These env vars are no longer used or need and were
being set incorrectly.
[ROCm] Use specific amdgpu version for EL8 systems
We were always installing the latest driver versions
but this had some side effects when yum would try
to download index files from a URL with changing content.
[ROCm] Fix formatting on python files
Reformatted with black
If `--use_cuda_nvcc` flag is set the NVCC compiler driver will be used to build the CUDA code (default behavior). Otherwise, if the flag `--nouse_cuda_nvcc` is set, only the clang compiler will be used to build the CUDA code (effectively disabling NVCC).
Mark `--use_clang` flag as deprecated.
Refactor `.bazelrc` configs to match the new flag and to cleanup all previous confusing names.
PiperOrigin-RevId: 678332548
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
Interactive causes bazel to output more
useful info when running locally.
* Fix issue with rocm el8 repo urls
Work around quirk with rocm version
when it ends with 0
* Fix package name conflict
Ubu22 and higher have a package name conflict
between the debian versions and the AMD provided
versions.
* [ROCm] Use clang env
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
Use get_rocm.py changes in ci_build to pull in
development builds for ROCm.
Specify ROCM_BUILD_JOB and ROCM_BUILD_NUM for
activating the development build path.
When `build_gpu_plugin` is true, three wheels will be produced (jaxlib, jax-cuda-pjrt and jax-cuda-plugin). If they are editable, they need to be placed in subdirectories to avoid overwrite.
Tested on GPU. After the editable wheels are built, they can be installed with `pip install -e /jax/dist/jax_gpu_pjrt /jax/dist/jaxlib /jax/dist/jax_gpu_plugin`.
PiperOrigin-RevId: 660984311
The plugin is released and the flag is no longer needed.
Also set default value of enable_gpu to False. enable_gpu will be removed in the next change.
PiperOrigin-RevId: 660059432
This lets us avoid bundling a whole another copy of LLVM with JAX packages
and so we can finally start building Mosaic GPU by default.
PiperOrigin-RevId: 638569750
