Merge branch 'main' into callback

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: mlr3tuning
 Title: Hyperparameter Optimization for 'mlr3'
-Version: 1.2.1.9000
+Version: 1.3.0.9000
 Authors@R: c(
     person("Marc", "Becker", , "[email protected]", role = c("cre", "aut"),
            comment = c(ORCID = "0000-0002-8115-0400")),
@@ -29,7 +29,7 @@ Depends:
     paradox (>= 1.0.1),
     R (>= 3.1.0)
 Imports:
-    bbotk (>= 1.4.1),
+    bbotk (>= 1.5.0),
     checkmate (>= 2.0.0),
     data.table,
     lgr,
@@ -39,7 +39,7 @@ Suggests:
     adagio,
     future,
     GenSA,
-    irace (>= 4.0.0),
+    irace (>= 4.1.0),
     knitr,
     mlflow,
     mlr3learners (>= 0.7.0),

NEWS.md

@@ -1,6 +1,9 @@
 # mlr3tuning (development version)
 
-perf: save models on worker only when requested in `ObjectiveTuningAsync`.
+# mlr3tuning 1.3.0
+
+* feat: Save `ArchiveAsyncTuning` to a `data.table` with `ArchiveAsyncTuningFrozen`.
+* perf: Save models on worker only when requested in `ObjectiveTuningAsync`.
 
 # mlr3tuning 1.2.1
 

R/ArchiveAsyncTuningFrozen.R

@@ -8,7 +8,7 @@
 #'
 #' @section S3 Methods:
 #' * `as.data.table(archive)`\cr
-#'   [ArchiveAsync] -> [data.table::data.table()]\cr
+#'   [ArchiveAsyncTuningFrozen] -> [data.table::data.table()]\cr
 #'   Returns a tabular view of all performed function calls of the Objective.
 #'   The `x_domain` column is unnested to separate columns.
 #'

R/TunerBatchIrace.R

@@ -53,6 +53,8 @@
 #'
 #' # load learner and set search space
 #' learner = lrn("classif.rpart", cp = to_tune(1e-04, 1e-1, logscale = TRUE))
+#'
+#' # runtime of the example is too long
 #' \donttest{
 #' # hyperparameter tuning on the pima indians diabetes data set
 #' instance = tune(
@@ -61,7 +63,7 @@
 #'   learner = learner,
 #'   resampling = rsmp("holdout"),
 #'   measure = msr("classif.ce"),
-#'   term_evals = 42
+#'   term_evals = 200
 #' )
 #'
 #' # best performing hyperparameter configuration

R/mlr_callbacks.R

@@ -433,7 +433,7 @@ load_callback_one_se_rule = function() {
 #' @name mlr3tuning.async_freeze_archive
 #'
 #' @description
-#' This [CallbackAsync] freezes the [ArchiveAsync] to [ArchiveAsyncFrozen] after the optimization has finished.
+#' This [CallbackAsyncTuning] freezes the [ArchiveAsyncTuning] to [ArchiveAsyncTuningFrozen] after the optimization has finished.
 #'
 #' @examples
 #' clbk("mlr3tuning.async_freeze_archive")

tests/testthat/test_TunerBatchIrace.R

@@ -31,7 +31,7 @@ test_that("TunerIrace works with dependencies", {
     learner = lrn("regr.rpart"),
     resampling = rsmp("holdout"),
     measures = msr("regr.mse"),
-    terminator = trm("evals", n_evals = 96),
+    terminator = trm("evals", n_evals = 200),
     search_space = search_space)
   tuner = tnr("irace")
   x = capture.output({tuner$optimize(instance)})
@@ -50,7 +50,7 @@ test_that("TunerIrace works with logical parameters", {
     learner = lrn("regr.rpart"),
     resampling = rsmp("holdout"),
     measures = msr("regr.mse"),
-    terminator = trm("evals", n_evals = 96),
+    terminator = trm("evals", n_evals = 200),
     search_space = search_space)
   tuner = tnr("irace")
   x = capture.output({tuner$optimize(instance)})
@@ -59,7 +59,7 @@ test_that("TunerIrace works with logical parameters", {
 
 test_that("TunerIrace uses digits", {
   search_space = ps(cp = p_dbl(lower = pi * 1e-20, upper = 5.242e12 / 1e13))
- instance = ti(
+  instance = ti(
     task = tsk("mtcars"),
     learner = lrn("regr.rpart"),
     resampling = rsmp("holdout"),
@@ -78,7 +78,7 @@ test_that("TunerIrace works with unnamed discrete values", {
     learner = lrn("regr.rpart"),
     resampling = rsmp("holdout"),
     measures = msr("regr.mse"),
-    terminator = trm("evals", n_evals = 96),
+    terminator = trm("evals", n_evals = 200),
     search_space = search_space)
   tuner = tnr("irace")
   x = capture.output({expect_data_table(tuner$optimize(instance))})