https://github.com/GPflow/GPflow
Revision 17781c21be71eacad81d2c0de32c319ec985c14b authored by Mark van der Wilk on 09 May 2018, 18:21:58 UTC, committed by GitHub on 09 May 2018, 18:21:58 UTC
* Start integrating gpflow-monitor in actions framework. * Initial commit for GPfow monitor integration with actions framework. * Quick fix to TriggeredAction. * Saver works. * PrintTimings added to actions. * simple callback action added. Needs to handle session correctly * ModelTensorBoard action seems to be working. More testing needed * Exclude monitor from testing. * Check if notebook coverage is included. * Moving back to removing coverage of monitor. * changed callback action to have access to the model * yet another edit to callback action in order to get access to the context * adding type annotations and cleanning up code * changed condition in the triggered action * Notebook, small bugfixes & LmlTensorBoard. * Add very simple test for monitor. * import of tqdm if not installed is now gracefully handled. * Added seq_exp_lin. * `force_run` now first test. * Fix `force_run` bug. * Updated test. * Actions test now also tests `CallbackAction`.
1 parent f867d66
Tip revision: 17781c21be71eacad81d2c0de32c319ec985c14b authored by Mark van der Wilk on 09 May 2018, 18:21:58 UTC
Inclusion of `gpflow-monitor` (#705)
Inclusion of `gpflow-monitor` (#705)
Tip revision: 17781c2
setup.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# pylint: skip-file
from setuptools import setup
from setuptools import find_packages
import re
import os
import sys
from pkg_resources import parse_version
# load version form _version.py
exec(open("gpflow/_version.py").read())
# Dependencies of GPflow
requirements = [
'numpy>=1.10.0',
'scipy>=0.18.0',
'pandas>=0.18.1',
'multipledispatch>=0.4.9',
'pytest>=3.5.0',
'h5py>=2.7.0'
'multipledispatch>=0.4.9'
]
min_tf_version = '1.5.0'
tf_cpu = 'tensorflow>={}'.format(min_tf_version)
tf_gpu = 'tensorflow-gpu>={}'.format(min_tf_version)
# Only detect TF if not installed or outdated. If not, do not do not list as
# requirement to avoid installing over e.g. tensorflow-gpu
# To avoid this, rely on importing rather than the package name (like pip).
try:
# If tf not installed, import raises ImportError
import tensorflow as tf
if parse_version(tf.VERSION) < parse_version(min_tf_version):
# TF pre-installed, but below the minimum required version
raise DeprecationWarning("TensorFlow version below minimum requirement")
except (ImportError, DeprecationWarning) as e:
# Add TensorFlow to dependencies to trigger installation/update
requirements.append(tf_cpu)
packages = find_packages('.')
package_data={'gpflow': ['gpflow/gpflowrc']}
setup(name='gpflow',
version=__version__,
author="James Hensman, Alex Matthews",
author_email="james.hensman@gmail.com",
description=("Gaussian process methods in tensorflow"),
license="Apache License 2.0",
keywords="machine-learning gaussian-processes kernels tensorflow",
url="http://github.com/GPflow/GPflow",
packages=packages,
install_requires=requirements,
package_data=package_data,
include_package_data=True,
test_suite='tests',
extras_require={'Tensorflow with GPU': [tf_gpu]},
classifiers=[
'License :: OSI Approved :: Apache Software License',
'Natural Language :: English',
'Operating System :: MacOS :: MacOS X',
'Operating System :: Microsoft :: Windows',
'Operating System :: POSIX :: Linux',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Topic :: Scientific/Engineering :: Artificial Intelligence'
])
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