Invention Publication
- Patent Title: PURE INTEGER QUANTIZATION METHOD FOR LIGHTWEIGHT NEURAL NETWORK (LNN)
-
Application No.: US17799933Application Date: 2021-09-22
-
Publication No.: US20230196095A1Publication Date: 2023-06-22
- Inventor: Weixiong JIANG , Yajun 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

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.
Public/Granted literature
- US11934954B2 Pure integer quantization method for lightweight neural network (LNN) Public/Granted day:2024-03-19
Information query