Metadata-Version: 2.4
Name: zij
Version: 0.1.0
Summary: A comprehensive library of deep learning optimizers
Author: Muhammad Junaid Ali Asif Raja
License: Apache-2.0
Project-URL: Homepage, https://github.com/junaidaliop/zij
Project-URL: Repository, https://github.com/junaidaliop/zij
Project-URL: Issues, https://github.com/junaidaliop/zij/issues
Keywords: optimization,deep-learning,optimizer,pytorch,machine-learning,adam,muon
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: THIRD_PARTY_NOTICES.md
Requires-Dist: torch<2.13,>=2.12
Dynamic: license-file

# zij

**A comprehensive library of deep learning optimizers.**

`zij` packages a large, growing collection of PyTorch optimizers — from the
`torch.optim` classics to current research methods (Muon, SOAP, Sophia, Prodigy,
Schedule-Free, GaLore, Lion, AdEMAMix, and many more) — behind one consistent
interface, each vendored from its original source with attribution and covered
by convergence tests.

```bash
pip install zij
```

```python
import zij

opt = zij.AdamW(model.parameters(), lr=3e-4)
opt = zij.Prodigy(model.parameters())              # learning-rate-free
opt = zij.GaLoreAdamW(model.parameters(), lr=1e-2)  # memory-efficient
opt = zij.SAM(model.parameters(), base_optimizer=zij.SGD, lr=0.1)  # sharpness-aware

zij.list_optimizers("adam*")              # discover by name
opt = zij.load_optimizer("soap")(model.parameters(), lr=2e-2)
```

Both `zij.AdamW` and `zij.optim.AdamW` work; the latter mirrors `torch.optim`.

When you use an optimizer, please cite **both** its original paper and `zij` —
the papers are linked in every class docstring.

The full **Canon of 573 optimization methods** (including paper-only methods
and the memory-efficient, fractional-order, and quantum families) lives in the
project repository:

**https://github.com/junaidaliop/zij**

Apache-2.0. Vendored components retain their original licenses; see
`THIRD_PARTY_NOTICES.md` in the repository.
