Performance issues with ogbl-biokg graph in DeepSNAP about deepsnap HOT 1 OPEN

Hi,

Thanks for pointing out this. Right, handling the graph data by using the NetworkX graph object seems not efficient. But the performance issue for generating the HeteroGraph might be mainly caused by what DeepSNAP does internally, transforming the NetworkX graph into tensors and in the link prediction case it will also split multiple negative edges. These can actually cause the performance / memory issue. One potential solution is to not use DeepSNAP if you don't need to manipulate the graph heavily (for example during training). You can use PyG directly with its transforms functions. Also, now the heterogeneous functionality has also been merged into the PyG and you can use it from PyG directly. If you have heavy graph manipulation requirements and need to use the graph algorithm from NetworkX, you can try to feed tensors directly such as this example but I am not sure whether this can work for the link prediction task (also not very sure about the performance). I will benchmark and try to find the performance issue if I have time recently.

Thanks.

from deepsnap.