[R-package] Add explicit return statement to R functions. (#3703)

* add explicit return statement to functions in callback.R

* add explicit return statement to functions in lgb.Booster.R

* add explicit return statement to functions in lgb.Dataset.R

* add explicit return statement to functions in lgb.Predictor.R

* add explicit return statement to functions in lgb.cv.R

* add explicit return statement to functions in lgb.interprete.R

* add explicit return statement to functions in lgb.plot.importance.R

* add explicit return statement to functions in saveRDS.lgb.Booster.R

* add explicit return statement to functions in utils.R

* add explicit return statement to functions in lgb.plot.interpretation.R

* add explicit return statement to functions in build_r.R

* fix typo

* return(self) -> return(invisible(self))

* fix some inconsistent indention

* fix test failure

* add another return() statement

* fix linting errors

R-package/R/aliases.R

@@ -7,74 +7,76 @@
 # [return] A named list, where each key is a parameter relevant to lgb.DataSet and each value is a character
 #          vector of corresponding aliases.
 .DATASET_PARAMETERS <- function() {
-    return(list(
-        "bin_construct_sample_cnt" = c(
-            "bin_construct_sample_cnt"
-            , "subsample_for_bin"
+    return(
+        list(
+            "bin_construct_sample_cnt" = c(
+                "bin_construct_sample_cnt"
+                , "subsample_for_bin"
+            )
+            , "categorical_feature" = c(
+                "categorical_feature"
+                , "cat_feature"
+                , "categorical_column"
+                , "cat_column"
+            )
+            , "data_random_seed" = c(
+                "data_random_seed"
+                , "data_seed"
+            )
+            , "enable_bundle" = c(
+                "enable_bundle"
+                , "is_enable_bundle"
+                , "bundle"
+            )
+            , "feature_pre_filter" = "feature_pre_filter"
+            , "forcedbins_filename" = "forcedbins_filename"
+            , "group_column" = c(
+                "group_column"
+                , "group"
+                , "group_id"
+                , "query_column"
+                , "query"
+                , "query_id"
+            )
+            , "header" = c(
+                "header"
+                , "has_header"
+            )
+            , "ignore_column" = c(
+                "ignore_column"
+                , "ignore_feature"
+                , "blacklist"
+            )
+            , "is_enable_sparse" = c(
+                "is_enable_sparse"
+                , "is_sparse"
+                , "enable_sparse"
+                , "sparse"
+            )
+            , "label_column" = c(
+                "label_column"
+                , "label"
+            )
+            , "max_bin" = "max_bin"
+            , "max_bin_by_feature" = "max_bin_by_feature"
+            , "min_data_in_bin" = "min_data_in_bin"
+            , "pre_partition" = c(
+                "pre_partition"
+                , "is_pre_partition"
+            )
+            , "two_round" = c(
+                "two_round"
+                , "two_round_loading"
+                , "use_two_round_loading"
+            )
+            , "use_missing" = "use_missing"
+            , "weight_column" = c(
+                "weight_column"
+                , "weight"
+            )
+            , "zero_as_missing" = "zero_as_missing"
         )
-        , "categorical_feature" = c(
-            "categorical_feature"
-            , "cat_feature"
-            , "categorical_column"
-            , "cat_column"
-        )
-        , "data_random_seed" = c(
-            "data_random_seed"
-            , "data_seed"
-        )
-        , "enable_bundle" = c(
-            "enable_bundle"
-            , "is_enable_bundle"
-            , "bundle"
-        )
-        , "feature_pre_filter" = "feature_pre_filter"
-        , "forcedbins_filename" = "forcedbins_filename"
-        , "group_column" = c(
-            "group_column"
-            , "group"
-            , "group_id"
-            , "query_column"
-            , "query"
-            , "query_id"
-        )
-        , "header" = c(
-            "header"
-            , "has_header"
-        )
-        , "ignore_column" = c(
-            "ignore_column"
-            , "ignore_feature"
-            , "blacklist"
-        )
-        , "is_enable_sparse" = c(
-            "is_enable_sparse"
-            , "is_sparse"
-            , "enable_sparse"
-            , "sparse"
-        )
-        , "label_column" = c(
-            "label_column"
-            , "label"
-        )
-        , "max_bin" = "max_bin"
-        , "max_bin_by_feature" = "max_bin_by_feature"
-        , "min_data_in_bin" = "min_data_in_bin"
-        , "pre_partition" = c(
-            "pre_partition"
-            , "is_pre_partition"
-        )
-        , "two_round" = c(
-            "two_round"
-            , "two_round_loading"
-            , "use_two_round_loading"
-        )
-        , "use_missing" = "use_missing"
-        , "weight_column" = c(
-            "weight_column"
-            , "weight"
-        )
-        , "zero_as_missing" = "zero_as_missing"
-    ))
+    )
 }
 
