style: apply black formatting

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

Author: Rusheel86

monai/losses/focal_loss.py

@@ -232,7 +232,9 @@ def forward(self, input: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
                 if mask is not None:
                     spatial_dims = list(range(2, len(target.shape)))
                     sum_mask = mask.sum(dim=spatial_dims, keepdim=True)
-                    loss = (loss * mask).sum(dim=spatial_dims, keepdim=True) / sum_mask.clamp(min=torch.finfo(mask.dtype).eps)
+                    loss = (loss * mask).sum(dim=spatial_dims, keepdim=True) / sum_mask.clamp(
+                        min=torch.finfo(mask.dtype).eps
+                    )
                 else:
                     loss = loss.mean(dim=list(range(2, len(target.shape))))
             loss = loss.sum()

tests/metrics/test_ignore_index_metrics.py

@@ -80,9 +80,8 @@ def test_metric_ignore_consistency(self, metric_class, kwargs):
         torch.testing.assert_close(res1, res2, msg=f"Failed for {metric_class.__name__}")
 
     @parameterized.expand(
-        [(metric_class, kwargs, ignore_index)
-         for metric_class, kwargs in TEST_METRICS
-         for ignore_index in (0, 1)])
+        [(metric_class, kwargs, ignore_index) for metric_class, kwargs in TEST_METRICS for ignore_index in (0, 1)]
+    )
     def test_metric_ignore_class_index(self, metric_class, kwargs, ignore_index):
         metric = metric_class(ignore_index=ignore_index, **kwargs)
 
@@ -175,9 +174,8 @@ def test_metric_ignore_consistency(self, metric_class, kwargs):
         torch.testing.assert_close(res1, res2, msg=f"Failed for {metric_class.__name__}")
 
     @parameterized.expand(
-        [(metric_class, kwargs, ignore_index)
-         for metric_class, kwargs in SCIPY_METRICS
-         for ignore_index in (0, 1)])
+        [(metric_class, kwargs, ignore_index) for metric_class, kwargs in SCIPY_METRICS for ignore_index in (0, 1)]
+    )
     def test_metric_ignore_class_index(self, metric_class, kwargs, ignore_index):
         metric = metric_class(ignore_index=ignore_index, **kwargs)