Remove on_train_batch_{start,end}(dataloader_idx=...)

CHANGELOG.md

@@ -150,7 +150,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed the deprecated `test_transforms` argument from the `LightningDataModule` constructor ([#12773](https://github.com/PyTorchLightning/pytorch-lightning/pull/12773))
 
 
-- Removed deprecated `dataloader_idx` argument from `on_train_batch_start/end` hooks `Callback` and `LightningModule` ([#12769](https://github.com/PyTorchLightning/pytorch-lightning/pull/12769))
+- Removed deprecated `dataloader_idx` argument from `on_train_batch_start/end` hooks `Callback` and `LightningModule` ([#12769](https://github.com/PyTorchLightning/pytorch-lightning/pull/12769), [#12977](https://github.com/PyTorchLightning/pytorch-lightning/pull/12977))
 
 
 - Removed deprecated `get_progress_bar_dict` property from `LightningModule` ([#12839](https://github.com/PyTorchLightning/pytorch-lightning/pull/12839))

pytorch_lightning/callbacks/base.py

@@ -107,23 +107,12 @@ def on_sanity_check_end(self, trainer: "pl.Trainer", pl_module: "pl.LightningMod
         """Called when the validation sanity check ends."""
 
     def on_train_batch_start(
-        self,
-        trainer: "pl.Trainer",
-        pl_module: "pl.LightningModule",
-        batch: Any,
-        batch_idx: int,
-        unused: int = 0,
+        self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", batch: Any, batch_idx: int
     ) -> None:
         """Called when the train batch begins."""
 
     def on_train_batch_end(
-        self,
-        trainer: "pl.Trainer",
-        pl_module: "pl.LightningModule",
-        outputs: STEP_OUTPUT,
-        batch: Any,
-        batch_idx: int,
-        unused: int = 0,
+        self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", outputs: STEP_OUTPUT, batch: Any, batch_idx: int
     ) -> None:
         """Called when the train batch ends."""
 

pytorch_lightning/callbacks/device_stats_monitor.py

@@ -48,12 +48,7 @@ def setup(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", stage: O
             raise MisconfigurationException("Cannot use DeviceStatsMonitor callback with Trainer that has no logger.")
 
     def on_train_batch_start(
-        self,
-        trainer: "pl.Trainer",
-        pl_module: "pl.LightningModule",
-        batch: Any,
-        batch_idx: int,
-        unused: int = 0,
+        self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", batch: Any, batch_idx: int
     ) -> None:
         if not trainer.loggers:
             raise MisconfigurationException("Cannot use `DeviceStatsMonitor` callback with `Trainer(logger=False)`.")
@@ -71,13 +66,7 @@ def on_train_batch_start(
             logger.log_metrics(prefixed_device_stats, step=trainer.fit_loop.epoch_loop._batches_that_stepped)
 
     def on_train_batch_end(
-        self,
-        trainer: "pl.Trainer",
-        pl_module: "pl.LightningModule",
-        outputs: STEP_OUTPUT,
-        batch: Any,
-        batch_idx: int,
-        unused: int = 0,
+        self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", outputs: STEP_OUTPUT, batch: Any, batch_idx: int
     ) -> None:
         if not trainer.loggers:
             raise MisconfigurationException("Cannot use `DeviceStatsMonitor` callback with `Trainer(logger=False)`.")

pytorch_lightning/loops/epoch/training_epoch_loop.py

@@ -186,20 +186,10 @@ def advance(self, data_fetcher: AbstractDataFetcher) -> None:  # type: ignore[ov
             # hook
             self.trainer._call_callback_hooks("on_batch_start")
 
