# TensorFlow Bazel configuration file.

# This file tries to group and simplify build options for TensorFlow

#

# ----CONFIG OPTIONS----

# Android options:

# android:

# android_arm:

# android_arm64:

# android_x86:

# android_x86_64:

#

# iOS options:

# ios:

# ios_armv7:

# ios_arm64:

# ios_x86_64:

# ios_fat:

#

# Macosx options

# darwin_arm64:

#

# Compiler options:

# cuda_clang: Use Clang when building CUDA code.

# avx_linux: Build with avx instruction set on linux.

# avx_win: Build with avx instruction set on windows

#

# Other build options:

# short_logs: Only log errors during build, skip warnings.

# verbose_logs: Show all compiler warnings during build.

# monolithic: Build all TF C++ code into a single shared object.

# dynamic_kernels: Try to link all kernels dynamically (experimental).

# dbg: Build with debug info

#

# TF version options;

# v2: Build TF v2

#

# Feature and Third party library support options:

# xla: Build TF with XLA

# tpu: Build TF with TPU support

# cuda: Build with CUDA support.

# cuda_clang Build with CUDA Clang support.

# rocm: Build with AMD GPU support (rocm)

# mkl: Enable full mkl support.

# tensorrt: Enable Tensorrt support.

# noaws: Disable AWS S3 storage support

# nogcp: Disable GCS support.

# nohdfs: Disable hadoop hdfs 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.

# rbe_win: General RBE options used on all windows builds.

#

# rbe_linux_cpu: RBE options to build with only CPU support.

# rbe_linux_cuda: RBE options to build with GPU support using clang.

#

# rbe_win_py39: Windows Python 3.9 RBE config

#

# tensorflow_testing_rbe_win: RBE options to use RBE with tensorflow-testing project on windows

#

# Embedded Linux options (experimental and only tested with TFLite build yet)

# elinux: General Embedded Linux options shared by all flavors.

# elinux_aarch64: Embedded Linux options for aarch64 (ARM64) CPU support.

# elinux_armhf: Embedded Linux options for armhf (ARMv7) CPU support.

#

# Release build options (for all operating systems)

# release_base: Common options for all builds on all operating systems.

# release_cpu_linux: Toolchain and CUDA options for Linux CPU builds.

# release_gpu_linux: Toolchain and CUDA options for Linux GPU builds.

# release_cpu_macos: Toolchain and CUDA options for MacOS CPU builds.

# release_cpu_windows: Toolchain and CUDA options for Windows CPU builds.

# Default build options. These are applied first and unconditionally.

# 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

build --define tsl_protobuf_header_only=true

build --define=use_fast_cpp_protos=true

build --define=allow_oversize_protos=true

build --spawn_strategy=standalone

build -c opt

# Make Bazel print out all options from rc files.

build --announce_rc

# TODO(mihaimaruseac): Document this option or remove if no longer needed

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 the following two lines once TF doesn't depend on Bazel wrapping

# all library archives in -whole_archive -no_whole_archive.

build --noincompatible_remove_legacy_whole_archive

build --features=-force_no_whole_archive

# TODO(mihaimaruseac): Document this option or remove if no longer needed

build --enable_platform_specific_config

# Enable XLA support by default.

build --define=with_xla_support=true

# TODO(mihaimaruseac): Document this option or remove if no longer needed

build --config=short_logs

# TODO(mihaimaruseac): Document this option or remove if no longer needed

build --config=v2

# Disable AWS/HDFS support by default

build --define=no_aws_support=true

build --define=no_hdfs_support=true

# TF now has `cc_shared_library` targets, so it needs the experimental flag

# TODO(rostam): Remove when `cc_shared_library` is enabled by default

build --experimental_cc_shared_library

# cc_shared_library ensures no library is linked statically more than once.

build --experimental_link_static_libraries_once=false

# Prevent regressions on those two incompatible changes

# TODO: remove those flags when they are flipped in the default Bazel version TF uses.

build --incompatible_enforce_config_setting_visibility

# TODO: also enable this flag after fixing the visbility violations

# build --incompatible_config_setting_private_default_visibility

# Default options should come above this line.

# 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

# Build everything statically for Android since all static libs are later

# bundled together into a single .so for deployment.

build:android --dynamic_mode=off

# Sets the default Apple platform to macOS.

build:macos --apple_platform_type=macos

# gRPC on MacOS requires this #define

build:macos --copt=-DGRPC_BAZEL_BUILD

# Avoid hitting command line argument limit

build:macos --features=archive_param_file

# Settings for MacOS on ARM CPUs.

build:macos_arm64 --cpu=darwin_arm64

build:macos_arm64 --macos_minimum_os=11.0

# 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_arm64e --config=ios

build:ios_arm64e --cpu=ios_arm64e

build:ios_sim_arm64 --config=ios

build:ios_sim_arm64 --cpu=ios_sim_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,i386,x86_64

