'test_CallbackAsyncFSelect.R:32:3',
'test_CallbackAsyncFSelect.R:62:3', 'test_CallbackAsyncFSelect.R:90:3',
'test_CallbackAsyncFSelect.R:120:3', 'test_CallbackAsyncFSelect.R:154:3',
'test_CallbackAsyncFSelect.R:181:3', 'test_CallbackAsyncFSelect.R:213:3',
'test_CallbackAsyncFSelect.R:242:3', 'test_CallbackAsyncFSelect.R:269:3',
'test_CallbackAsyncFSelect.R:298:3', 'test_CallbackAsyncFSelect.R:327:3',
'test_CallbackAsyncFSelect.R:354:3', 'test_CallbackAsyncFSelect.R:383:3',
'test_CallbackAsyncFSelect.R:419:3', 'test_CallbackAsyncFSelect.R:454:3',
'test_CallbackAsyncFSelect.R:488:3',
'test_FSelectInstanceAsyncMultiCrit.R:2:3',
'test_FSelectInstanceAsyncMultiCrit.R:30:3',
'test_FSelectInstanceAsyncMultiCrit.R:53:3',
'test_FSelectInstanceAsyncMultiCrit.R:77:3',
'test_FSelectInstanceAsyncMultiCrit.R:101:3',
'test_FSelectInstanceAsyncMultiCrit.R:129:3',
'test_FSelectInstanceAsyncSingleCrit.R:2:3',
'test_FSelectInstanceAsyncSingleCrit.R:29:3',
'test_FSelectInstanceAsyncSingleCrit.R:50:3',
'test_FSelectInstanceAsyncSingleCrit.R:73:3',
'test_FSelectInstanceAsyncSingleCrit.R:98:3',
'test_FSelectInstanceAsyncSingleCrit.R:124:3',
'test_FSelectorAsyncDesignPoints.R:2:3',
'test_FSelectorAsyncExhaustiveSearch.R:2:3',
'test_FSelectorAsyncRandomSearch.R:2:3', 'test_ObjectiveFSelectAsync.R:96:3',
'test_ObjectiveFSelectAsync.R:160:3', 'test_auto_fselector.R:24:3',
'test_auto_fselector.R:47:3', 'test_fsi_async.R:2:3',
'test_fsi_async.R:16:3', 'test_fsi_async.R:30:3', 'test_fsi_async.R:42:3',
'test_mlr_callbacks.R:108:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ArchiveBatchFSelect.R:2:3'): ArchiveBatchFSelect access methods work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:2:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:52:3'): ArchiveBatchFSelect as.data.table function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:52:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:157:3'): global ties method works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:157:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:198:3'): local ties method works when maximize measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:198:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:226:3'): local ties method works when minimize measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:226:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:254:3'): local ties method works with batches ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:254:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_AutoFSelector.R:137:3'): AutoFSelector works with GraphLearner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoFSelector.R:137:3
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 = `<S3: AutoFSelector>`, task = `<S3: TaskRegr>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3fselect:::.__AutoFSelector__.train(...)
12. └─self$fselector$optimize(instance)
13. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
21. └─inst$eval_batch(states)
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test_AutoFSelector.R:166:3'): AutoFSelector get_base_learner method works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─afs$train(tsk("pima")) at test_AutoFSelector.R:166:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<S3: AutoFSelector>`, task = `<S3: TaskClassif>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3fselect:::.__AutoFSelector__.train(...)
12. └─self$fselector$optimize(instance)
13. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
21. └─inst$eval_batch(as.data.table(X))
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test_AutoFSelector.R:211:3'): AutoFSelector hash works #647 in mlr3 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_AutoFSelector.R:211:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_FSelectInstanceMultiCrit.R:16:3'): eval_batch works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceMultiCrit.R:16:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceMultiCrit.R:29:3'): objective_function works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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$objective$eval_many(xss_trafoed)
7. └─bbotk:::.__Objective__eval_many(...)
8. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
9. │ └─base::eval.parent(expr, n = 1L)
10. │ └─base::eval(expr, p)
11. │ └─base::eval(expr, p)
12. └─private$.eval_many(xss = xss, resampling = `<list>`)
13. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
14. └─mlr3::benchmark(...)
15. └─ResultData$new(grid, data_extra, store_backends = store_backends)
16. └─mlr3 (local) initialize(...)
17. └─mlr3:::.__ResultData__initialize(...)
18. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
19. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceMultiCrit.R:37:3'): store_benchmark_result flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceMultiCrit.R:37:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:16:3'): eval_batch works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceSingleCrit.R:16:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:40:3'): objective_function works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$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$eval_batch(xdt)
5. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
6. └─self$objective$eval_many(xss_trafoed)
7. └─bbotk:::.__Objective__eval_many(...)
8. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
9. │ └─base::eval.parent(expr, n = 1L)
10. │ └─base::eval(expr, p)
11. │ └─base::eval(expr, p)
12. └─private$.eval_many(xss = xss, resampling = `<list>`)
13. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
14. └─mlr3::benchmark(...)
15. └─ResultData$new(grid, data_extra, store_backends = store_backends)
16. └─mlr3 (local) initialize(...)
17. └─mlr3:::.__ResultData__initialize(...)
18. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
19. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:48:3'): store_benchmark_result flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceSingleCrit.R:48:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:77:3'): always include variable works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectInstanceSingleCrit.R:77:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:103:3'): always include variables works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectInstanceSingleCrit.R:103:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:131:3'): objective contains no benchmark results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectInstanceSingleCrit.R:131:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
10. └─inst$eval_batch(as.data.table(X))
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorBatchDesignPoints.R:8:3'): default parameters work ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("design_points", design = design) at test_FSelectorBatchDesignPoints.R:8:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
14. └─instance$eval_batch(design[inds, ])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorBatchDesignPoints.R:20:3'): multi-crit works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector_2D("design_points", design = design) at test_FSelectorBatchDesignPoints.R:20:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
14. └─instance$eval_batch(design[inds, ])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:2:3'): default parameters work ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("exhaustive_search") at test_FSelectorExhaustiveSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:14:3'): max_features parameter works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("exhaustive_search", max_features = 2) at test_FSelectorExhaustiveSearch.R:14:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:23:3'): multi-crit works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector_2D("exhaustive_search") at test_FSelectorExhaustiveSearch.R:23:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:27:3'): batch_size parameter works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("exhaustive_search", batch_size = 2) at test_FSelectorExhaustiveSearch.R:27:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorGeneticSearch.R:4:3'): default parameters work ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("genetic_search", term_evals = 10) at test_FSelectorGeneticSearch.R:4:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchGeneticSearch__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─genalg::rbga.bin(...)
17. └─bbotk (local) evalFunc(population[object, ])
18. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
19. └─private$.objective_function(x, self, self$objective_multiplicator)
20. └─inst$eval_batch(xdt)
21. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
22. └─self$objective$eval_many(xss_trafoed)
23. └─bbotk:::.__Objective__eval_many(...)
24. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
25. │ └─base::eval.parent(expr, n = 1L)
26. │ └─base::eval(expr, p)
27. │ └─base::eval(expr, p)
28. └─private$.eval_many(xss = xss, resampling = `<list>`)
29. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
30. └─mlr3::benchmark(...)
31. └─ResultData$new(grid, data_extra, store_backends = store_backends)
32. └─mlr3 (local) initialize(...)
33. └─mlr3:::.__ResultData__initialize(...)
34. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
35. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:2:3'): importance is stored in the archive ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", store_models = TRUE) at test_FSelectorRFE.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:11:3'): default parameters work ─────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", store_models = TRUE) at test_FSelectorRFE.R:11:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:18:3'): recursive parameter works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", recursive = FALSE, store_models = TRUE) at test_FSelectorRFE.R:18:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:27:3'): feature_fraction parameter works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", feature_fraction = 0.9, store_models = TRUE) at test_FSelectorRFE.R:27:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:49:3'): feature_number parameter works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", feature_number = 1, store_models = TRUE) at test_FSelectorRFE.R:49:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:63:3'): subset_size parameter works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:83:3'): subset is full feature set works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", feature_number = 4, store_models = TRUE) at test_FSelectorRFE.R:83:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:131:3'): rank_importance function works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_FSelectorRFE.R:131:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:142:3'): average_importance function works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_FSelectorRFE.R:142:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:154:3'): works without storing models ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectorRFE.R:154:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
11. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:233:3'): optimal features are selected with rank ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFE.R:233:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:290:3'): optimal features are selected with mean ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFE.R:290:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:12:3'): extra columns are stored in the archive ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:12:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:32:3'): resampling is converted ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:32:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:61:3'): default parameters work ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:61:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:118:3'): optimal features are selected ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:118:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRandomSearch.R:2:3'): default parameters work ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("random_search", batch_size = 5, term_evals = 10) at test_FSelectorRandomSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(as.data.table(X))
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRandomSearch.R:6:3'): max_features parameter work ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("random_search", max_features = 1, term_evals = 10) at test_FSelectorRandomSearch.R:6:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(as.data.table(X))
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRandomSearch.R:12:3'): multi-crit works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(as.data.table(X))
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:2:3'): default parameters works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:11:3'): sbs strategy works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential", strategy = "sbs") at test_FSelectorSequential.R:11:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:20:3'): sfs strategy works with max_features parameter ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential", max_features = 2) at test_FSelectorSequential.R:20:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:26:3'): sbs strategy works with max_features parameter ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential", max_features = 2, strategy = "sbs") at test_FSelectorSequential.R:26:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:32:3'): optimization_path method works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:32:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:39:3'): optimization_path method works with included uhash ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:39:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:2:3'): default parameters work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("shadow_variable_search", store_models = TRUE) at test_FSelectorShadowVariableSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:14:3'): task is permuted ───────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:14:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
10. └─inst$eval_batch(states)
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:26:3'): first selected feature is a shadow variable works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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:::.__FSelectorBatch__optimize(...)
9. └─bbotk::optimize_batch_default(inst, self)
10. ├─base::tryCatch(...)
11. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
12. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
13. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
14. └─get_private(optimizer)$.optimize(instance)
15. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
16. └─inst$eval_batch(states)
17. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
18. └─self$objective$eval_many(xss_trafoed)
19. └─bbotk:::.__Objective__eval_many(...)
20. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
21. │ └─base::eval.parent(expr, n = 1L)
22. │ └─base::eval(expr, p)
23. │ └─base::eval(expr, p)
24. └─private$.eval_many(xss = xss, resampling = `<list>`)
25. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
26. └─mlr3::benchmark(...)
27. └─ResultData$new(grid, data_extra, store_backends = store_backends)
28. └─mlr3 (local) initialize(...)
29. └─mlr3:::.__ResultData__initialize(...)
30. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
31. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:35:3'): second selected feature is a shadow variable works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:35:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
10. └─inst$eval_batch(states)
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:54:3'): search is terminated by terminator works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:54:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
10. └─inst$eval_batch(states)
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:15:3'): ObjectiveFSelectBatch ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveFSelect.R:15:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:35:3'): ObjectiveFSelectBatch works with multiple measures ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveFSelect.R:35:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:54:3'): ObjectiveFSelectBatch works with store_models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveFSelect.R:54:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:67:5'): fast aggregation works ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_ObjectiveFSelect.R:66:3
2. │ └─base::force(expr)
3. └─mlr3fselect::fselect(...) at test_ObjectiveFSelect.R:67:5
4. └─fselector$optimize(instance)
5. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(as.data.table(X))
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:119:3'): fast aggregation conditions work ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ObjectiveFSelect.R:119:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:15:3'): objective async works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:15:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:37:3'): store benchmark result works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:37:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:61:3'): store models works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:61:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:85:3'): rush objective with multiple measures works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:85:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_embedded_ensemble_fselect.R:4:5'): embedded efs works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_embedded_ensemble_fselect.R:3:3
2. │ └─base::force(expr)
3. └─mlr3fselect::embedded_ensemble_fselect(...) at test_embedded_ensemble_fselect.R:4:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─ResultData$new(grid, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_embedded_ensemble_fselect.R:69:5'): combine embedded efs results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_embedded_ensemble_fselect.R:68:3
2. │ └─base::force(expr)
3. └─mlr3fselect::embedded_ensemble_fselect(...) at test_embedded_ensemble_fselect.R:69:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─ResultData$new(grid, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_ensemble_fselect.R:4:5'): efs works ────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_ensemble_fselect.R:3:3
2. │ └─base::force(expr)
3. └─mlr3fselect::ensemble_fselect(...) at test_ensemble_fselect.R:4:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─mlr3:::future_map(...)
6. └─future.apply::future_mapply(...)
7. └─future.apply:::future_xapply(...)
8. └─base::tryCatch(...)
9. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. └─base (local) tryCatchOne(...)
11. └─value[[3L]](cond)
12. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_ensemble_fselect.R:99:5'): efs works with rfe ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_ensemble_fselect.R:98:3
2. │ └─base::force(expr)
3. └─mlr3fselect::ensemble_fselect(...) at test_ensemble_fselect.R:99:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─mlr3:::future_map(...)
6. └─future.apply::future_mapply(...)
7. └─future.apply:::future_xapply(...)
8. └─base::tryCatch(...)
9. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. └─base (local) tryCatchOne(...)
11. └─value[[3L]](cond)
12. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_ensemble_fselect.R:349:3'): different callbacks can be set ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::ensemble_fselect(...) at test_ensemble_fselect.R:349:3
2. └─mlr3::benchmark(design, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:2:3'): extract_inner_fselect_archives function works with resample and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:11:3'): extract_inner_fselect_archives function works with resample and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_extract_inner_fselect_archives.R:11:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:24:3'): extract_inner_fselect_archives function works with benchmark and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:37:3'): extract_inner_fselect_archives function works with benchmark and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_archives.R:37:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:50:3'): extract_inner_fselect_archives function works with multiple tasks ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:61:3'): extract_inner_fselect_archives function works with no models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, resampling_outer, store_models = FALSE) at test_extract_inner_fselect_archives.R:61:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:70:3'): extract_inner_fselect_archives function works with no instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:80:3'): extract_inner_fselect_archives function works with benchmark and no models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = FALSE) at test_extract_inner_fselect_archives.R:80:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:92:3'): extract_inner_fselect_archives function works with mixed store instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:104:3'): extract_inner_fselect_archives function works with autofselector and learner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_archives.R:104:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:2:3'): extract_inner_fselect_results function works with resample and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:11:3'): extract_inner_fselect_results function works with resample and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_extract_inner_fselect_result.R:11:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:24:3'): extract_inner_fselect_results function works with benchmark and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:37:3'): extract_inner_fselect_results function works with benchmark and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:37:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:50:3'): extract_inner_fselect_results function works with multiple tasks ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:61:3'): extract_inner_fselect_results function works with no model ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, resampling_outer, store_models = FALSE) at test_extract_inner_fselect_result.R:61:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:70:3'): extract_inner_fselect_results function works no instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:80:3'): extract_inner_fselect_results function works with benchmark and no models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = FALSE) at test_extract_inner_fselect_result.R:80:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:92:3'): extract_inner_fselect_results function works with mixed store instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:104:3'): extract_inner_fselect_results function works with learner and autotuner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:104:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:113:3'): extract_inner_fselect_results function works with resample and return of instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:125:3'): extract_inner_fselect_results function works with benchmark and return of instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:125:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_fselect.R:2:3'): fselect function works with single measure ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:2:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_fselect.R:11:3'): fselect function works with multiple measures ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:11:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_fselect.R:20:3'): fselect function accepts string input for method ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:20:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_fselect_nested.R:2:3'): fselect_nested function works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_mlr_callbacks.R:4:3'): backup callback works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:4:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:23:3'): svm_rfe callbacks works ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:23:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
11. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:46:3'): one_se_rule callback works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:46:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
11. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
12. └─mlr3fselect (local) .f(.xi, ...)
13. └─inst$eval_batch(states[row_ids])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:65:3'): internal tuning callback works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:65:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:96:3'): internal tuning callback works with AutoFSelector ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─afs$train(tsk("pima")) at test_mlr_callbacks.R:96:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<S3: AutoFSelector>`, task = `<S3: TaskClassif>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3fselect:::.__AutoFSelector__.train(...)
12. └─self$fselector$optimize(instance)
13. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
21. └─inst$eval_batch(as.data.table(X))
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
[ FAIL 100 | WARN 27 | SKIP 52 | PASS 235 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.5.0
Check: examples
Result: ERROR
Running examples in ‘mlr3fselect-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: auto_fselector
> ### Title: Function for Automatic Feature Selection
> ### Aliases: auto_fselector
>
> ### ** Examples
>
> afs = auto_fselector(
+ fselector = fs("random_search"),
+ learner = lrn("classif.rpart"),
+ resampling = rsmp("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 4)
>
> afs$train(tsk("pima"))
INFO [17:17:47.556] [bbotk] Starting to optimize 8 parameter(s) with '<FSelectorBatchRandomSearch>' and '<TerminatorEvals> [n_evals=4, k=0]'
INFO [17:17:47.609] [bbotk] Evaluating 10 configuration(s)
INFO [17:17:47.675] [mlr3] Running benchmark with 10 resampling iterations
INFO [17:17:47.758] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:17:47.801] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:17:47.836] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:17:47.862] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:17:47.890] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:17:47.916] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:17:47.948] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:17:47.977] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:17:48.003] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:17:48.029] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:17:48.062] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: <Anonymous> ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.5.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [118s/169s]
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
Attaching package: 'data.table'
The following object is masked from 'package:base':
%notin%
Saving _problems/test_ArchiveBatchFSelect-8.R
Saving _problems/test_ArchiveBatchFSelect-58.R
Saving _problems/test_ArchiveBatchFSelect-164.R
Saving _problems/test_ArchiveBatchFSelect-204.R
Saving _problems/test_ArchiveBatchFSelect-232.R
Saving _problems/test_ArchiveBatchFSelect-260.R
Saving _problems/test_AutoFSelector-137.R
Saving _problems/test_AutoFSelector-166.R
Saving _problems/test_AutoFSelector-211.R
Saving _problems/test_FSelectInstanceMultiCrit-16.R
Saving _problems/test_FSelectInstanceMultiCrit-29.R
Saving _problems/test_FSelectInstanceMultiCrit-37.R
Saving _problems/test_FSelectInstanceSingleCrit-16.R
Saving _problems/test_FSelectInstanceSingleCrit-40.R
Saving _problems/test_FSelectInstanceSingleCrit-48.R
Saving _problems/test_FSelectInstanceSingleCrit-85.R
Saving _problems/test_FSelectInstanceSingleCrit-111.R
Saving _problems/test_FSelectInstanceSingleCrit-131.R
Saving _problems/test_FSelectorBatchDesignPoints-8.R
Saving _problems/test_FSelectorBatchDesignPoints-20.R
Saving _problems/test_FSelectorExhaustiveSearch-2.R
Saving _problems/test_FSelectorExhaustiveSearch-14.R
Saving _problems/test_FSelectorExhaustiveSearch-23.R
Saving _problems/test_FSelectorExhaustiveSearch-27.R
Saving _problems/test_FSelectorGeneticSearch-4.R
Saving _problems/test_FSelectorRFE-2.R
Saving _problems/test_FSelectorRFE-11.R
Saving _problems/test_FSelectorRFE-18.R
Saving _problems/test_FSelectorRFE-27.R
Saving _problems/test_FSelectorRFE-49.R
Saving _problems/test_FSelectorRFE-63.R
Saving _problems/test_FSelectorRFE-83.R
Saving _problems/test_FSelectorRFE-131.R
Saving _problems/test_FSelectorRFE-142.R
Saving _problems/test_FSelectorRFE-161.R
Saving _problems/test_FSelectorRFE-233.R
Saving _problems/test_FSelectorRFE-290.R
Saving _problems/test_FSelectorRFECV-12.R
Saving _problems/test_FSelectorRFECV-32.R
Saving _problems/test_FSelectorRFECV-61.R
Saving _problems/test_FSelectorRFECV-118.R
Saving _problems/test_FSelectorRandomSearch-2.R
Saving _problems/test_FSelectorRandomSearch-6.R
Saving _problems/test_FSelectorRandomSearch-12.R
Saving _problems/test_FSelectorSequential-2.R
Saving _problems/test_FSelectorSequential-11.R
Saving _problems/test_FSelectorSequential-20.R
Saving _problems/test_FSelectorSequential-26.R
Saving _problems/test_FSelectorSequential-32.R
Saving _problems/test_FSelectorSequential-39.R
Saving _problems/test_FSelectorShadowVariableSearch-2.R
Saving _problems/test_FSelectorShadowVariableSearch-14.R
Saving _problems/test_FSelectorShadowVariableSearch-26.R
Saving _problems/test_FSelectorShadowVariableSearch-35.R
Saving _problems/test_FSelectorShadowVariableSearch-54.R
Saving _problems/test_ObjectiveFSelect-15.R
Saving _problems/test_ObjectiveFSelect-35.R
Saving _problems/test_ObjectiveFSelect-54.R
Saving _problems/test_ObjectiveFSelect-74.R
Saving _problems/test_ObjectiveFSelect-126.R
Saving _problems/test_ObjectiveFSelectAsync-15.R
Saving _problems/test_ObjectiveFSelectAsync-37.R
Saving _problems/test_ObjectiveFSelectAsync-61.R
Saving _problems/test_ObjectiveFSelectAsync-85.R
Saving _problems/test_embedded_ensemble_fselect-9.R
Saving _problems/test_embedded_ensemble_fselect-74.R
Saving _problems/test_ensemble_fselect-13.R
Saving _problems/test_ensemble_fselect-108.R
Saving _problems/test_ensemble_fselect-359.R
Saving _problems/test_extract_inner_fselect_archives-3.R
Saving _problems/test_extract_inner_fselect_archives-12.R
Saving _problems/test_extract_inner_fselect_archives-24.R
Saving _problems/test_extract_inner_fselect_archives-37.R
Saving _problems/test_extract_inner_fselect_archives-50.R
Saving _problems/test_extract_inner_fselect_archives-61.R
Saving _problems/test_extract_inner_fselect_archives-70.R
Saving _problems/test_extract_inner_fselect_archives-80.R
Saving _problems/test_extract_inner_fselect_archives-92.R
Saving _problems/test_extract_inner_fselect_archives-104.R
Saving _problems/test_extract_inner_fselect_result-3.R
Saving _problems/test_extract_inner_fselect_result-12.R
Saving _problems/test_extract_inner_fselect_result-24.R
Saving _problems/test_extract_inner_fselect_result-37.R
Saving _problems/test_extract_inner_fselect_result-50.R
Saving _problems/test_extract_inner_fselect_result-61.R
Saving _problems/test_extract_inner_fselect_result-70.R
Saving _problems/test_extract_inner_fselect_result-80.R
Saving _problems/test_extract_inner_fselect_result-92.R
Saving _problems/test_extract_inner_fselect_result-104.R
Saving _problems/test_extract_inner_fselect_result-113.R
Saving _problems/test_extract_inner_fselect_result-125.R
Saving _problems/test_fselect-3.R
Saving _problems/test_fselect-12.R
Saving _problems/test_fselect-21.R
Saving _problems/test_fselect_nested-4.R
Saving _problems/test_mlr_callbacks-12.R
Saving _problems/test_mlr_callbacks-32.R
Saving _problems/test_mlr_callbacks-53.R
Saving _problems/test_mlr_callbacks-73.R
Saving _problems/test_mlr_callbacks-96.R
[ FAIL 100 | WARN 27 | SKIP 52 | PASS 235 ]
══ Skipped tests (52) ══════════════════════════════════════════════════════════
• On CRAN (52): 'test_ArchiveAsyncFSelect.R:2:3',
'test_ArchiveAsyncFSelect.R:51:3', 'test_ArchiveAsyncFSelect.R:107:3',
'test_ArchiveAsyncFSelect.R:133:3', 'test_ArchiveAsyncFSelect.R:155:3',
'test_ArchiveAsyncFSelect.R:181:3', 'test_ArchiveAsyncFSelectFrozen.R:2:3',
'test_AutoFSelector.R:2:3', 'test_AutoFSelector.R:29:3',
'test_AutoFSelector.R:64:3', 'test_AutoFSelector.R:219:3',
'test_CallbackAsyncFSelect.R:4:3', 'test_CallbackAsyncFSelect.R:32:3',
'test_CallbackAsyncFSelect.R:62:3', 'test_CallbackAsyncFSelect.R:90:3',
'test_CallbackAsyncFSelect.R:120:3', 'test_CallbackAsyncFSelect.R:154:3',
'test_CallbackAsyncFSelect.R:181:3', 'test_CallbackAsyncFSelect.R:213:3',
'test_CallbackAsyncFSelect.R:242:3', 'test_CallbackAsyncFSelect.R:269:3',
'test_CallbackAsyncFSelect.R:298:3', 'test_CallbackAsyncFSelect.R:327:3',
'test_CallbackAsyncFSelect.R:354:3', 'test_CallbackAsyncFSelect.R:383:3',
'test_CallbackAsyncFSelect.R:419:3', 'test_CallbackAsyncFSelect.R:454:3',
'test_CallbackAsyncFSelect.R:488:3',
'test_FSelectInstanceAsyncMultiCrit.R:2:3',
'test_FSelectInstanceAsyncMultiCrit.R:30:3',
'test_FSelectInstanceAsyncMultiCrit.R:53:3',
'test_FSelectInstanceAsyncMultiCrit.R:77:3',
'test_FSelectInstanceAsyncMultiCrit.R:101:3',
'test_FSelectInstanceAsyncMultiCrit.R:129:3',
'test_FSelectInstanceAsyncSingleCrit.R:2:3',
'test_FSelectInstanceAsyncSingleCrit.R:29:3',
'test_FSelectInstanceAsyncSingleCrit.R:50:3',
'test_FSelectInstanceAsyncSingleCrit.R:73:3',
'test_FSelectInstanceAsyncSingleCrit.R:98:3',
'test_FSelectInstanceAsyncSingleCrit.R:124:3',
'test_FSelectorAsyncDesignPoints.R:2:3',
'test_FSelectorAsyncExhaustiveSearch.R:2:3',
'test_FSelectorAsyncRandomSearch.R:2:3', 'test_ObjectiveFSelectAsync.R:96:3',
'test_ObjectiveFSelectAsync.R:160:3', 'test_auto_fselector.R:24:3',
'test_auto_fselector.R:47:3', 'test_fsi_async.R:2:3',
'test_fsi_async.R:16:3', 'test_fsi_async.R:30:3', 'test_fsi_async.R:42:3',
'test_mlr_callbacks.R:108:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ArchiveBatchFSelect.R:2:3'): ArchiveBatchFSelect access methods work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:2:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:52:3'): ArchiveBatchFSelect as.data.table function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:52:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:157:3'): global ties method works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:157:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:198:3'): local ties method works when maximize measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:198:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:226:3'): local ties method works when minimize measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:226:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:254:3'): local ties method works with batches ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:254:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_AutoFSelector.R:137:3'): AutoFSelector works with GraphLearner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoFSelector.R:137:3
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 = `<S3: AutoFSelector>`, task = `<S3: TaskRegr>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3fselect:::.__AutoFSelector__.train(...)
12. └─self$fselector$optimize(instance)
13. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
21. └─inst$eval_batch(states)
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test_AutoFSelector.R:166:3'): AutoFSelector get_base_learner method works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─afs$train(tsk("pima")) at test_AutoFSelector.R:166:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<S3: AutoFSelector>`, task = `<S3: TaskClassif>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3fselect:::.__AutoFSelector__.train(...)
12. └─self$fselector$optimize(instance)
13. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
21. └─inst$eval_batch(as.data.table(X))
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test_AutoFSelector.R:211:3'): AutoFSelector hash works #647 in mlr3 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_AutoFSelector.R:211:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_FSelectInstanceMultiCrit.R:16:3'): eval_batch works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceMultiCrit.R:16:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceMultiCrit.R:29:3'): objective_function works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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$objective$eval_many(xss_trafoed)
7. └─bbotk:::.__Objective__eval_many(...)
8. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
9. │ └─base::eval.parent(expr, n = 1L)
10. │ └─base::eval(expr, p)
11. │ └─base::eval(expr, p)
12. └─private$.eval_many(xss = xss, resampling = `<list>`)
13. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
14. └─mlr3::benchmark(...)
15. └─ResultData$new(grid, data_extra, store_backends = store_backends)
16. └─mlr3 (local) initialize(...)
17. └─mlr3:::.__ResultData__initialize(...)
18. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
19. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceMultiCrit.R:37:3'): store_benchmark_result flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceMultiCrit.R:37:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:16:3'): eval_batch works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceSingleCrit.R:16:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:40:3'): objective_function works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$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$eval_batch(xdt)
5. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
6. └─self$objective$eval_many(xss_trafoed)
7. └─bbotk:::.__Objective__eval_many(...)
8. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
9. │ └─base::eval.parent(expr, n = 1L)
10. │ └─base::eval(expr, p)
11. │ └─base::eval(expr, p)
12. └─private$.eval_many(xss = xss, resampling = `<list>`)
13. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
14. └─mlr3::benchmark(...)
15. └─ResultData$new(grid, data_extra, store_backends = store_backends)
16. └─mlr3 (local) initialize(...)
17. └─mlr3:::.__ResultData__initialize(...)
18. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
19. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:48:3'): store_benchmark_result flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceSingleCrit.R:48:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:77:3'): always include variable works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectInstanceSingleCrit.R:77:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:103:3'): always include variables works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectInstanceSingleCrit.R:103:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:131:3'): objective contains no benchmark results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectInstanceSingleCrit.R:131:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
10. └─inst$eval_batch(as.data.table(X))
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorBatchDesignPoints.R:8:3'): default parameters work ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("design_points", design = design) at test_FSelectorBatchDesignPoints.R:8:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
14. └─instance$eval_batch(design[inds, ])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorBatchDesignPoints.R:20:3'): multi-crit works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector_2D("design_points", design = design) at test_FSelectorBatchDesignPoints.R:20:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
14. └─instance$eval_batch(design[inds, ])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:2:3'): default parameters work ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("exhaustive_search") at test_FSelectorExhaustiveSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:14:3'): max_features parameter works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("exhaustive_search", max_features = 2) at test_FSelectorExhaustiveSearch.R:14:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:23:3'): multi-crit works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector_2D("exhaustive_search") at test_FSelectorExhaustiveSearch.R:23:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:27:3'): batch_size parameter works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("exhaustive_search", batch_size = 2) at test_FSelectorExhaustiveSearch.R:27:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorGeneticSearch.R:4:3'): default parameters work ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("genetic_search", term_evals = 10) at test_FSelectorGeneticSearch.R:4:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchGeneticSearch__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─genalg::rbga.bin(...)
17. └─bbotk (local) evalFunc(population[object, ])
18. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
19. └─private$.objective_function(x, self, self$objective_multiplicator)
20. └─inst$eval_batch(xdt)
21. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
22. └─self$objective$eval_many(xss_trafoed)
23. └─bbotk:::.__Objective__eval_many(...)
24. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
25. │ └─base::eval.parent(expr, n = 1L)
26. │ └─base::eval(expr, p)
27. │ └─base::eval(expr, p)
28. └─private$.eval_many(xss = xss, resampling = `<list>`)
29. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
30. └─mlr3::benchmark(...)
31. └─ResultData$new(grid, data_extra, store_backends = store_backends)
32. └─mlr3 (local) initialize(...)
33. └─mlr3:::.__ResultData__initialize(...)
34. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
35. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:2:3'): importance is stored in the archive ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", store_models = TRUE) at test_FSelectorRFE.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:11:3'): default parameters work ─────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", store_models = TRUE) at test_FSelectorRFE.R:11:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:18:3'): recursive parameter works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", recursive = FALSE, store_models = TRUE) at test_FSelectorRFE.R:18:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:27:3'): feature_fraction parameter works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", feature_fraction = 0.9, store_models = TRUE) at test_FSelectorRFE.R:27:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:49:3'): feature_number parameter works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", feature_number = 1, store_models = TRUE) at test_FSelectorRFE.R:49:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:63:3'): subset_size parameter works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:83:3'): subset is full feature set works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", feature_number = 4, store_models = TRUE) at test_FSelectorRFE.R:83:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:131:3'): rank_importance function works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_FSelectorRFE.R:131:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:142:3'): average_importance function works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_FSelectorRFE.R:142:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:154:3'): works without storing models ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectorRFE.R:154:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
11. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:233:3'): optimal features are selected with rank ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFE.R:233:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:290:3'): optimal features are selected with mean ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFE.R:290:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:12:3'): extra columns are stored in the archive ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:12:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:32:3'): resampling is converted ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:32:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:61:3'): default parameters work ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:61:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:118:3'): optimal features are selected ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:118:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRandomSearch.R:2:3'): default parameters work ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("random_search", batch_size = 5, term_evals = 10) at test_FSelectorRandomSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(as.data.table(X))
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRandomSearch.R:6:3'): max_features parameter work ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("random_search", max_features = 1, term_evals = 10) at test_FSelectorRandomSearch.R:6:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(as.data.table(X))
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRandomSearch.R:12:3'): multi-crit works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(as.data.table(X))
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:2:3'): default parameters works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:11:3'): sbs strategy works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential", strategy = "sbs") at test_FSelectorSequential.R:11:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:20:3'): sfs strategy works with max_features parameter ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential", max_features = 2) at test_FSelectorSequential.R:20:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:26:3'): sbs strategy works with max_features parameter ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential", max_features = 2, strategy = "sbs") at test_FSelectorSequential.R:26:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:32:3'): optimization_path method works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:32:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:39:3'): optimization_path method works with included uhash ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:39:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:2:3'): default parameters work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("shadow_variable_search", store_models = TRUE) at test_FSelectorShadowVariableSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:14:3'): task is permuted ───────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:14:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
10. └─inst$eval_batch(states)
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:26:3'): first selected feature is a shadow variable works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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:::.__FSelectorBatch__optimize(...)
9. └─bbotk::optimize_batch_default(inst, self)
10. ├─base::tryCatch(...)
11. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
12. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
13. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
14. └─get_private(optimizer)$.optimize(instance)
15. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
16. └─inst$eval_batch(states)
17. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
18. └─self$objective$eval_many(xss_trafoed)
19. └─bbotk:::.__Objective__eval_many(...)
20. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
21. │ └─base::eval.parent(expr, n = 1L)
22. │ └─base::eval(expr, p)
23. │ └─base::eval(expr, p)
24. └─private$.eval_many(xss = xss, resampling = `<list>`)
25. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
26. └─mlr3::benchmark(...)
27. └─ResultData$new(grid, data_extra, store_backends = store_backends)
28. └─mlr3 (local) initialize(...)
29. └─mlr3:::.__ResultData__initialize(...)
30. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
31. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:35:3'): second selected feature is a shadow variable works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:35:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
10. └─inst$eval_batch(states)
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:54:3'): search is terminated by terminator works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:54:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
10. └─inst$eval_batch(states)
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:15:3'): ObjectiveFSelectBatch ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveFSelect.R:15:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:35:3'): ObjectiveFSelectBatch works with multiple measures ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveFSelect.R:35:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:54:3'): ObjectiveFSelectBatch works with store_models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveFSelect.R:54:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:67:5'): fast aggregation works ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_ObjectiveFSelect.R:66:3
2. │ └─base::force(expr)
3. └─mlr3fselect::fselect(...) at test_ObjectiveFSelect.R:67:5
4. └─fselector$optimize(instance)
5. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(as.data.table(X))
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:119:3'): fast aggregation conditions work ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ObjectiveFSelect.R:119:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:15:3'): objective async works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:15:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:37:3'): store benchmark result works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:37:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:61:3'): store models works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:61:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:85:3'): rush objective with multiple measures works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:85:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_embedded_ensemble_fselect.R:4:5'): embedded efs works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_embedded_ensemble_fselect.R:3:3
2. │ └─base::force(expr)
3. └─mlr3fselect::embedded_ensemble_fselect(...) at test_embedded_ensemble_fselect.R:4:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─ResultData$new(grid, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_embedded_ensemble_fselect.R:69:5'): combine embedded efs results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_embedded_ensemble_fselect.R:68:3
2. │ └─base::force(expr)
3. └─mlr3fselect::embedded_ensemble_fselect(...) at test_embedded_ensemble_fselect.R:69:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─ResultData$new(grid, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_ensemble_fselect.R:4:5'): efs works ────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_ensemble_fselect.R:3:3
2. │ └─base::force(expr)
3. └─mlr3fselect::ensemble_fselect(...) at test_ensemble_fselect.R:4:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─mlr3:::future_map(...)
6. └─future.apply::future_mapply(...)
7. └─future.apply:::future_xapply(...)
8. └─base::tryCatch(...)
9. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. └─base (local) tryCatchOne(...)
11. └─value[[3L]](cond)
12. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_ensemble_fselect.R:99:5'): efs works with rfe ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_ensemble_fselect.R:98:3
2. │ └─base::force(expr)
3. └─mlr3fselect::ensemble_fselect(...) at test_ensemble_fselect.R:99:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─mlr3:::future_map(...)
6. └─future.apply::future_mapply(...)
7. └─future.apply:::future_xapply(...)
8. └─base::tryCatch(...)
9. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. └─base (local) tryCatchOne(...)
11. └─value[[3L]](cond)
12. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_ensemble_fselect.R:349:3'): different callbacks can be set ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::ensemble_fselect(...) at test_ensemble_fselect.R:349:3
2. └─mlr3::benchmark(design, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:2:3'): extract_inner_fselect_archives function works with resample and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:11:3'): extract_inner_fselect_archives function works with resample and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_extract_inner_fselect_archives.R:11:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:24:3'): extract_inner_fselect_archives function works with benchmark and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:37:3'): extract_inner_fselect_archives function works with benchmark and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_archives.R:37:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:50:3'): extract_inner_fselect_archives function works with multiple tasks ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:61:3'): extract_inner_fselect_archives function works with no models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, resampling_outer, store_models = FALSE) at test_extract_inner_fselect_archives.R:61:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:70:3'): extract_inner_fselect_archives function works with no instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:80:3'): extract_inner_fselect_archives function works with benchmark and no models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = FALSE) at test_extract_inner_fselect_archives.R:80:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:92:3'): extract_inner_fselect_archives function works with mixed store instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:104:3'): extract_inner_fselect_archives function works with autofselector and learner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_archives.R:104:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:2:3'): extract_inner_fselect_results function works with resample and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:11:3'): extract_inner_fselect_results function works with resample and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_extract_inner_fselect_result.R:11:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:24:3'): extract_inner_fselect_results function works with benchmark and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:37:3'): extract_inner_fselect_results function works with benchmark and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:37:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:50:3'): extract_inner_fselect_results function works with multiple tasks ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:61:3'): extract_inner_fselect_results function works with no model ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, resampling_outer, store_models = FALSE) at test_extract_inner_fselect_result.R:61:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:70:3'): extract_inner_fselect_results function works no instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:80:3'): extract_inner_fselect_results function works with benchmark and no models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = FALSE) at test_extract_inner_fselect_result.R:80:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:92:3'): extract_inner_fselect_results function works with mixed store instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:104:3'): extract_inner_fselect_results function works with learner and autotuner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:104:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:113:3'): extract_inner_fselect_results function works with resample and return of instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:125:3'): extract_inner_fselect_results function works with benchmark and return of instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:125:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_fselect.R:2:3'): fselect function works with single measure ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:2:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_fselect.R:11:3'): fselect function works with multiple measures ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:11:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_fselect.R:20:3'): fselect function accepts string input for method ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:20:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_fselect_nested.R:2:3'): fselect_nested function works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_mlr_callbacks.R:4:3'): backup callback works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:4:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:23:3'): svm_rfe callbacks works ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:23:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
11. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:46:3'): one_se_rule callback works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:46:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
11. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
12. └─mlr3fselect (local) .f(.xi, ...)
13. └─inst$eval_batch(states[row_ids])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:65:3'): internal tuning callback works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:65:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:96:3'): internal tuning callback works with AutoFSelector ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─afs$train(tsk("pima")) at test_mlr_callbacks.R:96:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<S3: AutoFSelector>`, task = `<S3: TaskClassif>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3fselect:::.__AutoFSelector__.train(...)
