.bazelrc

# 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_i386:
#     ios_x86_64:
#     ios_fat:
#
# Macosx options
#     darwin_arm64:
#
# Compiler options:
#     cuda_clang:             Use clang when building CUDA code.
#     c++17:                  Build with C++17 options (links with libc++)
#     c++1z:                  Build with C++17 options (links with libc++)
#     c++17_gcc:              Build with C++17 options (links with stdlibc++)
#     c++1z_gcc:              Build with C++17 options (links with stdlibc++)
#     avx_linux:              Build with avx instruction set on linux.
#     avx2_linux:             Build with avx2 instruction set on linux.
#     native_arch_linux:      Build with instruction sets available to the host machine on linux
#     avx_win:                Build with avx instruction set on windows
#     avx2_win:               Build with avx2 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).
#     libc++:           Link against libc++ instead of stdlibc++
#     asan:             Build with the clang address sanitizer
#     msan:             Build with the clang memory sanitizer
#     ubsan:            Build with the clang undefined behavior sanitizer
#     dbg:              Build with debug info
#
#
# TF version options;
#     v1: Build TF V1 (without contrib)
#     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 full cuda support.
#     rocm:         Build with AMD GPU support (rocm).
#     mkl:          Enable full mkl support.
#     tensorrt:     Enable Tensorrt support.
#     numa:         Enable numa using hwloc.
#     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:       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_cpu_linux:                  RBE options to build with only CPU support.
#     rbe_cpu_linux_ml2014:           RBE options to build with only CPU support (manylinux2014 compatible).
#     rbe_linux_cuda_nvcc_py*:        RBE options to build with GPU support using nvcc.
#     rbe_linux_cuda_nvcc_py39_ml2014 RBE options to build with GPU support using nvcc (manylinux2014 compatible).
#
#     rbe_linux_py3:        Linux Python 3 RBE config
#     rbe_linux_py3_ml2014: Linux Python 3 RBE config (manylinux2014 compatible)
#
#     rbe_win_py37: Windows Python 3.7 RBE config
#     rbe_win_py38: Windows Python 3.8 RBE config
#     rbe_win_py39: Windows Python 3.9 RBE config
#     rbe_win_py310: Windows Python 3.10 RBE config
#
#     tensorflow_testing_rbe_linux: RBE options to use RBE with tensorflow-testing project on linux
#     tensorflow_testing_rbe_win:   RBE options to use RBE with tensorflow-testing project on windows
#
#     rbe_lite_linux: RBE options to build TF Lite.
#
# 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_gpu_base:                Common options for GPU builds on Linux and Windows.
#     release_cpu_linux:               Toolchain and CUDA options for Linux CPU builds.
#     release_cpu_linux_manylinux2014: Toolchain and CUDA options for Linux CPU builds (manylinux2014 compatible).
#     release_cpu_macos:               Toolchain and CUDA options for MacOS CPU builds.
#     release_gpu_linux:               Toolchain and CUDA options for Linux GPU builds.
#     release_gpu_linux_manylinux2014: Toolchain and CUDA options for Linux GPU builds (manylinux2014 compatible).
#     release_cpu_windows:             Toolchain and CUDA options for Windows CPU builds.
#     release_gpu_windows:             Toolchain and CUDA options for Windows GPU 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=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 this line once TF doesn't depend on Bazel wrapping all library
# archives in -whole_archive -no_whole_archive.
build --noincompatible_remove_legacy_whole_archive

# 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

# Default options should come above this line.

# Allow builds using libc++ as a linker library
# This is mostly for OSSFuzz, so we also pass in the flags from environment to clean build file
build:libc++ --action_env=CC
build:libc++ --action_env=CXX
build:libc++ --action_env=CXXFLAGS=-stdlib=libc++
build:libc++ --action_env=PATH
build:libc++ --define force_libcpp=enabled
build:libc++ --linkopt -fuse-ld=lld

# Android configs. Bazel needs to have --cpu and --fat_apk_cpu both set to the
# target CPU to build transient dependencies correctly. See
# https://docs.bazel.build/versions/master/user-manual.html#flag--fat_apk_cpu
build:android --crosstool_top=//external:android/crosstool
build:android --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
build:android_arm --config=android
build:android_arm --cpu=armeabi-v7a
build:android_arm --fat_apk_cpu=armeabi-v7a
build:android_arm64 --config=android
build:android_arm64 --cpu=arm64-v8a
build:android_arm64 --fat_apk_cpu=arm64-v8a
build:android_x86 --config=android
build:android_x86 --cpu=x86
build:android_x86 --fat_apk_cpu=x86
build:android_x86_64 --config=android
build:android_x86_64 --cpu=x86_64
build:android_x86_64 --fat_apk_cpu=x86_64

