diff --git a/nets/yolo_training.py b/nets/yolo_training.py
index 484ea20ef880a52a3f6b3eb7a566a93cb9b6cd0a..85e33f930b337cafdf14036818946a291e09cfe1 100644
--- a/nets/yolo_training.py
+++ b/nets/yolo_training.py
@@ -403,14 +403,14 @@ class YOLOLoss(nn.Module):
                 matching_anchs[i].append(all_anch[layer_idx])
 
         for i in range(num_layer):
-            matching_bs[i]      = torch.cat(matching_bs[i], dim=0)
-            matching_as[i]      = torch.cat(matching_as[i], dim=0)
-            matching_gjs[i]     = torch.cat(matching_gjs[i], dim=0)
-            matching_gis[i]     = torch.cat(matching_gis[i], dim=0)
-            matching_targets[i] = torch.cat(matching_targets[i], dim=0)
-            matching_anchs[i]   = torch.cat(matching_anchs[i], dim=0)
-
-        return matching_bs, matching_as, matching_gjs, matching_gis, matching_targets, matching_anchs           
+            matching_bs[i]      = torch.cat(matching_bs[i], dim=0) if len(matching_bs[i]) != 0 else torch.Tensor(matching_bs[i])
+            matching_as[i]      = torch.cat(matching_as[i], dim=0) if len(matching_as[i]) != 0 else torch.Tensor(matching_as[i])
+            matching_gjs[i]     = torch.cat(matching_gjs[i], dim=0) if len(matching_gjs[i]) != 0 else torch.Tensor(matching_gjs[i])
+            matching_gis[i]     = torch.cat(matching_gis[i], dim=0) if len(matching_gis[i]) != 0 else torch.Tensor(matching_gis[i])
+            matching_targets[i] = torch.cat(matching_targets[i], dim=0) if len(matching_targets[i]) != 0 else torch.Tensor(matching_targets[i])
+            matching_anchs[i]   = torch.cat(matching_anchs[i], dim=0) if len(matching_anchs[i]) != 0 else torch.Tensor(matching_anchs[i])
+
+        return matching_bs, matching_as, matching_gjs, matching_gis, matching_targets, matching_anchs
 
     def find_3_positive(self, predictions, targets):
         #------------------------------------#