12. └─self$fselector$optimize(instance)
13. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
21. └─inst$eval_batch(as.data.table(X))
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
[ FAIL 100 | WARN 27 | SKIP 52 | PASS 235 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.5.0
Check: examples
Result: ERROR
Running examples in ‘mlr3fselect-Ex.R’ failed
The error most likely occurred in:
> ### Name: auto_fselector
> ### Title: Function for Automatic Feature Selection
> ### Aliases: auto_fselector
>
> ### ** Examples
>
> afs = auto_fselector(
+ fselector = fs("random_search"),
+ learner = lrn("classif.rpart"),
+ resampling = rsmp("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 4)
>
> afs$train(tsk("pima"))
INFO [17:46:14.464] [bbotk] Starting to optimize 8 parameter(s) with '<FSelectorBatchRandomSearch>' and '<TerminatorEvals> [n_evals=4, k=0]'
INFO [17:46:14.838] [bbotk] Evaluating 10 configuration(s)
INFO [17:46:15.200] [mlr3] Running benchmark with 10 resampling iterations
INFO [17:46:15.561] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:46:15.701] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:46:15.832] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:46:15.954] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:46:16.084] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:46:16.240] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:46:16.422] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:46:16.547] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:46:16.688] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:46:16.801] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:46:16.940] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: <Anonymous> ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.5.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [258s/495s]
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
Attaching package: 'data.table'
The following object is masked from 'package:base':
%notin%
Saving _problems/test_ArchiveBatchFSelect-8.R
Saving _problems/test_ArchiveBatchFSelect-58.R
Saving _problems/test_ArchiveBatchFSelect-164.R
Saving _problems/test_ArchiveBatchFSelect-204.R
Saving _problems/test_ArchiveBatchFSelect-232.R
Saving _problems/test_ArchiveBatchFSelect-260.R
Saving _problems/test_AutoFSelector-137.R
Saving _problems/test_AutoFSelector-166.R
Saving _problems/test_AutoFSelector-211.R
Saving _problems/test_FSelectInstanceMultiCrit-16.R
Saving _problems/test_FSelectInstanceMultiCrit-29.R
Saving _problems/test_FSelectInstanceMultiCrit-37.R
Saving _problems/test_FSelectInstanceSingleCrit-16.R
Saving _problems/test_FSelectInstanceSingleCrit-40.R
Saving _problems/test_FSelectInstanceSingleCrit-48.R
Saving _problems/test_FSelectInstanceSingleCrit-85.R
Saving _problems/test_FSelectInstanceSingleCrit-111.R
Saving _problems/test_FSelectInstanceSingleCrit-131.R
Saving _problems/test_FSelectorBatchDesignPoints-8.R
Saving _problems/test_FSelectorBatchDesignPoints-20.R
Saving _problems/test_FSelectorExhaustiveSearch-2.R
Saving _problems/test_FSelectorExhaustiveSearch-14.R
Saving _problems/test_FSelectorExhaustiveSearch-23.R
Saving _problems/test_FSelectorExhaustiveSearch-27.R
Saving _problems/test_FSelectorGeneticSearch-4.R
Saving _problems/test_FSelectorRFE-2.R
Saving _problems/test_FSelectorRFE-11.R
Saving _problems/test_FSelectorRFE-18.R
Saving _problems/test_FSelectorRFE-27.R
Saving _problems/test_FSelectorRFE-49.R
Saving _problems/test_FSelectorRFE-63.R
Saving _problems/test_FSelectorRFE-83.R
Saving _problems/test_FSelectorRFE-131.R
Saving _problems/test_FSelectorRFE-142.R
Saving _problems/test_FSelectorRFE-161.R
Saving _problems/test_FSelectorRFE-233.R
Saving _problems/test_FSelectorRFE-290.R
Saving _problems/test_FSelectorRFECV-12.R
Saving _problems/test_FSelectorRFECV-32.R
Saving _problems/test_FSelectorRFECV-61.R
Saving _problems/test_FSelectorRFECV-118.R
Saving _problems/test_FSelectorRandomSearch-2.R
Saving _problems/test_FSelectorRandomSearch-6.R
Saving _problems/test_FSelectorRandomSearch-12.R
Saving _problems/test_FSelectorSequential-2.R
Saving _problems/test_FSelectorSequential-11.R
Saving _problems/test_FSelectorSequential-20.R
Saving _problems/test_FSelectorSequential-26.R
Saving _problems/test_FSelectorSequential-32.R
Saving _problems/test_FSelectorSequential-39.R
Saving _problems/test_FSelectorShadowVariableSearch-2.R
Saving _problems/test_FSelectorShadowVariableSearch-14.R
Saving _problems/test_FSelectorShadowVariableSearch-26.R
Saving _problems/test_FSelectorShadowVariableSearch-35.R
Saving _problems/test_FSelectorShadowVariableSearch-54.R
Saving _problems/test_ObjectiveFSelect-15.R
Saving _problems/test_ObjectiveFSelect-35.R
Saving _problems/test_ObjectiveFSelect-54.R
Saving _problems/test_ObjectiveFSelect-74.R
Saving _problems/test_ObjectiveFSelect-126.R
Saving _problems/test_ObjectiveFSelectAsync-15.R
Saving _problems/test_ObjectiveFSelectAsync-37.R
Saving _problems/test_ObjectiveFSelectAsync-61.R
Saving _problems/test_ObjectiveFSelectAsync-85.R
Saving _problems/test_embedded_ensemble_fselect-9.R
Saving _problems/test_embedded_ensemble_fselect-74.R
Saving _problems/test_ensemble_fselect-13.R
Saving _problems/test_ensemble_fselect-108.R
Saving _problems/test_ensemble_fselect-359.R
Saving _problems/test_extract_inner_fselect_archives-3.R
Saving _problems/test_extract_inner_fselect_archives-12.R
Saving _problems/test_extract_inner_fselect_archives-24.R
Saving _problems/test_extract_inner_fselect_archives-37.R
Saving _problems/test_extract_inner_fselect_archives-50.R
Saving _problems/test_extract_inner_fselect_archives-61.R
Saving _problems/test_extract_inner_fselect_archives-70.R
Saving _problems/test_extract_inner_fselect_archives-80.R
Saving _problems/test_extract_inner_fselect_archives-92.R
Saving _problems/test_extract_inner_fselect_archives-104.R
Saving _problems/test_extract_inner_fselect_result-3.R
Saving _problems/test_extract_inner_fselect_result-12.R
Saving _problems/test_extract_inner_fselect_result-24.R
Saving _problems/test_extract_inner_fselect_result-37.R
Saving _problems/test_extract_inner_fselect_result-50.R
Saving _problems/test_extract_inner_fselect_result-61.R
Saving _problems/test_extract_inner_fselect_result-70.R
Saving _problems/test_extract_inner_fselect_result-80.R
Saving _problems/test_extract_inner_fselect_result-92.R
Saving _problems/test_extract_inner_fselect_result-104.R
Saving _problems/test_extract_inner_fselect_result-113.R
Saving _problems/test_extract_inner_fselect_result-125.R
Saving _problems/test_fselect-3.R
Saving _problems/test_fselect-12.R
Saving _problems/test_fselect-21.R
Saving _problems/test_fselect_nested-4.R
Saving _problems/test_mlr_callbacks-12.R
Saving _problems/test_mlr_callbacks-32.R
Saving _problems/test_mlr_callbacks-53.R
Saving _problems/test_mlr_callbacks-73.R
Saving _problems/test_mlr_callbacks-96.R
[ FAIL 100 | WARN 27 | SKIP 52 | PASS 235 ]
══ Skipped tests (52) ══════════════════════════════════════════════════════════
• On CRAN (52): 'test_ArchiveAsyncFSelect.R:2:3',
'test_ArchiveAsyncFSelect.R:51:3', 'test_ArchiveAsyncFSelect.R:107:3',
'test_ArchiveAsyncFSelect.R:133:3', 'test_ArchiveAsyncFSelect.R:155:3',
'test_ArchiveAsyncFSelect.R:181:3', 'test_ArchiveAsyncFSelectFrozen.R:2:3',
'test_AutoFSelector.R:2:3', 'test_AutoFSelector.R:29:3',
'test_AutoFSelector.R:64:3', 'test_AutoFSelector.R:219:3',
'test_CallbackAsyncFSelect.R:4:3', 'test_CallbackAsyncFSelect.R:32:3',
'test_CallbackAsyncFSelect.R:62:3', 'test_CallbackAsyncFSelect.R:90:3',
'test_CallbackAsyncFSelect.R:120:3', 'test_CallbackAsyncFSelect.R:154:3',
'test_CallbackAsyncFSelect.R:181:3', 'test_CallbackAsyncFSelect.R:213:3',
'test_CallbackAsyncFSelect.R:242:3', 'test_CallbackAsyncFSelect.R:269:3',
'test_CallbackAsyncFSelect.R:298:3', 'test_CallbackAsyncFSelect.R:327:3',
'test_CallbackAsyncFSelect.R:354:3', 'test_CallbackAsyncFSelect.R:383:3',
'test_CallbackAsyncFSelect.R:419:3', 'test_CallbackAsyncFSelect.R:454:3',
'test_CallbackAsyncFSelect.R:488:3',
'test_FSelectInstanceAsyncMultiCrit.R:2:3',
'test_FSelectInstanceAsyncMultiCrit.R:30:3',
'test_FSelectInstanceAsyncMultiCrit.R:53:3',
'test_FSelectInstanceAsyncMultiCrit.R:77:3',
'test_FSelectInstanceAsyncMultiCrit.R:101:3',
'test_FSelectInstanceAsyncMultiCrit.R:129:3',
'test_FSelectInstanceAsyncSingleCrit.R:2:3',
'test_FSelectInstanceAsyncSingleCrit.R:29:3',
'test_FSelectInstanceAsyncSingleCrit.R:50:3',
'test_FSelectInstanceAsyncSingleCrit.R:73:3',
'test_FSelectInstanceAsyncSingleCrit.R:98:3',
'test_FSelectInstanceAsyncSingleCrit.R:124:3',
'test_FSelectorAsyncDesignPoints.R:2:3',
'test_FSelectorAsyncExhaustiveSearch.R:2:3',
'test_FSelectorAsyncRandomSearch.R:2:3', 'test_ObjectiveFSelectAsync.R:96:3',
'test_ObjectiveFSelectAsync.R:160:3', 'test_auto_fselector.R:24:3',
'test_auto_fselector.R:47:3', 'test_fsi_async.R:2:3',
'test_fsi_async.R:16:3', 'test_fsi_async.R:30:3', 'test_fsi_async.R:42:3',
'test_mlr_callbacks.R:108:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ArchiveBatchFSelect.R:2:3'): ArchiveBatchFSelect access methods work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:2:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:52:3'): ArchiveBatchFSelect as.data.table function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:52:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:157:3'): global ties method works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:157:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:198:3'): local ties method works when maximize measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:198:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:226:3'): local ties method works when minimize measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:226:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:254:3'): local ties method works with batches ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:254:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_AutoFSelector.R:137:3'): AutoFSelector works with GraphLearner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoFSelector.R:137:3
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 = `<S3: AutoFSelector>`, task = `<S3: TaskRegr>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3fselect:::.__AutoFSelector__.train(...)
12. └─self$fselector$optimize(instance)
13. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
21. └─inst$eval_batch(states)
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test_AutoFSelector.R:166:3'): AutoFSelector get_base_learner method works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─afs$train(tsk("pima")) at test_AutoFSelector.R:166:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<S3: AutoFSelector>`, task = `<S3: TaskClassif>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3fselect:::.__AutoFSelector__.train(...)
12. └─self$fselector$optimize(instance)
13. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
21. └─inst$eval_batch(as.data.table(X))
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test_AutoFSelector.R:211:3'): AutoFSelector hash works #647 in mlr3 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_AutoFSelector.R:211:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_FSelectInstanceMultiCrit.R:16:3'): eval_batch works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceMultiCrit.R:16:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceMultiCrit.R:29:3'): objective_function works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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$objective$eval_many(xss_trafoed)
7. └─bbotk:::.__Objective__eval_many(...)
8. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
9. │ └─base::eval.parent(expr, n = 1L)
10. │ └─base::eval(expr, p)
11. │ └─base::eval(expr, p)
12. └─private$.eval_many(xss = xss, resampling = `<list>`)
13. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
14. └─mlr3::benchmark(...)
15. └─ResultData$new(grid, data_extra, store_backends = store_backends)
16. └─mlr3 (local) initialize(...)
17. └─mlr3:::.__ResultData__initialize(...)
18. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
19. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceMultiCrit.R:37:3'): store_benchmark_result flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceMultiCrit.R:37:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:16:3'): eval_batch works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceSingleCrit.R:16:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:40:3'): objective_function works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$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$eval_batch(xdt)
5. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
6. └─self$objective$eval_many(xss_trafoed)
7. └─bbotk:::.__Objective__eval_many(...)
8. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
9. │ └─base::eval.parent(expr, n = 1L)
10. │ └─base::eval(expr, p)
11. │ └─base::eval(expr, p)
12. └─private$.eval_many(xss = xss, resampling = `<list>`)
13. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
14. └─mlr3::benchmark(...)
15. └─ResultData$new(grid, data_extra, store_backends = store_backends)
16. └─mlr3 (local) initialize(...)
17. └─mlr3:::.__ResultData__initialize(...)
18. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
19. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:48:3'): store_benchmark_result flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceSingleCrit.R:48:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:77:3'): always include variable works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectInstanceSingleCrit.R:77:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:103:3'): always include variables works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectInstanceSingleCrit.R:103:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:131:3'): objective contains no benchmark results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectInstanceSingleCrit.R:131:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
10. └─inst$eval_batch(as.data.table(X))
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorBatchDesignPoints.R:8:3'): default parameters work ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("design_points", design = design) at test_FSelectorBatchDesignPoints.R:8:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
14. └─instance$eval_batch(design[inds, ])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorBatchDesignPoints.R:20:3'): multi-crit works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector_2D("design_points", design = design) at test_FSelectorBatchDesignPoints.R:20:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
14. └─instance$eval_batch(design[inds, ])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:2:3'): default parameters work ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("exhaustive_search") at test_FSelectorExhaustiveSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:14:3'): max_features parameter works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("exhaustive_search", max_features = 2) at test_FSelectorExhaustiveSearch.R:14:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:23:3'): multi-crit works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector_2D("exhaustive_search") at test_FSelectorExhaustiveSearch.R:23:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:27:3'): batch_size parameter works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("exhaustive_search", batch_size = 2) at test_FSelectorExhaustiveSearch.R:27:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorGeneticSearch.R:4:3'): default parameters work ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("genetic_search", term_evals = 10) at test_FSelectorGeneticSearch.R:4:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchGeneticSearch__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─genalg::rbga.bin(...)
17. └─bbotk (local) evalFunc(population[object, ])
18. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
19. └─private$.objective_function(x, self, self$objective_multiplicator)
20. └─inst$eval_batch(xdt)
21. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
22. └─self$objective$eval_many(xss_trafoed)
23. └─bbotk:::.__Objective__eval_many(...)
24. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
25. │ └─base::eval.parent(expr, n = 1L)
26. │ └─base::eval(expr, p)
27. │ └─base::eval(expr, p)
28. └─private$.eval_many(xss = xss, resampling = `<list>`)
29. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
30. └─mlr3::benchmark(...)
31. └─ResultData$new(grid, data_extra, store_backends = store_backends)
32. └─mlr3 (local) initialize(...)
33. └─mlr3:::.__ResultData__initialize(...)
34. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
35. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:2:3'): importance is stored in the archive ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", store_models = TRUE) at test_FSelectorRFE.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:11:3'): default parameters work ─────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", store_models = TRUE) at test_FSelectorRFE.R:11:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:18:3'): recursive parameter works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", recursive = FALSE, store_models = TRUE) at test_FSelectorRFE.R:18:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:27:3'): feature_fraction parameter works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", feature_fraction = 0.9, store_models = TRUE) at test_FSelectorRFE.R:27:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:49:3'): feature_number parameter works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", feature_number = 1, store_models = TRUE) at test_FSelectorRFE.R:49:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:63:3'): subset_size parameter works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:83:3'): subset is full feature set works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", feature_number = 4, store_models = TRUE) at test_FSelectorRFE.R:83:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:131:3'): rank_importance function works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_FSelectorRFE.R:131:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:142:3'): average_importance function works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_FSelectorRFE.R:142:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:154:3'): works without storing models ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectorRFE.R:154:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
11. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:233:3'): optimal features are selected with rank ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFE.R:233:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:290:3'): optimal features are selected with mean ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFE.R:290:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:12:3'): extra columns are stored in the archive ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:12:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:32:3'): resampling is converted ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:32:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:61:3'): default parameters work ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:61:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:118:3'): optimal features are selected ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:118:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRandomSearch.R:2:3'): default parameters work ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("random_search", batch_size = 5, term_evals = 10) at test_FSelectorRandomSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(as.data.table(X))
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRandomSearch.R:6:3'): max_features parameter work ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("random_search", max_features = 1, term_evals = 10) at test_FSelectorRandomSearch.R:6:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(as.data.table(X))
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRandomSearch.R:12:3'): multi-crit works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(as.data.table(X))
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:2:3'): default parameters works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:11:3'): sbs strategy works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential", strategy = "sbs") at test_FSelectorSequential.R:11:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:20:3'): sfs strategy works with max_features parameter ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential", max_features = 2) at test_FSelectorSequential.R:20:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:26:3'): sbs strategy works with max_features parameter ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential", max_features = 2, strategy = "sbs") at test_FSelectorSequential.R:26:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:32:3'): optimization_path method works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:32:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:39:3'): optimization_path method works with included uhash ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:39:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:2:3'): default parameters work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("shadow_variable_search", store_models = TRUE) at test_FSelectorShadowVariableSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:14:3'): task is permuted ───────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:14:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
10. └─inst$eval_batch(states)
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:26:3'): first selected feature is a shadow variable works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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:::.__FSelectorBatch__optimize(...)
9. └─bbotk::optimize_batch_default(inst, self)
10. ├─base::tryCatch(...)
11. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
12. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
13. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
14. └─get_private(optimizer)$.optimize(instance)
15. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
16. └─inst$eval_batch(states)
17. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
18. └─self$objective$eval_many(xss_trafoed)
19. └─bbotk:::.__Objective__eval_many(...)
20. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
21. │ └─base::eval.parent(expr, n = 1L)
22. │ └─base::eval(expr, p)
23. │ └─base::eval(expr, p)
24. └─private$.eval_many(xss = xss, resampling = `<list>`)
25. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
26. └─mlr3::benchmark(...)
27. └─ResultData$new(grid, data_extra, store_backends = store_backends)
28. └─mlr3 (local) initialize(...)
29. └─mlr3:::.__ResultData__initialize(...)
30. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
31. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:35:3'): second selected feature is a shadow variable works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:35:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
10. └─inst$eval_batch(states)
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:54:3'): search is terminated by terminator works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:54:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
10. └─inst$eval_batch(states)
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:15:3'): ObjectiveFSelectBatch ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveFSelect.R:15:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:35:3'): ObjectiveFSelectBatch works with multiple measures ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveFSelect.R:35:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:54:3'): ObjectiveFSelectBatch works with store_models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveFSelect.R:54:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:67:5'): fast aggregation works ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_ObjectiveFSelect.R:66:3
2. │ └─base::force(expr)
3. └─mlr3fselect::fselect(...) at test_ObjectiveFSelect.R:67:5
4. └─fselector$optimize(instance)
5. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(as.data.table(X))
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:119:3'): fast aggregation conditions work ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ObjectiveFSelect.R:119:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:15:3'): objective async works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:15:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:37:3'): store benchmark result works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:37:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:61:3'): store models works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:61:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:85:3'): rush objective with multiple measures works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:85:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_embedded_ensemble_fselect.R:4:5'): embedded efs works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_embedded_ensemble_fselect.R:3:3
2. │ └─base::force(expr)
3. └─mlr3fselect::embedded_ensemble_fselect(...) at test_embedded_ensemble_fselect.R:4:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─ResultData$new(grid, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_embedded_ensemble_fselect.R:69:5'): combine embedded efs results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_embedded_ensemble_fselect.R:68:3
2. │ └─base::force(expr)
3. └─mlr3fselect::embedded_ensemble_fselect(...) at test_embedded_ensemble_fselect.R:69:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─ResultData$new(grid, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_ensemble_fselect.R:4:5'): efs works ────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_ensemble_fselect.R:3:3
2. │ └─base::force(expr)
3. └─mlr3fselect::ensemble_fselect(...) at test_ensemble_fselect.R:4:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─mlr3:::future_map(...)
6. └─future.apply::future_mapply(...)
7. └─future.apply:::future_xapply(...)
8. └─base::tryCatch(...)
9. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. └─base (local) tryCatchOne(...)
11. └─value[[3L]](cond)
12. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_ensemble_fselect.R:99:5'): efs works with rfe ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_ensemble_fselect.R:98:3
2. │ └─base::force(expr)
3. └─mlr3fselect::ensemble_fselect(...) at test_ensemble_fselect.R:99:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─mlr3:::future_map(...)
6. └─future.apply::future_mapply(...)
7. └─future.apply:::future_xapply(...)
8. └─base::tryCatch(...)
9. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. └─base (local) tryCatchOne(...)
11. └─value[[3L]](cond)
12. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_ensemble_fselect.R:349:3'): different callbacks can be set ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::ensemble_fselect(...) at test_ensemble_fselect.R:349:3
2. └─mlr3::benchmark(design, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:2:3'): extract_inner_fselect_archives function works with resample and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:11:3'): extract_inner_fselect_archives function works with resample and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_extract_inner_fselect_archives.R:11:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:24:3'): extract_inner_fselect_archives function works with benchmark and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:37:3'): extract_inner_fselect_archives function works with benchmark and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_archives.R:37:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:50:3'): extract_inner_fselect_archives function works with multiple tasks ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:61:3'): extract_inner_fselect_archives function works with no models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, resampling_outer, store_models = FALSE) at test_extract_inner_fselect_archives.R:61:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:70:3'): extract_inner_fselect_archives function works with no instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:80:3'): extract_inner_fselect_archives function works with benchmark and no models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = FALSE) at test_extract_inner_fselect_archives.R:80:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:92:3'): extract_inner_fselect_archives function works with mixed store instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:104:3'): extract_inner_fselect_archives function works with autofselector and learner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_archives.R:104:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:2:3'): extract_inner_fselect_results function works with resample and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:11:3'): extract_inner_fselect_results function works with resample and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_extract_inner_fselect_result.R:11:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:24:3'): extract_inner_fselect_results function works with benchmark and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:37:3'): extract_inner_fselect_results function works with benchmark and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:37:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:50:3'): extract_inner_fselect_results function works with multiple tasks ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:61:3'): extract_inner_fselect_results function works with no model ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, resampling_outer, store_models = FALSE) at test_extract_inner_fselect_result.R:61:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:70:3'): extract_inner_fselect_results function works no instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:80:3'): extract_inner_fselect_results function works with benchmark and no models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = FALSE) at test_extract_inner_fselect_result.R:80:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:92:3'): extract_inner_fselect_results function works with mixed store instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:104:3'): extract_inner_fselect_results function works with learner and autotuner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:104:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:113:3'): extract_inner_fselect_results function works with resample and return of instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:125:3'): extract_inner_fselect_results function works with benchmark and return of instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:125:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_fselect.R:2:3'): fselect function works with single measure ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:2:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_fselect.R:11:3'): fselect function works with multiple measures ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:11:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_fselect.R:20:3'): fselect function accepts string input for method ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:20:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_fselect_nested.R:2:3'): fselect_nested function works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_mlr_callbacks.R:4:3'): backup callback works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:4:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:23:3'): svm_rfe callbacks works ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:23:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
11. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:46:3'): one_se_rule callback works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:46:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
11. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
12. └─mlr3fselect (local) .f(.xi, ...)
13. └─inst$eval_batch(states[row_ids])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:65:3'): internal tuning callback works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:65:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:96:3'): internal tuning callback works with AutoFSelector ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─afs$train(tsk("pima")) at test_mlr_callbacks.R:96:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<S3: AutoFSelector>`, task = `<S3: TaskClassif>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3fselect:::.__AutoFSelector__.train(...)
12. └─self$fselector$optimize(instance)
13. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
21. └─inst$eval_batch(as.data.table(X))
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
[ FAIL 100 | WARN 27 | SKIP 52 | PASS 235 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.5.0
Check: examples
Result: ERROR
Running examples in ‘mlr3fselect-Ex.R’ failed
The error most likely occurred in:
> ### Name: auto_fselector
> ### Title: Function for Automatic Feature Selection
> ### Aliases: auto_fselector
>
> ### ** Examples
>
> afs = auto_fselector(
+ fselector = fs("random_search"),
+ learner = lrn("classif.rpart"),
+ resampling = rsmp("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 4)
>
> afs$train(tsk("pima"))
INFO [12:29:22.914] [bbotk] Starting to optimize 8 parameter(s) with '<FSelectorBatchRandomSearch>' and '<TerminatorEvals> [n_evals=4, k=0]'
INFO [12:29:23.023] [bbotk] Evaluating 10 configuration(s)
INFO [12:29:23.187] [mlr3] Running benchmark with 10 resampling iterations
INFO [12:29:23.487] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [12:29:23.676] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [12:29:23.785] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [12:29:23.840] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [12:29:23.905] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [12:29:23.970] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [12:29:24.037] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [12:29:24.095] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [12:29:24.152] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [12:29:24.235] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [12:29:24.306] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: <Anonymous> ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.5.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [232s/305s]
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
Attaching package: 'data.table'
The following object is masked from 'package:base':
%notin%
Saving _problems/test_ArchiveBatchFSelect-8.R
Saving _problems/test_ArchiveBatchFSelect-58.R
Saving _problems/test_ArchiveBatchFSelect-164.R
Saving _problems/test_ArchiveBatchFSelect-204.R
Saving _problems/test_ArchiveBatchFSelect-232.R
Saving _problems/test_ArchiveBatchFSelect-260.R
Saving _problems/test_AutoFSelector-137.R
Saving _problems/test_AutoFSelector-166.R
Saving _problems/test_AutoFSelector-211.R
Saving _problems/test_FSelectInstanceMultiCrit-16.R
Saving _problems/test_FSelectInstanceMultiCrit-29.R
Saving _problems/test_FSelectInstanceMultiCrit-37.R
Saving _problems/test_FSelectInstanceSingleCrit-16.R
Saving _problems/test_FSelectInstanceSingleCrit-40.R
Saving _problems/test_FSelectInstanceSingleCrit-48.R
Saving _problems/test_FSelectInstanceSingleCrit-85.R
Saving _problems/test_FSelectInstanceSingleCrit-111.R
Saving _problems/test_FSelectInstanceSingleCrit-131.R
Saving _problems/test_FSelectorBatchDesignPoints-8.R
Saving _problems/test_FSelectorBatchDesignPoints-20.R
Saving _problems/test_FSelectorExhaustiveSearch-2.R
Saving _problems/test_FSelectorExhaustiveSearch-14.R
Saving _problems/test_FSelectorExhaustiveSearch-23.R
Saving _problems/test_FSelectorExhaustiveSearch-27.R
Saving _problems/test_FSelectorGeneticSearch-4.R
Saving _problems/test_FSelectorRFE-2.R
Saving _problems/test_FSelectorRFE-11.R
Saving _problems/test_FSelectorRFE-18.R
Saving _problems/test_FSelectorRFE-27.R
Saving _problems/test_FSelectorRFE-49.R
Saving _problems/test_FSelectorRFE-63.R
Saving _problems/test_FSelectorRFE-83.R
Saving _problems/test_FSelectorRFE-131.R
Saving _problems/test_FSelectorRFE-142.R
Saving _problems/test_FSelectorRFE-161.R
Saving _problems/test_FSelectorRFE-233.R
Saving _problems/test_FSelectorRFE-290.R
Saving _problems/test_FSelectorRFECV-12.R
Saving _problems/test_FSelectorRFECV-32.R
Saving _problems/test_FSelectorRFECV-61.R
Saving _problems/test_FSelectorRFECV-118.R
Saving _problems/test_FSelectorRandomSearch-2.R
Saving _problems/test_FSelectorRandomSearch-6.R
Saving _problems/test_FSelectorRandomSearch-12.R
Saving _problems/test_FSelectorSequential-2.R
Saving _problems/test_FSelectorSequential-11.R
Saving _problems/test_FSelectorSequential-20.R
Saving _problems/test_FSelectorSequential-26.R
Saving _problems/test_FSelectorSequential-32.R
Saving _problems/test_FSelectorSequential-39.R
Saving _problems/test_FSelectorShadowVariableSearch-2.R
Saving _problems/test_FSelectorShadowVariableSearch-14.R
Saving _problems/test_FSelectorShadowVariableSearch-26.R
Saving _problems/test_FSelectorShadowVariableSearch-35.R
Saving _problems/test_FSelectorShadowVariableSearch-54.R
Saving _problems/test_ObjectiveFSelect-15.R
Saving _problems/test_ObjectiveFSelect-35.R
Saving _problems/test_ObjectiveFSelect-54.R
Saving _problems/test_ObjectiveFSelect-74.R
Saving _problems/test_ObjectiveFSelect-126.R
Saving _problems/test_ObjectiveFSelectAsync-15.R
Saving _problems/test_ObjectiveFSelectAsync-37.R
Saving _problems/test_ObjectiveFSelectAsync-61.R
Saving _problems/test_ObjectiveFSelectAsync-85.R
Saving _problems/test_embedded_ensemble_fselect-9.R
Saving _problems/test_embedded_ensemble_fselect-74.R
Saving _problems/test_ensemble_fselect-13.R
Saving _problems/test_ensemble_fselect-108.R
Saving _problems/test_ensemble_fselect-359.R
Saving _problems/test_extract_inner_fselect_archives-3.R
Saving _problems/test_extract_inner_fselect_archives-12.R
Saving _problems/test_extract_inner_fselect_archives-24.R
Saving _problems/test_extract_inner_fselect_archives-37.R
Saving _problems/test_extract_inner_fselect_archives-50.R
Saving _problems/test_extract_inner_fselect_archives-61.R
Saving _problems/test_extract_inner_fselect_archives-70.R
Saving _problems/test_extract_inner_fselect_archives-80.R
Saving _problems/test_extract_inner_fselect_archives-92.R
Saving _problems/test_extract_inner_fselect_archives-104.R
Saving _problems/test_extract_inner_fselect_result-3.R
Saving _problems/test_extract_inner_fselect_result-12.R
Saving _problems/test_extract_inner_fselect_result-24.R
Saving _problems/test_extract_inner_fselect_result-37.R
Saving _problems/test_extract_inner_fselect_result-50.R
Saving _problems/test_extract_inner_fselect_result-61.R
Saving _problems/test_extract_inner_fselect_result-70.R
Saving _problems/test_extract_inner_fselect_result-80.R
Saving _problems/test_extract_inner_fselect_result-92.R
Saving _problems/test_extract_inner_fselect_result-104.R
Saving _problems/test_extract_inner_fselect_result-113.R
Saving _problems/test_extract_inner_fselect_result-125.R
Saving _problems/test_fselect-3.R
Saving _problems/test_fselect-12.R
Saving _problems/test_fselect-21.R
Saving _problems/test_fselect_nested-4.R
Saving _problems/test_mlr_callbacks-12.R
Saving _problems/test_mlr_callbacks-32.R
Saving _problems/test_mlr_callbacks-53.R
Saving _problems/test_mlr_callbacks-73.R
Saving _problems/test_mlr_callbacks-96.R
[ FAIL 100 | WARN 27 | SKIP 52 | PASS 235 ]
══ Skipped tests (52) ══════════════════════════════════════════════════════════
• On CRAN (52): 'test_ArchiveAsyncFSelect.R:2:3',
'test_ArchiveAsyncFSelect.R:51:3', 'test_ArchiveAsyncFSelect.R:107:3',
'test_ArchiveAsyncFSelect.R:133:3', 'test_ArchiveAsyncFSelect.R:155:3',
'test_ArchiveAsyncFSelect.R:181:3', 'test_ArchiveAsyncFSelectFrozen.R:2:3',
'test_AutoFSelector.R:2:3', 'test_AutoFSelector.R:29:3',
'test_AutoFSelector.R:64:3', 'test_AutoFSelector.R:219:3',
'test_CallbackAsyncFSelect.R:4:3', 'test_CallbackAsyncFSelect.R:32:3',
'test_CallbackAsyncFSelect.R:62:3', 'test_CallbackAsyncFSelect.R:90:3',
'test_CallbackAsyncFSelect.R:120:3', 'test_CallbackAsyncFSelect.R:154:3',
'test_CallbackAsyncFSelect.R:181:3', 'test_CallbackAsyncFSelect.R:213:3',
'test_CallbackAsyncFSelect.R:242:3', 'test_CallbackAsyncFSelect.R:269:3',
'test_CallbackAsyncFSelect.R:298:3', 'test_CallbackAsyncFSelect.R:327:3',
'test_CallbackAsyncFSelect.R:354:3', 'test_CallbackAsyncFSelect.R:383:3',
'test_CallbackAsyncFSelect.R:419:3', 'test_CallbackAsyncFSelect.R:454:3',
'test_CallbackAsyncFSelect.R:488:3',
'test_FSelectInstanceAsyncMultiCrit.R:2:3',
'test_FSelectInstanceAsyncMultiCrit.R:30:3',
'test_FSelectInstanceAsyncMultiCrit.R:53:3',
'test_FSelectInstanceAsyncMultiCrit.R:77:3',
'test_FSelectInstanceAsyncMultiCrit.R:101:3',
'test_FSelectInstanceAsyncMultiCrit.R:129:3',
'test_FSelectInstanceAsyncSingleCrit.R:2:3',
'test_FSelectInstanceAsyncSingleCrit.R:29:3',
'test_FSelectInstanceAsyncSingleCrit.R:50:3',
'test_FSelectInstanceAsyncSingleCrit.R:73:3',
'test_FSelectInstanceAsyncSingleCrit.R:98:3',
'test_FSelectInstanceAsyncSingleCrit.R:124:3',
'test_FSelectorAsyncDesignPoints.R:2:3',
'test_FSelectorAsyncExhaustiveSearch.R:2:3',
'test_FSelectorAsyncRandomSearch.R:2:3', 'test_ObjectiveFSelectAsync.R:96:3',
'test_ObjectiveFSelectAsync.R:160:3', 'test_auto_fselector.R:24:3',
'test_auto_fselector.R:47:3', 'test_fsi_async.R:2:3',
'test_fsi_async.R:16:3', 'test_fsi_async.R:30:3', 'test_fsi_async.R:42:3',
'test_mlr_callbacks.R:108:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ArchiveBatchFSelect.R:2:3'): ArchiveBatchFSelect access methods work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:2:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:52:3'): ArchiveBatchFSelect as.data.table function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:52:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:157:3'): global ties method works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:157:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:198:3'): local ties method works when maximize measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:198:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:226:3'): local ties method works when minimize measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:226:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchFSelect.R:254:3'): local ties method works with batches ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ArchiveBatchFSelect.R:254:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_AutoFSelector.R:137:3'): AutoFSelector works with GraphLearner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoFSelector.R:137:3
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 = `<TaskRegr>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3fselect:::.__AutoFSelector__.train(...)
12. └─self$fselector$optimize(instance)
13. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
21. └─inst$eval_batch(states)
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test_AutoFSelector.R:166:3'): AutoFSelector get_base_learner method works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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:::.__FSelectorBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
21. └─inst$eval_batch(as.data.table(X))
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test_AutoFSelector.R:211:3'): AutoFSelector hash works #647 in mlr3 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_AutoFSelector.R:211:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_FSelectInstanceMultiCrit.R:16:3'): eval_batch works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceMultiCrit.R:16:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceMultiCrit.R:29:3'): objective_function works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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$objective$eval_many(xss_trafoed)
7. └─bbotk:::.__Objective__eval_many(...)
8. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
9. │ └─base::eval.parent(expr, n = 1L)
10. │ └─base::eval(expr, p)
11. │ └─base::eval(expr, p)
12. └─private$.eval_many(xss = xss, resampling = `<list>`)
13. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
14. └─mlr3::benchmark(...)
15. └─ResultData$new(grid, data_extra, store_backends = store_backends)
16. └─mlr3 (local) initialize(...)
17. └─mlr3:::.__ResultData__initialize(...)
18. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
19. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceMultiCrit.R:37:3'): store_benchmark_result flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceMultiCrit.R:37:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:16:3'): eval_batch works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceSingleCrit.R:16:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:40:3'): objective_function works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$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$eval_batch(xdt)
5. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
6. └─self$objective$eval_many(xss_trafoed)
7. └─bbotk:::.__Objective__eval_many(...)
8. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
9. │ └─base::eval.parent(expr, n = 1L)
10. │ └─base::eval(expr, p)
11. │ └─base::eval(expr, p)
12. └─private$.eval_many(xss = xss, resampling = `<list>`)
13. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
14. └─mlr3::benchmark(...)
15. └─ResultData$new(grid, data_extra, store_backends = store_backends)
16. └─mlr3 (local) initialize(...)
17. └─mlr3:::.__ResultData__initialize(...)
18. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
19. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:48:3'): store_benchmark_result flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(xdt) at test_FSelectInstanceSingleCrit.R:48:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:77:3'): always include variable works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectInstanceSingleCrit.R:77:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:103:3'): always include variables works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectInstanceSingleCrit.R:103:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectInstanceSingleCrit.R:131:3'): objective contains no benchmark results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectInstanceSingleCrit.R:131:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
10. └─inst$eval_batch(as.data.table(X))
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorBatchDesignPoints.R:8:3'): default parameters work ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("design_points", design = design) at test_FSelectorBatchDesignPoints.R:8:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
14. └─instance$eval_batch(design[inds, ])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorBatchDesignPoints.R:20:3'): multi-crit works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector_2D("design_points", design = design) at test_FSelectorBatchDesignPoints.R:20:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
14. └─instance$eval_batch(design[inds, ])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:2:3'): default parameters work ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("exhaustive_search") at test_FSelectorExhaustiveSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:14:3'): max_features parameter works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("exhaustive_search", max_features = 2) at test_FSelectorExhaustiveSearch.R:14:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:23:3'): multi-crit works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector_2D("exhaustive_search") at test_FSelectorExhaustiveSearch.R:23:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorExhaustiveSearch.R:27:3'): batch_size parameter works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("exhaustive_search", batch_size = 2) at test_FSelectorExhaustiveSearch.R:27:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
12. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
13. └─mlr3fselect (local) .f(.xi, ...)
14. └─inst$eval_batch(states[row_ids])
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorGeneticSearch.R:4:3'): default parameters work ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("genetic_search", term_evals = 10) at test_FSelectorGeneticSearch.R:4:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchGeneticSearch__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─genalg::rbga.bin(...)
17. └─bbotk (local) evalFunc(population[object, ])
18. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
19. └─private$.objective_function(x, self, self$objective_multiplicator)
20. └─inst$eval_batch(xdt)
21. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
22. └─self$objective$eval_many(xss_trafoed)
23. └─bbotk:::.__Objective__eval_many(...)
24. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
25. │ └─base::eval.parent(expr, n = 1L)
26. │ └─base::eval(expr, p)
27. │ └─base::eval(expr, p)
28. └─private$.eval_many(xss = xss, resampling = `<list>`)
29. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
30. └─mlr3::benchmark(...)
31. └─ResultData$new(grid, data_extra, store_backends = store_backends)
32. └─mlr3 (local) initialize(...)
33. └─mlr3:::.__ResultData__initialize(...)
34. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
35. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:2:3'): importance is stored in the archive ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", store_models = TRUE) at test_FSelectorRFE.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:11:3'): default parameters work ─────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", store_models = TRUE) at test_FSelectorRFE.R:11:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:18:3'): recursive parameter works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", recursive = FALSE, store_models = TRUE) at test_FSelectorRFE.R:18:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:27:3'): feature_fraction parameter works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", feature_fraction = 0.9, store_models = TRUE) at test_FSelectorRFE.R:27:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:49:3'): feature_number parameter works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", feature_number = 1, store_models = TRUE) at test_FSelectorRFE.R:49:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:63:3'): subset_size parameter works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:83:3'): subset is full feature set works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("rfe", feature_number = 4, store_models = TRUE) at test_FSelectorRFE.R:83:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
12. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
13. └─inst$eval_batch(states)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:131:3'): rank_importance function works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_FSelectorRFE.R:131:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:142:3'): average_importance function works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("cv", folds = 3), store_models = TRUE) at test_FSelectorRFE.R:142:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:154:3'): works without storing models ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_FSelectorRFE.R:154:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
11. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:233:3'): optimal features are selected with rank ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFE.R:233:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFE.R:290:3'): optimal features are selected with mean ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFE.R:290:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:12:3'): extra columns are stored in the archive ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:12:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:32:3'): resampling is converted ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:32:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:61:3'): default parameters work ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:61:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRFECV.R:118:3'): optimal features are selected ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─optimizer$optimize(instance) at test_FSelectorRFECV.R:118:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchRFECV__.optimize(...)
10. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, folds = resampling_cv$iters)
11. └─inst$eval_batch(states)
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRandomSearch.R:2:3'): default parameters work ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("random_search", batch_size = 5, term_evals = 10) at test_FSelectorRandomSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(as.data.table(X))
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRandomSearch.R:6:3'): max_features parameter work ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("random_search", max_features = 1, term_evals = 10) at test_FSelectorRandomSearch.R:6:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(as.data.table(X))
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorRandomSearch.R:12:3'): multi-crit works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(as.data.table(X))
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:2:3'): default parameters works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:11:3'): sbs strategy works ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential", strategy = "sbs") at test_FSelectorSequential.R:11:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:20:3'): sfs strategy works with max_features parameter ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential", max_features = 2) at test_FSelectorSequential.R:20:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:26:3'): sbs strategy works with max_features parameter ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential", max_features = 2, strategy = "sbs") at test_FSelectorSequential.R:26:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:32:3'): optimization_path method works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:32:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorSequential.R:39:3'): optimization_path method works with included uhash ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("sequential") at test_FSelectorSequential.R:39:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchSequential__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:2:3'): default parameters work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_fselector("shadow_variable_search", store_models = TRUE) at test_FSelectorShadowVariableSearch.R:2:3
2. └─mlr3fselect::fselect(...)
3. └─fselector$optimize(instance)
4. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:14:3'): task is permuted ───────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:14:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
10. └─inst$eval_batch(states)
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:26:3'): first selected feature is a shadow variable works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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:::.__FSelectorBatch__optimize(...)
9. └─bbotk::optimize_batch_default(inst, self)
10. ├─base::tryCatch(...)
11. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
12. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
13. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
14. └─get_private(optimizer)$.optimize(instance)
15. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
16. └─inst$eval_batch(states)
17. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
18. └─self$objective$eval_many(xss_trafoed)
19. └─bbotk:::.__Objective__eval_many(...)
20. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
21. │ └─base::eval.parent(expr, n = 1L)
22. │ └─base::eval(expr, p)
23. │ └─base::eval(expr, p)
24. └─private$.eval_many(xss = xss, resampling = `<list>`)
25. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
26. └─mlr3::benchmark(...)
27. └─ResultData$new(grid, data_extra, store_backends = store_backends)
28. └─mlr3 (local) initialize(...)
29. └─mlr3:::.__ResultData__initialize(...)
30. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
31. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:35:3'): second selected feature is a shadow variable works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:35:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
10. └─inst$eval_batch(states)
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_FSelectorShadowVariableSearch.R:54:3'): search is terminated by terminator works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─fselector$optimize(instance) at test_FSelectorShadowVariableSearch.R:54:3
2. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3fselect:::.__FSelectorBatchShadowVariableSearch__.optimize(...)
10. └─inst$eval_batch(states)
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(xss_trafoed)
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:15:3'): ObjectiveFSelectBatch ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveFSelect.R:15:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:35:3'): ObjectiveFSelectBatch works with multiple measures ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveFSelect.R:35:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:54:3'): ObjectiveFSelectBatch works with store_models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveFSelect.R:54:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:67:5'): fast aggregation works ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_ObjectiveFSelect.R:66:3
2. │ └─base::force(expr)
3. └─mlr3fselect::fselect(...) at test_ObjectiveFSelect.R:67:5
4. └─fselector$optimize(instance)
5. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(as.data.table(X))
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelect.R:119:3'): fast aggregation conditions work ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_ObjectiveFSelect.R:119:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:15:3'): objective async works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:15:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:37:3'): store benchmark result works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:37:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:61:3'): store models works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:61:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveFSelectAsync.R:85:3'): rush objective with multiple measures works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveFSelectAsync.R:85:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3fselect:::.__ObjectiveFSelectAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_embedded_ensemble_fselect.R:4:5'): embedded efs works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_embedded_ensemble_fselect.R:3:3
2. │ └─base::force(expr)
3. └─mlr3fselect::embedded_ensemble_fselect(...) at test_embedded_ensemble_fselect.R:4:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─ResultData$new(grid, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_embedded_ensemble_fselect.R:69:5'): combine embedded efs results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_embedded_ensemble_fselect.R:68:3
2. │ └─base::force(expr)
3. └─mlr3fselect::embedded_ensemble_fselect(...) at test_embedded_ensemble_fselect.R:69:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─ResultData$new(grid, data_extra, store_backends = store_backends)
6. └─mlr3 (local) initialize(...)
7. └─mlr3:::.__ResultData__initialize(...)
8. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
9. └─data.table:::`[.data.table`(...)
── Error ('test_ensemble_fselect.R:4:5'): efs works ────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_ensemble_fselect.R:3:3
2. │ └─base::force(expr)
3. └─mlr3fselect::ensemble_fselect(...) at test_ensemble_fselect.R:4:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─mlr3:::future_map(...)
6. └─future.apply::future_mapply(...)
7. └─future.apply:::future_xapply(...)
8. └─base::tryCatch(...)
9. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. └─base (local) tryCatchOne(...)
11. └─value[[3L]](cond)
12. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_ensemble_fselect.R:99:5'): efs works with rfe ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global with_seed(...) at test_ensemble_fselect.R:98:3
2. │ └─base::force(expr)
3. └─mlr3fselect::ensemble_fselect(...) at test_ensemble_fselect.R:99:5
4. └─mlr3::benchmark(design, store_models = TRUE)
5. └─mlr3:::future_map(...)
6. └─future.apply::future_mapply(...)
7. └─future.apply:::future_xapply(...)
8. └─base::tryCatch(...)
9. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. └─base (local) tryCatchOne(...)
