formatting

Author: Borda

pl_examples/basic_examples/dali_image_classifier.py

@@ -197,23 +197,23 @@ def train_dataloader(self):
             self.pipe_train,
             size=len(self.mnist_train),
             auto_reset=True,
-            fill_last_batch=True
+            fill_last_batch=True,
         )
 
     def val_dataloader(self):
         return DALIClassificationLoader(
             self.pipe_val,
             size=len(self.mnist_val),
             auto_reset=True,
-            fill_last_batch=False
+            fill_last_batch=False,
         )
 
     def test_dataloader(self):
         return DALIClassificationLoader(
             self.pipe_test,
             size=len(self.mnist_test),
             auto_reset=True,
-            fill_last_batch=False
+            fill_last_batch=False,
         )
 
 

pl_examples/basic_examples/profiler_example.py

@@ -44,10 +44,7 @@
 
 class ModelToProfile(LightningModule):
 
-    def __init__(
-        self,
-        name: str = "resnet50"
-    ):
+    def __init__(self, name: str = "resnet50"):
         super().__init__()
         self.model = getattr(models, name)(pretrained=True)
         self.criterion = torch.nn.CrossEntropyLoss()

pl_examples/bug_report_model.py

@@ -1,6 +1,8 @@
 import os
+
 import torch
-from torch.utils.data import Dataset, DataLoader
+from torch.utils.data import DataLoader, Dataset
+
 from pytorch_lightning import LightningModule, Trainer
 
 

pytorch_lightning/accelerators/cpu.py

@@ -34,8 +34,6 @@ def setup(self, trainer: 'pl.Trainer', model: 'pl.LightningModule') -> None:
             )
 
         if "cpu" not in str(self.root_device):
-            raise MisconfigurationException(
-                f"Device should be CPU, got {self.root_device} instead."
-            )
+            raise MisconfigurationException(f"Device should be CPU, got {self.root_device} instead.")
 
         return super().setup(trainer, model)

pytorch_lightning/utilities/device_dtype_mixin.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 from typing import Optional, Union
+
 import torch
 from torch.nn import Module