tensorflow/.bazelrc
A. Unique TensorFlower 55de680725 Delete remote python repository rule calls from TF configs.
Remote configurations of python repositories are removed because hermetic Python repository rules install and configure python modules in Bazel cache on the host machine. The cache is shared across host and remote machines.

PiperOrigin-RevId: 671512134
2024-09-05 14:39:55 -07:00

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# 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.
# nogcp: Disable GCS 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_base: General RBE options used on all Windows builds. Not to be used standalone.
# rbe_win_clang: Options specific to compiling using Clang.
#
# rbe_linux_cpu: RBE options to build with only CPU support.
# rbe_linux_cuda: RBE options to build with GPU support using clang.
# rbe_linux_cuda_nvcc: RBE options to build with GPU support using nvcc.
#
# 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
# 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 visibility 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
# Default CUDA and CUDNN versions.
build:cuda --repo_env=HERMETIC_CUDA_VERSION="12.3.2"
build:cuda --repo_env=HERMETIC_CUDNN_VERSION="9.3.0"
# This flag is needed to include CUDA libraries.
build:cuda --@local_config_cuda//cuda:include_cuda_libs=true
# This configuration is used for building the wheels.
build:cuda_wheel --@local_config_cuda//cuda:include_cuda_libs=false
# CUDA: This config refers to building CUDA op kernels with clang.
build:cuda_clang --config=cuda
build:cuda_clang --@local_config_cuda//:cuda_compiler=clang
build:cuda_clang --copt=-Qunused-arguments
# Select supported compute capabilities (supported graphics cards).
# This is the same as the official TensorFlow builds.
# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX
# is forward compatible beyond the current compute capability major
# release while SASS is only forward compatible inside the current
# major release. Example: sm_80 kernels can run on sm_89 GPUs but
# not on sm_90 GPUs. compute_80 kernels though can also run on sm_90 GPUs.
build:cuda_clang --repo_env=HERMETIC_CUDA_COMPUTE_CAPABILITIES="sm_60,sm_70,sm_80,sm_89,compute_90"
# Set lld as the linker.
build:cuda_clang --host_linkopt="-fuse-ld=lld"
build:cuda_clang --host_linkopt="-lm"
build:cuda_clang --linkopt="-fuse-ld=lld"
build:cuda_clang --linkopt="-lm"
# Set up compilation CUDA version and paths and use the CUDA Clang toolchain.
build:cuda_clang_official --config=cuda_clang
build:cuda_clang_official --repo_env=HERMETIC_CUDA_VERSION="12.3.2"
build:cuda_clang_official --repo_env=HERMETIC_CUDNN_VERSION="9.3.0"
build:cuda_clang_official --action_env=CLANG_CUDA_COMPILER_PATH="/usr/lib/llvm-18/bin/clang"
build:cuda_clang_official --crosstool_top="@local_config_cuda//crosstool:toolchain"
# Build with nvcc for CUDA and clang for host
build:nvcc_clang --config=cuda
build:nvcc_clang --action_env=TF_NVCC_CLANG="1"
build:nvcc_clang --@local_config_cuda//:cuda_compiler=nvcc
# 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
build:sycl --crosstool_top=@local_config_sycl//crosstool:toolchain
build:sycl --define=using_sycl=true
build:sycl --define=tensorflow_mkldnn_contraction_kernel=0
build:sycl --repo_env TF_NEED_SYCL=1
# Options to disable default on features
build:nogcp --define=no_gcp_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++ compiler 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