# Sets the default Apple platform to macOS.
build:macos --apple_platform_type=macos

# gRPC on MacOS requires this #define
build:macos --copt=-DGRPC_BAZEL_BUILD

# Settings for MacOS on ARM CPUs.
build:macos_arm64 --cpu=darwin_arm64

# 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_i386 --config=ios
build:ios_i386 --cpu=ios_i386
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

# Please note that MKL on MacOS or windows is still not supported.
# If you would like to use a local MKL instead of downloading, please set the
# environment variable "TF_MKL_ROOT" every time before build.
build:mkl --define=build_with_mkl=true --define=enable_mkl=true
build:mkl --define=tensorflow_mkldnn_contraction_kernel=0
build:mkl --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).
# This build is for the inference regime only.
build:mkl_aarch64 --define=build_with_mkl_aarch64=true
build:mkl_aarch64 --define=tensorflow_mkldnn_contraction_kernel=0
build:mkl_aarch64 --define=build_with_openmp=true
build:mkl_aarch64 -c opt

# 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

# This config refers to building CUDA op kernels with clang.
build:cuda_clang --config=cuda
build:cuda_clang --repo_env TF_CUDA_CLANG=1
build:cuda_clang --@local_config_cuda//:cuda_compiler=clang

# 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
build:dbg --per_file_copt=+.*,-tensorflow.*@-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 TPU backend
build:tpu --define=with_tpu_support=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 extracted from configure script
build:numa --define=with_numa_support=true

# Options to disable default on features
build:noaws --define=no_aws_support=true
build:nogcp --define=no_gcp_support=true
build:nohdfs --define=no_hdfs_support=true
build:nonccl --define=no_nccl_support=true

build:stackdriver_support --define=stackdriver_support=true

# Modular TF build options
build:dynamic_kernels --define=dynamic_loaded_kernels=true
build:dynamic_kernels --copt=-DAUTOLOAD_DYNAMIC_KERNELS

# Build TF with C++ 17 features.
build:c++17 --cxxopt=-std=c++1z
build:c++17 --cxxopt=-stdlib=libc++
build:c++1z --config=c++17
build:c++17_gcc --cxxopt=-std=c++1z
build:c++1z_gcc --config=c++17_gcc

# Don't trigger --config=<host platform> when cross-compiling.
build:android --noenable_platform_specific_config
build:ios --noenable_platform_specific_config

# Suppress C++ compiler warnings, otherwise build logs become 10s of MBs.
build:android --copt=-w
build:ios --copt=-w
build:linux --copt=-w
build:linux --host_copt=-w
build:macos --copt=-w
build:windows --copt=/W0

# 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

# 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++ 14 mode.
build:android --cxxopt=-std=c++14
build:android --host_cxxopt=-std=c++14
build:ios --cxxopt=-std=c++14
build:ios --host_cxxopt=-std=c++14
build:linux --cxxopt=-std=c++17
build:linux --host_cxxopt=-std=c++17
build:linux --copt=-pthread
build:macos --cxxopt=-std=c++17
build:macos --host_cxxopt=-std=c++17
build:macos --copt=-pthread
build:windows --cxxopt=/std:c++14
build:windows --host_cxxopt=/std:c++14

# 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=/experimental:preprocessor
build:windows --host_copt=/experimental: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

# On windows, we never cross compile
build:windows --distinct_host_configuration=false
# On linux, don't cross compile by default
build:linux --distinct_host_configuration=false

# 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:avx2_linux --copt=-mavx2
build:native_arch_linux --copt=-march=native
build:avx_win --copt=/arch=AVX
build:avx2_win --copt=/arch=AVX2

# Options to build TensorFlow 1.x or 2.x.
build:v1 --define=tf_api_version=1 --action_env=TF2_BEHAVIOR=0
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

