Running ‘testthat_regression_tests.R’ [69s/98s]
Running the tests in ‘tests/testthat_regression_tests.R’ failed.
Complete output:
  > library("testthat")
  > library("patrick")
  > library("DoubleML")
  > 
  > testthat::test_check("DoubleML")
  Saving _problems/test-double_ml_cluster_not_implemented-13.R
  Saving _problems/test-double_ml_iivm-39.R
  Saving _problems/test-double_ml_iivm_binary_outcome-40.R
  Saving _problems/test-double_ml_iivm_parameter_passing-52.R
  Saving _problems/test-double_ml_iivm_parameter_passing-140.R
  Saving _problems/test-double_ml_iivm_parameter_passing-227.R
  Saving _problems/test-double_ml_iivm_parameter_passing-304.R
  Saving _problems/test-double_ml_iivm_trim-38.R
  Saving _problems/test-double_ml_iivm_tuning-76.R
  Saving _problems/test-double_ml_iivm_user_score-55.R
  Saving _problems/test-double_ml_irm-36.R
  Saving _problems/test-double_ml_irm_binary_outcome-40.R
  Saving _problems/test-double_ml_irm_loaded_mlr3learner-73.R
  Saving _problems/test-double_ml_irm_parameter_passing-50.R
  Saving _problems/test-double_ml_irm_parameter_passing-127.R
  Saving _problems/test-double_ml_irm_parameter_passing-127.R
  Saving _problems/test-double_ml_irm_parameter_passing-198.R
  Saving _problems/test-double_ml_irm_parameter_passing-260.R
  Saving _problems/test-double_ml_irm_trim-37.R
  Saving _problems/test-double_ml_irm_tuning-76.R
  Saving _problems/test-double_ml_irm_user_score-54.R
  Saving _problems/test-double_ml_pliv-36.R
  Saving _problems/test-double_ml_pliv_exception_handling-47.R
  Saving _problems/test-double_ml_pliv_one_way_cluster-56.R
  Saving _problems/test-double_ml_pliv_parameter_passing-54.R
  Saving _problems/test-double_ml_pliv_parameter_passing-150.R
  Saving _problems/test-double_ml_pliv_parameter_passing-240.R
  Saving _problems/test-double_ml_pliv_parameter_passing-321.R
  Saving _problems/test-double_ml_pliv_partial_functional_initializer-40.R
  Saving _problems/test-double_ml_pliv_partial_functional_initializer-82.R
  Saving _problems/test-double_ml_pliv_partial_functional_initializer-121.R
  Saving _problems/test-double_ml_pliv_partial_functional_initializer_IVtype-41.R
  Saving _problems/test-double_ml_pliv_tuning-98.R
  Saving _problems/test-double_ml_pliv_tuning-188.R
  Saving _problems/test-double_ml_pliv_two_way_cluster-50.R
  Saving _problems/test-double_ml_pliv_user_score-66.R
  Saving _problems/test-double_ml_plr-36.R
  Saving _problems/test-double_ml_plr_classifier-50.R
  Saving _problems/test-double_ml_plr_classifier-130.R
  Saving _problems/test-double_ml_plr_classifier-143.R
  Saving _problems/test-double_ml_plr_exception_handling-116.R
  Saving _problems/test-double_ml_plr_exception_handling-177.R
  Saving _problems/test-double_ml_plr_export_preds-49.R
  Saving _problems/test-double_ml_plr_loaded_mlr3learner-66.R
  Saving _problems/test-double_ml_plr_multitreat-43.R
  Saving _problems/test-double_ml_plr_nocrossfit-58.R
  Saving _problems/test-double_ml_plr_nocrossfit-58.R
  Saving _problems/test-double_ml_plr_nonorth-74.R
  Saving _problems/test-double_ml_plr_p_adjust-69.R
  Saving _problems/test-double_ml_plr_parameter_passing-57.R
  Saving _problems/test-double_ml_plr_parameter_passing-160.R
  Saving _problems/test-double_ml_plr_parameter_passing-264.R
  Saving _problems/test-double_ml_plr_parameter_passing-353.R
  Saving _problems/test-double_ml_plr_rep_cross_fit-44.R
  Saving _problems/test-double_ml_plr_set_samples-53.R
  Saving _problems/test-double_ml_plr_tuning-95.R
  Saving _problems/test-double_ml_plr_tuning-95.R
  Saving _problems/test-double_ml_plr_user_score-48.R
  Saving _problems/test-double_ml_print-12.R
  Saving _problems/test-double_ml_ssm_mar-36.R
  Saving _problems/test-double_ml_ssm_nonignorable-36.R
  Saving _problems/test-double_ml_ssm_tuning-75.R
  Saving _problems/test-double_ml_ssm_tuning-75.R
  [ FAIL 63 | WARN 0 | SKIP 7 | PASS 296 ]
  
  ══ Skipped tests (7) ═══════════════════════════════════════════════════════════
  • On CRAN (7): 'test-double_ml_datasets.R:15:1',
    'test-double_ml_pliv_multi_z_parameter_passing.R:7:1',
    'test-double_ml_pliv_partial_x.R:5:1',
    'test-double_ml_pliv_partial_xz.R:7:1',
    'test-double_ml_pliv_partial_xz_parameter_passing.R:5:1',
    'test-double_ml_pliv_partial_z.R:5:1',
    'test-double_ml_pliv_partial_z_parameter_passing.R:5:1'
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-double_ml_cluster_not_implemented.R:13:3'): Not yet implemented cluster features ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. └─dml_pliv_cluster$fit() at test-double_ml_cluster_not_implemented.R:13:3
    2.   └─private$nuisance_est(private$get__smpls())
    3.     └─private$nuisance_est_partialX(smpls, ...)
