Add tests for pickling with custom obj and metric. (#9943)

doc/tutorials/custom_metric_obj.rst

@@ -279,7 +279,6 @@ available at :ref:`sphx_glr_python_examples_custom_softmax.py`. Also, see
 Scikit-Learn Interface
 **********************
 
-
 The scikit-learn interface of XGBoost has some utilities to improve the integration with
 standard scikit-learn functions.  For instance, after XGBoost 1.6.0 users can use the cost
 function (not scoring functions) from scikit-learn out of the box:

doc/tutorials/saving_model.rst

@@ -101,6 +101,8 @@ snapshot generated by an earlier version of XGBoost may result in errors or unde
 **If a model is persisted with** ``pickle.dump`` (Python) or ``saveRDS`` (R), **then the model may
 not be accessible in later versions of XGBoost.**
 
+.. _custom-obj-metric:
+
 ***************************
 Custom objective and metric
 ***************************