Building from source¶
First, obtain the JAX source code:
git clone https://github.com/google/jax cd jax
Building JAX involves two steps:
Building or installing
jaxlib, the C++ support library for
Building or installing
jaxlib with pip¶
If you’re only modifying Python portions of JAX, we recommend installing
jaxlib from a prebuilt wheel using pip:
pip install jaxlib
See the JAX readme for full guidance on pip installation (e.g., for GPU support).
jaxlib from source¶
jaxlib from source, you must also install some prerequisites:
a C++ compiler (g++, clang, or MSVC)
On Ubuntu or Debian you can install the necessary prerequisites with:
sudo apt install g++ python python3-dev
If you are building on a Mac, make sure XCode and the XCode command line tools are installed.
See below for Windows build instructions.
sixpackage is required for during the jaxlib build only, and is not required at install time.
You can install the necessary Python dependencies using
pip install numpy scipy six wheel
jaxlib with CUDA support, you can run:
python build/build.py --enable_cuda pip install dist/*.whl # installs jaxlib (includes XLA)
python build/build.py --help for configuration options, including ways to
specify the paths to CUDA and CUDNN, which you must have installed. Here
python should be the name of your Python 3 interpreter; on some systems, you
may need to use
python3 instead. By default, the wheel is written to the
dist/ subdirectory of the current directory.
jaxlib without CUDA GPU support (CPU only), drop the
python build/build.py pip install dist/*.whl # installs jaxlib (includes XLA)
Additional Notes for Building
jaxlib from source on Windows¶
On Windows, follow Install Visual Studio to set up a C++ toolchain. Visual Studio 2019 version 16.5 or newer is required. If you need to build with CUDA enabled, follow the CUDA Installation Guide to set up a CUDA environment.
pacman -S patch realpath
Once everything is installed. Open PowerShell, and make sure MSYS2 is in the
path of the current session. Ensure
accessible. Activate the conda environment. The following command builds with
CUDA enabled, adjust it to whatever suitable for you:
python .\build\build.py ` --enable_cuda ` --cuda_path='C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v10.1' ` --cudnn_path='C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v10.1' ` --cuda_compute_capabilities='6.1' ` --cuda_version='10.1' ` --cudnn_version='7.6.5'
To build with debug information, add the flag
jaxlib has been installed, you can install
jax by running:
pip install -e . # installs jax
To upgrade to the latest version from GitHub, just run
git pull from the JAX
repository root, and rebuild by running
build.py or upgrading
necessary. You shouldn’t have to reinstall
pip install -e
sets up symbolic links from site-packages into the repository.
Running the tests¶
To run all the JAX tests, we recommend using
pytest-xdist, which can run tests in
parallel. First, install
pytest-benchmark by running
pip install pytest-xdist pytest-benchmark.
Then, from the repository root directory run:
pytest -n auto tests
JAX generates test cases combinatorially, and you can control the number of cases that are generated and checked for each test (default is 10). The automated tests currently use 25:
JAX_NUM_GENERATED_CASES=25 pytest -n auto tests
The automated tests also run the tests with default 64-bit floats and ints:
JAX_ENABLE_X64=1 JAX_NUM_GENERATED_CASES=25 pytest -n auto tests
You can run a more specific set of tests using pytest’s built-in selection mechanisms, or alternatively you can run a specific test file directly to see more detailed information about the cases being run:
python tests/lax_numpy_test.py --num_generated_cases=5
You can skip a few tests known as slow, by passing environment variable JAX_SKIP_SLOW_TESTS=1.
To specify a particular set of tests to run from a test file, you can pass a string
or regular expression via the
--test_targets flag. For example, you can run all
the tests of
python tests/lax_numpy_test.py --test_targets="testPad"
The Colab notebooks are tested for errors as part of the documentation build.
Note that to run the full pmap tests on a (multi-core) CPU only machine, you can run:
I.e. don’t use the -n auto option, since that effectively runs each test on a single-core worker.
mypy to check the type hints. To check types locally the same way
as Travis checks them:
pip install mypy mypy --config=mypy.ini --show-error-codes jax
To rebuild the documentation, install several packages:
pip install -r docs/requirements.txt
You must also install
pandoc in order to regenerate the notebooks.
See Install Pandoc,
or using Miniconda which
I have used successfully on the Mac:
conda install -c conda-forge pandoc.
If you do not want to install
pandoc then you should regenerate the documentation
without the notebooks.
You run at top-level one of the following commands:
sphinx-build -b html docs docs/build/html # with the notebooks sphinx-build -b html -D nbsphinx_execute=never docs docs/build/html # without the notebooks
You can then see the generated documentation in
Open the notebook with http://colab.research.google.com (then Upload from your
local repo), update it as needed,
Run all cells then
Download ipynb. You may want to test that it executes properly, using
Some of the notebooks are built automatically as part of the Travis pre-submit checks and as part of the Read the docs build. The build will fail if cells raise errors. If the errors are intentional, you can either catch them, or tag the cell with raises-exceptions metadata (example PR). You have to add this metadata by hand in the .ipynb file. It will be preserved when somebody else re-saves the notebook.
We exclude some notebooks from the build, e.g., because they contain long computations. See exclude_patterns in conf.py.
Documentation building on readthedocs.io¶
JAX’s auto-generated documentations is at jax.readthedocs.io.
The documentation building is controlled for the entire project by the
readthedocs JAX settings. The current settings
trigger a documentation build as soon as code is pushed to the GitHub
For each code version, the building process is driven by the
.readthedocs.yml and the
docs/conf.py configuration files.
For each automated documentation build you can see the documentation build logs.
If you want to test the documentation generation on Readthedocs, you can push code to the
branch. That branch is also built automatically, and you can
see the generated documentation here. If the documentation build
fails you may want to wipe the build environment for test-docs.
For a local test, I was able to do it in a fresh directory by replaying the commands I saw in the Readthedocs logs:
mkvirtualenv jax-docs # A new virtualenv mkdir jax-docs # A new directory cd jax-docs git clone --no-single-branch --depth 50 https://github.com/google/jax cd jax git checkout --force origin/test-docs git clean -d -f -f workon jax-docs python -m pip install --upgrade --no-cache-dir pip python -m pip install --upgrade --no-cache-dir -I Pygments==2.3.1 setuptools==41.0.1 docutils==0.14 mock==1.0.1 pillow==5.4.1 alabaster>=0.7,<0.8,!=0.7.5 commonmark==0.8.1 recommonmark==0.5.0 'sphinx<2' 'sphinx-rtd-theme<0.5' 'readthedocs-sphinx-ext<1.1' python -m pip install --exists-action=w --no-cache-dir -r docs/requirements.txt cd docs python `which sphinx-build` -T -E -b html -d _build/doctrees-readthedocs -D language=en . _build/html