 # [description] List of respected parameter aliases. Wrapped in a function to take advantage of
@@ -115,10 +117,12 @@
 # [returns]
 #     A character vector
 .NO_METRIC_STRINGS <- function() {
-    return(c(
-        "na"
-        , "None"
-        , "null"
-        , "custom"
-    ))
+    return(
+        c(
+            "na"
+            , "None"
+            , "null"
+            , "custom"
+        )
+    )
 }

R-package/R/callback.R

@@ -74,6 +74,8 @@ cb.reset.parameters <- function(new_params) {
 
     }
 
+    return(invisible(NULL))
+
   }
 
   callback <- function(env) {
@@ -95,15 +97,17 @@ cb.reset.parameters <- function(new_params) {
     })
 
     if (!is.null(env$model)) {
-      env$model$reset_parameter(params = pars)
+      return(env$model$reset_parameter(params = pars))
     }
 
+    return(invisible(NULL))
+
   }
 
   attr(callback, "call") <- match.call()
   attr(callback, "is_pre_iteration") <- TRUE
   attr(callback, "name") <- "cb.reset.parameters"
-  callback
+  return(callback)
 }
 
 # Format the evaluation metric string
@@ -116,9 +120,9 @@ format.eval.string <- function(eval_res, eval_err = NULL) {
 
   # Check for empty evaluation error
   if (!is.null(eval_err)) {
-    sprintf("%s\'s %s:%g+%g", eval_res$data_name, eval_res$name, eval_res$value, eval_err)
+    return(sprintf("%s\'s %s:%g+%g", eval_res$data_name, eval_res$name, eval_res$value, eval_err))
   } else {
-    sprintf("%s\'s %s:%g", eval_res$data_name, eval_res$name, eval_res$value)
+    return(sprintf("%s\'s %s:%g", eval_res$data_name, eval_res$name, eval_res$value))
   }
 
 }
@@ -150,7 +154,7 @@ merge.eval.string <- function(env) {
 
   }
 
-  paste0(msg, collapse = "  ")
+  return(paste0(msg, collapse = "  "))
 
 }
 
@@ -180,13 +184,15 @@ cb.print.evaluation <- function(period = 1L) {
 
     }
 
+    return(invisible(NULL))
+
   }
 
   # Store attributes
   attr(callback, "call") <- match.call()
   attr(callback, "name") <- "cb.print.evaluation"
 
-  callback
+  return(callback)
 
 }
 
@@ -253,13 +259,15 @@ cb.record.evaluation <- function() {
 
     }
 
+    return(invisible(NULL))
+
   }
 
   # Store attributes
   attr(callback, "call") <- match.call()
   attr(callback, "name") <- "cb.record.evaluation"
 
-  callback
+  return(callback)
 
 }
 
@@ -311,6 +319,8 @@ cb.early.stop <- function(stopping_rounds, first_metric_only = FALSE, verbose =
 
     }
 
+    return(invisible(NULL))
+
   }
 
   # Create callback
@@ -392,18 +402,21 @@ cb.early.stop <- function(stopping_rounds, first_metric_only = FALSE, verbose =
         env$met_early_stop <- TRUE
       }
     }
+
+    return(invisible(NULL))
+
   }
 
   attr(callback, "call") <- match.call()
   attr(callback, "name") <- "cb.early.stop"
 
-  callback
+  return(callback)
 
 }
 
 # Extract callback names from the list of callbacks
 callback.names <- function(cb_list) {
-  unlist(lapply(cb_list, attr, "name"))
+  return(unlist(lapply(cb_list, attr, "name")))
 }
 
 add.cb <- function(cb_list, cb) {
@@ -426,22 +439,24 @@ add.cb <- function(cb_list, cb) {
   }
 
