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lightgbm-org--lightgbm/R-package/R/lgb.restore_handle.R
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2026-07-13 13:27:18 +08:00

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#' @name lgb.restore_handle
#' @title Restore the C++ component of a de-serialized LightGBM model
#' @description After a LightGBM model object is de-serialized through functions such as \code{save} or
#' \code{saveRDS}, its underlying C++ object will be blank and needs to be restored to able to use it. Such
#' object is restored automatically when calling functions such as \code{predict}, but this function can be
#' used to forcibly restore it beforehand. Note that the object will be modified in-place.
#'
#' \emph{New in version 4.0.0}
#'
#' @details Be aware that fast single-row prediction configurations are not restored through this
#' function. If you wish to make fast single-row predictions using a \code{lgb.Booster} loaded this way,
#' call \link{lgb.configure_fast_predict} on the loaded \code{lgb.Booster} object.
#' @param model \code{lgb.Booster} object which was de-serialized and whose underlying C++ object and R handle
#' need to be restored.
#'
#' @return \code{lgb.Booster} (the same `model` object that was passed as input, invisibly).
#' @seealso \link{lgb.make_serializable}, \link{lgb.drop_serialized}.
#' @examples
#' \donttest{
#' library(lightgbm)
#' \dontshow{setLGBMthreads(2L)}
#' \dontshow{data.table::setDTthreads(1L)}
#' data("agaricus.train")
#' model <- lightgbm(
#' agaricus.train$data
#' , agaricus.train$label
#' , params = list(objective = "binary")
#' , nrounds = 5L
#' , verbose = 0
#' , num_threads = 2L
#' )
#' fname <- tempfile(fileext="rds")
#' saveRDS(model, fname)
#'
#' model_new <- readRDS(fname)
#' model_new$check_null_handle()
#' lgb.restore_handle(model_new)
#' model_new$check_null_handle()
#' }
#' @export
lgb.restore_handle <- function(model) {
if (!.is_Booster(x = model)) {
stop("lgb.restore_handle: model should be an ", sQuote("lgb.Booster", q = FALSE))
}
model$restore_handle()
return(invisible(model))
}