深度学习docker环境

GPU docker cuda 10.0 cudnn v7 python 3.6 anaconda 5.2.0 Jupyter Notebook @:8888 Xgboost latest(gpu) lightgbm latest(gpu) tensorflow 1.13.0rc0(pip) tensorboard latest (pip) @:6006 pytorch latest(pip) torchvision latest (pip) keras latest (pip) CPU docker python 3.6 anaconda 5.2.0 Jupyter Notebook @:8888 AwS api boto3(pip) Xgboost latest(pip) lightgbm latest install docker env sudo bash ./docker_install.sh pull docker from AWS ecr aws configure aws ecr get-login --no-include-email > login.sh sudo bash ./login.sh sudo rm login.sh sudo docker pull url:tag run gpu docker sudo docker run --runtime=nvidia --rm -d -p 8888:8888 -p 6006:6006 --name ml-gpu -e PASSWORD= -v /home/ubuntu/notebook:/notebook run cpu docker sudo docker run --rm -d -p 8888:8888 --name ml-cpu -e PASSWORD= -v /home/ubuntu/notebook:/notebook