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
Remote configurations of python repositories are removed because hermetic Python repository rules install and configure python modules in Bazel cache on the host machine. The cache is shared across host and remote machines.
PiperOrigin-RevId: 671512134
The CUDA and NCCL repositories are created on a host machine now and shared via Bazel cache between host and remote machines.
PiperOrigin-RevId: 671089856
Add `--@local_config_cuda//cuda:override_include_cuda_libs` to override settings for TF wheel.
Forbid building TF wheel with `--@local_config_cuda//cuda:include_cuda_libs=true`
PiperOrigin-RevId: 666848518
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
This is needed for hermetic CUDA integration in Google ML projects since tensorRT is not distributed in the same free way as other CUDA/CUDNN distributives.
PiperOrigin-RevId: 662601190
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
This removes commands that set up Python and JAX's build-time Python dependencies. These are now handled automatically by Bazel with hermetic Python.
We also no longer need to force Genrules to run locally to be able to set up `local_config_python` correctly.
This change should also resolve build failures in the cross-compile builds.
PiperOrigin-RevId: 636030000
