Docker - Anaconda and Tensorflow
Welcome to the anaconda/tensorflow image. This image was built to be used as a simple way
to run a standard ML system with tensorflow.
The latest branch will (by default) be setup to use the latest version of python and
tensorflow that are CPU based. This will allow for the system to use the standard
ubuntu base image.
However there are tags that will be created for the gpu specific versions of the system.
These will each be tagged as such.
So for every tensorflow example that exists a corresponding version will also exist that
will just have the appended tag value of -gpu, for example:
latest -> latest-gpu python35 -> python35-gpu python35-onbuild -> python35-onbuild-gpu
To use this image you will want to have a volume mounted at
/notebooks, and expose port
docker run -it --rm -p 8888:8888 -v $PWD:/notebooks mikewright/anaconda-tensorflow:latest-gpu
At this point you can open your browser to localhost:8888.
If you want to have your own tools installed you may do so by creating a Dockerfile based on the
onbuild tag. You will need to have your anaconda environment file created and named
and you will want to set the environment variable
CONDA_ENV to the name of the enviroment you created.
-- environment.yml name: myenv dependencies: - jupyter - pymc -- Dockerfile FROM mikewright/anaconda-tensorflow:latest-onbuild ENV CONDA_ENV myenv