Weighted-Entropy-based Quantization for Deep Neural Networks
本文提出了一種綜合考慮權重的重要性和頻率來進行量化的方式。它與其它量化方式的對比： 作者首先定義了被稱爲權重熵的變量： 這裏Pn代表了權重的頻率，In代表了它的重要性。作者設定了n個量化簇(cluster)，i(n,m)是計算第n個簇的第m個權重的重要性的函數，作者這裏簡單地選擇了平方函數。 上圖是權重量化的僞代碼：首先用平方函數計算每個權重的重要性，然後從小到大對其排序，並將它們均勻分爲n個間隔
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相關文章
- 1. Weighted-Entropy-based Quantization for Deep Neural Networks
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