# 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

build:monolithic --define tsl_protobuf_header_only=false

build:monolithic --experimental_link_static_libraries_once=false # b/229868128

# Please note that MKL on MacOS 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 --define=build_with_openmp=true

build:mkl -c opt

# config to build OneDNN backend with a user specified threadpool.

build:mkl_threadpool --define=build_with_mkl=true --define=enable_mkl=true

build:mkl_threadpool --define=tensorflow_mkldnn_contraction_kernel=0

build:mkl_threadpool --define=build_with_mkl_opensource=true

build:mkl_threadpool -c opt

# Config setting to build oneDNN with Compute Library for the Arm Architecture (ACL).

build:mkl_aarch64 --define=build_with_mkl_aarch64=true

build:mkl_aarch64 --define=build_with_openmp=true

build:mkl_aarch64 --define=build_with_acl=true

build:mkl_aarch64 -c opt

# Config setting to build oneDNN with Compute Library for the Arm Architecture (ACL).

# with Eigen threadpool support

build:mkl_aarch64_threadpool --define=build_with_mkl_aarch64=true

build:mkl_aarch64_threadpool -c opt

# CUDA: This config refers to building CUDA op kernels with nvcc.

build:cuda --repo_env TF_NEED_CUDA=1

build:cuda --crosstool_top=@local_config_cuda//crosstool:toolchain

build:cuda --@local_config_cuda//:enable_cuda

# CUDA: This config refers to building CUDA op kernels with clang.

build:cuda_clang --config=cuda

# Enable TensorRT optimizations https://developer.nvidia.com/tensorrt

build:cuda_clang --config=tensorrt

build:cuda_clang --action_env=TF_CUDA_CLANG="1"

build:cuda_clang --@local_config_cuda//:cuda_compiler=clang

# Select supported compute capabilities (supported graphics cards).

# This is the same as the official TensorFlow builds.

# See https://developer.nvidia.com/cuda-gpus#compute

# TODO(angerson, perfinion): What does sm_ vs compute_ mean? How can users

# select a good value for this? See go/tf-pip-cuda

build:cuda_clang --repo_env=TF_CUDA_COMPUTE_CAPABILITIES="sm_50,sm_60,sm_70,sm_75,compute_80"

# Set up compilation CUDA version and paths and use the CUDA Clang toolchain.

build:cuda_clang_official --config=cuda_clang

build:cuda_clang_official --action_env=TF_CUDA_VERSION="12"

build:cuda_clang_official --action_env=TF_CUDNN_VERSION="8"

build:cuda_clang_official --action_env=CUDA_TOOLKIT_PATH="/usr/local/cuda-12.2"

build:cuda_clang_official --action_env=GCC_HOST_COMPILER_PATH="/dt9/usr/bin/gcc"

build:cuda_clang_official --action_env=CLANG_CUDA_COMPILER_PATH="/usr/lib/llvm-17/bin/clang"

build:cuda_clang_official --action_env=LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"

build:cuda_clang_official --crosstool_top="@sigbuild-r2.14-clang_config_cuda//crosstool:toolchain"

# Debug config

build:dbg -c dbg

# Only include debug info for files under tensorflow/, excluding kernels, to

# reduce the size of the debug info in the binary. This is because if the debug

# sections in the ELF binary are too large, errors can occur. See

# https://github.com/tensorflow/tensorflow/issues/48919.

# Users can still include debug info for a specific kernel, e.g. with:

# --config=dbg --per_file_copt=+tensorflow/core/kernels/identity_op.*@-g

# Since this .bazelrc file is synced between the tensorflow/tensorflow repo and

# the openxla/xla repo, also include debug info for files under xla/.

build:dbg --per_file_copt=+.*,-tensorflow.*,-xla.*@-g0

build:dbg --per_file_copt=+tensorflow/core/kernels.*@-g0

# 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

# Config to build TF TPU

build:tpu --define=with_tpu_support=true

build:tpu --define=framework_shared_object=true

build:tpu --copt=-DLIBTPU_ON_GCE

build:tpu --define=enable_mlir_bridge=true

build:tensorrt --repo_env TF_NEED_TENSORRT=1

build:rocm --crosstool_top=@local_config_rocm//crosstool:toolchain

build:rocm --define=using_rocm_hipcc=true

build:rocm --define=tensorflow_mkldnn_contraction_kernel=0

build:rocm --repo_env TF_NEED_ROCM=1

# 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

# Modular TF build options

build:dynamic_kernels --define=dynamic_loaded_kernels=true

build:dynamic_kernels --copt=-DAUTOLOAD_DYNAMIC_KERNELS

# Don't trigger --config=<host platform> when cross-compiling.

build:android --noenable_platform_specific_config

build:ios --noenable_platform_specific_config

# Suppress all C++ compiler warnings, otherwise build logs become 10s of MBs.

build:android --copt=-w

build:ios --copt=-w

build:linux --host_copt=-w

build:macos --copt=-w

build:windows --copt=/W0

build:windows --host_copt=/W0

# Suppress most C++ complier warnings to reduce log size but allow

# for specific warnings to still be present.

build:linux --copt="-Wno-all"

