For the requirement of my lab, I use ubuntu and XRDP to build a virtual environment that can use GUI on it. And also I need to assign GPU resources to different people. I follow the tutorial from Nvidia Docker to build the docker, so I can assign GPU to the different user. Also, I use Anaconda to manager my python packages.
sudo docker build -t image_name:tag \
--build-arg USERNAME=username \
--build-arg USERPWD=yourpassword .
You can change the USERNAME
and USERPWD
by yourself. Or use the default setting on this image.
docker pull augustushsu/ubuntu18.04-xrdp:cuda10.0-cudnn7-anaconda
Use this command to download the image from Docker Hub
.
sudo docker run --gpus device=1 -it \
-p 33890:3389 \
-v /mnt/SSD:/data/SSD \
-v /mnt/HDD:/data/HDD \
-v /docker_config/config:/config \
image_name:tag
--gpus device
:Chose your GPU device. Or use all
.
-p
:This is port number on your host to container. host port : container port
-v
:For the directory of your host to the container. host directory : container port
For the default:
USERNAME
is username
USERPWD
is yourpassword
Before login, you need to use this command to start the xrdp
service.
service xrdp restart
You can find the script on the username
home directory named tf2.sh
and test_tf.py
.
tf2.sh
can create the tf2
enviroment and install Tensorflow2.0
.
test_tf.py
is a simple neural network on the Tensorflow website. Let you can simply test the environment.
You can find the detail on my Blog, but it is used in Chinese.
https://augustushsu.github.io/2019/12/23/DeepLearning-03/#more