Patent ID: 11941532
Assignee: ZHEJIANG LAB
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 1:
2. The method for adapting a deep learning framework to a hardware device based on a unified backend engine according to claim 1, wherein the step S1 comprises the following substeps:
S11: the deep learning framework registering the hardware device, adding a device field corresponding to the hardware device to a source code of the deep learning framework, creating an enumeration type of a device type for a hardware targeted by the unified backend engine, and adding the device field corresponding to the hardware in the device type;
S12: the deep learning framework registering the unified backend engine and adding a unified backend engine field to the deep learning framework;
S13: adding a compiler of the unified backend engine to the deep learning framework;
S14: the deep learning framework registering the compiler of the unified backend engine, and registering the newly added compiler in the unified backend engine;
S15: adding a computational graph executable object of the unified backend engine to the deep learning framework, adding a corresponding computational graph executable object for the unified backend engine, and implementing a running interface.