tests/testthat/_snaps/compute_metrics.md

In tune: Tidy Tuning Tools

metrics argument works (differing class metric types)

Code
  compute_metrics(res_auc, m_set_acc)
Condition
  Error in `compute_metrics()`:
  ! The supplied `metrics` argument has metrics of type "class", while the metrics used to generate predictions only used "prob" metrics.
  i To save predictions for class metrics, generate `x` with metrics of that type.

Code
  compute_metrics(res_acc, m_set_auc)
Condition
  Error in `compute_metrics()`:
  ! The supplied `metrics` argument has metrics of type "prob", while the metrics used to generate predictions only used "class" metrics.
  i To save predictions for prob metrics, generate `x` with metrics of that type.

metrics argument works (iterative tuning)

Code
  set.seed(1)
  res_rmse <- tune_bayes(nearest_neighbor("regression", neighbors = tune()), mpg ~
    ., vfold_cv(mtcars, v = 3), metrics = m_set_rmse, control = tune::control_bayes(
    save_pred = TRUE), iter = 2, initial = 3)

Code
  set.seed(1)
  res_both <- tune_bayes(nearest_neighbor("regression", neighbors = tune()), mpg ~
    ., vfold_cv(mtcars, v = 3), metrics = m_set_both, control = tune::control_bayes(
    save_pred = TRUE), iter = 2, initial = 3)

errors informatively with bad input

Code
  compute_metrics(res_rmse, metric_set(rsq))
Condition
  Error in `compute_metrics()`:
  ! `x` must have been generated with the control argument `save_pred = TRUE`.

Code
  compute_metrics("boop", metric_set(rsq))
Condition
  Error in `compute_metrics()`:
  ! No `compute_metrics()` method exists for a string.

Code
  compute_metrics(res_rmse_save_pred, "wheee")
Condition
  Error in `compute_metrics()`:
  ! `metrics` must be a metric set.

tune documentation built on April 17, 2026, 5:07 p.m.