Using a Jupyter Notebook within a Docker Container

Accelerated Computing NGC GPU Cloud Docker and NVIDIA Docker
4

For all of you struggling with this as well. I solved it by building my own container and adding some flags when running the container.

An example, adding Keras to the nvidia tensorflow container.

  1. Create a file called "Dockerfile"
  2. Enter the following 
    FROM nvcr.io/nvidia/tensorflow:18.08-py3
WORKDIR /my-ml-files
RUN pip install jupyter
EXPOSE 8888
RUN pip install keras
  3. Run the following in a terminal inside of the folder where you saved the "Dockerfile" 
    docker build -t my-nvidia-container .
  4. The container is now built. To run it run the following 
    docker run --runtime=nvidia -it my-nvidia-container

If you’re looking to add a folder with files to the docker container
Run the following command when starting the docker container instead

docker run --runtime=nvidia -it -v "/my-local-computer-files/:/my-docker-container/" my-nvidia-container

. Where if you change directory to

/my-docker-container/

inside of the container, your files in

/my-local-computer-files/

should be visible and accessible.

Access jupyter notebook
Add the flag

-p 8888:8888

to the command. You may combine this with the one above (

-v "/my-local-computer-files/:/my-docker-container/"

).
Example: 

docker run --runtime=nvidia -it -p "8888:8888" -v "/my-local-computer-files/:/my-docker-container/" my-nvidia-container

And when you’re inside of the docker container run

jupyter notebook --port=8888 --ip=0.0.0.0 --allow-root --no-browser .

and then you’ll be able to access it from your local browser at http://localhost:8888

Hope that helps.
Victor

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