Remove deprecated precision plugin checkpoint hooks

src/pytorch_lightning/CHANGELOG.md

@@ -199,9 +199,13 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Removed the deprecated way to set the distributed backend via the environment variable `PL_TORCH_DISTRIBUTED_BACKEND`, in favor of setting the `process_group_backend` in the strategy constructor ([#14693](https://github.com/Lightning-AI/lightning/pull/14693))
 
+
 - Removed the deprecated device attributes `Trainer.{devices,gpus,num_gpus,ipus,tpu_cores}` in favor of the accelerator-agnostic `Trainer.num_devices` ([#14829](https://github.com/Lightning-AI/lightning/pull/14829))
 
 
+- Removed the deprecated precision plugin checkpoint hooks `PrecisionPlugin.on_load_checkpoint` and `PrecisionPlugin.on_save_checkpoint` ([#14833](https://github.com/Lightning-AI/lightning/pull/14833))
+
+
 - Removed the deprecated `Trainer.root_gpu` attribute in favor of `Trainer.strategy.root_device` ([#14829](https://github.com/Lightning-AI/lightning/pull/14829))
 
 

src/pytorch_lightning/plugins/precision/precision_plugin.py

@@ -269,15 +269,3 @@ def load_state_dict(self, state_dict: Dict[str, Any]) -> None:
             state_dict: the precision plugin state returned by ``state_dict``.
         """
         pass
-
-    def on_save_checkpoint(self, checkpoint: Dict[str, Any]) -> None:
-        """``PrecisionPlugin.on_save_checkpoint`` was deprecated in v1.6 and will be removed in v1.8.
-
-        Use ``state_dict`` instead.
-        """
-
-    def on_load_checkpoint(self, checkpoint: Dict[str, Any]) -> None:
-        """``PrecisionPlugin.on_load_checkpoint`` was deprecated in v1.6 and will be removed in v1.8.
-
-        Use ``load_state_dict`` instead.
-        """

src/pytorch_lightning/trainer/configuration_validator.py

@@ -14,7 +14,6 @@
 import pytorch_lightning as pl
 from lightning_lite.utilities.warnings import PossibleUserWarning
 from pytorch_lightning.accelerators.ipu import IPUAccelerator
-from pytorch_lightning.plugins.precision.precision_plugin import PrecisionPlugin
 from pytorch_lightning.strategies import DataParallelStrategy
 from pytorch_lightning.trainer.states import TrainerFn
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
@@ -50,8 +49,6 @@ def verify_loop_configurations(trainer: "pl.Trainer") -> None:
     _check_deprecated_callback_hooks(trainer)
     # TODO: Delete on_epoch_start/on_epoch_end hooks in v1.8
     _check_on_epoch_start_end(model)
-    # TODO: Delete CheckpointHooks off PrecisionPlugin in v1.8
-    _check_precision_plugin_checkpoint_hooks(trainer)
     # TODO: Delete on_pretrain_routine_start/end hooks in v1.8
     _check_on_pretrain_routine(model)
     # TODO: Delete CheckpointHooks off LightningDataModule in v1.8
@@ -266,19 +263,6 @@ def _check_deprecated_callback_hooks(trainer: "pl.Trainer") -> None:
                 )
 
 
-def _check_precision_plugin_checkpoint_hooks(trainer: "pl.Trainer") -> None:
-    if is_overridden(method_name="on_save_checkpoint", instance=trainer.precision_plugin, parent=PrecisionPlugin):
-        rank_zero_deprecation(
-            "`PrecisionPlugin.on_save_checkpoint` was deprecated in"
-            " v1.6 and will be removed in v1.8. Use `state_dict` instead."
-        )
-    if is_overridden(method_name="on_load_checkpoint", instance=trainer.precision_plugin, parent=PrecisionPlugin):
-        rank_zero_deprecation(
-            "`PrecisionPlugin.on_load_checkpoint` was deprecated in"
-            " v1.6 and will be removed in v1.8. Use `load_state_dict` instead."
-        )
-
-
 def _check_datamodule_checkpoint_hooks(trainer: "pl.Trainer") -> None:
     if is_overridden(method_name="on_save_checkpoint", instance=trainer.datamodule):
         rank_zero_deprecation(

tests/tests_pytorch/deprecated_api/test_remove_1-8.py

@@ -23,7 +23,6 @@
 from pytorch_lightning.callbacks import ModelCheckpoint
 from pytorch_lightning.demos.boring_classes import BoringDataModule, BoringModel
 from pytorch_lightning.loggers import CSVLogger, Logger
-from pytorch_lightning.plugins.precision.precision_plugin import PrecisionPlugin
 from pytorch_lightning.profilers import AdvancedProfiler, SimpleProfiler
 from pytorch_lightning.strategies.ipu import LightningIPUModule
 from pytorch_lightning.trainer.configuration_validator import _check_datamodule_checkpoint_hooks
@@ -434,34 +433,6 @@ def _get_python_cprofile_total_duration(profile):
     np.testing.assert_allclose(recorded_total_duration, expected_total_duration, rtol=0.2)
 
 
-def test_v1_8_0_precision_plugin_checkpoint_hooks(tmpdir):
-    class PrecisionPluginSaveHook(PrecisionPlugin):
-        def on_save_checkpoint(self, checkpoint):
-            print("override on_save_checkpoint")
-
-    class PrecisionPluginLoadHook(PrecisionPlugin):
-        def on_load_checkpoint(self, checkpoint):
-            print("override on_load_checkpoint")
-
-    model = BoringModel()
-
-    precplugin_save = PrecisionPluginSaveHook()
-    trainer = Trainer(default_root_dir=tmpdir, max_epochs=1, plugins=[precplugin_save])
-    with pytest.deprecated_call(
-        match="`PrecisionPlugin.on_save_checkpoint` was deprecated in"
-        " v1.6 and will be removed in v1.8. Use `state_dict` instead."
-    ):
-        trainer.fit(model)
-
-    precplugin_load = PrecisionPluginLoadHook()
-    trainer = Trainer(default_root_dir=tmpdir, max_epochs=1, plugins=[precplugin_load])
-    with pytest.deprecated_call(
-        match="`PrecisionPlugin.on_load_checkpoint` was deprecated in"
-        " v1.6 and will be removed in v1.8. Use `load_state_dict` instead."
-    ):
-        trainer.fit(model)
-
-
 def test_v1_8_0_datamodule_checkpointhooks():
     class CustomBoringDataModuleSave(BoringDataModule):
         def on_save_checkpoint(self, checkpoint):