# Flag to enable remote config
common --experimental_repo_remote_exec

build:rbe --repo_env=BAZEL_DO_NOT_DETECT_CPP_TOOLCHAIN=1
build:rbe --google_default_credentials
build:rbe --bes_backend=buildeventservice.googleapis.com
build:rbe --bes_results_url="https://source.cloud.google.com/results/invocations"
build:rbe --bes_timeout=600s
build:rbe --define=EXECUTOR=remote
build:rbe --distinct_host_configuration=false
build:rbe --flaky_test_attempts=3
build:rbe --jobs=200
build:rbe --remote_executor=grpcs://remotebuildexecution.googleapis.com
build:rbe --remote_timeout=3600
build:rbe --spawn_strategy=remote,worker,standalone,local
test:rbe --test_env=USER=anon
# Attempt to minimize the amount of data transfer between bazel and the remote
# workers:
build:rbe --remote_download_toplevel

build:rbe_linux_base --config=rbe
build:rbe_linux_base --action_env=PATH="/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/go/bin"

build:rbe_linux --config=rbe_linux_base
# 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

# Use the GPU toolchain until the CPU one is ready.
# https://github.com/bazelbuild/bazel/issues/13623
build:rbe_cpu_linux_base --host_crosstool_top="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
build:rbe_cpu_linux_base --crosstool_top="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
build:rbe_cpu_linux_base --extra_toolchains="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain-linux-x86_64"
build:rbe_cpu_linux_base --extra_execution_platforms="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_cpu_linux_base --host_platform="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_cpu_linux_base --platforms="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"

build:rbe_cpu_linux --config=rbe_linux
build:rbe_cpu_linux --config=rbe_cpu_linux_base

# rbe config option that uses the manylinux2014 toolchain
build:rbe_cpu_linux_ml2014 --config=rbe_linux
build:rbe_cpu_linux_ml2014 --host_crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
build:rbe_cpu_linux_ml2014 --crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
build:rbe_cpu_linux_ml2014 --extra_toolchains="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain-linux-x86_64"
build:rbe_cpu_linux_ml2014 --extra_execution_platforms="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_cpu_linux_ml2014 --host_platform="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_cpu_linux_ml2014 --platforms="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"

build:rbe_lite_linux --config=rbe_linux_base
build:rbe_lite_linux --config=rbe_cpu_linux_base
build:rbe_lite_linux --config=rbe_linux_py3_base
build:rbe_lite_linux --noexperimental_check_desugar_deps

build:rbe_linux_cuda_base --config=rbe_linux
build:rbe_linux_cuda_base --config=cuda
build:rbe_linux_cuda_base --config=tensorrt
build:rbe_linux_cuda_base --action_env=TF_CUDA_VERSION=11
build:rbe_linux_cuda_base --action_env=TF_CUDNN_VERSION=8
build:rbe_linux_cuda_base --repo_env=REMOTE_GPU_TESTING=1
# TensorRT 7 for CUDA 11.1 is compatible with CUDA 11.2, but requires
# libnvrtc.so.11.1. See https://github.com/NVIDIA/TensorRT/issues/1064.
# TODO(b/187962120): Remove when upgrading to TensorRT 8.
test:rbe_linux_cuda_base --test_env=LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda-11.1/lib64"

build:rbe_linux_cuda11.2_nvcc_base --config=rbe_linux_cuda_base
build:rbe_linux_cuda11.2_nvcc_base --host_crosstool_top="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
build:rbe_linux_cuda11.2_nvcc_base --crosstool_top="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
build:rbe_linux_cuda11.2_nvcc_base --extra_toolchains="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain-linux-x86_64"
build:rbe_linux_cuda11.2_nvcc_base --extra_execution_platforms="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_linux_cuda11.2_nvcc_base --host_platform="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_linux_cuda11.2_nvcc_base --platforms="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_linux_cuda11.2_nvcc_base --repo_env=TF_CUDA_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda"
build:rbe_linux_cuda11.2_nvcc_base --repo_env=TF_TENSORRT_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_tensorrt"
build:rbe_linux_cuda11.2_nvcc_base --repo_env=TF_NCCL_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_nccl"
build:rbe_linux_cuda11.2_nvcc_py3.7 --config=rbe_linux_cuda11.2_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.7"
build:rbe_linux_cuda11.2_nvcc_py3.8 --config=rbe_linux_cuda11.2_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.8"
build:rbe_linux_cuda11.2_nvcc_py3.9 --config=rbe_linux_cuda11.2_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.9"
build:rbe_linux_cuda11.2_nvcc_py3.10 --config=rbe_linux_cuda11.2_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.10"

