cmake_minimum_required(VERSION 3.10 FATAL_ERROR) #cmake_policy(SET CMP0022 NEW) #cmake_policy(SET CMP0023 NEW) # Use compiler ID "AppleClang" instead of "Clang" for XCode. # Not setting this sometimes makes XCode C compiler gets detected as "Clang", # even when the C++ one is detected as "AppleClang". cmake_policy(SET CMP0010 NEW) cmake_policy(SET CMP0025 NEW) # Suppress warning flags in default MSVC configuration. It's not # mandatory that we do this (and we don't if cmake is old), but it's # nice when it's possible, and it's possible on our Windows configs. if(NOT CMAKE_VERSION VERSION_LESS 3.15.0) cmake_policy(SET CMP0092 NEW) endif() if(NOT CMAKE_VERSION VERSION_LESS 3.10) set(FIND_CUDA_MODULE_DEPRECATED ON) endif() # ---[ Project and semantic versioning. project(Torch CXX C) if(${CMAKE_SYSTEM_NAME} STREQUAL "Linux") set(LINUX TRUE) else() set(LINUX FALSE) endif() set(CMAKE_INSTALL_MESSAGE NEVER) # check and set CMAKE_CXX_STANDARD string(FIND "${CMAKE_CXX_FLAGS}" "-std=c++" env_cxx_standard) if(env_cxx_standard GREATER -1) message( WARNING "C++ standard version definition detected in environment variable." "PyTorch requires -std=c++14. Please remove -std=c++ settings in your environment.") endif() set(CMAKE_CXX_STANDARD 14) set(CMAKE_C_STANDARD 11) if(DEFINED GLIBCXX_USE_CXX11_ABI) if(${GLIBCXX_USE_CXX11_ABI} EQUAL 1) set(CXX_STANDARD_REQUIRED ON) set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -D_GLIBCXX_USE_CXX11_ABI=1") endif() endif() set(CMAKE_EXPORT_COMPILE_COMMANDS ON) # One variable that determines whether the current cmake process is being run # with the main Caffe2 library. This is useful for building modules - if # modules are built with the main Caffe2 library then one does not need to do # find caffe2 in the cmake script. One can usually guard it in some way like # if(NOT CAFFE2_CMAKE_BUILDING_WITH_MAIN_REPO) # find_package(Caffe2 REQUIRED) # endif() set(CAFFE2_CMAKE_BUILDING_WITH_MAIN_REPO ON) # Googletest's cmake files are going to set it on once they are processed. Let's # set it at the very beginning so that the entire build is deterministic. set(THREADS_PREFER_PTHREAD_FLAG ON) if(NOT DEFINED BLAS_SET_BY_USER) if(DEFINED BLAS) set(BLAS_SET_BY_USER TRUE) else() message(STATUS "Not forcing any particular BLAS to be found") set(BLAS_SET_BY_USER FALSE) endif() set(BLAS_SET_BY_USER ${BLAS_SET_BY_USER} CACHE STRING "Marks whether BLAS was manually set by user or auto-detected") endif() # Apple specific if(APPLE) # These lines are an attempt to make find_package(cuda) pick up # libcuda.dylib, and not cuda.framework. It doesn't work all # the time, but it seems to help for some users. # TODO: replace this with a more robust fix set(CMAKE_FIND_FRAMEWORK LAST) set(CMAKE_FIND_APPBUNDLE LAST) # Get clang version on macOS execute_process( COMMAND ${CMAKE_CXX_COMPILER} --version OUTPUT_VARIABLE clang_full_version_string ) string(REGEX REPLACE "Apple LLVM version ([0-9]+\\.[0-9]+).