def METHOD_NAME(
    path: Union[Path, str], loader_type: str = "csv_int"
) -> Dict[str, List[Union[float, int]]]:
    """Read a text file indicating sequences of number
    Examples:
        key1 1 2 3
        key2 34 5 6
        >>> d = load_num_sequence_text('text')
        >>> np.testing.assert_array_equal(d["key1"], np.array([1, 2, 3]))
    """
    assert check_argument_types()
    if loader_type == "text_int":
        delimiter = " "
        dtype = int
    elif loader_type == "text_float":
        delimiter = " "
        dtype = float
    elif loader_type == "csv_int":
        delimiter = ","
        dtype = int
    elif loader_type == "csv_float":
        delimiter = ","
        dtype = float
    else:
        raise ValueError(f"Not supported loader_type={loader_type}")
    # path looks like:
    #   utta 1,0
    #   uttb 3,4,5
    # -> return {'utta': np.ndarray([1, 0]),
    #            'uttb': np.ndarray([3, 4, 5])}
    d = read_2columns_text(path)
    # Using for-loop instead of dict-comprehension for debuggability
    retval = {}
    for k, v in d.items():
        try:
            retval[k] = [dtype(i) for i in v.split(delimiter)]
        except TypeError:
            logging.error(f'Error happened with path="{path}", id="{k}", value="{v}"')
            raise
    return retval