Skip to content

GitLab

Unverified Commit d24260fd authored by James Lamb's avatar James Lamb Committed by GitHub
Browse files

[R-package] require lgb.Dataset, remove support for passing 'colnames' and... 

[R-package] require lgb.Dataset, remove support for passing 'colnames' and 'categorical_feature' for lgb.train() and lgb.cv() (#6714)
parent c6d90bc7
Hide whitespace changes
Inline Side-by-side
Showing with 20 additions and 163 deletions
R-package/R/callback.R
View file @ d24260fd
...@@ -67,7 +67,7 @@ CB_ENV <- R6::R6Class( ...@@ -67,7 +67,7 @@ CB_ENV <- R6::R6Class(
} }
return(paste0(msg, collapse = " ")) return(paste(msg, collapse = " "))
} }
......
R-package/R/lgb.Dataset.R
View file @ d24260fd
...@@ -457,7 +457,7 @@ Dataset <- R6::R6Class( ...@@ -457,7 +457,7 @@ Dataset <- R6::R6Class(
if (!.is_null_handle(x = private$handle)) { if (!.is_null_handle(x = private$handle)) {
# Merge names with tab separation # Merge names with tab separation
merged_name <- paste0(as.list(private$colnames), collapse = "\t") merged_name <- paste(as.list(private$colnames), collapse = "\t")
.Call( .Call(
LGBM_DatasetSetFeatureNames_R LGBM_DatasetSetFeatureNames_R
, private$handle , private$handle
......
R-package/R/lgb.convert_with_rules.R
View file @ d24260fd
...@@ -5,7 +5,7 @@ ...@@ -5,7 +5,7 @@
vapply( vapply(
X = df X = df
, FUN = function(x) { , FUN = function(x) {
paste0(class(x), collapse = ",") paste(class(x), collapse = ",")
} }
, FUN.VALUE = character(1L) , FUN.VALUE = character(1L)
) )
......
R-package/R/lgb.cv.R
View file @ d24260fd
...@@ -25,8 +25,6 @@ CVBooster <- R6::R6Class( ...@@ -25,8 +25,6 @@ CVBooster <- R6::R6Class(
#' @description Cross validation logic used by LightGBM #' @description Cross validation logic used by LightGBM
#' @inheritParams lgb_shared_params #' @inheritParams lgb_shared_params
#' @param nfold the original dataset is randomly partitioned into \code{nfold} equal size subsamples. #' @param nfold the original dataset is randomly partitioned into \code{nfold} equal size subsamples.
#' @param label Deprecated. See "Deprecated Arguments" section below.
#' @param weight Deprecated. See "Deprecated Arguments" section below.
#' @param record Boolean, TRUE will record iteration message to \code{booster$record_evals} #' @param record Boolean, TRUE will record iteration message to \code{booster$record_evals}
#' @param showsd \code{boolean}, whether to show standard deviation of cross validation. #' @param showsd \code{boolean}, whether to show standard deviation of cross validation.
#' This parameter defaults to \code{TRUE}. Setting it to \code{FALSE} can lead to a #' This parameter defaults to \code{TRUE}. Setting it to \code{FALSE} can lead to a
...@@ -36,8 +34,6 @@ CVBooster <- R6::R6Class( ...@@ -36,8 +34,6 @@ CVBooster <- R6::R6Class(
#' @param folds \code{list} provides a possibility to use a list of pre-defined CV folds #' @param folds \code{list} provides a possibility to use a list of pre-defined CV folds
#' (each element must be a vector of test fold's indices). When folds are supplied, #' (each element must be a vector of test fold's indices). When folds are supplied,
#' the \code{nfold} and \code{stratified} parameters are ignored. #' the \code{nfold} and \code{stratified} parameters are ignored.
#' @param colnames Deprecated. See "Deprecated Arguments" section below.
#' @param categorical_feature Deprecated. See "Deprecated Arguments" section below.
#' @param callbacks List of callback functions that are applied at each iteration. #' @param callbacks List of callback functions that are applied at each iteration.
