gcc中的-Wl,rpath=<your_lib_dir>选项

gcc编译链接动态库时,很有可能编译通过,但是执行时,找不到动态链接库,那是

因为-L选项指定的路径只在编译时有效,编译出来的可执行文件不知道-L选项后面的值,

当然找不到。可以用ldd <your_execute>看看是不有 ‘not found’在你链接的库后面,

解决方法是通过-Wl,rpath=<your_lib_dir>,使得execute记住链接库的位置

CMake Error at /home/sniper/anaconda3/envs/yolov8/lib/python3.8/site-packages/cmake/data/share/cmake-3.25/Modules/CMakeTestCCompiler.cmake:70 (message): The C compiler "/usr/bin/gcc" is not able to compile a simple test program. It fails with the following output: Change Dir: /opt/projects/tensorrt-alpha/yolov8/build/CMakeFiles/CMakeScratch/TryCompile-TrXrKM Run Build Command(s):/usr/bin/make -f Makefile cmTC_7d457/fast && /usr/bin/make -f CMakeFiles/cmTC_7d457.dir/build.make CMakeFiles/cmTC_7d457.dir/build make[1]: 进入目录“/opt/projects/tensorrt-alpha/yolov8/build/CMakeFiles/CMakeScratch/TryCompile-TrXrKM” Building C object CMakeFiles/cmTC_7d457.dir/testCCompiler.c.o /usr/bin/gcc --sysroot=/usr/ -march=x86-64 -o CMakeFiles/cmTC_7d457.dir/testCCompiler.c.o -c /opt/projects/tensorrt-alpha/yolov8/build/CMakeFiles/CMakeScratch/TryCompile-TrXrKM/testCCompiler.c Linking C executable cmTC_7d457 /home/sniper/anaconda3/envs/yolov8/lib/python3.8/site-packages/cmake/data/bin/cmake -E cmake_link_script CMakeFiles/cmTC_7d457.dir/link.txt --verbose=1 /usr/bin/gcc --sysroot=/usr/ -march=x86-64 -Wl,-O2 -Wl,--sort-common -Wl,--as-needed -Wl,-z,relro -Wl,-z,now -Wl,--disable-new-dtags -Wl,--gc-sections -Wl,-rpath,/home/sniper/anaconda3/lib -Wl,-rpath-link,/home/sniper/anaconda3/lib -L/home/sniper/anaconda3/lib CMakeFiles/cmTC_7d457.dir/testCCompiler.c.o -o cmTC_7d457 /usr/bin/ld: 找不到 /lib/x86_64-linux-gnu/libc.so.6 于 /usr/ 内部 /usr/bin/ld: 找不到 /usr/lib/x86_64-linux-gnu/libc_nonshared.a 于 /usr/ 内部 /usr/bin/ld: 找不到 /lib/x86_64-linux-gnu/ld-linux-x86-64.so.2 于 /usr/ 内部 collect2: error: ld returned 1 exit status make[1]: *** [CMakeFiles/cmTC_7d457.dir/build.make:99:cmTC_7d457] 错误 1 make[1]: 离开目录“/opt/projects/tensorrt-alpha/yolov8/build/CMakeFiles/CMakeScratch/TryCompile-TrXrKM” make: *** [Makefile:127:cmTC_7d457/fast] 错误 2 CMake will not be able to correctly generate this project. Call Stack (most recent call first): CMakeLists.txt:25 (PROJECT) -- Configuring incomplete, errors occurred!
06-02
``` cc := g++ name := pro workdir := workspace srcdir := src objdir := objs stdcpp := c++11 cuda_home := /datav/software/anaconda3/lib/python3.9/site-packages/trtpy/trt8cuda112cudnn8 syslib := /datav/software/anaconda3/lib/python3.9/site-packages/trtpy/lib cpp_pkg := /datav/software/anaconda3/lib/python3.9/site-packages/trtpy/cpp-packages cuda_arch := nvcc := $(cuda_home)/bin/nvcc -ccbin=$(cc) # 定义cpp的路径查找和依赖项mk文件 cpp_srcs := $(shell find $(srcdir) -name "*.cpp") cpp_objs := $(cpp_srcs:.cpp=.cpp.o) cpp_objs := $(cpp_objs:$(srcdir)/%=$(objdir)/%) cpp_mk := $(cpp_objs:.cpp.o=.cpp.mk) # 定义cu文件的路径查找和依赖项mk文件 cu_srcs := $(shell find $(srcdir) -name "*.cu") cu_objs := $(cu_srcs:.cu=.cu.o) cu_objs := $(cu_objs:$(srcdir)/%=$(objdir)/%) cu_mk := $(cu_objs:.cu.o=.cu.mk) # 定义opencv和cuda需要用到的库文件 link_cuda := cudart cudnn link_trtpro := link_tensorRT := nvinfer nvinfer_plugin link_opencv := link_sys := stdc++ dl protobuf link_librarys := $(link_cuda) $(link_tensorRT) $(link_sys) $(link_opencv) # 定义头文件路径,请注意斜杠后边不能有空格 # 只需要写路径,不需要写-I include_paths := src \ $(cuda_home)/include/cuda \ $(cuda_home)/include/tensorRT \ $(cpp_pkg)/opencv4.2/include \ $(cuda_home)/include/protobuf # 定义库文件路径,只需要写路径,不需要写-L library_paths := $(cuda_home)/lib64 $(syslib) $(cpp_pkg)/opencv4.2/lib # 把library path给拼接为一个字符串,例如a b c => a:b:c # 然后使得LD_LIBRARY_PATH=a:b:c empty := library_path_export := $(subst $(empty) $(empty),:,$(library_paths)) # 把库路径和头文件路径拼接起来成一个,批量自动加-I、-L、-l run_paths := $(foreach item,$(library_paths),-Wl,-rpath=$(item)) include_paths := $(foreach item,$(include_paths),-I$(item)) library_paths := $(foreach item,$(library_paths),-L$(item)) link_librarys := $(foreach item,$(link_librarys),-l$(item)) # 如果是其他显卡,请修改-gencode=arch=compute_75,code=sm_75为对应显卡的能力 # 显卡对应的号码参考这里:https://developer.nvidia.com/zh-cn/cuda-gpus#compute # 如果是 jetson nano,提示找不到-m64指令,请删掉 -m64选项。不影响结果 cpp_compile_flags := -std=$(stdcpp) -w -g -O0 -m64 -fPIC -fopenmp -pthread cu_compile_flags := -std=$(stdcpp) -w -g -O0 -m64 $(cuda_arch) -Xcompiler "$(cpp_compile_flags)" link_flags := -pthread -fopenmp -Wl,-rpath='$$ORIGIN' cpp_compile_flags += $(include_paths) cu_compile_flags += $(include_paths) link_flags += $(library_paths) $(link_librarys) $(run_paths) # 如果头文件修改了,这里的指令可以让他自动编译依赖的cpp或者cu文件 ifneq ($(MAKECMDGOALS), clean) -include $(cpp_mk) $(cu_mk) endif $(name) : $(workdir)/$(name) all : $(name) run : $(name) @cd $(workdir) && ./$(name) $(run_args) $(workdir)/$(name) : $(cpp_objs) $(cu_objs) @echo Link $@ @mkdir -p $(dir $@) @$(cc) $^ -o $@ $(link_flags) $(objdir)/%.cpp.o : $(srcdir)/%.cpp @echo Compile CXX $< @mkdir -p $(dir $@) @$(cc) -c $< -o $@ $(cpp_compile_flags) $(objdir)/%.cu.o : $(srcdir)/%.cu @echo Compile CUDA $< @mkdir -p $(dir $@) @$(nvcc) -c $< -o $@ $(cu_compile_flags) # 编译cpp依赖项,生成mk文件 $(objdir)/%.cpp.mk : $(srcdir)/%.cpp @echo Compile depends C++ $< @mkdir -p $(dir $@) @$(cc) -M $< -MF $@ -MT $(@:.cpp.mk=.cpp.o) $(cpp_compile_flags) # 编译cu文件的依赖项,生成cumk文件 $(objdir)/%.cu.mk : $(srcdir)/%.cu @echo Compile depends CUDA $< @mkdir -p $(dir $@) @$(nvcc) -M $< -MF $@ -MT $(@:.cu.mk=.cu.o) $(cu_compile_flags) # 定义清理指令 clean : @rm -rf $(objdir) $(workdir)/$(name) $(workdir)/*.trtmodel $(workdir)/demo.onnx # 防止符号被当做文件 .PHONY : clean run $(name) # 导出依赖库路径,使得能够运行起来 export LD_LIBRARY_PATH:=$(library_path_export)```empty := library_path_export := $(subst $(empty) $(empty),:,$(library_paths))解释一下,每一行什么意思,具体一些
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