forked from ROCm/tensorflow-upstream
-
Notifications
You must be signed in to change notification settings - Fork 0
/
.bazelrc
887 lines (770 loc) · 49.8 KB
/
.bazelrc
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
# TensorFlow Bazel configuration file.
# This file tries to group and simplify build options for TensorFlow
#
# ----CONFIG OPTIONS----
# Android options:
# android:
# android_arm:
# android_arm64:
# android_x86:
# android_x86_64:
#
# iOS options:
# ios:
# ios_armv7:
# ios_arm64:
# ios_x86_64:
# ios_fat:
#
# Macosx options
# darwin_arm64:
#
# Compiler options:
# cuda_clang: Use Clang when building CUDA code.
# avx_linux: Build with avx instruction set on linux.
# avx_win: Build with avx instruction set on windows
#
# Other build options:
# short_logs: Only log errors during build, skip warnings.
# verbose_logs: Show all compiler warnings during build.
# monolithic: Build all TF C++ code into a single shared object.
# dynamic_kernels: Try to link all kernels dynamically (experimental).
# dbg: Build with debug info
#
# TF version options;
# v2: Build TF v2
#
# Feature and Third party library support options:
# xla: Build TF with XLA
# tpu: Build TF with TPU support
# cuda: Build with full cuda support.
# cuda_clang Build with CUDA Clang support.
# rocm: Build with AMD GPU support (rocm)
# mkl: Enable full mkl support.
# tensorrt: Enable Tensorrt support.
# noaws: Disable AWS S3 storage support
# nogcp: Disable GCS support.
# nohdfs: Disable hadoop hdfs support.
# nonccl: Disable nccl support.
#
#
# Remote build execution options (only configured to work with TF team projects for now.)
# rbe_base: General RBE options shared by all flavors.
# rbe_linux: General RBE options used on all linux builds.
# rbe_win: General RBE options used on all windows builds.
#
# rbe_linux_cpu: RBE options to build with only CPU support.
# rbe_linux_cuda: RBE options to build with GPU support using clang.
# rbe_linux_cuda_nvcc: RBE options to build with GPU support using nvcc.
#
# rbe_win_py39: Windows Python 3.9 RBE config
#
# tensorflow_testing_rbe_win: RBE options to use RBE with tensorflow-testing project on windows
#
# Embedded Linux options (experimental and only tested with TFLite build yet)
# elinux: General Embedded Linux options shared by all flavors.
# elinux_aarch64: Embedded Linux options for aarch64 (ARM64) CPU support.
# elinux_armhf: Embedded Linux options for armhf (ARMv7) CPU support.
#
# Release build options (for all operating systems)
# release_base: Common options for all builds on all operating systems.
# release_cpu_linux: Toolchain and CUDA options for Linux CPU builds.
# release_gpu_linux: Toolchain and CUDA options for Linux GPU builds.
# release_cpu_macos: Toolchain and CUDA options for MacOS CPU builds.
# release_cpu_windows: Toolchain and CUDA options for Windows CPU builds.
# Default build options. These are applied first and unconditionally.
# For projects which use TensorFlow as part of a Bazel build process, putting
# nothing in a bazelrc will default to a monolithic build. The following line
# opts in to modular op registration support by default.
build --define framework_shared_object=true
build --define tsl_protobuf_header_only=true
build --define=use_fast_cpp_protos=true
build --define=allow_oversize_protos=true
build --spawn_strategy=standalone
build -c opt
# Make Bazel print out all options from rc files.
build --announce_rc
# TODO(mihaimaruseac): Document this option or remove if no longer needed
build --define=grpc_no_ares=true
# See https://github.com/bazelbuild/bazel/issues/7362 for information on what
# --incompatible_remove_legacy_whole_archive flag does.
# This flag is set to true in Bazel 1.0 and newer versions. We tried to migrate
# Tensorflow to the default, however test coverage wasn't enough to catch the
# errors.
# There is ongoing work on Bazel team's side to provide support for transitive
# shared libraries. As part of migrating to transitive shared libraries, we
# hope to provide a better mechanism for control over symbol exporting, and
# then tackle this issue again.
#
# TODO: Remove the following two lines once TF doesn't depend on Bazel wrapping
# all library archives in -whole_archive -no_whole_archive.
build --noincompatible_remove_legacy_whole_archive
build --features=-force_no_whole_archive
# TODO(mihaimaruseac): Document this option or remove if no longer needed
build --enable_platform_specific_config
# Enable XLA support by default.
build --define=with_xla_support=true
# TODO(mihaimaruseac): Document this option or remove if no longer needed
build --config=short_logs
# TODO(mihaimaruseac): Document this option or remove if no longer needed
build --config=v2
# Disable AWS/HDFS support by default
build --define=no_aws_support=true
build --define=no_hdfs_support=true
# TF now has `cc_shared_library` targets, so it needs the experimental flag
# TODO(rostam): Remove when `cc_shared_library` is enabled by default
build --experimental_cc_shared_library
# cc_shared_library ensures no library is linked statically more than once.
build --experimental_link_static_libraries_once=false
# Prevent regressions on those two incompatible changes
# TODO: remove those flags when they are flipped in the default Bazel version TF uses.
build --incompatible_enforce_config_setting_visibility
# TODO: also enable this flag after fixing the visbility violations
# build --incompatible_config_setting_private_default_visibility
# Default options should come above this line.
# Android configs. Bazel needs to have --cpu and --fat_apk_cpu both set to the
# target CPU to build transient dependencies correctly. See
# https://docs.bazel.build/versions/master/user-manual.html#flag--fat_apk_cpu
build:android --crosstool_top=//external:android/crosstool
build:android --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
build:android_arm --config=android
build:android_arm --cpu=armeabi-v7a
build:android_arm --fat_apk_cpu=armeabi-v7a
build:android_arm64 --config=android
build:android_arm64 --cpu=arm64-v8a
build:android_arm64 --fat_apk_cpu=arm64-v8a
build:android_x86 --config=android
build:android_x86 --cpu=x86
build:android_x86 --fat_apk_cpu=x86
build:android_x86_64 --config=android
