PyTorch Lightning: Difference between revisions

Revision as of 15:32, 8 September 2021

Revision as of 18:44, 12 August 2022

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| platform = [[Cross-platform]]

| license = [[Apache 2.0]]

| website = https://www.pytorchlightninglightning.ai/

}}

PyTorch Lightning is an open-source [[Python (programming language)|Python]] library that provides a high-level interface for [[PyTorch]], a popular [[deep learning]] framework.<ref>{{Cite web|url=https://github.com/PyTorchLightning/pytorch-lightning|title=GitHub - PyTorch Lightning|last=|first=|date=2019-12-01|website=|url-status=live|archive-url=|archive-date=|access-date=}}</ref> It is a lightweight and high-performance framework that organizes PyTorch code to decouple the research from the engineering, making deep learning experiments easier to read and reproduce. It is designed to create scalable deep learning models that can easily run on distributed hardware while keeping the models hardware agnostic.

In 2019, Lightning was adopted by the [[Conference on Neural Information Processing Systems|NeurIPS]] Reproducibility Challenge as a standard for submitting PyTorch code to the conference.<ref>{{Cite web|url=https://reproducibility-challenge.github.io/neurips2019/resources/|title=Reproducibility Challenge @NeurIPS 2019|last=|first=|date=2019-12-01|website=NeurIPS|url-status=live|archive-url=|archive-date=|access-date=2019-12-01}}</ref>

In 2022, the PyTorch Lightning library officially became a part of the Lightning framework, an open-source framework managed by the original creators of PyTorch Lightning.

== References ==