   # Return element
-  cb_list
+  return(cb_list)
 
 }
 
 categorize.callbacks <- function(cb_list) {
 
   # Check for pre-iteration or post-iteration
-  list(
-    pre_iter = Filter(function(x) {
-      pre <- attr(x, "is_pre_iteration")
-      !is.null(pre) && pre
-    }, cb_list),
-    post_iter = Filter(function(x) {
-      pre <- attr(x, "is_pre_iteration")
-      is.null(pre) || !pre
-    }, cb_list)
+  return(
+    list(
+      pre_iter = Filter(function(x) {
+        pre <- attr(x, "is_pre_iteration")
+        !is.null(pre) && pre
+      }, cb_list),
+      post_iter = Filter(function(x) {
+        pre <- attr(x, "is_pre_iteration")
+        is.null(pre) || !pre
+      }, cb_list)
+    )
   )
 
 }

R-package/R/lgb.Booster.R

@@ -21,6 +21,8 @@ Booster <- R6::R6Class(
 
       }
 
+      return(invisible(NULL))
+
     },
 
     # Initialize will create a starter booster
@@ -137,6 +139,8 @@ Booster <- R6::R6Class(
 
       self$params <- params
 
+      return(invisible(NULL))
+
     },
 
     # Set training data name
@@ -320,10 +324,12 @@ Booster <- R6::R6Class(
     current_iter = function() {
 
       cur_iter <- 0L
-      lgb.call(
-        fun_name = "LGBM_BoosterGetCurrentIteration_R"
-        , ret = cur_iter
-        , private$handle
+      return(
+        lgb.call(
+          fun_name = "LGBM_BoosterGetCurrentIteration_R"
+          , ret = cur_iter
+          , private$handle
+        )
       )
 
     },
@@ -332,10 +338,12 @@ Booster <- R6::R6Class(
     upper_bound = function() {
 
       upper_bound <- 0.0
-      lgb.call(
-        fun_name = "LGBM_BoosterGetUpperBoundValue_R"
-        , ret = upper_bound
-        , private$handle
+      return(
+        lgb.call(
+          fun_name = "LGBM_BoosterGetUpperBoundValue_R"
+          , ret = upper_bound
+          , private$handle
+        )
       )
 
     },
@@ -344,10 +352,12 @@ Booster <- R6::R6Class(
     lower_bound = function() {
 
       lower_bound <- 0.0
-      lgb.call(
-        fun_name = "LGBM_BoosterGetLowerBoundValue_R"
-        , ret = lower_bound
-        , private$handle
+      return(
+        lgb.call(
+          fun_name = "LGBM_BoosterGetLowerBoundValue_R"
+          , ret = lower_bound
+          , private$handle
+        )
       )
 
     },
@@ -397,17 +407,19 @@ Booster <- R6::R6Class(
       }
 
       # Evaluate data
-      private$inner_eval(
-        data_name = name
-        , data_idx = data_idx
-        , feval = feval
+      return(
+        private$inner_eval(
+          data_name = name
+          , data_idx = data_idx
+          , feval = feval
+        )
       )
 
     },
 
     # Evaluation training data
     eval_train = function(feval = NULL) {
-      private$inner_eval(private$name_train_set, 1L, feval)
+      return(private$inner_eval(private$name_train_set, 1L, feval))
     },
 
     # Evaluation validation data
@@ -463,12 +475,14 @@ Booster <- R6::R6Class(
       }
 
       # Return model string
-      return(lgb.call.return.str(
-        fun_name = "LGBM_BoosterSaveModelToString_R"
-        , private$handle
-        , as.integer(num_iteration)
-        , as.integer(feature_importance_type)
-      ))
+      return(
+        lgb.call.return.str(
+          fun_name = "LGBM_BoosterSaveModelToString_R"
+          , private$handle
+          , as.integer(num_iteration)
+          , as.integer(feature_importance_type)
+        )
+      )
 
     },
 
@@ -480,11 +494,13 @@ Booster <- R6::R6Class(
         num_iteration <- self$best_iter
       }
 
