Package: DALEXtra
Check: examples
New result: ERROR
  Running examples in ‘DALEXtra-Ex.R’ failed
  The error most likely occurred in:
  
  > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
  > ### Name: explain_xgboost
  > ### Title: Create explainer from your xgboost model
  > ### Aliases: explain_xgboost
  > 
  > ### ** Examples
  > 
  > library("xgboost")
  > library("DALEXtra")
  > library("mlr")
  Loading required package: ParamHelpers
  > # 8th column is target that has to be omitted in X data
  > data <- as.matrix(createDummyFeatures(titanic_imputed[,-8]))
  > model <- xgboost(data, titanic_imputed$survived, nrounds = 10,
  +                  params = list(objective = "binary:logistic"),
  +                 prediction = TRUE)
  Warning in throw_err_or_depr_msg("Parameter(s) have been removed from this function: ",  :
    Parameter(s) have been removed from this function: params. This warning will become an error in a future version.
  Warning in throw_err_or_depr_msg("Passed unrecognized parameters: ", paste(head(names_unrecognized),  :
    Passed unrecognized parameters: prediction. This warning will become an error in a future version.
  > # explainer with encode functiom
  > explainer_1 <- explain_xgboost(model, data = titanic_imputed[,-8],
  +                                titanic_imputed$survived,
  +                                encode_function = function(data) {
  +  as.matrix(createDummyFeatures(data))
  + })
  Preparation of a new explainer is initiated
    -> model label       :  xgb.Booster  (  default  )
    -> data              :  2207  rows  7  cols 
    -> target variable   :  2207  values 
    -> predict function  :  yhat.xgb.Booster  will be used (  default  )
    -> predicted values  :  No value for predict function target column. (  default  )
  Error in strsplit(model$params$objective, ":", fixed = TRUE) : 
    non-character argument
  Calls: explain_xgboost ... explain -> model_info -> model_info.xgb.Booster -> strsplit
  Execution halted

Package: DALEXtra
Check: tests
New result: ERROR
    Running ‘testthat.R’ [156s/153s]
  Running the tests in ‘tests/testthat.R’ failed.
  Complete output:
    > library(testthat)
    > library(DALEXtra)
    Loading required package: DALEX
    Welcome to DALEX (version: 2.5.3).
    Find examples and detailed introduction at: http://ema.drwhy.ai/
    Additional features will be available after installation of: ggpubr.
    Use 'install_dependencies()' to get all suggested dependencies
    > 
    > test_check("DALEXtra")
    Preparation of a new explainer is initiated
      -> model label       :  LM 
      -> data              :  9000  rows  6  cols 
      -> target variable   :  9000  values 
      -> predict function  :  yhat.WrappedModel  will be used (  default  )
      -> predicted values  :  No value for predict function target column. (  default  )
      -> model_info        :  package mlr , ver. 2.19.3 , task regression (  default  ) 
      -> predicted values  :  numerical, min =  1792.597 , mean =  3506.836 , max =  6241.447  
      -> residual function :  difference between y and yhat (  default  )
      -> residuals         :  numerical, min =  -257.2555 , mean =  4.687686 , max =  472.356  
      A new explainer has been created!  
    Preparation of a new explainer is initiated
      -> model label       :  RF 
      -> data              :  9000  rows  6  cols 
      -> target variable   :  9000  values 
      -> predict function  :  yhat.WrappedModel  will be used (  default  )
      -> predicted values  :  No value for predict function target column. (  default  )
      -> model_info        :  package mlr , ver. 2.19.3 , task regression (  default  ) 
      -> predicted values  :  numerical, min =  1803.371 , mean =  3503.644 , max =  6247.912  
      -> residual function :  difference between y and yhat (  default  )
      -> residuals         :  numerical, min =  -567.8042 , mean =  7.880015 , max =  731.3791  
      A new explainer has been created!  
    Preparation of a new explainer is initiated
      -> model label       :  GBM 
      -> data              :  9000  rows  6  cols 
      -> target variable   :  9000  values 
      -> predict function  :  yhat.WrappedModel  will be used (  default  )
      -> predicted values  :  No value for predict function target column. (  default  )
      -> model_info        :  package mlr , ver. 2.19.3 , task regression (  default  ) 
      -> predicted values  :  numerical, min =  2122.542 , mean =  3503.611 , max =  6049.829  
      -> residual function :  difference between y and yhat (  default  )
      -> residuals         :  numerical, min =  -519.5424 , mean =  7.912275 , max =  730.9789  
      A new explainer has been created!  
    additional arguments ignored in warning()
    Preparation of a new explainer is initiated
      -> model label       :  ranger  (  default  )
      -> data              :  2207  rows  7  cols 
      -> target variable   :  2207  values 
      -> predict function  :  yhat.ranger  will be used (  default  )
      -> predicted values  :  No value for predict function target column. (  default  )
      -> model_info        :  package ranger , ver. 0.17.0 , task classification (  default  ) 
      -> predicted values  :  numerical, min =  0.009637921 , mean =  0.3217361 , max =  0.9912826  
      -> residual function :  difference between y and yhat (  default  )
      -> residuals         :  numerical, min =  -0.7823858 , mean =  0.0004206265 , max =  0.8839248  
      A new explainer has been created!  
    additional arguments ignored in warning()
    Saving _problems/test_xgboost_explain-13.R
    Saving _problems/test_xgboost_explain-31.R
    Saving _problems/test_xgboost_explain-50.R
    [ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
    
