https://github.com/GPflow/GPflow
Revision f8ee093244ad3a1666d282ca5bb1c26c8768a175 authored by Vincent Dutordoir on 26 February 2020, 09:52:47 UTC, committed by GitHub on 26 February 2020, 09:52:47 UTC
GPflow makes use of a multipledispatch Dispatcher that internally uses a generator. However, according to TensorFlow [Capabilities and Limitations](https://github.com/tensorflow/tensorflow/blob/560e2575ecad30bedff5b192f33f6d06b19ccaeb/tensorflow/python/autograph/LIMITATIONS.md) generators are not supported by AutoGraph and probably will never be. Thus, compiling code that passed though the dispatcher led to the following warnings: ```bash WARNING:tensorflow:Entity <bound method Dispatcher.dispatch_iter of <dispatched sample_conditional>> appears to be a generator function. It will not be converted by AutoGraph. WARNING: Entity <bound method Dispatcher.dispatch_iter of <dispatched sample_conditional>> appears to be a generator function. It will not be converted by AutoGraph. WARNING:tensorflow:Entity <bound method Dispatcher.dispatch_iter of <dispatched conditional>> appears to be a generator function. It will not be converted by AutoGraph. WARNING: Entity <bound method Dispatcher.dispatch_iter of <dispatched conditional>> appears to be a generator function. It will not be converted by AutoGraph. ``` This PR still uses the same dispatcher, but overwrites the problematic method that uses python generators and replaces it by a simple list. ### NOTE As of this PR we do not need to write `autograph=False` in `tf.function` anymore, and all the code inside dispatching gets compiled the same way as everything else :) !
1 parent 002b217
Tip revision: f8ee093244ad3a1666d282ca5bb1c26c8768a175 authored by Vincent Dutordoir on 26 February 2020, 09:52:47 UTC
Remove the use of generator in dispatcher (#1264)
Remove the use of generator in dispatcher (#1264)
Tip revision: f8ee093
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
is_py37 = sys.version_info.major == 3 and sys.version_info.minor == 7
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>=0.4.9',
'tabulate',
'gast==0.2.2',
]
if not is_py37:
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'
# 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)
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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