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Neural network model deployment method, device and equipment

A neural network model and deployment device technology, applied in biological neural network models, neural learning methods, neural architectures, etc., can solve problems such as large dependence on original training data

Pending Publication Date: 2021-02-02
SZ DJI TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] The embodiment of the present application provides a neural network model deployment method, device and equipment to solve the problem that the model deployment method in the prior art has a large dependence on the original training data

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  • Neural network model deployment method, device and equipment
  • Neural network model deployment method, device and equipment
  • Neural network model deployment method, device and equipment

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Embodiment Construction

[0031] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of this application.

[0032] The neural network model deployment method provided in the embodiment of the present application can be applied to any scenario where a convolutional neural network model needs to be deployed. Specifically, the neural network model deployment method may be executed by a neural network model deployment device. The schematic diagram of the application s...

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Abstract

The invention discloses a neural network model deployment method, device and equipment. The method comprises the following steps: obtaining a trained convolutional neural network model (201); carryingout matrix decomposition on a weight parameter of a convolutional layer in the convolutional neural network model to obtain a matrix decomposition result of the convolutional layer (202); according to the known matrix decomposition result, adjusting the structure of the convolutional neural network model to compress the convolutional neural network model to obtain a compressed model of the convolutional neural network model (203); and deploying (204) the compressed model. According to the method, dependence on original training data is reduced.

Description

technical field [0001] The present application relates to the technical field of neural networks, and in particular to a neural network model deployment method, device and equipment. Background technique [0002] With the continuous development of neural network technology, the application of convolutional neural network models is becoming more and more extensive. [0003] Generally, before deploying the trained convolutional neural network model, the trained convolutional neural network model can be compressed in the following two ways to reduce the size of the trained convolutional neural network model and reduce the calculation quantity. One way is to perform model compression by reducing the number of channels of the trained convolutional neural network model. Another way is to perform model compression by converting the weight parameters of the trained neural network model from floating-point weight parameters to fixed-point weight parameters. [0004] However, the a...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G06F17/16
CPCG06N3/08G06F17/16G06N3/045
Inventor 聂谷洪施泽浩孙扬
Owner SZ DJI TECH CO LTD