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https://github.com/pytorch/pytorch.git
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1. Move CUDNN code to seperate module. 2. Merge CUDNN public and private targets into a single private target. There is no need to expose CUDNN dependency. Pull Request resolved: https://github.com/pytorch/pytorch/pull/91676 Approved by: https://github.com/malfet
422 lines
16 KiB
CMake
422 lines
16 KiB
CMake
# ---[ cuda
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# Poor man's include guard
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if(TARGET torch::cudart)
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return()
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endif()
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# sccache is only supported in CMake master and not in the newest official
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# release (3.11.3) yet. Hence we need our own Modules_CUDA_fix to enable sccache.
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list(APPEND CMAKE_MODULE_PATH ${CMAKE_CURRENT_LIST_DIR}/../Modules_CUDA_fix)
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# We don't want to statically link cudart, because we rely on it's dynamic linkage in
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# python (follow along torch/cuda/__init__.py and usage of cudaGetErrorName).
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# Technically, we can link cudart here statically, and link libtorch_python.so
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# to a dynamic libcudart.so, but that's just wasteful.
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# However, on Windows, if this one gets switched off, the error "cuda: unknown error"
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# will be raised when running the following code:
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# >>> import torch
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# >>> torch.cuda.is_available()
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# >>> torch.cuda.current_device()
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# More details can be found in the following links.
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# https://github.com/pytorch/pytorch/issues/20635
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# https://github.com/pytorch/pytorch/issues/17108
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if(NOT MSVC)
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set(CUDA_USE_STATIC_CUDA_RUNTIME OFF CACHE INTERNAL "")
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endif()
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# Find CUDA.
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find_package(CUDA)
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if(NOT CUDA_FOUND)
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message(WARNING
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"Caffe2: CUDA cannot be found. Depending on whether you are building "
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"Caffe2 or a Caffe2 dependent library, the next warning / error will "
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"give you more info.")
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set(CAFFE2_USE_CUDA OFF)
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return()
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endif()
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# Enable CUDA language support
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set(CUDAToolkit_ROOT "${CUDA_TOOLKIT_ROOT_DIR}")
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# Pass clang as host compiler, which according to the docs
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# Must be done before CUDA language is enabled, see mast be done before
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# see https://cmake.org/cmake/help/v3.15/variable/CMAKE_CUDA_HOST_COMPILER.html
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if("${CMAKE_CXX_COMPILER_ID}" MATCHES "Clang")
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set(CMAKE_CUDA_HOST_COMPILER "${CMAKE_C_COMPILER}")
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endif()
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enable_language(CUDA)
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set(CMAKE_CUDA_STANDARD ${CMAKE_CXX_STANDARD})
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set(CMAKE_CUDA_STANDARD_REQUIRED ON)
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message(STATUS "Caffe2: CUDA detected: " ${CUDA_VERSION})
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message(STATUS "Caffe2: CUDA nvcc is: " ${CUDA_NVCC_EXECUTABLE})
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message(STATUS "Caffe2: CUDA toolkit directory: " ${CUDA_TOOLKIT_ROOT_DIR})
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if(CUDA_VERSION VERSION_LESS 11.0)
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message(FATAL_ERROR "PyTorch requires CUDA 11.0 or above.")
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endif()
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if(CUDA_FOUND)
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# Sometimes, we may mismatch nvcc with the CUDA headers we are
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# compiling with, e.g., if a ccache nvcc is fed to us by CUDA_NVCC_EXECUTABLE
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# but the PATH is not consistent with CUDA_HOME. It's better safe
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# than sorry: make sure everything is consistent.
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if(MSVC AND CMAKE_GENERATOR MATCHES "Visual Studio")
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# When using Visual Studio, it attempts to lock the whole binary dir when
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# `try_run` is called, which will cause the build to fail.
