[R-package] remove readRDS.lgb.Booster() and saveRDS.lgb.Booster() (#6246)

R-package/NAMESPACE

@@ -34,8 +34,6 @@ export(lgb.restore_handle)
 export(lgb.save)
 export(lgb.train)
 export(lightgbm)
-export(readRDS.lgb.Booster)
-export(saveRDS.lgb.Booster)
 export(setLGBMthreads)
 export(set_field)
 export(slice)

R-package/R/readRDS.lgb.Booster.R

-#' @name readRDS.lgb.Booster
-#' @title readRDS for \code{lgb.Booster} models (DEPRECATED)
-#' @description Calls \code{readRDS} in what is expected to be a serialized \code{lgb.Booster} object,
-#'              and then restores its handle through \code{lgb.restore_handle}.
-#'
-#'              \bold{This function throws a warning and will be removed in future versions.}
-#' @param file a connection or the name of the file where the R object is saved to or read from.
-#' @param refhook a hook function for handling reference objects.
-#'
-#' @return \code{lgb.Booster}
-#'
-#' @examples
-#' \donttest{
-#' library(lightgbm)
-#' \dontshow{setLGBMthreads(2L)}
-#' \dontshow{data.table::setDTthreads(1L)}
-#' data(agaricus.train, package = "lightgbm")
-#' train <- agaricus.train
-#' dtrain <- lgb.Dataset(train$data, label = train$label)
-#' data(agaricus.test, package = "lightgbm")
-#' test <- agaricus.test
-#' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-#' params <- list(
-#'   objective = "regression"
-#'   , metric = "l2"
-#'   , min_data = 1L
-#'   , learning_rate = 1.0
-#'   , num_threads = 2L
-#' )
-#' valids <- list(test = dtest)
-#' model <- lgb.train(
-#'   params = params
-#'   , data = dtrain
-#'   , nrounds = 10L
-#'   , valids = valids
-#'   , early_stopping_rounds = 5L
-#' )
-#' model_file <- tempfile(fileext = ".rds")
-#' saveRDS.lgb.Booster(model, model_file)
-#' new_model <- readRDS.lgb.Booster(model_file)
-#' }
-#' @export
-readRDS.lgb.Booster <- function(file, refhook = NULL) {
-
-  warning("'readRDS.lgb.Booster' is deprecated and will be removed in a future release. Use readRDS() instead.")
-
-  object <- readRDS(file = file, refhook = refhook)
-  lgb.restore_handle(object)
-  return(object)
-}

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

-#' @name saveRDS.lgb.Booster
-#' @title saveRDS for \code{lgb.Booster} models (DEPRECATED)
-#' @description Calls \code{saveRDS} on an \code{lgb.Booster} object, making it serializable before the call if
-#'              it isn't already.
-#'
-#'              \bold{This function throws a warning and will be removed in future versions.}
-#' @param object \code{lgb.Booster} object to serialize.
-#' @param file a connection or the name of the file where the R object is saved to or read from.
-#' @param ascii a logical. If TRUE or NA, an ASCII representation is written; otherwise (default),
-#'              a binary one is used. See the comments in the help for save.
-#' @param version the workspace format version to use. \code{NULL} specifies the current default
-#'                version (2). Versions prior to 2 are not supported, so this will only be relevant
-#'                when there are later versions.
-#' @param compress a logical specifying whether saving to a named file is to use "gzip" compression,
-#'                 or one of \code{"gzip"}, \code{"bzip2"} or \code{"xz"} to indicate the type of
-#'                 compression to be used. Ignored if file is a connection.
-#' @param refhook a hook function for handling reference objects.
-#' @param raw whether to save the model in a raw variable or not, recommended to leave it to \code{TRUE}.
-#'
-#' @return NULL invisibly.
-#'
-#' @examples
-#' \donttest{
-#' library(lightgbm)
-#' \dontshow{setLGBMthreads(2L)}
-#' \dontshow{data.table::setDTthreads(1L)}
-#' data(agaricus.train, package = "lightgbm")
-#' train <- agaricus.train
-#' dtrain <- lgb.Dataset(train$data, label = train$label)
-#' data(agaricus.test, package = "lightgbm")
-#' test <- agaricus.test
-#' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-#' params <- list(
-#'   objective = "regression"
-#'   , metric = "l2"
-#'   , min_data = 1L
-#'   , learning_rate = 1.0
-#'   , num_threads = 2L
-#' )
-#' valids <- list(test = dtest)
-#' model <- lgb.train(
-#'     params = params
-#'     , data = dtrain
-#'     , nrounds = 10L
-#'     , valids = valids
-#'     , early_stopping_rounds = 5L
-#' )
-#' model_file <- tempfile(fileext = ".rds")
-#' saveRDS.lgb.Booster(model, model_file)
-#' }
-#' @export
-saveRDS.lgb.Booster <- function(object,
-                                file,
-                                ascii = FALSE,
-                                version = NULL,
-                                compress = TRUE,
-                                refhook = NULL,
-                                raw = TRUE) {
-
-  warning("'saveRDS.lgb.Booster' is deprecated and will be removed in a future release. Use saveRDS() instead.")
-
-  if (!.is_Booster(x = object)) {
-    stop("saveRDS.lgb.Booster: object should be an ", sQuote("lgb.Booster"))
-  }
-
-  if (is.null(object$raw)) {
-    lgb.make_serializable(object)
-  }
-
-  saveRDS(
-    object
-    , file = file
-    , ascii = ascii
-    , version = version
-    , compress = compress
-    , refhook = refhook
-  )
-
-  return(invisible(NULL))
-}

