Running ‘testthat.R’ [16s/17s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > # This file is part of the standard setup for testthat.
  > # It is recommended that you do not modify it.
  > #
  > # Where should you do additional test configuration?
  > # Learn more about the roles of various files in:
  > # * https://r-pkgs.org/tests.html
  > # * https://testthat.r-lib.org/reference/test_package.html#special-files
  > 
  > library(testthat)
  > library(mllrnrs)
  > 
  > test_check("mllrnrs")
  
  CV fold: Fold1
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  CV fold: Fold1
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  CV fold: Fold1
  
  CV fold: Fold1
  
  CV fold: Fold2
  
  CV fold: Fold3
  
  CV fold: Fold1
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  CV fold: Fold1
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  CV fold: Fold1
  
  Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
  ... reducing initialization grid to 10 rows.
  
  CV fold: Fold1
  
  CV fold: Fold2
  
  CV fold: Fold3
  [ FAIL 15 | WARN 0 | SKIP 1 | PASS 6 ]
  
  ══ Skipped tests (1) ═══════════════════════════════════════════════════════════
  • On CRAN (1): 'test-lints.R:10:5'
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-glmnet_binary.R:65:5'): test nested cv, bayesian, binary - glmnet ──
  Error: Package "glmnet" must be installed to use 'learner = "LearnerGlmnet"'.
  Backtrace:
      ▆
   1. ├─mlexperiments::MLNestedCV$new(...) at test-glmnet_binary.R:65:5
   2. │ └─mlexperiments (local) initialize(...)
   3. │   └─super$initialize(...)
   4. │     └─super$initialize(learner = learner, seed = seed, ncores = ncores)
   5. │       ├─base::stopifnot(...)
   6. │       └─R6::is.R6(learner)
   7. └─mllrnrs::LearnerGlmnet$new(metric_optimization_higher_better = FALSE)
   8.   └─mllrnrs (local) initialize(...)
  ── Error ('test-glmnet_binary.R:110:5'): test nested cv, grid - glmnet, errors ──
  Error: Package "glmnet" must be installed to use 'learner = "LearnerGlmnet"'.
  Backtrace:
      ▆
   1. ├─mlexperiments::MLNestedCV$new(...) at test-glmnet_binary.R:110:5
   2. │ └─mlexperiments (local) initialize(...)
   3. │   └─super$initialize(...)
   4. │     └─super$initialize(learner = learner, seed = seed, ncores = ncores)
   5. │       ├─base::stopifnot(...)
   6. │       └─R6::is.R6(learner)
   7. └─mllrnrs::LearnerGlmnet$new(metric_optimization_higher_better = FALSE)
   8.   └─mllrnrs (local) initialize(...)
  ── Error ('test-glmnet_multiclass.R:65:5'): test nested cv, bayesian, multiclass - glmnet ──
  Error: Package "glmnet" must be installed to use 'learner = "LearnerGlmnet"'.
  Backtrace:
      ▆
   1. ├─mlexperiments::MLNestedCV$new(...) at test-glmnet_multiclass.R:65:5
   2. │ └─mlexperiments (local) initialize(...)
   3. │   └─super$initialize(...)
   4. │     └─super$initialize(learner = learner, seed = seed, ncores = ncores)
   5. │       ├─base::stopifnot(...)
   6. │       └─R6::is.R6(learner)
   7. └─mllrnrs::LearnerGlmnet$new(metric_optimization_higher_better = FALSE)
   8.   └─mllrnrs (local) initialize(...)
  ── Error ('test-glmnet_regression.R:65:5'): test nested cv, bayesian, regression - glmnet ──
  Error: Package "glmnet" must be installed to use 'learner = "LearnerGlmnet"'.
  Backtrace:
      ▆
   1. ├─mlexperiments::MLNestedCV$new(...) at test-glmnet_regression.R:65:5
   2. │ └─mlexperiments (local) initialize(...)
   3. │   └─super$initialize(...)
   4. │     └─super$initialize(learner = learner, seed = seed, ncores = ncores)
   5. │       ├─base::stopifnot(...)
   6. │       └─R6::is.R6(learner)
   7. └─mllrnrs::LearnerGlmnet$new(metric_optimization_higher_better = FALSE)
   8.   └─mllrnrs (local) initialize(...)
  ── Error ('test-glmnet_regression.R:110:5'): test nested cv, grid - glmnet ─────
  Error: Package "glmnet" must be installed to use 'learner = "LearnerGlmnet"'.
  Backtrace:
      ▆
   1. ├─mlexperiments::MLNestedCV$new(...) at test-glmnet_regression.R:110:5
   2. │ └─mlexperiments (local) initialize(...)
