A deep learning model compression method, device, storage medium and terminal equipment

Abstract

The invention discloses a deep learning model compression method and device, a storage medium and terminal equipment. the output of each layer of the deep learning model is calculated through a forward propagation algorithm, the output value of the deep learning model is finally obtained, and redundant parameters in the model are sparse by calculating the connection weight mean value of each nodeand deleting the nodes with the mean value of zero, so that the redundant parameters are removed. And the model precision is ensured through the loss function, and on the premise of ensuring that themodel precision is not obviously reduced, the model parameter quantity is greatly reduced, and the calculation amount in the training process is greatly reduced, so that the model can run on resource-limited edge computing equipment. According to the deep learning model compression method, the problem that a deep learning model is difficult to operate on resource-limited equipment due to the lackof a method for compressing the deep learning model at present is solved.

Description

technical field [0001] The invention relates to the field of edge computing in a cloud computing environment, in particular to a deep learning model compression method, device, storage medium and terminal equipment. Background technique [0002] Deep learning solves many challenging problems, and its results have been widely used in computer vision, speech recognition, natural language processing and other fields. Technologies such as image recognition, video processing, and speech recognition based on deep learning have great application prospects and demands on end devices of edge computing systems. However, training and executing deep learning models usually requires a lot of data storage space and super computing power. Existing edge computing devices have insufficient resources such as computing power, storage capacity, network bandwidth, and electricity to run deep learning models. The parameters of the deep learning model are huge and require a lot of computing powe...

AI Technical Summary

Problems solved by technology

[0003] The present invention provides a deep learning model compression method, device, storage medium and terminal equipment, aiming to solve the problem that the current lack of methods for compressing deep learning models makes it difficult for deep learning models to run on resource-limited devices

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