Method of neural network model computation-oriented intermediate representation by constructing physical computation graph, inferring information of input and output tensor edges of each node therein, performing memory optimization on tensor edges, and optimizing physical computation graph
US11823053B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 6, 2022 |
| Grant date | Nov 21, 2023 |
| Priority date | — |
| Expiry date | Apr 6, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The disclosure discloses a method of neural network model computation-oriented intermediate representation and apparatus thereof. The method includes the following steps: S1, parsing an input model file so as to acquire topological structure information of a neural network; S2, constructing a logical computation graph; S21, inferring physical layout information of each operator in the logical computation graph; S22, inferring meta attributes of each operator in the logical computation graph; S23, inferring description information of input and output logical tensors of each operator in the logical computation graph; S3, constructing a physical computation graph; S31, generating a physical computation graph, etc.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.