code: def load(prefix, epoch, ctx=None, **kwargs):
          
          symbol, arg_params, aux_params = load_checkpoint(prefix, epoch)
          return FeedForward(symbol, ctx=ctx,
                             arg_params=arg_params, aux_params=aux_params,
                             begin_epoch=epoch,
                             **kwargs)
docs: Load model checkpoint from file.
  
          Parameters
          ----------
          prefix : str
              Prefix of model name.
          epoch : int
              epoch number of model we would like to load.
          ctx : Context or list of Context, optional
              The device context of training and prediction.
          kwargs : dict
              Other parameters for model, including `num_epoch`, optimizer and `numpy_batch_size`.
  
          Returns
          -------
          model : FeedForward
              The loaded model that can be used for prediction.
  
          Notes
          -----
          - ``prefix-symbol.json`` will be saved for symbol.
          - ``prefix-epoch.params`` will be saved for parameters.