3d7a7d2516
This is consistent with other entries in the bazelrc and makes it possible to use the bazelrc file from other workspaces. PiperOrigin-RevId: 355427795 Change-Id: Idbc06f3b79e3ac1746e5243542b35ed01e91bddf
655 lines
34 KiB
Plaintext
655 lines
34 KiB
Plaintext
# TensorFlow Bazel configuration file.
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# This file tries to group and simplify build options for TensorFlow
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#
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# ----CONFIG OPTIONS----
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# Android options:
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# android:
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# android_arm:
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# android_arm64:
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# android_x86:
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# android_x86_64:
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#
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# iOS options:
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# ios:
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# ios_armv7:
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# ios_arm64:
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# ios_i386:
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# ios_x86_64:
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# ios_fat:
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#
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# Macosx options
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# darwin_arm64:
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#
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# Compiler options:
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# cuda_clang: Use clang when building CUDA code.
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# c++17: Build with C++17 options (links with libc++)
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# c++1z: Build with C++17 options (links with libc++)
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# c++17_gcc: Build with C++17 options (links with stdlibc++)
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# c++1z_gcc: Build with C++17 options (links with stdlibc++)
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# avx_linux: Build with avx instruction set on linux.
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# avx2_linux: Build with avx2 instruction set on linux.
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# native_arch_linux: Build with instruction sets available to the host machine on linux
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# avx_win: Build with avx instruction set on windows
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# avx2_win: Build with avx2 instruction set on windows
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#
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# Other build options:
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# short_logs: Only log errors during build, skip warnings.
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# verbose_logs: Show all compiler warnings during build.
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# monolithic: Build all TF C++ code into a single shared object.
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# dynamic_kernels: Try to link all kernels dynamically (experimental).
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# libc++: Link against libc++ instead of stdlibc++
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# asan: Build with the clang address sanitizer
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# msan: Build with the clang memory sanitizer
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# ubsan: Build with the clang undefined behavior sanitizer
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#
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#
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# TF version options;
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# v1: Build TF V1 (without contrib)
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# v2: Build TF v2
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#
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# Feature and Third party library support options:
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# xla: Build TF with XLA
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# tpu: Build TF with TPU support
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# using_cuda: CUDA is available to build system.
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# cuda: Build with full cuda support.
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# rocm: Build with AMD GPU support (rocm).
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# mkl: Enable full mkl support.
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# tensorrt: Enable Tensorrt support.
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# numa: Enable numa using hwloc.
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# noaws: Disable AWS S3 storage support
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# nogcp: Disable GCS support.
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# nohdfs: Disable hadoop hdfs support.
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# nonccl: Disable nccl support.
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#
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#
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# Remote build execution options (only configured to work with TF team projects for now.)
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# rbe: General RBE options shared by all flavors.
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# rbe_linux: General RBE options used on all linux builds.
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# rbe_win: General RBE options used on all windows builds.
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#
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# rbe_cpu_linux: RBE options to build with only CPU support.
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# rbe_linux_cuda_nvcc_py*: RBE options to build with GPU support using nvcc.
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#
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# rbe_linux_py2: Linux Python 2 RBE config.
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# rbe_linux_py3: Linux Python 3 RBE config
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#
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# rbe_win_py37: Windows Python 3.7 RBE config
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# rbe_win_py38: Windows Python 3.8 RBE config
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#
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# tensorflow_testing_rbe_linux: RBE options to use RBE with tensorflow-testing project on linux
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# tensorflow_testing_rbe_win: RBE options to use RBE with tensorflow-testing project on windows
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#
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# Embedded Linux options (experimental and only tested with TFLite build yet)
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# elinux: General Embedded Linux options shared by all flavors.
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# elinux_aarch64: Embedded Linux options for aarch64 (ARM64) CPU support.
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# elinux_armhf: Embedded Linux options for armhf (ARMv7) CPU support.
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#
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# Release build options (for all operating systems)
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# release_common: Common options for all builds on all operating systems.
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# release_windows_common: Common options for all builds on Windows.
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# release_gpu_common: Common options for GPU builds on Linux and Windows.
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# release_cpu_linux: Toolchain and CUDA options for Linux CPU builds.
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# release_cpu_macos: Toolchain and CUDA options for MacOS CPU builds.
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# release_gpu_linux: Toolchain and CUDA options for Linux GPU builds.
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# release_gpu_linux_cuda_10_1: Toolchain and CUDA options for CUDA 10.1 Linux GPU builds.
