Format

lightly/transforms/dino_transform.py

@@ -219,7 +219,7 @@ def __init__(
             T.RandomResizedCrop(
                 size=crop_size,
                 scale=crop_scale,
-                interpolation=PIL.Image.BICUBIC, # type: ignore[attr-defined]
+                interpolation=PIL.Image.BICUBIC,  # type: ignore[attr-defined]
             ),
             T.RandomHorizontalFlip(p=hf_prob),
             T.RandomVerticalFlip(p=vf_prob),

lightly/transforms/jigsaw.py

@@ -10,7 +10,6 @@
 from torch import Tensor
 from torchvision import transforms as T
 
-
 if TYPE_CHECKING:
     from numpy.typing import NDArray
 

lightly/transforms/rotation.py

@@ -65,7 +65,9 @@ class RandomRotateDegrees:
     """
 
     def __init__(self, prob: float, degrees: Union[float, Tuple[float, float]]):
-        self.transform: Callable[[Union[Image, Tensor]], Union[Image, Tensor]] = T.RandomApply([T.RandomRotation(degrees=degrees)], p=prob)
+        self.transform: Callable[
+            [Union[Image, Tensor]], Union[Image, Tensor]
+        ] = T.RandomApply([T.RandomRotation(degrees=degrees)], p=prob)
 
     def __call__(self, image: Union[Image, Tensor]) -> Union[Image, Tensor]:
         """Rotates the images with a given probability.

lightly/utils/benchmarking/linear_classifier.py

@@ -131,9 +131,9 @@ def validation_step(self, batch: Tuple[Tensor, ...], batch_idx: int) -> Tensor:
 
     # Type ignore is needed because return type of LightningModule.configure_optimizers
     # is complicated and typing changes between versions.
-    def configure_optimizers( # type: ignore[override]
+    def configure_optimizers(  # type: ignore[override]
         self,
-    ) -> Tuple[List[Optimizer], List[Dict[str, Union[Any, str]]]]: 
+    ) -> Tuple[List[Optimizer], List[Dict[str, Union[Any, str]]]]:
         parameters = list(self.classification_head.parameters())
         if not self.freeze_model:
             parameters += self.model.parameters()

lightly/utils/lars.py

@@ -102,14 +102,14 @@ def __setstate__(self, state: Dict[str, Any]) -> None:
 
         for group in self.param_groups:
             group.setdefault("nesterov", False)
-    
+
     # Type ignore for overloads is required for Python 3.7
-    @overload # type: ignore[override]
-    def step(self, closure: None = None) -> None: 
+    @overload  # type: ignore[override]
+    def step(self, closure: None = None) -> None:
         ...
 
-    @overload # type: ignore[override]
-    def step(self, closure: Callable[[], float]) -> float: 
+    @overload  # type: ignore[override]
+    def step(self, closure: Callable[[], float]) -> float:
         ...
 
     @torch.no_grad()

tests/helpers.py

@@ -1,9 +1,11 @@
-from torch import Tensor
 from typing import Any, List
 
+from torch import Tensor
+
+
 def assert_list_tensor(items: Any) -> List[Tensor]:
     """Makes sure that the input is a list of tensors.
-    
+
     Should be used in tests where functions return Union[List[Tensor], List[Image]] and
     we want to make sure that the output is a list of tensors.
 

tests/transforms/test_byol_transform.py

@@ -5,6 +5,7 @@
     BYOLView1Transform,
     BYOLView2Transform,
 )
+
 from .. import helpers
 
 

tests/transforms/test_densecl_transform.py

@@ -1,6 +1,7 @@
 from PIL import Image
 
 from lightly.transforms import DenseCLTransform
+
 from .. import helpers
 
 

tests/transforms/test_dino_transform.py

@@ -1,6 +1,7 @@
 from PIL import Image
 
 from lightly.transforms.dino_transform import DINOTransform, DINOViewTransform
+
 from .. import helpers
 
 

tests/transforms/test_fastsiam_transform.py

@@ -1,8 +1,10 @@
 from PIL import Image
 
 from lightly.transforms.fast_siam_transform import FastSiamTransform
+
 from .. import helpers
 
+
 def test_multi_view_on_pil_image() -> None:
     multi_view_transform = FastSiamTransform(num_views=3, input_size=32)
     sample = Image.new("RGB", (100, 100))

tests/transforms/test_moco_transform.py

@@ -1,6 +1,7 @@
 from PIL import Image
 
 from lightly.transforms.moco_transform import MoCoV1Transform, MoCoV2Transform
+
 from .. import helpers
 
 

tests/transforms/test_msn_transform.py

@@ -1,6 +1,7 @@
 from PIL import Image
 
 from lightly.transforms.msn_transform import MSNTransform, MSNViewTransform
+
 from .. import helpers
 
 

tests/transforms/test_pirl_transform.py

@@ -1,6 +1,7 @@
 from PIL import Image
 
 from lightly.transforms.pirl_transform import PIRLTransform
+
 from .. import helpers
 
 

tests/transforms/test_simclr_transform.py

@@ -1,6 +1,7 @@
 from PIL import Image
 
 from lightly.transforms.simclr_transform import SimCLRTransform, SimCLRViewTransform
+
 from .. import helpers
 
 

tests/transforms/test_simsiam_transform.py

@@ -1,6 +1,7 @@
 from PIL import Image
 
 from lightly.transforms.simsiam_transform import SimSiamTransform, SimSiamViewTransform
+
 from .. import helpers
 
 

tests/transforms/test_smog_transform.py

@@ -1,6 +1,7 @@
 from PIL import Image
 
 from lightly.transforms.smog_transform import SMoGTransform, SmoGViewTransform
+
 from .. import helpers
 
 

tests/transforms/test_swav_transform.py

@@ -1,8 +1,10 @@
 from PIL import Image
 
 from lightly.transforms.swav_transform import SwaVTransform, SwaVViewTransform
+
 from .. import helpers
 
+
 def test_view_on_pil_image() -> None:
     single_view_transform = SwaVViewTransform()
     sample = Image.new("RGB", (100, 100))

tests/transforms/test_vicreg_transform.py

@@ -1,6 +1,7 @@
 from PIL import Image
 
 from lightly.transforms.vicreg_transform import VICRegTransform, VICRegViewTransform
+
 from .. import helpers
 
 

tests/transforms/test_vicregl_transform.py

@@ -1,8 +1,10 @@
 from typing import List
+
 from PIL import Image
 from torch import Tensor
 
 from lightly.transforms.vicregl_transform import VICRegLTransform, VICRegLViewTransform
+
 from .. import helpers