build:linux --copt="-Wno-extra"

build:linux --copt="-Wno-deprecated"

build:linux --copt="-Wno-deprecated-declarations"

build:linux --copt="-Wno-ignored-attributes"

build:linux --copt="-Wno-array-bounds"

# Add unused-result as an error on Linux.

build:linux --copt="-Wunused-result"

build:linux --copt="-Werror=unused-result"

# Add switch as an error on Linux.

build:linux --copt="-Wswitch"

build:linux --copt="-Werror=switch"

# Required for building with clang

build:linux --copt="-Wno-error=unused-but-set-variable"

# Linux ARM64 specific options

build:linux_arm64 --copt="-mtune=generic" --copt="-march=armv8-a" --copt="-O3"

# On Windows, `__cplusplus` is wrongly defined without this switch

# See https://devblogs.microsoft.com/cppblog/msvc-now-correctly-reports-__cplusplus/

build:windows --copt=/Zc:__cplusplus

build:windows --host_copt=/Zc:__cplusplus

# 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

build:windows --host_copt=/D_USE_MATH_DEFINES

# Windows has a relatively short command line limit, which TF has begun to hit.

# See https://docs.bazel.build/versions/main/windows.html

build:windows --features=compiler_param_file

build:windows --features=archive_param_file

# Speed Windows compile times. Available in VS 16.4 (we are on 16.11). See

# https://groups.google.com/a/tensorflow.org/d/topic/build/SsW98Eo7l3o/discussion

build:windows --copt=/d2ReducedOptimizeHugeFunctions

build:windows --host_copt=/d2ReducedOptimizeHugeFunctions

# Enable the runfiles symlink tree on Windows. This makes it possible to build

# the pip package on Windows without an intermediate data-file archive, as the

# build_pip_package script in its current form (as of Aug 2023) uses the

# runfiles symlink tree to decide what to put into the Python wheel.

startup --windows_enable_symlinks

build:windows --enable_runfiles

# Default paths for TF_SYSTEM_LIBS

build:linux --define=PREFIX=/usr

build:linux --define=LIBDIR=$(PREFIX)/lib

build:linux --define=INCLUDEDIR=$(PREFIX)/include

build:linux --define=PROTOBUF_INCLUDE_PATH=$(PREFIX)/include

build:macos --define=PREFIX=/usr

build:macos --define=LIBDIR=$(PREFIX)/lib

build:macos --define=INCLUDEDIR=$(PREFIX)/include

build:macos --define=PROTOBUF_INCLUDE_PATH=$(PREFIX)/include

# TF_SYSTEM_LIBS do not work on windows.

# By default, build TF in C++ 17 mode.

build:android --cxxopt=-std=c++17

build:android --host_cxxopt=-std=c++17

build:ios --cxxopt=-std=c++17

build:ios --host_cxxopt=-std=c++17

build:linux --cxxopt=-std=c++17

build:linux --host_cxxopt=-std=c++17

build:macos --cxxopt=-std=c++17

build:macos --host_cxxopt=-std=c++17

build:windows --cxxopt=/std:c++17

build:windows --host_cxxopt=/std:c++17

# On windows, we still link everything into a single DLL.

build:windows --config=monolithic

# On linux, we dynamically link small amount of kernels

build:linux --config=dynamic_kernels

# Make sure to include as little of windows.h as possible

build:windows --copt=-DWIN32_LEAN_AND_MEAN

build:windows --host_copt=-DWIN32_LEAN_AND_MEAN

build:windows --copt=-DNOGDI

build:windows --host_copt=-DNOGDI

# MSVC (Windows): Standards-conformant preprocessor mode

# See https://docs.microsoft.com/en-us/cpp/preprocessor/preprocessor-experimental-overview

build:windows --copt=/Zc:preprocessor

build:windows --host_copt=/Zc:preprocessor

# Misc build options we need for windows.

build:windows --linkopt=/DEBUG

build:windows --host_linkopt=/DEBUG

build:windows --linkopt=/OPT:REF

build:windows --host_linkopt=/OPT:REF

build:windows --linkopt=/OPT:ICF

build:windows --host_linkopt=/OPT:ICF

# Verbose failure logs when something goes wrong

build:windows --verbose_failures

# Work around potential issues with large command lines on windows.

# See: https://github.com/bazelbuild/bazel/issues/5163

build:windows --features=compiler_param_file

