check values first (and evaluate them)

Author: topepo

R/linear_reg.R

@@ -107,6 +107,7 @@ translate.linear_reg <- function(x, engine = x$engine, ...) {
   x <- translate.default(x, engine, ...)
 
   if (engine == "glmnet") {
+    check_glmnet_penalty(x)
     if (any(names(x$eng_args) == "path_values")) {
       # Since we decouple the parsnip `penalty` argument from being the same
       # as the glmnet `lambda` value, this allows users to set the path
@@ -122,7 +123,6 @@ translate.linear_reg <- function(x, engine = x$engine, ...) {
     # Since the `fit` information is gone for the penalty, we need to have an
     # evaluated value for the parameter.
     x$args$penalty <- rlang::eval_tidy(x$args$penalty)
-    check_glmnet_penalty(x)
   }
   x
 }

R/logistic_reg.R

@@ -109,6 +109,7 @@ translate.logistic_reg <- function(x, engine = x$engine, ...) {
   arg_names <- names(arg_vals)
 
   if (engine == "glmnet") {
+    check_glmnet_penalty(x)
     if (any(names(x$eng_args) == "path_values")) {
       # Since we decouple the parsnip `penalty` argument from being the same
       # as the glmnet `lambda` value, this allows users to set the path
@@ -124,7 +125,6 @@ translate.logistic_reg <- function(x, engine = x$engine, ...) {
     # Since the `fit` information is gone for the penalty, we need to have an
     # evaluated value for the parameter.
     x$args$penalty <- rlang::eval_tidy(x$args$penalty)
-    check_glmnet_penalty(x)
   }
 
   if (engine == "LiblineaR") {

R/misc.R

@@ -324,10 +324,12 @@ stan_conf_int <- function(object, newdata) {
 }
 
 check_glmnet_penalty <- function(x) {
-  if (length(x$args$penalty) != 1) {
+  pen <- rlang::eval_tidy(x$args$penalty)
+
+  if (length(pen) != 1) {
     rlang::abort(c(
       "For the glmnet engine, `penalty` must be a single number (or a value of `tune()`).",
-      glue::glue("There are {length(x$args$penalty)} values for `penalty`."),
+      glue::glue("There are {length(pen)} values for `penalty`."),
       "To try multiple values for total regularization, use the tune package.",
       "To predict multiple penalties, use `multi_predict()`"
     ))

R/multinom_reg.R

@@ -100,6 +100,7 @@ translate.multinom_reg <- function(x, engine = x$engine, ...) {
   x <- translate.default(x, engine, ...)
 
   if (engine == "glmnet") {
+    check_glmnet_penalty(x)
     if (any(names(x$eng_args) == "path_values")) {
       # Since we decouple the parsnip `penalty` argument from being the same
       # as the glmnet `lambda` value, this allows users to set the path