# Map default to CUDA 11.2.
build:rbe_linux_cuda_nvcc_py37 --config=rbe_linux_cuda11.2_nvcc_py3.7
build:rbe_linux_cuda_nvcc_py38 --config=rbe_linux_cuda11.2_nvcc_py3.8
build:rbe_linux_cuda_nvcc_py39 --config=rbe_linux_cuda11.2_nvcc_py3.9
build:rbe_linux_cuda_nvcc_py310 --config=rbe_linux_cuda11.2_nvcc_py3.10

# RBE gpu config for manylinux2014
build:rbe_linux_cuda_nvcc_py39_ml2014 --config=rbe_linux_cuda_base
build:rbe_linux_cuda_nvcc_py39_ml2014 --host_crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
build:rbe_linux_cuda_nvcc_py39_ml2014 --crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
build:rbe_linux_cuda_nvcc_py39_ml2014 --extra_toolchains="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain-linux-x86_64"
build:rbe_linux_cuda_nvcc_py39_ml2014 --extra_execution_platforms="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_linux_cuda_nvcc_py39_ml2014 --host_platform="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_linux_cuda_nvcc_py39_ml2014 --platforms="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_linux_cuda_nvcc_py39_ml2014 --repo_env=TF_CUDA_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda"
build:rbe_linux_cuda_nvcc_py39_ml2014 --repo_env=TF_TENSORRT_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_tensorrt"
build:rbe_linux_cuda_nvcc_py39_ml2014 --repo_env=TF_NCCL_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_nccl"
build:rbe_linux_cuda_nvcc_py39_ml2014 --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.9"

# Deprecated configs that people might still use.
build:rbe_linux_cuda_nvcc --config=rbe_linux_cuda_nvcc_py39
build:rbe_gpu_linux       --config=rbe_linux_cuda_nvcc

build:rbe_linux_cuda_clang_base --config=rbe_linux_cuda_base
build:rbe_linux_cuda_clang_base --repo_env TF_CUDA_CLANG=1
build:rbe_linux_cuda_clang_base --@local_config_cuda//:cuda_compiler=clang
build:rbe_linux_cuda_clang_base --crosstool_top="@ubuntu18.04-clang_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
build:rbe_linux_cuda_clang_base --extra_toolchains="@ubuntu18.04-clang_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain-linux-x86_64"
build:rbe_linux_cuda_clang_base --extra_execution_platforms="@ubuntu18.04-clang_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_linux_cuda_clang_base --host_platform="@ubuntu18.04-clang_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_linux_cuda_clang_base --platforms="@ubuntu18.04-clang_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_linux_cuda_clang_base --repo_env=TF_CUDA_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda"
build:rbe_linux_cuda_clang_base --repo_env=TF_TENSORRT_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_tensorrt"
build:rbe_linux_cuda_clang_base --repo_env=TF_NCCL_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_nccl"
build:rbe_linux_cuda_clang_py37 --config=rbe_linux_cuda_clang_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.7"
build:rbe_linux_cuda_clang_py38 --config=rbe_linux_cuda_clang_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.8"
build:rbe_linux_cuda_clang_py39 --config=rbe_linux_cuda_clang_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.9"
build:rbe_linux_cuda_clang_py310 --config=rbe_linux_cuda_clang_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.10"

# ROCm
build:rbe_linux_rocm_base --config=rocm
build:rbe_linux_rocm_base --config=rbe_linux
build:rbe_linux_rocm_base --crosstool_top="@ubuntu18.04-gcc7_manylinux2010-rocm_config_rocm//crosstool:toolchain"
build:rbe_linux_rocm_base --extra_toolchains="@ubuntu18.04-gcc7_manylinux2010-rocm_config_rocm//crosstool:toolchain-linux-x86_64"
build:rbe_linux_rocm_base --extra_execution_platforms="@ubuntu18.04-gcc7_manylinux2010-rocm_config_platform//:platform"
build:rbe_linux_rocm_base --host_platform="@ubuntu18.04-gcc7_manylinux2010-rocm_config_platform//:platform"
build:rbe_linux_rocm_base --platforms="@ubuntu18.04-gcc7_manylinux2010-rocm_config_platform//:platform"
build:rbe_linux_rocm_base --action_env=TF_ROCM_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-rocm_config_rocm"
build:rbe_linux_rocm_py3.6 --config=rbe_linux_rocm_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-rocm_config_python3.6"
build:rbe_linux_rocm_py3.7 --config=rbe_linux_rocm_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-rocm_config_python3.7"
build:rbe_linux_rocm_py3.8 --config=rbe_linux_rocm_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-rocm_config_python3.8"
build:rbe_linux_rocm_py3.9 --config=rbe_linux_rocm_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-rocm_config_python3.9"
build:rbe_linux_rocm_py3.10 --config=rbe_linux_rocm_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-rocm_config_python3.10"

