updated model_checkpoint.py to add the facility of retaining periodic…

… checkpoints

src/lightning/pytorch/callbacks/model_checkpoint.py

@@ -136,6 +136,10 @@ class ModelCheckpoint(Checkpoint):
             If this is ``False``, then the check runs at the end of the validation.
         enable_version_counter: Whether to append a version to the existing file name.
             If this is ``False``, then the checkpoint files will be overwritten.
+        retain_periodic_ckpt: Whether to retain the periodic checkpoints when multiple checkpoints are
+        saved. If this is ``False``, then only the latest checkpoint will be saved. If this is ``True``,
+        don't change the default value of ``save_top_k``.
+            Default: ``False``.
 
     Note:
         For extra customization, ModelCheckpoint includes the following attributes:
@@ -228,6 +232,7 @@ def __init__(
         every_n_epochs: Optional[int] = None,
         save_on_train_epoch_end: Optional[bool] = None,
         enable_version_counter: bool = True,
+        retain_periodic_ckpt: bool = False,
     ):
         super().__init__()
         self.monitor = monitor
@@ -247,6 +252,7 @@ def __init__(
         self.best_model_path = ""
         self.last_model_path = ""
         self._last_checkpoint_saved = ""
+        self.retain_periodic_ckpt = retain_periodic_ckpt
 
         self.kth_value: Tensor
         self.dirpath: Optional[_PATH]
@@ -714,7 +720,12 @@ 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 self._should_remove_checkpoint(trainer, previous, filepath):
+        if (
+            self.save_top_k == 1
+            and not self.retain_periodic_ckpt
+            and previous
+            and self._should_remove_checkpoint(trainer, previous, filepath)
+        ):
             self._remove_checkpoint(trainer, previous)
 
     def _update_best_and_save(