{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/mycaffe-a-complete-c-re-write-of-caffe-with","title":"MyCaffe: A Complete C# Re-Write of Caffe with Reinforcement Learning","arxiv_id":"1810.02272","date":"2018-10-04","proceeding":null,"authors":["David W. Brown"],"abstract":"Over the past few years Caffe, from Berkeley AI Research, has gained a strong\nfollowing in the deep learning community with over 15K forks on the\ngithub.com/BLVC/Caffe site. With its well organized, very modular C++ design it\nis easy to work with and very fast. However, in the world of Windows\ndevelopment, C# has helped accelerate development with many of the enhancements\nthat it offers over C++, such as garbage collection, a very rich .NET\nprogramming framework and easy database access via Entity Frameworks. So how\ncan a C# developer use the advances of C# to take full advantage of the\nbenefits offered by the Berkeley Caffe deep learning system? The answer is the\nfully open source, 'MyCaffe' for Windows .NET programmers. MyCaffe is an open\nsource, complete C# language re-write of Berkeley's Caffe. This article\ndescribes the general architecture of MyCaffe including the newly added\nMyCaffeTrainerRL for Reinforcement Learning. In addition, this article\ndiscusses how MyCaffe closely follows the C++ Caffe, while talking efficiently\nto the low level NVIDIA CUDA hardware to offer a high performance, highly\nprogrammable deep learning system for Windows .NET programmers.","url_abs":"http://arxiv.org/abs/1810.02272v1","url_pdf":"http://arxiv.org/pdf/1810.02272v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"mycaffe-a-complete-c-re-write-of-caffe-with","repo_url":"https://github.com/MyCaffe/MyCaffe","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}