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# release_cpu_windows: Toolchain and CUDA options for Windows CPU builds.
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# release_gpu_windows: Toolchain and CUDA options for Windows GPU builds.
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# Allow builds using libc++ as a linker library
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# This is mostly for OSSFuzz, so we also pass in the flags from environment to clean build file
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build:libc++ --action_env=CC
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build:libc++ --action_env=CXX
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build:libc++ --action_env=CXXFLAGS=-stdlib=libc++
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build:libc++ --action_env=PATH
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build:libc++ --define force_libcpp=enabled
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build:libc++ --linkopt -fuse-ld=lld
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# Android configs. Bazel needs to have --cpu and --fat_apk_cpu both set to the
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# target CPU to build transient dependencies correctly. See
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# https://docs.bazel.build/versions/master/user-manual.html#flag--fat_apk_cpu
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build:android --crosstool_top=//external:android/crosstool
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build:android --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
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build:android_arm --config=android
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build:android_arm --cpu=armeabi-v7a
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build:android_arm --fat_apk_cpu=armeabi-v7a
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build:android_arm64 --config=android
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build:android_arm64 --cpu=arm64-v8a
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build:android_arm64 --fat_apk_cpu=arm64-v8a
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build:android_x86 --config=android
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build:android_x86 --cpu=x86
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build:android_x86 --fat_apk_cpu=x86
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build:android_x86_64 --config=android
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build:android_x86_64 --cpu=x86_64
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build:android_x86_64 --fat_apk_cpu=x86_64
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# Sets the default Apple platform to macOS.
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build --apple_platform_type=macos
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# iOS configs for each architecture and the fat binary builds.
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build:ios --apple_platform_type=ios
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build:ios --apple_bitcode=embedded --copt=-fembed-bitcode
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build:ios --copt=-Wno-c++11-narrowing
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build:ios_armv7 --config=ios
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build:ios_armv7 --cpu=ios_armv7
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build:ios_arm64 --config=ios
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build:ios_arm64 --cpu=ios_arm64
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build:ios_i386 --config=ios
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build:ios_i386 --cpu=ios_i386
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build:ios_x86_64 --config=ios
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build:ios_x86_64 --cpu=ios_x86_64
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build:ios_fat --config=ios
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build:ios_fat --ios_multi_cpus=armv7,arm64,i386,x86_64
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# Enables all the macos config options for macos_arm64
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build:macos_arm64 --config=macos
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build:macos_arm64 --apple_platform_type=macos
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build:macos_arm64 --cpu=darwin_arm64
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# Config to use a mostly-static build and disable modular op registration
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# support (this will revert to loading TensorFlow with RTLD_GLOBAL in Python).
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# By default, TensorFlow will build with a dependence on
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# //tensorflow:libtensorflow_framework.so.
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build:monolithic --define framework_shared_object=false
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# For projects which use TensorFlow as part of a Bazel build process, putting
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# nothing in a bazelrc will default to a monolithic build. The following line
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# opts in to modular op registration support by default.
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build --define framework_shared_object=true
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# For workaround https://github.com/bazelbuild/bazel/issues/8772 with Bazel >= 0.29.1
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build --java_toolchain=@org_tensorflow//third_party/toolchains/java:tf_java_toolchain
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build --host_java_toolchain=@org_tensorflow//third_party/toolchains/java:tf_java_toolchain
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# Please note that MKL on MacOS or windows is still not supported.
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# If you would like to use a local MKL instead of downloading, please set the
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# environment variable "TF_MKL_ROOT" every time before build.
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build:mkl --define=build_with_mkl=true --define=enable_mkl=true
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build:mkl --define=tensorflow_mkldnn_contraction_kernel=0
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build:mkl --define=build_with_openmp=true
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build:mkl -c opt
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# config to build OneDNN backend with a user specified threadpool.
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build:mkl_threadpool --define=build_with_mkl=true --define=enable_mkl=true
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build:mkl_threadpool --define=tensorflow_mkldnn_contraction_kernel=0
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build:mkl_threadpool --define=build_with_mkl_opensource=true
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build:mkl_threadpool --define=build_with_mkldnn_threadpool=true
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build:mkl_threadpool -c opt
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# Config setting to build with oneDNN and without the binary blob
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build:mkl_opensource_only --define=build_with_mkl=true --define=enable_mkl=true
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build:mkl_opensource_only --define=tensorflow_mkldnn_contraction_kernel=0
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build:mkl_opensource_only --define=build_with_mkl_opensource=true
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build:mkl_opensource_only --define=build_with_openmp=true
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build:mkl_opensource_only -c opt
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# Config setting to build with oneDNN for Arm.
