/conda-cuda

JupyterLab for AI in Docker! Anaconda and PyTorch GPU supported.

Primary LanguagePythonMIT LicenseMIT

Anaconda Docker Image with CUDA and cuDNN

CUDA Docker environment is supported by Ubuntu nvidia cuda toolkit. Instruction: CUDA and cuDNN Install | Pop!_OS.

This docker file is used for Ubuntu 22.04 LTS, CUDA version 12.1. You may change the base system and the CUDA version listed here: nvidia/cuda | Docker Hub.

Available Tags

More Docker tags are in other Git branches. Tag names convention: CUDA_VERSION[-anaconda][-torch_VERSION].

  • latest: My customized jupyter notebook
  • 11.8: CUDA 11.8, Miniconda installed
  • 11.8-anaconda: CUDA 11.8, Anaconda 23.07 installed
  • 11.8-torch_2.1.1: CUDA 11.8, Anaconda with PyTorch 2.1.1

Install & Usage

The images with Anaconda automatically run a jupyter notebook on port 8888. Working directory in container: /work/.

docker run --detach \
    --name conda-cuda \
    --restart unless-stopped \
    --ipc=host \
    --runtime=nvidia \
    --gpus all \
    -p 80:8888 \
    -v your_project:/work/project \
    muhac/conda-cuda:latest

You can use this notebook to check your PyTorch GPU environment.