Add function to remove checkpoint to allow override for extended clas…

…ses (#16067)

src/pytorch_lightning/callbacks/model_checkpoint.py

@@ -649,7 +649,7 @@ def _save_last_checkpoint(self, trainer: "pl.Trainer", monitor_candidates: Dict[
         previous, self.last_model_path = self.last_model_path, filepath
         self._save_checkpoint(trainer, filepath)
         if previous and previous != filepath:
-            trainer.strategy.remove_checkpoint(previous)
+            self._remove_checkpoint(trainer, previous)
 
     def _save_monitor_checkpoint(self, trainer: "pl.Trainer", monitor_candidates: Dict[str, Tensor]) -> None:
         assert self.monitor
@@ -668,7 +668,7 @@ def _save_none_monitor_checkpoint(self, trainer: "pl.Trainer", monitor_candidate
         previous, self.best_model_path = self.best_model_path, filepath
         self._save_checkpoint(trainer, filepath)
         if self.save_top_k == 1 and previous and previous != filepath:
-            trainer.strategy.remove_checkpoint(previous)
+            self._remove_checkpoint(trainer, previous)
 
     def _update_best_and_save(
         self, current: Tensor, trainer: "pl.Trainer", monitor_candidates: Dict[str, Tensor]
@@ -710,7 +710,7 @@ def _update_best_and_save(
         self._save_checkpoint(trainer, filepath)
 
         if del_filepath is not None and filepath != del_filepath:
-            trainer.strategy.remove_checkpoint(del_filepath)
+            self._remove_checkpoint(trainer, del_filepath)
 
     def to_yaml(self, filepath: Optional[_PATH] = None) -> None:
         """Saves the `best_k_models` dict containing the checkpoint paths with the corresponding scores to a YAML
@@ -727,3 +727,7 @@ def file_exists(self, filepath: _PATH, trainer: "pl.Trainer") -> bool:
         state to diverge between ranks."""
         exists = self._fs.exists(filepath)
         return trainer.strategy.broadcast(exists)
+
+    def _remove_checkpoint(self, trainer: "pl.Trainer", filepath: str) -> None:
+        """Calls the strategy to remove the checkpoint file."""
+        trainer.strategy.remove_checkpoint(filepath)