Lightning v2.4

Lightning AI ⚡ is excited to announce the release of Lightning 2.4. This is mainly a compatibility upgrade for PyTorch 2.4 and Python 3.12, with a sprinkle of a few features and bug fixes.

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Changes

PyTorch Lightning

Added

• Made saving non-distributed checkpoints fully atomic (#20011)
• Added dump_stats flag to AdvancedProfiler (#19703)
• Added a flag verbose to the seed_everything() function (#20108)
• Added support for PyTorch 2.4 (#20010)
• Added support for Python 3.12 (20078)
• The TQDMProgressBar now provides an option to retain prior training epoch bars (#19578)
• Added the count of modules in train and eval mode to the printed ModelSummary table (#20159)

Changed

• Triggering KeyboardInterrupt (Ctrl+C) during .fit(), .evaluate(), .test() or .predict() now terminates all processes launched by the Trainer and exits the program (#19976)
• Changed the implementation of how seeds are chosen for dataloader workers when using seed_everything(..., workers=True) (#20055)
• NumPy is no longer a required dependency (#20090)

Removed

• Removed support for PyTorch 2.1 (#20009)
• Removed support for Python 3.8 (#20071)

Fixed

• Avoid LightningCLI saving hyperparameters with class_path and init_args since this would be a breaking change (#20068)
• Fixed an issue that would cause too many printouts of the seed info when using seed_everything() (#20108)
• Fixed _LoggerConnector's _ResultMetric to move all registered keys to the device of the logged value if needed (#19814)
• Fixed _optimizer_to_device logic for special 'step' key in optimizer state causing performance regression (#20019)
• Fixed parameter counts in ModelSummary when model has distributed parameters (DTensor) (#20163)

Lightning Fabric

Added

• Made saving non-distributed checkpoints fully atomic (#20011)
• Added a flag verbose to the seed_everything() function (#20108)
• Added support for PyTorch 2.4 (#20028)
• Added support for Python 3.12 (20078)

Changed

• Changed the implementation of how seeds are chosen for dataloader workers when using seed_everything(..., workers=True) (#20055)
• NumPy is no longer a required dependency (#20090)

Removed

• Removed support for PyTorch 2.1 (#20009)
• Removed support for Python 3.8 (#20071)

Fixed

• Fixed an attribute error when loading a checkpoint into a quantized model using the _lazy_load() function (#20121)
• Fixed _optimizer_to_device logic for special 'step' key in optimizer state causing performance regression (#20019)

Full commit list: 2.3.0 -> 2.4.0

Contributors

We thank all our contributors who submitted pull requests for features, bug fixes and documentation updates.

New Contributors

• @SamuelLarkin made their first contribution in #19969
• @liambsmith made their first contribution in #19986
• @EtayLivne made their first contribution in #19915
• @elmuz made their first contribution in #19998
• @swyo made their first contribution in #19982
• @corwinjoy made their first contribution in #20011
• @omahs made their first contribution in #19979
• @linbo0518 made their first contribution in #20040
• @01AbhiSingh made their first contribution in #20055
• @K-H-Ismail made their first contribution in #20099
• @adosar made their first contribution in #20146
• @jojje made their first contribution in #19578

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