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Native PyTorch FSDP is a powerful alternative to regular DDP.
Pitch
Add the strategy to Lite. Build it using the existing implementation in Trainer.
If you enjoy Lightning, check out our other projects! ⚡
Metrics: Machine learning metrics for distributed, scalable PyTorch applications.
Lite: enables pure PyTorch users to scale their existing code on any kind of device while retaining full control over their own loops and optimization logic.
Flash: The fastest way to get a Lightning baseline! A collection of tasks for fast prototyping, baselining, fine-tuning, and solving problems with deep learning.
Bolts: Pretrained SOTA Deep Learning models, callbacks, and more for research and production with PyTorch Lightning and PyTorch.
Lightning Transformers: Flexible interface for high-performance research using SOTA Transformers leveraging PyTorch Lightning, Transformers, and Hydra.
The text was updated successfully, but these errors were encountered:
🚀 Feature
Motivation
Native PyTorch FSDP is a powerful alternative to regular DDP.
Pitch
Add the strategy to Lite. Build it using the existing implementation in Trainer.
If you enjoy Lightning, check out our other projects! ⚡
Metrics: Machine learning metrics for distributed, scalable PyTorch applications.
Lite: enables pure PyTorch users to scale their existing code on any kind of device while retaining full control over their own loops and optimization logic.
Flash: The fastest way to get a Lightning baseline! A collection of tasks for fast prototyping, baselining, fine-tuning, and solving problems with deep learning.
Bolts: Pretrained SOTA Deep Learning models, callbacks, and more for research and production with PyTorch Lightning and PyTorch.
Lightning Transformers: Flexible interface for high-performance research using SOTA Transformers leveraging PyTorch Lightning, Transformers, and Hydra.
The text was updated successfully, but these errors were encountered: