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Lightning v2.6.0 source code.tar.gz (16.4 MB)
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| Name | Modified | Size | Downloads / Week |
|---|---|---|---|
| Parent folder | |||
| pytorch_lightning-2.6.0-py3-none-any.whl | 2025-11-28 | 849.5 kB | |
| pytorch_lightning-2.6.0.tar.gz | 2025-11-28 | 658.9 kB | |
| lightning-2.6.0.tar.gz | 2025-11-28 | 656.5 kB | |
| lightning-2.6.0-py3-none-any.whl | 2025-11-28 | 846.0 kB | |
| lightning_fabric-2.6.0.tar.gz | 2025-11-28 | 201.0 kB | |
| lightning_fabric-2.6.0-py3-none-any.whl | 2025-11-28 | 255.5 kB | |
| Lightning v2.6.0 source code.tar.gz | 2025-11-28 | 16.4 MB | |
| Lightning v2.6.0 source code.zip | 2025-11-28 | 17.2 MB | |
| README.md | 2025-11-28 | 5.1 kB | |
| Totals: 9 Items | 37.1 MB | 0 | |
Changes in 2.6.0
PyTorch Lightning
Added
- Added `WeightAveraging` callback that wraps the PyTorch `AveragedModel` class ([#20545](https://github.com/Lightning-AI/pytorch-lightning/pull/20545)) - Added Torch-Tensorrt integration with `LightningModule` ([#20808](https://github.com/Lightning-AI/pytorch-lightning/pull/20808)) - Added time-based validation support though `val_check_interval` ([#21071](https://github.com/Lightning-AI/pytorch-lightning/pull/21071)) - Added attributes to access stopping reason in `EarlyStopping` callback ([#21188](https://github.com/Lightning-AI/pytorch-lightning/pull/21188)) - Added support for variable batch size in `ThroughputMonitor` ([#20236](https://github.com/Lightning-AI/pytorch-lightning/pull/20236)) - Added `EMAWeightAveraging` callback that wraps Lightning's `WeightAveraging` class ([#21260](https://github.com/Lightning-AI/pytorch-lightning/pull/21260))Changed
- Expose `weights_only` argument for `Trainer.{fit,validate,test,predict}` and let `torch` handle default value ([#21072](https://github.com/Lightning-AI/pytorch-lightning/pull/21072)) - Default to `RichProgressBar` and `RichModelSummary` if the rich package is available. Fallback to TQDMProgressBar and ModelSummary otherwise ([#20896](https://github.com/Lightning-AI/pytorch-lightning/pull/20896)) - Add MPS accelerator support for mixed precision ([#21209](https://github.com/Lightning-AI/pytorch-lightning/pull/21209))Fixed
- Fixed edgecase when `max_trials` is reached in `Tuner.scale_batch_size` ([#21187](https://github.com/Lightning-AI/pytorch-lightning/pull/21187)) - Fixed case where `LightningCLI` could not be initialized with `trainer_default` containing callbacks ([#21192](https://github.com/Lightning-AI/pytorch-lightning/pull/21192)) - Fixed missing reset when `ModelPruning` is applied with lottery ticket hypothesis ([#21191](https://github.com/Lightning-AI/pytorch-lightning/pull/21191)) - Fixed preventing recursive symlink creation iwhen `save_last='link'` and `save_top_k=-1` ([#21186](https://github.com/Lightning-AI/pytorch-lightning/pull/21186)) - Fixed `last.ckpt` being created and not linked to another checkpoint ([#21244](https://github.com/Lightning-AI/pytorch-lightning/pull/21244)) - Fixed bug that prevented `BackboneFinetuning` from being used together with `LearningRateFinder` ([#21224](https://github.com/Lightning-AI/pytorch-lightning/pull/21224)) - Fixed `ModelPruning` sparsity logging bug that caused incorrect sparsity percentages ([#21223](https://github.com/Lightning-AI/pytorch-lightning/pull/21223)) - Fixed `LightningCLI` loading of hyperparameters from `ckpt_path` failing for subclass model mode ([#21246](https://github.com/Lightning-AI/pytorch-lightning/pull/21246)) - Fixed check the init args only when the given frames are in `__init__` method ([#21227](https://github.com/Lightning-AI/pytorch-lightning/pull/21227)) - Fixed how `ThroughputMonitor` calculated training time ([#21291](https://github.com/Lightning-AI/pytorch-lightning/pull/21291)) - Fixed synchronization of gradients in manual optimization with `DDPStrategy(static_graph=True)` ([#21251](https://github.com/Lightning-AI/pytorch-lightning/pull/21251)) - Fixed FSDP mixed precision semantics and added user warning ([#21361](https://github.com/Lightning-AI/pytorch-lightning/pull/21361))Lightning Fabric
Changed
- Expose `weights_only` argument for `Trainer.{fit,validate,test,predict}` and let `torch` handle default value ([#21072](https://github.com/Lightning-AI/pytorch-lightning/pull/21072)) - Set `_DeviceDtypeModuleMixin._device` from torch's default device function ([#21164](https://github.com/Lightning-AI/pytorch-lightning/pull/21164)) - Added kwargs-filtering for `Fabric.call` to support different callback method signatures ([#21258](https://github.com/Lightning-AI/pytorch-lightning/pull/21258))Fixed
- Fixed issue in detecting MPIEnvironment with partial mpi4py installation ([#21353](https://github.com/Lightning-AI/pytorch-lightning/pull/21353)) - Learning rate scheduler is stepped at the end of epoch when `on_train_batch_start` returns -1 ([#21296](https://github.com/Lightning-AI/pytorch-lightning/issues/21296)). - Fixed FSDP mixed precision semantics and added user warning ([#21361](https://github.com/Lightning-AI/pytorch-lightning/pull/21361))Full commit list: 2.5.4 -> 2.5.5
Contributors
We thank all folks who submitted issues, features, fixes and doc changes. It's the only way we can collectively make Lightning :zap: better for everyone, nice job!
In particular, we would like to thank the authors of the pull-requests above
