It really doesn't have to do with most ML architectures. It has to do with experiment design. If some data used in testing is part of the training process there

It really doesn't have to do with most ML architectures. It has to do with experiment design. If some data used in testing is part of the training process there will be over fitting. That's why a final test set is required for unbiased evaluation.