# Before VS 2017 15.8, the member "type" would non-conformingly have an
# alignment of only alignof(max_align_t). VS 2017 15.8 was fixed to handle this
# correctly, but the fix inherently changes layout and breaks binary
# compatibility (*only* for uses of aligned_storage with extended alignments).
build:windows --copt=-D_ENABLE_EXTENDED_ALIGNED_STORAGE
build:windows --host_copt=-D_ENABLE_EXTENDED_ALIGNED_STORAGE
# 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
# Use Clang-cl compiler on Windows
build:win_clang --copt=/clang:-Weverything
build:win_clang --extra_toolchains=@local_config_cc//:cc-toolchain-x64_windows-clang-cl
build:win_clang --extra_execution_platforms=//tensorflow/tools/toolchains/win:x64_windows-clang-cl
build:win_clang --host_platform=//tensorflow/tools/toolchains/win:x64_windows-clang-cl
build:win_clang --compiler=clang-cl
build:win_clang --linkopt=/FORCE:MULTIPLE
build:win_clang --host_linkopt=/FORCE:MULTIPLE
test:win_clang --linkopt=/FORCE:MULTIPLE
test:win_clang --host_linkopt=/FORCE:MULTIPLE
# Same config as above but for XLA, which has different toolchain paths
build:win_clang_xla --copt=/clang:-Weverything
build:win_clang_xla --extra_toolchains=@local_config_cc//:cc-toolchain-x64_windows-clang-cl
build:win_clang_xla --extra_execution_platforms=//tools/toolchains/win:x64_windows-clang-cl
build:win_clang_xla --host_platform=//tools/toolchains/win:x64_windows-clang-cl
build:win_clang_xla --compiler=clang-cl
build:win_clang_xla --linkopt=/FORCE:MULTIPLE
build:win_clang_xla --host_linkopt=/FORCE:MULTIPLE
test:win_clang_xla --action_env=PATHEXT=.COM;.EXE;.BAT;.CMD;.VBS;.VBE;.JS;.JSE;.WSF;.WSH;.MSC;.PY;.PYW
test:win_clang_xla --linkopt=/FORCE:MULTIPLE
test:win_clang_xla --host_linkopt=/FORCE:MULTIPLE
# 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
# Enable all targets in XLA
build:cpu_cross --define=with_cross_compiler_support=true
# 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="@local_config_cuda//crosstool:toolchain"
build:rbe_linux_cpu --crosstool_top="@local_config_cuda//crosstool:toolchain"
build:rbe_linux_cpu --extra_toolchains="@local_config_cuda//crosstool:toolchain-linux-x86_64"
build:rbe_linux_cpu --repo_env=CC="/usr/lib/llvm-18/bin/clang"
build:rbe_linux_cpu --repo_env=TF_SYSROOT="/dt9"
build:rbe_linux_cpu --extra_execution_platforms="@sigbuild-r2.17-clang_config_platform//:platform"
build:rbe_linux_cpu --host_platform="@sigbuild-r2.17-clang_config_platform//:platform"
build:rbe_linux_cpu --platforms="@sigbuild-r2.17-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 --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"
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_nvcc --config=rbe_linux_cuda
build:rbe_linux_cuda_nvcc --config=nvcc_clang
build:rbe_linux_cuda_nvcc --repo_env TF_NCCL_USE_STUB=1
build:rbe_win_base --config=rbe_base
build:rbe_win_base --shell_executable=C:\\tools\\msys64\\usr\\bin\\bash.exe
build:rbe_win_base --remote_instance_name=projects/tensorflow-testing/instances/windows
# Don't build the python zip archive in the RBE build.
build:rbe_win_base --remote_download_minimal
build:rbe_win_base --enable_runfiles
build:rbe_win_base --nobuild_python_zip
build:rbe_win_base --define=override_eigen_strong_inline=true
build:rbe_win_clang --config=rbe_win_base
build:rbe_win_clang --crosstool_top="//tensorflow/tools/toolchains/win/20240424:toolchain"
build:rbe_win_clang --extra_toolchains="//tensorflow/tools/toolchains/win/20240424:cc-toolchain-x64_windows-clang-cl"
build:rbe_win_clang --extra_execution_platforms="//tensorflow/tools/toolchains/win:x64_windows-clang-cl"
build:rbe_win_clang --host_platform="//tensorflow/tools/toolchains/win:x64_windows-clang-cl"
build:rbe_win_clang --platforms="//tensorflow/tools/toolchains/win:x64_windows-clang-cl"
