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METHOD AND APPARATUS FOR OPTIMIZING QUANTIZATION MODEL, ELECTRONIC DEVICE, AND COMPUTER STORAGE MEDIUM

机译:用于优化量化模型,电子设备和计算机存储介质的方法和装置

摘要

An optimization method comprises determining jump ratios of embedding layer parameters of a trained quantization model in a predetermined time range. The quantization model comprises a neural network model obtained after quantization processing on the embedding layer parameters. The method also comprises determining a jump curve in the predetermined time range according to the jump ratios, and fitting the jump curve to obtain a corresponding time scaling parameter. The method also comprises optimizing an initial algorithm of the quantization model based on the time scaling parameter to obtain an optimized target optimization algorithm, and training the quantization model based on the target optimization algorithm.
机译:优化方法包括在预定时间范围内确定培训量化模型的嵌入层参数的跳跃比率。 量化模型包括在嵌入层参数上的量化处理之后获得的神经网络模型。 该方法还包括根据跳转比率确定预定时间范围内的跳跃曲线,并拟合跳转曲线以获得相应的时间缩放参数。 该方法还包括基于时间缩放参数优化量化模型的初始算法,以获得优化的目标优化算法,并基于目标优化算法训练量化模型。

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