[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

tests/losses/test_unified_focal_loss.py

@@ -22,11 +22,11 @@
 # Input Shape: (B, 1, H, W) -> Auto expanded internally
 TEST_CASE_BINARY_LOGITS = [
     {
-        "y_pred": torch.tensor([[[[10.0, -10.0], [-10.0, 10.0]]]]), 
-        "y_true": torch.tensor([[[[1.0, 0.0], [0.0, 1.0]]]]),       
+        "y_pred": torch.tensor([[[[10.0, -10.0], [-10.0, 10.0]]]]),
+        "y_true": torch.tensor([[[[1.0, 0.0], [0.0, 1.0]]]]),
     },
     0.0,
-    {"use_softmax": False, "to_onehot_y": False} 
+    {"use_softmax": False, "to_onehot_y": False}
 ]
 
 # 2. Binary Case (2 Channels input): Prediction matches GT perfectly
@@ -56,12 +56,12 @@
 # 4. Multi-Class Case: Wrong Prediction
 TEST_CASE_MULTICLASS_WRONG = [
     {
-        "y_pred": torch.tensor([[[[-10.0, -10.0], [-10.0, -10.0]], 
-                                 [[10.0, 10.0], [10.0, 10.0]], 
-                                 [[-10.0, -10.0], [-10.0, -10.0]]]]), 
+        "y_pred": torch.tensor([[[[-10.0, -10.0], [-10.0, -10.0]],
+                                 [[10.0, 10.0], [10.0, 10.0]],
+                                 [[-10.0, -10.0], [-10.0, -10.0]]]]),
         "y_true": torch.tensor([[[[0, 0], [0, 0]]]]), # GT is class 0, but Pred is class 1
     },
-    None, 
+    None,
     {"use_softmax": True, "to_onehot_y": True}
 ]
 
@@ -99,11 +99,11 @@ def test_with_cuda(self):
         # Binary logits case on GPU
         i = torch.tensor([[[[10.0, 0], [0, 10.0]]], [[[10.0, 0], [0, 10.0]]]]).cuda()
         j = torch.tensor([[[[1.0, 0], [0, 1.0]]], [[[1.0, 0], [0, 1.0]]]]).cuda()
-        
+
         output = loss(i, j)
         print(f"CUDA Output: {output.item()}")
         self.assertTrue(output.is_cuda)
-        self.assertLess(output.item(), 1.0) 
+        self.assertLess(output.item(), 1.0)
 
 if __name__ == "__main__":
-    unittest.main()
+    unittest.main()