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build:mkl_aarch64 --define=build_with_mkl_aarch64=true --define=enable_mkl=true
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build:mkl_aarch64 --define=tensorflow_mkldnn_contraction_kernel=0
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build:mkl_aarch64 --define=build_with_mkl_opensource=true
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build:mkl_aarch64 -c opt
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# This config refers to building with CUDA available. It does not necessarily
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# mean that we build CUDA op kernels.
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build:using_cuda --define=using_cuda=true
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build:using_cuda --action_env TF_NEED_CUDA=1
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build:using_cuda --crosstool_top=@local_config_cuda//crosstool:toolchain
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# Enable the mlir generated GPU kernels only for cuda builds.
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build --define=tensorflow_enable_mlir_generated_gpu_kernels=0
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# This is a more specific option, so it takes precedence over the line above for cuda builds.
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build:using_cuda --define=tensorflow_enable_mlir_generated_gpu_kernels=1
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# This config refers to building CUDA op kernels with nvcc.
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build:cuda --config=using_cuda
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build:cuda --define=using_cuda_nvcc=true
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# This config refers to building CUDA op kernels with clang.
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build:cuda_clang --config=using_cuda
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build:cuda_clang --define=using_cuda_clang=true
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build:cuda_clang --define=using_clang=true
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build:cuda_clang --action_env TF_CUDA_CLANG=1
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# dbg config, as a shorthand for '--config=opt -c dbg'
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build:dbg --config=opt -c dbg
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# for now, disable arm_neon. see: https://github.com/tensorflow/tensorflow/issues/33360
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build:dbg --cxxopt -DTF_LITE_DISABLE_X86_NEON
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# AWS SDK must be compiled in release mode. see: https://github.com/tensorflow/tensorflow/issues/37498
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build:dbg --copt -DDEBUG_BUILD
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# Config to build TPU backend
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build:tpu --define=with_tpu_support=true
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build:tensorrt --action_env TF_NEED_TENSORRT=1
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build:rocm --crosstool_top=@local_config_rocm//crosstool:toolchain
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build:rocm --define=using_rocm=true --define=using_rocm_hipcc=true
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build:rocm --action_env TF_NEED_ROCM=1
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# Options extracted from configure script
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build:numa --define=with_numa_support=true
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# Options to disable default on features
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build:noaws --define=no_aws_support=true
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build:nogcp --define=no_gcp_support=true
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build:nohdfs --define=no_hdfs_support=true
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build:nonccl --define=no_nccl_support=true
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build:stackdriver_support --define=stackdriver_support=true
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build --define=use_fast_cpp_protos=true
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build --define=allow_oversize_protos=true
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build --spawn_strategy=standalone
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build -c opt
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# Make Bazel print out all options from rc files.
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build --announce_rc
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# Other build flags.
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build --define=grpc_no_ares=true
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# See https://github.com/bazelbuild/bazel/issues/7362 for information on what
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# --incompatible_remove_legacy_whole_archive flag does.
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# This flag is set to true in Bazel 1.0 and newer versions. We tried to migrate
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# Tensorflow to the default, however test coverage wasn't enough to catch the
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# errors.
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# There is ongoing work on Bazel team's side to provide support for transitive
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# shared libraries. As part of migrating to transitive shared libraries, we
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# hope to provide a better mechanism for control over symbol exporting, and
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# then tackle this issue again.
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#
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# TODO: Remove this line once TF doesn't depend on Bazel wrapping all library
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# archives in -whole_archive -no_whole_archive.
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build --noincompatible_remove_legacy_whole_archive
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# These are bazel 2.0's incompatible flags. Tensorflow needs to use bazel 2.0.0
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# to use cc_shared_library, as part of the Tensorflow Build Improvements RFC:
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# https://github.com/tensorflow/community/pull/179
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build --noincompatible_prohibit_aapt1
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# Modular TF build options
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build:dynamic_kernels --define=dynamic_loaded_kernels=true
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build:dynamic_kernels --copt=-DAUTOLOAD_DYNAMIC_KERNELS
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# Build TF with C++ 17 features.
