visualize is failing on higher epoch and even the ratings are getting other values apart from the class_labels of [0,1] as epoch are increased

I am trying to solve a binary matrix completion problem using IGMC Algorithm. I have kept only 2 ratings [0,1]. When I feed the data of 0 and 1 labels, create a train test split, and run the code end to end it works fine but provided the epoch I limit it to 20. so when the epoch is kept at 20, the algorithm also works and the visualize also works fine and graphs are generated, but as the epoch is increased to 30 or 40 the training ensemble code runs fine and in the edge attributes there are different labels assigned apart from 0 and 1 such as 2, 3, 4 due to which the visualize option is failing with index error

edge_types = [class_values[edge_types[x]] for x in g.edges()]
IndexError: index 2 is out of bounds for axis 0 with size 2

Please let me know if I am missing something or need to understand some code behavior or if can I apply such a binary matrix completion problem with the IGMC algorithm in the first place.

[sagar-nyamagouda]

Thanks @muhanzhang I was able to find the root cause, this issue was occurring because I had such value labels in the adjacency matrix. This was occurring while constructing the CSR matrix, since the dataset had duplicate records.

[sagar-nyamagouda]

The issue was resolved by removing duplicate records from the dataset