Fix supersimplenet's SSNLoss device issue

Signed-off-by: Samet Akcay <samet.akcay@intel.com>

src/anomalib/models/image/supersimplenet/loss.py

@@ -39,8 +39,8 @@ def trunc_l1_loss(self, pred: torch.Tensor, target: torch.Tensor) -> torch.Tenso
         # push anomalous towards positive numbers
         fake_loss = torch.clip(-anomalous_scores + self.th, min=0)
 
-        true_loss = true_loss.mean() if len(true_loss) else torch.Tensor(0)
-        fake_loss = fake_loss.mean() if len(fake_loss) else torch.Tensor(0)
+        true_loss = true_loss.mean() if len(true_loss) else torch.tensor(0)
+        fake_loss = fake_loss.mean() if len(fake_loss) else torch.tensor(0)
 
         return true_loss + fake_loss