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I may add options for that in the future, but I don't think it has huge importance or impact, because the pre-training is unsupervised and mainly used to initialize the network weights in a way that allows fine-tuning to quickly converge, the actual error during pre-training is not so important.
Function preTrainDArch return last model.
May be is better to return best model + add stopAfterEpochs?
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