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build(deps-dev): bump pytorch-lightning from 2.2.0.post0 to 2.3.1
Bumps pytorch-lightning from 2.2.0.post0 to 2.3.1.
Release notes
Sourced from pytorch-lightning's releases.
Patch release v2.3.1
Includes minor bugfixes and stability improvements.
Full Changelog: https://github.com/Lightning-AI/pytorch-lightning/compare/2.3.0...2.3.1
Lightning v2.3: Tensor Parallelism and 2D Parallelism
Lightning AI is excited to announce the release of Lightning 2.3 :zap:
Did you know? The Lightning philosophy extends beyond a boilerplate-free deep learning framework: We've been hard at work bringing you Lightning Studio. Code together, prototype, train, deploy, host AI web apps. All from your browser, with zero setup.
This release introduces experimental support for Tensor Parallelism and 2D Parallelism, PyTorch 2.3 support, and several bugfixes and stability improvements.
Highlights
Tensor Parallelism (beta)
Tensor parallelism (TP) is a technique that splits up the computation of selected layers across GPUs to save memory and speed up distributed models. To enable TP as well as other forms of parallelism, we introduce a
ModelParallelStrategyfor both Lightning Trainer and Fabric. Under the hood, TP is enabled through new experimental PyTorch APIs like DTensor andtorch.distributed.tensor.parallel.PyTorch Lightning
Enabling TP in a model with PyTorch Lightning requires you to implement the
LightningModule.configure_model()method where you convert selected layers of a model to paralellized layers. This is an advanced feature, because it requires a deep understanding of the model architecture. Open the tutorial Studio to learn the basics of Tensor Parallelism.
import lightning as L from lightning.pytorch.strategies import ModelParallelStrategy from torch.distributed.tensor.parallel import ColwiseParallel, RowwiseParallel from torch.distributed.tensor.parallel import parallelize_module</tr></table>
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Commits
8b69285Patch release 2.3.1 (#20021)a42484cFix failing app tests (#19971)f6fd046Release 2.3.0 (#19954)a97814aUpdate README.mdfa5da26Update README.md (#19968)06ea3a0Fix resetting epoch loop restarting flag in LearningRateFinder (#19819)5fa32d9Ignore parameters causing ValueError when dumping to YAML (#19804)4f96c83Sanitize argument-free object params before logging (#19771)a611de0Removing numpy requirement from all files in examples/pytorch/domain_template...812ffdeFixsave_lasttype annotation for ModelCheckpoint (#19808)- Additional commits viewable in compare view
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