Remove deprecation warnings being called for on_{task}_dataloader (#9279)

* Avoid deprecation warnings being called when hooks are not implemented
* Update tests & changelog
* Apply suggestions from code review

Co-authored-by: Rohit Gupta <[email protected]>
Conflicts:
	CHANGELOG.md
	pytorch_lightning/core/hooks.py
	tests/deprecated_api/test_remove_1-7.py
	tests/trainer/test_trainer.py

Author: 2 people

CHANGELOG.md

@@ -14,6 +14,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Fixed an issues with export to ONNX format when a model has multiple inputs ([#8800](https://github.com/PyTorchLightning/pytorch-lightning/pull/8800))
 
+- Removed deprecation warnings being called for `on_{task}_dataloader` ([#9279](https://github.com/PyTorchLightning/pytorch-lightning/pull/9279))
+
 - Fixed save/load/resume from checkpoint for DeepSpeed Plugin (
     [#8397](https://github.com/PyTorchLightning/pytorch-lightning/pull/8397),
     [#8644](https://github.com/PyTorchLightning/pytorch-lightning/pull/8644),

pytorch_lightning/core/hooks.py

@@ -669,15 +669,35 @@ def predict_dataloader(self) -> EVAL_DATALOADERS:
     def on_train_dataloader(self) -> None:
         """Called before requesting the train dataloader."""
 
+        .. deprecated:: v1.5
+            :meth:`on_train_dataloader` is deprecated and will be removed in v1.7.0.
+            Please use :meth:`train_dataloader()` directly.
+        """
+
     def on_val_dataloader(self) -> None:
         """Called before requesting the val dataloader."""
 
+        .. deprecated:: v1.5
+            :meth:`on_val_dataloader` is deprecated and will be removed in v1.7.0.
+            Please use :meth:`val_dataloader()` directly.
+        """
+
     def on_test_dataloader(self) -> None:
         """Called before requesting the test dataloader."""
 
+        .. deprecated:: v1.5
+            :meth:`on_test_dataloader` is deprecated and will be removed in v1.7.0.
+            Please use :meth:`test_dataloader()` directly.
+        """
+
     def on_predict_dataloader(self) -> None:
         """Called before requesting the predict dataloader."""
 
+        .. deprecated:: v1.5
+            :meth:`on_predict_dataloader` is deprecated and will be removed in v1.7.0.
+            Please use :meth:`predict_dataloader()` directly.
+        """
+
     def transfer_batch_to_device(self, batch: Any, device: torch.device, dataloader_idx: int) -> Any:
         """
         Override this hook if your :class:`~torch.utils.data.DataLoader` returns tensors

tests/trainer/test_trainer.py

@@ -1896,3 +1896,53 @@ def current_memory():
     trainer_2.fit(model)
 
     assert current_memory() <= initial
+
+
+class TrainerStagesErrorsModel(BoringModel):
+    def on_train_start(self) -> None:
+        raise Exception("Error during train")
+
+    def on_validation_start(self) -> None:
+        raise Exception("Error during validation")
+
+    def on_test_start(self) -> None:
+        raise Exception("Error during test")
+
+    def on_predict_start(self) -> None:
+        raise Exception("Error during predict")
+
+
+@pytest.mark.parametrize(
+    "accelerator,num_processes",
+    [
+        (None, 1),
+        pytest.param("ddp_cpu", 2, marks=RunIf(skip_windows=True)),
+    ],
+)
+def test_error_handling_all_stages(tmpdir, accelerator, num_processes):
+    model = TrainerStagesErrorsModel()
+    trainer = Trainer(default_root_dir=tmpdir, accelerator=accelerator, num_processes=num_processes, fast_dev_run=True)
+
+    with pytest.raises(Exception, match=r"Error during train"), patch(
+        "pytorch_lightning.Trainer._on_exception"
+    ) as exception_hook:
+        trainer.fit(model)
+    exception_hook.assert_called()
+
+    with pytest.raises(Exception, match=r"Error during validation"), patch(
+        "pytorch_lightning.Trainer._on_exception"
+    ) as exception_hook:
+        trainer.validate(model)
+    exception_hook.assert_called()
+
+    with pytest.raises(Exception, match=r"Error during test"), patch(
+        "pytorch_lightning.Trainer._on_exception"
+    ) as exception_hook:
+        trainer.test(model)
+    exception_hook.assert_called()
+
+    with pytest.raises(Exception, match=r"Error during predict"), patch(
+        "pytorch_lightning.Trainer._on_exception"
+    ) as exception_hook:
+        trainer.predict(model, model.val_dataloader(), return_predictions=False)
+    exception_hook.assert_called()