Network quantization method and device, electronic equipment and storage medium

A quantization method and network technology, applied in the computer field, can solve problems such as low quantization efficiency, poor universality, and high overhead, and achieve the effect of improving quantization efficiency and reducing overhead

Pending Publication Date: 2021-06-01
SHANGHAI SENSETIME INTELLIGENT TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the quantization method of neural network in the related technology has high overhead, low quantization efficiency and poor universality.

Method used

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  • Network quantization method and device, electronic equipment and storage medium
  • Network quantization method and device, electronic equipment and storage medium
  • Network quantization method and device, electronic equipment and storage medium

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Embodiment Construction

[0028] Various exemplary embodiments, features, and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numbers in the figures indicate functionally identical or similar elements. While various aspects of the embodiments are shown in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

[0029] The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as superior or better than other embodiments.

[0030] The term "and / or" in this article is just an association relationship describing associated objects, which means that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist simultaneously, and there exists alone B these three situations. In addition, the term "at least one" herein mean...

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Abstract

The invention relates to a network quantification method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a trained first neural network; a pseudo quantization node is inserted into the first neural network to obtain a second neural network, the pseudo quantization node comprises a quantization parameter to be trained, and the quantization parameter is used for quantizing a network parameter of the first neural network; according to the first neural network and a preset training set, training a second neural network to obtain a trained second neural network; According to the quantization parameter in the trained second neural network, the network parameter of the first neural network is quantized to obtain a third neural network, and the data precision of the network parameter of the third neural network is smaller than the data precision of the network parameter of the first neural network. According to the embodiment of the invention, the quantification efficiency, convenience and universality of the neural network can be improved, and the overhead of network quantification is reduced.

Description

technical field [0001] The present disclosure relates to the field of computer technology, and in particular to a network quantification method and device, electronic equipment and a storage medium. Background technique [0002] At present, in order to enable the neural network to be deployed on mobile terminals, it is usually necessary to quantize the trained neural network. Quantization can be used to approximate high-precision data with low-precision data. However, the quantization method of the neural network in the related art has high overhead, low quantization efficiency, and poor universality. Contents of the invention [0003] The disclosure proposes a network quantization method and device, electronic equipment, and a storage medium. [0004] According to an aspect of the present disclosure, a network quantization method is provided, including: obtaining a trained first neural network; inserting a pseudo-quantization node into the first neural network to obtain...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08G06N3/04
CPCG06N3/04G06N3/082
Inventor 吉小洪姚超张行程
Owner SHANGHAI SENSETIME INTELLIGENT TECH CO LTD
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