# Linux CPU

build:rbe_linux_py3 --config=rbe_linux
build:rbe_linux_py3 --config=rbe_linux_py3_base
build:rbe_linux_py3_base --python_path="/usr/local/bin/python3.9"
build:rbe_linux_py3_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.9"

# rbe_linux_py3 with manylinux2014 toolchain
build:rbe_linux_py3_ml2014 --config=rbe_linux_py3
build:rbe_linux_py3_ml2014 --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.9"

build:rbe_win --config=rbe
build:rbe_win --crosstool_top="//tensorflow/tools/toolchains/win/tf_win_02212022:toolchain"
build:rbe_win --extra_toolchains="//tensorflow/tools/toolchains/win/tf_win_02212022: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
build:rbe_win --jobs=100

# 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_py37 --config=rbe
build:rbe_win_py37 --repo_env=TF_PYTHON_CONFIG_REPO="@windows_py37_config_python"
build:rbe_win_py37 --python_path=C:\\Python37\\python.exe

build:rbe_win_py38 --config=rbe
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
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

build:rbe_win_py310 --config=rbe
build:rbe_win_py310 --repo_env=PYTHON_BIN_PATH=C:\\Python310\\python.exe
build:rbe_win_py310 --repo_env=PYTHON_LIB_PATH=C:\\Python310\\lib\\site-packages
build:rbe_win_py310 --repo_env=TF_PYTHON_CONFIG_REPO=//tensorflow/tools/toolchains/win_1803/py310
build:rbe_win_py310 --python_path=C:\\Python310\\python.exe

# These you may need to change for your own GCP project.
build:tensorflow_testing_rbe --project_id=tensorflow-testing
common:tensorflow_testing_rbe_linux --remote_instance_name=projects/tensorflow-testing/instances/default_instance
build:tensorflow_testing_rbe_linux --config=tensorflow_testing_rbe
# Build GPU binaries for the RBE test machines (Tesla T4s).
build:tensorflow_testing_rbe_linux --repo_env=TF_CUDA_COMPUTE_CAPABILITIES=sm_75

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

# 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_aarch64 --distinct_host_configuration=true
build:elinux_armhf --config=elinux
build:elinux_armhf --cpu=armhf
build:elinux_armhf --distinct_host_configuration=true
build:elinux_armhf --copt -mfp16-format=ieee
# END TF REMOTE BUILD EXECUTION OPTIONS

# 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:release_base --config=v2
build:release_base --distinct_host_configuration=false
test:release_base --flaky_test_attempts=3
test:release_base --test_size_filters=small,medium

build:release_cpu_linux --config=release_base
build:release_cpu_linux --config=avx_linux
build:release_cpu_linux --crosstool_top="@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
test:release_cpu_linux --test_env=LD_LIBRARY_PATH

# manylinux2014 config for cpu
build:release_cpu_linux_manylinux2014 --config=release_base
build:release_cpu_linux_manylinux2014 --config=avx_linux
build:release_cpu_linux_manylinux2014 --crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
test:release_cpu_linux_manylinux2014 --test_env=LD_LIBRARY_PATH

build:release_cpu_macos --config=release_base
build:release_cpu_macos --config=avx_linux

build:release_gpu_base --config=cuda
build:release_gpu_base --action_env=TF_CUDA_VERSION="11"
build:release_gpu_base --action_env=TF_CUDNN_VERSION="8"
build:release_gpu_base --repo_env=TF_CUDA_COMPUTE_CAPABILITIES="sm_35,sm_50,sm_60,sm_70,sm_75,compute_80"

build:release_gpu_linux --config=release_cpu_linux
build:release_gpu_linux --config=release_gpu_base
build:release_gpu_linux --config=tensorrt
build:release_gpu_linux --action_env=CUDA_TOOLKIT_PATH="/usr/local/cuda-11.2"
build:release_gpu_linux --action_env=LD_LIBRARY_PATH="/usr/local/cuda:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/tensorrt/lib"
build:release_gpu_linux --action_env=GCC_HOST_COMPILER_PATH="/dt7/usr/bin/gcc"
build:release_gpu_linux --crosstool_top=@ubuntu18.04-gcc7_manylinux2010-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain

build:release_gpu_linux_11_4 --config=release_gpu_linux
build:release_gpu_linux_11_4 --action_env CUDA_TOOLKIT_PATH="/usr/local/cuda-11.4"
build:release_gpu_linux_11_4 --action_env=TF_CUDA_VERSION="11.4"
build:release_gpu_linux_11_4 --action_env=TF_CUDNN_VERSION="8.2"
build:release_gpu_linux_11_4 --crosstool_top=@ubuntu18.04-gcc7_manylinux2010-cuda11.4-cudnn8.2-tensorrt7.2_config_cuda//crosstool:toolchain

