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.bazelrc
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.bazelrc
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# Android configs. Bazel needs to have --cpu and --fat_apk_cpu both set to the
# target CPU to build transient dependencies correctly. See
# https://docs.bazel.build/versions/master/user-manual.html#flag--fat_apk_cpu
build:android --crosstool_top=//external:android/crosstool
build:android --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
build:android_arm --config=android
build:android_arm --cpu=armeabi-v7a
build:android_arm --fat_apk_cpu=armeabi-v7a
build:android_arm64 --config=android
build:android_arm64 --cpu=arm64-v8a
build:android_arm64 --fat_apk_cpu=arm64-v8a
build:android_x86 --config=android
build:android_x86 --cpu=x86
build:android_x86 --fat_apk_cpu=x86
build:android_x86_64 --config=android
build:android_x86_64 --cpu=x86_64
build:android_x86_64 --fat_apk_cpu=x86_64
# Sets the default Apple platform to macOS.
build --apple_platform_type=macos
# iOS configs for each architecture and the fat binary builds.
build:ios --apple_platform_type=ios
build:ios --apple_bitcode=embedded --copt=-fembed-bitcode
build:ios_armv7 --config=ios
build:ios_armv7 --cpu=ios_armv7
build:ios_armv7 --cops -Wno-c++11-narrowing
build:ios_arm64 --config=ios
build:ios_arm64 --cpu=ios_arm64
build:ios_x86_64 --config=ios
build:ios_x86_64 --cpu=ios_x86_64
build:ios_fat --config=ios
build:ios_fat --ios_multi_cpus=armv7,arm64,x86_64
build:ios_fat --copt -Wno-c++11-narrowing
# Config to use a mostly-static build and disable modular op registration
# support (this will revert to loading TensorFlow with RTLD_GLOBAL in Python).
# By default, TensorFlow will build with a dependence on
# //tensorflow:libtensorflow_framework.so.
build:monolithic --define framework_shared_object=false
# For projects which use TensorFlow as part of a Bazel build process, putting
# nothing in a bazelrc will default to a monolithic build. The following line
# opts in to modular op registration support by default.
build --define framework_shared_object=true
# Flags for open source build, always set to be true.
build --define open_source_build=true
test --define open_source_build=true
# For workaround https://github.com/bazelbuild/bazel/issues/8772 with Bazel >= 0.29.1
build --java_toolchain=//third_party/toolchains/java:tf_java_toolchain
build --host_java_toolchain=//third_party/toolchains/java:tf_java_toolchain
# Please note that MKL on MacOS or windows is still not supported.
# If you would like to use a local MKL instead of downloading, please set the
# environment variable "TF_MKL_ROOT" every time before build.
build:mkl --define=build_with_mkl=true --define=enable_mkl=true
build:mkl --define=tensorflow_mkldnn_contraction_kernel=0
build:mkl -c opt
# This config option is used to enable MKL-DNN open source library only,
# without depending on MKL binary version.
build:mkl_open_source_only --define=build_with_mkl_dnn_only=true
build:mkl_open_source_only --define=build_with_mkl_dnn_v1_only=true
build:mkl_open_source_only --define=build_with_mkl=true --define=enable_mkl=true
build:mkl_open_source_only --define=tensorflow_mkldnn_contraction_kernel=0
build:download_clang --crosstool_top=@local_config_download_clang//:toolchain
build:download_clang --define=using_clang=true
build:download_clang --action_env TF_DOWNLOAD_CLANG=1
# Instruct clang to use LLD for linking.
# This only works with GPU builds currently, since Bazel sets -B/usr/bin in
# auto-generated CPU crosstool, forcing /usr/bin/ld.lld to be preferred over
# the downloaded one.
build:download_clang_use_lld --linkopt='-fuse-ld=lld'
