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METHOD AND APPARATUS FOR GENERATING FIXED-POINT QUANTIZED NEURAL NETWORK

机译:生成定点量化神经网络的方法和装置

摘要

A method of generating a fixed-point quantized neural network includes analyzing a statistical distribution for each channel of floating-point parameter values of feature maps and a kernel for each channel from data of a pre-trained floating-point neural network, determining a fixed-point expression of each of the parameters for each channel statistically covering a distribution range of the floating-point parameter values based on the statistical distribution for each channel, determining fractional lengths of a bias and a weight for each channel among the parameters of the fixed-point expression for each channel based on a result of performing a convolution operation, and generating a fixed-point quantized neural network in which the bias and the weight for each channel have the determined fractional lengths.
机译:一种生成定点量化神经网络的方法,包括从预训练的浮点神经网络的数据分析特征图的浮点参数值的每个通道的统计分布以及每个通道的内核,确定固定点。基于每个通道的统计分布,在统计上覆盖浮点参数值的分布范围的每个通道的每个参数的点表达式,确定固定参数中每个通道的偏差和权重的小数长度基于执行卷积运算并生成定点量化神经网络的结果,对每个通道进行点表达式,其中每个通道的偏差和权重具有确定的分数长度。

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