Neural network model compression method, corpus translation method and device
US11556723B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 7, 2020 |
| Grant date | Jan 17, 2023 |
| Priority date | — |
| Expiry date | May 18, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/096
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for compressing a neural network model, includes: obtaining a set of training samples including a plurality of pairs of training samples, each pair of the training samples including source data and target data corresponding to the source data; training an original teacher model by using the source data as an input and using the target data as verification data; training intermediate teacher models based on the set of training samples and the original teacher model, one or more intermediate teacher models forming a set of teacher models; training multiple candidate student models based on the set of training samples, the original teacher model, and the set of teacher models, the multiple candidate student models forming a set of student models; and selecting a candidate student model of the multiple candidate student models as a target student model according to training results of the multiple candidate student models.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.