Transcription of TensorFlow: A System for Large-Scale Machine Learning
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TensorFlow: A System for Large-Scale Machine Learning
This paper is included in the Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16).November 2 4, 2016 Savannah, GA, USAISB N 978 -1- 931971-33 -1 Open access to the Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation is sponsored by : A System for Large-Scale Machine LearningMart n Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek G. Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng, Google : A System for Large-Scale Machine learningMart n Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean,Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur,Josh Levenberg, Rajat Monga, Sherry Moore, Derek G.
user defines a neural network as a directed acyclic graph of layers that terminates with a loss function. A layer is a composition of mathematical operators: for example, a fully connected layer multiplies its input by a weight ma-trix, adds a bias vector, and applies a non-linear function (suchasasigmoid)totheresult. Alossfunctionisascalar
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