Comprehensive guide for PyTorch Lightning - LightningModule, Trainer, distributed training, PyTorch 2.0 torch.compile integration, Lightning Fabric, and production best practices
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PyTorch Lightning for ML Research
Overview
PyTorch Lightning is the industry-standard framework that organizes PyTorch code to decouple research from engineering. It eliminates boilerplate while maintaining full PyTorch flexibility, enabling researchers to focus on model logic rather than training infrastructure.
Key Benefits:
Eliminates 90% of boilerplate code
Automatic distributed training (DDP, FSDP, DeepSpeed)
Hardware agnostic (CPU, GPU, TPU, MPS)
Built-in best practice
[Description truncada. Veja o README completo no GitHub.]