# Do not risk cache corruption. See:

# https://github.com/bazelbuild/bazel/issues/3360

build:linux --experimental_guard_against_concurrent_changes

# Configure short or long logs

build:short_logs --output_filter=DONT_MATCH_ANYTHING

build:verbose_logs --output_filter=

# Instruction set optimizations

# TODO(gunan): Create a feature in toolchains for avx/avx2 to

# avoid having to define linux/win separately.

build:avx_linux --copt=-mavx

build:avx_linux --host_copt=-mavx

build:avx_win --copt=/arch=AVX

# Options to build TensorFlow 1.x or 2.x.

# TODO(kanglan): Change v2's define to default behavior

build:v2 --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1

# Disable XLA on mobile.

build:xla --define=with_xla_support=true # TODO: remove, it's on by default.

build:android --define=with_xla_support=false

build:ios --define=with_xla_support=false

# BEGIN TF REMOTE BUILD EXECUTION OPTIONS

# Options when using remote execution

# WARNING: THESE OPTIONS WONT WORK IF YOU DO NOT HAVE PROPER AUTHENTICATION AND PERMISSIONS

# Allow creation of resultstore URLs for any bazel invocation

build:resultstore --google_default_credentials

build:resultstore --bes_backend=buildeventservice.googleapis.com

build:resultstore --bes_instance_name="tensorflow-testing"

build:resultstore --bes_results_url="https://source.cloud.google.com/results/invocations"

build:resultstore --bes_timeout=600s

# Flag to enable remote config

common --experimental_repo_remote_exec

# Make Bazel not try to probe the host system for a C++ toolchain.

build:rbe_base --config=resultstore

build:rbe_base --repo_env=BAZEL_DO_NOT_DETECT_CPP_TOOLCHAIN=1

build:rbe_base --define=EXECUTOR=remote

build:rbe_base --jobs=800

build:rbe_base --remote_executor=grpcs://remotebuildexecution.googleapis.com

build:rbe_base --remote_timeout=3600

build:rbe_base --spawn_strategy=remote,worker,standalone,local

# Attempt to minimize the amount of data transfer between bazel and the remote

# workers:

build:rbe_base --remote_download_toplevel

test:rbe_base --test_env=USER=anon

# TODO(kanglan): Check if we want to merge rbe_linux into rbe_linux_cpu.

build:rbe_linux --config=rbe_base

build:rbe_linux --action_env=PATH="/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/go/bin"

# Non-rbe settings we should include because we do not run configure

build:rbe_linux --config=avx_linux

# TODO(gunan): Check why we need this specified in rbe, but not in other builds.

build:rbe_linux --linkopt=-lrt

build:rbe_linux --host_linkopt=-lrt

build:rbe_linux --linkopt=-lm

build:rbe_linux --host_linkopt=-lm

build:rbe_linux_cpu --config=rbe_linux

# Linux cpu and cuda builds share the same toolchain now.

build:rbe_linux_cpu --host_crosstool_top="@sigbuild-r2.14-clang_config_cuda//crosstool:toolchain"

build:rbe_linux_cpu --crosstool_top="@sigbuild-r2.14-clang_config_cuda//crosstool:toolchain"

build:rbe_linux_cpu --extra_toolchains="@sigbuild-r2.14-clang_config_cuda//crosstool:toolchain-linux-x86_64"

build:rbe_linux_cpu --extra_execution_platforms="@sigbuild-r2.14-clang_config_platform//:platform"

build:rbe_linux_cpu --host_platform="@sigbuild-r2.14-clang_config_platform//:platform"

build:rbe_linux_cpu --platforms="@sigbuild-r2.14-clang_config_platform//:platform"

# This is needed for all Clang17 builds but must not be present in GCC builds.

build:rbe_linux_cpu --copt=-Wno-error=unused-command-line-argument

# This was added in clang-16 by https://reviews.llvm.org/D133574.

# Can be removed once upb is updated, since a type definition is used within

# offset of in the current version of ubp.

# See https://github.com/protocolbuffers/upb/blob/9effcbcb27f0a665f9f345030188c0b291e32482/upb/upb.c#L183.

build:rbe_linux_cpu --copt=-Wno-gnu-offsetof-extensions

# Python config is the same across all containers because the binary is the same

build:rbe_linux_cpu --repo_env=TF_PYTHON_CONFIG_REPO="@sigbuild-r2.14-clang_config_python"

build:rbe_linux_cpu --python_path="/usr/bin/python3"

