[aulin]

Not OP but restart and clear output can be quite compute intensive if you're working with big datasets or training ML models. There are many ways to mitigate this like saving weights and only redo the inference but it's not always worth it when you're iterating through models and parameters or doing exploratory data analysis. Most of the time you want to just keep results/outputs of previous run and improve from there

[dahart]

That’s a great point, I sometimes avoid clearing outputs when I’m playing with Pytorch just because retraining takes a while. This has been motivating me to learn how to be fluent with saving weights to disk.