You can work on the assignment in one of two ways: locally on your own machine, or on a virtual machine on Google Cloud.

Note: after following these instructions, you can skip the Working locally section.

As part of this course, you can use Google Cloud for your assignments. We recommend this route for anyone who is having trouble with installation set-up, or if you would like to use better CPU/GPU resources than you may have locally. Please see the set-up tutorial here for more details. :)

Working locally

Installing Anaconda: If you decide to work locally, we recommend using the free Anaconda Python distribution, which provides an easy way for you to handle package dependencies. Please be sure to download the Python 3 version, which currently installs Python 3.7. We are no longer supporting Python 2.

Anaconda Virtual environment: Once you have Anaconda installed, it makes sense to create a virtual environment for the course. If you choose not to use a virtual environment, it is up to you to make sure that all dependencies for the code are installed globally on your machine. To set up a virtual environment, run (in a terminal)

conda create -n cs231n python=3.7 anaconda

to create an environment called cs231n.

Then, to activate and enter the environment, run

source activate cs231n

To exit, you can simply close the window, or run

source deactivate cs231n

Note that every time you want to work on the assignment, you should run source activate cs231n (change to the name of your virtual env).

You may refer to this page for more detailed instructions on managing virtual environments with Anaconda.

Python virtualenv: Alternatively, you may use python virtualenv for the project. To set up a virtual environment, run the following:

cd assignment1
sudo pip install virtualenv      # This may already be installed
virtualenv -p python3 .env       # Create a virtual environment (python3)
# Note: you can also use "virtualenv .env" to use your default python (please note we support 3.6)
source .env/bin/activate         # Activate the virtual environment
pip install -r requirements.txt  # Install dependencies
# Work on the assignment for a while ...
deactivate                       # Exit the virtual environment