PyTorch logo black.svg
Original author(s)
  • Adam Paszke
  • Sam Gross
  • Soumith Chintala
  • Gregory Chanan
Developer(s)Facebook's AI Research lab (FAIR)
Initial releaseSeptember 2016 (2016-09)[1]
Stable release
1.7.1[2] Edit this on Wikidata / 10 December 2020 (10 December 2020)
Written in
Operating system
PlatformIA-32, x86-64
Available inEnglish
TypeLibrary for machine learning and deep learning

PyTorch is an open source machine learning library based on the Torch library,[3][4][5] used for applications such as computer vision and natural language processing,[6] primarily developed by Facebook's AI Research lab (FAIR).[7][8][9] It is 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.[10]

A number of pieces of Deep Learning software are built on top of PyTorch, including Tesla Autopilot,[11] Uber's Pyro,[12] HuggingFace's Transformers,[13] PyTorch Lightning,[14][15] and Catalyst.[16][17]

PyTorch provides two high-level features:[18]

  1. ^ Chintala, Soumith (1 September 2016). "PyTorch Alpha-1 release".
  2. ^ "Release 1.7.1". 10 December 2020. Retrieved 16 December 2020.
  3. ^ Yegulalp, Serdar (19 January 2017). "Facebook brings GPU-powered machine learning to Python". InfoWorld. Retrieved 11 December 2017.
  4. ^ Lorica, Ben (3 August 2017). "Why AI and machine learning researchers are beginning to embrace PyTorch". O'Reilly Media. Retrieved 11 December 2017.
  5. ^ 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.
  6. ^ "Natural Language Processing (NLP) with PyTorch – NLP with PyTorch documentation". Retrieved 2017-12-18.
  7. ^ Patel, Mo (2017-12-07). "When two trends fuse: PyTorch and recommender systems". O'Reilly Media. Retrieved 2017-12-18.
  8. ^ 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.
  9. ^ Arakelyan, Sophia (2017-11-29). "Tech giants are using open source frameworks to dominate the AI community". VentureBeat. Retrieved 2017-12-18.
  10. ^ "The C++ Frontend". PyTorch Master Documentation. Retrieved 2019-07-29.
  11. ^ Karpathy, Andrej. "PyTorch at Tesla - Andrej Karpathy, Tesla".
  12. ^ "Uber AI Labs Open Sources Pyro, a Deep Probabilistic Programming Language". Uber Engineering Blog. 2017-11-03. Retrieved 2017-12-18.
  13. ^ PYTORCH-TRANSFORMERS: PyTorch implementations of popular NLP Transformers, PyTorch Hub, 2019-12-01, retrieved 2019-12-01
  14. ^ PYTORCH-Lightning: The lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate, Lightning-Team, 2020-06-18, retrieved 2020-06-18
  15. ^ "Ecosystem Tools". Retrieved 2020-06-18.
  16. ^ GitHub - catalyst-team/catalyst: Accelerated DL & RL, Catalyst-Team, 2019-12-05, retrieved 2019-12-05
  17. ^ "Ecosystem Tools". Retrieved 2020-04-04.
  18. ^ "PyTorch – About". Archived from the original on 2018-06-15. Retrieved 2018-06-11.