[R-package] Add $raw to LightGBM (#347)

* Update lgb.Booster.R

* Add saveRDS (manual)

* Add documentation

* Change arguments passed from debug.

* Add readRDS, change way of saving.

* Change documentation.

* Add better documentation.

R-package/NAMESPACE

@@ -26,6 +26,8 @@ export(lgb.plot.interpretation)
 export(lgb.save)
 export(lgb.train)
 export(lightgbm)
+export(readRDS.lgb.Booster)
+export(saveRDS.lgb.Booster)
 export(setinfo)
 export(slice)
 import(methods)

R-package/R/lgb.Booster.R

@@ -195,7 +195,14 @@ Booster <- R6Class(
       predictor <- Predictor$new(private$handle)
       predictor$predict(data, num_iteration, rawscore, predleaf, header, reshape)
     },
-    to_predictor = function() { Predictor$new(private$handle) }
+    to_predictor = function() { Predictor$new(private$handle) },
+    raw = NA,
+    save = function() {
+      temp <- tempfile()
+      lgb.save(self, temp)
+      self$raw <- readChar(temp, file.info(temp)$size)
+      file.remove(temp)
+    }
   ),
   private = list(
     handle                   = NULL,

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

+#' readRDS for lgb.Booster models
+#'
+#' Attemps to load a model using RDS.
+#' 
+#' @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 an R object.
+#' 
+#' @examples
+#' \dontrun{
+#'   library(lightgbm)
+#'   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")
+#'   valids <- list(test=dtest)
+#'   model <- lgb.train(params, dtrain, 100, valids, min_data=1, learning_rate=1, early_stopping_rounds=10)
+#'   saveRDS.lgb.Booster(model, "model.rds")
+#'   new_model <- readRDS.lgb.Booster("model.rds")
+#' }
+#' @export
+
+readRDS.lgb.Booster <- function(file = "", refhook = NULL) {
+  
+  object <- readRDS(file = file, refhook = refhook)
+  if (!is.na(object$raw)) {
+    temp <- tempfile()
+    write(object$raw, temp)
+    object2 <- lgb.load(temp)
+    file.remove(temp)
+    object2$best_iter <- object$best_iter
+    object2$record_evals <- object$record_evals
+    return(object2)
+  } else {
+    return(object)
+  }
+  
+}

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

+#' saveRDS for lgb.Booster models
+#'
+#' Attemps to save a model using RDS. Has an additional parameter (\code{raw}) which decides whether to save the raw model or not.
+#' 
+#' @param object R 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
+#' \dontrun{
+#'   library(lightgbm)
+#'   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")
+#'   valids <- list(test=dtest)
+#'   model <- lgb.train(params, dtrain, 100, valids, min_data=1, learning_rate=1, early_stopping_rounds=10)
+#'   saveRDS.lgb.Booster(model, "model.rds")
+#' }
+#' @export
+
+saveRDS.lgb.Booster <- function(object, file = "", ascii = FALSE, version = NULL, compress = TRUE, refhook = NULL, raw = TRUE) {
+  
+  if (is.na(object$raw) & (raw)) {
+    object$save()
+    saveRDS(object, file = file, ascii = ascii, version = version, compress = compress, refhook = refhook)
+    object$raw <- NA
+  } else {
+    saveRDS(object, file = file, ascii = ascii, version = version, compress = compress, refhook = refhook)
+  }
+  
+}

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 lgb.Booster models}
+\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{
+an R object.
+}
+\description{
+Attemps to load a model using RDS.
+}
+\examples{
+\dontrun{
+  library(lightgbm)
+  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")
+  valids <- list(test=dtest)
+  model <- lgb.train(params, dtrain, 100, valids, min_data=1, learning_rate=1, early_stopping_rounds=10)
+  saveRDS.lgb.Booster(model, "model.rds")
+  new_model <- readRDS.lgb.Booster("model.rds")
+}
+}
+

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 lgb.Booster models}
+\usage{
+saveRDS.lgb.Booster(object, file = "", ascii = FALSE, version = NULL,
+  compress = TRUE, refhook = NULL, raw = TRUE)
+}
+\arguments{
+\item{object}{R 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{
+Attemps to save a model using RDS. Has an additional parameter (\code{raw}) which decides whether to save the raw model or not.
+}
+\examples{
+\dontrun{
+  library(lightgbm)
+  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")
+  valids <- list(test=dtest)
+  model <- lgb.train(params, dtrain, 100, valids, min_data=1, learning_rate=1, early_stopping_rounds=10)
+  saveRDS.lgb.Booster(model, "model.rds")
+}
+}
+