公开(公告)号：US20240378077A1

公开(公告)日：2024-11-14

申请号：US18782617

申请日：2024-07-24

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

Inventor： Guoxia WANG ,  Jinle ZENG ,  Xiyuan XIAO ,  Jiabin YANG ,  Dianhai YU ,  Haifeng WANG

IPC: G06F9/48 ,  G06F40/40

Abstract: A method of executing a task for a large language model, a device, and a storage medium are provided, which relate to a field of artificial intelligence technology, and in particular to fields of deep learning, large language model, natural language processing and computer vision technologies. The method includes: determining, by using a determination unit, a target attention task from a plurality of attention tasks to be processed, based on a sparse representation corresponding to a feature to be processed, where the target attention task is a task corresponding to a non-fully masked region of the feature, the sparse representation represents a mask position of the feature, and the mask position represents mask endpoint positions in at least two non-intersecting intervals in a mask matrix corresponding to the feature; and executing the target attention task by using a computing unit, so as to obtain an attention feature.

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.