2022
Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training
ICML 2022spotlight
Data clipping is crucial in reducing noise in quantization operations and improving the achievable accuracy of quantization-aware training (QAT). Current practices rely on heuristics to set clipping threshold scalars and cannot be shown to be optimal. We propose Optimally Clipped Tensors And Vectors…