ImportError: Failed to map segment from shared object for _C.so

[VoyageWang]

ImportError: Failed to map segment from shared object for _C.so

描述: run the code: python demo_video.py segmentation/evf-sam2-multitask
ImportError: /EVF-SAM/model/segment_anything_2/sam2/_C.so: failed to map segment from shared object

I have successfully compiled the code using python setup.py build_ext --inplace

/miniconda3/envs/evf-sam/lib/python3.10/site-packages/torch/utils/cpp_extension.py:428: UserWarning: There are no g++ version bounds defined for CUDA version 12.1
warnings.warn(f'There are no {compiler_name} version bounds defined for CUDA version {cuda_str_version}')
building 'sam2._C' extension
/miniconda3/envs/evf-sam/lib/python3.10/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation.
If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].
warnings.warn(
Emitting ninja build file EVF-SAM/model/segment_anything_2/build/temp.linux-x86_64-cpython-310/build.ninja...
Compiling objects...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
ninja: no work to do.
g++ -pthread -B /miniconda3/envs/evf-sam/compiler_compat -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O2 -Wall -fPIC -O2 -isystem miniconda3/envs/evf-sam/include -fPIC -O2 -isystem miniconda3/envs/evf-sam/include -pthread -B miniconda3/envs/evf-sam/compiler_compat -shared //EVF-SAM/model/segment_anything_2/build/temp.linux-x86_64-cpython-310/sam2/csrc/connected_components.o -Lminiconda3/envs/evf-sam/lib/python3.10/site-packages/torch/lib -L/cuda/cuda-12.1/lib64 -lc10 -ltorch -ltorch_cpu -ltorch_python -lcudart -lc10_cuda -ltorch_cuda -o build/lib.linux-x86_64-cpython-310/sam2/_C.so
copying build/lib.linux-x86_64-cpython-310/sam2/_C.so -> sam2

How to solve it, thanks for your attention!!!!

[CoderZhangYx]

Haven't encounter similar problem. Could you provide detailed compiling environment?
You may try:

1. pip install -U ninja
2. check if your python version, cuda version, pytorch version, cuda driver version, gpu type are compatible.

[VoyageWang]

Thanks for your reply! I have tried the original sam2 repo, which is ok for me. However, it stiff faces the same issue when I try evf-sam2. The environment is here：

OS: [Ubuntu 20.04]
Python版本: [ 3.10]
PyTorch版本: [ 2.3.1]
CUDA版本: [12.1]
GPU型号: [ NVIDIA RTX 3090]