#' @param reset_data Boolean, setting it to TRUE (not the default value) will transform the booster model #' @param reset_data Boolean, setting it to TRUE (not the default value) will transform the booster model
#' into a predictor model which frees up memory and the original datasets #' into a predictor model which frees up memory and the original datasets
...@@ -69,20 +65,12 @@ CVBooster <- R6::R6Class( ...@@ -69,20 +65,12 @@ CVBooster <- R6::R6Class(
#' ) #' )
#' } #' }
#' #'
#' @section Deprecated Arguments:
#'
#' A future release of \code{lightgbm} will require passing an \code{lgb.Dataset}
#' to argument \code{'data'}. It will also remove support for passing arguments
#' \code{'categorical_feature'}, \code{'colnames'}, \code{'label'}, and \code{'weight'}.
#'
#' @importFrom data.table data.table setorderv #' @importFrom data.table data.table setorderv
#' @export #' @export
lgb.cv <- function(params = list() lgb.cv <- function(params = list()
, data , data
, nrounds = 100L , nrounds = 100L
, nfold = 3L , nfold = 3L
, label = NULL
, weight = NULL
, obj = NULL , obj = NULL
, eval = NULL , eval = NULL
, verbose = 1L , verbose = 1L
...@@ -92,8 +80,6 @@ lgb.cv <- function(params = list() ...@@ -92,8 +80,6 @@ lgb.cv <- function(params = list()
, stratified = TRUE , stratified = TRUE
, folds = NULL , folds = NULL
, init_model = NULL , init_model = NULL
, colnames = NULL
, categorical_feature = NULL
, early_stopping_rounds = NULL , early_stopping_rounds = NULL
, callbacks = list() , callbacks = list()
, reset_data = FALSE , reset_data = FALSE
...@@ -104,33 +90,8 @@ lgb.cv <- function(params = list() ...@@ -104,33 +90,8 @@ lgb.cv <- function(params = list()
if (nrounds <= 0L) { if (nrounds <= 0L) {
stop("nrounds should be greater than zero") stop("nrounds should be greater than zero")
} }
# If 'data' is not an lgb.Dataset, try to construct one using 'label'
if (!.is_Dataset(x = data)) { if (!.is_Dataset(x = data)) {
warning(paste0( stop("lgb.cv: data must be an lgb.Dataset instance")
"Passing anything other than an lgb.Dataset object to lgb.cv() is deprecated. "
, "Either pass an lgb.Dataset object, or use lightgbm()."
))
if (is.null(label)) {
stop("'label' must be provided for lgb.cv if 'data' is not an 'lgb.Dataset'")
}
data <- lgb.Dataset(data = data, label = label)
}
# raise deprecation warnings if necessary
# ref: https://github.com/microsoft/LightGBM/issues/6435
args <- names(match.call())
if ("categorical_feature" %in% args) {
.emit_dataset_kwarg_warning("categorical_feature", "lgb.cv")
}
if ("colnames" %in% args) {
.emit_dataset_kwarg_warning("colnames", "lgb.cv")
}
if ("label" %in% args) {
.emit_dataset_kwarg_warning("label", "lgb.cv")
}
if ("weight" %in% args) {
.emit_dataset_kwarg_warning("weight", "lgb.cv")
} }
# set some parameters, resolving the way they were passed in with other parameters # set some parameters, resolving the way they were passed in with other parameters
...@@ -214,37 +175,17 @@ lgb.cv <- function(params = list() ...@@ -214,37 +175,17 @@ lgb.cv <- function(params = list()
data$construct() data$construct()
# Check interaction constraints # Check interaction constraints
cnames <- NULL
if (!is.null(colnames)) {
cnames <- colnames
} else if (!is.null(data$get_colnames())) {
cnames <- data$get_colnames()
}
params[["interaction_constraints"]] <- .check_interaction_constraints( params[["interaction_constraints"]] <- .check_interaction_constraints(
interaction_constraints = interaction_constraints interaction_constraints = interaction_constraints
, column_names = cnames , column_names = data$get_colnames()
) )
if (!is.null(weight)) {
data$set_field(field_name = "weight", data = weight)
}
# Update parameters with parsed parameters # Update parameters with parsed parameters
data$update_params(params = params) data$update_params(params = params)
# Create the predictor set # Create the predictor set
data$.__enclos_env__$private$set_predictor(predictor = predictor) data$.__enclos_env__$private$set_predictor(predictor = predictor)
# Write column names
if (!is.null(colnames)) {
data$set_colnames(colnames = colnames)
}
# Write categorical features
if (!is.null(categorical_feature)) {
data$set_categorical_feature(categorical_feature = categorical_feature)
}
if (!is.null(folds)) { if (!is.null(folds)) {
# Check for list of folds or for single value # Check for list of folds or for single value
......
