efficience about data augmentation on Large graph about graphcl

[yyou1996]

Hi @Wjk666,

Thanks for your interest. For NodeDrop, EdgePert and AttrMask augmentations, complexity should be O(K) (where K is the augmented number, e.g. the nodes dropped in NodeDrop), thus it is OK to scale up on larger graphs. For Subgraph the complexity might be higher since there is a while loop in it, so when comes to too large graph, I think you might consider updating the implementation a little bit.

Because in the way of GraphCL, it needs 4 GNN encoders at the same time per epoch.
Actually in GraphCL it only requires 1 GNN encoder, propagate for twice (2 augmented views). Things might be some different when comes to your case.

[junkangwu]

@yyou1996 Thanks a lot for your advice and suggestion, I think I have to check my code.