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string(RANDOM BUILD_SUFFIX)
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set(PROJECT_RANDOM_BINARY_DIR "${PROJECT_BINARY_DIR}/${BUILD_SUFFIX}")
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else()
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set(PROJECT_RANDOM_BINARY_DIR "${PROJECT_BINARY_DIR}")
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endif()
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set(file "${PROJECT_BINARY_DIR}/detect_cuda_version.cc")
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file(WRITE ${file} ""
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"#include <cuda.h>\n"
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"#include <cstdio>\n"
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"int main() {\n"
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" printf(\"%d.%d\", CUDA_VERSION / 1000, (CUDA_VERSION / 10) % 100);\n"
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" return 0;\n"
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"}\n"
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)
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if(NOT CMAKE_CROSSCOMPILING)
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try_run(run_result compile_result ${PROJECT_RANDOM_BINARY_DIR} ${file}
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CMAKE_FLAGS "-DINCLUDE_DIRECTORIES=${CUDA_INCLUDE_DIRS}"
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LINK_LIBRARIES ${CUDA_LIBRARIES}
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RUN_OUTPUT_VARIABLE cuda_version_from_header
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COMPILE_OUTPUT_VARIABLE output_var
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)
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if(NOT compile_result)
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message(FATAL_ERROR "Caffe2: Couldn't determine version from header: " ${output_var})
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endif()
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message(STATUS "Caffe2: Header version is: " ${cuda_version_from_header})
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if(NOT cuda_version_from_header STREQUAL ${CUDA_VERSION_STRING})
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# Force CUDA to be processed for again next time
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# TODO: I'm not sure if this counts as an implementation detail of
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# FindCUDA
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set(${cuda_version_from_findcuda} ${CUDA_VERSION_STRING})
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unset(CUDA_TOOLKIT_ROOT_DIR_INTERNAL CACHE)
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# Not strictly necessary, but for good luck.
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unset(CUDA_VERSION CACHE)
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# Error out
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message(FATAL_ERROR "FindCUDA says CUDA version is ${cuda_version_from_findcuda} (usually determined by nvcc), "
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"but the CUDA headers say the version is ${cuda_version_from_header}. This often occurs "
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"when you set both CUDA_HOME and CUDA_NVCC_EXECUTABLE to "
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"non-standard locations, without also setting PATH to point to the correct nvcc. "
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"Perhaps, try re-running this command again with PATH=${CUDA_TOOLKIT_ROOT_DIR}/bin:$PATH. "
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"See above log messages for more diagnostics, and see https://github.com/pytorch/pytorch/issues/8092 for more details.")
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endif()
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endif()
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endif()
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# Optionally, find TensorRT
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if(CAFFE2_USE_TENSORRT)
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find_path(TENSORRT_INCLUDE_DIR NvInfer.h
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HINTS ${TENSORRT_ROOT} ${CUDA_TOOLKIT_ROOT_DIR}
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PATH_SUFFIXES include)
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find_library(TENSORRT_LIBRARY nvinfer
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HINTS ${TENSORRT_ROOT} ${CUDA_TOOLKIT_ROOT_DIR}
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PATH_SUFFIXES lib lib64 lib/x64)
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find_package_handle_standard_args(
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TENSORRT DEFAULT_MSG TENSORRT_INCLUDE_DIR TENSORRT_LIBRARY)
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if(TENSORRT_FOUND)
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execute_process(COMMAND /bin/sh -c "[ -r \"${TENSORRT_INCLUDE_DIR}/NvInferVersion.h\" ] && awk '/^\#define NV_TENSORRT_MAJOR/ {print $3}' \"${TENSORRT_INCLUDE_DIR}/NvInferVersion.h\"" OUTPUT_VARIABLE TENSORRT_VERSION_MAJOR)
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execute_process(COMMAND /bin/sh -c "[ -r \"${TENSORRT_INCLUDE_DIR}/NvInferVersion.h\" ] && awk '/^\#define NV_TENSORRT_MINOR/ {print $3}' \"${TENSORRT_INCLUDE_DIR}/NvInferVersion.h\"" OUTPUT_VARIABLE TENSORRT_VERSION_MINOR)
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if(TENSORRT_VERSION_MAJOR)
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string(STRIP ${TENSORRT_VERSION_MAJOR} TENSORRT_VERSION_MAJOR)
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string(STRIP ${TENSORRT_VERSION_MINOR} TENSORRT_VERSION_MINOR)
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set(TENSORRT_VERSION "${TENSORRT_VERSION_MAJOR}.${TENSORRT_VERSION_MINOR}")
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#CAFFE2_USE_TRT is set in Dependencies
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -DTENSORRT_VERSION_MAJOR=${TENSORRT_VERSION_MAJOR}")
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -DTENSORRT_VERSION_MINOR=${TENSORRT_VERSION_MINOR}")
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else()
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message(WARNING "Caffe2: Cannot find ${TENSORRT_INCLUDE_DIR}/NvInferVersion.h. Assuming TRT 5.0 which is no longer supported. Turning the option off.")