R-package/R/lgb.train.R
View file @ d24260fd
...@@ -6,8 +6,6 @@ ...@@ -6,8 +6,6 @@
#' @inheritParams lgb_shared_params #' @inheritParams lgb_shared_params
#' @param valids a list of \code{lgb.Dataset} objects, used for validation #' @param valids a list of \code{lgb.Dataset} objects, used for validation
#' @param record Boolean, TRUE will record iteration message to \code{booster$record_evals} #' @param record Boolean, TRUE will record iteration message to \code{booster$record_evals}
#' @param colnames Deprecated. See "Deprecated Arguments" section below.
#' @param categorical_feature Deprecated. See "Deprecated Arguments" section below.
#' @param callbacks List of callback functions that are applied at each iteration. #' @param callbacks List of callback functions that are applied at each iteration.
#' @param reset_data Boolean, setting it to TRUE (not the default value) will transform the #' @param reset_data Boolean, setting it to TRUE (not the default value) will transform the
#' booster model into a predictor model which frees up memory and the #' booster model into a predictor model which frees up memory and the
...@@ -42,12 +40,6 @@ ...@@ -42,12 +40,6 @@
#' ) #' )
#' } #' }
#' #'
#' @section Deprecated Arguments:
#'
#' A future release of \code{lightgbm} will remove support for passing arguments
#' \code{'categorical_feature'} and \code{'colnames'}. Pass those things to
#' \code{lgb.Dataset} instead.
#'
#' @export #' @export
lgb.train <- function(params = list(), lgb.train <- function(params = list(),
data, data,
...@@ -59,8 +51,6 @@ lgb.train <- function(params = list(), ...@@ -59,8 +51,6 @@ lgb.train <- function(params = list(),
record = TRUE, record = TRUE,
eval_freq = 1L, eval_freq = 1L,
init_model = NULL, init_model = NULL,
colnames = NULL,
categorical_feature = NULL,
early_stopping_rounds = NULL, early_stopping_rounds = NULL,
callbacks = list(), callbacks = list(),
reset_data = FALSE, reset_data = FALSE,
...@@ -83,16 +73,6 @@ lgb.train <- function(params = list(), ...@@ -83,16 +73,6 @@ lgb.train <- function(params = list(),
} }
} }
# raise deprecation warnings if necessary
# ref: https://github.com/microsoft/LightGBM/issues/6435
args <- names(match.call())
if ("categorical_feature" %in% args) {
.emit_dataset_kwarg_warning("categorical_feature", "lgb.train")
}
if ("colnames" %in% args) {
.emit_dataset_kwarg_warning("colnames", "lgb.train")
}
# set some parameters, resolving the way they were passed in with other parameters # set some parameters, resolving the way they were passed in with other parameters
