PyTorch
 | 此條目需要精通或熟悉相关主题的编者参与及协助编辑。 (2018年10月3日) |
| 原作者 | Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan |
|---|---|
| 首次发布 | 2016年10月 |
| 当前版本 | 0.4.1（2018年7月26日） |
| 预览版本 | 1.0 rc1（2018年10月2日） |
| 源代码库 | github |
| 编程语言 | Python, C++, CUDA |
| 操作系统 | Linux, macOS, Windows |
| 类型 | 机器学习和深度学习库 |
| 许可协议 | |
| 网站 | pytorch |
PyTorch是一个开源的Python机器学习库，基于Torch，[1][2][3] 应用于人工智能领域，如自然语言处理。 [4] 它最初由Facebook的人工智能研究团队开发，[5][6][7] 并且被用于Uber的概率编程软件"Pyro"。[8]
PyTorch主要有两大特征：[9]
参考文献
- ^ Yegulalp, Serdar. Facebook brings GPU-powered machine learning to Python. InfoWorld. 19 January 2017 [11 December 2017].
- ^ Lorica, Ben. Why AI and machine learning researchers are beginning to embrace PyTorch. O'Reilly Media. 3 August 2017 [11 December 2017].
- ^ Ketkar, Nikhil. Deep Learning with Python. Apress, Berkeley, CA. 2017: 195–208. ISBN 9781484227657. doi:10.1007/978-1-4842-2766-4_12 （英语）.
- ^ Natural Language Processing (NLP) with PyTorch — NLP with PyTorch documentation. dl4nlp.info. [2017-12-18] （英语）.
- ^ Patel, Mo. When two trends fuse: PyTorch and recommender systems. O'Reilly Media. 2017-12-07 [2017-12-18] （英语）.
- ^ Mannes, John. Facebook and Microsoft collaborate to simplify conversions from PyTorch to Caffe2. TechCrunch. [2017-12-18] （英语）.
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. Tech giants are using open source frameworks to dominate the AI community. VentureBeat. 2017-11-29 [2017-12-18] （美国英语）.
- ^ Uber AI Labs Open Sources Pyro, a Deep Probabilistic Programming Language. Uber Engineering Blog. 2017-11-03 [2017-12-18] （美国英语）.
- ^ PyTorch – About. pytorch.org. [2018-06-11].
- ^ R.E. Wengert. A simple automatic derivative evaluation program. Comm. ACM. 1964, 7: 463–464. doi:10.1145/355586.364791.
- ^ Bartholomew-Biggs, Michael; Brown, Steven; Christianson, Bruce; Dixon, Laurence. Automatic differentiation of algorithms (PDF). Journal of Computational and Applied Mathematics. 2000, 124 (1-2): 171–190. Bibcode:2000JCoAM.124..171B. doi:10.1016/S0377-0427(00)00422-2.