# These you may need to change for your own GCP project.

common:rbe_linux_cpu --remote_instance_name=projects/tensorflow-testing/instances/default_instance

# TODO(kanglan): Remove it after toolchain update is complete.

build:rbe_linux_cpu_old --config=rbe_linux

build:rbe_linux_cpu_old --host_crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"

build:rbe_linux_cpu_old --crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"

build:rbe_linux_cpu_old --extra_toolchains="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain-linux-x86_64"

build:rbe_linux_cpu_old --extra_execution_platforms="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"

build:rbe_linux_cpu_old --host_platform="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"

build:rbe_linux_cpu_old --platforms="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"

build:rbe_linux_cpu_old --python_path="/usr/local/bin/python3.9"

build:rbe_linux_cpu_old --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.9"

common:rbe_linux_cpu_old --remote_instance_name=projects/tensorflow-testing/instances/default_instance

build:rbe_linux_cuda --config=cuda_clang_official

build:rbe_linux_cuda --config=rbe_linux_cpu

# For Remote build execution -- GPU configuration

build:rbe_linux_cuda --repo_env=REMOTE_GPU_TESTING=1

build:rbe_linux_cuda --repo_env=TF_CUDA_CONFIG_REPO="@sigbuild-r2.14-clang_config_cuda"

build:rbe_linux_cuda --repo_env=TF_TENSORRT_CONFIG_REPO="@sigbuild-r2.14-clang_config_tensorrt"

build:rbe_linux_cuda --repo_env=TF_NCCL_CONFIG_REPO="@sigbuild-r2.14-clang_config_nccl"

test:rbe_linux_cuda --test_env=LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"

# TODO(kanglan): Remove rbe_win and rbe_win_py3* after b/289091160 is fixed

build:rbe_win --config=rbe_base

build:rbe_win --crosstool_top="//tensorflow/tools/toolchains/win/tf_win_05022023:toolchain"

build:rbe_win --extra_toolchains="//tensorflow/tools/toolchains/win/tf_win_05022023:cc-toolchain-x64_windows"

build:rbe_win --extra_execution_platforms="//tensorflow/tools/toolchains/win:rbe_windows_ltsc2019"

build:rbe_win --host_platform="//tensorflow/tools/toolchains/win:rbe_windows_ltsc2019"

build:rbe_win --platforms="//tensorflow/tools/toolchains/win:rbe_windows_ltsc2019"

build:rbe_win --shell_executable=C:\\tools\\msys64\\usr\\bin\\bash.exe

build:rbe_win --experimental_strict_action_env=true

# TODO(gunan): Remove once we use MSVC 2019 with latest patches.

build:rbe_win --define=override_eigen_strong_inline=true

# Don't build the python zip archive in the RBE build.

build:rbe_win --remote_download_minimal

build:rbe_win --enable_runfiles

build:rbe_win --nobuild_python_zip

build:rbe_win_py38 --config=rbe_base

build:rbe_win_py38 --repo_env=PYTHON_BIN_PATH=C:\\Python38\\python.exe

build:rbe_win_py38 --repo_env=PYTHON_LIB_PATH=C:\\Python38\\lib\\site-packages

build:rbe_win_py38 --repo_env=TF_PYTHON_CONFIG_REPO=//tensorflow/tools/toolchains/win_1803/py38

build:rbe_win_py38 --python_path=C:\\Python38\\python.exe

build:rbe_win_py39 --config=rbe_base

build:rbe_win_py39 --repo_env=PYTHON_BIN_PATH=C:\\Python39\\python.exe

build:rbe_win_py39 --repo_env=PYTHON_LIB_PATH=C:\\Python39\\lib\\site-packages

build:rbe_win_py39 --repo_env=TF_PYTHON_CONFIG_REPO=//tensorflow/tools/toolchains/win_1803/py39

build:rbe_win_py39 --python_path=C:\\Python39\\python.exe

# TODO(kanglan): Merge tensorflow_testing_rbe_win into rbe_win

common:tensorflow_testing_rbe_win --remote_instance_name=projects/tensorflow-testing/instances/windows

