diff --git a/train.py b/train.py
index ceea5782..cea491c3 100644
--- a/train.py
+++ b/train.py
@@ -266,7 +266,7 @@ def train(cfg,
             pred = model(imgs)
 
             # Compute loss
-            loss, loss_items = compute_loss(pred, targets, model, giou_loss=not opt.xywh)
+            loss, loss_items = compute_loss(pred, targets, model)
             if torch.isnan(loss):
                 print('WARNING: nan loss detected, ending training')
                 return results
@@ -368,7 +368,6 @@ if __name__ == '__main__':
     parser.add_argument('--transfer', action='store_true', help='transfer learning flag')
     parser.add_argument('--nosave', action='store_true', help='only save final checkpoint')
     parser.add_argument('--notest', action='store_true', help='only test final epoch')
-    parser.add_argument('--xywh', action='store_true', help='use xywh loss instead of GIoU loss')
     parser.add_argument('--evolve', action='store_true', help='evolve hyperparameters')
     parser.add_argument('--bucket', type=str, default='', help='gsutil bucket')
     parser.add_argument('--img-weights', action='store_true', help='select training images by weight')
diff --git a/utils/utils.py b/utils/utils.py
index e8fdbfa4..76b53ebc 100755
--- a/utils/utils.py
+++ b/utils/utils.py
@@ -312,7 +312,7 @@ class FocalLoss(nn.Module):
             return loss
 
 
-def compute_loss(p, targets, model, giou_loss=True):  # predictions, targets, model
+def compute_loss(p, targets, model):  # predictions, targets, model
     ft = torch.cuda.FloatTensor if p[0].is_cuda else torch.Tensor
     lcls, lbox, lobj = ft([0]), ft([0]), ft([0])
     tcls, tbox, indices, anchor_vec = build_targets(model, targets)