Accuracy degradation aware bit rate allocation for layer-wise uniform quantization of weights in neural network
Jelena Nikolić,
Stefan Tomić,
Zoran Perić
et al.
Abstract:Motivated by the fact that optimizing quantization error fails to minimize the accuracy degradation caused by the quantization of Neural Network (NN) weights, in this paper, we highlight the need for a comprehensive analysis of post-training quantization, covering average bit rate, accuracy degradation and SQNR. One such analysis, for the layer-wise uniform quantization and its application is NN weight compression is presented in this paper. We introduce an additional aspect of Uniform Quantizer (UQ) choice, a… Show more
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