Method, device, equipment and system for obtaining model and readable storage medium

Abstract

The embodiment of the invention discloses a method, device, equipment and system for obtaining a model and a readable storage medium, central equipment receives federated learning data sent by edge equipment participating in the Nth round of federated learning, and the federated learning data sent by any edge equipment comprises model structure indication information and model data, the model structure indication information is used for indicating a sub-model structure adopted by any edge device in the Nth round of federated learning, and the model data comprises parameter data of a sub-model obtained by performing model training based on the sub-model structure; the sub-model structure is determined from the global model structure based on at least one of the equipment state and the model performance requirement of any edge equipment; and the central equipment obtains a global model of the Nth round of federated learning according to the federated learning data sent by the edge equipment participating in the Nth round of federated learning. The mode for obtaining the model is relatively high in flexibility and relatively high in efficiency.

Description

technical field [0001] The embodiments of the present application relate to the technical field of artificial intelligence, and in particular to a method, device, device, system, and readable storage medium for acquiring a model. Background technique [0002] With the continuous development of artificial intelligence technology, there are more and more types of machine learning models. Federated learning is an emerging artificial intelligence technology in recent years. Federated learning means that in the process of machine learning, each participant can conduct joint modeling with the help of other parties' data. All parties do not need to share data resources, that is, when the data does not come out of the local area, data joint training is carried out to establish a shared machine learning model. The federated learning architecture includes two layers of devices: the central server node (hereinafter referred to as the central device) and the edge client node (hereinaft...

AI Technical Summary

Problems solved by technology

[0005] This application proposes a method, device, equipment, system and readable storage medium for acquiring models, which are used to solve the problem of poor flexibility and low efficiency of acquiring models

Images