# END TF REMOTE BUILD EXECUTION OPTIONS

# TFLite build configs for generic embedded Linux

build:elinux --crosstool_top=@local_config_embedded_arm//:toolchain

build:elinux --host_crosstool_top=@bazel_tools//tools/cpp:toolchain

build:elinux_aarch64 --config=elinux

build:elinux_aarch64 --cpu=aarch64

build:elinux_armhf --config=elinux

build:elinux_armhf --cpu=armhf

build:elinux_armhf --copt -mfp16-format=ieee

# Config-specific options should come above this line.

# Load rc file written by ./configure.

try-import %workspace%/.tf_configure.bazelrc

# Load rc file with user-specific options.

try-import %workspace%/.bazelrc.user

# Here are bazelrc configs for release builds

# Build TensorFlow v2.

test:release_base --test_size_filters=small,medium

# TODO(b/294367488) disable after 2.15 brancut

test:release_base --flaky_test_attempts=3

# Target the AVX instruction set

build:release_linux_base --config=avx_linux

# Disable clang extention that rejects type definitions within offsetof.

# This was added in clang-16 by https://reviews.llvm.org/D133574.

# Can be removed once upb is updated, since a type definition is used within

# offset of in the current version of ubp.

# See https://github.com/protocolbuffers/upb/blob/9effcbcb27f0a665f9f345030188c0b291e32482/upb/upb.c#L183.

build:release_linux_base --copt=-Wno-gnu-offsetof-extensions

build:release_linux_base --copt=-Wno-error=array-parameter

build:release_linux_base --copt=-Wno-error=unused-command-line-argument

# Set lld as the linker.

build:release_linux_base --linkopt="-fuse-ld=lld"

build:release_linux_base --linkopt="-lm"

# We have some invalid linker scripts in the build,

# so we need to disable this check

build:release_linux_base --linkopt=-Wl,--undefined-version

# Container environment settings below this point.

# Use Python 3.X as installed in container image

build:release_linux_base --action_env PYTHON_BIN_PATH="/usr/bin/python3"

build:release_linux_base --action_env PYTHON_LIB_PATH="/usr/lib/tf_python"

build:release_linux_base --python_path="/usr/bin/python3"

# Set Clang as compiler. Use the actual path to clang installed in container.

build:release_linux_base --repo_env=CC="/usr/lib/llvm-17/bin/clang"

build:release_linux_base --repo_env=BAZEL_COMPILER="/usr/lib/llvm-17/bin/clang"

# Store performance profiling log in the mounted artifact directory.

# The profile can be viewed by visiting chrome://tracing in a Chrome browser.

# See https://docs.bazel.build/versions/main/skylark/performance.html#performance-profiling

build:release_linux_base --profile=/tf/pkg/profile.json.gz

# Test-related settings below this point.

test:release_linux_base --build_tests_only --keep_going --test_output=errors --verbose_failures=true

test:release_linux_base --local_test_jobs=HOST_CPUS

test:release_linux_base --test_env=LD_LIBRARY_PATH

# Give only the list of failed tests at the end of the log

test:release_linux_base --test_summary=short

# Use the Clang toolchain to compile

build:release_cpu_linux --config=release_linux_base

build:release_cpu_linux --crosstool_top="@sigbuild-r2.14-clang_config_cuda//crosstool:toolchain"

build:release_gpu_linux --config=release_cpu_linux

# Set up compilation CUDA version and paths and use the CUDA Clang toolchain.

# Note that linux cpu and cuda builds share the same toolchain now.

build:release_gpu_linux --config=cuda_clang_official

test:release_gpu_linux --test_env=LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"

# Local test jobs has to be 4 because parallel_gpu_execute is fragile, I think

test:release_gpu_linux --test_timeout=300,450,1200,3600 --local_test_jobs=4 --run_under=//tensorflow/tools/ci_build/gpu_build:parallel_gpu_execute

build:release_arm64_linux --config=release_linux_base

build:release_arm64_linux --config=linux_arm64

build:release_arm64_linux --crosstool_top="@ml2014_clang_aarch64_config_aarch64//crosstool:toolchain"

build:release_arm64_linux --config=mkl_aarch64_threadpool

build:release_arm64_linux --copt=-flax-vector-conversions

# The old gcc linux build options are preserved in the unsupported_*_linux

# configs. If your project fails to build with Clang, you can use these

# unsupported flags to replace the release flags in your build command.

# However, please note that the old toolchain is no longer officially supported

# by TensorFlow and the unsupported configs will be removed soon b/299962977. We

# strongly recommend that you migrate to Clang as your compiler for TensorFlow

# Linux builds. Instructions are available in the official documentation:

# https://www.tensorflow.org/install/source#install_clang_recommended_linux_only

# Another good option is to use our Docker containers to build and test TF:

# https://github.com/tensorflow/tensorflow/tree/master/tensorflow/tools/tf_sig_build_dockerfiles.

build:unsupported_cpu_linux --config=avx_linux

build:unsupported_cpu_linux --crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"

