Updating for mlp() engine specific args

Author: juliasilge

R/mlp.R

@@ -120,7 +120,8 @@ update.mlp <-
            hidden_units = NULL, penalty = NULL, dropout = NULL,
            epochs = NULL, activation = NULL,
            fresh = FALSE, ...) {
-    update_dot_check(...)
+
+    eng_args <- update_engine_parameters(object$eng_args, ...)
 
     if (!is.null(parameters)) {
       parameters <- check_final_param(parameters)
@@ -139,12 +140,15 @@ update.mlp <-
     # TODO make these blocks into a function and document well
     if (fresh) {
       object$args <- args
+      object$eng_args <- eng_args
     } else {
       null_args <- map_lgl(args, null_value)
       if (any(null_args))
         args <- args[!null_args]
       if (length(args) > 0)
         object$args[names(args)] <- args
+      if (length(eng_args) > 0)
+        object$eng_args[names(eng_args)] <- eng_args
     }
 
     new_model_spec(

tests/testthat/test_mlp.R

@@ -131,21 +131,23 @@ test_that('updating', {
   expr1_exp <- mlp(mode = "regression", hidden_units = 2) %>%
     set_engine("nnet", Hess = FALSE, abstol = varying())
 
-  expr2     <- mlp(mode = "regression", hidden_units = 7) %>% set_engine("nnet")
-  expr2_exp <- mlp(mode = "regression", hidden_units = 7) %>% set_engine("nnet", Hess = FALSE)
+  expr2     <- mlp(mode = "regression") %>% set_engine("nnet", Hess = varying())
+  expr2_exp <- mlp(mode = "regression") %>% set_engine("nnet", Hess = FALSE)
 
   expr3     <- mlp(mode = "regression", hidden_units = 7, epochs = varying()) %>% set_engine("keras")
 
   expr3_exp <- mlp(mode = "regression", hidden_units = 2) %>% set_engine("keras")
 
   expr4     <- mlp(mode = "classification", hidden_units = 2) %>% set_engine("nnet", Hess = FALSE, abstol = varying())
-  expr4_exp <- mlp(mode = "classification", hidden_units = 2) %>% set_engine("nnet", Hess = FALSE, abstol = varying())
+  expr4_exp <- mlp(mode = "classification", hidden_units = 2) %>% set_engine("nnet", Hess = FALSE, abstol = 1e-3)
 
   expr5     <- mlp(mode = "classification", hidden_units = 2) %>% set_engine("nnet", Hess = FALSE)
   expr5_exp <- mlp(mode = "classification", hidden_units = 2) %>% set_engine("nnet", Hess = FALSE, abstol = varying())
 
   expect_equal(update(expr1, hidden_units = 2), expr1_exp)
+  expect_equal(update(expr2, Hess = FALSE), expr2_exp)
   expect_equal(update(expr3, hidden_units = 2, fresh = TRUE), expr3_exp)
+  expect_equal(update(expr4, abstol = 1e-3), expr4_exp)
 
   param_tibb <- tibble::tibble(hidden_units = 3, dropout = .1)
   param_list <- as.list(param_tibb)