build:rbe_win_clang --compiler=clang-cl
build:rbe_win_clang --linkopt=/FORCE:MULTIPLE
build:rbe_win_clang --host_linkopt=/FORCE:MULTIPLE
# TODO(belitskiy): Rename `rbe_win_clang` to this, once done switching presubmits.
build:rbe_windows_x86_cpu --config=rbe_win_clang
# 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
try-import %workspace%/xla_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
# Enable support for all targets
build:release_base --config=cpu_cross
# Ensure release_base is set on linux
build:release_linux_base --config=release_base
# Disable clang extension 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-18/bin/clang"
build:release_linux_base --repo_env=BAZEL_COMPILER="/usr/lib/llvm-18/bin/clang"
# 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
# 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="@local_config_cuda//crosstool:toolchain"
build:release_cpu_linux --repo_env=TF_SYSROOT="/dt9"
# Target the AVX instruction set
build:release_cpu_linux --config=avx_linux
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
# 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
test:release_arm64_linux --flaky_test_attempts=3
# 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 --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"
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
# Base build configs for macOS
build:release_macos_base --action_env DEVELOPER_DIR=/Applications/Xcode.app/Contents/Developer
build:release_macos_base --define=no_nccl_support=true --output_filter=^$
# Ensure release_base is set on mac
build:release_macos_base --config=release_base
# Build configs for macOS x86
build:release_macos_x86 --config=release_macos_base
# Build with the AVX instruction set when on macOS x86
build:release_macos_x86 --config=avx_linux
build:release_macos_x86 --cpu=darwin
# Target Catalina as the minimum compatible OS version
build:release_macos_x86 --macos_minimum_os=10.15
build:release_macos_x86 --action_env MACOSX_DEPLOYMENT_TARGET=10.15
# Build configs for macOS Arm64
build:release_macos_arm64 --config=release_macos_base
build:release_macos_arm64 --cpu=darwin_arm64
build:release_macos_arm64 --define=tensorflow_mkldnn_contraction_kernel=0
# Target Moneterey as the minimum compatible OS version
build:release_macos_arm64 --macos_minimum_os=12.0
build:release_macos_arm64 --action_env MACOSX_DEPLOYMENT_TARGET=12.0
# Base test configs for macOS
test:release_macos_base --verbose_failures=true --local_test_jobs=HOST_CPUS
test:release_macos_base --test_timeout=300,450,1200,3600 --test_output=errors
test:release_macos_base --build_tests_only --keep_going
test:release_macos_base --flaky_test_attempts=3
# Test configs for macOS x86
test:release_macos_x86 --config=release_macos_base
# Test configs for macOS Arm64
test:release_macos_arm64 --config=release_macos_base
# Ensure release_base is set on windows
build:release_cpu_windows --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
# 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/ifrt,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. For macOS, use --config=tf_public_macos_cache
build:tf_public_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/january2024" --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
# Public cache for macOS builds
build:tf_public_macos_cache --remote_cache="https://storage.googleapis.com/tensorflow-macos-bazel-cache/oct2023" --remote_upload_local_results=false
# Cache pushes are limited to TF's CI system.
build:tf_public_macos_cache_push --config=tf_public_macos_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 --config=cuda_wheel -- //tensorflow/tools/lib_package:libtensorflow_test //tensorflow/tools/lib_package:libtensorflow_java_test
build:linux_libtensorflow_build --config=cuda_wheel -- //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/compiler/tf2tensorrt/... -//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,-benchmark-test,-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,-benchmark-test,-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/compiler/tf2tensorrt/... -//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/compiler/tf2tensorrt/... -//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 -//tensorflow/compiler/mlir/tfr/examples/customization:test_ops_test -//tensorflow/compiler/mlir/tfr/examples/mnist:mnist_ops_test -//tensorflow/compiler/mlir/tfr/examples/pad:pad_ops_test
# MACOS ARM64 WHEEL
test:macos_arm64_wheel_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test,-no_mac_arm64,-no_aarch64
test:macos_arm64_wheel_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test,-no_mac_arm64,-no_aarch64
test:macos_arm64_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium
test:macos_arm64_wheel_test --config=macos_arm64_wheel_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/compiler/aot/...
# MACOS X86 WHEEL
test:macos_x86_wheel_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py38,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test
test:macos_x86_wheel_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py38,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test
test:macos_x86_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium
test:macos_x86_wheel_test --config=macos_x86_wheel_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/compiler/aot/...
# 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.
# LINUX 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/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/...
# LINUX 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/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/...
# LINUX ARM64 PYCPP
# In Linux Arm64 presubmit/continuous build, we cross-compile the binaries on
# Linux x86 so that we can use RBE. Since tests still need to run on the single
# host Arm64 machine, the build becomes too slow (~30 min) to be a presubmit.
# For testing purposes, we want to see the runtime performance of an
# experimental job that is build-only, i.e, we only build the test targets and
# do not run them. By prefixing the configs with "build", we can run both
# `bazel build` and `bazel test` commands with the same config as test configs
# inherit from build.
build:linux_arm64_pycpp_test_filters --test_tag_filters=-no_oss,-no_aarch64,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only
build:linux_arm64_pycpp_test_filters --build_tag_filters=-no_oss,-no_aarch64,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only
build: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?