build:android_x86_64 --cpu=x86_64
build:android_x86_64 --fat_apk_cpu=x86_64
# Build everything statically for Android since all static libs are later
# bundled together into a single .so for deployment.
build:android --dynamic_mode=off
# Sets the default Apple platform to macOS.
build:macos --apple_platform_type=macos
# gRPC on MacOS requires this #define
build:macos --copt=-DGRPC_BAZEL_BUILD
# Avoid hitting command line argument limit
build:macos --features=archive_param_file
# Settings for MacOS on ARM CPUs.
build:macos_arm64 --cpu=darwin_arm64
build:macos_arm64 --macos_minimum_os=11.0
# iOS configs for each architecture and the fat binary builds.
build:ios --apple_platform_type=ios
build:ios --apple_bitcode=embedded --copt=-fembed-bitcode
build:ios --copt=-Wno-c++11-narrowing
build:ios_armv7 --config=ios
build:ios_armv7 --cpu=ios_armv7
build:ios_arm64 --config=ios
build:ios_arm64 --cpu=ios_arm64
build:ios_arm64e --config=ios
build:ios_arm64e --cpu=ios_arm64e
build:ios_sim_arm64 --config=ios
build:ios_sim_arm64 --cpu=ios_sim_arm64
build:ios_x86_64 --config=ios
build:ios_x86_64 --cpu=ios_x86_64
build:ios_fat --config=ios
build:ios_fat --ios_multi_cpus=armv7,arm64,i386,x86_64
# Config to use a mostly-static build and disable modular op registration
# support (this will revert to loading TensorFlow with RTLD_GLOBAL in Python).
# By default, TensorFlow will build with a dependence on
# //tensorflow:libtensorflow_framework.so.
build:monolithic --define framework_shared_object=false
build:monolithic --define tsl_protobuf_header_only=false
build:monolithic --experimental_link_static_libraries_once=false # b/229868128
# Please note that MKL on MacOS is still not supported.
# If you would like to use a local MKL instead of downloading, please set the
# environment variable "TF_MKL_ROOT" every time before build.
build:mkl --define=build_with_mkl=true --define=enable_mkl=true
build:mkl --define=tensorflow_mkldnn_contraction_kernel=0
build:mkl --define=build_with_openmp=true
build:mkl -c opt
# config to build OneDNN backend with a user specified threadpool.
build:mkl_threadpool --define=build_with_mkl=true --define=enable_mkl=true
build:mkl_threadpool --define=tensorflow_mkldnn_contraction_kernel=0
build:mkl_threadpool --define=build_with_mkl_opensource=true
build:mkl_threadpool -c opt
# Config setting to build oneDNN with Compute Library for the Arm Architecture (ACL).
build:mkl_aarch64 --define=build_with_mkl_aarch64=true
build:mkl_aarch64 --define=build_with_openmp=true
build:mkl_aarch64 --define=build_with_acl=true
build:mkl_aarch64 -c opt
# Config setting to build oneDNN with Compute Library for the Arm Architecture (ACL).
# with Eigen threadpool support
build:mkl_aarch64_threadpool --define=build_with_mkl_aarch64=true
build:mkl_aarch64_threadpool -c opt
# CUDA: This config refers to building CUDA op kernels with nvcc.
build:cuda --repo_env TF_NEED_CUDA=1
build:cuda --crosstool_top=@local_config_cuda//crosstool:toolchain
build:cuda --@local_config_cuda//:enable_cuda
# CUDA: This config refers to building CUDA op kernels with clang.
build:cuda_clang --config=cuda
# Enable TensorRT optimizations https://developer.nvidia.com/tensorrt
build:cuda_clang --config=tensorrt
build:cuda_clang --action_env=TF_CUDA_CLANG="1"
build:cuda_clang --@local_config_cuda//:cuda_compiler=clang
# Select supported compute capabilities (supported graphics cards).
# This is the same as the official TensorFlow builds.
# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX
# is forward compatible beyond the current compute capability major
# release while SASS is only forward compatible inside the current
# major release. Example: sm_80 kernels can run on sm_89 GPUs but
# not on sm_90 GPUs. compute_80 kernels though can also run on sm_90 GPUs.
build:cuda_clang --repo_env=TF_CUDA_COMPUTE_CAPABILITIES="sm_50,sm_60,sm_70,sm_80,compute_90"
# Set up compilation CUDA version and paths and use the CUDA Clang toolchain.
build:cuda_clang_official --config=cuda_clang
build:cuda_clang_official --action_env=TF_CUDA_VERSION="12"
build:cuda_clang_official --action_env=TF_CUDNN_VERSION="8"
build:cuda_clang_official --action_env=CUDA_TOOLKIT_PATH="/usr/local/cuda-12.2"
build:cuda_clang_official --action_env=GCC_HOST_COMPILER_PATH="/dt9/usr/bin/gcc"
build:cuda_clang_official --action_env=CLANG_CUDA_COMPILER_PATH="/usr/lib/llvm-17/bin/clang"
build:cuda_clang_official --action_env=LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"
build:cuda_clang_official --crosstool_top="@sigbuild-r2.16-clang_config_cuda//crosstool:toolchain"
# Debug config
build:dbg -c dbg
# Only include debug info for files under tensorflow/, excluding kernels, to
# reduce the size of the debug info in the binary. This is because if the debug
# sections in the ELF binary are too large, errors can occur. See
# https://github.com/tensorflow/tensorflow/issues/48919.
# Users can still include debug info for a specific kernel, e.g. with:
# --config=dbg --per_file_copt=+tensorflow/core/kernels/identity_op.*@-g
# Since this .bazelrc file is synced between the tensorflow/tensorflow repo and
# the openxla/xla repo, also include debug info for files under xla/.
build:dbg --per_file_copt=+.*,-tensorflow.*,-xla.*@-g0
build:dbg --per_file_copt=+tensorflow/core/kernels.*@-g0
# for now, disable arm_neon. see: https://github.com/tensorflow/tensorflow/issues/33360
build:dbg --cxxopt -DTF_LITE_DISABLE_X86_NEON
# AWS SDK must be compiled in release mode. see: https://github.com/tensorflow/tensorflow/issues/37498
build:dbg --copt -DDEBUG_BUILD
# Config to build TF TPU
build:tpu --define=with_tpu_support=true
build:tpu --define=framework_shared_object=true
build:tpu --copt=-DLIBTPU_ON_GCE
build:tpu --define=enable_mlir_bridge=true
build:tensorrt --repo_env TF_NEED_TENSORRT=1
build:rocm_base --crosstool_top=@local_config_rocm//crosstool:toolchain
build:rocm_base --define=using_rocm_hipcc=true
build:rocm_base --define=tensorflow_mkldnn_contraction_kernel=0
build:rocm_base --repo_env TF_NEED_ROCM=1
build:rocm --config=rocm_base
build:rocm --config=release_cpu_linux_base
build:rocm --action_env=CLANG_COMPILER_PATH="/usr/lib/llvm-17/bin/clang"
build:rocm --action_env=TF_ROCM_CLANG="1"
build:rocm --linkopt="-fuse-ld=lld"
