IndexError: "index out of range in self" in training on custom dataset

[leon-cas]

i, I was trying to use HGTConv on a custom graph with 5 different nodes, but I kept on running into an error IndexError: index out of range in self when node_type only has target node.

Error messages:
node_type = tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1..., 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1])
node_type.shape = (129,)
edge_index = tensor([[ 0, 1, 14, 3, 4, 5, 6, 7,...82, 184, 188, 189, 189,
190, 190, 192]])
edge_index.shape = (2, 353)

IndexError: index out of range in self
When calling: self.propagate(edge_index, node_inp=node_inp, node_type=node_type,
edge_type=edge_type, edge_time = edge_time)
Call ended by exception
meta_xs = gc(meta_xs, node_type_id, edge_index, edge_type, edge_time)
IndexError: index out of range in self
When calling: gc(meta_xs, node_type_id, edge_index, edge_type, edge_time)
Call ended by exception

I was looking at pyg-team/pytorch_geometric#2073 where suggestion "remove cached=True argument from the GCNConv layer can solve the index error.

and pyg-team/pytorch_geometric#1631: set add_self_loops=False in GATConv(..., add_self_loops=False), but no such argument in HGTConv.

[rickyqiao]

Hello leon-cas. I also encounter this problem when I use HGTConv. Had you solved this problem?