build:linux_arm64_pycpp_test --config=linux_arm64_pycpp_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//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 -//tensorflow/compiler/mlir/tfr/examples/customization:test_ops_test -//tensorflow/compiler/mlir/tfr/examples/mnist:mnist_ops_test -//tensorflow/compiler/mlir/tfr/examples/pad:pad_ops_test -//tensorflow/python/tools:aot_compiled_test
# CROSS-COMPILE ARM64 PYCPP
build:cross_compile_linux_arm64_pycpp_test --config=linux_arm64_pycpp_test
# Tests that fail only when cross-compiled
build:cross_compile_linux_arm64_pycpp_test -//tensorflow/compiler/mlir/quantization/stablehlo:convert_tf_quant_to_mhlo_int_test
# MACOS ARM64 PYCPP
test:macos_arm64_pycpp_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test,-no_mac_arm64,-no_aarch64
test:macos_arm64_pycpp_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test,-no_mac_arm64,-no_aarch64
test:macos_arm64_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium
test:macos_arm64_pycpp_test --config=macos_arm64_pycpp_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/compiler/aot/... -//tensorflow/core/kernels/image:resize_bicubic_op_test
# MACOS X86 PYCPP
# These are defined as build configs so that we can run a build only job. See
# the note under "ARM64 PYCPP" for more details.
build:macos_x86_pycpp_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py38,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test
build:macos_x86_pycpp_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py38,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test
build:macos_x86_pycpp_test_filters --keep_going --test_lang_filters=cc,py --test_size_filters=small,medium
build:macos_x86_pycpp_test --config=macos_x86_pycpp_test_filters -- //tensorflow/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/tools/toolchains/... -//tensorflow/lite/... -//tensorflow/compiler/aot/...
# CROSS-COMPILE MACOS X86 PYCPP
build:cross_compile_macos_x86_pycpp_test --config=macos_x86_pycpp_test
build:cross_compile_macos_x86_pycpp_test -//tensorflow/core/kernels:quantized_conv_ops_test -//tensorflow/core/kernels:quantized_matmul_op_test -//tensorflow/python/ops:quantized_conv_ops_test -//tensorflow/tools/graph_transforms:transforms_test -//tensorflow/python/tools:aot_compiled_test
# WINDOWS X86-64 CPU PYCPP
test:windows_x86_cpu_pycpp_test_filters --test_tag_filters=-no_windows,-windows_excluded,-no_oss,-oss_excluded,-gpu,-tpu,-benchmark-test
test:windows_x86_cpu_pycpp_test_filters --build_tag_filters=-no_windows,-windows_excluded,-no_oss,-oss_excluded,-benchmark-test
test:windows_x86_cpu_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium --test_timeout="300,450,1200,3600"
test:windows_x86_cpu_pycpp_test_opts --copt=/d2ReducedOptimizeHugeFunctions --host_copt=/d2ReducedOptimizeHugeFunctions --dynamic_mode=off --build_tests_only
test:windows_x86_cpu_pycpp_test --config=windows_x86_cpu_pycpp_test_opts --config=windows_x86_cpu_pycpp_test_filters -- //tensorflow/... -//tensorflow/java/... -//tensorflow/lite/... -//tensorflow/compiler/...
# END TF TEST SUITE OPTIONS
# START CROSS-COMPILE CONFIGS
# Set execution platform to Linux x86
# Note: Lot of the "host_" flags such as "host_cpu" and "host_crosstool_top"
# flags seem to be actually used to specify the execution platform details. It
# seems it is this way because these flags are old and predate the distinction
# between host and execution platform.
build:cross_compile_base --host_cpu=k8
build:cross_compile_base --host_crosstool_top=//tensorflow/tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite
build:cross_compile_base --extra_execution_platforms=//tensorflow/tools/toolchains/cross_compile/config:linux_x86_64
# XLA related settings for cross-compiled build. Certain paths are
# different in the XLA repo.
build:cross_compile_base_xla --host_cpu=k8
build:cross_compile_base_xla --host_crosstool_top=//tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite
build:cross_compile_base_xla --extra_execution_platforms=//tools/toolchains/cross_compile/config:linux_x86_64
build:rbe_cross_compile_base --config=rbe_base
build:rbe_cross_compile_base --remote_instance_name=projects/tensorflow-testing/instances/default_instance
