[R-package] [c++] add tighter multithreading control, avoid global OpenMP side...

[R-package] [c++] add tighter multithreading control, avoid global OpenMP side effects (fixes #4705, fixes #5102) (#6226)

R-package/man/lgb.Dataset.Rd

@@ -65,6 +65,8 @@ Construct \code{lgb.Dataset} object from dense matrix, sparse matrix
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train
 dtrain <- lgb.Dataset(train$data, label = train$label)

R-package/man/lgb.Dataset.construct.Rd

@@ -17,6 +17,8 @@ Construct Dataset explicitly
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train
 dtrain <- lgb.Dataset(train$data, label = train$label)

R-package/man/lgb.Dataset.create.valid.Rd

@@ -48,6 +48,8 @@ Construct validation data according to training data
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train
 dtrain <- lgb.Dataset(train$data, label = train$label)

R-package/man/lgb.Dataset.save.Rd

@@ -20,6 +20,8 @@ Please note that \code{init_score} is not saved in binary file.
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train
 dtrain <- lgb.Dataset(train$data, label = train$label)

R-package/man/lgb.Dataset.set.categorical.Rd

@@ -22,6 +22,8 @@ Set the categorical features of an \code{lgb.Dataset} object. Use this function
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train
 dtrain <- lgb.Dataset(train$data, label = train$label)

R-package/man/lgb.Dataset.set.reference.Rd

@@ -19,6 +19,8 @@ If you want to use validation data, you should set reference to training data
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 # create training Dataset
 data(agaricus.train, package ="lightgbm")
 train <- agaricus.train

R-package/man/lgb.configure_fast_predict.Rd

@@ -114,6 +114,8 @@ Calling this function multiple times with different parameters might not overrid
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 library(lightgbm)
 data(mtcars)
 X <- as.matrix(mtcars[, -1L])

R-package/man/lgb.cv.Rd

@@ -152,6 +152,8 @@ Cross validation logic used by LightGBM
 
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train
 dtrain <- lgb.Dataset(train$data, label = train$label)

R-package/man/lgb.dump.Rd

@@ -20,6 +20,8 @@ Dump LightGBM model to json
 \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)

R-package/man/lgb.get.eval.result.Rd

@@ -33,6 +33,8 @@ Given a \code{lgb.Booster}, return evaluation results for a
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 # train a regression model
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train

R-package/man/lgb.importance.Rd

@@ -25,6 +25,8 @@ Creates a \code{data.table} of feature importances in a model.
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train
 dtrain <- lgb.Dataset(train$data, label = train$label)

R-package/man/lgb.interprete.Rd

@@ -30,6 +30,8 @@ Computes feature contribution components of rawscore prediction.
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 Logit <- function(x) log(x / (1.0 - x))
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train

R-package/man/lgb.load.Rd

@@ -20,6 +20,8 @@ Load LightGBM takes in either a file path or model string.
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train
 dtrain <- lgb.Dataset(train$data, label = train$label)

R-package/man/lgb.model.dt.tree.Rd

@@ -40,6 +40,8 @@ Parse a LightGBM model json dump into a \code{data.table} structure.
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train
 dtrain <- lgb.Dataset(train$data, label = train$label)

R-package/man/lgb.plot.importance.Rd

@@ -38,6 +38,8 @@ Features are shown ranked in a decreasing importance order.
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train
 dtrain <- lgb.Dataset(train$data, label = train$label)

R-package/man/lgb.plot.interpretation.Rd

@@ -35,6 +35,8 @@ contribution of a feature. Features are shown ranked in a decreasing contributio
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 Logit <- function(x) {
   log(x / (1.0 - x))
 }

R-package/man/lgb.restore_handle.Rd

@@ -27,7 +27,10 @@ function. If you wish to make fast single-row predictions using a \code{lgb.Boos
 call \link{lgb.configure_fast_predict} on the loaded \code{lgb.Booster} object.
 }
 \examples{
+\donttest{
 library(lightgbm)
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 data("agaricus.train")
 model <- lightgbm(
   agaricus.train$data
@@ -45,6 +48,7 @@ model_new$check_null_handle()
 lgb.restore_handle(model_new)
 model_new$check_null_handle()
 }
+}
 \seealso{
 \link{lgb.make_serializable}, \link{lgb.drop_serialized}.
 }

R-package/man/lgb.save.Rd

@@ -21,6 +21,8 @@ Save LightGBM model
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 library(lightgbm)
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train

R-package/man/lgb.train.Rd

@@ -130,6 +130,8 @@ Low-level R interface to train a LightGBM model. Unlike \code{\link{lightgbm}},
 
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train
 dtrain <- lgb.Dataset(train$data, label = train$label)

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

@@ -121,6 +121,8 @@ If the model object has been configured for fast single-row predictions through
 }
 \examples{
 \donttest{
+\dontshow{setLGBMthreads(2L)}
+\dontshow{data.table::setDTthreads(1L)}
 data(agaricus.train, package = "lightgbm")
 train <- agaricus.train
 dtrain <- lgb.Dataset(train$data, label = train$label)