Transcription of TensorFlow: Large-Scale Machine Learning on …
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TensorFlow: Large-Scale Machine Learning on …
tensorflow : Large-Scale Machine Learning on Heterogeneous Distributed Systems(Preliminary White Paper, November 9, 2015)Mart n Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro,Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow,Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser,Manjunath Kudlur, Josh Levenberg, Dan Man e, Rajat Monga, Sherry Moore, Derek Murray,Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar,Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Vi egas, Oriol Vinyals,Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang ZhengGoogle Research AbstractTensorFlow [1] is an interface for expressing Machine learn-ing algorithms, and an implementation for executing such al-gorithms.
over different tensor element types (e.g., add of two ten-sors of type float versus add of two tensors of type int32). A kernel is a particular implementation of an operation that can be run on a particular type of device (e.g., CPU or GPU). A TensorFlow binary defines the sets of opera-tions and kernels available via a registration mechanism,
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