Does Automatic Mixed Precision (AMP) reduce the parameters of a model by half?

edit

No, Automatic Mixed Precision (AMP) does not reduce the parameters of a model by half. It is a technique that combines the benefits of both single-precision and half-precision floating-point numbers to improve the performance of training deep learning models. By using both data types, the model can perform calculations with less memory usage and faster processing speed, while still maintaining accuracy. The reduction in memory usage and processing speed can help with larger models, but does not necessarily reduce the number of parameters.