diff --git a/run_pplm-contact.py b/run_pplm-contact.py
index 727bfed..f53b626 100644
--- a/run_pplm-contact.py
+++ b/run_pplm-contact.py
@@ -310,13 +310,7 @@ def collect_all_features():
     return feats
 
 def predict_contact(feats, mode, device="cpu"):
-
     script_dir = os.path.dirname(os.path.abspath(__file__))
-    # if mode == "homo":
-    #     model_paths = [os.path.join(script_dir, "pplm_contact/models/pplm_contact.homo_" + str(i) + ".pkl") for i in range(1, 6)]
-    # else:
-    #     model_paths = [os.path.join(script_dir, "pplm_contact/models/pplm_contact.hetero_" + str(i) + ".pkl") for i in range(1, 6)]
-    #
     models_weight_ = torch.load(os.path.join(script_dir, "weights/pplm_contact_models.pkl"), map_location=device)
     if mode == "homo":
         models_weight = models_weight_['homo']
@@ -336,7 +330,6 @@ def predict_contact(feats, mode, device="cpu"):
     ensemble_pred_inter_contact = []
     with torch.no_grad():
         for model_weight in models_weight:
-            # checkpoint = torch.load(model_path, map_location=device)
             model.load_state_dict(model_weight)
             model.eval()
 
@@ -346,7 +339,7 @@ def predict_contact(feats, mode, device="cpu"):
                 contact_pred_ = model(intra2_1d, intra2_2d, intra1_1d, intra1_2d, inter_2d.transpose(-1, -2), intra2_Mdist, intra1_Mdist)
                 contact_pred = (contact_pred + contact_pred_.transpose(-1, -2)) / 2
 
-            pred_inter_contact = contact_pred  # [inter_contact_mask_ur]
+            pred_inter_contact = contact_pred 
             ensemble_pred_inter_contact.append(pred_inter_contact)
 
         pred_inter_contact = torch.stack(ensemble_pred_inter_contact)
@@ -354,6 +347,10 @@ def predict_contact(feats, mode, device="cpu"):
 
     return pred_inter_contact
 
+
+
+
+
 if __name__ == "__main__":
     main()