I use the dgl library to batch train the graph neural network model on a very large graph, and the sampling method is MultiLayerFullNeighborSampler(2). But even if the batch size is set to 1, a certain subgraph may have tens of millions of edges due to the high degree of nodes. Therefore, when the information is transmitted, the GPU memory will be exceeded.
How should I solve this problem?
