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CMakeLists.txt
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# ---[ Generate and install header and cpp files
include(../cmake/Codegen.cmake)
# ---[ Vulkan code gen
if(USE_VULKAN)
include(../cmake/VulkanCodegen.cmake)
endif()
# ---[ MSVC OpenMP modification
if(MSVC)
include(../cmake/public/utils.cmake)
endif()
# Debug messages - if you want to get a list of source files and examine
# target information, enable the following by -DPRINT_CMAKE_DEBUG_INFO=ON.
set(PRINT_CMAKE_DEBUG_INFO FALSE CACHE BOOL "print cmake debug information")
if(PRINT_CMAKE_DEBUG_INFO)
include(../cmake/DebugHelper.cmake)
endif()
# ATen parallelism settings
# OMP - OpenMP for intra-op, native thread pool for inter-op parallelism
# NATIVE - using native thread pool for intra- and inter-op parallelism
# TBB - using TBB for intra- and native thread pool for inter-op parallelism
if(INTERN_BUILD_MOBILE AND NOT BUILD_CAFFE2_MOBILE)
set(ATEN_THREADING "NATIVE" CACHE STRING "ATen parallel backend")
else()
if(USE_OPENMP)
set(ATEN_THREADING "OMP" CACHE STRING "ATen parallel backend")
elseif(USE_TBB)
set(ATEN_THREADING "TBB" CACHE STRING "ATen parallel backend")
else()
set(ATEN_THREADING "NATIVE" CACHE STRING "ATen parallel backend")
endif()
endif()
set(AT_PARALLEL_OPENMP 0)
set(AT_PARALLEL_NATIVE 0)
set(AT_PARALLEL_NATIVE_TBB 0)
message(STATUS "Using ATen parallel backend: ${ATEN_THREADING}")
if("${ATEN_THREADING}" STREQUAL "OMP")
set(AT_PARALLEL_OPENMP 1)
elseif("${ATEN_THREADING}" STREQUAL "NATIVE")
set(AT_PARALLEL_NATIVE 1)
elseif("${ATEN_THREADING}" STREQUAL "TBB")
if(NOT USE_TBB)
message(FATAL_ERROR "Using TBB backend but USE_TBB is off")
endif()
set(AT_PARALLEL_NATIVE_TBB 1)
else()
message(FATAL_ERROR "Unknown ATen parallel backend: ${ATEN_THREADING}")
endif()
# ---[ Declare source file lists
# ---[ ATen build
if(INTERN_BUILD_ATEN_OPS)
set(__caffe2_CMAKE_POSITION_INDEPENDENT_CODE ${CMAKE_POSITION_INDEPENDENT_CODE})
set(CMAKE_POSITION_INDEPENDENT_CODE ON)
add_subdirectory(../aten aten)
set(CMAKE_POSITION_INDEPENDENT_CODE ${__caffe2_CMAKE_POSITION_INDEPENDENT_CODE})
# Generate the headers wrapped by our operator
add_custom_command(OUTPUT ${CMAKE_CURRENT_BINARY_DIR}/contrib/aten/aten_op.h
COMMAND
"${PYTHON_EXECUTABLE}" ${CMAKE_CURRENT_SOURCE_DIR}/contrib/aten/gen_op.py
--aten_root=${CMAKE_CURRENT_SOURCE_DIR}/../aten
--template_dir=${CMAKE_CURRENT_SOURCE_DIR}/contrib/aten
--yaml_dir=${CMAKE_CURRENT_BINARY_DIR}/../aten/src/ATen
--install_dir=${CMAKE_CURRENT_BINARY_DIR}/contrib/aten
DEPENDS
ATEN_CPU_FILES_GEN_TARGET
${CMAKE_BINARY_DIR}/aten/src/ATen/Declarations.yaml
${CMAKE_CURRENT_SOURCE_DIR}/contrib/aten/gen_op.py
${CMAKE_CURRENT_SOURCE_DIR}/contrib/aten/aten_op_template.h)
add_custom_target(__aten_op_header_gen
DEPENDS ${CMAKE_CURRENT_BINARY_DIR}/contrib/aten/aten_op.h)
add_library(aten_op_header_gen INTERFACE)
add_dependencies(aten_op_header_gen __aten_op_header_gen)
# Add source, includes, and libs to lists
list(APPEND Caffe2_CPU_SRCS ${ATen_CPU_SRCS})
list(APPEND Caffe2_GPU_SRCS ${ATen_CUDA_SRCS})
list(APPEND Caffe2_GPU_SRCS_W_SORT_BY_KEY ${ATen_CUDA_SRCS_W_SORT_BY_KEY})
list(APPEND Caffe2_HIP_SRCS ${ATen_HIP_SRCS})
list(APPEND Caffe2_HIP_SRCS ${ATen_HIP_SRCS_W_SORT_BY_KEY})
list(APPEND Caffe2_CPU_TEST_SRCS ${ATen_CPU_TEST_SRCS})
list(APPEND Caffe2_GPU_TEST_SRCS ${ATen_CUDA_TEST_SRCS})
list(APPEND Caffe2_HIP_TEST_SRCS ${ATen_HIP_TEST_SRCS})
list(APPEND Caffe2_CPU_TEST_SRCS ${ATen_CORE_TEST_SRCS})
list(APPEND Caffe2_VULKAN_TEST_SRCS ${ATen_VULKAN_TEST_SRCS})
list(APPEND Caffe2_CPU_INCLUDE ${ATen_CPU_INCLUDE})
list(APPEND Caffe2_GPU_INCLUDE ${ATen_CUDA_INCLUDE})
list(APPEND Caffe2_HIP_INCLUDE ${ATen_HIP_INCLUDE})
list(APPEND Caffe2_VULKAN_INCLUDE ${ATen_VULKAN_INCLUDE})
list(APPEND Caffe2_DEPENDENCY_LIBS ${ATen_CPU_DEPENDENCY_LIBS})
list(APPEND Caffe2_CUDA_DEPENDENCY_LIBS ${ATen_CUDA_DEPENDENCY_LIBS})
list(APPEND Caffe2_HIP_DEPENDENCY_LIBS ${ATen_HIP_DEPENDENCY_LIBS})
list(APPEND Caffe2_DEPENDENCY_INCLUDE ${ATen_THIRD_PARTY_INCLUDE})
endif()
