[R-package] moved parameter validations up earlier in function calls (#…

…2663)

R-package/R/callback.R

@@ -29,11 +29,10 @@ cb.reset.parameters <- function(new_params) {
   # Run some checks in the beginning
   init <- function(env) {
 
-    # Store boosting rounds
-    nrounds <<- env$end_iteration - env$begin_iteration + 1L
-
     # Check for model environment
-    if (is.null(env$model)) { stop("Env should have a ", sQuote("model")) }
+    if (is.null(env$model)) {
+      stop("Env should have a ", sQuote("model"))
+    }
 
     # Some parameters are not allowed to be changed,
     # since changing them would simply wreck some chaos
@@ -50,6 +49,9 @@ cb.reset.parameters <- function(new_params) {
       )
     }
 
+    # Store boosting rounds
+    nrounds <<- env$end_iteration - env$begin_iteration + 1L
+
     # Check parameter names
     for (n in pnames) {
 
@@ -285,14 +287,14 @@ cb.early.stop <- function(stopping_rounds, verbose = TRUE) {
   # Initialization function
   init <- function(env) {
 
-    # Store evaluation length
-    eval_len <<- length(env$eval_list)
-
     # Early stopping cannot work without metrics
-    if (eval_len == 0L) {
+    if (length(env$eval_list) == 0L) {
       stop("For early stopping, valids must have at least one element")
     }
 
+    # Store evaluation length
+    eval_len <<- length(env$eval_list)
+
     # Check if verbose or not
     if (isTRUE(verbose)) {
       cat("Will train until there is no improvement in ", stopping_rounds, " rounds.\n\n", sep = "")

R-package/R/lgb.Booster.R

@@ -781,15 +781,21 @@ lgb.load <- function(filename = NULL, model_str = NULL) {
   }
 
   # Return new booster
-  if (!is.null(filename) && !file.exists(filename)) stop("lgb.load: file does not exist for supplied filename")
-  if (!is.null(filename)) return(invisible(Booster$new(modelfile = filename)))
+  if (!is.null(filename) && !file.exists(filename)) {
+    stop("lgb.load: file does not exist for supplied filename")
+  }
+  if (!is.null(filename)) {
+    return(invisible(Booster$new(modelfile = filename)))
+  }
 
   # Load from model_str
   if (!is.null(model_str) && !is.character(model_str)) {
     stop("lgb.load: model_str should be character")
   }
   # Return new booster
-  if (!is.null(model_str)) return(invisible(Booster$new(model_str = model_str)))
+  if (!is.null(model_str)) {
+    return(invisible(Booster$new(model_str = model_str)))
+  }
 
 }
 
@@ -831,8 +837,8 @@ lgb.save <- function(booster, filename, num_iteration = NULL) {
   }
 
   # Check if file name is character
-  if (!is.character(filename)) {
-    stop("lgb.save: filename should be a character")
+  if (!(is.character(filename) && length(filename) == 1L)) {
+    stop("lgb.save: filename should be a string")
   }
 
   # Store booster

R-package/R/lgb.Dataset.R

@@ -32,6 +32,14 @@ Dataset <- R6::R6Class(
                           info = list(),
                           ...) {
 
+      # validate inputs early to avoid unnecessary computation
+      if (!(is.null(reference) || lgb.check.r6.class(reference, "lgb.Dataset"))) {
+          stop("lgb.Dataset: If provided, reference must be a ", sQuote("lgb.Dataset"))
+      }
+      if (!(is.null(predictor) || lgb.check.r6.class(predictor, "lgb.Predictor"))) {
+          stop("lgb.Dataset: If provided, predictor must be a ", sQuote("lgb.Predictor"))
+      }
+
       # Check for additional parameters
       additional_params <- list(...)
 
@@ -56,20 +64,6 @@ Dataset <- R6::R6Class(
 
       }
 
-      # Check for dataset reference
-      if (!is.null(reference)) {
-        if (!lgb.check.r6.class(reference, "lgb.Dataset")) {
-          stop("lgb.Dataset: Can only use ", sQuote("lgb.Dataset"), " as reference")
-        }
-      }
-
-      # Check for predictor reference
-      if (!is.null(predictor)) {
-        if (!lgb.check.r6.class(predictor, "lgb.Predictor")) {
-          stop("lgb.Dataset: Only can use ", sQuote("lgb.Predictor"), " as predictor")
-        }
-      }
-
       # Check for matrix format
       if (is.matrix(data)) {
         # Check whether matrix is the correct type first ("double")

R-package/R/lgb.cv.R

@@ -22,7 +22,7 @@ CVBooster <- R6::R6Class(
 #' @description Cross validation logic used by LightGBM
 #' @inheritParams lgb_shared_params
 #' @param nfold the original dataset is randomly partitioned into \code{nfold} equal size subsamples.
-#' @param label vector of response values. Should be provided only when data is an R-matrix.
+#' @param label Vector of labels, used if \code{data} is not an \code{\link{lgb.Dataset}}
 #' @param weight vector of response values. If not NULL, will set to dataset
 #' @param obj objective function, can be character or custom objective function. Examples include
 #'            \code{regression}, \code{regression_l1}, \code{huber},
@@ -95,6 +95,19 @@ lgb.cv <- function(params = list()
                    , ...
                    ) {
 
