.. pytorch-optimizer documentation master file, created by sphinx-quickstart on Thu Feb 13 21:14:16 2020. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Welcome to pytorch-optimizer's documentation! ============================================= **torch-optimizer** -- collection of optimizers for PyTorch_. Simple example -------------- .. code:: python import torch_optimizer as optim # model = ... optimizer = optim.DiffGrad(model.parameters(), lr=0.001) optimizer.step() Installation ------------ Installation process is simple, just:: $ pip install torch_optimizer Supported Optimizers ==================== +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`AccSGD` | https://arxiv.org/abs/1803.05591 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`AdaBound` | https://arxiv.org/abs/1902.09843 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`AdaMod` | https://arxiv.org/abs/1910.12249 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`Adafactor`| https://arxiv.org/abs/1804.04235 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`AdamP` | https://arxiv.org/abs/1804.00325 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`AggMo` | https://arxiv.org/abs/2006.08217 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`DiffGrad` | https://arxiv.org/abs/1909.11015 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`Lamb` | https://arxiv.org/abs/1904.00962 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`NovoGrad` | https://arxiv.org/abs/1905.11286 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`PID` | https://www4.comp.polyu.edu.hk/~cslzhang/paper/CVPR18_PID.pdf | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`QHAdam` | https://arxiv.org/abs/1810.06801 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`QHM` | https://arxiv.org/abs/1810.06801 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`RAdam` | https://arxiv.org/abs/1908.03265 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`Ranger` | https://arxiv.org/abs/1908.00700v2 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`RangerQH` | https://arxiv.org/abs/1908.00700v2 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`RangerVA` | https://arxiv.org/abs/1908.00700v2 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`SGDP` | https://arxiv.org/abs/2006.08217 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`SGDW` | https://arxiv.org/abs/1608.03983 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`Shampoo` | https://arxiv.org/abs/1802.09568 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`SWATS` | https://arxiv.org/abs/1712.07628 | +-----------------+-------------------------------------------------------------------------------+ | | | | :ref:`Yogi` | https://papers.nips.cc/paper/8186-adaptive-methods-for-nonconvex-optimization | +-----------------+-------------------------------------------------------------------------------+ .. toctree:: :maxdepth: 2 :caption: Contents: Contents -------- .. toctree:: :maxdepth: 2 api examples contributing Indices and tables ================== * :ref:`genindex` * :ref:`modindex` * :ref:`search` .. _Python: https://www.python.org .. _PyTorch: https://github.com/pytorch/pytorch