[pyspark] unify the way for determining whether runs on the GPU. (#9724)

tests/test_distributed/test_gpu_with_spark/test_gpu_spark.py

@@ -251,10 +251,10 @@ def test_gpu_transform(spark_diabetes_dataset) -> None:
     model: SparkXGBRegressorModel = regressor.fit(train_df)
 
     # The model trained with GPUs, and transform with GPU configurations.
-    assert model._gpu_transform()
+    assert model._run_on_gpu()
 
     model.set_device("cpu")
-    assert not model._gpu_transform()
+    assert not model._run_on_gpu()
     # without error
     cpu_rows = model.transform(test_df).select("prediction").collect()
 
@@ -263,11 +263,11 @@ def test_gpu_transform(spark_diabetes_dataset) -> None:
 
     # The model trained with CPUs. Even with GPU configurations,
     # still prefer transforming with CPUs
-    assert not model._gpu_transform()
+    assert not model._run_on_gpu()
 
     # Set gpu transform explicitly.
     model.set_device("cuda")
-    assert model._gpu_transform()
+    assert model._run_on_gpu()
     # without error
     gpu_rows = model.transform(test_df).select("prediction").collect()