11. └─value[[3L]](cond)
12. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_ensemble_fselect.R:349:3'): different callbacks can be set ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::ensemble_fselect(...) at test_ensemble_fselect.R:349:3
2. └─mlr3::benchmark(design, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:2:3'): extract_inner_fselect_archives function works with resample and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:11:3'): extract_inner_fselect_archives function works with resample and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_extract_inner_fselect_archives.R:11:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:24:3'): extract_inner_fselect_archives function works with benchmark and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:37:3'): extract_inner_fselect_archives function works with benchmark and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_archives.R:37:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:50:3'): extract_inner_fselect_archives function works with multiple tasks ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:61:3'): extract_inner_fselect_archives function works with no models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, resampling_outer, store_models = FALSE) at test_extract_inner_fselect_archives.R:61:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:70:3'): extract_inner_fselect_archives function works with no instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:80:3'): extract_inner_fselect_archives function works with benchmark and no models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = FALSE) at test_extract_inner_fselect_archives.R:80:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:92:3'): extract_inner_fselect_archives function works with mixed store instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_archives.R:104:3'): extract_inner_fselect_archives function works with autofselector and learner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_archives.R:104:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:2:3'): extract_inner_fselect_results function works with resample and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:11:3'): extract_inner_fselect_results function works with resample and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect_nested(...) at test_extract_inner_fselect_result.R:11:3
2. └─mlr3::resample(task, afs, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:24:3'): extract_inner_fselect_results function works with benchmark and cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:37:3'): extract_inner_fselect_results function works with benchmark and repeated cv ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:37:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:50:3'): extract_inner_fselect_results function works with multiple tasks ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:61:3'): extract_inner_fselect_results function works with no model ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, resampling_outer, store_models = FALSE) at test_extract_inner_fselect_result.R:61:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:70:3'): extract_inner_fselect_results function works no instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:80:3'): extract_inner_fselect_results function works with benchmark and no models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = FALSE) at test_extract_inner_fselect_result.R:80:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:92:3'): extract_inner_fselect_results function works with mixed store instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:104:3'): extract_inner_fselect_results function works with learner and autotuner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:104:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:113:3'): extract_inner_fselect_results function works with resample and return of instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_fselect_result.R:125:3'): extract_inner_fselect_results function works with benchmark and return of instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_extract_inner_fselect_result.R:125:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_fselect.R:2:3'): fselect function works with single measure ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:2:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_fselect.R:11:3'): fselect function works with multiple measures ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:11:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_fselect.R:20:3'): fselect function accepts string input for method ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_fselect.R:20:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_fselect_nested.R:2:3'): fselect_nested function works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_mlr_callbacks.R:4:3'): backup callback works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:4:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:23:3'): svm_rfe callbacks works ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:23:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRFE__.optimize(...)
11. └─mlr3fselect:::rfe_workhorse(inst, subsets, recursive, aggregation)
12. └─inst$eval_batch(states)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:46:3'): one_se_rule callback works ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:46:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchExhaustiveSearch__.optimize(...)
11. └─mlr3misc::walk(chunks, function(row_ids) inst$eval_batch(states[row_ids]))
12. └─mlr3fselect (local) .f(.xi, ...)
13. └─inst$eval_batch(states[row_ids])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:65:3'): internal tuning callback works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3fselect::fselect(...) at test_mlr_callbacks.R:65:3
2. └─fselector$optimize(instance)
3. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
4. └─bbotk::optimize_batch_default(inst, self)
5. ├─base::tryCatch(...)
6. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
8. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
9. └─get_private(optimizer)$.optimize(instance)
10. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
11. └─inst$eval_batch(as.data.table(X))
12. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
13. └─self$objective$eval_many(xss_trafoed)
14. └─bbotk:::.__Objective__eval_many(...)
15. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
16. │ └─base::eval.parent(expr, n = 1L)
17. │ └─base::eval(expr, p)
18. │ └─base::eval(expr, p)
19. └─private$.eval_many(xss = xss, resampling = `<list>`)
20. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
21. └─mlr3::benchmark(...)
22. └─ResultData$new(grid, data_extra, store_backends = store_backends)
23. └─mlr3 (local) initialize(...)
24. └─mlr3:::.__ResultData__initialize(...)
25. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
26. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:96:3'): internal tuning callback works with AutoFSelector ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─afs$train(tsk("pima")) at test_mlr_callbacks.R:96:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AtFSlctr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3fselect:::.__AutoFSelector__.train(...)
12. └─self$fselector$optimize(instance)
13. └─mlr3fselect:::.__FSelectorBatch__optimize(...)
14. └─bbotk::optimize_batch_default(inst, self)
15. ├─base::tryCatch(...)
16. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
17. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
18. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
19. └─get_private(optimizer)$.optimize(instance)
20. └─mlr3fselect:::.__FSelectorBatchRandomSearch__.optimize(...)
21. └─inst$eval_batch(as.data.table(X))
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3fselect:::.__ObjectiveFSelectBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
[ FAIL 100 | WARN 27 | SKIP 52 | PASS 235 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Current CRAN status: ERROR: 4, OK: 9
Version: 1.0.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [76s/89s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3hyperband")
+ test_check("mlr3hyperband")
+ }
Loading required package: mlr3tuning
Loading required package: mlr3
Loading required package: paradox
Saving _problems/test_TunerBatchHyperband-7.R
Saving _problems/test_TunerBatchHyperband-16.R
Saving _problems/test_TunerBatchHyperband-25.R
Saving _problems/test_TunerBatchHyperband-34.R
Saving _problems/test_TunerBatchHyperband-47.R
Saving _problems/test_TunerBatchHyperband-58.R
Saving _problems/test_TunerBatchHyperband-68.R
Saving _problems/test_TunerBatchHyperband-82.R
Saving _problems/test_TunerBatchHyperband-167.R
Saving _problems/test_TunerBatchHyperband-178.R
Saving _problems/test_TunerBatchHyperband-189.R
Saving _problems/test_TunerBatchHyperband-203.R
Saving _problems/test_TunerBatchHyperband-219.R
Saving _problems/test_TunerBatchHyperband-236.R
Saving _problems/test_TunerBatchSuccessiveHalving-7.R
Saving _problems/test_TunerBatchSuccessiveHalving-16.R
Saving _problems/test_TunerBatchSuccessiveHalving-25.R
Saving _problems/test_TunerBatchSuccessiveHalving-34.R
Saving _problems/test_TunerBatchSuccessiveHalving-43.R
Saving _problems/test_TunerBatchSuccessiveHalving-65.R
Saving _problems/test_TunerBatchSuccessiveHalving-76.R
Saving _problems/test_TunerBatchSuccessiveHalving-85.R
Saving _problems/test_TunerBatchSuccessiveHalving-96.R
Saving _problems/test_TunerBatchSuccessiveHalving-181.R
Saving _problems/test_TunerBatchSuccessiveHalving-191.R
Saving _problems/test_TunerBatchSuccessiveHalving-201.R
Saving _problems/test_TunerBatchSuccessiveHalving-215.R
Saving _problems/test_TunerBatchSuccessiveHalving-231.R
Saving _problems/test_TunerBatchSuccessiveHalving-248.R
Saving _problems/test_TunerBatchSuccessiveHalving-259.R
Saving _problems/test_TunerBatchSuccessiveHalving-268.R
Saving _problems/test_TunerBatchSuccessiveHalving-277.R
[ FAIL 32 | WARN 0 | SKIP 1 | PASS 36 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test_TunerAsyncSuccessiveHalving.R:1:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_TunerBatchHyperband.R:7:3'): TunerBatchHyperband works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:7:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:16:3'): TunerBatchHyperband works with minimum budget > 1 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:16:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:25:3'): TunerBatchHyperband rounds budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:25:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:34:3'): TunerBatchHyperband works with eta = 2.5 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2.5, learner) at test_TunerBatchHyperband.R:34:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:47:3'): TunerBatchHyperband works with xgboost ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:47:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:58:3'): TunerBatchHyperband works with subsampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 3, graph_learner) at test_TunerBatchHyperband.R:58:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:68:3'): TunerBatchHyperband works works with multi-crit ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:68:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:82:3'): TunerBatchHyperband works with custom sampler ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner, sampler = sampler) at test_TunerBatchHyperband.R:82:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:167:3'): TunerBatchHyperband minimizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:167:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:178:3'): TunerBatchHyperband maximizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:178:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:189:3'): TunerBatchHyperband works with single budget value ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:189:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:198:3'): TunerBatchHyperband works with repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:198:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:214:3'): TunerBatchHyperband terminates itself ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:214:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:230:3'): TunerBatchHyperband works with infinite repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:230:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:7:3'): TunerBatchSuccessiveHalving works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:7:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:16:3'): TunerBatchSuccessiveHalving works with minimum budget > 1 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:16:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:25:3'): TunerBatchSuccessiveHalving rounds budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:25:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:34:3'): TunerBatchSuccessiveHalving works with eta = 2.5 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:34:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:43:3'): TunerBatchSuccessiveHalving adjusts minimum budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:43:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:65:3'): TunerBatchSuccessiveHalving works with xgboost ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:65:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:76:3'): TunerBatchSuccessiveHalving works with subsampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:76:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:85:3'): TunerBatchSuccessiveHalving works with multi-crit ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:85:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:96:3'): TunerBatchSuccessiveHalving works with custom sampler ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:96:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:181:3'): TunerBatchSuccessiveHalving minimizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:181:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:191:3'): TunerBatchSuccessiveHalving maximizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:191:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:201:3'): TunerBatchSuccessiveHalving works with single budget value ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:201:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:210:3'): TunerBatchSuccessiveHalving works with repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:210:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:226:3'): TunerBatchSuccessiveHalving terminates itself ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:226:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:242:3'): TunerBatchSuccessiveHalving works with infinite repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:242:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:259:3'): TunerBatchSuccessiveHalving works with r_max > n ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:259:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:268:3'): TunerBatchSuccessiveHalving works with r_max < n ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:268:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:277:3'): TunerBatchSuccessiveHalving works with r_max < n and adjust minimum budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:277:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
[ FAIL 32 | WARN 0 | SKIP 1 | PASS 36 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.0.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [54s/73s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3hyperband")
+ test_check("mlr3hyperband")
+ }
Loading required package: mlr3tuning
Loading required package: mlr3
Loading required package: paradox
Saving _problems/test_TunerBatchHyperband-7.R
Saving _problems/test_TunerBatchHyperband-16.R
Saving _problems/test_TunerBatchHyperband-25.R
Saving _problems/test_TunerBatchHyperband-34.R
Saving _problems/test_TunerBatchHyperband-47.R
Saving _problems/test_TunerBatchHyperband-58.R
Saving _problems/test_TunerBatchHyperband-68.R
Saving _problems/test_TunerBatchHyperband-82.R
Saving _problems/test_TunerBatchHyperband-167.R
Saving _problems/test_TunerBatchHyperband-178.R
Saving _problems/test_TunerBatchHyperband-189.R
Saving _problems/test_TunerBatchHyperband-203.R
Saving _problems/test_TunerBatchHyperband-219.R
Saving _problems/test_TunerBatchHyperband-236.R
Saving _problems/test_TunerBatchSuccessiveHalving-7.R
Saving _problems/test_TunerBatchSuccessiveHalving-16.R
Saving _problems/test_TunerBatchSuccessiveHalving-25.R
Saving _problems/test_TunerBatchSuccessiveHalving-34.R
Saving _problems/test_TunerBatchSuccessiveHalving-43.R
Saving _problems/test_TunerBatchSuccessiveHalving-65.R
Saving _problems/test_TunerBatchSuccessiveHalving-76.R
Saving _problems/test_TunerBatchSuccessiveHalving-85.R
Saving _problems/test_TunerBatchSuccessiveHalving-96.R
Saving _problems/test_TunerBatchSuccessiveHalving-181.R
Saving _problems/test_TunerBatchSuccessiveHalving-191.R
Saving _problems/test_TunerBatchSuccessiveHalving-201.R
Saving _problems/test_TunerBatchSuccessiveHalving-215.R
Saving _problems/test_TunerBatchSuccessiveHalving-231.R
Saving _problems/test_TunerBatchSuccessiveHalving-248.R
Saving _problems/test_TunerBatchSuccessiveHalving-259.R
Saving _problems/test_TunerBatchSuccessiveHalving-268.R
Saving _problems/test_TunerBatchSuccessiveHalving-277.R
[ FAIL 32 | WARN 0 | SKIP 1 | PASS 36 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test_TunerAsyncSuccessiveHalving.R:1:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_TunerBatchHyperband.R:7:3'): TunerBatchHyperband works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:7:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:16:3'): TunerBatchHyperband works with minimum budget > 1 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:16:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:25:3'): TunerBatchHyperband rounds budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:25:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:34:3'): TunerBatchHyperband works with eta = 2.5 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2.5, learner) at test_TunerBatchHyperband.R:34:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:47:3'): TunerBatchHyperband works with xgboost ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:47:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:58:3'): TunerBatchHyperband works with subsampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 3, graph_learner) at test_TunerBatchHyperband.R:58:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:68:3'): TunerBatchHyperband works works with multi-crit ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:68:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:82:3'): TunerBatchHyperband works with custom sampler ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner, sampler = sampler) at test_TunerBatchHyperband.R:82:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:167:3'): TunerBatchHyperband minimizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:167:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:178:3'): TunerBatchHyperband maximizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:178:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:189:3'): TunerBatchHyperband works with single budget value ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:189:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:198:3'): TunerBatchHyperband works with repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:198:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:214:3'): TunerBatchHyperband terminates itself ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:214:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:230:3'): TunerBatchHyperband works with infinite repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:230:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:7:3'): TunerBatchSuccessiveHalving works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:7:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:16:3'): TunerBatchSuccessiveHalving works with minimum budget > 1 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:16:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:25:3'): TunerBatchSuccessiveHalving rounds budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:25:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:34:3'): TunerBatchSuccessiveHalving works with eta = 2.5 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:34:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:43:3'): TunerBatchSuccessiveHalving adjusts minimum budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:43:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:65:3'): TunerBatchSuccessiveHalving works with xgboost ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:65:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:76:3'): TunerBatchSuccessiveHalving works with subsampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:76:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:85:3'): TunerBatchSuccessiveHalving works with multi-crit ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:85:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:96:3'): TunerBatchSuccessiveHalving works with custom sampler ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:96:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:181:3'): TunerBatchSuccessiveHalving minimizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:181:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:191:3'): TunerBatchSuccessiveHalving maximizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:191:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:201:3'): TunerBatchSuccessiveHalving works with single budget value ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:201:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:210:3'): TunerBatchSuccessiveHalving works with repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:210:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:226:3'): TunerBatchSuccessiveHalving terminates itself ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:226:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:242:3'): TunerBatchSuccessiveHalving works with infinite repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:242:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:259:3'): TunerBatchSuccessiveHalving works with r_max > n ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:259:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:268:3'): TunerBatchSuccessiveHalving works with r_max < n ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:268:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:277:3'): TunerBatchSuccessiveHalving works with r_max < n and adjust minimum budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:277:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
[ FAIL 32 | WARN 0 | SKIP 1 | PASS 36 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.0.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [121s/238s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3hyperband")
+ test_check("mlr3hyperband")
+ }
Loading required package: mlr3tuning
Loading required package: mlr3
Loading required package: paradox
Saving _problems/test_TunerBatchHyperband-7.R
Saving _problems/test_TunerBatchHyperband-16.R
Saving _problems/test_TunerBatchHyperband-25.R
Saving _problems/test_TunerBatchHyperband-34.R
Saving _problems/test_TunerBatchHyperband-47.R
Saving _problems/test_TunerBatchHyperband-58.R
Saving _problems/test_TunerBatchHyperband-68.R
Saving _problems/test_TunerBatchHyperband-82.R
Saving _problems/test_TunerBatchHyperband-167.R
Saving _problems/test_TunerBatchHyperband-178.R
Saving _problems/test_TunerBatchHyperband-189.R
Saving _problems/test_TunerBatchHyperband-203.R
Saving _problems/test_TunerBatchHyperband-219.R
Saving _problems/test_TunerBatchHyperband-236.R
Saving _problems/test_TunerBatchSuccessiveHalving-7.R
Saving _problems/test_TunerBatchSuccessiveHalving-16.R
Saving _problems/test_TunerBatchSuccessiveHalving-25.R
Saving _problems/test_TunerBatchSuccessiveHalving-34.R
Saving _problems/test_TunerBatchSuccessiveHalving-43.R
Saving _problems/test_TunerBatchSuccessiveHalving-65.R
Saving _problems/test_TunerBatchSuccessiveHalving-76.R
Saving _problems/test_TunerBatchSuccessiveHalving-85.R
Saving _problems/test_TunerBatchSuccessiveHalving-96.R
Saving _problems/test_TunerBatchSuccessiveHalving-181.R
Saving _problems/test_TunerBatchSuccessiveHalving-191.R
Saving _problems/test_TunerBatchSuccessiveHalving-201.R
Saving _problems/test_TunerBatchSuccessiveHalving-215.R
Saving _problems/test_TunerBatchSuccessiveHalving-231.R
Saving _problems/test_TunerBatchSuccessiveHalving-248.R
Saving _problems/test_TunerBatchSuccessiveHalving-259.R
Saving _problems/test_TunerBatchSuccessiveHalving-268.R
Saving _problems/test_TunerBatchSuccessiveHalving-277.R
[ FAIL 32 | WARN 0 | SKIP 1 | PASS 36 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test_TunerAsyncSuccessiveHalving.R:1:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_TunerBatchHyperband.R:7:3'): TunerBatchHyperband works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:7:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:16:3'): TunerBatchHyperband works with minimum budget > 1 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:16:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:25:3'): TunerBatchHyperband rounds budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:25:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:34:3'): TunerBatchHyperband works with eta = 2.5 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2.5, learner) at test_TunerBatchHyperband.R:34:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:47:3'): TunerBatchHyperband works with xgboost ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:47:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:58:3'): TunerBatchHyperband works with subsampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 3, graph_learner) at test_TunerBatchHyperband.R:58:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:68:3'): TunerBatchHyperband works works with multi-crit ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:68:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:82:3'): TunerBatchHyperband works with custom sampler ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner, sampler = sampler) at test_TunerBatchHyperband.R:82:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:167:3'): TunerBatchHyperband minimizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:167:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:178:3'): TunerBatchHyperband maximizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:178:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:189:3'): TunerBatchHyperband works with single budget value ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:189:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:198:3'): TunerBatchHyperband works with repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:198:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:214:3'): TunerBatchHyperband terminates itself ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:214:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:230:3'): TunerBatchHyperband works with infinite repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:230:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:7:3'): TunerBatchSuccessiveHalving works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:7:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:16:3'): TunerBatchSuccessiveHalving works with minimum budget > 1 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:16:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:25:3'): TunerBatchSuccessiveHalving rounds budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:25:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:34:3'): TunerBatchSuccessiveHalving works with eta = 2.5 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:34:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:43:3'): TunerBatchSuccessiveHalving adjusts minimum budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:43:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:65:3'): TunerBatchSuccessiveHalving works with xgboost ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:65:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:76:3'): TunerBatchSuccessiveHalving works with subsampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:76:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:85:3'): TunerBatchSuccessiveHalving works with multi-crit ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:85:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:96:3'): TunerBatchSuccessiveHalving works with custom sampler ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:96:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:181:3'): TunerBatchSuccessiveHalving minimizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:181:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:191:3'): TunerBatchSuccessiveHalving maximizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:191:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:201:3'): TunerBatchSuccessiveHalving works with single budget value ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:201:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:210:3'): TunerBatchSuccessiveHalving works with repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:210:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:226:3'): TunerBatchSuccessiveHalving terminates itself ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:226:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:242:3'): TunerBatchSuccessiveHalving works with infinite repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:242:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:259:3'): TunerBatchSuccessiveHalving works with r_max > n ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:259:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:268:3'): TunerBatchSuccessiveHalving works with r_max < n ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:268:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:277:3'): TunerBatchSuccessiveHalving works with r_max < n and adjust minimum budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:277:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
[ FAIL 32 | WARN 0 | SKIP 1 | PASS 36 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.0.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [110s/193s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3hyperband")
+ test_check("mlr3hyperband")
+ }
Loading required package: mlr3tuning
Loading required package: mlr3
Loading required package: paradox
Saving _problems/test_TunerBatchHyperband-7.R
Saving _problems/test_TunerBatchHyperband-16.R
Saving _problems/test_TunerBatchHyperband-25.R
Saving _problems/test_TunerBatchHyperband-34.R
Saving _problems/test_TunerBatchHyperband-47.R
Saving _problems/test_TunerBatchHyperband-58.R
Saving _problems/test_TunerBatchHyperband-68.R
Saving _problems/test_TunerBatchHyperband-82.R
Saving _problems/test_TunerBatchHyperband-167.R
Saving _problems/test_TunerBatchHyperband-178.R
Saving _problems/test_TunerBatchHyperband-189.R
Saving _problems/test_TunerBatchHyperband-203.R
Saving _problems/test_TunerBatchHyperband-219.R
Saving _problems/test_TunerBatchHyperband-236.R
Saving _problems/test_TunerBatchSuccessiveHalving-7.R
Saving _problems/test_TunerBatchSuccessiveHalving-16.R
Saving _problems/test_TunerBatchSuccessiveHalving-25.R
Saving _problems/test_TunerBatchSuccessiveHalving-34.R
Saving _problems/test_TunerBatchSuccessiveHalving-43.R
Saving _problems/test_TunerBatchSuccessiveHalving-65.R
Saving _problems/test_TunerBatchSuccessiveHalving-76.R
Saving _problems/test_TunerBatchSuccessiveHalving-85.R
Saving _problems/test_TunerBatchSuccessiveHalving-96.R
Saving _problems/test_TunerBatchSuccessiveHalving-181.R
Saving _problems/test_TunerBatchSuccessiveHalving-191.R
Saving _problems/test_TunerBatchSuccessiveHalving-201.R
Saving _problems/test_TunerBatchSuccessiveHalving-215.R
Saving _problems/test_TunerBatchSuccessiveHalving-231.R
Saving _problems/test_TunerBatchSuccessiveHalving-248.R
Saving _problems/test_TunerBatchSuccessiveHalving-259.R
Saving _problems/test_TunerBatchSuccessiveHalving-268.R
Saving _problems/test_TunerBatchSuccessiveHalving-277.R
[ FAIL 32 | WARN 0 | SKIP 1 | PASS 36 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test_TunerAsyncSuccessiveHalving.R:1:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_TunerBatchHyperband.R:7:3'): TunerBatchHyperband works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:7:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:16:3'): TunerBatchHyperband works with minimum budget > 1 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:16:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:25:3'): TunerBatchHyperband rounds budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:25:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:34:3'): TunerBatchHyperband works with eta = 2.5 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2.5, learner) at test_TunerBatchHyperband.R:34:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:47:3'): TunerBatchHyperband works with xgboost ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:47:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:58:3'): TunerBatchHyperband works with subsampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 3, graph_learner) at test_TunerBatchHyperband.R:58:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:68:3'): TunerBatchHyperband works works with multi-crit ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:68:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:82:3'): TunerBatchHyperband works with custom sampler ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner, sampler = sampler) at test_TunerBatchHyperband.R:82:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:167:3'): TunerBatchHyperband minimizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:167:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:178:3'): TunerBatchHyperband maximizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(...) at test_TunerBatchHyperband.R:178:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:189:3'): TunerBatchHyperband works with single budget value ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_hyperband(eta = 2, learner) at test_TunerBatchHyperband.R:189:3
2. └─mlr3tuning::tune(...) at ./helper.R:26:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:198:3'): TunerBatchHyperband works with repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:198:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:214:3'): TunerBatchHyperband terminates itself ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:214:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchHyperband.R:230:3'): TunerBatchHyperband works with infinite repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchHyperband.R:230:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchHyperband__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:7:3'): TunerBatchSuccessiveHalving works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:7:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:16:3'): TunerBatchSuccessiveHalving works with minimum budget > 1 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:16:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:25:3'): TunerBatchSuccessiveHalving rounds budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:25:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:34:3'): TunerBatchSuccessiveHalving works with eta = 2.5 ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:34:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:43:3'): TunerBatchSuccessiveHalving adjusts minimum budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:43:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:65:3'): TunerBatchSuccessiveHalving works with xgboost ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:65:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:76:3'): TunerBatchSuccessiveHalving works with subsampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:76:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:85:3'): TunerBatchSuccessiveHalving works with multi-crit ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:85:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:96:3'): TunerBatchSuccessiveHalving works with custom sampler ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:96:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:181:3'): TunerBatchSuccessiveHalving minimizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:181:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:191:3'): TunerBatchSuccessiveHalving maximizes measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:191:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:201:3'): TunerBatchSuccessiveHalving works with single budget value ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:201:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:210:3'): TunerBatchSuccessiveHalving works with repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:210:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:226:3'): TunerBatchSuccessiveHalving terminates itself ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:226:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:242:3'): TunerBatchSuccessiveHalving works with infinite repetitions ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchSuccessiveHalving.R:242:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
13. └─inst$eval_batch(xdt)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:259:3'): TunerBatchSuccessiveHalving works with r_max > n ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:259:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:268:3'): TunerBatchSuccessiveHalving works with r_max < n ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:268:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchSuccessiveHalving.R:277:3'): TunerBatchSuccessiveHalving works with r_max < n and adjust minimum budget ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3hyperband:::test_tuner_successive_halving(...) at test_TunerBatchSuccessiveHalving.R:277:3
2. └─mlr3tuning::tune(...) at ./helper.R:61:3
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3hyperband:::.__OptimizerBatchSuccessiveHalving__.optimize(...)
14. └─inst$eval_batch(xdt)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
[ FAIL 32 | WARN 0 | SKIP 1 | PASS 36 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Current CRAN status: ERROR: 4, OK: 9
Version: 0.14.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [47s/68s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3learners")
+ test_check("mlr3learners")
+ }
Loading required package: mlr3
Saving _problems/test_classif_cv_glmnet-12.R
Saving _problems/test_classif_glmnet-9.R
Saving _problems/test_classif_kknn-6.R
Saving _problems/test_classif_lda-6.R
Saving _problems/test_classif_log_reg-4.R
Saving _problems/test_classif_qda-6.R
Saving _problems/test_classif_ranger-7.R
Saving _problems/test_classif_ranger-105.R
Saving _problems/test_classif_svm-6.R
Saving _problems/test_regr_cv_glmnet-12.R
Saving _problems/test_regr_glmnet-9.R
Saving _problems/test_regr_kknn-6.R
Saving _problems/test_regr_lm-4.R
Saving _problems/test_regr_ranger-6.R
Saving _problems/test_regr_ranger-433.R
Saving _problems/test_regr_svm-6.R
Saving _problems/test_regr_svm-14.R
[ FAIL 21 | WARN 0 | SKIP 4 | PASS 614 ]
══ Skipped tests (4) ═══════════════════════════════════════════════════════════
• On CRAN (4): 'test_classif_nnet.R:2:1', 'test_classif_xgboost.R:2:1',
'test_regr_nnet.R:2:1', 'test_regr_xgboost.R:2:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_classif_cv_glmnet.R:12:3'): autotest ───────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single", N = 100L) at test_classif_cv_glmnet.R:12:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_glmnet.R:9:3'): autotest ───────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_classif_glmnet.R:9:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_kknn.R:6:3'): autotest ─────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_kknn.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_lda.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_classif_lda.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_log_reg.R:4:3'): autotest ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_log_reg.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_multinom.R:6:19'): autotest ────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_classif_multinom.R:6:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner) at test_classif_multinom.R:6:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_classif_naive_bayes.R:6:19'): autotest ─────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_classif_naive_bayes.R:6:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner) at test_classif_naive_bayes.R:6:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_classif_qda.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, N = 100L, exclude = "feat_single") at test_classif_qda.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_ranger.R:7:3'): autotest ───────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_ranger.R:7:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_ranger.R:105:3'): oob_error available without stored model ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout"), store_models = FALSE) at test_classif_ranger.R:105:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_classif_svm.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_svm.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_cv_glmnet.R:12:3'): autotest ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_regr_cv_glmnet.R:12:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_glmnet.R:9:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_regr_glmnet.R:9:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_kknn.R:6:3'): autotest ────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_kknn.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_km.R:6:19'): autotest ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_regr_km.R:6:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner, exclude = "feat_single", N = 50) at test_regr_km.R:6:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_regr_km.R:13:19'): autotest w/ jitter ──────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_regr_km.R:13:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner, exclude = "feat_single|reordered", N = 50) at test_regr_km.R:13:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_regr_lm.R:4:3'): autotest ──────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_lm.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_ranger.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, N = 50L) at test_regr_ranger.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_ranger.R:433:3'): oob_error available without stored model ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout"), store_models = FALSE) at test_regr_ranger.R:433:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_regr_svm.R:6:3'): autotest ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_svm.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_svm.R:14:3'): autotest with type nu-regression (#209) ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_svm.R:14:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
[ FAIL 21 | WARN 0 | SKIP 4 | PASS 614 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.14.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [31s/50s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3learners")
+ test_check("mlr3learners")
+ }
Loading required package: mlr3
Saving _problems/test_classif_cv_glmnet-12.R
Saving _problems/test_classif_glmnet-9.R
Saving _problems/test_classif_kknn-6.R
Saving _problems/test_classif_lda-6.R
Saving _problems/test_classif_log_reg-4.R
Saving _problems/test_classif_qda-6.R
Saving _problems/test_classif_ranger-7.R
Saving _problems/test_classif_ranger-105.R
Saving _problems/test_classif_svm-6.R
Saving _problems/test_regr_cv_glmnet-12.R
Saving _problems/test_regr_glmnet-9.R
Saving _problems/test_regr_kknn-6.R
Saving _problems/test_regr_lm-4.R
Saving _problems/test_regr_ranger-6.R
Saving _problems/test_regr_ranger-433.R
Saving _problems/test_regr_svm-6.R
Saving _problems/test_regr_svm-14.R
[ FAIL 21 | WARN 0 | SKIP 4 | PASS 614 ]
══ Skipped tests (4) ═══════════════════════════════════════════════════════════
• On CRAN (4): 'test_classif_nnet.R:2:1', 'test_classif_xgboost.R:2:1',
'test_regr_nnet.R:2:1', 'test_regr_xgboost.R:2:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_classif_cv_glmnet.R:12:3'): autotest ───────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single", N = 100L) at test_classif_cv_glmnet.R:12:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_glmnet.R:9:3'): autotest ───────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_classif_glmnet.R:9:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_kknn.R:6:3'): autotest ─────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_kknn.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_lda.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_classif_lda.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_log_reg.R:4:3'): autotest ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_log_reg.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_multinom.R:6:19'): autotest ────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_classif_multinom.R:6:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner) at test_classif_multinom.R:6:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_classif_naive_bayes.R:6:19'): autotest ─────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_classif_naive_bayes.R:6:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner) at test_classif_naive_bayes.R:6:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_classif_qda.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, N = 100L, exclude = "feat_single") at test_classif_qda.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_ranger.R:7:3'): autotest ───────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_ranger.R:7:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_ranger.R:105:3'): oob_error available without stored model ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout"), store_models = FALSE) at test_classif_ranger.R:105:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_classif_svm.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_svm.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_cv_glmnet.R:12:3'): autotest ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_regr_cv_glmnet.R:12:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_glmnet.R:9:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_regr_glmnet.R:9:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_kknn.R:6:3'): autotest ────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_kknn.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_km.R:6:19'): autotest ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_regr_km.R:6:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner, exclude = "feat_single", N = 50) at test_regr_km.R:6:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_regr_km.R:13:19'): autotest w/ jitter ──────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_regr_km.R:13:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner, exclude = "feat_single|reordered", N = 50) at test_regr_km.R:13:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_regr_lm.R:4:3'): autotest ──────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_lm.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_ranger.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, N = 50L) at test_regr_ranger.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_ranger.R:433:3'): oob_error available without stored model ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout"), store_models = FALSE) at test_regr_ranger.R:433:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_regr_svm.R:6:3'): autotest ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_svm.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_svm.R:14:3'): autotest with type nu-regression (#209) ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_svm.R:14:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
[ FAIL 21 | WARN 0 | SKIP 4 | PASS 614 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.14.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [72s/155s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3learners")
+ test_check("mlr3learners")
+ }
Loading required package: mlr3
Saving _problems/test_classif_cv_glmnet-12.R
Saving _problems/test_classif_glmnet-9.R
Saving _problems/test_classif_kknn-6.R
Saving _problems/test_classif_lda-6.R
Saving _problems/test_classif_log_reg-4.R
Saving _problems/test_classif_qda-6.R
Saving _problems/test_classif_ranger-7.R
Saving _problems/test_classif_ranger-105.R
Saving _problems/test_classif_svm-6.R
Saving _problems/test_regr_cv_glmnet-12.R
Saving _problems/test_regr_glmnet-9.R
Saving _problems/test_regr_kknn-6.R
Saving _problems/test_regr_lm-4.R
Saving _problems/test_regr_ranger-6.R
Saving _problems/test_regr_ranger-433.R
Saving _problems/test_regr_svm-6.R
Saving _problems/test_regr_svm-14.R
[ FAIL 21 | WARN 0 | SKIP 4 | PASS 614 ]
══ Skipped tests (4) ═══════════════════════════════════════════════════════════
• On CRAN (4): 'test_classif_nnet.R:2:1', 'test_classif_xgboost.R:2:1',
'test_regr_nnet.R:2:1', 'test_regr_xgboost.R:2:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_classif_cv_glmnet.R:12:3'): autotest ───────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single", N = 100L) at test_classif_cv_glmnet.R:12:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_glmnet.R:9:3'): autotest ───────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_classif_glmnet.R:9:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_kknn.R:6:3'): autotest ─────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_kknn.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_lda.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_classif_lda.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_log_reg.R:4:3'): autotest ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_log_reg.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_multinom.R:6:19'): autotest ────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_classif_multinom.R:6:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner) at test_classif_multinom.R:6:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_classif_naive_bayes.R:6:19'): autotest ─────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_classif_naive_bayes.R:6:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner) at test_classif_naive_bayes.R:6:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_classif_qda.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, N = 100L, exclude = "feat_single") at test_classif_qda.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_ranger.R:7:3'): autotest ───────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_ranger.R:7:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_ranger.R:105:3'): oob_error available without stored model ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout"), store_models = FALSE) at test_classif_ranger.R:105:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_classif_svm.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_svm.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_cv_glmnet.R:12:3'): autotest ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_regr_cv_glmnet.R:12:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_glmnet.R:9:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_regr_glmnet.R:9:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_kknn.R:6:3'): autotest ────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_kknn.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_km.R:6:19'): autotest ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_regr_km.R:6:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner, exclude = "feat_single", N = 50) at test_regr_km.R:6:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_regr_km.R:13:19'): autotest w/ jitter ──────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_regr_km.R:13:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner, exclude = "feat_single|reordered", N = 50) at test_regr_km.R:13:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_regr_lm.R:4:3'): autotest ──────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_lm.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_ranger.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, N = 50L) at test_regr_ranger.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_ranger.R:433:3'): oob_error available without stored model ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout"), store_models = FALSE) at test_regr_ranger.R:433:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_regr_svm.R:6:3'): autotest ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_svm.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_svm.R:14:3'): autotest with type nu-regression (#209) ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_svm.R:14:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
[ FAIL 21 | WARN 0 | SKIP 4 | PASS 614 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.14.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [67s/124s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3learners")
+ test_check("mlr3learners")
+ }
Loading required package: mlr3
Saving _problems/test_classif_cv_glmnet-12.R
Saving _problems/test_classif_glmnet-9.R
Saving _problems/test_classif_kknn-6.R
Saving _problems/test_classif_lda-6.R
Saving _problems/test_classif_log_reg-4.R
Saving _problems/test_classif_qda-6.R
Saving _problems/test_classif_ranger-7.R
Saving _problems/test_classif_ranger-105.R
Saving _problems/test_classif_svm-6.R
Saving _problems/test_regr_cv_glmnet-12.R
Saving _problems/test_regr_glmnet-9.R
Saving _problems/test_regr_kknn-6.R
Saving _problems/test_regr_lm-4.R
Saving _problems/test_regr_ranger-6.R
Saving _problems/test_regr_ranger-433.R
Saving _problems/test_regr_svm-6.R
Saving _problems/test_regr_svm-14.R
[ FAIL 21 | WARN 0 | SKIP 4 | PASS 614 ]
══ Skipped tests (4) ═══════════════════════════════════════════════════════════
• On CRAN (4): 'test_classif_nnet.R:2:1', 'test_classif_xgboost.R:2:1',
'test_regr_nnet.R:2:1', 'test_regr_xgboost.R:2:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_classif_cv_glmnet.R:12:3'): autotest ───────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single", N = 100L) at test_classif_cv_glmnet.R:12:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_glmnet.R:9:3'): autotest ───────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_classif_glmnet.R:9:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_kknn.R:6:3'): autotest ─────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_kknn.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_lda.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_classif_lda.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_log_reg.R:4:3'): autotest ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_log_reg.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_multinom.R:6:19'): autotest ────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_classif_multinom.R:6:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner) at test_classif_multinom.R:6:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_classif_naive_bayes.R:6:19'): autotest ─────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_classif_naive_bayes.R:6:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner) at test_classif_naive_bayes.R:6:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_classif_qda.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, N = 100L, exclude = "feat_single") at test_classif_qda.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_ranger.R:7:3'): autotest ───────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_ranger.R:7:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_classif_ranger.R:105:3'): oob_error available without stored model ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout"), store_models = FALSE) at test_classif_ranger.R:105:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_classif_svm.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_classif_svm.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_cv_glmnet.R:12:3'): autotest ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_regr_cv_glmnet.R:12:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_glmnet.R:9:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, exclude = "feat_single") at test_regr_glmnet.R:9:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_kknn.R:6:3'): autotest ────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_kknn.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_km.R:6:19'): autotest ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_regr_km.R:6:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner, exclude = "feat_single", N = 50) at test_regr_km.R:6:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_regr_km.R:13:19'): autotest w/ jitter ──────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─utils::capture.output(...) at test_regr_km.R:13:3
2. │ └─base::withVisible(...elt(i))
3. └─global run_autotest(learner, exclude = "feat_single|reordered", N = 50) at test_regr_km.R:13:19
4. └─global run_experiment(task, learner, NULL, configure_learner)
5. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
6. └─ResultData$new(data, data_extra, store_backends = store_backends)
7. └─mlr3 (local) initialize(...)
8. └─mlr3:::.__ResultData__initialize(...)
9. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
10. └─data.table:::`[.data.table`(...)
── Error ('test_regr_lm.R:4:3'): autotest ──────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_lm.R:4:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_ranger.R:6:3'): autotest ──────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner, N = 50L) at test_regr_ranger.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_ranger.R:433:3'): oob_error available without stored model ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, rsmp("holdout"), store_models = FALSE) at test_regr_ranger.R:433:3
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_regr_svm.R:6:3'): autotest ─────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_svm.R:6:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
── Error ('test_regr_svm.R:14:3'): autotest with type nu-regression (#209) ─────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global run_autotest(learner) at test_regr_svm.R:14:3
2. └─global run_experiment(task, learner, NULL, configure_learner)
3. └─mlr3::resample(task, learner_encapsulated, rsmp("holdout"), store_models = TRUE)
4. └─ResultData$new(data, data_extra, store_backends = store_backends)
5. └─mlr3 (local) initialize(...)
6. └─mlr3:::.__ResultData__initialize(...)
7. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
8. └─data.table:::`[.data.table`(...)
[ FAIL 21 | WARN 0 | SKIP 4 | PASS 614 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Current CRAN status: ERROR: 4, OK: 9
Version: 0.3.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [331s/377s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library(testthat)
+ library(checkmate)
+ library(mlr3mbo)
+ test_check("mlr3mbo")
+ }
Loading required package: mlr3tuning
Loading required package: mlr3
Loading required package: paradox
Attaching package: 'mlr3mbo'
The following object is masked from 'package:testthat':
it
Loading required namespace: mlr3learners
Loading required namespace: DiceKriging
Loading required namespace: rgenoud
WARN [04:36:24.614] [bbotk] Optimizer Error.
Saving _problems/test_ResultAssignerArchive-79.R
Saving _problems/test_ResultAssignerSurrogate-110.R
Saving _problems/test_TunerMbo-52.R
Saving _problems/test_TunerMbo-79.R
Saving _problems/test_TunerMbo-143.R
Saving _problems/test_TunerMbo-158.R
[ FAIL 6 | WARN 2 | SKIP 18 | PASS 1043 ]
══ Skipped tests (18) ══════════════════════════════════════════════════════════
• On CRAN (17): 'test_AcqFunctionEHVIGH.R:35:3',
'test_AcqFunctionStochasticCB.R:2:3', 'test_AcqFunctionStochasticCB.R:30:3',
'test_AcqFunctionStochasticCB.R:59:3', 'test_AcqFunctionStochasticCB.R:89:3',
'test_AcqFunctionStochasticCB.R:119:3', 'test_AcqFunctionStochasticEI.R:2:3',
'test_AcqFunctionStochasticEI.R:31:3', 'test_AcqFunctionStochasticEI.R:60:3',
'test_OptimizerADBO.R:2:3', 'test_OptimizerAsyncMbo.R:2:3',
'test_OptimizerAsyncMbo.R:24:3', 'test_OptimizerMbo.R:2:3',
'test_ResultAssignerSurrogate.R:16:3', 'test_TunerADBO.R:2:3',
'test_TunerAsyncMbo.R:2:3', 'test_TunerMbo.R:2:3'
• empty test (1): 'test_bayesopt_ego.R:55:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ResultAssignerArchive.R:79:3'): ResultAssignerArchive passes internal tuned values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), nrows = 1L) at test_ResultAssignerArchive.R:79:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
14. ├─mlr3misc::invoke(...)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─self$loop_function(...)
19. └─instance$eval_batch(design)
20. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
21. └─self$objective$eval_many(xss_trafoed)
22. └─bbotk:::.__Objective__eval_many(...)
23. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
24. │ └─base::eval.parent(expr, n = 1L)
25. │ └─base::eval(expr, p)
26. │ └─base::eval(expr, p)
27. └─private$.eval_many(xss = xss, resampling = `<list>`)
28. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
29. └─mlr3::benchmark(...)
30. └─ResultData$new(grid, data_extra, store_backends = store_backends)
31. └─mlr3 (local) initialize(...)
32. └─mlr3:::.__ResultData__initialize(...)
33. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
34. └─data.table:::`[.data.table`(...)
── Error ('test_ResultAssignerSurrogate.R:110:3'): ResultAssignerSurrogate passes internal tuned values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), nrows = 1L) at test_ResultAssignerSurrogate.R:110:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
14. ├─mlr3misc::invoke(...)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─self$loop_function(...)
19. └─instance$eval_batch(design)
20. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
21. └─self$objective$eval_many(xss_trafoed)
22. └─bbotk:::.__Objective__eval_many(...)
23. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
24. │ └─base::eval.parent(expr, n = 1L)
25. │ └─base::eval(expr, p)
26. │ └─base::eval(expr, p)
27. └─private$.eval_many(xss = xss, resampling = `<list>`)
28. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
29. └─mlr3::benchmark(...)
30. └─ResultData$new(grid, data_extra, store_backends = store_backends)
31. └─mlr3 (local) initialize(...)
32. └─mlr3:::.__ResultData__initialize(...)
33. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
34. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:52:3'): Constructing TunerMbo and ABs ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerMbo.R:52:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─self$loop_function(...)
17. └─instance$eval_batch(design)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:72:3'): TunerMbo sugar ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerMbo.R:72:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
13. ├─mlr3misc::invoke(...)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─self$loop_function(...)
18. └─instance$eval_batch(design)
19. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
20. └─self$objective$eval_many(xss_trafoed)
21. └─bbotk:::.__Objective__eval_many(...)
22. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
23. │ └─base::eval.parent(expr, n = 1L)
24. │ └─base::eval(expr, p)
25. │ └─base::eval(expr, p)
26. └─private$.eval_many(xss = xss, resampling = `<list>`)
27. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
28. └─mlr3::benchmark(...)
