QuantizeWrapperV2 quantizes the weights and activations of the keras layer it wraps. This involves converting high-precision weights and activations to lower precision formats. When you apply QAT, the layers are modified to support quantization during training and this results in slightly increasing the number of parameters to manage the quantization process. To learn more about it, please refer this document.