# 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.

# 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_linux_cuda_nvcc_py*: RBE options to build with GPU support using nvcc.

#

# rbe_linux_py3: Linux Python 3 RBE config

#

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

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

# 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

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

build --experimental_link_static_libraries_once=false

# 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

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_sim_arm64 --config=ios

build:ios_sim_arm64 --cpu=ios_sim_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

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

# 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).

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

# 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/galeone/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/galeone/tensorflow/issues/33360

build:dbg --cxxopt -DTF_LITE_DISABLE_X86_NEON

# AWS SDK must be compiled in release mode. see: https://github.com/galeone/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

build:rocm --experimental_link_static_libraries_once=false # b/230048163

# 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

# 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

build:windows --host_copt=/W0

# 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

# 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

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

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

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

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

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

build:rbe_cpu_linux_base --platforms="@ubuntu20.04-gcc9_manylinux2014-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

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

build:rbe_linux_cuda11.2_nvcc_base --crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"

build:rbe_linux_cuda11.2_nvcc_base --extra_toolchains="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain-linux-x86_64"

build:rbe_linux_cuda11.2_nvcc_base --extra_execution_platforms="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"

build:rbe_linux_cuda11.2_nvcc_base --host_platform="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"

build:rbe_linux_cuda11.2_nvcc_base --platforms="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"

build:rbe_linux_cuda11.2_nvcc_base --repo_env=TF_CUDA_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda"

build:rbe_linux_cuda11.2_nvcc_base --repo_env=TF_TENSORRT_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_tensorrt"

build:rbe_linux_cuda11.2_nvcc_base --repo_env=TF_NCCL_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-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="@ubuntu20.04-gcc9_manylinux2014-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="@ubuntu20.04-gcc9_manylinux2014-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="@ubuntu20.04-gcc9_manylinux2014-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="@ubuntu20.04-gcc9_manylinux2014-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

# 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="@ubuntu20.04-clang_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"

build:rbe_linux_cuda_clang_base --extra_toolchains="@ubuntu20.04-clang_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain-linux-x86_64"

build:rbe_linux_cuda_clang_base --extra_execution_platforms="@ubuntu20.04-clang_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"

build:rbe_linux_cuda_clang_base --host_platform="@ubuntu20.04-clang_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"

build:rbe_linux_cuda_clang_base --platforms="@ubuntu20.04-clang_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"

build:rbe_linux_cuda_clang_base --repo_env=TF_CUDA_CONFIG_REPO="@ubuntu20.04-clang_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda"

build:rbe_linux_cuda_clang_base --repo_env=TF_TENSORRT_CONFIG_REPO="@ubuntu20.04-clang_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_tensorrt"

build:rbe_linux_cuda_clang_base --repo_env=TF_NCCL_CONFIG_REPO="@ubuntu20.04-clang_manylinux2014-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="@ubuntu20.04-clang_manylinux2014-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="@ubuntu20.04-clang_manylinux2014-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="@ubuntu20.04-clang_manylinux2014-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="@ubuntu20.04-clang_manylinux2014-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="@ubuntu20.04-gcc9_manylinux2014-rocm_config_rocm//crosstool:toolchain"

build:rbe_linux_rocm_base --extra_toolchains="@ubuntu20.04-gcc9_manylinux2014-rocm_config_rocm//crosstool:toolchain-linux-x86_64"

build:rbe_linux_rocm_base --extra_execution_platforms="@ubuntu20.04-gcc9_manylinux2014-rocm_config_platform//:platform"

build:rbe_linux_rocm_base --host_platform="@ubuntu20.04-gcc9_manylinux2014-rocm_config_platform//:platform"

build:rbe_linux_rocm_base --platforms="@ubuntu20.04-gcc9_manylinux2014-rocm_config_platform//:platform"

build:rbe_linux_rocm_base --action_env=TF_ROCM_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-rocm_config_rocm"

build:rbe_linux_rocm_py3.7 --config=rbe_linux_rocm_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-rocm_config_python3.7"

build:rbe_linux_rocm_py3.8 --config=rbe_linux_rocm_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-rocm_config_python3.8"

build:rbe_linux_rocm_py3.9 --config=rbe_linux_rocm_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-rocm_config_python3.9"

build:rbe_linux_rocm_py3.10 --config=rbe_linux_rocm_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-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="@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_06152022:toolchain"

build:rbe_win --extra_toolchains="//tensorflow/tools/toolchains/win/tf_win_06152022: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="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"

test:release_cpu_linux --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/cuda-11.1/lib64:/usr/local/tensorrt/lib"

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

build:release_gpu_linux --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

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/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/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=