[R-package] make finalize() in R6 classes private (#6833)

R-package/DESCRIPTION

@@ -53,7 +53,7 @@ Suggests:
 Depends:
     R (>= 3.5)
 Imports:
-    R6 (>= 2.0),
+    R6 (>= 2.4.0),
     data.table (>= 1.9.6),
     graphics,
     jsonlite (>= 1.0),

R-package/R/lgb.Booster.R

@@ -11,16 +11,6 @@ Booster <- R6::R6Class(
     record_evals = list(),
     data_processor = NULL,
 
-    # Finalize will free up the handles
-    finalize = function() {
-      .Call(
-        LGBM_BoosterFree_R
-        , private$handle
-      )
-      private$handle <- NULL
-      return(invisible(NULL))
-    },
-
     # Initialize will create a starter booster
     initialize = function(params = list(),
                           train_set = NULL,
@@ -711,6 +701,17 @@ Booster <- R6::R6Class(
     set_objective_to_none = FALSE,
     train_set_version = 0L,
     fast_predict_config = list(),
+
+    # finalize() will free up the handles
+    finalize = function() {
+      .Call(
+        LGBM_BoosterFree_R
+        , private$handle
+      )
+      private$handle <- NULL
+      return(invisible(NULL))
+    },
+
     # Predict data
     inner_predict = function(idx) {
 

R-package/R/lgb.Dataset.R

@@ -30,16 +30,6 @@ Dataset <- R6::R6Class(
   cloneable = FALSE,
   public = list(
 
-    # Finalize will free up the handles
-    finalize = function() {
-      .Call(
-        LGBM_DatasetFree_R
-        , private$handle
-      )
-      private$handle <- NULL
-      return(invisible(NULL))
-    },
-
     # Initialize will create a starter dataset
     initialize = function(data,
                           params = list(),
@@ -210,7 +200,7 @@ Dataset <- R6::R6Class(
         if (is.null(private$raw_data)) {
           stop(paste0(
             "Attempting to create a Dataset without any raw data. "
-            , "This can happen if you have called Dataset$finalize() or if this Dataset was saved with saveRDS(). "
+            , "This can happen if the Dataset's finalizer was called or if this Dataset was saved with saveRDS(). "
             , "To avoid this error in the future, use lgb.Dataset.save() or "
             , "Dataset$save_binary() to save lightgbm Datasets."
           ))
@@ -608,7 +598,7 @@ Dataset <- R6::R6Class(
           # If updating failed but raw data is available, modify the params
           # on the R side and re-set ("deconstruct") the Dataset
           private$params <- new_params
-          self$finalize()
+          private$finalize()
         })
       }
       return(invisible(self))
@@ -649,7 +639,7 @@ Dataset <- R6::R6Class(
       private$categorical_feature <- categorical_feature
 
       # Finalize and return self
-      self$finalize()
+      private$finalize()
       return(invisible(self))
 
     },
@@ -681,7 +671,7 @@ Dataset <- R6::R6Class(
       private$reference <- reference
 
       # Finalize and return self
-      self$finalize()
+      private$finalize()
       return(invisible(self))
 
     },
@@ -713,6 +703,16 @@ Dataset <- R6::R6Class(
     info = NULL,
     version = 0L,
 
+    # finalize() will free up the handles
+    finalize = function() {
+      .Call(
+        LGBM_DatasetFree_R
+        , private$handle
+      )
+      private$handle <- NULL
+      return(invisible(NULL))
+    },
+
     get_handle = function() {
 
       # Get handle and construct if needed
@@ -749,7 +749,7 @@ Dataset <- R6::R6Class(
       private$predictor <- predictor
 
       # Finalize and return self
-      self$finalize()
+      private$finalize()
       return(invisible(self))
 
     }

R-package/R/lgb.Predictor.R

@@ -8,24 +8,6 @@ Predictor <- R6::R6Class(
   cloneable = FALSE,
   public = list(
 
-    # Finalize will free up the handles
-    finalize = function() {
-
-      # Check the need for freeing handle
-      if (private$need_free_handle) {
-
-        .Call(
-          LGBM_BoosterFree_R
-          , private$handle
-        )
-        private$handle <- NULL
-
-      }
-
-      return(invisible(NULL))
-
-    },
-
     # Initialize will create a starter model
     initialize = function(modelfile, params = list(), fast_predict_config = list()) {
       private$params <- .params2str(params = params)
@@ -531,5 +513,17 @@ Predictor <- R6::R6Class(
         .equal_or_both_null(private$fast_predict_config$num_iteration, num_iteration)
       )
     }
+
+    # finalize() will free up the handles
+    , finalize = function() {
+      if (private$need_free_handle) {
+        .Call(
+          LGBM_BoosterFree_R
+          , private$handle
+        )
+        private$handle <- NULL
+      }
+      return(invisible(NULL))
+    }
   )
 )

R-package/src/lightgbm_R.cpp

@@ -270,7 +270,7 @@ void _DatasetFinalizer(SEXP handle) {
 SEXP LGBM_NullBoosterHandleError_R() {
   Rf_error(
       "Attempting to use a Booster which no longer exists and/or cannot be restored. "
-      "This can happen if you have called Booster$finalize() "
+      "This can happen if the Booster's finalizer was called "
       "or if this Booster was saved through saveRDS() using 'serializable=FALSE'.");
   return R_NilValue;
 }
@@ -285,7 +285,7 @@ void _AssertDatasetHandleNotNull(SEXP handle) {
   if (Rf_isNull(handle) || !R_ExternalPtrAddr(handle)) {
     Rf_error(
       "Attempting to use a Dataset which no longer exists. "
-      "This can happen if you have called Dataset$finalize() or if this Dataset was saved with saveRDS(). "
+      "This can happen if the Dataset's finalizer was called or if this Dataset was saved with saveRDS(). "
       "To avoid this error in the future, use lgb.Dataset.save() or Dataset$save_binary() to save lightgbm Datasets.");
   }
 }

