| Name | Modified | Size | Downloads / Week |
|---|---|---|---|
| Parent folder | |||
| Opacus v1.6.0 source code.tar.gz | 2026-05-05 | 1.2 MB | |
| Opacus v1.6.0 source code.zip | 2026-05-05 | 1.4 MB | |
| README.md | 2026-05-05 | 1.4 kB | |
| Totals: 3 Items | 2.7 MB | 0 | |
New features
Better interoperability with modern training stacks
- Add non-wrapping mode for better compatibility with Transformers, Accelerate, and libraries that expect the original module hierarchy (
wrap_model=False) (#794) - Add arithmetic operations support to
DPTensorFastGradientClipping, making it easier to integrate Opacus with custom loss compositions and external trainers (#805)
Distributed and large-model training
- Add support for Fully Sharded Data Parallel (FSDP) training, including a tutorial and a new example (#761,#772,#781,#782)
- Add support for mixed and low precision training (#764)
- Add 1D tensor parallelism support for fast gradient clipping, together with toy and Llama examples; this support is currently beta (#776)
Others
- Add ability to register custom noise accountants (#784)
Bug fixes
- Fix epsilon/noise accounting when using adaptive gradient clipping (#807, [#779])
- Fix fast gradient clipping when using
ignore_indexmasking, so ignored tokens do not affect the reduced loss incorrectly (#808) - Replace empty-batch handling inside
DPDataLoaderwith a structure-aware approach, fixing failures for custom batch structures under Poisson sampling (#806) - Treat
IAccountant.mechanismcorrectly duringstate_dicthandling (#778)
Compatibility
- Require
torch>=2.6.0(#770)