A previous post showed beginners how to try out deep learning libraries by

  1. using an Amazon Machine Image (AMI) pre-installed with deep learning libraries
  2. setting up a Jupyter notebook server to play with said libraries

If you have VirtualBox and Vagrant, you can follow a similar procedure on your own computer. The advantage is that you can develop locally, then deploy on an expensive AWS EC2 gpu instance when your scripts are ready.

For example, Caffe, the machine vision framework, allows you to seamlessly transition between cpu- and gpu-mode, and is available as a vagrant box running Ubuntu 14.04 (**64-bit), with Caffe pre-installed.

To add the box, type on the command line: vagrant box add malthejorgensen/caffe-deeplearning

If you don’t already have VirtualBox and Vagrant installed, you can find instructions online, or look at my dotfiles to get an idea.


SSH authentication failure

For me, the box had the wrong public key in /home/vagrant/.ssh/authorized_keys file, which gave me “authentication failure” upon starting up the box with vagrant up. This was fixed by:

Manually ssh into the box: vagrant ssh.

Then type (key taken from here):

echo "ssh-rsa AAAAB3NzaC1yc2EAAAABIwAAAQEA6NF8iallvQVp22WDkTkyrtvp9eWW6A8YVr+kz4TjGYe7gHzIw+niNltGEFHzD8+v1I2YJ6oXevct1YeS0o9HZyN1Q9qgCgzUFtdOKLv6IedplqoPkcmF0aYet2PkEDo3MlTBckFXPITAMzF8dJSIFo9D8HfdOV0IAdx4O7PtixWKn5y2hMNG0zQPyUecp4pzC6kivAIhyfHilFR61RGL+GPXQ2MWZWFYbAGjyiYJnAmCP3NOTd0jMZEnDkbUvxhMmBYSdETk1rRgm+R4LOzFUGaHqHDLKLX+FIPKcF96hrucXzcWyLbIbEgE98OHlnVYCzRdK8jlqm8tehUc9c9WhQ== vagrant insecure public key" > ~/.ssh/authorized_keys

Log out of the box, reload the box with vagrant reload, and hopefully the ssh authentication error is fixed.

Jupyter notebook server

By default, the box has a notebook server on port 8003 that starts up from the /home/vagrant/caffe/examples directory, to be used in conjunction with port forwarding set in the Vagrant file: config.vm.network "forwarded_port", guest: 8003, host: 8003 With the default setup, go to http://localhost:8003 in your browser to access /home/vagrant/caffe/examples.

The default server setup limits access to only /home/vagrant/caffe/examples, so I prefer to set up my own configuration of the jupyter notebook server on port 8888 (allowing port forwarding of port 8888 in the Vagrantfile as well) and then start up the server from /home/vagrant, or wherever I’m working. To do this,

Log in to the box: vagrant ssh

Then create the notebook config file ~/.jupyter/jupyter_notebook_config.py containing the following lines:

c.NotebookApp.ip = '*'
c.NotebookApp.open_browser = False
c.NotebookApp.port = 8888


Here’s the vagrant file that worked for me:

** This is a 64-bit box, so you need to have Intel VT-x enabled in your BIOS.

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Cathy Yeh Avatar Cathy Yeh Cathy Yeh got a PhD at UC Santa Barbara studying soft-matter/polymer physics. After stints in a translational modeling group at Pfizer in San Diego, Driver (a no longer extant startup trying to match cancer patients to clinical trials) in San Francisco, and Square, she is currently participating in the OpenAI Scholars program.

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