This change is a part of the initiative to test the JAX wheels in the presubmit properly.
The list of the changes:
1. JAX wheel build rule verifies that `--@local_config_cuda//cuda:include_cuda_libs=false` during the wheel build. There is a way to pass the restriction by providing `--@local_config_cuda//cuda:override_include_cuda_libs=true`.
2. The JAX version number (which is also used in the wheel filenames) is stored in `_version` variable in the file [version.py](https://github.com/jax-ml/jax/blob/main/jax/version.py). The custom repository rule `jax_python_wheel_version_repository` saves this value in `wheel_version.bzl`, so it becomes available in Bazel build phase.
3. The version suffix of the wheel in the build rule output depends on the environment variables.
The version suffix chunks that are not reproducible shouldn’t be calculated as a part of the wheel binary: for example, the current date changes every day, thus the wheels built today and tomorrow on the same code version will be technically different. To maintain reproducible wheel content, we need to pass suffix chunks in a form of environment variables.
4. Environment variables combinations for creating wheels with different versions:
* `0.5.1.dev0+selfbuilt` (local build, default build rule behavior): `--repo_env=ML_WHEEL_TYPE=snapshot`
* `0.5.1` (release): `--repo_env=ML_WHEEL_TYPE=release`
* `0.5.1rc1` (release candidate): `--repo_env=ML_WHEEL_TYPE=release --repo_env=ML_WHEEL_VERSION_SUFFIX=rc1`
* `0.5.1.dev20250128+3e75e20c7` (nightly build): `--repo_env=ML_WHEEL_TYPE=custom --repo_env=ML_WHEEL_BUILD_DATE=20250128 --repo_env=ML_WHEEL_GIT_HASH=$(git rev-parse HEAD)`
PiperOrigin-RevId: 723552265
This PR depends on https://github.com/openxla/xla/pull/17169. The change does not fail existing builds, but to be able to use python 3.13 functionality in jax the corresponding XLA pr needs to land first and get integrated with JAX (happens automatically).
PiperOrigin-RevId: 675243989
1) Hermetic CUDA rules allow building wheels with GPU support on a machine without GPUs, as well as running Bazel GPU tests on a machine with only GPUs and NVIDIA driver installed. When `--config=cuda` is provided in Bazel options, Bazel will download CUDA, CUDNN and NCCL redistributions in the cache, and use them during build and test phases.
[Default location of CUNN redistributions](https://developer.download.nvidia.com/compute/cudnn/redist/)
[Default location of CUDA redistributions](https://developer.download.nvidia.com/compute/cuda/redist/)
[Default location of NCCL redistributions](https://pypi.org/project/nvidia-nccl-cu12/#history)
2) To include hermetic CUDA rules in your project, add the following in the WORKSPACE of the downstream project dependent on XLA.
Note: use `@local_tsl` instead of `@tsl` in Tensorflow project.
```
load(
"@tsl//third_party/gpus/cuda/hermetic:cuda_json_init_repository.bzl",
"cuda_json_init_repository",
)
cuda_json_init_repository()
load(
"@cuda_redist_json//:distributions.bzl",
"CUDA_REDISTRIBUTIONS",
"CUDNN_REDISTRIBUTIONS",
)
load(
"@tsl//third_party/gpus/cuda/hermetic:cuda_redist_init_repositories.bzl",
"cuda_redist_init_repositories",
"cudnn_redist_init_repository",
)
cuda_redist_init_repositories(
cuda_redistributions = CUDA_REDISTRIBUTIONS,
)
cudnn_redist_init_repository(
cudnn_redistributions = CUDNN_REDISTRIBUTIONS,
)
load(
"@tsl//third_party/gpus/cuda/hermetic:cuda_configure.bzl",
"cuda_configure",
)
cuda_configure(name = "local_config_cuda")
load(
"@tsl//third_party/nccl/hermetic:nccl_redist_init_repository.bzl",
"nccl_redist_init_repository",
)
nccl_redist_init_repository()
load(
"@tsl//third_party/nccl/hermetic:nccl_configure.bzl",
"nccl_configure",
)
nccl_configure(name = "local_config_nccl")
```
PiperOrigin-RevId: 662981325
Also some documentation improvements/clarifications.
This allows it to not remove unused local wheels from the dist directory to avoid conflicts.
PiperOrigin-RevId: 650697758
This is a necessary first step before adding DUCC support to XLA,
otherwise the JAX tests in the XLA repo pull from JAX's copy,
which has slightly different build rules.
PiperOrigin-RevId: 576880208
nanobind has a number of advantages (https://nanobind.readthedocs.io/en/latest/why.html), notably speed of compilation and dispatch, but the main reason to do this for these bindings is because nanobind can target the Python Stable ABI starting with Python 3.12. This means that we will not need to ship per-Python version CUDA plugins starting with Python 3.12.
PiperOrigin-RevId: 559898790
Fixes build error:
Label
'@org_tensorflow//tensorflow/tsl/platform/default:build_config.bzl' is
invalid because 'tensorflow/tsl/platform/default' is not a package.