29. └─ResultData$new(grid, data_extra, store_backends = store_backends)
30. └─mlr3 (local) initialize(...)
31. └─mlr3:::.__ResultData__initialize(...)
32. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
33. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:143:3'): TunerMbo args ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerMbo.R:143:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─self$loop_function(...)
17. └─instance$eval_batch(design)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:158:3'): TunerMbo reset ─────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerMbo.R:158:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─self$loop_function(...)
17. └─instance$eval_batch(design)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
[ FAIL 6 | WARN 2 | SKIP 18 | PASS 1043 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.3.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [248s/291s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library(testthat)
+ library(checkmate)
+ library(mlr3mbo)
+ test_check("mlr3mbo")
+ }
Loading required package: mlr3tuning
Loading required package: mlr3
Loading required package: paradox
Attaching package: 'mlr3mbo'
The following object is masked from 'package:testthat':
it
Loading required namespace: mlr3learners
Loading required namespace: DiceKriging
Loading required namespace: rgenoud
WARN [17:19:19.461] [bbotk] Optimizer Error.
Saving _problems/test_ResultAssignerArchive-79.R
Saving _problems/test_ResultAssignerSurrogate-110.R
Saving _problems/test_TunerMbo-52.R
Saving _problems/test_TunerMbo-79.R
Saving _problems/test_TunerMbo-143.R
Saving _problems/test_TunerMbo-158.R
[ FAIL 6 | WARN 2 | SKIP 18 | PASS 1043 ]
══ Skipped tests (18) ══════════════════════════════════════════════════════════
• On CRAN (17): 'test_AcqFunctionEHVIGH.R:35:3',
'test_AcqFunctionStochasticCB.R:2:3', 'test_AcqFunctionStochasticCB.R:30:3',
'test_AcqFunctionStochasticCB.R:59:3', 'test_AcqFunctionStochasticCB.R:89:3',
'test_AcqFunctionStochasticCB.R:119:3', 'test_AcqFunctionStochasticEI.R:2:3',
'test_AcqFunctionStochasticEI.R:31:3', 'test_AcqFunctionStochasticEI.R:60:3',
'test_OptimizerADBO.R:2:3', 'test_OptimizerAsyncMbo.R:2:3',
'test_OptimizerAsyncMbo.R:24:3', 'test_OptimizerMbo.R:2:3',
'test_ResultAssignerSurrogate.R:16:3', 'test_TunerADBO.R:2:3',
'test_TunerAsyncMbo.R:2:3', 'test_TunerMbo.R:2:3'
• empty test (1): 'test_bayesopt_ego.R:55:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ResultAssignerArchive.R:79:3'): ResultAssignerArchive passes internal tuned values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), nrows = 1L) at test_ResultAssignerArchive.R:79:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
14. ├─mlr3misc::invoke(...)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─self$loop_function(...)
19. └─instance$eval_batch(design)
20. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
21. └─self$objective$eval_many(xss_trafoed)
22. └─bbotk:::.__Objective__eval_many(...)
23. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
24. │ └─base::eval.parent(expr, n = 1L)
25. │ └─base::eval(expr, p)
26. │ └─base::eval(expr, p)
27. └─private$.eval_many(xss = xss, resampling = `<list>`)
28. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
29. └─mlr3::benchmark(...)
30. └─ResultData$new(grid, data_extra, store_backends = store_backends)
31. └─mlr3 (local) initialize(...)
32. └─mlr3:::.__ResultData__initialize(...)
33. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
34. └─data.table:::`[.data.table`(...)
── Error ('test_ResultAssignerSurrogate.R:110:3'): ResultAssignerSurrogate passes internal tuned values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), nrows = 1L) at test_ResultAssignerSurrogate.R:110:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
14. ├─mlr3misc::invoke(...)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─self$loop_function(...)
19. └─instance$eval_batch(design)
20. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
21. └─self$objective$eval_many(xss_trafoed)
22. └─bbotk:::.__Objective__eval_many(...)
23. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
24. │ └─base::eval.parent(expr, n = 1L)
25. │ └─base::eval(expr, p)
26. │ └─base::eval(expr, p)
27. └─private$.eval_many(xss = xss, resampling = `<list>`)
28. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
29. └─mlr3::benchmark(...)
30. └─ResultData$new(grid, data_extra, store_backends = store_backends)
31. └─mlr3 (local) initialize(...)
32. └─mlr3:::.__ResultData__initialize(...)
33. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
34. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:52:3'): Constructing TunerMbo and ABs ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerMbo.R:52:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─self$loop_function(...)
17. └─instance$eval_batch(design)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:72:3'): TunerMbo sugar ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerMbo.R:72:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
13. ├─mlr3misc::invoke(...)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─self$loop_function(...)
18. └─instance$eval_batch(design)
19. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
20. └─self$objective$eval_many(xss_trafoed)
21. └─bbotk:::.__Objective__eval_many(...)
22. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
23. │ └─base::eval.parent(expr, n = 1L)
24. │ └─base::eval(expr, p)
25. │ └─base::eval(expr, p)
26. └─private$.eval_many(xss = xss, resampling = `<list>`)
27. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
28. └─mlr3::benchmark(...)
29. └─ResultData$new(grid, data_extra, store_backends = store_backends)
30. └─mlr3 (local) initialize(...)
31. └─mlr3:::.__ResultData__initialize(...)
32. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
33. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:143:3'): TunerMbo args ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerMbo.R:143:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─self$loop_function(...)
17. └─instance$eval_batch(design)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:158:3'): TunerMbo reset ─────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerMbo.R:158:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─self$loop_function(...)
17. └─instance$eval_batch(design)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
[ FAIL 6 | WARN 2 | SKIP 18 | PASS 1043 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.3.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [9m/17m]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library(testthat)
+ library(checkmate)
+ library(mlr3mbo)
+ test_check("mlr3mbo")
+ }
Loading required package: mlr3tuning
Loading required package: mlr3
Loading required package: paradox
Attaching package: 'mlr3mbo'
The following object is masked from 'package:testthat':
it
Loading required namespace: mlr3learners
Loading required namespace: DiceKriging
Loading required namespace: rgenoud
WARN [17:53:07.134] [bbotk] Optimizer Error.
Saving _problems/test_ResultAssignerArchive-79.R
Saving _problems/test_ResultAssignerSurrogate-110.R
Saving _problems/test_TunerMbo-52.R
Saving _problems/test_TunerMbo-79.R
Saving _problems/test_TunerMbo-143.R
Saving _problems/test_TunerMbo-158.R
[ FAIL 6 | WARN 2 | SKIP 18 | PASS 1043 ]
══ Skipped tests (18) ══════════════════════════════════════════════════════════
• On CRAN (17): 'test_AcqFunctionEHVIGH.R:35:3',
'test_AcqFunctionStochasticCB.R:2:3', 'test_AcqFunctionStochasticCB.R:30:3',
'test_AcqFunctionStochasticCB.R:59:3', 'test_AcqFunctionStochasticCB.R:89:3',
'test_AcqFunctionStochasticCB.R:119:3', 'test_AcqFunctionStochasticEI.R:2:3',
'test_AcqFunctionStochasticEI.R:31:3', 'test_AcqFunctionStochasticEI.R:60:3',
'test_OptimizerADBO.R:2:3', 'test_OptimizerAsyncMbo.R:2:3',
'test_OptimizerAsyncMbo.R:24:3', 'test_OptimizerMbo.R:2:3',
'test_ResultAssignerSurrogate.R:16:3', 'test_TunerADBO.R:2:3',
'test_TunerAsyncMbo.R:2:3', 'test_TunerMbo.R:2:3'
• empty test (1): 'test_bayesopt_ego.R:55:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ResultAssignerArchive.R:79:3'): ResultAssignerArchive passes internal tuned values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), nrows = 1L) at test_ResultAssignerArchive.R:79:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
14. ├─mlr3misc::invoke(...)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─self$loop_function(...)
19. └─instance$eval_batch(design)
20. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
21. └─self$objective$eval_many(xss_trafoed)
22. └─bbotk:::.__Objective__eval_many(...)
23. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
24. │ └─base::eval.parent(expr, n = 1L)
25. │ └─base::eval(expr, p)
26. │ └─base::eval(expr, p)
27. └─private$.eval_many(xss = xss, resampling = `<list>`)
28. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
29. └─mlr3::benchmark(...)
30. └─ResultData$new(grid, data_extra, store_backends = store_backends)
31. └─mlr3 (local) initialize(...)
32. └─mlr3:::.__ResultData__initialize(...)
33. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
34. └─data.table:::`[.data.table`(...)
── Error ('test_ResultAssignerSurrogate.R:110:3'): ResultAssignerSurrogate passes internal tuned values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), nrows = 1L) at test_ResultAssignerSurrogate.R:110:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
14. ├─mlr3misc::invoke(...)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─self$loop_function(...)
19. └─instance$eval_batch(design)
20. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
21. └─self$objective$eval_many(xss_trafoed)
22. └─bbotk:::.__Objective__eval_many(...)
23. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
24. │ └─base::eval.parent(expr, n = 1L)
25. │ └─base::eval(expr, p)
26. │ └─base::eval(expr, p)
27. └─private$.eval_many(xss = xss, resampling = `<list>`)
28. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
29. └─mlr3::benchmark(...)
30. └─ResultData$new(grid, data_extra, store_backends = store_backends)
31. └─mlr3 (local) initialize(...)
32. └─mlr3:::.__ResultData__initialize(...)
33. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
34. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:52:3'): Constructing TunerMbo and ABs ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerMbo.R:52:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─self$loop_function(...)
17. └─instance$eval_batch(design)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:72:3'): TunerMbo sugar ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerMbo.R:72:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
13. ├─mlr3misc::invoke(...)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─self$loop_function(...)
18. └─instance$eval_batch(design)
19. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
20. └─self$objective$eval_many(xss_trafoed)
21. └─bbotk:::.__Objective__eval_many(...)
22. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
23. │ └─base::eval.parent(expr, n = 1L)
24. │ └─base::eval(expr, p)
25. │ └─base::eval(expr, p)
26. └─private$.eval_many(xss = xss, resampling = `<list>`)
27. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
28. └─mlr3::benchmark(...)
29. └─ResultData$new(grid, data_extra, store_backends = store_backends)
30. └─mlr3 (local) initialize(...)
31. └─mlr3:::.__ResultData__initialize(...)
32. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
33. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:143:3'): TunerMbo args ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerMbo.R:143:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─self$loop_function(...)
17. └─instance$eval_batch(design)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:158:3'): TunerMbo reset ─────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerMbo.R:158:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─self$loop_function(...)
17. └─instance$eval_batch(design)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
[ FAIL 6 | WARN 2 | SKIP 18 | PASS 1043 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.3.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [8m/11m]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library(testthat)
+ library(checkmate)
+ library(mlr3mbo)
+ test_check("mlr3mbo")
+ }
Loading required package: mlr3tuning
Loading required package: mlr3
Loading required package: paradox
Attaching package: 'mlr3mbo'
The following object is masked from 'package:testthat':
it
Loading required namespace: mlr3learners
Loading required namespace: DiceKriging
Loading required namespace: rgenoud
WARN [12:33:12.193] [bbotk] Optimizer Error.
Saving _problems/test_ResultAssignerArchive-79.R
Saving _problems/test_ResultAssignerSurrogate-110.R
Saving _problems/test_TunerMbo-52.R
Saving _problems/test_TunerMbo-79.R
Saving _problems/test_TunerMbo-143.R
Saving _problems/test_TunerMbo-158.R
[ FAIL 6 | WARN 2 | SKIP 18 | PASS 1043 ]
══ Skipped tests (18) ══════════════════════════════════════════════════════════
• On CRAN (17): 'test_AcqFunctionEHVIGH.R:35:3',
'test_AcqFunctionStochasticCB.R:2:3', 'test_AcqFunctionStochasticCB.R:30:3',
'test_AcqFunctionStochasticCB.R:59:3', 'test_AcqFunctionStochasticCB.R:89:3',
'test_AcqFunctionStochasticCB.R:119:3', 'test_AcqFunctionStochasticEI.R:2:3',
'test_AcqFunctionStochasticEI.R:31:3', 'test_AcqFunctionStochasticEI.R:60:3',
'test_OptimizerADBO.R:2:3', 'test_OptimizerAsyncMbo.R:2:3',
'test_OptimizerAsyncMbo.R:24:3', 'test_OptimizerMbo.R:2:3',
'test_ResultAssignerSurrogate.R:16:3', 'test_TunerADBO.R:2:3',
'test_TunerAsyncMbo.R:2:3', 'test_TunerMbo.R:2:3'
• empty test (1): 'test_bayesopt_ego.R:55:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ResultAssignerArchive.R:79:3'): ResultAssignerArchive passes internal tuned values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), nrows = 1L) at test_ResultAssignerArchive.R:79:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
14. ├─mlr3misc::invoke(...)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─self$loop_function(...)
19. └─instance$eval_batch(design)
20. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
21. └─self$objective$eval_many(xss_trafoed)
22. └─bbotk:::.__Objective__eval_many(...)
23. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
24. │ └─base::eval.parent(expr, n = 1L)
25. │ └─base::eval(expr, p)
26. │ └─base::eval(expr, p)
27. └─private$.eval_many(xss = xss, resampling = `<list>`)
28. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
29. └─mlr3::benchmark(...)
30. └─ResultData$new(grid, data_extra, store_backends = store_backends)
31. └─mlr3 (local) initialize(...)
32. └─mlr3:::.__ResultData__initialize(...)
33. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
34. └─data.table:::`[.data.table`(...)
── Error ('test_ResultAssignerSurrogate.R:110:3'): ResultAssignerSurrogate passes internal tuned values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), nrows = 1L) at test_ResultAssignerSurrogate.R:110:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
14. ├─mlr3misc::invoke(...)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─self$loop_function(...)
19. └─instance$eval_batch(design)
20. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
21. └─self$objective$eval_many(xss_trafoed)
22. └─bbotk:::.__Objective__eval_many(...)
23. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
24. │ └─base::eval.parent(expr, n = 1L)
25. │ └─base::eval(expr, p)
26. │ └─base::eval(expr, p)
27. └─private$.eval_many(xss = xss, resampling = `<list>`)
28. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
29. └─mlr3::benchmark(...)
30. └─ResultData$new(grid, data_extra, store_backends = store_backends)
31. └─mlr3 (local) initialize(...)
32. └─mlr3:::.__ResultData__initialize(...)
33. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
34. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:52:3'): Constructing TunerMbo and ABs ───────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerMbo.R:52:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─self$loop_function(...)
17. └─instance$eval_batch(design)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:72:3'): TunerMbo sugar ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerMbo.R:72:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
13. ├─mlr3misc::invoke(...)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─self$loop_function(...)
18. └─instance$eval_batch(design)
19. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
20. └─self$objective$eval_many(xss_trafoed)
21. └─bbotk:::.__Objective__eval_many(...)
22. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
23. │ └─base::eval.parent(expr, n = 1L)
24. │ └─base::eval(expr, p)
25. │ └─base::eval(expr, p)
26. └─private$.eval_many(xss = xss, resampling = `<list>`)
27. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
28. └─mlr3::benchmark(...)
29. └─ResultData$new(grid, data_extra, store_backends = store_backends)
30. └─mlr3 (local) initialize(...)
31. └─mlr3:::.__ResultData__initialize(...)
32. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
33. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:143:3'): TunerMbo args ──────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerMbo.R:143:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─self$loop_function(...)
17. └─instance$eval_batch(design)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerMbo.R:158:3'): TunerMbo reset ─────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerMbo.R:158:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─mlr3mbo:::.__OptimizerMbo__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─mlr3mbo:::.__OptimizerMbo__.optimize(...)
12. ├─mlr3misc::invoke(...)
13. │ └─base::eval.parent(expr, n = 1L)
14. │ └─base::eval(expr, p)
15. │ └─base::eval(expr, p)
16. └─self$loop_function(...)
17. └─instance$eval_batch(design)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
[ FAIL 6 | WARN 2 | SKIP 18 | PASS 1043 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: ERROR: 5, OK: 8
Version: 1.5.1
Check: examples
Result: ERROR
Running examples in ‘mlr3tuning-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### 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)
>
> # tune hyperparameters and fit final model
> at$train(task, row_ids = split$train)
INFO [04:35:35.454] [bbotk] Starting to optimize 1 parameter(s) with '<OptimizerBatchRandomSearch>' and '<TerminatorEvals> [n_evals=4, k=0]'
INFO [04:35:35.685] [bbotk] Evaluating 1 configuration(s)
INFO [04:35:35.743] [mlr3] Running benchmark with 1 resampling iterations
INFO [04:35:35.932] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 1/1)
INFO [04:35:36.006] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: <Anonymous> ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.5.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [98s/110s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3tuning")
+ test_check("mlr3tuning")
+ }
Loading required package: mlr3
Loading required package: paradox
Saving _problems/test_ArchiveBatchTuning-11.R
Saving _problems/test_ArchiveBatchTuning-126.R
Saving _problems/test_ArchiveBatchTuning-277.R
Saving _problems/test_AutoTuner-10.R
Saving _problems/test_AutoTuner-42.R
Saving _problems/test_AutoTuner-77.R
Saving _problems/test_AutoTuner-93.R
Saving _problems/test_AutoTuner-118.R
Saving _problems/test_AutoTuner-155.R
Saving _problems/test_AutoTuner-184.R
Saving _problems/test_AutoTuner-246.R
Saving _problems/test_AutoTuner-282.R
Saving _problems/test_AutoTuner-308.R
Saving _problems/test_AutoTuner-373.R
Saving _problems/test_AutoTuner-389.R
Saving _problems/test_AutoTuner-420.R
Saving _problems/test_AutoTuner-434.R
Saving _problems/test_AutoTuner-480.R
Saving _problems/test_AutoTuner-606.R
Saving _problems/test_AutoTuner-625.R
Saving _problems/test_AutoTuner-676.R
Saving _problems/test_AutoTuner-699.R
Saving _problems/test_CallbackBatchTuning-17.R
Saving _problems/test_CallbackBatchTuning-37.R
Saving _problems/test_CallbackBatchTuning-59.R
Saving _problems/test_CallbackBatchTuning-80.R
Saving _problems/test_CallbackBatchTuning-103.R
Saving _problems/test_CallbackBatchTuning-127.R
Saving _problems/test_CallbackBatchTuning-150.R
Saving _problems/test_CallbackBatchTuning-171.R
Saving _problems/test_CallbackBatchTuning-191.R
Saving _problems/test_CallbackBatchTuning-214.R
Saving _problems/test_CallbackBatchTuning-235.R
Saving _problems/test_CallbackBatchTuning-255.R
Saving _problems/test_CallbackBatchTuning-284.R
Saving _problems/test_CallbackBatchTuning-312.R
Saving _problems/test_CallbackBatchTuning-339.R
Saving _problems/test_CallbackBatchTuning-367.R
Saving _problems/test_ObjectiveTuningAsync-12.R
Saving _problems/test_ObjectiveTuningAsync-32.R
Saving _problems/test_ObjectiveTuningAsync-54.R
Saving _problems/test_ObjectiveTuningAsync-76.R
Saving _problems/test_ObjectiveTuningBatch-14.R
Saving _problems/test_ObjectiveTuningBatch-37.R
Saving _problems/test_ObjectiveTuningBatch-52.R
Saving _problems/test_ObjectiveTuningBatch-69.R
Saving _problems/test_ObjectiveTuningBatch-105.R
Saving _problems/test_ObjectiveTuningBatch-128.R
Saving _problems/test_ObjectiveTuningBatch-149.R
Saving _problems/test_Tuner-5.R
Saving _problems/test_Tuner-46.R
Saving _problems/test_Tuner-90.R
Saving _problems/test_Tuner-121.R
Saving _problems/test_Tuner-188.R
Saving _problems/test_Tuner-212.R
Saving _problems/test_Tuner-242.R
Saving _problems/test_Tuner-294.R
Saving _problems/test_Tuner-336.R
Saving _problems/test_Tuner-355.R
Saving _problems/test_TunerBatchCmaes-19.R
Saving _problems/test_TunerBatchDesignPoints-3.R
Saving _problems/test_TunerBatchFromOptimizerBatch-13.R
Saving _problems/test_TunerBatchGenSA-4.R
Saving _problems/test_TunerBatchGenSA-23.R
Saving _problems/test_TunerBatchGenSA-31.R
Saving _problems/test_TunerBatchGridSearch-2.R
Saving _problems/test_TunerBatchGridSearch-22.R
# 2025-12-20 04:36:36 CET: Initialization
# Elitist race
# Elitist new instances: 1
# Elitist limit: 2
# nbIterations: 2
# minNbSurvival: 2
# nbParameters: 1
# seed: 572377441
# confidence level: 0.95
# budget: 42
# mu: 5
# deterministic: FALSE
# 2025-12-20 04:36:36 CET: Iteration 1 of 2
# experimentsUsed: 0
# remainingBudget: 42
# currentBudget: 21
# nbConfigurations: 3
# Markers:
x No test is performed.
c Configurations are discarded only due to capping.
- The test is performed and some configurations are discarded.
= The test is performed but no configuration is discarded.
! The test is performed and configurations could be discarded but elite configurations are preserved.
. All alive configurations are elite and nothing is discarded.
+-+-----------+-----------+-----------+----------------+-----------+--------+-----+----+------+
| | Instance| Alive| Best| Mean best| Exp so far| W time| rho|KenW| Qvar|
+-+-----------+-----------+-----------+----------------+-----------+--------+-----+----+------+
Saving _problems/test_TunerBatchIrace-4.R
Saving _problems/test_TunerBatchNLoptr-5.R
Saving _problems/test_TunerBatchRandomSearch-2.R
Saving _problems/test_TunerInternal-18.R
Saving _problems/test_TuningInstanceBatchMultiCrit-19.R
Saving _problems/test_TuningInstanceBatchMultiCrit-35.R
Saving _problems/test_TuningInstanceBatchMultiCrit-64.R
Saving _problems/test_TuningInstanceBatchMultiCrit-114.R
Saving _problems/test_TuningInstanceBatchMultiCrit-129.R
Saving _problems/test_TuningInstanceBatchMultiCrit-186.R
Saving _problems/test_TuningInstanceBatchSingleCrit-9.R
Saving _problems/test_TuningInstanceBatchSingleCrit-46.R
Saving _problems/test_TuningInstanceBatchSingleCrit-55.R
Saving _problems/test_TuningInstanceBatchSingleCrit-76.R
Saving _problems/test_TuningInstanceBatchSingleCrit-99.R
Saving _problems/test_TuningInstanceBatchSingleCrit-128.R
Saving _problems/test_TuningInstanceBatchSingleCrit-136.R
Saving _problems/test_TuningInstanceBatchSingleCrit-170.R
Saving _problems/test_TuningInstanceBatchSingleCrit-220.R
Saving _problems/test_TuningInstanceBatchSingleCrit-237.R
Saving _problems/test_TuningInstanceBatchSingleCrit-413.R
Saving _problems/test_TuningInstanceBatchSingleCrit-428.R
Saving _problems/test_TuningInstanceBatchSingleCrit-459.R
Saving _problems/test_TuningInstanceBatchSingleCrit-484.R
Saving _problems/test_error_handling-12.R
Saving _problems/test_error_handling-36.R
Saving _problems/test_extract_inner_tuning_archives-11.R
Saving _problems/test_extract_inner_tuning_archives-131.R
Saving _problems/test_extract_inner_tuning_results-11.R
Saving _problems/test_extract_inner_tuning_results-131.R
Saving _problems/test_mlr_callbacks-14.R
Saving _problems/test_mlr_callbacks-31.R
Saving _problems/test_mlr_callbacks-290.R
Saving _problems/test_mlr_callbacks-307.R
Saving _problems/test_mlr_callbacks-340.R
Saving _problems/test_mlr_callbacks-445.R
Saving _problems/test_trafos-10.R
Saving _problems/test_trafos-34.R
Saving _problems/test_tune-4.R
Saving _problems/test_tune-14.R
Saving _problems/test_tune-24.R
Saving _problems/test_tune_nested-6.R
[ FAIL 113 | WARN 9 | SKIP 68 | PASS 191 ]
══ Skipped tests (68) ══════════════════════════════════════════════════════════
• On CRAN (68): 'test_ArchiveAsyncTuning.R:2:3',
'test_ArchiveAsyncTuning.R:61:3', 'test_ArchiveAsyncTuning.R:119:3',
'test_ArchiveAsyncTuning.R:146:3', 'test_ArchiveAsyncTuning.R:169:3',
'test_ArchiveAsyncTuning.R:209:3', 'test_ArchiveAsyncTuning.R:251:3',
'test_ArchiveAsyncTuning.R:284:3', 'test_ArchiveAsyncTuningFrozen.R:2:3',
'test_AutoTuner.R:640:3', 'test_CallbackAsyncTuning.R:4:3',
'test_CallbackAsyncTuning.R:33:3', 'test_CallbackAsyncTuning.R:64:3',
'test_CallbackAsyncTuning.R:93:3', 'test_CallbackAsyncTuning.R:124:3',
'test_CallbackAsyncTuning.R:160:3', 'test_CallbackAsyncTuning.R:188:3',
'test_CallbackAsyncTuning.R:222:3', 'test_CallbackAsyncTuning.R:252:3',
'test_CallbackAsyncTuning.R:281:3', 'test_CallbackAsyncTuning.R:312:3',
'test_CallbackAsyncTuning.R:343:3', 'test_CallbackAsyncTuning.R:373:3',
'test_CallbackAsyncTuning.R:405:3', 'test_CallbackAsyncTuning.R:443:3',
'test_CallbackAsyncTuning.R:480:3', 'test_CallbackAsyncTuning.R:516:3',
'test_Tuner.R:53:1', 'test_TunerAsyncDesignPoints.R:2:3',
'test_TunerAsyncGridSearch.R:2:3', 'test_TunerAsyncRandomSearch.R:2:3',
'test_TuningInstanceAsyncMultiCrit.R:2:3',
'test_TuningInstanceAsyncMultiCrit.R:30:3',
'test_TuningInstanceAsyncMultiCrit.R:57:3',
'test_TuningInstanceAsyncMultiCrit.R:81:3',
'test_TuningInstanceAsyncMultiCrit.R:106:3',
'test_TuningInstanceAsyncMultiCrit.R:134:3',
'test_TuningInstanceAsyncMultiCrit.R:189:3',
'test_TuningInstanceAsyncMultiCrit.R:236:3',
'test_TuningInstanceAsyncMultiCrit.R:261:3',
'test_TuningInstanceAsyncSingleCrit.R:2:3',
'test_TuningInstanceAsyncSingleCrit.R:29:3',
'test_TuningInstanceAsyncSingleCrit.R:54:3',
'test_TuningInstanceAsyncSingleCrit.R:78:3',
'test_TuningInstanceAsyncSingleCrit.R:104:3',
'test_TuningInstanceAsyncSingleCrit.R:131:3',
'test_TuningInstanceAsyncSingleCrit.R:182:3',
'test_TuningInstanceAsyncSingleCrit.R:213:3',
'test_TuningInstanceAsyncSingleCrit.R:226:3',
'test_TuningInstanceAsyncSingleCrit.R:240:3',
'test_TuningInstanceAsyncSingleCrit.R:266:3', 'test_auto_tuner.R:25:3',
'test_auto_tuner.R:48:3', 'test_mlr_callbacks.R:40:3',
'test_mlr_callbacks.R:93:3', 'test_mlr_callbacks.R:117:3',
'test_mlr_callbacks.R:141:3', 'test_mlr_callbacks.R:162:3',
'test_mlr_callbacks.R:192:3', 'test_mlr_callbacks.R:218:3',
'test_mlr_callbacks.R:251:3', 'test_mlr_callbacks.R:410:3',
'test_mlr_callbacks.R:452:3', 'test_mlr_callbacks.R:480:3',
'test_ti_async.R:2:3', 'test_ti_async.R:16:3', 'test_ti_async.R:30:3',
'test_ti_async.R:42:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ArchiveBatchTuning.R:11:3'): ArchiveTuning access methods work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_ArchiveBatchTuning.R:11:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchTuning.R:126:3'): ArchiveTuning as.data.table function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_ArchiveBatchTuning.R:126:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchTuning.R:277:3'): ArchiveBatchTuning as.data.table function works for internally tuned values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_ArchiveBatchTuning.R:277:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:10:3'): AutoTuner / train+predict ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:10:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
23. └─inst$eval_batch(g$data[inds])
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:42:3'): AutoTuner / resample ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, r_outer, store_models = TRUE) at test_AutoTuner.R:42:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:77:3'): nested resamppling results are consistent ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), lrn, cv2, store_models = TRUE) at test_AutoTuner.R:77:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:93:3'): AT training does not change learner in instance args ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:93:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:118:3'): AutoTuner works with graphlearner ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:118:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
23. └─inst$eval_batch(g$data[inds])
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:155:3'): Nested resampling works with graphlearner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, at, resampling_outer, store_models = TRUE) at test_AutoTuner.R:155:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:184:3'): store_tuning_instance, store_benchmark_result and store_models flags work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
23. └─inst$eval_batch(g$data[inds])
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:246:3'): predict_type works ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:246:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:282:3'): search space from TuneToken works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("iris")) at test_AutoTuner.R:282:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:308:3'): AutoTuner get_base_learner method works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("pima")) at test_AutoTuner.R:308:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:373:3'): AutoTuner hash works #647 in mlr3 ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_AutoTuner.R:373:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:389:3'): AutoTuner works with empty search space ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("pima")) at test_AutoTuner.R:389:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:420:3'): AutoTuner importance method works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("penguins")) at test_AutoTuner.R:420:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:434:3'): AutoTuner selected_features method works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("penguins")) at test_AutoTuner.R:434:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:480:3'): AutoTuner works with instantiated resampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:480:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:606:3'): marshalable learner ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:606:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:625:3'): marshal ───────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:625:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:676:3'): AutoTuner works with internal tuning and validation ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:676:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:699:3'): AutoTuner works when internal_search_space is part of primary search space ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:699:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:10:3'): on_optimization_begin works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:10:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:30:3'): on_optimization_end works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:30:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:52:3'): on_optimizer_after_eval works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:52:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:73:3'): on_optimizer_after_eval works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:73:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:96:3'): on_eval_after_design works ───────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:96:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:120:3'): on_eval_after_benchmark and on_eval_before_archive works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:120:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:143:3'): on_tuning_result_begin in TuningInstanceSingleCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:143:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:164:3'): on_result_end in TuningInstanceSingleCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:164:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:184:3'): on_result in TuningInstanceSingleCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:184:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:207:3'): on_tuning_result_begin in TuningInstanceBatchMultiCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:207:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:228:3'): on_result_end in TuningInstanceBatchMultiCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:228:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:248:3'): on_result in TuningInstanceBatchMultiCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:248:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:277:3'): on_resample_begin works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:277:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:305:3'): on_resample_before_train works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:305:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:332:3'): on_resample_before_predict works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:332:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:360:3'): on_resample_end works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:360:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:12:3'): objective async works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:12:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:32:3'): store benchmark result works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:32:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:54:3'): store models works ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:54:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:76:3'): rush objective with multiple measures works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:76:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:14:3'): ObjectiveTuningBatch ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:14:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:37:3'): ObjectiveTuningBatch - Multiple measures ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:37:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:52:3'): ObjectiveTuningBatch - Store models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:52:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:69:3'): runtime of learners is added ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:69:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:105:3'): tuner can modify resampling ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─instance$eval_batch(data.table(cp = 0.001)) at test_ObjectiveTuningBatch.R:105:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:128:3'): benchmark clone works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, clone = c()) at test_ObjectiveTuningBatch.R:128:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:149:3'): objects are cloned ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:149:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:5:5'): API ─────────────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(rs$optimize(inst), nrows = 1) at test_Tuner.R:5:5
2. │ └─checkmate::checkDataTable(...)
3. └─rs$optimize(inst)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
14. └─inst$eval_batch(design$data)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:46:3'): we get a result when some subordinate params are not fulfilled ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(d) at test_Tuner.R:46:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:90:3'): Tuner works with graphlearner ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_Tuner.R:90:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:121:3'): Tuner works with instantiated resampling ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─rs$optimize(inst) at test_Tuner.R:121:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:182:3'): internal single crit ──────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:182:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:205:3'): internal single crit without benchmark_result ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:205:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:235:3'): internal multi crit ───────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:235:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:294:3'): internal tuning: branching ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_Tuner.R:294:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:325:3'): parameter transformations can be used with internal tuning ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:325:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:348:3'): tag internal tune token manually in primary search space ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:348:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchCmaes.R:12:3'): TunerBatchCmaes ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchCmaes.R:12:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchCmaes__.optimize(...)
13. ├─mlr3misc::invoke(...)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─adagio::pureCMAES(...)
18. └─adagio (local) fun(arx[, k])
19. └─bbotk (local) fct(x, ...)
20. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
21. └─private$.objective_function(x, self, self$objective_multiplicator)
22. └─inst$eval_batch(xdt)
23. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
24. └─self$objective$eval_many(xss_trafoed)
25. └─bbotk:::.__Objective__eval_many(...)
26. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
27. │ └─base::eval.parent(expr, n = 1L)
28. │ └─base::eval(expr, p)
29. │ └─base::eval(expr, p)
30. └─private$.eval_many(xss = xss, resampling = `<list>`)
31. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
32. └─mlr3::benchmark(...)
33. └─ResultData$new(grid, data_extra, store_backends = store_backends)
34. └─mlr3 (local) initialize(...)
35. └─mlr3:::.__ResultData__initialize(...)
36. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
37. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchDesignPoints.R:3:3'): TunerBatchDesignPoints ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner(...) at test_TunerBatchDesignPoints.R:3:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchFromOptimizerBatch.R:13:3'): TunerBatchFromOptimizerBatch parameter set works after cloning ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner_2$optimize(instance) at test_TunerBatchFromOptimizerBatch.R:13:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGenSA.R:4:3'): TunerBatchGenSA ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global test_tuner("gensa") at test_TunerBatchGenSA.R:4:3
2. │ └─tuner$optimize(inst)
3. │ └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. │ └─private$.optimizer$optimize(inst)
5. │ └─bbotk:::.__OptimizerBatch__optimize(...)
6. │ └─bbotk::optimize_batch_default(inst, self)
7. │ ├─base::tryCatch(...)
8. │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. │ └─get_private(optimizer)$.optimize(instance)
12. │ └─bbotk:::.__OptimizerBatchGenSA__.optimize(...)
13. │ └─GenSA::GenSA(...)
14. └─GenSA (local) `<fn>`(`<dbl>`)
15. └─bbotk (local) fn(par, ...)
16. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
17. └─private$.objective_function(x, self, self$objective_multiplicator)
18. └─inst$eval_batch(xdt)
19. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
20. └─self$objective$eval_many(xss_trafoed)
21. └─bbotk:::.__Objective__eval_many(...)
22. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
23. │ └─base::eval.parent(expr, n = 1L)
24. │ └─base::eval(expr, p)
25. │ └─base::eval(expr, p)
26. └─private$.eval_many(xss = xss, resampling = `<list>`)
27. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
28. └─mlr3::benchmark(...)
29. └─ResultData$new(grid, data_extra, store_backends = store_backends)
30. └─mlr3 (local) initialize(...)
31. └─mlr3:::.__ResultData__initialize(...)
32. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
33. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGenSA.R:23:3'): TunerBatchGenSA with int params and trafo ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─tt$optimize(inst) at test_TunerBatchGenSA.R:23:3
2. │ └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. │ └─private$.optimizer$optimize(inst)
4. │ └─bbotk:::.__OptimizerBatch__optimize(...)
5. │ └─bbotk::optimize_batch_default(inst, self)
6. │ ├─base::tryCatch(...)
7. │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. │ └─get_private(optimizer)$.optimize(instance)
11. │ └─bbotk:::.__OptimizerBatchGenSA__.optimize(...)
12. │ └─GenSA::GenSA(...)
13. └─GenSA (local) `<fn>`(`<dbl>`)
14. └─bbotk (local) fn(par, ...)
15. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
16. └─private$.objective_function(x, self, self$objective_multiplicator)
17. └─inst$eval_batch(xdt)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGenSA.R:31:3'): TunerBatchGenSA - Optimize wrapper with maximize measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─tt$optimize(inst) at test_TunerBatchGenSA.R:31:3
2. │ └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. │ └─private$.optimizer$optimize(inst)
4. │ └─bbotk:::.__OptimizerBatch__optimize(...)
5. │ └─bbotk::optimize_batch_default(inst, self)
6. │ ├─base::tryCatch(...)
7. │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. │ └─get_private(optimizer)$.optimize(instance)
11. │ └─bbotk:::.__OptimizerBatchGenSA__.optimize(...)
12. │ └─GenSA::GenSA(...)
13. └─GenSA (local) `<fn>`(`<dbl>`)
14. └─bbotk (local) fn(par, ...)
15. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
16. └─private$.objective_function(x, self, self$objective_multiplicator)
17. └─inst$eval_batch(xdt)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGridSearch.R:2:3'): TunerGridSearch ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner(...) at test_TunerBatchGridSearch.R:2:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGridSearch.R:22:3'): TunerGridSearch with TerminatorNone ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TunerBatchGridSearch.R:22:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:4:3'): TunerIrace ────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner("irace", term_evals = 42) at test_TunerBatchIrace.R:4:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
13. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─irace::irace(scenario = scenario)
18. └─irace:::irace_common(scenario, simple = TRUE)
19. └─irace:::irace_run(scenario = scenario)
20. └─irace:::elitist_race(...)
21. └─irace:::race_wrapper(...)
22. └─irace:::race_wrapper_helper(...)
23. └─irace:::execute_experiments(...)
24. └─scenario$targetRunnerParallel(...)
25. └─tuning_instance$eval_batch(xdt)
26. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
27. └─self$objective$eval_many(xss_trafoed)
28. └─bbotk:::.__Objective__eval_many(...)
29. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
30. │ └─base::eval.parent(expr, n = 1L)
31. │ └─base::eval(expr, p)
32. │ └─base::eval(expr, p)
33. └─private$.eval_many(xss = xss, resampling = `<list>`)
34. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
35. └─mlr3::benchmark(...)
36. └─ResultData$new(grid, data_extra, store_backends = store_backends)
37. └─mlr3 (local) initialize(...)
38. └─mlr3:::.__ResultData__initialize(...)
39. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
40. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:37:36'): TunerIrace works with dependencies ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:37:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. └─tuner$optimize(instance) at test_TunerBatchIrace.R:37:36
6. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
7. └─private$.optimizer$optimize(inst)
8. └─bbotk:::.__OptimizerBatch__optimize(...)
9. └─bbotk::optimize_batch_default(inst, self)
10. ├─base::tryCatch(...)
11. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
12. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
13. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
14. └─get_private(optimizer)$.optimize(instance)
15. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
16. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─irace::irace(scenario = scenario)
21. └─irace:::irace_common(scenario, simple = TRUE)
22. └─irace:::irace_run(scenario = scenario)
23. └─irace:::elitist_race(...)
24. └─irace:::race_wrapper(...)
25. └─irace:::race_wrapper_helper(...)
26. └─irace:::execute_experiments(...)
27. └─scenario$targetRunnerParallel(...)
28. └─tuning_instance$eval_batch(xdt)
29. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
30. └─self$objective$eval_many(xss_trafoed)
31. └─bbotk:::.__Objective__eval_many(...)
32. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
33. │ └─base::eval.parent(expr, n = 1L)
34. │ └─base::eval(expr, p)
35. │ └─base::eval(expr, p)
36. └─private$.eval_many(xss = xss, resampling = `<list>`)
37. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
38. └─mlr3::benchmark(...)
39. └─ResultData$new(grid, data_extra, store_backends = store_backends)
40. └─mlr3 (local) initialize(...)
41. └─mlr3:::.__ResultData__initialize(...)
42. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
43. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:56:36'): TunerIrace works with logical parameters ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:56:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. └─tuner$optimize(instance) at test_TunerBatchIrace.R:56:36
6. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
7. └─private$.optimizer$optimize(inst)
8. └─bbotk:::.__OptimizerBatch__optimize(...)
9. └─bbotk::optimize_batch_default(inst, self)
10. ├─base::tryCatch(...)
11. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
12. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
13. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
14. └─get_private(optimizer)$.optimize(instance)
15. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
16. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─irace::irace(scenario = scenario)
21. └─irace:::irace_common(scenario, simple = TRUE)
22. └─irace:::irace_run(scenario = scenario)
23. └─irace:::elitist_race(...)
24. └─irace:::race_wrapper(...)
25. └─irace:::race_wrapper_helper(...)
26. └─irace:::execute_experiments(...)
27. └─scenario$targetRunnerParallel(...)
28. └─tuning_instance$eval_batch(xdt)
29. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
30. └─self$objective$eval_many(xss_trafoed)
31. └─bbotk:::.__Objective__eval_many(...)
32. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
33. │ └─base::eval.parent(expr, n = 1L)
34. │ └─base::eval(expr, p)
35. │ └─base::eval(expr, p)
36. └─private$.eval_many(xss = xss, resampling = `<list>`)
37. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
38. └─mlr3::benchmark(...)
39. └─ResultData$new(grid, data_extra, store_backends = store_backends)
40. └─mlr3 (local) initialize(...)
41. └─mlr3:::.__ResultData__initialize(...)
42. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
43. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:70:36'): TunerIrace uses digits ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:70:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. ├─checkmate::expect_data_table(tuner$optimize(instance)) at test_TunerBatchIrace.R:70:36
6. │ └─checkmate::checkDataTable(...)
7. └─tuner$optimize(instance)
8. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
9. └─private$.optimizer$optimize(inst)
10. └─bbotk:::.__OptimizerBatch__optimize(...)
11. └─bbotk::optimize_batch_default(inst, self)
12. ├─base::tryCatch(...)
13. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
14. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
15. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
16. └─get_private(optimizer)$.optimize(instance)
17. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
18. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─irace::irace(scenario = scenario)
23. └─irace:::irace_common(scenario, simple = TRUE)
24. └─irace:::irace_run(scenario = scenario)
25. └─irace:::elitist_race(...)
26. └─irace:::race_wrapper(...)
27. └─irace:::race_wrapper_helper(...)
28. └─irace:::execute_experiments(...)
29. └─scenario$targetRunnerParallel(...)
30. └─tuning_instance$eval_batch(xdt)
31. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
32. └─self$objective$eval_many(xss_trafoed)
33. └─bbotk:::.__Objective__eval_many(...)
34. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
35. │ └─base::eval.parent(expr, n = 1L)
36. │ └─base::eval(expr, p)
37. │ └─base::eval(expr, p)
38. └─private$.eval_many(xss = xss, resampling = `<list>`)
39. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
40. └─mlr3::benchmark(...)
41. └─ResultData$new(grid, data_extra, store_backends = store_backends)
42. └─mlr3 (local) initialize(...)
43. └─mlr3:::.__ResultData__initialize(...)
44. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
45. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:84:36'): TunerIrace works with unnamed discrete values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:84:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. ├─checkmate::expect_data_table(tuner$optimize(instance)) at test_TunerBatchIrace.R:84:36
6. │ └─checkmate::checkDataTable(...)
7. └─tuner$optimize(instance)
8. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
9. └─private$.optimizer$optimize(inst)
10. └─bbotk:::.__OptimizerBatch__optimize(...)
11. └─bbotk::optimize_batch_default(inst, self)
12. ├─base::tryCatch(...)
13. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
14. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
15. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
16. └─get_private(optimizer)$.optimize(instance)
17. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
18. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─irace::irace(scenario = scenario)
23. └─irace:::irace_common(scenario, simple = TRUE)
24. └─irace:::irace_run(scenario = scenario)
25. └─irace:::elitist_race(...)
26. └─irace:::race_wrapper(...)
27. └─irace:::race_wrapper_helper(...)
28. └─irace:::execute_experiments(...)
29. └─scenario$targetRunnerParallel(...)
30. └─tuning_instance$eval_batch(xdt)
31. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
32. └─self$objective$eval_many(xss_trafoed)
33. └─bbotk:::.__Objective__eval_many(...)
34. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
35. │ └─base::eval.parent(expr, n = 1L)
36. │ └─base::eval(expr, p)
37. │ └─base::eval(expr, p)
38. └─private$.eval_many(xss = xss, resampling = `<list>`)
39. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
40. └─mlr3::benchmark(...)
41. └─ResultData$new(grid, data_extra, store_backends = store_backends)
42. └─mlr3 (local) initialize(...)
43. └─mlr3:::.__ResultData__initialize(...)
44. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
45. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchNLoptr.R:5:3'): TunerNLoptr ──────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner("nloptr", algorithm = "NLOPT_LN_BOBYQA", term_evals = 4) at test_TunerBatchNLoptr.R:5:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchNLoptr__.optimize(...)
13. ├─mlr3misc::invoke(...)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─nloptr::nloptr(...)
18. └─bbotk (local) eval_f(x0, ...)
19. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
20. └─private$.objective_function(x, self, self$objective_multiplicator)
21. └─inst$eval_batch(xdt)
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchRandomSearch.R:2:3'): TunerRandomSearch ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner("random_search") at test_TunerBatchRandomSearch.R:2:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerInternal.R:18:3'): tuner internal works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerInternal.R:18:3
2. └─mlr3tuning:::.__TunerBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3tuning:::.__TunerBatchInternal__.optimize(...)
10. └─inst$eval_batch(data.table())
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(list(list()))
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:19:3'): tuning with multiple objectives ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchMultiCrit.R:19:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:35:3'): store_benchmark_result and store_models flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(...) at test_TuningInstanceBatchMultiCrit.R:35:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:64:3'): check_values flag with parameter set dependencies ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchMultiCrit.R:64:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:114:3'): TuneToken and result_learner_param_vals works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TuningInstanceBatchMultiCrit.R:114:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
12. └─instance$eval_batch(design[inds, ])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:122:3'): TuningInstanceBatchMultiCrit and empty search space works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TuningInstanceBatchMultiCrit.R:122:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(list(list()))
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:186:3'): Batch multi-crit internal tuning works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), min.rows = 1) at test_TuningInstanceBatchMultiCrit.R:186:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
14. └─inst$eval_batch(design$data)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:9:3'): TuningInstanceBatchSingleCrit ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(...) at test_TuningInstanceBatchSingleCrit.R:9:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:46:3'): archive one row (#40) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(data.table(cp = 0.1)) at test_TuningInstanceBatchSingleCrit.R:46:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:55:3'): eval_batch and termination ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(design[1:2, ]) at test_TuningInstanceBatchSingleCrit.R:55:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:76:3'): the same experiment can be added twice ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(d) at test_TuningInstanceBatchSingleCrit.R:76:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:99:3'): tuning with custom resampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchSingleCrit.R:99:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:128:3'): non-scalar hyperpars (#201) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tnr("random_search")$optimize(inst) at test_TuningInstanceBatchSingleCrit.R:128:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:136:3'): store_benchmark_result and store_models flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(...) at test_TuningInstanceBatchSingleCrit.R:136:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:170:3'): check_values flag with parameter set dependencies ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchSingleCrit.R:170:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:220:3'): TuneToken and result_learner_param_vals works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TuningInstanceBatchSingleCrit.R:220:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
12. └─instance$eval_batch(design[inds, ])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:230:3'): TuningInstanceBatchSingleCrit and empty search space works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TuningInstanceBatchSingleCrit.R:230:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(list(list()))
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:413:3'): objective contains no benchmark results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TuningInstanceBatchSingleCrit.R:413:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(list(list()))
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:422:3'): dependencies in defaults work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_class(...) at test_TuningInstanceBatchSingleCrit.R:422:3
2. │ └─checkmate::checkClass(x, classes, ordered, null.ok)
3. └─mlr3tuning::tune(...)
4. └─tuner$optimize(instance)
5. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
6. └─private$.optimizer$optimize(inst)
7. └─bbotk:::.__OptimizerBatch__optimize(...)
8. └─bbotk::optimize_batch_default(inst, self)
9. ├─base::tryCatch(...)
10. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
11. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
12. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
13. └─get_private(optimizer)$.optimize(instance)
14. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
15. └─inst$eval_batch(design$data)
16. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
17. └─self$objective$eval_many(xss_trafoed)
18. └─bbotk:::.__Objective__eval_many(...)
19. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
20. │ └─base::eval.parent(expr, n = 1L)
21. │ └─base::eval(expr, p)
22. │ └─base::eval(expr, p)
23. └─private$.eval_many(xss = xss, resampling = `<list>`)
24. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
25. └─mlr3::benchmark(...)
26. └─ResultData$new(grid, data_extra, store_backends = store_backends)
27. └─mlr3 (local) initialize(...)
28. └─mlr3:::.__ResultData__initialize(...)
29. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
30. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:459:3'): Batch single-crit internal tuning works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), nrows = 1) at test_TuningInstanceBatchSingleCrit.R:459:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
14. └─inst$eval_batch(design$data)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Failure ('test_TuningInstanceBatchSingleCrit.R:478:3'): required parameter can be tuned internally without having a value set ──
Expected `tune(...)` not to throw any errors.
Actually got a <simpleError> with message:
attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TuningInstanceBatchSingleCrit.R:478:3
2. │ └─testthat:::expect_condition_matching_(...)
3. │ └─testthat:::quasi_capture(...)
4. │ ├─testthat (local) .capture(...)
5. │ │ └─base::withCallingHandlers(...)
6. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
7. └─mlr3tuning::tune(...)
8. └─tuner$optimize(instance)
9. └─mlr3tuning:::.__TunerBatch__optimize(...)
10. └─bbotk::optimize_batch_default(inst, self)
11. ├─base::tryCatch(...)
12. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
13. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
14. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
15. └─get_private(optimizer)$.optimize(instance)
16. └─mlr3tuning:::.__TunerBatchInternal__.optimize(...)
17. └─inst$eval_batch(data.table())
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(list(list()))
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_error_handling.R:12:3'): failing learner ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─mlr3tuning:::expect_resample_error(tt$optimize(instance), "classif.debug->train") at test_error_handling.R:12:3
2. │ ├─base::withCallingHandlers(...) at ./helper.R:26:3
3. │ └─testthat::expect_error(...)
4. │ └─testthat:::expect_condition_matching_(...)
5. │ └─testthat:::quasi_capture(...)
6. │ ├─testthat (local) .capture(...)
7. │ │ └─base::withCallingHandlers(...)
8. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
9. └─tt$optimize(instance)
10. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
11. └─private$.optimizer$optimize(inst)
12. └─bbotk:::.__OptimizerBatch__optimize(...)
13. └─bbotk::optimize_batch_default(inst, self)
14. ├─base::tryCatch(...)
15. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
16. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
17. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
18. └─get_private(optimizer)$.optimize(instance)
19. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
20. └─inst$eval_batch(design$data)
21. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
22. └─self$objective$eval_many(xss_trafoed)
23. └─bbotk:::.__Objective__eval_many(...)
24. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
25. │ └─base::eval.parent(expr, n = 1L)
26. │ └─base::eval(expr, p)
27. │ └─base::eval(expr, p)
28. └─private$.eval_many(xss = xss, resampling = `<list>`)
29. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
30. └─mlr3::benchmark(...)
31. └─ResultData$new(grid, data_extra, store_backends = store_backends)
32. └─mlr3 (local) initialize(...)
33. └─mlr3:::.__ResultData__initialize(...)
34. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
35. └─data.table:::`[.data.table`(...)
── Error ('test_error_handling.R:36:3'): predictions missing ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─mlr3tuning:::expect_resample_error(tt$optimize(instance), "missing") at test_error_handling.R:36:3
2. │ ├─base::withCallingHandlers(...) at ./helper.R:26:3
3. │ └─testthat::expect_error(...)
4. │ └─testthat:::expect_condition_matching_(...)
5. │ └─testthat:::quasi_capture(...)
6. │ ├─testthat (local) .capture(...)
7. │ │ └─base::withCallingHandlers(...)
8. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
9. └─tt$optimize(instance)
10. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
11. └─private$.optimizer$optimize(inst)
12. └─bbotk:::.__OptimizerBatch__optimize(...)
13. └─bbotk::optimize_batch_default(inst, self)
14. ├─base::tryCatch(...)
15. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
16. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
17. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
18. └─get_private(optimizer)$.optimize(instance)
19. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
20. └─inst$eval_batch(design$data)
21. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
22. └─self$objective$eval_many(xss_trafoed)
23. └─bbotk:::.__Objective__eval_many(...)
24. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
25. │ └─base::eval.parent(expr, n = 1L)
26. │ └─base::eval(expr, p)
27. │ └─base::eval(expr, p)
28. └─private$.eval_many(xss = xss, resampling = `<list>`)
29. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
30. └─mlr3::benchmark(...)
31. └─ResultData$new(grid, data_extra, store_backends = store_backends)
32. └─mlr3 (local) initialize(...)
33. └─mlr3:::.__ResultData__initialize(...)
34. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
35. └─data.table:::`[.data.table`(...)
── Error ('test_extract_inner_tuning_archives.R:11:3'): extract_inner_tuning_archives function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, at, resampling_outer, store_models = TRUE) at test_extract_inner_tuning_archives.R:11:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_tuning_archives.R:131:3'): works with internal tuning ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(...) at test_extract_inner_tuning_archives.R:131:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_tuning_results.R:11:3'): extract_inner_tuning_results function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, at, resampling_outer, store_models = TRUE) at test_extract_inner_tuning_results.R:11:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_tuning_results.R:131:3'): extract_inner_tuning_results returns tuning_instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("penguins"), at, resampling_outer, store_models = TRUE) at test_extract_inner_tuning_results.R:131:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_mlr_callbacks.R:6:3'): backup callback works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:6:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:23:3'): backup callback works with standalone tuner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:23:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:282:3'): batch default configuration callback works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:282:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. └─mlr3misc::call_back(...)
8. └─mlr3misc::walk(...)
9. └─mlr3misc (local) .f(.xi, ...)
10. └─callback$call(stage, context)
11. └─self[[stage]](self, context)
12. └─context$instance$eval_batch(xdt)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:299:3'): batch default configuration callback works with logscale ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:299:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. └─mlr3misc::call_back(...)
8. └─mlr3misc::walk(...)
9. └─mlr3misc (local) .f(.xi, ...)
10. └─callback$call(stage, context)
11. └─self[[stage]](self, context)
12. └─context$instance$eval_batch(xdt)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:332:3'): batch default configuration callback works without transformation and with logscale ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:332:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. └─mlr3misc::call_back(...)
8. └─mlr3misc::walk(...)
9. └─mlr3misc (local) .f(.xi, ...)
10. └─callback$call(stage, context)
11. └─self[[stage]](self, context)
12. └─context$instance$eval_batch(xdt)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:437:3'): one se rule callback works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:437:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_trafos.R:10:3'): simple exp trafo works ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_trafos.R:10:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
12. └─instance$eval_batch(design[inds, ])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_trafos.R:34:3'): trafo where param names change ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_trafos.R:34:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_tune.R:3:3'): tune function works with one measure ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_tune.R:3:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_tune.R:13:3'): tune function works with multiple measures ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_tune.R:13:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_tune.R:23:3'): tune function works without measure ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_tune.R:23:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_tune_nested.R:5:3'): tune_nested function works ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune_nested(...) at test_tune_nested.R:5:3
2. └─mlr3::resample(task, at, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
[ FAIL 113 | WARN 9 | SKIP 68 | PASS 191 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.5.1
Check: examples
Result: ERROR
Running examples in ‘mlr3tuning-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: AutoTuner
> ### Title: Class for Automatic Tuning
> ### Aliases: AutoTuner
>
> ### ** Examples
>
> # Automatic Tuning
>
> # split to train and external set
> task = tsk("penguins")
> split = partition(task, ratio = 0.8)
>
> # load learner and set search space
> learner = lrn("classif.rpart",
+ cp = to_tune(1e-04, 1e-1, logscale = TRUE)
+ )
>
> # create auto tuner
> at = auto_tuner(
+ tuner = tnr("random_search"),
+ learner = learner,
+ resampling = rsmp ("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 4)
>
> # tune hyperparameters and fit final model
> at$train(task, row_ids = split$train)
INFO [17:18:14.071] [bbotk] Starting to optimize 1 parameter(s) with '<OptimizerBatchRandomSearch>' and '<TerminatorEvals> [n_evals=4, k=0]'
INFO [17:18:14.155] [bbotk] Evaluating 1 configuration(s)
INFO [17:18:14.177] [mlr3] Running benchmark with 1 resampling iterations
INFO [17:18:14.255] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 1/1)
INFO [17:18:14.289] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: <Anonymous> ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.5.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [68s/94s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3tuning")
+ test_check("mlr3tuning")
+ }
Loading required package: mlr3
Loading required package: paradox
Saving _problems/test_ArchiveBatchTuning-11.R
Saving _problems/test_ArchiveBatchTuning-126.R
Saving _problems/test_ArchiveBatchTuning-277.R
Saving _problems/test_AutoTuner-10.R
Saving _problems/test_AutoTuner-42.R
Saving _problems/test_AutoTuner-77.R
Saving _problems/test_AutoTuner-93.R
Saving _problems/test_AutoTuner-118.R
Saving _problems/test_AutoTuner-155.R
Saving _problems/test_AutoTuner-184.R
Saving _problems/test_AutoTuner-246.R
Saving _problems/test_AutoTuner-282.R
Saving _problems/test_AutoTuner-308.R
Saving _problems/test_AutoTuner-373.R
Saving _problems/test_AutoTuner-389.R
Saving _problems/test_AutoTuner-420.R
Saving _problems/test_AutoTuner-434.R
Saving _problems/test_AutoTuner-480.R
Saving _problems/test_AutoTuner-606.R
Saving _problems/test_AutoTuner-625.R
Saving _problems/test_AutoTuner-676.R
Saving _problems/test_AutoTuner-699.R
Saving _problems/test_CallbackBatchTuning-17.R
Saving _problems/test_CallbackBatchTuning-37.R
Saving _problems/test_CallbackBatchTuning-59.R
Saving _problems/test_CallbackBatchTuning-80.R
Saving _problems/test_CallbackBatchTuning-103.R
Saving _problems/test_CallbackBatchTuning-127.R
Saving _problems/test_CallbackBatchTuning-150.R
Saving _problems/test_CallbackBatchTuning-171.R
Saving _problems/test_CallbackBatchTuning-191.R
Saving _problems/test_CallbackBatchTuning-214.R
Saving _problems/test_CallbackBatchTuning-235.R
Saving _problems/test_CallbackBatchTuning-255.R
Saving _problems/test_CallbackBatchTuning-284.R
Saving _problems/test_CallbackBatchTuning-312.R
Saving _problems/test_CallbackBatchTuning-339.R
Saving _problems/test_CallbackBatchTuning-367.R
Saving _problems/test_ObjectiveTuningAsync-12.R
Saving _problems/test_ObjectiveTuningAsync-32.R
Saving _problems/test_ObjectiveTuningAsync-54.R
Saving _problems/test_ObjectiveTuningAsync-76.R
Saving _problems/test_ObjectiveTuningBatch-14.R
Saving _problems/test_ObjectiveTuningBatch-37.R
Saving _problems/test_ObjectiveTuningBatch-52.R
Saving _problems/test_ObjectiveTuningBatch-69.R
Saving _problems/test_ObjectiveTuningBatch-105.R
Saving _problems/test_ObjectiveTuningBatch-128.R
Saving _problems/test_ObjectiveTuningBatch-149.R
Saving _problems/test_Tuner-5.R
Saving _problems/test_Tuner-46.R
Saving _problems/test_Tuner-90.R
Saving _problems/test_Tuner-121.R
Saving _problems/test_Tuner-188.R
Saving _problems/test_Tuner-212.R
Saving _problems/test_Tuner-242.R
Saving _problems/test_Tuner-294.R
Saving _problems/test_Tuner-336.R
Saving _problems/test_Tuner-355.R
Saving _problems/test_TunerBatchCmaes-19.R
Saving _problems/test_TunerBatchDesignPoints-3.R
Saving _problems/test_TunerBatchFromOptimizerBatch-13.R
Saving _problems/test_TunerBatchGenSA-4.R
Saving _problems/test_TunerBatchGenSA-23.R
Saving _problems/test_TunerBatchGenSA-31.R
Saving _problems/test_TunerBatchGridSearch-2.R
Saving _problems/test_TunerBatchGridSearch-22.R
# 2025-12-20 17:19:04 CET: Initialization
# Elitist race
# Elitist new instances: 1
# Elitist limit: 2
# nbIterations: 2
# minNbSurvival: 2
# nbParameters: 1
# seed: 81639095
# confidence level: 0.95
# budget: 42
# mu: 5
# deterministic: FALSE
# 2025-12-20 17:19:04 CET: Iteration 1 of 2
# experimentsUsed: 0
# remainingBudget: 42
# currentBudget: 21
# nbConfigurations: 3
# Markers:
x No test is performed.
c Configurations are discarded only due to capping.
- The test is performed and some configurations are discarded.
= The test is performed but no configuration is discarded.
! The test is performed and configurations could be discarded but elite configurations are preserved.
. All alive configurations are elite and nothing is discarded.
+-+-----------+-----------+-----------+----------------+-----------+--------+-----+----+------+
| | Instance| Alive| Best| Mean best| Exp so far| W time| rho|KenW| Qvar|
+-+-----------+-----------+-----------+----------------+-----------+--------+-----+----+------+
Saving _problems/test_TunerBatchIrace-4.R
Saving _problems/test_TunerBatchNLoptr-5.R
Saving _problems/test_TunerBatchRandomSearch-2.R
Saving _problems/test_TunerInternal-18.R
Saving _problems/test_TuningInstanceBatchMultiCrit-19.R
Saving _problems/test_TuningInstanceBatchMultiCrit-35.R
Saving _problems/test_TuningInstanceBatchMultiCrit-64.R
Saving _problems/test_TuningInstanceBatchMultiCrit-114.R
Saving _problems/test_TuningInstanceBatchMultiCrit-129.R
Saving _problems/test_TuningInstanceBatchMultiCrit-186.R
Saving _problems/test_TuningInstanceBatchSingleCrit-9.R
Saving _problems/test_TuningInstanceBatchSingleCrit-46.R
Saving _problems/test_TuningInstanceBatchSingleCrit-55.R
Saving _problems/test_TuningInstanceBatchSingleCrit-76.R
Saving _problems/test_TuningInstanceBatchSingleCrit-99.R
Saving _problems/test_TuningInstanceBatchSingleCrit-128.R
Saving _problems/test_TuningInstanceBatchSingleCrit-136.R
Saving _problems/test_TuningInstanceBatchSingleCrit-170.R
Saving _problems/test_TuningInstanceBatchSingleCrit-220.R
Saving _problems/test_TuningInstanceBatchSingleCrit-237.R
Saving _problems/test_TuningInstanceBatchSingleCrit-413.R
Saving _problems/test_TuningInstanceBatchSingleCrit-428.R
Saving _problems/test_TuningInstanceBatchSingleCrit-459.R
Saving _problems/test_TuningInstanceBatchSingleCrit-484.R
Saving _problems/test_error_handling-18.R
Saving _problems/test_error_handling-36.R
Saving _problems/test_extract_inner_tuning_archives-11.R
Saving _problems/test_extract_inner_tuning_archives-131.R
Saving _problems/test_extract_inner_tuning_results-11.R
Saving _problems/test_extract_inner_tuning_results-131.R
Saving _problems/test_mlr_callbacks-14.R
Saving _problems/test_mlr_callbacks-31.R
Saving _problems/test_mlr_callbacks-290.R
Saving _problems/test_mlr_callbacks-307.R
Saving _problems/test_mlr_callbacks-340.R
Saving _problems/test_mlr_callbacks-445.R
Saving _problems/test_trafos-10.R
Saving _problems/test_trafos-34.R
Saving _problems/test_tune-4.R
Saving _problems/test_tune-14.R
Saving _problems/test_tune-24.R
Saving _problems/test_tune_nested-6.R
[ FAIL 113 | WARN 9 | SKIP 68 | PASS 192 ]
══ Skipped tests (68) ══════════════════════════════════════════════════════════
• On CRAN (68): 'test_ArchiveAsyncTuning.R:2:3',
'test_ArchiveAsyncTuning.R:61:3', 'test_ArchiveAsyncTuning.R:119:3',
'test_ArchiveAsyncTuning.R:146:3', 'test_ArchiveAsyncTuning.R:169:3',
'test_ArchiveAsyncTuning.R:209:3', 'test_ArchiveAsyncTuning.R:251:3',
'test_ArchiveAsyncTuning.R:284:3', 'test_ArchiveAsyncTuningFrozen.R:2:3',
'test_AutoTuner.R:640:3', 'test_CallbackAsyncTuning.R:4:3',
'test_CallbackAsyncTuning.R:33:3', 'test_CallbackAsyncTuning.R:64:3',
'test_CallbackAsyncTuning.R:93:3', 'test_CallbackAsyncTuning.R:124:3',
'test_CallbackAsyncTuning.R:160:3', 'test_CallbackAsyncTuning.R:188:3',
'test_CallbackAsyncTuning.R:222:3', 'test_CallbackAsyncTuning.R:252:3',
'test_CallbackAsyncTuning.R:281:3', 'test_CallbackAsyncTuning.R:312:3',
'test_CallbackAsyncTuning.R:343:3', 'test_CallbackAsyncTuning.R:373:3',
'test_CallbackAsyncTuning.R:405:3', 'test_CallbackAsyncTuning.R:443:3',
'test_CallbackAsyncTuning.R:480:3', 'test_CallbackAsyncTuning.R:516:3',
'test_Tuner.R:53:1', 'test_TunerAsyncDesignPoints.R:2:3',
'test_TunerAsyncGridSearch.R:2:3', 'test_TunerAsyncRandomSearch.R:2:3',
'test_TuningInstanceAsyncMultiCrit.R:2:3',
'test_TuningInstanceAsyncMultiCrit.R:30:3',
'test_TuningInstanceAsyncMultiCrit.R:57:3',
'test_TuningInstanceAsyncMultiCrit.R:81:3',
'test_TuningInstanceAsyncMultiCrit.R:106:3',
'test_TuningInstanceAsyncMultiCrit.R:134:3',
'test_TuningInstanceAsyncMultiCrit.R:189:3',
'test_TuningInstanceAsyncMultiCrit.R:236:3',
'test_TuningInstanceAsyncMultiCrit.R:261:3',
'test_TuningInstanceAsyncSingleCrit.R:2:3',
'test_TuningInstanceAsyncSingleCrit.R:29:3',
'test_TuningInstanceAsyncSingleCrit.R:54:3',
'test_TuningInstanceAsyncSingleCrit.R:78:3',
'test_TuningInstanceAsyncSingleCrit.R:104:3',
'test_TuningInstanceAsyncSingleCrit.R:131:3',
'test_TuningInstanceAsyncSingleCrit.R:182:3',
'test_TuningInstanceAsyncSingleCrit.R:213:3',
'test_TuningInstanceAsyncSingleCrit.R:226:3',
'test_TuningInstanceAsyncSingleCrit.R:240:3',
'test_TuningInstanceAsyncSingleCrit.R:266:3', 'test_auto_tuner.R:25:3',
'test_auto_tuner.R:48:3', 'test_mlr_callbacks.R:40:3',
'test_mlr_callbacks.R:93:3', 'test_mlr_callbacks.R:117:3',
'test_mlr_callbacks.R:141:3', 'test_mlr_callbacks.R:162:3',
'test_mlr_callbacks.R:192:3', 'test_mlr_callbacks.R:218:3',
'test_mlr_callbacks.R:251:3', 'test_mlr_callbacks.R:410:3',
'test_mlr_callbacks.R:452:3', 'test_mlr_callbacks.R:480:3',
'test_ti_async.R:2:3', 'test_ti_async.R:16:3', 'test_ti_async.R:30:3',
'test_ti_async.R:42:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ArchiveBatchTuning.R:11:3'): ArchiveTuning access methods work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_ArchiveBatchTuning.R:11:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchTuning.R:126:3'): ArchiveTuning as.data.table function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_ArchiveBatchTuning.R:126:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchTuning.R:277:3'): ArchiveBatchTuning as.data.table function works for internally tuned values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_ArchiveBatchTuning.R:277:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:10:3'): AutoTuner / train+predict ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:10:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
23. └─inst$eval_batch(g$data[inds])
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:42:3'): AutoTuner / resample ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, r_outer, store_models = TRUE) at test_AutoTuner.R:42:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:77:3'): nested resamppling results are consistent ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), lrn, cv2, store_models = TRUE) at test_AutoTuner.R:77:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:93:3'): AT training does not change learner in instance args ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:93:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:118:3'): AutoTuner works with graphlearner ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:118:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
23. └─inst$eval_batch(g$data[inds])
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:155:3'): Nested resampling works with graphlearner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:184:3'): store_tuning_instance, store_benchmark_result and store_models flags work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
23. └─inst$eval_batch(g$data[inds])
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:246:3'): predict_type works ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:246:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:282:3'): search space from TuneToken works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("iris")) at test_AutoTuner.R:282:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:308:3'): AutoTuner get_base_learner method works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("pima")) at test_AutoTuner.R:308:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:373:3'): AutoTuner hash works #647 in mlr3 ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_AutoTuner.R:373:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:389:3'): AutoTuner works with empty search space ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("pima")) at test_AutoTuner.R:389:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:420:3'): AutoTuner importance method works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("penguins")) at test_AutoTuner.R:420:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:434:3'): AutoTuner selected_features method works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("penguins")) at test_AutoTuner.R:434:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:480:3'): AutoTuner works with instantiated resampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:480:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:606:3'): marshalable learner ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:606:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:625:3'): marshal ───────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:625:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:676:3'): AutoTuner works with internal tuning and validation ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:676:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:699:3'): AutoTuner works when internal_search_space is part of primary search space ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:699:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:10:3'): on_optimization_begin works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:10:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:30:3'): on_optimization_end works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:30:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:52:3'): on_optimizer_after_eval works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:52:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:73:3'): on_optimizer_after_eval works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:73:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:96:3'): on_eval_after_design works ───────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:96:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:120:3'): on_eval_after_benchmark and on_eval_before_archive works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:120:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:143:3'): on_tuning_result_begin in TuningInstanceSingleCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:143:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:164:3'): on_result_end in TuningInstanceSingleCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:164:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:184:3'): on_result in TuningInstanceSingleCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:184:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:207:3'): on_tuning_result_begin in TuningInstanceBatchMultiCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:207:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:228:3'): on_result_end in TuningInstanceBatchMultiCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:228:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:248:3'): on_result in TuningInstanceBatchMultiCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:248:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:277:3'): on_resample_begin works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:277:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:305:3'): on_resample_before_train works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:305:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:332:3'): on_resample_before_predict works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:332:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:360:3'): on_resample_end works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:360:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:12:3'): objective async works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:12:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:32:3'): store benchmark result works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:32:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:54:3'): store models works ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:54:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:76:3'): rush objective with multiple measures works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:76:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:14:3'): ObjectiveTuningBatch ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:14:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:37:3'): ObjectiveTuningBatch - Multiple measures ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:37:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:52:3'): ObjectiveTuningBatch - Store models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:52:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:69:3'): runtime of learners is added ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:69:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:105:3'): tuner can modify resampling ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─instance$eval_batch(data.table(cp = 0.001)) at test_ObjectiveTuningBatch.R:105:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:128:3'): benchmark clone works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, clone = c()) at test_ObjectiveTuningBatch.R:128:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:149:3'): objects are cloned ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:149:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:5:5'): API ─────────────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(rs$optimize(inst), nrows = 1) at test_Tuner.R:5:5
2. │ └─checkmate::checkDataTable(...)
3. └─rs$optimize(inst)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
14. └─inst$eval_batch(design$data)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:46:3'): we get a result when some subordinate params are not fulfilled ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(d) at test_Tuner.R:46:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:90:3'): Tuner works with graphlearner ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_Tuner.R:90:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:121:3'): Tuner works with instantiated resampling ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─rs$optimize(inst) at test_Tuner.R:121:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:182:3'): internal single crit ──────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:182:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:205:3'): internal single crit without benchmark_result ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:205:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:235:3'): internal multi crit ───────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:235:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:294:3'): internal tuning: branching ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_Tuner.R:294:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:325:3'): parameter transformations can be used with internal tuning ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:325:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:348:3'): tag internal tune token manually in primary search space ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:348:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchCmaes.R:12:3'): TunerBatchCmaes ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchCmaes.R:12:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchCmaes__.optimize(...)
13. ├─mlr3misc::invoke(...)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─adagio::pureCMAES(...)
18. └─adagio (local) fun(arx[, k])
19. └─bbotk (local) fct(x, ...)
20. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
21. └─private$.objective_function(x, self, self$objective_multiplicator)
22. └─inst$eval_batch(xdt)
23. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
24. └─self$objective$eval_many(xss_trafoed)
25. └─bbotk:::.__Objective__eval_many(...)
26. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
27. │ └─base::eval.parent(expr, n = 1L)
28. │ └─base::eval(expr, p)
29. │ └─base::eval(expr, p)
30. └─private$.eval_many(xss = xss, resampling = `<list>`)
31. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
32. └─mlr3::benchmark(...)
33. └─ResultData$new(grid, data_extra, store_backends = store_backends)
34. └─mlr3 (local) initialize(...)
35. └─mlr3:::.__ResultData__initialize(...)
36. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
37. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchDesignPoints.R:3:3'): TunerBatchDesignPoints ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner(...) at test_TunerBatchDesignPoints.R:3:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchFromOptimizerBatch.R:13:3'): TunerBatchFromOptimizerBatch parameter set works after cloning ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner_2$optimize(instance) at test_TunerBatchFromOptimizerBatch.R:13:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGenSA.R:4:3'): TunerBatchGenSA ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global test_tuner("gensa") at test_TunerBatchGenSA.R:4:3
2. │ └─tuner$optimize(inst)
3. │ └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. │ └─private$.optimizer$optimize(inst)
5. │ └─bbotk:::.__OptimizerBatch__optimize(...)
6. │ └─bbotk::optimize_batch_default(inst, self)
7. │ ├─base::tryCatch(...)
8. │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. │ └─get_private(optimizer)$.optimize(instance)
12. │ └─bbotk:::.__OptimizerBatchGenSA__.optimize(...)
13. │ └─GenSA::GenSA(...)
14. └─GenSA (local) `<fn>`(`<dbl>`)
15. └─bbotk (local) fn(par, ...)
16. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
17. └─private$.objective_function(x, self, self$objective_multiplicator)
18. └─inst$eval_batch(xdt)
19. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
20. └─self$objective$eval_many(xss_trafoed)
21. └─bbotk:::.__Objective__eval_many(...)
22. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
23. │ └─base::eval.parent(expr, n = 1L)
24. │ └─base::eval(expr, p)
25. │ └─base::eval(expr, p)
26. └─private$.eval_many(xss = xss, resampling = `<list>`)
27. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
28. └─mlr3::benchmark(...)
29. └─ResultData$new(grid, data_extra, store_backends = store_backends)
30. └─mlr3 (local) initialize(...)
31. └─mlr3:::.__ResultData__initialize(...)
32. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
33. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGenSA.R:23:3'): TunerBatchGenSA with int params and trafo ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─tt$optimize(inst) at test_TunerBatchGenSA.R:23:3
2. │ └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. │ └─private$.optimizer$optimize(inst)
4. │ └─bbotk:::.__OptimizerBatch__optimize(...)
5. │ └─bbotk::optimize_batch_default(inst, self)
6. │ ├─base::tryCatch(...)
7. │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. │ └─get_private(optimizer)$.optimize(instance)
11. │ └─bbotk:::.__OptimizerBatchGenSA__.optimize(...)
12. │ └─GenSA::GenSA(...)
13. └─GenSA (local) `<fn>`(`<dbl>`)
14. └─bbotk (local) fn(par, ...)
15. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
16. └─private$.objective_function(x, self, self$objective_multiplicator)
17. └─inst$eval_batch(xdt)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGenSA.R:31:3'): TunerBatchGenSA - Optimize wrapper with maximize measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─tt$optimize(inst) at test_TunerBatchGenSA.R:31:3
2. │ └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. │ └─private$.optimizer$optimize(inst)
4. │ └─bbotk:::.__OptimizerBatch__optimize(...)
5. │ └─bbotk::optimize_batch_default(inst, self)
6. │ ├─base::tryCatch(...)
7. │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. │ └─get_private(optimizer)$.optimize(instance)
11. │ └─bbotk:::.__OptimizerBatchGenSA__.optimize(...)
12. │ └─GenSA::GenSA(...)
13. └─GenSA (local) `<fn>`(`<dbl>`)
14. └─bbotk (local) fn(par, ...)
15. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
16. └─private$.objective_function(x, self, self$objective_multiplicator)
17. └─inst$eval_batch(xdt)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGridSearch.R:2:3'): TunerGridSearch ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner(...) at test_TunerBatchGridSearch.R:2:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGridSearch.R:22:3'): TunerGridSearch with TerminatorNone ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TunerBatchGridSearch.R:22:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:4:3'): TunerIrace ────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner("irace", term_evals = 42) at test_TunerBatchIrace.R:4:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
13. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─irace::irace(scenario = scenario)
18. └─irace:::irace_common(scenario, simple = TRUE)
19. └─irace:::irace_run(scenario = scenario)
20. └─irace:::elitist_race(...)
21. └─irace:::race_wrapper(...)
22. └─irace:::race_wrapper_helper(...)
23. └─irace:::execute_experiments(...)
24. └─scenario$targetRunnerParallel(...)
25. └─tuning_instance$eval_batch(xdt)
26. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
27. └─self$objective$eval_many(xss_trafoed)
28. └─bbotk:::.__Objective__eval_many(...)
29. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
30. │ └─base::eval.parent(expr, n = 1L)
31. │ └─base::eval(expr, p)
32. │ └─base::eval(expr, p)
33. └─private$.eval_many(xss = xss, resampling = `<list>`)
34. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
35. └─mlr3::benchmark(...)
36. └─ResultData$new(grid, data_extra, store_backends = store_backends)
37. └─mlr3 (local) initialize(...)
38. └─mlr3:::.__ResultData__initialize(...)
39. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
40. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:37:36'): TunerIrace works with dependencies ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:37:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. └─tuner$optimize(instance) at test_TunerBatchIrace.R:37:36
6. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
7. └─private$.optimizer$optimize(inst)
8. └─bbotk:::.__OptimizerBatch__optimize(...)
9. └─bbotk::optimize_batch_default(inst, self)
10. ├─base::tryCatch(...)
11. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
12. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
13. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
14. └─get_private(optimizer)$.optimize(instance)
15. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
16. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─irace::irace(scenario = scenario)
21. └─irace:::irace_common(scenario, simple = TRUE)
22. └─irace:::irace_run(scenario = scenario)
23. └─irace:::elitist_race(...)
24. └─irace:::race_wrapper(...)
25. └─irace:::race_wrapper_helper(...)
26. └─irace:::execute_experiments(...)
27. └─scenario$targetRunnerParallel(...)
28. └─tuning_instance$eval_batch(xdt)
29. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
30. └─self$objective$eval_many(xss_trafoed)
31. └─bbotk:::.__Objective__eval_many(...)
32. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
33. │ └─base::eval.parent(expr, n = 1L)
34. │ └─base::eval(expr, p)
35. │ └─base::eval(expr, p)
36. └─private$.eval_many(xss = xss, resampling = `<list>`)
37. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
38. └─mlr3::benchmark(...)
39. └─ResultData$new(grid, data_extra, store_backends = store_backends)
40. └─mlr3 (local) initialize(...)
41. └─mlr3:::.__ResultData__initialize(...)
42. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
43. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:56:36'): TunerIrace works with logical parameters ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:56:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. └─tuner$optimize(instance) at test_TunerBatchIrace.R:56:36
6. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
7. └─private$.optimizer$optimize(inst)
8. └─bbotk:::.__OptimizerBatch__optimize(...)
9. └─bbotk::optimize_batch_default(inst, self)
10. ├─base::tryCatch(...)
11. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
12. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
13. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
14. └─get_private(optimizer)$.optimize(instance)
15. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
16. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─irace::irace(scenario = scenario)
21. └─irace:::irace_common(scenario, simple = TRUE)
22. └─irace:::irace_run(scenario = scenario)
23. └─irace:::elitist_race(...)
24. └─irace:::race_wrapper(...)
25. └─irace:::race_wrapper_helper(...)
26. └─irace:::execute_experiments(...)
27. └─scenario$targetRunnerParallel(...)
28. └─tuning_instance$eval_batch(xdt)
29. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
30. └─self$objective$eval_many(xss_trafoed)
31. └─bbotk:::.__Objective__eval_many(...)
32. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
33. │ └─base::eval.parent(expr, n = 1L)
34. │ └─base::eval(expr, p)
35. │ └─base::eval(expr, p)
36. └─private$.eval_many(xss = xss, resampling = `<list>`)
37. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
38. └─mlr3::benchmark(...)
39. └─ResultData$new(grid, data_extra, store_backends = store_backends)
40. └─mlr3 (local) initialize(...)
41. └─mlr3:::.__ResultData__initialize(...)
42. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
43. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:70:36'): TunerIrace uses digits ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:70:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. ├─checkmate::expect_data_table(tuner$optimize(instance)) at test_TunerBatchIrace.R:70:36
6. │ └─checkmate::checkDataTable(...)
7. └─tuner$optimize(instance)
8. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
9. └─private$.optimizer$optimize(inst)
10. └─bbotk:::.__OptimizerBatch__optimize(...)
11. └─bbotk::optimize_batch_default(inst, self)
12. ├─base::tryCatch(...)
13. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
14. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
15. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
16. └─get_private(optimizer)$.optimize(instance)
17. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
18. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─irace::irace(scenario = scenario)
23. └─irace:::irace_common(scenario, simple = TRUE)
24. └─irace:::irace_run(scenario = scenario)
25. └─irace:::elitist_race(...)
26. └─irace:::race_wrapper(...)
27. └─irace:::race_wrapper_helper(...)
28. └─irace:::execute_experiments(...)
29. └─scenario$targetRunnerParallel(...)
30. └─tuning_instance$eval_batch(xdt)
31. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
32. └─self$objective$eval_many(xss_trafoed)
33. └─bbotk:::.__Objective__eval_many(...)
34. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
35. │ └─base::eval.parent(expr, n = 1L)
36. │ └─base::eval(expr, p)
37. │ └─base::eval(expr, p)
38. └─private$.eval_many(xss = xss, resampling = `<list>`)
39. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
40. └─mlr3::benchmark(...)
41. └─ResultData$new(grid, data_extra, store_backends = store_backends)
42. └─mlr3 (local) initialize(...)
43. └─mlr3:::.__ResultData__initialize(...)
44. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
45. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:84:36'): TunerIrace works with unnamed discrete values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:84:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. ├─checkmate::expect_data_table(tuner$optimize(instance)) at test_TunerBatchIrace.R:84:36
6. │ └─checkmate::checkDataTable(...)
7. └─tuner$optimize(instance)
8. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
9. └─private$.optimizer$optimize(inst)
10. └─bbotk:::.__OptimizerBatch__optimize(...)
11. └─bbotk::optimize_batch_default(inst, self)
12. ├─base::tryCatch(...)
13. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
14. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
15. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
16. └─get_private(optimizer)$.optimize(instance)
17. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
18. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─irace::irace(scenario = scenario)
23. └─irace:::irace_common(scenario, simple = TRUE)
24. └─irace:::irace_run(scenario = scenario)
25. └─irace:::elitist_race(...)
26. └─irace:::race_wrapper(...)
27. └─irace:::race_wrapper_helper(...)
28. └─irace:::execute_experiments(...)
29. └─scenario$targetRunnerParallel(...)
30. └─tuning_instance$eval_batch(xdt)
31. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
32. └─self$objective$eval_many(xss_trafoed)
33. └─bbotk:::.__Objective__eval_many(...)
34. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
35. │ └─base::eval.parent(expr, n = 1L)
36. │ └─base::eval(expr, p)
37. │ └─base::eval(expr, p)
38. └─private$.eval_many(xss = xss, resampling = `<list>`)
39. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
40. └─mlr3::benchmark(...)
41. └─ResultData$new(grid, data_extra, store_backends = store_backends)
42. └─mlr3 (local) initialize(...)
43. └─mlr3:::.__ResultData__initialize(...)
44. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
45. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchNLoptr.R:5:3'): TunerNLoptr ──────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner("nloptr", algorithm = "NLOPT_LN_BOBYQA", term_evals = 4) at test_TunerBatchNLoptr.R:5:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchNLoptr__.optimize(...)
13. ├─mlr3misc::invoke(...)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─nloptr::nloptr(...)
18. └─bbotk (local) eval_f(x0, ...)
19. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
20. └─private$.objective_function(x, self, self$objective_multiplicator)
21. └─inst$eval_batch(xdt)
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchRandomSearch.R:2:3'): TunerRandomSearch ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner("random_search") at test_TunerBatchRandomSearch.R:2:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerInternal.R:18:3'): tuner internal works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerInternal.R:18:3
2. └─mlr3tuning:::.__TunerBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3tuning:::.__TunerBatchInternal__.optimize(...)
10. └─inst$eval_batch(data.table())
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(list(list()))
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:19:3'): tuning with multiple objectives ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchMultiCrit.R:19:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:35:3'): store_benchmark_result and store_models flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(...) at test_TuningInstanceBatchMultiCrit.R:35:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:64:3'): check_values flag with parameter set dependencies ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchMultiCrit.R:64:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:114:3'): TuneToken and result_learner_param_vals works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TuningInstanceBatchMultiCrit.R:114:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
12. └─instance$eval_batch(design[inds, ])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:122:3'): TuningInstanceBatchMultiCrit and empty search space works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TuningInstanceBatchMultiCrit.R:122:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(list(list()))
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:186:3'): Batch multi-crit internal tuning works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), min.rows = 1) at test_TuningInstanceBatchMultiCrit.R:186:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
14. └─inst$eval_batch(design$data)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:9:3'): TuningInstanceBatchSingleCrit ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(...) at test_TuningInstanceBatchSingleCrit.R:9:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:46:3'): archive one row (#40) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(data.table(cp = 0.1)) at test_TuningInstanceBatchSingleCrit.R:46:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:55:3'): eval_batch and termination ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(design[1:2, ]) at test_TuningInstanceBatchSingleCrit.R:55:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:76:3'): the same experiment can be added twice ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(d) at test_TuningInstanceBatchSingleCrit.R:76:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:99:3'): tuning with custom resampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchSingleCrit.R:99:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:128:3'): non-scalar hyperpars (#201) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tnr("random_search")$optimize(inst) at test_TuningInstanceBatchSingleCrit.R:128:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:136:3'): store_benchmark_result and store_models flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(...) at test_TuningInstanceBatchSingleCrit.R:136:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:170:3'): check_values flag with parameter set dependencies ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchSingleCrit.R:170:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:220:3'): TuneToken and result_learner_param_vals works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TuningInstanceBatchSingleCrit.R:220:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
12. └─instance$eval_batch(design[inds, ])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:230:3'): TuningInstanceBatchSingleCrit and empty search space works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TuningInstanceBatchSingleCrit.R:230:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(list(list()))
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:413:3'): objective contains no benchmark results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TuningInstanceBatchSingleCrit.R:413:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(list(list()))
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:422:3'): dependencies in defaults work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_class(...) at test_TuningInstanceBatchSingleCrit.R:422:3
2. │ └─checkmate::checkClass(x, classes, ordered, null.ok)
3. └─mlr3tuning::tune(...)
