python_setup_instructions.md

Python Setup Instructions (Local)

Setup

Installing Anaconda: We recommend using Anaconda Python distribution which provides an easy way for you to handle package dependencies. Please be sure to download the Python 3 version.

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 tdt4265 python=3.6 anaconda

to create a environment called tdt4265.

Then, to activate and enter the environment, run

source activate tdt4265

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

source deactivate tdt419tdt42655

Note that every time you want to work on the assignment, you should run source activate tdt4265 (change to the name of your virtual env).

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

Installing requirements for tdt4265

We use several python packages in this course. To install requirements you can use either pip or conda. First, activate and enter your environment with

source activate tdt4265

Then install pytorch and torchvision by the following command

MACOS:

conda install pytorch torchvision -c pytorch

Linux or Windows:

conda install pytorch torchvision cpuonly -c pytorch

You can also follow the tutorial on the pytorch website.

Note, if you have a PC with NVIDIA GPU (Linux or windows), you need to install CUDA and CUDNN first if you want to utilize your GPU. Installing CUDA and CUDNN is outside of the scope for this tutorial.

Install tqdm.

conda install tqdm

Finally, install scikit-image:

conda install -c conda-forge scikit-image

Launching jupyter notebook

Once you have finished the environment setup, and installed the required packages, you can launch jupyter notebook with the command:

jupyter notebook

Then, if you open a jupyter notebook file (.ipynb), you will see the active environment in the top right corner. To change the kernel to the right environment select kernel -> change kernel -> Python tdt4265.

If your environment is not showing up in the list of kernels, you can take a quick look on this stackoverflow post.