Method for accelerating neural network structure selection

Abstract

The invention discloses a method for accelerating neural network structure selection, and relates to the technical field of neural networks, the method comprises the following steps of: reading a global.txt file by using a main thread M; judging whether the number of the neural network structures recorded in the file is smaller than t or not; if so, judging whether a neural network structure whichis not recorded in the global.txt file exists line by line or not; if so, querying an idle display card; enabling the main thread M to start a sub-thread; putting an unrecorded neural network structure on an idle display card for training through the sub-thread; after the main thread M is dormant for a certain time, continuously judging whether a neural network structure which is not recorded inthe global.txt file exists or not; and writing the unrecorded neural network structure into the global.txt file after the sub-thread training is completed, and selecting the optimal neural network structure corresponding to the current scene from the updated global.txt file. According to the method, the accurate neural network structure with the optimal performance is obtained, and the cost is relatively low.

Description

technical field [0001] The invention relates to the technical field of neural networks, and more specifically relates to a method for accelerating the selection of neural network structures. Background technique [0002] In today's society, artificial intelligence technology based on deep learning has had an important impact on people's daily life, and it has also brought great convenience. For example, through automatic face comparison on self-service machines, commonly used banking services are no longer needed. Line up at the counter. The main method of today's deep learning technology is the neural network, and in order to achieve the optimal effect of the deep learning technology, it is necessary to design a specific neural network structure for the current task, and then train the network structure based on the data of the current task. Since the structure of the neural network depends on the specific task, it is necessary to design the best corresponding neural netwo...

AI Technical Summary

Problems solved by technology

[0021] The purpose of the present invention is: in order to solve the problem that the existing neural network structure selection method speeds up the selection by reducing the number of training times or training data, which may easily cause the selected neural network structure to be wrong or have poor performance. The present invention provides a A method to accelerate the selection of neural network structure, using a complete training cycle, on all test data sets, by designing corresponding algorithms, making full use of all GPUs equipped on a single machine, to achieve accelerated selection of neural network structure