# in `params`. # in `params`.
# this ensures that the model stored with Booster$save() correctly represents # this ensures that the model stored with Booster$save() correctly represents
...@@ -171,21 +151,12 @@ lgb.train <- function(params = list(), ...@@ -171,21 +151,12 @@ lgb.train <- function(params = list(),
# Construct datasets, if needed # Construct datasets, if needed
data$update_params(params = params) data$update_params(params = params)
if (!is.null(categorical_feature)) {
data$set_categorical_feature(categorical_feature)
}
data$construct() data$construct()
# Check interaction constraints # Check interaction constraints
cnames <- NULL
if (!is.null(colnames)) {
cnames <- colnames
} else if (!is.null(data$get_colnames())) {
cnames <- data$get_colnames()
}
params[["interaction_constraints"]] <- .check_interaction_constraints( params[["interaction_constraints"]] <- .check_interaction_constraints(
interaction_constraints = interaction_constraints interaction_constraints = interaction_constraints
, column_names = cnames , column_names = data$get_colnames()
) )
# Update parameters with parsed parameters # Update parameters with parsed parameters
...@@ -194,11 +165,6 @@ lgb.train <- function(params = list(), ...@@ -194,11 +165,6 @@ lgb.train <- function(params = list(),
# Create the predictor set # Create the predictor set
data$.__enclos_env__$private$set_predictor(predictor) data$.__enclos_env__$private$set_predictor(predictor)
# Write column names
if (!is.null(colnames)) {
data$set_colnames(colnames)
}
valid_contain_train <- FALSE valid_contain_train <- FALSE
train_data_name <- "train" train_data_name <- "train"
reduced_valid_sets <- list() reduced_valid_sets <- list()
......
R-package/R/utils.R
View file @ d24260fd
...@@ -34,7 +34,7 @@ ...@@ -34,7 +34,7 @@
# If a parameter has multiple values, join those values together with commas. # If a parameter has multiple values, join those values together with commas.
# trimws() is necessary because format() will pad to make strings the same width # trimws() is necessary because format() will pad to make strings the same width
val <- paste0( val <- paste(
trimws( trimws(
format( format(
x = unname(params[[i]]) x = unname(params[[i]])
...@@ -46,7 +46,7 @@ ...@@ -46,7 +46,7 @@
if (nchar(val) <= 0L) next # Skip join if (nchar(val) <= 0L) next # Skip join
# Join key value # Join key value
pair <- paste0(c(param_names[[i]], val), collapse = "=") pair <- paste(c(param_names[[i]], val), collapse = "=")
ret <- c(ret, pair) ret <- c(ret, pair)
} }
...@@ -55,7 +55,7 @@ ...@@ -55,7 +55,7 @@
return("") return("")
} }
return(paste0(ret, collapse = " ")) return(paste(ret, collapse = " "))
} }
...@@ -115,7 +115,7 @@ ...@@ -115,7 +115,7 @@
# Turn indices 0-based and convert to string # Turn indices 0-based and convert to string
for (j in seq_along(interaction_constraints)) { for (j in seq_along(interaction_constraints)) {
interaction_constraints[[j]] <- paste0( interaction_constraints[[j]] <- paste0(
"[", paste0(interaction_constraints[[j]] - 1L, collapse = ","), "]" "[", paste(interaction_constraints[[j]] - 1L, collapse = ","), "]"
) )
} }
return(interaction_constraints) return(interaction_constraints)
...@@ -258,19 +258,3 @@ ...@@ -258,19 +258,3 @@
return(a == b) return(a == b)
} }
} }
# ref: https://github.com/microsoft/LightGBM/issues/6435
.emit_dataset_kwarg_warning <- function(calling_function, argname) {
msg <- sprintf(
paste0(
"Argument '%s' to %s() is deprecated and will be removed in a future release. "
, "Set '%s' with lgb.Dataset() instead. "
, "See https://github.com/microsoft/LightGBM/issues/6435."
