This docker image supports with jupyter, pytorch and cuda.
docker run --rm -it \
-p 8888:8888 \
-e JUPYTER_TOKEN=passwd \
tverous/pytorch-notebook:latest
docker run --rm -it \
--gpus all \
-p 8888:8888 \
-e JUPYTER_TOKEN=passwd \
tverous/pytorch-notebook:latest
docker run --rm -it \
--gpus all \
-p 8888:8888 \
-e JUPYTER_TOKEN=passwd \
-v /local_vol:/docker_vol \
tverous/pytorch-notebook:latest
When you start a notebook server with token authentication enabled (default), a token is generated to use for authentication.
This token is logged to the terminal, so that you can copy/paste the URL into your browser:
If you did not specify the token before starting the container, make sure to copy/paste the token logged on the terminal
[I 11:59:16.597 NotebookApp] The Jupyter Notebook is running at:
http://localhost:8888/?token=c8de56fa4deed24899803e93c227592aef6538f93025fe01
Make sure to update the localhost of the url to your remote server IP, if you are running the container remotely.
Press Ctrl + p
and Ctrl + q
to detach the tty.
docker run --rm \ # remove the container when it exits
-it \ # pseudo-TTY
-p 8888:8888 \ # port forwarding: <Host>:<Container>
--gpus all \ # support all gpus (docker > 19.03)
-v /local_vol:/docker_vol \ # volume: mapping local folder to container
-e JUPYTER_TOKEN=passwd \ # Jupyter password: passwd
-d tverous/pytorch-notebook:latest