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set(CAFFE2_USE_TENSORRT OFF)
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endif()
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else()
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message(WARNING
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"Caffe2: Cannot find TensorRT library. Turning the option off.")
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set(CAFFE2_USE_TENSORRT OFF)
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endif()
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endif()
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# ---[ CUDA libraries wrapper
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# find libcuda.so and lbnvrtc.so
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# For libcuda.so, we will find it under lib, lib64, and then the
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# stubs folder, in case we are building on a system that does not
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# have cuda driver installed. On windows, we also search under the
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# folder lib/x64.
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find_library(CUDA_CUDA_LIB cuda
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PATHS ${CUDA_TOOLKIT_ROOT_DIR}
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PATH_SUFFIXES lib lib64 lib/stubs lib64/stubs lib/x64)
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find_library(CUDA_NVRTC_LIB nvrtc
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PATHS ${CUDA_TOOLKIT_ROOT_DIR}
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PATH_SUFFIXES lib lib64 lib/x64)
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if(CUDA_NVRTC_LIB AND NOT CUDA_NVRTC_SHORTHASH)
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if("${PYTHON_EXECUTABLE}" STREQUAL "")
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set(_python_exe "python")
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else()
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set(_python_exe "${PYTHON_EXECUTABLE}")
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endif()
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execute_process(
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COMMAND "${_python_exe}" -c
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"import hashlib;hash=hashlib.sha256();hash.update(open('${CUDA_NVRTC_LIB}','rb').read());print(hash.hexdigest()[:8])"
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RESULT_VARIABLE _retval
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OUTPUT_VARIABLE CUDA_NVRTC_SHORTHASH)
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if(NOT _retval EQUAL 0)
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message(WARNING "Failed to compute shorthash for libnvrtc.so")
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set(CUDA_NVRTC_SHORTHASH "XXXXXXXX")
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else()
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string(STRIP "${CUDA_NVRTC_SHORTHASH}" CUDA_NVRTC_SHORTHASH)
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message(STATUS "${CUDA_NVRTC_LIB} shorthash is ${CUDA_NVRTC_SHORTHASH}")
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endif()
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endif()
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# Create new style imported libraries.
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# Several of these libraries have a hardcoded path if CAFFE2_STATIC_LINK_CUDA
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# is set. This path is where sane CUDA installations have their static
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# libraries installed. This flag should only be used for binary builds, so
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# end-users should never have this flag set.
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# cuda
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add_library(caffe2::cuda UNKNOWN IMPORTED)
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set_property(
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TARGET caffe2::cuda PROPERTY IMPORTED_LOCATION
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${CUDA_CUDA_LIB})
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set_property(
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TARGET caffe2::cuda PROPERTY INTERFACE_INCLUDE_DIRECTORIES
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${CUDA_INCLUDE_DIRS})
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# cudart. CUDA_LIBRARIES is actually a list, so we will make an interface
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# library.