)
, argname
, calling_function
, argname
)
warning(msg)
return(invisible(NULL))
}
R-package/man/lgb.cv.Rd
View file @ d24260fd
...@@ -9,8 +9,6 @@ lgb.cv( ...@@ -9,8 +9,6 @@ lgb.cv(
data, data,
nrounds = 100L, nrounds = 100L,
nfold = 3L, nfold = 3L,
label = NULL,
weight = NULL,
obj = NULL, obj = NULL,
eval = NULL, eval = NULL,
verbose = 1L, verbose = 1L,
...@@ -20,8 +18,6 @@ lgb.cv( ...@@ -20,8 +18,6 @@ lgb.cv(
stratified = TRUE, stratified = TRUE,
folds = NULL, folds = NULL,
init_model = NULL, init_model = NULL,
colnames = NULL,
categorical_feature = NULL,
early_stopping_rounds = NULL, early_stopping_rounds = NULL,
callbacks = list(), callbacks = list(),
reset_data = FALSE, reset_data = FALSE,
...@@ -41,10 +37,6 @@ may allow you to pass other types of data like \code{matrix} and then separately ...@@ -41,10 +37,6 @@ may allow you to pass other types of data like \code{matrix} and then separately
\item{nfold}{the original dataset is randomly partitioned into \code{nfold} equal size subsamples.} \item{nfold}{the original dataset is randomly partitioned into \code{nfold} equal size subsamples.}
\item{label}{Deprecated. See "Deprecated Arguments" section below.}
\item{weight}{Deprecated. See "Deprecated Arguments" section below.}
\item{obj}{objective function, can be character or custom objective function. Examples include \item{obj}{objective function, can be character or custom objective function. Examples include
\code{regression}, \code{regression_l1}, \code{huber}, \code{regression}, \code{regression_l1}, \code{huber},
\code{binary}, \code{lambdarank}, \code{multiclass}, \code{multiclass}} \code{binary}, \code{lambdarank}, \code{multiclass}, \code{multiclass}}
...@@ -103,10 +95,6 @@ the \code{nfold} and \code{stratified} parameters are ignored.} ...@@ -103,10 +95,6 @@ the \code{nfold} and \code{stratified} parameters are ignored.}
\item{init_model}{path of model file or \code{lgb.Booster} object, will continue training from this model} \item{init_model}{path of model file or \code{lgb.Booster} object, will continue training from this model}
\item{colnames}{Deprecated. See "Deprecated Arguments" section below.}
\item{categorical_feature}{Deprecated. See "Deprecated Arguments" section below.}
\item{early_stopping_rounds}{int. Activates early stopping. When this parameter is non-null, \item{early_stopping_rounds}{int. Activates early stopping. When this parameter is non-null,
training will stop if the evaluation of any metric on any validation set training will stop if the evaluation of any metric on any validation set
fails to improve for \code{early_stopping_rounds} consecutive boosting rounds. fails to improve for \code{early_stopping_rounds} consecutive boosting rounds.
...@@ -131,14 +119,6 @@ a trained model \code{lgb.CVBooster}. ...@@ -131,14 +119,6 @@ a trained model \code{lgb.CVBooster}.
\description{ \description{
Cross validation logic used by LightGBM Cross validation logic used by LightGBM
} }
\section{Deprecated Arguments}{
A future release of \code{lightgbm} will require passing an \code{lgb.Dataset}
to argument \code{'data'}. It will also remove support for passing arguments
\code{'categorical_feature'}, \code{'colnames'}, \code{'label'}, and \code{'weight'}.
}
\section{Early Stopping}{ \section{Early Stopping}{
......
R-package/man/lgb.train.Rd
View file @ d24260fd
...@@ -15,8 +15,6 @@ lgb.train( ...@@ -15,8 +15,6 @@ lgb.train(
record = TRUE, record = TRUE,
eval_freq = 1L, eval_freq = 1L,
init_model = NULL, init_model = NULL,
colnames = NULL,
categorical_feature = NULL,
early_stopping_rounds = NULL, early_stopping_rounds = NULL,
callbacks = list(), callbacks = list(),
reset_data = FALSE, reset_data = FALSE,
...@@ -82,10 +80,6 @@ printing of evaluation during training} ...@@ -82,10 +80,6 @@ printing of evaluation during training}
\item{init_model}{path of model file or \code{lgb.Booster} object, will continue training from this model} \item{init_model}{path of model file or \code{lgb.Booster} object, will continue training from this model}
\item{colnames}{Deprecated. See "Deprecated Arguments" section below.}
\item{categorical_feature}{Deprecated. See "Deprecated Arguments" section below.}
\item{early_stopping_rounds}{int. Activates early stopping. When this parameter is non-null, \item{early_stopping_rounds}{int. Activates early stopping. When this parameter is non-null,
training will stop if the evaluation of any metric on any validation set training will stop if the evaluation of any metric on any validation set
fails to improve for \code{early_stopping_rounds} consecutive boosting rounds. fails to improve for \code{early_stopping_rounds} consecutive boosting rounds.
