Under Ubuntu18.04。When I compile the number, there is an error calling the libwarp_perspective.so file。

[yeyuxmf]

OSError: /home/huang/vsopencv/extension-script/example_app/build/warp_perspective/libwarp_perspective.so: undefined symbol: _ZN3c1017RegisterOperators25checkSchemaAndRegisterOp_ERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEONS0_7OptionsE

[yeyuxmf]

(pytorch) huang@huang-ubuntu:~/vsopencv/extension-script/example_app/warp_perspective/build$ cmake -DCMAKE_PREFIX_PATH=/home/huang/libtorch1.2.0/libtorch .. -- The C compiler identification is GNU 7.4.0 -- The CXX compiler identification is GNU 7.4.0 -- Check for working C compiler: /usr/bin/cc -- Check for working C compiler: /usr/bin/cc -- works -- Detecting C compiler ABI info -- Detecting C compiler ABI info - done -- Detecting C compile features -- Detecting C compile features - done -- Check for working CXX compiler: /usr/bin/c++ -- Check for working CXX compiler: /usr/bin/c++ -- works -- Detecting CXX compiler ABI info -- Detecting CXX compiler ABI info - done -- Detecting CXX compile features -- Detecting CXX compile features - done -- Looking for pthread.h -- Looking for pthread.h - found -- Performing Test CMAKE_HAVE_LIBC_PTHREAD -- Performing Test CMAKE_HAVE_LIBC_PTHREAD - Failed -- Looking for pthread_create in pthreads -- Looking for pthread_create in pthreads - not found -- Looking for pthread_create in pthread -- Looking for pthread_create in pthread - found -- Found Threads: TRUE
-- Found CUDA: /usr/local/cuda-10.0 (found version "10.0") -- Caffe2: CUDA detected: 10.0 -- Caffe2: CUDA nvcc is: /usr/local/cuda-10.0/bin/nvcc -- Caffe2: CUDA toolkit directory: /usr/local/cuda-10.0 -- Caffe2: Header version is: 10.0 -- Found CUDNN: /usr/local/cuda-10.0/include
-- Found cuDNN: v7.6.4 (include: /usr/local/cuda-10.0/include, library: /usr/local/cuda-10.0/lib64/libcudnn.so) -- Autodetected CUDA architecture(s): 7.5 -- Added CUDA NVCC flags for: -gencode;arch=compute_75,code=sm_75 -- Found torch: /home/huang/libtorch1.2.0/libtorch/lib/libtorch.so
-- Pytorch status: -- libraries: torch;torch_library;/home/huang/libtorch1.2.0/libtorch/lib/libc10.so;/usr/lib/x86_64-linux-gnu/libcuda.so;/usr/local/cuda-10.0/lib64/libnvrtc.so;/usr/local/cuda-10.0/lib64/libnvToolsExt.so;/usr/local/cuda-10.0/lib64/libcudart.so;/home/huang/libtorch1.2.0/libtorch/lib/libc10_cuda.so -- Configuring done -- Generating done -- Build files have been written to: /home/huang/vsopencv/extension-script/example_app/warp_perspective/build (pytorch) huang@huang-ubuntu:~/vsopencv/extension-script/example_app/warp_perspective/build$ make Scanning dependencies of target warp_perspective [ 50%] Building CXX object CMakeFiles/warp_perspective.dir/op.cpp.o /home/huang/vsopencv/extension-script/example_app/warp_perspective/op.cpp:11:78: warning: ‘torch::jit::RegisterOperators::RegisterOperators(const string&, Implementation&&) [with Implementation = at::Tensor (*)(at::Tensor, at::Tensor); std::__cxx11::string = std::__cxx11::basic_string]’ is deprecated [-Wdeprecated-declarations] torch::jit::RegisterOperators("my_ops::warp_perspective", &warp_perspective); ^ In file included from /home/huang/libtorch1.2.0/libtorch/include/torch/script.h:5:0, from /home/huang/vsopencv/extension-script/example_app/warp_perspective/op.cpp:1: /home/huang/libtorch1.2.0/libtorch/include/torch/csrc/jit/custom_operator.h:28:3: note: declared here RegisterOperators(const std::string& name, Implementation&& implementation) { ^~~~~~~~~~~~~~~~~ [100%] Linking CXX shared library libwarp_perspective.so [100%] Built target warp_perspective (pytorch) huang@huang-ubuntu:~/vsopencv/extension-script/example_app/warp_perspective/build$ cmake -DCMAKE_PREFIX_PATH=/home/huang/libtorch1.2.0/libtorch ..

[zetyquickly]

Why don't you use a provided docker?

[yeyuxmf]

@zetyquickly The anaconda tool I use. But it's not about using containers. Containers are just convenient to provide a clean environment.

[leerumor]

@zetyquickly The anaconda tool I use. But it's not about using containers. Containers are just convenient to provide a clean environment.

I got the same error with docker, and several other issues. What version of pytorch do you use?