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build:c++17 --cxxopt=-std=c++1z
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build:c++17 --cxxopt=-stdlib=libc++
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build:c++1z --config=c++17
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build:c++17_gcc --cxxopt=-std=c++1z
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build:c++1z_gcc --config=c++17_gcc
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# Enable using platform specific build settings, except when cross-compiling for
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# mobile platforms.
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build --enable_platform_specific_config
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build:android --noenable_platform_specific_config
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build:ios --noenable_platform_specific_config
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build:macos_arm64 --noenable_platform_specific_config
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# Suppress C++ compiler warnings, otherwise build logs become 10s of MBs.
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build:android --copt=-w
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build:ios --copt=-w
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build:linux --copt=-w
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build:linux --host_copt=-w
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build:macos --copt=-w
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build:windows --copt=/W0
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# Tensorflow uses M_* math constants that only get defined by MSVC headers if
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# _USE_MATH_DEFINES is defined.
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build:windows --copt=/D_USE_MATH_DEFINES
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build:windows --host_copt=/D_USE_MATH_DEFINES
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# Default paths for TF_SYSTEM_LIBS
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build:linux --define=PREFIX=/usr
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build:linux --define=LIBDIR=$(PREFIX)/lib
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build:linux --define=INCLUDEDIR=$(PREFIX)/include
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build:linux --define=PROTOBUF_INCLUDE_PATH=$(PREFIX)/include
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build:macos --define=PREFIX=/usr
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build:macos --define=LIBDIR=$(PREFIX)/lib
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build:macos --define=INCLUDEDIR=$(PREFIX)/include
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build:macos --define=PROTOBUF_INCLUDE_PATH=$(PREFIX)/include
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# TF_SYSTEM_LIBS do not work on windows.
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# By default, build TF in C++ 14 mode.
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build:android --cxxopt=-std=c++14
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build:android --host_cxxopt=-std=c++14
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build:ios --cxxopt=-std=c++14
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build:ios --host_cxxopt=-std=c++14
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build:linux --cxxopt=-std=c++14
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build:linux --host_cxxopt=-std=c++14
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build:macos --cxxopt=-std=c++14
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build:macos --host_cxxopt=-std=c++14
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build:windows --cxxopt=/std:c++14
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build:windows --host_cxxopt=/std:c++14
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# On windows, we still link everything into a single DLL.
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build:windows --config=monolithic
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# On linux, we dynamically link small amount of kernels
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build:linux --config=dynamic_kernels
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# Make sure to include as little of windows.h as possible
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build:windows --copt=-DWIN32_LEAN_AND_MEAN
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build:windows --host_copt=-DWIN32_LEAN_AND_MEAN
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build:windows --copt=-DNOGDI
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build:windows --host_copt=-DNOGDI
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# MSVC (Windows): Standards-conformant preprocessor mode
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# See https://docs.microsoft.com/en-us/cpp/preprocessor/preprocessor-experimental-overview
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build:windows --copt=/experimental:preprocessor
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build:windows --host_copt=/experimental:preprocessor
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# Misc build options we need for windows.
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build:windows --linkopt=/DEBUG
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build:windows --host_linkopt=/DEBUG
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build:windows --linkopt=/OPT:REF
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build:windows --host_linkopt=/OPT:REF
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build:windows --linkopt=/OPT:ICF
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build:windows --host_linkopt=/OPT:ICF
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build:windows --experimental_strict_action_env=true
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# Verbose failure logs when something goes wrong
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build:windows --verbose_failures
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# On windows, we never cross compile
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build:windows --distinct_host_configuration=false
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# Suppress all warning messages.
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build:short_logs --output_filter=DONT_MATCH_ANYTHING
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build:verbose_logs --output_filter=
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build --config=short_logs
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# Instruction set optimizations
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# TODO(gunan): Create a feature in toolchains for avx/avx2 to
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# avoid having to define linux/win separately.
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build:avx_linux --copt=-mavx
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build:avx_linux --host_copt=-mavx
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build:avx2_linux --copt=-mavx2
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build:native_arch_linux --copt=-march=native
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build:avx_win --copt=/arch=AVX
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build:avx2_win --copt=/arch=AVX2
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# Options to build TensorFlow 1.x or 2.x.
