Args:
            iterator (iterator): Batch of text to encode.
            *args: Arguments passed onto ``Encoder.__init__``.
            dim (int, optional): Dimension along which to concatenate tensors.
            **kwargs: Keyword arguments passed onto ``Encoder.__init__``.

        Returns
            torch.Tensor, list of int: Encoded and padded batch of sequences; Original lengths of
                sequences.

def batch_encode(self, iterator, *args, dim=0, **kwargs):
        """
        Args:
            iterator (iterator): Batch of text to encode.
            *args: Arguments passed onto ``Encoder.__init__``.
            dim (int, optional): Dimension along which to concatenate tensors.
            **kwargs: Keyword arguments passed onto ``Encoder.__init__``.

        Returns
            torch.Tensor, list of int: Encoded and padded batch of sequences; Original lengths of
                sequences.
        """
        return stack_and_pad_tensors(
            super().batch_encode(iterator), padding_index=self.padding_index, dim=dim)