Computing resources acquisition method and device, electronic equipment and storage medium

Abstract

The invention provides a computing resources acquisition method and device, electronic equipment and a storage medium, and the method comprises the steps: determining topological information for model training according to scene information and training sample data; obtaining operator resources information of each operator included in the topological information according to the topological information; and obtaining target resources information for model training according to the operator resources information of each operator. Topological information used for model training is determined based on scene information and training sample data input by a user, operator resources information of each operator included in the topological information and target resource information used for model training are calculated subsequently, and the user is assisted in completing configuration of computing resources corresponding to model training. The interference caused by human factors is reduced, and the deviation between the computing resources required during model training and the computing resources configured by the user is reduced.

Description

technical field [0001] The present application relates to the technical field of machine learning, and in particular to a computing resource acquisition method, device, electronic equipment and storage medium. Background technique [0002] The algorithm model based on machine learning has the advantages of short prediction time after sufficient training and high prediction accuracy, and is widely used in various fields. [0003] During the training process of the algorithm model, the computing resources required for different algorithm model training will change accordingly. The above computing resources for model training need to be manually configured by the user. Under the interference of human factors, the required computing resources for algorithm model training The deviation between the computing resources and the computing resources configured by the user is large. If the configured computing resources are insufficient, memory overflow may easily occur, or if the conf...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the embodiments of the present application is to provide a computing resource acquisition method, device, electronic device and storage medium, which are used to solve the problem of a large deviation between the computing resources required for algorithm model training and the computing resources configured by the user

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