    ══ Skipped tests (11) ══════════════════════════════════════════════════════════
    • Conda test env needed for tests (6): 'test_create_env.R:6:3',
      'test_create_env.R:27:3', 'test_create_env.R:40:3',
      'test_keras_explain.R:6:2', 'test_scikitlearn_explain.R:6:3',
      'tests_prints.R:8:3'
    • JAVA entry needed for tests (4): 'test_h2o_explain.R:8:3',
      'test_h2o_explain.R:33:3', 'test_h2o_explain.R:56:3',
      'test_h2o_explain.R:90:3'
    • Test with windows (1): 'test_champion_challenger.R:5:3'
    
    ══ Failed tests ════════════════════════════════════════════════════════════════
    ── Error ('test_xgboost_explain.R:11:3'): creating explainer classif ───────────
    Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
    Backtrace:
        ▆
     1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:11:3
     2.   └─DALEX::explain(...)
     3.     ├─DALEX::model_info(model, is_multiclass = task_subtype)
     4.     └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
     5.       └─base::strsplit(model$params$objective, ":", fixed = TRUE)
    ── Error ('test_xgboost_explain.R:29:3'): creating explainer regr ──────────────
    Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
    Backtrace:
        ▆
     1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:29:3
     2.   └─DALEX::explain(...)
     3.     ├─DALEX::model_info(model, is_multiclass = task_subtype)
     4.     └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
     5.       └─base::strsplit(model$params$objective, ":", fixed = TRUE)
    ── Error ('test_xgboost_explain.R:48:3'): creating explainer multi ─────────────
    Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
    Backtrace:
        ▆
     1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:48:3
     2.   └─DALEX::explain(...)
     3.     ├─DALEX::model_info(model, is_multiclass = task_subtype)
     4.     └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
     5.       └─base::strsplit(model$params$objective, ":", fixed = TRUE)
    
    [ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
    Error:
    ! Test failures.
    Execution halted

Package: mlr3benchmark
Check: examples
New result: ERROR
  Running examples in ‘mlr3benchmark-Ex.R’ failed
  The error most likely occurred in:
  
  > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
  > ### Name: autoplot.BenchmarkAggr
  > ### Title: Plots for BenchmarkAggr
  > ### Aliases: autoplot.BenchmarkAggr
  > 
  > ### ** Examples
  > 
  > if (requireNamespaces(c("mlr3learners", "mlr3", "rpart", "xgboost"))) {
  + library(mlr3)
  + library(mlr3learners)
  + library(ggplot2)
  + 
  + set.seed(1)
  + task = tsks(c("iris", "sonar", "wine", "zoo"))
  + learns = lrns(c("classif.featureless", "classif.rpart", "classif.xgboost"))
  + learns$classif.xgboost$param_set$values$nrounds = 50
  + bm = benchmark(benchmark_grid(task, learns, rsmp("cv", folds = 3)))
  + obj = as_benchmark_aggr(bm)
  + 
  + # mean and error bars
  + autoplot(obj, type = "mean", level = 0.95)
  + 
  + if (requireNamespace("PMCMRplus", quietly = TRUE)) {
  +   # critical differences
  +   autoplot(obj, type = "cd",style = 1)
  +   autoplot(obj, type = "cd",style = 2)
  + 
  +   # post-hoc friedman-nemenyi
  +   autoplot(obj, type = "fn")
  + }
  + 
  + }
  INFO  [17:58:21.711] [mlr3] Running benchmark with 36 resampling iterations
  INFO  [17:58:21.724] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3)
  INFO  [17:58:21.743] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3)
  INFO  [17:58:21.761] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3)
  INFO  [17:58:21.779] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3)
  INFO  [17:58:21.800] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3)
  INFO  [17:58:21.822] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3)
  INFO  [17:58:21.844] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 1/3)
  INFO  [17:58:21.885] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 2/3)
  INFO  [17:58:21.918] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 3/3)
  INFO  [17:58:21.950] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3)
  INFO  [17:58:21.968] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3)
  INFO  [17:58:21.987] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3)
  INFO  [17:58:22.006] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3)
  INFO  [17:58:22.045] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3)
  INFO  [17:58:22.072] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3)
  INFO  [17:58:22.100] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 1/3)
  INFO  [17:58:22.152] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 2/3)
  INFO  [17:58:22.203] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 3/3)
  INFO  [17:58:22.255] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 1/3)
  INFO  [17:58:22.271] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 2/3)
  INFO  [17:58:22.287] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 3/3)
  INFO  [17:58:22.304] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 1/3)
  INFO  [17:58:22.325] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 2/3)
  INFO  [17:58:22.347] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 3/3)
  INFO  [17:58:22.368] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 1/3)
  INFO  [17:58:22.402] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 2/3)
  INFO  [17:58:22.436] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 3/3)
  INFO  [17:58:22.470] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 1/3)
  INFO  [17:58:22.486] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 2/3)
  INFO  [17:58:22.503] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 3/3)
  INFO  [17:58:22.519] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 1/3)
  INFO  [17:58:22.540] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 2/3)
  INFO  [17:58:22.561] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 3/3)
  INFO  [17:58:22.582] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 1/3)
  INFO  [17:58:22.627] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 2/3)
  INFO  [17:58:22.666] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 3/3)
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  INFO  [17:58:22.716] [mlr3] Finished benchmark
  Error: Global Friedman test non-significant (p > 0.05), try type = 'mean' instead.
  Execution halted

Package: mlr3tuning
Check: examples
New result: ERROR
  Running examples in ‘mlr3tuning-Ex.R’ failed
  The error most likely occurred in:
  
  > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
  > ### Name: mlr_tuners_internal
  > ### Title: Hyperparameter Tuning with Internal Tuning
  > ### Aliases: mlr_tuners_internal TunerBatchInternal
  > 
  > ### ** Examples
  > 
  > ## Don't show: 
  > if (mlr3misc::require_namespaces(c("mlr3learners", "xgboost"), quietly = TRUE)) withAutoprint({ # examplesIf
  + ## End(Don't show)
  + library(mlr3learners)
  + 
  + # Retrieve task
  + task = tsk("pima")
  + 
  + # Load learner and set search space
  + learner = lrn("classif.xgboost",
  +   nrounds = to_tune(upper = 1000, internal = TRUE),
  +   early_stopping_rounds = 10,
  +   validate = "test",
  +   eval_metric = "merror"
  + )
  + 
  + # Internal hyperparameter tuning on the pima indians diabetes data set
  + instance = tune(
  +   tnr("internal"),
  +   tsk("iris"),
  +   learner,
  +   rsmp("cv", folds = 3),
  +   msr("internal_valid_score", minimize = TRUE, select = "merror")
  + )
  + 
  + # best performing hyperparameter configuration
  + instance$result_learner_param_vals
  + 
  + instance$result_learner_param_vals$internal_tuned_values
  + ## Don't show: 
  + }) # examplesIf
  > library(mlr3learners)
  > task = tsk("pima")
  > learner = lrn("classif.xgboost", nrounds = to_tune(upper = 1000, internal = TRUE), 
  +     early_stopping_rounds = 10, validate = "test", eval_metric = "merror")
  > instance = tune(tnr("internal"), tsk("iris"), learner, rsmp("cv", folds = 3), 
  +     msr("internal_valid_score", minimize = TRUE, select = "merror"))
  INFO  [17:57:02.822] [bbotk] Starting to optimize 0 parameter(s) with '<TunerBatchInternal>' and '<TerminatorNone>'
  INFO  [17:57:02.825] [bbotk] Evaluating 1 configuration(s)
  INFO  [17:57:02.839] [mlr3] Running benchmark with 3 resampling iterations
  INFO  [17:57:02.865] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 1/3)
  INFO  [17:57:02.925] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 2/3)
  INFO  [17:57:02.979] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 3/3)
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: eval_metric, nthread, num_class. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in throw_err_or_depr_msg("Parameter '", match_old, "' has been renamed to '",  :
    Parameter 'watchlist' has been renamed to 'evals'. This warning will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: eval_metric, nthread, num_class. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in throw_err_or_depr_msg("Parameter '", match_old, "' has been renamed to '",  :
    Parameter 'watchlist' has been renamed to 'evals'. This warning will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: eval_metric, nthread, num_class. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in throw_err_or_depr_msg("Parameter '", match_old, "' has been renamed to '",  :
    Parameter 'watchlist' has been renamed to 'evals'. This warning will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning: Caught simpleError. Canceling all iterations ...
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: eval_metric, nthread, num_class. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in throw_err_or_depr_msg("Parameter '", match_old, "' has been renamed to '",  :
    Parameter 'watchlist' has been renamed to 'evals'. This warning will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
    Passed invalid function arguments: eval_metric, nthread, num_class. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
  Warning in throw_err_or_depr_msg("Parameter '", match_old, "' has been renamed to '",  :
    Parameter 'watchlist' has been renamed to 'evals'. This warning will become an error in a future version.
  Warning in check.custom.obj(params, objective) :
    Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
  Error in names(x) <- nm : attempt to set an attribute on NULL
  Calls: withAutoprint ... tryCatchList -> tryCatchOne -> <Anonymous> -> onError
  Execution halted
  Examples with CPU (user + system) or elapsed time > 5s
                          user system elapsed
  AutoTuner              5.757  0.231   5.991
  mlr3tuning.one_se_rule 5.244  0.016   5.309

Package: vetiver
Check: tests
New result: ERROR
    Running ‘testthat.R’ [18s/18s]
  Running the tests in ‘tests/testthat.R’ failed.
  Complete output:
    > library(testthat)
    > library(vetiver)
    > 
    > test_check("vetiver")
    Loading required package: ggplot2
    Loading required package: lattice
    
    Create a Model Card for your published model
    * Model Cards provide a framework for transparent, responsible reporting
    * Use the vetiver `.Rmd` template as a place to start
    This message is displayed once per session.
    This is mgcv 1.9-4. For overview type '?mgcv'.
    