# We have some invalid linker scripts in the build,
# so we need to disable this check
build:rocm --linkopt=-Wl,--undefined-version
# Disable clang extention that rejects type definitions within offsetof.
# This was added in clang-16 by https://reviews.llvm.org/D133574.
# Can be removed once upb is updated, since a type definition is used within
# offset of in the current version of ubp.
# See https://github.com/protocolbuffers/upb/blob/9effcbcb27f0a665f9f345030188c0b291e32482/upb/upb.c#L183.
build:rocm --copt=-Wno-gnu-offsetof-extensions
# TODO(rocm): Temporary due to https://github.com/openxla/xla/blob/49ad52b580ad2b81f24cc888f5cc571eb649f373/xla/stream_executor/rocm/rocm_blas.cc#L154
# to make it work with build_rocm_python3
build:rocm --copt="-Wno-unused-result"
# Options to disable default on features
build:noaws --define=no_aws_support=true
build:nogcp --define=no_gcp_support=true
build:nohdfs --define=no_hdfs_support=true
build:nonccl --define=no_nccl_support=true
# Modular TF build options
build:dynamic_kernels --define=dynamic_loaded_kernels=true
build:dynamic_kernels --copt=-DAUTOLOAD_DYNAMIC_KERNELS
# Don't trigger --config=<host platform> when cross-compiling.
build:android --noenable_platform_specific_config
build:ios --noenable_platform_specific_config
# Suppress all C++ compiler warnings, otherwise build logs become 10s of MBs.
build:android --copt=-w
build:ios --copt=-w
build:linux --host_copt=-w
build:macos --copt=-w
build:windows --copt=/W0
build:windows --host_copt=/W0
# Suppress most C++ complier warnings to reduce log size but allow
# for specific warnings to still be present.
build:linux --copt="-Wno-all"
build:linux --copt="-Wno-extra"
build:linux --copt="-Wno-deprecated"
build:linux --copt="-Wno-deprecated-declarations"
build:linux --copt="-Wno-ignored-attributes"
build:linux --copt="-Wno-array-bounds"
# TODO(rocm): Re-enable on clang switch
#build:linux --copt="-Wno-error=array-parameter"
# Add unused-result as an error on Linux.
build:linux --copt="-Wunused-result"
build:linux --copt="-Werror=unused-result"
# Add switch as an error on Linux.
build:linux --copt="-Wswitch"
build:linux --copt="-Werror=switch"
# Required for building with clang
build:linux --copt="-Wno-error=unused-but-set-variable"
# We have some invalid linker scripts in the build,
# so we need to disable this check
build:linux --linkopt=-Wl,--undefined-version
build:linux --host_linkopt=-Wl,--undefined-version
# Linux ARM64 specific options
build:linux_arm64 --copt="-mtune=generic" --copt="-march=armv8-a" --copt="-O3"