    4.       └─DoubleML:::dml_cv_predict(...)
    5.         └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.           └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.             └─mlr3 (local) initialize(...)
    8.               └─mlr3:::.__ResultData__initialize(...)
    9.                 ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.                 └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_iivm.R:32:5'): Unit tests for IIVM: rpart_dml2_LATE_1e-05 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_irmiv(...) at test-double_ml_iivm.R:32:5
   3.   └─DoubleML:::fit_nuisance_iivm(...) at ./helper-11-dml_iivm.R:23:5
   4.     └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-11-dml_iivm.R:145:3
   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-double_ml_iivm_binary_outcome.R:32:5'): Unit tests for IIVM: log_reg_dml2_LATE_0.025 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_irmiv(...) at test-double_ml_iivm_binary_outcome.R:32:5
   3.   └─DoubleML:::fit_nuisance_iivm(...) at ./helper-11-dml_iivm.R:23:5
   4.     └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-11-dml_iivm.R:145:3
   5.       └─ResultData$new(data, data_extra, store_backends = store_backends)
   6.         └─mlr3 (local) initialize(...)
   7.           └─mlr3:::.__ResultData__initialize(...)
   8.             ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   9.             └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_iivm_parameter_passing.R:41:5'): Unit tests for parameter passing of IIVM (oop vs fun): rpart_dml2_LATE_1e-05 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_irmiv(...) at test-double_ml_iivm_parameter_passing.R:41:5
   3.   └─DoubleML:::fit_nuisance_iivm(...) at ./helper-11-dml_iivm.R:23:5
   4.     └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-11-dml_iivm.R:145:3
   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-double_ml_iivm_parameter_passing.R:129:5'): Unit tests for parameter passing of IIVM (no cross-fitting) rpart_dml1_LATE_1e-05 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_irmiv(...) at test-double_ml_iivm_parameter_passing.R:129:5
   3.   └─DoubleML:::fit_nuisance_iivm(...) at ./helper-11-dml_iivm.R:23:5
   4.     └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-11-dml_iivm.R:145:3
   5.       └─ResultData$new(data, data_extra, store_backends = store_backends)
   6.         └─mlr3 (local) initialize(...)
   7.           └─mlr3:::.__ResultData__initialize(...)
   8.             ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   9.             └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_iivm_parameter_passing.R:227:5'): Unit tests for parameter passing of IIVM (fold-wise vs global) rpart_dml2_LATE_1e-05 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─dml_iivm_obj$fit() at test-double_ml_iivm_parameter_passing.R:227:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.         └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.           └─mlr3 (local) initialize(...)
    8.             └─mlr3:::.__ResultData__initialize(...)
    9.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_iivm_parameter_passing.R:304:5'): Unit tests for parameter passing of IIVM (default vs explicit) rpart_dml2_LATE_1e-05 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─dml_iivm_default$fit() at test-double_ml_iivm_parameter_passing.R:304:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.         └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.           └─mlr3 (local) initialize(...)
    8.             └─mlr3:::.__ResultData__initialize(...)
    9.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_iivm_trim.R:31:5'): Unit tests for IIVM: rpart_dml2_LATE_truncate_0.05 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_irmiv(...) at test-double_ml_iivm_trim.R:31:5
   3.   └─DoubleML:::fit_nuisance_iivm(...) at ./helper-11-dml_iivm.R:23:5
   4.     └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-11-dml_iivm.R:145:3
   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-double_ml_iivm_tuning.R:76:5'): Unit tests for tuning of IIVM: rpart_dml2_LATE_TRUE_TRUE_1_FALSE ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mliivm_obj_tuned$tune(...) at test-double_ml_iivm_tuning.R:76:5
    3.   └─private$nuisance_tuning(...)
    4.     └─DoubleML:::dml_tune(...)
    5.       └─base::lapply(...)
    6.         └─DoubleML (local) FUN(X[[i]], ...)
    7.           └─DoubleML:::tune_instance(tune_settings$tuner, x)
    8.             └─tuner$optimize(tuning_instance)
    9.               └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
   10.                 └─private$.optimizer$optimize(inst)
   11.                   └─bbotk:::.__OptimizerBatch__optimize(...)
   12.                     └─bbotk::optimize_batch_default(inst, self)
   13.                       ├─base::tryCatch(...)
   14.                       │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
   15.                       │   └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
   16.                       │     └─base (local) doTryCatch(return(expr), name, parentenv, handler)
   17.                       └─get_private(optimizer)$.optimize(instance)
   18.                         └─bbotk:::.__OptimizerBatchRandomSearch__.optimize(...)
