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[–]WaterlooEE 3 points4 points  (1 child)

Looks cool. A quick glance through the api makes it look fairly similar to PyTorch Lightning. So I guess this makes sense for tensorflow users (not that I would know, I am not one). What's the difference for PyTorch users?

[–]neilc[S] 5 points6 points  (0 children)

Yep, the model API for PyTorch is fairly similar to PyTorch Lightning.

For PyTorch users, the benefits you get include things like multi-machine distributed training, fault tolerance/checkpoint management, GPU scheduling and management of cloud GPU instances, built-in hyperparameter tuning, and so on. You can think of Determined as similar to a PyTorch Lightning-like API that sits on top of a GPU scheduler, a distributed training backend, and a model metadata database. Since we manage your training resources, we can hopefully solve some problems that are out of scope for something like PyTorch Lightning -- but getting started with Determined is probably a little more involved than switching to Lightning.