# manylinux2014 config for gpu
build:release_gpu_linux_manylinux2014 --config=release_gpu_linux
build:release_gpu_linux_manylinux2014 --action_env=GCC_HOST_COMPILER_PATH="/dt9/usr/bin/gcc"
build:release_gpu_linux_manylinux2014 --crosstool_top=@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain


build:release_cpu_windows --config=release_base
build:release_cpu_windows --config=avx_win
build:release_cpu_windows --define=no_tensorflow_py_deps=true
# First available in VS 16.4. Speeds Windows compile times by a lot. See
# https://groups.google.com/a/tensorflow.org/d/topic/build/SsW98Eo7l3o/discussion
build:release_cpu_windows --copt=/d2ReducedOptimizeHugeFunctions --host_copt=/d2ReducedOptimizeHugeFunctions

build:release_gpu_windows --config=release_cpu_windows
build:release_gpu_windows --config=release_gpu_base

# Address sanitizer
# CC=clang bazel build --config asan
build:asan --strip=never
build:asan --copt -fsanitize=address
build:asan --copt -DADDRESS_SANITIZER
build:asan --copt -g
build:asan --copt -O3
build:asan --copt -fno-omit-frame-pointer
build:asan --linkopt -fsanitize=address

# Memory sanitizer
# CC=clang bazel build --config msan
build:msan --strip=never
build:msan --copt -fsanitize=memory
build:msan --copt -DMEMORY_SANITIZER
build:msan --copt -g
build:msan --copt -O3
build:msan --copt -fno-omit-frame-pointer
build:msan --linkopt -fsanitize=memory

# Undefined Behavior Sanitizer
# CC=clang bazel build --config ubsan
build:ubsan --strip=never
build:ubsan --copt -fsanitize=undefined
build:ubsan --copt -DUNDEFINED_BEHAVIOR_SANITIZER
build:ubsan --copt -g
build:ubsan --copt -O3
build:ubsan --copt -fno-omit-frame-pointer
build:ubsan --linkopt -fsanitize=undefined
build:ubsan --linkopt -lubsan

# Disable TFRT integration for now unless --config=tfrt is specified.
build      --deleted_packages=tensorflow/compiler/mlir/tfrt,tensorflow/compiler/mlir/tfrt/benchmarks,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/analysis,tensorflow/compiler/mlir/tfrt/tests/jit,tensorflow/compiler/mlir/tfrt/tests/lhlo_to_tfrt,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/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/tfrt/common,tensorflow/core/tfrt/eager,tensorflow/core/tfrt/eager/backends/cpu,tensorflow/core/tfrt/eager/backends/gpu,tensorflow/core/tfrt/eager/core_runtime,tensorflow/core/tfrt/eager/cpp_tests/core_runtime,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
build:tfrt --deleted_packages=

# Experimental configuration for building XLA GPU lowering to TFRT.
build:experimental_enable_xlir --config=tfrt
build:experimental_enable_xlir --@tf_runtime//:enable_gpu
build:experimental_enable_xlir --@rules_cuda//cuda:cuda_runtime=//tensorflow/compiler/xla/service/gpu:cuda_runtime_for_xlir
build:experimental_enable_xlir --nocheck_visibility
build:experimental_enable_xlir --incompatible_strict_action_env
build:experimental_enable_xlir --config=monolithic

# bazel test --config=experimental_enable_bef_thunk \
#   //tensorflow/compiler/xla/service/gpu:bef_thunk_tests
build:experimental_enable_bef_thunk      --config=experimental_enable_xlir
test:experimental_enable_bef_thunk       --test_env=XLA_FLAGS=--xla_gpu_bef_thunk

# bazel test --config=experimental_enable_bef_executable \
#   //tensorflow/compiler/xla/service/gpu:bef_executable_tests
build:experimental_enable_bef_executable --config=experimental_enable_xlir
test:experimental_enable_bef_executable  --test_env=XLA_FLAGS=--xla_gpu_bef_executable