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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
build --action_env PYTHON_BIN_PATH="/usr/local/bin/python3" build --python_path="/usr/local/bin/python3" # Build TensorFlow v2 build --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1 # Use lld as the linker build --linkopt="-fuse-ld=lld" build --linkopt="-lm" build --linkopt="-Wl,--undefined-version" # Prevent double-compilation of some TF code, ref. b/183279666 (internal)
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ci/official/containers/linux_arm64/builder.devtoolset/build_devtoolset.sh
--enable-initfini-array \ --enable-languages="c,c++" \ --enable-linker-build-id \ --enable-plugin \ --enable-shared \ --enable-threads=posix \ --with-default-libstdcxx-abi=${LIBSTDCXX_ABI} \ --with-gcc-major-version-only \ --with-linker-hash-style="gnu" \ && \ make -j$(nproc) && \ make install
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ci/official/README.md
# variables in between script executions. To forcibly remove the # container and start fresh, run "docker rm -f tf". Removing the container # destroys some temporary bazel data and causes longer builds. # # You will need the NVIDIA Container Toolkit for GPU testing: # https://github.com/NVIDIA/nvidia-container-toolkit # # Note: if you interrupt a bazel command on docker (ctrl-c), you
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