def METHOD_NAME(self, ids, skip_special_tokens=False):
    """Converts a sequence of ids in Tabular tokens using the vocab."""
    tokens = []
    sizes = self.code_column.sizes
    ids_size = sum(sizes)
    cindex = 0
    eor_pos = find_index_of(ids, self.eor)
    eod_pos = find_index_of(ids, self.eod)
    if eor_pos >= 0 and eod_pos >= 0:
        idd = min(eor_pos, eod_pos)
        cindex = (ids_size - idd) % ids_size
    elif eor_pos >= 0 and eod_pos < 0:
        idd = eor_pos
        cindex = (ids_size - idd) % ids_size
    elif eod_pos >= 0 and eor_pos < 0:
        idd = eod_pos
        cindex = (ids_size - idd) % ids_size
    cum_sizes = numpy.cumsum(sizes)
    old_column_index = -1
    token_ids = []
    for i in ids:
        if i in self.special_tokens_decoder:
            if not skip_special_tokens:
                tokens.append(self.special_tokens_decoder[i])
        else:
            index = cindex % ids_size
            column_index = numpy.where(index < cum_sizes)[0][0]
            column = self.code_column.columns[column_index]
            if old_column_index != column_index:
                token_ids = [i]
                old_column_index = column_index
            else:
                token_ids.append(i)
            if len(token_ids) == sizes[column_index]:
                tokens.append(self.code_column.decode(column, token_ids))
            cindex += 1
    return tokens