...@@ -109,14 +103,6 @@ Low-level R interface to train a LightGBM model. Unlike \code{\link{lightgbm}}, ...@@ -109,14 +103,6 @@ Low-level R interface to train a LightGBM model. Unlike \code{\link{lightgbm}},
this function is focused on performance (e.g. speed, memory efficiency). It is also this function is focused on performance (e.g. speed, memory efficiency). It is also
less likely to have breaking API changes in new releases than \code{\link{lightgbm}}. less likely to have breaking API changes in new releases than \code{\link{lightgbm}}.
} }
\section{Deprecated Arguments}{
A future release of \code{lightgbm} will remove support for passing arguments
\code{'categorical_feature'} and \code{'colnames'}. Pass those things to
\code{lgb.Dataset} instead.
}
\section{Early Stopping}{ \section{Early Stopping}{
......
R-package/src/install.libs.R
View file @ d24260fd
...@@ -51,7 +51,7 @@ inst_dir <- file.path(R_PACKAGE_SOURCE, "inst", fsep = "/") ...@@ -51,7 +51,7 @@ inst_dir <- file.path(R_PACKAGE_SOURCE, "inst", fsep = "/")
, "make this faster." , "make this faster."
)) ))
} }
cmd <- paste0(cmd, " ", paste0(args, collapse = " ")) cmd <- paste0(cmd, " ", paste(args, collapse = " "))
exit_code <- system(cmd) exit_code <- system(cmd)
} }
......
R-package/tests/testthat/test_basic.R
View file @ d24260fd
...@@ -433,7 +433,7 @@ test_that("lgb.cv() rejects negative or 0 value passed to nrounds", { ...@@ -433,7 +433,7 @@ test_that("lgb.cv() rejects negative or 0 value passed to nrounds", {
} }
}) })
test_that("lgb.cv() throws an informative error if 'data' is not an lgb.Dataset and labels are not given", { test_that("lgb.cv() throws an informative error if 'data' is not an lgb.Dataset", {
bad_values <- list( bad_values <- list(
4L 4L
, "hello" , "hello"
...@@ -454,7 +454,7 @@ test_that("lgb.cv() throws an informative error if 'data' is not an lgb.Dataset ...@@ -454,7 +454,7 @@ test_that("lgb.cv() throws an informative error if 'data' is not an lgb.Dataset
, 10L , 10L
, nfold = 5L , nfold = 5L
) )
}, regexp = "'label' must be provided for lgb.cv if 'data' is not an 'lgb.Dataset'", fixed = TRUE) }, regexp = "lgb.cv: data must be an lgb.Dataset instance", fixed = TRUE)
} }
}) })
......
R-package/tests/testthat/test_lgb.Booster.R
View file @ d24260fd
...@@ -888,7 +888,7 @@ test_that("Saving a model with different feature importance types works", { ...@@ -888,7 +888,7 @@ test_that("Saving a model with different feature importance types works", {
.feat_importance_from_string <- function(model_string) { .feat_importance_from_string <- function(model_string) {
file_lines <- strsplit(model_string, "\n", fixed = TRUE)[[1L]] file_lines <- strsplit(model_string, "\n", fixed = TRUE)[[1L]]
start_indx <- which(grepl("^feature_importances\\:$", file_lines)) + 1L start_indx <- which(file_lines == "feature_importances:") + 1L
blank_line_indices <- which(file_lines == "") blank_line_indices <- which(file_lines == "")
end_indx <- blank_line_indices[blank_line_indices > start_indx][1L] - 1L end_indx <- blank_line_indices[blank_line_indices > start_indx][1L] - 1L
importances <- file_lines[start_indx: end_indx] importances <- file_lines[start_indx: end_indx]
...@@ -955,7 +955,7 @@ test_that("Saving a model with unknown importance type fails", { ...@@ -955,7 +955,7 @@ test_that("Saving a model with unknown importance type fails", {
.params_from_model_string <- function(model_str) { .params_from_model_string <- function(model_str) {
