首页> 外国专利> Method for optimizing on-device neural network model by using sub-kernel searching module and device using the same

Method for optimizing on-device neural network model by using sub-kernel searching module and device using the same

机译:通过使用相同的子内核搜索模块和设备优化设备神经网络模型的方法

摘要

A method for optimizing an on-device neural network model by using a Sub-kernel Searching Module is provided. The method includes steps of a learning device (a) if a Big Neural Network Model having a capacity capable of performing a targeted task by using a maximal computing power of an edge device has been trained to generate a first inference result on an input data, allowing the Sub-kernel Searching Module to identify constraint and a state vector corresponding to the training data, to generate architecture information on a specific sub-kernel suitable for performing the targeted task on the training data, (b) optimizing the Big Neural Network Model according to the architecture information to generate a specific Small Neural Network Model for generating a second inference result on the training data, and (c) training the Sub-kernel Searching Module by using the first and the second inference result.
机译:提供了一种通过使用子内核搜索模块来优化On-Device神经网络模型的方法。该方法包括学习设备(a)的步骤,如果已经训练了能够通过使用边缘设备的最大计算能力执行目标任务的大神经网络模型已经训练以在输入数据上生成第一推断结果,允许子内核搜索模块识别与训练数据对应的约束和状态向量,以生成适合于在训练数据上执行目标任务的特定子内核的架构信息,(b)优化大神经网络模型根据架构信息,用于生成特定的小神经网络模型,用于在训练数据上生成第二推断结果,并且(c)通过使用第一和第二推断结果训练子内核搜索模块。

著录项

  • 公开/公告号US10970633B1

    专利类型

  • 公开/公告日2021-04-06

    原文格式PDF

  • 申请/专利权人 STRADVISION INC.;

    申请/专利号US202017135301

  • 申请日2020-12-28

  • 分类号G06N3/02;G06N3/08;G06K9/62;G06N20/10;

  • 国家 US

  • 入库时间 2022-08-24 18:04:45

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