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 1.7.0 #193

Closed dependabot[bot] closed 1 year ago

dependabot[bot] commented 1 year ago

Bumps pytorch-lightning from 1.6.4 to 1.7.0.

Release notes

Sourced from pytorch-lightning's releases.

PyTorch Lightning 1.7: Apple Silicon support, Native FSDP, Collaborative training, and multi-GPU support with Jupyter notebooks

The core team is excited to announce the release of PyTorch Lightning 1.7 :zap:

PyTorch Lightning 1.7 is the culmination of work from 106 contributors who have worked on features, bug-fixes, and documentation for a total of over 492 commits since 1.6.0.

Highlights

Apple Silicon Support

For those using PyTorch 1.12 on M1 or M2 Apple machines, we have created the MPSAccelerator. MPSAccelerator enables accelerated GPU training on Apple’s Metal Performance Shaders (MPS) as a backend process.


NOTE

Support for this accelerator is currently marked as experimental in PyTorch. Because many operators are still missing, you may run into a few rough edges.


# Selects the accelerator
trainer = pl.Trainer(accelerator="mps")

Equivalent to

from pytorch_lightning.accelerators import MPSAccelerator trainer = pl.Trainer(accelerator=MPSAccelerator())

Defaults to "mps" when run on M1 or M2 Apple machines

to avoid code changes when switching computers

trainer = pl.Trainer(accelerator="gpu")

Native Fully Sharded Data Parallel Strategy

PyTorch 1.12 also added native support for Fully Sharded Data Parallel (FSDP). Previously, PyTorch Lightning enabled this by using the fairscale project. You can now choose between both options.


NOTE

Support for this strategy is marked as beta in PyTorch.


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dependabot[bot] commented 1 year ago

Superseded by #197.