# On Windows, `__cplusplus` is wrongly defined without this switch
# See https://devblogs.microsoft.com/cppblog/msvc-now-correctly-reports-__cplusplus/
build:windows --copt=/Zc:__cplusplus
build:windows --host_copt=/Zc:__cplusplus
# Tensorflow uses M_* math constants that only get defined by MSVC headers if
# _USE_MATH_DEFINES is defined.
build:windows --copt=/D_USE_MATH_DEFINES
build:windows --host_copt=/D_USE_MATH_DEFINES
# Windows has a relatively short command line limit, which TF has begun to hit.
# See https://docs.bazel.build/versions/main/windows.html
build:windows --features=compiler_param_file
build:windows --features=archive_param_file
# Speed Windows compile times. Available in VS 16.4 (we are on 16.11). See
# https://groups.google.com/a/tensorflow.org/d/topic/build/SsW98Eo7l3o/discussion
build:windows --copt=/d2ReducedOptimizeHugeFunctions
build:windows --host_copt=/d2ReducedOptimizeHugeFunctions
# Enable the runfiles symlink tree on Windows. This makes it possible to build
# the pip package on Windows without an intermediate data-file archive, as the
# build_pip_package script in its current form (as of Aug 2023) uses the
# runfiles symlink tree to decide what to put into the Python wheel.
startup --windows_enable_symlinks
build:windows --enable_runfiles
# Default paths for TF_SYSTEM_LIBS
build:linux --define=PREFIX=/usr
build:linux --define=LIBDIR=$(PREFIX)/lib
build:linux --define=INCLUDEDIR=$(PREFIX)/include
build:linux --define=PROTOBUF_INCLUDE_PATH=$(PREFIX)/include
build:macos --define=PREFIX=/usr
build:macos --define=LIBDIR=$(PREFIX)/lib
build:macos --define=INCLUDEDIR=$(PREFIX)/include
build:macos --define=PROTOBUF_INCLUDE_PATH=$(PREFIX)/include
# TF_SYSTEM_LIBS do not work on windows.
# By default, build TF in C++ 17 mode.
build:android --cxxopt=-std=c++17
build:android --host_cxxopt=-std=c++17
build:ios --cxxopt=-std=c++17
build:ios --host_cxxopt=-std=c++17
build:linux --cxxopt=-std=c++17
build:linux --host_cxxopt=-std=c++17
build:macos --cxxopt=-std=c++17
build:macos --host_cxxopt=-std=c++17
build:windows --cxxopt=/std:c++17
build:windows --host_cxxopt=/std:c++17
# On windows, we still link everything into a single DLL.
build:windows --config=monolithic
# On linux, we dynamically link small amount of kernels
build:linux --config=dynamic_kernels
# Make sure to include as little of windows.h as possible
build:windows --copt=-DWIN32_LEAN_AND_MEAN
build:windows --host_copt=-DWIN32_LEAN_AND_MEAN
build:windows --copt=-DNOGDI
build:windows --host_copt=-DNOGDI
# MSVC (Windows): Standards-conformant preprocessor mode
# See https://docs.microsoft.com/en-us/cpp/preprocessor/preprocessor-experimental-overview
build:windows --copt=/Zc:preprocessor
build:windows --host_copt=/Zc:preprocessor
# Misc build options we need for windows.
build:windows --linkopt=/DEBUG
build:windows --host_linkopt=/DEBUG
build:windows --linkopt=/OPT:REF
build:windows --host_linkopt=/OPT:REF
build:windows --linkopt=/OPT:ICF
build:windows --host_linkopt=/OPT:ICF
# Verbose failure logs when something goes wrong
build:windows --verbose_failures
# Work around potential issues with large command lines on windows.
# See: https://github.com/bazelbuild/bazel/issues/5163
build:windows --features=compiler_param_file
# Do not risk cache corruption. See:
# https://github.com/bazelbuild/bazel/issues/3360
build:linux --experimental_guard_against_concurrent_changes
# Configure short or long logs
build:short_logs --output_filter=DONT_MATCH_ANYTHING
build:verbose_logs --output_filter=
# Instruction set optimizations
# TODO(gunan): Create a feature in toolchains for avx/avx2 to
# avoid having to define linux/win separately.
build:avx_linux --copt=-mavx
build:avx_linux --host_copt=-mavx
build:avx_win --copt=/arch:AVX
# Use Clang-cl compiler on Windows
build:win_clang --copt=/clang:-Weverything
build:win_clang --extra_toolchains=@local_config_cc//:cc-toolchain-x64_windows-clang-cl
build:win_clang --extra_execution_platforms=//tensorflow/tools/toolchains/win:x64_windows-clang-cl
build:win_clang --host_platform=//tensorflow/tools/toolchains/win:x64_windows-clang-cl
build:win_clang --compiler=clang-cl
build:win_clang --linkopt=/FORCE:MULTIPLE
build:win_clang --host_linkopt=/FORCE:MULTIPLE
test:win_clang --linkopt=/FORCE:MULTIPLE
test:win_clang --host_linkopt=/FORCE:MULTIPLE
# Options to build TensorFlow 1.x or 2.x.
# TODO(kanglan): Change v2's define to default behavior
build:v2 --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1
# Disable XLA on mobile.
build:xla --define=with_xla_support=true # TODO: remove, it's on by default.
build:android --define=with_xla_support=false
build:ios --define=with_xla_support=false
# BEGIN TF REMOTE BUILD EXECUTION OPTIONS
# Options when using remote execution
# WARNING: THESE OPTIONS WONT WORK IF YOU DO NOT HAVE PROPER AUTHENTICATION AND PERMISSIONS
# Allow creation of resultstore URLs for any bazel invocation
build:resultstore --google_default_credentials
build:resultstore --bes_backend=buildeventservice.googleapis.com
build:resultstore --bes_instance_name="tensorflow-testing"
build:resultstore --bes_results_url="https://source.cloud.google.com/results/invocations"
build:resultstore --bes_timeout=600s
# Flag to enable remote config
common --experimental_repo_remote_exec
# Make Bazel not try to probe the host system for a C++ toolchain.
build:rbe_base --config=resultstore
build:rbe_base --repo_env=BAZEL_DO_NOT_DETECT_CPP_TOOLCHAIN=1
build:rbe_base --define=EXECUTOR=remote
build:rbe_base --jobs=800
build:rbe_base --remote_executor=grpcs://remotebuildexecution.googleapis.com
build:rbe_base --remote_timeout=3600
build:rbe_base --spawn_strategy=remote,worker,standalone,local
# Attempt to minimize the amount of data transfer between bazel and the remote
# workers:
build:rbe_base --remote_download_toplevel
test:rbe_base --test_env=USER=anon
# TODO(kanglan): Check if we want to merge rbe_linux into rbe_linux_cpu.
build:rbe_linux --config=rbe_base
build:rbe_linux --action_env=PATH="/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/go/bin"
# Non-rbe settings we should include because we do not run configure
build:rbe_linux --config=avx_linux
# TODO(gunan): Check why we need this specified in rbe, but not in other builds.
build:rbe_linux --linkopt=-lrt
build:rbe_linux --host_linkopt=-lrt
build:rbe_linux --linkopt=-lm
build:rbe_linux --host_linkopt=-lm
build:rbe_linux_cpu --config=rbe_linux
# Linux cpu and cuda builds share the same toolchain now.
build:rbe_linux_cpu --host_crosstool_top="@sigbuild-r2.16-clang_config_cuda//crosstool:toolchain"
build:rbe_linux_cpu --crosstool_top="@sigbuild-r2.16-clang_config_cuda//crosstool:toolchain"
build:rbe_linux_cpu --extra_toolchains="@sigbuild-r2.16-clang_config_cuda//crosstool:toolchain-linux-x86_64"
build:rbe_linux_cpu --extra_execution_platforms="@sigbuild-r2.16-clang_config_platform//:platform"
build:rbe_linux_cpu --host_platform="@sigbuild-r2.16-clang_config_platform//:platform"
build:rbe_linux_cpu --platforms="@sigbuild-r2.16-clang_config_platform//:platform"
# This is needed for all Clang17 builds but must not be present in GCC builds.
build:rbe_linux_cpu --copt=-Wno-error=unused-command-line-argument
# This was added in clang-16 by https://reviews.llvm.org/D133574.
# Can be removed once upb is updated, since a type definition is used within
# offset of in the current version of ubp.
# See https://github.com/protocolbuffers/upb/blob/9effcbcb27f0a665f9f345030188c0b291e32482/upb/upb.c#L183.
build:rbe_linux_cpu --copt=-Wno-gnu-offsetof-extensions
# Python config is the same across all containers because the binary is the same
build:rbe_linux_cpu --repo_env=TF_PYTHON_CONFIG_REPO="@sigbuild-r2.16-clang_config_python"
build:rbe_linux_cpu --python_path="/usr/bin/python3"
# These you may need to change for your own GCP project.
common:rbe_linux_cpu --remote_instance_name=projects/tensorflow-testing/instances/default_instance
