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CI

GPU-enabled docker container with Jupyterlab for artificial intelligence

bio.tools entry RRID entry

General information

Project name: An accessible infrastructure for artificial intelligence using a docker-based Jupyterlab in Galaxy

Project home page: https://github.com/usegalaxy-eu/gpu-jupyterlab-docker

Docker file: https://github.com/usegalaxy-eu/gpu-jupyterlab-docker/blob/master/Dockerfile

Container at Quay.io: https://quay.io/galaxy/docker-ml-jupyterlab/tags

Galaxy tool (that runs this container): https://github.com/usegalaxy-eu/galaxy/blob/release_23.0_europe/tools/interactive/interactivetool_ml_jupyter_notebook.xml

Data: https://zenodo.org/record/6091361 (to run sample notebooks at https://github.com/anuprulez/gpu_jupyterlab_ct_image_segmentation)

How to use: Galaxy training network tutorial

Operating system(s): Linux

Programming language(s): Python, Docker, XML

iPython sample notebooks: https://github.com/anuprulez/gpu_jupyterlab_ct_image_segmentation

Other requirements: Docker 20.10.21, (Optional) CUDA 11.8, CUDA DNN 8

License: MIT License

RRID: SCR_022695

bioToolsID: gpu-enabled_docker_container_with_jupyterlab_for_ai

Running steps:

  1. Download container: docker pull quay.io/galaxy/docker-ml-jupyterlab:galaxy-integration-0.3

  2. Run container (on host without Nvidia GPU): docker run -it -p 8888:8888 -v <<path to local folder>>:/import quay.io/galaxy/docker-ml-jupyterlab:galaxy-integration-0.3

  3. Run container (on host with Nvidia GPU): docker run -it --gpus all -p 8888:8888 -v <<path to local folder>>:/import quay.io/galaxy/docker-ml-jupyterlab:galaxy-integration-0.3

  4. Open the link to the Jupyterlab (e.g. http://<<host>>:8888/ipython/lab)

List of packages for Machine learning and deep learning

  • Python (version: 3.10.0)
  • Jupyterlab (version: 3.6.5)
  • Jupyterlab-git (version: 0.41.0)
  • Scikit learn (version: 1.1.2)
  • Scikit image (version: 0.21.0)
  • Tensorflow (version: 2.11)
  • ONNX (version: 1.12.0)
  • Nibabel (5.1.0)
  • OpenCV (version: 4.7)
  • CUDA (version: 11.8)
  • CUDA DNN (version: 8.6)
  • Bqplot (version: 0.12.39)
  • Bokeh (version: 3.2.0)
  • Matplotlib (version: 3.7.2)
  • Seaborn (version: 0.12.2)
  • Voila (version: 0.4.1)
  • Jupyterlab-nvdashboard (version: 0.8.0)
  • Py3Dmol (version: 2.0.3)
  • Elyra AI (version: 3.15.0)
  • Colabfold (version: 1.5.2)
  • Bioblend (version: 1.1.1)
  • Biopython (version: 1.81)
  • many more ...