Bug: `GCNConv` in `to_hetero` with single node type

🐛 Describe the bug

I just started using heterogeneous graphs, so far I have roughly 1 year experience with homogeneous graphs using your library. I have a graph with just 1 node type (“gene”) but multiple edge types between the nodes. My HeteroData object prints as follows:

HeteroData(
  gene={
    x=[16433, 93],
    y=[16433],
    train_mask=[16433],
    test_mask=[16433],
    val_mask=False
  },
  (gene, BioPlex30HCT116, gene)={ edge_index=[2, 95370] },
  (gene, BioPlex30293T, gene)={ edge_index=[2, 156370] },
  (gene, HuRI, gene)={ edge_index=[2, 74488] }
)

I convert my GCN-based model (that runs fine with a homogeneous Data object) using the to_hetero() function.

I then pass my data into the model as follows:

out = model(data.x_dict, data.edge_index_dict)

where data is the HeteroData Object described above.

However, I get an error and I think it is because it expects edge_weight somewhere:

Traceback (most recent call last):
    out = model(data.x_dict, data.edge_index_dict)
  File "/home/fratajcz/anaconda3/envs/compat/lib/python3.7/site-packages/torch/fx/graph_module.py", line 308, in wrapped_call
    return cls_call(self, *args, **kwargs)
  File "/home/fratajcz/anaconda3/envs/compat/lib/python3.7/site-packages/torch/fx/graph_module.py", line 308, in wrapped_call
    return cls_call(self, *args, **kwargs)
  File "/home/fratajcz/anaconda3/envs/compat/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "<eval_with_key_1>", line 7, in forward
    edge_weight__gene__BioPlex30HCT116__gene = edge_weight.get(('gene', 'BioPlex30HCT116', 'gene'))
AttributeError: 'NoneType' object has no attribute 'get'

Do I have to specify edge weights in heterogeneous graphs? The Documentation doesnt mention it. It is weird that the traceback does mention only torch packages and not torch_geometric.

Cheers and thanks, Florin

Environment

• PyG version: 2.0.1
• PyTorch version: 1.8.0
• OS: CentOS Linux 7
• Python version: 3.7
• CUDA/cuDNN version: irrelevant
• How you installed PyTorch and PyG (conda, pip, source): conda
• Any other relevant information (e.g., version of torch-scatter): torch_scatter: 2.0.8

[rusty1s]

Yes, you can only use GCNConv for passing messages to the same node type, e.g.:

HeteroConv({
    ...
    ('movie', 'is_similar', 'movie'): GCNConv(...),
    ...
})

This is a limitation of GCNConv as it does not support bipartite message passing.

[aayyad89]

Thanks, I did not get that.