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#' @name readRDS.gpb.Booster
#' @title readRDS for \code{gpb.Booster} models
#' @description Attempts to load a model stored in a \code{.rds} file, using \code{\link[base]{readRDS}}
#' @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{gpb.Booster}
#'
#' @examples
#' \donttest{
#' library(gpboost)
#' data(agaricus.train, package = "gpboost")
#' train <- agaricus.train
#' dtrain <- gpb.Dataset(train$data, label = train$label)
#' data(agaricus.test, package = "gpboost")
#' test <- agaricus.test
#' dtest <- gpb.Dataset.create.valid(dtrain, test$data, label = test$label)
#' params <- list(objective = "regression", metric = "l2")
#' valids <- list(test = dtest)
#' model <- gpb.train(
#' params = params
#' , data = dtrain
#' , nrounds = 10L
#' , valids = valids
#' , min_data = 1L
#' , learning_rate = 1.0
#' , early_stopping_rounds = 5L
#' )
#' model_file <- tempfile(fileext = ".rds")
#' saveRDS.gpb.Booster(model, model_file)
#' new_model <- readRDS.gpb.Booster(model_file)
#' }
#' @export
readRDS.gpb.Booster <- function(file, refhook = NULL) {
object <- readRDS(file = file, refhook = refhook)
# Check if object has the model stored
if (!is.na(object$raw)) {
# Create temporary model for the model loading
object2 <- gpb.load(model_str = object$raw)
# Restore best iteration and recorded evaluations
object2$best_iter <- object$best_iter
object2$record_evals <- object$record_evals
object2$params <- object$params
# Return newly loaded object
return(object2)
} else {
# Return RDS loaded object
return(object)
}
}
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