{"id":16473583,"url":"https://github.com/guumaster/playground-docker-gpu-jupyterlab","last_synced_at":"2025-07-29T11:09:18.112Z","repository":{"id":67988979,"uuid":"158126225","full_name":"guumaster/playground-docker-gpu-jupyterlab","owner":"guumaster","description":"Docker image with gpu support and jupyterlab installed","archived":false,"fork":false,"pushed_at":"2018-11-19T12:02:14.000Z","size":85,"stargazers_count":1,"open_issues_count":0,"forks_count":3,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-02-28T12:43:32.120Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/guumaster.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-11-18T20:57:06.000Z","updated_at":"2021-12-02T11:42:44.000Z","dependencies_parsed_at":"2023-02-23T16:31:43.492Z","dependency_job_id":null,"html_url":"https://github.com/guumaster/playground-docker-gpu-jupyterlab","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/guumaster/playground-docker-gpu-jupyterlab","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/guumaster%2Fplayground-docker-gpu-jupyterlab","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/guumaster%2Fplayground-docker-gpu-jupyterlab/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/guumaster%2Fplayground-docker-gpu-jupyterlab/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/guumaster%2Fplayground-docker-gpu-jupyterlab/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/guumaster","download_url":"https://codeload.github.com/guumaster/playground-docker-gpu-jupyterlab/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/guumaster%2Fplayground-docker-gpu-jupyterlab/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":267677266,"owners_count":24126313,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-07-29T02:00:12.549Z","response_time":2574,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-10-11T12:27:28.663Z","updated_at":"2025-07-29T11:09:18.082Z","avatar_url":"https://github.com/guumaster.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# JupyterLab with Tensorflow\n\n\n## Pre-requisites\n\n- Install `nvidia-dirvers` for your graphic card and make sure that `nvidia-smi` outputs information about the installed driver.\n\n\n## Installation \n\n\n### nvidia-docker\n\nAdd `nvidia-docker` repo and install `nvidia-docker2` plugin.\n\n```\ncurl -s -L https://nvidia.github.io/nvidia-docker/gpgkey |   sudo apt-key add -\ndistribution=$(. /etc/os-release;echo $ID$VERSION_ID)\necho $distribution\ncurl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list |   sudo tee /etc/apt/sources.list.d/nvidia-docker.list\napt-get update\napt-get install -y nvidia-docker2\nservice docker restart\n\n```\n\nThen add `nvidia` as  `default-runtime` in the file `/etc/docker/daemon.json`. Edit like this:\n\n```\n{\n  \"default-runtime\": \"nvidia\",\n  \"runtimes\": ... \n}\n```\n\n\n\n### Test GPU support\n\nYou can check if your local configuration is correct and your containers would have GPU support with this commmands:\n\n```\ndocker run --rm nvidia/cuda:9.0-base nvidia-smi\n\n# Output something like this:\n# +-----------------------------------------------------------------------------+\n# | NVIDIA-SMI 415.13       Driver Version: 415.13       CUDA Version: 10.0     |\n# |-------------------------------+----------------------+----------------------+\n# | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n# | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n# |===============================+======================+======================|\n# |   0  GeForce GTX 105...  Off  | 00000000:01:00.0 Off |                  N/A |\n# | N/A   40C    P8    N/A /  N/A |   3743MiB /  4042MiB |      0%      Default |\n# +-------------------------------+----------------------+----------------------+\n#                                                                                \n# +-----------------------------------------------------------------------------+\n# | Processes:                                                       GPU Memory |\n# |  GPU       PID   Type   Process name                             Usage      |\n# |=============================================================================|\n# +-----------------------------------------------------------------------------+\n\n```\n\n## Build image\n\n### Setup .env\n\nFirst copy `.env-example` to `.env` and fill the info with the data obtained from `id`\n\n```\n$ id\n#   uid=1000(mr_robot) gid=1002(mr_robot) groups=1002(mr_robot)\n\n# edit .env like this:\nNB_USER=mr_robot\nNB_UID=1000\nNB_GID=1000\n```\n\nThis is necessary so the notebooks would be mounted with write permissions for your host user\n\n\n### build with docker\n\n```\ndocker build -t jupyter-lab . \n```\n\n*NOTE:* This is the moment to grab that coffee. It'd take long to build.\n\n\n## Test JupyterLab GPU support\n\nTo test if everything is ok and there is GPU support run this command:\n\n```\ndocker run --rm jupyter-lab nvidia-smi\n\n# Output similar to the above example\n```\n\n## Usage\n\nOnce you have your image built. Add a persistence volume to save your notebooks and start the service.\n\n### Run docker-compose\n\n```\ndocker-compose up\n```\n\n## Adding notebooks\n\nYou can add notebooks as volumes shared to the container. Edit `docker-compose.yml`. 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