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build:v1 --define=tf_api_version=1
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build:v2 --define=tf_api_version=2
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build:v1 --action_env=TF2_BEHAVIOR=0
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build:v2 --action_env=TF2_BEHAVIOR=1
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build --config=v2
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test --config=v2
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# Enable XLA
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build:xla --define=with_xla_support=true
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# BEGIN TF REMOTE BUILD EXECUTION OPTIONS
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# Options when using remote execution
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# WARNING: THESE OPTIONS WONT WORK IF YOU DO NOT HAVE PROPER AUTHENTICATION AND PERMISSIONS
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# Flag to enable remote config
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common --experimental_repo_remote_exec
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build:rbe --action_env=BAZEL_DO_NOT_DETECT_CPP_TOOLCHAIN=1
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build:rbe --google_default_credentials
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build:rbe --bes_backend=buildeventservice.googleapis.com
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build:rbe --bes_results_url="https://source.cloud.google.com/results/invocations"
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build:rbe --bes_timeout=600s
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build:rbe --define=EXECUTOR=remote
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build:rbe --distinct_host_configuration=false
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build:rbe --flaky_test_attempts=3
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build:rbe --jobs=200
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build:rbe --remote_executor=grpcs://remotebuildexecution.googleapis.com
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build:rbe --remote_timeout=3600
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build:rbe --spawn_strategy=remote,worker,standalone,local
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test:rbe --test_env=USER=anon
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# Attempt to minimize the amount of data transfer between bazel and the remote
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# workers:
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build:rbe --remote_download_toplevel
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build:rbe_linux --config=rbe
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build:rbe_linux --action_env=PATH="/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/go/bin"
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build:rbe_linux --host_javabase=@bazel_toolchains//configs/ubuntu16_04_clang/1.1:jdk8
|
|
build:rbe_linux --javabase=@bazel_toolchains//configs/ubuntu16_04_clang/1.1:jdk8
|
|
build:rbe_linux --host_java_toolchain=@bazel_tools//tools/jdk:toolchain_hostjdk8
|
|
build:rbe_linux --java_toolchain=@bazel_tools//tools/jdk:toolchain_hostjdk8
|
|
|
|
# Non-rbe settings we should include because we do not run configure
|
|
build:rbe_linux --config=xla
|
|
build:rbe_linux --config=avx_linux
|
|
build:rbe_linux --config=short_logs
|
|
# 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_cpu_linux --config=rbe_linux
|
|
build:rbe_cpu_linux --host_crosstool_top="@org_tensorflow//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010:toolchain"
|
|
build:rbe_cpu_linux --crosstool_top="@org_tensorflow//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010:toolchain"
|
|
build:rbe_cpu_linux --extra_toolchains="@org_tensorflow//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010:cc-toolchain-k8"
|
|
build:rbe_cpu_linux --extra_execution_platforms="@ubuntu16.04-manylinux2010-py3_config_platform//:platform"
|
|
build:rbe_cpu_linux --extra_execution_platforms="@ubuntu16.04-manylinux2010-py3_config_platform//:platform"
|
|
build:rbe_cpu_linux --host_platform="@ubuntu16.04-manylinux2010-py3_config_platform//:platform"
|
|
build:rbe_cpu_linux --platforms="@ubuntu16.04-manylinux2010-py3_config_platform//:platform"
|
|
|
|