file_lines <- strsplit(model_str, "\n", fixed = TRUE)[[1L]] file_lines <- strsplit(model_str, "\n", fixed = TRUE)[[1L]]
start_indx <- which(grepl("^parameters\\:$", file_lines)) + 1L start_indx <- which(file_lines == "parameters:") + 1L
blank_line_indices <- which(file_lines == "") blank_line_indices <- which(file_lines == "")
end_indx <- blank_line_indices[blank_line_indices > start_indx][1L] - 1L end_indx <- blank_line_indices[blank_line_indices > start_indx][1L] - 1L
params <- file_lines[start_indx: end_indx] params <- file_lines[start_indx: end_indx]
...@@ -1532,7 +1532,7 @@ test_that("Booster's print, show, and summary work correctly", { ...@@ -1532,7 +1532,7 @@ test_that("Booster's print, show, and summary work correctly", {
} }
.has_expected_content_for_finalized_model <- function(printed_txt) { .has_expected_content_for_finalized_model <- function(printed_txt) {
expect_true(any(grepl("^LightGBM Model$", printed_txt))) expect_true(any(printed_txt == "LightGBM Model"))
expect_true(any(grepl("Booster handle is invalid", printed_txt, fixed = TRUE))) expect_true(any(grepl("Booster handle is invalid", printed_txt, fixed = TRUE)))
} }
......
R-package/tests/testthat/test_parameters.R
View file @ d24260fd
...@@ -18,7 +18,7 @@ test_that("Feature penalties work properly", { ...@@ -18,7 +18,7 @@ test_that("Feature penalties work properly", {
num_leaves = 5L num_leaves = 5L
, learning_rate = 0.05 , learning_rate = 0.05
, objective = "binary" , objective = "binary"
, feature_penalty = paste0(feature_penalties, collapse = ",") , feature_penalty = paste(feature_penalties, collapse = ",")
, metric = "binary_error" , metric = "binary_error"
, num_threads = .LGB_MAX_THREADS , num_threads = .LGB_MAX_THREADS
) )
......
build_r.R
View file @ d24260fd
...@@ -121,7 +121,7 @@ if (length(parsed_args[["make_args"]]) > 0L) { ...@@ -121,7 +121,7 @@ if (length(parsed_args[["make_args"]]) > 0L) {
pattern = "make_args_from_build_script <- character(0L)" pattern = "make_args_from_build_script <- character(0L)"
, replacement = paste0( , replacement = paste0(
"make_args_from_build_script <- c(\"" "make_args_from_build_script <- c(\""
, paste0(parsed_args[["make_args"]], collapse = "\", \"") , paste(parsed_args[["make_args"]], collapse = "\", \"")
, "\")" , "\")"
) )
, x = install_libs_content , x = install_libs_content
...@@ -167,7 +167,7 @@ if (length(parsed_args[["make_args"]]) > 0L) { ...@@ -167,7 +167,7 @@ if (length(parsed_args[["make_args"]]) > 0L) {
, "make this faster." , "make this faster."
)) ))
} }
cmd <- paste0(cmd, " ", paste0(args, collapse = " ")) cmd <- paste0(cmd, " ", paste(args, collapse = " "))
exit_code <- system(cmd) exit_code <- system(cmd)
} }
...@@ -426,6 +426,6 @@ install_args <- c("CMD", "INSTALL", "--no-multiarch", "--with-keep.source", tarb ...@@ -426,6 +426,6 @@ install_args <- c("CMD", "INSTALL", "--no-multiarch", "--with-keep.source", tarb
if (INSTALL_AFTER_BUILD) { if (INSTALL_AFTER_BUILD) {
.run_shell_command(install_cmd, install_args) .run_shell_command(install_cmd, install_args)
} else { } else {
cmd <- paste0(install_cmd, " ", paste0(install_args, collapse = " ")) cmd <- paste0(install_cmd, " ", paste(install_args, collapse = " "))
print(sprintf("Skipping installation. Install the package with command '%s'", cmd)) print(sprintf("Skipping installation. Install the package with command '%s'", cmd))
} }
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment