https://github.com/GPflow/GPflow
Revision ad6e03114fa6903585c31da1528a47f4dcb2049d authored by Vincent Dutordoir on 15 September 2020, 15:37:25 UTC, committed by GitHub on 15 September 2020, 15:37:25 UTC
* HeteroskedasticLikelihood base class draft * fixup * cleanup * cleanup heteroskedastic * multioutput likelihood WIP * Notebook exemplifying HeteroskedasticTFPDistribution usage (#1462) * fixes * typo fix; reshaping fix * notebook showing how to use HeteroskedasticTFPDistribution likelihood * converting to .pct.py format * removed .ipynb * better descriptions * black auto-formatting Co-authored-by: Gustavo Carvalho <gustavo.carvalho@delfosim.com> * note and bugfix * add comment * Adding heteroskedastic tests (#1508) These tests ensure that heteroskedastic likelihood with a constant variance, will give the same results as a Gaussian likelihood with the same variance. * testing * added QuadratureLikelihood to base, refactored ScalarLikelihood to use it * fix * using the first dimension to hold the quadrature summation * adapting ndiagquad wrapper * merged with gustavocmv/quadrature-change-shape * removed unecessary tf.init_scope * removed print and tf.print * removed print and tf.print * Type annotations Co-authored-by: Vincent Dutordoir <dutordoirv@gmail.com> * Work * Fix test * Remove multioutput from PR * Fix notebook * Add student t test * More tests * Copyright * Removed NDiagGHQuadratureLikelihood class in favor of non-abstract QuadratureLikelihood * _set_latent_and_observation_dimension_eagerly * n_gh ---> num_gauss_hermite_points * removed NDiagGHQuadratureLikelihood from test * black * bugfix * removing NDiagGHQuadratureLikelihood from test * fixed bad commenting * black * refactoring scalar likelihood * adding dtype casts to quadrature * black * small merging fixes * DONE: swap n_gh for num_gauss_hermite_points * black Co-authored-by: ST John <st@prowler.io> Co-authored-by: gustavocmv <47801305+gustavocmv@users.noreply.github.com> Co-authored-by: Gustavo Carvalho <gustavo.carvalho@delfosim.com> Co-authored-by: st-- <st--@users.noreply.github.com> Co-authored-by: joshuacoales-pio <47976939+joshuacoales-pio@users.noreply.github.com>
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Tip revision: ad6e03114fa6903585c31da1528a47f4dcb2049d authored by Vincent Dutordoir on 15 September 2020, 15:37:25 UTC
Multi Latent Likelihoods using new quadrature Likelihoods (#1559)
Multi Latent Likelihoods using new quadrature Likelihoods (#1559)
Tip revision: ad6e031
setup.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# pylint: skip-file
import os
import sys
from setuptools import find_packages, setup
##### Dependencies of GPflow
# We do not want to install tensorflow in the readthedocs environment, where we
# use autodoc_mock_imports instead. Hence we use this flag to decide whether or
# not to append tensorflow and tensorflow_probability to the requirements:
if os.environ.get("READTHEDOCS") != "True":
requirements = [
"tensorflow>=2.1.0",
"tensorflow-probability>0.10.0", # tensorflow-probability==0.10.0 doesn't install correctly, https://github.com/tensorflow/probability/issues/991
"setuptools>=41.0.0", # to satisfy dependency constraints
]
else:
requirements = []
requirements.extend(
["numpy", "scipy", "multipledispatch>=0.6", "tabulate", "typing_extensions",]
)
if sys.version_info < (3, 7):
requirements.append("dataclasses") # became part of stdlib in python 3.7
def read_file(filename):
with open(filename, encoding="utf-8") as f:
return f.read().strip()
version = read_file("VERSION")
readme_text = read_file("README.md")
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",
long_description=readme_text,
long_description_content_type="text/markdown",
license="Apache License 2.0",
keywords="machine-learning gaussian-processes kernels tensorflow",
url="https://www.gpflow.org",
project_urls={
"Source on GitHub": "https://github.com/GPflow/GPflow",
"Documentation": "https://gpflow.readthedocs.io",
},
packages=packages,
include_package_data=True,
install_requires=requirements,
extras_require={"ImageToTensorBoard": ["matplotlib"]},
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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