Metadata-Version: 1.2
Name: geoopt
Version: 0.2.0
Summary: Unofficial implementation for “Riemannian Adaptive Optimization Methods” ICLR2019 and more
Home-page: https://github.com/geoopt/geoopt
Author: Geoopt Developers
Maintainer-email: maxim.v.kochurov@gmail.com
License: Apache License, Version 2.0
Description: geoopt
        ======
        
        |Python Package Index| |Read The Docs| |Build Status| |Coverage Status| |Codestyle Black| |Gitter|
        
        Manifold aware ``pytorch.optim``.
        
        Unofficial implementation for `“Riemannian Adaptive Optimization
        Methods”`_ ICLR2019 and more.
        
        Installation
        ------------
        Make sure you have pytorch>=1.4.0 installed
        
        There are two ways to install geoopt:
        
        1. GitHub (preferred so far) due to active development
        
        .. code-block:: bash
        
            pip install git+https://github.com/geoopt/geoopt.git
        
        
        2. pypi (this might be significantly behind master branch)
        
        .. code-block:: bash
        
            pip install geoopt
        
        The preferred way to install geoopt will change once stable project stage is achieved.
        Now, pypi is behind master as we actively develop and implement new features.
        
        
        PyTorch Support
        ~~~~~~~~~~~~~~~
        Geoopt officially supports 2 latest stable versions of pytorch upstream or the latest major release.
        We also test against the nightly build, but do not be 100% sure about compatibility.
        As for older pytorch versions, you may use it on your own risk.
        
        What is done so far
        -------------------
        
        Work is in progress but you can already use this. Note that API might
        change in future releases.
        
        Tensors
        ~~~~~~~
        
        -  ``geoopt.ManifoldTensor`` – just as torch.Tensor with additional
           ``manifold`` keyword argument.
        -  ``geoopt.ManifoldParameter`` – same as above, recognized in
           ``torch.nn.Module.parameters`` as correctly subclassed.
        
        All above containers have special methods to work with them as with
        points on a certain manifold
        
        -  ``.proj_()`` – inplace projection on the manifold.
        -  ``.proju(u)`` – project vector ``u`` on the tangent space. You need
           to project all vectors for all methods below.
        -  ``.egrad2rgrad(u)`` – project gradient ``u`` on Riemannian manifold
        -  ``.inner(u, v=None)`` – inner product at this point for two
           **tangent** vectors at this point. The passed vectors are not
           projected, they are assumed to be already projected.
        -  ``.retr(u)`` – retraction map following vector ``u``
        -  ``.expmap(u)`` – exponential map following vector ``u`` (if expmap is not available in closed form, best approximation is used)
        -  ``.transp(v, u)`` – transport vector ``v``  with direction ``u``
        -  ``.retr_transp(v, u)`` – transport ``self``, vector ``v``
           (and possibly more vectors) with direction ``u``
           (returns are plain tensors)
        
        Manifolds
        ~~~~~~~~~
        
        -  ``geoopt.Euclidean`` – unconstrained manifold in ``R`` with
           Euclidean metric
        -  ``geoopt.Stiefel`` – Stiefel manifold on matrices
           ``A in R^{n x p} : A^t A=I``, ``n >= p``
        -  ``geoopt.Sphere`` - Sphere manifold ``||x||=1``
        -  ``geoopt.BirkhoffPolytope`` - manifold of Doubly Stochastic matrices
        -  ``geoopt.Stereographic`` - Constant curvature stereographic projection model
        -  ``geoopt.SphereProjection`` - Sphere stereographic projection model
        -  ``geoopt.PoincareBall`` - Poincare ball model (`wiki for Poincare ball <https://en.wikipedia.org/wiki/Poincar%C3%A9_disk_model>`_)
        -  ``geoopt.Lorentz`` - Hyperboloid model (`wiki for Hyperboloid <https://en.wikipedia.org/wiki/Hyperboloid_model>`_)
        -  ``geoopt.ProductManifold`` - Product manifold constructor
        -  ``geoopt.Scaled`` - Scaled version of the manifold. Similar to `Learning Mixed-Curvature Representations in Product Spaces <https://openreview.net/forum?id=HJxeWnCcF7>`_ if combined with ``ProductManifold``
        
        
        All manifolds implement methods necessary to manipulate tensors on manifolds and
        tangent vectors to be used in general purpose. See more in `documentation`_.
        
        Optimizers
        ~~~~~~~~~~
        
        -  ``geoopt.optim.RiemannianSGD`` – a subclass of ``torch.optim.SGD``
           with the same API
        -  ``geoopt.optim.RiemannianAdam`` – a subclass of ``torch.optim.Adam``
        
        Samplers
        ~~~~~~~~
        
        -  ``geoopt.samplers.RSGLD`` – Riemannian Stochastic Gradient Langevin
           Dynamics
        -  ``geoopt.samplers.RHMC`` – Riemannian Hamiltonian Monte-Carlo
        -  ``geoopt.samplers.SGRHMC`` – Stochastic Gradient Riemannian
           Hamiltonian Monte-Carlo
        
        
        Citing Geoopt
        ~~~~~~~~~~~~~
        If you find this project useful in your research, please kindly add this bibtex entry in references and cite.
        
        .. code:: bibtex
        
            @misc{geoopt2020kochurov,
                title={Geoopt: Riemannian Optimization in PyTorch},
                author={Max Kochurov and Rasul Karimov and Serge Kozlukov},
                year={2020},
                eprint={2005.02819},
                archivePrefix={arXiv},
                primaryClass={cs.CG}
            }
        
        
        .. _“Riemannian Adaptive Optimization Methods”: https://openreview.net/forum?id=r1eiqi09K7
        .. _documentation: https://geoopt.readthedocs.io/en/latest/manifolds.html
        
        
        .. |Python Package Index| image:: https://img.shields.io/pypi/v/geoopt.svg
           :target: https://pypi.python.org/pypi/geoopt
        .. |Read The Docs| image:: https://readthedocs.org/projects/geoopt/badge/?version=latest
           :target: https://geoopt.readthedocs.io/en/latest/?badge=latest
           :alt: Documentation Status
        .. |Build Status| image:: https://travis-ci.com/geoopt/geoopt.svg?branch=master
           :target: https://travis-ci.com/geoopt/geoopt
        .. |Coverage Status| image:: https://coveralls.io/repos/github/geoopt/geoopt/badge.svg?branch=master
           :target: https://coveralls.io/github/geoopt/geoopt?branch=master
        .. |Codestyle Black| image:: https://img.shields.io/badge/code%20style-black-000000.svg
           :target: https://github.com/ambv/black
        .. |Gitter| image:: https://badges.gitter.im/geoopt/community.png
           :target: https://gitter.im/geoopt/community
        
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6.0
