mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 21:14:14 +08:00
Summary:
Running commands:
```bash
shopt -s globstar
sed -e 's/IF (/if(/g' -e 's/IF(/if(/g' -e 's/if (/if(/g' -e 's/ELSE (/else(/g' -e 's/ELSE(/else(/g' -e 's/else (/else(/g' -e 's/ENDif(/endif(/g' -e 's/ELSEif(/elseif(/g' -i CMakeLists.txt
sed -e 's/IF (/if(/g' -e 's/IF(/if(/g' -e 's/if (/if(/g' -e 's/ELSE (/else(/g' -e 's/ELSE(/else(/g' -e 's/else (/else(/g' -e 's/ENDif(/endif(/g' -e 's/ELSEif(/elseif(/g' -i caffe2/**/CMakeLists.txt
sed -e 's/IF (/if(/g' -e 's/IF(/if(/g' -e 's/if (/if(/g' -e 's/ELSE (/else(/g' -e 's/ELSE(/else(/g' -e 's/else (/else(/g' -e 's/ENDif(/endif(/g' -e 's/ELSEif(/elseif(/g' -i torch/**/CMakeLists.txt
sed -e 's/IF (/if(/g' -e 's/IF(/if(/g' -e 's/if (/if(/g' -e 's/ELSE (/else(/g' -e 's/ELSE(/else(/g' -e 's/else (/else(/g' -e 's/ENDif(/endif(/g' -e 's/ELSEif(/elseif(/g' -i c10/**/CMakeLists.txt
sed -e 's/IF (/if(/g' -e 's/IF(/if(/g' -e 's/if (/if(/g' -e 's/ELSE (/else(/g' -e 's/ELSE(/else(/g' -e 's/else (/else(/g' -e 's/ENDif(/endif(/g' -e 's/ELSEif(/elseif(/g' -i cmake/**/*.cmake
sed -e 's/IF (/if(/g' -e 's/IF(/if(/g' -e 's/if (/if(/g' -e 's/ELSE (/else(/g' -e 's/ELSE(/else(/g' -e 's/else (/else(/g' -e 's/ENDif(/endif(/g' -e 's/ELSEif(/elseif(/g' -i cmake/**/*.cmake.in
```
We may further convert all the commands into lowercase according to the following issue: 77543bde41
.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35521
Differential Revision: D20704382
Pulled By: malfet
fbshipit-source-id: 42186b9b1660c34428ab7ceb8d3f7a0ced5d2e80
465 lines
18 KiB
CMake
465 lines
18 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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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: " ${CUDA_TOOLKIT_ROOT_DIR})
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if(CUDA_VERSION VERSION_LESS 9.0)
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message(FATAL_ERROR "PyTorch requires CUDA 9.0 and above.")
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endif()
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if(CUDA_FOUND)
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# Sometimes, we may mismatch nvcc with the CUDA headers we are
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# compiling with, e.g., if a ccache nvcc is fed to us by CUDA_NVCC_EXECUTABLE
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# but the PATH is not consistent with CUDA_HOME. It's better safe
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# than sorry: make sure everything is consistent.
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if(MSVC AND CMAKE_GENERATOR MATCHES "Visual Studio")
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# When using Visual Studio, it attempts to lock the whole binary dir when
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# `try_run` is called, which will cause the build to fail.
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string(RANDOM BUILD_SUFFIX)
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set(PROJECT_RANDOM_BINARY_DIR "${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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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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# Find cuDNN.
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if(CAFFE2_STATIC_LINK_CUDA AND NOT USE_STATIC_CUDNN)
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message(WARNING "cuDNN will be linked statically because CAFFE2_STATIC_LINK_CUDA is ON. "
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"Set USE_STATIC_CUDNN to ON to suppress this warning.")