test:unsupported_cpu_linux --test_env=LD_LIBRARY_PATH

test:unsupported_cpu_linux --config=release_base

build:unsupported_gpu_linux --config=cuda

build:unsupported_gpu_linux --config=unsupported_cpu_linux

build:unsupported_gpu_linux --action_env=TF_CUDA_VERSION="11"

build:unsupported_gpu_linux --action_env=TF_CUDNN_VERSION="8"

build:unsupported_gpu_linux --repo_env=TF_CUDA_COMPUTE_CAPABILITIES="sm_35,sm_50,sm_60,sm_70,sm_75,compute_80"

build:unsupported_gpu_linux --config=tensorrt

build:unsupported_gpu_linux --action_env=CUDA_TOOLKIT_PATH="/usr/local/cuda-11.2"

build:unsupported_gpu_linux --action_env=LD_LIBRARY_PATH="/usr/local/cuda:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda-11.1/lib64:/usr/local/tensorrt/lib"

build:unsupported_gpu_linux --action_env=GCC_HOST_COMPILER_PATH="/dt9/usr/bin/gcc"

build:unsupported_gpu_linux --crosstool_top=@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain

build:release_cpu_macos --config=avx_linux

test:release_cpu_macos --config=release_base

# TODO(kanglan): Update windows configs after b/289091160 is fixed

build:release_cpu_windows --config=avx_win

build:release_cpu_windows --define=no_tensorflow_py_deps=true

test:release_cpu_windows --config=release_base

# Exclude TFRT integration for anything but Linux.

build:android --config=no_tfrt

build:macos --config=no_tfrt

build:windows --config=no_tfrt

build:rocm --config=no_tfrt

build:no_tfrt --deleted_packages=tensorflow/compiler/mlir/tfrt,tensorflow/compiler/mlir/tfrt/benchmarks,tensorflow/compiler/mlir/tfrt/ir,tensorflow/compiler/mlir/tfrt/ir/mlrt,tensorflow/compiler/mlir/tfrt/jit/python_binding,tensorflow/compiler/mlir/tfrt/jit/transforms,tensorflow/compiler/mlir/tfrt/python_tests,tensorflow/compiler/mlir/tfrt/tests,tensorflow/compiler/mlir/tfrt/tests/mlrt,tensorflow/compiler/mlir/tfrt/tests/ir,tensorflow/compiler/mlir/tfrt/tests/analysis,tensorflow/compiler/mlir/tfrt/tests/jit,tensorflow/compiler/mlir/tfrt/tests/lhlo_to_tfrt,tensorflow/compiler/mlir/tfrt/tests/lhlo_to_jitrt,tensorflow/compiler/mlir/tfrt/tests/tf_to_corert,tensorflow/compiler/mlir/tfrt/tests/tf_to_tfrt_data,tensorflow/compiler/mlir/tfrt/tests/saved_model,tensorflow/compiler/mlir/tfrt/transforms/lhlo_gpu_to_tfrt_gpu,tensorflow/compiler/mlir/tfrt/transforms/mlrt,tensorflow/core/runtime_fallback,tensorflow/core/runtime_fallback/conversion,tensorflow/core/runtime_fallback/kernel,tensorflow/core/runtime_fallback/opdefs,tensorflow/core/runtime_fallback/runtime,tensorflow/core/runtime_fallback/util,tensorflow/core/runtime_fallback/test,tensorflow/core/runtime_fallback/test/gpu,tensorflow/core/runtime_fallback/test/saved_model,tensorflow/core/runtime_fallback/test/testdata,tensorflow/core/tfrt/stubs,tensorflow/core/tfrt/tfrt_session,tensorflow/core/tfrt/mlrt,tensorflow/core/tfrt/mlrt/attribute,tensorflow/core/tfrt/mlrt/kernel,tensorflow/core/tfrt/mlrt/bytecode,tensorflow/core/tfrt/mlrt/interpreter,tensorflow/compiler/mlir/tfrt/translate/mlrt,tensorflow/compiler/mlir/tfrt/translate/mlrt/testdata,tensorflow/core/tfrt/gpu,tensorflow/core/tfrt/run_handler_thread_pool,tensorflow/core/tfrt/runtime,tensorflow/core/tfrt/saved_model,tensorflow/core/tfrt/graph_executor,tensorflow/core/tfrt/saved_model/tests,tensorflow/core/tfrt/tpu,tensorflow/core/tfrt/utils,tensorflow/core/tfrt/utils/debug,tensorflow/core/tfrt/saved_model/python,tensorflow/core/tfrt/graph_executor/python,tensorflow/core/tfrt/saved_model/utils

