tests/testthat/_snaps/logging.md

In tidymodels/tune: Tidy Tuning Tools

low-level messages

Code
  siren("a", "werewolf")
Condition
  Error in `match.arg()`:
  ! 'arg' should be one of "warning", "go", "danger", "success", "info"

Code
  siren("bat", "info")
Message
  i bat

Code
  siren("bat", "go")
Message
  > bat

Code
  siren("bat", "danger")
Message
  x bat

Code
  siren("bat", "warning")
Message
  ! bat

Code
  siren("bat", "success")
Message
  v bat

tune_log

Code
  tune_log(ctrl_t, rs, task = "cube", type = "go")
Message
  > Fold01: cube
Output
  NULL

Code
  tune_log(ctrl_t, NULL, task = "cube", type = "go")
Message
  > cube
Output
  NULL

Code
  tune_log(ctrl_t, rs, task = "cube", type = "success")
Message
  v Fold01: cube
Output
  NULL

log issues

Code
  problems_1 <- log_problems(note_1, ctrl_f, rs, "toledo", res_1, bad_only = FALSE)
Message
  x Fold01: toledo: Error in log("a"): non-numeric argument to mathematical function

Code
  problems_2 <- log_problems(note_1, ctrl_f, rs, "toledo", res_3, bad_only = FALSE)
Message
  ! Fold01: toledo: NaNs produced

catch and log issues

Code
  out_1 <- .catch_and_log(log("a"), control = ctrl_f, split_labels = rs, "toledo",
  bad_only = FALSE, notes = null)
Message
  x Fold01: toledo: Error in log("a"): non-numeric argument to mathematical function

Code
  out_3 <- .catch_and_log(log(-1), control = ctrl_f, split_labels = rs, "toledo",
  bad_only = FALSE, notes = null)
Message
  ! Fold01: toledo: NaNs produced

Code
  out_5 <- .catch_and_log(log("a"), control = ctrl_f, split_labels = NULL,
  "toledo", bad_only = FALSE, notes = null)
Message
  x toledo: Error in log("a"): non-numeric argument to mathematical function

Code
  out_6 <- .catch_and_log(log(-1), control = ctrl_f, split_labels = NULL,
  "toledo", bad_only = FALSE, notes = null)
Message
  ! toledo: NaNs produced

logging iterations

Code
  log_best(ctrl_t, 10, sc_1)
Message

  -- Iteration 10 ----------------------------------------------------------------

  i Current best:       0.8=7 (@iter 2)
Output
  NULL

logging search info

Code
  check_and_log_flow(ctrl_t, tb_1 %>% mutate(.mean = .mean * NA))
Message
  x Skipping to next iteration
Condition
  Error:
  ! no loop for break/next, jumping to top level

Code
  check_and_log_flow(ctrl_t, tb_1 %>% mutate(.mean = .mean * NA) %>% slice(1))
Message
  x Halting search
Condition
  Error:
  ! no loop for break/next, jumping to top level

current results

Code
  log_progress(ctrl_t, tb_2, maximize = FALSE, objective = "a")
Message
  (x) Newest results:   a=4 (+/-0.4)

Code
  log_progress(ctrl_t, tb_2, maximize = TRUE, objective = "b")
Message
  <3 Newest results:    b=8 (+/-0.8)

Code
  log_progress(ctrl_t, tb_2, maximize = TRUE, objective = "a")
Message
  <3 Newest results:    a=4 (+/-0.4)

show parameters

Code
  param_msg(ctrl_t, iris[1, 4:5])
Message
  i Petal.Width=0.2, Species=setosa

acquisition functions

Code
  acq_summarizer(ctrl_t, 1, conf_bound(I))
Message
  i Kappa value: 1

Code
  acq_summarizer(ctrl_t, 1, exp_improve(I))
Message
  i Trade-off value: 1

Code
  acq_summarizer(ctrl_t, 1, prob_improve(I))
Message
  i Trade-off value: 1

interactive logger works (fit_resamples, warning + error)

