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setup.py
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setup.py
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from setuptools import setup, find_packages
import codecs
import os
import re
here = os.path.abspath(os.path.dirname(__file__))
# loading README (TODO convert to rst?)
with codecs.open(os.path.join(here, 'README.md'), encoding='utf-8') as readme_file:
long_description = readme_file.read()
# loading version from setup.py
with codecs.open(os.path.join(here, 'agentnet/__init__.py'), encoding='utf-8') as init_file:
version_match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]", init_file.read(), re.M)
version_string = version_match.group(1)
assert version_string.startswith('0.')
setup(
name="agentnet",
version=version_string,
description="AgentNet - a library for Deep Reinforcement Learning and custom recurrent network design and research",
long_description=long_description,
# Author details
author_email="[email protected]",
url="https://github.com/yandexdataschool/AgentNet",
# Choose your license
license='MIT',
packages=find_packages(),
classifiers=[
# Indicate who your project is intended for
'Development Status :: 3 - Alpha',
'Intended Audience :: Science/Research',
'Intended Audience :: Developers',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
# Pick your license as you wish (should match "license" above)
"License :: OSI Approved :: MIT License",
# Specify the Python versions you support here. In particular, ensure
# that you indicate whether you support Python 2, Python 3 or both.
'Programming Language :: Python :: 2.7 ',
'Programming Language :: Python :: 3.4 ',
'Programming Language :: Python :: 3.5 ',
],
# What does your project relate to?
keywords='machine learning, reinforcement learning, MDP, POMDP, ' + \
'deep learning, Q-network, Markov Decision Process, experiment platform',
# List run-time dependencies here. These will be installed by pip when your project is installed.
install_requires=[
'six',
'lasagne',
'theano >= 0.8.2',
'numpy>=1.9',
#'matplotlib >= 1.4'
],
)