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cpu.bazelrc
cpu.bazelrc 1.62 KiB
# This bazelrc can build a CPU-supporting TF package.
# Hopefully it's compatible with manylinux2010.
# Convenient cache configurations
# Use a cache directory mounted to /tf/cache. Very useful!
build:sigbuild_local_cache --disk_cache=/tf/cache
# Use the public-access TF DevInfra cache (read only)
build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache" --remote_upload_local_results=false
# Write to the TF DevInfra cache (only works for internal TF CI)
build:sigbuild_remote_cache_push --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache" --google_default_credentials
# Use Python 3.X as installed in container image
build --action_env PYTHON_BIN_PATH="/usr/bin/python3"
build --action_env PYTHON_LIB_PATH="/usr/lib/tf_python"
build --python_path="/usr/bin/python3"
# Build TensorFlow v2
build --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1
# Prevent double-compilation of some TF code, ref. b/183279666 (internal)
# > TF's gen_api_init_files has a genrule to run the core TensorFlow code
# > on the host machine. If we don't have --distinct_host_configuration=false,
# > the core TensorFlow code will be built once for the host and once for the
# > target platform.
# See also https://docs.bazel.build/versions/master/guide.html#build-configurations-and-cross-compilation
build --distinct_host_configuration=false
# Target the AVX instruction set
build --copt=-mavx --host_copt=-mavx
# Use the NVCC toolchain to compile for manylinux2010
build --crosstool_top=@org_tensorflow//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda11.2:toolchain