   19.                           └─inst$eval_batch(design$data)
   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-double_ml_iivm_user_score.R:55:5'): Unit tests for IIVM, callable score: regr.rpart_classif.rpart_dml2_0 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mliivm_obj$fit() at test-double_ml_iivm_user_score.R:55:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, 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-double_ml_irm.R:32:5'): Unit tests for IRM: rpart_dml1_ATTE_0 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_irm(...) at test-double_ml_irm.R:32:5
   3.   └─DoubleML:::fit_nuisance_irm(...) at ./helper-10-dml_irm.R:21:5
   4.     └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-10-dml_irm.R:138:3
   5.       └─ResultData$new(data, data_extra, store_backends = store_backends)
   6.         └─mlr3 (local) initialize(...)
   7.           └─mlr3:::.__ResultData__initialize(...)
   8.             ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   9.             └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_irm_binary_outcome.R:35:5'): Unit tests for IRM: rpart_dml1_ATTE_0 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_irm(...) at test-double_ml_irm_binary_outcome.R:35:5
   3.   └─DoubleML:::fit_nuisance_irm(...) at ./helper-10-dml_irm.R:21:5
   4.     └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-10-dml_irm.R:138:3
   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-double_ml_irm_loaded_mlr3learner.R:73:5'): Unit tests for IRM: dml1_ATTE_0 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlirm$fit() at test-double_ml_irm_loaded_mlr3learner.R:73:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, 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-double_ml_irm_parameter_passing.R:41:5'): Unit tests for parameter passing of IRM (oop vs fun): rpart_dml2_ATE_1e-05 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_irm(...) at test-double_ml_irm_parameter_passing.R:41:5
   3.   └─DoubleML:::fit_nuisance_irm(...) at ./helper-10-dml_irm.R:21:5
   4.     └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-10-dml_irm.R:138:3
   5.       └─ResultData$new(data, data_extra, store_backends = store_backends)
   6.         └─mlr3 (local) initialize(...)
   7.           └─mlr3:::.__ResultData__initialize(...)
   8.             ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   9.             └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_irm_parameter_passing.R:118:5'): Unit tests for parameter passing of IRM (no cross-fitting) rpart_dml1_ATE_1e-05 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_irm(...) at test-double_ml_irm_parameter_passing.R:118:5
   3.   └─DoubleML:::fit_nuisance_irm(...) at ./helper-10-dml_irm.R:21:5
   4.     └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-10-dml_irm.R:138:3
   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-double_ml_irm_parameter_passing.R:118:5'): Unit tests for parameter passing of IRM (no cross-fitting) rpart_dml1_ATTE_1e-05 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_irm(...) at test-double_ml_irm_parameter_passing.R:118:5
   3.   └─DoubleML:::fit_nuisance_irm(...) at ./helper-10-dml_irm.R:21:5
   4.     └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-10-dml_irm.R:138:3
   5.       └─ResultData$new(data, data_extra, store_backends = store_backends)
   6.         └─mlr3 (local) initialize(...)
   7.           └─mlr3:::.__ResultData__initialize(...)
   8.             ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   9.             └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_irm_parameter_passing.R:198:5'): Unit tests for parameter passing of IRM (fold-wise vs global) rpart_dml2_ATE_1e-05 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlirm_obj$fit() at test-double_ml_irm_parameter_passing.R:198:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.         └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.           └─mlr3 (local) initialize(...)
    8.             └─mlr3:::.__ResultData__initialize(...)
    9.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_irm_parameter_passing.R:260:5'): Unit tests for parameter passing of IRM (default vs explicit) rpart_dml2_ATE_1e-05 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─dml_irm_default$fit() at test-double_ml_irm_parameter_passing.R:260:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.         └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.           └─mlr3 (local) initialize(...)
    8.             └─mlr3:::.__ResultData__initialize(...)
    9.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_irm_trim.R:31:5'): Unit tests for IRM: rpart_dml2_ATTE_truncate_0.05 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_irm(...) at test-double_ml_irm_trim.R:31:5
   3.   └─DoubleML:::fit_nuisance_irm(...) at ./helper-10-dml_irm.R:21:5
   4.     └─mlr3::resample(task_m, ml_m, resampling_m, store_models = TRUE) at ./helper-10-dml_irm.R:138:3
   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-double_ml_irm_tuning.R:76:5'): Unit tests for tuning of PLR: rpart_dml2_ATE_FALSE_1 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlirm_obj_tuned$tune(...) at test-double_ml_irm_tuning.R:76:5
    3.   └─private$nuisance_tuning(...)
    4.     └─DoubleML:::dml_tune(...)
    5.       └─base::lapply(...)
    6.         └─DoubleML (local) FUN(X[[i]], ...)
    7.           └─DoubleML:::tune_instance(tune_settings$tuner, x)
    8.             └─tuner$optimize(tuning_instance)
    9.               └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
   10.                 └─private$.optimizer$optimize(inst)
   11.                   └─bbotk:::.__OptimizerBatch__optimize(...)
   12.                     └─bbotk::optimize_batch_default(inst, self)
   13.                       ├─base::tryCatch(...)
   14.                       │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
   15.                       │   └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
   16.                       │     └─base (local) doTryCatch(return(expr), name, parentenv, handler)
   17.                       └─get_private(optimizer)$.optimize(instance)
   18.                         └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
   19.                           └─inst$eval_batch(g$data[inds])
   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-double_ml_irm_user_score.R:54:5'): Unit tests for IRM, callable score: regr.rpart_classif.rpart_dml2_1e-05 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlirm_obj$fit() at test-double_ml_irm_user_score.R:54:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, 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-double_ml_pliv.R:29:5'): Unit tests for PLIV: regr.lm_dml1_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_pliv(...) at test-double_ml_pliv.R:29:5
   3.   └─DoubleML:::fit_nuisance_pliv(...) at ./helper-09-dml_pliv.R:22:5
   4.     └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-09-dml_pliv.R:114:3
   5.       └─ResultData$new(data, data_extra, store_backends = store_backends)
   6.         └─mlr3 (local) initialize(...)
