PyTorch

PyTorch
Original author(s)
  • Adam Paszke
  • Sam Gross
  • Soumith Chintala
  • Gregory Chanan
Developer(s)Meta AI
Initial releaseSeptember 2016; 8 years ago (2016-09)[1]
Stable release
2.5.0[2] Edit this on Wikidata / 17 October 2024; 39 days ago (17 October 2024)
Repositorygithub.com/pytorch/pytorch
Written in
Operating system
PlatformIA-32, x86-64, ARM64
Available inEnglish
TypeLibrary for machine learning and deep learning
LicenseBSD-3[3]
Websitepytorch.org
Part of a series on
Machine learning
and data mining
Paradigms
Problems
Clustering
Dimensionality reduction
Structured prediction
Anomaly detection
Artificial neural network
Reinforcement learning
Learning with humans
Model diagnostics
Mathematical foundations
Journals and conferences
Related articles

PyTorch is a machine learning library based on the Torch library,[4][5][6] used for applications such as computer vision and natural language processing,[7] originally developed by Meta AI and now part of the Linux Foundation umbrella.[8][9][10][11] It is one of the most popular deep learning frameworks, alongside others such as TensorFlow and PaddlePaddle[12][13], offering free and open-source software released under the modified BSD license. Although the Python interface is more polished and the primary focus of development, PyTorch also has a C++ interface.[14]

A number of pieces of deep learning software are built on top of PyTorch, including Tesla Autopilot,[15] Uber's Pyro,[16] Hugging Face's Transformers,[17] PyTorch Lightning,[18][19] and Catalyst.[20][21]

PyTorch provides two high-level features:[22]

  1. ^ Chintala, Soumith (1 September 2016). "PyTorch Alpha-1 release". GitHub.
  2. ^ "PyTorch 2.5.0 Release, SDPA CuDNN backend, Flex Attention". 17 October 2024. Retrieved 17 October 2024.
  3. ^ Claburn, Thomas (12 September 2022). "PyTorch gets lit under The Linux Foundation". The Register.
  4. ^ Yegulalp, Serdar (19 January 2017). "Facebook brings GPU-powered machine learning to Python". InfoWorld. Retrieved 11 December 2017.
  5. ^ Lorica, Ben (3 August 2017). "Why AI and machine learning researchers are beginning to embrace PyTorch". O'Reilly Media. Retrieved 11 December 2017.
  6. ^ Ketkar, Nikhil (2017). "Introduction to PyTorch". Deep Learning with Python. Apress, Berkeley, CA. pp. 195–208. doi:10.1007/978-1-4842-2766-4_12. ISBN 9781484227657.
  7. ^ Moez Ali (Jun 2023). "NLP with PyTorch: A Comprehensive Guide". datacamp.com. Retrieved 2024-04-01.
  8. ^ Patel, Mo (2017-12-07). "When two trends fuse: PyTorch and recommender systems". O'Reilly Media. Retrieved 2017-12-18.
  9. ^ Mannes, John. "Facebook and Microsoft collaborate to simplify conversions from PyTorch to Caffe2". TechCrunch. Retrieved 2017-12-18. FAIR is accustomed to working with PyTorch – a deep learning framework optimized for achieving state of the art results in research, regardless of resource constraints. Unfortunately in the real world, most of us are limited by the computational capabilities of our smartphones and computers.
  10. ^ Arakelyan, Sophia (2017-11-29). "Tech giants are using open source frameworks to dominate the AI community". VentureBeat. Retrieved 2017-12-18.
  11. ^ "PyTorch strengthens its governance by joining the Linux Foundation". pytorch.org. Retrieved 2022-09-13.
  12. ^ "Top 30 Open Source Projects". Open Source Project Velocity by CNCF. Retrieved 2023-10-12.
  13. ^ "Welcome to the PaddlePaddle GitHub". PaddlePaddle Official Github Repo. Retrieved 2024-10-28.
  14. ^ "The C++ Frontend". PyTorch Master Documentation. Retrieved 2019-07-29.
  15. ^ Karpathy, Andrej (6 November 2019). "PyTorch at Tesla - Andrej Karpathy, Tesla". YouTube.
  16. ^ "Uber AI Labs Open Sources Pyro, a Deep Probabilistic Programming Language". Uber Engineering Blog. 2017-11-03. Retrieved 2017-12-18.
  17. ^ PYTORCH-TRANSFORMERS: PyTorch implementations of popular NLP Transformers, PyTorch Hub, 2019-12-01, retrieved 2019-12-01
  18. ^ PYTORCH-Lightning: The lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate, Lightning-Team, 2020-06-18, retrieved 2020-06-18
  19. ^ "Ecosystem Tools". pytorch.org. Retrieved 2020-06-18.
  20. ^ GitHub - catalyst-team/catalyst: Accelerated DL & RL, Catalyst-Team, 2019-12-05, retrieved 2019-12-05
  21. ^ "Ecosystem Tools". pytorch.org. Retrieved 2020-04-04.
  22. ^ "PyTorch – About". pytorch.org. Archived from the original on 2018-06-15. Retrieved 2018-06-11.