+  # validate parameters
+  if (nrounds <= 0L) {
+    stop("nrounds should be greater than zero")
+  }
+
+  # If 'data' is not an lgb.Dataset, try to construct one using 'label'
+  if (!lgb.is.Dataset(data)) {
+    if (is.null(label)) {
+      stop("'label' must be provided for lgb.cv if 'data' is not an 'lgb.Dataset'")
+    }
+    data <- lgb.Dataset(data, label = label)
+  }
+
   # Setup temporary variables
   params <- append(params, list(...))
   params$verbose <- verbose
@@ -103,10 +116,6 @@ lgb.cv <- function(params = list()
   fobj <- NULL
   feval <- NULL
 
-  if (nrounds <= 0L) {
-    stop("nrounds should be greater than zero")
-  }
-
   # Check for objective (function or not)
   if (is.function(params$objective)) {
     fobj <- params$objective
@@ -141,14 +150,6 @@ lgb.cv <- function(params = list()
     end_iteration <- begin_iteration + nrounds - 1L
   }
 
-  # Check for training dataset type correctness
-  if (!lgb.is.Dataset(data)) {
-    if (is.null(label)) {
-      stop("Labels must be provided for lgb.cv")
-    }
-    data <- lgb.Dataset(data, label = label)
-  }
-
   # Check for weights
   if (!is.null(weight)) {
     data$setinfo("weight", weight)

R-package/R/lgb.importance.R

@@ -36,7 +36,7 @@
 lgb.importance <- function(model, percentage = TRUE) {
 
   # Check if model is a lightgbm model
-  if (!inherits(model, "lgb.Booster")) {
+  if (!lgb.is.Booster(model)) {
     stop("'model' has to be an object of class lgb.Booster")
   }
 

R-package/R/lgb.train.R

@@ -65,6 +65,23 @@ lgb.train <- function(params = list(),
                       reset_data = FALSE,
                       ...) {
 
+  # validate inputs early to avoid unnecessary computation
+  if (nrounds <= 0L) {
+    stop("nrounds should be greater than zero")
+  }
+  if (!lgb.is.Dataset(data)) {
+    stop("lgb.train: data must be an lgb.Dataset instance")
+  }
+  if (length(valids) > 0L) {
+    if (!is.list(valids) || !all(vapply(valids, lgb.is.Dataset, logical(1L)))) {
+      stop("lgb.train: valids must be a list of lgb.Dataset elements")
+    }
+    evnames <- names(valids)
+    if (is.null(evnames) || !all(nzchar(evnames))) {
+      stop("lgb.train: each element of valids must have a name")
+    }
+  }
+
   # Setup temporary variables
   additional_params <- list(...)
   params <- append(params, additional_params)
@@ -74,10 +91,6 @@ lgb.train <- function(params = list(),
   fobj <- NULL
   feval <- NULL
 
-  if (nrounds <= 0L) {
-    stop("nrounds should be greater than zero")
-  }
-
   # Check for objective (function or not)
   if (is.function(params$objective)) {
     fobj <- params$objective
@@ -112,30 +125,6 @@ lgb.train <- function(params = list(),
     end_iteration <- begin_iteration + nrounds - 1L
   }
 
-  # Check for training dataset type correctness
-  if (!lgb.is.Dataset(data)) {
-    stop("lgb.train: data only accepts lgb.Dataset object")
-  }
-
-  # Check for validation dataset type correctness
-  if (length(valids) > 0L) {
-
-    # One or more validation dataset
-
-    # Check for list as input and type correctness by object
-    if (!is.list(valids) || !all(vapply(valids, lgb.is.Dataset, logical(1L)))) {
-      stop("lgb.train: valids must be a list of lgb.Dataset elements")
-    }
-
-    # Attempt to get names
-    evnames <- names(valids)
-
-    # Check for names existance
-    if (is.null(evnames) || !all(nzchar(evnames))) {
-      stop("lgb.train: each element of the valids must have a name tag")
-    }
-  }
-
   # Update parameters with parsed parameters
   data$update_params(params)
 

R-package/R/lightgbm.R

@@ -1,8 +1,11 @@
 #' @name lgb_shared_params
 #' @title Shared parameter docs
 #' @description Parameter docs shared by \code{lgb.train}, \code{lgb.cv}, and \code{lightgbm}
-#' @param callbacks List of callback functions that are applied at each iteration.
-#' @param data a \code{lgb.Dataset} object, used for training
+#' @param callbacks list of callback functions
+#'        List of callback functions that are applied at each iteration.
+#' @param data a \code{lgb.Dataset} object, used for training. Some functions, such as \code{\link{lgb.cv}},
+#'             may allow you to pass other types of data like \code{matrix} and then separately supply
+#'             \code{label} as a keyword argument.
 #' @param early_stopping_rounds int. Activates early stopping. Requires at least one validation data
 #'                              and one metric. If there's more than one, will check all of them
 #'                              except the training data. Returns the model with (best_iter + early_stopping_rounds).
@@ -57,11 +60,14 @@ lightgbm <- function(data,
                      callbacks = list(),
                      ...) {
 
-  # Set data to a temporary variable
-  dtrain <- data
+  # validate inputs early to avoid unnecessary computation
   if (nrounds <= 0L) {
     stop("nrounds should be greater than zero")
   }
+
+  # Set data to a temporary variable
+  dtrain <- data
+
   # Check whether data is lgb.Dataset, if not then create lgb.Dataset manually
   if (!lgb.is.Dataset(dtrain)) {
     dtrain <- lgb.Dataset(data, label = label, weight = weight)