Method and apparatus for generating fixed-point quantized neural network
US11588496B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 1, 2018 |
| Grant date | Feb 21, 2023 |
| Priority date | — |
| Expiry date | Nov 16, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method of generating a fixed-point quantized neural network includes analyzing a statistical distribution for each channel of floating-point parameter values of feature maps and a kernel for each channel from data of a pre-trained floating-point neural network, determining a fixed-point expression of each of the parameters for each channel statistically covering a distribution range of the floating-point parameter values based on the statistical distribution for each channel, determining fractional lengths of a bias and a weight for each channel among the parameters of the fixed-point expression for each channel based on a result of performing a convolution operation, and generating a fixed-point quantized neural network in which the bias and the weight for each channel have the determined fractional lengths.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.