Fix using categorical data with the score function of ranker. (#9753)

tests/python/test_with_sklearn.py

@@ -12,7 +12,7 @@ from sklearn.utils.estimator_checks import parametrize_with_checks
 
 import xgboost as xgb
 from xgboost import testing as tm
-from xgboost.testing.ranking import run_ranking_qid_df
+from xgboost.testing.ranking import run_ranking_categorical, run_ranking_qid_df
 from xgboost.testing.shared import get_feature_weights, validate_data_initialization
 from xgboost.testing.updater import get_basescore
 
@@ -173,6 +173,11 @@ def test_ranking():
     np.testing.assert_almost_equal(pred, pred_orig)
 
 
+@pytest.mark.skipif(**tm.no_pandas())
+def test_ranking_categorical() -> None:
+    run_ranking_categorical(device="cpu")
+
+
 def test_ranking_metric() -> None:
     from sklearn.metrics import roc_auc_score