Refactoring your models to lightningis simple, allows you to get rid of a ton of boilerplate, reduce cognitive load, and gives you the ultimate flexibility to iterate on research ideas faster with all the latest deep learning best practices. ...
PyTorch Lightning Best Practices and Tips In this section, we will outline a few debugging, optimization and organization tips. Debugging strategies Use the fast_dev_run option. This will run only one batch of training, validation, and testing to catch any errors before running all epochs: train...
Beginners in deep learning can use PyTorch Lightning to learn best practices. Its integration capabilities and modular design make it a specified tool for efficiency and productivity in deep learning and machine leaning projects.Prerequisites to Learn PyTorch Lightning...
Strong ecosystem: It has a rich library of tools, extensions, and pre-trained models and often inspires other related projects like PyTorch Lightning. Dynamic computation graphs: Unlike TensorFlow’s (PyTorch’s main competitor) initial static graphs, PyTorch’s dynamic computation approach made debugg...
To give a little insight, we were (at least) the third owner of this code - with some parts dating back to 2016. In the deep learning world, 6 years might as well be an entire epoch. We ended up refactoring it to PyTorch Lightning and using thelightning-hydra-template. It worked won...
Lightning has two additional, more ambitious motivations: reproducibility and democratizing best practices which only PyTorch power-users would implement (Distributed training, 16-bit precision, etc…). I’ll discuss these motivations in detail in later sections. ...
Lightning has two additional, more ambitious motivations: reproducibility and democratizing best practices which only PyTorch power-users would implement (Distributed training, 16-bit precision, etc…). I’ll discuss these motivations in detail in later sections. ...
Lightning is being adopted by top researchers and AI labs around the world, and we are working hard to make sure we provide a smooth experience and support for all the latest best practices. Detail changes Added Added SyncBN for DDP (#2801, #2838) Added basic CSVLogger (#2721) Added ...
PyTorch Lightning + Hydra. A very general, feature-rich template for rapid and scalable ML experimentation with best practices. ⚡🔥⚡ - happyfox-dot/lightning-hydra-template
Overall, Lightning guarantees rigorously tested, correct, modern best practices for the automated parts. How flexible is it? As you see, you're just organizing your PyTorch code - there's no abstraction. And for the stuff that the Trainer abstracts out you canoverride any partyou want to do...