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To reference or cite the objects present in the Software Heritage archive, permalinks based on SoftWare Hash IDentifiers (SWHIDs) must be used.
Select below a type of object currently browsed in order to display its associated SWHID and permalink.

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Citations

This interface enables to generate software citations, provided that the root directory of browsed objects contains a citation.cff or codemeta.json file.
Select below a type of object currently browsed in order to generate citations for them.

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Generate software citation in BibTex format (requires biblatex-software package)
Generating citation ...
#!/usr/bin/env python
# -*- coding: utf-8 -*-

# pylint: skip-file

from setuptools import find_packages, setup

##### Dependencies of GPflow

requirements = [
    "check_shapes>=1.0.0",
    "deprecated",
    "multipledispatch>=0.6",
    "numpy",
    "packaging",
    "scipy",
    "setuptools>=41.0.0",  # to satisfy dependency constraints
    "tabulate",
    "tensorflow-probability>=0.12.0",
    "tensorflow>=2.4.0; platform_system!='Darwin' or platform_machine!='arm64'",
    # NOTE: Support of Apple Silicon MacOS platforms is in an experimental mode
    "tensorflow-macos>=2.4.0; platform_system=='Darwin' and platform_machine=='arm64'",
    # NOTE: once we require tensorflow-probability>=0.12, we can remove our custom deepcopy handling
    "typing_extensions",
]


def read_file(filename: str) -> str:
    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.github.io/GPflow/",
    },
    packages=packages,
    package_data={"": ["*.lark"]},
    include_package_data=True,
    install_requires=requirements,
    extras_require={"ImageToTensorBoard": ["matplotlib"]},
    python_requires=">=3.7",
    classifiers=[
        "Development Status :: 5 - Production/Stable",
        "Environment :: GPU :: NVIDIA CUDA",
        "Intended Audience :: Developers",
        "Intended Audience :: Education",
        "Intended Audience :: Science/Research",
        "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 :: 3.7",
        "Programming Language :: Python :: 3.8",
        "Programming Language :: Python :: 3.9",
        "Programming Language :: Python :: 3.10",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
        "Typing :: Typed",
    ],
)

Software Heritage — Copyright (C) 2015–2025, The Software Heritage developers. License: GNU AGPLv3+.
The source code of Software Heritage itself is available on our development forge.
The source code files archived by Software Heritage are available under their own copyright and licenses.
Terms of use: Archive access, API— Contact— JavaScript license information— Web API

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