   3. │   └─super$initialize(...)
   4. │     └─super$initialize(learner = learner, seed = seed, ncores = ncores)
   5. │       ├─base::stopifnot(...)
   6. │       └─R6::is.R6(learner)
   7. └─mllrnrs::LearnerGlmnet$new(metric_optimization_higher_better = FALSE)
   8.   └─mllrnrs (local) initialize(...)
  ── Error ('test-lightgbm_binary.R:107:5'): test nested cv, bayesian, binary - lightgbm ──
  Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
  Backtrace:
       ▆
    1. └─lightgbm_optimizer$execute() at test-lightgbm_binary.R:107:5
    2.   └─mlexperiments:::.run_cv(self = self, private = private)
    3.     └─mlexperiments:::.fold_looper(self, private)
    4.       ├─base::do.call(private$cv_run_model, run_args)
    5.       └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<named list>`, fold_test = `<named list>`)
    6.         ├─base::do.call(.cv_run_nested_model, args)
    7.         └─mlexperiments (local) `<fn>`(...)
    8.           └─hparam_tuner$execute(k = self$k_tuning)
    9.             └─private$select_optimizer(self, private)
   10.               └─BayesianOptimizer$new(...)
   11.                 └─mlexperiments (local) initialize(...)
  ── Error ('test-lightgbm_multiclass.R:109:5'): test nested cv, bayesian, multiclass - lightgbm ──
  Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
  Backtrace:
       ▆
    1. └─lightgbm_optimizer$execute() at test-lightgbm_multiclass.R:109:5
    2.   └─mlexperiments:::.run_cv(self = self, private = private)
    3.     └─mlexperiments:::.fold_looper(self, private)
    4.       ├─base::do.call(private$cv_run_model, run_args)
    5.       └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<named list>`, fold_test = `<named list>`)
    6.         ├─base::do.call(.cv_run_nested_model, args)
    7.         └─mlexperiments (local) `<fn>`(...)
    8.           └─hparam_tuner$execute(k = self$k_tuning)
    9.             └─private$select_optimizer(self, private)
   10.               └─BayesianOptimizer$new(...)
   11.                 └─mlexperiments (local) initialize(...)
  ── Error ('test-lightgbm_regression.R:106:5'): test nested cv, bayesian, regression - lightgbm ──
  Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
  Backtrace:
       ▆
    1. └─lightgbm_optimization$execute() at test-lightgbm_regression.R:106:5
    2.   └─mlexperiments:::.run_cv(self = self, private = private)
    3.     └─mlexperiments:::.fold_looper(self, private)
    4.       ├─base::do.call(private$cv_run_model, run_args)
    5.       └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<named list>`, fold_test = `<named list>`)
    6.         ├─base::do.call(.cv_run_nested_model, args)
    7.         └─mlexperiments (local) `<fn>`(...)
    8.           └─hparam_tuner$execute(k = self$k_tuning)
    9.             └─private$select_optimizer(self, private)
   10.               └─BayesianOptimizer$new(...)
   11.                 └─mlexperiments (local) initialize(...)
  ── Error ('test-ranger_binary.R:73:5'): test nested cv, bayesian, binary - ranger ──
  Error: Package "ranger" must be installed to use 'learner = "LearnerRanger"'.
  Backtrace:
      ▆
   1. ├─mlexperiments::MLNestedCV$new(...) at test-ranger_binary.R:73:5
   2. │ └─mlexperiments (local) initialize(...)
   3. │   └─super$initialize(...)
   4. │     └─super$initialize(learner = learner, seed = seed, ncores = ncores)
   5. │       ├─base::stopifnot(...)
   6. │       └─R6::is.R6(learner)
   7. └─mllrnrs::LearnerRanger$new()
   8.   └─mllrnrs (local) initialize(...)
  ── Error ('test-ranger_multiclass.R:73:5'): test nested cv, bayesian, regression - ranger ──
  Error: Package "ranger" must be installed to use 'learner = "LearnerRanger"'.
  Backtrace:
      ▆
   1. ├─mlexperiments::MLNestedCV$new(...) at test-ranger_multiclass.R:73:5
   2. │ └─mlexperiments (local) initialize(...)
   3. │   └─super$initialize(...)
   4. │     └─super$initialize(learner = learner, seed = seed, ncores = ncores)
   5. │       ├─base::stopifnot(...)
