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Docker container with Python3, Tensorflow and Jupyter for training models on AWS

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tensorflow-jupyter-aws-docker

Docker container with Python3, Tensorflow and Jupyter for training models on AWS Store all notebooks to local or to S3 bucket

Steps:

  1. Create a S3 bucket on AWS

  2. Clone the repo

  3. Build docker image

    docker build -t tensorflow-jupyter-aws-docker .
    
  4. Run Docker

    • Option 1: Run docker with S3 Contents Managers

      1. Credentials Ensure AWS credentials are available in your shell, if not set them manually:
        export AWS_ACCESS_KEY_ID=###
        export AWS_SECRET_ACCESS_KEY=###
        export AWS_SESSION_TOKEN=###
        
      2. Run image
        docker run -it --rm \
            -p=8888:8888 \
            --name=tensorflow-jupyter-aws-docker \
            -e "AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID" \
            -e "AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY" \
            -e "AWS_SESSION_TOKEN=$AWS_SESSION_TOKEN" \
            -e "AWS_REGION=$AWS_REGION" \
            -e "AWS_S3_BUCKET=your-s3-bucket-name" \
            tensorflow-jupyter-aws-docker develop
        

      NOTE: AWS_SESSION_TOKEN might be optional

    • Option2: To docker with local filesystem

      1. Run image
      docker run -it --rm \
          -p=8888:8888 \
          --name=tensorflow-jupyter-aws-docker \
          -v $(pwd)/notebooks:/opt/docker/notebooks \
          tensorflow-jupyter-aws-docker develop
      
  5. Open the Jupyter notebook

    From the terminal, copy the notebook url with token in browser

    [I 07:19:30.621 NotebookApp] Writing notebook server cookie secret to /root/.local/share/jupyter/runtime/notebook_cookie_secret
    jupyter_http_over_ws extension initialized. Listening on /http_over_websocket
    [I 07:19:31.551 NotebookApp] Serving contents
    [I 07:19:31.551 NotebookApp] The Jupyter Notebook is running at:
    [I 07:19:31.552 NotebookApp] http://(b4e1cc10327f or 127.0.0.1):8888/?token=a3e4a939f857d0a9ba40daa73dc7a20cbd6219947843f3ca
    [I 07:19:31.552 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
    [C 07:19:31.558 NotebookApp]
    
        To access the notebook, open this file in a browser:
            file:///root/.local/share/jupyter/runtime/nbserver-12-open.html
        Or copy and paste one of these URLs:
            http://(b4e1cc10327f or 127.0.0.1):8888/?token=a3e4a939f857d0a9ba40daa73dc7a20cbd6219947843f3ca
    

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Docker container with Python3, Tensorflow and Jupyter for training models on AWS

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