Distributed model training method and device, storage medium and computer equipment

Abstract

The embodiment of the invention discloses a distributed model training method and device, a storage medium and computer equipment. The invention is related to the field of machine learning of artificial intelligence; the method comprises the steps of obtaining a model structure and sample data of a target model; sending a model message to each graphics processor, and triggering each graphics processor to train a target model; based on the preset sample number of the sample labels and the number of the graphics processors, performing multiple times of data sampling on the sample data to obtain multiple groups of training sample data; sending the training sample data to a corresponding graphics processor, triggering the graphics processor to train a target model based on the training sample data, and updating training parameters of the target model among the graphics processors to obtain updated training parameters of the trained target model; and when the updated training parameters meet a preset training termination condition, outputting the trained target model. The speed of model training can be effectively improved.

Description

technical field

[0001] The present application relates to the field of artificial intelligence, in particular to a distributed model training method, device, storage medium and computer equipment. Background technique

[0002] With the rapid development of artificial intelligence science, more and more problems can be solved by neural network models in daily life. Before applying neural network models to solve problems, training neural network models is a key step. In the prior art , model training usually requires a large amount of sample data. Before training, the sample data is transmitted to the training machine, and distributed data sampling is performed through the training machine, and the sampled training sample data is input into the neural network model for training, so that the neural network model The network parameters are updated.

[0003] During the research and practice of the prior art, the inventors of the present application found that the sample data com...

Examples

Embodiment Construction

[0057] The technical solutions in the embodiments of the application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the application. Obviously, the embodiments described in the application are only part of the embodiments of the application, not all implementations example. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts belong to the scope of protection of this application.

[0058] Artificial Intelligence (AI) is a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the nature of intelligence and pr...

technical field

[0001] The present application relates to the field of artificial intelligence, in particular to a distributed model training method, device, storage medium and computer equipment. Background technique

[0002] With the rapid development of artificial intelligence science, more and more problems can be solved by neural network models in daily life. Before applying neural network models to solve problems, training neural network models is a key step. In the prior art , model training usually requires a large amount of sample data. Before training, the sample data is transmitted to the training machine, and distributed data sampling is performed through the training machine, and the sampled training sample data is input into the neural network model for training, so that the neural network model The network parameters are updated.

[0003] During the research and practice of the prior art, the inventors of the present application found that the sample data com...

Examples

Embodiment Construction

[0057] The technical solutions in the embodiments of the application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the application. Obviously, the embodiments described in the application are only part of the embodiments of the application, not all implementations example. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts belong to the scope of protection of this application.

[0058] Artificial Intelligence (AI) is a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the nature of intelligence and pr...

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