Fix logic.

dmsr.py

@@ -97,17 +97,17 @@ class HeteroGNN(torch.nn.Module):
 
         edge_weight = data.edge_feature  # Edge weights need to be reformated to match model's requirements.
         keys = [key for key in edge_weight]
+        edge_weight2 = {}
         for key in keys:
             newKey = key[1]
-            edge_weight[newKey] = edge_weight[key]
-            del edge_weight[key]
+            edge_weight2[newKey] = edge_weight[key]
 
-        x = self.convs1(x, edge_index, edge_weight)
+        x = self.convs1(x, edge_index, edge_weight2)
         x = forward_op(x, self.bns1)
         x = forward_op(x, self.relus1)
 
         x = forward_op(x, self.dropout1)
-        x = self.convs2(x, edge_index, edge_weight)
+        x = self.convs2(x, edge_index, edge_weight2)
         x = forward_op(x, self.bns2)
 
         return x