*" "\\1" CLANG_VERSION_STRING ${clang_full_version_string}) message( STATUS "CLANG_VERSION_STRING: " ${CLANG_VERSION_STRING} ) # RPATH stuff set(CMAKE_MACOSX_RPATH ON) if(NOT IOS) # Determine if we can link against ML Compute set(MLCOMPUTE_FOUND OFF) execute_process( COMMAND bash -c "xcrun --sdk macosx --show-sdk-path" OUTPUT_VARIABLE _macosx_sdk_path OUTPUT_STRIP_TRAILING_WHITESPACE) set(_SDK_SEARCH_PATH "${_macosx_sdk_path}/System/Library/Frameworks/") set(_FRAMEWORK_SEARCH_PATH "/System/Library/Frameworks/") find_library(_MLCompute_fwrk_path_ NAMES MLCompute PATHS ${_FRAMEWORK_SEARCH_PATH} NO_DEFAULT_PATH) find_library(_MLCompute_sdk_path_ NAMES MLCompute PATHS ${_SDK_SEARCH_PATH} NO_DEFAULT_PATH) if(EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/mlc) set(_MLC_FOLDER_EXISTS YES) else() set(_MLC_FOLDER_EXISTS NO) endif() if(_MLCompute_fwrk_path_ AND _MLCompute_sdk_path_ AND _MLC_FOLDER_EXISTS) set(MLCOMPUTE_FOUND ON) message(STATUS "ML Compute framework found") else() message(STATUS "ML Compute framework not found") endif() endif() endif() set(CPU_AARCH64 OFF) set(CPU_INTEL OFF) if(CMAKE_SYSTEM_PROCESSOR MATCHES "(AMD64|x86_64)") set(CPU_INTEL ON) elseif(CMAKE_SYSTEM_PROCESSOR MATCHES "^(aarch64|arm64)") set(CPU_AARCH64 ON) endif() # For non-supported platforms, turn USE_DISTRIBUTED off by default. # It is not tested and likely won't work without additional changes. if(NOT LINUX AND NOT WIN32) set(USE_DISTRIBUTED OFF CACHE STRING "Use distributed") # On macOS, if USE_DISTRIBUTED is enabled (specified by the user), # then make Gloo build with the libuv transport. if(APPLE AND USE_DISTRIBUTED) set(USE_LIBUV ON CACHE STRING "") endif() endif() # ---[ Options. # Note to developers: if you add an option below, make sure you also add it to # cmake/Summary.cmake so that the summary prints out the option values. include(CMakeDependentOption) option(ATEN_NO_TEST "Do not build ATen test binaries" OFF) option(BUILD_BINARY "Build C++ binaries" OFF) option(BUILD_DOCS "Build Caffe2 documentation" OFF) option(BUILD_CUSTOM_PROTOBUF "Build and use Caffe2's own protobuf under third_party" ON) option(BUILD_PYTHON "Build Python binaries" ON) option(BUILD_CAFFE2 "Master flag to build Caffe2" ON) option(BUILD_LITE_INTERPRETER "Master flag to build Lite Interpreter" OFF) cmake_dependent_option( BUILD_CAFFE2_OPS "Build Caffe2 operators" ON "BUILD_CAFFE2" OFF) cmake_dependent_option( BUILD_CAFFE2_MOBILE "Build libcaffe2 for mobile (deprecating)" OFF "BUILD_CAFFE2" OFF) option(BUILD_SHARED_LIBS "Build libcaffe2.so" ON) cmake_dependent_option( CAFFE2_LINK_LOCAL_PROTOBUF "If set, build protobuf inside libcaffe2.so." ON "BUILD_SHARED_LIBS AND BUILD_CUSTOM_PROTOBUF" OFF) cmake_dependent_option( CAFFE2_USE_MSVC_STATIC_RUNTIME "Using MSVC static runtime libraries" ON "NOT BUILD_SHARED_LIBS" OFF) option(BUILD_TEST "Build C++ test binaries (need gtest and gbenchmark)" OFF) option(BUILD_STATIC_RUNTIME_BENCHMARK "Build C++ binaries for static runtime benchmarks (need gbenchmark)" OFF) option(BUILD_TENSOREXPR_BENCHMARK "Build C++ binaries for tensorexpr benchmarks (need gbenchmark)" OFF) option(BUILD_MOBILE_BENCHMARK "Build C++ test binaries for mobile (ARM) targets(need gtest and gbenchmark)" OFF) option(BUILD_MOBILE_TEST "Build C++ test binaries for mobile (ARM) targets(need gtest and gbenchmark)" OFF) option(BUILD_JNI "Build JNI bindings" OFF) option(BUILD_MOBILE_AUTOGRAD "Build autograd function in mobile build (in development)" OFF) cmake_dependent_option( INSTALL_TEST "Install test