4. └─tuner$optimize(instance)
5. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
6. └─private$.optimizer$optimize(inst)
7. └─bbotk:::.__OptimizerBatch__optimize(...)
8. └─bbotk::optimize_batch_default(inst, self)
9. ├─base::tryCatch(...)
10. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
11. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
12. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
13. └─get_private(optimizer)$.optimize(instance)
14. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
15. └─inst$eval_batch(design$data)
16. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
17. └─self$objective$eval_many(xss_trafoed)
18. └─bbotk:::.__Objective__eval_many(...)
19. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
20. │ └─base::eval.parent(expr, n = 1L)
21. │ └─base::eval(expr, p)
22. │ └─base::eval(expr, p)
23. └─private$.eval_many(xss = xss, resampling = `<list>`)
24. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
25. └─mlr3::benchmark(...)
26. └─ResultData$new(grid, data_extra, store_backends = store_backends)
27. └─mlr3 (local) initialize(...)
28. └─mlr3:::.__ResultData__initialize(...)
29. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
30. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:459:3'): Batch single-crit internal tuning works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), nrows = 1) at test_TuningInstanceBatchSingleCrit.R:459:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
14. └─inst$eval_batch(design$data)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Failure ('test_TuningInstanceBatchSingleCrit.R:478:3'): required parameter can be tuned internally without having a value set ──
Expected `tune(...)` not to throw any errors.
Actually got a <simpleError> with message:
attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TuningInstanceBatchSingleCrit.R:478:3
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$optimize(instance)
9. └─mlr3tuning:::.__TunerBatch__optimize(...)
10. └─bbotk::optimize_batch_default(inst, self)
11. ├─base::tryCatch(...)
12. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
13. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
14. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
15. └─get_private(optimizer)$.optimize(instance)
16. └─mlr3tuning:::.__TunerBatchInternal__.optimize(...)
17. └─inst$eval_batch(data.table())
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(list(list()))
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_error_handling.R:18:3'): failing learner ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tt$optimize(instance) at test_error_handling.R:18:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_error_handling.R:36:3'): predictions missing ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─mlr3tuning:::expect_resample_error(tt$optimize(instance), "missing") at test_error_handling.R:36:3
2. │ ├─base::withCallingHandlers(...) at ./helper.R:26:3
3. │ └─testthat::expect_error(...)
4. │ └─testthat:::expect_condition_matching_(...)
5. │ └─testthat:::quasi_capture(...)
6. │ ├─testthat (local) .capture(...)
7. │ │ └─base::withCallingHandlers(...)
8. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
9. └─tt$optimize(instance)
10. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
11. └─private$.optimizer$optimize(inst)
12. └─bbotk:::.__OptimizerBatch__optimize(...)
13. └─bbotk::optimize_batch_default(inst, self)
14. ├─base::tryCatch(...)
15. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
16. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
17. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
18. └─get_private(optimizer)$.optimize(instance)
19. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
20. └─inst$eval_batch(design$data)
21. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
22. └─self$objective$eval_many(xss_trafoed)
23. └─bbotk:::.__Objective__eval_many(...)
24. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
25. │ └─base::eval.parent(expr, n = 1L)
26. │ └─base::eval(expr, p)
27. │ └─base::eval(expr, p)
28. └─private$.eval_many(xss = xss, resampling = `<list>`)
29. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
30. └─mlr3::benchmark(...)
31. └─ResultData$new(grid, data_extra, store_backends = store_backends)
32. └─mlr3 (local) initialize(...)
33. └─mlr3:::.__ResultData__initialize(...)
34. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
35. └─data.table:::`[.data.table`(...)
── Error ('test_extract_inner_tuning_archives.R:11:3'): extract_inner_tuning_archives function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, at, resampling_outer, store_models = TRUE) at test_extract_inner_tuning_archives.R:11:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_tuning_archives.R:131:3'): works with internal tuning ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(...) at test_extract_inner_tuning_archives.R:131:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_tuning_results.R:11:3'): extract_inner_tuning_results function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, at, resampling_outer, store_models = TRUE) at test_extract_inner_tuning_results.R:11:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_tuning_results.R:131:3'): extract_inner_tuning_results returns tuning_instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("penguins"), at, resampling_outer, store_models = TRUE) at test_extract_inner_tuning_results.R:131:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_mlr_callbacks.R:6:3'): backup callback works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:6:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:23:3'): backup callback works with standalone tuner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:23:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:282:3'): batch default configuration callback works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:282:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. └─mlr3misc::call_back(...)
8. └─mlr3misc::walk(...)
9. └─mlr3misc (local) .f(.xi, ...)
10. └─callback$call(stage, context)
11. └─self[[stage]](self, context)
12. └─context$instance$eval_batch(xdt)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:299:3'): batch default configuration callback works with logscale ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:299:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. └─mlr3misc::call_back(...)
8. └─mlr3misc::walk(...)
9. └─mlr3misc (local) .f(.xi, ...)
10. └─callback$call(stage, context)
11. └─self[[stage]](self, context)
12. └─context$instance$eval_batch(xdt)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:332:3'): batch default configuration callback works without transformation and with logscale ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:332:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. └─mlr3misc::call_back(...)
8. └─mlr3misc::walk(...)
9. └─mlr3misc (local) .f(.xi, ...)
10. └─callback$call(stage, context)
11. └─self[[stage]](self, context)
12. └─context$instance$eval_batch(xdt)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:437:3'): one se rule callback works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:437:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_trafos.R:10:3'): simple exp trafo works ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_trafos.R:10:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
12. └─instance$eval_batch(design[inds, ])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_trafos.R:34:3'): trafo where param names change ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_trafos.R:34:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_tune.R:3:3'): tune function works with one measure ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_tune.R:3:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_tune.R:13:3'): tune function works with multiple measures ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_tune.R:13:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_tune.R:23:3'): tune function works without measure ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_tune.R:23:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_tune_nested.R:5:3'): tune_nested function works ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune_nested(...) at test_tune_nested.R:5:3
2. └─mlr3::resample(task, at, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
[ FAIL 113 | WARN 9 | SKIP 68 | PASS 192 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.5.1
Check: examples
Result: ERROR
Running examples in ‘mlr3tuning-Ex.R’ failed
The error most likely occurred in:
> ### Name: AutoTuner
> ### Title: Class for Automatic Tuning
> ### Aliases: AutoTuner
>
> ### ** Examples
>
> # Automatic Tuning
>
> # split to train and external set
> task = tsk("penguins")
> split = partition(task, ratio = 0.8)
>
> # load learner and set search space
> learner = lrn("classif.rpart",
+ cp = to_tune(1e-04, 1e-1, logscale = TRUE)
+ )
>
> # create auto tuner
> at = auto_tuner(
+ tuner = tnr("random_search"),
+ learner = learner,
+ resampling = rsmp ("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 4)
>
> # tune hyperparameters and fit final model
> at$train(task, row_ids = split$train)
INFO [17:52:25.703] [bbotk] Starting to optimize 1 parameter(s) with '<OptimizerBatchRandomSearch>' and '<TerminatorEvals> [n_evals=4, k=0]'
INFO [17:52:26.076] [bbotk] Evaluating 1 configuration(s)
INFO [17:52:26.196] [mlr3] Running benchmark with 1 resampling iterations
INFO [17:52:26.729] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 1/1)
INFO [17:52:27.021] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: <Anonymous> ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.5.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [161s/301s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3tuning")
+ test_check("mlr3tuning")
+ }
Loading required package: mlr3
Loading required package: paradox
Saving _problems/test_ArchiveBatchTuning-11.R
Saving _problems/test_ArchiveBatchTuning-126.R
Saving _problems/test_ArchiveBatchTuning-277.R
Saving _problems/test_AutoTuner-10.R
Saving _problems/test_AutoTuner-42.R
Saving _problems/test_AutoTuner-77.R
Saving _problems/test_AutoTuner-93.R
Saving _problems/test_AutoTuner-118.R
Saving _problems/test_AutoTuner-155.R
Saving _problems/test_AutoTuner-184.R
Saving _problems/test_AutoTuner-246.R
Saving _problems/test_AutoTuner-282.R
Saving _problems/test_AutoTuner-308.R
Saving _problems/test_AutoTuner-373.R
Saving _problems/test_AutoTuner-389.R
Saving _problems/test_AutoTuner-420.R
Saving _problems/test_AutoTuner-434.R
Saving _problems/test_AutoTuner-480.R
Saving _problems/test_AutoTuner-606.R
Saving _problems/test_AutoTuner-625.R
Saving _problems/test_AutoTuner-676.R
Saving _problems/test_AutoTuner-699.R
Saving _problems/test_CallbackBatchTuning-17.R
Saving _problems/test_CallbackBatchTuning-37.R
Saving _problems/test_CallbackBatchTuning-59.R
Saving _problems/test_CallbackBatchTuning-80.R
Saving _problems/test_CallbackBatchTuning-103.R
Saving _problems/test_CallbackBatchTuning-127.R
Saving _problems/test_CallbackBatchTuning-150.R
Saving _problems/test_CallbackBatchTuning-171.R
Saving _problems/test_CallbackBatchTuning-191.R
Saving _problems/test_CallbackBatchTuning-214.R
Saving _problems/test_CallbackBatchTuning-235.R
Saving _problems/test_CallbackBatchTuning-255.R
Saving _problems/test_CallbackBatchTuning-284.R
Saving _problems/test_CallbackBatchTuning-312.R
Saving _problems/test_CallbackBatchTuning-339.R
Saving _problems/test_CallbackBatchTuning-367.R
Saving _problems/test_ObjectiveTuningAsync-12.R
Saving _problems/test_ObjectiveTuningAsync-32.R
Saving _problems/test_ObjectiveTuningAsync-54.R
Saving _problems/test_ObjectiveTuningAsync-76.R
Saving _problems/test_ObjectiveTuningBatch-14.R
Saving _problems/test_ObjectiveTuningBatch-37.R
Saving _problems/test_ObjectiveTuningBatch-52.R
Saving _problems/test_ObjectiveTuningBatch-69.R
Saving _problems/test_ObjectiveTuningBatch-105.R
Saving _problems/test_ObjectiveTuningBatch-128.R
Saving _problems/test_ObjectiveTuningBatch-149.R
Saving _problems/test_Tuner-5.R
Saving _problems/test_Tuner-46.R
Saving _problems/test_Tuner-90.R
Saving _problems/test_Tuner-121.R
Saving _problems/test_Tuner-188.R
Saving _problems/test_Tuner-212.R
Saving _problems/test_Tuner-242.R
Saving _problems/test_Tuner-294.R
Saving _problems/test_Tuner-336.R
Saving _problems/test_Tuner-355.R
Saving _problems/test_TunerBatchCmaes-19.R
Saving _problems/test_TunerBatchDesignPoints-3.R
Saving _problems/test_TunerBatchFromOptimizerBatch-13.R
Saving _problems/test_TunerBatchGenSA-4.R
Saving _problems/test_TunerBatchGenSA-23.R
Saving _problems/test_TunerBatchGenSA-31.R
Saving _problems/test_TunerBatchGridSearch-2.R
Saving _problems/test_TunerBatchGridSearch-22.R
# 2025-12-19 17:55:07 GMT: Initialization
# Elitist race
# Elitist new instances: 1
# Elitist limit: 2
# nbIterations: 2
# minNbSurvival: 2
# nbParameters: 1
# seed: 1838032318
# confidence level: 0.95
# budget: 42
# mu: 5
# deterministic: FALSE
# 2025-12-19 17:55:07 GMT: Iteration 1 of 2
# experimentsUsed: 0
# remainingBudget: 42
# currentBudget: 21
# nbConfigurations: 3
# Markers:
x No test is performed.
c Configurations are discarded only due to capping.
- The test is performed and some configurations are discarded.
= The test is performed but no configuration is discarded.
! The test is performed and configurations could be discarded but elite configurations are preserved.
. All alive configurations are elite and nothing is discarded.
+-+-----------+-----------+-----------+----------------+-----------+--------+-----+----+------+
| | Instance| Alive| Best| Mean best| Exp so far| W time| rho|KenW| Qvar|
+-+-----------+-----------+-----------+----------------+-----------+--------+-----+----+------+
Saving _problems/test_TunerBatchIrace-4.R
Saving _problems/test_TunerBatchNLoptr-5.R
Saving _problems/test_TunerBatchRandomSearch-2.R
Saving _problems/test_TunerInternal-18.R
Saving _problems/test_TuningInstanceBatchMultiCrit-19.R
Saving _problems/test_TuningInstanceBatchMultiCrit-35.R
Saving _problems/test_TuningInstanceBatchMultiCrit-64.R
Saving _problems/test_TuningInstanceBatchMultiCrit-114.R
Saving _problems/test_TuningInstanceBatchMultiCrit-129.R
Saving _problems/test_TuningInstanceBatchMultiCrit-186.R
Saving _problems/test_TuningInstanceBatchSingleCrit-9.R
Saving _problems/test_TuningInstanceBatchSingleCrit-46.R
Saving _problems/test_TuningInstanceBatchSingleCrit-55.R
Saving _problems/test_TuningInstanceBatchSingleCrit-76.R
Saving _problems/test_TuningInstanceBatchSingleCrit-99.R
Saving _problems/test_TuningInstanceBatchSingleCrit-128.R
Saving _problems/test_TuningInstanceBatchSingleCrit-136.R
Saving _problems/test_TuningInstanceBatchSingleCrit-170.R
Saving _problems/test_TuningInstanceBatchSingleCrit-220.R
Saving _problems/test_TuningInstanceBatchSingleCrit-237.R
Saving _problems/test_TuningInstanceBatchSingleCrit-413.R
Saving _problems/test_TuningInstanceBatchSingleCrit-428.R
Saving _problems/test_TuningInstanceBatchSingleCrit-459.R
Saving _problems/test_TuningInstanceBatchSingleCrit-484.R
Saving _problems/test_error_handling-18.R
Saving _problems/test_error_handling-36.R
Saving _problems/test_extract_inner_tuning_archives-11.R
Saving _problems/test_extract_inner_tuning_archives-131.R
Saving _problems/test_extract_inner_tuning_results-11.R
Saving _problems/test_extract_inner_tuning_results-131.R
Saving _problems/test_mlr_callbacks-14.R
Saving _problems/test_mlr_callbacks-31.R
Saving _problems/test_mlr_callbacks-290.R
Saving _problems/test_mlr_callbacks-307.R
Saving _problems/test_mlr_callbacks-340.R
Saving _problems/test_mlr_callbacks-445.R
Saving _problems/test_trafos-10.R
Saving _problems/test_trafos-34.R
Saving _problems/test_tune-4.R
Saving _problems/test_tune-14.R
Saving _problems/test_tune-24.R
Saving _problems/test_tune_nested-6.R
[ FAIL 113 | WARN 9 | SKIP 68 | PASS 192 ]
══ Skipped tests (68) ══════════════════════════════════════════════════════════
• On CRAN (68): 'test_ArchiveAsyncTuning.R:2:3',
'test_ArchiveAsyncTuning.R:61:3', 'test_ArchiveAsyncTuning.R:119:3',
'test_ArchiveAsyncTuning.R:146:3', 'test_ArchiveAsyncTuning.R:169:3',
'test_ArchiveAsyncTuning.R:209:3', 'test_ArchiveAsyncTuning.R:251:3',
'test_ArchiveAsyncTuning.R:284:3', 'test_ArchiveAsyncTuningFrozen.R:2:3',
'test_AutoTuner.R:640:3', 'test_CallbackAsyncTuning.R:4:3',
'test_CallbackAsyncTuning.R:33:3', 'test_CallbackAsyncTuning.R:64:3',
'test_CallbackAsyncTuning.R:93:3', 'test_CallbackAsyncTuning.R:124:3',
'test_CallbackAsyncTuning.R:160:3', 'test_CallbackAsyncTuning.R:188:3',
'test_CallbackAsyncTuning.R:222:3', 'test_CallbackAsyncTuning.R:252:3',
'test_CallbackAsyncTuning.R:281:3', 'test_CallbackAsyncTuning.R:312:3',
'test_CallbackAsyncTuning.R:343:3', 'test_CallbackAsyncTuning.R:373:3',
'test_CallbackAsyncTuning.R:405:3', 'test_CallbackAsyncTuning.R:443:3',
'test_CallbackAsyncTuning.R:480:3', 'test_CallbackAsyncTuning.R:516:3',
'test_Tuner.R:53:1', 'test_TunerAsyncDesignPoints.R:2:3',
'test_TunerAsyncGridSearch.R:2:3', 'test_TunerAsyncRandomSearch.R:2:3',
'test_TuningInstanceAsyncMultiCrit.R:2:3',
'test_TuningInstanceAsyncMultiCrit.R:30:3',
'test_TuningInstanceAsyncMultiCrit.R:57:3',
'test_TuningInstanceAsyncMultiCrit.R:81:3',
'test_TuningInstanceAsyncMultiCrit.R:106:3',
'test_TuningInstanceAsyncMultiCrit.R:134:3',
'test_TuningInstanceAsyncMultiCrit.R:189:3',
'test_TuningInstanceAsyncMultiCrit.R:236:3',
'test_TuningInstanceAsyncMultiCrit.R:261:3',
'test_TuningInstanceAsyncSingleCrit.R:2:3',
'test_TuningInstanceAsyncSingleCrit.R:29:3',
'test_TuningInstanceAsyncSingleCrit.R:54:3',
'test_TuningInstanceAsyncSingleCrit.R:78:3',
'test_TuningInstanceAsyncSingleCrit.R:104:3',
'test_TuningInstanceAsyncSingleCrit.R:131:3',
'test_TuningInstanceAsyncSingleCrit.R:182:3',
'test_TuningInstanceAsyncSingleCrit.R:213:3',
'test_TuningInstanceAsyncSingleCrit.R:226:3',
'test_TuningInstanceAsyncSingleCrit.R:240:3',
'test_TuningInstanceAsyncSingleCrit.R:266:3', 'test_auto_tuner.R:25:3',
'test_auto_tuner.R:48:3', 'test_mlr_callbacks.R:40:3',
'test_mlr_callbacks.R:93:3', 'test_mlr_callbacks.R:117:3',
'test_mlr_callbacks.R:141:3', 'test_mlr_callbacks.R:162:3',
'test_mlr_callbacks.R:192:3', 'test_mlr_callbacks.R:218:3',
'test_mlr_callbacks.R:251:3', 'test_mlr_callbacks.R:410:3',
'test_mlr_callbacks.R:452:3', 'test_mlr_callbacks.R:480:3',
'test_ti_async.R:2:3', 'test_ti_async.R:16:3', 'test_ti_async.R:30:3',
'test_ti_async.R:42:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ArchiveBatchTuning.R:11:3'): ArchiveTuning access methods work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_ArchiveBatchTuning.R:11:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchTuning.R:126:3'): ArchiveTuning as.data.table function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_ArchiveBatchTuning.R:126:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchTuning.R:277:3'): ArchiveBatchTuning as.data.table function works for internally tuned values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_ArchiveBatchTuning.R:277:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:10:3'): AutoTuner / train+predict ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:10:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
23. └─inst$eval_batch(g$data[inds])
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:42:3'): AutoTuner / resample ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, r_outer, store_models = TRUE) at test_AutoTuner.R:42:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:77:3'): nested resamppling results are consistent ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), lrn, cv2, store_models = TRUE) at test_AutoTuner.R:77:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:93:3'): AT training does not change learner in instance args ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:93:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:118:3'): AutoTuner works with graphlearner ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:118:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
23. └─inst$eval_batch(g$data[inds])
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:155:3'): Nested resampling works with graphlearner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:184:3'): store_tuning_instance, store_benchmark_result and store_models flags work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
23. └─inst$eval_batch(g$data[inds])
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:246:3'): predict_type works ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:246:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:282:3'): search space from TuneToken works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("iris")) at test_AutoTuner.R:282:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:308:3'): AutoTuner get_base_learner method works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("pima")) at test_AutoTuner.R:308:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:373:3'): AutoTuner hash works #647 in mlr3 ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_AutoTuner.R:373:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:389:3'): AutoTuner works with empty search space ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("pima")) at test_AutoTuner.R:389:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:420:3'): AutoTuner importance method works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("penguins")) at test_AutoTuner.R:420:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:434:3'): AutoTuner selected_features method works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("penguins")) at test_AutoTuner.R:434:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:480:3'): AutoTuner works with instantiated resampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:480:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:606:3'): marshalable learner ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:606:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:625:3'): marshal ───────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:625:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:676:3'): AutoTuner works with internal tuning and validation ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:676:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:699:3'): AutoTuner works when internal_search_space is part of primary search space ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:699:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:10:3'): on_optimization_begin works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:10:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:30:3'): on_optimization_end works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:30:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:52:3'): on_optimizer_after_eval works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:52:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:73:3'): on_optimizer_after_eval works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:73:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:96:3'): on_eval_after_design works ───────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:96:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:120:3'): on_eval_after_benchmark and on_eval_before_archive works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:120:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:143:3'): on_tuning_result_begin in TuningInstanceSingleCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:143:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:164:3'): on_result_end in TuningInstanceSingleCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:164:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:184:3'): on_result in TuningInstanceSingleCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:184:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:207:3'): on_tuning_result_begin in TuningInstanceBatchMultiCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:207:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:228:3'): on_result_end in TuningInstanceBatchMultiCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:228:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:248:3'): on_result in TuningInstanceBatchMultiCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:248:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:277:3'): on_resample_begin works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:277:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:305:3'): on_resample_before_train works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:305:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:332:3'): on_resample_before_predict works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:332:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:360:3'): on_resample_end works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:360:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:12:3'): objective async works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:12:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:32:3'): store benchmark result works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:32:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:54:3'): store models works ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:54:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:76:3'): rush objective with multiple measures works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:76:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:14:3'): ObjectiveTuningBatch ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:14:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:37:3'): ObjectiveTuningBatch - Multiple measures ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:37:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:52:3'): ObjectiveTuningBatch - Store models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:52:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:69:3'): runtime of learners is added ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:69:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:105:3'): tuner can modify resampling ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─instance$eval_batch(data.table(cp = 0.001)) at test_ObjectiveTuningBatch.R:105:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:128:3'): benchmark clone works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, clone = c()) at test_ObjectiveTuningBatch.R:128:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:149:3'): objects are cloned ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:149:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:5:5'): API ─────────────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(rs$optimize(inst), nrows = 1) at test_Tuner.R:5:5
2. │ └─checkmate::checkDataTable(...)
3. └─rs$optimize(inst)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
14. └─inst$eval_batch(design$data)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:46:3'): we get a result when some subordinate params are not fulfilled ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(d) at test_Tuner.R:46:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:90:3'): Tuner works with graphlearner ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_Tuner.R:90:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:121:3'): Tuner works with instantiated resampling ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─rs$optimize(inst) at test_Tuner.R:121:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:182:3'): internal single crit ──────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:182:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:205:3'): internal single crit without benchmark_result ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:205:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:235:3'): internal multi crit ───────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:235:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:294:3'): internal tuning: branching ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_Tuner.R:294:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:325:3'): parameter transformations can be used with internal tuning ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:325:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:348:3'): tag internal tune token manually in primary search space ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:348:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchCmaes.R:12:3'): TunerBatchCmaes ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchCmaes.R:12:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchCmaes__.optimize(...)
13. ├─mlr3misc::invoke(...)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─adagio::pureCMAES(...)
18. └─adagio (local) fun(arx[, k])
19. └─bbotk (local) fct(x, ...)
20. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
21. └─private$.objective_function(x, self, self$objective_multiplicator)
22. └─inst$eval_batch(xdt)
23. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
24. └─self$objective$eval_many(xss_trafoed)
25. └─bbotk:::.__Objective__eval_many(...)
26. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
27. │ └─base::eval.parent(expr, n = 1L)
28. │ └─base::eval(expr, p)
29. │ └─base::eval(expr, p)
30. └─private$.eval_many(xss = xss, resampling = `<list>`)
31. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
32. └─mlr3::benchmark(...)
33. └─ResultData$new(grid, data_extra, store_backends = store_backends)
34. └─mlr3 (local) initialize(...)
35. └─mlr3:::.__ResultData__initialize(...)
36. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
37. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchDesignPoints.R:3:3'): TunerBatchDesignPoints ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner(...) at test_TunerBatchDesignPoints.R:3:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchFromOptimizerBatch.R:13:3'): TunerBatchFromOptimizerBatch parameter set works after cloning ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner_2$optimize(instance) at test_TunerBatchFromOptimizerBatch.R:13:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGenSA.R:4:3'): TunerBatchGenSA ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global test_tuner("gensa") at test_TunerBatchGenSA.R:4:3
2. │ └─tuner$optimize(inst)
3. │ └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. │ └─private$.optimizer$optimize(inst)
5. │ └─bbotk:::.__OptimizerBatch__optimize(...)
6. │ └─bbotk::optimize_batch_default(inst, self)
7. │ ├─base::tryCatch(...)
8. │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. │ └─get_private(optimizer)$.optimize(instance)
12. │ └─bbotk:::.__OptimizerBatchGenSA__.optimize(...)
13. │ └─GenSA::GenSA(...)
14. └─GenSA (local) `<fn>`(`<dbl>`)
15. └─bbotk (local) fn(par, ...)
16. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
17. └─private$.objective_function(x, self, self$objective_multiplicator)
18. └─inst$eval_batch(xdt)
19. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
20. └─self$objective$eval_many(xss_trafoed)
21. └─bbotk:::.__Objective__eval_many(...)
22. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
23. │ └─base::eval.parent(expr, n = 1L)
24. │ └─base::eval(expr, p)
25. │ └─base::eval(expr, p)
26. └─private$.eval_many(xss = xss, resampling = `<list>`)
27. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
28. └─mlr3::benchmark(...)
29. └─ResultData$new(grid, data_extra, store_backends = store_backends)
30. └─mlr3 (local) initialize(...)
31. └─mlr3:::.__ResultData__initialize(...)
32. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
33. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGenSA.R:23:3'): TunerBatchGenSA with int params and trafo ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─tt$optimize(inst) at test_TunerBatchGenSA.R:23:3
2. │ └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. │ └─private$.optimizer$optimize(inst)
4. │ └─bbotk:::.__OptimizerBatch__optimize(...)
5. │ └─bbotk::optimize_batch_default(inst, self)
6. │ ├─base::tryCatch(...)
7. │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. │ └─get_private(optimizer)$.optimize(instance)
11. │ └─bbotk:::.__OptimizerBatchGenSA__.optimize(...)
12. │ └─GenSA::GenSA(...)
13. └─GenSA (local) `<fn>`(`<dbl>`)
14. └─bbotk (local) fn(par, ...)
15. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
16. └─private$.objective_function(x, self, self$objective_multiplicator)
17. └─inst$eval_batch(xdt)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGenSA.R:31:3'): TunerBatchGenSA - Optimize wrapper with maximize measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─tt$optimize(inst) at test_TunerBatchGenSA.R:31:3
2. │ └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. │ └─private$.optimizer$optimize(inst)
4. │ └─bbotk:::.__OptimizerBatch__optimize(...)
5. │ └─bbotk::optimize_batch_default(inst, self)
6. │ ├─base::tryCatch(...)
7. │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. │ └─get_private(optimizer)$.optimize(instance)
11. │ └─bbotk:::.__OptimizerBatchGenSA__.optimize(...)
12. │ └─GenSA::GenSA(...)
13. └─GenSA (local) `<fn>`(`<dbl>`)
14. └─bbotk (local) fn(par, ...)
15. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
16. └─private$.objective_function(x, self, self$objective_multiplicator)
17. └─inst$eval_batch(xdt)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGridSearch.R:2:3'): TunerGridSearch ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner(...) at test_TunerBatchGridSearch.R:2:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGridSearch.R:22:3'): TunerGridSearch with TerminatorNone ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TunerBatchGridSearch.R:22:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:4:3'): TunerIrace ────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner("irace", term_evals = 42) at test_TunerBatchIrace.R:4:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
13. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─irace::irace(scenario = scenario)
18. └─irace:::irace_common(scenario, simple = TRUE)
19. └─irace:::irace_run(scenario = scenario)
20. └─irace:::elitist_race(...)
21. └─irace:::race_wrapper(...)
22. └─irace:::race_wrapper_helper(...)
23. └─irace:::execute_experiments(...)
24. └─scenario$targetRunnerParallel(...)
25. └─tuning_instance$eval_batch(xdt)
26. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
27. └─self$objective$eval_many(xss_trafoed)
28. └─bbotk:::.__Objective__eval_many(...)
29. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
30. │ └─base::eval.parent(expr, n = 1L)
31. │ └─base::eval(expr, p)
32. │ └─base::eval(expr, p)
33. └─private$.eval_many(xss = xss, resampling = `<list>`)
34. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
35. └─mlr3::benchmark(...)
36. └─ResultData$new(grid, data_extra, store_backends = store_backends)
37. └─mlr3 (local) initialize(...)
38. └─mlr3:::.__ResultData__initialize(...)
39. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
40. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:37:36'): TunerIrace works with dependencies ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:37:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. └─tuner$optimize(instance) at test_TunerBatchIrace.R:37:36
6. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
7. └─private$.optimizer$optimize(inst)
8. └─bbotk:::.__OptimizerBatch__optimize(...)
9. └─bbotk::optimize_batch_default(inst, self)
10. ├─base::tryCatch(...)
11. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
12. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
13. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
14. └─get_private(optimizer)$.optimize(instance)
15. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
16. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─irace::irace(scenario = scenario)
21. └─irace:::irace_common(scenario, simple = TRUE)
22. └─irace:::irace_run(scenario = scenario)
23. └─irace:::elitist_race(...)
24. └─irace:::race_wrapper(...)
25. └─irace:::race_wrapper_helper(...)
26. └─irace:::execute_experiments(...)
27. └─scenario$targetRunnerParallel(...)
28. └─tuning_instance$eval_batch(xdt)
29. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
30. └─self$objective$eval_many(xss_trafoed)
31. └─bbotk:::.__Objective__eval_many(...)
32. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
33. │ └─base::eval.parent(expr, n = 1L)
34. │ └─base::eval(expr, p)
35. │ └─base::eval(expr, p)
36. └─private$.eval_many(xss = xss, resampling = `<list>`)
37. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
38. └─mlr3::benchmark(...)
39. └─ResultData$new(grid, data_extra, store_backends = store_backends)
40. └─mlr3 (local) initialize(...)
41. └─mlr3:::.__ResultData__initialize(...)
42. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
43. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:56:36'): TunerIrace works with logical parameters ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:56:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. └─tuner$optimize(instance) at test_TunerBatchIrace.R:56:36
6. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
7. └─private$.optimizer$optimize(inst)
8. └─bbotk:::.__OptimizerBatch__optimize(...)
9. └─bbotk::optimize_batch_default(inst, self)
10. ├─base::tryCatch(...)
11. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
12. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
13. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
14. └─get_private(optimizer)$.optimize(instance)
15. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
16. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─irace::irace(scenario = scenario)
21. └─irace:::irace_common(scenario, simple = TRUE)
22. └─irace:::irace_run(scenario = scenario)
23. └─irace:::elitist_race(...)
24. └─irace:::race_wrapper(...)
25. └─irace:::race_wrapper_helper(...)
26. └─irace:::execute_experiments(...)
27. └─scenario$targetRunnerParallel(...)
28. └─tuning_instance$eval_batch(xdt)
29. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
30. └─self$objective$eval_many(xss_trafoed)
31. └─bbotk:::.__Objective__eval_many(...)
32. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
33. │ └─base::eval.parent(expr, n = 1L)
34. │ └─base::eval(expr, p)
35. │ └─base::eval(expr, p)
36. └─private$.eval_many(xss = xss, resampling = `<list>`)
37. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
38. └─mlr3::benchmark(...)
39. └─ResultData$new(grid, data_extra, store_backends = store_backends)
40. └─mlr3 (local) initialize(...)
41. └─mlr3:::.__ResultData__initialize(...)
42. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
43. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:70:36'): TunerIrace uses digits ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:70:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. ├─checkmate::expect_data_table(tuner$optimize(instance)) at test_TunerBatchIrace.R:70:36
6. │ └─checkmate::checkDataTable(...)
7. └─tuner$optimize(instance)
8. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
9. └─private$.optimizer$optimize(inst)
10. └─bbotk:::.__OptimizerBatch__optimize(...)
11. └─bbotk::optimize_batch_default(inst, self)
12. ├─base::tryCatch(...)
13. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
14. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
15. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
16. └─get_private(optimizer)$.optimize(instance)
17. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
18. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─irace::irace(scenario = scenario)
23. └─irace:::irace_common(scenario, simple = TRUE)
24. └─irace:::irace_run(scenario = scenario)
25. └─irace:::elitist_race(...)
26. └─irace:::race_wrapper(...)
27. └─irace:::race_wrapper_helper(...)
28. └─irace:::execute_experiments(...)
29. └─scenario$targetRunnerParallel(...)
30. └─tuning_instance$eval_batch(xdt)
31. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
32. └─self$objective$eval_many(xss_trafoed)
33. └─bbotk:::.__Objective__eval_many(...)
34. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
35. │ └─base::eval.parent(expr, n = 1L)
36. │ └─base::eval(expr, p)
37. │ └─base::eval(expr, p)
38. └─private$.eval_many(xss = xss, resampling = `<list>`)
39. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
40. └─mlr3::benchmark(...)
41. └─ResultData$new(grid, data_extra, store_backends = store_backends)
42. └─mlr3 (local) initialize(...)
43. └─mlr3:::.__ResultData__initialize(...)
44. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
45. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:84:36'): TunerIrace works with unnamed discrete values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:84:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. ├─checkmate::expect_data_table(tuner$optimize(instance)) at test_TunerBatchIrace.R:84:36
6. │ └─checkmate::checkDataTable(...)
7. └─tuner$optimize(instance)
8. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
9. └─private$.optimizer$optimize(inst)
10. └─bbotk:::.__OptimizerBatch__optimize(...)
11. └─bbotk::optimize_batch_default(inst, self)
12. ├─base::tryCatch(...)
13. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
14. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
15. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
16. └─get_private(optimizer)$.optimize(instance)
17. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
18. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─irace::irace(scenario = scenario)
23. └─irace:::irace_common(scenario, simple = TRUE)
24. └─irace:::irace_run(scenario = scenario)
25. └─irace:::elitist_race(...)
26. └─irace:::race_wrapper(...)
27. └─irace:::race_wrapper_helper(...)
28. └─irace:::execute_experiments(...)
29. └─scenario$targetRunnerParallel(...)
30. └─tuning_instance$eval_batch(xdt)
31. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
32. └─self$objective$eval_many(xss_trafoed)
33. └─bbotk:::.__Objective__eval_many(...)
34. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
35. │ └─base::eval.parent(expr, n = 1L)
36. │ └─base::eval(expr, p)
37. │ └─base::eval(expr, p)
38. └─private$.eval_many(xss = xss, resampling = `<list>`)
39. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
40. └─mlr3::benchmark(...)
41. └─ResultData$new(grid, data_extra, store_backends = store_backends)
42. └─mlr3 (local) initialize(...)
43. └─mlr3:::.__ResultData__initialize(...)
44. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
45. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchNLoptr.R:5:3'): TunerNLoptr ──────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner("nloptr", algorithm = "NLOPT_LN_BOBYQA", term_evals = 4) at test_TunerBatchNLoptr.R:5:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchNLoptr__.optimize(...)
13. ├─mlr3misc::invoke(...)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─nloptr::nloptr(...)
18. └─bbotk (local) eval_f(x0, ...)
19. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
20. └─private$.objective_function(x, self, self$objective_multiplicator)
21. └─inst$eval_batch(xdt)
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchRandomSearch.R:2:3'): TunerRandomSearch ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner("random_search") at test_TunerBatchRandomSearch.R:2:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerInternal.R:18:3'): tuner internal works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerInternal.R:18:3
2. └─mlr3tuning:::.__TunerBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3tuning:::.__TunerBatchInternal__.optimize(...)
10. └─inst$eval_batch(data.table())
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(list(list()))
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:19:3'): tuning with multiple objectives ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchMultiCrit.R:19:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:35:3'): store_benchmark_result and store_models flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(...) at test_TuningInstanceBatchMultiCrit.R:35:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:64:3'): check_values flag with parameter set dependencies ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchMultiCrit.R:64:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:114:3'): TuneToken and result_learner_param_vals works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TuningInstanceBatchMultiCrit.R:114:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
12. └─instance$eval_batch(design[inds, ])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:122:3'): TuningInstanceBatchMultiCrit and empty search space works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TuningInstanceBatchMultiCrit.R:122:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(list(list()))
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:186:3'): Batch multi-crit internal tuning works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), min.rows = 1) at test_TuningInstanceBatchMultiCrit.R:186:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
14. └─inst$eval_batch(design$data)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:9:3'): TuningInstanceBatchSingleCrit ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(...) at test_TuningInstanceBatchSingleCrit.R:9:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:46:3'): archive one row (#40) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(data.table(cp = 0.1)) at test_TuningInstanceBatchSingleCrit.R:46:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:55:3'): eval_batch and termination ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(design[1:2, ]) at test_TuningInstanceBatchSingleCrit.R:55:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:76:3'): the same experiment can be added twice ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(d) at test_TuningInstanceBatchSingleCrit.R:76:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:99:3'): tuning with custom resampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchSingleCrit.R:99:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:128:3'): non-scalar hyperpars (#201) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tnr("random_search")$optimize(inst) at test_TuningInstanceBatchSingleCrit.R:128:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:136:3'): store_benchmark_result and store_models flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(...) at test_TuningInstanceBatchSingleCrit.R:136:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:170:3'): check_values flag with parameter set dependencies ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchSingleCrit.R:170:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:220:3'): TuneToken and result_learner_param_vals works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TuningInstanceBatchSingleCrit.R:220:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
12. └─instance$eval_batch(design[inds, ])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:230:3'): TuningInstanceBatchSingleCrit and empty search space works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TuningInstanceBatchSingleCrit.R:230:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(list(list()))
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:413:3'): objective contains no benchmark results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TuningInstanceBatchSingleCrit.R:413:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(list(list()))
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:422:3'): dependencies in defaults work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_class(...) at test_TuningInstanceBatchSingleCrit.R:422:3
2. │ └─checkmate::checkClass(x, classes, ordered, null.ok)
3. └─mlr3tuning::tune(...)
4. └─tuner$optimize(instance)
5. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
6. └─private$.optimizer$optimize(inst)
7. └─bbotk:::.__OptimizerBatch__optimize(...)
8. └─bbotk::optimize_batch_default(inst, self)
9. ├─base::tryCatch(...)
10. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
11. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
12. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
13. └─get_private(optimizer)$.optimize(instance)
14. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
15. └─inst$eval_batch(design$data)
16. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
17. └─self$objective$eval_many(xss_trafoed)
18. └─bbotk:::.__Objective__eval_many(...)
19. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
20. │ └─base::eval.parent(expr, n = 1L)
21. │ └─base::eval(expr, p)
22. │ └─base::eval(expr, p)
23. └─private$.eval_many(xss = xss, resampling = `<list>`)
24. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
25. └─mlr3::benchmark(...)
26. └─ResultData$new(grid, data_extra, store_backends = store_backends)
27. └─mlr3 (local) initialize(...)
28. └─mlr3:::.__ResultData__initialize(...)
29. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
30. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:459:3'): Batch single-crit internal tuning works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), nrows = 1) at test_TuningInstanceBatchSingleCrit.R:459:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
14. └─inst$eval_batch(design$data)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Failure ('test_TuningInstanceBatchSingleCrit.R:478:3'): required parameter can be tuned internally without having a value set ──
Expected `tune(...)` not to throw any errors.
Actually got a <simpleError> with message:
attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TuningInstanceBatchSingleCrit.R:478:3
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$optimize(instance)
9. └─mlr3tuning:::.__TunerBatch__optimize(...)
10. └─bbotk::optimize_batch_default(inst, self)
11. ├─base::tryCatch(...)
12. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
13. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
14. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
15. └─get_private(optimizer)$.optimize(instance)
16. └─mlr3tuning:::.__TunerBatchInternal__.optimize(...)
17. └─inst$eval_batch(data.table())
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(list(list()))
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_error_handling.R:18:3'): failing learner ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tt$optimize(instance) at test_error_handling.R:18:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_error_handling.R:36:3'): predictions missing ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─mlr3tuning:::expect_resample_error(tt$optimize(instance), "missing") at test_error_handling.R:36:3
2. │ ├─base::withCallingHandlers(...) at ./helper.R:26:3
3. │ └─testthat::expect_error(...)
4. │ └─testthat:::expect_condition_matching_(...)
5. │ └─testthat:::quasi_capture(...)
6. │ ├─testthat (local) .capture(...)
7. │ │ └─base::withCallingHandlers(...)
8. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
9. └─tt$optimize(instance)
10. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
11. └─private$.optimizer$optimize(inst)
12. └─bbotk:::.__OptimizerBatch__optimize(...)
13. └─bbotk::optimize_batch_default(inst, self)
14. ├─base::tryCatch(...)
15. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
16. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
17. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
18. └─get_private(optimizer)$.optimize(instance)
19. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
20. └─inst$eval_batch(design$data)
21. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
22. └─self$objective$eval_many(xss_trafoed)
23. └─bbotk:::.__Objective__eval_many(...)
24. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
25. │ └─base::eval.parent(expr, n = 1L)
26. │ └─base::eval(expr, p)
27. │ └─base::eval(expr, p)
28. └─private$.eval_many(xss = xss, resampling = `<list>`)
29. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
30. └─mlr3::benchmark(...)
31. └─ResultData$new(grid, data_extra, store_backends = store_backends)
32. └─mlr3 (local) initialize(...)
33. └─mlr3:::.__ResultData__initialize(...)
34. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
35. └─data.table:::`[.data.table`(...)
── Error ('test_extract_inner_tuning_archives.R:11:3'): extract_inner_tuning_archives function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, at, resampling_outer, store_models = TRUE) at test_extract_inner_tuning_archives.R:11:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_tuning_archives.R:131:3'): works with internal tuning ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(...) at test_extract_inner_tuning_archives.R:131:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_tuning_results.R:11:3'): extract_inner_tuning_results function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, at, resampling_outer, store_models = TRUE) at test_extract_inner_tuning_results.R:11:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_tuning_results.R:131:3'): extract_inner_tuning_results returns tuning_instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("penguins"), at, resampling_outer, store_models = TRUE) at test_extract_inner_tuning_results.R:131:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_mlr_callbacks.R:6:3'): backup callback works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:6:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:23:3'): backup callback works with standalone tuner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:23:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:282:3'): batch default configuration callback works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:282:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. └─mlr3misc::call_back(...)
8. └─mlr3misc::walk(...)
9. └─mlr3misc (local) .f(.xi, ...)
10. └─callback$call(stage, context)
11. └─self[[stage]](self, context)
12. └─context$instance$eval_batch(xdt)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:299:3'): batch default configuration callback works with logscale ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:299:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. └─mlr3misc::call_back(...)
8. └─mlr3misc::walk(...)
9. └─mlr3misc (local) .f(.xi, ...)
