xref: /aosp_15_r20/external/tflite-support/.bazelrc (revision b16991f985baa50654c05c5adbb3c8bbcfb40082)

# This file is based on tensorflow's (v2.2.0) .bazelrc found here:
# https://github.com/tensorflow/tensorflow/blob/v2.2.0/.bazelrc

# Sets the default Apple platform to macOS.

build --apple_platform_type=macos

# Enable using platform specific build settings
build --enable_platform_specific_config

# Flag to enable remote config. Required starting from TF 2.2.
common --experimental_repo_remote_exec

# 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

# Suppress C++ compiler warnings, otherwise build logs become 10s of MBs.
build:android --copt=-w
build:linux --copt=-w
build:macos --copt=-w
build:windows --copt=/w

# Android workspace configurations. Should be replaced by an interative configure in the future.
build --action_env ANDROID_NDK_HOME
build --action_env ANDROID_NDK_API_LEVEL
build --action_env ANDROID_BUILD_TOOLS_VERSION
build --action_env ANDROID_SDK_API_LEVEL
build --action_env ANDROID_SDK_HOME

# 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

# 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 --copt=-Wno-c++11-narrowing
build:ios_armv7 --config=ios
build:ios_armv7 --cpu=ios_armv7
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

# By default, build TF in C++ 14 mode.
build:android --cxxopt=-std=c++14
build:android --host_cxxopt=-std=c++14
build:ios --cxxopt=-std=c++14
build:ios --host_cxxopt=-std=c++14
build:linux --cxxopt=-std=c++14
build:linux --host_cxxopt=-std=c++14
build:macos --cxxopt=-std=c++14
build:macos --host_cxxopt=-std=c++14
build:windows --cxxopt=/std:c++14
build:windows --host_cxxopt=/std:c++14

# 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

# ASAN build
build:asan --strip=never
build:asan --copt -fsanitize=address
build:asan --copt -DADDRESS_SANITIZER
build:asan --copt -O1
build:asan --copt -g
build:asan --copt -fno-omit-frame-pointer
build:asan --linkopt -fsanitize=address

# Flags for open source build, always set to be true.
build --define open_source_build=true
test --define open_source_build=true

# dbg config, as a shorthand for '--config=opt -c dbg'
build:dbg --config=opt -c dbg
# for now, disable arm_neon. see: https://github.com/tensorflow/tensorflow/issues/33360
build:dbg --cxxopt -DTF_LITE_DISABLE_X86_NEON
# AWS SDK must be compiled in release mode. see: https://github.com/tensorflow/tensorflow/issues/37498
build:dbg --copt -DDEBUG_BUILD

build --define=use_fast_cpp_protos=true
build --define=allow_oversize_protos=true

build --spawn_strategy=standalone
build -c opt

# Adding "--cxxopt=-D_GLIBCXX_USE_CXX11_ABI=0" creates parity with TF
# compilation options. It also addresses memory use due to
# copy-on-write semantics of std::strings of the older ABI.
build --cxxopt=-D_GLIBCXX_USE_CXX11_ABI=0

# 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

# These are bazel 2.0's incompatible flags. Tensorflow needs to use bazel 2.0.0
# to use cc_shared_library, as part of the Tensorflow Build Improvements RFC:
# https://github.com/tensorflow/community/pull/179
build --noincompatible_prohibit_aapt1

# 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

# Enable using platform specific build settings, except when cross-compiling for
# mobile platforms.
build --enable_platform_specific_config
build:android --noenable_platform_specific_config
build:ios --noenable_platform_specific_config

# Suppress all warning messages.
build:short_logs --output_filter=DONT_MATCH_ANYTHING
build:verbose_logs --output_filter=
build --config=short_logs

# 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

# Options from ./configure
try-import %workspace%/.tf_configure.bazelrc

# Put user-specific options in .bazelrc.user
try-import %workspace%/.bazelrc.user