bug fix for non-package models

NEWS.md

@@ -33,6 +33,8 @@
 
 * Fixed bug where some models fit using `fit_xy()` couldn't predict (#1166).
 
+* Fixed bug related to using local (non-package) models (#1229)
+
 * `tunable()` now references a dials object for the `mixture` parameter (#1236)
 
 ## Breaking Change

R/misc.R

@@ -241,13 +241,15 @@ prompt_missing_implementation <- function(spec,
 #' @keywords internal
 #' @export
 show_call <- function(object) {
-  object$method$fit$args <-
-    map(object$method$fit$args, convert_arg)
+  object$method$fit$args <- map(object$method$fit$args, convert_arg)
 
-  call2(object$method$fit$func["fun"],
-    !!!object$method$fit$args,
-    .ns = object$method$fit$func["pkg"]
-  )
+  fn_info <- as.list(object$method$fit$func)
+  if (!any(names(fn_info) == "pkg")) {
+    res <- call2(fn_info$fun, !!!object$method$fit$args)
+  } else {
+    res <- call2(fn_info$fun, !!!object$method$fit$args, .ns = fn_info$pkg)
+  }
+  res
 }
 
 convert_arg <- function(x) {
@@ -301,8 +303,8 @@ check_args.default <- function(object, call = rlang::caller_env()) {
 
 # ------------------------------------------------------------------------------
 
-# copied form recipes
-
+# copied from recipes
+# nocov start
 names0 <- function(num, prefix = "x", call = rlang::caller_env()) {
   if (num < 1) {
     cli::cli_abort("{.arg num} should be > 0.", call = call)
@@ -311,7 +313,7 @@ names0 <- function(num, prefix = "x", call = rlang::caller_env()) {
   ind <- gsub(" ", "0", ind)
   paste0(prefix, ind)
 }
-
+# nocov end
 
 # ------------------------------------------------------------------------------
 

parsnip.Rproj

@@ -1,6 +1,7 @@
 Version: 1.0
 ProjectId: 7f6c9ff5-6b9a-4235-8666-12db5ef65d49
 
+
 RestoreWorkspace: No
 SaveWorkspace: No
 AlwaysSaveHistory: Default

tests/testthat/_snaps/misc.md

@@ -243,3 +243,15 @@
       Error in `.get_prediction_column_names()`:
       ! Prediction information could not be found for this `linear_reg()` with engine "lm" and mode "Depeche". Does a parsnip extension package need to be loaded?
 
+# register local models
+
+    Code
+      my_model() %>% translate("my_engine")
+    Output
+      my model Model Specification (regression)
+
+      Computational engine: my_engine 
+
+      Model fit template:
+      my_model_fun(formula = missing_arg(), data = missing_arg())
+

tests/testthat/test-misc.R

@@ -299,3 +299,44 @@ test_that('obtaining prediction columns', {
   )
 
 })
+
+
+# ------------------------------------------------------------------------------
+
+# https://github.com/tidymodels/parsnip/issues/1229
+test_that('register local models', {
+  set_new_model("my_model")
+  set_model_mode(model = "my_model", mode = "regression")
+  set_model_engine(
+    "my_model",
+    mode = "regression",
+    eng = "my_engine"
+  )
+
+  my_model <-
+    function(mode = "regression") {
+      new_model_spec(
+        "my_model",
+        args = list(),
+        eng_args = NULL,
+        mode = mode,
+        method = NULL,
+        engine = NULL
+      )
+    }
+
+  set_fit(
+    model = "my_model",
+    eng = "my_engine",
+    mode = "regression",
+    value = list(
+      interface = "matrix",
+      protect = c("formula", "data"),
+      func = c(fun = "my_model_fun"),
+      defaults = list()
+    )
+  )
+
+  expect_snapshot(my_model() %>% translate("my_engine"))
+})
+