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[ptrblck]

@snip3r77

I’m just wondering if SubsetRandomSampler include stratify whereby % of classes are consistent in train and valid.

No, SubsetRandomSampler will just randomly shuffle the passed indices.

@snip3r77

Last but not least, is this the usual way to split 80/20 between train and test(codewise) or is there a train-test-split( apologies as I’m looking from the sklearn angle)?

This would be a valid way, but I’m often using sklearn methods, in case I need to create stratified splits etc. If you are OK with adding sklearn as a dependency to your script, I would just use these methods.