Channel pruning method based on variational structure optimization network

• Main Authors: ZENG XIN, DAI CHENG, SONG GAOYU, LIU XINGANG, HAN SHUO, SUN RUICHENG
• Format: Patent
• Language: Chinese; English
• Published: 12.01.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; PHYSICS

The invention belongs to the technical field of convolutional neural network compression and acceleration, and particularly provides a channel pruning method based on a variational structure optimization network, and the method comprises the steps: compressing a deep convolutional neural network model through a channel pruning technology based on the variational structure optimization network. According to the method, the application limitation of an existing large neural network on resource limitation is considered, a channel pruning technology is adopted to compress an original network, network parameters are compressed as much as possible on the premise that the performance of the original network is not affected, memory occupation of an active layer in the forward propagation process of the network is reduced, and the floating point operation frequency during operation is reduced; therefore, the target of a lightweight network is achieved. By automatically optimizing the network structure, the parameter r