R-package/tests/testthat/test_Predictor.R

 library(Matrix)
 
-test_that("Predictor$finalize() should not fail", {
+test_that("Predictor's finalizer should not fail", {
     X <- as.matrix(as.integer(iris[, "Species"]), ncol = 1L)
     y <- iris[["Sepal.Length"]]
     dtrain <- lgb.Dataset(X, label = y)
@@ -21,11 +21,11 @@ test_that("Predictor$finalize() should not fail", {
 
     expect_false(.is_null_handle(predictor$.__enclos_env__$private$handle))
 
-    predictor$finalize()
+    predictor$.__enclos_env__$private$finalize()
     expect_true(.is_null_handle(predictor$.__enclos_env__$private$handle))
 
     # calling finalize() a second time shouldn't cause any issues
-    predictor$finalize()
+    predictor$.__enclos_env__$private$finalize()
     expect_true(.is_null_handle(predictor$.__enclos_env__$private$handle))
 })
 

R-package/tests/testthat/test_dataset.R

@@ -351,7 +351,7 @@ test_that("Dataset$update_params() works correctly for recognized Dataset parame
   }
 })
 
-test_that("Dataset$finalize() should not fail on an already-finalized Dataset", {
+test_that("Dataset's finalizer should not fail on an already-finalized Dataset", {
   dtest <- lgb.Dataset(
     data = test_data
     , label = test_label
@@ -361,11 +361,11 @@ test_that("Dataset$finalize() should not fail on an already-finalized Dataset",
   dtest$construct()
   expect_false(.is_null_handle(dtest$.__enclos_env__$private$handle))
 
-  dtest$finalize()
+  dtest$.__enclos_env__$private$finalize()
   expect_true(.is_null_handle(dtest$.__enclos_env__$private$handle))
 
   # calling finalize() a second time shouldn't cause any issues
-  dtest$finalize()
+  dtest$.__enclos_env__$private$finalize()
   expect_true(.is_null_handle(dtest$.__enclos_env__$private$handle))
 })
 

R-package/tests/testthat/test_lgb.Booster.R

-test_that("Booster$finalize() should not fail", {
+test_that("Booster's finalizer should not fail", {
     X <- as.matrix(as.integer(iris[, "Species"]), ncol = 1L)
     y <- iris[["Sepal.Length"]]
     dtrain <- lgb.Dataset(X, label = y)
@@ -15,11 +15,11 @@ test_that("Booster$finalize() should not fail", {
 
     expect_false(.is_null_handle(bst$.__enclos_env__$private$handle))
 
-    bst$finalize()
+    bst$.__enclos_env__$private$finalize()
     expect_true(.is_null_handle(bst$.__enclos_env__$private$handle))
 
     # calling finalize() a second time shouldn't cause any issues
-    bst$finalize()
+    bst$.__enclos_env__$private$finalize()
     expect_true(.is_null_handle(bst$.__enclos_env__$private$handle))
 })
 
@@ -195,7 +195,7 @@ test_that("Loading a Booster from a text file works", {
     lgb.save(bst, model_file)
 
     # finalize the booster and destroy it so you know we aren't cheating
-    bst$finalize()
+    bst$.__enclos_env__$private$finalize()
     expect_null(bst$.__enclos_env__$private$handle)
     rm(bst)
 
@@ -238,7 +238,7 @@ test_that("boosters with linear models at leaves can be written to text file and
     preds <- predict(bst, X)
     model_file <- tempfile(fileext = ".model")
     lgb.save(bst, model_file)
-    bst$finalize()
+    bst$.__enclos_env__$private$finalize()
     expect_null(bst$.__enclos_env__$private$handle)
     rm(bst)
 
@@ -275,7 +275,7 @@ test_that("Loading a Booster from a string works", {
     model_string <- bst$save_model_to_string()
 
     # finalize the booster and destroy it so you know we aren't cheating
-    bst$finalize()
+    bst$.__enclos_env__$private$finalize()
     expect_null(bst$.__enclos_env__$private$handle)
     rm(bst)
 
@@ -313,7 +313,7 @@ test_that("Saving a large model to string should work", {
     expect_gt(nchar(model_string), 1024L * 1024L)
 
     # finalize the booster and destroy it so you know we aren't cheating
-    bst$finalize()
+    bst$.__enclos_env__$private$finalize()
     expect_null(bst$.__enclos_env__$private$handle)
     rm(bst)
 
@@ -383,7 +383,7 @@ test_that("If a string and a file are both passed to lgb.load() the file is used
     lgb.save(bst, model_file)
 
     # finalize the booster and destroy it so you know we aren't cheating
-    bst$finalize()
+    bst$.__enclos_env__$private$finalize()
     expect_null(bst$.__enclos_env__$private$handle)
     rm(bst)
 
@@ -1508,7 +1508,7 @@ test_that("boosters with linear models at leaves can be written to RDS and re-lo
     preds <- predict(bst, X)
     model_file <- tempfile(fileext = ".rds")
     saveRDS(bst, file = model_file)
-    bst$finalize()
+    bst$.__enclos_env__$private$finalize()
     expect_null(bst$.__enclos_env__$private$handle)
     rm(bst)
 
@@ -1562,7 +1562,7 @@ test_that("Booster's print, show, and summary work correctly", {
         .has_expected_content_for_fitted_model(log_txt)
 
         #--- should not fail for finalized models ---#
-        model$finalize()
+        model$.__enclos_env__$private$finalize()
 
         # print()
         log_txt <- capture.output({