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Local/Biglab setup

Miniconda is a package, dependency and environment management for python (amongst other languages). It lets you install different versions of python, different versions of various packages in different environments which makes working on multiple projects (with different dependencies) easy.

There are two ways to use miniconda,

  1. Use an existing installation from another user: On biglab, add the following line at the end of your ~/.bashrc file.
    export PATH="/home1/c/cis530/miniconda3/bin:$PATH"
    

    Then run the following command

    source ~/.bashrc
    

    If you run the command $ which conda, the output should be /home1/c/cis530/miniconda3/bin/conda.

  2. Installing Miniconda from scratch: On biglab, run the following commands. Press Enter/Agree to all prompts during installation.
    $ wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
    $ chmod +x Miniconda3-latest-Linux-x86_64.sh
    $ bash Miniconda3-latest-Linux-x86_64.sh
    

    After successful installation, running the command $ which conda should output /home1/m/$USERNAME/miniconda3/bin/conda.

Installing Pytorch and Jupyter

For this assignment, you’ll be using Pytorch and Jupyter.

  1. If you used the existing miniconda installation from 1. above, you’re good to go. Stop wasting time and start working on the assignment!

  2. Intrepid students who installed their own miniconda version from 2. above, need to install their own copy of Pytorch and Jupyter. To install Pytorch, run the command

    conda install pytorch-cpu torchvision -c pytorch
    

    To check, run python and import torch. This should run without giving errors. To install jupyter, run the command (it might take a while)

    conda install jupyter
    

    Running the command jupyter --version should yield the version installed.

How to use Jupyter notebook

For this homework, you have the option of using jupyter notebook, which lets you interactively edit your code within the web browser. Jupyter reads files in the .ipynb format. To launch from biglab, do the following.

  1. On biglab, navigate to the directory with your code files and type jupyter notebook --port 8888 --no-browser. If you are having token issues, you may need to also add the argument --NotebookApp.token=''.
  2. In your local terminal, set up port forward by typing ssh -N -f -L localhost:8888:localhost:8888 yourname@biglab.seas.upenn.edu.
  3. In your local web browser, navigate to localhost:8888.