diff --git a/ogb/io/read_graph_pyg.py b/ogb/io/read_graph_pyg.py
index ff61b8f..2f80cde 100644
--- a/ogb/io/read_graph_pyg.py
+++ b/ogb/io/read_graph_pyg.py
@@ -51,7 +51,7 @@ def read_graph_pyg(raw_dir, add_inverse_edge = False, additional_node_files = []
         add_order_info_01(g)  # DAGNN
         # length of longest path
         # layer ids start with 0 so max, gives actual path length and -1 is not necessary
-        g.len_longest_path = float(torch.max(g._bi_layer_idx0).item())
+        g.len_longest_path = float(torch.max(g.bi_layer_idx0).item())
 
     return pyg_graph_list
 
diff --git a/ogbg-code/model/dagnn.py b/ogbg-code/model/dagnn.py
index 9d505df..1cbca2e 100644
--- a/ogbg-code/model/dagnn.py
+++ b/ogbg-code/model/dagnn.py
@@ -128,8 +128,8 @@ def _get_output_nodes(self, G, reverse=0):
     def forward(self, G):
         # need to create these here since pyg's batching otherwise messes up the indices
         G.bi_layer_index = torch.stack([
-            torch.stack([G._bi_layer_idx0, G._bi_layer_index0], dim=0),
-            torch.stack([G._bi_layer_idx1, G._bi_layer_index1], dim=0)
+            torch.stack([G.bi_layer_idx0, G.bi_layer_index0], dim=0),
+            torch.stack([G.bi_layer_idx1, G.bi_layer_index1], dim=0)
         ], dim=0)
 
         device = G.x.device
diff --git a/src/utils_dag.py b/src/utils_dag.py
index 94c074d..271ec5c 100644
--- a/src/utils_dag.py
+++ b/src/utils_dag.py
@@ -43,10 +43,10 @@ def add_order_info_01(graph):
     l1 = top_sort(ei2, graph.num_nodes)
     ns = torch.LongTensor([i for i in range(graph.num_nodes)])
 
-    graph.__setattr__("_bi_layer_idx0", l0)
-    graph.__setattr__("_bi_layer_index0", ns)
-    graph.__setattr__("_bi_layer_idx1", l1)
-    graph.__setattr__("_bi_layer_index1", ns)
+    graph.__setattr__("bi_layer_idx0", l0)
+    graph.__setattr__("bi_layer_index0", ns)
+    graph.__setattr__("bi_layer_idx1", l1)
+    graph.__setattr__("bi_layer_index1", ns)
 
     assert_order(graph.edge_index, l0, ns)
     assert_order(ei2, l1, ns)