# ---[ Caffe2 build
# Note: the folders that are being commented out have not been properly
# addressed yet.
if(NOT MSVC AND USE_XNNPACK)
if(NOT TARGET fxdiv)
set(FXDIV_BUILD_TESTS OFF CACHE BOOL "")
set(FXDIV_BUILD_BENCHMARKS OFF CACHE BOOL "")
add_subdirectory(
"${FXDIV_SOURCE_DIR}"
"${CMAKE_BINARY_DIR}/FXdiv")
endif()
endif()
add_subdirectory(core)
add_subdirectory(serialize)
add_subdirectory(utils)
if(BUILD_CAFFE2 OR (NOT USE_FBGEMM))
add_subdirectory(perfkernels)
endif()
# Skip modules that are not used by libtorch mobile yet.
if(BUILD_CAFFE2 AND (NOT INTERN_BUILD_MOBILE OR BUILD_CAFFE2_MOBILE))
add_subdirectory(contrib)
add_subdirectory(predictor)
add_subdirectory(predictor/emulator)
add_subdirectory(core/nomnigraph)
if(USE_NVRTC)
add_subdirectory(cuda_rtc)
endif()
add_subdirectory(db)
add_subdirectory(distributed)
# add_subdirectory(experiments) # note, we may remove this folder at some point
add_subdirectory(ideep)
add_subdirectory(image)
add_subdirectory(video)
add_subdirectory(mobile)
add_subdirectory(mpi)
add_subdirectory(observers)
add_subdirectory(onnx)
if(BUILD_CAFFE2_OPS)
add_subdirectory(operators)
add_subdirectory(operators/rnn)
if(USE_FBGEMM)
add_subdirectory(quantization/server)
endif()
if(USE_QNNPACK)
add_subdirectory(operators/quantized)
endif()
endif()
add_subdirectory(opt)
add_subdirectory(proto)
add_subdirectory(python)
add_subdirectory(queue)
add_subdirectory(sgd)
add_subdirectory(share)
# add_subdirectory(test) # todo: use caffe2_gtest_main instead of gtest_main because we will need to call GlobalInit
add_subdirectory(transforms)
endif()
if(NOT BUILD_CAFFE2)
add_subdirectory(proto)
endif()
# Advanced: if we have allow list specified, we will do intersections for all
# main lib srcs.
if(CAFFE2_ALLOWLISTED_FILES)
caffe2_do_allowlist(Caffe2_CPU_SRCS CAFFE2_ALLOWLISTED_FILES)
caffe2_do_allowlist(Caffe2_GPU_SRCS CAFFE2_ALLOWLISTED_FILES)
caffe2_do_allowlist(Caffe2_HIP_SRCS CAFFE2_ALLOWLISTED_FILES)
endif()
if(BUILD_SPLIT_CUDA)
# Splitting the source files that'll be in torch_cuda between torch_cuda_cu and torch_cuda_cpp
foreach(tmp ${Caffe2_GPU_SRCS})
if("${tmp}" MATCHES "(.*aten.*\\.cu|.*(b|B)las.*|.*((s|S)olver|Register.*CUDA|Legacy|THC|TensorShapeCUDA|BatchLinearAlgebra).*\\.cpp)" AND NOT "${tmp}" MATCHES ".*(THC((CachingHost)?Allocator|General)).*")
# Currently, torch_cuda_cu will have all the .cu files in aten, as well as some others that depend on those files
list(APPEND Caffe2_GPU_SRCS_CU ${tmp})
else()
list(APPEND Caffe2_GPU_SRCS_CPP ${tmp})
endif()
endforeach()
foreach(tmp ${Caffe2_GPU_SRCS_W_SORT_BY_KEY})
if("${tmp}" MATCHES ".*aten.*\\.cu" AND NOT "${tmp}" MATCHES ".*TensorFactories.*")
list(APPEND Caffe2_GPU_SRCS_W_SORT_BY_KEY_CU ${tmp})
else()
list(APPEND Caffe2_GPU_SRCS_W_SORT_BY_KEY_CPP ${tmp})
endif()
endforeach()
endif()
if(PRINT_CMAKE_DEBUG_INFO)
message(STATUS "CPU sources: ")
foreach(tmp ${Caffe2_CPU_SRCS})
message(STATUS " " ${tmp})
endforeach()
message(STATUS "GPU sources: ")
foreach(tmp ${Caffe2_GPU_SRCS})
message(STATUS " " ${tmp})
endforeach()
if(BUILD_SPLIT_CUDA)
message(STATUS "GPU sources: (for torch_cuda_cpp)")
foreach(tmp ${Caffe2_GPU_SRCS_CPP})
message(STATUS " " ${tmp})
endforeach()
message(STATUS "GPU sources: (for torch_cuda_cu)")
foreach(tmp ${Caffe2_GPU_SRCS_CU})
message(STATUS " " ${tmp})
endforeach()
endif()
message(STATUS "GPU sources (w/ sort by key): ")
foreach(tmp ${Caffe2_GPU_SRCS_W_SORT_BY_KEY})
message(STATUS " " ${tmp})
endforeach()
if(BUILD_SPLIT_CUDA)
message(STATUS "torch_cuda_cu GPU sources (w/ sort by key): ")
foreach(tmp ${Caffe2_GPU_SRCS_W_SORT_BY_KEY_CU})
message(STATUS " " ${tmp})
endforeach()
message(STATUS "torch_cuda_cpp GPU sources (w/ sort by key): ")
foreach(tmp ${Caffe2_GPU_SRCS_W_SORT_BY_KEY_CPP})
message(STATUS " " ${tmp})
endforeach()
endif()
message(STATUS "CPU include: ")
foreach(tmp ${Caffe2_CPU_INCLUDE})
message(STATUS " " ${tmp})
endforeach()
message(STATUS "GPU include: ")
foreach(tmp ${Caffe2_GPU_INCLUDE})
message(STATUS " " ${tmp})
endforeach()
message(STATUS "CPU test sources: ")
foreach(tmp ${Caffe2_CPU_TEST_SRCS})
message(STATUS " " ${tmp})
endforeach()
message(STATUS "GPU test sources: ")
foreach(tmp ${Caffe2_GPU_TEST_SRCS})
message(STATUS " " ${tmp})
endforeach()
message(STATUS "HIP sources: ")
foreach(tmp ${Caffe2_HIP_SRCS})
message(STATUS " " ${tmp})
endforeach()
message(STATUS "HIP test sources: ")
foreach(tmp ${Caffe2_HIP_TEST_SRCS})
message(STATUS " " ${tmp})
endforeach()
message(STATUS "ATen CPU test sources: ")
foreach(tmp ${ATen_CPU_TEST_SRCS})
message(STATUS " " ${tmp})
endforeach()
message(STATUS "ATen CUDA test sources: ")
foreach(tmp ${ATen_CUDA_TEST_SRCS})
message(STATUS " " ${tmp})
endforeach()
message(STATUS "ATen HIP test sources: ")
foreach(tmp ${ATen_HIP_TEST_SRCS})
message(STATUS " " ${tmp})
endforeach()
message(STATUS "ATen Vulkan test sources: ")
foreach(tmp ${ATen_VULKAN_TEST_SRCS})
message(STATUS " " ${tmp})
endforeach()
endif()
if(NOT INTERN_BUILD_MOBILE OR BUILD_CAFFE2_MOBILE)
# ---[ List of libraries to link with
add_library(caffe2_protos STATIC $<TARGET_OBJECTS:Caffe2_PROTO>)
add_dependencies(caffe2_protos Caffe2_PROTO)
