Black format pytorch_lightning/core/hooks.py (#3575)

Split out changes from #3563 to make that PR easier to review. This formats the file according to the Black formatter

pytorch_lightning/core/hooks.py

@@ -12,14 +12,14 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from typing import Any, Union, List
+from typing import Any, List, Union
 
 import torch
+from pytorch_lightning.utilities import AMPType, move_data_to_device, rank_zero_warn
 from torch import Tensor
 from torch.optim.optimizer import Optimizer
 from torch.utils.data import DataLoader
 
-from pytorch_lightning.utilities import move_data_to_device, AMPType, rank_zero_warn
 
 try:
     from apex import amp
@@ -28,7 +28,6 @@
 
 
 class ModelHooks:
-
     def setup(self, stage: str):
         """
         Called at the beginning of fit and test.
@@ -113,7 +112,9 @@ def on_pretrain_routine_end(self) -> None:
         """
         # do something at the end of the pretrain routine
 
-    def on_train_batch_start(self, batch: Any, batch_idx: int, dataloader_idx: int) -> None:
+    def on_train_batch_start(
+        self, batch: Any, batch_idx: int, dataloader_idx: int
+    ) -> None:
         """
         Called in the training loop before anything happens for that batch.
 
@@ -126,7 +127,9 @@ def on_train_batch_start(self, batch: Any, batch_idx: int, dataloader_idx: int)
         """
         # do something when the batch starts
 
-    def on_train_batch_end(self, batch: Any, batch_idx: int, dataloader_idx: int) -> None:
+    def on_train_batch_end(
+        self, batch: Any, batch_idx: int, dataloader_idx: int
+    ) -> None:
         """
         Called in the training loop after the batch.
 
@@ -137,7 +140,9 @@ def on_train_batch_end(self, batch: Any, batch_idx: int, dataloader_idx: int) ->
         """
         # do something when the batch ends
 
-    def on_validation_batch_start(self, batch: Any, batch_idx: int, dataloader_idx: int) -> None:
+    def on_validation_batch_start(
+        self, batch: Any, batch_idx: int, dataloader_idx: int
+    ) -> None:
         """
         Called in the validation loop before anything happens for that batch.
 
@@ -148,7 +153,9 @@ def on_validation_batch_start(self, batch: Any, batch_idx: int, dataloader_idx:
         """
         # do something when the batch starts
 
-    def on_validation_batch_end(self, batch: Any, batch_idx: int, dataloader_idx: int) -> None:
+    def on_validation_batch_end(
+        self, batch: Any, batch_idx: int, dataloader_idx: int
+    ) -> None:
         """
         Called in the validation loop after the batch.
 
@@ -159,7 +166,9 @@ def on_validation_batch_end(self, batch: Any, batch_idx: int, dataloader_idx: in
         """
         # do something when the batch ends
 
-    def on_test_batch_start(self, batch: Any, batch_idx: int, dataloader_idx: int) -> None:
+    def on_test_batch_start(
+        self, batch: Any, batch_idx: int, dataloader_idx: int
+    ) -> None:
         """
         Called in the test loop before anything happens for that batch.
 
@@ -170,7 +179,9 @@ def on_test_batch_start(self, batch: Any, batch_idx: int, dataloader_idx: int) -
         """
         # do something when the batch starts
 
-    def on_test_batch_end(self, batch: Any, batch_idx: int, dataloader_idx: int) -> None:
+    def on_test_batch_end(
+        self, batch: Any, batch_idx: int, dataloader_idx: int
+    ) -> None:
         """
         Called in the test loop after the batch.
 
@@ -288,7 +299,9 @@ def on_after_backward(self):
 
         """
 
-    def backward(self, trainer, loss: Tensor, optimizer: Optimizer, optimizer_idx: int) -> None:
+    def backward(
+        self, trainer, loss: Tensor, optimizer: Optimizer, optimizer_idx: int
+    ) -> None:
         """
         Override backward with your own implementation if you need to.
 
@@ -311,7 +324,13 @@ def backward(self, trainer, loss, optimizer, optimizer_idx):
         """
         loss.backward()
 
-    def amp_scale_loss(self, unscaled_loss, optimizer, optimizer_idx, amp_backend: AMPType):
+    def amp_scale_loss(
+        self,
+        unscaled_loss: Tensor,
+        optimizer: Optimizer,
+        optimizer_idx: int,
+        amp_backend: AMPType,
+    ):
         if amp_backend == AMPType.NATIVE:
             scaled_loss = self.trainer.scaler.scale(unscaled_loss)
         else:
@@ -321,7 +340,6 @@ def amp_scale_loss(self, unscaled_loss, optimizer, optimizer_idx, amp_backend: A
 
 
 class DataHooks:
-
     def prepare_data(self) -> None:
         """
         Use this to download and prepare data.
@@ -412,7 +430,9 @@ def train_dataloader(self):
                     return loader
 
         """
-        rank_zero_warn('`train_dataloader` must be implemented to be used with the Lightning Trainer')
+        rank_zero_warn(
+            "`train_dataloader` must be implemented to be used with the Lightning Trainer"
+        )
 
     def test_dataloader(self) -> Union[DataLoader, List[DataLoader]]:
         r"""