Quantization

Quantization is a promising technique aimed at reducing the computational cost of neural network training and improving model efficiency and resource utilization by using low-cost fixed-point numbers (such as int8/int16) to replace high-cost floating-point numbers (such as float32). This technique is suitable for large-scale deep learning applications.