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Are we sure we want to override transform? That prevents us from calling fit then transform separately on our graphs. Usually you wouldn't want to in practice, but I don't see why we should prevent it (since sklearn API allows for it)?
Might be better to check specifically if the new transform inputs are out-of-sample, and then raise NotImplementedError for that. But that is also trickier to implement.
Expected Behavior
We never tested or intended the out of sample transform to work for those multiple graph embeddings as the inputs wouldn't even make sense
Additional Details
BaseEmbedMulti
class and have them raise a not implemented errorThe text was updated successfully, but these errors were encountered: