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setup.py
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setup.py
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# Copyright 2018 The JAX Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import importlib
import os
from setuptools import setup, find_packages
project_name = 'jax'
_current_jaxlib_version = '0.4.28'
# The following should be updated with each new jaxlib release.
_latest_jaxlib_version_on_pypi = '0.4.28'
_default_cuda12_cudnn_version = '91'
_available_cuda12_cudnn_versions = [_default_cuda12_cudnn_version]
_libtpu_version = '0.1.dev20240508'
def load_version_module(pkg_path):
spec = importlib.util.spec_from_file_location(
'version', os.path.join(pkg_path, 'version.py'))
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module
_version_module = load_version_module(project_name)
__version__ = _version_module._get_version_for_build()
_cmdclass = _version_module._get_cmdclass(project_name)
_minimum_jaxlib_version = _version_module._minimum_jaxlib_version
with open('README.md', encoding='utf-8') as f:
_long_description = f.read()
setup(
name=project_name,
version=__version__,
cmdclass=_cmdclass,
description='Differentiate, compile, and transform Numpy code.',
long_description=_long_description,
long_description_content_type='text/markdown',
author='JAX team',
author_email='jax-dev@google.com',
packages=find_packages(exclude=["examples", "jax/src/internal_test_util"]),
package_data={'jax': ['py.typed', "*.pyi", "**/*.pyi"]},
python_requires='>=3.9',
install_requires=[
'ml_dtypes>=0.4.0',
'numpy>=1.22',
"numpy>=1.23.2; python_version>='3.11'",
"numpy>=1.26.0; python_version>='3.12'",
'opt_einsum',
'scipy>=1.9',
"scipy>=1.11.1; python_version>='3.12'",
# Required by xla_bridge.discover_pjrt_plugins for forwards compat with
# Python versions < 3.10. Can be dropped when 3.10 is the minimum
# required Python version.
'importlib_metadata>=4.6;python_version<"3.10"',
],
extras_require={
# Minimum jaxlib version; used in testing.
'minimum-jaxlib': [f'jaxlib=={_minimum_jaxlib_version}'],
# CPU-only jaxlib can be installed via:
# $ pip install jax[cpu]
'cpu': [f'jaxlib=={_current_jaxlib_version}'],
# Used only for CI builds that install JAX from github HEAD.
'ci': [f'jaxlib=={_latest_jaxlib_version_on_pypi}'],
# Cloud TPU VM jaxlib can be installed via:
# $ pip install jax[tpu] -f https://storage.googleapis.com/jax-releases/libtpu_releases.html
'tpu': [
f'jaxlib=={_current_jaxlib_version}',
f'libtpu-nightly=={_libtpu_version}',
'requests', # necessary for jax.distributed.initialize
],
# CUDA installations require adding the JAX CUDA releases URL, e.g.,
# Cuda installation defaulting to a CUDA and Cudnn version defined above.
# $ pip install jax[cuda] -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
'cuda': [f"jaxlib=={_current_jaxlib_version}+cuda12.cudnn{_default_cuda12_cudnn_version}"],
'cuda12_pip': [
f"jaxlib=={_current_jaxlib_version}+cuda12.cudnn{_default_cuda12_cudnn_version}",
"nvidia-cublas-cu12>=12.1.3.1",
"nvidia-cuda-cupti-cu12>=12.1.105",
"nvidia-cuda-nvcc-cu12>=12.1.105",
"nvidia-cuda-runtime-cu12>=12.1.105",
# https://docs.nvidia.com/deeplearning/cudnn/developer/misc.html#cudnn-api-compatibility
"nvidia-cudnn-cu12>=9.0,<10.0",
"nvidia-cufft-cu12>=11.0.2.54",
"nvidia-cusolver-cu12>=11.4.5.107",
"nvidia-cusparse-cu12>=12.1.0.106",
"nvidia-nccl-cu12>=2.18.1",
# nvjitlink is not a direct dependency of JAX, but it is a transitive
# dependency via, for example, cuSOLVER. NVIDIA's cuSOLVER packages
# do not have a version constraint on their dependencies, so the
# package doesn't get upgraded even though not doing that can cause
# problems (https://github.com/google/jax/issues/18027#issuecomment-1756305196)
# Until NVIDIA add version constraints, add a version constraint
# here.
"nvidia-nvjitlink-cu12>=12.1.105",
],
'cuda12': [
f"jaxlib=={_current_jaxlib_version}",
f"jax-cuda12-plugin=={_current_jaxlib_version}",
"nvidia-cublas-cu12>=12.1.3.1",
"nvidia-cuda-cupti-cu12>=12.1.105",
"nvidia-cuda-nvcc-cu12>=12.1.105",
"nvidia-cuda-runtime-cu12>=12.1.105",
"nvidia-cudnn-cu12>=9.0,<10.0",
"nvidia-cufft-cu12>=11.0.2.54",
"nvidia-cusolver-cu12>=11.4.5.107",
"nvidia-cusparse-cu12>=12.1.0.106",
"nvidia-nccl-cu12>=2.18.1",
# nvjitlink is not a direct dependency of JAX, but it is a transitive
# dependency via, for example, cuSOLVER. NVIDIA's cuSOLVER packages
# do not have a version constraint on their dependencies, so the
# package doesn't get upgraded even though not doing that can cause
# problems (https://github.com/google/jax/issues/18027#issuecomment-1756305196)
# Until NVIDIA add version constraints, add a version constraint
# here.
"nvidia-nvjitlink-cu12>=12.1.105",
],
# Target that does not depend on the CUDA pip wheels, for those who want
# to use a preinstalled CUDA.
'cuda12_local': [
f"jaxlib=={_current_jaxlib_version}+cuda12.cudnn{_default_cuda12_cudnn_version}",
],
# CUDA installations require adding jax releases URL; e.g.
# $ pip install jax[cuda12_cudnn89] -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
**{f'cuda12_cudnn{cudnn_version}': f"jaxlib=={_current_jaxlib_version}+cuda12.cudnn{cudnn_version}"
for cudnn_version in _available_cuda12_cudnn_versions}
},
url='https://github.com/google/jax',
license='Apache-2.0',
classifiers=[
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
],
zip_safe=False,
)