Workflows examples

DESCRIPTION

@@ -18,7 +18,8 @@ Imports:
     tibble,    
     purrr,
     dplyr,
-    cli
+    cli,
+    recipes
 Suggests: 
     testthat (>= 3.0.0),
     modeldata,

NAMESPACE

@@ -1,5 +1,8 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(bake,step_collapse)
+S3method(prep,step_collapse)
+S3method(print,step_collapse)
 export(compile_keras_grid)
 export(create_keras_functional_spec)
 export(create_keras_sequential_spec)
@@ -24,6 +27,7 @@ export(register_keras_loss)
 export(register_keras_metric)
 export(register_keras_optimizer)
 export(remove_keras_spec)
+export(step_collapse)
 importFrom(cli,cli_alert_danger)
 importFrom(cli,cli_alert_info)
 importFrom(cli,cli_alert_success)
@@ -37,6 +41,8 @@ importFrom(dplyr,filter)
 importFrom(dplyr,select)
 importFrom(keras3,to_categorical)
 importFrom(parsnip,update_dot_check)
+importFrom(recipes,bake)
+importFrom(recipes,prep)
 importFrom(rlang,arg_match)
 importFrom(rlang,dots_list)
 importFrom(rlang,enquos)

R/register_core_model.R

@@ -21,6 +21,7 @@ register_core_model <- function(model_name, mode) {
   parsnip::set_model_mode(model_name, mode)
   parsnip::set_model_engine(model_name, mode, "keras")
   parsnip::set_dependency(model_name, "keras", "keras3")
+  parsnip::set_dependency(model_name, "keras", "kerasnip")
 
   parsnip::set_encoding(
     model = model_name,

R/step_collapse.R

@@ -0,0 +1,141 @@
+#' Collapse Predictors into a single list-column
+#'
+#' `step_collapse()` creates a a *specification* of a recipe step that will
+#'  convert a group of predictors into a single list-column. This is useful
+#'  for custom models that need the predictors in a different format.
+#'
+#' @param recipe A recipe object. The step will be added to the sequence of
+#'   operations for this recipe.
+#' @param ... One or more selector functions to choose which variables are
+#'   affected by the step. See `[selections()]` for more details. For the `tidy`
+#'   method, these are not currently used.
+#' @param role For model terms created by this step, what analysis role should
+#'   they be assigned?. By default, the new columns are used as predictors.
+#' @param trained A logical to indicate if the quantities for preprocessing
+#'   have been estimated.
+#' @param columns A character string of the selected variable names. This is
+#'   `NULL` until the step is trained by `[prep.recipe()]`.
+#' @param new_col A character string for the name of the new list-column. The
+#'   default is "predictor_matrix".
+#' @param skip A logical. Should the step be skipped when the recipe is
+#'   baked by `[bake.recipe()]`? While all operations are baked when `prep` is run,
+#'   skipping when `bake` is run may be other times when it is desirable to
+#'   skip a processing step.
+#' @param id A character string that is unique to this step to identify it.
+#'
+#' @return An updated version of `recipe` with the new step added to the
+#'   sequence of existing steps (if any). For the `tidy` method, a tibble with
+#'   columns `terms` which is the columns that are affected and `value` which is
+#'   the type of collapse.
+#'
+#' @examples
+#' library(recipes)
+#'
+#' # 2 predictors
+#' dat <- data.frame(
+#'   x1 = 1:10,
+#'   x2 = 11:20,
+#'   y = 1:10
+#' )
+#'
+#' rec <- recipe(y ~ ., data = dat) %>%
+#'   step_collapse(x1, x2, new_col = "pred") %>%
+#'   prep()
+#'
+#' bake(rec, new_data = NULL)
+#' @importFrom recipes prep bake
+#' @export
+step_collapse <- function(
+  recipe,
+  ...,
+  role = "predictor",
+  trained = FALSE,
+  columns = NULL,
+  new_col = "predictor_matrix",
+  skip = FALSE,
+  id = recipes::rand_id("collapse")
+) {
+  recipes::add_step(
+    recipe,
+    step_collapse_new(
+      terms = enquos(...),
+      role = role,
+      trained = trained,
+      columns = columns,
+      new_col = new_col,
+      skip = skip,
+      id = id
+    )
+  )
+}
+
+step_collapse_new <- function(
+  terms,
+  role,
+  trained,
+  columns,
+  new_col,
+  skip,
+  id
+) {
+  recipes::step(
+    subclass = "collapse",
+    terms = terms,
+    role = role,
+    trained = trained,
+    columns = columns,
+    new_col = new_col,
+    skip = skip,
+    id = id
+  )
+}
+
+#' @export
+prep.step_collapse <- function(x, training, info = NULL, ...) {
+  col_names <- recipes::recipes_eval_select(x$terms, training, info)
+
+  step_collapse_new(
+    terms = x$terms,
+    role = x$role,
+    trained = TRUE,
+    columns = col_names,
+    new_col = x$new_col,
+    skip = x$skip,
+    id = x$id
+  )
+}
+
+#' @export
+bake.step_collapse <- function(object, new_data, ...) {
+  recipes::check_new_data(object$columns, object, new_data)
+
+  rows_list <- apply(
+    new_data[, object$columns, drop = FALSE],
+    1,
+    function(row) matrix(row, nrow = 1),
+    simplify = FALSE
+  )
+
+  new_data[[object$new_col]] <- rows_list
+
+  # drop original predictor columns
+  new_data <- new_data[, setdiff(names(new_data), object$columns), drop = FALSE]
+
+  new_data
+}
+
+#' @export
+print.step_collapse <- function(x, ...) {
+  if (is.null(x$columns)) {
+    cat("Collapse predictors into list-column (unprepped)\\n")
+  } else {
+    cat(
+      "Collapse predictors into list-column:",
+      paste(x$columns, collapse = ", "),
+      " -> ",
+      x$new_col,
+      "\\n"
+    )
+  }
+  invisible(x)
+}

_pkgdown.yml

@@ -19,6 +19,8 @@ guides:
     contents:
       - sequential_model
       - functional_api
+      - workflows_sequential
+      - workflows_functional
 
 # examples:
 
@@ -54,6 +56,12 @@ reference:
       - extract_keras_model
       - keras_evaluate
 
+  - title: "Custom recipe steps"
+    desc: >
+      Custom stpes for recipe which uses kerasnip models specifications
+    contents:
+      - step_collapse
+
 development:
   mode: auto
 
@@ -75,6 +83,11 @@ navbar:
           href: articles/sequential_model.html
         - text: "Functional API"
           href: articles/functional_api.html
+        - text: "Workflows"
+        - text: "Sequential Model"
+          href: articles/workflows_sequential.html
+        - text: "Functional API"
+          href: articles/workflows_functional.html
     github:
       icon: fa-github
       href: https://github.com/davidrsch/kerasnip