{ "info": { "author": "Epist\u00edmio", "author_email": "xavier.bouthillier@umontreal.ca", "bugtrack_url": null, "classifiers": [ "Development Status :: 1 - Planning", "Intended Audience :: Developers", "Intended Audience :: Education", "Intended Audience :: Science/Research", "License :: OSI Approved :: BSD License", "Operating System :: POSIX", "Operating System :: Unix", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Artificial Intelligence" ], "description": "*****\nOr\u00edon\n*****\n\n|pypi| |py_versions| |license| |rtfd| |codecov| |travis|\n\n.. |pypi| image:: https://img.shields.io/pypi/v/orion.svg\n :target: https://pypi.python.org/pypi/orion\n :alt: Current PyPi Version\n\n.. |py_versions| image:: https://img.shields.io/pypi/pyversions/orion.svg\n :target: https://pypi.python.org/pypi/orion\n :alt: Supported Python Versions\n\n.. |license| image:: https://img.shields.io/badge/License-BSD%203--Clause-blue.svg\n :target: https://opensource.org/licenses/BSD-3-Clause\n :alt: BSD 3-clause license\n\n.. |rtfd| image:: https://readthedocs.org/projects/orion/badge/?version=latest\n :target: https://orion.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n\n.. |codecov| image:: https://codecov.io/gh/Epistimio/orion/branch/master/graph/badge.svg\n :target: https://codecov.io/gh/Epistimio/orion\n :alt: Codecov Report\n\n.. |travis| image:: https://travis-ci.org/Epistimio/orion.svg?branch=master\n :target: https://travis-ci.org/Epistimio/orion\n :alt: Travis tests\n\nOr\u00edon is an asynchronous framework for black-box function optimization.\n\nIts purpose is to serve as a meta-optimizer for machine learning models\nand training, as well as a flexible experimentation\nplatform for large scale asynchronous optimization procedures.\n\nCore design value is the minimum disruption of a researcher's workflow.\nIt allows fast and efficient tuning, providing minimum simple non-intrusive\n(not even necessary!) helper *client* interface for a user's script.\n\nSo if ``./run.py --mini-batch=50`` looks like what you execute normally,\nnow what you have to do looks like this:\n\n``orion -n experiment_name ./run.py --mini-batch~'randint(32, 256)'``\n\nCheck out `user's guide-101`_ for the simplest of demonstrations!\n\n.. _user's guide-101: https://orion.readthedocs.io/en/latest/user/pytorch.html\n\nFeatures\n========\n*As simple and as complex you want*\n\n- Simple and natural, but also explicit and verbose, search domain definitions\n- Minimal and non-intrusive client interface for reporting\n target function values\n- Database logging (currently powered by MongoDB_)\n- Flexible configuration\n- Explicit experiment termination conditions\n- Algorithms algorithms algorithms:\n Skopt_'s bayesian optimizers are at hand without writing.\n Random search is the default.\n **only** a single line of code.\n- More algorithms:\n Implementing and distributing algorithms is as easy as possible!\n Check `developer's guide-101`_. Expect algorithm plugins to pop out quickly!\n- Came up with an idea?\n Your intuition is still at play:\n Help your optima hunter now by a command line interface.\n- And other many more already there or coming soon!\n\n.. _MongoDB: https://www.mongodb.com/\n.. _Skopt: https://scikit-optimize.github.io/\n.. _developer's guide-101: https://orion.readthedocs.io/en/latest/developer/testing.html\n\nInstallation\n============\n\nInstall Or\u00edon by running:\n\n``pip install orion``\n\nFor more information read the `full installation docs`_.\n\n.. _full installation docs: https://orion.readthedocs.io/en/latest/install/core.html\n\nContribute or Ask\n=================\n\nDo you have a question or issues?\nDo you want to report a bug or suggest a feature? 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