# If we are going to link protobuf locally inside caffe2 libraries, what we will do is
# to create a helper static library that always contains libprotobuf source files, and
# link the caffe2 related dependent libraries to it.
target_include_directories(caffe2_protos INTERFACE $<INSTALL_INTERFACE:include>)
# Reason for this public dependency is as follows:
# (1) Strictly speaking, we should not expose any Protobuf related functions. We should
# only use function interfaces wrapped with our own public API, and link protobuf
# locally.
# (2) However, currently across the Caffe2 codebase, we have extensive use of protobuf
# functionalities. For example, not only libcaffe2.so uses it, but also other
# binaries such as python extensions etc. As a result, we will have to have a
# transitive dependency to libprotobuf.
#
# Good thing is that, if we specify CAFFE2_LINK_LOCAL_PROTOBUF, then we do not need to
# separately deploy protobuf binaries - libcaffe2.so will contain all functionalities
# one needs. One can verify this via ldd.
#
# TODO item in the future includes:
# (1) Enable using lite protobuf
# (2) Properly define public API that do not directly depend on protobuf itself.
# (3) Expose the libprotobuf.a file for dependent libraries to link to.
#
# What it means for users/developers?
# (1) Users: nothing affecting the users, other than the fact that CAFFE2_LINK_LOCAL_PROTOBUF
# avoids the need to deploy protobuf.
# (2) Developers: if one simply uses core caffe2 functionality without using protobuf,
# nothing changes. If one has a dependent library that uses protobuf, then one needs to
# have the right protobuf version as well as linking to libprotobuf.a.
target_link_libraries(caffe2_protos PUBLIC protobuf::libprotobuf)
if(NOT BUILD_SHARED_LIBS)
install(TARGETS caffe2_protos ARCHIVE DESTINATION "${CMAKE_INSTALL_LIBDIR}")
endif()
endif()
# ==========================================================
# formerly-libtorch
# ==========================================================
set(TORCH_SRC_DIR "${PROJECT_SOURCE_DIR}/torch")
set(TORCH_ROOT "${PROJECT_SOURCE_DIR}")
if(NOT TORCH_INSTALL_BIN_DIR)
set(TORCH_INSTALL_BIN_DIR bin)
endif()
if(NOT TORCH_INSTALL_INCLUDE_DIR)
set(TORCH_INSTALL_INCLUDE_DIR include)
endif()
if(NOT TORCH_INSTALL_LIB_DIR)
set(TORCH_INSTALL_LIB_DIR lib)
endif()
if(NOT INTERN_BUILD_MOBILE OR NOT BUILD_CAFFE2_MOBILE)
set(CMAKE_POSITION_INDEPENDENT_CODE TRUE)
# Generate files
set(TOOLS_PATH "${TORCH_ROOT}/tools")
configure_file("${TORCH_SRC_DIR}/_utils_internal.py"
"${TOOLS_PATH}/shared/_utils_internal.py"
COPYONLY)
# Generate header with version info
configure_file("${TORCH_SRC_DIR}/csrc/api/include/torch/version.h.in"
"${TORCH_SRC_DIR}/csrc/api/include/torch/version.h"
@ONLY)
set(GENERATED_CXX_TORCH
"${TORCH_SRC_DIR}/csrc/autograd/generated/Functions.cpp"
)
if(NOT INTERN_DISABLE_AUTOGRAD AND NOT BUILD_LITE_INTERPRETER)
list(APPEND GENERATED_CXX_TORCH
"${TORCH_SRC_DIR}/csrc/autograd/generated/VariableType_0.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/VariableType_1.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/VariableType_2.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/VariableType_3.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/VariableType_4.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/TraceType_0.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/TraceType_1.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/TraceType_2.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/TraceType_3.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/TraceType_4.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/ADInplaceOrViewType_0.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/ADInplaceOrViewType_1.cpp"
)
endif()
set(GENERATED_H_TORCH
"${TORCH_SRC_DIR}/csrc/autograd/generated/Functions.h"
"${TORCH_SRC_DIR}/csrc/autograd/generated/variable_factories.h"
)
if(NOT INTERN_DISABLE_AUTOGRAD)
list(APPEND GENERATED_H_TORCH
"${TORCH_SRC_DIR}/csrc/autograd/generated/VariableType.h"
)
endif()
set(GENERATED_CXX_PYTHON
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_functions_0.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_functions_1.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_functions_2.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_functions_3.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_functions_4.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_variable_methods.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_torch_functions_0.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_torch_functions_1.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_torch_functions_2.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_nn_functions.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_fft_functions.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_linalg_functions.cpp"
