glmnet multi_predict(): Check type for all modes (#900)

* check type for all modes

* bump version in anticipation of #897 being merged first

* update NEWS

* update to merge PR

Author: hfrick

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: parsnip
 Title: A Common API to Modeling and Analysis Functions
-Version: 1.0.4.9002
+Version: 1.0.4.9003
 Authors@R: c(
     person("Max", "Kuhn", , "max@posit.co", role = c("aut", "cre")),
     person("Davis", "Vaughan", , "davis@posit.co", role = "aut"),

NEWS.md

@@ -16,6 +16,8 @@
 
 * Several internal functions (to help work with `Surv` objects) were added as a standalone file that can be used in other packages via `usethis::use_standalone("tidymodels/parsnip")`. 
 
+* `multi_predict()` methods for `linear_reg()`, `logistic_reg()`, and `multinomial_reg()` models fitted with the `"glmnet"` engine now check the `type` better and error accordingly (#900).
+
 * Rather than being implemented in each method, the check for the `new_data` argument being mistakenly passed as `newdata` to `multi_predict()` now happens in the generic. Packages re-exporting the `multi_predict()` generic and implementing now-duplicate checks may see new failures and can remove their own analogous checks. This check already existed in all `predict()` methods (via `predict.model_fit()`) and all parsnip `multi_predict()` methods (#525).
 
 * `logistic_reg()` will now warn at `fit()` when the outcome has more than two levels (#545).

R/glmnet-engines.R

@@ -173,14 +173,20 @@ multi_predict_glmnet <- function(object,
                                  type = NULL,
                                  penalty = NULL,
                                  ...) {
+  type <- check_pred_type(object, type)
+  check_spec_pred_type(object, type)
+  if (type == "prob") {
+    check_spec_levels(object)
+  }
+
+  dots <- list(...)
+
   if (object$spec$mode == "classification") {
     if (is_quosure(penalty)) {
       penalty <- eval_tidy(penalty)
     }
   }
 
-  dots <- list(...)
-
   object$spec <- eval_args(object$spec)
 
   if (is.null(penalty)) {
@@ -195,12 +201,6 @@ multi_predict_glmnet <- function(object,
   model_type <- class(object$spec)[1]
 
   if (object$spec$mode == "classification") {
-    if (is.null(type)) {
-      type <- "class"
-    }
-    if (!(type %in% c("class", "prob", "link", "raw"))) {
-      rlang::abort("`type` should be either 'class', 'link', 'raw', or 'prob'.")
-    }
     if (type == "prob" |
         model_type == "logistic_reg") {
       dots$type <- "response"