R-package/man/readRDS.lgb.Booster.Rd

-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/readRDS.lgb.Booster.R
-\name{readRDS.lgb.Booster}
-\alias{readRDS.lgb.Booster}
-\title{readRDS for \code{lgb.Booster} models (DEPRECATED)}
-\usage{
-readRDS.lgb.Booster(file, refhook = NULL)
-}
-\arguments{
-\item{file}{a connection or the name of the file where the R object is saved to or read from.}
-
-\item{refhook}{a hook function for handling reference objects.}
-}
-\value{
-\code{lgb.Booster}
-}
-\description{
-Calls \code{readRDS} in what is expected to be a serialized \code{lgb.Booster} object,
-             and then restores its handle through \code{lgb.restore_handle}.
-
-             \bold{This function throws a warning and will be removed in future versions.}
-}
-\examples{
-\donttest{
-library(lightgbm)
-\dontshow{setLGBMthreads(2L)}
-\dontshow{data.table::setDTthreads(1L)}
-data(agaricus.train, package = "lightgbm")
-train <- agaricus.train
-dtrain <- lgb.Dataset(train$data, label = train$label)
-data(agaricus.test, package = "lightgbm")
-test <- agaricus.test
-dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-params <- list(
-  objective = "regression"
-  , metric = "l2"
-  , min_data = 1L
-  , learning_rate = 1.0
-  , num_threads = 2L
-)
-valids <- list(test = dtest)
-model <- lgb.train(
-  params = params
-  , data = dtrain
-  , nrounds = 10L
-  , valids = valids
-  , early_stopping_rounds = 5L
-)
-model_file <- tempfile(fileext = ".rds")
-saveRDS.lgb.Booster(model, model_file)
-new_model <- readRDS.lgb.Booster(model_file)
-}
-}

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

-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/saveRDS.lgb.Booster.R
-\name{saveRDS.lgb.Booster}
-\alias{saveRDS.lgb.Booster}
-\title{saveRDS for \code{lgb.Booster} models (DEPRECATED)}
-\usage{
-saveRDS.lgb.Booster(
-  object,
-  file,
-  ascii = FALSE,
-  version = NULL,
-  compress = TRUE,
-  refhook = NULL,
-  raw = TRUE
-)
-}
-\arguments{
-\item{object}{\code{lgb.Booster} object to serialize.}
-
-\item{file}{a connection or the name of the file where the R object is saved to or read from.}
-
-\item{ascii}{a logical. If TRUE or NA, an ASCII representation is written; otherwise (default),
-a binary one is used. See the comments in the help for save.}
-
-\item{version}{the workspace format version to use. \code{NULL} specifies the current default
-version (2). Versions prior to 2 are not supported, so this will only be relevant
-when there are later versions.}
-
-\item{compress}{a logical specifying whether saving to a named file is to use "gzip" compression,
-or one of \code{"gzip"}, \code{"bzip2"} or \code{"xz"} to indicate the type of
-compression to be used. Ignored if file is a connection.}
-
-\item{refhook}{a hook function for handling reference objects.}
-
-\item{raw}{whether to save the model in a raw variable or not, recommended to leave it to \code{TRUE}.}
-}
-\value{
-NULL invisibly.
-}
-\description{
-Calls \code{saveRDS} on an \code{lgb.Booster} object, making it serializable before the call if
-             it isn't already.
-
-             \bold{This function throws a warning and will be removed in future versions.}
-}
-\examples{
-\donttest{
-library(lightgbm)
-\dontshow{setLGBMthreads(2L)}
-\dontshow{data.table::setDTthreads(1L)}
-data(agaricus.train, package = "lightgbm")
-train <- agaricus.train
-dtrain <- lgb.Dataset(train$data, label = train$label)
-data(agaricus.test, package = "lightgbm")
-test <- agaricus.test
-dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
-params <- list(
-  objective = "regression"
-  , metric = "l2"
-  , min_data = 1L
-  , learning_rate = 1.0
-  , num_threads = 2L
-)
-valids <- list(test = dtest)
-model <- lgb.train(
-    params = params
-    , data = dtrain
-    , nrounds = 10L
-    , valids = valids
-    , early_stopping_rounds = 5L
-)
-model_file <- tempfile(fileext = ".rds")
-saveRDS.lgb.Booster(model, model_file)
-}
-}

