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.

def load(prefix, epoch, ctx=None, **kwargs):
        """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.
        """
        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)