PyTorch Lightning Tutorial - Lightweight PyTorch Wrapper For ML Researchers

PyTorch Lightning is a lightweight PyTorch wrapper that helps you scale your models and write less boilerplate code. In this Tutorial we learn about this framework and how we can convert our PyTorch code to a Lightning code.

Lightning is nothing more than organized PyTorch code, so once you’ve organized it into a LightningModule, it automates most of the training for you.The beauty of Lightning is that it handles the details of when to validate, when to call .eval(), turning off gradients, detaching graphs, making sure you don’t enable shuffle for val, etc…

In this Tutorial we convert the code from the PyTorch beginner Course #13 to a Lightning code.

Code on GitHub:

Lightning Repo


conda install pytorch-lightning -c conda-forge or pip install pytorch-lightning

FREE VS Code / PyCharm Extensions I Use

🪁 Code faster with Kite, AI-powered autocomplete: Link *

✅ Write cleaner code with Sourcery, instant refactoring suggestions: Link *

* These are affiliate links. By clicking on it you will not have any additional costs, instead you will support me and my project. Thank you! 🙏

Check out my Courses