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add_library(torch::cudart INTERFACE IMPORTED)
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if(CAFFE2_STATIC_LINK_CUDA)
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set_property(
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TARGET torch::cudart PROPERTY INTERFACE_LINK_LIBRARIES
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"${CUDA_cudart_static_LIBRARY}")
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if(NOT WIN32)
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set_property(
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TARGET torch::cudart APPEND PROPERTY INTERFACE_LINK_LIBRARIES
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rt dl)
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endif()
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else()
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set_property(
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TARGET torch::cudart PROPERTY INTERFACE_LINK_LIBRARIES
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${CUDA_LIBRARIES})
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endif()
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set_property(
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TARGET torch::cudart PROPERTY INTERFACE_INCLUDE_DIRECTORIES
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${CUDA_INCLUDE_DIRS})
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# nvToolsExt
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add_library(torch::nvtoolsext INTERFACE IMPORTED)
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if(MSVC)
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if(NOT NVTOOLEXT_HOME)
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set(NVTOOLEXT_HOME "C:/Program Files/NVIDIA Corporation/NvToolsExt")
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endif()
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if(DEFINED ENV{NVTOOLSEXT_PATH})
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set(NVTOOLEXT_HOME $ENV{NVTOOLSEXT_PATH})
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file(TO_CMAKE_PATH ${NVTOOLEXT_HOME} NVTOOLEXT_HOME)
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endif()
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set_target_properties(
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torch::nvtoolsext PROPERTIES
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INTERFACE_LINK_LIBRARIES ${NVTOOLEXT_HOME}/lib/x64/nvToolsExt64_1.lib
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INTERFACE_INCLUDE_DIRECTORIES ${NVTOOLEXT_HOME}/include)
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elseif(APPLE)
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set_property(
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TARGET torch::nvtoolsext PROPERTY INTERFACE_LINK_LIBRARIES
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${CUDA_TOOLKIT_ROOT_DIR}/lib/libnvrtc.dylib
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${CUDA_TOOLKIT_ROOT_DIR}/lib/libnvToolsExt.dylib)
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else()
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find_library(LIBNVTOOLSEXT libnvToolsExt.so PATHS ${CUDA_TOOLKIT_ROOT_DIR}/lib64/)
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set_property(
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TARGET torch::nvtoolsext PROPERTY INTERFACE_LINK_LIBRARIES
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${LIBNVTOOLSEXT})
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endif()
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# cublas. CUDA_CUBLAS_LIBRARIES is actually a list, so we will make an
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# interface library similar to cudart.
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add_library(caffe2::cublas INTERFACE IMPORTED)
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if(CAFFE2_STATIC_LINK_CUDA AND NOT WIN32)
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set_property(
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TARGET caffe2::cublas PROPERTY INTERFACE_LINK_LIBRARIES
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${CUDA_CUBLAS_LIBRARIES})
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# Add explicit dependency to cudart_static to fix
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# libcublasLt_static.a.o): undefined reference to symbol 'cudaStreamWaitEvent'
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# error adding symbols: DSO missing from command line
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set_property(
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TARGET caffe2::cublas APPEND PROPERTY INTERFACE_LINK_LIBRARIES
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"${CUDA_cudart_static_LIBRARY}" rt dl)
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else()
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set_property(
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TARGET caffe2::cublas PROPERTY INTERFACE_LINK_LIBRARIES
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${CUDA_CUBLAS_LIBRARIES})
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endif()
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set_property(
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TARGET caffe2::cublas PROPERTY INTERFACE_INCLUDE_DIRECTORIES
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${CUDA_INCLUDE_DIRS})
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# cudnn interface
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# static linking is handled by USE_STATIC_CUDNN environment variable
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if(CAFFE2_USE_CUDNN)
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if(USE_STATIC_CUDNN)
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set(CUDNN_STATIC ON CACHE BOOL "")
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else()
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set(CUDNN_STATIC OFF CACHE BOOL "")
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endif()
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find_package(CUDNN)
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if(NOT CUDNN_FOUND)
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message(WARNING
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"Cannot find cuDNN library. Turning the option off")
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set(CAFFE2_USE_CUDNN OFF)
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else()
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if(CUDNN_VERSION VERSION_LESS "8.0.0")
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message(FATAL_ERROR "PyTorch requires cuDNN 8 and above.")