# XLA depends on some local Python headers that are configured as Genrule. They
# are present on the local host machine but not on the remote execution machine,
# leading to build failures. To resolve the issue, the following line is added
# to make sure all Genrule targets are excuted locally.
build:rbe_cross_compile_base_xla --config=rbe_cross_compile_base
build:rbe_cross_compile_base_xla --strategy=Genrule=standalone
# Due to the above strategy, all Genrule commands are executed locally, but the
# following actions invoke tools (E.g `flatc`, `llvm-tblgen`, etc.) that are
# only executabe on the RBE (x86) machine, so the strategy_regexp options are
# added to override and run the actions using remote strategy.
build:rbe_cross_compile_base_xla --strategy_regexp='Generating code from table.*=remote'
build:rbe_cross_compile_base_xla --strategy_regexp='Generating flatbuffer files.*=remote'
build:rbe_cross_compile_base_xla --strategy_regexp='Executing genrule @llvm-project.*=remote'
# Test-related settings below this point
# We cannot run cross-compiled tests on the remote Linux x86 VMs so we need to
# force all tests to run locally on the Aarch64 host.
test:rbe_cross_compile_base --strategy=TestRunner=local --build_tests_only
test:rbe_cross_compile_base --verbose_failures=true --local_test_jobs=HOST_CPUS --test_output=errors
test:rbe_cross_compile_base_xla --config=rbe_cross_compile_base
# START LINUX AARCH64 CROSS-COMPILE CONFIGS
build:cross_compile_linux_arm64 --config=cross_compile_base
# Set the target CPU to Aarch64
build:cross_compile_linux_arm64 --platforms=//tensorflow/tools/toolchains/cross_compile/config:linux_aarch64
build:cross_compile_linux_arm64 --cpu=aarch64
build:cross_compile_linux_arm64 --crosstool_top=//tensorflow/tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite
# XLA uses different paths for platforms and crosstool_top.
build:cross_compile_linux_arm64_xla --config=cross_compile_base_xla
build:cross_compile_linux_arm64_xla --platforms=//tools/toolchains/cross_compile/config:linux_aarch64
build:cross_compile_linux_arm64_xla --crosstool_top=//tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite
# RBE cross-compile configs for Linux Aarch64
build:rbe_cross_compile_linux_arm64 --config=cross_compile_linux_arm64
build:rbe_cross_compile_linux_arm64 --config=rbe_cross_compile_base
test:rbe_cross_compile_linux_arm64 --config=rbe_cross_compile_base
# RBE cross-compile configs for XLA Linux Aarch64
build:rbe_cross_compile_linux_arm64_xla --config=cross_compile_linux_arm64_xla
build:rbe_cross_compile_linux_arm64_xla --config=rbe_cross_compile_base_xla
test:rbe_cross_compile_linux_arm64_xla --config=rbe_cross_compile_base_xla
# END LINUX AARCH64 CROSS-COMPILE CONFIGS
# START MACOS CROSS-COMPILE CONFIGS
build:cross_compile_macos_x86 --config=cross_compile_base
build:cross_compile_macos_x86 --config=nonccl
# Target Catalina (10.15) as the minimum supported OS
build:cross_compile_macos_x86 --action_env MACOSX_DEPLOYMENT_TARGET=10.15
# Set the target CPU to Darwin x86
build:cross_compile_macos_x86 --platforms=//tensorflow/tools/toolchains/cross_compile/config:darwin_x86_64
build:cross_compile_macos_x86 --cpu=darwin
build:cross_compile_macos_x86 --crosstool_top=//tensorflow/tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite
# When RBE cross-compiling for macOS, we need to explicitly register the
# toolchain. Otherwise, oddly, RBE complains that a "docker container must be
# specified".
build:cross_compile_macos_x86 --extra_toolchains=//tensorflow/tools/toolchains/cross_compile/config:macos-x86-cross-compile-cc-toolchain
# Map --platforms=darwin_x86_64 to --cpu=darwin and vice-versa to make selects()
# and transistions that use these flags work.
build:cross_compile_macos_x86 --platform_mappings=tensorflow/tools/toolchains/cross_compile/config/platform_mappings
# RBE cross-compile configs for Darwin x86
build:rbe_cross_compile_macos_x86 --config=cross_compile_macos_x86 --remote_download_minimal
build:rbe_cross_compile_macos_x86 --bes_backend="" --bes_results_url="" --bes_timeout="0s"
build:rbe_cross_compile_macos_x86 --experimental_remote_build_event_upload="minimal"
build:rbe_cross_compile_macos_x86 --config=rbe_cross_compile_base
build:rbe_cross_compile_macos_x86 --bes_upload_mode=nowait_for_upload_complete
test:rbe_cross_compile_macos_x86 --config=rbe_cross_compile_base
# Increase the test timeout as tests often take longer on mac.
test:rbe_cross_compile_macos_x86 --test_timeout=300,450,1200,3600
# Limit jobs to 100 to avoid running into "out of memory" issues (b/316266643)
build:rbe_cross_compile_macos_x86 --jobs=100
test:rbe_cross_compile_macos_x86 --jobs=100
# END MACOS CROSS-COMPILE CONFIGS
# END CROSS-COMPILE CONFIGS
# Try to load the XLA warnings config if available
try-import %workspace%/warnings.bazelrc