# This config refers to building with CUDA available. It does not necessarily
# mean that we build CUDA op kernels.
build:using_cuda --define=using_cuda=true
build:using_cuda --action_env TF_NEED_CUDA=1
build:using_cuda --crosstool_top=@local_config_cuda//crosstool:toolchain
# This config refers to building CUDA op kernels with nvcc.
build:cuda --config=using_cuda
build:cuda --define=using_cuda_nvcc=true
# This config refers to building CUDA op kernels with clang.
build:cuda_clang --config=using_cuda
build:cuda_clang --define=using_cuda_clang=true
build:cuda_clang --define=using_clang=true
build:cuda_clang --action_env TF_CUDA_CLANG=1
build:tensorrt --action_env TF_NEED_TENSORRT=1
build:rocm --crosstool_top=@local_config_rocm//crosstool:toolchain
build:rocm --define=using_rocm=true --define=using_rocm_hipcc=true
build:rocm --action_env TF_NEED_ROCM=1
build:sycl --crosstool_top=@local_config_sycl//crosstool:toolchain
build:sycl --define=using_sycl=true
build:sycl --action_env TF_NEED_OPENCL_SYCL=1
build:sycl_nodouble --config=sycl
build:sycl_nodouble --cxxopt -DTENSORFLOW_SYCL_NO_DOUBLE
build:sycl_nodouble --config=sycl
build:sycl_asan --copt -fno-omit-frame-pointer --copt -fsanitize-coverage=3 --copt -DGPR_NO_DIRECT_SYSCALLS --linkopt -fPIC --linkopt -fsanitize=address
build:sycl_nodouble --config=sycl
build:sycl_trisycl --define=using_trisycl=true
# Options extracted from configure script
build:ngraph --define=with_ngraph_support=true
build:numa --define=with_numa_support=true
# Options to disable default on features
build:noaws --define=no_aws_support=true
build:nogcp --define=no_gcp_support=true
build:nohdfs --define=no_hdfs_support=true
build:nonccl --define=no_nccl_support=true
build --define=use_fast_cpp_protos=true
build --define=allow_oversize_protos=true
build --spawn_strategy=standalone
build --strategy=Genrule=standalone
build -c opt
# By default, build TF in C++ 14 mode.
build --cxxopt=-std=c++14
build --host_cxxopt=-std=c++14
# Make Bazel print out all options from rc files.
build --announce_rc
# Other build flags.
build --define=grpc_no_ares=true
# See https://github.com/bazelbuild/bazel/issues/7362 for information on what
# --incompatible_remove_legacy_whole_archive flag does.
# This flag is set to true in Bazel 1.0 and newer versions. We tried to migrate
# Tensorflow to the default, however test coverage wasn't enough to catch the
# errors.
# There is ongoing work on Bazel team's side to provide support for transitive
# shared libraries. As part of migrating to transitive shared libraries, we
# hope to provide a better mechanism for control over symbol exporting, and
# then tackle this issue again.
#
# TODO: Remove this line once TF doesn't depend on Bazel wrapping all library
# archives in -whole_archive -no_whole_archive.
build --noincompatible_remove_legacy_whole_archive
# Modular TF build options
build:dynamic_kernels --define=dynamic_loaded_kernels=true
build:dynamic_kernels --copt=-DAUTOLOAD_DYNAMIC_KERNELS
# Build TF with C++ 17 features.
build:c++17 --cxxopt=-std=c++1z
build:c++17 --cxxopt=-stdlib=libc++
build:c++1z --config=c++17
# Tensorflow uses M_* math constants that only get defined by MSVC headers if
# _USE_MATH_DEFINES is defined.
build:windows --copt=/D_USE_MATH_DEFINES
# Default paths for TF_SYSTEM_LIBS
build --define=PREFIX=/usr
build --define=LIBDIR=$(PREFIX)/lib
build --define=INCLUDEDIR=$(PREFIX)/include
# Suppress all warning messages.
build:short_logs --output_filter=DONT_MATCH_ANYTHING
# Options when using remote execution
build:rbe --action_env=BAZEL_DO_NOT_DETECT_CPP_TOOLCHAIN=1
build:rbe --auth_enabled=true
build:rbe --auth_scope=https://www.googleapis.com/auth/cloud-source-tools
build:rbe --define=EXECUTOR=remote
build:rbe --flaky_test_attempts=3
build:rbe --jobs=200
build:rbe --remote_accept_cached=true
build:rbe --remote_cache=remotebuildexecution.googleapis.com
build:rbe --remote_executor=remotebuildexecution.googleapis.com
build:rbe --remote_local_fallback=false
build:rbe --remote_timeout=600
build:rbe --spawn_strategy=remote,worker,sandboxed,local
build:rbe --strategy=Genrule=remote,worker,sandboxed,local
build:rbe --strategy=Closure=remote,worker,sandboxed,local
build:rbe --strategy=Javac=remote,worker,sandboxed,local
build:rbe --strategy=TestRunner=remote,worker,sandboxed,local
build:rbe --tls_enabled
test:rbe --test_env=USER=anon
# Options to build TensorFlow 1.x or 2.x.
build:v1 --define=tf_api_version=1
build:v2 --define=tf_api_version=2
build:v1 --action_env=TF2_BEHAVIOR=0
build:v2 --action_env=TF2_BEHAVIOR=1
build --config=v2
test --config=v2
# Default options should come above this line
# Options from ./configure
try-import %workspace%/.tf_configure.bazelrc
# Put user-specific options in .bazelrc.user
try-import %workspace%/.bazelrc.user