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endif()
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endif()
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add_library(torch::cudnn INTERFACE IMPORTED)
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target_include_directories(torch::cudnn INTERFACE ${CUDNN_INCLUDE_PATH})
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if(CUDNN_STATIC AND NOT WIN32)
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target_link_options(torch::cudnn INTERFACE
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"-Wl,--exclude-libs,libcudnn_static.a")
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else()
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target_link_libraries(torch::cudnn INTERFACE ${CUDNN_LIBRARY_PATH})
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endif()
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else()
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message(STATUS "USE_CUDNN is set to 0. Compiling without cuDNN support")
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endif()
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# curand
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add_library(caffe2::curand UNKNOWN IMPORTED)
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if(CAFFE2_STATIC_LINK_CUDA AND NOT WIN32)
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set_property(
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TARGET caffe2::curand PROPERTY IMPORTED_LOCATION
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"${CUDA_TOOLKIT_ROOT_DIR}/lib64/libcurand_static.a")
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set_property(
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TARGET caffe2::curand PROPERTY INTERFACE_LINK_LIBRARIES
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"${CUDA_TOOLKIT_ROOT_DIR}/lib64/libculibos.a" dl)
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else()
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set_property(
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TARGET caffe2::curand PROPERTY IMPORTED_LOCATION
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${CUDA_curand_LIBRARY})
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endif()
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set_property(
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TARGET caffe2::curand PROPERTY INTERFACE_INCLUDE_DIRECTORIES
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${CUDA_INCLUDE_DIRS})
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# cufft. CUDA_CUFFT_LIBRARIES is actually a list, so we will make an
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# interface library similar to cudart.
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add_library(caffe2::cufft INTERFACE IMPORTED)
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if(CAFFE2_STATIC_LINK_CUDA AND NOT WIN32)
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set_property(
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TARGET caffe2::cufft PROPERTY INTERFACE_LINK_LIBRARIES
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"${CUDA_TOOLKIT_ROOT_DIR}/lib64/libcufft_static_nocallback.a"
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"${CUDA_TOOLKIT_ROOT_DIR}/lib64/libculibos.a" dl)
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else()
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set_property(
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TARGET caffe2::cufft PROPERTY INTERFACE_LINK_LIBRARIES
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${CUDA_CUFFT_LIBRARIES})
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endif()
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set_property(
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TARGET caffe2::cufft PROPERTY INTERFACE_INCLUDE_DIRECTORIES
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${CUDA_INCLUDE_DIRS})
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# TensorRT
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if(CAFFE2_USE_TENSORRT)
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add_library(caffe2::tensorrt UNKNOWN IMPORTED)
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set_property(
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TARGET caffe2::tensorrt PROPERTY IMPORTED_LOCATION
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${TENSORRT_LIBRARY})
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set_property(
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TARGET caffe2::tensorrt PROPERTY INTERFACE_INCLUDE_DIRECTORIES
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${TENSORRT_INCLUDE_DIR})
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endif()
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# nvrtc
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add_library(caffe2::nvrtc UNKNOWN IMPORTED)
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set_property(
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TARGET caffe2::nvrtc PROPERTY IMPORTED_LOCATION
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${CUDA_NVRTC_LIB})
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set_property(
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TARGET caffe2::nvrtc PROPERTY INTERFACE_INCLUDE_DIRECTORIES
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${CUDA_INCLUDE_DIRS})
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# Add onnx namepsace definition to nvcc
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if(ONNX_NAMESPACE)
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list(APPEND CUDA_NVCC_FLAGS "-DONNX_NAMESPACE=${ONNX_NAMESPACE}")
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else()
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list(APPEND CUDA_NVCC_FLAGS "-DONNX_NAMESPACE=onnx_c2")
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endif()
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# Don't activate VC env again for Ninja generators with MSVC on Windows if CUDAHOSTCXX is not defined
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# by adding --use-local-env.
