Machine learning algorithm always need lots of computing resource, generally, the computer is big and noisy, and most of them are host on Linux system, so most of us run our code on a remote server. How to set up the remote development environment to make us work smoothly is really important.
There includes several stuffs we have to set up:
- file transfer with server
- UI on remote
- machine learning environment
- remote development tool
Notice: If you are in **mainland China **, you’d better set up a proxy to go through GFW, so that you can enjoy free network, you need to set up you proxy both on browser and terminal, since you need to download many packages on terminal when you setting up you environment, otherwise it may cost you lots of time to set up stuffs. For how to set up network proxy, refer to my post—set up VPS.
Special statement: This tutorial is only for learning and research, thanks.
basically, we should visit our remote sever through ssh connection. refer this for ssh without password.
you can rename your ssh sever by edit
Host my_server HostName example.com # ip or domain name User root # user name
then your can just visit your server by
In addition, if you need to connect your server through a jumper machine, refer my note that how to make your ssh more smoothly by adding ssh tunnel.
If visiting your server should through a SSL based VPN, and the VPN client only has Windows version, and your host machine is linux, then how to make it work on your Linux? refer my post—Enabling SSL VPN on Linux.
file transfer with server
just refer my another post Transfer files, using scp or sshfs.
machine learning environment
just install some basic tools on Linux, such as
git vim tmux htop etc.
you can write a shell scrip to do all that, and I will publish a scrip on my Github to duo that later.
machine learning frameworks:
how to set up environment
most remote servers are using python as high-level development language, there are several python package management tools, such as pip, conda, and python virtual environment managers, such as miniconda, anaconda, pyenv, and I personally recommend conda, your can use Miniconda or anaconda.
you’d better set up an python environment which separate your env with system, since there amy be other people also using your machine, mixing up stuffs may make your env heavy and out of your control. moreover, setting up a virtual env make your transplant your env easier.
some basic conda command, for more, refer conda cmd.
conda install numpy conda remove numpy conda create -n myenv conda create –n test_env python=3.6 conda list conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/ conda config --set show_channel_urls yes here modify ~/.condarc and change the priority of channels, make sure the new added channel is first! conda activate $ENVIRONMENT_NAME conda deactivate
remote development tool
some developer do like just write code on vim via ssh to their server, so how to develop on remote? one is Jupyter notebook, you can rite code and view plot figures on browser, for IDE, I recommend Pytorch, it can write code on local and automatically synchronize to your remote server and run code on your remote server with your local Pycharm IDE.
looking for more about jupyter set up, refer my note jupyter and tensorboard configuration
if you want to set specific GPU in your python program, please us
export CUDA_VISIBLE_DEVICES=0,1 text.py, if you are in Jupyter, there is a way to set it, but sometime it doesn’t work, so I recommend you just add the following line to your ‘~/.bashrc’, then you needn’t to set it every time.
tensorboard is a monitor for your to trace and debug your algorithm. also visited on browser after remote server set up it.
for set up pycharm to work on remove server, refer this post for to to set up.
on pycharm, you can edit, run and debug your code on remote server. and it also sport matplotlib to plot figures on remote and view them in IDE.
vs code can only edit remote file, but can not run it on remote via local interface, for details, referDeveloping on a remote server
view remote UI on local
basically, you can use X11 forward to do it, just use
ssh -X name@domain, on Linux, you only need basic set up
.ssh/config to enable X11 forward, and to test it, just run
xclock on remote server, and there will be a clock ui pop up on your local machine.
for windows user, your need install and open a X11 server first, you can install xming.