    Attaching package: 'parsnip'
    
    The following object is masked from 'package:e1071':
    
        tune
    
    
    Attaching package: 'probably'
    
    The following objects are masked from 'package:base':
    
        as.factor, as.ordered
    
    
    Attaching package: 'tune'
    
    The following object is masked from 'package:e1071':
    
        tune
    
    The following object is masked from 'package:vetiver':
    
        load_pkgs
    
    
    Attaching package: 'rsample'
    
    The following object is masked from 'package:e1071':
    
        permutations
    
    The following object is masked from 'package:caret':
    
        calibration
    
    
    Attaching package: 'recipes'
    
    The following object is masked from 'package:stats':
    
        step
    
    Your rsconnect bundle has been created at:
    * /home/hornik/tmp/scratch/RtmpX1K48v/file4e1ef2649213f/bundle4e1ef13b10141.tar.gz
    Saving _problems/test-xgboost-9.R
    [ FAIL 1 | WARN 2 | SKIP 70 | PASS 221 ]
    
    ══ Skipped tests (70) ══════════════════════════════════════════════════════════
    • On CRAN (70): 'test-api.R:16:1', 'test-api.R:77:1', 'test-attach-pkgs.R:2:5',
      'test-attach-pkgs.R:7:5', 'test-attach-pkgs.R:12:5', 'test-caret.R:22:1',
      'test-caret.R:65:5', 'test-choose-version.R:4:5',
      'test-choose-version.R:33:1', 'test-create-ptype.R:41:1',
      'test-dashboard.R:13:5', 'test-gam.R:8:1', 'test-gam.R:60:5',
      'test-glm.R:7:1', 'test-glm.R:59:5', 'test-keras.R:1:1',
      'test-kproto.R:14:1', 'test-kproto.R:65:5', 'test-luz.R:1:1',
      'test-mlr3.R:3:1', 'test-mlr3.R:52:5', 'test-monitor.R:66:5',
      'test-monitor.R:72:5', 'test-monitor.R:79:5', 'test-monitor.R:124:5',
      'test-pin-read-write.R:3:1', 'test-pin-read-write.R:17:1',
      'test-pin-read-write.R:132:5', 'test-predict.R:1:1', 'test-probably.R:48:1',
      'test-probably.R:98:5', 'test-probably.R:109:1', 'test-probably.R:159:5',
      'test-probably.R:170:1', 'test-probably.R:220:5', 'test-probably.R:232:1',
      'test-probably.R:282:5', 'test-ranger.R:9:1', 'test-ranger.R:13:1',
      'test-ranger.R:62:5', 'test-recipe.R:14:1', 'test-recipe.R:58:5',
      'test-rsconnect.R:18:5', 'test-sagemaker.R:4:5', 'test-sagemaker.R:25:5',
      'test-sagemaker.R:49:1', 'test-sagemaker.R:77:1', 'test-sagemaker.R:98:1',
      'test-sagemaker.R:112:1', 'test-sagemaker.R:161:1', 'test-stacks.R:1:1',
      'test-tidymodels.R:21:1', 'test-tidymodels.R:71:5',
      'test-type-convert.R:15:1', 'test-type-convert.R:31:1',
      'test-type-convert.R:47:1', 'test-write-docker.R:5:5',
      'test-write-docker.R:17:5', 'test-write-docker.R:35:5',
      'test-write-docker.R:52:5', 'test-write-docker.R:65:5',
      'test-write-docker.R:81:5', 'test-write-docker.R:88:5',
      'test-write-plumber.R:4:5', 'test-write-plumber.R:17:5',
      'test-write-plumber.R:38:5', 'test-write-plumber.R:57:5',
      'test-write-plumber.R:71:5', 'test-write-plumber.R:84:5',
      'test-write-plumber.R:98:5'
    
    ══ Failed tests ════════════════════════════════════════════════════════════════
    ── Error ('test-xgboost.R:9:1'): (code run outside of `test_that()`) ───────────
    Error in `matrix(NA_real_, ncol = model$nfeatures, dimnames = list("", model$feature_names))`: non-numeric matrix extent
    Backtrace:
        ▆
     1. └─vetiver::vetiver_model(cars_xgb, "cars2") at test-xgboost.R:9:1
     2.   └─vetiver::vetiver_create_ptype(model, save_prototype, ...)
     3.     ├─vetiver::vetiver_ptype(model, ...)
     4.     └─vetiver:::vetiver_ptype.xgb.Booster(model, ...)
     5.       └─base::matrix(...)
    
    [ FAIL 1 | WARN 2 | SKIP 70 | PASS 221 ]
    Error:
    ! Test failures.
    Execution halted