setup.py

#!/usr/bin/env python
# vim: set fileencoding=utf-8 :
# Andre Anjos <andre.anjos@idiap.ch>
# Mon 16 Apr 08:18:08 2012 CEST

from setuptools import setup

from setuptools import setup, dist
dist.Distribution(dict(setup_requires=['bob.extension']))

from bob.extension.utils import load_requirements, find_packages
install_requires = load_requirements()

# The only thing we do in this file is to call the setup() function with all
# parameters that define our package.
setup(

    # This is the basic information about your project. Modify all this
    # information before releasing code publicly.
    name='bob.learn.tensorflow',
    version=open("version.txt").read().rstrip(),
    description='Bob bindings for tensorflow',
    url='',
    license='BSD',
    author='Tiago de Freitas Pereira',
    author_email='tiago.pereira@idiap.ch',
    keywords='tensorflow',

    # If you have a better, long description of your package, place it on the
    # 'doc' directory and then hook it here
    long_description=open('README.rst').read(),

    # This line is required for any distutils based packaging.
    include_package_data=True,

    # This line defines which packages should be installed when you "install"
    # this package. All packages that are mentioned here, but are not installed
    # on the current system will be installed locally and only visible to the
    # scripts of this package. Don't worry - You won't need administrative
    # privileges when using buildout.
    install_requires=install_requires,
    packages=find_packages(),
    zip_safe=False,
    entry_points={

        # main entry for bob tf cli
        'bob.cli': [
            'tf = bob.learn.tensorflow.script.tf:tf',
            'keras = bob.learn.tensorflow.script.keras:keras',
        ],

        # bob tf scripts
        'bob.learn.tensorflow.cli': [
            'cache-dataset = bob.learn.tensorflow.script.cache_dataset:cache_dataset',
            'cgm-dataset = bob.learn.tensorflow.script.cgm:cgm_dataset',
            'compute-statistics = bob.learn.tensorflow.script.compute_statistics:compute_statistics',
            'dataset-to-hdf5 = bob.learn.tensorflow.script.db_to_tfrecords:dataset_to_hdf5',
            'datasets-to-tfrecords = bob.learn.tensorflow.script.db_to_tfrecords:datasets_to_tfrecords',
            'db-to-tfrecords = bob.learn.tensorflow.script.db_to_tfrecords:db_to_tfrecords',
            'describe-tfrecord = bob.learn.tensorflow.script.db_to_tfrecords:describe_tfrecord',
            'distance-matrix = bob.learn.tensorflow.script.cgm:distance_matrix',
            'eval = bob.learn.tensorflow.script.eval:eval',
            'predict = bob.learn.tensorflow.script.predict_bio:predict',
            'predict-bio = bob.learn.tensorflow.script.predict_bio:predict_bio',
            'style-transfer = bob.learn.tensorflow.script.style_transfer:style_transfer',
            'train = bob.learn.tensorflow.script.train:train',
            'train-and-evaluate = bob.learn.tensorflow.script.train_and_evaluate:train_and_evaluate',
            'trim = bob.learn.tensorflow.script.trim:trim',
        ],
        # bob keras scripts
        'bob.learn.tensorflow.keras_cli': [
            'fit = bob.learn.tensorflow.script.fit:fit',
        ],
    },

    # Classifiers are important if you plan to distribute this package through
    # PyPI. You can find the complete list of classifiers that are valid and
    # useful here (http://pypi.python.org/pypi?%3Aaction=list_classifiers).
    classifiers=[
        'Framework :: Bob',
        'Development Status :: 3 - Alpha',
        'Intended Audience :: Developers',
        'License :: OSI Approved :: BSD License',
        'Natural Language :: English',
        'Programming Language :: Python',
        'Topic :: Scientific/Engineering :: Artificial Intelligence',
    ],
)