# BEGIN TF CACHE HELPER OPTIONS

# Options when using remote execution

# WARNING: THESE OPTIONS WONT WORK IF YOU DO NOT HAVE PROPER AUTHENTICATION AND PERMISSIONS

# Use --config=tf_public_cache to try and use the TensorFlow public build cache

# to build TensorFlow. Look at ci/official/envs to find which types of jobs

# push to the cache.

build:tf_public_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/september2022" --remote_upload_local_results=false

# Cache pushes are limited to TF's CI system.

build:tf_public_cache_push --config=tf_public_cache --remote_upload_local_results=true --google_default_credentials

# END TF CACHE HELPER OPTIONS

# BEGIN TF TEST SUITE OPTIONS

# These are convenience config options that effectively declare TF's CI test suites. Look

# at the scripts of ci/official/ to see how TF's CI uses them.

# LIBTENSORFLOW TESTS are for building Libtensorflow archives. These are CUDA/CPU-agnostic.

test:linux_libtensorflow_test -- //tensorflow/tools/lib_package:libtensorflow_test //tensorflow/tools/lib_package:libtensorflow_java_test

build:linux_libtensorflow_build -- //tensorflow/tools/lib_package:libtensorflow.tar.gz //tensorflow/tools/lib_package:libtensorflow_jni.tar.gz //tensorflow/java:libtensorflow.jar //tensorflow/java:libtensorflow-src.jar //tensorflow/tools/lib_package:libtensorflow_proto.zip

# PYTHON TESTS run a suite of Python tests intended for verifying that the Python wheel

# will work properly. These are usually run Nightly or upon Release.

# CPU WHEEL

test:linux_cpu_wheel_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310

test:linux_cpu_wheel_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310

test:linux_cpu_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium

test:linux_cpu_wheel_test --config=linux_cpu_wheel_test_filters -- //tensorflow/... -//tensorflow/wheel/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/compiler/xrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/...

# CUDA WHEEL

test:linux_cuda_wheel_test_filters --test_tag_filters=gpu,requires-gpu,-no_gpu,-no_oss,-oss_excluded,-oss_serial,-no_cuda11,-no_oss_py38,-no_oss_py39,-no_oss_py310

test:linux_cuda_wheel_test_filters --build_tag_filters=gpu,requires-gpu,-no_gpu,-no_oss,-oss_excluded,-oss_serial,-no_cuda11,-no_oss_py38,-no_oss_py39,-no_oss_py310

test:linux_cuda_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium

test:linux_cuda_wheel_test --config=linux_cuda_wheel_test_filters -- //tensorflow/... -//tensorflow/wheel/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/compiler/xrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/...

# ARM64 WHEEL

test:linux_arm64_wheel_test_filters --test_tag_filters=-no_oss,-no_aarch64,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310

test:linux_arm64_wheel_test_filters --build_tag_filters=-no_oss,-no_aarch64,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310

test:linux_arm64_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium

test:linux_arm64_wheel_test --config=linux_arm64_wheel_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/compiler/xrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/core/grappler/optimizers:auto_mixed_precision_test_cpu -//tensorflow/core/grappler/optimizers:remapper_test_cpu -//tensorflow/core/kernels/image:resize_bicubic_op_test

# PYCPP TESTS run a suite of Python and C++ tests to verify general correctness over

# the whole TF code base. These are usually run continuously or upon presubmit.

# CPU PYCPP:

test:linux_cpu_pycpp_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only

test:linux_cpu_pycpp_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only

test:linux_cpu_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium

test:linux_cpu_pycpp_test --config=linux_cpu_pycpp_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/compiler/xrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/...

# CUDA PYCPP:

test:linux_cuda_pycpp_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-benchmark-test,-v1only,gpu,-no_gpu,-no_gpu_presubmit,-no_cuda11

test:linux_cuda_pycpp_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-benchmark-test,-v1only,gpu,-no_gpu,-no_gpu_presubmit,-no_cuda11

test:linux_cuda_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium

test:linux_cuda_pycpp_test --config=linux_cuda_pycpp_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/compiler/xrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/...

# ARM64 PYCPP

test:linux_arm64_pycpp_test_filters --test_tag_filters=-no_oss,-no_aarch64,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only

test:linux_arm64_pycpp_test_filters --build_tag_filters=-no_oss,-no_aarch64,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only

test:linux_arm64_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium --flaky_test_attempts=3

# TODO(michaelhudgins): Why do we need to specifically omit go and java here?

test:linux_arm64_pycpp_test --config=linux_arm64_pycpp_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/compiler/xrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/core/grappler/optimizers:auto_mixed_precision_test_cpu -//tensorflow/core/grappler/optimizers:remapper_test_cpu -//tensorflow/core/kernels/image:resize_bicubic_op_test

# END TF TEST SUITE OPTIONS