I trying to reproduce the same example and after @BarclayII fixes, it’s returning the following errors:

```
IndexError Traceback (most recent call last)
<ipython-input-14-862ce3753e90> in <module>()
29 predictions = []
30 ratings = []
---> 31 for pair_graph, blocks in t:
32 user_emb, item_emb = model(blocks)
33 prediction = model.compute_score(pair_graph, user_emb, item_emb)
5 frames
<ipython-input-9-500f9e8310e7> in construct_blocks(self, seeds, user_item_pairs_to_remove)
56 sampled_with_edges_removed = dgl.remove_edges(
57 sampled_with_edges_removed, edges_to_remove, 'watched-by')
---> 58 sampled_eids = sampled_eids[sampled_with_edges_removed.edges['watched'].data[dgl.EID]]
59 sampled_eids_rev = sampled_eids_rev[sampled_with_edges_removed.edges['watched-by'].data[dgl.EID]]
60
IndexError: index 47282 is out of bounds for dimension 0 with size 44138
```

Also, it’s not 100% clear to me if to use the `LinkPredictionMinibatchSampler`

I need to replace the class `MinibatchSampler`

in the variable `sampler`

and implement a new loss function to replace the rmse. Is it right?