公开(公告)号：US20250005446A1

公开(公告)日：2025-01-02

申请号：US18547090

申请日：2022-11-02

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Weihang CHEN ,  Haifeng WANG ,  Yunfei ZHANG ,  Risheng YUAN ,  Tianyu CHEN ,  Hongyu LIU ,  Xiaoguang HU ,  Dianhai YU ,  Yanjun MA

IPC: G06N20/00

Abstract: An operator processing method of a deep learning framework an electronic device, and a storage medium are provided, which relate to a field of computer technology, especially in a field of artificial intelligence technology such as deep learning. The specific implementation scheme includes: acquiring an operator to be processed, where the operator to be processed includes a template parameter independent of the deep learning framework and an operator kernel function; parsing, in response to receiving an input information for the operator to be processed, the template parameter by using the input information to obtain a plurality of complete template parameters related to the deep learning framework; and processing the operator kernel function according to the plurality of complete template parameters, to obtain an available operator for the deep learning framework.

公开(公告)号：US20220374238A1

公开(公告)日：2022-11-24

申请号：US17572140

申请日：2022-01-10

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Weihang CHEN ,  Jiabin YANG ,  Hongyu LIU ,  Xiang LAN

IPC: G06F9/38 ,  G06F9/30 ,  G06F9/54

Abstract: The present disclosure provides an operator registration method and apparatus for a deep learning framework, a device and a storage medium, relates to the field of computer technologies, and specifically to the field of artificial intelligence such as deep learning. The operator registration method for a deep learning framework includes: receiving registration information provided by a user for registering operators with the deep learning framework, the registration information including: a custom calculation function, the custom calculation function being written in a manner irrelevant to the deep learning framework; building operator meta-information in the deep learning framework based on the registration information; and constructing a to-be-registered operator within the deep learning framework based on the operator meta-information, and registering the to-be-registered operator in a global operator table within the deep learning framework. The present disclosure can simplify an operator registration process.