torch.cuda.is_available() cuda是否可用;
torch.cuda.device_count() 返回gpu数量;
torch.cuda.get_device_name(0) 返回gpu名字,设备索引默认从0开始;
torch.cuda.current_device()
cuda是nvidia gpu的编程接口,opencl是amd gpu的编程接口
torch.cuda.get_device_name(0) AssertionError: Torch not compiled with CUDA enabled
查看安装版本,支持gpu
解决办法
pip uninstall pytorch # conda uninstall pytorch, if you use conda
nvcc -V # 查看 nvcc 版本
sudo rm -f /usr/local/cuda # optional, only if you already have this symlink
sudo ln -s /usr/local/cuda-10.0 /usr/local/cuda
# 将如下路径加入环境变量,如~/.bashrc
export CUDA_HOME=/usr/local/cuda
export PATH="/usr/local/cuda/bin:$PATH"
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64"
export LIBRARY_PATH="$LIBRARY_PATH:/usr/local/cuda/lib64"
source ~/.bashrc # 确保路径被加载
# 编译并安装 pytorch
conda install numpy pyyaml mkl=2019.3 mkl-include setuptools cmake cffi typing
conda install -c pytorch magma-cuda100 # optional step
# clone the pytorch source code
git clone --recursive https://github.com/pytorch/pytorch
cd pytorch
make clean # make clean is needed in my case
export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
sudo python setup.py install # sudo is needed in my case.
torch.__version__ #查看pytorch版本
torch.version.cuda #查看pytorch版本 查询cuda版本none,需要重新编译cuda
cuda版本为none,原因是下载的时候版本选错误了