Optional normalization for learning to rank. (#10094)

tests/python-gpu/test_gpu_ranking.py

@@ -6,6 +6,7 @@ import pytest
 
 import xgboost
 from xgboost import testing as tm
+from xgboost.testing.ranking import run_normalization
 
 pytestmark = tm.timeout(30)
 
@@ -126,3 +127,7 @@ def test_with_mq2008(objective, metric) -> None:
     dtest = xgboost.DMatrix(x_test, y_test, qid=qid_test)
 
     comp_training_with_rank_objective(dtrain, dtest, objective, metric)
+
+
+def test_normalization() -> None:
+    run_normalization("cuda")

tests/python/test_ranking.py

@@ -13,6 +13,7 @@ import xgboost
 from xgboost import testing as tm
 from xgboost.testing.data import RelDataCV, simulate_clicks, sort_ltr_samples
 from xgboost.testing.params import lambdarank_parameter_strategy
+from xgboost.testing.ranking import run_normalization
 
 
 def test_ndcg_custom_gain():
@@ -188,6 +189,10 @@ def test_unbiased() -> None:
     assert df["ti+"].iloc[-1] < df["ti+"].iloc[0]
 
 
+def test_normalization() -> None:
+    run_normalization("cpu")
+
+
 class TestRanking:
     @classmethod
     def setup_class(cls):