And for a deeper dive into JAX: Common gotchas and sharp edges The Autodiff Cookbook, Part 1: easy and powerful automatic differentiation in JAX Directly using XLA in Python MAML Tutorial with JAX Generative Mo
python build/build.py --enable_cuda pip install -e build#install jaxlib (includes XLA)pip install -e.#install jax (pure Python) Seepython build/build.py --helpfor configuration options, including ways to specify the paths to CUDA and CUDNN, which you must have installed. The build also ...
python build/build.py --enable_cuda pip install -e build # install jaxlib (includes XLA) pip install -e . # install jax (pure Python) See python build/build.py --help for configuration options, including ways to specify the paths to CUDA and CUDNN, which you must have installed. The...
The Python version must match your Python interpreter. There are prebuilt wheels for Python 2.7, 3.6, and 3.7; for anything else, you must build from source. Running the tests To run all the JAX tests, we recommend using pytest-xdist, which can run tests in parallel. First, install pytes...
The Python version must match your Python interpreter. There are prebuilt wheels for Python 2.7, 3.6, and 3.7; for anything else, you must build from source. Running the tests To run all the JAX tests, we recommend usingpytest-xdist, which can run tests in parallel. First, installpytest-...
The Python version must match your Python interpreter. There are prebuilt wheels for Python 2.7, 3.6, and 3.7; for anything else, you must build from source. To run all the JAX tests, we recommend usingpytest-xdist, which can run tests in parallel. First, installpytest-xdistby runningpip...
NumPy also does a lot of work to cast any array-like function arguments to arrays, as in np.sum([x, y]), while jax.numpy typically requires explicit casting of array arguments, like np.sum(np.array([x, y])). For automatic differentiation with grad, JAX has the same restrictions as...
The Python version must match your Python interpreter. There are prebuilt wheels for Python 2.7, 3.6, and 3.7; for anything else, you must build from source. Running the tests To run all the JAX tests, we recommend using pytest-xdist, which can run tests in parallel. First, install pytes...
And for a deeper dive into JAX: Common gotchas and sharp edges The Autodiff Cookbook, Part 1: easy and powerful automatic differentiation in JAX Directly using XLA in Python MAML Tutorial with JAX. Installation JAX is written in pure Python, but it depends on XLA, which needs to be compiled...
NumPy also does a lot of work to cast any array-like function arguments to arrays, as in np.sum([x, y]), while jax.numpy typically requires explicit casting of array arguments, like np.sum(np.array([x, y])). For automatic differentiation with grad, JAX has the same restrictions as...