Remove deprecated call_hook

docs/source-pytorch/extensions/loops.rst

@@ -150,12 +150,7 @@ Here is a simple example how to add a new hook:
 
     class CustomFitLoop(FitLoop):
         def advance(self):
-            # ... whatever code before
-
-            # pass anything you want to the hook
-            self.trainer.call_hook("my_new_hook", *args, **kwargs)
-
-            # ... whatever code after
+            """Put your custom logic here."""
 
 Now simply attach the correct loop in the trainer directly:
 

src/pytorch_lightning/CHANGELOG.md

@@ -221,6 +221,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Removed the deprecated `Trainer.use_amp` and `LightningModule.use_amp` attributes ([#14832](https://github.com/Lightning-AI/lightning/pull/14832))
 
+
 - Removed the deprecated `Trainer.run_stage` in favor of `Trainer.{fit,validate,test,predict}`
 
 
@@ -232,9 +233,13 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Remove the deprecated `Trainer.should_rank_save_checkpoint` ([#14885](https://github.com/Lightning-AI/lightning/pull/14885))
 
+
 - Removed the deprecated `TrainerDataLoadingMixin` ([#14888](https://github.com/Lightning-AI/lightning/pull/14888))
 
 
+- Removed the deprecated `Trainer.call_hook` in favor of `Trainer._call_callback_hooks`, `Trainer._call_lightning_module_hook`, `Trainer._call_ttp_hook`, and `Trainer._call_accelerator_hook` ([#14869](https://github.com/Lightning-AI/lightning/pull/14869))
+
+
 ### Fixed
 
 - Fixed an issue with `LightningLite.setup()` not setting the `.device` attribute correctly on the returned wrapper ([#14822](https://github.com/Lightning-AI/lightning/pull/14822))

src/pytorch_lightning/trainer/trainer.py

@@ -1289,45 +1289,6 @@ def _call_teardown_hook(self) -> None:
         # summarize profile results
         self.profiler.describe()
 
-    def call_hook(
-        self, hook_name: str, *args: Any, pl_module: Optional["pl.LightningModule"] = None, **kwargs: Any
-    ) -> Any:
-        r"""
-        .. deprecated:: v1.6
-            The Trainer's `call_hook` method was deprecated in v1.6 and will be removed in v1.8.
-        """
-        rank_zero_deprecation("The Trainer's `call_hook` method was deprecated in v1.6 and will be removed in v1.8.")
-        pl_module = self.lightning_module or pl_module
-        if pl_module:
-            prev_fx_name = pl_module._current_fx_name
-            pl_module._current_fx_name = hook_name
-
-        # always profile hooks
-        with self.profiler.profile(hook_name):
-
-            # first call trainer hook
-            callback_fx = getattr(self, hook_name, None)
-            if callable(callback_fx):
-                callback_fx(*args, **kwargs)
-
-            # next call hook in lightningModule
-            output = None
-            model_fx = getattr(pl_module, hook_name, None)
-            if callable(model_fx):
-                output = model_fx(*args, **kwargs)
-
-            # call the strategy hook
-            if hook_name not in ("setup", "teardown", "on_train_start") and hasattr(self.strategy, hook_name):
-                strategy_hook = getattr(self.strategy, hook_name)
-                strategy_output = strategy_hook(*args, **kwargs)
-                output = strategy_output if output is None else output
-
-        if pl_module:
-            # restore current_fx when nested context
-            pl_module._current_fx_name = prev_fx_name
-
-        return output
-
     def _call_lightning_module_hook(
         self,
         hook_name: str,

tests/tests_pytorch/deprecated_api/test_remove_1-8.py

@@ -52,18 +52,6 @@ def on_init_end(self, trainer):
         trainer.validate(model)
 
 
-def test_v1_8_0_deprecated_call_hook():
-    trainer = Trainer(
-        max_epochs=1,
-        limit_val_batches=0.1,
-        limit_train_batches=0.2,
-        enable_progress_bar=False,
-        logger=False,
-    )
-    with pytest.deprecated_call(match="was deprecated in v1.6 and will be removed in v1.8."):
-        trainer.call_hook("test_hook")
-
-
 @pytest.mark.parametrize("fn_prefix", ["validated", "tested", "predicted"])
 def test_v1_8_0_trainer_ckpt_path_attributes(fn_prefix: str):
     test_attr = f"{fn_prefix}_ckpt_path"