# TODO(kanglan): Remove it after toolchain update is complete.
build:rbe_linux_cpu_old --config=rbe_linux
build:rbe_linux_cpu_old --host_crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
build:rbe_linux_cpu_old --crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
build:rbe_linux_cpu_old --extra_toolchains="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain-linux-x86_64"
build:rbe_linux_cpu_old --extra_execution_platforms="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_linux_cpu_old --host_platform="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_linux_cpu_old --platforms="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_platform//:platform"
build:rbe_linux_cpu_old --python_path="/usr/local/bin/python3.9"
build:rbe_linux_cpu_old --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_python3.9"
common:rbe_linux_cpu_old --remote_instance_name=projects/tensorflow-testing/instances/default_instance
build:rbe_linux_cuda --config=cuda_clang_official
build:rbe_linux_cuda --config=rbe_linux_cpu
# For Remote build execution -- GPU configuration
build:rbe_linux_cuda --repo_env=REMOTE_GPU_TESTING=1
build:rbe_linux_cuda --repo_env=TF_CUDA_CONFIG_REPO="@sigbuild-r2.16-clang_config_cuda"
build:rbe_linux_cuda --repo_env=TF_TENSORRT_CONFIG_REPO="@sigbuild-r2.16-clang_config_tensorrt"
build:rbe_linux_cuda --repo_env=TF_NCCL_CONFIG_REPO="@sigbuild-r2.16-clang_config_nccl"
test:rbe_linux_cuda --test_env=LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"
# ROCm
# TODO(rocm) Is this actualy used?
build:rbe_linux_rocm_base --config=rocm_base
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_py3.9 --config=rbe_linux_rocm_base --repo_env=TF_PYTHON_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-rocm_config_python3.9"
build:rbe_linux_cuda_nvcc --config=rbe_linux_cuda
build:rbe_linux_cuda_nvcc --repo_env TF_NCCL_USE_STUB=1
build:rbe_linux_cuda_nvcc --action_env=TF_NVCC_CLANG="1"
# TODO(kanglan): Remove rbe_win and rbe_win_py3* after b/289091160 is fixed
build:rbe_win --config=rbe_base
build:rbe_win --crosstool_top="//tensorflow/tools/toolchains/win/tf_win_05022023:toolchain"
build:rbe_win --extra_toolchains="//tensorflow/tools/toolchains/win/tf_win_05022023:cc-toolchain-x64_windows"
build:rbe_win --extra_execution_platforms="//tensorflow/tools/toolchains/win:rbe_windows_ltsc2019"
build:rbe_win --host_platform="//tensorflow/tools/toolchains/win:rbe_windows_ltsc2019"
build:rbe_win --platforms="//tensorflow/tools/toolchains/win:rbe_windows_ltsc2019"
build:rbe_win --shell_executable=C:\\tools\\msys64\\usr\\bin\\bash.exe
build:rbe_win --experimental_strict_action_env=true
# TODO(gunan): Remove once we use MSVC 2019 with latest patches.
build:rbe_win --define=override_eigen_strong_inline=true
# Don't build the python zip archive in the RBE build.
build:rbe_win --remote_download_minimal
build:rbe_win --enable_runfiles
build:rbe_win --nobuild_python_zip
build:rbe_win_py38 --config=rbe_base
build:rbe_win_py38 --repo_env=PYTHON_BIN_PATH=C:\\Python38\\python.exe
build:rbe_win_py38 --repo_env=PYTHON_LIB_PATH=C:\\Python38\\lib\\site-packages
build:rbe_win_py38 --repo_env=TF_PYTHON_CONFIG_REPO=//tensorflow/tools/toolchains/win_1803/py38
build:rbe_win_py38 --python_path=C:\\Python38\\python.exe
build:rbe_win_py39 --config=rbe_base
build:rbe_win_py39 --repo_env=PYTHON_BIN_PATH=C:\\Python39\\python.exe
build:rbe_win_py39 --repo_env=PYTHON_LIB_PATH=C:\\Python39\\lib\\site-packages
build:rbe_win_py39 --repo_env=TF_PYTHON_CONFIG_REPO=//tensorflow/tools/toolchains/win_1803/py39
build:rbe_win_py39 --python_path=C:\\Python39\\python.exe
# TODO(kanglan): Merge tensorflow_testing_rbe_win into rbe_win
common:tensorflow_testing_rbe_win --remote_instance_name=projects/tensorflow-testing/instances/windows
# END TF REMOTE BUILD EXECUTION OPTIONS
# TFLite build configs for generic embedded Linux
build:elinux --crosstool_top=@local_config_embedded_arm//:toolchain
build:elinux --host_crosstool_top=@bazel_tools//tools/cpp:toolchain
build:elinux_aarch64 --config=elinux
build:elinux_aarch64 --cpu=aarch64
build:elinux_armhf --config=elinux
build:elinux_armhf --cpu=armhf
build:elinux_armhf --copt -mfp16-format=ieee
# Config-specific options should come above this line.
# Load rc file written by ./configure.
try-import %workspace%/.tf_configure.bazelrc
# Load rc file with user-specific options.
try-import %workspace%/.bazelrc.user
# Here are bazelrc configs for release builds
# Build TensorFlow v2.
test:release_base --test_size_filters=small,medium
# Target the AVX instruction set
build:release_linux_base --config=avx_linux
# Disable clang extention that rejects type definitions within offsetof.
# This was added in clang-16 by https://reviews.llvm.org/D133574.
# Can be removed once upb is updated, since a type definition is used within
# offset of in the current version of ubp.
# See https://github.com/protocolbuffers/upb/blob/9effcbcb27f0a665f9f345030188c0b291e32482/upb/upb.c#L183.
build:release_linux_base --copt=-Wno-gnu-offsetof-extensions
build:release_linux_base --copt=-Wno-error=array-parameter
build:release_linux_base --copt=-Wno-error=unused-command-line-argument
# Set lld as the linker.
build:release_linux_base --linkopt="-fuse-ld=lld"
build:release_linux_base --linkopt="-lm"
# We have some invalid linker scripts in the build,
# so we need to disable this check
build:release_linux_base --linkopt=-Wl,--undefined-version
# Container environment settings below this point.
# Use Python 3.X as installed in container image
build:release_linux_base --action_env PYTHON_BIN_PATH="/usr/bin/python3"
build:release_linux_base --action_env PYTHON_LIB_PATH="/usr/lib/tf_python"
build:release_linux_base --python_path="/usr/bin/python3"
# Set Clang as compiler. Use the actual path to clang installed in container.
build:release_cpu_linux_base --repo_env=CC="/usr/lib/llvm-17/bin/clang"
build:release_cpu_linux_base --repo_env=BAZEL_COMPILER="/usr/lib/llvm-17/bin/clang"
# Test-related settings below this point.
test:release_linux_base --build_tests_only --keep_going --test_output=errors --verbose_failures=true
test:release_linux_base --local_test_jobs=HOST_CPUS
test:release_linux_base --test_env=LD_LIBRARY_PATH
# Give only the list of failed tests at the end of the log
test:release_linux_base --test_summary=short
# Use the Clang toolchain to compile
build:release_cpu_linux --config=release_linux_base
build:release_cpu_linux --crosstool_top="@sigbuild-r2.16-clang_config_cuda//crosstool:toolchain"
