diff --git a/src/models/pro_mod.py b/src/models/pro_mod.py
index 404a224f..148cc25d 100644
--- a/src/models/pro_mod.py
+++ b/src/models/pro_mod.py
@@ -351,21 +351,21 @@ def forward_pro(self, data):
                                   self.edge_weight != 'binary') else None
         
         target_x = self.relu(target_x)
-        ei_drp, _, _ = dropout_node(ei, p=self.dropout_prot_p, num_nodes=target_x.shape[0], 
-                                        training=self.training)
+        # ei_drp, _, _ = dropout_node(ei, p=self.dropout_prot_p, num_nodes=target_x.shape[0], 
+        #                                 training=self.training)
         
         # conv1
-        xt = self.pro_conv1(target_x, ei_drp, ew)
+        xt = self.pro_conv1(target_x, ei, ew)
         xt = self.relu(xt)
-        ei_drp, _, _ = dropout_node(ei, p=self.dropout_prot_p, num_nodes=target_x.shape[0], 
-                                        training=self.training)
+        # ei_drp, _, _ = dropout_node(ei, p=self.dropout_prot_p, num_nodes=target_x.shape[0], 
+        #                                 training=self.training)
         # conv2
-        xt = self.pro_conv2(xt, ei_drp, ew)
+        xt = self.pro_conv2(xt, ei, ew)
         xt = self.relu(xt)
-        ei_drp, _, _ = dropout_node(ei, p=self.dropout_prot_p, num_nodes=target_x.shape[0], 
-                                        training=self.training)
+        # ei_drp, _, _ = dropout_node(ei, p=self.dropout_prot_p, num_nodes=target_x.shape[0], 
+        #                                 training=self.training)
         # conv3
-        xt = self.pro_conv3(xt, ei_drp, ew)
+        xt = self.pro_conv3(xt, ei, ew)
         xt = self.relu(xt)
 
         # flatten/pool