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_special_functions.cpp"
)
set(GENERATED_H_PYTHON
"${TORCH_SRC_DIR}/csrc/autograd/generated/python_functions.h"
)
set(GENERATED_TESTING_PYTHON
"${TORCH_SRC_DIR}/testing/_internal/generated/annotated_fn_args.py"
)
set(TORCH_GENERATED_CODE
${GENERATED_CXX_TORCH}
${GENERATED_H_TORCH}
${GENERATED_CXX_PYTHON}
${GENERATED_H_PYTHON}
${GENERATED_TESTING_PYTHON}
)
add_custom_command(
OUTPUT
${TORCH_GENERATED_CODE}
COMMAND
"${PYTHON_EXECUTABLE}" tools/setup_helpers/generate_code.py
--declarations-path "${CMAKE_BINARY_DIR}/aten/src/ATen/Declarations.yaml"
--native-functions-path "aten/src/ATen/native/native_functions.yaml"
--nn-path "aten/src"
$<$<BOOL:${INTERN_DISABLE_AUTOGRAD}>:--disable-autograd>
$<$<BOOL:${SELECTED_OP_LIST}>:--selected-op-list-path="${SELECTED_OP_LIST}">
--force_schema_registration
DEPENDS
"${TORCH_ROOT}/aten/src/ATen/native/native_functions.yaml"
"${CMAKE_BINARY_DIR}/aten/src/ATen/Declarations.yaml"
"${TOOLS_PATH}/autograd/templates/VariableType.h"
"${TOOLS_PATH}/autograd/templates/VariableType.cpp"
"${TOOLS_PATH}/autograd/templates/ADInplaceOrViewType.cpp"
"${TOOLS_PATH}/autograd/templates/TraceType.cpp"
"${TOOLS_PATH}/autograd/templates/Functions.h"
"${TOOLS_PATH}/autograd/templates/Functions.cpp"
"${TOOLS_PATH}/autograd/templates/python_functions.h"
"${TOOLS_PATH}/autograd/templates/python_functions.cpp"
"${TOOLS_PATH}/autograd/templates/python_variable_methods.cpp"
"${TOOLS_PATH}/autograd/templates/python_torch_functions.cpp"
"${TOOLS_PATH}/autograd/templates/python_nn_functions.cpp"
"${TOOLS_PATH}/autograd/templates/python_fft_functions.cpp"
"${TOOLS_PATH}/autograd/templates/python_linalg_functions.cpp"
"${TOOLS_PATH}/autograd/templates/python_special_functions.cpp"
"${TOOLS_PATH}/autograd/templates/variable_factories.h"
"${TOOLS_PATH}/autograd/templates/annotated_fn_args.py.in"
"${TOOLS_PATH}/autograd/deprecated.yaml"
"${TOOLS_PATH}/autograd/derivatives.yaml"
"${TOOLS_PATH}/autograd/gen_autograd_functions.py"
"${TOOLS_PATH}/autograd/gen_autograd.py"
"${TOOLS_PATH}/autograd/gen_python_functions.py"
"${TOOLS_PATH}/autograd/gen_variable_factories.py"
"${TOOLS_PATH}/autograd/gen_variable_type.py"
"${TOOLS_PATH}/autograd/gen_inplace_or_view_type.py"
"${TOOLS_PATH}/autograd/load_derivatives.py"
WORKING_DIRECTORY "${TORCH_ROOT}")
# Required workaround for libtorch_python.so build
# see https://samthursfield.wordpress.com/2015/11/21/cmake-dependencies-between-targets-and-files-and-custom-commands/#custom-commands-in-different-directories
add_custom_target(
generate-torch-sources
DEPENDS ${TORCH_GENERATED_CODE}
)
set(TORCH_SRCS ${GENERATED_CXX_TORCH})
list(APPEND TORCH_SRCS ${GENERATED_H_TORCH})
list(APPEND LIBTORCH_CMAKE_SRCS "")
list(APPEND LITE_EAGER_SYMOBLICATION_SRCS "")
if(USE_SOURCE_DEBUG_ON_MOBILE)
append_filelist("libtorch_lite_eager_symbolication" LITE_EAGER_SYMOBLICATION_SRCS)
# For source debug on lite interpreter, we have to add dependency on pickling
# but references to read/writeArchiveAndTensor is not built for mobile
# so this condition specifically says we are building for source debug
# on mobile.
if(BUILD_LITE_INTERPRETER)
set_source_files_properties(${TORCH_SRC_DIR}/csrc/jit/serialization/pickle.cpp PROPERTIES COMPILE_FLAGS "-DC10_MOBILE -DFEATURE_TORCH_MOBILE")
endif()
endif()
list(APPEND LITE_PROFILER_SRCS "")
if(USE_LITE_INTERPRETER_PROFILER)
append_filelist("libtorch_edge_profiler_sources " LITE_PROFILER_SRCS)
endif()
# Switch between the full jit interpreter and lite interpreter
if(BUILD_LITE_INTERPRETER)
append_filelist("libtorch_lite_cmake_sources" LIBTORCH_CMAKE_SRCS)
list(APPEND LIBTORCH_CMAKE_SRCS ${LITE_EAGER_SYMOBLICATION_SRCS})
list(APPEND LIBTORCH_CMAKE_SRCS ${LITE_PROFILER_SRCS})
set(CMAKE_POSITION_INDEPENDENT_CODE TRUE)
else()
append_filelist("libtorch_cmake_sources" LIBTORCH_CMAKE_SRCS)
if(CMAKE_CXX_COMPILER_ID MATCHES "Clang" OR CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
# TODO: Delete this line once https://github.com/pytorch/pytorch/pull/55889 lands
set_source_files_properties(../torch/csrc/jit/serialization/export.cpp PROPERTIES COMPILE_FLAGS -Wno-deprecated-declarations)
# TODO: Delete this when https://github.com/pytorch/pytorch/issues/35026 is fixed
set_source_files_properties(../torch/csrc/autograd/record_function_ops.cpp PROPERTIES COMPILE_FLAGS -Wno-deprecated-declarations)
endif()
endif()
list(APPEND TORCH_SRCS ${LIBTORCH_CMAKE_SRCS})
if(PRINT_CMAKE_DEBUG_INFO)
message(STATUS "Interpreter sources: ")
foreach(tmp ${LIBTORCH_CMAKE_SRCS})
message(STATUS " " ${tmp})
endforeach()
endif()
