diff --git a/python-package/xgboost/training.py b/python-package/xgboost/training.py
index e07bab87cf18..b36e75d3a163 100644
--- a/python-package/xgboost/training.py
+++ b/python-package/xgboost/training.py
@@ -11,7 +11,7 @@
 from . import callback
 
 
-def _is_new_callback(callbacks: Optional[List[callback.TrainingCallback]]) -> None:
+def _assert_new_callback(callbacks: Optional[List[callback.TrainingCallback]]) -> None:
     is_new_callback: bool = not callbacks or all(
         isinstance(c, callback.TrainingCallback) for c in callbacks
     )
@@ -40,14 +40,14 @@ def _train_internal(params, dtrain,
 
     start_iteration = 0
 
-    _is_new_callback(callbacks)
+    _assert_new_callback(callbacks)
     if verbose_eval:
         verbose_eval = 1 if verbose_eval is True else verbose_eval
         callbacks.append(callback.EvaluationMonitor(period=verbose_eval))
     if early_stopping_rounds:
-        callbacks.append(callback.EarlyStopping(
-            rounds=early_stopping_rounds, maximize=maximize
-        ))
+        callbacks.append(
+            callback.EarlyStopping(rounds=early_stopping_rounds, maximize=maximize)
+        )
     callbacks = callback.CallbackContainer(callbacks, metric=feval)
 
     bst = callbacks.before_training(bst)
@@ -445,15 +445,17 @@ def cv(params, dtrain, num_boost_round=10, nfold=3, stratified=False, folds=None
 
     # setup callbacks
     callbacks = [] if callbacks is None else callbacks
-    _is_new_callback(callbacks)
+    _assert_new_callback(callbacks)
 
     if isinstance(verbose_eval, bool) and verbose_eval:
         verbose_eval = 1 if verbose_eval is True else verbose_eval
-        callbacks.append(callback.EvaluationMonitor(period=verbose_eval,
-                                                    show_stdv=show_stdv))
+        callbacks.append(
+            callback.EvaluationMonitor(period=verbose_eval, show_stdv=show_stdv)
+        )
     if early_stopping_rounds:
-        callbacks.append(callback.EarlyStopping(
-            rounds=early_stopping_rounds, maximize=maximize))
+        callbacks.append(
+            callback.EarlyStopping(rounds=early_stopping_rounds, maximize=maximize)
+        )
     callbacks = callback.CallbackContainer(callbacks, metric=feval, is_cv=True)
 
     booster = _PackedBooster(cvfolds)