build:release_gpu_linux --config=release_cpu_linux
# Set up compilation CUDA version and paths and use the CUDA Clang toolchain.
# Note that linux cpu and cuda builds share the same toolchain now.
build:release_gpu_linux --config=cuda_clang_official
test:release_gpu_linux --test_env=LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"
# Local test jobs has to be 4 because parallel_gpu_execute is fragile, I think
test:release_gpu_linux --test_timeout=300,450,1200,3600 --local_test_jobs=4 --run_under=//tensorflow/tools/ci_build/gpu_build:parallel_gpu_execute
build:release_arm64_linux --config=release_linux_base
build:release_arm64_linux --config=linux_arm64
build:release_arm64_linux --crosstool_top="@ml2014_clang_aarch64_config_aarch64//crosstool:toolchain"
build:release_arm64_linux --config=mkl_aarch64_threadpool
build:release_arm64_linux --copt=-flax-vector-conversions
test:release_arm64_linux --flaky_test_attempts=3
# The old gcc linux build options are preserved in the unsupported_*_linux
# configs. If your project fails to build with Clang, you can use these
# unsupported flags to replace the release flags in your build command.
# However, please note that the old toolchain is no longer officially supported
# by TensorFlow and the unsupported configs will be removed soon b/299962977. We
# strongly recommend that you migrate to Clang as your compiler for TensorFlow
# Linux builds. Instructions are available in the official documentation:
# https://www.tensorflow.org/install/source#install_clang_recommended_linux_only
# Another good option is to use our Docker containers to build and test TF:
# https://github.com/tensorflow/tensorflow/tree/master/tensorflow/tools/tf_sig_build_dockerfiles.
build:unsupported_cpu_linux --config=avx_linux
build:unsupported_cpu_linux --crosstool_top="@ubuntu20.04-gcc9_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain"
test:unsupported_cpu_linux --test_env=LD_LIBRARY_PATH
test:unsupported_cpu_linux --config=release_base
build:unsupported_gpu_linux --config=cuda
build:unsupported_gpu_linux --config=unsupported_cpu_linux
build:unsupported_gpu_linux --action_env=TF_CUDA_VERSION="11"
build:unsupported_gpu_linux --action_env=TF_CUDNN_VERSION="8"
build:unsupported_gpu_linux --repo_env=TF_CUDA_COMPUTE_CAPABILITIES="sm_35,sm_50,sm_60,sm_70,sm_75,compute_80"
build:unsupported_gpu_linux --config=tensorrt
build:unsupported_gpu_linux --action_env=CUDA_TOOLKIT_PATH="/usr/local/cuda-11.2"
build:unsupported_gpu_linux --action_env=LD_LIBRARY_PATH="/usr/local/cuda:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda-11.1/lib64:/usr/local/tensorrt/lib"
build:unsupported_gpu_linux --action_env=GCC_HOST_COMPILER_PATH="/dt9/usr/bin/gcc"
build:unsupported_gpu_linux [email protected]_manylinux2014-cuda11.2-cudnn8.1-tensorrt7.2_config_cuda//crosstool:toolchain
build:release_cpu_macos --config=avx_linux
test:release_cpu_macos --config=release_base
# Base build configs for macOS
build:release_macos_base --action_env DEVELOPER_DIR=/Applications/Xcode.app/Contents/Developer
