setting stop_iter with brulee model

[topepo]

library(tidymodels)
# requires brulee; make sure to load it after install to get extra downloads

set.seed(1)
mlp(hidden_units = 5, epochs = 100) %>% 
  set_engine("brulee", stop_iter = 5)  %>% 
  set_mode("regression") %>% 
  fit(price ~ latitude + longitude, data = Sacramento)
#> Warning: The following arguments cannot be manually modified and were removed:
#> stop_iter.
#> parsnip model object
#> 
#> Multilayer perceptron
#> 
#> relu activation
#> 5 hidden units,  21 model parameters
#> 932 samples, 2 features, numeric outcome 
#> weight decay: 0.001 
#> dropout proportion: 0 
#> batch size: 839 
#> learn rate: 0.01 
#> scaled validation loss after 8 epochs: 1.03

# based on "loss after X epochs" it is actually working

^{Created on 2024-01-16 with reprex v2.0.2}

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