old_contents: from distutils.core import setup
  from setuptools import setup
  import glob
  
  subpackages = glob.glob("hypergan/*/")
  subpackages += glob.glob("hypergan/*/*/")
  subpackages += glob.glob("hypergan/*/*/*/")
  subpackages = [s.replace("/", ".") for s in subpackages]
  
  setup(
    name = 'hypergan',
    packages = ['hypergan']+subpackages,
    include_package_data=True,
    version = '1.0.0',
    description = 'A customizable generative adversarial network with reproducible configurations.  Build your own content generator.',
    author = 'HyperGAN',
    author_email = 'hypergan@protonmail.com',
    maintainer = "hypergan developers",
    maintainer_email = 'hypergan@protonmail.com',
    license = "MIT",
    url = 'https://github.com/255BITS/hypergan', 
    keywords = ['hypergan', 'neural network', 'procedural content generation', 'generative adversarial network', 'pytorch'], # arbitrary keywords
    classifiers = [
        'Development Status :: 4 - Beta',
        'Topic :: Scientific/Engineering :: Artificial Intelligence', 
        'Topic :: Artistic Software', 
        'Topic :: Internet :: WWW/HTTP :: Dynamic Content',
        'Intended Audience :: Science/Research',
        'Intended Audience :: Developers',
        'Programming Language :: Python :: 3',
        'Programming Language :: Python :: 3.4',
        'Programming Language :: Python :: 3.5',
        'Programming Language :: Python :: 3.6',
        'Operating System :: POSIX',
        'Operating System :: Unix',
        'Operating System :: MacOS',
        ],
    platforms = ["Linux", "Mac OS-X", "Unix", "Windows"],
    scripts = ['bin/hypergan']
  )
  
new_contents: from distutils.core import setup
  from setuptools import setup
  import glob
  
  subpackages = glob.glob("hypergan/*/")
  subpackages += glob.glob("hypergan/*/*/")
  subpackages += glob.glob("hypergan/*/*/*/")
  subpackages = [s.replace("/", ".") for s in subpackages]
  
  setup(
    name = 'hypergan',
    packages = ['hypergan']+subpackages,
    include_package_data=True,
    version = '1.0.0',
    description = 'A customizable generative adversarial network with reproducible configurations.  Build your own content generator.',
    long_description = 'HyperGAN is an AI framework for building Generative Adversarial Networks. There are examples for building classifiers, content generators, sequence generation, and aligning two datasets. Check out the github for more information.',
    author = 'HyperGAN',
    author_email = 'hypergan@protonmail.com',
    maintainer = "hypergan developers",
    maintainer_email = 'hypergan@protonmail.com',
    license = "MIT",
    url = 'https://github.com/255BITS/hypergan', 
    keywords = ['hypergan', 'neural network', 'procedural content generation', 'generative adversarial network', 'pytorch'], # arbitrary keywords
    classifiers = [
        'Development Status :: 4 - Beta',
        'Topic :: Scientific/Engineering :: Artificial Intelligence', 
        'Topic :: Artistic Software', 
        'Topic :: Internet :: WWW/HTTP :: Dynamic Content',
        'Intended Audience :: Science/Research',
        'Intended Audience :: Developers',
        'Programming Language :: Python :: 3',
        'Programming Language :: Python :: 3.4',
        'Programming Language :: Python :: 3.5',
        'Programming Language :: Python :: 3.6',
        'Operating System :: POSIX',
        'Operating System :: Unix',
        'Operating System :: MacOS',
        ],
    platforms = ["Linux", "Mac OS-X", "Unix", "Windows"],
    scripts = ['bin/hypergan']
  )
  
subject: add long_description to pypi