build:rbe_linux_cuda_base --config=rbe_linux
|
|
build:rbe_linux_cuda_base --repo_env=TF_NEED_TENSORRT=1
|
|
build:rbe_linux_cuda_base --repo_env=TF_CUDA_VERSION=10
|
|
build:rbe_linux_cuda_base --repo_env=TF_CUDNN_VERSION=7
|
|
build:rbe_linux_cuda_base --repo_env=REMOTE_GPU_TESTING=1
|
|
build:rbe_linux_cuda_base --repo_env=TF_NEED_CUDA=1
|
|
test:rbe_linux_cuda_base --test_env=LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"
|
|
|
|
build:rbe_linux_cuda10.1_nvcc_base --config=rbe_linux_cuda_base
|
|
build:rbe_linux_cuda10.1_nvcc_base --define=using_cuda_nvcc=true
|
|
build:rbe_linux_cuda10.1_nvcc_base --host_crosstool_top="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_cuda//crosstool:toolchain"
|
|
build:rbe_linux_cuda10.1_nvcc_base --crosstool_top="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_cuda//crosstool:toolchain"
|
|
build:rbe_linux_cuda10.1_nvcc_base --extra_toolchains="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_cuda//crosstool:toolchain-linux-x86_64"
|
|
build:rbe_linux_cuda10.1_nvcc_base --extra_execution_platforms="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_platform//:platform"
|
|
build:rbe_linux_cuda10.1_nvcc_base --host_platform="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_platform//:platform"
|
|
build:rbe_linux_cuda10.1_nvcc_base --platforms="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_platform//:platform"
|
|
build:rbe_linux_cuda10.1_nvcc_base --repo_env=TF_CUDA_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_cuda"
|
|
build:rbe_linux_cuda10.1_nvcc_base --repo_env=TF_TENSORRT_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_tensorrt"
|
|
build:rbe_linux_cuda10.1_nvcc_base --repo_env=TF_NCCL_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_nccl"
|
|
build:rbe_linux_cuda10.1_nvcc_py2.7 --config=rbe_linux_cuda10.1_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_python2.7"
|
|
build:rbe_linux_cuda10.1_nvcc_py3.5 --config=rbe_linux_cuda10.1_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_python3.5"
|
|
build:rbe_linux_cuda10.1_nvcc_py3.6 --config=rbe_linux_cuda10.1_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_python3.6"
|
|
build:rbe_linux_cuda10.1_nvcc_py3.7 --config=rbe_linux_cuda10.1_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_python3.7"
|
|
build:rbe_linux_cuda10.1_nvcc_py3.8 --config=rbe_linux_cuda10.1_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda10.1-cudnn7-tensorrt6.0_config_python3.8"
|
|
|
|
build:rbe_linux_cuda11.0_nvcc_base --config=rbe_linux_cuda_base
|
|
build:rbe_linux_cuda11.0_nvcc_base --define=using_cuda_nvcc=true
|
|
build:rbe_linux_cuda11.0_nvcc_base --host_crosstool_top="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_cuda//crosstool:toolchain"
|
|
build:rbe_linux_cuda11.0_nvcc_base --crosstool_top="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_cuda//crosstool:toolchain"
|
|
build:rbe_linux_cuda11.0_nvcc_base --extra_toolchains="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_cuda//crosstool:toolchain-linux-x86_64"
|
|
build:rbe_linux_cuda11.0_nvcc_base --extra_execution_platforms="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_platform//:platform"
|
|
build:rbe_linux_cuda11.0_nvcc_base --host_platform="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_platform//:platform"
|
|
build:rbe_linux_cuda11.0_nvcc_base --platforms="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_platform//:platform"
|
|
build:rbe_linux_cuda11.0_nvcc_base --repo_env=TF_CUDA_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_cuda"
|
|
build:rbe_linux_cuda11.0_nvcc_base --repo_env=TF_TENSORRT_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_tensorrt"
|
|
build:rbe_linux_cuda11.0_nvcc_base --repo_env=TF_NCCL_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_nccl"
|
|
build:rbe_linux_cuda11.0_nvcc_py2.7 --config=rbe_linux_cuda11.0_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_python2.7"
|
|
build:rbe_linux_cuda11.0_nvcc_py3.5 --config=rbe_linux_cuda11.0_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_python3.5"
|
|
build:rbe_linux_cuda11.0_nvcc_py3.6 --config=rbe_linux_cuda11.0_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_python3.6"
|
|
build:rbe_linux_cuda11.0_nvcc_py3.7 --config=rbe_linux_cuda11.0_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_python3.7"
|
|
build:rbe_linux_cuda11.0_nvcc_py3.8 --config=rbe_linux_cuda11.0_nvcc_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_python3.8"
