Commit 332d0158 authored by Guillaume HEUSCH's avatar Guillaume HEUSCH
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include README.rst buildout.cfg COPYING version.txt requirements.txt
recursive-include doc *.py *.rst
.. vim: set fileencoding=utf-8 :
.. Wed 3 May 09:06:37 CEST 2017
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Generative Adversarial Networks using PyTorch
This package is part of the signal-processing and machine learning toolbox
Bob_. It provides tools to build, train and evaluate GANs for face processing.
Follow our `installation`_ instructions. Then, using the Python interpreter
provided by the distribution, build this package with::
$ buildout
For questions or reporting issues to this software package, contact our
development `mailing list`_.
.. Place your references here:
.. _bob:
.. _installation:
.. _mailing list:
# see
from pkgutil import extend_path
__path__ = extend_path(__path__, __name__)
# see
from pkgutil import extend_path
__path__ = extend_path(__path__, __name__)
# see
from pkgutil import extend_path
__path__ = extend_path(__path__, __name__)
# gets sphinx autodoc done right - don't remove it
def __appropriate__(*args):
"""Says object was actually declared here, an not on the import module.
*args: An iterable of objects to modify
Resolves `Sphinx referencing issues
for obj in args: obj.__module__ = __name__
__all__ = [_ for _ in dir() if not _.startswith('_')]
# gets sphinx autodoc done right - don't remove it
__all__ = [_ for _ in dir() if not _.startswith('_')]
; vim: set fileencoding=utf-8 :
parts = scripts
eggs = bob.learn.pytorch
extensions = bob.buildout
auto-checkout = *
develop = .
; options for bob.buildout
debug = false
verbose = true
newest = false
bob.db.fargo = fs bob.db.fargo full-path=/remote/idiap.svm/
bob.db.casia_webface = fs bob.db.casia_webface full-path=/remote/idiap.svm/
bob.db.mnist = fs bob.db.mnist full-path=/remote/idiap.svm/
recipe = bob.buildout:scripts
dependent-scripts = true
#!/usr/bin/env python
# vim: set fileencoding=utf-8 :
# Andre Anjos <>
# Mon 16 Apr 08:18:08 2012 CEST
# Copyright (C) Idiap Research Institute, Martigny, Switzerland
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, version 3 of the License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <>.
# This file contains the python (distutils/setuptools) instructions so your
# package can be installed on **any** host system. It defines some basic
# information like the package name for instance, or its homepage.
# It also defines which other packages this python package depends on and that
# are required for this package's operation. The python subsystem will make
# sure all dependent packages are installed or will install them for you upon
# the installation of this package.
# The 'buildout' system we use here will go further and wrap this package in
# such a way to create an isolated python working environment. Buildout will
# make sure that dependencies which are not yet installed do get installed, but
# **without** requiring administrative privileges on the host system. This
# allows you to test your package with new python dependencies w/o requiring
# administrative interventions.
from setuptools import setup
# The only thing we do in this file is to call the setup() function with all
# parameters that define our package.
# This is the basic information about your project. Modify all this
# information before releasing code publicly.
name = 'bob.learn.pytorch',
version = open("version.txt").read().rstrip(),
description = 'Examples',
url = '',
license = 'BSD',
author = 'Guillaume Heusch',
author_email = '',
keywords = 'pytorch',
# 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 = [
entry_points = {
# scripts should be declared using this entry:
'console_scripts': [
# 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 (
classifiers = [
'Framework :: PyTorch',
'Development Status :: 3 - Alpha',
'Intended Audience :: Developers',
'License :: OSI Approved :: BSD License',
'Natural Language :: English',
'Programming Language :: Python',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
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