https://github.com/GPflow/GPflow
Revision c8e8f00e7d488784a09fe6d8fd8dc6632b6723bf authored by ilia-kats on 30 March 2020, 11:20:14 UTC, committed by GitHub on 30 March 2020, 11:20:14 UTC
Changes setattr_by_path to delete the attribute before setting it again. When simply replacing a Parameter with tf.Constant, tensorflow did not update its internal list of tracked variables, which prevented deepcopying and pickling of frozen models. Explicitly deleting the tracked variable before assigning a constant value forces tensorflow to update its state. Workaround for https://github.com/tensorflow/tensorflow/issues/37806
1 parent 0b9e1f0
Tip revision: c8e8f00e7d488784a09fe6d8fd8dc6632b6723bf authored by ilia-kats on 30 March 2020, 11:20:14 UTC
enable pickling of frozen models (#1338)
enable pickling of frozen models (#1338)
Tip revision: c8e8f00
setup.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# pylint: skip-file
import os
import sys
from pathlib import Path
from pkg_resources import parse_version
from setuptools import find_packages, setup
on_rtd = os.environ.get("READTHEDOCS", None) == "True" # copied from the docs
# Dependencies of GPflow
requirements = ["numpy>=1.10.0", "scipy>=0.18.0", "multipledispatch>=0.6", "tabulate"]
if sys.version_info < (3, 7):
# became part of stdlib in python 3.7
requirements.append("dataclasses")
if not on_rtd:
requirements.append("tensorflow-probability>=0.9")
min_tf_version = "2.1.0"
tf_cpu = "tensorflow"
tf_gpu = "tensorflow-gpu"
# for latest_version() [see https://github.com/GPflow/GPflow/issues/1348]:
def latest_version(package_name):
import json
from urllib import request
import re
url = f"https://pypi.python.org/pypi/{package_name}/json"
data = json.load(request.urlopen(url))
# filter out rc and beta releases and, more generally, any releases that
# do not contain exclusively numbers and dots.
versions = [parse_version(v) for v in data["releases"].keys() if re.match("^[0-9.]+$", v)]
versions.sort()
return versions[-1] # return latest 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# Only detect TF if not installed or outdated.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):
# Add TensorFlow to dependencies to trigger installation/update
if not on_rtd:
# Do not add TF if we are installing GPflow on readthedocs
requirements.append(tf_cpu)
gast_requirement = (
"gast>=0.2.2,<0.3"
if latest_version("tensorflow") < parse_version("2.2")
else "gast>=0.3.3"
)
requirements.append(gast_requirement)
with open(str(Path(".", "VERSION").absolute())) as version_file:
version = version_file.read().strip()
packages = find_packages(".", exclude=["tests"])
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,
include_package_data=True,
install_requires=requirements,
extras_require={"Tensorflow with GPU": [tf_gpu]},
python_requires=">=3.6",
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 :: 3.6",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
)
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