10. └─callback$call(stage, context)
11. └─self[[stage]](self, context)
12. └─context$instance$eval_batch(xdt)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:332:3'): batch default configuration callback works without transformation and with logscale ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:332:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. └─mlr3misc::call_back(...)
8. └─mlr3misc::walk(...)
9. └─mlr3misc (local) .f(.xi, ...)
10. └─callback$call(stage, context)
11. └─self[[stage]](self, context)
12. └─context$instance$eval_batch(xdt)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:437:3'): one se rule callback works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:437:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_trafos.R:10:3'): simple exp trafo works ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_trafos.R:10:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
12. └─instance$eval_batch(design[inds, ])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_trafos.R:34:3'): trafo where param names change ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_trafos.R:34:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_tune.R:3:3'): tune function works with one measure ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_tune.R:3:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_tune.R:13:3'): tune function works with multiple measures ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_tune.R:13:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_tune.R:23:3'): tune function works without measure ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_tune.R:23:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_tune_nested.R:5:3'): tune_nested function works ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune_nested(...) at test_tune_nested.R:5:3
2. └─mlr3::resample(task, at, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
[ FAIL 113 | WARN 9 | SKIP 68 | PASS 192 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.5.1
Check: examples
Result: ERROR
Running examples in ‘mlr3tuning-Ex.R’ failed
The error most likely occurred in:
> ### Name: AutoTuner
> ### Title: Class for Automatic Tuning
> ### Aliases: AutoTuner
>
> ### ** Examples
>
> # Automatic Tuning
>
> # split to train and external set
> task = tsk("penguins")
> split = partition(task, ratio = 0.8)
>
> # load learner and set search space
> learner = lrn("classif.rpart",
+ cp = to_tune(1e-04, 1e-1, logscale = TRUE)
+ )
>
> # create auto tuner
> at = auto_tuner(
+ tuner = tnr("random_search"),
+ learner = learner,
+ resampling = rsmp ("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 4)
>
> # tune hyperparameters and fit final model
> at$train(task, row_ids = split$train)
INFO [12:31:49.692] [bbotk] Starting to optimize 1 parameter(s) with '<OptimizerBatchRandomSearch>' and '<TerminatorEvals> [n_evals=4, k=0]'
INFO [12:31:49.978] [bbotk] Evaluating 1 configuration(s)
INFO [12:31:50.038] [mlr3] Running benchmark with 1 resampling iterations
INFO [12:31:50.288] [mlr3] Applying learner 'classif.rpart' on task 'penguins' (iter 1/1)
INFO [12:31:50.374] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: <Anonymous> ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.5.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [148s/185s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("checkmate")
+ library("mlr3tuning")
+ test_check("mlr3tuning")
+ }
Loading required package: mlr3
Loading required package: paradox
Saving _problems/test_ArchiveBatchTuning-11.R
Saving _problems/test_ArchiveBatchTuning-126.R
Saving _problems/test_ArchiveBatchTuning-277.R
Saving _problems/test_AutoTuner-10.R
Saving _problems/test_AutoTuner-42.R
Saving _problems/test_AutoTuner-77.R
Saving _problems/test_AutoTuner-93.R
Saving _problems/test_AutoTuner-118.R
Saving _problems/test_AutoTuner-155.R
Saving _problems/test_AutoTuner-184.R
Saving _problems/test_AutoTuner-246.R
Saving _problems/test_AutoTuner-282.R
Saving _problems/test_AutoTuner-308.R
Saving _problems/test_AutoTuner-373.R
Saving _problems/test_AutoTuner-389.R
Saving _problems/test_AutoTuner-420.R
Saving _problems/test_AutoTuner-434.R
Saving _problems/test_AutoTuner-480.R
Saving _problems/test_AutoTuner-606.R
Saving _problems/test_AutoTuner-625.R
Saving _problems/test_AutoTuner-676.R
Saving _problems/test_AutoTuner-699.R
Saving _problems/test_CallbackBatchTuning-17.R
Saving _problems/test_CallbackBatchTuning-37.R
Saving _problems/test_CallbackBatchTuning-59.R
Saving _problems/test_CallbackBatchTuning-80.R
Saving _problems/test_CallbackBatchTuning-103.R
Saving _problems/test_CallbackBatchTuning-127.R
Saving _problems/test_CallbackBatchTuning-150.R
Saving _problems/test_CallbackBatchTuning-171.R
Saving _problems/test_CallbackBatchTuning-191.R
Saving _problems/test_CallbackBatchTuning-214.R
Saving _problems/test_CallbackBatchTuning-235.R
Saving _problems/test_CallbackBatchTuning-255.R
Saving _problems/test_CallbackBatchTuning-284.R
Saving _problems/test_CallbackBatchTuning-312.R
Saving _problems/test_CallbackBatchTuning-339.R
Saving _problems/test_CallbackBatchTuning-367.R
Saving _problems/test_ObjectiveTuningAsync-12.R
Saving _problems/test_ObjectiveTuningAsync-32.R
Saving _problems/test_ObjectiveTuningAsync-54.R
Saving _problems/test_ObjectiveTuningAsync-76.R
Saving _problems/test_ObjectiveTuningBatch-14.R
Saving _problems/test_ObjectiveTuningBatch-37.R
Saving _problems/test_ObjectiveTuningBatch-52.R
Saving _problems/test_ObjectiveTuningBatch-69.R
Saving _problems/test_ObjectiveTuningBatch-105.R
Saving _problems/test_ObjectiveTuningBatch-128.R
Saving _problems/test_ObjectiveTuningBatch-149.R
Saving _problems/test_Tuner-5.R
Saving _problems/test_Tuner-46.R
Saving _problems/test_Tuner-90.R
Saving _problems/test_Tuner-121.R
Saving _problems/test_Tuner-188.R
Saving _problems/test_Tuner-212.R
Saving _problems/test_Tuner-242.R
Saving _problems/test_Tuner-294.R
Saving _problems/test_Tuner-336.R
Saving _problems/test_Tuner-355.R
Saving _problems/test_TunerBatchCmaes-19.R
Saving _problems/test_TunerBatchDesignPoints-3.R
Saving _problems/test_TunerBatchFromOptimizerBatch-13.R
Saving _problems/test_TunerBatchGenSA-4.R
Saving _problems/test_TunerBatchGenSA-23.R
Saving _problems/test_TunerBatchGenSA-31.R
Saving _problems/test_TunerBatchGridSearch-2.R
Saving _problems/test_TunerBatchGridSearch-22.R
# 2025-12-19 12:33:32 GMT: Initialization
# Elitist race
# Elitist new instances: 1
# Elitist limit: 2
# nbIterations: 2
# minNbSurvival: 2
# nbParameters: 1
# seed: 1957750406
# confidence level: 0.95
# budget: 42
# mu: 5
# deterministic: FALSE
# 2025-12-19 12:33:33 GMT: Iteration 1 of 2
# experimentsUsed: 0
# remainingBudget: 42
# currentBudget: 21
# nbConfigurations: 3
# Markers:
x No test is performed.
c Configurations are discarded only due to capping.
- The test is performed and some configurations are discarded.
= The test is performed but no configuration is discarded.
! The test is performed and configurations could be discarded but elite configurations are preserved.
. All alive configurations are elite and nothing is discarded.
+-+-----------+-----------+-----------+----------------+-----------+--------+-----+----+------+
| | Instance| Alive| Best| Mean best| Exp so far| W time| rho|KenW| Qvar|
+-+-----------+-----------+-----------+----------------+-----------+--------+-----+----+------+
Saving _problems/test_TunerBatchIrace-4.R
Saving _problems/test_TunerBatchNLoptr-5.R
Saving _problems/test_TunerBatchRandomSearch-2.R
Saving _problems/test_TunerInternal-18.R
Saving _problems/test_TuningInstanceBatchMultiCrit-19.R
Saving _problems/test_TuningInstanceBatchMultiCrit-35.R
Saving _problems/test_TuningInstanceBatchMultiCrit-64.R
Saving _problems/test_TuningInstanceBatchMultiCrit-114.R
Saving _problems/test_TuningInstanceBatchMultiCrit-129.R
Saving _problems/test_TuningInstanceBatchMultiCrit-186.R
Saving _problems/test_TuningInstanceBatchSingleCrit-9.R
Saving _problems/test_TuningInstanceBatchSingleCrit-46.R
Saving _problems/test_TuningInstanceBatchSingleCrit-55.R
Saving _problems/test_TuningInstanceBatchSingleCrit-76.R
Saving _problems/test_TuningInstanceBatchSingleCrit-99.R
Saving _problems/test_TuningInstanceBatchSingleCrit-128.R
Saving _problems/test_TuningInstanceBatchSingleCrit-136.R
Saving _problems/test_TuningInstanceBatchSingleCrit-170.R
Saving _problems/test_TuningInstanceBatchSingleCrit-220.R
Saving _problems/test_TuningInstanceBatchSingleCrit-237.R
Saving _problems/test_TuningInstanceBatchSingleCrit-413.R
Saving _problems/test_TuningInstanceBatchSingleCrit-428.R
Saving _problems/test_TuningInstanceBatchSingleCrit-459.R
Saving _problems/test_TuningInstanceBatchSingleCrit-484.R
Saving _problems/test_error_handling-18.R
Saving _problems/test_error_handling-36.R
Saving _problems/test_extract_inner_tuning_archives-11.R
Saving _problems/test_extract_inner_tuning_archives-131.R
Saving _problems/test_extract_inner_tuning_results-11.R
Saving _problems/test_extract_inner_tuning_results-131.R
Saving _problems/test_mlr_callbacks-14.R
Saving _problems/test_mlr_callbacks-31.R
Saving _problems/test_mlr_callbacks-290.R
Saving _problems/test_mlr_callbacks-307.R
Saving _problems/test_mlr_callbacks-340.R
Saving _problems/test_mlr_callbacks-445.R
Saving _problems/test_trafos-10.R
Saving _problems/test_trafos-34.R
Saving _problems/test_tune-4.R
Saving _problems/test_tune-14.R
Saving _problems/test_tune-24.R
Saving _problems/test_tune_nested-6.R
[ FAIL 113 | WARN 9 | SKIP 68 | PASS 192 ]
══ Skipped tests (68) ══════════════════════════════════════════════════════════
• On CRAN (68): 'test_ArchiveAsyncTuning.R:2:3',
'test_ArchiveAsyncTuning.R:61:3', 'test_ArchiveAsyncTuning.R:119:3',
'test_ArchiveAsyncTuning.R:146:3', 'test_ArchiveAsyncTuning.R:169:3',
'test_ArchiveAsyncTuning.R:209:3', 'test_ArchiveAsyncTuning.R:251:3',
'test_ArchiveAsyncTuning.R:284:3', 'test_ArchiveAsyncTuningFrozen.R:2:3',
'test_AutoTuner.R:640:3', 'test_CallbackAsyncTuning.R:4:3',
'test_CallbackAsyncTuning.R:33:3', 'test_CallbackAsyncTuning.R:64:3',
'test_CallbackAsyncTuning.R:93:3', 'test_CallbackAsyncTuning.R:124:3',
'test_CallbackAsyncTuning.R:160:3', 'test_CallbackAsyncTuning.R:188:3',
'test_CallbackAsyncTuning.R:222:3', 'test_CallbackAsyncTuning.R:252:3',
'test_CallbackAsyncTuning.R:281:3', 'test_CallbackAsyncTuning.R:312:3',
'test_CallbackAsyncTuning.R:343:3', 'test_CallbackAsyncTuning.R:373:3',
'test_CallbackAsyncTuning.R:405:3', 'test_CallbackAsyncTuning.R:443:3',
'test_CallbackAsyncTuning.R:480:3', 'test_CallbackAsyncTuning.R:516:3',
'test_Tuner.R:53:1', 'test_TunerAsyncDesignPoints.R:2:3',
'test_TunerAsyncGridSearch.R:2:3', 'test_TunerAsyncRandomSearch.R:2:3',
'test_TuningInstanceAsyncMultiCrit.R:2:3',
'test_TuningInstanceAsyncMultiCrit.R:30:3',
'test_TuningInstanceAsyncMultiCrit.R:57:3',
'test_TuningInstanceAsyncMultiCrit.R:81:3',
'test_TuningInstanceAsyncMultiCrit.R:106:3',
'test_TuningInstanceAsyncMultiCrit.R:134:3',
'test_TuningInstanceAsyncMultiCrit.R:189:3',
'test_TuningInstanceAsyncMultiCrit.R:236:3',
'test_TuningInstanceAsyncMultiCrit.R:261:3',
'test_TuningInstanceAsyncSingleCrit.R:2:3',
'test_TuningInstanceAsyncSingleCrit.R:29:3',
'test_TuningInstanceAsyncSingleCrit.R:54:3',
'test_TuningInstanceAsyncSingleCrit.R:78:3',
'test_TuningInstanceAsyncSingleCrit.R:104:3',
'test_TuningInstanceAsyncSingleCrit.R:131:3',
'test_TuningInstanceAsyncSingleCrit.R:182:3',
'test_TuningInstanceAsyncSingleCrit.R:213:3',
'test_TuningInstanceAsyncSingleCrit.R:226:3',
'test_TuningInstanceAsyncSingleCrit.R:240:3',
'test_TuningInstanceAsyncSingleCrit.R:266:3', 'test_auto_tuner.R:25:3',
'test_auto_tuner.R:48:3', 'test_mlr_callbacks.R:40:3',
'test_mlr_callbacks.R:93:3', 'test_mlr_callbacks.R:117:3',
'test_mlr_callbacks.R:141:3', 'test_mlr_callbacks.R:162:3',
'test_mlr_callbacks.R:192:3', 'test_mlr_callbacks.R:218:3',
'test_mlr_callbacks.R:251:3', 'test_mlr_callbacks.R:410:3',
'test_mlr_callbacks.R:452:3', 'test_mlr_callbacks.R:480:3',
'test_ti_async.R:2:3', 'test_ti_async.R:16:3', 'test_ti_async.R:30:3',
'test_ti_async.R:42:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_ArchiveBatchTuning.R:11:3'): ArchiveTuning access methods work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_ArchiveBatchTuning.R:11:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchTuning.R:126:3'): ArchiveTuning as.data.table function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_ArchiveBatchTuning.R:126:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_ArchiveBatchTuning.R:277:3'): ArchiveBatchTuning as.data.table function works for internally tuned values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_ArchiveBatchTuning.R:277:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:10:3'): AutoTuner / train+predict ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:10:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
23. └─inst$eval_batch(g$data[inds])
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:42:3'): AutoTuner / resample ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), at, r_outer, store_models = TRUE) at test_AutoTuner.R:42:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:77:3'): nested resamppling results are consistent ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("iris"), lrn, cv2, store_models = TRUE) at test_AutoTuner.R:77:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:93:3'): AT training does not change learner in instance args ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:93:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:118:3'): AutoTuner works with graphlearner ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:118:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
23. └─inst$eval_batch(g$data[inds])
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:155:3'): Nested resampling works with graphlearner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
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. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:184:3'): store_tuning_instance, store_benchmark_result and store_models flags work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
23. └─inst$eval_batch(g$data[inds])
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:246:3'): predict_type works ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:246:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:282:3'): search space from TuneToken works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("iris")) at test_AutoTuner.R:282:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:308:3'): AutoTuner get_base_learner method works ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("pima")) at test_AutoTuner.R:308:3
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$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:373:3'): AutoTuner hash works #647 in mlr3 ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, store_models = TRUE) at test_AutoTuner.R:373:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_AutoTuner.R:389:3'): AutoTuner works with empty search space ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("pima")) at test_AutoTuner.R:389:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:420:3'): AutoTuner importance method works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("penguins")) at test_AutoTuner.R:420:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:434:3'): AutoTuner selected_features method works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(tsk("penguins")) at test_AutoTuner.R:434:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:480:3'): AutoTuner works with instantiated resampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:480:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:606:3'): marshalable learner ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:606:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:625:3'): marshal ───────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:625:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(list(list()))
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:676:3'): AutoTuner works with internal tuning and validation ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:676:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_AutoTuner.R:699:3'): AutoTuner works when internal_search_space is part of primary search space ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─at$train(task) at test_AutoTuner.R:699:3
2. └─mlr3:::.__Learner__train(...)
3. └─mlr3:::learner_train(...)
4. └─mlr3misc::encapsulate(...)
5. ├─mlr3misc::invoke(...)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─mlr3 (local) .f(learner = `<AutoTunr>`, task = `<TskClssf>`)
10. └─get_private(learner)$.train(task)
11. └─mlr3tuning:::.__AutoTuner__.train(...)
12. └─self$tuner$optimize(instance)
13. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
14. └─private$.optimizer$optimize(inst)
15. └─bbotk:::.__OptimizerBatch__optimize(...)
16. └─bbotk::optimize_batch_default(inst, self)
17. ├─base::tryCatch(...)
18. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
19. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
20. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
21. └─get_private(optimizer)$.optimize(instance)
22. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
23. └─inst$eval_batch(design$data)
24. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
25. └─self$objective$eval_many(xss_trafoed)
26. └─bbotk:::.__Objective__eval_many(...)
27. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
28. │ └─base::eval.parent(expr, n = 1L)
29. │ └─base::eval(expr, p)
30. │ └─base::eval(expr, p)
31. └─private$.eval_many(xss = xss, resampling = `<list>`)
32. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
33. └─mlr3::benchmark(...)
34. └─ResultData$new(grid, data_extra, store_backends = store_backends)
35. └─mlr3 (local) initialize(...)
36. └─mlr3:::.__ResultData__initialize(...)
37. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
38. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:10:3'): on_optimization_begin works ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:10:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:30:3'): on_optimization_end works ────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:30:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:52:3'): on_optimizer_after_eval works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:52:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:73:3'): on_optimizer_after_eval works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:73:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:96:3'): on_eval_after_design works ───────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:96:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:120:3'): on_eval_after_benchmark and on_eval_before_archive works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:120:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:143:3'): on_tuning_result_begin in TuningInstanceSingleCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:143:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:164:3'): on_result_end in TuningInstanceSingleCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:164:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:184:3'): on_result in TuningInstanceSingleCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:184:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:207:3'): on_tuning_result_begin in TuningInstanceBatchMultiCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:207:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:228:3'): on_result_end in TuningInstanceBatchMultiCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:228:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:248:3'): on_result in TuningInstanceBatchMultiCrit works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:248:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:277:3'): on_resample_begin works ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:277:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:305:3'): on_resample_before_train works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:305:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:332:3'): on_resample_before_predict works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:332:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_CallbackBatchTuning.R:360:3'): on_resample_end works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_CallbackBatchTuning.R:360:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:12:3'): objective async works ───────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:12:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:32:3'): store benchmark result works ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:32:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:54:3'): store models works ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:54:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningAsync.R:76:3'): rush objective with multiple measures works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─objective$eval(xs) at test_ObjectiveTuningAsync.R:76:3
2. └─bbotk:::.__Objective__eval(...)
3. ├─mlr3misc::invoke(private$.eval, xs = xs, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval(xs = xs, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningAsync__.eval(...)
9. └─mlr3::resample(...)
10. └─ResultData$new(data, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:14:3'): ObjectiveTuningBatch ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:14:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:37:3'): ObjectiveTuningBatch - Multiple measures ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:37:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:52:3'): ObjectiveTuningBatch - Store models ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:52:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:69:3'): runtime of learners is added ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:69:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:105:3'): tuner can modify resampling ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─instance$eval_batch(data.table(cp = 0.001)) at test_ObjectiveTuningBatch.R:105:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:128:3'): benchmark clone works ──────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(grid, clone = c()) at test_ObjectiveTuningBatch.R:128:3
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_ObjectiveTuningBatch.R:149:3'): objects are cloned ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─obj$eval_many(xss) at test_ObjectiveTuningBatch.R:149:3
2. └─bbotk:::.__Objective__eval_many(...)
3. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
4. │ └─base::eval.parent(expr, n = 1L)
5. │ └─base::eval(expr, p)
6. │ └─base::eval(expr, p)
7. └─private$.eval_many(xss = xss, resampling = `<list>`)
8. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
9. └─mlr3::benchmark(...)
10. └─ResultData$new(grid, data_extra, store_backends = store_backends)
11. └─mlr3 (local) initialize(...)
12. └─mlr3:::.__ResultData__initialize(...)
13. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
14. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:5:5'): API ─────────────────────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(rs$optimize(inst), nrows = 1) at test_Tuner.R:5:5
2. │ └─checkmate::checkDataTable(...)
3. └─rs$optimize(inst)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
14. └─inst$eval_batch(design$data)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:46:3'): we get a result when some subordinate params are not fulfilled ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(d) at test_Tuner.R:46:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:90:3'): Tuner works with graphlearner ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_Tuner.R:90:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:121:3'): Tuner works with instantiated resampling ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─rs$optimize(inst) at test_Tuner.R:121:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:182:3'): internal single crit ──────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:182:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:205:3'): internal single crit without benchmark_result ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:205:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:235:3'): internal multi crit ───────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:235:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:294:3'): internal tuning: branching ────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_Tuner.R:294:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:325:3'): parameter transformations can be used with internal tuning ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:325:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_Tuner.R:348:3'): tag internal tune token manually in primary search space ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_Tuner.R:348:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchCmaes.R:12:3'): TunerBatchCmaes ──────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TunerBatchCmaes.R:12:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchCmaes__.optimize(...)
13. ├─mlr3misc::invoke(...)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─adagio::pureCMAES(...)
18. └─adagio (local) fun(arx[, k])
19. └─bbotk (local) fct(x, ...)
20. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
21. └─private$.objective_function(x, self, self$objective_multiplicator)
22. └─inst$eval_batch(xdt)
23. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
24. └─self$objective$eval_many(xss_trafoed)
25. └─bbotk:::.__Objective__eval_many(...)
26. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
27. │ └─base::eval.parent(expr, n = 1L)
28. │ └─base::eval(expr, p)
29. │ └─base::eval(expr, p)
30. └─private$.eval_many(xss = xss, resampling = `<list>`)
31. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
32. └─mlr3::benchmark(...)
33. └─ResultData$new(grid, data_extra, store_backends = store_backends)
34. └─mlr3 (local) initialize(...)
35. └─mlr3:::.__ResultData__initialize(...)
36. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
37. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchDesignPoints.R:3:3'): TunerBatchDesignPoints ─────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner(...) at test_TunerBatchDesignPoints.R:3:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
13. └─instance$eval_batch(design[inds, ])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchFromOptimizerBatch.R:13:3'): TunerBatchFromOptimizerBatch parameter set works after cloning ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner_2$optimize(instance) at test_TunerBatchFromOptimizerBatch.R:13:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGenSA.R:4:3'): TunerBatchGenSA ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─global test_tuner("gensa") at test_TunerBatchGenSA.R:4:3
2. │ └─tuner$optimize(inst)
3. │ └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. │ └─private$.optimizer$optimize(inst)
5. │ └─bbotk:::.__OptimizerBatch__optimize(...)
6. │ └─bbotk::optimize_batch_default(inst, self)
7. │ ├─base::tryCatch(...)
8. │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. │ └─get_private(optimizer)$.optimize(instance)
12. │ └─bbotk:::.__OptimizerBatchGenSA__.optimize(...)
13. │ └─GenSA::GenSA(...)
14. └─GenSA (local) `<fn>`(`<dbl>`)
15. └─bbotk (local) fn(par, ...)
16. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
17. └─private$.objective_function(x, self, self$objective_multiplicator)
18. └─inst$eval_batch(xdt)
19. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
20. └─self$objective$eval_many(xss_trafoed)
21. └─bbotk:::.__Objective__eval_many(...)
22. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
23. │ └─base::eval.parent(expr, n = 1L)
24. │ └─base::eval(expr, p)
25. │ └─base::eval(expr, p)
26. └─private$.eval_many(xss = xss, resampling = `<list>`)
27. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
28. └─mlr3::benchmark(...)
29. └─ResultData$new(grid, data_extra, store_backends = store_backends)
30. └─mlr3 (local) initialize(...)
31. └─mlr3:::.__ResultData__initialize(...)
32. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
33. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGenSA.R:23:3'): TunerBatchGenSA with int params and trafo ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─tt$optimize(inst) at test_TunerBatchGenSA.R:23:3
2. │ └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. │ └─private$.optimizer$optimize(inst)
4. │ └─bbotk:::.__OptimizerBatch__optimize(...)
5. │ └─bbotk::optimize_batch_default(inst, self)
6. │ ├─base::tryCatch(...)
7. │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. │ └─get_private(optimizer)$.optimize(instance)
11. │ └─bbotk:::.__OptimizerBatchGenSA__.optimize(...)
12. │ └─GenSA::GenSA(...)
13. └─GenSA (local) `<fn>`(`<dbl>`)
14. └─bbotk (local) fn(par, ...)
15. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
16. └─private$.objective_function(x, self, self$objective_multiplicator)
17. └─inst$eval_batch(xdt)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGenSA.R:31:3'): TunerBatchGenSA - Optimize wrapper with maximize measure ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─tt$optimize(inst) at test_TunerBatchGenSA.R:31:3
2. │ └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. │ └─private$.optimizer$optimize(inst)
4. │ └─bbotk:::.__OptimizerBatch__optimize(...)
5. │ └─bbotk::optimize_batch_default(inst, self)
6. │ ├─base::tryCatch(...)
7. │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. │ └─get_private(optimizer)$.optimize(instance)
11. │ └─bbotk:::.__OptimizerBatchGenSA__.optimize(...)
12. │ └─GenSA::GenSA(...)
13. └─GenSA (local) `<fn>`(`<dbl>`)
14. └─bbotk (local) fn(par, ...)
15. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
16. └─private$.objective_function(x, self, self$objective_multiplicator)
17. └─inst$eval_batch(xdt)
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(xss_trafoed)
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGridSearch.R:2:3'): TunerGridSearch ──────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner(...) at test_TunerBatchGridSearch.R:2:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchGridSearch.R:22:3'): TunerGridSearch with TerminatorNone ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TunerBatchGridSearch.R:22:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:4:3'): TunerIrace ────────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner("irace", term_evals = 42) at test_TunerBatchIrace.R:4:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
13. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─irace::irace(scenario = scenario)
18. └─irace:::irace_common(scenario, simple = TRUE)
19. └─irace:::irace_run(scenario = scenario)
20. └─irace:::elitist_race(...)
21. └─irace:::race_wrapper(...)
22. └─irace:::race_wrapper_helper(...)
23. └─irace:::execute_experiments(...)
24. └─scenario$targetRunnerParallel(...)
25. └─tuning_instance$eval_batch(xdt)
26. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
27. └─self$objective$eval_many(xss_trafoed)
28. └─bbotk:::.__Objective__eval_many(...)
29. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
30. │ └─base::eval.parent(expr, n = 1L)
31. │ └─base::eval(expr, p)
32. │ └─base::eval(expr, p)
33. └─private$.eval_many(xss = xss, resampling = `<list>`)
34. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
35. └─mlr3::benchmark(...)
36. └─ResultData$new(grid, data_extra, store_backends = store_backends)
37. └─mlr3 (local) initialize(...)
38. └─mlr3:::.__ResultData__initialize(...)
39. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
40. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:37:36'): TunerIrace works with dependencies ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:37:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. └─tuner$optimize(instance) at test_TunerBatchIrace.R:37:36
6. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
7. └─private$.optimizer$optimize(inst)
8. └─bbotk:::.__OptimizerBatch__optimize(...)
9. └─bbotk::optimize_batch_default(inst, self)
10. ├─base::tryCatch(...)
11. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
12. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
13. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
14. └─get_private(optimizer)$.optimize(instance)
15. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
16. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─irace::irace(scenario = scenario)
21. └─irace:::irace_common(scenario, simple = TRUE)
22. └─irace:::irace_run(scenario = scenario)
23. └─irace:::elitist_race(...)
24. └─irace:::race_wrapper(...)
25. └─irace:::race_wrapper_helper(...)
26. └─irace:::execute_experiments(...)
27. └─scenario$targetRunnerParallel(...)
28. └─tuning_instance$eval_batch(xdt)
29. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
30. └─self$objective$eval_many(xss_trafoed)
31. └─bbotk:::.__Objective__eval_many(...)
32. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
33. │ └─base::eval.parent(expr, n = 1L)
34. │ └─base::eval(expr, p)
35. │ └─base::eval(expr, p)
36. └─private$.eval_many(xss = xss, resampling = `<list>`)
37. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
38. └─mlr3::benchmark(...)
39. └─ResultData$new(grid, data_extra, store_backends = store_backends)
40. └─mlr3 (local) initialize(...)
41. └─mlr3:::.__ResultData__initialize(...)
42. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
43. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:56:36'): TunerIrace works with logical parameters ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:56:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. └─tuner$optimize(instance) at test_TunerBatchIrace.R:56:36
6. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
7. └─private$.optimizer$optimize(inst)
8. └─bbotk:::.__OptimizerBatch__optimize(...)
9. └─bbotk::optimize_batch_default(inst, self)
10. ├─base::tryCatch(...)
11. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
12. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
13. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
14. └─get_private(optimizer)$.optimize(instance)
15. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
16. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─irace::irace(scenario = scenario)
21. └─irace:::irace_common(scenario, simple = TRUE)
22. └─irace:::irace_run(scenario = scenario)
23. └─irace:::elitist_race(...)
24. └─irace:::race_wrapper(...)
25. └─irace:::race_wrapper_helper(...)
26. └─irace:::execute_experiments(...)
27. └─scenario$targetRunnerParallel(...)
28. └─tuning_instance$eval_batch(xdt)
29. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
30. └─self$objective$eval_many(xss_trafoed)
31. └─bbotk:::.__Objective__eval_many(...)
32. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
33. │ └─base::eval.parent(expr, n = 1L)
34. │ └─base::eval(expr, p)
35. │ └─base::eval(expr, p)
36. └─private$.eval_many(xss = xss, resampling = `<list>`)
37. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
38. └─mlr3::benchmark(...)
39. └─ResultData$new(grid, data_extra, store_backends = store_backends)
40. └─mlr3 (local) initialize(...)
41. └─mlr3:::.__ResultData__initialize(...)
42. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
43. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:70:36'): TunerIrace uses digits ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:70:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. ├─checkmate::expect_data_table(tuner$optimize(instance)) at test_TunerBatchIrace.R:70:36
6. │ └─checkmate::checkDataTable(...)
7. └─tuner$optimize(instance)
8. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
9. └─private$.optimizer$optimize(inst)
10. └─bbotk:::.__OptimizerBatch__optimize(...)
11. └─bbotk::optimize_batch_default(inst, self)
12. ├─base::tryCatch(...)
13. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
14. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
15. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
16. └─get_private(optimizer)$.optimize(instance)
17. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
18. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─irace::irace(scenario = scenario)
23. └─irace:::irace_common(scenario, simple = TRUE)
24. └─irace:::irace_run(scenario = scenario)
25. └─irace:::elitist_race(...)
26. └─irace:::race_wrapper(...)
27. └─irace:::race_wrapper_helper(...)
28. └─irace:::execute_experiments(...)
29. └─scenario$targetRunnerParallel(...)
30. └─tuning_instance$eval_batch(xdt)
31. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
32. └─self$objective$eval_many(xss_trafoed)
33. └─bbotk:::.__Objective__eval_many(...)
34. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
35. │ └─base::eval.parent(expr, n = 1L)
36. │ └─base::eval(expr, p)
37. │ └─base::eval(expr, p)
38. └─private$.eval_many(xss = xss, resampling = `<list>`)
39. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
40. └─mlr3::benchmark(...)
41. └─ResultData$new(grid, data_extra, store_backends = store_backends)
42. └─mlr3 (local) initialize(...)
43. └─mlr3:::.__ResultData__initialize(...)
44. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
45. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchIrace.R:84:36'): TunerIrace works with unnamed discrete values ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─base::suppressMessages(...) at test_TunerBatchIrace.R:84:3
2. │ └─base::withCallingHandlers(...)
3. ├─utils::capture.output(...)
4. │ └─base::withVisible(...elt(i))
5. ├─checkmate::expect_data_table(tuner$optimize(instance)) at test_TunerBatchIrace.R:84:36
6. │ └─checkmate::checkDataTable(...)
7. └─tuner$optimize(instance)
8. └─mlr3tuning:::.__TunerBatchIrace__optimize(...)
9. └─private$.optimizer$optimize(inst)
10. └─bbotk:::.__OptimizerBatch__optimize(...)
11. └─bbotk::optimize_batch_default(inst, self)
12. ├─base::tryCatch(...)
13. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
14. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
15. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
16. └─get_private(optimizer)$.optimize(instance)
17. └─bbotk:::.__OptimizerBatchIrace__.optimize(...)
18. ├─mlr3misc::invoke(irace::irace, scenario = scenario, .opts = allow_partial_matching)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─irace::irace(scenario = scenario)
23. └─irace:::irace_common(scenario, simple = TRUE)
24. └─irace:::irace_run(scenario = scenario)
25. └─irace:::elitist_race(...)
26. └─irace:::race_wrapper(...)
27. └─irace:::race_wrapper_helper(...)
28. └─irace:::execute_experiments(...)
29. └─scenario$targetRunnerParallel(...)
30. └─tuning_instance$eval_batch(xdt)
31. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
32. └─self$objective$eval_many(xss_trafoed)
33. └─bbotk:::.__Objective__eval_many(...)
34. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
35. │ └─base::eval.parent(expr, n = 1L)
36. │ └─base::eval(expr, p)
37. │ └─base::eval(expr, p)
38. └─private$.eval_many(xss = xss, resampling = `<list>`)
39. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
40. └─mlr3::benchmark(...)
41. └─ResultData$new(grid, data_extra, store_backends = store_backends)
42. └─mlr3 (local) initialize(...)
43. └─mlr3:::.__ResultData__initialize(...)
44. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
45. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchNLoptr.R:5:3'): TunerNLoptr ──────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner("nloptr", algorithm = "NLOPT_LN_BOBYQA", term_evals = 4) at test_TunerBatchNLoptr.R:5:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchNLoptr__.optimize(...)
13. ├─mlr3misc::invoke(...)
14. │ └─base::eval.parent(expr, n = 1L)
15. │ └─base::eval(expr, p)
16. │ └─base::eval(expr, p)
17. └─nloptr::nloptr(...)
18. └─bbotk (local) eval_f(x0, ...)
19. └─bbotk:::.__OptimInstanceBatch__objective_function(...)
20. └─private$.objective_function(x, self, self$objective_multiplicator)
21. └─inst$eval_batch(xdt)
22. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
23. └─self$objective$eval_many(xss_trafoed)
24. └─bbotk:::.__Objective__eval_many(...)
25. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
26. │ └─base::eval.parent(expr, n = 1L)
27. │ └─base::eval(expr, p)
28. │ └─base::eval(expr, p)
29. └─private$.eval_many(xss = xss, resampling = `<list>`)
30. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
31. └─mlr3::benchmark(...)
32. └─ResultData$new(grid, data_extra, store_backends = store_backends)
33. └─mlr3 (local) initialize(...)
34. └─mlr3:::.__ResultData__initialize(...)
35. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
36. └─data.table:::`[.data.table`(...)
── Error ('test_TunerBatchRandomSearch.R:2:3'): TunerRandomSearch ──────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─global test_tuner("random_search") at test_TunerBatchRandomSearch.R:2:3
2. └─tuner$optimize(inst)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TunerInternal.R:18:3'): tuner internal works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TunerInternal.R:18:3
2. └─mlr3tuning:::.__TunerBatch__optimize(...)
3. └─bbotk::optimize_batch_default(inst, self)
4. ├─base::tryCatch(...)
5. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
6. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
7. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
8. └─get_private(optimizer)$.optimize(instance)
9. └─mlr3tuning:::.__TunerBatchInternal__.optimize(...)
10. └─inst$eval_batch(data.table())
11. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
12. └─self$objective$eval_many(list(list()))
13. └─bbotk:::.__Objective__eval_many(...)
14. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
15. │ └─base::eval.parent(expr, n = 1L)
16. │ └─base::eval(expr, p)
17. │ └─base::eval(expr, p)
18. └─private$.eval_many(xss = xss, resampling = `<list>`)
19. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
20. └─mlr3::benchmark(...)
21. └─ResultData$new(grid, data_extra, store_backends = store_backends)
22. └─mlr3 (local) initialize(...)
23. └─mlr3:::.__ResultData__initialize(...)
24. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
25. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:19:3'): tuning with multiple objectives ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchMultiCrit.R:19:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:35:3'): store_benchmark_result and store_models flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(...) at test_TuningInstanceBatchMultiCrit.R:35:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:64:3'): check_values flag with parameter set dependencies ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchMultiCrit.R:64:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:114:3'): TuneToken and result_learner_param_vals works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TuningInstanceBatchMultiCrit.R:114:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
12. └─instance$eval_batch(design[inds, ])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:122:3'): TuningInstanceBatchMultiCrit and empty search space works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TuningInstanceBatchMultiCrit.R:122:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(list(list()))
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchMultiCrit.R:186:3'): Batch multi-crit internal tuning works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), min.rows = 1) at test_TuningInstanceBatchMultiCrit.R:186:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
14. └─inst$eval_batch(design$data)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:9:3'): TuningInstanceBatchSingleCrit ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(...) at test_TuningInstanceBatchSingleCrit.R:9:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:46:3'): archive one row (#40) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(data.table(cp = 0.1)) at test_TuningInstanceBatchSingleCrit.R:46:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:55:3'): eval_batch and termination ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(design[1:2, ]) at test_TuningInstanceBatchSingleCrit.R:55:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:76:3'): the same experiment can be added twice ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(d) at test_TuningInstanceBatchSingleCrit.R:76:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:99:3'): tuning with custom resampling ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchSingleCrit.R:99:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:128:3'): non-scalar hyperpars (#201) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tnr("random_search")$optimize(inst) at test_TuningInstanceBatchSingleCrit.R:128:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:136:3'): store_benchmark_result and store_models flag works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─inst$eval_batch(...) at test_TuningInstanceBatchSingleCrit.R:136:3
2. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
3. └─self$objective$eval_many(xss_trafoed)
4. └─bbotk:::.__Objective__eval_many(...)
5. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
6. │ └─base::eval.parent(expr, n = 1L)
7. │ └─base::eval(expr, p)
8. │ └─base::eval(expr, p)
9. └─private$.eval_many(xss = xss, resampling = `<list>`)
10. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
11. └─mlr3::benchmark(...)
12. └─ResultData$new(grid, data_extra, store_backends = store_backends)
13. └─mlr3 (local) initialize(...)
14. └─mlr3:::.__ResultData__initialize(...)
15. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
16. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:170:3'): check_values flag with parameter set dependencies ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_TuningInstanceBatchSingleCrit.R:170:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:220:3'): TuneToken and result_learner_param_vals works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TuningInstanceBatchSingleCrit.R:220:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
12. └─instance$eval_batch(design[inds, ])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:230:3'): TuningInstanceBatchSingleCrit and empty search space works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_TuningInstanceBatchSingleCrit.R:230:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(list(list()))
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:413:3'): objective contains no benchmark results ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance) at test_TuningInstanceBatchSingleCrit.R:413:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(list(list()))
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:422:3'): dependencies in defaults work ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_class(...) at test_TuningInstanceBatchSingleCrit.R:422:3
2. │ └─checkmate::checkClass(x, classes, ordered, null.ok)
3. └─mlr3tuning::tune(...)
4. └─tuner$optimize(instance)
5. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
6. └─private$.optimizer$optimize(inst)
7. └─bbotk:::.__OptimizerBatch__optimize(...)
8. └─bbotk::optimize_batch_default(inst, self)
9. ├─base::tryCatch(...)
10. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
11. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
12. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
13. └─get_private(optimizer)$.optimize(instance)
14. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
15. └─inst$eval_batch(design$data)
16. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
17. └─self$objective$eval_many(xss_trafoed)
18. └─bbotk:::.__Objective__eval_many(...)
19. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
20. │ └─base::eval.parent(expr, n = 1L)
21. │ └─base::eval(expr, p)
22. │ └─base::eval(expr, p)
23. └─private$.eval_many(xss = xss, resampling = `<list>`)
24. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
25. └─mlr3::benchmark(...)
26. └─ResultData$new(grid, data_extra, store_backends = store_backends)
27. └─mlr3 (local) initialize(...)
28. └─mlr3:::.__ResultData__initialize(...)
29. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
30. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceBatchSingleCrit.R:459:3'): Batch single-crit internal tuning works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─checkmate::expect_data_table(tuner$optimize(instance), nrows = 1) at test_TuningInstanceBatchSingleCrit.R:459:3
2. │ └─checkmate::checkDataTable(...)
3. └─tuner$optimize(instance)
4. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
5. └─private$.optimizer$optimize(inst)
6. └─bbotk:::.__OptimizerBatch__optimize(...)
7. └─bbotk::optimize_batch_default(inst, self)
8. ├─base::tryCatch(...)
9. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
10. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
11. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
12. └─get_private(optimizer)$.optimize(instance)
13. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
14. └─inst$eval_batch(design$data)
15. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
16. └─self$objective$eval_many(xss_trafoed)
17. └─bbotk:::.__Objective__eval_many(...)
18. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
19. │ └─base::eval.parent(expr, n = 1L)
20. │ └─base::eval(expr, p)
21. │ └─base::eval(expr, p)
22. └─private$.eval_many(xss = xss, resampling = `<list>`)
23. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
24. └─mlr3::benchmark(...)
25. └─ResultData$new(grid, data_extra, store_backends = store_backends)
26. └─mlr3 (local) initialize(...)
27. └─mlr3:::.__ResultData__initialize(...)
28. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
29. └─data.table:::`[.data.table`(...)
── Failure ('test_TuningInstanceBatchSingleCrit.R:478:3'): required parameter can be tuned internally without having a value set ──
Expected `tune(...)` not to throw any errors.
Actually got a <simpleError> with message:
attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─testthat::expect_error(...) at test_TuningInstanceBatchSingleCrit.R:478:3
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$optimize(instance)
9. └─mlr3tuning:::.__TunerBatch__optimize(...)
10. └─bbotk::optimize_batch_default(inst, self)
11. ├─base::tryCatch(...)
12. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
13. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
14. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
15. └─get_private(optimizer)$.optimize(instance)
16. └─mlr3tuning:::.__TunerBatchInternal__.optimize(...)
17. └─inst$eval_batch(data.table())
18. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
19. └─self$objective$eval_many(list(list()))
20. └─bbotk:::.__Objective__eval_many(...)
21. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
22. │ └─base::eval.parent(expr, n = 1L)
23. │ └─base::eval(expr, p)
24. │ └─base::eval(expr, p)
25. └─private$.eval_many(xss = xss, resampling = `<list>`)
26. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
27. └─mlr3::benchmark(...)
28. └─ResultData$new(grid, data_extra, store_backends = store_backends)
29. └─mlr3 (local) initialize(...)
30. └─mlr3:::.__ResultData__initialize(...)
31. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
32. └─data.table:::`[.data.table`(...)
── Error ('test_error_handling.R:18:3'): failing learner ───────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tt$optimize(instance) at test_error_handling.R:18:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_error_handling.R:36:3'): predictions missing ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. ├─mlr3tuning:::expect_resample_error(tt$optimize(instance), "missing") at test_error_handling.R:36:3
2. │ ├─base::withCallingHandlers(...) at ./helper.R:26:3
3. │ └─testthat::expect_error(...)
4. │ └─testthat:::expect_condition_matching_(...)
5. │ └─testthat:::quasi_capture(...)
6. │ ├─testthat (local) .capture(...)
7. │ │ └─base::withCallingHandlers(...)
8. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
9. └─tt$optimize(instance)
10. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
11. └─private$.optimizer$optimize(inst)
12. └─bbotk:::.__OptimizerBatch__optimize(...)
13. └─bbotk::optimize_batch_default(inst, self)
14. ├─base::tryCatch(...)
15. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
16. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
17. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
18. └─get_private(optimizer)$.optimize(instance)
19. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
20. └─inst$eval_batch(design$data)
21. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
22. └─self$objective$eval_many(xss_trafoed)
23. └─bbotk:::.__Objective__eval_many(...)
24. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
25. │ └─base::eval.parent(expr, n = 1L)
26. │ └─base::eval(expr, p)
27. │ └─base::eval(expr, p)
28. └─private$.eval_many(xss = xss, resampling = `<list>`)
29. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
30. └─mlr3::benchmark(...)
31. └─ResultData$new(grid, data_extra, store_backends = store_backends)
32. └─mlr3 (local) initialize(...)
33. └─mlr3:::.__ResultData__initialize(...)
34. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
35. └─data.table:::`[.data.table`(...)
── Error ('test_extract_inner_tuning_archives.R:11:3'): extract_inner_tuning_archives function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, at, resampling_outer, store_models = TRUE) at test_extract_inner_tuning_archives.R:11:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_tuning_archives.R:131:3'): works with internal tuning ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(...) at test_extract_inner_tuning_archives.R:131:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_tuning_results.R:11:3'): extract_inner_tuning_results function works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, at, resampling_outer, store_models = TRUE) at test_extract_inner_tuning_results.R:11:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_extract_inner_tuning_results.R:131:3'): extract_inner_tuning_results returns tuning_instance ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(tsk("penguins"), at, resampling_outer, store_models = TRUE) at test_extract_inner_tuning_results.R:131:3
2. └─mlr3:::future_map(...)
3. └─future.apply::future_mapply(...)
4. └─future.apply:::future_xapply(...)
5. └─base::tryCatch(...)
6. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
7. └─base (local) tryCatchOne(...)
8. └─value[[3L]](cond)
9. └─future.apply:::onError(e, futures = fs, debug = debug)
── Error ('test_mlr_callbacks.R:6:3'): backup callback works ───────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:6:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:23:3'): backup callback works with standalone tuner ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:23:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
13. └─inst$eval_batch(g$data[inds])
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:282:3'): batch default configuration callback works ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:282:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. └─mlr3misc::call_back(...)
8. └─mlr3misc::walk(...)
9. └─mlr3misc (local) .f(.xi, ...)
10. └─callback$call(stage, context)
11. └─self[[stage]](self, context)
12. └─context$instance$eval_batch(xdt)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:299:3'): batch default configuration callback works with logscale ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:299:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. └─mlr3misc::call_back(...)
8. └─mlr3misc::walk(...)
9. └─mlr3misc (local) .f(.xi, ...)
10. └─callback$call(stage, context)
11. └─self[[stage]](self, context)
12. └─context$instance$eval_batch(xdt)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:332:3'): batch default configuration callback works without transformation and with logscale ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:332:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. └─mlr3misc::call_back(...)
8. └─mlr3misc::walk(...)
9. └─mlr3misc (local) .f(.xi, ...)
10. └─callback$call(stage, context)
11. └─self[[stage]](self, context)
12. └─context$instance$eval_batch(xdt)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_mlr_callbacks.R:437:3'): one se rule callback works ────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_mlr_callbacks.R:437:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_trafos.R:10:3'): simple exp trafo works ────────────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_trafos.R:10:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchDesignPoints__.optimize(...)
12. └─instance$eval_batch(design[inds, ])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_trafos.R:34:3'): trafo where param names change ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(inst) at test_trafos.R:34:3
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
12. └─inst$eval_batch(g$data[inds])
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_tune.R:3:3'): tune function works with one measure ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_tune.R:3:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_tune.R:13:3'): tune function works with multiple measures ──────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_tune.R:13:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_tune.R:23:3'): tune function works without measure ─────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune(...) at test_tune.R:23:3
2. └─tuner$optimize(instance)
3. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
4. └─private$.optimizer$optimize(inst)
5. └─bbotk:::.__OptimizerBatch__optimize(...)
6. └─bbotk::optimize_batch_default(inst, self)
7. ├─base::tryCatch(...)
8. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. └─get_private(optimizer)$.optimize(instance)
12. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
13. └─inst$eval_batch(design$data)
14. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
15. └─self$objective$eval_many(xss_trafoed)
16. └─bbotk:::.__Objective__eval_many(...)
17. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
18. │ └─base::eval.parent(expr, n = 1L)
19. │ └─base::eval(expr, p)
20. │ └─base::eval(expr, p)
21. └─private$.eval_many(xss = xss, resampling = `<list>`)
22. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
23. └─mlr3::benchmark(...)
24. └─ResultData$new(grid, data_extra, store_backends = store_backends)
25. └─mlr3 (local) initialize(...)
26. └─mlr3:::.__ResultData__initialize(...)
27. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
28. └─data.table:::`[.data.table`(...)
── Error ('test_tune_nested.R:5:3'): tune_nested function works ────────────────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3tuning::tune_nested(...) at test_tune_nested.R:5:3
2. └─mlr3::resample(task, at, outer_resampling, store_models = TRUE)
3. └─mlr3:::future_map(...)
4. └─future.apply::future_mapply(...)
5. └─future.apply:::future_xapply(...)
6. └─base::tryCatch(...)
7. └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. └─base (local) tryCatchOne(...)
9. └─value[[3L]](cond)
10. └─future.apply:::onError(e, futures = fs, debug = debug)
[ FAIL 113 | WARN 9 | SKIP 68 | PASS 192 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.5.0
Check: examples
Result: ERROR
Running examples in ‘mlr3tuning-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: mlr_tuners_internal
> ### Title: Hyperparameter Tuning with Internal Tuning
> ### Aliases: mlr_tuners_internal TunerBatchInternal
>
> ### ** Examples
>
> ## Don't show:
> if (mlr3misc::require_namespaces(c("mlr3learners", "xgboost"), quietly = TRUE)) withAutoprint({ # examplesIf
+ ## End(Don't show)
+ library(mlr3learners)
+
+ # Retrieve task
+ task = tsk("pima")
+
+ # Load learner and set search space
+ learner = lrn("classif.xgboost",
+ nrounds = to_tune(upper = 1000, internal = TRUE),
+ early_stopping_rounds = 10,
+ validate = "test",
+ eval_metric = "merror"
+ )
+
+ # Internal hyperparameter tuning on the pima indians diabetes data set
+ instance = tune(
+ tnr("internal"),
+ tsk("iris"),
+ learner,
+ rsmp("cv", folds = 3),
+ msr("internal_valid_score", minimize = TRUE, select = "merror")
+ )
+
+ # best performing hyperparameter configuration
+ instance$result_learner_param_vals
+
+ instance$result_learner_param_vals$internal_tuned_values
+ ## Don't show:
+ }) # examplesIf
> library(mlr3learners)
> task = tsk("pima")
> learner = lrn("classif.xgboost", nrounds = to_tune(upper = 1000, internal = TRUE),
+ early_stopping_rounds = 10, validate = "test", eval_metric = "merror")
> instance = tune(tnr("internal"), tsk("iris"), learner, rsmp("cv", folds = 3),
+ msr("internal_valid_score", minimize = TRUE, select = "merror"))
INFO [16:06:08.310] [bbotk] Starting to optimize 0 parameter(s) with '<TunerBatchInternal>' and '<TerminatorNone>'
INFO [16:06:08.317] [bbotk] Evaluating 1 configuration(s)
INFO [16:06:08.343] [mlr3] Running benchmark with 3 resampling iterations
INFO [16:06:08.388] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 1/3)
INFO [16:06:08.491] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 2/3)
INFO [16:06:08.580] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 3/3)
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: eval_metric, nthread, num_class. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in throw_err_or_depr_msg("Parameter '", match_old, "' has been renamed to '", :
Parameter 'watchlist' has been renamed to 'evals'. This warning will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: eval_metric, nthread, num_class. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in throw_err_or_depr_msg("Parameter '", match_old, "' has been renamed to '", :
Parameter 'watchlist' has been renamed to 'evals'. This warning will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: eval_metric, nthread, num_class. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in throw_err_or_depr_msg("Parameter '", match_old, "' has been renamed to '", :
Parameter 'watchlist' has been renamed to 'evals'. This warning will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning: Caught simpleError. Canceling all iterations ...
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: eval_metric, nthread, num_class. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in throw_err_or_depr_msg("Parameter '", match_old, "' has been renamed to '", :
Parameter 'watchlist' has been renamed to 'evals'. This warning will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: eval_metric, nthread, num_class. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in throw_err_or_depr_msg("Parameter '", match_old, "' has been renamed to '", :
Parameter 'watchlist' has been renamed to 'evals'. This warning will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Error in names(x) <- nm : attempt to set an attribute on NULL
Calls: withAutoprint ... tryCatchList -> tryCatchOne -> <Anonymous> -> onError
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
AutoTuner 6.623 0.329 7.717
mlr3tuning.one_se_rule 6.293 0.096 6.887
Flavor: r-release-linux-x86_64
Current CRAN status: ERROR: 4, OK: 9
Version: 0.6.0
Check: examples
Result: ERROR
Running examples in ‘mlr3tuningspaces-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: TuningSpace
> ### Title: Tuning Spaces
> ### Aliases: TuningSpace
>
> ### ** Examples
>
> library(mlr3tuning)
>
> # Get default tuning space of rpart learner
> tuning_space = lts("classif.rpart.default")
>
> # Set tuning space
> learner = lrn("classif.rpart")
> learner$param_set$values = tuning_space$values
>
> # Tune learner
> instance = tune(
+ tnr("random_search"),
+ task = tsk("pima"),
+ learner = learner,
+ resampling = rsmp ("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 10)
INFO [04:34:35.550] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerBatchRandomSearch>' and '<TerminatorEvals> [n_evals=10, k=0]'
INFO [04:34:35.770] [bbotk] Evaluating 1 configuration(s)
INFO [04:34:35.852] [mlr3] Running benchmark with 1 resampling iterations
INFO [04:34:36.060] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [04:34:36.207] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: tune ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.6.0
Check: examples
Result: ERROR
Running examples in ‘mlr3tuningspaces-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: TuningSpace
> ### Title: Tuning Spaces
> ### Aliases: TuningSpace
>
> ### ** Examples
>
> library(mlr3tuning)
>
> # Get default tuning space of rpart learner
> tuning_space = lts("classif.rpart.default")
>
> # Set tuning space
> learner = lrn("classif.rpart")
> learner$param_set$values = tuning_space$values
>
> # Tune learner
> instance = tune(
+ tnr("random_search"),
+ task = tsk("pima"),
+ learner = learner,
+ resampling = rsmp ("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 10)
INFO [17:17:47.934] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerBatchRandomSearch>' and '<TerminatorEvals> [n_evals=10, k=0]'
INFO [17:17:48.029] [bbotk] Evaluating 1 configuration(s)
INFO [17:17:48.089] [mlr3] Running benchmark with 1 resampling iterations
INFO [17:17:48.179] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:17:48.237] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: tune ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.6.0
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")
>
> # Set tuning space
> learner = lrn("classif.rpart")
> learner$param_set$values = tuning_space$values
>
> # Tune learner
> instance = tune(
+ tnr("random_search"),
+ task = tsk("pima"),
+ learner = learner,
+ resampling = rsmp ("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 10)
INFO [17:50:56.812] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerBatchRandomSearch>' and '<TerminatorEvals> [n_evals=10, k=0]'
INFO [17:50:57.095] [bbotk] Evaluating 1 configuration(s)
INFO [17:50:57.169] [mlr3] Running benchmark with 1 resampling iterations
INFO [17:50:57.569] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [17:50:57.816] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: tune ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.6.0
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")
>
> # Set tuning space
> learner = lrn("classif.rpart")
> learner$param_set$values = tuning_space$values
>
> # Tune learner
> instance = tune(
+ tnr("random_search"),
+ task = tsk("pima"),
+ learner = learner,
+ resampling = rsmp ("holdout"),
+ measure = msr("classif.ce"),
+ term_evals = 10)
INFO [12:30:35.483] [bbotk] Starting to optimize 3 parameter(s) with '<OptimizerBatchRandomSearch>' and '<TerminatorEvals> [n_evals=10, k=0]'
INFO [12:30:36.023] [bbotk] Evaluating 1 configuration(s)
INFO [12:30:36.160] [mlr3] Running benchmark with 1 resampling iterations
INFO [12:30:36.579] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/1)
INFO [12:30:36.810] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: tune ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Current CRAN status: NOTE: 3, OK: 10
Version: 0.3.1
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘mlr3proba’
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Current CRAN status: ERROR: 4, NOTE: 3, OK: 6
Version: 0.10.1
Check: examples
Result: ERROR
Running examples in ‘mlr3viz-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: autoplot.BenchmarkResult
> ### Title: Plots for Benchmark Results
> ### Aliases: autoplot.BenchmarkResult
>
> ### ** Examples
>
> if (requireNamespace("mlr3")) {
+ library(mlr3)
+ library(mlr3viz)
+
+ tasks = tsks(c("pima", "sonar"))
+ learner = lrns(c("classif.featureless", "classif.rpart"),
+ predict_type = "prob")
+ resampling = rsmps("cv")
+ object = benchmark(benchmark_grid(tasks, learner, resampling))
+
+ head(fortify(object))
+ autoplot(object)
+ autoplot(object$clone(deep = TRUE)$filter(task_ids = "pima"), type = "roc")
+ }
Loading required namespace: mlr3
INFO [04:35:29.782] [mlr3] Running benchmark with 40 resampling iterations
INFO [04:35:30.057] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 1/10)
INFO [04:35:30.141] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 2/10)
INFO [04:35:30.179] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 3/10)
INFO [04:35:30.238] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 4/10)
INFO [04:35:30.311] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 5/10)
INFO [04:35:30.410] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 6/10)
INFO [04:35:30.446] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 7/10)
INFO [04:35:30.630] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 8/10)
INFO [04:35:30.664] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 9/10)
INFO [04:35:30.699] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 10/10)
INFO [04:35:30.850] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/10)
INFO [04:35:30.918] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 2/10)
INFO [04:35:30.962] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 3/10)
INFO [04:35:31.178] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 4/10)
INFO [04:35:31.243] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 5/10)
INFO [04:35:31.350] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 6/10)
INFO [04:35:31.465] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 7/10)
INFO [04:35:31.564] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 8/10)
INFO [04:35:31.962] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 9/10)
INFO [04:35:32.017] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 10/10)
INFO [04:35:32.064] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/10)
INFO [04:35:32.109] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/10)
INFO [04:35:32.161] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/10)
INFO [04:35:32.240] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 4/10)
INFO [04:35:32.274] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 5/10)
INFO [04:35:32.317] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 6/10)
INFO [04:35:32.351] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 7/10)
INFO [04:35:32.421] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 8/10)
INFO [04:35:32.472] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 9/10)
INFO [04:35:32.551] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 10/10)
INFO [04:35:32.585] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/10)
INFO [04:35:32.649] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/10)
INFO [04:35:32.752] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/10)
INFO [04:35:32.821] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 4/10)
INFO [04:35:32.890] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 5/10)
INFO [04:35:32.951] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 6/10)
INFO [04:35:33.016] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 7/10)
INFO [04:35:33.077] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 8/10)
INFO [04:35:33.139] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 9/10)
INFO [04:35:33.214] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 10/10)
INFO [04:35:33.296] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: benchmark ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.10.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [79s/43s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3viz")
+ test_check("mlr3viz")
+ }
Starting 2 test processes.
> test_EnsembleFSResult.R: Loading required namespace: vdiffr
Saving _problems/test_BenchmarkResult-7.R
> test_Filter.R: Loading required namespace: vdiffr
Saving _problems/test_LearnerClassif-6.R
> test_OptimInstanceSingleCrit.R: Loading required package: paradox
> test_OptimInstanceSingleCrit.R: Loading required namespace: mlr3learners
> test_PredictionRegr.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
Saving _problems/test_ResampleResult-7.R
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TuningInstanceSingleCrit.R: Loading required package: mlr3
Saving _problems/test_TuningInstanceSingleCrit-24.R
Saving _problems/test_plot_learner_prediction-8.R
Saving _problems/test_plot_learner_prediction-41.R
Saving _problems/test_plot_learner_prediction-51.R
[ FAIL 7 | WARN 50 | SKIP 20 | PASS 63 ]
══ Skipped tests (20) ══════════════════════════════════════════════════════════
• On CRAN (20): 'test_Filter.R:3:1', 'test_LearnerClassif.R:11:1',
'test_EnsembleFSResult.R:4:1', 'test_LearnerClassifCVGlmnet.R:8:1',
'test_LearnerClassifRpart.R:6:1', 'test_LearnerClustHierarchical.R:7:3',
'test_LearnerClasssifGlmnet.R:8:1', 'test_LearnerRegrCVGlmnet.R:8:1',
'test_LearnerRegrGlmnet.R:7:1', 'test_LearnerRegr.R:1:1',
'test_LearnerRegr.R:11:1', 'test_LearnerRegr.R:21:1',
'test_LearnerRegrRpart.R:6:1', 'test_PredictionClassif.R:8:1',
'test_PredictionClust.R:8:3', 'test_PredictionRegr.R:3:1',
'test_OptimInstanceSingleCrit.R:35:1', 'test_TaskClust.R:4:1',
'test_TaskRegr.R:3:1', 'test_TaskClassif.R:3:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_BenchmarkResult.R:7:1'): (code run outside of `test_that()`) ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(mlr3::benchmark_grid(tasks, learner, resampling)) at test_BenchmarkResult.R:7:1
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_LearnerClassif.R:6:3'): autoplot.PredictionClassif decision boundary probability ──
Error in ``[.data.table`(grid, , `:=`(".prob.response", .SD[, paste0("prob.", get("response")), with = FALSE]), by = "response")`: attempt access index 7/7 in VECTOR_ELT
Backtrace:
▆
1. ├─ggplot2::autoplot(learner, type = "prediction", task = task) at test_LearnerClassif.R:6:3
2. ├─mlr3viz:::autoplot.LearnerClassifRpart(...)
3. ├─base::NextMethod()
4. └─mlr3viz:::autoplot.LearnerClassif(...)
5. └─mlr3viz:::predict_grid(...)
6. ├─...[]
7. └─data.table:::`[.data.table`(...)
── Error ('test_ResampleResult.R:7:1'): (code run outside of `test_that()`) ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_ResampleResult.R:7:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceSingleCrit.R:24:1'): (code run outside of `test_that()`) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance)
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:8:3'): plot_learner_prediction.LearnerClassif ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:8:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:41:3'): plot_learner_prediction.LearnerRegr 2d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:41:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:51:3'): plot_learner_prediction.LearnerRegr 1d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:51:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 50 | SKIP 20 | PASS 63 ]
Deleting unused snapshots: 'BenchmarkResult/bmr-boxplot.svg',
'BenchmarkResult/bmr-holdout-ci.svg', 'BenchmarkResult/bmr-holdout-roc.svg',
'BenchmarkResult/bmr-prc.svg', 'BenchmarkResult/bmr-roc.svg',
'LearnerClassif/learner-classif-prob.svg',
'LearnerClustHierarchical/learner-clust-agnes.svg',
'LearnerClustHierarchical/learner-clust-hclust.svg',
'PredictionClust/predictionclust-pca.svg',
'PredictionClust/predictionclust-scatter.svg',
'PredictionClust/predictionclust-sil.svg',
'ResampleResult/resampleresult-boxplot.svg',
'ResampleResult/resampleresult-histogram.svg',
'ResampleResult/resampleresult-prc.svg',
'ResampleResult/resampleresult-roc.svg',
'TuningInstanceSingleCrit/tisc-incumbent.svg',
'TuningInstanceSingleCrit/tisc-marginal-01.svg',
'TuningInstanceSingleCrit/tisc-marginal-02.svg', …,
'plot_learner_prediction/learner-prediction-prob.svg', and
'plot_learner_prediction/learner-prediction-response.svg'
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.10.1
Check: examples
Result: ERROR
Running examples in ‘mlr3viz-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: autoplot.BenchmarkResult
> ### Title: Plots for Benchmark Results
> ### Aliases: autoplot.BenchmarkResult
>
> ### ** Examples
>
> if (requireNamespace("mlr3")) {
+ library(mlr3)
+ library(mlr3viz)
+
+ tasks = tsks(c("pima", "sonar"))
+ learner = lrns(c("classif.featureless", "classif.rpart"),
+ predict_type = "prob")
+ resampling = rsmps("cv")
+ object = benchmark(benchmark_grid(tasks, learner, resampling))
+
+ head(fortify(object))
+ autoplot(object)
+ autoplot(object$clone(deep = TRUE)$filter(task_ids = "pima"), type = "roc")
+ }
Loading required namespace: mlr3
INFO [17:18:08.352] [mlr3] Running benchmark with 40 resampling iterations
INFO [17:18:08.477] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 1/10)
INFO [17:18:08.526] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 2/10)
INFO [17:18:08.565] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 3/10)
INFO [17:18:08.606] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 4/10)
INFO [17:18:08.634] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 5/10)
INFO [17:18:08.673] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 6/10)
INFO [17:18:08.748] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 7/10)
INFO [17:18:08.922] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 8/10)
INFO [17:18:08.998] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 9/10)
INFO [17:18:09.076] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 10/10)
INFO [17:18:09.148] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/10)
INFO [17:18:09.194] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 2/10)
INFO [17:18:09.223] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 3/10)
INFO [17:18:09.258] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 4/10)
INFO [17:18:09.303] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 5/10)
INFO [17:18:09.335] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 6/10)
INFO [17:18:09.373] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 7/10)
INFO [17:18:09.403] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 8/10)
INFO [17:18:09.740] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 9/10)
INFO [17:18:09.767] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 10/10)
INFO [17:18:09.815] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/10)
INFO [17:18:09.903] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/10)
INFO [17:18:09.982] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/10)
INFO [17:18:10.064] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 4/10)
INFO [17:18:10.141] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 5/10)
INFO [17:18:10.189] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 6/10)
INFO [17:18:10.240] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 7/10)
INFO [17:18:10.282] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 8/10)
INFO [17:18:10.326] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 9/10)
INFO [17:18:10.354] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 10/10)
INFO [17:18:10.393] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/10)
INFO [17:18:10.439] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/10)
INFO [17:18:10.481] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/10)
INFO [17:18:10.519] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 4/10)
INFO [17:18:10.555] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 5/10)
INFO [17:18:10.614] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 6/10)
INFO [17:18:10.685] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 7/10)
INFO [17:18:10.755] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 8/10)
INFO [17:18:10.835] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 9/10)
INFO [17:18:10.925] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 10/10)
INFO [17:18:11.022] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: benchmark ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.10.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [53s/28s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3viz")
+ test_check("mlr3viz")
+ }
Starting 2 test processes.
> test_EnsembleFSResult.R: Loading required namespace: vdiffr
Saving _problems/test_BenchmarkResult-7.R
> test_Filter.R: Loading required namespace: vdiffr
Saving _problems/test_LearnerClassif-6.R
> test_OptimInstanceSingleCrit.R: Loading required package: paradox
> test_PredictionRegr.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
Saving _problems/test_ResampleResult-7.R
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TuningInstanceSingleCrit.R: Loading required package: mlr3
Saving _problems/test_TuningInstanceSingleCrit-24.R
Saving _problems/test_plot_learner_prediction-8.R
Saving _problems/test_plot_learner_prediction-41.R
Saving _problems/test_plot_learner_prediction-51.R
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
══ Skipped tests (20) ══════════════════════════════════════════════════════════
• On CRAN (20): 'test_Filter.R:3:1', 'test_LearnerClassif.R:11:1',
'test_EnsembleFSResult.R:4:1', 'test_LearnerClassifCVGlmnet.R:8:1',
'test_LearnerClassifRpart.R:6:1', 'test_LearnerClasssifGlmnet.R:8:1',
'test_LearnerClustHierarchical.R:7:3', 'test_LearnerRegrCVGlmnet.R:8:1',
'test_LearnerRegr.R:1:1', 'test_LearnerRegr.R:11:1',
'test_LearnerRegr.R:21:1', 'test_LearnerRegrGlmnet.R:7:1',
'test_LearnerRegrRpart.R:6:1', 'test_PredictionClassif.R:8:1',
'test_PredictionClust.R:8:3', 'test_PredictionRegr.R:3:1',
'test_OptimInstanceSingleCrit.R:35:1', 'test_TaskClust.R:4:1',
'test_TaskRegr.R:3:1', 'test_TaskClassif.R:3:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_BenchmarkResult.R:7:1'): (code run outside of `test_that()`) ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(mlr3::benchmark_grid(tasks, learner, resampling)) at test_BenchmarkResult.R:7:1
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_LearnerClassif.R:6:3'): autoplot.PredictionClassif decision boundary probability ──
Error in ``[.data.table`(grid, , `:=`(".prob.response", .SD[, paste0("prob.", get("response")), with = FALSE]), by = "response")`: attempt access index 7/7 in VECTOR_ELT
Backtrace:
▆
1. ├─ggplot2::autoplot(learner, type = "prediction", task = task) at test_LearnerClassif.R:6:3
2. ├─mlr3viz:::autoplot.LearnerClassifRpart(...)
3. ├─base::NextMethod()
4. └─mlr3viz:::autoplot.LearnerClassif(...)
5. └─mlr3viz:::predict_grid(...)
6. ├─...[]
7. └─data.table:::`[.data.table`(...)
── Error ('test_ResampleResult.R:7:1'): (code run outside of `test_that()`) ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_ResampleResult.R:7:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceSingleCrit.R:24:1'): (code run outside of `test_that()`) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance)
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:8:3'): plot_learner_prediction.LearnerClassif ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:8:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:41:3'): plot_learner_prediction.LearnerRegr 2d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:41:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:51:3'): plot_learner_prediction.LearnerRegr 1d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:51:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
Deleting unused snapshots: 'BenchmarkResult/bmr-boxplot.svg',
'BenchmarkResult/bmr-holdout-ci.svg', 'BenchmarkResult/bmr-holdout-roc.svg',
'BenchmarkResult/bmr-prc.svg', 'BenchmarkResult/bmr-roc.svg',
'LearnerClassif/learner-classif-prob.svg',
'LearnerClustHierarchical/learner-clust-agnes.svg',
'LearnerClustHierarchical/learner-clust-hclust.svg',
'PredictionClust/predictionclust-pca.svg',
'PredictionClust/predictionclust-scatter.svg',
'PredictionClust/predictionclust-sil.svg',
'ResampleResult/resampleresult-boxplot.svg',
'ResampleResult/resampleresult-histogram.svg',
'ResampleResult/resampleresult-prc.svg',
'ResampleResult/resampleresult-roc.svg',
'TuningInstanceSingleCrit/tisc-incumbent.svg',
'TuningInstanceSingleCrit/tisc-marginal-01.svg',
'TuningInstanceSingleCrit/tisc-marginal-02.svg', …,
'plot_learner_prediction/learner-prediction-prob.svg', and
'plot_learner_prediction/learner-prediction-response.svg'
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.10.1
Check: examples
Result: ERROR
Running examples in ‘mlr3viz-Ex.R’ failed
The error most likely occurred in:
> ### Name: autoplot.BenchmarkResult
> ### Title: Plots for Benchmark Results
> ### Aliases: autoplot.BenchmarkResult
>
> ### ** Examples
>
> if (requireNamespace("mlr3")) {
+ library(mlr3)
+ library(mlr3viz)
+
+ tasks = tsks(c("pima", "sonar"))
+ learner = lrns(c("classif.featureless", "classif.rpart"),
+ predict_type = "prob")
+ resampling = rsmps("cv")
+ object = benchmark(benchmark_grid(tasks, learner, resampling))
+
+ head(fortify(object))
+ autoplot(object)
+ autoplot(object$clone(deep = TRUE)$filter(task_ids = "pima"), type = "roc")
+ }
Loading required namespace: mlr3
INFO [17:51:57.263] [mlr3] Running benchmark with 40 resampling iterations
INFO [17:51:57.821] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 1/10)
INFO [17:51:57.953] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 2/10)
INFO [17:51:58.076] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 3/10)
INFO [17:51:58.179] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 4/10)
INFO [17:51:58.309] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 5/10)
INFO [17:51:58.448] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 6/10)
INFO [17:51:58.507] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 7/10)
INFO [17:51:58.804] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 8/10)
INFO [17:51:58.930] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 9/10)
INFO [17:51:59.030] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 10/10)
INFO [17:51:59.192] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/10)
INFO [17:51:59.447] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 2/10)
INFO [17:51:59.647] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 3/10)
INFO [17:51:59.849] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 4/10)
INFO [17:52:00.014] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 5/10)
INFO [17:52:00.145] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 6/10)
INFO [17:52:00.297] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 7/10)
INFO [17:52:00.466] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 8/10)
INFO [17:52:00.820] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 9/10)
INFO [17:52:00.884] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 10/10)
INFO [17:52:00.993] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/10)
INFO [17:52:01.140] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/10)
INFO [17:52:01.221] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/10)
INFO [17:52:01.333] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 4/10)
INFO [17:52:01.479] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 5/10)
INFO [17:52:01.608] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 6/10)
INFO [17:52:01.706] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 7/10)
INFO [17:52:01.762] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 8/10)
INFO [17:52:01.841] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 9/10)
INFO [17:52:01.893] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 10/10)
INFO [17:52:02.004] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/10)
INFO [17:52:02.238] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/10)
INFO [17:52:02.496] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/10)
INFO [17:52:02.664] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 4/10)
INFO [17:52:02.761] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 5/10)
INFO [17:52:02.961] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 6/10)
INFO [17:52:03.170] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 7/10)
INFO [17:52:03.374] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 8/10)
INFO [17:52:03.579] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 9/10)
INFO [17:52:03.825] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 10/10)
INFO [17:52:03.987] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: benchmark ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.10.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [135s/127s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3viz")
+ test_check("mlr3viz")
+ }
Starting 2 test processes.
> test_EnsembleFSResult.R: Loading required namespace: vdiffr
Saving _problems/test_BenchmarkResult-7.R
> test_Filter.R: Loading required namespace: vdiffr
Saving _problems/test_LearnerClassif-6.R
> test_OptimInstanceSingleCrit.R: Loading required package: paradox
> test_PredictionRegr.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
Saving _problems/test_ResampleResult-7.R
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TuningInstanceSingleCrit.R: Loading required package: paradox
Saving _problems/test_plot_learner_prediction-8.R
Saving _problems/test_plot_learner_prediction-41.R
Saving _problems/test_plot_learner_prediction-51.R
Saving _problems/test_TuningInstanceSingleCrit-24.R
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
══ Skipped tests (20) ══════════════════════════════════════════════════════════
• On CRAN (20): 'test_Filter.R:3:1', 'test_LearnerClassif.R:11:1',
'test_LearnerClassifCVGlmnet.R:8:1', 'test_EnsembleFSResult.R:4:1',
'test_LearnerClassifRpart.R:6:1', 'test_LearnerClasssifGlmnet.R:8:1',
'test_LearnerClustHierarchical.R:7:3', 'test_LearnerRegrCVGlmnet.R:8:1',
'test_LearnerRegrGlmnet.R:7:1', 'test_LearnerRegr.R:1:1',
'test_LearnerRegr.R:11:1', 'test_LearnerRegr.R:21:1',
'test_LearnerRegrRpart.R:6:1', 'test_PredictionClassif.R:8:1',
'test_PredictionClust.R:8:3', 'test_PredictionRegr.R:3:1',
'test_OptimInstanceSingleCrit.R:35:1', 'test_TaskClust.R:4:1',
'test_TaskClassif.R:3:1', 'test_TaskRegr.R:3:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_BenchmarkResult.R:7:1'): (code run outside of `test_that()`) ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(mlr3::benchmark_grid(tasks, learner, resampling)) at test_BenchmarkResult.R:7:1
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_LearnerClassif.R:6:3'): autoplot.PredictionClassif decision boundary probability ──
Error in ``[.data.table`(grid, , `:=`(".prob.response", .SD[, paste0("prob.", get("response")), with = FALSE]), by = "response")`: attempt access index 7/7 in VECTOR_ELT
Backtrace:
▆
1. ├─ggplot2::autoplot(learner, type = "prediction", task = task) at test_LearnerClassif.R:6:3
2. ├─mlr3viz:::autoplot.LearnerClassifRpart(...)
3. ├─base::NextMethod()
4. └─mlr3viz:::autoplot.LearnerClassif(...)
5. └─mlr3viz:::predict_grid(...)
6. ├─...[]
7. └─data.table:::`[.data.table`(...)
── Error ('test_ResampleResult.R:7:1'): (code run outside of `test_that()`) ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_ResampleResult.R:7:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:8:3'): plot_learner_prediction.LearnerClassif ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:8:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:41:3'): plot_learner_prediction.LearnerRegr 2d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:41:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:51:3'): plot_learner_prediction.LearnerRegr 1d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:51:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceSingleCrit.R:24:1'): (code run outside of `test_that()`) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance)
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
Deleting unused snapshots: 'BenchmarkResult/bmr-boxplot.svg',
'BenchmarkResult/bmr-holdout-ci.svg', 'BenchmarkResult/bmr-holdout-roc.svg',
'BenchmarkResult/bmr-prc.svg', 'BenchmarkResult/bmr-roc.svg',
'LearnerClassif/learner-classif-prob.svg',
'LearnerClustHierarchical/learner-clust-agnes.svg',
'LearnerClustHierarchical/learner-clust-hclust.svg',
'PredictionClust/predictionclust-pca.svg',
'PredictionClust/predictionclust-scatter.svg',
'PredictionClust/predictionclust-sil.svg',
'ResampleResult/resampleresult-boxplot.svg',
'ResampleResult/resampleresult-histogram.svg',
'ResampleResult/resampleresult-prc.svg',
'ResampleResult/resampleresult-roc.svg',
'TuningInstanceSingleCrit/tisc-incumbent.svg',
'TuningInstanceSingleCrit/tisc-marginal-01.svg',
'TuningInstanceSingleCrit/tisc-marginal-02.svg', …,
'plot_learner_prediction/learner-prediction-prob.svg', and
'plot_learner_prediction/learner-prediction-response.svg'
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.10.1
Check: examples
Result: ERROR
Running examples in ‘mlr3viz-Ex.R’ failed
The error most likely occurred in:
> ### Name: autoplot.BenchmarkResult
> ### Title: Plots for Benchmark Results
> ### Aliases: autoplot.BenchmarkResult
>
> ### ** Examples
>
> if (requireNamespace("mlr3")) {
+ library(mlr3)
+ library(mlr3viz)
+
+ tasks = tsks(c("pima", "sonar"))
+ learner = lrns(c("classif.featureless", "classif.rpart"),
+ predict_type = "prob")
+ resampling = rsmps("cv")
+ object = benchmark(benchmark_grid(tasks, learner, resampling))
+
+ head(fortify(object))
+ autoplot(object)
+ autoplot(object$clone(deep = TRUE)$filter(task_ids = "pima"), type = "roc")
+ }
Loading required namespace: mlr3
INFO [12:31:59.527] [mlr3] Running benchmark with 40 resampling iterations
INFO [12:31:59.933] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 1/10)
INFO [12:32:00.106] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 2/10)
INFO [12:32:00.197] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 3/10)
INFO [12:32:00.328] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 4/10)
INFO [12:32:00.477] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 5/10)
INFO [12:32:00.571] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 6/10)
INFO [12:32:00.664] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 7/10)
INFO [12:32:00.860] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 8/10)
INFO [12:32:00.907] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 9/10)
INFO [12:32:00.952] [mlr3] Applying learner 'classif.featureless' on task 'pima' (iter 10/10)
INFO [12:32:01.041] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 1/10)
INFO [12:32:01.160] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 2/10)
INFO [12:32:01.285] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 3/10)
INFO [12:32:01.365] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 4/10)
INFO [12:32:01.513] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 5/10)
INFO [12:32:01.637] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 6/10)
INFO [12:32:01.802] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 7/10)
INFO [12:32:01.922] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 8/10)
INFO [12:32:02.520] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 9/10)
INFO [12:32:02.613] [mlr3] Applying learner 'classif.rpart' on task 'pima' (iter 10/10)
INFO [12:32:02.682] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/10)
INFO [12:32:02.770] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/10)
INFO [12:32:02.847] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/10)
INFO [12:32:02.982] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 4/10)
INFO [12:32:03.091] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 5/10)
INFO [12:32:03.177] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 6/10)
INFO [12:32:03.324] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 7/10)
INFO [12:32:03.427] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 8/10)
INFO [12:32:03.556] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 9/10)
INFO [12:32:03.638] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 10/10)
INFO [12:32:03.783] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/10)
INFO [12:32:04.022] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/10)
INFO [12:32:04.202] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/10)
INFO [12:32:04.418] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 4/10)
INFO [12:32:04.603] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 5/10)
INFO [12:32:04.808] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 6/10)
INFO [12:32:04.951] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 7/10)
INFO [12:32:05.076] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 8/10)
INFO [12:32:05.254] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 9/10)
INFO [12:32:05.447] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 10/10)
INFO [12:32:05.667] [mlr3] Finished benchmark
Error in `[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash") :
attempt access index 9/9 in VECTOR_ELT
Calls: benchmark ... initialize -> .__ResultData__initialize -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.10.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [127s/112s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> if (requireNamespace("testthat", quietly = TRUE)) {
+ library("testthat")
+ library("mlr3viz")
+ test_check("mlr3viz")
+ }
Starting 2 test processes.
> test_EnsembleFSResult.R: Loading required namespace: vdiffr
Saving _problems/test_BenchmarkResult-7.R
> test_Filter.R: Loading required namespace: vdiffr
Saving _problems/test_LearnerClassif-6.R
> test_OptimInstanceSingleCrit.R: Loading required package: paradox
> test_PredictionRegr.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
Saving _problems/test_ResampleResult-7.R
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TaskClassif.R: `stat_bin()` using `bins = 30`. Pick better value `binwidth`.
> test_TuningInstanceSingleCrit.R: Loading required package: mlr3
Saving _problems/test_plot_learner_prediction-8.R
Saving _problems/test_plot_learner_prediction-41.R
Saving _problems/test_plot_learner_prediction-51.R
Saving _problems/test_TuningInstanceSingleCrit-24.R
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
══ Skipped tests (20) ══════════════════════════════════════════════════════════
• On CRAN (20): 'test_Filter.R:3:1', 'test_LearnerClassif.R:11:1',
'test_EnsembleFSResult.R:4:1', 'test_LearnerClassifRpart.R:6:1',
'test_LearnerClassifCVGlmnet.R:8:1', 'test_LearnerClustHierarchical.R:7:3',
'test_LearnerClasssifGlmnet.R:8:1', 'test_LearnerRegrCVGlmnet.R:8:1',
'test_LearnerRegr.R:1:1', 'test_LearnerRegr.R:11:1',
'test_LearnerRegr.R:21:1', 'test_LearnerRegrGlmnet.R:7:1',
'test_LearnerRegrRpart.R:6:1', 'test_PredictionClassif.R:8:1',
'test_PredictionClust.R:8:3', 'test_PredictionRegr.R:3:1',
'test_OptimInstanceSingleCrit.R:35:1', 'test_TaskClassif.R:3:1',
'test_TaskClust.R:4:1', 'test_TaskRegr.R:3:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_BenchmarkResult.R:7:1'): (code run outside of `test_that()`) ───
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::benchmark(mlr3::benchmark_grid(tasks, learner, resampling)) at test_BenchmarkResult.R:7:1
2. └─ResultData$new(grid, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_LearnerClassif.R:6:3'): autoplot.PredictionClassif decision boundary probability ──
Error in ``[.data.table`(grid, , `:=`(".prob.response", .SD[, paste0("prob.", get("response")), with = FALSE]), by = "response")`: attempt access index 7/7 in VECTOR_ELT
Backtrace:
▆
1. ├─ggplot2::autoplot(learner, type = "prediction", task = task) at test_LearnerClassif.R:6:3
2. ├─mlr3viz:::autoplot.LearnerClassifRpart(...)
3. ├─base::NextMethod()
4. └─mlr3viz:::autoplot.LearnerClassif(...)
5. └─mlr3viz:::predict_grid(...)
6. ├─...[]
7. └─data.table:::`[.data.table`(...)
── Error ('test_ResampleResult.R:7:1'): (code run outside of `test_that()`) ────
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3::resample(task, learner, resampling) at test_ResampleResult.R:7:1
2. └─ResultData$new(data, data_extra, store_backends = store_backends)
3. └─mlr3 (local) initialize(...)
4. └─mlr3:::.__ResultData__initialize(...)
5. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
6. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:8:3'): plot_learner_prediction.LearnerClassif ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:8:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:41:3'): plot_learner_prediction.LearnerRegr 2d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:41:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_plot_learner_prediction.R:51:3'): plot_learner_prediction.LearnerRegr 1d ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─mlr3viz::plot_learner_prediction(learner, task, expand_range = 0.1) at test_plot_learner_prediction.R:51:3
2. └─mlr3::resample(...)
3. └─ResultData$new(data, data_extra, store_backends = store_backends)
4. └─mlr3 (local) initialize(...)
5. └─mlr3:::.__ResultData__initialize(...)
6. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
7. └─data.table:::`[.data.table`(...)
── Error ('test_TuningInstanceSingleCrit.R:24:1'): (code run outside of `test_that()`) ──
Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
Backtrace:
▆
1. └─tuner$optimize(instance)
2. └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
3. └─private$.optimizer$optimize(inst)
4. └─bbotk:::.__OptimizerBatch__optimize(...)
5. └─bbotk::optimize_batch_default(inst, self)
6. ├─base::tryCatch(...)
7. │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
8. │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
9. │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
10. └─get_private(optimizer)$.optimize(instance)
11. └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
12. └─inst$eval_batch(design$data)
13. └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
14. └─self$objective$eval_many(xss_trafoed)
15. └─bbotk:::.__Objective__eval_many(...)
16. ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
17. │ └─base::eval.parent(expr, n = 1L)
18. │ └─base::eval(expr, p)
19. │ └─base::eval(expr, p)
20. └─private$.eval_many(xss = xss, resampling = `<list>`)
21. └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
22. └─mlr3::benchmark(...)
23. └─ResultData$new(grid, data_extra, store_backends = store_backends)
24. └─mlr3 (local) initialize(...)
25. └─mlr3:::.__ResultData__initialize(...)
26. ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
27. └─data.table:::`[.data.table`(...)
[ FAIL 7 | WARN 51 | SKIP 20 | PASS 63 ]
Deleting unused snapshots: 'BenchmarkResult/bmr-boxplot.svg',
'BenchmarkResult/bmr-holdout-ci.svg', 'BenchmarkResult/bmr-holdout-roc.svg',
'BenchmarkResult/bmr-prc.svg', 'BenchmarkResult/bmr-roc.svg',
'LearnerClassif/learner-classif-prob.svg',
'LearnerClustHierarchical/learner-clust-agnes.svg',
'LearnerClustHierarchical/learner-clust-hclust.svg',
'PredictionClust/predictionclust-pca.svg',
'PredictionClust/predictionclust-scatter.svg',
'PredictionClust/predictionclust-sil.svg',
'ResampleResult/resampleresult-boxplot.svg',
'ResampleResult/resampleresult-histogram.svg',
'ResampleResult/resampleresult-prc.svg',
'ResampleResult/resampleresult-roc.svg',
'TuningInstanceSingleCrit/tisc-incumbent.svg',
'TuningInstanceSingleCrit/tisc-marginal-01.svg',
'TuningInstanceSingleCrit/tisc-marginal-02.svg', …,
'plot_learner_prediction/learner-prediction-prob.svg', and
'plot_learner_prediction/learner-prediction-response.svg'
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.10.1
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘mlr3proba’
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Current CRAN status: OK: 13