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update for torch==1.12.1+cu116 and torch-geometric==2.0.4. #8

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update for torch==1.12.1+cu116 and torch-geometric==2.0.4. #8

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2 changes: 1 addition & 1 deletion ogb/io/read_graph_pyg.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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

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4 changes: 2 additions & 2 deletions ogbg-code/model/dagnn.py
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Expand Up @@ -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
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8 changes: 4 additions & 4 deletions src/utils_dag.py
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Expand Up @@ -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)
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