def METHOD_NAME(self):
    """Move to the next stage of quantization."""
    if self.quantization_step >= len(self.layers_to_quantize):
        # Maybe we just finished the last training step or we loaded
        # a checkpoint for an iterative PQ model which previously
        # finished training. Either way, don't quantize again.
        return
    logger.info(
        "quantizing model (step={}; layers_to_quantize[step]={})".format(
            self.quantization_step, self.layers_to_quantize[self.quantization_step]
        )
    )
    quantized_layers = pq.quantize_model_(
        self.trainer.get_model(),
        self.size_tracker,
        self.layers_to_quantize,
        self.block_sizes_config,
        self.n_centroids_config,
        METHOD_NAME=self.quantization_step,
    )
    logger.info("quantized layers: {}".format(quantized_layers))
    logger.info(self.size_tracker)
    self.quantization_step += 1
    # reintialize the Trainer since model parameters have changed
    self.trainer.reinitialize()