tests.

Author: trivialfis

jvm-packages/xgboost4j-spark-gpu/src/main/scala/ml/dmlc/xgboost4j/scala/spark/GpuXGBoostPlugin.scala

@@ -102,7 +102,7 @@ class GpuXGBoostPlugin extends XGBoostPlugin {
   private[spark] def validate[T <: XGBoostEstimator[T, M], M <: XGBoostModel[M]](
       estimator: XGBoostEstimator[T, M],
       dataset: Dataset[_]): Unit = {
-    require(estimator.getTreeMethod == "gpu_hist" || estimator.getDevice != "cpu",
+    require(estimator.getDevice != "cpu",
       "Using Spark-Rapids to accelerate XGBoost must set device=cuda")
   }
 

jvm-packages/xgboost4j-spark-gpu/src/test/scala/ml/dmlc/xgboost4j/scala/spark/GpuXGBoostPluginSuite.scala

@@ -129,10 +129,6 @@ class GpuXGBoostPluginSuite extends GpuTestSuite {
 
       classifier.setDevice("gpu")
       plugin.validate(classifier, df)
-
-      classifier.setDevice("cpu")
-      classifier.setTreeMethod("gpu_hist")
-      plugin.validate(classifier, df)
     }
   }
 

jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostEstimator.scala

@@ -374,7 +374,7 @@ private[spark] trait XGBoostEstimator[
 
   private[spark] def getRuntimeParameters(isLocal: Boolean,
       configs: Map[String, AnyRef] = Map.empty): RuntimeParams = {
-    val runOnGpu = if (getDevice != "cpu" || getTreeMethod == "gpu_hist") true else false
+    val runOnGpu = if (getDevice != "cpu") true else false
     RuntimeParams(
       getNumWorkers,
       getNumRound,

jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/params/TreeBoosterParams.scala

@@ -231,7 +231,7 @@ private[spark] trait TreeBoosterParams extends Params {
 
 private[spark] object BoosterParams {
 
-  val supportedTreeMethods = HashSet("auto", "exact", "approx", "hist", "gpu_hist")
+  val supportedTreeMethods = HashSet("auto", "exact", "approx", "hist")
 
   val supportedUpdaters = HashSet("grow_colmaker", "grow_histmaker", "grow_quantile_histmaker",
     "grow_gpu_hist", "grow_gpu_approx", "sync", "refresh", "prune")

jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostEstimatorSuite.scala

@@ -133,16 +133,6 @@ class XGBoostEstimatorSuite extends AnyFunSuite with PerTest with TmpFolderPerSu
       Map("device" -> "cuda")).setNumWorkers(1).setNumRound(1)
       .getRuntimeParameters(true)
     assert(runtimeParams.runOnGpu)
-
-    runtimeParams = new XGBoostClassifier(
-      Map("device" -> "cpu", "tree_method" -> "gpu_hist")).setNumWorkers(1).setNumRound(1)
-      .getRuntimeParameters(true)
-    assert(runtimeParams.runOnGpu)
-
-    runtimeParams = new XGBoostClassifier(
-      Map("device" -> "cuda", "tree_method" -> "gpu_hist")).setNumWorkers(1).setNumRound(1)
-      .getRuntimeParameters(true)
-    assert(runtimeParams.runOnGpu)
   }
 
   test("missing value exception for sparse vector") {

python-package/xgboost/spark/core.py

@@ -506,7 +506,6 @@ def _run_on_gpu(self) -> bool:
         return (
             use_cuda(self.getOrDefault(self.device))
             or self.getOrDefault(self.use_gpu)
-            or self.getOrDefault(self.getParam("tree_method")) == "gpu_hist"
         )
 
     def _col_is_defined_not_empty(self, param: "Param[str]") -> bool:

tests/cpp/gbm/test_gbtree.cc

@@ -245,11 +245,11 @@ TEST(GBTree, ChooseTreeMethod) {
           {{"hist", "cuda"}, "grow_gpu_hist"},
           {{"hist", "cuda:0"}, "grow_gpu_hist"},
           {{"hist", std::nullopt}, "grow_quantile_histmaker"},
-          // gpu_hist
-          {{"gpu_hist", "cpu"}, "grow_gpu_hist"},
-          {{"gpu_hist", "cuda"}, "grow_gpu_hist"},
-          {{"gpu_hist", "cuda:0"}, "grow_gpu_hist"},
-          {{"gpu_hist", std::nullopt}, "grow_gpu_hist"},
+          // approx
+          {{"approx", "cpu"}, "grow_gpu_approx"},
+          {{"approx", "cuda"}, "grow_gpu_approx"},
+          {{"approx", "cuda:0"}, "grow_gpu_approx"},
+          {{"approx", std::nullopt}, "grow_gpu_approx"},
           // exact
           {{"exact", "cpu"}, "grow_colmaker,prune"},
           {{"exact", "cuda"}, "err"},

tests/test_distributed/test_with_spark/test_spark_local.py

@@ -921,12 +921,12 @@ def test_device_param(self, reg_data: RegData, clf_data: ClfData) -> None:
         with pytest.raises(ValueError, match="not supported for distributed"):
             regressor.fit(reg_data.reg_df_train)
 
-        reg = SparkXGBRegressor(device="cuda", tree_method="gpu_hist")
+        reg = SparkXGBRegressor(device="cuda", tree_method="hist")
         reg._validate_params()
         reg = SparkXGBRegressor(device="cuda")
         reg._validate_params()
 
-        clf = SparkXGBClassifier(device="cuda", tree_method="gpu_hist")
+        clf = SparkXGBClassifier(device="cuda", tree_method="hist")
         clf._validate_params()
         clf = SparkXGBClassifier(device="cuda")
         clf._validate_params()
@@ -941,7 +941,7 @@ def test_gpu_params(self) -> None:
         clf = SparkXGBClassifier(device="cuda")
         assert clf._run_on_gpu()
 
-        clf = SparkXGBClassifier(tree_method="gpu_hist")
+        clf = SparkXGBClassifier(tree_method="hist")
         assert clf._run_on_gpu()
 
         clf = SparkXGBClassifier(use_gpu=True)