Ammend iou_fn tests

Author: adityagandhamal

test/test_ops.py

@@ -1367,8 +1367,6 @@ def assert_empty_loss(iou_fn, dtype, device):
     loss = iou_fn(box1, box2, reduction="none")
     assert loss.numel() == 0, f"{str(iou_fn)} for two empty box should be empty"
 
-def assert_reduction_mode(iou_fn, box1, box2, reduction):
-    assert iou_fn(box1, box2, reduction) == ValueError
 
 class TestGeneralizedBoxIouLoss:
     # We refer to original test: https://github.com/facebookresearch/fvcore/blob/main/tests/test_giou_loss.py
@@ -1399,7 +1397,8 @@ def test_giou_loss(self, dtype, device):
         # Test reduction value
         # reduction value other than ["none", "mean", "sum"] should raise a ValueError
         with pytest.raises(ValueError, match="Invalid"):
-            assert_reduction_mode(ops.generalized_box_iou_loss, box1s, box2s, reduction="xyz")
+            ops.generalized_box_iou_loss(box1s, box2s, reduction="xyz")
+            
 
     @pytest.mark.parametrize("device", cpu_and_gpu())
     @pytest.mark.parametrize("dtype", [torch.float32, torch.half])
@@ -1421,7 +1420,7 @@ def test_ciou_loss(self, dtype, device):
         assert_iou_loss(ops.complete_box_iou_loss, box1s, box2s, 2.4500, device=device, reduction="sum")
 
         with pytest.raises(ValueError, match="Invalid"):
-            assert_reduction_mode(ops.complete_box_iou_loss, box1s, box2s, reduction="xyz")
+            ops.complete_box_iou_loss(box1s, box2s, reduction="xyz")
 
     @pytest.mark.parametrize("device", cpu_and_gpu())
     @pytest.mark.parametrize("dtype", [torch.float32, torch.half])
@@ -1443,7 +1442,7 @@ def test_distance_iou_loss(self, dtype, device):
         assert_iou_loss(ops.distance_box_iou_loss, box1s, box2s, 2.4500, device=device, reduction="sum")
 
         with pytest.raises(ValueError, match="Invalid"):
-            assert_reduction_mode(ops.distance_box_iou_loss, box1s, box2s, reduction="xyz")
+            ops.distance_box_iou_loss(box1s, box2s, reduction="xyz")
 
     @pytest.mark.parametrize("device", cpu_and_gpu())
     @pytest.mark.parametrize("dtype", [torch.float32, torch.half])
@@ -1576,7 +1575,7 @@ def test_reduction_mode(self, device, dtype, reduction="xyz"):
         torch.random.manual_seed(0)      
         inputs, targets = self._generate_diverse_input_target_pair(device=device, dtype=dtype)
         with pytest.raises(ValueError, match="Invalid"):
-            ops.sigmoid_focal_loss(inputs, targets, 0.25, 2, reduction) == ValueError
+            ops.sigmoid_focal_loss(inputs, targets, 0.25, 2, reduction)