   7.           └─mlr3:::.__ResultData__initialize(...)
   8.             ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   9.             └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_pliv_exception_handling.R:46:3'): Unit tests for deprecation warnings of PLIV ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─testthat::expect_warning(dml_obj$tune(par_grids), regexp = msg) at test-double_ml_pliv_exception_handling.R:46:3
    2. │ └─testthat:::quasi_capture(...)
    3. │   ├─testthat (local) .capture(...)
    4. │   │ └─base::withCallingHandlers(...)
    5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. └─dml_obj$tune(par_grids)
    7.   └─super$tune(param_set, tune_settings, tune_on_folds)
    8.     └─private$nuisance_tuning(...)
    9.       └─private$nuisance_tuning_partialX(...)
   10.         └─DoubleML:::dml_tune(...)
   11.           └─base::lapply(...)
   12.             └─DoubleML (local) FUN(X[[i]], ...)
   13.               └─DoubleML:::tune_instance(tune_settings$tuner, x)
   14.                 └─tuner$optimize(tuning_instance)
   15.                   └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
   16.                     └─private$.optimizer$optimize(inst)
   17.                       └─bbotk:::.__OptimizerBatch__optimize(...)
   18.                         └─bbotk::optimize_batch_default(inst, self)
   19.                           ├─base::tryCatch(...)
   20.                           │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
   21.                           │   └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
   22.                           │     └─base (local) doTryCatch(return(expr), name, parentenv, handler)
   23.                           └─get_private(optimizer)$.optimize(instance)
   24.                             └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
   25.                               └─inst$eval_batch(g$data[inds])
   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-double_ml_pliv_one_way_cluster.R:56:5'): Unit tests for PLIV with one-way clustering: regr.lm_dml1_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlpliv_obj$fit() at test-double_ml_pliv_one_way_cluster.R:56:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─private$nuisance_est_partialX(smpls, ...)
    5.       └─DoubleML:::dml_cv_predict(...)
    6.         └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    7.           └─ResultData$new(data, data_extra, store_backends = store_backends)
    8.             └─mlr3 (local) initialize(...)
    9.               └─mlr3:::.__ResultData__initialize(...)
   10.                 ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   11.                 └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_pliv_parameter_passing.R:43:5'): Unit tests for parameter passing of PLIV (oop vs fun): regr.rpart_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_pliv(...) at test-double_ml_pliv_parameter_passing.R:43:5
   3.   └─DoubleML:::fit_nuisance_pliv(...) at ./helper-09-dml_pliv.R:22:5
   4.     └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-09-dml_pliv.R:114:3
   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-double_ml_pliv_parameter_passing.R:138:5'): Unit tests for parameter passing of PLIV (no cross-fitting) regr.rpart_dml1_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_pliv(...) at test-double_ml_pliv_parameter_passing.R:138:5
   3.   └─DoubleML:::fit_nuisance_pliv(...) at ./helper-09-dml_pliv.R:22:5
   4.     └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-09-dml_pliv.R:114:3
   5.       └─ResultData$new(data, data_extra, store_backends = store_backends)
   6.         └─mlr3 (local) initialize(...)
   7.           └─mlr3:::.__ResultData__initialize(...)
   8.             ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   9.             └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_pliv_parameter_passing.R:240:5'): Unit tests for parameter passing of PLIV (fold-wise vs global) regr.rpart_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─dml_pliv_obj$fit() at test-double_ml_pliv_parameter_passing.R:240:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─private$nuisance_est_partialX(smpls, ...)
    5.       └─DoubleML:::dml_cv_predict(...)
    6.         └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    7.           └─ResultData$new(data, data_extra, store_backends = store_backends)
    8.             └─mlr3 (local) initialize(...)
    9.               └─mlr3:::.__ResultData__initialize(...)
   10.                 ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   11.                 └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_pliv_parameter_passing.R:321:5'): Unit tests for parameter passing of PLIV (default vs explicit) regr.rpart_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─dml_pliv_default$fit() at test-double_ml_pliv_parameter_passing.R:321:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─private$nuisance_est_partialX(smpls, ...)
    5.       └─DoubleML:::dml_cv_predict(...)
    6.         └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    7.           └─ResultData$new(data, data_extra, store_backends = store_backends)
    8.             └─mlr3 (local) initialize(...)
    9.               └─mlr3:::.__ResultData__initialize(...)
   10.                 ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   11.                 └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_pliv_partial_functional_initializer.R:40:5'): Unit tests for PLIV (partialX functional initialization): regr.lm_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlpliv_obj$fit() at test-double_ml_pliv_partial_functional_initializer.R:40:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─private$nuisance_est_partialX(smpls, ...)
    5.       └─DoubleML:::dml_cv_predict(...)
    6.         └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    7.           └─ResultData$new(data, data_extra, store_backends = store_backends)
    8.             └─mlr3 (local) initialize(...)
    9.               └─mlr3:::.__ResultData__initialize(...)