R-package/pkgdown/_pkgdown.yml

@@ -85,8 +85,6 @@ reference:
     - '`lgb.save`'
     - '`lgb.load`'
     - '`lgb.model.dt.tree`'
-    - '`saveRDS.lgb.Booster`'
-    - '`readRDS.lgb.Booster`'
   - title: Model Interpretation
     desc: Analyze your models
     contents:

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

@@ -1252,45 +1252,6 @@ test_that("lgb.cv() correctly handles passing through params to the model file",
 
 })
 
-test_that("params (including dataset params) should be stored in .rds file for Booster", {
-    data(agaricus.train, package = "lightgbm")
-    dtrain <- lgb.Dataset(
-        agaricus.train$data
-        , label = agaricus.train$label
-        , params = list(
-            max_bin = 17L
-        )
-    )
-    params <- list(
-        objective = "binary"
-        , max_depth = 4L
-        , bagging_fraction = 0.8
-        , verbose = .LGB_VERBOSITY
-        , num_threads = .LGB_MAX_THREADS
-    )
-    bst <- Booster$new(
-        params = params
-        , train_set = dtrain
-    )
-    bst_file <- tempfile(fileext = ".rds")
-    expect_warning(saveRDS.lgb.Booster(bst, file = bst_file))
-
-    expect_warning({
-        bst_from_file <- readRDS.lgb.Booster(file = bst_file)
-    })
-    expect_identical(
-        bst_from_file$params
-        , list(
-            objective = "binary"
-            , max_depth = 4L
-            , bagging_fraction = 0.8
-            , verbose = .LGB_VERBOSITY
-            , num_threads = .LGB_MAX_THREADS
-            , max_bin = 17L
-        )
-    )
-})
-
 test_that("params (including dataset params) should be stored in .rds file for Booster", {
     data(agaricus.train, package = "lightgbm")
     dtrain <- lgb.Dataset(
@@ -1350,46 +1311,6 @@ test_that("Handle is automatically restored when calling predict", {
     expect_equal(pred_before, pred_after)
 })
 
-test_that("boosters with linear models at leaves work with saveRDS.lgb.Booster and readRDS.lgb.Booster", {
-    X <- matrix(rnorm(100L), ncol = 1L)
-    labels <- 2L * X + runif(nrow(X), 0L, 0.1)
-    dtrain <- lgb.Dataset(
-        data = X
-        , label = labels
-    )
-
-    params <- list(
-        objective = "regression"
-        , verbose = .LGB_VERBOSITY
-        , metric = "mse"
-        , seed = 0L
-        , num_leaves = 2L
-        , num_threads = .LGB_MAX_THREADS
-    )
-
-    bst <- lgb.train(
-        data = dtrain
-        , nrounds = 10L
-        , params = params
-    )
-    expect_true(.is_Booster(bst))
-
-    # save predictions, then write the model to a file and destroy it in R
-    preds <- predict(bst, X)
-    model_file <- tempfile(fileext = ".rds")
-    expect_warning(saveRDS.lgb.Booster(bst, file = model_file))
-    bst$finalize()
-    expect_null(bst$.__enclos_env__$private$handle)
-    rm(bst)
-
-    # load the booster and make predictions...should be the same
-    expect_warning({
-        bst2 <- readRDS.lgb.Booster(file = model_file)
-    })
-    preds2 <- predict(bst2, X)
-    expect_identical(preds, preds2)
-})
-
 test_that("boosters with linear models at leaves can be written to RDS and re-loaded successfully", {
     X <- matrix(rnorm(100L), ncol = 1L)
     labels <- 2L * X + runif(nrow(X), 0L, 0.1)