Designed for heavy computations in TensorFlow using Python 3.
Dockerfile: https://github.com/Jrachman/tensorflow-py3-docker/blob/master/Dockerfile
Developer: Julian Rachman (jmrachman@gmail.com)
Setup and run
Pre-built image
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There is a pre-built image that was created: https://hub.docker.com/r/julianrachman/tensorflow-py3/
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Execute
docker pull julianrachman/tensorflow-py3:latestin the terminal. -
Use
docker run -it --network=host -p 8888:8888 -e "PASSWORD=pass" --name jrtfpy3 julianrachman/tensorflow-py3:latestto run this. -
Run
config/run_jupyter.sh --allow-rootand you are set! Just visit http://localhost:8888 and the password should be "pass."
Local build
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Download the GitHub repository (https://github.com/Jrachman/tensorflow-py3-docker/), extract, and navigate to the directory where the
Dockerfileis located using your terminal. -
Then execute the command
docker build . -
After the build is complete, execute
docker images, find the most recentIMAGE ID -
Now execute
docker run -it -p 8888:8888 -e "PASSWORD=pass" --name jrtfpy3 <IMAGE ID> -
Run
config/run_jupyter.sh --allow-rootand you are set! Just visit http://localhost:8888 and the password should be "pass."
Docker Compose build
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docker-compose build -
docker-compose up
Git
Clone
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Navigate to the Docker container terminal and make sure you are in the "notebooks" directory.
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git clone <your repsoitory URL>
Initial push
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Navigate to the Docker container terminal and make sure you are in the "notebooks" directory.
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Configure Git for the first time by running the command
git config --global user.name "<NAME>" && git config --global user.email "<EMAIL>" -
git init -
git add . -
git commit -m "First commit" -
git remote add origin <remote repository URL> -
git remote -v -
git push -u origin master
Further pushing
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Navigate to the Docker container terminal and make sure you are in the "notebooks" directory.
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git status -
git add . -
git commit -m "<MESSAGE>" -
git push -u origin master