tmux + EC2 + deep learning
If you are training deep neural nets on AWS EC2 instances tmux can make you more efficient. It takes a long time to train these models and since you are connecting to your EC2 instance using
ssh your interface is a single shell instance. The naive approach would leave you in a situation where you can’t do anything while your model is training.
tmux helps solve this problem.
You may want to:
- Continue training your model after you disconnect from the EC2 instance.
- Launch TensorBoard and visualize your model while it is training.
- Look at some files your model creates while it is training such as images. (Since I don’t know of any way to view images on an EC2 instance I transfer them to my local computer with
$ scp -i aws_key.pem ubuntu@EC2_IP_ADDRESS:~/PATH_TO_FILE_ON_EC2 ~/PATH_TO_FILE_ON_LOCAL).
- Do other stuff on the EC2 instance while your model is training.
tmux is already installed if your instance is running Ubuntu. If running Amazon Linux installing
tmux is simple:
$ sudo yum install tmux.
Then before you start training your model run:
$ tmux and you will enter a
tmux session. Once in this session train your model as you normally would, for example:
$ python train_model.py. Now you can leave the session with
Ctrl + b and then d and you can re-enter the session with
tmux attach. To end the session when you are done or want to stop training your model run:
$ tmux kill-session.
This is a minimal guide to getting started w/ tmux & EC2. If you have any input/tips please comment and share w/ us!
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