pytorch-lightning

Why we included this project

Most PyTorch projects eventually hit the same wall: the training loop works on one GPU, then you need mixed precision, checkpointing, and multi-node orchestration, and suddenly you are maintaining infrastructure instead of models. PyTorch Lightning wraps your code in a LightningModule and Trainer so that scaling from a single CPU to a cluster of GPUs does not require rewriting the core logic. Researchers and engineers get reproducible experiment structure out of the box, and the companion Fabric library offers a lower-level path for those who want finer control without the full framework. It is a solid pick for anyone building custom models in PyTorch who would rather spend time on architecture than on plumbing.