|
|
|
|
# Map default to CUDA 11 for PY35 and greater.
|
|
build:rbe_linux_cuda_nvcc_py27 --config=rbe_linux_cuda10.1_nvcc_py2.7
|
|
build:rbe_linux_cuda_nvcc_py35 --config=rbe_linux_cuda11.0_nvcc_py3.5
|
|
build:rbe_linux_cuda_nvcc_py36 --config=rbe_linux_cuda11.0_nvcc_py3.6
|
|
build:rbe_linux_cuda_nvcc_py37 --config=rbe_linux_cuda11.0_nvcc_py3.7
|
|
build:rbe_linux_cuda_nvcc_py38 --config=rbe_linux_cuda11.0_nvcc_py3.8
|
|
|
|
# Deprecated configs that people might still use.
|
|
build:rbe_linux_cuda_nvcc --config=rbe_linux_cuda_nvcc_py36
|
|
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 --crosstool_top="@ubuntu18.04-clang_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_cuda//crosstool:toolchain"
|
|
build:rbe_linux_cuda_clang_base --extra_toolchains="@ubuntu18.04-clang_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_cuda//crosstool:toolchain-linux-x86_64"
|
|
build:rbe_linux_cuda_clang_base --extra_execution_platforms="@ubuntu18.04-clang_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_platform//:platform"
|
|
build:rbe_linux_cuda_clang_base --host_platform="@ubuntu18.04-clang_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_platform//:platform"
|
|
build:rbe_linux_cuda_clang_base --platforms="@ubuntu18.04-clang_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_platform//:platform"
|
|
build:rbe_linux_cuda_clang_base --repo_env=TF_CUDA_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_cuda"
|
|
build:rbe_linux_cuda_clang_base --repo_env=TF_TENSORRT_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_tensorrt"
|
|
build:rbe_linux_cuda_clang_base --repo_env=TF_NCCL_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_nccl"
|
|
build:rbe_linux_cuda_clang_base --define=using_cuda_clang=true
|
|
build:rbe_linux_cuda_clang_py27 --config=rbe_linux_cuda_clang_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_python2.7"
|
|
build:rbe_linux_cuda_clang_py35 --config=rbe_linux_cuda_clang_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_python3.5"
|
|
build:rbe_linux_cuda_clang_py36 --config=rbe_linux_cuda_clang_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_config_python3.6"
|
|
build:rbe_linux_cuda_clang_py37 --config=rbe_linux_cuda_clang_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-clang_manylinux2010-cuda11.0-cudnn8-tensorrt7.1_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-cuda11.0-cudnn8-tensorrt7.1_config_python3.8"
|
|
|
|
# ROCm
|
|
build:rbe_linux_rocm_base --config=rbe_linux
|
|
build:rbe_linux_rocm_base --repo_env=TF_NEED_ROCM=1
|
|
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_base --define=using_rocm_hipcc=true
|
|
build:rbe_linux_rocm_py2.7 --config=rbe_linux_rocm_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-rocm_config_python2.7"
|
|
build:rbe_linux_rocm_py3.5 --config=rbe_linux_rocm_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu18.04-gcc7_manylinux2010-rocm_config_python3.5"
|
|
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"
|
|
|
|
# Linux CPU
|
|
build:rbe_linux_py2 --config=rbe_linux
|
|
build:rbe_linux_py2 --repo_env=PYTHON_BIN_PATH="/usr/bin/python2"
|
|
build:rbe_linux_py2 --python_path="/usr/bin/python2"
|
|
build:rbe_linux_py2 --repo_env=TF_PYTHON_CONFIG_REPO="@org_tensorflow//third_party/toolchains/preconfig/ubuntu16.04/py"
|
|
|
|
build:rbe_linux_py3 --config=rbe_linux
|
|
build:rbe_linux_py3 --python_path="/usr/bin/python3"
|
|
build:rbe_linux_py3 --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu16.04-manylinux2010-py3_config_python"
|
|
|
|
build:rbe_win --config=rbe
|
|
build:rbe_win --crosstool_top="@org_tensorflow//third_party/toolchains/preconfig/win/tf_win_08062020:toolchain"
|
|
build:rbe_win --extra_toolchains="@org_tensorflow//third_party/toolchains/preconfig/win/tf_win_08062020:cc-toolchain-x64_windows"
|
|
build:rbe_win --host_javabase="@org_tensorflow//third_party/toolchains/preconfig/win:windows_jdk8"
|
|
build:rbe_win --javabase="@org_tensorflow//third_party/toolchains/preconfig/win:windows_jdk8"
|
|
build:rbe_win --extra_execution_platforms="@org_tensorflow//third_party/toolchains/preconfig/win:rbe_windows_ltsc2019"
|
|
build:rbe_win --host_platform="@org_tensorflow//third_party/toolchains/preconfig/win:rbe_windows_ltsc2019"
|
|
build:rbe_win --platforms="@org_tensorflow//third_party/toolchains/preconfig/win:rbe_windows_ltsc2019"
|
|
build:rbe_win --shell_executable=C:\\tools\\msys64\\usr\\bin\\bash.exe
|
|
|
|
# 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
|
|
|
|
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=@org_tensorflow//third_party/toolchains/preconfig/win_1803/py38
|
|
build:rbe_win_py38 --python_path=C:\\Python38\\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:tensorflow_testing_rbe_linux --config=rbe
|
|
build:tensorflow_testing_rbe_linux --config=rbe_linux
|
|
|
|
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_armhf --config=elinux
|
|
build:elinux_armhf --cpu=armhf
|
|
# END TF REMOTE BUILD EXECUTION OPTIONS
|
|
|
|
# Default options should come above this line
|
|
|
|
# Options from ./configure
|
|
try-import %workspace%/.tf_configure.bazelrc
|
|
|
|
# Put user-specific options in .bazelrc.user
|
|
try-import %workspace%/.bazelrc.user
|
|
|
|
# Here are bazelrc configs for release builds
|
|
build:release_common --config=opt
|
|
build:release_common --config=v2
|
|
build:release_common --distinct_host_configuration=false
|
|
build:release_common --action_env TF_CONFIGURE_IOS="0"
