Easy Lightning

Easy Lightning is a flexible and extensible framework for building deep learning models with ease using PyTorch Lightning. It simplifies training, experimentation, and deployment across tasks and datasets — with a focus on modularity and reproducibility.

It currently includes two main modules:

• EasyTorch — designed for vision and general deep learning tasks.
• EasyRec — tailored specifically for building recommendation systems.

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🚀 Features

• Modular Design: Plug in new datasets, models, loss functions, or optimizers with minimal effort.
• Config-Driven: Fully customizable experiments via YAML configuration files.
• Extendable Framework: Add your own components — from metrics to data augmentations — without changing the core logic.
• Built-in Modules: Includes EasyTorch and EasyRec for general-purpose and recommendation system tasks.

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📦 Installation and ⚡ QuickStart

pip install easy-lightning

Initialize a new project scaffold:

easy-lightning-init

This will create the configuration and directory structure needed to get started right away.

📚 Documentation

Full guides, configuration tutorials, and API references are available at:

🔗 Easy Lightning Docs

📖 How to cite

If you use Easy Lightning in your research or project, please cite us:

@article{betello2024reproducible,
  title={A Reproducible Analysis of Sequential Recommender Systems},
  author={Betello, Filippo and Purificato, Antonio and Siciliano, Federico and Trappolini, Giovanni and Bacciu, Andrea and Tonellotto, Nicola and Silvestri, Fabrizio},
  journal={IEEE Access},
  year={2024},
  publisher={IEEE}
}

🤝 Contributing

We welcome contributions! If you want to add a new module or fix a bug, feel free to open an issue or submit a pull request.