About the int8 training question

[UmeTFE]

Yes, I tried the methods of quantization, but I don’t think they are the methods that I want. I want “training”, not “inference” or using float to simulate the “int”.

A similar question is here:

Problem about training with int8

Hello everyone, Recently, we are focusing on training with int8, not inference on int8. Considering the numerical limitation of int8, at first we keep all parameters in fp32 and only quantize convolution layer (conduct int8 operation) as it is the most compute-intensive part of a model. During the past months, we have achieved some progress (such accuracy comparable to fp32 training and faster than fp32 training), and our paper is accepted by CVPR2020 (https://arxiv.org/pdf/1912.12607.pdf). No…