-      lgb.call.return.str(
-        fun_name = "LGBM_BoosterDumpModel_R"
-        , private$handle
-        , as.integer(num_iteration)
-        , as.integer(feature_importance_type)
+      return(
+        lgb.call.return.str(
+          fun_name = "LGBM_BoosterDumpModel_R"
+          , private$handle
+          , as.integer(num_iteration)
+          , as.integer(feature_importance_type)
+        )
       )
 
     },
@@ -510,7 +526,8 @@ Booster <- R6::R6Class(
 
       # Predict on new data
       predictor <- Predictor$new(private$handle, ...)
-      predictor$predict(
+      return(
+        predictor$predict(
           data = data
           , start_iteration = start_iteration
           , num_iteration = num_iteration
@@ -519,13 +536,14 @@ Booster <- R6::R6Class(
           , predcontrib = predcontrib
           , header = header
           , reshape = reshape
+        )
       )
 
     },
 
     # Transform into predictor
     to_predictor = function() {
-      Predictor$new(private$handle)
+      return(Predictor$new(private$handle))
     },
 
     # Used for save
@@ -537,6 +555,8 @@ Booster <- R6::R6Class(
       # Overwrite model in object
       self$raw <- self$save_model_to_string(NULL)
 
+      return(invisible(NULL))
+
     }
 
   ),
@@ -780,8 +800,9 @@ predict.lgb.Booster <- function(object,
   }
 
   # Return booster predictions
-  object$predict(
-    data = data
+  return(
+    object$predict(
+      data = data
       , start_iteration = start_iteration
       , num_iteration = num_iteration
       , rawscore = rawscore
@@ -789,7 +810,8 @@ predict.lgb.Booster <- function(object,
       , predcontrib =  predcontrib
       , header = header
       , reshape = reshape
-    , ...
+      , ...
+    )
   )
 }
 
@@ -896,10 +918,12 @@ lgb.save <- function(booster, filename, num_iteration = NULL) {
   }
 
   # Store booster
-  invisible(booster$save_model(
-    filename = filename
-    , num_iteration = num_iteration
-  ))
+  return(
+    invisible(booster$save_model(
+      filename = filename
+      , num_iteration = num_iteration
+    ))
+  )
 
 }
 
@@ -941,7 +965,7 @@ lgb.dump <- function(booster, num_iteration = NULL) {
   }
 
   # Return booster at requested iteration
-  booster$dump_model(num_iteration =  num_iteration)
+  return(booster$dump_model(num_iteration =  num_iteration))
 
 }
 
@@ -1045,5 +1069,5 @@ lgb.get.eval.result <- function(booster, data_name, eval_name, iters = NULL, is_
   iters <- iters - delta
 
   # Return requested result
-  as.numeric(result[iters])
+  return(as.numeric(result[iters]))
 }

R-package/R/lgb.Dataset.R

@@ -18,6 +18,8 @@ Dataset <- R6::R6Class(
 
       }
 
+      return(invisible(NULL))
+
     },
 
     # Initialize will create a starter dataset
@@ -85,6 +87,8 @@ Dataset <- R6::R6Class(
       private$info <- info
       private$version <- 0L
 
+      return(invisible(NULL))
+
     },
 
     create_valid = function(data,
@@ -325,16 +329,18 @@ Dataset <- R6::R6Class(
         num_col <- 0L
 
         # Get numeric data and numeric features
-        c(
-          lgb.call(
-            fun_name = "LGBM_DatasetGetNumData_R"
-            , ret = num_row
-            , private$handle
-          ),
-          lgb.call(
-            fun_name = "LGBM_DatasetGetNumFeature_R"
-            , ret = num_col
-            , private$handle
+        return(
+          c(
+            lgb.call(
+              fun_name = "LGBM_DatasetGetNumData_R"
+              , ret = num_row
+              , private$handle
+            ),
+            lgb.call(
+              fun_name = "LGBM_DatasetGetNumFeature_R"
+              , ret = num_col
+              , private$handle
+            )
           )
         )
 
@@ -342,7 +348,7 @@ Dataset <- R6::R6Class(
 
         # Check if dgCMatrix (sparse matrix column compressed)
         # NOTE: requires Matrix package
-        dim(private$raw_data)
+        return(dim(private$raw_data))
 
       } else {
 
@@ -368,12 +374,12 @@ Dataset <- R6::R6Class(
             , private$handle
         )
         private$colnames <- as.character(base::strsplit(cnames, "\t")[[1L]])
-        private$colnames
+        return(private$colnames)
 
