Remove deprecated checkpoint_callback flag in Trainer

CHANGELOG.md

@@ -112,6 +112,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Removed
 
+- Removed the deprecated `checkpoint_callback` argument from the `Trainer` constructor ([#13027](https://github.com/PyTorchLightning/pytorch-lightning/pull/13027))
+
+
 - Removed the deprecated `TestTubeLogger` ([#12859](https://github.com/PyTorchLightning/pytorch-lightning/pull/12859))
 
 

docs/source/common/trainer.rst

@@ -535,12 +535,6 @@ Example::
     # run val loop every 10 training epochs
     trainer = Trainer(check_val_every_n_epoch=10)
 
-checkpoint_callback
-^^^^^^^^^^^^^^^^^^^
-
-.. warning:: `checkpoint_callback` has been deprecated in v1.5 and will be removed in v1.7.
-    To disable checkpointing, pass ``enable_checkpointing = False`` to the Trainer instead.
-
 
 default_root_dir
 ^^^^^^^^^^^^^^^^

legacy/simple_classif_training.py

@@ -156,7 +156,6 @@ def main_train(dir_path, max_epochs: int = 20):
         default_root_dir=dir_path,
         gpus=int(torch.cuda.is_available()),
         precision=(16 if torch.cuda.is_available() else 32),
-        checkpoint_callback=True,
         callbacks=[stopping],
         min_epochs=3,
         max_epochs=max_epochs,

pytorch_lightning/trainer/connectors/callback_connector.py

@@ -43,7 +43,6 @@ def __init__(self, trainer):
     def on_trainer_init(
         self,
         callbacks: Optional[Union[List[Callback], Callback]],
-        checkpoint_callback: Optional[bool],
         enable_checkpointing: bool,
         enable_progress_bar: bool,
         process_position: int,
@@ -71,7 +70,7 @@ def on_trainer_init(
 
         # configure checkpoint callback
         # pass through the required args to figure out defaults
-        self._configure_checkpoint_callbacks(checkpoint_callback, enable_checkpointing)
+        self._configure_checkpoint_callbacks(enable_checkpointing)
 
         # configure the timer callback.
         # responsible to stop the training when max_time is reached.
@@ -133,15 +132,7 @@ def _configure_accumulated_gradients(
         self.trainer.accumulate_grad_batches = grad_accum_callback.get_accumulate_grad_batches(0)
         self.trainer.accumulation_scheduler = grad_accum_callback
 
-    def _configure_checkpoint_callbacks(self, checkpoint_callback: Optional[bool], enable_checkpointing: bool) -> None:
-        if checkpoint_callback is not None:
-            rank_zero_deprecation(
-                f"Setting `Trainer(checkpoint_callback={checkpoint_callback})` is deprecated in v1.5 and will "
-                f"be removed in v1.7. Please consider using `Trainer(enable_checkpointing={checkpoint_callback})`."
-            )
-            # if both are set then checkpoint only if both are True
-            enable_checkpointing = checkpoint_callback and enable_checkpointing
-
+    def _configure_checkpoint_callbacks(self, enable_checkpointing: bool) -> None:
         if self.trainer.checkpoint_callbacks:
             if not enable_checkpointing:
                 raise MisconfigurationException(

pytorch_lightning/trainer/trainer.py

@@ -132,7 +132,6 @@ class Trainer(
     def __init__(
         self,
         logger: Union[Logger, Iterable[Logger], bool] = True,
-        checkpoint_callback: Optional[bool] = None,
         enable_checkpointing: bool = True,
         callbacks: Optional[Union[List[Callback], Callback]] = None,
         default_root_dir: Optional[str] = None,
@@ -234,13 +233,6 @@ def __init__(
             callbacks: Add a callback or list of callbacks.
                 Default: ``None``.
 
-            checkpoint_callback: If ``True``, enable checkpointing.
-                Default: ``None``.
-
-                .. deprecated:: v1.5
-                    ``checkpoint_callback`` has been deprecated in v1.5 and will be removed in v1.7.
-                    Please consider using ``enable_checkpointing`` instead.
-
             enable_checkpointing: If ``True``, enable checkpointing.
                 It will configure a default ModelCheckpoint callback if there is no user-defined ModelCheckpoint in
                 :paramref:`~pytorch_lightning.trainer.trainer.Trainer.callbacks`.
@@ -514,7 +506,6 @@ def __init__(
         # Declare attributes to be set in _callback_connector on_trainer_init
         self._callback_connector.on_trainer_init(
             callbacks,
-            checkpoint_callback,
             enable_checkpointing,
             enable_progress_bar,
             process_position,

tests/deprecated_api/test_remove_1-7.py

@@ -154,11 +154,6 @@ def test_v1_7_0_deprecate_lightning_distributed(tmpdir):
         _ = LightningDistributed()
 
 
-def test_v1_7_0_checkpoint_callback_trainer_constructor(tmpdir):
-    with pytest.deprecated_call(match=r"Setting `Trainer\(checkpoint_callback=True\)` is deprecated in v1.5"):
-        _ = Trainer(checkpoint_callback=True)
-
-
 def test_v1_7_0_deprecate_on_post_move_to_device(tmpdir):
     class TestModel(BoringModel):
         def on_post_move_to_device(self):