|
|
|
|
build:release_cpu_linux --config=release_common
|
|
build:release_cpu_linux --config=avx_linux
|
|
# We use the same toolchain for CPU/GPU packages.
|
|
# Did not add this to the defaults in case this changes.
|
|
build:release_cpu_linux --crosstool_top=@org_tensorflow//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda10.1:toolchain
|
|
|
|
build:release_cpu_macos --config=release_common
|
|
build:release_cpu_macos --config=avx_linux
|
|
|
|
build:release_gpu_common --config=release_common
|
|
build:release_gpu_common --config=cuda
|
|
build:release_gpu_common --config=tensorrt
|
|
build:release_gpu_common --action_env CUDA_TOOLKIT_PATH="/usr/local/cuda-11.0"
|
|
build:release_gpu_common --action_env=TF_CUDA_VERSION="11"
|
|
build:release_gpu_common --action_env=TF_CUDNN_VERSION="8"
|
|
build:release_gpu_common --action_env=TF_NEED_TENSORRT="1"
|
|
build:release_gpu_common --action_env=TF_CUDA_COMPUTE_CAPABILITIES="sm_35,sm_50,sm_60,sm_70,sm_75,compute_80"
|
|
build:release_gpu_common --action_env=TENSORRT_INSTALL_PATH="/usr/local/tensorrt"
|
|
build:release_gpu_common --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_common --action_env=GCC_HOST_COMPILER_PATH="/usr/bin/gcc-5"
|
|
|
|
|
|
build:release_gpu_linux --config=release_gpu_common
|
|
build:release_gpu_linux --config=avx_linux
|
|
build:release_gpu_linux --crosstool_top=@org_tensorflow//third_party/toolchains/preconfig/ubuntu16.04/gcc7_manylinux2010-nvcc-cuda11:toolchain
|
|
build:release_windows_common --config=release_common
|
|
build:release_windows_common --define=no_tensorflow_py_deps=true
|
|
build:release_windows_common --announce_rc
|
|
|
|
# First available in VS 16.4. Speeds Windows compile times by a lot. See
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# https://groups.google.com/a/tensorflow.org/d/topic/build/SsW98Eo7l3o/discussion
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build:release_windows_common --copt=/d2ReducedOptimizeHugeFunctions --host_copt=/d2ReducedOptimizeHugeFunctions
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build:release_cpu_windows --config=release_windows_common
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build:release_gpu_windows --config=release_windows_common
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build:release_gpu_linux_cuda_10_1 --config=release_gpu_linux
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build:release_gpu_linux_cuda_10_1 --action_env CUDA_TOOLKIT_PATH="/usr/local/cuda-10.1"
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build:release_gpu_linux_cuda_10_1 --action_env=TF_CUDA_VERSION="10"
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build:release_gpu_linux_cuda_10_1 --action_env=TF_CUDNN_VERSION="7"
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# Address sanitizer
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# CC=clang bazel build --config asan
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build:asan --strip=never
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build:asan --copt -fsanitize=address
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build:asan --copt -DADDRESS_SANITIZER
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build:asan --copt -g
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build:asan --copt -O3
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build:asan --copt -fno-omit-frame-pointer
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build:asan --linkopt -fsanitize=address
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# Memory sanitizer
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# CC=clang bazel build --config asan
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build:msan --strip=never
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build:msan --copt -fsanitize=memory
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build:msan --copt -DADDRESS_SANITIZER
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build:msan --copt -g
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build:msan --copt -O3
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build:msan --copt -fno-omit-frame-pointer
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build:msan --linkopt -fsanitize=memory
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# Undefined Behavior Sanitizer
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# CC=clang bazel build --config asan
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build:ubsan --strip=never
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build:ubsan --copt -fsanitize=undefined
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build:ubsan --copt -g
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build:ubsan --copt -O3
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build:ubsan --copt -fno-omit-frame-pointer
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build:ubsan --linkopt -fsanitize=undefined
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build:ubsan --linkopt -lubsan
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