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if(MSVC AND CMAKE_GENERATOR STREQUAL "Ninja" AND NOT DEFINED ENV{CUDAHOSTCXX})
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list(APPEND CUDA_NVCC_FLAGS "--use-local-env")
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endif()
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# setting nvcc arch flags
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torch_cuda_get_nvcc_gencode_flag(NVCC_FLAGS_EXTRA)
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# CMake 3.18 adds integrated support for architecture selection, but we can't rely on it
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set(CMAKE_CUDA_ARCHITECTURES OFF)
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list(APPEND CUDA_NVCC_FLAGS ${NVCC_FLAGS_EXTRA})
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message(STATUS "Added CUDA NVCC flags for: ${NVCC_FLAGS_EXTRA}")
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# disable some nvcc diagnostic that appears in boost, glog, glags, opencv, etc.
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foreach(diag cc_clobber_ignored integer_sign_change useless_using_declaration
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set_but_not_used field_without_dll_interface
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base_class_has_different_dll_interface
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dll_interface_conflict_none_assumed
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dll_interface_conflict_dllexport_assumed
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implicit_return_from_non_void_function
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unsigned_compare_with_zero
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declared_but_not_referenced
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bad_friend_decl)
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list(APPEND SUPPRESS_WARNING_FLAGS --diag_suppress=${diag})
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endforeach()
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string(REPLACE ";" "," SUPPRESS_WARNING_FLAGS "${SUPPRESS_WARNING_FLAGS}")
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list(APPEND CUDA_NVCC_FLAGS -Xcudafe ${SUPPRESS_WARNING_FLAGS})
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set(CUDA_PROPAGATE_HOST_FLAGS_BLOCKLIST "-Werror")
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if(MSVC)
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list(APPEND CUDA_NVCC_FLAGS "--Werror" "cross-execution-space-call")
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list(APPEND CUDA_NVCC_FLAGS "--no-host-device-move-forward")
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endif()
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# Debug and Release symbol support
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if(MSVC)
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if(${CAFFE2_USE_MSVC_STATIC_RUNTIME})
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string(APPEND CMAKE_CUDA_FLAGS_DEBUG " -Xcompiler /MTd")
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string(APPEND CMAKE_CUDA_FLAGS_MINSIZEREL " -Xcompiler /MT")
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string(APPEND CMAKE_CUDA_FLAGS_RELEASE " -Xcompiler /MT")
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string(APPEND CMAKE_CUDA_FLAGS_RELWITHDEBINFO " -Xcompiler /MT")
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else()
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string(APPEND CMAKE_CUDA_FLAGS_DEBUG " -Xcompiler /MDd")
|
|
string(APPEND CMAKE_CUDA_FLAGS_MINSIZEREL " -Xcompiler /MD")
|
|
string(APPEND CMAKE_CUDA_FLAGS_RELEASE " -Xcompiler /MD")
|
|
string(APPEND CMAKE_CUDA_FLAGS_RELWITHDEBINFO " -Xcompiler /MD")
|
|
endif()
|
|
if(CUDA_NVCC_FLAGS MATCHES "Zi")
|
|
list(APPEND CUDA_NVCC_FLAGS "-Xcompiler" "-FS")
|
|
endif()
|
|
elseif(CUDA_DEVICE_DEBUG)
|
|
list(APPEND CUDA_NVCC_FLAGS "-g" "-G") # -G enables device code debugging symbols
|
|
endif()
|
|
|
|
# Set expt-relaxed-constexpr to suppress Eigen warnings
|
|
list(APPEND CUDA_NVCC_FLAGS "--expt-relaxed-constexpr")
|
|
|
|
# Set expt-extended-lambda to support lambda on device
|
|
list(APPEND CUDA_NVCC_FLAGS "--expt-extended-lambda")
|
|
|
|
foreach(FLAG ${CUDA_NVCC_FLAGS})
|
|
string(FIND "${FLAG}" " " flag_space_position)
|
|
if(NOT flag_space_position EQUAL -1)
|
|
message(FATAL_ERROR "Found spaces in CUDA_NVCC_FLAGS entry '${FLAG}'")
|
|
endif()
|
|
string(APPEND CMAKE_CUDA_FLAGS " ${FLAG}")
|
|
endforeach()
|