Adding unit test for training on slices of ldb.Dataset

R-package/tests/testthat/test_basic.R

@@ -3861,3 +3861,39 @@ test_that("Evaluation metrics aren't printed as a single-element vector", {
   })
   expect_false(grepl("[1] \"[1]", log_txt, fixed = TRUE))
 })
+
+test_that("lgb.train() can use slices of an lgb.Dataset for train and valid data", {
+
+  data("iris")
+
+  ds <- lgb.Dataset(
+    as.matrix(iris[, 1:3])
+    , label = iris[, 4]
+  )
+
+  train <- lgb.slice.Dataset(ds, seq(1, 100))
+  test <- lgb.slice.Dataset(ds, seq(101, 150))
+
+  test_mat <- as.matrix(iris[101:150, 1:3])
+  test_label <- iris[101:150, 4]
+
+  params <- list(
+    metric = "l2"
+    , objective = "regression"
+    , num_threads = .LGB_MAX_THREADS
+  )
+
+  model <- lgb.train(
+    params = params
+    , data = train
+    , nrounds = 1L
+    , verbose = .LGB_VERBOSITY
+    , valids = list(test = test)
+  )
+
+  y_hat <- predict(model, newdata = test_mat) 
+  model_l2 <- model$eval_valid()[[1]]$value
+  independent_l2 <- mean((test_label - y_hat) ** 2)
+
+  expect_equal(model_l2, independent_l2, tolerance = 0.0001)
+})