PyTorch Documentation, PyTorch Team, 2024 (PyTorch Foundation) - Official and comprehensive guide to PyTorch's API and functionalities, essential for understanding core concepts and practical implementation.
PyTorch: An Imperative Style, High-Performance Deep Learning Library, Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, Soumith Chintala, 2019Advances in Neural Information Processing Systems 32, Vol. 32 (Curran Associates, Inc.)DOI: 10.48550/arXiv.1912.01703 - Introduces PyTorch's design principles, including its dynamic computational graph and imperative programming model.
Deep Learning with PyTorch, Eli Stevens, Luca Antiga, and Thomas Viehmann, 2020 (Manning Publications) - A practical guide to building deep learning models using PyTorch, covering core features and development workflows.