Great Library!

I have one question about link_prediction.py in RGCN. More specifically, in codes below

```
g, node_id, edge_type, node_norm, data, labels = \
utils.generate_sampled_graph_and_labels(
train_data, args.graph_batch_size, args.graph_split_size,
num_rels, adj_list, degrees, args.negative_sample)
```

g, node_id, edge_type, node_norm are the subgraph used to pass messages. (used for encoding). data and label are used to calculate loss based on the forward embeddings after message passing.(used for decoding and cal loss on this batch)

Why the edges in g are included in ‘data’, which means you used seen edges to predict this seen edges and propagate the loss. I am confused about this. Thanks very much for help!