Patent ID: 11861498
Assignee: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 16:
17. The non-transitory computer readable storage medium according to claim 14, wherein the compressing the to-be-compressed neural network model using the target value, the first bit width and the second bit width to obtain the compression result of the to-be-compressed neural network model comprises:
acquiring training data;
thinning parameters in the to-be-compressed neural network model according to the target value, the first bit width and the second bit width to obtain a thinned neural network model;
training the thinned neural network model using the training data to obtain a loss function value and model precision of the thinned neural network model;
in response to determining that the model precision does not meet a first preset condition and after adjusting the parameters of the to-be-compressed neural network model using the loss function value, proceeding to the obtaining the thinned neural network model until the model precision meets the first preset condition, and taking the thinned neural network model as a second neural network model; and
obtaining the compression result of the to-be-compressed neural network model according to the second neural network model.