       } else if (is.matrix(private$raw_data) || methods::is(private$raw_data, "dgCMatrix")) {
 
         # Check if dgCMatrix (sparse matrix column compressed)
-        colnames(private$raw_data)
+        return(colnames(private$raw_data))
 
       } else {
 
@@ -470,7 +476,7 @@ Dataset <- R6::R6Class(
         }
       }
 
-      private$info[[name]]
+      return(private$info[[name]])
 
     },
 
@@ -522,17 +528,19 @@ Dataset <- R6::R6Class(
     slice = function(idxset, ...) {
 
       # Perform slicing
-      Dataset$new(
-        data = NULL
-        , params = private$params
-        , reference = self
-        , colnames = private$colnames
-        , categorical_feature = private$categorical_feature
-        , predictor = private$predictor
-        , free_raw_data = private$free_raw_data
-        , used_indices = sort(idxset, decreasing = FALSE)
-        , info = NULL
-        , ...
+      return(
+        Dataset$new(
+          data = NULL
+          , params = private$params
+          , reference = self
+          , colnames = private$colnames
+          , categorical_feature = private$categorical_feature
+          , predictor = private$predictor
+          , free_raw_data = private$free_raw_data
+          , used_indices = sort(idxset, decreasing = FALSE)
+          , info = NULL
+          , ...
+        )
       )
 
     },
@@ -679,7 +687,7 @@ Dataset <- R6::R6Class(
       if (lgb.is.null.handle(x = private$handle)) {
         self$construct()
       }
-      private$handle
+      return(private$handle)
 
     },
 
@@ -753,18 +761,20 @@ lgb.Dataset <- function(data,
                         ...) {
 
   # Create new dataset
-  invisible(Dataset$new(
-    data = data
-    , params = params
-    , reference = reference
-    , colnames = colnames
-    , categorical_feature = categorical_feature
-    , predictor = NULL
-    , free_raw_data = free_raw_data
-    , used_indices = NULL
-    , info = info
-    , ...
-  ))
+  return(
+    invisible(Dataset$new(
+      data = data
+      , params = params
+      , reference = reference
+      , colnames = colnames
+      , categorical_feature = categorical_feature
+      , predictor = NULL
+      , free_raw_data = free_raw_data
+      , used_indices = NULL
+      , info = info
+      , ...
+    ))
+  )
 
 }
 
@@ -796,7 +806,7 @@ lgb.Dataset.create.valid <- function(dataset, data, info = list(), ...) {
   }
 
   # Create validation dataset
-  invisible(dataset$create_valid(data = data, info = info, ...))
+  return(invisible(dataset$create_valid(data = data, info = info, ...)))
 
 }
 
@@ -822,7 +832,7 @@ lgb.Dataset.construct <- function(dataset) {
   }
 
   # Construct the dataset
-  invisible(dataset$construct())
+  return(invisible(dataset$construct()))
 
 }
 
@@ -856,7 +866,7 @@ dim.lgb.Dataset <- function(x, ...) {
     stop("dim.lgb.Dataset: input data should be an lgb.Dataset object")
   }
 
-  x$dim()
+  return(x$dim())
 
 }
 
@@ -893,7 +903,7 @@ dimnames.lgb.Dataset <- function(x) {
   }
 
   # Return dimension names
-  list(NULL, x$get_colnames())
+  return(list(NULL, x$get_colnames()))
 
 }
 
@@ -932,7 +942,7 @@ dimnames.lgb.Dataset <- function(x) {
 
   # Set column names properly, and return
   x$set_colnames(colnames = value[[2L]])
-  x
+  return(x)
 
 }
 
@@ -970,7 +980,7 @@ slice.lgb.Dataset <- function(dataset, idxset, ...) {
   }
 
   # Return sliced set
-  invisible(dataset$slice(idxset = idxset, ...))
+  return(invisible(dataset$slice(idxset = idxset, ...)))
 
