Custom data + negative samples about seal_ogb HOT 2 OPEN

Update:
I realized the code supports existing negative edges if already given in split_dict.
Also if I want to incorporate my edge features (list of vectors) into training do I add it in this line?

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Hello ercz16,

"the code supports existing negative edges if already given in split_dict." Yes, then no negative edge sampling is needed.

"does this implementation keep node embeddings limited to the training data and not used again in test data to possibly prevent data leakage?" Could you please provide more details on it? Currently, our model produces new node embeddings in each forward process as long as you do not use --train_node_embedding option.

"if I want to incorporate my edge features (list of vectors) into training do I add it in this line", Yes. You can change the model here to some models that can take edge feature as input. Like GINE https://pytorch-geometric.readthedocs.io/en/latest/generated/torch_geometric.nn.conv.GINEConv.html#torch_geometric.nn.conv.GINEConv

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