Code
  res_fit <- fit_resamples(parsnip::nearest_neighbor("regression", "kknn"),
  Sale_Price ~ ., rsample::vfold_cv(modeldata::ames[, c(72, 40:45)], 5), control = control_resamples(
    extract = function(x) {
      raise_warning()
      raise_error()
    }))
Message
  > A | warning: ope! yikes.
  > B | error:   AHHhH

Code
  catalog_summary_test
Output
  A: x5   B: x5

interactive logger works (fit_resamples, rlang warning + error)

Code
  res_fit <- fit_resamples(parsnip::nearest_neighbor("regression", "kknn"),
  Sale_Price ~ ., rsample::vfold_cv(modeldata::ames[, c(72, 40:45)], 5), control = control_resamples(
    extract = function(x) {
      raise_warning_rl()
      raise_error_rl()
    }))
Message
  > A | warning: ope! yikes. (but rlang)
  > B | error:   AHHhH (but rlang)

Code
  catalog_summary_test
Output
  A: x5   B: x5

interactive logger works (fit_resamples, multiline)

Code
  res_fit <- fit_resamples(parsnip::nearest_neighbor("regression", "kknn"),
  Sale_Price ~ ., rsample::vfold_cv(modeldata::ames[, c(72, 40:45)], 5), control = control_resamples(
    extract = raise_multiline_conditions))
Message
  > A | warning: hmmm what's happening
  > B | error:   aHHHksdjvndiuf

Code
  catalog_summary_test
Output
  A: x5   B: x5

interactive logger works (fit_resamples, occasional error)

Code
  res_fit <- fit_resamples(parsnip::nearest_neighbor("regression", "kknn"),
  Sale_Price ~ ., rsample::vfold_cv(modeldata::ames[, c(72, 40:45)], 5), control = control_resamples(
    extract = later))
Message
  > A | error:   this errors now! ha!

Code
  catalog_summary_test
Output
  A: x2

interactive logger works (fit_resamples, occasional errors)

Code
  res_fit <- fit_resamples(parsnip::nearest_neighbor("regression", "kknn"),
  Sale_Price ~ ., rsample::vfold_cv(modeldata::ames[, c(72, 40:45)], 10),
  control = control_resamples(extract = function(x) {
    once()
    later()
  }))
Message
  > A | error:   oh no
  > B | error:   this errors now! ha!

Code
  catalog_summary_test
Output
  A: x1   B: x6

interactive logger works (fit_resamples, many distinct errors)

Code
  res_fit <- fit_resamples(parsnip::nearest_neighbor("regression", "kknn"),
  Sale_Price ~ ., rsample::vfold_cv(modeldata::ames[, c(72, 40:45)], 5), control = control_resamples(
    extract = numbered))
Message
  > A | error:   error number 1
  > B | error:   error number 2
  > C | error:   error number 3
  > D | error:   error number 4
  > E | error:   error number 5

Code
  catalog_summary_test
Output
  A: x1   B: x1   C: x1   D: x1   E: x1

interactive logger works (tune grid, error)

Code
  res_fit <- tune_grid(parsnip::nearest_neighbor("regression", "kknn",
    dist_power = tune()), Sale_Price ~ ., rsample::vfold_cv(modeldata::ames[, c(
    72, 40:45)], 5), grid = 5, control = control_grid(extract = raise_error))
Message
  > A | error:   AHHhH

Code
  catalog_summary_test
Output
  A: x25

interactive logger works (bayesian, error)

Code
  res_grid <- tune_bayes(parsnip::nearest_neighbor("regression", "kknn",
    dist_power = tune()), Sale_Price ~ ., rsample::vfold_cv(modeldata::ames[, c(
    72, 40:45)], 5), initial = 5, iter = 5, control = control_bayes(extract = raise_error))
Message
  > A | error:   AHHhH

Code
  catalog_summary_test
Output
  A: x50

tidymodels/tune documentation built on April 12, 2025, 9:40 p.m.