 }
 
@@ -1020,7 +1030,7 @@ getinfo.lgb.Dataset <- function(dataset, name, ...) {
     stop("getinfo.lgb.Dataset: input dataset should be an lgb.Dataset object")
   }
 
-  dataset$getinfo(name = name)
+  return(dataset$getinfo(name = name))
 
 }
 
@@ -1074,7 +1084,7 @@ setinfo.lgb.Dataset <- function(dataset, name, info, ...) {
   }
 
   # Set information
-  invisible(dataset$setinfo(name = name, info = info))
+  return(invisible(dataset$setinfo(name = name, info = info)))
 }
 
 #' @name lgb.Dataset.set.categorical
@@ -1106,7 +1116,7 @@ lgb.Dataset.set.categorical <- function(dataset, categorical_feature) {
   }
 
   # Set categoricals
-  invisible(dataset$set_categorical_feature(categorical_feature = categorical_feature))
+  return(invisible(dataset$set_categorical_feature(categorical_feature = categorical_feature)))
 
 }
 
@@ -1138,7 +1148,7 @@ lgb.Dataset.set.reference <- function(dataset, reference) {
   }
 
   # Set reference
-  invisible(dataset$set_reference(reference = reference))
+  return(invisible(dataset$set_reference(reference = reference)))
 }
 
 #' @name lgb.Dataset.save
@@ -1171,5 +1181,5 @@ lgb.Dataset.save <- function(dataset, fname) {
   }
 
   # Store binary
-  invisible(dataset$save_binary(fname = fname))
+  return(invisible(dataset$save_binary(fname = fname)))
 }

R-package/R/lgb.Predictor.R

@@ -23,6 +23,8 @@ Predictor <- R6::R6Class(
 
       }
 
+      return(invisible(NULL))
+
     },
 
     # Initialize will create a starter model
@@ -59,16 +61,20 @@ Predictor <- R6::R6Class(
       class(handle) <- "lgb.Booster.handle"
       private$handle <- handle
 
+      return(invisible(NULL))
+
     },
 
     # Get current iteration
     current_iter = function() {
 
       cur_iter <- 0L
-      lgb.call(
-        fun_name = "LGBM_BoosterGetCurrentIteration_R"
-        , ret = cur_iter
-        , private$handle
+      return(
+        lgb.call(
+          fun_name = "LGBM_BoosterGetCurrentIteration_R"
+          , ret = cur_iter
+          , private$handle
+        )
       )
 
     },

R-package/R/lgb.cv.R

@@ -9,10 +9,11 @@ CVBooster <- R6::R6Class(
     boosters = list(),
     initialize = function(x) {
       self$boosters <- x
+      return(invisible(NULL))
     },
     reset_parameter = function(new_params) {
       for (x in boosters) { x$reset_parameter(new_params) }
-      self
+      return(invisible(self))
     }
   )
 )
@@ -563,7 +564,7 @@ lgb.stratified.folds <- function(y, k = 10L) {
 
   out <- split(seq(along = y), foldVector)
   names(out) <- NULL
-  out
+  return(out)
 }
 
 lgb.merge.cv.result <- function(msg, showsd = TRUE) {
@@ -615,9 +616,11 @@ lgb.merge.cv.result <- function(msg, showsd = TRUE) {
   }
 
   # Return errors
-  list(
-    eval_list = ret_eval
-    , eval_err_list = ret_eval_err
+  return(
+    list(
+      eval_list = ret_eval
+      , eval_err_list = ret_eval_err
+    )
   )
 
 }

R-package/R/lgb.interprete.R

@@ -137,9 +137,11 @@ single.tree.interprete <- function(tree_dt,
     , current_value = leaf_dt[["leaf_value"]]
   )
 
-  data.table::data.table(
-    Feature = feature_seq
-    , Contribution = diff.default(value_seq)
+  return(
+    data.table::data.table(
+      Feature = feature_seq
+      , Contribution = diff.default(value_seq)
+    )
   )
 
 }

R-package/R/lgb.plot.importance.R

@@ -91,6 +91,6 @@ lgb.plot.importance <- function(tree_imp,
                , las = 1L
            )]
 
-  invisible(tree_imp)
+  return(invisible(tree_imp))
 
 }

R-package/R/lgb.plot.interpretation.R

@@ -124,6 +124,7 @@ lgb.plot.interpretation <- function(tree_interpretation_dt,
 
     }
   }
+  return(invisible(NULL))
 }
 
 #' @importFrom graphics barplot

R-package/R/metrics.R

@@ -7,29 +7,31 @@
 #          are returned from the C++ side. For example, if you use `metric = "mse"` in your code,
 #          the metric name `"l2"` will be returned.
 .METRICS_HIGHER_BETTER <- function() {
-    return(c(
-        "l1" = FALSE
-        , "l2" = FALSE
-        , "mape" = FALSE
-        , "rmse" = FALSE
-        , "quantile" = FALSE
-        , "huber" = FALSE
-        , "fair" = FALSE
-        , "poisson" = FALSE
-        , "gamma" = FALSE
-        , "gamma_deviance" = FALSE
-        , "tweedie" = FALSE
-        , "ndcg" = TRUE
-        , "map" = TRUE
-        , "auc" = TRUE
-        , "average_precision" = TRUE
-        , "binary_logloss" = FALSE
-        , "binary_error" = FALSE
-        , "auc_mu" = TRUE
-        , "multi_logloss" = FALSE
-        , "multi_error" = FALSE
-        , "cross_entropy" = FALSE
-        , "cross_entropy_lambda" = FALSE
-        , "kullback_leibler" = FALSE
-    ))
+    return(
+        c(
+            "l1" = FALSE
+            , "l2" = FALSE
+            , "mape" = FALSE
+            , "rmse" = FALSE
+            , "quantile" = FALSE
+            , "huber" = FALSE
+            , "fair" = FALSE
+            , "poisson" = FALSE
+            , "gamma" = FALSE
+            , "gamma_deviance" = FALSE
+            , "tweedie" = FALSE
+            , "ndcg" = TRUE
+            , "map" = TRUE
+            , "auc" = TRUE
+            , "average_precision" = TRUE
+            , "binary_logloss" = FALSE
+            , "binary_error" = FALSE
+            , "auc_mu" = TRUE
+            , "multi_logloss" = FALSE
+            , "multi_error" = FALSE
+            , "cross_entropy" = FALSE
+            , "cross_entropy_lambda" = FALSE
+            , "kullback_leibler" = FALSE
+        )
+    )
 }

R-package/R/saveRDS.lgb.Booster.R

@@ -66,6 +66,8 @@ saveRDS.lgb.Booster <- function(object,
     # Free model from memory
     object$raw <- NA
 
+    return(invisible(NULL))
+
   } else {
 
     saveRDS(
@@ -77,6 +79,8 @@ saveRDS.lgb.Booster <- function(object,
       , refhook = refhook
     )
 
+    return(invisible(NULL))
+
   }
 
 }

R-package/R/utils.R

 lgb.is.Booster <- function(x) {
-  lgb.check.r6.class(object = x, name = "lgb.Booster")
+  return(lgb.check.r6.class(object = x, name = "lgb.Booster"))
 }
 
 lgb.is.Dataset <- function(x) {
-  lgb.check.r6.class(object = x, name = "lgb.Dataset")
+  return(lgb.check.r6.class(object = x, name = "lgb.Dataset"))
 }
 
 lgb.null.handle <- function() {
@@ -15,7 +15,7 @@ lgb.null.handle <- function() {
 }
 
 lgb.is.null.handle <- function(x) {
-  is.null(x) || is.na(x)
+  return(is.null(x) || is.na(x))
 }
 
 lgb.encode.char <- function(arr, len) {
@@ -54,6 +54,9 @@ lgb.last_error <- function() {
   }
 
   stop("api error: ", lgb.encode.char(arr = err_msg, len = act_len))
+
+  return(invisible(NULL))
+
 }
 
 lgb.call <- function(fun_name, ret, ...) {
@@ -232,14 +235,14 @@ lgb.c_str <- function(x) {
 
   ret <- charToRaw(as.character(x))
   ret <- c(ret, as.raw(0L))
-  ret
+  return(ret)
 
 }
 
 lgb.check.r6.class <- function(object, name) {
 
   # Check for non-existence of R6 class or named class
-  all(c("R6", name) %in% class(object))
+  return(all(c("R6", name) %in% class(object)))
 
 }
 

build_r.R

@@ -53,6 +53,7 @@ install_libs_content <- .replace_flag("use_msys2", USING_MSYS2, install_libs_con
   if (!all(res)) {
     stop("Copying files failed!")
   }
+  return(invisible(NULL))
 }
 
 # system() will not raise an R exception if the process called