# Required workaround for LLVM 9 includes.
if(NOT MSVC)
set_source_files_properties(${TORCH_SRC_DIR}/csrc/jit/tensorexpr/llvm_jit.cpp PROPERTIES COMPILE_FLAGS -Wno-noexcept-type)
# Force -Werror on several files
set_source_files_properties(${CMAKE_CURRENT_LIST_DIR}/../aten/src/ATen/native/mkldnn/Pooling.cpp PROPERTIES COMPILE_FLAGS "-Werror")
endif()
# Disable certain warnings for GCC-9.X
if(CMAKE_COMPILER_IS_GNUCXX AND (CMAKE_CXX_COMPILER_VERSION VERSION_GREATER 9.0.0))
# See https://github.com/pytorch/pytorch/issues/38856
set_source_files_properties(${TORCH_SRC_DIR}/csrc/jit/tensorexpr/llvm_jit.cpp PROPERTIES COMPILE_FLAGS "-Wno-redundant-move -Wno-noexcept-type")
set_source_files_properties(${TORCH_SRC_DIR}/csrc/jit/tensorexpr/llvm_codegen.cpp PROPERTIES COMPILE_FLAGS -Wno-init-list-lifetime)
endif()
if(NOT INTERN_DISABLE_MOBILE_INTERP)
set(MOBILE_SRCS
${TORCH_SRC_DIR}/csrc/jit/mobile/function.cpp
${TORCH_SRC_DIR}/csrc/jit/mobile/import.cpp
${TORCH_SRC_DIR}/csrc/jit/mobile/import_data.cpp
${TORCH_SRC_DIR}/csrc/jit/mobile/model_compatibility.cpp
${TORCH_SRC_DIR}/csrc/jit/mobile/module.cpp
${TORCH_SRC_DIR}/csrc/jit/mobile/observer.cpp
${TORCH_SRC_DIR}/csrc/jit/mobile/interpreter.cpp
${TORCH_SRC_DIR}/csrc/jit/mobile/train/export_data.cpp
${TORCH_SRC_DIR}/csrc/jit/mobile/train/optim/sgd.cpp
${TORCH_SRC_DIR}/csrc/jit/mobile/train/random.cpp
${TORCH_SRC_DIR}/csrc/jit/mobile/train/sequential.cpp
)
list(APPEND TORCH_SRCS ${MOBILE_SRCS})
list(APPEND TORCH_SRCS ${LITE_EAGER_SYMOBLICATION_SRCS})
endif()
# This one needs to be unconditionally added as Functions.cpp is also unconditionally added
list(APPEND TORCH_SRCS
${TORCH_SRC_DIR}/csrc/autograd/FunctionsManual.cpp
${TORCH_SRC_DIR}/csrc/utils/out_types.cpp
)
if(NOT INTERN_DISABLE_AUTOGRAD AND NOT BUILD_LITE_INTERPRETER)
list(APPEND TORCH_SRCS
${TORCH_SRC_DIR}/csrc/autograd/TraceTypeManual.cpp
${TORCH_SRC_DIR}/csrc/autograd/VariableTypeManual.cpp
)
endif()
if(NOT INTERN_BUILD_MOBILE AND NOT BUILD_LITE_INTERPRETER)
list(APPEND TORCH_SRCS
${TORCH_SRC_DIR}/csrc/api/src/jit.cpp
${TORCH_SRC_DIR}/csrc/jit/mobile/backport.cpp
${TORCH_SRC_DIR}/csrc/jit/mobile/backport_manager.cpp
${TORCH_SRC_DIR}/csrc/jit/serialization/onnx.cpp
${TORCH_SRC_DIR}/csrc/jit/serialization/export.cpp
${TORCH_SRC_DIR}/csrc/jit/serialization/export_module.cpp
${TORCH_SRC_DIR}/csrc/jit/codegen/fuser/cpu/fused_kernel.cpp
${TORCH_SRC_DIR}/csrc/jit/api/module_save.cpp
${TORCH_SRC_DIR}/csrc/utils/byte_order.cpp
)
# Disable legacy import of building without Caffe2 support
if(BUILD_CAFFE2)
list(APPEND TORCH_SRCS
${TORCH_SRC_DIR}/csrc/jit/serialization/import_legacy.cpp
)
else()
set_source_files_properties(
${TORCH_SRC_DIR}/csrc/jit/serialization/import.cpp
PROPERTIES COMPILE_FLAGS "-DC10_DISABLE_LEGACY_IMPORT"
)
endif()
if(USE_DISTRIBUTED)
append_filelist("libtorch_distributed_base_sources" TORCH_SRCS)
if(NOT WIN32)
append_filelist("libtorch_distributed_extra_sources" TORCH_SRCS)
endif()
endif()
endif()
if(USE_CUDA OR USE_ROCM)
append_filelist("libtorch_cuda_core_sources" Caffe2_GPU_HIP_JIT_FUSERS_SRCS)
endif()
if(USE_CUDA)
if(BUILD_SPLIT_CUDA)
list(APPEND Caffe2_GPU_SRCS_CU ${Caffe2_GPU_HIP_JIT_FUSERS_SRCS})
else()
list(APPEND Caffe2_GPU_SRCS ${Caffe2_GPU_HIP_JIT_FUSERS_SRCS})
endif()
add_library(caffe2_nvrtc SHARED ${ATen_NVRTC_STUB_SRCS})
if(MSVC)
# Delay load nvcuda.dll so we can import torch compiled with cuda on a CPU-only machine
set(DELAY_LOAD_FLAGS "-DELAYLOAD:nvcuda.dll;delayimp.lib")
else()
set(DELAY_LOAD_FLAGS "")
endif()
target_link_libraries(caffe2_nvrtc ${CUDA_NVRTC} ${CUDA_CUDA_LIB} ${CUDA_NVRTC_LIB} ${DELAY_LOAD_FLAGS})
target_include_directories(caffe2_nvrtc PRIVATE ${CUDA_INCLUDE_DIRS})
install(TARGETS caffe2_nvrtc DESTINATION "${TORCH_INSTALL_LIB_DIR}")
if(USE_NCCL AND BUILD_SPLIT_CUDA)
list(APPEND Caffe2_GPU_SRCS_CPP
${TORCH_SRC_DIR}/csrc/cuda/nccl.cpp)
elseif(USE_NCCL)
list(APPEND Caffe2_GPU_SRCS
${TORCH_SRC_DIR}/csrc/cuda/nccl.cpp)
endif()
if(USE_DISTRIBUTED)
if(BUILD_SPLIT_CUDA)
set(_target "Caffe2_GPU_SRCS_CPP")
else()
set(_target "Caffe2_GPU_SRCS")
endif()
append_filelist("libtorch_cuda_distributed_base_sources" ${_target})
if(NOT WIN32)
append_filelist("libtorch_cuda_distributed_extra_sources" ${_target})
endif()
endif()
set_source_files_properties(
${TORCH_ROOT}/aten/src/ATen/cuda/detail/LazyNVRTC.cpp
PROPERTIES COMPILE_DEFINITIONS "NVRTC_SHORTHASH=${CUDA_NVRTC_SHORTHASH}"
)
set_source_files_properties(${TORCH_SRC_DIR}/csrc/jit/passes/frozen_conv_add_relu_fusion.cpp PROPERTIES COMPILE_FLAGS "-DUSE_CUDA=1")
endif()
if(USE_MLCOMPUTE)
include(../mlc/mlc_build.cmake)
endif()
if(USE_ROCM)
list(APPEND Caffe2_HIP_SRCS ${Caffe2_GPU_HIP_JIT_FUSERS_SRCS})
if(USE_NCCL)
list(APPEND Caffe2_HIP_SRCS
${TORCH_SRC_DIR}/csrc/cuda/nccl.cpp)
endif()
if(USE_DISTRIBUTED)
append_filelist("libtorch_cuda_distributed_base_sources" Caffe2_HIP_SRCS)
if(NOT WIN32)
append_filelist("libtorch_cuda_distributed_extra_sources" Caffe2_HIP_SRCS)
endif()
endif()
