def METHOD_NAME(self, column_data: Iterable[str]) -> torch.Tensor:
    """
    Encodes pre-processed data into OHE. Unknown/unrecognized classes vector of all 0s.
    :param column_data: Pre-processed data to encode
    :returns: Encoded data of form :math:`N_{rows} x N_{categories}`
    """ # noqa
    if not self.is_prepared:
        raise Exception(
            'You need to call "prepare" before calling "encode" or "decode".'
        )
    ret = torch.zeros(size=(len(column_data), self.output_size))
    for idx, word in enumerate(column_data):
        index = self.map.get(word, None)
        if index is not None:
            ret[idx, index] = 1
        if self.use_unknown and index is None:
            ret[idx, 0] = 1
    return torch.Tensor(ret)