build:release_macos_base --define=no_nccl_support=true --output_filter=^$
# Build configs for macOS x86
build:release_macos_x86 --config=release_macos_base
# Build with the AVX instruction set when on macOS x86
build:release_macos_x86 --config=avx_linux
build:release_macos_x86 --cpu=darwin
# Target Catalina as the minimum compatible OS version
build:release_macos_x86 --macos_minimum_os=10.15
build:release_macos_x86 --action_env MACOSX_DEPLOYMENT_TARGET=10.15
# Build configs for macOS Arm64
build:release_macos_arm64 --config=release_macos_base
build:release_macos_arm64 --cpu=darwin_arm64
build:release_macos_arm64 --define=tensorflow_mkldnn_contraction_kernel=0
# Target Moneterey as the minimum compatible OS version
build:release_macos_arm64 --macos_minimum_os=12.0
build:release_macos_arm64 --action_env MACOSX_DEPLOYMENT_TARGET=12.0
# Base test configs for macOS
test:release_macos_base --verbose_failures=true --local_test_jobs=HOST_CPUS
test:release_macos_base --test_timeout=300,450,1200,3600 --test_output=errors
test:release_macos_base --build_tests_only --keep_going
test:release_macos_base --flaky_test_attempts=3
# Test configs for macOS x86
test:release_macos_x86 --config=release_macos_base
# Test configs for macOS Arm64
test:release_macos_arm64 --config=release_macos_base
# TODO(kanglan): Update windows configs after b/289091160 is fixed
build:release_cpu_windows --config=avx_win
build:release_cpu_windows --define=no_tensorflow_py_deps=true
test:release_cpu_windows --config=release_base
# Exclude TFRT integration for anything but Linux.
build:android --config=no_tfrt
build:macos --config=no_tfrt
build:windows --config=no_tfrt
build:rocm_base --config=no_tfrt
build:no_tfrt --deleted_packages=tensorflow/compiler/mlir/tfrt,tensorflow/compiler/mlir/tfrt/benchmarks,tensorflow/compiler/mlir/tfrt/ir,tensorflow/compiler/mlir/tfrt/ir/mlrt,tensorflow/compiler/mlir/tfrt/jit/python_binding,tensorflow/compiler/mlir/tfrt/jit/transforms,tensorflow/compiler/mlir/tfrt/python_tests,tensorflow/compiler/mlir/tfrt/tests,tensorflow/compiler/mlir/tfrt/tests/ifrt,tensorflow/compiler/mlir/tfrt/tests/mlrt,tensorflow/compiler/mlir/tfrt/tests/ir,tensorflow/compiler/mlir/tfrt/tests/analysis,tensorflow/compiler/mlir/tfrt/tests/jit,tensorflow/compiler/mlir/tfrt/tests/lhlo_to_tfrt,tensorflow/compiler/mlir/tfrt/tests/lhlo_to_jitrt,tensorflow/compiler/mlir/tfrt/tests/tf_to_corert,tensorflow/compiler/mlir/tfrt/tests/tf_to_tfrt_data,tensorflow/compiler/mlir/tfrt/tests/saved_model,tensorflow/compiler/mlir/tfrt/transforms/lhlo_gpu_to_tfrt_gpu,tensorflow/compiler/mlir/tfrt/transforms/mlrt,tensorflow/core/runtime_fallback,tensorflow/core/runtime_fallback/conversion,tensorflow/core/runtime_fallback/kernel,tensorflow/core/runtime_fallback/opdefs,tensorflow/core/runtime_fallback/runtime,tensorflow/core/runtime_fallback/util,tensorflow/core/runtime_fallback/test,tensorflow/core/runtime_fallback/test/gpu,tensorflow/core/runtime_fallback/test/saved_model,tensorflow/core/runtime_fallback/test/testdata,tensorflow/core/tfrt/stubs,tensorflow/core/tfrt/tfrt_session,tensorflow/core/tfrt/mlrt,tensorflow/core/tfrt/mlrt/attribute,tensorflow/core/tfrt/mlrt/kernel,tensorflow/core/tfrt/mlrt/bytecode,tensorflow/core/tfrt/mlrt/interpreter,tensorflow/compiler/mlir/tfrt/translate/mlrt,tensorflow/compiler/mlir/tfrt/translate/mlrt/testdata,tensorflow/core/tfrt/gpu,tensorflow/core/tfrt/run_handler_thread_pool,tensorflow/core/tfrt/runtime,tensorflow/core/tfrt/saved_model,tensorflow/core/tfrt/graph_executor,tensorflow/core/tfrt/saved_model/tests,tensorflow/core/tfrt/tpu,tensorflow/core/tfrt/utils,tensorflow/core/tfrt/utils/debug,tensorflow/core/tfrt/saved_model/python,tensorflow/core/tfrt/graph_executor/python,tensorflow/core/tfrt/saved_model/utils
# BEGIN TF CACHE HELPER OPTIONS
# Options when using remote execution
# WARNING: THESE OPTIONS WONT WORK IF YOU DO NOT HAVE PROPER AUTHENTICATION AND PERMISSIONS
# Use --config=tf_public_cache to try and use the TensorFlow public build cache
# to build TensorFlow. Look at ci/official/envs to find which types of jobs
# push to the cache. For macOS, use --config=tf_public_macos_cache
build:tf_public_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/september2022" --remote_upload_local_results=false
# Cache pushes are limited to TF's CI system.
build:tf_public_cache_push --config=tf_public_cache --remote_upload_local_results=true --google_default_credentials
# Public cache for macOS builds
build:tf_public_macos_cache --remote_cache="https://storage.googleapis.com/tensorflow-macos-bazel-cache/oct2023" --remote_upload_local_results=false
# Cache pushes are limited to TF's CI system.
build:tf_public_macos_cache_push --config=tf_public_macos_cache --remote_upload_local_results=true --google_default_credentials
# END TF CACHE HELPER OPTIONS
# BEGIN TF TEST SUITE OPTIONS
# These are convenience config options that effectively declare TF's CI test suites. Look
# at the scripts of ci/official/ to see how TF's CI uses them.
# LIBTENSORFLOW TESTS are for building Libtensorflow archives. These are CUDA/CPU-agnostic.
test:linux_libtensorflow_test -- //tensorflow/tools/lib_package:libtensorflow_test //tensorflow/tools/lib_package:libtensorflow_java_test
build:linux_libtensorflow_build -- //tensorflow/tools/lib_package:libtensorflow.tar.gz //tensorflow/tools/lib_package:libtensorflow_jni.tar.gz //tensorflow/java:libtensorflow.jar //tensorflow/java:libtensorflow-src.jar //tensorflow/tools/lib_package:libtensorflow_proto.zip
# PYTHON TESTS run a suite of Python tests intended for verifying that the Python wheel
# will work properly. These are usually run Nightly or upon Release.
# CPU WHEEL
test:linux_cpu_wheel_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310
test:linux_cpu_wheel_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310
test:linux_cpu_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium
test:linux_cpu_wheel_test --config=linux_cpu_wheel_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/...
# CUDA WHEEL
test:linux_cuda_wheel_test_filters --test_tag_filters=gpu,requires-gpu,-no_gpu,-no_oss,-oss_excluded,-oss_serial,-benchmark-test,-no_cuda11,-no_oss_py38,-no_oss_py39,-no_oss_py310
test:linux_cuda_wheel_test_filters --build_tag_filters=gpu,requires-gpu,-no_gpu,-no_oss,-oss_excluded,-oss_serial,-benchmark-test,-no_cuda11,-no_oss_py38,-no_oss_py39,-no_oss_py310
test:linux_cuda_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium
test:linux_cuda_wheel_test --config=linux_cuda_wheel_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/...
# ARM64 WHEEL
test:linux_arm64_wheel_test_filters --test_tag_filters=-no_oss,-no_aarch64,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310
test:linux_arm64_wheel_test_filters --build_tag_filters=-no_oss,-no_aarch64,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only,-no_oss_py38,-no_oss_py39,-no_oss_py310
test:linux_arm64_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium
test:linux_arm64_wheel_test --config=linux_arm64_wheel_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/core/grappler/optimizers:auto_mixed_precision_test_cpu -//tensorflow/core/grappler/optimizers:remapper_test_cpu -//tensorflow/core/kernels/image:resize_bicubic_op_test -//tensorflow/compiler/mlir/tfr/examples/customization:test_ops_test -//tensorflow/compiler/mlir/tfr/examples/mnist:mnist_ops_test -//tensorflow/compiler/mlir/tfr/examples/pad:pad_ops_test
# MACOS ARM64 WHEEL
test:macos_arm64_wheel_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test,-no_mac_arm64,-no_aarch64
test:macos_arm64_wheel_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test,-no_mac_arm64,-no_aarch64
test:macos_arm64_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium
test:macos_arm64_wheel_test --config=macos_arm64_wheel_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/compiler/aot/...
# MACOS X86 WHEEL
test:macos_x86_wheel_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py38,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test
test:macos_x86_wheel_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py38,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test
test:macos_x86_wheel_test_filters --test_lang_filters=py --test_size_filters=small,medium
test:macos_x86_wheel_test --config=macos_x86_wheel_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/compiler/aot/...
# PYCPP TESTS run a suite of Python and C++ tests to verify general correctness over
# the whole TF code base. These are usually run continuously or upon presubmit.
# CPU PYCPP:
test:linux_cpu_pycpp_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only
test:linux_cpu_pycpp_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only
test:linux_cpu_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium
test:linux_cpu_pycpp_test --config=linux_cpu_pycpp_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/...
