I tried using tidymodels and grid to tune brulee logistic regression and it gave me error that expeced "mixture" tuning to be a double. But if I do hyper_log_grid$mixture %>% class() its output is 'numeric'. Numeric implies double right? Man, I even added %>% as.double() at the input.

Here's my code:

```
wf_brulee <-
workflow() %>%
add_recipe(X_rec) %>%
add_model(brulee_spec)
grid_ctrl <-
control_grid(
save_pred = TRUE,
parallel_over = "everything",
save_workflow = TRUE
)
hyper_log_grid <- grid_latin_hypercube(
penalty(),
mixture(range = as.double(c(0.0,1.0))),
original = T,
size = 10
)
grid_brulee_hyper <-
wf_brulee %>%
tune_grid(
resamples = X_folds,
grid = hyper_log_grid,
control = grid_ctrl
)
grid_brulee_hyper %>%
show_best(metric = "roc_auc")
```

Here's the error:

```
collect_notes(x = grid_brulee_hyper) %>%
pull(note)
```

```
[1] "\033[1m\033[33mError\033[39m in \033[38;5;254m`check_double()`\033[39m:\033[22m\n\033[33m!\033[39m brulee_logistic_reg() expected 'mixture' to be a double."
[2] "\033[1m\033[33mError\033[39m in \033[38;5;254m`check_double()`\033[39m:\033[22m\n\033[33m!\033[39m brulee_logistic_reg() expected 'mixture' to be a double."
[3] "\033[1m\033[33mError\033[39m in \033[38;5;254m`check_double()`\033[39m:\033[22m\n\033[33m!\033[39m brulee_logistic_reg() expected 'mixture' to be a double."
[4] "\033[1m\033[33mError\033[39m in \033[38;5;254m`check_double()`\033[39m:\033[22m\n\033[33m!\033[39m brulee_logistic_reg() expected 'mixture' to be a double."
```