Delete deprecated save function

CHANGELOG.md

@@ -69,6 +69,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Removed the deprecated `optimizer_idx` from `training_step` as an accepted argument in manual optimization ([#8576](https://github.com/PyTorchLightning/pytorch-lightning/pull/8576))
 
+
+- Removed the deprecated `save_function` property in `ModelCheckpoint` ([#8680](https://github.com/PyTorchLightning/pytorch-lightning/pull/8680))
+
 ### Fixed
 
 - Fixed `trainer.fit_loop.split_idx` always returning `None` ([#8601](https://github.com/PyTorchLightning/pytorch-lightning/pull/8601))

pytorch_lightning/callbacks/model_checkpoint.py

@@ -25,7 +25,7 @@
 from copy import deepcopy
 from datetime import timedelta
 from pathlib import Path
-from typing import Any, Callable, Dict, Optional, Union
+from typing import Any, Dict, Optional, Union
 from weakref import proxy
 
 import numpy as np
@@ -247,14 +247,12 @@ def __init__(
         self.__init_ckpt_dir(dirpath, filename)
         self.__init_triggers(every_n_train_steps, every_n_epochs, train_time_interval, period)
         self.__validate_init_configuration()
-        self._save_function = None
 
     def on_pretrain_routine_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None:
         """
         When pretrain routine starts we build the ckpt dir on the fly
         """
         self.__resolve_ckpt_dir(trainer)
-        self._save_function = trainer.save_checkpoint
         if self._save_on_train_epoch_end is None:
             # if the user runs validation multiple times per training epoch, we try to save checkpoint after
             # validation instead of on train epoch end
@@ -507,22 +505,6 @@ def period(self, value: Optional[int]) -> None:
         )
         self._period = value
 
-    @property
-    def save_function(self) -> Optional[Callable]:
-        rank_zero_deprecation(
-            "Property `save_function` in `ModelCheckpoint` is deprecated in v1.3 and will be removed in v1.5."
-            " Please use `trainer.save_checkpoint` instead."
-        )
-        return self._save_function
-
-    @save_function.setter
-    def save_function(self, value: Optional[Callable]) -> None:
-        rank_zero_deprecation(
-            "Property `save_function` in `ModelCheckpoint` is deprecated in v1.3 and will be removed in v1.5."
-            " Please use `trainer.save_checkpoint` instead."
-        )
-        self._save_function = value
-
     def _del_model(self, trainer: "pl.Trainer", filepath: str) -> None:
         if trainer.should_rank_save_checkpoint and self._fs.exists(filepath):
             self._fs.rm(filepath)

tests/deprecated_api/test_remove_1-5.py

@@ -42,14 +42,6 @@ def test_v1_5_0_model_checkpoint_save_checkpoint():
         model_ckpt.save_checkpoint(trainer, object())
 
 
-def test_v1_5_0_model_checkpoint_save_function():
-    model_ckpt = ModelCheckpoint()
-    with pytest.deprecated_call(match="Property `save_function` in `ModelCheckpoint` is deprecated in v1.3"):
-        model_ckpt.save_function = lambda *_, **__: None
-    with pytest.deprecated_call(match="Property `save_function` in `ModelCheckpoint` is deprecated in v1.3"):
-        _ = model_ckpt.save_function
-
-
 @mock.patch("pytorch_lightning.loggers.wandb.wandb")
 def test_v1_5_0_wandb_unused_sync_step(_):
     with pytest.deprecated_call(match=r"v1.2.1 and will be removed in v1.5"):