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CLAI


Technion Collaborative AI (Spring 2024)

Sarah Keren

Itay Segev โ€ข Andrey Elashkin

Jupyter Notebook tutorials for the Technion's CS 236203 course Collaborative AI

Open In Colab Open In NBViewer

Agenda

File Topics Covered
Setting Up The Working Environment.pdf Guide for installing Anaconda locally with Python 3 and PyTorch, integration with PyCharm and using GPU on Google Colab
tutorials/tut01/Jupyter101.ipynb Basic introduction to Jupyter Notebooks, covering essential features like creating and running cells, and writing markdown for documentation.
tutorials/tut01/PytorchFundamentals.ipynb Basic of PyTorch, focusing on tensor operations, neural network construction, and training models.
tutorials/tut01/Gymnasium.ipynb Using Gymnasium for creating and interacting with reinforcement learning environments, including setting up environments, running simulations, and implementing agents.
tutorials/tut01/PettingZooDemo.ipynb Demonstration of the PettingZoo library for multi-agent reinforcement learning, covering environment setup, interaction, and agent implementation.
tutorials/tut01/StableBaselines.ipynb Overview of the Stable Baselines3 library for reinforcement learning, covering setup, training, and evaluation of RL models.

Running The Notebooks

You can view the tutorials online or download and run locally.

Running Online

Service Usage
Jupyter Nbviewer Render and view the notebooks (can not edit)
Google Colab Render, view, edit and save the notebooks to Google Drive (limited time)

Jupyter Nbviewer:

nbviewer

Press on the "Open in Colab" button below to use Google Colab:

Open In Colab

Running Locally

Press "Download ZIP" under the green button Clone or download or use git to clone the repository using the following command: git clone https://github.com/CLAIR-LAB-TECHNION/CLAI.git (in cmd/PowerShell in Windows or in the Terminal in Linux/Mac)

Open the folder in Jupyter Notebook (it is recommended to use Anaconda). Installation instructions can be found in Setting Up The Working Environment.pdf.

Installation Instructions

For the complete guide, with step-by-step images, please consult Setting Up The Working Environment.pdf

  1. Get Anaconda with Python 3, follow the instructions according to your OS (Windows/Mac/Linux) at: https://www.anaconda.com/download
  2. Install the basic packages using the provided environment.yml file by running: conda env create -f environment.yml which will create a new conda environment named CLAI. If you did this, you will only need to install PyTorch, see the table below.
  3. Alternatively, you can create a new environment for the course and install packages from scratch: In Windows open Anaconda Prompt from the start menu, in Mac/Linux open the terminal and run conda create --name CLAI. Full guide at https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-with-commands
  4. To activate the environment, open the terminal (or Anaconda Prompt in Windows) and run conda activate CLAI
  5. Install the required libraries according to the table below (to search for a specific library and the corresponding command you can also look at https://anaconda.org/)

Libraries to Install

Library Command to Run
Jupyter Notebook conda install -c conda-forge notebook
numpy conda install -c conda-forge numpy
matplotlib conda install -c conda-forge matplotlib
tqdm conda install -c conda-forge tqdm
gymnasium pip install gymnasium
pettingzoo pip install pettingzoo
stable-baselines3 pip install stable-baselines3
pytorch (cpu) conda install pytorch torchvision torchaudio cpuonly -c pytorch (get command from PyTorch.org)
pytorch (gpu) conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia (get command from PyTorch.org)
  1. To open the notebooks, open Ananconda Navigator or run jupyter notebook in the terminal (or Anaconda Prompt in Windows) while the CLAI environment is activated.


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