PyTorch

PyTorch
TipePustaka perangkat lunak, Pustaka Python, perangkat lunak bebas dan sumber terbuka dan machine learning framework (en) Terjemahkan Edit nilai pada Wikidata
BerdasarkanTorch (en) Terjemahkan Edit nilai pada Wikidata
Versi pertamaSeptember 2016; 8 tahun lalu (2016-09)[1]
Versi stabil
2.5.0 (17 Oktober 2024) Edit nilai pada Wikidata
GenrePustaka untuk pemelajaran mesin dan pemelajaran mendalam
LisensiBSD
Bahasa
Daftar bahasa

Inggris

Karakteristik teknis
Sistem operasi
Bahasa pemrogramanC++, Python, C (mul) Terjemahkan dan cuda Edit nilai pada Wikidata
Informasi tambahan
Situs webpytorch.org
Stack ExchangeEtiqueta Edit nilai pada Wikidata
Pelacakan kesalahanLaman pelacakan Edit nilai pada Wikidata
Subredditpytorch Edit nilai pada Wikidata
Panduan penggunaLaman panduan Edit nilai pada Wikidata
X: PyTorch Youtube: UCWXI5YeOsh03QvJ59PMaXFw GitHub: pytorch Modifica els identificadors a Wikidata
Sunting di Wikidata Sunting di Wikidata • Sunting kotak info • L • B
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PyTorch adalah pustaka pemelajaran mesin sumber terbuka yang dibuat berdasarkan pustaka Torch.[3][4][5] PyTorch digunakan untuk aplikasi seperti penglihatan komputer dan pemrosesan bahasa alami.[6] Pustaka ini terutama dikembangkan oleh lab Penelitian AI Facebook, Facebook's AI Research lab (FAIR).[7][8][9] PyTorch adalah perangkat lunak bebas dan sumber terbuka yang dirilis di bawah lisensi BSD Modifikasi. Meskipun antarmuka Python lebih stabil dan merupakan fokus utama pengembangan, PyTorch juga memiliki antarmuka C++.[10]

Sejumlah perangkat lunak pemelajaran mendalam dibangun di atas PyTorch, termasuk Tesla Autopilot,[11] Uber's Pyro,[12] HuggingFace's Transformers,[13] PyTorch Lightning,[14][15] dan Catalyst.[16][17]

Referensi

  1. ^ Chintala, Soumith (1 September 2016). "PyTorch Alpha-1 release". 
  2. ^ "PyTorch 2.5.0 Release, SDPA CuDNN backend, Flex Attention". 17 Oktober 2024. Diakses tanggal 17 Oktober 2024. 
  3. ^ Yegulalp, Serdar (19 January 2017). "Facebook brings GPU-powered machine learning to Python". InfoWorld. Diakses tanggal 11 December 2017. 
  4. ^ Lorica, Ben (3 August 2017). "Why AI and machine learning researchers are beginning to embrace PyTorch". O'Reilly Media. Diakses tanggal 11 December 2017. 
  5. ^ Ketkar, Nikhil (2017). "Introduction to PyTorch". Deep Learning with Python (dalam bahasa Inggris). Apress, Berkeley, CA. hlm. 195–208. doi:10.1007/978-1-4842-2766-4_12. ISBN 9781484227657. 
  6. ^ "Natural Language Processing (NLP) with PyTorch – NLP with PyTorch documentation". dl4nlp.info (dalam bahasa Inggris). Diakses tanggal 2017-12-18. 
  7. ^ Patel, Mo (2017-12-07). "When two trends fuse: PyTorch and recommender systems". O'Reilly Media (dalam bahasa Inggris). Diakses tanggal 2017-12-18. 
  8. ^ Mannes, John. "Facebook and Microsoft collaborate to simplify conversions from PyTorch to Caffe2". TechCrunch (dalam bahasa Inggris). Diakses tanggal 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 (dalam bahasa Inggris). Diakses tanggal 2017-12-18. 
  10. ^ "The C++ Frontend". PyTorch Master Documentation. Diakses tanggal 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 (dalam bahasa Inggris). 2017-11-03. Diakses tanggal 2017-12-18. 
  13. ^ PYTORCH-TRANSFORMERS: PyTorch implementations of popular NLP Transformers, PyTorch Hub, 2019-12-01, diakses tanggal 2019-12-01 
  14. ^ PYTORCH-Lightning: The lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate, Lightning-Team, 2020-06-18, diakses tanggal 2020-06-18 
  15. ^ "Ecosystem Tools". pytorch.org (dalam bahasa Inggris). Diakses tanggal 2020-06-18. 
  16. ^ GitHub - catalyst-team/catalyst: Accelerated DL & RL, Catalyst-Team, 2019-12-05, diakses tanggal 2019-12-05 
  17. ^ "Ecosystem Tools". pytorch.org (dalam bahasa Inggris). Diakses tanggal 2020-04-04. 

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