transition from add_tailor(prop) and method to fit.workflow(calibration)

DESCRIPTION

@@ -42,7 +42,6 @@ Suggests:
     methods,
     modeldata (>= 1.0.0),
     recipes (>= 1.0.10.9000),
-    rsample (>= 1.2.1.9000),
     rmarkdown,
     testthat (>= 3.0.0)
 VignetteBuilder: 
@@ -54,7 +53,6 @@ Config/Needs/website:
     tidyverse/tidytemplate,
     yardstick
 Remotes:
-    tidymodels/rsample,
     tidymodels/recipes,
     tidymodels/parsnip,
     tidymodels/tailor,

R/post-action-tailor.R

@@ -44,7 +44,7 @@
 #' be used to train the postprocessor.
 #'
 #' In some situations, randomly splitting `fit.workflow(data)` (with
-#' [rsample::initial_split()], for example) is sufficient to prevent data
+#' `rsample::initial_split()`, for example) is sufficient to prevent data
 #' leakage. However, `fit.workflow(data)` could also have arisen as:
 #'
 #' ```
@@ -59,7 +59,7 @@
 #' datasets, resulting in the preprocessor and model generating predictions on
 #' rows they've seen before. Similarly problematic situations could arise in the
 #' context of other resampling situations, like time-based splits.
-#' In general, use the [rsample::inner_split()] function to prevent data
+#' In general, use the `rsample::inner_split()` function to prevent data
 #' leakage when resampling; when workflows with postprocessors that require
 #' training are passed to the tune package, this is handled internally.
 #'

R/utils.R

@@ -40,20 +40,6 @@ validate_tailor_available <- function(..., call = caller_env()) {
   invisible()
 }
 
-validate_rsample_available <- function(..., call = caller_env()) {
-  check_dots_empty()
-
-  if (!requireNamespace("rsample", quietly = TRUE)) {
-    cli_abort(
-      "The {.pkg rsample} package must be available to add a tailor that
-       requires training.",
-      call = call
-    )
-  }
-
-  invisible()
-}
-
 # ------------------------------------------------------------------------------
 
 # https://github.com/r-lib/tidyselect/blob/10e00cea2fff3585fc827b6a7eb5e172acadbb2f/R/utils.R#L109

tests/testthat/test-post-action-tailor.R

@@ -109,7 +109,6 @@ test_that("postprocessor fit aligns with manually fitted version (no calibration
 
 test_that("postprocessor fit aligns with manually fitted version (with calibration)", {
   skip_if_not_installed("modeldata")
-  skip_if_not_installed("rsample")
 
   # create example data
   y <- seq(0, 7, .1)