add saveload to raw

R-package/R/utils.R

@@ -57,10 +57,13 @@ xgb.Booster <- function(params = list(), cachelist = list(), modelfile = NULL) {
     }
   }
   if (!is.null(modelfile)) {
-    if (typeof(modelfile) != "character") {
-      stop("xgb.Booster: modelfile must be character")
+    if (typeof(modelfile) == "character") {
+      .Call("XGBoosterLoadModel_R", handle, modelfile, PACKAGE = "xgboost")
+    } else if (typeof(modelfile) == "raw") {
+      .Call("XGBoosterLoadModelFromRaw_R", handle, modelfile, PACKAGE = "xgboost")      
+    } else {
+      stop("xgb.Booster: modelfile must be character or raw vector")
     }
-    .Call("XGBoosterLoadModel_R", handle, modelfile, PACKAGE = "xgboost")
   }
   return(structure(handle, class = "xgb.Booster"))
 }

R-package/R/xgb.save.raw.R

@@ -0,0 +1,27 @@
+#' Save xgboost model to R's raw vector,
+#' user can call xgb.load to load the model back from raw vector
+#' 
+#' Save xgboost model from xgboost or xgb.train
+#' 
+#' @param model the model object.
+#' 
+#' @examples
+#' data(agaricus.train, package='xgboost')
+#' data(agaricus.test, package='xgboost')
+#' train <- agaricus.train
+#' test <- agaricus.test
+#' bst <- xgboost(data = train$data, label = train$label, max.depth = 2, 
+#'                eta = 1, nround = 2,objective = "binary:logistic")
+#' raw <- xgb.save(bst)
+#' bst <- xgb.load(raw)
+#' pred <- predict(bst, test$data)
+#' @export
+#' 
+xgb.save.raw <- function(model) {
+  if (class(model) == "xgb.Booster") {
+    raw <- .Call("XGBoosterModelToRaw_R", model, PACKAGE = "xgboost")
+    return(raw)
+  }
+  stop("xgb.raw: the input must be xgb.Booster. Use xgb.DMatrix.save to save
+       xgb.DMatrix object.")
+}