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endif()
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if(CAFFE2_STATIC_LINK_CUDA OR 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(CAFFE2_USE_CUDNN AND NOT CUDNN_FOUND)
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message(WARNING
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"Caffe2: Cannot find cuDNN library. Turning the option off")
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set(CAFFE2_USE_CUDNN OFF)
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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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# ---[ Extract versions
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if(CAFFE2_USE_CUDNN)
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# Get cuDNN version
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file(READ ${CUDNN_INCLUDE_PATH}/cudnn.h CUDNN_HEADER_CONTENTS)
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string(REGEX MATCH "define CUDNN_MAJOR * +([0-9]+)"
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CUDNN_VERSION_MAJOR "${CUDNN_HEADER_CONTENTS}")
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string(REGEX REPLACE "define CUDNN_MAJOR * +([0-9]+)" "\\1"
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CUDNN_VERSION_MAJOR "${CUDNN_VERSION_MAJOR}")
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string(REGEX MATCH "define CUDNN_MINOR * +([0-9]+)"
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CUDNN_VERSION_MINOR "${CUDNN_HEADER_CONTENTS}")
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string(REGEX REPLACE "define CUDNN_MINOR * +([0-9]+)" "\\1"
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CUDNN_VERSION_MINOR "${CUDNN_VERSION_MINOR}")
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string(REGEX MATCH "define CUDNN_PATCHLEVEL * +([0-9]+)"
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CUDNN_VERSION_PATCH "${CUDNN_HEADER_CONTENTS}")
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string(REGEX REPLACE "define CUDNN_PATCHLEVEL * +([0-9]+)" "\\1"
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CUDNN_VERSION_PATCH "${CUDNN_VERSION_PATCH}")
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# Assemble cuDNN version
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if(NOT CUDNN_VERSION_MAJOR)
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set(CUDNN_VERSION "?")
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else()
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set(CUDNN_VERSION
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"${CUDNN_VERSION_MAJOR}.${CUDNN_VERSION_MINOR}.${CUDNN_VERSION_PATCH}")
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endif()
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message(STATUS "Found cuDNN: v${CUDNN_VERSION} (include: ${CUDNN_INCLUDE_PATH}, library: ${CUDNN_LIBRARY_PATH})")
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if(CUDNN_VERSION VERSION_LESS "7.0.0")
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message(FATAL_ERROR "PyTorch requires cuDNN 7 and above.")
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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 ${CUDA_TOOLKIT_ROOT_DIR}
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PATH_SUFFIXES lib lib64 lib/x64)
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# Create new style imported libraries.
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# Several of these libraries have a hardcoded path if CAFFE2_STATIC_LINK_CUDA
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# is set. This path is where sane CUDA installations have their static
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# libraries installed. This flag should only be used for binary builds, so
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# end-users should never have this flag set.
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# cuda
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add_library(caffe2::cuda UNKNOWN IMPORTED)
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set_property(
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TARGET caffe2::cuda PROPERTY IMPORTED_LOCATION
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${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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# cudnn
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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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add_library(caffe2::cudnn UNKNOWN IMPORTED)
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set_property(
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TARGET caffe2::cudnn PROPERTY IMPORTED_LOCATION
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${CUDNN_LIBRARY_PATH})
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set_property(
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TARGET caffe2::cudnn PROPERTY INTERFACE_INCLUDE_DIRECTORIES
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${CUDNN_INCLUDE_PATH})
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if(CUDNN_STATIC AND NOT WIN32)
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set_property(
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TARGET caffe2::cudnn PROPERTY INTERFACE_LINK_LIBRARIES
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"${CUDA_TOOLKIT_ROOT_DIR}/lib64/libculibos.a" dl)
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endif()
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endif()
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# curand
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add_library(caffe2::curand UNKNOWN IMPORTED)
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if(CAFFE2_STATIC_LINK_CUDA AND NOT WIN32)
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set_property(
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TARGET caffe2::curand PROPERTY IMPORTED_LOCATION
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"${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.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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${TENSORRT_INCLUDE_DIR})
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endif()
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# cublas. CUDA_CUBLAS_LIBRARIES is actually a list, so we will make an
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# interface library similar to cudart.
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add_library(caffe2::cublas INTERFACE IMPORTED)
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if(CAFFE2_STATIC_LINK_CUDA AND NOT WIN32)
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set_property(
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TARGET caffe2::cublas PROPERTY INTERFACE_LINK_LIBRARIES
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"${CUDA_TOOLKIT_ROOT_DIR}/lib64/libcublas_static.a")
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if(CUDA_VERSION VERSION_GREATER_EQUAL 10.1)
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set_property(
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TARGET caffe2::cublas APPEND PROPERTY INTERFACE_LINK_LIBRARIES
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"${CUDA_TOOLKIT_ROOT_DIR}/lib64/libcublasLt_static.a")
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endif()
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else()
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set_property(
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TARGET caffe2::cublas PROPERTY INTERFACE_LINK_LIBRARIES
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${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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${CUDA_INCLUDE_DIRS})
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# nvrtc
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add_library(caffe2::nvrtc UNKNOWN IMPORTED)
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set_property(
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TARGET caffe2::nvrtc PROPERTY IMPORTED_LOCATION
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${CUDA_NVRTC_LIB})
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set_property(
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TARGET caffe2::nvrtc PROPERTY INTERFACE_INCLUDE_DIRECTORIES
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${CUDA_INCLUDE_DIRS})
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# Note: in theory, we can add similar dependent library wrappers. For
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# now, Caffe2 only uses the above libraries, so we will only wrap
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# these.
