ALIVE Documentation

Documentation for the Ateneo de Manila University Laboratory for Visual and Intelligent Environments (ALIVE). This repository contains lab processes, guidelines, and shared assets.

Workstation Usage

Lab members may use the workstations to train models for thesis work or project tasks. The servers run Ubuntu Linux, so please be comfortable working in a Linux environment.

Quick Start

1. Log in to your workstation account.
2. Create and activate a Python environment:

python -m venv env
source env/bin/activate
pip install -r requirements.txt

3. Start tmux and run your script:

tmux
python run.py

4. Detach from tmux when needed:

Ctrl+b d

Dos and Don’ts

• Do use tmux for long-running processes.
• Do keep scripts bug-free and tested before running.
• Do use your official Ateneo email for account requests or support.
• Don’t run Jupyter Notebooks on the workstation.
• Don’t leave Docker containers running after training.

Time Usage

• Students can only run for 24 hours max.
• First come, first serve.
• Only 2 groups can run a process at the same time in a workstation.

Troubleshooting

• Cannot reattach to tmux: list sessions with tmux ls, then attach with tmux attach -t <index>.
• tmux says “no server running”: start a new session with tmux.
• python uses the wrong environment: activate venv again with source env/bin/activate.
• pip install fails: confirm requirements.txt exists and you have network access.
• Docker commands fail: make sure docker compose is installed and your compose file is in the current directory.

Contact

Lab Admin Team

• Dr. Patricia Abu (pabu@ateneo.edu)
• Dr. Raphael Alampay (ralampay@ateneo.edu)
• Josh Ong (jdong@ateneo.edu)
• Antonnio Diccion Jr (antonio.jr.diccion@student.atene.edu)
• Ricardo Marvic Ver Lising (rlising@ateneo.edu)

Prerequisites

• Ensure you have a workstation user account. Contact Sir Mikee Lising (rlising@ateneo.edu) via email or Google Chat using your official Ateneo email.
• Prepare bug-free scripts to run. Please do not use Jupyter Notebooks on the workstation.

Training Usage (Python)

1. Log in to your workstation account.
2. Choose a runtime setup:

Option 1: Python Isolated Environment

Create an isolated environment using venv (or another tool like pyenv). Ensure you have a requirements.txt file.

Example using venv:

python -m venv env
source env/bin/activate
pip install -r requirements.txt

Option 2: Docker

If you have your own Dockerfile or docker-compose.yml, build your image:

docker compose build .

3. Run your process inside a tmux session:

Start tmux:

tmux

Run your script:

Option 1: Python Isolated Environment

source env/bin/activate
python run.py

Option 2: Docker

docker compose up -d app

Stop your container after training:

docker compose down

Detach from the session:

Ctrl+b d

Reattach to a session:

List running sessions:

tmux ls

Attach to a session (where 0 is the session index):

tmux attach -t 0