def METHOD_NAME(self, model, **kwargs):
    for name, module in model.named_modules():
        if isinstance(module, quant_nn.TensorQuantizer):
            if module._calibrator is not None:
                if isinstance(module._calibrator, calib.MaxCalibrator):
                    module.load_calib_amax()
                else:
                    module.load_calib_amax(**kwargs)
            if hasattr(module, "clip"):
                module.init_learn_amax()
            if self.verbose:
                print(f"{name:40}: {module}")