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# Special care for windows platform: we know that 32-bit windows does not
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# support cuda.
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if(${CMAKE_SYSTEM_NAME} STREQUAL "Windows")
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if(NOT (CMAKE_SIZEOF_VOID_P EQUAL 8))
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message(FATAL_ERROR
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"CUDA support not available with 32-bit windows. Did you "
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"forget to set Win64 in the generator target?")
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return()
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endif()
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endif()
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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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# CUDA 9.0 & 9.1 require GCC version <= 5
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# Although they support GCC 6, but a bug that wasn't fixed until 9.2 prevents
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# them from compiling the std::tuple header of GCC 6.
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# See Sec. 2.2.1 of
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# https://developer.download.nvidia.com/compute/cuda/9.2/Prod/docs/sidebar/CUDA_Toolkit_Release_Notes.pdf
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if((CUDA_VERSION VERSION_EQUAL 9.0) OR
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(CUDA_VERSION VERSION_GREATER 9.0 AND CUDA_VERSION VERSION_LESS 9.2))
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if(CMAKE_C_COMPILER_ID STREQUAL "GNU" AND
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NOT CMAKE_C_COMPILER_VERSION VERSION_LESS 6.0 AND
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CUDA_HOST_COMPILER STREQUAL CMAKE_C_COMPILER)
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message(FATAL_ERROR
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"CUDA ${CUDA_VERSION} is not compatible with std::tuple from GCC version "
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">= 6. Please upgrade to CUDA 9.2 or set the following environment "
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"variable to use another version (for example): \n"
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" export CUDAHOSTCXX='/usr/bin/gcc-5'\n")
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endif()
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endif()
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# CUDA 9.0 / 9.1 require MSVC version < 19.12
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# CUDA 9.2 require MSVC version < 19.13
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# CUDA 10.0 require MSVC version < 19.20
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if((CUDA_VERSION VERSION_EQUAL 9.0) OR
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(CUDA_VERSION VERSION_GREATER 9.0 AND CUDA_VERSION VERSION_LESS 9.2))
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if(CMAKE_CXX_COMPILER_ID STREQUAL "MSVC" AND
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NOT CMAKE_CXX_COMPILER_VERSION VERSION_LESS 19.12 AND
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NOT DEFINED ENV{CUDAHOSTCXX})
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message(FATAL_ERROR
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"CUDA ${CUDA_VERSION} is not compatible with MSVC toolchain version "
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">= 19.12. (a.k.a Visual Studio 2017 Update 5, VS 15.5) "
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"Please upgrade to CUDA >= 9.2 or set the following environment "
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"variable to use another version (for example): \n"
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" set \"CUDAHOSTCXX=C:\\Program Files (x86)\\Microsoft Visual Studio"
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"\\2017\\Enterprise\\VC\\Tools\\MSVC\\14.11.25503\\bin\\HostX64\\x64\\cl.exe\"\n")
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endif()
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elseif(CUDA_VERSION VERSION_EQUAL 9.2)
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if(CMAKE_CXX_COMPILER_ID STREQUAL "MSVC" AND
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NOT CMAKE_CXX_COMPILER_VERSION VERSION_LESS 19.13 AND
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NOT DEFINED ENV{CUDAHOSTCXX})
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message(FATAL_ERROR
|
|
"CUDA ${CUDA_VERSION} is not compatible with MSVC toolchain version "
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|
">= 19.13. (a.k.a Visual Studio 2017 Update 7, VS 15.7) "
|
|
"Please upgrade to CUDA >= 10.0 or set the following environment "
|
|
"variable to use another version (for example): \n"
|
|
" set \"CUDAHOSTCXX=C:\\Program Files (x86)\\Microsoft Visual Studio"
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|
"\\2017\\Enterprise\\VC\\Tools\\MSVC\\14.12.25827\\bin\\HostX64\\x64\\cl.exe\"\n")
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endif()
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elseif(CUDA_VERSION VERSION_EQUAL 10.0)
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|
if(CMAKE_CXX_COMPILER_ID STREQUAL "MSVC" AND
|
|
NOT CMAKE_CXX_COMPILER_VERSION VERSION_LESS 19.20 AND
|
|
NOT DEFINED ENV{CUDAHOSTCXX})
|
|
message(FATAL_ERROR
|
|
"CUDA ${CUDA_VERSION} is not compatible with MSVC toolchain version "
|
|
">= 19.20. (a.k.a Visual Studio 2019, VS 16.0) "
|
|
"Please upgrade to CUDA >= 10.1 or set the following environment "
|
|
"variable to use another version (for example): \n"
|
|
" set \"CUDAHOSTCXX=C:\\Program Files (x86)\\Microsoft Visual Studio"
|
|
"\\2017\\Enterprise\\VC\\Tools\\MSVC\\14.16.27023\\bin\\HostX64\\x64\\cl.exe\"\n")
|
|
endif()
|
|
endif()
