How to use graph augmentation when learning on large graphs

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Hello! Thanks for the codes! I have a question on how to use the augmentation including RE and MF mentioned in the paper on a large graph. Now, I randomly select a minibatch of nodes from the large graph, and then a subgraph can be generated. I sample 15,10,5 neighbours at the first-, second-, and third-hop. However, I am not sure how to do the graph augmentation to obtain two views. Should I generate two views of the raw large graph first and then sample subgraphs, or should I produce two views for the subgraphs at the first-hop? Could you please upload codes on large graph training? Thank you very much!!!