[R-package] raise informative errors directly when Booster creation fails (#5014)

R-package/R/lgb.Booster.R

@@ -26,15 +26,10 @@ Booster <- R6::R6Class(
                           modelfile = NULL,
                           model_str = NULL) {
 
-      # Create parameters and handle
       handle <- NULL
 
-      # Attempts to create a handle for the dataset
-      try({
-
-        # Check if training dataset is not null
       if (!is.null(train_set)) {
-          # Check if training dataset is lgb.Dataset or not
+
         if (!lgb.is.Dataset(train_set)) {
           stop("lgb.Booster: Can only use lgb.Dataset as training data")
         }
@@ -54,7 +49,6 @@ Booster <- R6::R6Class(
         private$num_dataset <- 1L
         private$init_predictor <- train_set$.__enclos_env__$private$predictor
 
-          # Check if predictor is existing
         if (!is.null(private$init_predictor)) {
 
           # Merge booster
@@ -107,16 +101,6 @@ Booster <- R6::R6Class(
 
       }
 
-      })
-
-      # Check whether the handle was created properly if it was not stopped earlier by a stop call
-      if (isTRUE(lgb.is.null.handle(x = handle))) {
-
-        stop("lgb.Booster: cannot create Booster handle")
-
-      } else {
-
-        # Create class
       class(handle) <- "lgb.Booster.handle"
       private$handle <- handle
       private$num_class <- 1L
@@ -126,8 +110,6 @@ Booster <- R6::R6Class(
         , private$num_class
       )
 
-      }
-
       self$params <- params
 
       return(invisible(NULL))

R-package/tests/testthat/test_lgb.Booster.R

@@ -947,7 +947,76 @@ test_that("Booster$new() using a Dataset with a null handle should raise an info
                 verbose = VERBOSITY
             )
         )
-    }, regexp = "lgb.Booster: cannot create Booster handle")
+    }, regexp = "Attempting to create a Dataset without any raw data")
+})
+
+test_that("Booster$new() raises informative errors for malformed inputs", {
+  data(agaricus.train, package = "lightgbm")
+  train <- agaricus.train
+  dtrain <- lgb.Dataset(train$data, label = train$label)
+
+  # no inputs
+  expect_error({
+    Booster$new()
+  }, regexp = "lgb.Booster: Need at least either training dataset, model file, or model_str")
+
+  # unrecognized objective
+  expect_error({
+    Booster$new(
+      params = list(objective = "not_a_real_objective")
+      , train_set = dtrain
+    )
+  }, regexp = "Unknown objective type name: not_a_real_objective")
+
+  # train_set is not a Dataset
+  expect_error({
+    Booster$new(
+      train_set = data.table::data.table(rnorm(1L:10L))
+    )
+  }, regexp = "lgb.Booster: Can only use lgb.Dataset as training data")
+
+  # model file isn't a string
+  expect_error({
+    Booster$new(
+      modelfile = list()
+    )
+  }, regexp = "lgb.Booster: Can only use a string as model file path")
+
+  # model file doesn't exist
+  expect_error({
+    Booster$new(
+      params = list()
+      , modelfile = "file-that-does-not-exist.model"
+    )
+  }, regexp = "Could not open file-that-does-not-exist.model")
+
+  # model file doesn't contain a valid LightGBM model
+  model_file <- tempfile(fileext = ".model")
+  writeLines(
+    text = c("make", "good", "predictions")
+    , con = model_file
+  )
+  expect_error({
+    Booster$new(
+      params = list()
+      , modelfile = model_file
+    )
+  }, regexp = "Unknown model format or submodel type in model file")
+
+  # malformed model string
+  expect_error({
+    Booster$new(
+      params = list()
+      , model_str = "a\nb\n"
+    )
+  }, regexp = "Model file doesn't specify the number of classes")
+
+  # model string isn't character or raw
+  expect_error({
+    Booster$new(
+      model_str = numeric()
+    )
+  }, regexp = "lgb.Booster: Can only use a character/raw vector as model_str")
 })
 
 # this is almost identical to the test above it, but for lgb.cv(). A lot of code