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Technical Report: NEMO DNN Quantization for Deployment Model

2020-04-13 13:23:27
Francesco Conti

Abstract

This technical report aims at defining a formal framework for Deep Neural Network (DNN) layer-wise quantization, focusing in particular on the problems related to the final deployment. It also acts as a documentation for the NEMO (NEural Minimization for pytOrch) framework. It describes the four DNN representations used in NEMO (FullPrecision, FakeQuantized, QuantizedDeployable and IntegerDeployable), focusing in particular on a formal definition of the latter two. An important feature of this model, and in particular the IntegerDeployable representation, is that it enables DNN inference using purely integers - without resorting to real-valued numbers in any part of the computation and without relying on an explicit fixed-point numerical representation.

Abstract (translated)

URL

https://arxiv.org/abs/2004.05930

PDF

https://arxiv.org/pdf/2004.05930.pdf


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