安装 Spconv
# 测试 Pytorch 版本
python -c "import torch; print(torch.__version__)"
QA
1. 出现 broken 的问题
-- The CUDA compiler identification is unknown
-- Check for working CUDA compiler: /sbin/nvcc
-- Check for working CUDA compiler: /sbin/nvcc -- broken
CMake Error at /usr/local/share/cmake-3.13/Modules/CMakeTestCUDACompiler.cmake:46 (message):
The CUDA compiler
"/sbin/nvcc"
is not able to compile a simple test program
issue 上有对应的解法,在 Spconv 根目录下的 CMakeLists.txt
文件中下面这一行前加一点设置
if (SPCONV_BuildCUDA)
加如下的设置:
set(CMAKE_CUDA_COMPILER "/usr/local/cuda/bin/nvcc")
2. 出现 Could NOT find CUDNN 问题
改了上面的问题后,出现了找不到 CUDNN 的问题:
Could NOT find CUDNN (missing: CUDNN_LIBRARY_PATH CUDNN_INCLUDE_PATH)
去下载一个 CUDNN 装上即可:
- cuDNN Runtime Library for Ubuntu16.04 (Deb)
- cuDNN Developer Library for Ubuntu16.04 (Deb)
- cuDNN Code Samples and User Guide for Ubuntu16.04 (Deb)
安装三个包:
sudo dpkg -i libcudnn7_7.4.2.24-1+cuda10.0_amd64.deb
sudo dpkg -i libcudnn7-dev_7.4.2.24-1+cuda10.0_amd64.deb
sudo dpkg -i libcudnn7-doc_7.4.2.24-1+cuda10.0_amd64.deb
一定要加上 CUDNN 的路径,之前 CUDA 的路径没有版本号!
export LD_LIBRARY_PATH=/usr/local/cuda-10.0/lib64:$LD_LIBRARY_PATH
export PATH=/usr/local/cuda-10.0/bin:$PATH
最后刷新 bash:
source ~/.bashrc
再去安装 Spconv 即可。