• Patent Title: PURE INTEGER QUANTIZATION METHOD FOR LIGHTWEIGHT NEURAL NETWORK (LNN)
  • Application No.: US17799933
    Application Date: 2021-09-22
  • Publication No.: US20230196095A1
    Publication Date: 2023-06-22
  • Inventor: Weixiong JIANGYajun HA
  • Applicant: SHANGHAITECH UNIVERSITY
  • Applicant Address: CN Shanghai
  • Assignee: SHANGHAITECH UNIVERSITY
  • Current Assignee: SHANGHAITECH UNIVERSITY
  • Current Assignee Address: CN Shanghai
  • Priority: CN 2110421738.5 2021.04.20
  • International Application: PCT/CN2021/119513 2021.09.22
  • Date entered country: 2022-08-16
  • Main IPC: G06N3/08
  • IPC: G06N3/08
PURE INTEGER QUANTIZATION METHOD FOR LIGHTWEIGHT NEURAL NETWORK (LNN)
Abstract:
A pure integer quantization method for a lightweight neural network (LNN) is provided. The method includes the following steps: acquiring a maximum value of each pixel in each of the channels of the feature map of a current layer; dividing a value of each pixel in each of the channels of the feature map by a t-th power of the maximum value, t∈[0,1]; multiplying a weight in each of the channels by the maximum value of each pixel in each of the channels of the corresponding feature map; and convolving the processed feature map with the processed weight to acquire the feature map of a next layer. The algorithm is verified on SkyNet and MobileNet respectively, and lossless INT8 quantization on SkyNet and maximum quantization accuracy so far on MobileNetv2 are achieved.
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