Hello, I am trying to get pytorch running inside docker, but not having much luck. Here is some terminal output first from the host machine, then immediately after running inside of a base nvidia/cuda docker image:
$ nvidia-smi ... | NVIDIA-SMI 440.44 Driver Version: 440.44 CUDA Version: 10.2 | ... $ nvidia-docker run --rm -it nvidia/cuda:10.2-base-ubuntu18.04 /bin/bash # nvidia-smi ... | NVIDIA-SMI 440.44 Driver Version: 440.44 CUDA Version: 10.2 | ... # apt-get update && apt-get install -y python3 python3-pip && pip3 install torch torchvision ... # python3 -m torch.utils.collect_env Collecting environment information... PyTorch version: 1.6.0 Is debug build: No CUDA used to build PyTorch: 10.2 OS: Ubuntu 18.04.5 LTS GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0 CMake version: Could not collect Python version: 3.6 Is CUDA available: No CUDA runtime version: Could not collect GPU models and configuration: GPU 0: GeForce RTX 2080 SUPER Nvidia driver version: 440.44 cuDNN version: Could not collect Versions of relevant libraries: [pip3] numpy==1.19.2 [pip3] torch==1.6.0 [pip3] torchvision==0.7.0 [conda] Could not collect
I am using prepackaged nvidia/cuda docker containers and a minimal python install, so I’m not sure what could be going wrong. All of the problems I have found other people have so far have caused
nvidia-smi to not work properly, but in my case, it is working fine, yet torch still says CUDA is not available.