Question About Graph Sparsity/Edges

[coopersvajda]

Hey There,
So I'm currently trying to use the equiformer for a protein/ligand prediction task. I've inherited the dataset from an earlier model I've made and it is in the PyG batching format of one large graph made of sub graphs. I've got the adjacency matrices made of shape [1, N, N] as shown in example and am passing to the model. But the loss is directly related to the size of the batch being fed, which means something is up with graphs talking to one another. I'm using the settings of 'num_neighbors=0' and 'max_sparse_neighbors=32'. My understanding from the documentation is that this means I'll only be selecting 32 neighbors for each node, and those neighbors must come from the adjacency matrix. Is that understanding correct? Or if there are some small graphs with >32 nodes am I going to start cross contaminating? Additionally, if I wanted to convert the format of dataset to the suggested batching system (with masks), would it I simply set num_neighbors to 32 and call it a day?

[lucidrains]

@coopersvajda yes, your understanding is correct and no it should never cross contaminate