Dynamic quantization for deep neural network inference system and method
US10878273B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 6, 2018 |
| Grant date | Dec 29, 2020 |
| Priority date | — |
| Expiry date | Dec 31, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/82
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for dynamically quantizing feature maps of a received image. The method includes convolving an image based on a predicted maximum value, a predicted minimum value, trained kernel weights and the image data. The input data is quantized based on the predicted minimum value and predicted maximum value. The output of the convolution is computed into an accumulator and re-quantized. The re-quantized value is output to an external memory. The predicted min value and the predicted max value are computed based on the previous max values and min values with a weighted average or a pre-determined formula. Initial min value and max value are computed based on known quantization methods and utilized for initializing the predicted min value and predicted max value in the quantization process.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.