   10.                 ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   11.                 └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_pliv_partial_functional_initializer.R:82:5'): Unit tests for PLIV (partialZ functional initialization): regr.lm_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlpliv_partZ$fit() at test-double_ml_pliv_partial_functional_initializer.R:82:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─private$nuisance_est_partialZ(smpls, ...)
    5.       └─DoubleML:::dml_cv_predict(...)
    6.         └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    7.           └─ResultData$new(data, data_extra, store_backends = store_backends)
    8.             └─mlr3 (local) initialize(...)
    9.               └─mlr3:::.__ResultData__initialize(...)
   10.                 ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   11.                 └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_pliv_partial_functional_initializer.R:121:5'): Unit tests for PLIV (partialXZ functional initialization): regr.lm_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlpliv_partXZ$fit() at test-double_ml_pliv_partial_functional_initializer.R:121:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─private$nuisance_est_partialXZ(smpls, ...)
    5.       └─DoubleML:::dml_cv_predict(...)
    6.         └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    7.           └─ResultData$new(data, data_extra, store_backends = store_backends)
    8.             └─mlr3 (local) initialize(...)
    9.               └─mlr3:::.__ResultData__initialize(...)
   10.                 ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   11.                 └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_pliv_partial_functional_initializer_IVtype.R:41:5'): Unit tests for PLIV (partialX functional initialization): regr.lm_dml2_IV-type ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlpliv_obj$fit() at test-double_ml_pliv_partial_functional_initializer_IVtype.R:41:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─private$nuisance_est_partialX(smpls, ...)
    5.       └─DoubleML:::dml_cv_predict(...)
    6.         └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    7.           └─ResultData$new(data, data_extra, store_backends = store_backends)
    8.             └─mlr3 (local) initialize(...)
    9.               └─mlr3:::.__ResultData__initialize(...)
   10.                 ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   11.                 └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_pliv_tuning.R:98:5'): Unit tests for tuning of PLIV dml2_partialling out_1_FALSE ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlpliv_obj_tuned$tune(...) at test-double_ml_pliv_tuning.R:98:5
    3.   └─super$tune(param_set, tune_settings, tune_on_folds)
    4.     └─private$nuisance_tuning(...)
    5.       └─private$nuisance_tuning_partialX(...)
    6.         └─DoubleML:::dml_tune(...)
    7.           └─base::lapply(...)
    8.             └─DoubleML (local) FUN(X[[i]], ...)
    9.               └─DoubleML:::tune_instance(tune_settings$tuner, x)
   10.                 └─tuner$optimize(tuning_instance)
   11.                   └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
   12.                     └─private$.optimizer$optimize(inst)
   13.                       └─bbotk:::.__OptimizerBatch__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)$.optimize(instance)
   20.                             └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
   21.                               └─inst$eval_batch(g$data[inds])
   22.                                 └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
   23.                                   └─self$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]]$hash), by = "uhash"]
   36.                                                   └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_pliv_tuning.R:188:5'): Unit tests for tuning of PLIV (multiple Z) dml2_partialling out_1_FALSE ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlpliv_obj_tuned$tune(...) at test-double_ml_pliv_tuning.R:188:5
    3.   └─super$tune(param_set, tune_settings, tune_on_folds)
    4.     └─private$nuisance_tuning(...)
    5.       └─private$nuisance_tuning_partialX(...)
    6.         └─DoubleML:::dml_tune(...)
    7.           └─base::lapply(...)
    8.             └─DoubleML (local) FUN(X[[i]], ...)
    9.               └─DoubleML:::tune_instance(tune_settings$tuner, x)
   10.                 └─tuner$optimize(tuning_instance)
   11.                   └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
   12.                     └─private$.optimizer$optimize(inst)
   13.                       └─bbotk:::.__OptimizerBatch__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)$.optimize(instance)
   20.                             └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
   21.                               └─inst$eval_batch(g$data[inds])
   22.                                 └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
   23.                                   └─self$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]]$hash), by = "uhash"]
   36.                                                   └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_pliv_two_way_cluster.R:50:5'): Unit tests for PLIV with two-way clustering: regr.lm_dml1_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlpliv_obj$fit() at test-double_ml_pliv_two_way_cluster.R:50:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─private$nuisance_est_partialX(smpls, ...)
    5.       └─DoubleML:::dml_cv_predict(...)
    6.         └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    7.           └─ResultData$new(data, data_extra, store_backends = store_backends)
    8.             └─mlr3 (local) initialize(...)
    9.               └─mlr3:::.__ResultData__initialize(...)
   10.                 ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   11.                 └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_pliv_user_score.R:66:5'): Unit tests for PLIV, callable score: regr.lm_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlpliv_obj$fit() at test-double_ml_pliv_user_score.R:66:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─private$nuisance_est_partialX(smpls, ...)
    5.       └─DoubleML:::dml_cv_predict(...)
    6.         └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    7.           └─ResultData$new(data, data_extra, store_backends = store_backends)
    8.             └─mlr3 (local) initialize(...)
    9.               └─mlr3:::.__ResultData__initialize(...)
   10.                 ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   11.                 └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_plr.R:30:5'): Unit tests for PLR: regr.lm_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─DoubleML:::dml_plr(...) at test-double_ml_plr.R:30:5
    3.   └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:22:5
    4.     └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
    5.       └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
    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-double_ml_plr_classifier.R:44:7'): Unit tests for PLR with classifier for ml_m: regr.rpart_classif.rpart_regr.rpart_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─DoubleML:::dml_plr(...) at test-double_ml_plr_classifier.R:44:7
    3.   └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:22:5
    4.     └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
    5.       └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
    6.         └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.           └─mlr3 (local) initialize(...)
