add eval_time_target as an attribute (#782)

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: tune
 Title: Tidy Tuning Tools
-Version: 1.1.2.9003
+Version: 1.1.2.9004
 Authors@R: c(
     person("Max", "Kuhn", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0003-2402-136X")),

NAMESPACE

@@ -139,6 +139,7 @@ export(.estimate_metrics)
 export(.filter_perf_metrics)
 export(.get_extra_col_names)
 export(.get_fingerprint)
+export(.get_tune_eval_time_target)
 export(.get_tune_eval_times)
 export(.get_tune_metric_names)
 export(.get_tune_metrics)

NEWS.md

@@ -18,7 +18,7 @@
 
 * Improves documentation related to the hyperparameters associated with extracted objects that are generated from submodels. See the "Extracting with submodels" section of `?collect_extracts` to learn more.
 
-* An `eval_time` attribute was added to tune objects. There is also a `.get_tune_eval_times()` function.
+* `eval_time` and `eval_time_target` attribute was added to tune objects. There are also  `.get_tune_eval_times()` and `.get_tune_eval_time_target()` functions.
 
 * `augment()` methods to `tune_results`, `resample_results`, and `last_fit` objects now always returns tibbles (#759).
 

R/compat-vctrs-helpers.R

@@ -17,6 +17,7 @@ new_tune_results_from_template <- function(x, to) {
     parameters = attrs$parameters,
     metrics = attrs$metrics,
     eval_time = attrs$eval_time,
+    eval_time_target = attrs$eval_time_target,
     outcomes = attrs$outcomes,
     rset_info = attrs$rset_info
   )
@@ -107,6 +108,7 @@ new_resample_results_from_template <- function(x, to) {
     parameters = attrs$parameters,
     metrics = attrs$metrics,
     eval_time = attrs$eval_time,
+    eval_time_target = attrs$eval_time_target,
     outcomes = attrs$outcomes,
     rset_info = attrs$rset_info
   )
@@ -137,6 +139,7 @@ new_iteration_results_from_template <- function(x, to) {
     parameters = attrs$parameters,
     metrics = attrs$metrics,
     eval_time = attrs$eval_time,
+    eval_time_target = attrs$eval_time_target,
     outcomes = attrs$outcomes,
     rset_info = attrs$rset_info,
     workflow = attrs$workflow

R/iteration_results.R

@@ -33,6 +33,7 @@ new_iteration_results <-
            parameters,
            metrics,
            eval_time,
+           eval_time_target,
            outcomes = character(0),
            rset_info,
            workflow) {
@@ -41,6 +42,7 @@ new_iteration_results <-
       parameters = parameters,
       metrics = metrics,
       eval_time = eval_time,
+      eval_time_target = eval_time_target,
       outcomes = outcomes,
       rset_info = rset_info,
       workflow = workflow,

R/resample.R

@@ -161,6 +161,7 @@ resample_workflow <- function(workflow, resamples, metrics, control,
     parameters = attributes$parameters,
     metrics = attributes$metrics,
     eval_time = attributes$eval_time,
+    eval_time_target = NULL,
     outcomes = attributes$outcomes,
     rset_info = attributes$rset_info,
     workflow = attributes$workflow

R/resample_results.R

@@ -19,6 +19,7 @@ new_resample_results <-
            parameters,
            metrics,
            eval_time,
+           eval_time_target = NULL,
            outcomes = character(0),
            rset_info,
            workflow = NULL) {
@@ -27,6 +28,7 @@ new_resample_results <-
       parameters = parameters,
       metrics = metrics,
       eval_time = eval_time,
+      eval_time_target = eval_time_target,
       outcomes = outcomes,
       rset_info = rset_info,
       workflow = workflow,

R/tune_bayes.R

@@ -306,6 +306,7 @@ tune_bayes_workflow <-
         parameters = param_info,
         metrics = metrics,
         eval_time = eval_time,
+        eval_time_target = metrics_time,
         outcomes = outcomes,
         rset_info = rset_info,
         workflow = NULL
@@ -479,6 +480,7 @@ tune_bayes_workflow <-
         parameters = param_info,
         metrics = metrics,
         eval_time = eval_time,
+        eval_time_target = metrics_time,
         outcomes = outcomes,
         rset_info = rset_info,
         workflow = workflow_output

R/tune_grid.R

@@ -379,6 +379,7 @@ tune_grid_workflow <- function(workflow,
     parameters = pset,
     metrics = metrics,
     eval_time = eval_time,
+    eval_time_target = NULL,
     outcomes = outcomes,
     rset_info = rset_info,
     workflow = workflow

R/tune_results.R

@@ -102,6 +102,7 @@ new_tune_results <-
            parameters,
            metrics,
            eval_time,
+           eval_time_target,
            outcomes = character(0),
            rset_info,
            ...,
@@ -111,6 +112,7 @@ new_tune_results <-
       parameters = parameters,
       metrics = metrics,
       eval_time = eval_time,
+      eval_time_target = eval_time_target,
       outcomes = outcomes,
       rset_info = rset_info,
       ...,

R/utils.R

@@ -176,6 +176,17 @@ new_bare_tibble <- function(x, ..., class = character()) {
   res
 }
 
+#' @export
+#' @rdname tune_accessor
+.get_tune_eval_time_target <- function(x) {
+  x <- attributes(x)
+  if (any(names(x) == "eval_time_target")) {
+    res <- x$eval_time_target
+  } else {
+    res <- NULL
+  }
+  res
+}
 
 #' @export
 #' @rdname tune_accessor

tests/testthat/test-bayes.R

@@ -54,6 +54,7 @@ test_that("tune recipe only", {
   expect_false(identical(num_comp, expr(tune())))
   expect_true(res_workflow$trained)
   expect_null(.get_tune_eval_times(res))
+  expect_null(.get_tune_eval_time_target(res))
 
   set.seed(1)
   expect_error(

tests/testthat/test-grid.R

@@ -28,6 +28,7 @@ test_that("tune recipe only", {
   expect_false(identical(num_comp, expr(tune())))
   expect_true(res_workflow$trained)
   expect_null(.get_tune_eval_times(res))
+  expect_null(.get_tune_eval_time_target(res))
 })
 
 # ------------------------------------------------------------------------------

tests/testthat/test-last-fit.R

@@ -26,6 +26,7 @@ test_that("formula method", {
     nrow(rsample::testing(split))
   )
   expect_null(.get_tune_eval_times(res))
+  expect_null(.get_tune_eval_time_target(res))
 
 })
 

tests/testthat/test-resample.R

@@ -15,6 +15,7 @@ test_that("`fit_resamples()` returns a `resample_result` object", {
   expect_equal(result, .Last.tune.result)
 
   expect_null(.get_tune_eval_times(result))
+  expect_null(.get_tune_eval_time_target(result))
 })
 
 test_that("can use `fit_resamples()` with a formula", {