Docker

ML Docker Image installed on the Interaction Station ML computers:
Deepo. It includes:

• cudnn
• theano
• tensorflow
• sonnet
• pytorch
• keras
• lasagne
• mxnet
• cntk
• chainer
• caffe
• caffe2
• torch

docker run -it ufoym/deepo:gpu bash Installing Docker CE on Ubuntu 16.04:

• sudo apt-get install apt-transport-https ca-certificates curl software-properties-common
• curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
• sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu xenial stable"
• sudo apt-get update

• More info: https://unix.stackexchange.com/questions/363048/unable-to-locate-package-docker-ce-on-a-64bit-ubuntu

Installing Deepo:

• Prerequisite 1: Nvidia driver
• Prerequisite 2: nvidia-docker
• Deepo (for GPU)

UUID of a partition

• sudo blkid

FSTab

Give permissions to new MachineLearning partition

• sudo chmod -R a+rwx /media/MachineLearning/

Change Docker root dir using systemd

• systemctl status docker.service
• sudo nano /etc/default/docker
• Edit ExecStart line to look like this ExecStart =/usr/bin/dockerd -g /media/MachineLearning/docker -H fd://
• systemctl daemon-reload
• systemctl restart docker
• sudo docker info - verify the root dir has updated
• https://github.com/IronicBadger/til/blob/master/docker/change-docker-root.md

Docker - clean up all the volumes

• sudo docker system prune -a -f --volumes

NTFS fstab wizard:

• sudo apt-get install ntfs-config
• sudo ntfs-config

Format large capacity HD with fs ExFat for having access to it from Ubuntu:

• On Windows 10
• cmd
• diskpart
• select disk '#' (where # is the number of the target drive)
• list part
• select part # (where # is the number of the partition)
• format fs=exfat QUICK