# CUDA PYCPP:
test:linux_cuda_pycpp_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-benchmark-test,-v1only,gpu,-no_gpu,-no_gpu_presubmit,-no_cuda11
test:linux_cuda_pycpp_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-benchmark-test,-v1only,gpu,-no_gpu,-no_gpu_presubmit,-no_cuda11
test:linux_cuda_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium
test:linux_cuda_pycpp_test --config=linux_cuda_pycpp_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/...
# ARM64 PYCPP
test:linux_arm64_pycpp_test_filters --test_tag_filters=-no_oss,-no_aarch64,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only
test:linux_arm64_pycpp_test_filters --build_tag_filters=-no_oss,-no_aarch64,-oss_excluded,-oss_serial,-gpu,-tpu,-benchmark-test,-v1only
test:linux_arm64_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium --flaky_test_attempts=3
# TODO(michaelhudgins): Why do we need to specifically omit go and java here?
test:linux_arm64_pycpp_test --config=linux_arm64_pycpp_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/core/grappler/optimizers:auto_mixed_precision_test_cpu -//tensorflow/core/grappler/optimizers:remapper_test_cpu -//tensorflow/core/kernels/image:resize_bicubic_op_test -//tensorflow/compiler/mlir/tfr/examples/customization:test_ops_test -//tensorflow/compiler/mlir/tfr/examples/mnist:mnist_ops_test -//tensorflow/compiler/mlir/tfr/examples/pad:pad_ops_test -//tensorflow/python/tools:aot_compiled_test
# CROSS-COMPILE ARM64 PYCPP
test:cross_compile_linux_arm64_pycpp_test --config=linux_arm64_pycpp_test
# Tests that fail only when cross-compiled
test:cross_compile_linux_arm64_pycpp_test -//tensorflow/compiler/mlir/quantization/stablehlo:convert_tf_quant_to_mhlo_int_test
# MACOS ARM64 PYCPP
test:macos_arm64_pycpp_test_filters --test_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test,-no_mac_arm64,-no_aarch64
test:macos_arm64_pycpp_test_filters --build_tag_filters=-no_oss,-oss_excluded,-oss_serial,-no_oss_py39,-no_oss_py310,-nomac,-no_mac,-mac_excluded,-v1only,-gpu,-tpu,-benchmark-test,-no_mac_arm64,-no_aarch64
test:macos_arm64_pycpp_test_filters --test_lang_filters=cc,py --test_size_filters=small,medium
test:macos_arm64_pycpp_test --config=macos_arm64_pycpp_test_filters -- //tensorflow/... -//tensorflow/python/integration_testing/... -//tensorflow/compiler/tf2tensorrt/... -//tensorflow/core/tpu/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/... -//tensorflow/go/... -//tensorflow/java/... -//tensorflow/compiler/aot/... -//tensorflow/core/kernels/image:resize_bicubic_op_test
# END TF TEST SUITE OPTIONS
# START CROSS-COMPILE CONFIGS
# Set execution platform to Linux x86
# Note: Lot of the "host_" flags such as "host_cpu" and "host_crosstool_top"
# flags seem to be actually used to specify the execution platform details. It
# seems it is this way because these flags are old and predate the distinction
# between host and execution platform.
build:cross_compile_base --host_cpu=k8
build:cross_compile_base --host_crosstool_top=//tensorflow/tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite
build:cross_compile_base --extra_execution_platforms=//tensorflow/tools/toolchains/cross_compile/config:linux_x86_64
build:rbe_cross_compile_base --config=rbe_base
build:rbe_cross_compile_base --remote_instance_name=projects/tensorflow-testing/instances/default_instance
# Test-related settings below this point
# We cannot run cross-compiled tests on the remote Linux x86 VMs so we need to
# force all tests to run locally on the Aarch64 host.
test:rbe_cross_compile_base --strategy=TestRunner=local --build_tests_only
test:rbe_cross_compile_base --verbose_failures=true --local_test_jobs=HOST_CPUS --test_output=errors
# START LINUX AARCH64 CROSS-COMPILE CONFIGS
build:cross_compile_linux_arm64 --config=cross_compile_base
# Set the target CPU to Aarch64
build:cross_compile_linux_arm64 --platforms=//tensorflow/tools/toolchains/cross_compile/config:linux_aarch64
build:cross_compile_linux_arm64 --cpu=aarch64
build:cross_compile_linux_arm64 --crosstool_top=//tensorflow/tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite
# RBE cross-compile configs for Linux Aarch64
build:rbe_cross_compile_linux_arm64 --config=cross_compile_linux_arm64
build:rbe_cross_compile_linux_arm64 --config=rbe_cross_compile_base
test:rbe_cross_compile_linux_arm64 --config=rbe_cross_compile_base
# END LINUX AARCH64 CROSS-COMPILE CONFIGS
# START MACOS CROSS-COMPILE CONFIGS
build:cross_compile_macos_x86 --config=cross_compile_base
build:cross_compile_macos_x86 --config=nonccl
# Target Catalina (10.15) as the minimum supported OS
build:cross_compile_macos_x86 --action_env MACOSX_DEPLOYMENT_TARGET=10.15
# Set the target CPU to Darwin x86
build:cross_compile_macos_x86 --platforms=//tensorflow/tools/toolchains/cross_compile/config:darwin_x86_64
build:cross_compile_macos_x86 --cpu=darwin
build:cross_compile_macos_x86 --crosstool_top=//tensorflow/tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite
# When RBE cross-compiling for macOS, we need to explictly register the
# toolchain. Otherwise, oddly, RBE complains that a "docker container must be
# specified".
build:cross_compile_macos_x86 --extra_toolchains=//tensorflow/tools/toolchains/cross_compile/config:macos-x86-cross-compile-cc-toolchain
# Map --platforms=darwin_x86_64 to --cpu=darwin and vice-versa to make selects()
# and transistions that use these flags work.
build:cross_compile_macos_x86 --platform_mappings=tensorflow/tools/toolchains/cross_compile/config/platform_mappings
# RBE cross-compile configs for Darwin x86
build:rbe_cross_compile_macos_x86 --config=cross_compile_macos_x86
build:rbe_cross_compile_macos_x86 --config=rbe_cross_compile_base
test:rbe_cross_compile_macos_x86 --config=rbe_cross_compile_base
# END MACOS CROSS-COMPILE CONFIGS
# END CROSS-COMPILE CONFIGS