philipz/keras repository overview

⁠Using Keras via Nvidia-Docker

This directory contains Dockerfile to make it easy to get up and running with Keras via Docker⁠.

⁠Installing Docker

General installation instructions are on the Docker site⁠, but we give some quick links here:

• OSX⁠: docker toolbox⁠
• ubuntu⁠

⁠Running the container

For GPU support install NVidia drivers (ideally latest) and nvidia-docker⁠. Run using

nvidia-docker run --name keras --rm -v $(pwd)/src:/src -v $(pwd)/data:/data -p 8888:8888 -e KERAS_BACKEND=tensorflow philipz/keras

Note: If you would have a problem running nvidia-docker you may try the old way we have used. But it is not recommended. If you find a bug in the nvidia-docker report it there please and try using the nvidia-docker as described above.

$ export CUDA_SO=$(\ls /usr/lib/x86_64-linux-gnu/libcuda.* | xargs -I{} echo '-v {}:{}')
$ export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
$ docker run -it -p 8888:8888 $CUDA_SO $DEVICES gcr.io/tensorflow/tensorflow:latest-gpu