The code in DGL github: dgl/examples/pytorch/graphsage/node_classification.py at line 93
Validation should be conducted using MultiLayerFullNeighborSampler but not NeighborSampler which is the same as the train_dataloader?
It depends. The results from a NeighborSampler with randomly sampled neighbors are unbiased estimations of results from a MultiLayerFullNeighborSampler. And that’s also why we can use such sampling during training. Of course, if you want results with lower variance, you can definitely use a MultiLayerFullNeighborSampler instead.
1 Like
This topic was automatically closed 30 days after the last reply. New replies are no longer allowed.