    8.             └─mlr3:::.__ResultData__initialize(...)
    9.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.               └─data.table:::`[.data.table`(...)
  ── Failure ('test-double_ml_plr_classifier.R:129:3'): Unit tests for exception handling of PLR with classifier for ml_m: ──
  `double_mlplr_obj$fit()` threw an error with unexpected message.
  Expected match: "Assertion on 'levels\\(data\\[\\[target\\]\\])' failed: .* set \\{'0','1'\\}"
  Actual message: "attempt access index 9/9 in VECTOR_ELT"
  Backtrace:
       ▆
    1. ├─testthat::expect_error(double_mlplr_obj$fit(), regexp = msg) at test-double_ml_plr_classifier.R:129:3
    2. │ └─testthat:::quasi_capture(...)
    3. │   ├─testthat (local) .capture(...)
    4. │   │ └─base::withCallingHandlers(...)
    5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. └─double_mlplr_obj$fit()
    7.   └─private$nuisance_est(private$get__smpls())
    8.     └─DoubleML:::dml_cv_predict(...)
    9.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
   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`(...)
  ── Failure ('test-double_ml_plr_classifier.R:142:3'): Unit tests for exception handling of PLR with classifier for ml_m: ──
  `double_mlplr_obj$fit()` threw an error with unexpected message.
  Expected match: "Assertion on 'levels\\(data\\[\\[target\\]\\])' failed: .* set \\{'0','1'\\}"
  Actual message: "attempt access index 9/9 in VECTOR_ELT"
  Backtrace:
       ▆
    1. ├─testthat::expect_error(double_mlplr_obj$fit(), regexp = msg) at test-double_ml_plr_classifier.R:142:3
    2. │ └─testthat:::quasi_capture(...)
    3. │   ├─testthat (local) .capture(...)
    4. │   │ └─base::withCallingHandlers(...)
    5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. └─double_mlplr_obj$fit()
    7.   └─private$nuisance_est(private$get__smpls())
    8.     └─DoubleML:::dml_cv_predict(...)
    9.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
   10.         └─ResultData$new(data, data_extra, store_backends = store_backends)
   11.           └─mlr3 (local) initialize(...)
   12.             └─mlr3:::.__ResultData__initialize(...)
   13.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   14.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_plr_exception_handling.R:116:7'): Unit tests for exception handling of PLR: regr.lm_dml1_IV-type_FALSE_4_1_TRUE ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlplr_obj$fit() at test-double_ml_plr_exception_handling.R:116:7
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.         └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.           └─mlr3 (local) initialize(...)
    8.             └─mlr3:::.__ResultData__initialize(...)
    9.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_plr_exception_handling.R:176:3'): Unit tests for deprecation warnings of PLR ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─testthat::expect_warning(dml_obj$tune(par_grids), regexp = msg) at test-double_ml_plr_exception_handling.R:176:3
    2. │ └─testthat:::quasi_capture(...)
    3. │   ├─testthat (local) .capture(...)
    4. │   │ └─base::withCallingHandlers(...)
    5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. └─dml_obj$tune(par_grids)
    7.   └─super$tune(param_set, tune_settings, tune_on_folds)
    8.     └─private$nuisance_tuning(...)
    9.       └─DoubleML:::dml_tune(...)
   10.         └─base::lapply(...)
   11.           └─DoubleML (local) FUN(X[[i]], ...)
   12.             └─DoubleML:::tune_instance(tune_settings$tuner, x)
   13.               └─tuner$optimize(tuning_instance)
   14.                 └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
   15.                   └─private$.optimizer$optimize(inst)
   16.                     └─bbotk:::.__OptimizerBatch__optimize(...)
   17.                       └─bbotk::optimize_batch_default(inst, self)
   18.                         ├─base::tryCatch(...)
   19.                         │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
   20.                         │   └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
   21.                         │     └─base (local) doTryCatch(return(expr), name, parentenv, handler)
   22.                         └─get_private(optimizer)$.optimize(instance)
   23.                           └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
   24.                             └─inst$eval_batch(g$data[inds])
   25.                               └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
   26.                                 └─self$objective$eval_many(xss_trafoed)
   27.                                   └─bbotk:::.__Objective__eval_many(...)
   28.                                     ├─mlr3misc::invoke(private$.eval_many, xss = xss, .args = self$constants$values)
   29.                                     │ └─base::eval.parent(expr, n = 1L)
   30.                                     │   └─base::eval(expr, p)
   31.                                     │     └─base::eval(expr, p)
   32.                                     └─private$.eval_many(xss = xss, resampling = `<list>`)
   33.                                       └─mlr3tuning:::.__ObjectiveTuningBatch__.eval_many(...)
   34.                                         └─mlr3::benchmark(...)
   35.                                           └─ResultData$new(grid, data_extra, store_backends = store_backends)
   36.                                             └─mlr3 (local) initialize(...)
   37.                                               └─mlr3:::.__ResultData__initialize(...)
