tf-docker.sh

# Run interactive python tensorflow container
docker run --rm -it --name py-tf --entrypoint python tensorflow/tensorflow:1.3.0-py3

# Run jupyter notebook container
docker run --rm -dit -p 8888:8888 -p 6006:6006 -v "${PWD}":/notebooks --name notebook tensorflow/tensorflow:1.3.0-py3

# Run on ubuntu server with GPU and have it run on startup
nvidia-docker run -dit \
  -p 8888:8888 -p 6006:6006 \
  -v /home/nbs:/notebooks \
  --name notebook \
  --restart unless-stopped \
  tensorflow/tensorflow:1.3.0-gpu-py3
  
# Run on ubuntu server with GPU for specific script and also map volume for log & checkpoint output to host machine
nvidia-docker run --rm -dit \
  -p 8888:8888 -p 6006:6006 \
  -v /home/nbs:/notebooks \
  -v /home/tf-logs:/tmp/tf-logs \
  --name tf-script \
  --entrypoint train-script.sh \
  tensorflow/tensorflow:1.3.0-gpu-py3