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How Docker runs Tensorboard and jupyter

Shulou Source: shulou.com Published: 2022-06-01 13:34:50 11月15日 Update

This article mainly shows you "Docker how to run Tensorboard and jupyter", the content is easy to understand, clear, hope to help you solve your doubts, the following let the editor lead you to study and learn "how Docker runs Tensorboard and jupyter" this article.

First create a docker volumes

Docker volume create-name notebooksdocker volume create-name logs

Note: this is the volume information saved by the volume created by docker for notebook and log that jupyter runs.

Then create two directories locally to actually mount notebooks and logs

Note: the catalog is created according to your own situation.

Sudo mkdir / home/dyufei/docker/notebookssudo mkdir / home/dyufei/docker/logs

Docker runs jupyter (create jupyter container)

Docker run\-name jupyter\-d\-v notebooks:/home/dyufei/docker/notebooks\-v logs:/home/dyufei/docker/logs\-e "PASSWORD=abc123\-p 8888purr 8888\ tensorflow/tensorflow

Note:

-- name to create the container name: jupyter

-v Mount the local / home/dyufei/docker/logs directory to docker's logs volume

-e "PASSWORD=abc123" is the password for jupyter to start the login. You can set your own password as you like.

-p is port mapping

Docker runs jupyter (create tensorboard container)

Docker run\-name tensorboard\-d\-v logs:/home/dyufei/docker/logs\-e "PASSWORD=abc123"\-p 6006 logs:/home/dyufei/docker/logs 6006\ tensorflow/tensorflow:latest\ tensorboard-- logdir / home/dyufei/docker/logs

The great task has been completed! So you can open it in the browser.

Http://localhost:8888/

Http://localhost:6006/

Just try it

Tensorboard and jupyter run and stop

The above command creates and runs the tnsorboard and jupyter containers, and then you can directly start and stop the container to run and stop Tensorboard and jupyter.

1) stop

Docker stop jupyterdocker stop tensorboard

2) start

Docker start jupyterdocker start tensorboard above is all the content of the article "how Docker runs Tensorboard and jupyter". Thank you for reading! I believe we all have a certain understanding, hope to share the content to help you, if you want to learn more knowledge, welcome to follow the industry information channel!

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