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Neural Network Training Method, Neural Network Training Apparatus and Electronic Device

机译:神经网络训练方法,神经网络训练装置及电子设备

摘要

Disclosed are a neural network training method, a neural network training device and an electronic device. The neural network training method includes: training a first neural network to be trained by using sample data; determining an indicator parameter of the first neural network in a current training process; determining an update manner corresponding to a preset condition if the indicator parameter meets the preset condition; and updating a parameter of a batch normalization layer in the first neural network based on the update manner. In this way, sparsing of a feature map output by a neural network is implemented, thereby reducing an amount of data to be transmitted and improving computation speed of a chip.
机译:本发明公开了一种神经网络训练方法,神经网络训练装置和电子设备。该神经网络训练方法包括:通过使用样本数据来训练要训练的第一神经网络;在当前训练过程中确定所述第一神经网络的指标参数;如果指示符参数满足预设条件,则确定与预设条件对应的更新方式;基于所述更新方式,在所述第一神经网络中更新批归一化层的参数。这样,实现了神经网络输出的特征图的稀疏化,从而减少了要传输的数据量,提高了芯片的计算速度。

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