   38.                                                 ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   39.                                                 └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_plr_export_preds.R:49:5'): Unit tests for for the export of predictions: regr.rpart_regr.rpart_regr.rpart_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlplr_obj$fit(store_predictions = TRUE, store_models = TRUE) at test-double_ml_plr_export_preds.R:49:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.         └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.           └─mlr3 (local) initialize(...)
    8.             └─mlr3:::.__ResultData__initialize(...)
    9.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_plr_loaded_mlr3learner.R:66:5'): Unit tests for PLR: dml1_IV-type ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlplr$fit() at test-double_ml_plr_loaded_mlr3learner.R:66:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.         └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.           └─mlr3 (local) initialize(...)
    8.             └─mlr3:::.__ResultData__initialize(...)
    9.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_plr_multitreat.R:37:5'): Unit tests for PLR: regr.lm_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─DoubleML:::dml_plr_multitreat(...) at test-double_ml_plr_multitreat.R:37:5
    3.   └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:89:7
    4.     └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
    5.       └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
    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-double_ml_plr_nocrossfit.R:51:5'): Unit tests for PLR: regr.lm_dml2_partialling out_FALSE_1 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─DoubleML:::dml_plr(...) at test-double_ml_plr_nocrossfit.R:51:5
    3.   └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:22:5
    4.     └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
    5.       └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
    6.         └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.           └─mlr3 (local) initialize(...)
    8.             └─mlr3:::.__ResultData__initialize(...)
    9.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_plr_nocrossfit.R:51:5'): Unit tests for PLR: regr.lm_dml2_partialling out_FALSE_2 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─DoubleML:::dml_plr(...) at test-double_ml_plr_nocrossfit.R:51:5
    3.   └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:22:5
    4.     └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
    5.       └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
    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-double_ml_plr_nonorth.R:74:5'): Unit tests for PLR: regr.lm_dml1_non_orth_score_w_g_3_2 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlplr_obj$fit() at test-double_ml_plr_nonorth.R:74:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, 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-double_ml_plr_p_adjust.R:69:5'): Unit tests for PLR: regr.rpart_dml1_partialling out_romano-wolf_TRUE ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlplr_obj$fit() at test-double_ml_plr_p_adjust.R:69:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, 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-double_ml_plr_parameter_passing.R:48:5'): Unit tests for parameter passing of PLR (oop vs fun) regr.rpart_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─DoubleML:::dml_plr_multitreat(...) at test-double_ml_plr_parameter_passing.R:48:5
    3.   └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:89:7
    4.     └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
    5.       └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
    6.         └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.           └─mlr3 (local) initialize(...)
    8.             └─mlr3:::.__ResultData__initialize(...)
    9.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_plr_parameter_passing.R:150:5'): Unit tests for parameter passing of PLR (no cross-fitting) regr.rpart_dml1_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─DoubleML:::dml_plr_multitreat(...) at test-double_ml_plr_parameter_passing.R:150:5
    3.   └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:89:7
    4.     └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
    5.       └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
    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-double_ml_plr_parameter_passing.R:264:5'): Unit tests for parameter passing of PLR (fold-wise vs global) regr.rpart_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlplr_obj$fit() at test-double_ml_plr_parameter_passing.R:264:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, 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-double_ml_plr_parameter_passing.R:353:5'): Unit tests for parameter passing of PLR (default vs explicit) regr.rpart_dml2_partialling out ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─dml_plr_default$fit() at test-double_ml_plr_parameter_passing.R:353:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, 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-double_ml_plr_rep_cross_fit.R:38:5'): Unit tests for PLR: regr.lm_dml1_partialling out_5 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─DoubleML:::dml_plr(...) at test-double_ml_plr_rep_cross_fit.R:38:5
    3.   └─DoubleML:::fit_plr_single_split(...) at ./helper-08-dml_plr.R:22:5
    4.     └─DoubleML:::fit_nuisance_plr(...) at ./helper-08-dml_plr.R:141:3
    5.       └─mlr3::resample(task_l, ml_l, resampling_l, store_models = TRUE) at ./helper-08-dml_plr.R:225:3
    6.         └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.           └─mlr3 (local) initialize(...)
    8.             └─mlr3:::.__ResultData__initialize(...)
    9.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_plr_set_samples.R:53:5'): PLR with external sample provision: regr.rpart_dml2_partialling out_2_1 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlplr_obj$fit() at test-double_ml_plr_set_samples.R:53:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.         └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.           └─mlr3 (local) initialize(...)
    8.             └─mlr3:::.__ResultData__initialize(...)
    9.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_plr_tuning.R:95:5'): Unit tests for tuning of PLR: regr.rpart_regr.rpart_dml2_partialling out_1_FALSE ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlplr_obj_tuned$tune(...) at test-double_ml_plr_tuning.R:95:5
    3.   └─super$tune(param_set, tune_settings, tune_on_folds)
    4.     └─private$nuisance_tuning(...)
    5.       └─DoubleML:::dml_tune(...)
    6.         └─base::lapply(...)
    7.           └─DoubleML (local) FUN(X[[i]], ...)
    8.             └─DoubleML:::tune_instance(tune_settings$tuner, x)
    9.               └─tuner$optimize(tuning_instance)
   10.                 └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
   11.                   └─private$.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:::.__OptimizerBatchGridSearch__.optimize(...)
