JetTrain: IDE-Native Machine Learning Experiments
Artem Trofimov Mikhail Kostyukov Sergei Ugdyzhekov Natalia Ponomareva Igor Naumov Maksim Melekhovets
Integrated development environments (IDEs) are prevalent code-writing and
debugging tools. However, they have yet to be widely adopted for launching
machine learning (ML) experiments. This work aims to fill this gap by
introducing JetTrain, an IDE-integrated tool that delegates specific tasks from
an IDE to remote computational resources. A user can write and debug code
locally and then seamlessly run it remotely using on-demand hardware. We argue
that this approach can lower the entry barrier for ML training problems and
increase experiment throughput.