|
|
|
|
# Don't activate VC env again for Ninja generators with MSVC on Windows if CUDAHOSTCXX is not defined
|
|
# by adding --use-local-env.
|
|
if(MSVC AND CMAKE_GENERATOR STREQUAL "Ninja" AND NOT DEFINED ENV{CUDAHOSTCXX})
|
|
list(APPEND CUDA_NVCC_FLAGS "--use-local-env")
|
|
# For CUDA < 9.2, --cl-version xxx is also required.
|
|
# We could detect cl version according to the following variable
|
|
# https://cmake.org/cmake/help/latest/variable/MSVC_TOOLSET_VERSION.html#variable:MSVC_TOOLSET_VERSION.
|
|
# 140 = VS 2015 (14.0)
|
|
# 141 = VS 2017 (15.0)
|
|
if(CUDA_VERSION VERSION_LESS 9.2)
|
|
if(MSVC_TOOLSET_VERSION EQUAL 140)
|
|
list(APPEND CUDA_NVCC_FLAGS "--cl-version" "2015")
|
|
elseif(MSVC_TOOLSET_VERSION EQUAL 141)
|
|
list(APPEND CUDA_NVCC_FLAGS "--cl-version" "2017")
|
|
else()
|
|
message(STATUS "We could not auto-detect the cl-version for MSVC_TOOLSET_VERSION=${MSVC_TOOLSET_VERSION}")
|
|
endif()
|
|
endif()
|
|
endif()
|
|
|
|
# setting nvcc arch flags
|
|
torch_cuda_get_nvcc_gencode_flag(NVCC_FLAGS_EXTRA)
|
|
list(APPEND CUDA_NVCC_FLAGS ${NVCC_FLAGS_EXTRA})
|
|
message(STATUS "Added CUDA NVCC flags for: ${NVCC_FLAGS_EXTRA}")
|
|
|
|
# disable some nvcc diagnostic that appears in boost, glog, glags, opencv, etc.
|
|
foreach(diag cc_clobber_ignored integer_sign_change useless_using_declaration set_but_not_used)
|
|
list(APPEND CUDA_NVCC_FLAGS -Xcudafe --diag_suppress=${diag})
|
|
endforeach()
|
|
|
|
# Set C++14 support
|
|
set(CUDA_PROPAGATE_HOST_FLAGS_BLACKLIST "-Werror")
|
|
if(MSVC)
|
|
list(APPEND CUDA_PROPAGATE_HOST_FLAGS_BLACKLIST "/EHa")
|
|
else()
|
|
list(APPEND CUDA_NVCC_FLAGS "-std=c++14")
|
|
list(APPEND CUDA_NVCC_FLAGS "-Xcompiler" "-fPIC")
|
|
endif()
|
|
|
|
# OpenMP flags for NVCC with Clang-cl
|
|
if("${CMAKE_CXX_SIMULATE_ID}" STREQUAL "MSVC"
|
|
AND "${CMAKE_CXX_COMPILER_ID}" STREQUAL "Clang")
|
|
list(APPEND CUDA_PROPAGATE_HOST_FLAGS_BLACKLIST "-Xclang" "-fopenmp")
|
|
if(MSVC_TOOLSET_VERSION LESS 142)
|
|
list(APPEND CUDA_NVCC_FLAGS "-Xcompiler" "-openmp")
|
|
else()
|
|
list(APPEND CUDA_NVCC_FLAGS "-Xcompiler" "-openmp:experimental")
|
|
endif()
|
|
endif()
|
|
|
|
# Debug and Release symbol support
|
|
if(MSVC)
|
|
if(${CAFFE2_USE_MSVC_STATIC_RUNTIME})
|
|
list(APPEND CUDA_NVCC_FLAGS "-Xcompiler" "-MT$<$<CONFIG:Debug>:d>")
|
|
else()
|
|
list(APPEND CUDA_NVCC_FLAGS "-Xcompiler" "-MD$<$<CONFIG:Debug>:d>")
|
|
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")
|