style: reformat with black 25.11.0

Signed-off-by: Rusheel Sharma <rusheelhere@gmail.com>

Author: Rusheel86

monai/losses/dice.py

@@ -214,9 +214,11 @@ def forward(self, input: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
                 self.class_weight = torch.as_tensor([self.class_weight] * num_of_classes)
             else:
                 if self.class_weight.shape[0] != num_of_classes:
-                    raise ValueError("""the length of the `weight` sequence should be the same as the number of classes.
+                    raise ValueError(
+                        """the length of the `weight` sequence should be the same as the number of classes.
                         If `include_background=False`, the weight should not include
-                        the background category class 0.""")
+                        the background category class 0."""
+                    )
             if self.class_weight.min() < 0:
                 raise ValueError("the value/values of the `weight` should be no less than 0.")
             # apply class_weight to loss

monai/losses/focal_loss.py

@@ -191,9 +191,11 @@ def forward(self, input: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
                 self.class_weight = torch.as_tensor([self.class_weight] * num_of_classes)
             else:
                 if self.class_weight.shape[0] != num_of_classes:
-                    raise ValueError("""the length of the `weight` sequence should be the same as the number of classes.
+                    raise ValueError(
+                        """the length of the `weight` sequence should be the same as the number of classes.
                         If `include_background=False`, the weight should not include
-                        the background category class 0.""")
+                        the background category class 0."""
+                    )
             if self.class_weight.min() < 0:
                 raise ValueError("the value/values of the `weight` should be no less than 0.")
             # apply class_weight to loss