-            # TODO: Update this in v1.7 (deprecation: #9816)
-            model_fx = self.trainer.lightning_module.on_train_batch_start
-            extra_kwargs = (
-                {"dataloader_idx": 0}
-                if callable(model_fx) and is_param_in_hook_signature(model_fx, "dataloader_idx", explicit=True)
-                else {}
-            )
-
             # hook
-            self.trainer._call_callback_hooks("on_train_batch_start", batch, batch_idx, **extra_kwargs)
-            response = self.trainer._call_lightning_module_hook(
-                "on_train_batch_start", batch, batch_idx, **extra_kwargs
-            )
-            self.trainer._call_strategy_hook("on_train_batch_start", batch, batch_idx, **extra_kwargs)
+            self.trainer._call_callback_hooks("on_train_batch_start", batch, batch_idx)
+            response = self.trainer._call_lightning_module_hook("on_train_batch_start", batch, batch_idx)
+            self.trainer._call_strategy_hook("on_train_batch_start", batch, batch_idx)
             if response == -1:
                 self.batch_progress.increment_processed()
                 raise StopIteration
@@ -223,17 +213,8 @@ def advance(self, data_fetcher: AbstractDataFetcher) -> None:  # type: ignore[ov
             num_optimizers=len(self.trainer.optimizers),
         )
 
-        # TODO: Update this in v1.7 (deprecation: #9816)
-        model_fx = self.trainer.lightning_module.on_train_batch_end
-        extra_kwargs = (
-            {"dataloader_idx": 0}
-            if callable(model_fx) and is_param_in_hook_signature(model_fx, "dataloader_idx", explicit=True)
-            else {}
-        )
-        self.trainer._call_callback_hooks("on_train_batch_end", batch_end_outputs, batch, batch_idx, **extra_kwargs)
-        self.trainer._call_lightning_module_hook(
-            "on_train_batch_end", batch_end_outputs, batch, batch_idx, **extra_kwargs
-        )
+        self.trainer._call_callback_hooks("on_train_batch_end", batch_end_outputs, batch, batch_idx)
+        self.trainer._call_lightning_module_hook("on_train_batch_end", batch_end_outputs, batch, batch_idx)
         self.trainer._call_callback_hooks("on_batch_end")
         self.trainer._logger_connector.on_batch_end()
 

pytorch_lightning/trainer/configuration_validator.py

@@ -38,8 +38,6 @@ def verify_loop_configurations(trainer: "pl.Trainer") -> None:
         __verify_train_val_loop_configuration(trainer, model)
         __verify_manual_optimization_support(trainer, model)
         __check_training_step_requires_dataloader_iter(model)
-        # TODO: Remove this in v1.7 (deprecation: #9816)
-        _check_dl_idx_in_on_train_batch_hooks(model)
     elif trainer.state.fn == TrainerFn.VALIDATING:
         __verify_eval_loop_configuration(trainer, model, "val")
     elif trainer.state.fn == TrainerFn.TESTING:
@@ -304,29 +302,13 @@ def _check_on_pretrain_routine(model: "pl.LightningModule") -> None:
             )
 
 
-def _check_dl_idx_in_on_train_batch_hooks(model: "pl.LightningModule") -> None:
-    for hook in ("on_train_batch_start", "on_train_batch_end"):
-        if is_param_in_hook_signature(getattr(model, hook), "dataloader_idx", explicit=True):
-            rank_zero_deprecation(
-                f"Base `LightningModule.{hook}` hook signature has changed in v1.5."
-                " The `dataloader_idx` argument will be removed in v1.7."
-            )
-
-
 def _check_deprecated_callback_hooks(trainer: "pl.Trainer") -> None:
     for callback in trainer.callbacks:
         if is_overridden(method_name="on_keyboard_interrupt", instance=callback):
             rank_zero_deprecation(
                 "The `on_keyboard_interrupt` callback hook was deprecated in v1.5 and will be removed in v1.7."
                 " Please use the `on_exception` callback hook instead."
             )
-        # TODO: Remove this in v1.7 (deprecation: #9816)
-        for hook in ("on_train_batch_start", "on_train_batch_end"):
-            if is_param_in_hook_signature(getattr(callback, hook), "dataloader_idx", explicit=True):
-                rank_zero_deprecation(
-                    f"Base `Callback.{hook}` hook signature has changed in v1.5."
-                    " The `dataloader_idx` argument will be removed in v1.7."
-                )
         if is_overridden(method_name="on_init_start", instance=callback):
             rank_zero_deprecation(
                 "The `on_init_start` callback hook was deprecated in v1.6 and will be removed in v1.8."