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|Original author(s)||Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan|
|Initial release||October 2016|
0.3.0 / 5 December 2017
|Written in||Python, C, CUDA|
|Operating system||Linux, macOS|
|Type||Library for machine learning and deep learning|
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PyTorch is an open source machine learning library for Python, used for applications such as natural language processing. It is primarily developed by Facebook's artificial-intelligence research group, and Uber's "Pyro" software for probabilistic programming is built upon it.
Others articles of the Topic Free software : Pigment (software), Fresco (windowing system), wmii, wpkg, DHTMLX, PeerCast, JQuarks
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- Comparison of deep learning software
- Torch (machine learning)
- Yegulalp, Serdar (19 January 2017). "Facebook brings GPU-powered machine learning to Python". InfoWorld. Retrieved 11 December 2017.
- Lorica, Ben (3 August 2017). "Why AI and machine learning researchers are beginning to embrace PyTorch". O'Reilly Media. Retrieved 11 December 2017.
- Ketkar, Nikhil (2017). Deep Learning with Python. Apress, Berkeley, CA. pp. 195–208. doi:10.1007/978-1-4842-2766-4_12. ISBN 9781484227657. Search this book on
- "Natural Language Processing (NLP) with PyTorch — NLP with PyTorch documentation". dl4nlp.info. Retrieved 2017-12-18.
- Patel, Mo (2017-12-07). "When two trends fuse: PyTorch and recommender systems". O'Reilly Media. Retrieved 2017-12-18.
- 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.
- Arakelyan, Sophia (2017-11-29). "Tech giants are using open source frameworks to dominate the AI community". VentureBeat. Retrieved 2017-12-18.
- "Uber AI Labs Open Sources Pyro, a Deep Probabilistic Programming Language". Uber Engineering Blog. 2017-11-03. Retrieved 2017-12-18.
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