# caffe2_nvrtc's stubs to driver APIs are useful for HIP.
# See NOTE [ ATen NVRTC Stub and HIP ]
add_library(caffe2_nvrtc SHARED ${ATen_NVRTC_STUB_SRCS})
target_link_libraries(caffe2_nvrtc ${PYTORCH_HIP_HCC_LIBRARIES} ${ROCM_HIPRTC_LIB})
target_compile_definitions(caffe2_nvrtc PRIVATE USE_ROCM __HIP_PLATFORM_HCC__)
install(TARGETS caffe2_nvrtc DESTINATION "${TORCH_INSTALL_LIB_DIR}")
endif()
if(NOT NO_API AND NOT BUILD_LITE_INTERPRETER)
list(APPEND TORCH_SRCS
${TORCH_SRC_DIR}/csrc/api/src/cuda.cpp
${TORCH_SRC_DIR}/csrc/api/src/data/datasets/mnist.cpp
${TORCH_SRC_DIR}/csrc/api/src/data/samplers/distributed.cpp
${TORCH_SRC_DIR}/csrc/api/src/data/samplers/random.cpp
${TORCH_SRC_DIR}/csrc/api/src/data/samplers/sequential.cpp
${TORCH_SRC_DIR}/csrc/api/src/data/samplers/stream.cpp
${TORCH_SRC_DIR}/csrc/api/src/enum.cpp
${TORCH_SRC_DIR}/csrc/api/src/imethod.cpp
${TORCH_SRC_DIR}/csrc/api/src/serialize.cpp
${TORCH_SRC_DIR}/csrc/api/src/jit.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/init.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/module.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/_functions.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/activation.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/adaptive.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/batchnorm.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/normalization.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/instancenorm.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/conv.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/dropout.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/distance.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/embedding.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/fold.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/linear.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/loss.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/padding.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/pixelshuffle.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/pooling.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/rnn.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/upsampling.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/transformer.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/modules/container/functional.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/activation.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/adaptive.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/batchnorm.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/embedding.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/instancenorm.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/normalization.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/conv.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/dropout.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/linear.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/padding.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/pooling.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/rnn.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/vision.cpp
${TORCH_SRC_DIR}/csrc/api/src/nn/options/transformer.cpp
${TORCH_SRC_DIR}/csrc/api/src/optim/adagrad.cpp
${TORCH_SRC_DIR}/csrc/api/src/optim/adam.cpp
${TORCH_SRC_DIR}/csrc/api/src/optim/adamw.cpp
${TORCH_SRC_DIR}/csrc/api/src/optim/lbfgs.cpp
${TORCH_SRC_DIR}/csrc/api/src/optim/optimizer.cpp
${TORCH_SRC_DIR}/csrc/api/src/optim/rmsprop.cpp
${TORCH_SRC_DIR}/csrc/api/src/optim/serialize.cpp
${TORCH_SRC_DIR}/csrc/api/src/optim/sgd.cpp
${TORCH_SRC_DIR}/csrc/api/src/optim/schedulers/lr_scheduler.cpp
${TORCH_SRC_DIR}/csrc/api/src/optim/schedulers/step_lr.cpp
${TORCH_SRC_DIR}/csrc/api/src/serialize/input-archive.cpp
${TORCH_SRC_DIR}/csrc/api/src/serialize/output-archive.cpp
${TORCH_SRC_DIR}/csrc/utils/crash_handler.cpp
)
endif()
list(APPEND Caffe2_CPU_SRCS ${TORCH_SRCS})
endif()
# NOTE [ Linking AVX-n and non-AVX-n files ]
#
# Regardless of the CPU capabilities, we build some files with AVX2, and AVX512
# instruction set. If the host CPU doesn't support those, we simply ignore their
# functions at runtime during dispatch.
#
# We must make sure that those files are at the end of the input list when
# linking the torch_cpu library. Otherwise, the following error scenario might
# occur:
# 1. A non-AVX2 and an AVX2 file both call a function defined with the `inline`
# keyword
# 2. The compiler decides not to inline this function
# 3. Two different versions of the machine code are generated for this function:
# one without AVX2 instructions and one with AVX2.
# 4. When linking, the AVX2 version is found earlier in the input object files,
# so the linker makes the entire library use it, even in code not guarded by
# the dispatcher.
# 5. A CPU without AVX2 support executes this function, encounters an AVX2
# instruction and crashes.
#
# Thus we organize the input files in the following order:
# 1. All files with no AVX-n support
# 2. All files with AVX2 support ('*AVX2.cpp')
# 3. All files with AVX512 support ('*AVX512.cpp')
set(Caffe2_CPU_SRCS_NON_AVX)
set(Caffe2_CPU_SRCS_AVX2)
set(Caffe2_CPU_SRCS_AVX512)
foreach(input_filename ${Caffe2_CPU_SRCS})
if(${input_filename} MATCHES "AVX2\\.cpp")
list(APPEND Caffe2_CPU_SRCS_AVX2 ${input_filename})
elseif(${input_filename} MATCHES "AVX512\\.cpp")
list(APPEND Caffe2_CPU_SRCS_AVX512 ${input_filename})
else()
list(APPEND Caffe2_CPU_SRCS_NON_AVX ${input_filename})
endif()
endforeach(input_filename)
set(Caffe2_CPU_SRCS ${Caffe2_CPU_SRCS_NON_AVX} ${Caffe2_CPU_SRCS_AVX2} ${Caffe2_CPU_SRCS_AVX512})
# ==========================================================
# END formerly-libtorch sources
# ==========================================================
add_library(torch_cpu ${Caffe2_CPU_SRCS})
if(HAVE_SOVERSION)
set_target_properties(torch_cpu PROPERTIES
VERSION ${TORCH_VERSION} SOVERSION ${TORCH_SOVERSION})
endif()
torch_compile_options(torch_cpu) # see cmake/public/utils.cmake
if(USE_PRECOMPILED_HEADERS)
target_precompile_headers(torch_cpu PRIVATE
"$<$<COMPILE_LANGUAGE:CXX>:ATen/ATen.h>")
# Exclude some files from using PCH
set_source_files_properties(
# Errors when ATen.h is included
${Torch_BINARY_DIR}/aten/src/ATen/core/TensorMethods.cpp
# Builds with incompatible compiler flags
${Caffe2_CPU_SRCS_AVX2}
${Caffe2_CPU_SRCS_AVX512}
PROPERTIES SKIP_PRECOMPILE_HEADERS ON)
endif()
# Pass path to PocketFFT
if(AT_POCKETFFT_ENABLED)
if(CMAKE_VERSION VERSION_LESS "3.11")
target_include_directories(torch_cpu PRIVATE "${POCKETFFT_INCLUDE_DIR}")
else()
set_source_files_properties(
"${PROJECT_SOURCE_DIR}/aten/src/ATen/native/mkl/SpectralOps.cpp"
PROPERTIES INCLUDE_DIRECTORIES "${POCKETFFT_INCLUDE_DIR}")
endif()
endif()
if(CMAKE_COMPILER_IS_GNUCXX AND BUILD_LIBTORCH_CPU_WITH_DEBUG)