   6. │       └─R6::is.R6(learner)
   7. └─mllrnrs::LearnerRanger$new()
   8.   └─mllrnrs (local) initialize(...)
  ── Error ('test-ranger_regression.R:73:5'): test nested cv, bayesian, regression - ranger ──
  Error: Package "ranger" must be installed to use 'learner = "LearnerRanger"'.
  Backtrace:
      ▆
   1. ├─mlexperiments::MLNestedCV$new(...) at test-ranger_regression.R:73:5
   2. │ └─mlexperiments (local) initialize(...)
   3. │   └─super$initialize(...)
   4. │     └─super$initialize(learner = learner, seed = seed, ncores = ncores)
   5. │       ├─base::stopifnot(...)
   6. │       └─R6::is.R6(learner)
   7. └─mllrnrs::LearnerRanger$new()
   8.   └─mllrnrs (local) initialize(...)
  ── Error ('test-ranger_regression.R:111:5'): test nested cv, grid - ranger ─────
  Error: Package "ranger" must be installed to use 'learner = "LearnerRanger"'.
  Backtrace:
      ▆
   1. ├─mlexperiments::MLNestedCV$new(...) at test-ranger_regression.R:111:5
   2. │ └─mlexperiments (local) initialize(...)
   3. │   └─super$initialize(...)
   4. │     └─super$initialize(learner = learner, seed = seed, ncores = ncores)
   5. │       ├─base::stopifnot(...)
   6. │       └─R6::is.R6(learner)
   7. └─mllrnrs::LearnerRanger$new()
   8.   └─mllrnrs (local) initialize(...)
  ── Error ('test-xgboost_binary.R:104:5'): test nested cv, bayesian, binary:logistic - xgboost ──
  Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
  Backtrace:
       ▆
    1. └─xgboost_optimizer$execute() at test-xgboost_binary.R:104:5
    2.   └─mlexperiments:::.run_cv(self = self, private = private)
    3.     └─mlexperiments:::.fold_looper(self, private)
    4.       ├─base::do.call(private$cv_run_model, run_args)
    5.       └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<named list>`, fold_test = `<named list>`)
    6.         ├─base::do.call(.cv_run_nested_model, args)
    7.         └─mlexperiments (local) `<fn>`(...)
    8.           └─hparam_tuner$execute(k = self$k_tuning)
    9.             └─private$select_optimizer(self, private)
   10.               └─BayesianOptimizer$new(...)
   11.                 └─mlexperiments (local) initialize(...)
  ── Error ('test-xgboost_multiclass.R:107:5'): test nested cv, bayesian, multi:softprob - xgboost, with weights ──
  Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
  Backtrace:
       ▆
    1. └─xgboost_optimizer$execute() at test-xgboost_multiclass.R:107:5
    2.   └─mlexperiments:::.run_cv(self = self, private = private)
    3.     └─mlexperiments:::.fold_looper(self, private)
    4.       ├─base::do.call(private$cv_run_model, run_args)
    5.       └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<named list>`, fold_test = `<named list>`)
    6.         ├─base::do.call(.cv_run_nested_model, args)
    7.         └─mlexperiments (local) `<fn>`(...)
    8.           └─hparam_tuner$execute(k = self$k_tuning)
    9.             └─private$select_optimizer(self, private)
   10.               └─BayesianOptimizer$new(...)
   11.                 └─mlexperiments (local) initialize(...)
  ── Error ('test-xgboost_regression.R:103:5'): test nested cv, bayesian, reg:squarederror - xgboost ──
  Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
  Backtrace:
       ▆
    1. └─xgboost_optimizer$execute() at test-xgboost_regression.R:103:5
    2.   └─mlexperiments:::.run_cv(self = self, private = private)
    3.     └─mlexperiments:::.fold_looper(self, private)
    4.       ├─base::do.call(private$cv_run_model, run_args)
    5.       └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<named list>`, fold_test = `<named list>`)
    6.         ├─base::do.call(.cv_run_nested_model, args)
    7.         └─mlexperiments (local) `<fn>`(...)
    8.           └─hparam_tuner$execute(k = self$k_tuning)
    9.             └─private$select_optimizer(self, private)
   10.               └─BayesianOptimizer$new(...)
   11.                 └─mlexperiments (local) initialize(...)
  
  [ FAIL 15 | WARN 0 | SKIP 1 | PASS 6 ]
  Error: Test failures
  Execution halted