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WORKSPACE
"cuda_configure", ) cuda_configure(name = "local_config_cuda") load( "@local_tsl//third_party/nccl/hermetic:nccl_redist_init_repository.bzl", "nccl_redist_init_repository", ) nccl_redist_init_repository() load( "@local_tsl//third_party/nccl/hermetic:nccl_configure.bzl", "nccl_configure", )
Registered: Tue Oct 29 12:39:09 UTC 2024 - Last Modified: Fri Oct 11 16:49:28 UTC 2024 - 3K bytes - Viewed (0) -
CODEOWNERS
/tensorflow/c/eager @qqfish /tensorflow/core/common_runtime/eager @qqfish /tenosrflow/core/debug @caisq /tensorflow/core/kernels/mkl/ @penpornk /tensorflow/core/kernels/sparse/ @penpornk /tensorflow/core/nccl/ @azaks2 @chsigg /tensorflow/python/autograph/ @mdanatg /tensorflow/python/debug @caisq /tensorflow/python/eager @rohan100jain /tensorflow/tools/docs/ @markdaoust /tensorflow/compiler/mlir/ @aminim
Registered: Tue Oct 29 12:39:09 UTC 2024 - Last Modified: Fri May 27 21:02:49 UTC 2022 - 563 bytes - Viewed (0) -
configure.py
set_hermetic_cuda_compute_capabilities(environ_cp) set_cuda_local_path(environ_cp, 'CUDA', 'LOCAL_CUDA_PATH') set_cuda_local_path(environ_cp, 'CUDNN', 'LOCAL_CUDNN_PATH') set_cuda_local_path(environ_cp, 'NCCL', 'LOCAL_NCCL_PATH') if 'LD_LIBRARY_PATH' in environ_cp and environ_cp.get( 'LD_LIBRARY_PATH') != '1': write_action_env_to_bazelrc('LD_LIBRARY_PATH',
Registered: Tue Oct 29 12:39:09 UTC 2024 - Last Modified: Wed Oct 02 22:16:02 UTC 2024 - 48.2K bytes - Viewed (1) -
.bazelrc
# cuda_clang Build with CUDA Clang support. # rocm: Build with AMD GPU support (rocm) # mkl: Enable full mkl support. # nogcp: Disable GCS support. # nonccl: Disable nccl support. # # # Remote build execution options (only configured to work with TF team projects for now.) # rbe_base: General RBE options shared by all flavors. # rbe_linux: General RBE options used on all linux builds.
Registered: Tue Oct 29 12:39:09 UTC 2024 - Last Modified: Mon Oct 28 22:02:31 UTC 2024 - 51.3K bytes - Viewed (0) -
RELEASE.md
## Breaking Changes * Prebuilt binaries are now (as of TensorFlow 1.10) built against NCCL 2.2 and no longer include NCCL in the binary install. TensorFlow usage with multiple GPUs and NCCL requires upgrade to [NCCL 2.2](https://developer.nvidia.com/nccl). See updated install guides: [TensorFlow GPU support](https://www.tensorflow.org/install/gpu) and
Registered: Tue Oct 29 12:39:09 UTC 2024 - Last Modified: Tue Oct 22 14:33:53 UTC 2024 - 735.3K bytes - Viewed (0)