   20.                             └─inst$eval_batch(g$data[inds])
   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-double_ml_plr_tuning.R:95:5'): Unit tests for tuning of PLR: regr.rpart_regr.rpart_dml2_partialling out_1_TRUE ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlplr_obj_tuned$tune(...) at test-double_ml_plr_tuning.R:95:5
    3.   └─super$tune(param_set, tune_settings, tune_on_folds)
    4.     └─private$nuisance_tuning(...)
    5.       └─DoubleML:::dml_tune(...)
    6.         └─base::lapply(...)
    7.           └─DoubleML (local) FUN(X[[i]], ...)
    8.             └─DoubleML:::tune_instance(tune_settings$tuner, x)
    9.               └─tuner$optimize(tuning_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)$.optimize(instance)
   19.                           └─bbotk:::.__OptimizerBatchGridSearch__.optimize(...)
   20.                             └─inst$eval_batch(g$data[inds])
   21.                               └─bbotk:::.__OptimInstanceBatch__eval_batch(...)
   22.                                 └─self$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]]$hash), by = "uhash"]
   35.                                                 └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_plr_user_score.R:48:5'): Unit tests for PLR, callable score: regr.lm_dml1_3_2 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlplr_obj$fit() at test-double_ml_plr_user_score.R:48:5
    3.   └─private$nuisance_est(private$get__smpls())
    4.     └─DoubleML:::dml_cv_predict(...)
    5.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
    6.         └─ResultData$new(data, data_extra, store_backends = store_backends)
    7.           └─mlr3 (local) initialize(...)
    8.             └─mlr3:::.__ResultData__initialize(...)
    9.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   10.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_print.R:12:1'): (code run outside of `test_that()`) ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. └─dml_plr$fit() at test-double_ml_print.R:12:1
   2.   └─private$nuisance_est(private$get__smpls())
   3.     └─DoubleML:::dml_cv_predict(...)
   4.       └─mlr3::resample(task_pred, ml_learner, resampling_smpls, store_models = TRUE)
   5.         └─ResultData$new(data, data_extra, store_backends = store_backends)
   6.           └─mlr3 (local) initialize(...)
   7.             └─mlr3:::.__ResultData__initialize(...)
   8.               ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   9.               └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_ssm_mar.R:32:5'): Unit tests for SSM, missing-at-random: cv_glmnet_dml1_missing-at-random_0 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_ssm(...) at test-double_ml_ssm_mar.R:32:5
   3.   └─DoubleML:::fit_nuisance_ssm(...) at ./helper-17-dml_ssm.R:22:5
   4.     └─mlr3::resample(task_pi, ml_pi, resampling_pi, store_models = TRUE) at ./helper-17-dml_ssm.R:147:5
   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-double_ml_ssm_nonignorable.R:32:5'): Unit tests for SSM, nonignorable nonresponse: cv_glmnet_dml1_nonignorable_0 ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
      ▆
   1. ├─rlang::eval_tidy(code, test_args)
   2. └─DoubleML:::dml_ssm(...) at test-double_ml_ssm_nonignorable.R:32:5
   3.   └─DoubleML:::fit_nuisance_ssm(...) at ./helper-17-dml_ssm.R:22:5
   4.     └─mlr3::resample(...) at ./helper-17-dml_ssm.R:239:7
   5.       └─ResultData$new(data, data_extra, store_backends = store_backends)
   6.         └─mlr3 (local) initialize(...)
   7.           └─mlr3:::.__ResultData__initialize(...)
   8.             ├─data[, `:=`("task_hash", task[[1L]]$hash), by = "uhash"]
   9.             └─data.table:::`[.data.table`(...)
  ── Error ('test-double_ml_ssm_tuning.R:75:5'): Unit tests for tuning of SSM: rpart_dml2_missing-at-random_1_FALSE ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlssm_obj_tuned$tune(...) at test-double_ml_ssm_tuning.R:75:5
    3.   └─super$tune(param_set, tune_settings, tune_on_folds)
    4.     └─private$nuisance_tuning(...)
    5.       └─DoubleML:::dml_tune(...)
    6.         └─base::lapply(...)
    7.           └─DoubleML (local) FUN(X[[i]], ...)
    8.             └─DoubleML:::tune_instance(tune_settings$tuner, x)
    9.               └─tuner$optimize(tuning_instance)
   10.                 └─mlr3tuning:::.__TunerBatchFromOptimizerBatch__optimize(...)
   11.                   └─private$.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-double_ml_ssm_tuning.R:75:5'): Unit tests for tuning of SSM: rpart_dml2_nonignorable_1_FALSE ──
  Error in ``[.data.table`(data, , `:=`("task_hash", task[[1L]]$hash), by = "uhash")`: attempt access index 9/9 in VECTOR_ELT
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(code, test_args)
    2. └─double_mlssm_obj_tuned$tune(...) at test-double_ml_ssm_tuning.R:75:5
    3.   └─super$tune(param_set, tune_settings, tune_on_folds)
    4.     └─private$nuisance_tuning(...)
    5.       └─DoubleML:::dml_tune(...)
    6.         └─base::lapply(...)
    7.           └─DoubleML (local) FUN(X[[i]], ...)
    8.             └─DoubleML:::tune_instance(tune_settings$tuner, x)
    9.               └─tuner$optimize(tuning_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`(...)
  
  [ FAIL 63 | WARN 0 | SKIP 7 | PASS 296 ]
  Error:
  ! Test failures.
  Execution halted