remove deprecated reload_dataloaders_every_epoch from Trainer

CHANGELOG.md

@@ -133,6 +133,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed deprecated `CheckpointConnector.hpc_load` property in favor of `CheckpointConnector.restore` ([#10525](https://github.com/PyTorchLightning/pytorch-lightning/pull/10525))
 
 
+- Removed deprecated `reload_dataloaders_every_epoch` from `Trainer` in favour of `reload_dataloaders_every_n_epochs` ([#10481](https://github.com/PyTorchLightning/pytorch-lightning/pull/10481))
+
+
 
 ### Fixed
 

pytorch_lightning/trainer/connectors/data_connector.py

@@ -64,7 +64,6 @@ def on_trainer_init(
         self,
         check_val_every_n_epoch: int,
         reload_dataloaders_every_n_epochs: int,
-        reload_dataloaders_every_epoch: bool,
         prepare_data_per_node: Optional[bool] = None,
     ) -> None:
         self.trainer.datamodule = None
@@ -83,13 +82,6 @@ def on_trainer_init(
 
         self.trainer.check_val_every_n_epoch = check_val_every_n_epoch
 
-        if reload_dataloaders_every_epoch:
-            reload_dataloaders_every_n_epochs = int(reload_dataloaders_every_epoch)
-            rank_zero_deprecation(
-                "`reload_dataloaders_every_epoch` is deprecated in v1.4 and will be removed in v1.6."
-                " Please use `reload_dataloaders_every_n_epochs` in Trainer."
-            )
-
         if not isinstance(reload_dataloaders_every_n_epochs, int) or (reload_dataloaders_every_n_epochs < 0):
             raise MisconfigurationException(
                 f"`reload_dataloaders_every_n_epochs` should be an int >= 0, got {reload_dataloaders_every_n_epochs}."

pytorch_lightning/trainer/trainer.py

@@ -162,7 +162,6 @@ def __init__(
         benchmark: bool = False,
         deterministic: bool = False,
         reload_dataloaders_every_n_epochs: int = 0,
-        reload_dataloaders_every_epoch: bool = False,
         auto_lr_find: Union[bool, str] = False,
         replace_sampler_ddp: bool = True,
         detect_anomaly: bool = False,
@@ -341,12 +340,6 @@ def __init__(
 
             reload_dataloaders_every_n_epochs: Set to a non-negative integer to reload dataloaders every n epochs.
 
-            reload_dataloaders_every_epoch: Set to True to reload dataloaders every epoch.
-
-                .. deprecated:: v1.4
-                    ``reload_dataloaders_every_epoch`` has been deprecated in v1.4 and will be removed in v1.6.
-                    Please use ``reload_dataloaders_every_n_epochs``.
-
             replace_sampler_ddp: Explicitly enables or disables sampler replacement. If not specified this
                 will toggled automatically when DDP is used. By default it will add ``shuffle=True`` for
                 train sampler and ``shuffle=False`` for val/test sampler. If you want to customize it,
@@ -515,7 +508,6 @@ def __init__(
         self._data_connector.on_trainer_init(
             check_val_every_n_epoch,
             reload_dataloaders_every_n_epochs,
-            reload_dataloaders_every_epoch,
             prepare_data_per_node,
         )
 

tests/models/test_hooks.py

@@ -866,7 +866,7 @@ def call(hook, fn, *args, **kwargs):
         limit_predict_batches=batches,
         enable_progress_bar=False,
         enable_model_summary=False,
-        reload_dataloaders_every_epoch=True,
+        reload_dataloaders_every_n_epochs=True,
     )
 
     called = []

tests/trainer/test_dataloaders.py

@@ -1276,7 +1276,7 @@ def validation_step(self, batch, batch_idx):
         # the val dataloader on the first epoch because this only tracks the training epoch
         # meaning multiple passes through the validation data within a single training epoch
         # would not have the dataloader reloaded.
-        # This breaks the assumption behind reload_dataloaders_every_epoch=True
+        # This breaks the assumption behind reload_dataloaders_every_n_epochs=True
         call.val_dataloader(),
         call.train_dataloader(),
         call.val_dataloader(),