# To enable debug fission we need to build libtorch_cpu with debug info on,
# but this increases link time and peak memory usage if we use the
# REL_WITH_DEB_INFO env var since that enables it for everything, but it's
# only really necessary for libtorch_cpu.
target_compile_options(torch_cpu PRIVATE "-g")
endif()
if(USE_LLVM AND LLVM_FOUND)
llvm_map_components_to_libnames(LLVM_LINK_LIBS
support core analysis executionengine instcombine
scalaropts transformutils ${LLVM_TARGETS_TO_BUILD} orcjit)
target_link_libraries(torch_cpu PRIVATE ${LLVM_LINK_LIBS})
if(APPLE)
set(LINKER_SCRIPT "${CMAKE_CURRENT_SOURCE_DIR}/unexported_symbols.lds")
set_target_properties(torch_cpu PROPERTIES LINK_DEPENDS ${LINKER_SCRIPT})
set_target_properties(torch_cpu PROPERTIES LINK_FLAGS "-Wl,-unexported_symbols_list,${LINKER_SCRIPT}")
elseif(UNIX)
set(LINKER_SCRIPT "${CMAKE_CURRENT_SOURCE_DIR}/version_script.lds")
set_target_properties(torch_cpu PROPERTIES LINK_DEPENDS ${LINKER_SCRIPT})
target_link_libraries(torch_cpu PRIVATE "-Wl,--version-script=${LINKER_SCRIPT}")
endif()
endif(USE_LLVM AND LLVM_FOUND)
# This is required for older versions of CMake, which don't allow
# specifying add_library() without a list of source files
set(DUMMY_EMPTY_FILE ${CMAKE_BINARY_DIR}/empty.cpp)
if(MSVC)
set(DUMMY_FILE_CONTENT "__declspec(dllexport) int ignore_this_library_placeholder(){return 0\\;}")
else()
set(DUMMY_FILE_CONTENT "")
endif()
file(WRITE ${DUMMY_EMPTY_FILE} ${DUMMY_FILE_CONTENT})
# Wrapper library for people who link against torch and expect both CPU and CUDA support
# Contains "torch_cpu" and "torch_cuda"
add_library(torch ${DUMMY_EMPTY_FILE})
if(BUILD_SPLIT_CUDA)
# When we split torch_cuda, we want a dummy torch_cuda library that contains both parts
add_library(torch_cuda ${DUMMY_EMPTY_FILE})
endif()
if(HAVE_SOVERSION)
set_target_properties(torch PROPERTIES
VERSION ${TORCH_VERSION} SOVERSION ${TORCH_SOVERSION})
endif()
if(USE_ROCM)
filter_list(__caffe2_hip_srcs_cpp Caffe2_HIP_SRCS "\\.(cu|hip)$")
set_source_files_properties(${__caffe2_hip_srcs_cpp} PROPERTIES HIP_SOURCE_PROPERTY_FORMAT 1)
endif()
# Compile exposed libraries.
if(USE_ROCM)
set(CUDA_LINK_LIBRARIES_KEYWORD PRIVATE)
hip_add_library(torch_hip ${Caffe2_HIP_SRCS})
set(CUDA_LINK_LIBRARIES_KEYWORD)
torch_compile_options(torch_hip) # see cmake/public/utils.cmake
# TODO: Not totally sure if this is live or not
if(USE_NCCL)
target_link_libraries(torch_hip PRIVATE __caffe2_nccl)
target_compile_definitions(torch_hip PRIVATE USE_NCCL)
endif()
if(USE_PRECOMPILED_HEADERS)
target_precompile_headers(torch_hip PRIVATE
"$<$<COMPILE_LANGUAGE:CXX>:ATen/ATen.h>")
endif()
elseif(USE_CUDA)
set(CUDA_LINK_LIBRARIES_KEYWORD PRIVATE)
if(CUDA_SEPARABLE_COMPILATION)
# Separate compilation fails when kernels using `thrust::sort_by_key`
# are linked with the rest of CUDA code. Workaround by linking them separately
set(_generated_name "torch_cuda_w_sort_by_key_intermediate_link${CMAKE_C_OUTPUT_EXTENSION}")
set(torch_cuda_w_sort_by_key_link_file "${CMAKE_CURRENT_BINARY_DIR}/CMakeFiles/torch_cuda.dir/${CMAKE_CFG_INTDIR}/${_generated_name}")
cuda_wrap_srcs(torch_cuda OBJ Caffe2_GPU_W_SORT_BY_KEY_OBJ ${Caffe2_GPU_SRCS_W_SORT_BY_KEY})
CUDA_LINK_SEPARABLE_COMPILATION_OBJECTS("${torch_cuda_w_sort_by_key_link_file}" torch_cpu "${_options}" "${torch_cuda_SEPARABLE_COMPILATION_OBJECTS}")
set( torch_cuda_SEPARABLE_COMPILATION_OBJECTS )
# Pass compiled sort-by-key object + device-linked fatbin as extra dependencies of torch_cuda
cuda_add_library(torch_cuda ${Caffe2_GPU_SRCS} ${torch_cuda_w_sort_by_key_link_file} ${Caffe2_GPU_W_SORT_BY_KEY_OBJ})
elseif(BUILD_SPLIT_CUDA)
cuda_add_library(torch_cuda_cpp ${Caffe2_GPU_SRCS_CPP} ${Caffe2_GPU_SRCS_W_SORT_BY_KEY_CPP})
cuda_add_library(torch_cuda_cu ${Caffe2_GPU_SRCS_CU} ${Caffe2_GPU_SRCS_W_SORT_BY_KEY_CU})
else()
cuda_add_library(torch_cuda ${Caffe2_GPU_SRCS} ${Caffe2_GPU_SRCS_W_SORT_BY_KEY})
endif()
set(CUDA_LINK_LIBRARIES_KEYWORD)
if(BUILD_SPLIT_CUDA)
torch_compile_options(torch_cuda_cpp) # see cmake/public/utils.cmake
torch_compile_options(torch_cuda_cu) # see cmake/public/utils.cmake
target_compile_definitions(torch_cuda_cpp PRIVATE BUILD_SPLIT_CUDA)
target_compile_definitions(torch_cuda_cpp PRIVATE USE_CUDA)
target_compile_definitions(torch_cuda_cu PRIVATE BUILD_SPLIT_CUDA)
target_compile_definitions(torch_cuda_cu PRIVATE USE_CUDA)
else()
torch_compile_options(torch_cuda) # see cmake/public/utils.cmake
target_compile_definitions(torch_cuda PRIVATE USE_CUDA)
endif()
if(USE_NCCL AND BUILD_SPLIT_CUDA)
target_link_libraries(torch_cuda_cpp PRIVATE __caffe2_nccl)
target_compile_definitions(torch_cuda_cpp PRIVATE USE_NCCL)
elseif(USE_NCCL)
target_link_libraries(torch_cuda PRIVATE __caffe2_nccl)
target_compile_definitions(torch_cuda PRIVATE USE_NCCL)
endif()
if(USE_PRECOMPILED_HEADERS)
if(BUILD_SPLIT_CUDA)
target_precompile_headers(torch_cuda_cpp PRIVATE
"$<$<COMPILE_LANGUAGE:CXX>:ATen/ATen.h>"
"$<$<COMPILE_LANGUAGE:CXX>:ATen/cuda/CUDAContext.h>")
else()
target_precompile_headers(torch_cuda PRIVATE
"$<$<COMPILE_LANGUAGE:CXX>:ATen/ATen.h>"
"$<$<COMPILE_LANGUAGE:CXX>:ATen/cuda/CUDAContext.h>")
endif()
endif()
endif()
if(USE_CUDA OR USE_ROCM)
if(BUILD_SPLIT_CUDA)
set(TORCHLIB_FLAVOR torch_cuda_cu) # chose torch_cuda_cu here since JIT is in torch_cuda_cpp
elseif(USE_CUDA)
set(TORCHLIB_FLAVOR torch_cuda)
elseif(USE_ROCM)
set(TORCHLIB_FLAVOR torch_hip)
endif()
# The list of NVFUSER runtime files
list(APPEND NVFUSER_RUNTIME_FILES
${TORCH_SRC_DIR}/csrc/jit/codegen/cuda/runtime/block_reduction.cu
${TORCH_SRC_DIR}/csrc/jit/codegen/cuda/runtime/broadcast.cu
${TORCH_SRC_DIR}/csrc/jit/codegen/cuda/runtime/fp16_support.cu
${TORCH_SRC_DIR}/csrc/jit/codegen/cuda/runtime/grid_reduction.cu
${TORCH_SRC_DIR}/csrc/jit/codegen/cuda/runtime/helpers.cu
${TORCH_SRC_DIR}/csrc/jit/codegen/cuda/runtime/random_numbers.cu
${TORCH_SRC_DIR}/csrc/jit/codegen/cuda/runtime/tensor.cu
${CMAKE_CURRENT_SOURCE_DIR}/../aten/src/ATen/cuda/detail/PhiloxCudaStateRaw.cuh
${CMAKE_CURRENT_SOURCE_DIR}/../aten/src/ATen/cuda/detail/UnpackRaw.cuh
)
file(MAKE_DIRECTORY "${CMAKE_BINARY_DIR}/include/nvfuser_resources")
# "stringify" NVFUSER runtime sources
# (generate C++ header files embedding the original input as a string literal)
set(NVFUSER_STRINGIFY_TOOL "${TORCH_SRC_DIR}/csrc/jit/codegen/cuda/tools/stringify_file.py")
foreach(src ${NVFUSER_RUNTIME_FILES})
get_filename_component(filename ${src} NAME_WE)
set(dst "${CMAKE_BINARY_DIR}/include/nvfuser_resources/${filename}.h")
add_custom_command(
COMMENT "Stringify NVFUSER runtime source file"
OUTPUT ${dst}
DEPENDS ${src}
COMMAND ${PYTHON_EXECUTABLE} ${NVFUSER_STRINGIFY_TOOL} -i ${src} -o ${dst}
)
add_custom_target(nvfuser_rt_${filename} DEPENDS ${dst})
add_dependencies(${TORCHLIB_FLAVOR} nvfuser_rt_${filename})
# also generate the resource headers during the configuration step
# (so tools like clang-tidy can run w/o requiring a real build)
execute_process(COMMAND
${PYTHON_EXECUTABLE} ${NVFUSER_STRINGIFY_TOOL} -i ${src} -o ${dst})
endforeach()
target_include_directories(${TORCHLIB_FLAVOR} PRIVATE "${CMAKE_BINARY_DIR}/include")
endif()
if(NOT MSVC AND USE_XNNPACK)
TARGET_LINK_LIBRARIES(torch_cpu PRIVATE fxdiv)
endif()
# ==========================================================
# formerly-libtorch flags
# ==========================================================
if(NOT INTERN_BUILD_MOBILE)
# Forces caffe2.pb.h to be generated before its dependents are compiled.
# Adding the generated header file to the ${TORCH_SRCS} list is not sufficient
# to establish the dependency, since the generation procedure is declared in a different CMake file.
# See https://samthursfield.wordpress.com/2015/11/21/cmake-dependencies-between-targets-and-files-and-custom-commands/#custom-commands-in-different-directories
add_dependencies(torch_cpu Caffe2_PROTO)
endif()
# Codegen selected_mobile_ops.h for template selective build
if(BUILD_LITE_INTERPRETER AND SELECTED_OP_LIST)
add_custom_command(
OUTPUT ${CMAKE_BINARY_DIR}/aten/src/ATen/selected_mobile_ops.h
COMMAND
"${PYTHON_EXECUTABLE}" -m tools.lite_interpreter.gen_selected_mobile_ops_header
--yaml_file_path "${SELECTED_OP_LIST}"
--output_file_path "${CMAKE_BINARY_DIR}/aten/src/ATen"
WORKING_DIRECTORY "${TORCH_ROOT}")
add_custom_target(