binaries if BUILD_TEST is on" ON "BUILD_TEST" OFF) option(USE_CPP_CODE_COVERAGE "Compile C/C++ with code coverage flags" OFF) option(COLORIZE_OUTPUT "Colorize output during compilation" ON) option(USE_ASAN "Use Address Sanitizer" OFF) option(USE_TSAN "Use Thread Sanitizer" OFF) option(USE_CUDA "Use CUDA" ON) # BUILD_SPLIT_CUDA must also be exported as an environment variable before building, with # `export BUILD_SPLIT_CUDA=1` because cpp_extension.py can only work properly if this variable # also exists in the environment. # This option is incompatible with CUDA_SEPARABLE_COMPILATION. cmake_dependent_option( BUILD_SPLIT_CUDA "Split torch_cuda library into torch_cuda_cu and torch_cuda_cpp" OFF "USE_CUDA AND NOT CUDA_SEPARABLE_COMPILATION" OFF) option(USE_FAST_NVCC "Use parallel NVCC build" OFF) option(USE_ROCM "Use ROCm" ON) option(CAFFE2_STATIC_LINK_CUDA "Statically link CUDA libraries" OFF) cmake_dependent_option( USE_CUDNN "Use cuDNN" ON "USE_CUDA" OFF) cmake_dependent_option( USE_STATIC_CUDNN "Use cuDNN static libraries" OFF "USE_CUDNN" OFF) cmake_dependent_option( USE_WHOLE_CUDNN "Use whole-library linking for cuDNN" OFF "USE_STATIC_CUDNN" OFF) cmake_dependent_option( USE_EXPERIMENTAL_CUDNN_V8_API "Use experimental cuDNN v8 API" OFF "USE_CUDNN" OFF) option(USE_FBGEMM "Use FBGEMM (quantized 8-bit server operators)" ON) option(USE_KINETO "Use Kineto profiling library" ON) option(USE_BREAKPAD "Use breakpad crash dump library" ON) option(USE_CUPTI_SO "Use CUPTI as a shared library" OFF) option(USE_FAKELOWP "Use FakeLowp operators" OFF) option(USE_FFMPEG "Use ffmpeg" OFF) option(USE_GFLAGS "Use GFLAGS" OFF) option(USE_GLOG "Use GLOG" OFF) option(USE_LEVELDB "Use LEVELDB" OFF) option(USE_LITE_PROTO "Use lite protobuf instead of full." OFF) option(USE_LMDB "Use LMDB" OFF) option(USE_MAGMA "Use MAGMA" ON) option(USE_METAL "Use Metal for Caffe2 iOS build" ON) option(USE_PYTORCH_METAL "Use Metal for PyTorch iOS build" OFF) option(USE_PYTORCH_METAL_EXPORT "Export Metal models on MacOSX desktop" OFF) option(USE_NATIVE_ARCH "Use -march=native" OFF) cmake_dependent_option( USE_MLCOMPUTE "Use ML Compute for macOS build" ON "MLCOMPUTE_FOUND" OFF) cmake_dependent_option( USE_NCCL "Use NCCL" ON "USE_CUDA OR USE_ROCM;UNIX;NOT APPLE" OFF) cmake_dependent_option(USE_RCCL "Use RCCL" ON USE_NCCL OFF) cmake_dependent_option( USE_STATIC_NCCL "Use static NCCL" OFF "USE_NCCL" OFF) cmake_dependent_option( USE_SYSTEM_NCCL "Use system-wide NCCL" OFF "USE_NCCL" OFF) option(USE_NNAPI "Use NNAPI" OFF) option(USE_NNPACK "Use NNPACK" ON) cmake_dependent_option( USE_NUMA "Use NUMA. Only available on Linux." ON "LINUX" OFF) cmake_dependent_option( USE_NVRTC "Use NVRTC. Only available if USE_CUDA is on." OFF "USE_CUDA" OFF) option(USE_NUMPY "Use NumPy" ON) option(USE_OBSERVERS "Use observers module." OFF) option(USE_OPENCL "Use OpenCL" OFF) option(USE_OPENCV "Use OpenCV" OFF) option(USE_OPENMP "Use OpenMP for parallel code" ON) cmake_dependent_option( USE_PRECOMPILED_HEADERS "Use pre-compiled headers to accelerate build. Requires cmake >= 3.16." OFF "CMAKE_VERSION VERSION_LESS \"3.16\"" OFF) option(USE_PROF "Use profiling" OFF) option(USE_QNNPACK "Use QNNPACK (quantized 8-bit operators)" ON) option(USE_PYTORCH_QNNPACK "Use ATen/QNNPACK (quantized 8-bit operators)" ON) option(USE_REDIS "Use Redis" OFF) option(USE_ROCKSDB "Use RocksDB" OFF) option(USE_SNPE "Use Qualcomm's SNPE library" OFF) option(USE_SYSTEM_EIGEN_INSTALL "Use system Eigen instead of the one under third_party" OFF) option(USE_TENSORRT "Using Nvidia TensorRT library" OFF) cmake_dependent_option( USE_VALGRIND "Use Valgrind. Only available on Linux." ON "LINUX" OFF) if(NOT DEFINED USE_VULKAN) cmake_dependent_option( USE_VULKAN "Use Vulkan GPU backend" ON "ANDROID" OFF) endif() if(IOS) set(USE_BREAKPAD OFF) endif() option(USE_SOURCE_DEBUG_ON_MOBILE "Enable " ON) option(USE_LITE_INTERPRETER_PROFILER "Enable " ON) option(USE_VULKAN_FP16_INFERENCE "Vulkan - Use fp16 inference" OFF) option(USE_VULKAN_RELAXED_PRECISION "Vulkan - Use relaxed precision math in the kernels (mediump)" OFF) option(USE_VULKAN_SHADERC_RUNTIME "Vulkan - Use runtime shader compilation as opposed to build-time (needs libshaderc)" OFF) option(USE_XNNPACK "Use XNNPACK" ON) option(USE_ZMQ "Use ZMQ" OFF) option(USE_ZSTD "Use ZSTD" OFF) # Ensure that an MKLDNN build is the default for x86 CPUs # but optional for AArch64 (dependent on -DUSE_MKLDNN). cmake_dependent_option( USE_MKLDNN "Use MKLDNN. Only available on x86, x86_64, and AArch64." "${CPU_INTEL}" "CPU_INTEL OR CPU_AARCH64" OFF) cmake_dependent_option( USE_MKLDNN_ACL "Use Compute Library for the Arm architecture." OFF "USE_MKLDNN AND CPU_AARCH64" OFF) set(MKLDNN_ENABLE_CONCURRENT_EXEC ${USE_MKLDNN}) cmake_dependent_option( USE_MKLDNN_CBLAS "Use CBLAS in MKLDNN" OFF "USE_MKLDNN" OFF) option(USE_DISTRIBUTED "Use distributed" ON) cmake_dependent_option( USE_MPI "Use MPI for Caffe2. Only available if USE_DISTRIBUTED is on." ON "USE_DISTRIBUTED" OFF) cmake_dependent_option( USE_GLOO "Use Gloo. Only available if USE_DISTRIBUTED is on." ON "USE_DISTRIBUTED" OFF) cmake_dependent_option( USE_GLOO_WITH_OPENSSL "Use Gloo with OpenSSL. Only available if USE_GLOO is on." OFF "USE_GLOO AND LINUX AND NOT INTERN_BUILD_MOBILE" OFF) cmake_dependent_option( USE_C10D_GLOO "USE C10D GLOO" ON "USE_DISTRIBUTED;USE_GLOO" OFF) cmake_dependent_option( USE_C10D_NCCL "USE C10D NCCL" ON "USE_DISTRIBUTED;USE_NCCL" OFF) cmake_dependent_option( USE_C10D_MPI "USE C10D MPI" ON "USE_DISTRIBUTED;USE_MPI" OFF) cmake_dependent_option( USE_TENSORPIPE "Use TensorPipe. Only available if USE_DISTRIBUTED is on." ON "USE_DISTRIBUTED" OFF) option(USE_TBB "Use TBB (Deprecated)" OFF) cmake_dependent_option( USE_SYSTEM_TBB "Use system-provided Intel TBB." OFF "USE_TBB" OFF) option(ONNX_ML "Enable traditional ONNX ML API." ON) option(HAVE_SOVERSION "Whether to add SOVERSION to the shared objects" OFF) option(BUILD_LIBTORCH_CPU_WITH_DEBUG "Enable RelWithDebInfo for libtorch_cpu target only" OFF) cmake_dependent_option( USE_DEPLOY "Build embedded torch::deploy interpreter. See torch/csrc/deploy/README.md for more info." OFF "BUILD_PYTHON" OFF) cmake_dependent_option(USE_CCACHE "Attempt using CCache to wrap the compilation" ON "UNIX" OFF) option(WERROR "Build with -Werror supported by the compiler" OFF) option(USE_COREML_DELEGATE "Use the CoreML backend through delegate APIs" OFF) if(USE_CCACHE) find_program(CCACHE_PROGRAM ccache) if(CCACHE_PROGRAM) set(CMAKE_C_COMPILER_LAUNCHER "${CCACHE_PROGRAM}" CACHE STRING "C compiler launcher") set(CMAKE_CXX_COMPILER_LAUNCHER "${CCACHE_PROGRAM}" CACHE STRING "CXX compiler launcher") set(CMAKE_CUDA_COMPILER_LAUNCHER "${CCACHE_PROGRAM}" CACHE STRING "CUDA compiler launcher") else() message(STATUS "Could not find ccache. Consider installing ccache to speed up compilation.") endif() endif() # Since TensorPipe does not support Windows, set it to OFF when WIN32 detected # On Windows platform, if user does not install libuv in build conda env and # does not set libuv_ROOT environment variable. Set USE_DISTRIBUTED to OFF. if(WIN32) set(USE_TENSORPIPE OFF) message(WARNING "TensorPipe cannot be used on Windows. Set it to OFF") if(USE_DISTRIBUTED AND NOT DEFINED ENV{libuv_ROOT}) find_library( libuv_tmp_LIBRARY NAMES uv libuv HINTS $ENV{CONDA_PREFIX}\\Library $ENV{PREFIX}\\Library PATH_SUFFIXES lib NO_DEFAULT_PATH) if(NOT libuv_tmp_LIBRARY) set(USE_DISTRIBUTED OFF) set(USE_GLOO OFF) message( WARNING "Libuv is not installed in current conda env. Set USE_DISTRIBUTED to OFF. " "Please run command 'conda install -c conda-forge libuv=1.39' to install libuv.") else() set(ENV{libuv_ROOT} ${libuv_tmp_LIBRARY}/../../) endif() endif() endif() if(USE_GLOO_WITH_OPENSSL) set(USE_TCP_OPENSSL_LOAD ON CACHE STRING "") endif() # Linux distributions do not want too many embedded sources, in that sense we # need to be able to build pytorch with an (almost) empty third_party # directory. # USE_SYSTEM_LIBS is a shortcut variable to toggle all the # USE_SYSTEM_* # variables on. Individual USE_SYSTEM_* variables can be toggled with # USE_SYSTEM_LIBS being "OFF". option(USE_SYSTEM_LIBS "Use all available system-provided libraries." OFF) option(USE_SYSTEM_CPUINFO "Use system-provided cpuinfo." OFF) option(USE_SYSTEM_SLEEF "Use system-provided sleef." OFF) option(USE_SYSTEM_GLOO "Use system-provided gloo." OFF) option(USE_SYSTEM_FP16 "Use system-provided fp16." OFF) option(USE_SYSTEM_PYBIND11 "Use system-provided PyBind11." OFF) option(USE_SYSTEM_PTHREADPOOL "Use system-provided pthreadpool." OFF) option(USE_SYSTEM_PSIMD "Use system-provided psimd." OFF) option(USE_SYSTEM_FXDIV "Use system-provided fxdiv." OFF) option(USE_SYSTEM_BENCHMARK "Use system-provided google benchmark." OFF) option(USE_SYSTEM_ONNX "Use system-provided onnx." OFF) option(USE_SYSTEM_XNNPACK "Use system-provided xnnpack." OFF) option(USE_GOLD_LINKER "Use ld.gold to link" OFF) if(USE_SYSTEM_LIBS) set(USE_SYSTEM_CPUINFO ON) set(USE_SYSTEM_SLEEF ON) set(USE_SYSTEM_GLOO ON) set(BUILD_CUSTOM_PROTOBUF OFF) set(USE_SYSTEM_EIGEN_INSTALL ON) set(USE_SYSTEM_FP16 ON) set(USE_SYSTEM_PTHREADPOOL ON) set(USE_SYSTEM_PSIMD ON) set(USE_SYSTEM_FXDIV ON) set(USE_SYSTEM_BENCHMARK ON) set(USE_SYSTEM_ONNX ON) set(USE_SYSTEM_XNNPACK ON) set(USE_SYSTEM_PYBIND11 ON) if(USE_TBB) set(USE_SYSTEM_TBB ON) endif() endif() # Used when building Caffe2 through setup.py option(BUILDING_WITH_TORCH_LIBS "Tell cmake if Caffe2 is being built alongside torch libs" ON) # /Z7 override option # When generating debug symbols, CMake default to use the flag /Zi. # However, it is not compatible with sccache. So we rewrite it off. # But some users don't use sccache; this override is for them. cmake_dependent_option( MSVC_Z7_OVERRIDE "Work around sccache bug by replacing /Zi and /ZI with /Z7 when using MSVC (if you are not using sccache, you can turn this OFF)" ON "MSVC" OFF) if(NOT USE_SYSTEM_ONNX) set(ONNX_NAMESPACE "onnx_torch" CACHE STRING "A namespace for ONNX; needed to build with other frameworks that share ONNX.") else() set(ONNX_NAMESPACE "onnx" CACHE STRING "A namespace for ONNX; needed to build with other frameworks that share ONNX.") endif() set(SELECTED_OP_LIST "" CACHE STRING "Path to the yaml file that contains the list of operators to include for custom build. Include all operators by default.") set(OP_DEPENDENCY "" CACHE STRING "Path to the yaml file that contains the op dependency graph for custom build.") set(STATIC_DISPATCH_BACKEND "" CACHE STRING "Name of the backend for which static dispatch code is generated, e.g.: CPU.") # This is a fix for a rare build issue on Ubuntu: # symbol lookup error: miniconda3/envs/pytorch-py3.7/lib/libmkl_intel_lp64.so: undefined symbol: mkl_blas_dsyrk # https://software.intel.com/en-us/articles/symbol-lookup-error-when-linking-intel-mkl-with-gcc-on-ubuntu if(LINUX) set(CMAKE_SHARED_LINKER_FLAGS "${CMAKE_SHARED_LINKER_FLAGS} -Wl,--no-as-needed") endif() if(MSVC) set(CMAKE_NINJA_CMCLDEPS_RC OFF) foreach(flag_var CMAKE_C_FLAGS CMAKE_C_FLAGS_DEBUG CMAKE_C_FLAGS_RELEASE CMAKE_C_FLAGS_MINSIZEREL CMAKE_C_FLAGS_RELWITHDEBINFO CMAKE_CXX_FLAGS CMAKE_CXX_FLAGS_DEBUG CMAKE_CXX_FLAGS_RELEASE CMAKE_CXX_FLAGS_MINSIZEREL CMAKE_CXX_FLAGS_RELWITHDEBINFO) # Replace /Zi and /ZI with /Z7 if(MSVC_Z7_OVERRIDE) if(${flag_var} MATCHES "/Z[iI]") string(REGEX REPLACE "/Z[iI]" "/Z7" ${flag_var} "${${flag_var}}") endif(${flag_var} MATCHES "/Z[iI]") endif(MSVC_Z7_OVERRIDE) # Turn off warnings on Windows. In an ideal world we'd be warning # clean on Windows too, but this is too much work for our # non-Windows developers. # # NB: Technically, this is not necessary if CMP0092 was applied # properly, but only cmake >= 3.15 has this policy, so we nail # it one more time just be safe. # # NB2: This is NOT enough to prevent warnings from nvcc on MSVC. 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Other settings may " "generate files that are not well tested.") endif() if(USE_CUDA OR USE_ROCM) # TODO: check if we should include other cuda dependency libraries # to the interface as well. endif() # Note(jiayq): when building static libraries, all PRIVATE dependencies # will also become interface libraries, and as a result if there are any # dependency libraries that are not exported, the following install export # script will fail. As a result, we will only provide the targets cmake # files for shared lib installation. 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For the binaries, they will be linked to the Caffe2 main # libraries, as well as all the modules that are built with Caffe2 (the ones # built in the previous Modules section above). if(BUILD_BINARY) add_subdirectory(binaries) endif() # ---[ JNI if(BUILD_JNI) set(BUILD_LIBTORCH_WITH_JNI 1) set(FBJNI_SKIP_TESTS 1) add_subdirectory(android/pytorch_android) endif() include(cmake/Summary.cmake) caffe2_print_configuration_summary() # ---[ Torch Deploy if(USE_DEPLOY) add_subdirectory(torch/csrc/deploy) endif()