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ray-project / ray_lightning

Pytorch Lightning Distributed Accelerators using Ray
Apache License 2.0
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Bump pytorch-lightning from 1.6.4 to 1.8.0.post1 #226

Closed dependabot[bot] closed 1 year ago

dependabot[bot] commented 1 year ago

Bumps pytorch-lightning from 1.6.4 to 1.8.0.post1.

Release notes

Sourced from pytorch-lightning's releases.

Minor pkg stability fix

What's Changed

New Contributors

Full Changelog: https://github.com/Lightning-AI/lightning/compare/1.8.0...1.8.0.post1

Lightning 1.8: Colossal-AI Strategy, Commands and Secrets for Apps, FSDP Improvements and More!

The core team is excited to announce the release of Lightning 1.8 :zap:

Lightning v1.8 is the culmination of work from 52 contributors who have worked on features, bug-fixes, and documentation for a total of over 550+ commits since v1.7.

Highlights

Colossal-AI

Colossal-AI focuses on improving efficiency when training large-scale AI models with billions of parameters. With the new Colossal-AI strategy in Lightning 1.8, you can train existing models like GPT-3 with up to half as many GPUs as usually needed. You can also train models up to twice as big with the same number of GPUs, saving you significant cost. Here is how you use it:

# Select the strategy with good defaults
trainer = Trainer(strategy="colossalai")

or tune parameters to your liking


from lightning.pytorch.strategies import ColossalAIStrategy


trainer = Trainer(strategy=ColossalAIStrategy(placement_policy="cpu", ...))

You can find Colossal-AI's benchmarks with Lightning on GPT-2 here.

Under the hood, Colossal-AI implements different parallelism algorithms that are especially interesting for the development of SOTA transformer models:

  • Data Parallelism
  • Pipeline Parallelism
  • 1D, 2D, 2.5D, 3D Tensor Parallelism
  • Sequence Parallelism
  • Zero Redundancy Optimization

... (truncated)

Commits


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dependabot[bot] commented 1 year ago

Superseded by #227.