Merge branch 'tidymodels:main' into variable-fold-weights

Author: tjburch

.Rbuildignore

@@ -18,3 +18,4 @@ _cache$
 ^LICENSE\.md$
 ^CODE_OF_CONDUCT\.md$
 ^man-roxygen$
+^\.vscode$

.github/workflows/R-CMD-check.yaml

@@ -6,9 +6,9 @@
 # usethis::use_github_action("check-standard") will install it.
 on:
   push:
-    branches: [main, master]
+    branches: [main, master, 'melodie-switch']
   pull_request:
-    branches: [main, master]
+    branches: [main, master, 'melodie-switch']
 
 name: R-CMD-check.yaml
 

.github/workflows/test-coverage.yaml

@@ -2,9 +2,9 @@
 # Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
 on:
   push:
-    branches: [main, master]
+    branches: [main, master, 'melodie-switch']
   pull_request:
-    branches: [main, master]
+    branches: [main, master, 'melodie-switch']
 
 name: test-coverage.yaml
 

.vscode/settings.json

@@ -0,0 +1,5 @@
+{
+    "cSpell.words": [
+        "mirai"
+    ]
+}

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: tune
 Title: Tidy Tuning Tools
-Version: 1.3.0.9001
+Version: 1.3.0.9005
 Authors@R: c(
     person("Max", "Kuhn", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0003-2402-136X")),
@@ -19,22 +19,19 @@ Depends:
 Imports:
     cli (>= 3.3.0),
     dials (>= 1.3.0.9000),
-    doFuture (>= 1.0.0),
     dplyr (>= 1.1.0),
-    foreach,
-    future (>= 1.33.0),
-    future.apply,
     generics (>= 0.1.2),
     ggplot2,
     glue (>= 1.6.2),
     GPfit,
     hardhat (>= 1.4.0.9002),
     lifecycle (>= 1.0.0),
+    parallel,
     parsnip (>= 1.2.1.9003),
     purrr (>= 1.0.0),
     recipes (>= 1.1.0.9001),
     rlang (>= 1.1.4),
-    rsample (>= 1.2.1.9000),
+    rsample (>= 1.3.0.9003),
     tailor,
     tibble (>= 3.1.0),
     tidyr (>= 1.2.0),
@@ -47,10 +44,13 @@ Suggests:
     C50,
     censored (>= 0.3.0),
     covr,
+    future (>= 1.33.0),
+    future.apply,
     kernlab,
     kknn,
     knitr,
     mgcv,
+    mirai (>= 2.4.0),
     modeldata,
     probably,
     scales,
@@ -61,6 +61,7 @@ Suggests:
     xgboost,
     xml2
 Remotes:
+    tidymodels/rsample,
     tidymodels/tailor,
     tidymodels/workflows
 Config/Needs/website: pkgdown, tidymodels, kknn, doParallel, doFuture,

NAMESPACE

@@ -49,9 +49,6 @@ S3method(last_fit,workflow)
 S3method(load_pkgs,character)
 S3method(load_pkgs,model_spec)
 S3method(load_pkgs,workflow)
-S3method(melodie_grid,default)
-S3method(melodie_grid,model_spec)
-S3method(melodie_grid,workflow)
 S3method(merge,model_spec)
 S3method(merge,recipe)
 S3method(min_grid,C5_rules)
@@ -74,6 +71,7 @@ S3method(outcome_names,recipe)
 S3method(outcome_names,terms)
 S3method(outcome_names,tune_results)
 S3method(outcome_names,workflow)
+S3method(outcome_names,workflow_variables)
 S3method(parameters,model_spec)
 S3method(parameters,recipe)
 S3method(parameters,workflow)
@@ -139,7 +137,6 @@ S3method(vec_restore,iteration_results)
 S3method(vec_restore,resample_results)
 S3method(vec_restore,tune_results)
 export(.catch_and_log)
-export(.catch_and_log_fit)
 export(.config_key_from_metrics)
 export(.estimate_metrics)
 export(.filter_perf_metrics)
@@ -220,7 +217,6 @@ export(is_workflow)
 export(last_fit)
 export(load_pkgs)
 export(maybe_choose_eval_time)
-export(melodie_grid)
 export(message_wrap)
 export(metrics_info)
 export(min_grid)
@@ -295,10 +291,6 @@ importFrom(dplyr,slice)
 importFrom(dplyr,starts_with)
 importFrom(dplyr,ungroup)
 importFrom(dplyr,vars)
-importFrom(foreach,"%dopar%")
-importFrom(foreach,foreach)
-importFrom(foreach,getDoParName)
-importFrom(future.apply,future_lapply)
 importFrom(generics,augment)
 importFrom(generics,min_grid)
 importFrom(generics,required_pkgs)

NEWS.md

@@ -1,9 +1,28 @@
 # tune (development version)
 
+## Changes to `tune_grid()`. 
+
+* A major rewrite and refactor of the underlying code that runs `tune_grid()` was made. 
+
+* The pattern of `.config` values has changed from `Preprocessor{num}_Model{num}` to `pre{num}_mod{num}_post{num}`. 
+
 * The package will now log a backtrace for errors and warnings that occur during tuning. When a tuning process encounters issues, see the new `trace` column in the `collect_notes(.Last.tune.result)` output to find precisely where the error occurred (#873).
 
 * Post-processing: new `schedule_grid()` for scheduling a grid including post-processing (#988).
 
+## Other Changes
+
+* Introduced support for parallel processing with mirai in addition to the currently supported framework future. See `?parallelism` to learn more (#1028).
+
+* Sequential and parallel processing all use the same L'Ecuyer-CMRG seeds (conditional on `parallel_over`) (#1033). 
+
+* `int_pctl()` now includes an option (`keep_replicates`) to retain the individual bootstrap estimates. It also processes the resamples more efficiently (#1000).
+
+## Breaking Changes
+
+* The `foreach` package is no longer supported. Instead, use the future or mirai packages.  
+* The parallel backend(s) and the methods of constructing seeds for workers have changed. There will be a lack of reproducibility between objects created in this version of tune and previous versions.
+
 # tune 1.3.0
 
 * The package will now warn when parallel processing has been enabled with foreach but not with future. See [`?parallelism`](https://tune.tidymodels.org/dev/reference/parallelism.html) to learn more about transitioning your code to future (#878, #866). The next version of tune will move to a pure future implementation. 

R/0_imports.R

@@ -20,10 +20,8 @@
 #' @importFrom cli cli_alert_danger cli_alert_info cli_alert_warning
 #' @importFrom cli cli_alert_success cli_alert
 #' @importFrom cli cli_inform cli_warn cli_abort qty
-#' @importFrom foreach foreach getDoParName %dopar%
 #' @importFrom tibble obj_sum size_sum
 #' @import rlang
-#' @importFrom future.apply future_lapply
 
 # ------------------------------------------------------------------------------
 # Only a small number of functions in workflows.

R/case_weights.R

@@ -61,10 +61,19 @@ extract_case_weights <- function(data, workflow) {
   }
 
   loc <- eval_select_case_weights(col, data)
+  if (length(loc) != 1) {
+    # Can't happen now, make sure it doesn't happen in the future
+    cli::cli_abort("Only a single case weight column is allowed. {length(loc)}
+                   were found: {.val {names(loc)}}.")
+  }
 
-  case_weights <- data[[loc]]
+  if (!tibble::is_tibble(data)) {
+    data <- tibble::as_tibble(data)
+  }
+  case_weights <- data[, loc]
+  case_weights <- stats::setNames(case_weights, case_weights_column_name())
 
-  if (!hardhat::is_case_weights(case_weights)) {
+  if (!hardhat::is_case_weights(data[[names(loc)]])) {
     cli::cli_abort(
       "Case weights must be a supported case weights type, as determined by
       {.fn hardhat::is_case_weights}."

R/checks.R

@@ -190,7 +190,7 @@ check_parameters <- function(wflow, pset = NULL, data, grid_names = character(0)
       cli::format_inline(
         "Creating pre-processing data to finalize {num_unk} unknown parameter{?s}: {.val {unk_names}}")
 
-    tune_log(list(verbose = TRUE), split_labels = NULL, msg, type = "info")
+    tune_log(list(verbose = TRUE), split_labels = NULL, task = msg, type = "info")
 
     x <- workflows::.fit_pre(wflow, data)$pre$mold$predictors
     pset$object <- purrr::map(pset$object, dials::finalize, x = x)
@@ -436,7 +436,7 @@ check_initial <- function(x,
     if (ctrl$verbose) {
       message()
       msg <- cli::format_inline(" Generating a set of {nrow(x)} initial parameter results")
-      tune_log(ctrl, split_labels = NULL, msg, type = "go")
+      tune_log(ctrl, split_labels = NULL, task = msg, type = "go")
     }
 
     grid_ctrl <- ctrl
@@ -452,7 +452,7 @@ check_initial <- function(x,
     )
 
     if (ctrl$verbose) {
-      tune_log(ctrl, split_labels = NULL, "Initialization complete", type = "success")
+      tune_log(ctrl, split_labels = NULL, task = "Initialization complete", type = "success")
       message()
     }
   } else {
@@ -497,16 +497,6 @@ check_initial <- function(x,
   x
 }
 
-get_objective_name <- function(x, metrics) {
-  if (is.null(x)) {
-    metric_data <- metrics_info(metrics)
-    x <- metric_data$.metric[1]
-  } else {
-    # check for a name or acquisition function
-  }
-  x
-}
-
 # ------------------------------------------------------------------------------
 
 check_class_or_null <- function(x, cls = "numeric") {